1,004,594 results on '"Mohammed, A."'
Search Results
2. Effects of nutritive and non-nutritive feed supplements on feed utilization, growth and reproductive performances in mammals
- Author
-
Mohammed, A.A., Al-Gherair, I., Al-Suwaiegh, S., Al-Khamis, S., Alessa, F., Al-Madni, A., and Al-Ghamdi, A.
- Published
- 2024
- Full Text
- View/download PDF
3. The Effects of the Great Depression on Children's Intergenerational Mobility
- Author
-
Bailey, Martha J., Lin, Peter Z., Mohammed, A. R. Shariq, and Prettyman, Alexa
- Published
- 2024
4. English as a Foreign Language Teaching Approaches in Saudi K-12 Education: Teacher-Centered or Student-Centered
- Author
-
Razan Mohammed Alqahtani and Munassir Alhamami
- Abstract
This study explores the educational methodologies employed by Saudi English as a foreign language (EFL) teacher, with a specific emphasis on contrasting teacher-centered approaches and student-centered approaches. Additionally, the research examines the teachers' personal beliefs regarding the most effective approach for implementation in EFL classrooms. To gather data, an online questionnaire was administered to 42 EFL teachers across Saudi K-12 schools in the Southern part of Saudi Arabia. The questionnaire comprised two sections: a demographic information segment and an inquiry into teachers' perspectives and practices. The results of the study showed a dichotomy. While a majority of participants professed that both teacher-centered and student-centered methodologies carry equal importance, a more nuanced picture emerged when examining their claimed practices versus actual classroom behavior. The majority of EFL K-12 instructors in Saudi classrooms leaned toward adopting teacher-centered approaches. These findings hold significant implications for EFL teacher training and professional development courses. This may be due to teachers' lack of confidence in implementing student-centered approaches, the traditional educational culture in Saudi Arabia, or pressure to prepare students for high-stakes exams. The study suggests that teacher education programs should focus on developing teachers' understanding and confidence in using student-centered approaches and that the Ministry of Education should create a more supportive environment for student-centered teaching approaches.
- Published
- 2024
5. Geopolitics over Brahmaputra Water: Dam Constructions in Tibet and Arunachal Pradesh
- Author
-
Mohammed, A.N. and Basu, Biswajit
- Published
- 2022
6. African Academics in Norway: Experiences of Inclusion and Exclusion and Impact on Mental Wellbeing
- Author
-
Mohammed-Awal Alhassan, Ahmed Bawa Kuyini, Boitumelo Mangope, and Thenjiwe Emily Major
- Abstract
This study explored the experiences of inclusion and exclusion of African academics in Norway in various sectors of the society and their participation in these sectors. Using a mixed method research approach, 166 African academics completed a 20-item questionnaire entitled Perceived Exclusion Scale (PES) and two open-ended questions about their mental effects and coping mechanisms of exclusion. Descriptive statistics and qualitative analysis procedures were used to analyze the data. The results showed that the participants experienced exclusion in almost all the sectors of the Norwegian society with concomitant effects of depression and insomnia for most of the participants. Participants mentioned acceptance, confrontational strategy, avoidance strategy, theological group discussion and positive attitudes as key coping mechanisms to exclusion and discrimination. This study could be used as a baseline for future research on the psychological and mental health effects of discrimination of Africans and African-Norwegians. The study is a pointer to the public discourses on the positive sides of immigration in general and the role of migrants' contribution to the Norwegian society.
- Published
- 2024
7. Exploring Complex Biological Processes through Artificial Intelligence
- Author
-
Fatima Rahioui, Mohammed Ali Tahri Jouti, and Mohammed El Ghzaoui
- Abstract
Artificial intelligence (AI) is now affecting all aspects of our social lives. Without always knowing it, we interact daily with intelligent systems. They serve us invisibly. At least that is the goal we assign to them: to make our lives better, task by task. Artificial intelligence has the potential to make biology education more engaging, personalized, and effective by providing students with interactive simulations, personalized learning experiences, and other tools that help them understand complex biological concepts. In this paper, we discuss the integration of AI into the virtual classroom, which significantly enhances student learning experiences in various ways. The study shows that an effective integration of technology into the virtual classroom requires a thoughtful approach that aligns with educational goals and the specific needs of students. In fact, interactive simulations can help make biology more engaging and memorable for students. Besides, personalized learning AI algorithms can help biology students receive a more tailored and effective learning experience, helping them to better understand the course material and develop a deeper appreciation for the natural world. In this work, we will discuss the use of AI to enhance interactive simulation-based cellular processes, with additional application in anatomy, physiology, and ecology teaching. Moreover, this paper discusses how AI could be used to analyze student data and propose personalized learning using adaptive assessments, content recommendations, and data sciences. This paper illustrates examples of AI algorithms that could be useful for teaching biology.
- Published
- 2024
8. Coexistence via trophic cascade in plant-herbivore-carnivore systems under intense predation pressure
- Author
-
Mohammed, Mozzamil, Mohammed, Mohammed AY, Alsammani, Abdallah, Bakheet, Mohamed, Hui, Cang, and Landi, Pietro
- Subjects
Quantitative Biology - Populations and Evolution - Abstract
Carnivores interact with herbivores to indirectly impact plant populations, creating trophic cascades within plant-herbivore-carnivore systems. We developed and analyzed a food chain model to gain a mechanistic understanding of the critical roles carnivores play in ecosystems where plants face intense herbivory. Our model incorporates key factors such as seed production rates, seed germination probabilities, local plant interactions, herbivory rates, and carnivore predation rates. In the absence of carnivores, herbivores significantly reduce plant densities, often driving plants to extinction under high herbivory rates. However, the presence of carnivores suppresses herbivore populations, allowing plants to recover from herbivore pressure. We found that plant densities increase with carnivore predation rates, highlighting top-down effects and underscoring the importance of conserving carnivores in ecosystems where plants are at high risk of extinction from herbivory. Our results also show that carnivore density increases with seed-production rates, while herbivore density remains constant, indicating that plants benefit carnivores more than herbivores. This increase in carnivore density driven by high seed-production rates reflects bottom-up effects in the system. Overall, our study demonstrates that plants, herbivores, and carnivores can coexist even under intense predation stress. It suggests that carnivores play a crucial role in regulating plant and herbivore populations, with significant potential for maintaining biodiversity within ecosystems.
- Published
- 2024
9. MIS-ME: A Multi-modal Framework for Soil Moisture Estimation
- Author
-
Rakib, Mohammed, Mohammed, Adil Aman, Diggins, D. Cole, Sharma, Sumit, Sadler, Jeff Michael, Ochsner, Tyson, and Bagavathi, Arun
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning - Abstract
Soil moisture estimation is an important task to enable precision agriculture in creating optimal plans for irrigation, fertilization, and harvest. It is common to utilize statistical and machine learning models to estimate soil moisture from traditional data sources such as weather forecasts, soil properties, and crop properties. However, there is a growing interest in utilizing aerial and geospatial imagery to estimate soil moisture. Although these images capture high-resolution crop details, they are expensive to curate and challenging to interpret. Imagine, an AI-enhanced software tool that predicts soil moisture using visual cues captured by smartphones and statistical data given by weather forecasts. This work is a first step towards that goal of developing a multi-modal approach for soil moisture estimation. In particular, we curate a dataset consisting of real-world images taken from ground stations and their corresponding weather data. We also propose MIS-ME - Meteorological & Image based Soil Moisture Estimator, a multi-modal framework for soil moisture estimation. Our extensive analysis shows that MIS-ME achieves a MAPE of 10.14%, outperforming traditional unimodal approaches with a reduction of 3.25% in MAPE for meteorological data and 2.15% in MAPE for image data, highlighting the effectiveness of tailored multi-modal approaches. Our code and dataset will be available at https://github.com/OSU-Complex-Systems/MIS-ME.git., Comment: Accepted by DSAA2024
- Published
- 2024
10. ATHAR: A High-Quality and Diverse Dataset for Classical Arabic to English Translation
- Author
-
Khalil, Mohammed and Sabry, Mohammed
- Subjects
Computer Science - Computation and Language ,Computer Science - Artificial Intelligence - Abstract
Classical Arabic represents a significant era, encompassing the golden age of Arab culture, philosophy, and scientific literature. With a broad consensus on the importance of translating these literatures to enrich knowledge dissemination across communities, the advent of large language models (LLMs) and translation systems offers promising tools to facilitate this goal. However, we have identified a scarcity of translation datasets in Classical Arabic, which are often limited in scope and topics, hindering the development of high-quality translation systems. In response, we present the ATHAR dataset, comprising 66,000 high-quality Classical Arabic to English translation samples that cover a wide array of subjects including science, culture, and philosophy. Furthermore, we assess the performance of current state-of-the-art LLMs under various settings, concluding that there is a need for such datasets in current systems. Our findings highlight how models can benefit from fine-tuning or incorporating this dataset into their pretraining pipelines. The dataset is publicly available on the HuggingFace Data Hub at \url{https://huggingface.co/datasets/mohamed-khalil/ATHAR}.
- Published
- 2024
11. Rooting behavior of pomegranate (Punica granatum L.) hardwood cuttings in relation to genotype and irrigation frequency
- Author
-
Salih, Kocher Omer, Mohammed, Aram Akram, Faraj, Jamal Mahmood, Raouf, Anwar Mohammed, and Tahir, Nawroz Abdul-Razzak
- Subjects
Quantitative Biology - Other Quantitative Biology - Abstract
The study was conducted to determine the best irrigation frequency for rooting hardwood cuttings of some pomegranate genotypes that are cultivated in Halabja province, Kurdistan Region, Iraq. The hardwood cuttings were collected from 11 genotypes, which were 'Salakhani Trsh' (G1), 'Salakhani Mekhosh' (G2), 'Amriki' (G3), 'Twekl Sury Trsh' (G4), 'Twekl Astury Naw Spy' (G5), 'Hanara Sherina' (G6), 'Kawa Hanary Sherin' (G7), 'Kawa Hanary Trsh' (G8), 'Malesay Twekl Asture' (G9), 'Malesay Twekl Tank' (G10), and 'Sura Hanary Trsh' (G11). The genotypes were subjected to irrigation applications by 1-day, 2-day, 7-day, or 10-day frequencies. Among pomegranates, G11, G6, and G7 produced 95, 90, and 83% rooting percentages, which were significantly higher than the rest of other genotypes. The lowest rooting percentages (28, 36, 38, and 40%) were found in G1, G5, G3, and G10, respectively. The effect of irrigation frequencies on the genotypes confirmed that a 7-day frequency was the best irrigation frequency to achieve the maximum rooting percentages (93, 86, 80, 73, 53, and 40%) in G6, G9, G2, G4, G3, and G1, respectively. In contrast, the minimum rooting percentage (20%) was recorded in G3 with a 1-day frequency and in G1 with 10-day frequency. In this study, it was found that the cuttings of G11, G6, and G7 had the best ability to form roots, and irrigation with a 7-day frequency was the best for the cuttings of all the 11 pomegranate genotypes investigated.
- Published
- 2024
12. Enhancing Pronunciation Learning through High Variability Phonetic Training: A Meta-Analysis
- Author
-
Hassan Saleh Mahdi and Mohammed Ali Mohsen
- Abstract
High-Variability Phonetic Training (HVPT) has demonstrated effectiveness in second language (L2) acquisition. This study utilizes a meta-analysis to explore the influence of high variability on learning L2 pronunciation and identifies the factors that moderate this impact. The studies were collected using a keyword search in the SCOPUS database. In total, our meta-analysis incorporated 18 primary studies that presented results obtained from experimental and control group designs, encompassing a total of 22 effect sizes. The results of our meta-analysis revealed that the overall effect size of HVPT on L2 pronunciation was medium (g = 0.77). Specifically, the effect size was large for consonant sounds and lexical tones, particularly pronounced when utilized by advanced learners. For beginners, the effect size was medium. The context in which the training was conducted also played a role, with a medium effect size observed when sentences were used. Additionally, the number of talkers involved in the study influenced the effect size, with a medium effect size found when 5 to 8 talkers were included. In other cases, the reported effect sizes were either small or non-significant.
- Published
- 2024
13. Information Literacy and Discourse Analysis for Verifying Information among EFL Learners
- Author
-
Yaseen Ali Azi, Sami Abdullah Hamdi, and Mohammed Ahmad Okasha
- Abstract
The task of verifying credible and original information is now more complicated, especially for undergraduate students. This study uses information literacy and discourse analysis to develop English as a foreign language learners' critical reading skills while verifying information on social media. A reading test including false news was used to assess the learners' awareness of the credibility of social media information. Then, they were divided into experimental and control groups. The experimental group was trained in evaluating a set of false news using information literacy and discourse analysis skills. The control group did not receive any training. The experiment was conducted again on both groups. The results show a significant improvement among the experimental group compared to the control group. The findings of this study shed light on the growing need for creating a pedagogical space in English as a foreign language classroom that focuses on raising learners' awareness of information literacy and discourse analysis skills to read with critical perspectives.
- Published
- 2024
14. Reflective Practices among Secondary School Computer Science Teachers: Their Point of View
- Author
-
Lubna Mohammed Alshamrani
- Abstract
Reflective practice is an essential catalyst through which the benefits of teaching and learning can be reaped. Through it, weaknesses and strengths can be identified in a way that helps raise the level of addressing challenges that may arise as well as overcome them. This paper presents the critical reflective practices among computer science secondary school teachers from their point of view in Riyadh, Saudi Arabia. To this extent, the study aims to determine the degree of critical reflective practices among computer science secondary school teachers in Riyadh from their perspective. The paper also seeks to investigate the effects of variables such as gender, qualifications and experience on the perceptions of the aforementioned teachers, towards the critical reflective practices among computer science secondary school teachers. The study tool is a questionnaire which consisted of two dimensions and was distributed to a population of 739 participants. From this, the study sample comprised (223) computer science teachers working in secondary school in Riyadh. The findings revealed that there is no significant difference in the estimation degree concerning the critical reflective practices due to the gender. From the results, it was also established that there is no significant difference in the degree of estimation in relation to the critical reflective practices due to educational qualification variables. On the contrary however, there is a significant difference in the degree of estimation in regard to the critical reflective practices due to the years of experience variable. These differences were evident in a group of those with more than 10 years of experience. The other findings produced by the study highlight that the participants are in agreement about the importance of critical reflective practices. The degree of reflective practice, which is from the participants' point of view, is considered to be of a high value. The majority of the subjects opted to agree with the practice of reflection after a training session. It was determined from the results that some of the most common strategies favored by practitioners involved the communal practice of mind reflection with individuals from outside the school.
- Published
- 2024
15. The Degree of Special Education Teachers' Employment of Electronic Educational Games in Teaching Disabled Students
- Author
-
Burhan Mahmoud Hamadneh, Mamoun Mohammed AL-Azzam, Turki Mahdi Alqarni, and Abdulaziz Derwesh Almalki
- Abstract
The study aimed to reveal the degree of special education teachers' employment of electronic educational games in teaching the disabled. It also showed statistical differences according to the variables of gender, academic qualification, and years of experience. To achieve the objectives of the study, the descriptive survey method was used. The study sample consisted of (96) male and female teachers, of whom (47) male and (47) female teachers were chosen in a stratified random manner from the Directorate of Education for Najran region in the Kingdom of Saudi Arabia in the academic year 2022/2023. A questionnaire consisting of (30) items was used, distributed in three domains: planning, implementation, and evaluation. The results showed that the degree of special education teachers' employment of electronic educational games in teaching students with disabilities obtained a mean of (2.57), with a low degree. The results also showed that there are statistically significant differences in the responses of the study sample about the degree of special education teachers' employment of electronic educational games in teaching students with disabilities due to the variables of academic qualification in favor of postgraduate studies, and years of experience in favor of more than ten years. However, there was no statistically significant difference due to the gender variable. The study recommended that the Ministry of Education should pay attention to holding and organizing various specialized training programs to develop the capabilities of special education teachers to employ electronic educational games in teaching, especially in planning, implementation, and evaluation.
- Published
- 2024
16. Evaluating the Quality of Teaching Performance among Jordanian Teachers in Light of Certain Demographic Variables
- Author
-
Mohammed S. Al-Rsa'I, Dima Waswas, Ahmad Altawarah, and Fatina Al-Rowad
- Abstract
The quality of teachers' teaching performance depends on several factors, and development of their performance should be made according to a sound scientific methodology, so the study aims to assess the teachers' teaching performance quality in Ma'an, Southern Jordan, and identify the extent to which their performance is affected by some variables (Gender, Professional Experience, Teaching Stages, and Training). In order to achieve the study objectives, the descriptive survey method was used, and a measure of teaching performance quality was determined, consisting of three fields (Planning, Implementation, and Assessment) and including (40) items. The scale was used by educational supervisors to assess the quality of teachers' performance in Ma'an, and (347) male and female teachers were assessed. The results showed that teachers' performance was average in general, but their performance of the first three grades was the weakest, while it was also shown that the female teachers' performance was superior to that of male teachers. The performance of specialized teachers in the scientific field was better than the performance of their counterparts in the humanitarian field. The study showed the positive impact of professional experience and training on the quality of teaching performance. The study also demonstrated the importance of the first five years in the teachers' work, therefore, the necessity of focusing on training and qualification at this stage was recommended, as well as training pre-service teachers appropriately.
- Published
- 2024
17. Robo Academic Advisor: Can Chatbots and Artificial Intelligence Replace Human Interaction?
- Author
-
Mohammed Muneerali Thottoli, Badria Hamed Alruqaishi, and Arockiasamy Soosaimanickam
- Abstract
Purpose: Chatbots and artificial intelligence (AI) have the potential to alleviate some of the challenges faced by humans. Faculties frequently swamped with teaching and research may find it difficult to act in a parental role for students by offering them individualized advice. Hence, the primary purpose of this study is to review the literature on chatbots and AI in light of their role in auto-advising systems. The authors aimed to gain insights into the most pertinent topics and concerns related to robo academic advisor and identify any gaps in the literature that could serve as potential avenues for further research. Design/methodology/approach: The research employs a systematic literature review and bibliometric techniques to find 67 primary papers that have been published between 1984 and 2023. Using the Scopus database, the researchers built a summary of the literature on chatbots and AI in academic advice. Findings: Chatbot applications can be a promising approach to address the challenges of balancing personalized student advising with automation. More empirical research is required, especially on chatbots and other AI-based advising systems, to understand their effectiveness and how they can be integrated into educational settings. Research limitations/implications: This research's sample size may restrict its findings' generalizability. Furthermore, the study's focus on chatbots may overlook the potential benefits of other AI technologies in enhancing robo academic advising systems. Future research could explore the impact of robo academic advisors in diverse societal backgrounds to gain a more comprehensive understanding of their implications. Practical implications: Higher educational institutions (HEIs) should establish a robo academic advising system that serves various stakeholders. The system's chatbots and AI features must be user-friendly, considering the customers' familiarity with robots. Originality/value: This study contributes to a better understanding of HEIs' perceptions of the adoption of chatbots and AI in academic advising by providing insightful information about the main forces behind robo academic advising, illuminating the most frequently studied uses of chatbots and AI in academic advising.
- Published
- 2024
18. Exploring the Relationship between Critical Thinking, Attitude, and Anxiety in Shaping the Adoption of Artificial Intelligence in Translation among Saudi Translators
- Author
-
Hassan Saleh Mahdi and Yousef Mohammed Sahari
- Abstract
Critical thinking and anxiety influenced the translation competence of translators. This study sought to examine the interactions between critical thinking, attitude, and anxiety influenced the translation competence of translators. This study adopted an empirical approach to collect data from 145 student translators from many colleges in Saudi Arabia. The questionnaire was used as a data collection tool. Data were analyzed by using structural equation modelling to find out the relationship between the study factors. The results indicated that there was a negative relationship between AI anxiety with critical thinking and attitude. However, there was a strong positive relationship between attitude with critical thinking, and Machine Translation anxiety. Also, there was a positive relationship between Machine Translation anxiety with AI anxiety and critical thinking.
- Published
- 2024
19. Researching Multi-Disciplinary Diversities and Optimizing Their Inherent Strengths and Opportunities: The Role Played by UNILAG Research Management Office
- Author
-
Emeka Patrick Okonji, Gbadamosi Morufu, and Amuda Mohammed Hakeem Olawale
- Abstract
The University of Lagos is one of Nigeria's premiere Universities, established in 1962 with core values emphasizing commitment to quality academic learning and character, integrity, continuous improvement of staff professionalism and competence, as well as a strong commitment to cutting-edge research. In 2012, the University established the Research and Innovation Office, which was subsequently restructured into two offices: the Research Management Office, and the Innovation and Technology Transfer Office, for more efficient functioning. Over the years, the Office has provided enormous support to over 1,700 academic faculty and researchers for cutting-edge research built on a multi-disciplinary approach. This paper provides a detailed discussion of the strategies employed by the Research Management Office to promote multi-disciplinary research from inception to date, the results of efforts to promote collaboration across the currently existing wealth of diversity in academic and research disciplines among researchers in over 12 faculties of the University, the successes recorded, and the challenges faced. The paper further makes recommendations for the advancement of these strategies, and suggestions for pragmatic solutions to challenges experienced while drawing practical and applicable lessons from international best practices for supporting multi-disciplinary research.
- Published
- 2024
20. A Systematic Review of Gamification in MOOCs: Effects on Student Motivation, Engagement, and Dropout Rates
- Author
-
Alj Zakaria, Bouayad Anas, and Mohammed Ouçamah Cherkaoui Malki
- Abstract
A massive open online course (MOOC) is a powerful tool for expanding educational opportunities, but one of the major challenges facing MOOCs is the high dropout rate. Low completion rates indicate issues with student engagement and motivation. Gamification, the incorporation of game elements in non-game contexts, has shown promise in increasing engagement and completion rates in education. This systematic review aims to explore the current state of research on gamification in MOOCs, including the most commonly used gamification aspects, their impact on motivation and engagement, and the influence on dropout rates. We searched several databases, such as Google Scholar, Scopus, and ERIC, from 2014 to 2021 and included studies that focused on the application of gamification in MOOCs and its effects on motivation, engagement, and dropout rates. A total of 16 studies were analyzed, and the results were synthesized to address the research questions posed. The results of this systematic literature review indicate that while research on gamification in MOOCs is still in its early stages, several studies have shown that gamification elements such as badges, levels, leaderboards, challenges, and rewards significantly affect student motivation and engagement, and reduce dropout rates in MOOCs. However, the effectiveness of these elements varies depending on their specific design, implementation, and alignment with students' intrinsic motivations and goals.
- Published
- 2024
21. Effects of Tyre Derived Aggregate (TDA) as Partial Replacement of Coarse Aggregate in Concrete
- Author
-
Sulaiman, T. A, Mohammed, A., Aliyu, I., Abdullahi, M, and Abdurrahman, A.
- Subjects
Compressive Strength ,Temperature ,Tire Derived Aggregate (TDA) ,workability ,Technology - Abstract
The usage and reuse of waste tyre rubber in concrete production can cut down the use of raw materials which contributes to economic efficiency and sustainable development of the construction industry. This study is directed at assessing the effects of using the Tyre Derived Aggregate (TDA) as a substitute for coarse aggregate in concrete. A sum of eighty-six square cubes of 100 mm was cast and cured in fresh water for up to 28 days. Setting times, consistency and soundness tests were carried out on cement paste. However, slump, compressive strength and durability (i.e. water absorption) tests were carried out on the concrete. The results unveiled that the physical characteristics of cement considered fulfilled BS EN 196-3 (1995), and the slump of fresh concrete decreased as the percentage of TDA content stepped up. The water absorption raised, while the density of concrete made with TDA decreased as the percentage of TDA content stepped up. However, the strength of TDA-concrete increased as the curing age increased, and it decreased as the portion of TDA content raised. Nevertheless, the strength at 0%, 5% and 10% were 23, 21.67 and 18.33 N/mm2 respectively. However, the strength of TDA-concrete made with 0 % TDA and 5 % TDA subjected to different temperatures decreased as the temperature increased, however, even at 500C the strength of concrete made with 5% TDA was found to be 20.5 N/mm2 which is within the target compressive strength. It was concluded that the usage of TDA content in the production of concrete should not be greater than 5 % for better performance.
- Published
- 2022
22. A Riemannian Approach for Spatiotemporal Analysis and Generation of 4D Tree-shaped Structures
- Author
-
Khanam, Tahmina, Laga, Hamid, Bennamoun, Mohammed, Wang, Guanjin, Sohel, Ferdous, Boussaid, Farid, Wang, Guan, and Srivastava, Anuj
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence ,Computer Science - Graphics - Abstract
We propose the first comprehensive approach for modeling and analyzing the spatiotemporal shape variability in tree-like 4D objects, i.e., 3D objects whose shapes bend, stretch, and change in their branching structure over time as they deform, grow, and interact with their environment. Our key contribution is the representation of tree-like 3D shapes using Square Root Velocity Function Trees (SRVFT). By solving the spatial registration in the SRVFT space, which is equipped with an L2 metric, 4D tree-shaped structures become time-parameterized trajectories in this space. This reduces the problem of modeling and analyzing 4D tree-like shapes to that of modeling and analyzing elastic trajectories in the SRVFT space, where elasticity refers to time warping. In this paper, we propose a novel mathematical representation of the shape space of such trajectories, a Riemannian metric on that space, and computational tools for fast and accurate spatiotemporal registration and geodesics computation between 4D tree-shaped structures. Leveraging these building blocks, we develop a full framework for modelling the spatiotemporal variability using statistical models and generating novel 4D tree-like structures from a set of exemplars. We demonstrate and validate the proposed framework using real 4D plant data.
- Published
- 2024
23. Novel Many-to-Many NOMA-based Communication Protocols for Vehicular Platoons
- Author
-
Bahbahani, Mohammed S., Yahya, Hamad, and Alsusa, Emad
- Subjects
Electrical Engineering and Systems Science - Signal Processing - Abstract
Non-orthogonal multiple access (NOMA) is a promising technique for ultra-reliable low-latency communication as it provides higher spectral efficiency and lower latency. In this work, we propose novel many-to-many (M2M) NOMA-based schemes to exchange broadcast, multicast, and unicast messages between cluster heads (CHs) of vehicular platoons. Specifically, we design uplink-M2M-NOMA (UM-NOMA), downlink-M2M-NOMA (DM-NOMA) and joint uplink-downlink-M2M-NOMA (UDM-NOMA) schemes for peer-to-peer vehicular ad hoc networks (VANETs). We propose a unique clustering design for full-duplex communication that utilizes the high throughput millimeter-wave (mmWave) channels. Furthermore, we investigate jointly optimal CH selection (CHS) and power allocation (PA) to maximize the network sum rate and devise a computationally efficient tailored-greedy algorithm that yields near-optimal performance. We also propose a super-cluster formation protocol to further limit the overhead of successive interference cancellation (SIC). The results reveal that in most of the considered scenarios, the proposed UDM-NOMA scheme outperforms orthogonal multiple access (OMA) in terms of sum rate by up to 50% even when the SIC receiver errors reach 10%.
- Published
- 2024
24. Matmul or No Matmal in the Era of 1-bit LLMs
- Author
-
Malekar, Jinendra, Elbtity, Mohammed E., and Co, Ramtin Zand
- Subjects
Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
The advent of 1-bit large language models (LLMs) has attracted considerable attention and opened up new research opportunities. However, 1-bit LLMs only improve a fraction of models by applying extreme quantization to the projection layers while leaving attention heads unchanged. Therefore, to avoid fundamentally wrong choices of goals in future research, it is crucial to understand the actual improvements in computation and memory usage that 1-bit LLMs can deliver. In this work, we present an adaptation of Amdahl's Law tailored for the 1-bit LLM context, which illustrates how partial improvements in 1-bit LLMs impact overall model performance. Through extensive experiments, we uncover key nuances across different model architectures and hardware configurations, offering a roadmap for future research in the era of 1-bit LLMs., Comment: 13 pages, 12 figures
- Published
- 2024
25. Effect of IBA concentration and water soaking on rooting hardwood cuttings of black mulberry (Morus nigra L.)
- Author
-
Aziz, Rasul Rafiq, Mohammed, Aram Akram, Ahmad, Faraydwn Karim, and Ali, Ari Jamil
- Subjects
Quantitative Biology - Other Quantitative Biology - Abstract
The research was conducted at the College of Agricultural Sciences Engineering/University of Sulaimani/ Kurdistan Region-Iraqi to investigate effects of different concentrations of IBA (0, 3000, 4000 and 5000 ppm) and soaking in water for 24 hours on propagation black mulberry (Morus nigra L.) by hardwood cuttings. In this research the parameters of rooting percentage, root number, root length, sprout bud number, shoot length and shoot diameter were measured. Effect of individual factors showed that the highest rooting percentage (15%) was achieved in cuttings soaked in water for 24 hours, as well as improving other traits. Also, the best (23.33%) rooting was found in cuttings dipped in 4000 ppm IBA. Interaction effects of the two factors showed that cuttings treated with 4000 ppm IBA and soaked in water for 24 hours gave the highest (40%) rooting, and the highest other root and shoot traits were achieved in the same interaction as well.
- Published
- 2024
26. Beyond Labels: Aligning Large Language Models with Human-like Reasoning
- Author
-
Kabir, Muhammad Rafsan, Sultan, Rafeed Mohammad, Asif, Ihsanul Haque, Ahad, Jawad Ibn, Rahman, Fuad, Amin, Mohammad Ruhul, Mohammed, Nabeel, and Rahman, Shafin
- Subjects
Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Aligning large language models (LLMs) with a human reasoning approach ensures that LLMs produce morally correct and human-like decisions. Ethical concerns are raised because current models are prone to generating false positives and providing malicious responses. To contribute to this issue, we have curated an ethics dataset named Dataset for Aligning Reasons (DFAR), designed to aid in aligning language models to generate human-like reasons. The dataset comprises statements with ethical-unethical labels and their corresponding reasons. In this study, we employed a unique and novel fine-tuning approach that utilizes ethics labels and their corresponding reasons (L+R), in contrast to the existing fine-tuning approach that only uses labels (L). The original pre-trained versions, the existing fine-tuned versions, and our proposed fine-tuned versions of LLMs were then evaluated on an ethical-unethical classification task and a reason-generation task. Our proposed fine-tuning strategy notably outperforms the others in both tasks, achieving significantly higher accuracy scores in the classification task and lower misalignment rates in the reason-generation task. The increase in classification accuracies and decrease in misalignment rates indicate that the L+R fine-tuned models align more with human ethics. Hence, this study illustrates that injecting reasons has substantially improved the alignment of LLMs, resulting in more human-like responses. We have made the DFAR dataset and corresponding codes publicly available at https://github.com/apurba-nsu-rnd-lab/DFAR., Comment: Accepted in ICPR 2024
- Published
- 2024
27. BAUST Lipi: A BdSL Dataset with Deep Learning Based Bangla Sign Language Recognition
- Author
-
Hadiuzzaman, Md, Ali, Mohammed Sowket, Sultana, Tamanna, Shafi, Abdur Raj, Miah, Abu Saleh Musa, and Shin, Jungpil
- Subjects
Computer Science - Computer Vision and Pattern Recognition - Abstract
People commonly communicate in English, Arabic, and Bengali spoken languages through various mediums. However, deaf and hard-of-hearing individuals primarily use body language and sign language to express their needs and achieve independence. Sign language research is burgeoning to enhance communication with the deaf community. While many researchers have made strides in recognizing sign languages such as French, British, Arabic, Turkish, and American, there has been limited research on Bangla sign language (BdSL) with less-than-satisfactory results. One significant barrier has been the lack of a comprehensive Bangla sign language dataset. In our work, we introduced a new BdSL dataset comprising alphabets totaling 18,000 images, with each image being 224x224 pixels in size. Our dataset encompasses 36 Bengali symbols, of which 30 are consonants and the remaining six are vowels. Despite our dataset contribution, many existing systems continue to grapple with achieving high-performance accuracy for BdSL. To address this, we devised a hybrid Convolutional Neural Network (CNN) model, integrating multiple convolutional layers, activation functions, dropout techniques, and LSTM layers. Upon evaluating our hybrid-CNN model with the newly created BdSL dataset, we achieved an accuracy rate of 97.92\%. We are confident that both our BdSL dataset and hybrid CNN model will be recognized as significant milestones in BdSL research.
- Published
- 2024
28. Zak-OTFS with Interleaved Pilots to Extend the Region of Predictable Operation
- Author
-
Jayachandran, Jinu, Khan, Imran Ali, Mohammed, Saif Khan, Hadani, Ronny, Chockalingam, Ananthanarayanan, and Calderbank, Robert
- Subjects
Electrical Engineering and Systems Science - Signal Processing ,Computer Science - Information Theory - Abstract
When the delay period of the Zak-OTFS carrier is greater than the delay spread of the channel, and the Doppler period of the carrier is greater than the Doppler spread of the channel, the effective channel filter taps can simply be read off from the response to a single pilot carrier waveform. The input-output (I/O) relation can then be reconstructed for a sampled system that operates under finite duration and bandwidth constraints. We introduce a framework for pilot design in the delay-Doppler (DD) domain which makes it possible to support users with very different delay-Doppler characteristics when it is not possible to choose a single delay and Doppler period to support all users. The method is to interleave single pilots in the DD domain, and to choose the pilot spacing so that the I/O relation can be reconstructed by solving a small linear system of equations., Comment: This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
- Published
- 2024
29. Higgs production at NLL accuracy in the BFKL approach
- Author
-
Celiberto, Francesco Giovanni, Rose, Luigi Delle, Fucilla, Michael, Gatto, Gabriele, Ivanov, Dmitry Yu., Mohammed, Mohammed M. A., and Papa, Alessandro
- Subjects
High Energy Physics - Phenomenology ,High Energy Physics - Experiment ,Nuclear Theory - Abstract
Precision physics in the Higgs sector has been one of the main challenges of particle physics in the recent years. The pure fixed-order calculations entering the collinear factorization framework, which have been pushed up to next-cube-leading-order, are not able to describe the entire kinematic spectrum. In particular sectors, they have to be necessarily enhanced by all-order resummations. In the so-called semi-hard regime, large energy-type logarithms spoil the perturbative convergence of the series and must be resummed to all orders. This resummation is a core ingredient for a correct description of the inclusive hadroproduction of a forward Higgs boson in the limit of small Bjorken $x$, as well as for a precision study of inclusive forward emissions of a Higgs boson in association with a backward identified object. A complete resummation for these processes can be achieved at the at next-to-leading logarithmic accuracy thanks to the Balitsky-Fadin-Kuraev-Lipatov approach. In the present work we present and discuss a series of recent phenomenological results within a partial next-to-leading accuracy. They include the analysis of rapidity and azimuthal-angle differential rates for Higgs plus jet and Higgs plus charm reactions in forward and ultraforward directions of rapidity at the LHC., Comment: 5 pages, 1 figure, proceedings of the 31st International Workshop on Deep Inelastic Scattering (DIS2024), 8-12 April 2024, Grenoble, France
- Published
- 2024
30. Possible wormholes in $f(R)$ gravity sourced by solitonic quantum wave and cold dark matter halos and their repulsive gravity effect
- Author
-
Errehymy, Abdelghani, Khedif, Youssef, Donmez, Orhan, Daoud, Mohammed, Myrzakulov, Kairat, and Bekov, Sabit
- Subjects
General Relativity and Quantum Cosmology - Abstract
In this paper, we present new generalized wormhole (WH) solutions within the context of $f(R)$ gravity. Specifically, we focus on $f(R)$ gravitational theories formulated in the metric formalism, with our investigation centered on a power-law form represented by $f(R) = \epsilon R^{\chi}$. Here, $\epsilon$ is an arbitrary constant, and $\chi$ is a real number. Notably, this form possesses the advantageous property of reducing to Einstein gravity when $\epsilon=1$ and $\chi=1$. To obtain these novel WH solutions, we establish the general field equations for any $f(R)$ theory within the framework of Morris-Thorne spacetime, assuming metric coefficients that are independent of time. By utilizing an anisotropic matter source and a specific type of energy density associated with solitonic quantum wave (SQW) and cold dark matter (CDM) halos, we calculate two distinct WH solutions. We thoroughly investigate the properties of the exotic matter (ExoM) residing within the WH geometry and analyze the matter contents through energy conditions (ECs). Both analytical and graphical methods are employed in this analysis to examine the validity of different regions. Notably, the calculated shape functions for the WH geometry satisfy the necessary conditions in both scenarios, emphasizing their reliability. This ExoM is characterized by an energy-momentum tensor that violates the null energy condition (NEC) and, consequently, the weak energy condition as well, in the vicinity of the WH throats. Furthermore, we investigated the repulsive effect of gravity and discovered that its presence results in a negative deflection angle for photons following null geodesics. Importantly, we observed that the deflection angle consistently exhibits negative values across all $r_0$ values in both scenarios, indicating the manifestation of the repulsive gravity effect., Comment: Accepted for publication in the European Physical Journal C, 15 pages, 18 figures
- Published
- 2024
31. A Survey on Model MoErging: Recycling and Routing Among Specialized Experts for Collaborative Learning
- Author
-
Yadav, Prateek, Raffel, Colin, Muqeeth, Mohammed, Caccia, Lucas, Liu, Haokun, Chen, Tianlong, Bansal, Mohit, Choshen, Leshem, and Sordoni, Alessandro
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computation and Language - Abstract
The availability of performant pre-trained models has led to a proliferation of fine-tuned expert models that are specialized to a particular domain or task. Model MoErging methods aim to recycle expert models to create an aggregate system with improved performance or generalization. A key component of MoErging methods is the creation of a router that decides which expert model(s) to use for a particular input or application. The promise, effectiveness, and large design space of MoErging has spurred the development of many new methods over the past few years. This rapid pace of development has made it challenging to compare different MoErging methods, which are rarely compared to one another and are often validated in different experimental setups. To remedy such gaps, we present a comprehensive survey of MoErging methods that includes a novel taxonomy for cataloging key design choices and clarifying suitable applications for each method. Apart from surveying MoErging research, we inventory software tools and applications that make use of MoErging. We additionally discuss related fields of study such as model merging, multitask learning, and mixture-of-experts models. Taken as a whole, our survey provides a unified overview of existing MoErging methods and creates a solid foundation for future work in this burgeoning field., Comment: 26 pages
- Published
- 2024
32. DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts
- Author
-
Islam, Mohammed Saidul, Laskar, Md Tahmid Rahman, Parvez, Md Rizwan, Hoque, Enamul, and Joty, Shafiq
- Subjects
Computer Science - Computation and Language - Abstract
Data-driven storytelling is a powerful method for conveying insights by combining narrative techniques with visualizations and text. These stories integrate visual aids, such as highlighted bars and lines in charts, along with textual annotations explaining insights. However, creating such stories requires a deep understanding of the data and meticulous narrative planning, often necessitating human intervention, which can be time-consuming and mentally taxing. While Large Language Models (LLMs) excel in various NLP tasks, their ability to generate coherent and comprehensive data stories remains underexplored. In this work, we introduce a novel task for data story generation and a benchmark containing 1,449 stories from diverse sources. To address the challenges of crafting coherent data stories, we propose a multiagent framework employing two LLM agents designed to replicate the human storytelling process: one for understanding and describing the data (Reflection), generating the outline, and narration, and another for verification at each intermediary step. While our agentic framework generally outperforms non-agentic counterparts in both model-based and human evaluations, the results also reveal unique challenges in data story generation.
- Published
- 2024
33. A Recurrent YOLOv8-based framework for Event-Based Object Detection
- Author
-
Silva, Diego A., Smagulova, Kamilya, Elsheikh, Ahmed, Fouda, Mohammed E., and Eltawil, Ahmed M.
- Subjects
Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence - Abstract
Object detection is crucial in various cutting-edge applications, such as autonomous vehicles and advanced robotics systems, primarily relying on data from conventional frame-based RGB sensors. However, these sensors often struggle with issues like motion blur and poor performance in challenging lighting conditions. In response to these challenges, event-based cameras have emerged as an innovative paradigm. These cameras, mimicking the human eye, demonstrate superior performance in environments with fast motion and extreme lighting conditions while consuming less power. This study introduces ReYOLOv8, an advanced object detection framework that enhances a leading frame-based detection system with spatiotemporal modeling capabilities. We implemented a low-latency, memory-efficient method for encoding event data to boost the system's performance. We also developed a novel data augmentation technique tailored to leverage the unique attributes of event data, thus improving detection accuracy. Our models outperformed all comparable approaches in the GEN1 dataset, focusing on automotive applications, achieving mean Average Precision (mAP) improvements of 5%, 2.8%, and 2.5% across nano, small, and medium scales, respectively.These enhancements were achieved while reducing the number of trainable parameters by an average of 4.43% and maintaining real-time processing speeds between 9.2ms and 15.5ms. On the PEDRo dataset, which targets robotics applications, our models showed mAP improvements ranging from 9% to 18%, with 14.5x and 3.8x smaller models and an average speed enhancement of 1.67x.
- Published
- 2024
34. A Comprehensive Review of Solitonic Inequalities in Riemannian Geometry
- Author
-
Chen, Bang-Yen, Choudhary, Majid Ali, Nisar, Mohammed, and Siddiqi, Mohd Danish
- Subjects
Mathematics - Differential Geometry ,53B25, 53C1, , 53C20, 53C21, 53C25, 53C40 - Abstract
In Riemannian geometry, Ricci soliton inequalities are an important field of study that provide profound insights into the geometric and analytic characteristics of Riemannian manifolds. An extensive study of Ricci soliton inequalities is given in this review article, which also summarizes their historical evolution, core ideas, important findings, and applications. We investigate the complex interactions between curvature conditions and geometric inequalities as well as the several kinds of Ricci solitons, such as expanding, steady, and shrinking solitons. We also go over current developments, unresolved issues, and possible paths for further study in this fascinating area., Comment: 26 pages
- Published
- 2024
35. Observation of muonic Dalitz decays of $\chi_{b}$ mesons and precise spectroscopy of hidden-beauty states
- Author
-
LHCb collaboration, Aaij, R., Abdelmotteleb, A. S. W., Beteta, C. Abellan, Abudinén, F., Ackernley, T., Adefisoye, A. A., Adeva, B., Adinolfi, M., Adlarson, P., Agapopoulou, C., Aidala, C. A., Ajaltouni, Z., Akar, S., Akiba, K., Albicocco, P., Albrecht, J., Alessio, F., Alexander, M., Aliouche, Z., Cartelle, P. Alvarez, Amalric, R., Amato, S., Amey, J. L., Amhis, Y., An, L., Anderlini, L., Andersson, M., Andreianov, A., Andreola, P., Andreotti, M., Andreou, D., Anelli, A., Ao, D., Archilli, F., Argenton, M., Cuendis, S. Arguedas, Artamonov, A., Artuso, M., Aslanides, E., Da Silva, R. Ataíde, Atzeni, M., Audurier, B., Bacher, D., Perea, I. Bachiller, Bachmann, S., Bachmayer, M., Back, J. J., Rodriguez, P. Baladron, Balagura, V., Baldini, W., Balzani, L., Bao, H., Leite, J. Baptista de Souza, Pretel, C. Barbero, Barbetti, M., Barbosa, I. R., Barlow, R. J., Barnyakov, M., Barsuk, S., Barter, W., Bartolini, M., Bartz, J., Basels, J. M., Bashir, S., Bassi, G., Batsukh, B., Battista, P. B., Bay, A., Beck, A., Becker, M., Bedeschi, F., Bediaga, I. B., Behling, N. B., Belin, S., Bellee, V., Belous, K., Belov, I., Belyaev, I., Benane, G., Bencivenni, G., Ben-Haim, E., Berezhnoy, A., Bernet, R., Andres, S. Bernet, Bertolin, A., Betancourt, C., Betti, F., Bex, J., Bezshyiko, Ia., Bhom, J., Bieker, M. S., Biesuz, N. V., Billoir, P., Biolchini, A., Birch, M., Bishop, F. C. R., Bitadze, A., Bizzeti, A., Blake, T., Blanc, F., Blank, J. E., Blusk, S., Bocharnikov, V., Boelhauve, J. A., Garcia, O. Boente, Boettcher, T., Bohare, A., Boldyrev, A., Bolognani, C. S., Bolzonella, R., Bondar, N., Bordelius, A., Borgato, F., Borghi, S., Borsato, M., Borsuk, J. T., Bouchiba, S. A., Bovill, M., Bowcock, T. J. V., Boyer, A., Bozzi, C., Rodriguez, A. Brea, Breer, N., Brodzicka, J., Gonzalo, A. Brossa, Brown, J., Brundu, D., Buchanan, E., Buonaura, A., Buonincontri, L., Burke, A. T., Burr, C., Butter, J. S., Buytaert, J., Byczynski, W., Cadeddu, S., Cai, H., Caillet, A. C., Calabrese, R., Ramirez, S. Calderon, Calefice, L., Cali, S., Calvi, M., Gomez, M. Calvo, Magalhaes, P. Camargo, Bouzas, J. I. Cambon, Campana, P., Perez, D. H. Campora, Quezada, A. F. Campoverde, Capelli, S., Capriotti, L., Caravaca-Mora, R., Carbone, A., Salgado, L. Carcedo, Cardinale, R., Cardini, A., Carniti, P., Carus, L., Vidal, A. Casais, Caspary, R., Casse, G., Godinez, J. Castro, Cattaneo, M., Cavallero, G., Cavallini, V., Celani, S., Cervenkov, D., Cesare, S., Chadwick, A. J., Chahrour, I., Charles, M., Charpentier, Ph., Chatzianagnostou, E., Chefdeville, M., Chen, C., Chen, S., Chen, Z., Chernov, A., Chernyshenko, S., Chiotopoulos, X., Chobanova, V., Cholak, S., Chrzaszcz, M., Chubykin, A., Chulikov, V., Ciambrone, P., Vidal, X. Cid, Ciezarek, G., Cifra, P., Clarke, P. E. L., Clemencic, M., Cliff, H. V., Closier, J., Toapaxi, C. Cocha, Coco, V., Cogan, J., Cogneras, E., Cojocariu, L., Collins, P., Colombo, T., Colonna, M. C., Comerma-Montells, A., Congedo, L., Contu, A., Cooke, N., Corredoira, I., Correia, A., Corti, G., Meldrum, J. J. Cottee, Couturier, B., Craik, D. C., Torres, M. Cruz, Rivera, E. Curras, Currie, R., Da Silva, C. L., Dadabaev, S., Dai, L., Dai, X., Dall'Occo, E., Dalseno, J., D'Ambrosio, C., Daniel, J., Danilina, A., d'Argent, P., Davidson, A., Davies, J. E., Davis, A., Francisco, O. De Aguiar, De Angelis, C., De Benedetti, F., de Boer, J., De Bruyn, K., De Capua, S., De Cian, M., Da Graca, U. De Freitas Carneiro, De Lucia, E., De Miranda, J. M., De Paula, L., De Serio, M., De Simone, P., De Vellis, F., de Vries, J. A., Debernardis, F., Decamp, D., Dedu, V., Dekkers, S., Del Buono, L., Delaney, B., Dembinski, H. -P., Deng, J., Denysenko, V., Deschamps, O., Dettori, F., Dey, B., Di Nezza, P., Diachkov, I., Didenko, S., Ding, S., Dittmann, L., Dobishuk, V., Docheva, A. D., Dong, C., Donohoe, A. M., Dordei, F., Reis, A. C. dos, Dowling, A. D., Duan, W., Duda, P., Dudek, M. W., Dufour, L., Duk, V., Durante, P., Duras, M. M., Durham, J. M., Durmus, O. D., Dziurda, A., Dzyuba, A., Easo, S., Eckstein, E., Egede, U., Egorychev, A., Egorychev, V., Eisenhardt, S., Ejopu, E., Eklund, L., Elashri, M., Ellbracht, J., Ely, S., Ene, A., Epple, E., Eschle, J., Esen, S., Evans, T., Fabiano, F., Falcao, L. N., Fan, Y., Fang, B., Fantini, L., Faria, M., Farmer, K., Fazzini, D., Felkowski, L., Feng, M., Feo, M., Casani, A. Fernandez, Gomez, M. Fernandez, Fernez, A. D., Ferrari, F., Rodrigues, F. Ferreira, Ferrillo, M., Ferro-Luzzi, M., Filippov, S., Fini, R. A., Fiorini, M., Firlej, M., Fischer, K. L., Fitzgerald, D. S., Fitzpatrick, C., Fiutowski, T., Fleuret, F., Fontana, M., Foreman, L. F., Forty, R., Foulds-Holt, D., Lima, V. Franco, Sevilla, M. Franco, Frank, M., Franzoso, E., Frau, G., Frei, C., Friday, D. A., Fu, J., Fuehring, Q., Fujii, Y., Fulghesu, T., Gabriel, E., Galati, G., Galati, M. D., Torreira, A. Gallas, Galli, D., Gambetta, S., Gandelman, M., Gandini, P., Ganie, B., Gao, H., Gao, R., Gao, T. Q., Gao, Y., Garau, M., Martin, L. M. Garcia, Moreno, P. Garcia, Pardiñas, J. García, Garg, K. G., Garrido, L., Gaspar, C., Geertsema, R. E., Gerken, L. L., Gersabeck, E., Gersabeck, M., Gershon, T., Ghizzo, S. G., Ghorbanimoghaddam, Z., Giambastiani, L., Giasemis, F. I., Gibson, V., Giemza, H. K., Gilman, A. L., Giovannetti, M., Gioventù, A., Girardey, L., Gironell, P. Gironella, Giugliano, C., Giza, M. A., Gkougkousis, E. L., Glaser, F. C., Gligorov, V. V., Göbel, C., Golobardes, E., Golubkov, D., Golutvin, A., Gomes, A., Fernandez, S. Gomez, Abrantes, F. Goncalves, Goncerz, M., Gong, G., Gooding, J. A., Gorelov, I. V., Gotti, C., Grabowski, J. P., Cardoso, L. A. Granado, Graugés, E., Graverini, E., Grazette, L., Graziani, G., Grecu, A. T., Greeven, L. M., Grieser, N. A., Grillo, L., Gromov, S., Gu, C., Guarise, M., Guerry, L., Guittiere, M., Guliaeva, V., Günther, P. A., Guseinov, A. -K., Gushchin, E., Guz, Y., Gys, T., Habermann, K., Hadavizadeh, T., Hadjivasiliou, C., Haefeli, G., Haen, C., Haimberger, J., Hajheidari, M., Hallett, G. H., Halvorsen, M. M., Hamilton, P. M., Hammerich, J., Han, Q., Han, X., Hansmann-Menzemer, S., Hao, L., Harnew, N., Hartmann, M., Hashmi, S., He, J., Hemmer, F., Henderson, C., Henderson, R. D. L., Hennequin, A. M., Hennessy, K., Henry, L., Herd, J., Gascon, P. Herrero, Heuel, J., Hicheur, A., Mendizabal, G. Hijano, Hill, D., Hollitt, S. E., Horswill, J., Hou, R., Hou, Y., Howarth, N., Hu, J., Hu, W., Hu, X., Huang, W., Hulsbergen, W., Hunter, R. J., Hushchyn, M., Hutchcroft, D., Idzik, M., Ilin, D., Ilten, P., Inglessi, A., Iniukhin, A., Ishteev, A., Ivshin, K., Jacobsson, R., Jage, H., Elles, S. J. Jaimes, Jakobsen, S., Jans, E., Jashal, B. K., Jawahery, A., Jevtic, V., Jiang, E., Jiang, X., Jiang, Y., Jiang, Y. J., John, M., Rajan, A. John Rubesh, Johnson, D., Jones, C. R., Jones, T. P., Joshi, S., Jost, B., Castella, J. Juan, Jurik, N., Juszczak, I., Kaminaris, D., Kandybei, S., Kane, M., Kang, Y., Kar, C., Karacson, M., Karpenkov, D., Kauniskangas, A., Kautz, J. W., Kazanecki, M. K., Keizer, F., Kenzie, M., Ketel, T., Khanji, B., Kharisova, A., Kholodenko, S., Khreich, G., Kirn, T., Kirsebom, V. S., Kitouni, O., Klaver, S., Kleijne, N., Klimaszewski, K., Kmiec, M. R., Koliiev, S., Kolk, L., Konoplyannikov, A., Kopciewicz, P., Koppenburg, P., Korolev, M., Kostiuk, I., Kot, O., Kotriakhova, S., Kozachuk, A., Kravchenko, P., Kravchuk, L., Kreps, M., Krokovny, P., Krupa, W., Krzemien, W., Kshyvanskyi, O. K., Kubis, S., Kucharczyk, M., Kudryavtsev, V., Kulikova, E., Kupsc, A., Kutsenko, B. K., Lacarrere, D., Gonzalez, P. Laguarta, Lai, A., Lampis, A., Lancierini, D., Gomez, C. Landesa, Lane, J. J., Lane, R., Lanfranchi, G., Langenbruch, C., Langer, J., Lantwin, O., Latham, T., Lazzari, F., Lazzeroni, C., Gac, R. Le, Lee, H., Lefèvre, R., Leflat, A., Legotin, S., Lehuraux, M., Cid, E. Lemos, Leroy, O., Lesiak, T., Lesser, E., Leverington, B., Li, A., Li, C., Li, H., Li, K., Li, L., Li, M., Li, P., Li, P. -R., Li, Q., Li, S., Li, T., Li, Y., Lian, Z., Liang, X., Libralon, S., Lin, C., Lin, T., Lindner, R., Lisovskyi, V., Litvinov, R., Liu, F. L., Liu, G., Liu, K., Liu, S., Liu, W., Liu, Y., Liu, Y. L., Salvia, A. Lobo, Loi, A., Castro, J. Lomba, Long, T., Lopes, J. H., Huertas, A. Lopez, Soliño, S. López, Lu, Q., Lucarelli, C., Lucchesi, D., Martinez, M. Lucio, Lukashenko, V., Luo, Y., Lupato, A., Luppi, E., Lynch, K., Lyu, X. -R., Ma, G. M., Ma, R., Maccolini, S., Machefert, F., Maciuc, F., Mack, B., Mackay, I., Mackey, L. M., Mohan, L. R. Madhan, Madurai, M. J., Maevskiy, A., Magdalinski, D., Maisuzenko, D., Majewski, M. W., Malczewski, J. J., Malde, S., Malentacca, L., Malinin, A., Maltsev, T., Manca, G., Mancinelli, G., Mancuso, C., Escalero, R. Manera, Manuzzi, D., Marangotto, D., Marchand, J. F., Marchevski, R., Marconi, U., Mariani, E., Mariani, S., Benito, C. Marin, Marks, J., Marshall, A. M., Martel, L., Martelli, G., Martellotti, G., Martinazzoli, L., Martinelli, M., Santos, D. Martinez, Vidal, F. Martinez, Massafferri, A., Matev, R., Mathad, A., Matiunin, V., Matteuzzi, C., Mattioli, K. R., Mauri, A., Maurice, E., Mauricio, J., Mayencourt, P., de Cos, J. Mazorra, Mazurek, M., McCann, M., Mcconnell, L., McGrath, T. H., McHugh, N. T., McNab, A., McNulty, R., Meadows, B., Meier, G., Melnychuk, D., Meng, F. M., Merk, M., Merli, A., Garcia, L. Meyer, Miao, D., Miao, H., Mikhasenko, M., Milanes, D. A., Minotti, A., Minucci, E., Miralles, T., Mitreska, B., Mitzel, D. S., Modak, A., Mohammed, R. A., Moise, R. D., Mokhnenko, S., Cardenas, E. F. Molina, Mombächer, T., Monk, M., Monteil, S., Gomez, A. Morcillo, Morello, G., Morello, M. J., Morgenthaler, M. P., Moron, J., Morris, A. B., Morris, A. G., Mountain, R., Mu, H., Mu, Z. M., Muhammad, E., Muheim, F., Mulder, M., Müller, K., Muñoz-Rojas, F., Murta, R., Naik, P., Nakada, T., Nandakumar, R., Nanut, T., Nasteva, I., Needham, M., Neri, N., Neubert, S., Neufeld, N., Neustroev, P., Nicolini, J., Nicotra, D., Niel, E. M., Nikitin, N., Nogarolli, P., Nogga, P., Normand, C., Fernandez, J. Novoa, Nowak, G., Nunez, C., Nur, H. N., Oblakowska-Mucha, A., Obraztsov, V., Oeser, T., Okamura, S., Okhotnikov, A., Okhrimenko, O., Oldeman, R., Oliva, F., Olocco, M., Onderwater, C. J. G., O'Neil, R. H., Osthues, D., Goicochea, J. M. Otalora, Owen, P., Oyanguren, A., Ozcelik, O., Paciolla, F., Padee, A., Padeken, K. O., Pagare, B., Pais, P. R., Pajero, T., Palano, A., Palutan, M., Panshin, G., Paolucci, L., Papanestis, A., Pappagallo, M., Pappalardo, L. L., Pappenheimer, C., Parkes, C., Passalacqua, B., Passaleva, G., Passaro, D., Pastore, A., Patel, M., Patoc, J., Patrignani, C., Paul, A., Pawley, C. J., Pellegrino, A., Peng, J., Altarelli, M. Pepe, Perazzini, S., Pereima, D., Da Costa, H. Pereira, Castro, A. Pereiro, Perret, P., Perro, A., Petridis, K., Petrolini, A., Pfaller, J. P., Pham, H., Pica, L., Piccini, M., Piccolo, L., Pietrzyk, B., Pietrzyk, G., Pinci, D., Pisani, F., Pizzichemi, M., Placinta, V., Casasus, M. Plo, Poeschl, T., Polci, F., Lener, M. Poli, Poluektov, A., Polukhina, N., Polyakov, I., Polycarpo, E., Ponce, S., Popov, D., Poslavskii, S., Prasanth, K., Prouve, C., Provenzano, D., Pugatch, V., Punzi, G., Qasim, S., Qian, Q. Q., Qian, W., Qin, N., Qu, S., Quagliani, R., Trejo, R. I. Rabadan, Rademacker, J. H., Rama, M., García, M. Ramírez, De Oliveira, V. Ramos, Pernas, M. Ramos, Rangel, M. S., Ratnikov, F., Raven, G., De Miguel, M. Rebollo, Redi, F., Reich, J., Reiss, F., Ren, Z., Resmi, P. K., Ribatti, R., Ricart, G. R., Riccardi, D., Ricciardi, S., Richardson, K., Richardson-Slipper, M., Rinnert, K., Robbe, P., Robertson, G., Rodrigues, E., Fernandez, E. Rodriguez, Lopez, J. A. Rodriguez, Rodriguez, E. Rodriguez, Roensch, J., Rogachev, A., Rogovskiy, A., Rolf, D. L., Roloff, P., Romanovskiy, V., Lamas, M. Romero, Vidal, A. Romero, Romolini, G., Ronchetti, F., Rong, T., Rotondo, M., Roy, S. R., Rudolph, M. S., Diaz, M. Ruiz, Fernandez, R. A. Ruiz, Vidal, J. Ruiz, Ryzhikov, A., Ryzka, J., Saavedra-Arias, J. J., Silva, J. J. Saborido, Sadek, R., Sagidova, N., Sahoo, D., Sahoo, N., Saitta, B., Salomoni, M., Sanderswood, I., Santacesaria, R., Rios, C. Santamarina, Santimaria, M., Santoro, L., Santovetti, E., Saputi, A., Saranin, D., Sarnatskiy, A., Sarpis, G., Sarpis, M., Satriano, C., Satta, A., Saur, M., Savrina, D., Sazak, H., Smead, L. G. Scantlebury, Scarabotto, A., Schael, S., Scherl, S., Schiller, M., Schindler, H., Schmelling, M., Schmidt, B., Schmitt, S., Schmitz, H., Schneider, O., Schopper, A., Schulte, N., Schulte, S., Schune, M. H., Schwemmer, R., Schwering, G., Sciascia, B., Sciuccati, A., Sellam, S., Semennikov, A., Senger, T., Soares, M. Senghi, Sergi, A., Serra, N., Sestini, L., Seuthe, A., Shang, Y., Shangase, D. M., Shapkin, M., Sharma, R. S., Shchemerov, I., Shchutska, L., Shears, T., Shekhtman, L., Shen, Z., Sheng, S., Shevchenko, V., Shi, B., Shi, Q., Shimizu, Y., Shmanin, E., Shorkin, R., Shupperd, J. D., Coutinho, R. Silva, Simi, G., Simone, S., Skidmore, N., Skwarnicki, T., Slater, M. W., Smallwood, J. C., Smith, E., Smith, K., Smith, M., Snoch, A., Lavra, L. Soares, Sokoloff, M. D., Soler, F. J. P., Solomin, A., Solovev, A., Solovyev, I., Song, R., Song, Y., Song, Y. S., De Almeida, F. L. Souza, De Paula, B. Souza, Norella, E. Spadaro, Spedicato, E., Speer, J. G., Spiridenkov, E., Spradlin, P., Sriskaran, V., Stagni, F., Stahl, M., Stahl, S., Stanislaus, S., Stein, E. N., Steinkamp, O., Stenyakin, O., Stevens, H., Strekalina, D., Su, Y., Suljik, F., Sun, J., Sun, L., Sun, Y., Sundfeld, D., Sutcliffe, W., Swallow, P. N., Swientek, K., Swystun, F., Szabelski, A., Szumlak, T., Tan, Y., Tat, M. D., Terentev, A., Terzuoli, F., Teubert, F., Thomas, E., Thompson, D. J. D., Tilquin, H., Tisserand, V., T'Jampens, S., Tobin, M., Tomassetti, L., Tonani, G., Tong, X., Machado, D. Torres, Toscano, L., Tou, D. Y., Trippl, C., Tuci, G., Tuning, N., Uecker, L. H., Ukleja, A., Unverzagt, D. J., Ursov, E., Usachov, A., Ustyuzhanin, A., Uwer, U., Vagnoni, V., Cadenas, V. Valcarce, Valenti, G., Canudas, N. Valls, Van Hecke, H., van Herwijnen, E., Van Hulse, C. B., Van Laak, R., van Veghel, M., Vasquez, G., Gomez, R. Vazquez, Regueiro, P. Vazquez, Sierra, C. Vázquez, Vecchi, S., Velthuis, J. J., Veltri, M., Venkateswaran, A., Verdoglia, M., Vesterinen, M., Benet, D. Vico, Villalba, P. V. Vidrier, Diaz, M. Vieites, Vilasis-Cardona, X., Figueras, E. Vilella, Villa, A., Vincent, P., Volle, F. C., Bruch, D. vom, Voropaev, N., Vos, K., Vouters, G., Vrahas, C., Wagner, J., Walsh, J., Walton, E. J., Wan, G., Wang, C., Wang, G., Wang, J., Wang, M., Wang, N. W., Wang, R., Wang, X., Wang, X. W., Wang, Y., Wang, Z., Ward, J. A., Waterlaat, M., Watson, N. K., Websdale, D., Wei, Y., Wendel, J., Westhenry, B. D. C., White, C., Whitehead, M., Whiter, E., Wiederhold, A. R., Wiedner, D., Wilkinson, G., Wilkinson, M. K., Williams, M., Williams, M. R. J., Williams, R., Williams, Z., Wilson, F. F., Wislicki, W., Witek, M., Witola, L., Wormser, G., Wotton, S. A., Wu, H., Wu, J., Wu, Y., Wu, Z., Wyllie, K., Xian, S., Xiang, Z., Xie, Y., Xu, A., Xu, J., Xu, L., Xu, M., Xu, Z., Yang, D., Yang, K., Yang, S., Yang, X., Yang, Y., Yang, Z., Yeroshenko, V., Yeung, H., Yin, H., Yu, C. Y., Yu, J., Yuan, X., Yuan, Y, Zaffaroni, E., Zavertyaev, M., Zdybal, M., Zenesini, F., Zeng, C., Zeng, M., Zhang, C., Zhang, D., Zhang, J., Zhang, L., Zhang, S., Zhang, Y., Zhang, Y. Z., Zhao, Y., Zharkova, A., Zhelezov, A., Zheng, S. Z., Zheng, X. Z., Zheng, Y., Zhou, T., Zhou, X., Zhou, Y., Zhovkovska, V., Zhu, L. Z., Zhu, X., Zhukov, V., Zhuo, J., Zou, Q., Zuliani, D., and Zunica, G.
- Subjects
High Energy Physics - Experiment - Abstract
The decays of the $\chi_{b1}(1P)$, $\chi_{b2}(1P)$, $\chi_{b1}(2P)$ and $\chi_{b2}(2P)$~mesons into the~$\Upsilon(1S)\mu^+\mu^-$ final state are observed with a high significance using proton-proton collision data collected with the LHCb detector and corresponding to an integrated luminosity of 9fb$^{-1}$. The newly observed decays together with the $\Upsilon(2S)\rightarrow \Upsilon(1S)\pi^+\pi^-$ and $\Upsilon(3S)\rightarrow \Upsilon(2S)\pi^+\pi^-$ decay modes are used for precision measurements of the mass and mass splittings for the hidden-beauty states., Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2024-025.html
- Published
- 2024
36. LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection
- Author
-
Abassy, Mervat, Elozeiri, Kareem, Aziz, Alexander, Ta, Minh Ngoc, Tomar, Raj Vardhan, Adhikari, Bimarsha, Ahmed, Saad El Dine, Wang, Yuxia, Afzal, Osama Mohammed, Xie, Zhuohan, Mansurov, Jonibek, Artemova, Ekaterina, Mikhailov, Vladislav, Xing, Rui, Geng, Jiahui, Iqbal, Hasan, Mujahid, Zain Muhammad, Mahmoud, Tarek, Tsvigun, Akim, Aji, Alham Fikri, Shelmanov, Artem, Habash, Nizar, Gurevych, Iryna, and Nakov, Preslav
- Subjects
Computer Science - Computation and Language - Abstract
The widespread accessibility of large language models (LLMs) to the general public has significantly amplified the dissemination of machine-generated texts (MGTs). Advancements in prompt manipulation have exacerbated the difficulty in discerning the origin of a text (human-authored vs machinegenerated). This raises concerns regarding the potential misuse of MGTs, particularly within educational and academic domains. In this paper, we present $\textbf{LLM-DetectAIve}$ -- a system designed for fine-grained MGT detection. It is able to classify texts into four categories: human-written, machine-generated, machine-written machine-humanized, and human-written machine-polished. Contrary to previous MGT detectors that perform binary classification, introducing two additional categories in LLM-DetectiAIve offers insights into the varying degrees of LLM intervention during the text creation. This might be useful in some domains like education, where any LLM intervention is usually prohibited. Experiments show that LLM-DetectAIve can effectively identify the authorship of textual content, proving its usefulness in enhancing integrity in education, academia, and other domains. LLM-DetectAIve is publicly accessible at https://huggingface.co/spaces/raj-tomar001/MGT-New. The video describing our system is available at https://youtu.be/E8eT_bE7k8c.
- Published
- 2024
37. Hierarchical Neural Constructive Solver for Real-world TSP Scenarios
- Author
-
Goh, Yong Liang, Cao, Zhiguang, Ma, Yining, Dong, Yanfei, Dupty, Mohammed Haroon, and Lee, Wee Sun
- Subjects
Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Existing neural constructive solvers for routing problems have predominantly employed transformer architectures, conceptualizing the route construction as a set-to-sequence learning task. However, their efficacy has primarily been demonstrated on entirely random problem instances that inadequately capture real-world scenarios. In this paper, we introduce realistic Traveling Salesman Problem (TSP) scenarios relevant to industrial settings and derive the following insights: (1) The optimal next node (or city) to visit often lies within proximity to the current node, suggesting the potential benefits of biasing choices based on current locations. (2) Effectively solving the TSP requires robust tracking of unvisited nodes and warrants succinct grouping strategies. Building upon these insights, we propose integrating a learnable choice layer inspired by Hypernetworks to prioritize choices based on the current location, and a learnable approximate clustering algorithm inspired by the Expectation-Maximization algorithm to facilitate grouping the unvisited cities. Together, these two contributions form a hierarchical approach towards solving the realistic TSP by considering both immediate local neighbourhoods and learning an intermediate set of node representations. Our hierarchical approach yields superior performance compared to both classical and recent transformer models, showcasing the efficacy of the key designs., Comment: Accepted to KDD 2024
- Published
- 2024
- Full Text
- View/download PDF
38. Pan-African Citizen Science e-Lab: An Emerging Online Platform for Astronomy Research, Education and Outreach in Africa
- Author
-
Marcel, Miracle Chibuzor, Diaby, Kassamba Abdel Aziz, Guennoun, Meryem, Nabifo, Betty Rose, Elattar, Mohamed, Rajaonarivelo, Andoniaina, Pius, Privatus, Kgobathe, Molly Nkamogelang, Luis, Immanuel, Shilunga, Sigrid, Etteyeb, Nejmeddine, Qhomane, Keketso, Nyangi, Samuel, Kalunga, Tresford Chilufya, Assano, Nunes Alfredo, Jequecene, Edson Domingos, Joseph, Mafuka Lusala, Sudum, Esaenwi, Gerald, Jorbedom Leelabari, Gore, Christopher Tombe Louis, Hosny, Kareem Waleed, Yasser, Nagat, Franck, Jocelyn, Kourouma, Mamoudou, Bobb, Baboucarr, Jaiteh, Kebab, Sylla, Salma, Obame, Hans Essone, Kiyeng, Dennis, Ngwanw, Thobekile Sandra, Simon, Tawanda Kelvin, Sulayman, Saja Alhoush, Regaibi, Salma, Yahaya, Souley, Ornela, Tengwi Mogou, Viyuyi, Henry Sanderson, Matambo, Fortune Tatenda, Asare-Darko, Matthias, Gbaba, Christian Kontoa Koussouwa, da Silva, Moisés, Joseph, Ntahompagaze, Gomes, Gilberto, Mkhabela, Bongiwe Portia, Bvumbwe, Bauleni, Nkhowani, Tshombe, Gahou, Mawugnon Axel, Abotsi-Masters, Sarah, Simbizi, René, Mugisha, Salomon, Saeed, Ahmed, Eldaw, Mohammed Yahya Alradi, Thomas, Allen, ridha, Ben Abdallah, kaseha, Dieumerci, Baradei, Sherine Ahmed El, Hussein, Nahla Hazem, Fabrice, Bado, Anekwe, Ngozika Frances, Ramessur, Arvind, Koroma, Mohamed Ali, Safary, Harold, Leonardo, Oosthuizen, Dlamini, Mdumiseni Wisdom Dabulizwe, Djabbi, Mamadou Mahamat, Angela, Nonofo, Jalloh, Mamaja, Balde, Mamadou, Olayiwola, Joy, Ibharalu, Elijah, Tchangole, Thierry Martial, Memberu, Kirubel, Dinsa, Lidia, and Ezeakunne, Chidozie Gospel
- Subjects
Astrophysics - Instrumentation and Methods for Astrophysics ,Physics - Physics Education - Abstract
Citizen science offers an opportunity for ordinary people, known as citizen scientists or citizen astronomers in the context of astronomy, to contribute to scientific research. The Pan-African Citizen Science e-Lab (PACS e-Lab) was founded to promote and engage the African public in citizen science and soft astronomy research to advance space research and exploration and enhance space education and outreach. PACS e-Lab, in collaboration with several international astronomy research, education, and outreach organizations, currently runs several projects including but not limited to asteroid search, exoplanet photometry, research writing for peer-reviewed publications, astrophoto visual development, and Amateur Radio contact with astronauts aboard the International Space Station (ARISS). Despite several challenges, the group has engaged over 600 Africans from more than 40 countries and is working towards covering the entire continent in the future. PACS e-Lab's development efforts resonate with seven United Nations Sustainable Development Goals (UN-SDGs)., Comment: 32 pages,17 figures, 2 Tables
- Published
- 2024
39. Pan-African Asteroid Search Campaign: Africa's Contribution to Planetary Defense
- Author
-
Marcel, Miracle Chibuzor, Diaby, Kassamba Abdel Aziz, Guennoun, Meryem, Nabifo, Betty Rose, Elattar, Mohamed, Rajaonarivelo, Andoniaina, Pius, Privatus, Kgobathe, Molly Nkamogelang, Luis, Immanuel, Shilunga, Sigrid, Etteyeb, Nejmeddine, Qhomane, Keketso, Nyangi, Samuel, Kalunga, Tresford Chilufya, Assano, Nunes Alfredo, Jequecene, Edson Domingos, Joseph, Mafuka Lusala, Sudum, Esaenwi, Gerald, Jorbedom Leelabari, Gore, Christopher Tombe Louis, Hosny, Kareem Waleed, Yasser, Nagat, Franck, Jocelyn, Kourouma, Mamoudou, Bobb, Baboucarr, Jaiteh, Kebab, Sylla, Salma, Obame, Hans Essone, Kiyeng, Dennis, Ngwanw, Thobekile Sandra, Simon, Tawanda Kelvin, Sulayman, Saja Alhoush, Regaibi, Salma, Yahaya, Souley, Ornela, Tengwi Mogou, Viyuyi, Henry Sanderson, Matambo, Fortune Tatenda, Asare-Darko, Matthias, Gbaba, Christian Kontoa Koussouwa, da Silva, Moisés, Joseph, Ntahompagaze, Gomes, Gilberto, Mkhabela, Bongiwe Portia, Bvumbwe, Bauleni, Nkhowani, Tshombe, Gahou, Mawugnon Axel, Abotsi-Masters, Sarah, Simbizi, René, Mugisha, Salomon, Saeed, Ahmed, Eldaw, Mohammed Yahya Alradi, Thomas, Allen, ridha, Ben Abdallah, kaseha, Dieumerci, Baradei, Sherine Ahmed El, Hussein, Nahla Hazem, Fabrice, Bado, Anekwe, Ngozika Frances, Ramessur, Arvind, Koroma, Mohamed Ali, Safary, Harold, Leonardo, Oosthuizen, Dlamini, Mdumiseni Wisdom Dabulizwe, Djabbi, Mamadou Mahamat, Angela, Nonofo, Jalloh, Mamaja, Balde, Mamadou, Olayiwola, Joy, Ibharalu, Elijah, Tchangole, Thierry Martial, Memberu, Kirubel, Dinsa, Lidia, and Ezeakunne, Chidozie Gospel
- Subjects
Physics - Physics Education ,Astrophysics - Earth and Planetary Astrophysics - Abstract
Asteroid search is a global effort for planetary defense. The International Astronomical Search Collaboration (IASC) is the leading global educational outreach program that provides high-quality astronomical datasets to citizen scientists to discover asteroids. Since December 4, 2020, the Pan-African Citizen Science e-Lab (PACS e-Lab) has been IASC's biggest partner on the continent in recruiting and training citizen scientists in asteroid search endeavors. Over 30 asteroids have been discovered by 60 citizen scientists. About 595 citizen scientists from over 40 countries have been engaged in the project up to the time of composing this literature. The group is set to expand its endeavors to the rest of the continent and aims to engage thousands of citizen scientists., Comment: 16 pages, 10 figures, 5 Tables
- Published
- 2024
40. Segment Anything in Medical Images and Videos: Benchmark and Deployment
- Author
-
Ma, Jun, Kim, Sumin, Li, Feifei, Baharoon, Mohammed, Asakereh, Reza, Lyu, Hongwei, and Wang, Bo
- Subjects
Electrical Engineering and Systems Science - Image and Video Processing ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Recent advances in segmentation foundation models have enabled accurate and efficient segmentation across a wide range of natural images and videos, but their utility to medical data remains unclear. In this work, we first present a comprehensive benchmarking of the Segment Anything Model 2 (SAM2) across 11 medical image modalities and videos and point out its strengths and weaknesses by comparing it to SAM1 and MedSAM. Then, we develop a transfer learning pipeline and demonstrate SAM2 can be quickly adapted to medical domain by fine-tuning. Furthermore, we implement SAM2 as a 3D slicer plugin and Gradio API for efficient 3D image and video segmentation. The code has been made publicly available at \url{https://github.com/bowang-lab/MedSAM}.
- Published
- 2024
41. GUP corrected Casimir Wormholes with Electric Charge in $f(R,L_m)$ Gravity
- Author
-
Rizwan, Mohammed Muzakkir, Hassan, Zinnat, and Sahoo, P. K.
- Subjects
General Relativity and Quantum Cosmology ,High Energy Physics - Theory - Abstract
In this letter, we study and investigate the effects of the Generalised Uncertainty Principle (GUP) and electric charge on Casimir wormhole geometry in the Curvature-Lagrangian coupled $f(R,L_m)$ gravity. The functional form of the considered model is $f(R,L_m)=\frac{R}{2\kappa}+L_m^{\,\,\alpha}$, corresponding to it the analytic shape function is found. For our analysis, we study the wormhole spacetimes for three particular models for the redshift function. We observe that the null energy condition is violated despite a positive contribution from the electromagnetic energy density. We also note that electric charges, GUP effects, and higher model parameter values increase the throat length. Further, we have studied the deflection of light using the Gauss-Bonnet theorem, emphasizing the contribution from GUP by including higher-order terms., Comment: Comments are welcome
- Published
- 2024
42. Efficient ECC-based authentication scheme for fog-based IoT environment
- Author
-
Shaaban, Mohamed Ali, Alsharkawy, Almohammady S., AbouKreisha, Mohammad T., and Razek, Mohammed Abdel
- Subjects
Computer Science - Cryptography and Security - Abstract
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
- Published
- 2024
- Full Text
- View/download PDF
43. Log-Gaussian Cox Processes for Spatiotemporal Traffic Fatality Estimation in Addis Ababa
- Author
-
Abebe, Yassin Tesfaw, Seid, Abdu Mohammed, and Roininen, Lassi
- Subjects
Statistics - Applications - Abstract
We investigate the spatiotemporal dynamics of traffic accidents in Addis Ababa, Ethiopia, using 2016--2019 data. We formulate the traffic accident intensity as a log-Gaussian Cox Process and model it as a spatiotemporal point process with and without fixed and random effect components that incorporate possible covariates and spatial correlation information. The covariate includes population density and distance of accident locations from schools, from markets, from bus stops and from worship places. We estimate the posterior of the state variables using integrated nested Laplace approximations with stochastic partial differential equations approach by considering Mat\`ern prior. Deviance and Watanabe - Akaike information criteria are used to check the performance of the models. We implement the methodology to map traffic accident intensity over Addis Ababa entirely and on its road networks and visualize the potential traffic accident hotspot areas. The comparison of the observation with the model output reveals that the covariates considered has significant effect for the accident intensity. Moreover, the information criteria results reveal the model with covariate performs well compared with the model without covariates. We obtained temporal correlation of the log-intensity as 0.78 indicating the existence of similar traffic fatality trend in space during the study period.
- Published
- 2024
44. Post-Newtonian observables for aligned-spin binaries to sixth order in spin from gravitational self-force and Compton amplitudes
- Author
-
Bautista, Yilber Fabian, Khalil, Mohammed, Sergola, Matteo, Kavanagh, Chris, and Vines, Justin
- Subjects
General Relativity and Quantum Cosmology ,High Energy Physics - Theory - Abstract
Accurate modeling of compact binaries is essential for gravitational-wave detection and parameter estimation, with spin being an important effect to include in waveform models. In this paper, we derive new post-Newtonian (PN) results for the conservative aligned-spin dynamics at next-to-next-to-leading order for the spin$^3$ and spin$^4$ contributions, in addition to the next-to-leading order (NLO) spin$^5$ and spin$^6$ contributions. One approach we follow is the Tutti Frutti method, which relates PN and gravitational self-force (GSF) results through the redshift and spin-precession invariants, by making use of the simple dependence of the scattering angle on the symmetric mass ratio. However, an ambiguity arises at the NLO spin$^5$ contribution, due to transcendental functions of the Kerr spin in the redshift; this is also the order at which Compton amplitudes calculations are affected by spurious poles. Therefore, we follow an additional approach to determine the NLO spin$^5$ and spin$^6$ dynamics: using on-shell Compton amplitudes obtained from black hole perturbation theory. The Compton amplitude used in this work is composed of the unambiguous tree-level far-zone part reported in [Phys. Rev. D 109, no.8, 084071 (2024)], as well as the full, non-interfering with the far-zone, $\ell=2$ partial wave contributions from the near zone, which are responsible for capturing Kerr finite-size effects. Other results in this paper include deriving the scattering angle of a spinning test body in a Kerr background from a parametrized worldline action, and computing the redshift and spin-precession invariants for eccentric orbits without an eccentricity expansion., Comment: 35 pages, 3 ancillary files
- Published
- 2024
45. On a novel fractional Caputo-derivative Orlicz space
- Author
-
Ayoub, Kasmi, Houssine, Azroul El, and Mohammed, Shimi
- Subjects
Mathematics - Functional Analysis ,Mathematics - Analysis of PDEs ,46E30, 46E35, 35R11, 35A15 - Abstract
In this work, we aim to explore whether a novel type of fractional space can be defined using Orlicz spaces and fractional calculus. This inquiry is fruitful, as extending classical results to new contexts can lead to a better and deeper understanding of those classical results. Our main objective is to introduce a new fractional Caputo-derivative Orlicz space, denoted by $\mathcal{O}^{\alpha,G}(\Lambda, \mathbb{R}) $. We are interested in several qualitative properties of this space, such as reflexivity, completeness, and separability. Additionally, we establish a continuous embedding results of this space into a suitable Orlicz space and the space of continuous functions. As an application, we use the mountain-pass theorem (MPT) to ensure the existence of a nontrivial weak solution for a new class of fractional-type problems in Orlicz space.
- Published
- 2024
46. TransRx-6G-V2X : Transformer Encoder-Based Deep Neural Receiver For Next Generation of Cellular Vehicular Communications
- Author
-
Saleem, Osama, Ribouh, Soheyb, Alfaqawi, Mohammed, Bensrhair, Abdelaziz, and Merdrignac, Pierre
- Subjects
Electrical Engineering and Systems Science - Signal Processing - Abstract
End-to-end wireless communication is new concept expected to be widely used in the physical layer of future wireless communication systems (6G). It involves the substitution of transmitter and receiver block components with a deep neural network (DNN), aiming to enhance the efficiency of data transmission. This will ensure the transition of autonomous vehicles (AVs) from self-autonomy to full collaborative autonomy, that requires vehicular connectivity with high data throughput and minimal latency. In this article, we propose a novel neural network receiver based on transformer architecture, named TransRx, designed for vehicle-to-network (V2N) communications. The TransRx system replaces conventional receiver block components in traditional communication setups. We evaluated our proposed system across various scenarios using different parameter sets and velocities ranging from 0 to 120 km/h over Urban Macro-cell (UMa) channels as defined by 3GPP. The results demonstrate that TransRx outperforms the state-of-the-art systems, achieving a 3.5dB improvement in convergence to low Bit Error Rate (BER) compared to convolutional neural network (CNN)-based neural receivers, and an 8dB improvement compared to traditional baseline receiver configurations. Furthermore, our proposed system exhibits robust generalization capabilities, making it suitable for deployment in large-scale environments.
- Published
- 2024
47. Future of Artificial Intelligence in Agile Software Development
- Author
-
Mahboob, Mariyam, Ahmed, Mohammed Rayyan Uddin, Zia, Zoiba, Ali, Mariam Shakeel, and Ahmed, Ayman Khaleel
- Subjects
Computer Science - Software Engineering ,Computer Science - Artificial Intelligence - Abstract
The advent of Artificial intelligence has promising advantages that can be utilized to transform the landscape of software project development. The Software process framework consists of activities that constantly require routine human interaction, leading to the possibility of errors and uncertainties. AI can assist software development managers, software testers, and other team members by leveraging LLMs, GenAI models, and AI agents to perform routine tasks, risk analysis and prediction, strategy recommendations, and support decision making. AI has the potential to increase efficiency and reduce the risks encountered by the project management team while increasing the project success rates. Additionally, it can also break down complex notions and development processes for stakeholders to make informed decisions. In this paper, we propose an approach in which AI tools and technologies can be utilized to bestow maximum assistance for agile software projects, which have become increasingly favored in the industry in recent years.
- Published
- 2024
48. Leveraging Large Language Models (LLMs) for Traffic Management at Urban Intersections: The Case of Mixed Traffic Scenarios
- Author
-
Masri, Sari, Ashqar, Huthaifa I., and Elhenawy, Mohammed
- Subjects
Computer Science - Computation and Language ,Computer Science - Computers and Society - Abstract
Urban traffic management faces significant challenges due to the dynamic environments, and traditional algorithms fail to quickly adapt to this environment in real-time and predict possible conflicts. This study explores the ability of a Large Language Model (LLM), specifically, GPT-4o-mini to improve traffic management at urban intersections. We recruited GPT-4o-mini to analyze, predict position, detect and resolve the conflicts at an intersection in real-time for various basic scenarios. The key findings of this study to investigate whether LLMs can logically reason and understand the scenarios to enhance the traffic efficiency and safety by providing real-time analysis. The study highlights the potential of LLMs in urban traffic management creating more intelligent and more adaptive systems. Results showed the GPT-4o-mini was effectively able to detect and resolve conflicts in heavy traffic, congestion, and mixed-speed conditions. The complex scenario of multiple intersections with obstacles and pedestrians saw successful conflict management as well. Results show that the integration of LLMs promises to improve the effectiveness of traffic control for safer and more efficient urban intersection management.
- Published
- 2024
49. Design and Implementation of ARA Wireless Living Lab for Rural Broadband and Applications
- Author
-
Islam, Taimoor Ul, Boateng, Joshua Ofori, Nadim, Md, Zu, Guoying, Shahid, Mukaram, Li, Xun, Zhang, Tianyi, Reddy, Salil, Xu, Wei, Atalar, Ataberk, Lee, Vincent, Chen, Yung-Fu, Gosling, Evan, Permatasari, Elisabeth, Somiah, Christ, Meng, Zhibo, Babu, Sarath, Soliman, Mohammed, Hussain, Ali, Qiao, Daji, Zheng, Mai, Boyraz, Ozdal, Guan, Yong, Arora, Anish, Selim, Mohamed, Ahmad, Arsalan, Cohen, Myra B., Luby, Mike, Chandra, Ranveer, Gross, James, and Zhang, Hongwei
- Subjects
Computer Science - Networking and Internet Architecture ,Computer Science - Emerging Technologies - Abstract
To address the rural broadband challenge and to leverage the unique opportunities that rural regions provide for piloting advanced wireless applications, we design and implement the ARA wireless living lab for research and innovation in rural wireless systems and their applications in precision agriculture, community services, and so on. ARA focuses on the unique community, application, and economic context of rural regions, and it features the first-of-its-kind, real-world deployment of long-distance, high-capacity wireless x-haul and access platforms across a rural area of diameter over 30 km. With both software-defined radios and programmable COTS systems and through effective orchestration of these wireless resources with fiber as well as compute resources embedded end-to-end across user equipment, base stations, edge, and cloud, ARA offers programmability, performance, robustness, and heterogeneity at the same time, thus enabling rural-focused co-evolution of wireless and applications while helping advance the frontiers of wireless systems in domains such as O-RAN, NextG, and agriculture applications. Here we present the design principles and implementation strategies of ARA, characterize its performance and heterogeneity, and highlight example wireless and application experiments uniquely enabled by ARA., Comment: 17 pages, 18 figures
- Published
- 2024
50. Event-Arguments Extraction Corpus and Modeling using BERT for Arabic
- Author
-
Aljabari, Alaa, Duaibes, Lina, Jarrar, Mustafa, and Khalilia, Mohammed
- Subjects
Computer Science - Computation and Language - Abstract
Event-argument extraction is a challenging task, particularly in Arabic due to sparse linguistic resources. To fill this gap, we introduce the \hadath corpus ($550$k tokens) as an extension of Wojood, enriched with event-argument annotations. We used three types of event arguments: $agent$, $location$, and $date$, which we annotated as relation types. Our inter-annotator agreement evaluation resulted in $82.23\%$ $Kappa$ score and $87.2\%$ $F_1$-score. Additionally, we propose a novel method for event relation extraction using BERT, in which we treat the task as text entailment. This method achieves an $F_1$-score of $94.01\%$. To further evaluate the generalization of our proposed method, we collected and annotated another out-of-domain corpus (about $80$k tokens) called \testNLI and used it as a second test set, on which our approach achieved promising results ($83.59\%$ $F_1$-score). Last but not least, we propose an end-to-end system for event-arguments extraction. This system is implemented as part of SinaTools, and both corpora are publicly available at {\small \url{https://sina.birzeit.edu/wojood}}
- Published
- 2024
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.