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With the development of computer technology, automatic test paper generation systems have gradually become an effective tool for detecting and maintaining national machine security and protecting the rights and interests of workers. This article achieved multi-level oral scores for different types of questions through online scoring using artificial neural networks in recent years. Based on its specific situation and evaluation index requirements, an analysis module that is reasonable, efficient, and in line with the hierarchical structure and module requirements of national conditions has been designed to complete the research on automatic test paper generation technology, in order to help better manage and allocate human resources and improve production efficiency. Afterwards, this article conducted functional testing on the technical module. The test results showed that the scalability of the system was over 82%. [ABSTRACT FROM AUTHOR]

• Paper-patent citation linkages may serve as early signs for predicting delayed recognized knowledge in science. • Such papers may firstly encounter negative citations and then patent citations and finally get widely recognized. • The trans-fields technological impact is important for under-cited scientific knowledge to become highly cited. • Several trans-fields of science-technology interactions, such as "physics/mathematics - computer technology" are discovered. • Text mining both authors' claims and citing sentences is proposed for identifying potential transformative knowledge. In this study, we investigate the extent to which patent citations to papers can serve as early signs for predicting delayed recognized knowledge in science using a comparative study with a control group, i.e., instant recognition papers. We identify the two opposite groups of papers by the Bcp measure, a parameter-free index for identifying papers which were recognized with delay. We provide a macro (Science/Nature papers dataset) and micro (a case chosen from the dataset) evidence on paper-patent citation linkages as early signs for predicting delayed recognized knowledge in science. It appears that papers with delayed recognition show a stronger and longer technical impact than instant recognition papers. We provide indication that in the more recent years papers with delayed recognition are awakened more often and earlier by a patent rather than by a scientific paper (also called "prince"). We also found that patent citations seem to play an important role to avoid instant recognition papers to level off or to become a so called "flash in the pan", i.e., instant recognition. It also appears that the sleeping beauties may firstly encounter negative citations and then patent citations and finally get widely recognized. In contrast to the two focused fields (biology and chemistry) for instant recognition papers, delayed recognition papers are rather evenly distributed in biology, chemistry, psychology, geology, materials science, and physics. We discovered several pairs of "science sleeping"-"technology inducing", such as "biology-biotechnology/pharmaceuticals", "chemistry-chemical engineering", as well as some trans-fields science-technology interactions, such as "psychology - computer technology/control technology/audio-visual technology", "physics - computer technology", and "mathematics-computer technology". We propose in further research to discover the potential ahead of time and transformative research by using citation delay analysis, patent & NPL analysis, and citation context analysis. [ABSTRACT FROM AUTHOR]

This paper introduces a kind of intelligent lubricating oil quality detector integrating computer technology. On the basis of the traditional lubricating oil quality detection, through the introduction of advanced computer technology, the equipment realizes the automation of the detection process, the intelligence of data processing and the convenience of remote monitoring and management. This paper not only expounds the system structure and working principle of the detector, but also discusses the application of computer technology in the detection process. [ABSTRACT FROM AUTHOR]

Landscape design has a long history, from ancient royal gardens to modern urban parks, and its design concepts and techniques are constantly evolving. Nowadays, with the improvement of people's environmental requirements, landscape design is also constantly innovating. Although the landscape has made great progress, in actual operation, there are problems such as communication barriers with customers, difficulty in design implementation, and inability to preview the design effect in real time. Computer augmented reality technology has begun to play an important role in landscape design. Augmented Reality (AR) overlays the virtual 3D model into the real scene, previews the effect of design implementation in real time, carries out data analysis and optimization, and improves the design better to meet the needs of the public. In order to scientifically evaluate the effect of computer augmented reality technology in landscape design, this paper sets two main indicators: efficiency and quality. Efficiency is primarily concerned with the speed difference compared to traditional design methods. By means of comparative experiments, the time required to use augmented reality technology is calculated. Quality is mainly based on user feedback and expert review. Through users' actual experience of landscape design under augmented reality technology, their feedback is collected, and combined with professional review, the performance of augmented reality technology in design quality is comprehensively evaluated. This paper investigates the evaluation results of people in four landscapes (green plants, pavilions, ancient buildings, fountains). The survey results show that the fountain design quality is 80 points, the efficiency score is consistent with the pavilion, the feasibility score exceeds 80 points (82), and the user satisfaction is 5 points higher than the pavilion design. [ABSTRACT FROM AUTHOR]

With the rapid development of computer technology, a new educational model, the innovative education learner model, has emerged as a product of the deep integration of technology and education. In this paper, we will begin by organizing the theories and models related to technology acceptance. We will select the UTAUT model, known for its high explanatory power, as the theoretical framework. Subsequently, we will comprehensively analyze the dataset and conduct in-depth habit mining. The effectiveness of applying K-means concepts to address the classification of clusters of learners' learning habits is confirmed. The feasibility of the LSTM algorithm in predicting learners for exercise responses is also demonstrated. Next, a learning cluster construction method based on intelligent learner clustering is proposed. The methods of MDS+K-means and spectral clustering are selected for clustering. Learning clusters are constructed, and the performance of the two types of algorithms is compared and analyzed. Finally, the enhanced text feature extraction algorithm is utilized to design and implement the corresponding system for the practical application of the innovative educational learner model. The final experiment proves that the text features extracted by the model are effective, with an error rate of only about 2.8%, thus demonstrating that the intelligent educational learning model in this paper is reasonable. [ABSTRACT FROM AUTHOR]

This paper presents the findings about implementing a machine learning (ML) technique to optimize the performance of 5 G mm wave applications utilizing multiple-input multiple-output (MIMO) antennas operating at the 28 GHz frequency band. This article examines various methodologies, including simulation, measurement, and the utilization of an RLC-equivalent circuit model, to evaluate the appropriateness of an antenna for its intended applications. In addition to its compact dimensions, the proposed design exhibits a maximum gain of 10.34 dBi, superior isolation exceeding 26 dB, and a broad bandwidth of 16.56 % Centered at 28 GHz and spanning from 25.905 to 30.544 GHz. Another supervised regression machine learning technique is utilized to predict the antenna's gain accurately. Machine learning (ML) models can be assessed by several measures, such as the variance score, R square, mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and Mean Absolute Percentage Error (MAPE). Among the six machine learning models considered, it is seen that the Gaussian Process Regression (GPR) model exhibits the lowest error and achieves the highest level of accuracy in forecasting gain. The antenna under consideration has promising qualities for its intended use in high-band 5 G applications. This is evidenced by the modelling findings obtained from Computer Simulation Technology (CST) and Advanced Design System (ADS)and the measured and projected results derived using machine learning methodologies. [ABSTRACT FROM AUTHOR]

This paper proposes a deep neural network (DNN)-based approach for radiation pattern synthesis of 8 elements phased array antenna. For this purpose, 181 points of a desired radiation pattern are fed as input to the DNN and phases of array elements are extracted as the outputs. Existing DNN techniques for radiation pattern synthesis are not directly applicable to higher-order arrays as the dataset size grows exponentially with array dimensions. To overcome this bottleneck, we propose novel and efficient methods of generating datasets for DNN. Specifically, by leveraging the constant phase-shift characteristic of the phased array antenna, dataset size is reduced by several orders of magnitude and made independent of the array size. This has considerable advantages in terms of speed and complexity, especially in real-time applications as the DNN can immediately learn and synthesize the desired patterns. The performance of the proposed methods is validated by using an ideal square beam and an optimal array pattern as reference inputs to the DNN. The results generated in MATLAB as well as in CST, demonstrate the effectiveness of the proposed methods in synthesizing the desired radiation patterns. [ABSTRACT FROM AUTHOR]

The paper deals with the design issue of the computer simulation models of the traction inverter reflecting request on the rapid investigation of the efficiency performance under various operational conditions. According to this, a piece-wised linearized simulation tool PLECS is selected for model development, which considers the relevant loss behaviour of the main power circuit semiconductor components. The topologies, for which the simulation models are created, are topologies, one of which is commonly used across the automotive industry as the heart of the traction drive (VSI – Voltage Source Inverter), and its perspective alternative three-level traction inverter topology T-NPC – T-type Neutral Point Clamped. The simulation models created in the given simulation tool are thus subjected to the analysis of power parameters, which also include the calculated power losses of the entire system of semiconductor devices for both topologies of the traction inverter. Based on the obtained power parameters, the efficiency performance under various operational conditions of both topologies is evaluated. The presented methodology enables rapid investigation of operational performance enabling fast optimization methods. Any design of linearized simulation models in the PLECS simulation tool, whose core consists of semiconductor elements, can be analyzed by the proposed methodology. [ABSTRACT FROM AUTHOR]

With the rapid development of computer technology, intelligent cockpit has increasingly become a trend in on-board related equipment. The intelligent cockpit system can not only provide auxiliary support for users in the driving environment, but also greatly improve driving efficiency. With the advancement of technology and the improvement of people's material lives, people's demand for driving environment safety and intelligence is gradually increasing. In order to effectively enhance the interactivity of the intelligent cockpit and ensure the safety of users' driving, this article effectively analyzed the performance and functional requirements of the intelligent cockpit, and combined speech recognition algorithms to construct an artificial intelligence (AI) speech interaction system. On this basis, this paper provides an in-depth study of intelligent cockpit design. To verify the effectiveness of the intelligent cockpit application, it was tested from four aspects: system operation accuracy, command response time, system security, and user experience. The test findings showed that at the level of system command response time, the response time of driving assistance commands, entertainment media commands, and traffic information commands was basically concentrated below 300 milliseconds. From the specific test results, it can be seen that the intelligent cockpit based on the artificial intelligence voice interaction system can quickly respond to users' different command needs through precise speech recognition. [ABSTRACT FROM AUTHOR]

In Victoria, Australia, senior secondary mathematics students are expected to use technology and thus need to make decisions about using pen-and-paper (P&P) or technology when solving mathematics problems. The predominant technology is a Computer Algebra System (CAS). This study investigated the beliefs about CAS held by twelve Year 11 students as they learnt to use CAS and whether these beliefs were stable over time. These students held a range of beliefs related to the usefulness of CAS, speed of CAS compared to P&P, whether CAS is proper mathematics, choice of CAS or P&P, ease of use, the correctness of answers and solving problems in Mathematical Methods (i.e. the mathematics subject studied). Beliefs are often described as being stable (e.g. McLeod, 1992), but some researchers stress stability needs to be determined empirically rather than being seen as a characteristic of beliefs (e.g. Liljedahl et al., 2012). For this sample of students, stability (rather than instability) is a feature of students' beliefs about CAS. [ABSTRACT FROM AUTHOR]

The abstract should summarize the content of the paper. Try to keep the abstract below 200 words. Do not make references nor display equations in the abstract. The journal will be printed by photo-offset from the same-sized copy prepared by you. Your manuscript should be printed on A4 paper (21.0 cm x 29.7 cm). It is imperative that the margins and style described below be adhered to carefully. This will enable us to keep uniformity in the final printed copies of the Journal. Please keep in mind that the manuscript you prepare will be photographed and printed as it is received. Readability of copy is of paramount importance. [ABSTRACT FROM AUTHOR]

The prediction of final semester grades is a crucial undertaking in education, offering insights into student performance and enabling timely interventions to support their academic journey. This paper employs a deep learning approach, specifically gated recurrent unit (GRU), in conjunction with feature optimization using analysis of variance (ANOVA), to forecast final semester grades. The predictive model is trained and evaluated on a handcrafted grade prediction dataset, which contains the academic performance of the students during Plus 2 and from Semester 1 to Semester 4 of a group of Computer science and Engineering majors in Kerala. By processing historical academic records and contextual information, the GRU model learns to predict future performance accurately. To enhance the model's efficacy and interpretability, ANOVA is applied to optimize the feature selection process. This statistical technique identifies the most influential factors contributing to final grades, refining the model's predictive power while reducing dimensionality. The experimental results showcase the model's effectiveness in predicting final semester grades, demonstrating superior accuracy and performance compared to grade prediction using CNN with Bayesian optimization and LSTM with L1-Norm optimization. [ABSTRACT FROM AUTHOR]

Recently, the technology of Underwater computer vision has played a vital role by improving the quality of underwater images owing to its significance in different applications in marines, such as military, resource development, biological research, and underwater environmental assessments. Moreover, light is absorbed and scattered while propagating through water, leading to color distortion. Additionally, floating micro-particles in the water contribute to low image contrast, resulting in blurry and poorly lit underwater images with a color cast. Therefore, many researchers have been attracted to developing diverse computer vision-based methods to improve the quality of underwater images, such as restoration, enhancement, and deep-learning techniques to restore and enhance degraded underwater images. Although numerous studies have attempted to address these issues, there is still much room for improvement in the quality of the produced images. To this end, this paper proposes a new enhancement method to improve underwater image quality. The presented approach utilizes the Coronavirus herd immunity optimizer algorithm for underwater image enhancement (CHIO-UIE) and is evaluated using standard measures on public datasets. The empirical results demonstrate that the CHIO-UIE method enhances the quality of images based on qualitative and quantitative evaluations, successfully improving underwater images with low contrast and light by significantly enhancing the visual impact of distorted underwater images across various underwater environments. [ABSTRACT FROM AUTHOR]

The safety of people's lives and property is the primary factor for the success of urban construction. Therefore, in order to better maintain social stability and harmony, relying on computer technology to effectively detect violence and to make decision support has important theoretical and practical significance. Aiming at the shortcomings of traditional manual design feature extraction methods, this paper proposes a super automatic violence detection method based on the combination of Deep Learning and trajectory in AI systems. Firstly, aiming at the problem of complex time and high accuracy of traditional manual feature extraction, a deep spatiotemporal violence detection method based on three-dimensional convolution and trajectory in AI systems is proposed. We improve the IDT algorithm to extract the target trajectory, and carry out three-dimensional convolution and pooling operation to calculate the deep-seated temporal and spatial information in the video frame, so as to realize peer-to-peer detection in AI systems. Secondly, in order to further improve the acquired deep-seated time and space information and utilization rate and achieve high detection rate, the feature fusion of double stream convolution and three-dimensional convolution is proposed, and the feature extraction of continuous video frame sequence is carried out by three-dimensional convolution neural network (C3D), which can effectively extract the fusion feature information of time and space in the classification layer, so as to obtain the final classification result. Finally, in order to solve the problem of too deep network level and slow convergence, dense convolution is introduced, which reduces the parameters of the network model and time complexity. Experimental results show that compared with other mainstream algorithms, this method is more effective and stable, and can be applied to the detection of violent abnormal behavior in video. Meanwhile, the method proposed in this paper has important theoretical value and practical significance for decision support of video surveillance system in AI systems. [ABSTRACT FROM AUTHOR]

[Display omitted] • Review of the knowledge structure using CiteSpace, VOSviewer, and SciMAT. • Visualizing the evolution of traffic collision reconstruction: the field is developing. • Analyzing co-word, co-citation, and major themes in traffic collision reconstruction. • Authors and institutions need more collaboration. • Head injury and uncertainty are hotspots: interdisciplinary research is the future. Traffic collisions are incidents with high fatality rate which generate billions of US dollars of loss worldwide each year. Post-collision scene reconstruction, which involves knowledge of multiple disciplines, is an important approach to restore the traffic collision and infer the cause of it. This paper uses software CiteSpace, VOSviewer, and SciMAT to conduct a visualization study of knowledge mapping on the literature of traffic collision scene reconstruction from 2001 to 2021 based on the Web of Science database. Knowledge mapping is a cutting-edge research method in scientometric, which has been widely applied in medicine and informatics. Compared with traditional literature review, knowledge mapping with visual techniques identifies hot keywords and key literature in the field more scientifically, and displays them in schematic diagrams intuitively which allows to further predict potential hotspots. A total of 803 original papers are retrieved to analyze and discuss the evolution of the field in the past 20 years, from macro to micro, in term of background information, popular themes, and knowledge structure. Results indicate the number of publications in this field is limited, and collaborations among authors and among institutions are insufficient. In the meantime, mappings imply the top three hot themes being scene reconstruction, computer technology, and injuries. The introduction of AI related technologies, such as neural networks and genetic algorithms, into collision reconstruction would be a potential research direction. [ABSTRACT FROM AUTHOR]

Artificial Intelligence (AI) techniques are becoming more and more sophisticated showing the potential to deeply understand and predict consumer behaviour in a way to boost the retail sector; however, retail-sensitive considerations underpinning their deployment have been poorly explored to date. This paper explores the application of AI technologies in the retail sector, focusing on their potential to enhance decision-making processes by preventing major ethical risks inherent to them, such as the propagation of bias and systems' lack of explainability. Drawing on recent literature on AI ethics, this study proposes a methodological path for the design and the development of trustworthy, unbiased, and more explainable AI systems in the retail sector. Such framework grounds on European (EU) AI ethics principles and addresses the specific nuances of retail applications. To do this, we first examine the VRAI framework, a deep learning model used to analyse shopper interactions, people counting and re-identification, to highlight the critical need for transparency and fairness in AI operations. Second, the paper proposes actionable strategies for integrating high-level ethical guidelines into practical settings, and particularly, to mitigate biases leading to unfair outcomes in AI systems and improve their explainability. By doing so, the paper aims to show the key added value of embedding AI ethics requirements into AI practices and computer vision technology to truly promote technically and ethically robust AI in the retail domain. • Establishment of AI ethics guidelines for the retail domain. • Design of a detailed framework for AI ethics. • Evaluation of the VRAI framework on new explainability metrics. • Recommendations for AI transparency improvements. • Integration of ethics into the design of AI systems. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Computer Science & Technology (JCS&T) is the property of Journal of Computer Science & Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of advanced computer technology in the healthcare industry has the potential to improve patient care and therapeutic results. The goal of this project is to improve data security, privacy, and decentralisation in healthcare by integrating blockchain and Internet of Things (IoT) technologies. The adoption of IoT devices makes it possible to gather and analyse patient sensory data in real-time; however centralised processing and storage present problems such as data manipulation and privacy issues. The study investigates the creation of a decentralised IoT-based e-healthcare system that takes these issues into account by utilising blockchain technology. In addition, the paper also emphasises how blockchain use has advanced smart contract technologies. Smart contracts provide safe user authentication for IoT device access, assuring responsibility, traceability, and data integrity. The study investigates the potentially game-changing applications of blockchain technology in healthcare, such as enhanced data interoperability, patient-cantered care, reduced administrative procedures, and increased transaction transparency. The report also highlights the significance of blockchain in managing pharmaceutical supply chains, considering the essential influence on patient welfare and safety. Effective management is essential in the healthcare business because supply chain interruptions or breaches can have serious implications. The present level of research in blockchain-enabled IoT applications for healthcare is examined comprehensively using the PRISMA framework and records from the Scopus database. The three most important research topics are cloud computing, fog computing, and medical services. The results highlight the important role that blockchain-enabled IoT applications have played in enhancing data security and privacy in the healthcare industry. Real-time data gathering, precise diagnoses, individualised treatments, and simplified administrative procedures are all made possible by the integration of blockchain and IoT. Additionally, scalable solutions and insightful data for healthcare decision-making are provided via fog computing, cloud computing, machine learning, and smart contracts. [ABSTRACT FROM AUTHOR]

Virtual humans have become a hot research topic in recent years due to the development of AI technology and computer graphics. In this survey, we provide a comprehensive review of the interaction design of 3D virtual humans. We first categorize the interac- tion design of virtual humans into speech, eye, facial expressions, and posture interactions. Then we describe the combination of different modalities of virtual humans in the multimodal interaction design section. We also summarize the applications of intelli- gent virtual humans in the fields of education, healthcare, and work assistance. The final part of the paper discusses the remaining challenges and opportunities in virtual human interaction design, along with future directions in this field. This paper hopes to help researchers quickly understand the characteristics of various modal interactions in the process of designing intelligent virtual humans and provide design guidance and suggestions. [ABSTRACT FROM AUTHOR]

With the rapid development of computer technology. Many scholars pay close attention to computer graphics algorithms, which makes computer graphics widely used in various fields and enters a new revolutionary era. The purpose of this paper is to study the evaluation of computer graphics algorithm demonstration systems. Combining theory with practice, on the basis of careful analysis of the principle of graphics algorithm, a new idea of synchronization of graphics production process and a specific algorithm for realizing graphics are proposed, and most graphics in computer graphics are visualized. It breaks the limitation that only two-dimensional graphic simulation effects can be realized, and increases the interactive user control system. The algorithm complexity is significantly reduced, the graphics creation speed is increased, and the simulation effect is more realistic. After the introduction of this visual teaching demonstration system, these abstract principles can be explained intuitively, which can significantly improve the teaching quality. [ABSTRACT FROM AUTHOR]

In university-level education, the computer network is a mandatory course for computer science and engineering majors. A computer network course provides theoretical and hands-on foundations for network connectivity, network topologies, internet protocols, networking devices, and gateways. In the traditional classroom, students face challenges in gaining essential knowledge and self-efficacy. Teachers face challenges in assessing students' quality of knowledge due to the abundance of online computer science teaching resources. Chatbot technologies have the potential to overcome these challenges and enhance essential knowledge and self-efficacy. However, the argument remains whether a course-specific standard chatbot or a generalizable chatbot could produce high-quality answers. Therefore, in this paper, we research 1) to what extent does using chatbots improve higher education students' essential knowledge of computers network? and 2) to what extent does using chatbots improve the self-efficacy of higher education students? Our first insight indicates that groundbreaking generalizable chatbots such as You and ChatGPT produce rather detailed answers to the questions associated with computer network courses, but those answers may not be the model answers that teachers expect from the students. Hence, research-based course-specific standard chatbots are required to teach computer network topics effectively. [ABSTRACT FROM AUTHOR]

In a world whose attention to environmental and health problems is very high, the issue of properly managing nuclear waste is of a primary importance. Information and Communication Technologies have the due to support the definition of the next-generation plants for temporary storage of such wasting materials. This paper investigates on the adoption of one of the most cutting-edge techniques in computer science and engineering, i.e. Digital Twins, with the combination of other modern methods and technologies as Internet of Things, model-based and data-driven approaches. The result is the definition of a methodology able to support the construction of risk-aware facilities for storing nuclear waste. [ABSTRACT FROM AUTHOR]

Computer courses in public schools are typically taught by traditional methods, that involve images and written text explanations. This makes the content of learning materials unclear and hard to understand. Moreover, it is not easy for public schools to equip computer labs with the required devices, as schools have limited budgets. In this paper a protype using VR technology was introduced and assessed in terms of usability, and acceptance. The aim was to provide an interactive virtual learning environment for teaching/learning computer hardware with the most effective method that allow keeping pace with the rapid evolution in this field. The prototype was based on the use of a VR headset to allow the user to explore the internal components of a computer. A test in terms of functionalities and usability was conducted. Results confirmed that the prototype functions were successfully implemented. Subsequent tests on usability proved satisfactory. It is expected that the proposed prototype and study will enrich the teaching methods of public schools with limited budgets - especially for practical and applied courses. [ABSTRACT FROM AUTHOR]

In the last ten years, many different innovative learning methodologies have been proposed for engineering education. In those new approaches, students learning, and evaluation are usually supported by a catalogue of creative activities, practices, and presentations which may be very numerous if competencies to be acquired are heterogeneous and must cover a large knowledge area, such as in cybersecurity courses. In addition, when a high number of students are enrolled in the course, deadlines must be strict, to enable professors to evaluate all students and activities properly and on time. Due to this requiring schedule, students often cannot work all competencies with the expected depth, and their learning decreases. New instruments are needed to facilitate the learning of the students and the evaluation process are needed. Therefore, in this paper we proposed a new automated scheduling tool, based on graph theory, to fill this gap. The tool employs graph coloring algorithms to calculate all possible schedules for evaluation activities. Students may freely choose the schedule that best fits their personal situation, learning progress, background, etc. using a web portal where all solutions from the coloring algorithm are displayed. This tool was deployed in the Computer Engineering degree at Universidad Politécnica de Madrid, Spain. A pilot experience was conducted for three years (2020-2022) in the context of a cybersecurity course to analyze how this new tool improves the learning and the evaluation process of students. Results show both academic results and the students' and professor' satisfaction improve in a significant manner. [ABSTRACT FROM AUTHOR]

The paper inhere presents the implementation of one idea that has been realized during the COVID-19 pandemics in the period from 2019 until 2022 i.e. the implementation of the software product PTC Mathcad in the virtual training of students, illustrating in an interactive and attractive way the surge theory in second order linear electrical circuits. [ABSTRACT FROM AUTHOR]

Internet technology, as a product of the development of the network era, connects a large number of hardware devices, but the connection of many devices makes its corresponding security be greatly tested. The network security technology and the corresponding computer hardware security technology have become the focus of people's attention. At the same time, the construction of multimedia database based on this related technology has become the development trend of people's research and attention. Most of the conventional computer security technology focuses on the security construction of the operating system, which has certain openness, so its corresponding reliability is very low, but also uncontrollable. Based on this, this paper proposes a design scheme of the public security architecture on the embedded terminal, and realizes the design of the multimedia security broadcast control system based on this scheme, and realizes the play and storage of multimedia files, as well as the interaction between the corresponding media servers. The wireless network embedded security terminal designed in this paper includes client terminal identity authentication, corresponding media content protection and storage, and real-time broadcast content monitoring. Finally, the experiment is carried out based on the proposed design scheme. The experimental results show that the embedded security terminal proposed in this paper has obvious performance advantages, and its correctness and availability have been verified in practice. [ABSTRACT FROM AUTHOR]

The use of information in sports and technology is a vital sign to measure the development management of your sport and sporting strength. Artificial Intelligence is cutting-edge in mathematical technology and computer research that is growing and conducting the necessary research. Assessed the essence of PE training and teaching, assembled an applicable version of VR technology in this field. Those options that come with VR technology include awareness, attendance, interactivity, freedom, etc. It will be broadly used in PE instruction and will play a substantial role. This computer understands the center of computer mathematics, and applying these to primary education and education is essential. This paper's objective isn't to design and examine computer applications in the sports business except to concentrate on a single component of sports instruction with computer calculations. It's a fundamental technology for analyzing the trajectories of study objects. By way of instance, this paper assesses image processing in sports and puts forward a few suggestions. [ABSTRACT FROM AUTHOR]

The Journal of Computer Science & Technology (JCS&T) has achieved the third quartile (Q3) ranking in the Computer Science subject area according to Scimago Journal & Country Rank (SJR). The latest issue of the journal features five papers covering various topics such as high-performance computing, visualization, machine learning, software engineering, and e-government. The papers were authored by 21 individuals from nine different universities in Argentina, Ecuador, Jordan, Spain, and Uruguay. Additionally, the issue includes an overview of a Ph.D. thesis. The editor expresses gratitude to the editorial staff, authors, reviewers, and collaborating universities for their contributions to this edition. [Extracted from the article]

The technological revolutions greatly impact current and future Classrooms. These advances in technology include the revolution of artificial intelligence, virtual reality, and super highspeed internet. In the coming next generation (6G), the data rate will be very sufficient for live scenes in virtual reality applications such as telepresence and teleoperation. This paper review and discuss next-generation technologies in AI, VR, and communication. Moreover, we examine the motivation for establishing an Advanced Technology based Smart and Immersive Classroom (SIC) and the advantages of its availability to the virtual society. Recent advances in computer and communications technology have delivered capabilities to tomorrow's SIC. Advances in virtual reality and real-time streaming on the internet have created a revolution in curricula and classrooms. Index Terms--Virtual Reality in education; 6G for education, Artificial Intelligence in education, Immersive Classroom. [ABSTRACT FROM AUTHOR]

Copyright of Revista Brasileira de Medicina do Esporte is the property of Redprint Editora Ltda. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To achieve ever-increasing productivity requirements in serial production, while ensuring product quality and machining process stability, special workpiece specific fixtures are required. Designing such a device can be a very complex and demanding process, requiring a high level of experience and insight from the designer. The purpose of this work is to show the potential possibilities of applying modern software tools to the fixture design process in order to provide reliable part positioning and clamping, while lowering the experience level required on the designer's part. The example analysed in the paper shows how applying modern software can enable detailed fixture evaluation and process optimisation in the early stages of fixture design, significantly reducing the risks associated with the classical design process and provide a deeper insight into the behaviour of the fixturing system. [ABSTRACT FROM AUTHOR]

With the advances in data communication, high speed internet in terabits per second, and the coming next generation (6G), where the data rate will be very sufficient for virtual reality application such as telepresence and tele-operation, the old-new concept of virtual university will be revolutionized. This paper presents a review for one type of distance learning, which is online synchronous education supported by multimedia and Virtual Reality (VR) or simply a virtual university (VU) or Virtual Classroom (VC). We review the concept of the VU for the past and how it will be in the coming futures. We review, its types, component, and how it will be. Furthermore, we review and discussed next generation VU/VC obstacles in addition to their cons and pros. Moreover, we examine the motivation for establishing VU/VC and the advantages of its availability to the virtual society. Recent advances in computer and communications technology have delivered capabilities to today's distance learning and virtual classroom. Advances in virtual reality, real-time streaming on the internet have created a revolution in curricula and classrooms. We explain how to integrate multimedia, 3D videos, Virtual Reality (VR), tele-operation, tele-presence, and Internet-based learning technologies into a common framework for the virtual classroom. [ABSTRACT FROM AUTHOR]

This article presents a literature review of the studies conducted on problems of location and relocation of Emergency Medical Services (EMS) vehicles. A detailed analysis is made of the components that influence the development of the problem, the information extracted from the referenced articles, for the development of this paper were: the implemented methodologies, the variables involved in the system, performance measures, computer technology tools (software) implemented for the development of these methodologies, mathematical models, simulation models and others, found in the literature review, each item classified according to its function. Finally, an analysis of new technologies in the development of the subject is made and a proposal is made to address this problem with industries 4.0. [ABSTRACT FROM AUTHOR]

High performance computing is now a major area where business and computing technologies need resilient high performance to meet business continuity and real-time needs. However, many top-level business and technology organizations are still in the process of improving high performance and traffic resiliency to ensure the availability of the system at all times. Machine learning is an important advancement of computer technology that helps in decision making by prediction and classification mechanism based on historical data. In this paper, we propose and integrate the concept of high-performance computing with artificial intelligence machine learning techniques in cloud platforms. The networking and computing performance data are used to validate, predict and classify the traffic and performance patterns and ensure system performance and continuous traffic flow resiliency decisions. The proposed integrated design approach has been analyzed on different step actions and decisions based on machine learning regression and classification models, which auto-correct the performance of the system at real run time instances. Our machine learning integrated design simulated results show its traffic resilience performs proactively 38.15% faster with respect to the failure point recovery along with 7.5% business cost savings as compared to today's existing non-machine learning based design models. [ABSTRACT FROM AUTHOR]

High performance computing is now a major area where business and computing technologies need resilient high performance to meet business continuity and real-time needs. However, many top-level business and technology organizations are still in the process of improving high performance and traffic resiliency to ensure the availability of the system at all times. Machine learning is an important advancement of computer technology that helps in decision making by prediction and classification mechanism based on historical data. In this paper, we propose and integrate the concept of high-performance computing with artificial intelligence machine learning techniques in cloud platforms. The networking and computing performance data are used to validate, predict and classify the traffic and performance patterns and ensure system performance and continuous traffic flow resiliency decisions. The proposed integrated design approach has been analyzed on different step actions and decisions based on machine learning regression and classification models, which auto-correct the performance of the system at real run time instances. Our machine learning integrated design simulated results show its traffic resilience performs proactively 38.15% faster with respect to the failure point recovery along with 7.5% business cost savings as compared to today's existing non-machine learning based design models. [ABSTRACT FROM AUTHOR]

In this paper, a new hybrid beamforming approach based on the 2D convolution and genetic algorithm (GA), denoted as C/GA, is proposed for side lobe level (SLL) reduction and size miniaturization of planar antenna arrays (PAA). The convolution algorithm determines the elements excitations, whereas the GA optimizes the element spacing to adjust the half power beamwidth (HPBW). Two beamforming approaches are derived from the C/GA approach. The first one is the single-stage C/GA that is denoted as (SC/GA), where the convolution of the excitation matrix by itself is performed just once. The SC/GA yields a twofold decrease in the SLL. The second is the double-stage C/GA, (DC/GA), which is developed for further SLL reduction, where the convolution of the excitation matrix by itself is performed twice successively, resulting in a fourfold decrease in the SLL. However, both SC/GA and DC/GA approaches provide high dynamic range ratios (DRR). This issue is addressed either by taking the middle excitations of the estimated excitation matrices or by performing array thinning by turning off the edge elements of the synthesized PAAs, which indeed minimizes the array size. The practical validation of the proposed approaches is realized using the computer simulation technology (CST) microwave package. [ABSTRACT FROM AUTHOR]

A dual band microstrip antenna for WIMAX and WLAN applications is analyzed and presented in this paper. The proposed antenna has semicircular slot in patch and Defected Ground Structure (DGS) technique for the improvement of its bandwidth and gain. Computer Simulation Technology (CST) software is used to design and simulate the performance characteristics. The proposed antenna has the dimensions as 28 x 26•6𝑚𝑚². The fabricated antenna provides a good reflection coefficient of -48 dB and -44.5 dB at a center frequency of 3.4 GHz and 5.5 GHz. Gain achieved by the antenna is 2.72 dB and 3.87 dB for WLAN and WIMAX application. Good agreements have been found between simulated and measured results. These results confirm that the fabricated antenna is very promising for WLAN and WIMAX applications. [ABSTRACT FROM AUTHOR]

The computer technology searching for a preferable point in any factor space delivers to the extremum with regard to quantitative scalar response within scope of intelligent DSS-sphere, which was considered in this paper. The problem of universalization and planning (design) of extreme experiments in relation to complex objects in the conditions of significant limitation including the allowable number of experiments and sub-catastrophic duration of them was solved. A technology that involves the separation of three linked stages of optimization was proposed.The computer technology searching for a preferable point in any factor space delivers to the extremum with regard to quantitative scalar response within scope of intelligent DSS-sphere, which was considered in this paper. The problem of universalization and planning (design) of extreme experiments in relation to complex objects in the conditions of significant limitation including the allowable number of experiments and sub-catastrophic duration of them was solved. A technology that involves the separation of three linked stages of optimization was proposed. [ABSTRACT FROM AUTHOR]

In the Internet age, the proliferation of multimedia computer technology (MCT) brings unprecedented opportunities to English teaching in colleges. This paper firstly carries out a questionnaire survey on the current status of personalized teaching of college English, and summed up the main problems with the current teaching mode. On this basis, the authors developed an MCT-based personalized English teaching design, with the aid of information technology (IT) and online teaching platform. To verify its effect, the proposed design was tested through contrastive experiment. The results show that the MCT-based personalized English teaching design could improve the interests and performance of English learning, and cultivate a good learning habit. In summary, this paper explores the personalized teaching of college English from both theoretical and practical angles, laying a good basis for highquality English teaching and personalized development of students. [ABSTRACT FROM AUTHOR]

Cryptography is a type of computer technology that is used for ensuring security, hiding information, and more. Bitcoins is the most recognized cryptocurrency. It is a person to person virtual currency which is used for online transactions. In this paper, an attempt has been made to analyses the price volatility of bitcoins. Further, a detailed content analysis has been presented in this paper. This study considers a study period of 8 and half years ranging from 19th June 2010 to 31st December 2018. Bitcoins prices were considered as variable to study the volatility of Bitcoins prices. Unit Root analysis is employed to check the Stationarity of the data series of bitcoins prices. ARCH Test, Volatility Clustering, ARCH, GARCH, TARCH and EGARCH have been used to analyze the price volatility. It was found that good news has more effect on the volatility of Bitcoins price returns than the bad news. [ABSTRACT FROM AUTHOR]

In today's learning approaches for engineering students, practical courses frequently complement traditional theoretical lectures. This practical element allows an early perspective into the real world of engineering, augments student motivation, and enables students to acquire soft skills early. This paper aims to demonstrate the usage of one of the ergonomics risk assessment (ERA) apps that has been learned in the class; which can also be used as an assessment aid in student's practical sessions in the workplace. This apps has been evaluated for its effectiveness by a group of students in the classroom setting prior to be used in the actual workplace. Evaluation results show that this learning aid improves student's communication skills and assists companies to improve their working conditions. Based on the effectiveness assessment, students find that this apps is really useful for their assessment as it provides fast calculation on the results and can store it in the drive. Based on the practical session in the workplace, the findings from the ERA apps show that the current working condition in this study is under medium ergonomic risk exposure level. Therefore, there is a need to improve the working condition by considering improvement on the workplace environment as well as interaction between worker and tools for maintenance. This app is indeed beneficial for practical engineering students as a peer learning process and for industry in terms of work place improvements. In conclusion, this paper describes how this risk assessment app helps induce student to think as an actual engineer and also to solve real-world tasks with limited resources. [ABSTRACT FROM AUTHOR]

The research presented in this paper aims at egg fertility detection during incubation based on the presence of the embryo. To obtain an optimal detection method that does not adversely affect the incubation process, the presented approach uses computer technology to analyze the images obtained from the egg candling process, and to obtain information about the presence of an egg embryo. This study applies the Support Vector Machine (SVM) classifier method using the second-order statistical feature extraction input to detect the chicken egg's fertility. The feature extraction is based on the Gray-Level Co-occurrence Matrix (GLCM) approach with 6 parameters: Energy (En), Contrast (Ct), Entropy (Et), Variance (V), Correlation (Cr), and Homogeneity (H). This study develops a manual detection process that takes a long time and improves the research accuracy of the backpropagation method. The dataset used consisted of 100 images of chicken eggs, including 50 images for each type: fertile and infertile. The preprocessing of the images included cropping, grayscaling, and image enhancement using CLAHE (Contrast Limited Adaptive Histogram Equalization) and HE (Histogram Equalization) methods. Such process can improve the image to get its GLCM parameters. The extracted GLCM parameters are input to the egg fertility detection process performed by the SVM classifier-based method. The presented SVM-GLCM approach was able to detect fertile and infertile eggs with a success rate of 98.20%, which was an improvement over the previous research. This research can be a reference for implementing the detection of chicken egg fertility in the incubation machine to obtain optimal hatching results. [ABSTRACT FROM AUTHOR]

With today's advanced technology microstrip patch antennas are more flexible and stronger than ever before. These antennas can work on various frequencies ranging from low to high for a huge variety of applications including medical, military and quite a few more. This paper presents the textile antennas those are designed for Wi-MAX application with the frequency range of 3.09-3.94 GHz, fifth generation (5G) lower band with the resonant frequency of 4.23-5.65 GHz and UWB 4.62-10.74 GHz applications. This work also introducing a single C-shape etching slot (CSES) in a rectangular patch antenna. The textile substrate (jeans) has been applied to reduce the surface wave losses and design a wearable textile antenna using microstrip line feed technology. Bending effect up to 750 and radiation effect on human tissue as specific absorption rate (SAR) are analyzed using Computer Simulation Technology (CST) tools. Textile antennas for multiple band applications can be created using CSES which can be attributed to cotton, denim cotton and polyester. [ABSTRACT FROM AUTHOR]

• Creative learning in computer science is necessary and important to define. • The variable creative learning in computing needs to be operationalized and measured through universal metrics and scales. • The development of creative learning in computer science does not depend entirely on the curriculum but on how it is taught. The training of creative computer professionals is considered a strategic process in different countries because it is essential for the computerization of society. This paper proposes an approach to the study of creative computer science learning for the digital transformation of modern society. The aim of the research was to evaluate the creative learning of computer science during the training of computer science professionals. An instrument derived from previous research and metrics was applied to evaluate creative learning in the two groups of terminal years of the computer engineering course at the University of Matanzas with a mixed paradigm. The quantitative analysis diagnosed that more than sixty-five percent of the students are evaluated as poor and fair in both years. The qualitative analysis revealed the inadequacies of the teaching staff in the use of computer science teaching approaches, and the four stages of formation of creative learning in computer science in the degree course: pre-university stage, basic stage, professional stage and research stage. They also revealed three key factors in the formation of creative learning in computer science: the integration of subjects, the solution of real projects, and the mainly emotional support provided by teachers and other professionals to students during their integration into the computerization of organizations. [ABSTRACT FROM AUTHOR]

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This paper briefly describes the overall concept of "TRAVEL TYCOON GREECE" (TTGR), a novel business simulation game which aims to simulate realistically a complete tourism experience. The latest image processing and computer graphics technologies were utilized to create accurate 3D backgrounds with different levels of detail, which were incorporated in the game engine and serve as a realistic and accurate terrain allowing the user to navigate in selected historical and touristic areas of Greece. A series of real-world scenarios representing multiple components of the tourism section were designed primarily for entertainment and marketing purposes. In order to motivate users to participate in the game or remain active, an incorporated ticketing platform allows users to win offers such as touristic products and services. [ABSTRACT FROM AUTHOR]

In this paper, we describe technological advances for supporting persons with aphasia in philosophical dialogues about personally relevant and contestable questions. A computer game-based application for iPads is developed and researched through Living Lab inspired workshops in order to promote the target group’s communicative participation during group argumentation. We outline some central parts of the background theory of the application and some of its main features, which are related to needs of the target group. Methodological issues connected to the design and use of Living Labs with persons with aphasia are discussed. We describe a few problems with researching development of communicative participation during group argumentation using an app assisted intervention for the target group and suggest some possible solutions. [ABSTRACT FROM AUTHOR]

Artificial intelligence represents the theory and direction of the development of computer technologies that imitate human intelligence, senses, and behaviour, such as visual perception, speech recognition, decision making, and language translation. A neural network is a method in artificial intelligence that teaches computers to process data in a way inspired by the human brain using neurons and hidden layers. The developed software system for traffic sign recognition is based on a neural network. The programming languages used are Python and JavaScript. Vue.js and Vuetify were used for the development of the user interface, Flask for the server part of the application's functionality and communication, and TensorFlow for the creation of neural networks. This paper gives an overview of the basic concepts and history of artificial intelligence, neural networks, and a brief description of the implementation of the software system. [ABSTRACT FROM AUTHOR]