Search

Tertiary education is at the forefront of future-proof education providing a theoretical foundation to advance knowledge and drive innovation. Exploring preservice teachers’ perspective of what it takes to remain relevant amidst this increasingly complex, uncertain, volatile, ambiguous world is proactively necessary as emerging configurations challenge the role of teachers and the dynamics of the educative process. These preservice general science teachers (n=113) describe their point of view on ensuring the relevance of science education in the future through drawing and narrative description. Qualitative data were analyzed using thematic analysis, and four main themes emerged. Their perception of how Science education can be future-proofed centered on (1) highly advanced technology use, (2) personalized and adaptive learning (3) curated and open accessible learning resources, and (4) sustainability, social responsibility, and ethics-centered. These conceptions enable these future teachers who are also future leaders to prepare for the challenges and opportunities of a future world. These findings offer valuable insights into the need for teacher training institutions to recalibrate for the future skills in education that their graduates must possess and the curriculum development to promote innovative and inclusive teaching practices. more...

In order to achieve zero carbon emissions, new concepts and algorithms are needed in the control of renewable energy to ensure the safe and reliable operation of the grid under the trend of zero carbonization in the future. In this paper, the ensemble learning soft sensor model is applied to the outlet temperature control of the solar thermal power collection system. Due to the lack of accuracy and diversity of base learners in traditional ensemble methods, ensemble pruning is ignored, and the lack of adaptability. So, the estimated performance falls short of the expected value. Therefore, a novel predictive control method for the outlet temperature of the collector system is proposed based on the Gaussian process regression selective ensemble learning soft sensing model (SESMGPR). Firstly, the collecting heat field temperature values were extracted from the Dunhuang Dacheng solar photothermal power plant as historical data, and the subsets and subspaces of the historical data were obtained by bootstrap and partial least squares regression (PLS), respectively. Secondly, the local domain (LTs) was identified by Gaussian mixture model (GMM) clustering, and the local GPR model was established for each LT to obtain the base model (MGPR). Finally, the set pruning strategy based on a genetic algorithm (GA) was used to select the MGPR model with high estimation performance, and the base models were fused by the Stacking algorithm to obtain the SESMGPR model. Besides, adaptive control is used to alleviate the performance degradation of SESMGPR due to the randomness of solar radiation, ambient temperature, wind speed, etc. Experimental results show that the SESMGPR method can effectively handle time-varying variations of the solar thermal power collection system and maintain high prediction accuracy. more...

This paper introduces an innovative solution for increasing precision of fixed-width radix-4 Booth multipliers through variable error compensation functions that leverage Approximation of Carry Function (ACF). Error compensation mechanisms typically comprise two carries-ideal and base carry functions–strategically chosen to minimize mean error. We present three distinct methods-ACF-1, ACF-2, and ACF-3—each employing fixed base values with varying column information (w) and bit lengths (N). Comparative analyses against recent studies demonstrate that our proposed fixed-width Booth multiplier using ACF-1 stands out in terms of accuracy and efficiency tradeoffs. more...

In recent years, with the gradual progress of automatic driving technology, semantic segmentation of road scenes, as the core of this technology, has become a hot spot of research. However, nowadays, most of the convolutional (CNN)-based methods appear to be inefficient and costly due to the factors of large amount of detection data and complex structure. It limits their performance in dealing with some fast response (real-time) tasks. Addressing the above problems, this paper proposes a capsule network-based semantic segmentation method for road images, which achieves a good balance between recognition efficiency and detection speed. Specifically, the DDC-Net designed based on capsule network is used as the baseline network, and different connection paths are dynamically selected according to pixel affinity during forward propagation. In addition, DDC-S and DDC-G are designed for spatial detail fusion and semantic fusion, respectively, and the local feature extraction module (LFCE) is designed using a two-branch structure. Numerous experiments show that the method described in this paper outperforms most of the current CNN-based methods in terms of model size, recognition flexibility and overall performance. In ADE20K and Cityscapes test datasets, the method described in this paper achieves 74.5% and 79.4% mean intersection and merger ratio (mIoU) accuracies at 63.9fps and 64.8fps, and the experimental results demonstrate the effectiveness of our method. more...

This study deals with the electrochemical behaviors of SS316L at various temperatures in a 3M KOH solution. The mounted SS316L was subjected to electrochemical measurement using a Potentiostat with an exposure area of 1 cm². Following electrochemical measurements, the samples were analyzed with a Scanning electron microscope equipped with Energy dispersive spectroscopy (SEM-EDS) to observe the surface morphology and element distribution. Identifying the phases present in the samples is done through X-ray diffraction (XRD). On the basis of SEM images, the surface roughness was also examined. According to OCP investigations, only the lowest solution temperature sample (30 °C) show that they are moving forward in a positive direction. Shifting to a higher solution temperature (from 30 to 50 °C) led to an increase in passive current density according to LSV oxidation measurement. The lowest solution temperature sample (30 °C) shows the lowest corrosion rate and a higher capacitive arc. In contrast, higher hydrogen production is seen in the highest solution temperature sample (50 °C). Moreover, all samples shows p-type and n-type semiconducting properties. According to EDS measurements, the Mn element was not detected in all samples after the electrochemical test due to was sacrificing during corrosion occurs. All samples contain face-centered cubic (fcc)-austenite (γ − Fe) as its main phase. The surface of SS316L did not show any oxides to form, probably due to an excessively thin or nanoscale oxide layer on the surface. more...

The proliferation of Internet of Things (IoT) applications has significantly increased the demand for communication protocols that are both resilient and energy-efficient. Among these, Low Power Wide Area Network (LPWAN) technologies - specifically Long-Range Wide Area Network (LoRaWAN) - offer long-distance wireless connectivity for IoT devices, characterized by their extended transmission range and minimal energy consumption. However, the mobility of IoT devices introduces challenges in optimizing energy efficiency. This study provides a comprehensive review of energy-efficient routing algorithms for LoRaWAN in mobile IoT applications. A systematic approach is employed, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, to identify, evaluate, and synthesize pertinent literature, offering an in-depth exploration of existing methodologies, their advantages and limitations, and potential avenues for future research. Key topics examined include AI-enhanced adaptive data rate (ADR) methods, coding schemes based on the Chinese Remainder Theorem (CRT), and processes utilizing Variable Order Hidden Markov Models (VHMM). These approaches have demonstrated improvements in packet delivery ratios (PDRs), latency reduction, and energy efficiency within mobile IoT contexts. Despite notable advancements, significant opportunities remain for enhancing scalability, developing hybrid solutions, applying these methodologies in real-world contexts, and implementing robust security protocols. This paper contributes valuable insights into the current landscape of energy-aware routing protocols for LoRaWAN in mobile IoT applications and outlines critical areas for future research aimed at achieving sustainable and efficient IoT networks. more...

This study investigates the potential of Super 1 sorghum starch-chitosan-based adhesive for eco-friendly particleboards. Sorghum starch was extracted and characterized, its viscoamylographic profile was analyzed, and adhesive composites were prepared with varying chitosan concentrations. FTIR analysis revealed the formation of hydrogen bonds between hydroxyl groups (−OH) on sorghum starch and amino groups (−NH2) on chitosan, enhancing the stability and mechanical strength of the composites. Chitosan addition altered the crystal structure of starch, increasing amorphinity and material flexibility, as evidenced by XRD analysis. Viscoamylographic profiles indicated good gelation ability and viscosity. Sorghum starch-chitosan adhesive holds promise as an alternative to synthetic adhesives for the fabrication of eco-friendly particleboards. Further research is warranted to evaluate the adhesive performance in particleboard production and optimize the formulation and production process for broader construction applications. more...

Ocimum sanctum (OS) Linn, is a medicinal herb that has been used in traditional medicine science ancient time. It contains an array of complex and diverse biologically active phytochemical constituents that can act as a reducing and stabilizing agent for synthesizing metal nanoparticles (NPs). Herein, OS aqueous leaf extract was used to synthesize eco-friendly round and rod-shaped Ag NPs. The synthesized spherical and rod-shaped Ag NPs were analyzed by indirect methods by analysis of plasma band (UV-vis spectra) and thin films X-ray diffraction (XRD) peaks. Whereas, for direct methods, morphologies of synthesized Ag NPs were recoded using HR-TEM. Ag NPs demonstrated dose-dependent antibacterial efficacy against bacteria ( S. aureus). The MIC and MBC values of spherical Ag NPs against 106CFU/mL of S. aureus were found to be 2.74 and 3.80µ g/mL, respectively. However, MIC and MBC values of Ag nano-rod were observed at 7.20µ g/mL and 13µ g/mL, respectively. SEM micrographs indicate that morphologies of spherical shape and nano-rod Ag NPs treated S. aureus showed breakdown, merge, and elongated morphologies with the presence of Ag NPs (nano-rod) inside of the S. aureus. more...

We present a novel and effective algorithm to solve non-linear fractional order partial integro-differential equations which is based on the optimal perturbation iteration transform method. The fractional order derivative will be in the Caputo-Atangana-Baleanu sense. The optimal perturbation iteration transform method is a combination between the Laplace transform and the perturbation iteration algorithm. The solution is described by the suggested method as a quickly convergent series. To demonstrates the applicability of the proposed technique, two model examples are solved. The present paper also unveils that optimal perturbation iteration transform method quickly converges to the precise answers of the provided equations at a reduced iteration value. more...

At present, the detection of surface defects of paper-plastic composite bags still mainly depends on manual visual inspection, which is very inefficient and easy to cause false detection. Based on the algorithm which combines edge detection and adaptive region growth, binary images of the surface defect areas is extracted, six types of shape features and seven types of invariant moment features are defined by calculation as the basis to complete the effective extraction of the surface features, then a paper-plastic composite bags surface defect detection platform is built to complete the defect detection experiment, the defect screening experiment was completed by the rapid screening method of its surface defect image based on gradient projection difference. At the same time, based on Genetic Algorithm (GA), Particle Swarm Optimization, and Grey Wolf Optimization, parameter optimization models of Support Vector Machine were established, respectively. Through experimental comparison, some results show that the defect detection and classification accuracy rate reach 96.83% based on the GA, and the detection speed with the screening method is 3.75 times faster than that without the screening method. Therefore, the reliability of the image classification and screening method for bags surface defects proposed in this study is verified. more...

Petroleum products are vital to the country’s economy and are transported by pipelines. The main goal of this article is to investigate one of the components of crude oil, sulphur, and examine the impact on carbon steel pipes (API 5L [X60, X46, and X42] and A106 pipe) and demonstrate how sulphur content affects various types of API 5L XL independently from the other significant factors present in the crude oil. The sulphur has a huge impact on the mechanical characteristics and corrosion resistance of petroleum pipelines. We found that an increase in the sulphur content led to an increase in the corrosion rate (CR) and decreased the mechanical properties. It has been shown that the safest and most economical way to transport crude oil is through pipeline networks for gas and oil. Internal and external corrosions are the primary problems with API 5L and other steel pipelines used in the transportation of oil and gas. The TR-TCXRF (X-ray Fluorescence Sulphur Tester) instrument is used in this study to determine the sulphur content of crude oil. Using weight loss and the Tafel extrapolation method, the CR, corrosion potential, and corrosion current of carbon steel pipes A106 and API 5L (X60, X46, and X42) in four immersion solutions were calculated. Using an optical microscope, scanning electron microscope, and energy dispersive spectroscopy (EDS), the products of corrosion were iron sulphate (Fe2SO4) and iron sulphide (FeS), and iron oxide (Fe2O3); the corrosion properties of the samples were measured morphologically. The results showed that the pipeline CR significantly increases with increasing concentration of sulphur content. X60 pipe was more resistant to corrosion than X46 and X42 in API 5L-type pipes. more...

In Iran, more than 50,000 hectares of sunflowers (oil and nuts) are cultivated annually. Conventional grain combine harvesters are not compatible with the unique characteristics of sunflowers, leading to significant grain losses during harvesting. Therefore, it is currently being harvested manually. Manual harvesting increases labor hardships, energy and time consumption, and production costs. In this research, to harvest sunflower seeds, modifications were made on conventional head of a combine harvester (John deer 1055) to allow simultaneous harvesting, threshing, and cleaning of the sunflower seeds. After designing and fabricating the accessory, the improved head in field conditions was evaluated and compared with conventional harvesting methods. The field evaluation of the improved head was based on a randomized complete block design with three replications. The treatments involved three different harvesting methods: 1) using a modified combine head, 2) employing a combine equipped with pan attachment, and 3) manual harvesting. In each of the machine treatments, beating and cleaning units were set up for sunflower harvest. The results showed that there was a significant difference between the treatments concerning machine losses, field capacity, and harvesting costs, all at the 5% significance level. In the modified combine, combine with pans attachment, and manual method, combine losses were 0.72, 4.85, and 6%, and field capacity was 1.2, 1.13, and 0.12 ha h-1, respectively. The profit-to-cost ratio was 13.97, 13.3, and 3.01, respectively. The grain breakage percentage was 3, 3.3, and 0.56, respectively. According to the results, due to lower losses, appropriate field capacity, and lower harvesting costs, the use of John deer 1055 combine with the modified head is recommended for harvesting of the sunflower. more...

Magnetic resonance imaging (MRI) is a non-destructive technique for determining the quality of fruits which, with different protocols, shows the density and structure of hydrogen atoms in the fruit in which it is placed. This study compared MRI images of healthy and bruised apple flesh tissues, both with and without pests, using various protocols to identify the best one. For this purpose, magnetic resonance imaging (MRI) using two protocols: T1 (Spin-lattice relaxation time) and T2 (Spin-spin relaxation time), was carried out on 200 apple fruits that were loaded during storage. The loading of fruits was performed at four levels: 150, 300, 450, and 600 N in a quasi-static manner, and then stored for periods of 25, 50, and 75 days at 4 °C. At the end of each storage period, imaging was carried out. Then, the contrast of T1 and T2 images of healthy and bruised tissue of apple fruit with and without pests using ImageJ software was determined. It was concluded that the healthy tissue of apple fruit without pests was clearer in T1 images than in T2 images. It has also been seen that the bruised area of fruits without pests in T2 images is more recognizable than in T1 images. more...

The main objective of this research is to create a comprehensive and adaptable framework for assessing performance in agricultural supply chains and develop two improving approaches. The most relevant performance measures are selected to assess the current status of services in agricultural supply chains (ASCs). The contribution of this research is related to the selection of key performance indicators (KPIs) and approaches for enhancing ASC performance. The proposed framework comprises performance measurement and a service selection process. Two approaches have been developed based on the selected KPIs of services in ASC to identify which services require improvement. The proposed approaches are robust and versatile tools for agricultural managers to strategize and enhance their supply chains. A case study is also presented from Iran. For this region, selection approaches prioritize agricultural services such as postproduction consulting, financial support, mechanization, business consulting, and input supply. The framework shows that these services should be improved in order to better meet the needs of the region under study. more...

Optimal use of resources, including energy, is one of the most important principles in modern and sustainable agricultural systems. Exergy analysis and life cycle assessment were used to study the efficient use of inputs, energy consumption reduction, and various environmental effects in the corn production system in Lorestan province, Iran. The required data were collected from farmers in Lorestan province using random sampling. The Cobb-Douglas equation and data envelopment analysis were utilized for modeling and optimizing cumulative energy and exergy consumption (CEnC and CExC) and devising strategies to mitigate the environmental impacts of corn production. The Cobb-Douglas equation results revealed that electricity, diesel fuel, and N-fertilizer were the major contributors to CExC in the corn production system. According to the Data Envelopment Analysis (DEA) results, the average efficiency of all farms in terms of CExC was 94.7% in the CCR model and 97.8% in the BCC model. Furthermore, the results indicated that there was excessive consumption of inputs, particularly potassium and phosphate fertilizers. By adopting more suitable methods based on DEA of efficient farmers, it was possible to save 6.47, 10.42, 7.40, 13.32, 31.29, 3.25, and 6.78% in the exergy consumption of diesel fuel, electricity, machinery, chemical fertilizers, biocides, seeds, and irrigation, respectively. more...

The IoT monitoring system for stingless bee colonies aims to provide real-time information about temperature, humidity, and hive weight in response to the issue of colony collapse disorder (CCD) caused by human intervention in beekeeping. It also aims to improve the current monitoring methods for the bees more effectively and efficiently. The monitoring system features a water-cooling control system to maintain an optimal temperature for Tetragonula Biroi (Stingless Bees). The system also includes a user dashboard for remote monitoring and alerts the beekeeper when it is time to harvest. It’s primarily built around the ESP8266-MOD microcontroller, with an Arduino Mega 2560 R3 for the water valve control system. Data were collected from a DHT22 sensor for temperature and humidity, and load cells connected to an HX711 amplifier for hive weight. The system was tested by comparing samples from the system and actual measuring instruments using MAPE for two months, and it demonstrated 98.74% and 97.89% accuracy for surrounding temperature and humidity, respectively. An accuracy of 95.92% for the weight scale and 93% for the water valve control system was also obtained. Hives equipped with the IoT system gained 3.414% more weight than those without it, indicating that the project succeeded in achieving its objectives. more...

Diagnosing plant diseases is an important part of crop management and can significantly affect the quantity and quality of production. Traditional methods of visual assessment by human observers are time-consuming, costly, and error-prone, making accurate diagnosis and differentiation between various diseases difficult. Advances in agriculture have enabled the use of non-destructive machine vision systems for plant disease detection, and color imaging sensors have demonstrated great potential in this field. This study presents a framework for diagnosing early blight and late blight diseases in potatoes using a combination of Relief feature selection algorithms and Random Forest classification, along with color, texture, and shape features in three color spaces: RGB, HSV, and CIELAB (Lab*). The results indicated that the diagnostic accuracy for the early blight and late blight disease groups, as well as the healthy leaf group, were 94.71%, 95%, and 95.2%, respectively. The overall accuracy for disease classification was 95.99%. Additionally, the diagnostic accuracy for the early blight and late blight disease groups, along with the healthy leaf group, was 91.07%, 98.36%, and 98.93%, respectively, with an overall classification accuracy of 96.12%. After separating the diseased area from the healthy part of the leaf, a total of 150 features were extracted, including 45 color, 99 textural, and 6 shape features. The most effective features for disease detection were identified using a combination of all three feature sets. This study demonstrated that integrating these three sets of features can lead to a more accurate classification of potato leaves and provide valuable insights into the diagnosis and classification of potato diseases. This approach can help farmers and other plant disease specialists to accurately diagnose and manage potato diseases, and ultimately lead to an increase in product quality and yield. more...

In this study, the air drying of cumin seeds was boosted by cold plasma pre-treatment (CPt) followed by high-power ultrasound waves (USp). To examine the impact of included effects, different CP exposure times (0, 15, and 30 s), sonication powers (0, 60, 120, and 180 W), and drying air temperatures (30, 35, and 40 ºC) were selected as input variables. A series of well-designed experiments were conducted to evaluate drying time, effective moisture diffusivity, and energy consumption, as well as color change and rupture force of dried seeds for each drying program. Numerical investigations can effectively bypass the challenges associated with experimental analysis. Therefore, the wavelet-based neural network (WNN), the multilayer perceptron neural network (MLPNN), and the radial-basis function neural network (RBFNN), as three well-known artificial neural networks models, were used to map the inputs and output data and the results were compared with the Multiple Quadratic Regression (MQR) analysis. According to the results, the WNN model with an average correlation coefficient of R2 > 0.92 for the train data set, and R2 > 0.83 for the test data set provided the most beneficial tool for evaluating the drying process of cumin seeds. more...

In some countries, people commonly consume hazelnuts in their shells to extend shelf life or due to technological limitations. Therefore, open-shell hazelnuts are more marketable. At the semi-industrial scale, open-shell and closed-shell hazelnuts are currently separated from each other through visual inspection. This study aims to develop a new algorithm to separate open-shell hazelnuts from cracked or closed-shell hazelnuts. In the first approach, dimension reduction techniques such as Sequential Forward Feature Selection (SFFS) and Principal Component Analysis (PCA) were used to select or extract a combination of color, texture, and grayscale features for the model’s input. In the second approach, individual features were used directly as inputs. In this study, three famous machine learning models, including Support Vector Machine (SVM), K-nearest neighbors (KNN), and Multi-Layer Perceptron (MLP) were employed. The results indicated that the SFFS method had a greater effect on improving the performance of the models than the PCA method. However, there was no significant difference between the performance of the models developed with combined features (98.00%) and that of the models using individual features (98.67%). The overall results of this study indicated that the MLP model, with one hidden layer, a dropout of 0.3, and 10 neurons using Histogram of Oriented Gradients (HOG) features as input, is a good choice for classifying hazelnuts into two classes of open-shell and closed-shell. more...

Depending on renewable energy in buildings has become an urgent necessity that represents an important part of relying on operating buildings using renewable energy technologies. This importance has increased with the global energy crisis. There has been a development in the systems and technologies of the renewable energy use in buildings, accompanied by several techniques to integrate it with the building elements, but it was not sufficient to reach the stage of complete integration between the building elements and the renewable energy elements, especially in the architectural elements of the building envelope. The problem of the research discusses the separation between the architectural elements of the building envelope and the technical systems for the solar energy technologies, as it appeared more clearly with the use of these technologies in buildings, which may cause an obstacle that is not architecturally accepted by the users. The research aims to study the environmental impact of the integration of photovoltaic units with the openings of the building's outer envelope through a proposed methodology for the design steps of integrated sun breakers, applying it to one of the widely typical building models represented by the prototype models for schools in the Educational Buildings Authority. The research concluded the importance of amending the prototype design standards for school buildings for external windows, taking into consideration the differences between the climatic regions in Egypt, as it appeared that the energy-generating sun breakers have a positive impact on the natural lighting levels, thermal comfort and energy consumption, as the sun breakers contributed to increasing the natural lighting area from 62.50% to approximately 89% as a percentage of the internal area of ​​the classroom, in addition to improving the level of thermal comfort by 48%, while achieving savings in energy consumption by about 14% by activating its role as a renewable energy generating element, which indicates the importance of the study, especially in the prototype buildings to achieve a positive impact throughout the Arab Republic of Egypt. الإعتماد على الطاقات المتجددة أصبح من الضرورة الملحة للإعتماد على تشغيل المباني باستخدام تقنياتها، وقد ازدادات هذه الأهمية مع أزمة الطاقة العالمية، وقد حدث تطور ملحوظ في نظم توليد الطاقات المتجددة في المباني مصاحبا تقنيات لدمجها مع عناصر المبنى إلا أنها لم تكن بالقدر الكافي للوصول للتكامل التام بين عناصر المبنى وعناصر مولدات الطاقة، خاصة في عناصرالغلاف الخارجي بحيث تساهم في توليد الطاقة من خلال منظور معماري متكامل. وتكمن إشكالية البحث في الانفصال ما بين عناصرالغلاف الخارجي ونظم إستغلال الطاقة الشمسية، حيث ظهرت واضحة مع التوسع في استخدام تلك التقنيات، مما قد يسبب عائقا لعدم القبول المعماري لمستخدمي المباني.وتهدف الدراسة إلى دراسة الأثر البيئي لتكامل وحدات الخلايا الفوتوفولتية مع فتحات الغلاف الخارجي للمبنى من خلال منهجية مقترحة للخطوات التصميمية للكاسرات الشمسية التكاملية المولدة للطاقة، وذلك تطبيقا على أحد نماذج المباني النمطية واسعة التطبيق والمتمثلة في النماذج الموحدة للمدارس.وقد توصلت الدراسة إلى أهمية تعديل المعايير التصميمية لنماذج المدارس للنوافذ مع الوضع في الإعتبار الإختلافات بين الأقاليم المناخية، حيث ظهر للكاسرات الشمسية المولدة للطاقة الأثر الإيجابي على مستويات الإضاءة الطبيعية والراحة الحرارية والطاقة المستهلكة للفراغ، حيث ساهمت في زيادة مسطح الإضاءة الطبيعية من 62.50 % إلى ما يقارب 89 % كنسبة من المسطح الداخلي للفصل، إضافة إلى تحسين مستوى الراحة الحرارية بنسبة 48 % بعد استخدام الكاسرات، مع تحقيق الوفر في الطاقة المستهلكة بنسبة حوالي 14% من خلال تفعيل دورها كعنصر مولد للطاقة المتجددة على مستوى الفصل الواحد، الأمر الذي يظهر أهمية التطبيق خاصة في نماذج المباني النمطية واسعة الإنتشار لتحقيق الأثر الإيجابي على نطاق كافة أنحاء جمهورية مصر العربية. more...

Abstract: The issue of distorting and demolishing buildings with a distinctive architectural style is a widespread phenomenon in recent times, leading to their disappearance, and thus the loss of the distinctive general character of the place, in order to keep pace with the requirements of the era through the owner, where old buildings with distinctive value are distorted and demolished and modern buildings are built in terms of form and content, where the entire surface of the land is exploited and build high-rise buildings. with modern materials to exploit the place and benefit from it to the maximum possible marketing benefit, then some theoretical reference studies were conducted to study some concepts, standards and specifications related to valuable buildings that are considered a distinctive architectural style and stipulated in Law No. 144 of 2006, then moving to field studies of those buildings in some different governorates through monitoring, photography and interviewing some experts and officials as well as the owners of those buildings with a distinctive architectural style, in order to reach results that were presented through the research, then moving to the questionnaire to survey the opinion and participate in the thought to know the extent of society's awareness of the importance of this topic, where a group of architects and students studying in the field of architecture and the general public participated, and the door was opened for dialogue for discussion and presentation of different ideas. In addition to conducting some interviews to present proposals to reach results and recommendations, and from this standpoint, this research is an invitation to pay attention to buildings with a distinctive architectural style that represent some areas of distinctive value, and to benefit from them while educating current generations to preserve them because they represent the thought and culture of society in specific time periods, and they are an important legacy from previous generations that must be developed to be handed over to future generations. الملخص :يعد موضوع تشويه وهدم المباني ذات الطراز المعماري المتميز ظاهرة منتشرة في الآونة الأخيرة مما يؤدى إلى اندثارها، وبالتالي ضياع الطابع العام المميز للمكان، وذلك لمواكبة متطلبات العصر من خلال المالك حيث تشويه وهدم المباني القديمة ذات القيمة المتميزة وبناء عمارات حديثة من حيث الشكل والمضمون حيث استغلال كامل مسطح الأرض وبناء مباني ذات ارتفاعات شاهقة بمواد بناء حديثة مستعملة وذلك لاستغلال المكان والاستفادة منه أقصى استفادة تسويقية ممكنة، ومن هنا قد تم التوجه إلى عمل بعض الدراسات النظرية المرجعية وذلك لدراسة بعض المفاهيم والمعايير والمواصفات والتي تخص المباني ذات القيمة والتي تعد طراز معماري متميز والمنصوص عليها بالقانون رقم 144 لسنة 2006، ثم الانتقال إلى الدراسات الميدانية لتلك المباني ببعض المحافظات المختلفة وذلك من خلال الرصد والتصوير ومقابلة بعض الخبراء والمسؤولين وكذلك ملاك تلك المباني ذات الطراز المعماري المتميز، وذلك للوصول إلى نتائج تم عرضها من خلال البحث، ثم الانتقال إلي الاستبيان لاستطلاع الرأي والمشاركة في الفكر لمعرفة مدى إدراك المجتمع لأهمية ذلك الموضوع حيث شارك فيه مجموعة من المهندسين المعماريين والطلاب الدارسين في مجال العمارة والعامة من الناس، وقد تم فتح باب الحوار للمناقشة وعرض الأفكار المختلفة، بخلاف إجراء بعض المقابلات لعرض المقترحات للوصول إلى نتائج وتوصيات، ومن هذا المنطلق فإن هذا البحث دعوه للاهتمام بالمباني ذات الطراز المعماري المتميز والتي تمثل بعض المناطق ذات القيمة المتميزة، والاستفادة منها مع توعية الأجيال الحالية للحفاظ عليها لأنها تمثل فكر وثقافة المجتمع في فترات زمنية محددة، وهي تعد موروث هام من الأجيال السابقة يجب تنميته لتسليمه للأجيال القادمة. more...

University buildings consume a large percentage of energy rates in buildings in general due to their occupants, their activities and their occupancy pattern, as the higher education sector constitutes a small but important part of the existing global buildings sector, which is 20% of the non-residential horizontal area. Universities can be considered “small cities” due to their size, number of occupants, and various complex activities. Therefore, huge energy savings can be achieved when improving and raising the efficiency of energy consumption in this sector. Therefore, the research focuses on evaluating the energy efficiency of university educational buildings, the standards followed to reduce energy consumption in the educational building and identifying the most important strategies that must be followed to adapt university buildings using the Design Builder program, as many universities around the world have moved to reduce energy consumption in buildings and university campuses to be a nucleus for spreading awareness in the wider community about the importance of energy efficiency due to the huge potential for reducing energy in this sector. The research concluded with a set of results, the most important of which are: The use of double walls is an effective means of increasing the thermal conductivity of the wall; The thermal conductivity of a material increases with the thickness of that material, and the total thermal conductivity of a multi-layer material is the sum of the thermal conductivity of all the layers inside it. The effect of different alternatives on the energy consumption of the roof varies, but the most effective alternative is to make a canopy of wood with a green roof underneath it. Sunbreakers also have a greater effect when used on the windows of the southern facade. الملخص تستهلك المباني الجامعية نسبة كبيرة من معدلات الطاقة في المباني بشكل عام بسبب شاغليها وأنشطتهم ونمط إشغالها، حيث يشكل قطاع التعليم العالي جزءاً صغيراً ولكن هاماً من قطاع المباني العالمية القائمة والمتمثل في 20 % من المساحة الأفقية غير السكنية، فيمكن إعتبار الجامعات ”مدن صغيرة” نظراً لحجمها، وعدد شاغليها، والأنشطة المعقدة المختلفة بها، وبالتالي يمكن تحقيق وفورات ضخمة في الطاقة عند تحسين ورفع كفاءة إستهلاك الطاقة في هذا القطاع، لذا يركز البحث على تقييم كفاءة الطاقة في المباني التعليمية الجامعية، والمعايير المتبعة لخفض إستهلاك الطاقة في المبنى التعليمي وتحديد أهم الإستراتيجيات التي يجب إتباعها لتكيف المباني الجامعية وذلك بإستخدام برنامحDesign Builder، حيث إتجهت العديد من الجامعات على مستوى العالم إلى خفض إستهلاك الطاقة في المباني والحرم الجامعي لتكون نواه لنشر الوعي في المجتمع الأوسع بأهمية كفاءة الطاقة نظراً للإمكانيات الضخمة لتخفيض الطاقة في هذا القطاع. وقد خلص البحث إلى مجموعة من النتائج أهمها: أن إستخدام الحوائط المزدوجة من الوسائل الفعالة لزيادة الموصلية الحرارية للحائط؛ حيث تزداد الموصلية الحرارية للمادة بزيادة سمك هذه المادة، كما أن الموصلية الحرارية الكلية لمادة متعددة الطبقات هي مجموع الموصلية الحرارية لكل الطبقات الداخلة بها، ويتفاوت تأثير البدائل المختلفة على إستهلاك الطاقة بالسقف، إلا أن أكثر البدائل فاعلية كان عمل مظلة من الخشب وأسفلها سقف أخضر، كما تؤثر كاسرات الشمس بشكل أكبر عند إستخدامها على نوافذ الواجهة الجنوبية. more...

Hand mobility and dexterity are crucial for daily activities, yet conditions such as stroke and wrist-related injuries can severely impair these functions. A prevalent post-stroke condition, spasticity, is characterized by high muscle tone and stiffness, making joint flexion significantly more strenuous. This study addresses the substantial torque required for effective wrist rehabilitation in stroke survivors. Our approach involves optimizing the dimensions of a Stephenson III six-bar mechanism to minimize the peak assisting torque, leveraging wrist stiffness data from stroke patients. The genetic algorithm is used to optimize the mechanism dimensions to get a nonlinear angular displacement function between the input and output links. This drastically reduces the required actuation torque. Rigorous validation of the optimized mechanism was conducted using Simscape Multibody dynamics simulation environments. Remarkably, the optimized mechanism achieves a peak actuation torque of just 1.64 N.m when assisting users with typical wrist spasticity, a stark contrast to the 11.69 N.m required when the joint is directly actuated. This research not only offers a promising avenue for developing efficient, lightweight, and cost-effective rehabilitation devices but also holds the potential to significantly enhance the quality of life for individuals with impaired wrist mobility. more...

4.0 mm thick cold-rolled AA5754 and AA5052 aluminum alloy plates were friction stir welded (FSW) under different rotation rates, welding speeds, and tilt angles. Tool pin profiles; cylindrical threaded, square, taper threaded, and triangular have been used to fabricate the joints. The influence of these welding parameters on microstructure, mechanical properties and corrosion resistances were investigated by means of the optical microscope (OM), scanning electron microscope (SEM), potentiodynamic polarization, and microhardness tests. The experiments are performed based on L16 orthogonal array considering the Taguchi technique for four design factors and four parametric levels. The welding parameters and tool pin profile play major roles in deciding the weld quality. This study reveals that the square pin profile tool creates welds that are both mechanically robust and free from metallurgical defects, outperforming other pin profiles. The square pin tool, when used with a rotational speed of 1000 rpm, delivers superior results, traverse velocity of 56 mm/min, and tool tilt angle of 4º gives high resistance to corrosion compared with other tool profiles. more...

The built environment enhances human life, prompting architects and engineers to adopt innovative technologies for better building performance. Thermochromic glass has gained attention as a sustainable solution for improving energy efficiency by adjusting solar heat gains based on external temperatures. This study examines the energy performance of thermochromic glass in an office building in Cairo's new administrative capital, known for its hot-arid climate, using advanced simulation tools to compare its thermal and optical properties to conventional glazing systems including Design Builder Software Ltd. and Energy Plus, to analyze two distinct building scenarios: one with conventional glazing and the other using thermochromic glass technology. Both scenarios incorporated typical occupancy patterns, heating, ventilating, and air conditioning systems, to evaluate energy consumption, thermal comfort, and daylight performance. Study findings indicate that thermochromic glass significantly reduces cooling energy demand by limiting solar heat gain during peak temperatures while maintaining adequate daylight levels. It recorded remarkable reductions in solar heat gain through the building's external glazing system, achieving reductions of up to 90.18 % compared to buildings with conventional glazing. This translates to annual energy savings of up to 51.16 % compared to conventional glazing, highlighting its potential to decrease energy loads in areas with extreme heat. Additionally, this system enhances indoor thermal comfort by minimizing overheating and decreasing reliance on artificial cooling systems. The findings highlight the viability of thermochromic glass as a cost-effective and environmentally friendly technology for sustainable building design in hot-arid climates. more...

Utilizing waste rubber in concrete enhances its ductility, toughness, and impact resistance while reducing the structural members' weight. Additionally, incorporating waste rubber supports the creation of environmentally friendly concrete and promotes sustainable production, which is increasingly emphasized nowadays. This research examines the behavior of full-scale rubberized reinforced concrete (RC) columns under concentric loading. Eight reinforced concrete columns with dimensions of 300×300×1200 mm were constructed and subjected to concentric loading until failure. The primary variables in this study were concrete type and stirrup configuration, and spacing. Two columns, cast with normal concrete, served as references for comparison with six rubberized RC columns. The rubberized concrete mix had crumb rubber (CR) at 20% volume substitution for sand, ensuring admissible fresh properties and minimal strength depletion. Key design considerations, including damage progression, ultimate strength, ductility, and toughness, were analyzed. The findings indicate that rubberized concrete can achieve comparable performance to traditional concrete, with improvements in ductility. An increase in strength and ductility were recorded for the concrete cores of well-confined columns. more...

This paper presents the development of an innovative responsive space divider designed to enhance co-working environments. This study seeks to create an adaptive architectural feature that reacts to user activity, ultimately boosting productivity, collaboration, and well-being. It draws on principles from interactive architecture, color theory, and user-centered design.The design approach was inspired by the remarkable color-changing abilities of chameleons, leading to the creation of a fortune teller-themed device that showcases four distinct color combinations. The prototype employed an Arduino-based control system that processes data from motion and sound sensors to enable the divider to switch between four operational modes: focus, learning, collaborative, and socializing. Every cell of the space divider is associated with a unique color palette informed by the principles of color psychology, creating an optimal environment for various performance tasks within the interior space.The fabricated prototype employed a complex methodology, combining digital modeling with physical prototyping. The study selected PET fabric as the primary material for the divider pieces, aligning environmental goals with durability and aesthetic qualities. The creation of this responsive space divider prototype showcases the possibilities of integrating interactive technology with architectural elements, promoting more flexible and user-focused work environments. This project lays the groundwork for future explorations into interactive architecture in co-working spaces, potentially transforming the design and interaction within shared workspaces. more...

Asphalt pavement production and construction needs substantial amount of energy and non-renewable materials. Therefore, using recycled materials seems necessary to create more sustainable asphalt concrete pavements. This article aims to examine the performance of sustainable asphalt mixtures incorporating reclaimed asphalt pavement and investigate and evaluate the cracking resistance of the produced mixtures. To achieve the study objectives, an experimental program was designed for the hot asphalt mixtures using four different bitumen contents (4.5, 5.0, 5.5, and 6.0%), four RAP contents (20%, 40%, 60%, and 80%), in addition to a control mix (without RAP). Marshall Test method was used to investigate the volumetric and mechanical properties of the prepared asphalt mixtures containing RAP. The load-displacement analysis was performed to investigate and evaluate the indices of cracking resistance, fracture energy and fracture work density by using Indirect Tensile Testing program. The results indicated that the volumetric and mechanical properties; stability, Stiffness, and density of the mixtures containing RAP are greatly similar to those of the hot asphalt mixture without RAP. The analysis of indirect tensile strength results indicated that the cracking parameters; CT Index, CRI Index and FST Index containing 40% RAP are higher than those of the other RAP mixtures. Statistical analysis showed that Stiffness, stability, air void and flow of RAP mixtures were significant. Also, the fracture energy, indirect tensile strength and fracture work density of RAP mixes were not significantly different from the control mix except in some cases. more...

This paper investigates the controversial historically / decayed al-Hattaba, a neighborhood in the heart of Historic Cairo, Egypt, that is set for demolition by the state. The state’s unwillingness to consider alternative approaches when dealing with decayed settings raises the controversial question: Should the city’s layers of decay be removed, or should they be saved? We used urban decay photographs along the boundaries of al-Hattaba, where three entities clashed: the neighborhood’s urban fabric, the Saladin Citadel, and Bab-Al-Wazier cemeteries, to contribute an answer to this question. We present an alternative view reflecting marginalized ruination qualities, as a physical narration for the political and economic dilemmas, as a manifestation of lost past, memories and potentials, and to introduce new orders to common space classifications. Our methodology included an in-depth literature review of alternative theories, photo-walks through al-Hattaba and thematic photo-analysis. Through the findings of this study, we argue that al-Hattaba is a decayed yet still living setting with potential for revival. It holds historical, social, and cultural significance. Proper management and investment could transform it into an alternative city experience. While decayed, Al-Hattaba should not be demolished, as doing so would erase its valuable history. This study aims to spark dialogue on preserving decaying spaces like Al-Hattaba and reconsidering what is deemed worthy of saving. more...

Self-motion Robots and their static environments are the main topics for trajectory planning researchers, especially when the environments contain static and movable obstacles that make the robots' mission harder to reach their target. Therefore, accurate and comprehensive knowledge of autonomous robots' control strategies makes us take the basic steps to build our approach in mobile robot trajectory planning. Accordingly, in this research paper, we will provide an accurate detail of two path planning algorithms A star and 4_sector wavefront algorithms. Some modifications and improvements to its software structure for each algorithm will reduce the time it takes for the robot to reach the desired goal, taking into account the presence of obstacles in the map that is dealt with and how to avoid collision with it, especially dead-end obstacles, which cause the robot to enter into a state of making wrong decisions that can lead to a collision or a significant waste of time required to reach the specified goal. The simulation results of the A-star algorithm and 4_sector wavefront methods using MATLAB program are achieved in different ways using inputs via camera, then image processing is applied to determine the locations of obstacles, starting point, free space, and target point for the robot without any position error. The wavefront algorithm takes a shorter time than the A-star method to reach the final position. more...

Abstract This study critically evaluates the predictive performance of the Hardening Soil Model (HSM) and the Hypoplastic Model with small-strain stiffness (HYPO-Small) for simulating the behavior of shallow foundations on sandy soils subjected to vertical loading. Both models were rigorously calibrated using experimental data derived from site-specific and laboratory tests, particularly triaxial testing, ensuring a robust representation of the complex, nonlinear soil behavior under loading conditions. Model validation was carried out through controlled load tests, affirming their reliability in predicting real-world responses. The findings reveal that the HYPO-Small model is particularly effective in capturing the nonlinear and cyclic characteristics of soil behavior, excelling in the simulation of hysteresis effects and small-strain stiffness. These capabilities make it highly suitable for advanced analyses of soil-structure interactions under cyclic loading conditions. In contrast, the HSM provides more accurate predictions of initial stiffness and early-stage settlements, offering substantial value in the preliminary design phase of foundation systems. By rigorously validating both models through comprehensive numerical simulations, this study delineates their respective advantages and limitations, providing a clear framework for geotechnical engineers to select the most appropriate constitutive model for achieving optimized, efficient, and cost-effective foundation designs. more...

The escalating hazard of weather change necessitates pressing advancements in carbon-mitigating technologies. The CO₂ capture with zeolites involves working by physical and chemical adsorption, taking advantage of the high surface area, porosity, and the crystalline structure zeolites possess. Zeolites, with their incredible adsorption properties, have emerged as promising materials for carbon capture. However, optimizing zeolite structures to maximize carbon capture efficiency is a complicated and useful resource-extensive technique. Traditional optimization techniques, at the same time effective, are regularly restricted using their computational demands and incapability to fully discover the considerable design space, leading to suboptimal answers. This study introduces a novel integrated model that mixes Genetic Algorithms (GA) with Generative Adversarial Networks (GANs) to enhance the layout and optimization of zeolite systems for carbon capture. GAN stands for generative adversarial networks, which are actual AIs that create realistic data, whereas GA resembles the process of natural selection to get the best solution. They both enhance the zeolite design in this study. The GA component successfully searches the design space by iteratively choosing and evolving promising zeolite systems, even as the GAN aspect generates new, high-capacity systems based totally on learned styles from present facts. This GA-GAN hybrid approach addresses the constraints of modern-day strategies by enabling a complete exploration of feasible zeolite configurations and improving the probability of identifying the optimal approach. Optimization of the zeolite structure is done by a blend of genetic algorithms in conjunction with Generative Adversarial Networks for improved adsorption capacity, surface area, and selectivity of CO₂ capture. The latest research report has found that the GA-GAN mix model completely outperforms classical optimization methods, a promising tool for advanced carbon capture materials development to this end. The study introduces a brand-new approach to finding the best zeolite designs by merging the characteristics of genetic algorithms and generative adversarial networks. The findings and analysis imply that it is indeed this combined model that will push the carbon capture drive in the future, thus helping global climate change. more...

Rolling bearings are critical components in many machines, and their performance is vital to ensure the smooth and efficient operation of various industrial systems. Accurate fault diagnosis and prediction of rolling bearings' remaining useful life (RUL) are essential for implementing effective predictive maintenance strategies. This paper proposes a hybrid approach using a feedforward MLP and LSTM network to improve fault detection and RUL estimation. The dataset includes voltage signals recorded under various fault conditions, such as inner and outer raceway defects. The signals were pre-processed using normalization and band-pass filtering to enhance data quality before feature extraction. STFT was employed to transform the voltage signals into time-frequency representations for detailed analysis of transient characteristics. The hybrid MLP-LSTM model leverages the strengths of both architectures: the MLP captures complex, non-linear relationships, while the LSTM handles sequential dependencies. The model's performance was compared against traditional methods such as FCN, SVM, Decision Tree, KNN, LSTM, and CNN-BILSTM, with the proposed model demonstrating superior results. Our findings highlight the model's effectiveness in identifying bearing faults and accurately predicting RUL, leading to more informed maintenance decisions. The proposed approach can significantly reduce unplanned downtime, extend the operational life of critical machinery, and optimize maintenance schedules. The model achieved an accuracy of 99.9 %, sensitivity of 98.90 %, and specificity of 98.16 %, which is implemented by Python, outperforming existing methods and proving its suitability for predictive maintenance in industrial applications. more...

In this work, animal rabies disease is explored through a nonlinear mathematical model. The necessary conditions under the fractional operator is considered for the existence and uniqueness of solutions. The parameters are estimated through the model calibration with the confirmed cases of rabies in cattle, from 1996 to 2002, in India. Numerical results portray that fractional order gives good fit to the real data in comparison with the classical order. Moreover, different control strategies, based on the sensitivity of parameters, are discussed for the controlling and reduction of the infection. more...

An analysis of the prominent translation and storage effects is considered in the presence of a wavy flow of generalized Newtonian fluid, namely Cross fluid. A class of practical applications is related to the significance of a reservoir in terms of water and other liquid materials which helps to bind the stream's natural flows. In particular, the fluid reservoir is also experiencing some natural and forced convection, which can be practically represented via the mixed convection phenomenon. However, the current assumptions for the entire study indicate the physical effects of gravity, activation energy, viscous dissipation, wavy surface amplitude, Joule heating, and vertical external magnetic field. All the results are disposed of in the form of wavy flow speed, thermal as well as concentration plots. Furthermore, the drag forces along vertical and horizontal directions, rate of heat, and mass flows are illustrated to show the surface force effect on the flow. The amplitude enhances the drag force and an opposite trend is noticed in the visualization of the rate of heat transfer. The higher Lorentz forces and Weissenberg number reduced the flow velocity of the liquid. The rate of mass transfer is escalated through larger values of Schmidt number and reduced for higher values of activation energy. The larger variation in the Richardson number escalates the flow speed of the materials. A well-matched comparison with the previous results is provided to show the validity of the method. more...

Capstone design course prepares students for career advancement and professional practice, where it mainly focuses on collaborative team settings. One of the main challenges facing the capstone design course is grouping the students into teams based on their professional and assigning the formulated groups to faculty members based on their preferences and teaching load. This study uses lexicographical analysis and a heuristic algorithm to handle this challenge, considering two performance measures: the students' and faculty members' satisfaction levels. The lexicographical analysis is an approach that prioritizes multiple performance measures in a strict hierarchical order. Meanwhile, the heuristic algorithm is used to find the near optimal solution. The students' satisfaction levels are measured based on their preferences, which are determined based on grade point average (GPA). On the other hand, the faculty member satisfaction levels are estimated based on the value of the overload resulting from assigning the capstone course students to faculty members. The results conclude that the propounded lexicographical analysis could be utilized when the faculty member satisfaction levels have more weight than the students' satisfaction levels. Meanwhile, the proposed heuristic algorithm could be applied when the students' satisfaction levels are more important than the faculty members' satisfaction levels. more...

Medical imaging is pivotal in modern healthcare, offering a visual window into the human body’s intricate structures and functions. However, the scarcity of diverse and representative medical images significantly limits research progress. Today, deep learning algorithms are increasingly incorporated into the medical imaging domain to automate the diagnostic process. The success of these algorithms relies heavily on vast and diverse datasets. Insufficient data hampers the training and validation of these algorithms, resulting in suboptimal performance, biased results, and reduced generalizability. This paper introduces a pioneering approach that employs a Convolutional Autoencoder (CA) to synthetically generate medical images. The synthetic images produced are then added to the existing database to create an augmented dataset. This augmented dataset is subsequently used for classification with a convolutional neural network. Experiments were conducted on publicly available datasets—the chest CT-scan dataset and the IQ-OTH/NCCD lung cancer dataset. The synthetic image generation capability of the CA was compared with traditional augmentation methods such as flipping, rotating, shearing, shifting, zooming, and sub-sampling. Results showed that the CA-based augmented dataset achieved an accuracy of 91 %, compared to 83 % with the traditional augmentation-based dataset. more...

The integration of carbon nanotube (CNT)-based materials into sustainable technologies has unlocked new potential for addressing critical global challenges, such as water scarcity, energy demands, and climate change. This study explores the transformative applications of CNTs in desalination, hydrogen production, and CO₂ hydrogenation. The objectives are to enhance process efficiency, develop cost-effective solutions, and contribute to environmental sustainability. CNT-based membranes exhibit unprecedented performance in water desalination due to their unique structural properties, including high permeability, selective ion rejection, and antifouling characteristics. Their nanoscale channels mimic biological aquaporins, enabling energy-efficient desalination processes. Functionalization further enhances these membranes by improving fouling control and ion rejection. In hydrogen production, CNTs demonstrate superior electrocatalytic properties for water splitting. The study emphasizes the role of nitrogen and boron doping in increasing reaction rates and reducing overpotential in hydrogen evolution reactions. Additionally, CNT composites integrated with transition metals such as cobalt and nickel significantly enhance catalytic activity and stability, promoting hydrogen production with minimal energy input. For CO₂ hydrogenation, CNTs serve as highly effective catalysts and catalyst supports. Their sp²-carbon framework and high thermal and electrical conductivity enable efficient CO₂ activation and selective conversion into hydrocarbons and alcohols. Functionalization and the incorporation of metal nanoparticles further optimize these processes, making CNTs a key player in greenhouse gas mitigation. This study highlights the novelty of CNT-based materials in delivering scalable, sustainable solutions to pressing environmental challenges. By addressing limitations such as production costs and environmental impact, this research sets a foundation for advancing CNT technologies in critical applications. more...

Water level forecasting plays a vital role in environmental protection and flood management because reliable predictions allow for the deployment of early warning systems to alert the public to minimize the impacts of flooding. This study presents an enhanced approach for weekly water level and flood prediction by integrating data decomposition techniques with machine learning models. Specifically, Ensemble Empirical Mode Decomposition (EEMD) was applied to disaggregate the original water level data into distinct Intrinsic Mode Functions (IMFs) to simplify complexity and enhance periodicity detection. A secondary decomposition was performed on the high-frequency IMF 1, derived from EEMD, to further refine the data features. The K-Nearest Neighbor (KNN) and Support Vector Machine (SVM) models, optimized using Improved Particle Swarm Optimization (PSO), were employed for forecasting. The effectiveness of these hybrid models was evaluated using various performance metrics, revealing that the DEEMD-KNN-PSO and DEEMD-SVM-PSO models significantly outperformed other single decomposition and standalone models. Among these, the DEEMD-KNN-PSO model demonstrated superior accuracy in predicting water levels, showcasing its potential for reliable flood prediction in the Klang River region of Sri Muda, Malaysia. This approach highlights the value of data decomposition and machine learning optimization for improving water level prediction accuracy. more...

In recent years, legal system is gradually moving towards digitalization and networking, which has brought unprecedented improvement to the convenience and efficiency of legal services. The construction and implementation of legal system network has established a unified legal management information platform, standardized business processing procedures and improved work efficiency. However, cybersecurity issues are becoming increasingly prominent and are one of the key factors constraining the digitalization process of the legal system. Especially how to ensure the authenticity of user identity and the security of communication has become an important challenge faced by legal system network. Therefore, we propose an efficient anonymous authentication and key negotiation protocol for legal system network. This protocol generates entity authentication key through chebyshev chaotic mapping and uses a three-factor authentication mechanism to enhance security. Finally, the model and scyther tool prove that the protocol is secure and informal analysis verifies its effectiveness in security features. The experimental findings demonstrate superior computational efficiency and enhanced security. more...

In this work, we take advantage of the characteristic of bulk Dirac semimetals (BDS) that their Fermi level can be controlled by electrostatic doping, as well as the phase transition characteristics of vanadium dioxide (VO2). Combining these two materials, we designed a terahertz metamaterial absorber with multiple control methods. It has four absorption peaks in the range of 1.5 THz to 6 THz, and the absorption rates are all above 95 %, reaching a maximum of 99.8 %. When the Fermi level of Dirac semimetals rises from 80 to 100 meV, the resonance frequency of four absorption bands of our equipment goes up, and the absorption rate remains stable, some even magnifying. The absorption peak with the largest increase in amplitude changed from 92.4 % to 99.9 %, an increase of 7.5 %. The maximum regulation range of the absorption peaks is as high as 0.34 THz. In addition, we explained the absorption principle of the equipment from two aspects: relative impedance matching and analysis of the electric field intensity distribution map, and we demonstrated the rationality of our absorber structure design through parameter scanning. Our absorber also has excellent polarization insensitivity and high refractive index sensitivity. It has potential application value in sensing, detection, medical and other fields, and our design provides new reference value for absorber designs with multiple regulation methods. more...

The abnormal use of antibiotics can absolutely have negative effects on human health. The accumulation of antibiotics in the human body, often through the food chain, will lead to increase the drug resistance and compromise immunity. It will be a main risk as it decreases the efficiency of antibiotics in treatment of the bacterial diseases. Also, it can cause more serious health issues. It is important to apply antibiotics carefully and as healthcare professionals recommend to reduce these risks and maintain the efficiency of these vital chemical compounds. Therefore, it is crucial to research developing sensitive and efficient sensors for detecting ofloxacin (OFL) antibiotic residues in many substances. The proposed photoelectrode displays a higher photocatalytic activity toward the PEC oxidation of OFL. Under the optimal experience conditions, the BiVO4-based PEC sensor displayed a broad concentration range from 20 to 18000 nM with detection limit (LOD) of 7.22 nM. In addition, the proposed sensor exhibited high reproducibility, selectivity and stability in OFL determination. As a result, the proposed sensor with a recovery percentage of 99.15–103.8 can be successfully used in real biological and environmental samples. more...

This study demonstrates the successful application of a new magnetic molecularly imprinted polymer sorbent for the selective and efficient extraction of stanozolol, followed by detection using liquid chromatography-mass spectrometry. To fabricate the magnetic sorbent, the surface of iron oxide nanoparticles was modified using methacrylic acid. Subsequently, these modified particles served as the core for synthesizing the magnetic molecularly imprinted polymer shell. The resulting sorbent was successfully characterized using scanning electron microscopy, Fourier-transform infrared spectroscopy, vibrating sample magnetometry, thermogravimetric analysis and N2 adsorption-desorption methods. The magnetic molecularly imprinted polymer sorbent exhibits superior extraction performance due to its high specificity and affinity for stanozolol, resulting from the imprinting process. Under optimal experimental conditions, the method achieved a calibration range of 0.4–25 ng mL−1, with an impressive detection limit of 0.02 ng mL−1. The novel extraction method exhibited excellent reproducibility and high selectivity, making it an attractive tool for the detection of stanozolol abuse. The practical utility of this methodology was successfully demonstrated through analysis of athlete urine samples, with recovery rates ranging from 92.4 % to 106.2 %. more...

The critical significance of probability distributions in the analysis of real-world phenomena is broadly recognized; however, there is a lack of probability distributions capable of effectively modeling practical data sets. In the quest to analyze real data, researchers often strive to discover new and more effective statistical models. Consequently, numerous probability-based methodologies are created and applied. A majority of these methodologies rely on the introduction of new parameters, which can occasionally result in re-parameterizations. Focusing on this particular research domain, we unveil a new statistical methodology intended to enhance the distributional flexibility of probability distributions. This methodology, which incorporates arcsine and sine functions, is known as the arcsine-sine-G (ASS-G) method. Informed by the ASS-G method, a new variant of the exponentiated exponential distribution has been established, called the arcsine-sine-exponentiated exponential (ASSE-exponential) distribution. Estimators associated with the ASSE-exponential distribution have been successfully obtained. Their performance is scrutinized through a simulation study. In addition, properties concerning quartiles and identifiability are derived. Ultimately, the relevance of the ASSE-exponential distribution is established by examining two data sets sourced from music therapy and reliability engineering. Based on certain evaluation tests, we show the fitting performance of the ASSE-exponential distribution against the rival models. more...

A closed-loop supply chain model incorporating government involvement has been developed to optimize the utilization of waste products, quantifying the quality level of such products. The utilization of game theory within the model allows for an examination of how government incentives and penalties for remanufacturing impact pricing decisions within the closed-loop supply chain. Additionally, a profit coordination contract has been proposed to enhance supply chain profits in decentralized decision-making environments. The findings indicate that: (1) Amid uncertainties in recycling quality, recycling price of retailers, buyback price of manufacturers, recycling quantity, recycling rate, and the profitability of supply chain node enterprises exhibit negative correlations with the remanufacturing quality threshold. A lower threshold for remanufacturing quality can increase the enthusiasm of retailers for recycling and manufacturers for remanufacturing. (2) The increase in government incentives and punishments for remanufacturing will lead to a decrease in the profit of the supply chain. Centralized decision-making yields superior equilibrium solutions for recycling price of retailers, buyback price of manufacturers, and new product quantities compared to decentralized approaches. (3) Regulatory policies aimed at incentivizing remanufacturing rates influence pricing and demand for supply chain products. Government incentives and penalties exert significant influence on enhancing recovery rates. Therefore, it is advisable for the government to adopt suitable standards for remanufacturing incentives and penalties, while enterprises should bolster research, development, and investment in remanufacturing technology to enhance remanufacturing capabilities and stimulate the production of more recycled products, thereby ameliorating resource recycling and mitigating environmental risks. more...

The primary goal of this work is to examine the dynamic movement and chaos of a governed system by the nonlinear forced Mathieu equation (NFME). The multiple-time-scales approach (MTSA) is applied at the third-order level of approximation to provide the approximate solutions of this equation. Concurrently, the modulation equations (MEs) are created and the resonance case is investigated according to the solvability restrictions. Consequently, the solutions are verified at steady-state’s scenario. The criteria of Routh-Hurwitz (CRH) are applied to investigate and appraise the stability/instability zones in line with steady-state solutions. The amplitudes and phases throughout a designated period have been graphed to depict the motion at a particular instant. Furthermore, graphed representations of the acquired results, resonance responses, and stability regions are supplied to assess the impacts of different applied parameter values on the system's conduct. Three first-order equations are created from a non-autonomous second-order differential equation (DE) for solving computationally. Utilizing the Runge-Kutta algorithm, various motion types of the system are shown according to a bifurcation diagram, temporal history, Poincaré map, Lyapunov exponent (LE), and phase portrait. The outcomes also unequivocally show that the studied model possesses rich and sophisticated nonlinear dynamic phenomena, including periodic, period-doubling, period-quadrupling, and chaotic vibrations. Overall, the pendulum model described by the NFME has diverse applications ranging from mechanical engineering and structural dynamics to seismology, and robotics. It offers a mathematical foundation for comprehending the complex dynamics of pendulum-based systems under external forcing and nonlinear effects. more...

The low-temperature oxidation experiments were conducted on lignite immersed in water with short (50 days) and long (200 days) at three different heating rates (0.25℃/min,0.5℃/min, and 1℃/min), providing a theoretical foundation for the assessment of spontaneous combustion risk in goaf coal. Research shows that the heating rate of 1℃/min significantly increases the risk of spontaneous combustion for coal submerged in water, when compared to the other two heating rates. After undergoing a short-time of immersion, the coal sample demonstrates pronounced characteristics of low-temperature oxidation, with both carbon-oxygen gas and heat release intensity showing an exponential relationship with temperature. Compared with short-term soaked coal, coal samples soaked for a long time have lower apparent activation energy and the highest risk of spontaneous combustion. The analysis of the limit parameters suggests that a longer immersion time elevates the susceptibility to spontaneous combustion. more...

Amidst rising global demand for sustainable energy substitutes and the complex hindrances connected with a full-scale shift to new technologies, internal combustion engines (ICEs) using biofuels like biodiesel are progressively acquiring a vital role. However, an immediate global focus is required for cost-effective and echo-friendly biodiesel production. The issues linked with the operating parameters of these ICEs mandate methodical optimization. The study utilized microbubble-mediated esterification with p-toluene sulfonic acid, achieving 89.9 % biodiesel conversion from waste chicken fat in 30 min. Waste chicken fat biodiesel (WCFB) met ASTM D6751 and EN-14214 standards, demonstrating its potential as an alternative fuel. A single-cylinder, direct-ignition engine was tested with WCFB blends (10 %, 20 %, 30 %, and 40 %) to assess performance and emissions in comparison to diesel fuel. Using response surface methodology, optimized conditions (14.2 %WCFB and 1845 rpm) resulted in a 5.6 % increase in torque, 8.9 % more brake power, and a 7.7 % improvement in brake thermal efficiency, along with a 15.9 % reduction in brake-specific fuel consumption. Carbon monoxide emissions decreased by 4.6 %, while exhaust gas temperature and NOx emissions increased by 10.9 % and 4 %, respectively. This study aligns with multiple sustainable development goals, contributing to a more sustainable and resilient future for the planet. more...

This work presents four sets of welded multi-wires on Cu sheet (e.g., A-(95/95mm2), B-(35, 35, 25/35, 35, 25 mm2), C-(50, 35, 10/50, 35, 10 mm2), D-(35, 35, 25/50, 35, 10 mm2)) using ultrasonic wire harness welding (USWW). Forming quality of multi-wire joint, examination of microstructures, root gaps influence, fractographic analysis and surface micro-topography were investigated and clarified. Tensile strength and microhardness of samples in B-(35, 35, 25/35, 35, 25 mm2) increases up to peak load (6527.7 N and 484.5 HV) under welding energy of 1000 J. Tensile strength of B-(35, 35, 25/35, 35, 25 mm2/(6527.7 N)) is 29.2 % higher than A-(95/95mm2/(3681 N)) under effect of root gap. Maximum hardness of Cu plate in group B was obtained 484.5HV and maximum hardness of sample reached 363.2HV and 251HV in group C and A respectively. Stability of sample in group B is generally increased by 20.5 % compared to A3, C5 and D2. Failure displacement of joint A3 is 35 % higher than joint B1. Failure displacement of joint C5 is 15 % higher than joint D2. EDS analysis experienced Cu content at welded interface is higher compared to rest of locations which generates more fine grains structures to increase strength and weldability of joints. Kathmatic microscope investigated microtopographical features in group B sample wherein regular surface size was measured to be approximately 10μm. A standard root gap allows welded sheet to penetrate amid multi-wires being joined tightly and ensures a strong bond in group B. more...

Addressing the privacy security challenges in identity access and data transmission for cloud-assisted intelligent gymnasium, this paper designs a secure identity access and data transmission scheme (SIA-DTS). SIA-DTS employs a three-factor authentication method to achieve secure authentication, protects the privacy of identities, utilizes elliptic curves for enhanced performance and security, and applies lightweight hash operations to minimize computational load. It also establishes secure session keys through Diffie-Hellman key exchange for data transmission security. SIA-DTS is proved to be secure and meets various security requirements as shown by the mode and informal analysis. Furthermore, performance analysis reveals that SIA-DTS significantly reduces computation and communication overhead, thereby improving operational efficiency. Data availability: All relevant data are within the paper. more...