University of Science and Technology Journal for Engineering and Technology
University of Science and Technology Journal for Engineering and Technology (USTJET) is an Open Access Peer-Reviewed Journal Published Biyearly by University of Science and Technology - Yemen. The journal welcomes articles that contribute to a wide spectrum coverage of science and technology. Originality, high quality and significance of the scientific content are essentially considered. Online ISSN: 2959-3166 Print ISSN: 2959-3158
Credit Card Fraud Detection Using Machine Learning Models: A Study Review
Advances in technology have led to the emergence of digital payments. As credit card transactions have become the most common payment method and increasingly sophisticated methods have been adopted by fraudsters, detecting fraudulent transactions has become crucial due to the financial losses incurred by both cardholders and financial institutions. This study aims to review existing research on Credit Card Fraud Detection (CCFD) to provide future researchers with insights into the latest Machine Learning (ML) models applied in this field. This study adopts a critical literature review approach to explore and analyze current studies. With the rapid advancements in CCFD using ML models, which have addressed numerous challenges in this domain, it has become increasingly difficult to identify the techniques that contribute most significantly to its development, as well as the research gaps that require further research. Therefore, this review identifies 20 research articles published between 2022 and 2025. The focus on studies from the past four years ensures coverage of up-to-date developments and the latest technologies. The findings of this review highlight the most effective ML models and CCFD datasets, identify key research gaps, and outline the key evaluation metrics utilized in the field of CCFD, thereby supporting future studies.
Copyright (c) 2026 The copyright is transferred to the University of Science and Technology, Sana’a, Yemen. https://creativecommons.org/licenses/by/4.0
Brain Tumor Classification Using Deep Ensemble Learning Based on Voting Technique
Brain tumor classification is a crucial process in the medical diagnosis field of brain lesions for obtaining a correct diagnosis and then beginning treatment planning. In this study, an ensemble learning approach using a VGG19 model is proposed to achieve high classification accuracy. Three VGG19 models with varying parameters are trained independently. The predictions of the three models are combined using ensemble learning based on the voting technique. The models were trained on a comprehensive dataset of brain MRI scans containing 7,041 MRI images, split into 80% training and 20% testing sets. The raw train dataset is resized and then fed to the three VGG19 models individually. The entire test dataset is preprocessed with sharpening techniques to enhance the details of brain images. The proposed approach achieved an impressive accuracy of 99.33 % on the test dataset, surpassing state-of-the-art methods in brain tumor classification. Furthermore, the proposed approach obtained high precision, specificity, recall, and F1-score, showing its strength. The results demonstrate the effectiveness of the proposed approach compared to individual models, with significant improvements observed through ensemble learning. This study contributes to the field of medical diagnosis by providing an accurate framework for auto-brain tumor classification.
Software-Defined Networking (SDN), despite enabling centralized control and dynamic programmability, exposes critical security vulnerabilities particularly to Distributed Denial-of-Service (DDoS) threats targeting centralized controllers. This review synthesizes recent detection methods, including entropy-driven statistical models, machine learning-based classifiers, and hybrid techniques integrating both approaches. Entropy-based methods are computationally lightweight but often yield high incorrect detections during peak traffic bursts. Pure ML approaches, while highly accurate, struggle with hardware demands incompatible with legacy SDN infrastructure. Hybrid models significantly improve detection robustness; however, they face practical implementation hurdles related to complexity and scalability. While pure ML approaches excel in deep feature extraction, their substantial hardware demands often surpass what most real-world SDN environments can accommodate.
A Decade in Computational Quranic Studies (2016–2025): A Systematic Survey of the Evolution from Statistical Methods to Large Language Models
The intersection of artificial intelligence and sacred scripture represents a critical yet underexplored frontier in the digital humanities. This paper presents the first decade-spanning, systematic survey of computational Qur’anic studies (2016–2025), tracing the field’s evolution from fragmented, ontology-based prototypes to a coherent, methodologically mature research discipline. Through a rigorous, multi-phase systematic review of 112 peer-reviewed studies, we map a transformative trajectory across three eras: a Foundational Era (2016–2019) focused on knowledge representation; a Transformer Turn (2020–2023) driven by community benchmarks and Arabic transformer models; and an Acceleration Era (2024–2025) marked by the integration of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). Our longitudinal analysis uncovers a clear paradigm shift—from rule-based and statistical methods toward deep architectures explicitly engineered for ethical and theological fidelity. While remarkable advances have been achieved in Qur’anic Question Answering, Verse Authentication, and Recitation Analysis, the field still faces major gaps in multilingual applications, computational modeling of canonical recitation traditions (Qira¯’a¯t), and the deep integration of classical tafs¯ır scholarship. By introducing a structured taxonomy, a diachronic synthesis of research trends, and a strategic roadmap for the next decade, this survey reframes computational Qur’anic studies as both a case study and a catalyst for innovation in responsible, explainable, and theologically grounded AI.
A Comprehensive Review of Recent Advances, Architectures, Applications, Open Challenges, and Future Research Directions in Internet of Things
Recently, the Internet of Things (IoT) has gained significant popularity and has become a fundamental part of our world. Nowadays, IoT applications are more frequent than we think; the number of IoT devices is exponentially increasing. Many significant studies and research investigations were introduced to improve technology using IoT. However, for researchers who have a lack of holistic technical knowledge and recent advances of IoT, numerous topics and issues related to advances of IoT must be addressed from a before IoT can fully realize its potential, such as IoT architecture, components including hardware, operating systems (OSs), communication technologies, protocols, and applications. This paper conducts a holistic review of recent advances, visions, evolution, architectures, Components (hardware, middleware, and OSs), and applications of IoT. In addition, the paper investigates the recent challenges, open issues, and future research of IoT technologies. This paper assists researchers in understanding the key advances with a technical depth of the Internet of Things and the recent applications in the real world. The paper identifies IoT priority challenges and open issues, providing a guide for those leading IoT initiatives and revealing opportunities for future IoT research.
A Roadmap for Cloud Computing Migration in Yemeni Universities Using the ROCCA Model
This paper explores the implementation of cloud computing in Yemeni universities, leveraging insights from the Roadmap for Cloud Computing Adoption (ROCCA) model to address the unique needs of academic institutions. Cloud computing offers significant benefits, including scalability, cost efficiency, enhanced collaboration, and improved access to resources, which are essential for supporting research, teaching, and administrative functions. However, the migration to cloud computing presents challenges such as data security, regulatory compliance, and managing diverse workloads. To address these complexities, this paper proposes a tailored framework for cloud computing migration, spanning the entire lifecycle from analysis and design to adoption, migration, and management. The findings underscore that a well-planned and executed cloud computing strategy can enhance institutional flexibility, security, and operational efficiency, enabling higher education institutions to fully harness the transformative potential of cloud technologies while mitigating associated risks. This framework provides actionable guidelines and best practices to support academic institutions in achieving a successful and sustainable transition to cloud-based systems.
Copyright (c) 2025 The copyright is transferred to the University of Science and Technology, Sana’a, Yemen. https://creativecommons.org/licenses/by/4.0
Analyzing the Effect of Business Intelligence and Analytics on Organization Performance from Dynamic Capabilities Perspective in Yemeni Private
In developing countries, the role of business intelligence and analytics (BI&A) in enhancing organizational performance remains underexplored, particularly in the higher education sector. Therefore, this study aimed to analyze the effects of BI&A on organizational performance through dynamic capabilities and innovation in Yemeni private universities. This study proposed a conceptual model comprising three independent variables (IT infrastructure, BI&A staff experience, and top management support), two mediating variables (dynamic capabilities and innovation), and one dependent variable (organizational performance). Data were collected through a questionnaire that included 269 academic and administrative employees in five private universities (University of Science and Technology, Queen Arwa University, Al-Nasser University, Al-Razi University, and Al-Rasheed University). Data were analyzed using regression analysis, correlation analysis, and factor analysis. The results revealed that BI&A staff experience and top management support significantly influence organizational performance indirectly through dynamic capabilities and innovation. However, IT infrastructure showed no significant effect on performance. The findings suggest university leaders should strengthen BI&A-related capabilities to improve organizational performance through innovation and dynamic capabilities.
Performance of Granular Volcanic Ash-Cement-Fine Soil Mixture for Sub-Base Coarse of Road Pavement in Yemen
Granular Volcanic Ash (GVA) is a material of volcanic activity characterized by a rough surface, low specific gravity, non-plasticity particles with poor gradation, and high porosity because of its mineral structure. This study aimed to evaluate the performance of GVA-cement-fine soil mixtures as a sub-base material for flexible pavement in Yemen. GVA was blended with fine soil at 0%, 10%, 20%, and 30% by dry weight of GVA to improve gradation and reduce the required cement. The mixtures were stabilized with 2%, 5%, and 8% cement by dry weight of GVA. Performance was assessed through compaction characteristics, unconfined compressive strength (UCS), indirect tensile strength (ITS), wetting–drying durability, and ultrasonic pulse velocity (UPV) on samples cured for 7 and 28 days. The results revealed that the applied compaction energy reduced the fineness modules of the coarse GVA by 23%. Increases in cement content and curing time produced higher UCS, ITS, and UPV values. The GVA-cement-fine soil mixture met the strength and durability requirements for a sub-base for medium-traffic roads when GVA contained 20% fine soil and was stabilized with 5% cement.
Invasive and Non-Invasive Rapid Detection of Malaria Using Magneto-Optical Technique
Due to the widespread presence of malaria in our country and the increasing number of deaths caused by it, especially in remote areas, along with the challenges of laboratory tests that require time and incur high costs, we have developed a device for detecting malaria in the body. This device relies on the detection of hemozoin particles through a strong magnetic field, taking advantage of the nature of hemozoin particles formed in the blood. The magnetic field is applied in two scenarios: the first case involves directing infrared rays at the sample or finger in the absence of a magnetic field, and the second case involves the presence of a magnetic field. Subsequently, the results are transmitted, and the difference between the two cases is calculated. This device has the capability to scan for malaria in short time, in any environment and anywhere. It is user-friendly, making it accessible to anyone. This device represents the first steps toward finally eliminating this deadly disease through early and rapid detection.
Assessment of University Students' Awareness Level of War’s Environmental Effects and Other Environmental Issues: A Case Study at the University of Science and Technology, Sana’a, Yemen
Drinking water pollution, climate change, soil pollution, resource depletion and other environmental issues are serious concerns worldwide. Many countries implement policies and educational programs to enhance environmental awareness in society aiming to achieve environmental sustainability. Developing countries, including Yemen, face significant challenges in raising environmental awareness, and ongoing wars contributed to political instability, economic hardships, weak enforcement of environmental regulations, and limited educational programs causing environmental concerns to be frequently overlooked. The environmental effects of the ongoing war in Yemen are a major concern. Assessing individual’s knowledge of environmental issues possess regarding the environment is essential for establishing the sustainability of a community. This will foster a robust national environmental movement aimed at conserving the environment through the resolution of environmental issues. The present study intends to assess the students’ awareness level toward national environmental issues including “environmental impacts of wars in Yemen” and global environmental issues. The study was conducted among undergraduate and postgraduate students of the University of Science and Technology (USTY), Sana’a, Yemen. The survey covered 407 students from 7 faculties having 30 undergraduate programs and 10 postgraduate programs. The questionnaire consisting of 25 questions to measure the students’ knowledge and awareness level of national and global environmental issues. The study reveals that, around 42.71% of students being aware about national environmental issues while only 29.70% for global environmental issues. The study findings expose that the students' mean awareness level regarding national and global environmental issues falls within level 3, classified as, ‘limited awareness’ indicating that students may be aware of the problem but not aware of its causes and effects. The students’ average awareness level toward national environmental issues are higher than that in global environmental issues. The students’ awareness level for most of the national environmental issue including ‘environmental effects of war’ falls within level 4, classified as ‘moderated awareness’ indicating that students may be aware of the problem and its causes but not aware of its effects while, awareness of global environmental issue varies, with an average fall within level 3, classified as, ‘limited awareness’. On the other hand, female shows higher awareness than male and the students from the Faculty of Medicine shows highest awareness, followed by those from Engineering. As for the academic level, third year students exhibit the highest awareness, followed by second year student. In terms of degree level, postgraduate students show highest awareness than undergraduate students. The results of the study are consistent with related studies pertaining to environmental awareness in Yemen and other developing countries. These findings highlight the necessity of improving environmental education and awareness programs at universities, where environmental understanding empowers students to respond to global environmental challenges and participate in sustainable efforts.
The Impact of Using Social Media in Learning on the Academic Performance of Yemeni University Students
Currently, social media is very popular among students and has a great impact on academic performance. However, there remains a significant scarcity of research focused on the impact of social media on the academic performance of the students in Yemen universities. Therefore, the aim of this study is to address this issue by investigating the impact of social media on the academic performance of students in Yemeni universities. A descriptive analytical method was used. This study developed a model using the Technology Acceptance Model (TAM) and constructivist theory. The model included six independent variables representing interactions for learning, participation in learning, perceived interest, ease of use, time spent, IT infrastructure, and one dependent variable, academic performance. IT infrastructure is included in the study model and is an important variable, but it has been overlooked in previous studies. This study applied a quantitative method and analysis through surveying 382 university students selected from the University of Science and Technology and Sana'a University. The data were analyzed via regression analysis. The results of the study reveal a statistically significant positive impact of using social media on students’ academic performance. The results show there are a positive relationship between all independent variables in the model namely, interaction for education, participation for education, perceived usefulness, ease of use, time spent, and IT infrastructure and the dependent variable which is academic performance. Based on the findings, the study introduced recommendations for the respective stakeholders in Yemeni universities to leverage social media to foster academic performance of the students through increasing interaction for education, expanding participation of students in education, highlighting perceived benefits of social media for students, ensuring ease of use, managing time spent on social media, and enhancing IT Infrastructure.
Copyright (c) 2025 University of Science and Technology Journal for Engineering and Technology https://creativecommons.org/licenses/by/4.0
Comprehensive Survey of Lightweight Ciphers for Resource-Constrained IoT Devices
The rapid growth of IoT devices has highlighted the need for effective security solutions suitable for resource-constrained environments. Since traditional cryptography methods are often computationally expensive, this has resulted in the creation of lightweight cryptography (LWC), which aims to develop efficient ciphers that balance security, performance, and resource efficiency. This survey paper explores lightweight cryptographic algorithms, mainly hardware-based block ciphers, by analyzing 43 widely used ciphers based on key metrics in hardware implementation such as throughput, efficiency, energy consumption, and hardware area. These metrics are critical for evaluating cryptographic solutions for IoT devices with constrained resources. The study identifies trade-offs between security, performance, and resource efficiency, with some ciphers performing well in high-speed applications and others optimized for low energy and minimal hardware use. By providing a comparative analysis, this work aims to assist researchers and developers in selecting suitable cryptographic solutions, contributing to the advancement of IoT security and encouraging further exploration in this important area.
Adaptive Burst Assembly with Dynamic Ratio Control for Improved QOS and Fairness in Optical Burst Switching Networks
Optical Burst Switching (OBS) is a promising technology for next-generation Internet backbones. Ensuring Quality of Service (QoS) for real-time traffic within OBS networks while maintaining fairness for all traffic classes remains a significant challenge. Existing composite burst assembly schemes often rely on fixed ratios of high-priority traffic, which are often suboptimal for dynamically varying network conditions leading to increased packet loss, increased latency, and unfairness to lower-priority traffic. This paper addresses these limitations by introducing an enhanced Adaptive Burst Assembly (ABA) scheme. The ABA scheme builds upon established techniques, such as burst segmentation, to dynamically adjust the proportion of high-priority traffic within bursts. The key improvement is the addition of a dynamic ratio adjustment mechanism based on real-time network traffic load measurements. Simulation results demonstrate that the ABA scheme outperforms traditional fixed-ratio methods in reducing high-priority traffic packet loss. While this work builds on well-established concepts in OBS networks, its unique contribution lies in the adaptive nature of the burst assembly process and its focus on balancing both performance and fairness.
A Framework of Business Intelligence Systems Effect on Decision-Making Quality in Higher Education Institutions
The rapid change in the universities environment has increased the need for business intelligence systems (BIS) to leverage the data generated by the educational process. BI tools facilitate decision-making by processing information and converting it into meaningful knowledge. However, the effect of these systems on the decision-making quality, especially in the education sector, has not been verified. This study aims to develop a theoretical model to explore factors of BI that affect decision-making quality in higher education institutions in Yemen. Five independent variables were proposed: data quality, BI scope, BI users, BI management, and BI capabilities. BI capabilities were included as a new variable Based on stakeholder interviews. Data were collected using a survey of 128 decision-makers in some Yemeni universities and analyzed using regression analysis. The results showed that BISs have a significant positive effect on the decision-making quality in higher education institutions at (R2 = .513), supporting all hypotheses. Also, the results indicated that using BIS in educational institutions in Yemen is still in its early stages. Moreover, BI management had the highest positive effect, followed by BI scope, data quality, BI users, and BI capabilities, which confirms a positive relationship between BI aspects and decision-making quality in higher education.
An Adaptive Framework for Risk Management in Agile Methodology
Software companies face numerous risks during the software development process, particularly when using Agile methodologies due to their dynamic nature. This dynamism makes it challenging for development teams to anticipate and effectively manage potential risks. The Agile approach's focus on speed sometimes impedes a comprehensive risk assessment, making it challenging to prioritize and address risks effectively. Ignoring these risks during software development can significantly impact product quality and customer satisfaction, potentially causing severe damage to both companies and clients. In this paper, an adaptive framework for risk management in an agile method for software development has been proposed. In general, the extent of risk management application in software companies in Sana'a that use the agile method in developing software was surveyed, identifying the risks likely to occur and their impact on the project, and then proposing a risk management framework that helps in reducing risks. Through the study, it was shown that the proposed framework is important and effective for risk management in the agile methodology so it obtained a rate of 69.6% from the perspective of local software companies.
A Practical Study to Enhance Pressure Signal Quality in Mechanical Ventilators Using Moving Average Filtration: A Comparative Study
Undesirable noise and interference present a substantial obstacle in the process of obtaining biomedical signals for analysis and diagnosis. It is necessary to reduce the noise and enhance signal quality for many designs of medical devices such as Mechanical Ventilators (MV), patient monitors and overall biosignal processing. To contribute for addressing this problem, and for medical applications such as MV which are used for critical diseases such as pneumonia, COVID 19 etc. This paper, conducted comparative study to evaluate the performance of a 3-point Moving Average Filter (MAF) and a 5-point MAF in order to reducing noise and improving signal quality in MVs which are used in medical applications. MATLAB was utilized to perform filter approximation, realization and analysis. LabVIEW was employed for pressure signal data acquisition, implementation, and Signal-to-Noise Ratio (SNR) calculation. Experimental data, which needed for filters implementation, were obtained by running a MV connected to an artificial lung and a reference device which is used to measure pressure signal. In general, 3 point presented better SNR against 5 points MAF for pressure signal required in MVs. This approach can potentially enhance healthcare quality by providing better quality of biomedical signals which are used in medical devices.
Copyright (c) 2024 University of Science and Technology Journal for Engineering and Technology
Cement Kiln Dust as Substitute Fillers for Hot Mix Asphalt
To reduce construction costs, eliminate environmental issues, and protect natural resources, waste and by-product materials are frequently substituted for raw components in asphalt mixtures. This study investigates the feasibility of employing cement kiln dust (CKD), which is abundantly available in various regions of Yemen, as substitute hot mix asphalt filler (HMA) for conventional fillers. A traditional filler, basalt filler (BF), was partially and totally replaced at different percentages of CKD with 25%, 50%, 75%, and 100% by weight of fillers. The evaluation of the planned HMA was done using conventional mechanical and volumetric characteristics. A total of 15 bituminous concrete mix specimens with bitumen content of 4%, 4.5%, 5%, 5.5%, and 6% were created, and the optimum asphalt content was 5.24 %. The impacts of four different (CKD) samples with filler contents of 25%, 50%, 75%, and 100% by weight were compared with respect to bituminous concrete performance. The outcomes of the experiment demonstrated that CKD may substitute 75% of the BF at a bitumen content of 5.24%, 13.76 KN Marshall stability value, 4.02% air voids, 75 % VFB, 2.370 g/cm3 bulk density and 2.57 mm flow. Therefore, incorporating CKD as fillers in HMA is a sustainable solution that enhances performance, durability, and environmental benefits in road asphalt construction.
Authentication Techniques in 5G Network Slicing Security: A Survey
Emerging network slicing technology is a key feature of 5G cellular networks. Network slice and cloud computing provide promising solutions in 5G architecture. Network Slicing Security (NSS) is also important in 5G research. The emerging environment is a fertile breeding ground for the attacker. This study discusses authentication techniques in fifth-generation networks, as the authentication process is the first wall of defense against various network attacks. Meanwhile, techniques and algorithms are important in achieving confidentiality, integrity, and availability while maintaining speed and accuracy. The diversity and multiplicity of devices, in addition to the movement between slices and operators, make the authentication process extremely important. This article presents and explains the main issues related to network segment threats and attacks, highlighting the authentication techniques used in NS. The authentication process mainly focuses on the use of encryption and digital signature technology, either implicitly within the devices or directly when connecting to the network.
Bismuth Improvements on the Mechanical Performance of an As-Cast Eutectic Sn-Cu Alloy
The eutectic Sn-Cu alloy considered one of the potential alternatives to the toxic Sn-Pb solder alloys. This work aims to improve the mechanical performance of the eutectic Sn-Cu alloy in terms of rupture time and creep properties through studying the effects of bismuth (Bi) and silver (Ag) contents with x = 0.3 and 0.5 wt.% for each on the mechanical properties of as-cast eutectic Sn-Cu alloy. Ternary as-cast Sn-Cu-X (X= Bi or Ag) alloys were investigated using x-ray diffractions (XRD) and Creep testing machine. The results revealed that the 0.3 and 0.5 wt.% of Bi additions to the as-cast eutectic Sn-Cu alloy do not promote the Cu6Sn5 IMC formation but just shifted it from 102 to the 202 orientations. The above-mentioned Bi additions have refined the β-Sn particle size and enlarged Cu6Sn5 IMC, thus reduced the lattice distortion that is directly enhanced the mechanical performance and reliability for these as-cast alloys through the tensile tests with different loads at room temperature (RT). Adding 0.3 and 0.5 wt.% of Bi to the as-cast eutectic alloy formed other IMC (Ag3Sn) alongside the Cu6Sn5 phase which is mismatched with it due to their different crystal structures (Ag3Sn (orthorhombic) and Cu6Sn5 (Hex)). For that, the structural stability decreased, which leads to low resistance for the external forces and low mechanical reliability. The mechanical improvements (high rupture time (5498.85 s), low strain rate, and stress exponent (9.48)) that have been reported with the 0.5 wt.% of Bi addition to the as-cast eutectic alloy which is strongly related to its high structural stability compared to that for the other additions. From the mechanical point of view, the Sn-0.7Cu-0.5Bi alloy is recommended to be the most mechanical reliable alloy for the large-scale production and processing soldering and electronic assembly.
A Novel Method for Designing Electronic Logic Circuits
This scientific paper presents a novel method for designing single and multi-output electronic logic circuits. The produced circuit consists of two parts. The first part consists of (n-1) XOR gates, where "n" is the number of input signals to the logic circuits. This part is called the linear part of the circuit. The second part is designed by any method used in designing logic circuits. This part called the non-linear part of the circuit. The suggested method can be programmed by any high level programming language to be used on any digital computer especially with the circuits which have a large number of input signals.
Comprehensive Survey of Image Steganography Systems based on FPGA Implementation
Steganography is the art of concealed communication. The basic idea of steganography is to hide secret data inside a cover media in an undetectable manner. Cover media and Secret data can be any popular digital media such as image, video, audio, or text. Various types of image steganography methods have been proposed according to the cover image domain, i.e. spatial domain and transform domain. The spatial domain methods are easy and simple while the transform domain methods are more complex. However, the transform domain methods are more robust against image processing operations. Besides, they are more secure and less detectable in an unsecured channel. The recent steganography methods are based on sophisticated algorithms that include several computational time-consuming tasks, and hence they are unable to embed and extract the hidden data in real-time. Therefore, the trend is to implement the steganography methods in the hardware to speed up their processing time and so improves the efficacy of steganography techniques. FPGA is used in various fields in the modern era due to lower development cost, flexibility, and reconfigurability. Most of the published steganography techniques carried out on FPGA are based on the spatial domain. In this paper, it has comprehensively studied and reviewed various existing implementations of image steganography on FPGAs. This includes studying their general operations, requirements, and performance evaluations. This review would assist researchers in finding the research gaps in FPGA implementation of steganography methods for real-time applications.
Degree-Based Topological Indices of the Benzenoid Circumcoronene Series
This paper deals with some types of topological indices called valency-based indices or degree-Based Indices. Specifically, Multiplicative Forgotten, Multiplicative Yemen, modified Forgotten, modified Yemen, generalized modified first Zagreb, generalized modified sum connectivity, and generalized modified product connectivity indices of the benzenoid circumcoronene series are computed. Moreover, the formulas of polynomials for all these topological indices were derived.
Effect of Using Fine Volcanic Ash Instead of Crushed Basalt Filler in Hot Mix Asphalt
Numerous studies over the years have demonstrated the significance and impact of filler in influencing the physical and mechanical properties of Hot Mix Asphalts (HMAs). To overcome such issues, as environmentally friendly alternatives, several different materials for construction have been proposed. This led to an investigation into the potential use of fine volcanic ash (FVA) as a hot mix asphalt filler alternative. In order to prepare bituminous concrete mix sample with conventional basalt filler (BF) as control mix. The Marshall Mix design approach was used to calculate the effective bitumen content. A total of 15 bituminous concrete mix specimens with bitumen content of 4%, 4.5%, 5%, 5.5%, and 6% were created, and the optimum asphalt content was 5.24 %. The impacts of five different (FVA) samples with filler contents of 15%, 30%, 45%, and 60% by weight were compared with respect to bituminous concrete performance. The Marshall stability of a total of 30 samples with varying amounts of (FVA) were investigated. The outcomes were compared with a conventional bituminous concrete mixture. The results showed that fine volcanic ash may substitute 30% of the basalt filler at a bitumen content of 5.24%, 13.84 KN Marshall stability value, 4.0% air voids, 74.77% VFB, 2.380 g/cm3 bulk density and 3.54 mm flow. Therefore, the combination of 30% Fine Volcanic Ash by weight of Basalt Filler satisfies the ASTM Specifications, while the remaining VA content satisfies the basic requirements of the ASTM Specifications.
Healthy Placemaking in the Public Space in Sana'a City: A Case Study (The Main Square of Qaa Al-Olfi)
The public space with its components (streets and public parks) occupied an important place in the history of urban design and community health, as they are the determinants and resilient elements of health within cities. Modern concepts and design methods have been developed in response to urban health pandemics, including the creation of a healthy placemaking that achieves the health of the population within the urban context; Due to the lack of applications by principles healthy placemaking in streets and public parks in Sanaa, it has negatively impacted the daily health activities of residents, The research problem is that Sanaa's streets and public parks do not have any urban design to promote the health of Yemenis in the face of the pandemics; he study object is to create guided design models for the streets and public park in the study area, which simulate the applications of healthy placemaking to help planners provide solutions to face the spread of diseases and pandemics in urban areas, The importance of this research comes in the form of the first Yemeni urban study that deals exclusively with the issue of healthy placemaking in the streets and public parks during of urban health pandemics. The research followed the descriptive inductive approach in studying the theoretical concepts and the practical approach in creating design models the applications of the health placemaking during health pandemics on the study area.
Natural Radionuclides Concentrations and Associated Radiation Hazard of Some Building Rocks Used in Taiz City, Yemen
Building materials comprise a diverse range of natural rocks that contain varying mineral components including radionuclides. Gamma spectrometry-based high-purity Germanium detectors were utilized to measure the activity concentrations of natural radionuclides: Radium-226 (226Ra), Thorium-232 (232Th), and Potassium-40 (40K) in various building rock samples found within and surrounding Taiz city. The activity concentrations of 226Ra, 232Th, and 40K vary from 27.79 ± 0.77 to 234.49 ± 3.13 Bq.kg-1, 25.82 ± 0.40 to 415.31 ± 2.47 Bq.kg-1, and 457.91±2.61 to 1139.56 ± 5.43 Bq.kg-1 with overall average value of 71.55 Bq.kg-1, 93.87 Bq.kg-1, 966.88 Bq.kg-1 respectively, these values were higher than the permissible thresholds. Furthermore, several radiation hazard indices were estimated including the radium equivalent (Raeq), the external hazard index (Hex), the internal hazard index (Hin), the gamma level index (Iɤ), the dose rate(Dɤ), the annual effective dose equivalent (AEDE), the excess lifetime cancer risk (ELCR), and the annual gonadal dose equivalent (AGDE). The findings illustrated that Basalt rocks have the minimum values of radiation hazard indices while the Himatite rocks have the maximum values of radiation hazard. The average values of radiation risks for most of building rocks fall below the recommended limits for safety. Based on the Radiation hazard indices of building rock samples, it can be concluded that with the exception of hematite rocks, all the examined rocks are considered safe for use in construction materials and pose non-significant radiation risks. The awareness about natural radioactivity levels of building rocks is critical for planning and performing strategies in radiation safety of buildings.
Low-Cost Automated Storage and Retrieval System for Chemicals Warehouses and Central Refrigerators
The Automated Storage and Retrieval Systems are known as ASRSs which is moved by a mechanical system and controlled by electronical system. The system has introduced many advantages in the production, storage, distribution, and customer services. Many of the proposed systems use high techniques, complex programs, and an intractable interface, and besides their complexity in programming and using, they still at a high cost. The paper proposes a simple and low-cost Automated Storage and Retrieval System using Arduino boards to control the whole system. This work has been studied on specific sites, which are Chemicals Warehouses and Central Refrigerators. The system has been designed and implemented based on two components, Hardware and Software. The proposed system determines the types of goods, pick them up and put them on the suitable shelve depends on its type. The system was designed with a database to store information and an executable file installed in computers to follow up on entered quantities and to order quantities when needed.
Effect of Replacing Conventional Base Materials with Granular Volcanic Ash on Engineering Properties
Granular Volcanic Ash (GVA) is a material of volcanic activity; it has a rough surface, a low specific gravity, and a high porosity because of the structures of the minerals in it. The purpose of this study was to find a way to utilize this waste material, which is widely distributed across Yemen, by using GVA for the placement of conventional coarse aggregate (basalt aggregate) while constructing roads. In this study, Red and Black GVA materials were combined with conventional coarse aggregate for use in the construction of pavement. Base coarse materials were blended with GVA aggregate and examined for their engineering characteristics in an experimental study. Conventional coarse aggregate was partially replaced by five replacement levels from GVA, corresponding to 10%, 20%, 30%, 40%, and 50% of the dry aggregate's total weight, were applied. As a control, a sample with no volcanic ash had been used. According to the results of experiment tests includes: density, California bearing ratio (CBR), abrasion percentage, and permeability test, it is possible to replace some of the basalt aggregates with GVA. Results showed that the engineering properties of base coarse materials specifications for CBR, and abrasion percentage were satisfied for volcanic ash percentages up to 20%.
Copyright (c) 2023 University of Science and Technology Journal for Engineering and Technology
A Comprehensive Analysis of the Oxygen Inhalation Lounges
Oxygen lounges have become increasingly popular in recent years as a way to boost energy and alleviate stress. The concept behind oxygen lounges is based on the idea that extra oxygen can provide numerous health benefits, such as increasing energy, improving mental clarity, and reducing stress and anxiety. However, the scientific evidence to support these claims is limited, and there are potential risks associated with their use, such as oxygen toxicity. This article explores the history and science behind oxygen lounges, their potential health benefits, as well as any potential risks associated with their use. Additionally, it discusses the regulation of oxygen lounges in Yemen especially Sana’a that has no establishments of what sort, where there are currently no specific regulations or guidelines for their operation, despite that Sana’a is famous of lacking of oxygen due to the geographical nature of the city, as the city is located on mountain heights. While oxygen lounges may provide some potential health benefits, the scientific evidence on their effectiveness is limited, and customers should approach them with caution, particularly if they have any underlying medical conditions.
Developing a Pathogen Sterilization Robot based on Ultraviolet Radiation
The role of robots for disinfection and sterilize purposes is increasing with time, due to the challenge of the global Covid-19 pandemic, which led to a shortage in the availability of traditional surface disinfectants due to their extensive use also because of the poor efficiency in sterilizing using the normal methods of cleaning. All that considered and after we have studied the effect of ultraviolet radiation on viruses, we proposed to develop a pathogen sterilization robot based on Ultraviolet radiation. This project is designed to develop a sterilization robot using Hector_SLAM technology for navigation. The aim of our work is to contribute to combating the spread of Covid-19 in hospitals, public transportation, airlines and any closed areas and to develop a new method for sterilizing. The sterilization robot sterilizes pathogens and viruses in rooms. The robot move around autonomously and it is equipment with ultraviolet rays, and it turns off automatically when humans are around to keep them safe due to the danger of radiation.
Using Three-Dimensional Modeling Techniques in Digital Preservation of Urban Plans for the Old Walled City of Shibam Hadramawt
Historic cities have great importance in our time because they represent a cultural, social and urban wealth for societies, where historical cities gain their importance through the values ​​and principles that are reflected on the reality of the city, its personality, its social and topographic components, its planning and urban form. The traditional methods and paths of preservation have taken long periods of time and have been affected by the political and economic situation of the country which until our current situation, still living a period of instability. The study object is to create a vision for a preservation digital platform of the historical city of Shibam, Hadramout using 3D modeling techniques. The study importance is that using 3D modeling techniques and a set of metadata associated with each graphic object of historical urban elements would help in digital preservation. The research followed the descriptive inductive approach in studying the theoretical concepts and the practical approach in creating the digital platform for the three-dimensional modeling technologies.