bluuebunny/crossref_metadata_2025 huggingface dataset:
Information Literacy Instructions, Digital Resource Integration, and Students’ Academic Success
Authors: Canaria Mary Joy C , Yango Antonio R. , Bautista Susana C.
Published: August 2024

In the contemporary higher education landscape, the fusion of information literacy education and seamless integration of digital resources is imperative for fostering students' academic success amidst a surge in information flow and technological progression. Educational institutions, including the San Pedro College of Business Administration (SPCBA) in the Philippines, strive to synchronize with the evolving demands of the 21st century by prioritizing the roles of information literacy instruction and digital resource integration in shaping students' academic trajectories. This study aimed to elucidate the intricate relationship between information literacy instruction, digital resource integration, and academic success at SPCBA. Data collected from 180 college students through survey questionnaires revealed a high level effectiveness of information literacy, robust digital resource integration, and significant academic success. Correlation analyses uncovered moderate associations between information literacy instruction and digital resource integration, as well as between information literacy instruction and academic success. Additionally, digital resource integration exhibited a significant correlation with academic success. Regression analysis further highlighted that information literacy instruction significantly predicts academic success, especially when combined with digital resource integration. In light of these findings, recommendations were proposed to enhance information literacy programs, integrate digital resources into curricula, foster collaboration between faculty and librarians, and conduct regular assessments for improvement. This study contributes to the literature on information literacy, digital resource integration, and academic success, providing insights for optimizing student learning outcomes in the digital age. Further research is encouraged to explore the nuanced dynamics of this relationship and develop targeted interventions for educational enhancement.
Correlation of Glycated Albumin With Glycated Hemoglobin as a Marker for Assessment of Beta Cell Function in Type 2 Diabetes
Authors: Kishwar Lakhiar  , Aamir Hussain  , Yar Muhammad Nizamani  , Hanozia Shah  , Hafsa Usman Shaikh  , Hira Saeed Khan
Published: August 2024

Objective: To evaluate a relationship between Glycated Albumin and Hba1c in comparison to Serum as predictor for Beta Cell Function in and type-2 diabetes population.
Methodology: A descriptive cross-sectional study was conducted among 163 diabetic patients, aged 30 to 70 years and both genders who presented at the Lumhs Civil/Jamshoro OPD and wards with diagnosis of Diabetes Mellitus for at least 6 months or more. A 5cc blood sample was collected from each participant using EDTA tubes for the analysis of glycated albumin and glycated hemoglobin. All data collection procedures were conducted with utmost regard for participant privacy and confidentiality using study proforma and spss version 26 was used for analysis.
Result: The mean age of the participants was 62.06±11.03 years. Out of 163 patients 50.3% were male and 49.6% were female. Correlation analyses of the findings had revealed that a significant correlations p<0.001was present between HbA1C levels and glycated hemoglobin levels whereas a significant relation was also found between Body Mass Index and HbA1C and glycated hemoglobin levels.
Conclusion: The study concludes that both glycated albumin were recorded high among diagnosed type 2 diabetic mellitus patients, with a strong correlation between HbA1C levels and glycated hemoglobin levels whereas a significant relation was also found between Body Mass Index and HbA1C and glycated hemoglobin levels.
INSERÇÃO MUNDIAL E COMPETITIVIDADE DA AGRICULTURA BRASILEIRA.
Authors: Schneider Braun Mirian Beatriz , De Lima Jandir Ferrera , Cardoso Rubiane Daniele
Published: August 2024

O objetivo central desse trabalho é avaliar a inserção do Brasil no comércio internacional de produtos agrícolas, tendo como marco regulatório a Organização Mundial de Comércio – WTO; e a atuação da política comercial brasileira dentro desse contexto. Discute-se até que ponto a política comercial brasileira tem os efeitos desejados sobre o setor, uma vez que este é amplamente afetado pela regulação, ou mesmo ações do comércio (ou retaliações) que ocorrem no contexto internacional. Em princípio faz-se uma análise histórica da política comercial brasileira e seus efeitos sobre os fluxos de comércio de produtos agrícolas brasileiros. Na segunda parte, infere-se a situação atual das exportações e importações desses produtos, uma avaliação das medidas de política comercial, e seus efeitos sobre esses fluxos de comércio. Em termos internacionais, o que salta aos olhos é o fato de países considerados ricos destinarem vultuosas somas em apoio à agricultura, dados os seus efeitos distributivos sobre suas economias, enquanto o Brasil destina um esforço muito maior (e penoso) à indústria, concentradora de renda e sem a devida resposta em termos de inserção no mercado internacional, além da pífia atuação da política comercial brasileira na garantia de mercados para ambos os setores, principalmente para a agricultura.
CONSIDERAÇÕES A RESPEITO DAS ORIGENS, DOS ACONTECIMENTOS E DAS CONSEQUÊNCIAS DA CRISE ECONÔMICA MUNDIAL ATUAL
Authors: Rippel Ricardo , Rippel Valderice Cecília Limberger
Published: August 2024

O objetivo do artigo é discutir e apresentar considerações a respeito das origens, dos acontecimentos e das consequências que envolvem a crise econômica mundial atual. Evidencia-se que essa crise tem suas origens e seus desdobramentos no setor financeiro, e vem afetando praticamente toda a economia mundial. O impacto internacional gerado tem suas raízes na "bolha da Internet" de 2001. Ressalta-se que a crise foi de fato revelada ao mundo a partir do mês de fevereiro do ano de 2007, como sendo uma crise financeira, que acontecia no coração do sistema capitalista, ou seja, na economia norte-americana. Alerta-se que a crise era e é, até os dias de hoje, muito grave e, nas palavras de diversos economistas, a mais grave crise do sistema capitalista desde 1929, com possibilidades de transformar-se em sistêmica, entendida como uma interrupção da cadeia de pagamentos da economia global, interrupção que tende a atingir generalizadamente todos os setores econômicos mundiais. Assim, no presente estudo se apresentam, cronologicamente, os principais fatos que envolvem o surgimento, a eclosão e a expansão desta crise econômica mundial atual. Busca-se demonstrar os fatos que levaram a sua ocorrência, evidenciando como os acontecimentos se deram.
Uma análise da balança comercial agrícola brasileira a guisa de sua evolução histórica recente
Authors: Schneider Braun Mirian Beatriz
Published: August 2024

A evolução histórica da balança comercial agrícola do Brasil esteve diretamente ligada aos objetivos da política comercial brasileira que, por sua vez, foram resultantes da interação de fatores internos e externos. Uma sucessão de ciclos de exploração de produtos primários comandou a dinâmica agroindustrial no País até o século 20, e as balanças comerciais – pró-exportação – foram comandadas por produtos como o açúcar, café, borracha, entre outros. Com o modelo de substituição de importações (década de 30 em diante), que priorizou os setores industriais, a agricultura nacional foi relegada ao segundo plano, embora dela sempre fosse cobrada divisas. Mais recentemente, na década de 70, foram definidas políticas concretas de apoio à agricultura, promovendo sua modernização, mormente para produtos considerados tradeables. Assim, foi reformulada a base técnica do setor, traduzida na indução e difusão do uso de insumos modernos e de maquinaria agrícola, visando o aumento de produtividade dos fatores terra e trabalho. O escopo dessa política consistia em dar condições para o crescimento econômico, gerar divisas para sustentar a balança comercial e arrefecer o custo de vida - por meio da diminuição dos preços agrícolas. Sendo assim, o tipo de produto de origem agrícola, que passa a compor a pauta de exportações, já não é mais o produto primário apenas, mas sim, produtos com diferentes níveis de processamento da indústria. Na década de 80, à agricultura coube a tarefa mor de gerar superávits comerciais, a fim de equilibrar o balanço de pagamentos, agravado pela crise da dívida externa e pelos mal sucedidos planos de combate à inflação. Na década de 90, a abertura comercial veio eliminar a proteção de alguns segmentos agroindustriais e os produtores brasileiros foram forçados a se adaptarem ao novo ambiente competitivo. A implantação do real aprofundou a desproteção desse setor, via elevação dos juros e valorização do câmbio (na fase inicial do Plano). Não obstante, as exportações agrícolas brasileiras vêm aumentando, diante desse cenário, a busca crescente por technological capabilities. A balança comercial agrícola não é maior, principalmente, em função da proteção que os países desenvolvidos exercem no contexto do comércio internacional agrícola. A política comercial brasileira deve agir de forma clara na busca de acordos comerciais, que garantam maior inserção dos produtos brasileiros no mercado mundial, evitando os efeitos nocivos da proteção destinada às agriculturas daqueles países.
Development of a Novel Backup Fault Protection Algorithm for Low-Voltage DC Microgrids based on Local Measurements and Chi-square Statistics
Authors: Bui Duong Minh , Le Duy Phuc , Nguyen Hieu Minh
Published: August 2024

A direct-current microgrid (MG) can be susceptible to extremely high fault currents contributed by the output filter capacitors of power converters and can also face protection challenges because of the non-zero crossing of fault currents. In a Low-Voltage Direct Current (LVDC) MG, low-fault-tolerance converters such as boost converters and bidirectional converters mostly require a fast and adaptable fault protection scheme that can detect and clear quickly faults irrespective of a wide range of fault impedances in the system. Several current- and voltage-derivative-based protection methods with communication support have been developed to primarily protect DC MGs due to their high sensitivity and selectivity. Over-current and under-voltage-based protection schemes are mostly suggested as backup protections for the DC MGs. To accurately detect and rapidly clear the faults even in the case of communication failure from the primary protection, this paper proposes a novel backup fault protection scheme with high selectivity, adaptability, and scalability for islanded LVDC MGs based on local measurements along with Chi-square-distribution-based statistics. Specifically, this developed backup protection not only applies a cumulative summation methodology for the locally measured signals to extract derivative and integral characteristics of the current and voltage, but also uses the Chi-square-distribution-based statistics to consistently calculate tripping thresholds for the effective detection of different fault events in the LVDC MG, regardless of variable fault resistances and the communication-link damage. As a result, the proposed backup protection is capable of accurately detecting various DC faults to secondarily protect the source and load branches of the system within the expected time frame of a few milliseconds and has been validated through multiple staged fault tests from an off-grid and ungrounded 1kW and 48VDC MG testbed.
Performance Evaluation of Data Mining Techniques to Enhance the Reusability of Object-Oriented (O-O) Systems
Authors: Bisht Bharti , Gandhi Parul
Published: August 2024

The software industry is evolving at a rapid pace, making it necessary to optimize efforts and accelerate the software development process. Software can be reused to achieve quality and productivity goals. Reusability is a crucial measure that can be used to increase the overall level of software quality in less time and effort. To better understand the necessity of enhancing the software reusability of Object-Oriented (O-O) systems, this study employed a semi-automated approach to measure the values of class-level software metrics on an input dataset collected from the MAVEN repository. This paper explored several previous studies, data strategies, and tools to predict reusability in O-O software systems. This study compares various data mining techniques to identify the most suitable approach for enhancing the reusability of O-O software systems. The analysis was based on performance parameters such as precision, MSE, and accuracy rates. Due to its higher precision and lower MSE, the SOM technique is considered one of the top data mining approaches to increase the reusability of O-O software systems. However, the results show that the different levels of reusability in O-O software systems are not adequately addressed in current solutions.
Structural Behavior of Reinforced Concrete Flat Plates Strengthened by Horizontal Reinforcement
Authors: Ameen Ali N. , Al-Sherrawi Mohannad H.
Published: August 2024

Flat plate structures consist of a slab supported directly by columns without beams or drop panels, resulting in a thinner slab with more efficient use of space. Despite these advantages, a flat plate slab is subjected to brittle punching shear. Sudden collapse may occur when a column pushes a piece of concrete from the slab above it. This paper displays Finite Element Analysis (FEA) using ABAQUS/ CAE 2019 to simulate the punching shear impact on a flat plate strengthened with horizontal steel bars of varying number and diameter, located at the compressive side of the slab. A numerical model was constructed with 8-noded hexahedral 3D brick elements for concrete and 2-noded linear 2D beam elements for steel reinforcement. The model was adapted based on experimental data. A parametric analysis was conducted to evaluate the impact of placing horizontal steel bars at the compression side of the flat plate and changing the quantity and size of these bars on the slab's performance. The results illustrate that the shear capacity increases from 17.07% to 28.13% as the bar diameter increases and from 19.17% to 54.82% as the number of bars increases.
Raft Thickness Rational Design for Megatall Skyscrapers: Case Studies
Authors: Van Hoa Cao
Published: August 2024

The design process for tall buildings involves three main steps: Estimating roughly the sizes of foundation and superstructure components, verifying the determined sizes with full consideration of the interactions between soil, piles, raft, and superstructure to ensure the bearing capacity and deformation of all elements, and optimizing the design with parametric analysis. However, the thickness of the rafts in existing buildings appears to be very thick and varies to the point of confusion. It is noticeable that some buildings have a considerable height but a relatively small raft thickness and vice versa. To address this issue, a simplified graphical method is proposed to determine the raft thickness for the initial design phase. As megatall skyscrapers become increasingly common, a more comprehensive study of rafts is necessary. This article explores the process of designing and constructing rafts for tall and megatall skyscrapers. The study aims to validate and extend the graphical method and establish a basis for the raft thickness optimization process. The research shows that the number of floors strongly affects the thickness of the rafts. However, the elastic modulus is significantly influenced when the ratio of the raft thickness to the number of floors is less than 5% and vice versa.
Assessment of Wind Energy Potential for achieving Sustainable Development Goal 7 in the Rural Region of Jeje, Nigeria
Authors: Kassem Youssef , Camur Huseyin , Apreala Terry
Published: August 2024

The implementation of a decentralized energy system has the potential to improve the life quality of the people who live in remote rural areas with limited or nonexistent power sources. Renewable energy technologies can be very important in the production of power. The main purpose of this study is to assess Jeje, Nigeria's wind energy potential, using a reanalysis and analysis dataset. To this aim, data on wind speed at a height of 10 m were gathered from a variety of sources, including EAR5, EAR5 Ag, EAR5 Land, CFSR, and MERRA-2. The Weibull distribution function, commonly employed to evaluate wind energy potential, was utilized. A maximum wind power density value of 15.75 W/m2 was obtained when the MERRA-2 dataset was implemented. The results indicate that large-scale wind turbines are not a viable alternative in this area. Thus, the performance of six wind turbines, expressed by output power with a cut in speed ranging between 1 and 1.5 m/s, was investigated. The results demonstrated that the AWI-E1000T is the most efficient wind turbine under consideration. In addition, it has been shown that each considered turbine can be installed in this area based on the data acquired from the MERRA-2 and CFSR.
Blockchain-Inspired Lightweight Dynamic Encryption Schemes for a Secure Health Care Information Exchange System
Authors: Aruna Etikala , Sahayadhas Arun
Published: August 2024

The telemedicine sector has entered a new phase marked by the integration of Internet of Things (IoT) devices to identify and then send patient health data to medical terminals for additional diagnostic and therapeutic procedures. Today, patients can receive prompt and expert medical care at home in comfortable settings. Due to the unique nature of these services, it is essential to verify patient healthcare data, as it contains a greater amount of personal information that is vulnerable to privacy violations and data breaches. Blockchain technology has attracted interest in addressing security concerns due to its decentralized, immutable, shared, and distributed characteristics. This study proposes lightweight dynamic blockchain-enabled encryption schemes to secure physiological data during authentication and exchange processes. The proposed scheme introduces the logistic Advanced Encryption Scheme (AES) that combines chaotic logistic maps to secure the data in the blockchain network and mitigate different attacks. The model was deployed on the Ethereum blockchain and performance metrics, such as computation and transaction time, were calculated and compared with other current blockchain-inspired encryption models. Furthermore, the NIST test was conducted to prove the strength of the proposed scheme. The proposed model exhibits high security and a shorter transaction time (0.964 s) than other existing schemes. Finally, the proposed model generates high-dynamic keys that are suitable for defending against unpredictable attacks on blockchain.
Assessing Wear Coefficient and Predicting Surface Wear of Polymer Gears: A Practical Approach
Authors: Muratovic Enis , Muminovic Adil , Pervan Nedim , Delic Muamer , Muminovic Adis , Saric Isad
Published: August 2024

With the ever-increasing number of polymer materials and the current number of commercially available materials, the polymer gear design process, regarding the wear lifetime predictions, is a difficult task given that there are very limited data on wear coefficients that can be deployed to evaluate the wear behavior of polymer gears. This study focuses on the classic steel/polymer engagements that result in a wear-induced failure of polymer gears and proposes a simple methodology based on the employment of optical methods that can be used to assess the necessary wear coefficient. Polymer gear testing, performed on an open-loop test rig, along with VDI 2736 guidelines for polymer gear design, serves as a starting point for the detailed analysis of the wear process putting into service a digital microscope that leads to the evaluation of the wear coefficient. The same wear coefficient, as presented within the scope of this study, can be implemented in a rather simple wear prediction model, based on Archard’s wear formulation. The developed model is established on the iterative numerical procedure that accounts for the changes in tooth flank geometry due to wear and investigates the surface wear impact on the contact pressure distribution to completely describe the behavior of polymer gears in different stages of their lifetime. Although a simple one, the developed wear prediction model is sufficient for most engineering applications, as the model prediction and experimental data agree well with each other, and can be utilized to reduce the need to perform time-consuming testing.
Enhancing Enterprise Financial Fraud Detection Using Machine Learning
Authors: Ismail Mustafa Mohamed , Haq Mohd Anul
Published: August 2024

The aim of their research is to improve the detection of financial fraud in enterprises through the utilization of artificial intelligence (AI) methodologies. The framework employs machine learning algorithms and data analytics to accurately identify patterns, anomalies, and signs of fraudulent activity. They employed exploratory data analysis approaches to identify instances of missing values and imbalanced data. The selection of the Random Forest Classifier is based on its ability to consistently capture intricate patterns and efficiently tackle the problem of multicollinearity. The isolation forest approach yielded an accuracy of 99.7%, while the local outlier factor method achieved an accuracy of 99.8%. Similarly, the Random Forest algorithm demonstrated an accuracy of 99.9%. The objective of their study is to aid organizations in proactively identifying instances of fraud by utilizing artificial intelligence methodologies.
Effect of Magnetic Treatment on Seawater Determined by Quartz Crystal Microbalance: Mechanisms of Crystal Deposition
Authors: Alimi Fathi
Published: August 2024

This study investigated the effect of a magnetic field on the crystal deposition of treated seawater to determine the mechanism of calcium carbonate deposition on the quartz surface. Several samples of standard seawater (43 g/L) were circulated through a permanent magnetic field of 0.16 T at a fixed temperature, pH, and flow rate. Scaling experiments showed that magnetic treatment of seawater enhanced the precipitation of calcium carbonate and that two superposed phases were deposited. A first layer formed with crystals of aragonite covering the whole surface of the quartz, and then a second phase of calcite was deposited. In the untreated solutions, only homogeneous agglomerates of aragonite were deposited.
Improvement of Torque Control for an Assistant Electric Power Steering System using a Type-2 Fuzzy Logic Controller
Authors: Ha Vo Thanh
Published: August 2024

This article explains how a type 2 fuzzy logic controller can improve the torque of a 3-phase Permanent Magnet Synchronous Motor (PMSM) in an electric power steering system. The goal is to ensure effective electric power steering under various road conditions and speeds. The implementation of type-2 FLS involves fuzzification, inference, and output processing. Type-reduction methods are more advanced than type-1 defuzzification methods, handling more rule uncertainties. While computationally demanding, a simple type-reduction computation process is outlined for interval type-2 fuzzy sets. The type 2 fuzzy logic controller algorithm manages the PMSM motor using Field-Oriented Control (FOC), adjusting the motor voltage based on torque, speed, and steering angle sensor inputs. The study's results provide a solid basis for future research on designing and controlling electric power steering systems with precision and efficiency. This research sets the stage for improved electric power steering systems, contributing to the development of intelligent automotive technologies.
Finite Element Modeling for Flexible Pavement Behavior under Repeated Axle Load
Authors: Aljaleel Zainab M. , Yasoub Nahla , Atemim Yahya K. H.
Published: August 2024

Accurate assessment of flexible pavement behavior requires a computational model that is able to predict the permanent deformation of the pavement under heavy load and its response with different thicknesses. This study developed several realistic models using advanced Finite Element Analysis (FEA) techniques employing the ABAQUS/CAE finite element program. The model integrates measured tire pavement contact stresses, moving wheel loads, and the viscoelastic properties of the asphalt layer. The model undergoes fine-tuning through the utilization of implicit dynamic analysis and variance in thickness. The simulations demonstrate that the viscoelastic behavior is more susceptible to changes in thickness. Furthermore, variation in thicknesses showed different pavement and rut depth behavior. The thinner the thickness is, the less resistance is applied to loading pressure and when the number of load repetitions increases, the depth of the rut also increases, leading to permanent deformation and consolidation with each passage of a heavy vehicle.
Selection of Crankshaft Manufacturing Material by the PIV Method
Authors: Nguyen Hong Son , Hieu Tran Trung , Thang Nguyen Manh , Tan Huynh Nhu , Can Nguyen Tien , Thao Pham Thi , Bao Nguyen Chi
Published: August 2024

The type of material employed in crankshaft production has a great influence on the performance, durability, and product lifespan. There are many types of material that can be used to manufacture crankshafts, but choosing the best one is a complicated work. This study is carried out to select the best material type among four commonly deployed types, including 1080 steel, 18CrMo4 steel, 4130 steel, and S48C steel. Fifteen parameters (criteria) were chosen to describe each material. The weights of the criteria were determined by three methods, including the Mean weight method, the Entropy weight method, and the MEREC (Method based on the Removal Effects of Criteria) weight method. To rank the steel types, the PIV (Proximity Indexed Value) method was adopted, and it was demonstrated that the ranks did not depend on the weighting method followed. S48C is the best choice among the four types of steel generally utilized for crankshaft production.
A Kinetic and Morphological Study of Barite Precipitation Reaction in the Presence of Fe3+ and Mn2+ Ions
Authors: Mechi Lassaad
Published: August 2024

The precipitation mode of barium sulphate (BaSO4) in the presence of mineral additives plays an important role in many industrial processes. Therefore, in this paper, a study of the precipitation reaction of a saturated barium sulphate solution in the presence of metal ions Fe3+ and Mn2+, found in industrial waters and in the geochemical evolutions of paleoenvironments, is presented. XRD, conductivity, FTIR spectroscopy, and SEM were used to investigate the barite precipitation reaction in the presence of a known amount of Fe3+ and Mn2+ ions. Conductivity measurements showed that the presence of Fe3+ accelerated both induction and crystal growth stages. On the other hand, adding Mn2+ ions did not affect the kinetics of the precipitation reaction. Solid analysis showed that the barite lattice was doped with low levels of manganese.
Safeguarding Identities with GAN-based Face Anonymization
Authors: Al-Khasawneh Mahmoud Ahmad , Mahmoud Marwan
Published: August 2024

Effective anonymous facial registration techniques are critical to address privacy concerns arising from facial recognition technology. This study presents an intelligent anonymity platform that incorporates blockchain with advanced privacy and uses a CIAGAN-powered approach. This solution addresses the immediate need for privacy in facial recognition technology. The proposed system uses advanced techniques to anonymously generate highly realistic and effective facial images. The widespread use of facial recognition systems places greater emphasis on privacy concerns, emphasizing the need for strong enrollment mechanisms. The proposed system uses CIAGAN to address this challenge and generate facial images while preserving important attributes. Blockchain storage ensures that data integrity and security are maintained. The process begins with detailed image preprocessing steps to improve data quality and eliminate unwanted noise. CIAGAN can generate anonymous face images with important facial attributes to complicate the recognition of specific objects. A dataset of 202,599 facial images was used. Performance metrics such as PSNR and SSIM indicate image quality and uniformity. The PSNR obtained was 35.0516, indicating a unique image anonymization process.
Maximizing DRL-based Energy Efficiency in IRS-NOMA using a DDPG Algorithm for the Next Generation of Wireless Communications
Authors: Audah Kamil , Noordin Nor K. , Hussein Wala'a , Rasid Mod Fadlee B. A. , Sali Aduwati , Flah Aymen
Published: August 2024

Combining Intelligent Reflecting Surfaces (IRSs) with Non-Orthogonal Multiple Access (NOMA) effectively enhances communication. This study introduces a NOMA-assisted Downlink Transmission (DT) system, emphasizing Energy Efficiency (EE) optimization. EE, crucial in Wireless Communications (WCs), measures data transmission relative to energy consumption. This study focuses on a Deep Deterministic Policy Gradient (DDPG) algorithm that intelligently adjusts IRS phase-shift matrices and access point beamforming in NOMA DT. Beamforming directs signals to users for optimal strength and quality, while phase shift control enhances signal coverage and quality. Strategic IRS placement improves user signal transmissions. The simulation results demonstrate significantly improved EE compared to other algorithms, such as Deep Q Network (DQN) and Proximal Policy Optimization (PPO), showcasing the effectiveness of the combined IRS and NOMA approach in enhancing communication systems' EE.
Microscale Thermal Management: A Review of Nanofluid Applications in Microfluidic Channels
Authors: Samylingam Lingenthiran , Aslfattahi Navid , Kadirgama Kumaran , Ramasamy Devarajan , Sazali Norazlianie , Wan Harun Wan Sharuzi , Kuang Kok Chee , Zolpakar Nor Atiqah , Ghazali Mohd Fairusham
Published: August 2024

This critical review study focuses on the integration of nanofluids with microfluidic channels. This emerging field, which combines nanotechnology and microfluidics, has the potential to transform the control of temperatures and monitoring completely. Nanofluids, which are fluids containing nanoparticles like metals or oxides, greatly improve the heat management capabilities of base fluids. These materials are highly efficient in transferring and conducting heat, making them ideal for applications such as cooling electronics and medical diagnostics. The addition of nanofluids to microfluidic routes, typically measured in micrometers, greatly simplifies fluid flow and heat transfer regulation. The article includes several research studies demonstrating how nanofluids enhance the performance of microfluidic systems compared to conventional fluids. The benefits are examined, including the potential for reduced size and increased energy efficiency of heat exchanges and cooling systems. As a result, these technologies are better suited for implementation in the healthcare and industry sectors.
Analyzing Safety Management Practices affecting Safety Performance in the Electrical Industry: A Systematic Review
Authors: Tawfeeq Omar Munaf , Thiruchelvam Sivadass A. L. , Abidin Izham Bin Zainal
Published: August 2024

Workplace accidents can be avoided through meticulous planning, systematic organization, and through evaluating the efficacy of implemented control measures. Acquiring high standards in a safety management system can be achieved using models that facilitate the execution of proactive steps to mitigate work-related risks. This study aimed to ascertain the presence of effective safety practices throughout the implementation of safety performance measures. A systematic literature review was carried out following the guidelines provided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Thirty articles in English, published between 2010 and 2020, were identified by a comprehensive search in the Scopus, Science Direct, and Web of Science databases, based on certain criteria. The results demonstrated the efficacy of safety management practices and their impact on safety performance. The predominant focus of the evaluations was procedural safety, with relatively little emphasis placed on the elements of human safety that were significantly overlooked.
Modeling and Predicting Steam Power Plant Condenser Vacuum based on Small-sized Operation Data
Authors: Mursadin Aqli , Iriyanto Andi Yuwenda
Published: August 2024

The condenser vacuum is an important variable in steam power plants. Monitoring and controlling this variable requires predicting its behavior. This paper develops further Autoregressive-Generalized Autoregressive Conditional Heteroscedasticity (AR-GARCH) models for this purpose, using lagged values of predictors. The predictors include the inlet temperature of the condenser cooling water and the active power of the generator. Models can be adequately trained with small-sized data, making them suitable for use in thermal plants, which are often regularly maintained with operating conditions being reset, rendering past data obsolete. Training and testing were carried out using operation data from an actual steam power plant generating unit during a period in which it faced the prospect of an emergency turbine shutdown. When the models pass all the required statistical tests, they tend to outperform other techniques, including autoregressive neural networks and support vector regression, in terms of prediction. This study also discusses an implementation scenario. The choice of training sizes and model variants can be flexible, enhancing the models' practicality for real operational situations. This study also provides additional directions for further research.
The Effect of Fly Ash and Silica Fume on the Rheology of Cement Slurries of Ordinary Portland Cement of Grade 43 and 53
Authors: Khan Ahmad Waqar , Kumar Sanjay
Published: August 2024

Cement slurry is the medium of dispersion of coarse and fine aggregates when preparing concrete. The flow behavior of the cement slurries is governed by rheological parameters. The lower the value of these parameters is, the better the flowability and homogeneity of the cement slurry are. Static shear stress (τs), dynamic shear stress (τd), and the thixotropic index (β) are the basic rheological parameters. The effect of fly ash and silica fume on the rheology of Ordinary Portland Concrete (OPC) 43 and OPC 53 was studied by conducting tests on a coaxial rotating-type viscometer. Fly ash dosage was increased from 10% to 30% by the weight of cement in increment steps of 5% in binary and ternary mixes. Silica fume was kept constant at 5% in the ternary mixes. It was found that τs increases with fly ash in the OPC 43 but remains almost constant for the OPC 53 in both binary and ternary mixes. τd was almost constant for both the cement slurries in both binary and ternary mixes. β increases with an increase in fly ash for OPC 43 in binary and ternary slurries but decreases in OPC 53 slurries. The increment of fly ash increases the reversible built in the OPC 43 slurries, which can be broken on the application of shear. Thus, OPC 43 is a better cement from the rheological point of view in the development of various concrete mixes.
Design of Dual Band Substrate Integrated Waveguide (SIW) Antenna with Modified Slot for Ka-Band Applications
Authors: Agilesh Saravanan Ramamoorthi , Madhav Boddapati T. P. , Gangadhar A. , Chintalapati Sarada Sowjanya
Published: August 2024

This paper introduces a dual-feed substrate integrated waveguide antenna design with a modified H-Slot (DFH-SIW) for Ka-band 5G applications. In general, 5G base stations operating in Ka-band applications need large bandwidth-based antennas with high gain to solve the problem of path loss and high data capacity. To resonate with an ideal bandwidth at 28/38 GHz, this study proposes a high-gain antenna with a modified H-slot. This study used the CST EM tool to design the proposed antenna model and evaluate and optimize its characteristics. The proposed dual feed antenna has compact dimensions of 12×12×1.2 mm and was constructed on a Roger 5880 substrate with an appropriate permittivity of 2.2 and a minimal loss tangent of 0.0009. The proposed dual-feed antenna showed an ideal reflection coefficient of less than -10dB and a bandwidth of 3.7 GHz and 3.23 GHz at operating frequencies of 28 and 38 GHz, respectively. The proposed design operates at the 28 GHz frequency with 73.2% efficiency and 4.3 dBi gain, and at 38 GHz with 83.68% efficiency and 6.7 dBi gain. This antenna is intended to be used in future 5G wireless networks and has outstanding overall performance in terms of return loss, gain, and wide bandwidth.
A Study of Cyberbullying Detection and Classification Techniques: A Machine Learning Approach
Authors: Unnava Srinadh , Parasana Sankara Rao
Published: August 2024

The popularity of online social networks has increased the prevalence of cyberbullying, making it necessary to develop efficient detection and classification methods to mitigate its negative consequences. This study offers a comprehensive comparative analysis of various machine-learning techniques to detect and classify cyberbullying. Using various datasets and platforms, this study investigates and compares the performance of various algorithms, including both conventional and cutting-edge deep learning models. To determine the best practices in various scenarios, this study includes a thorough review of feature engineering, model selection, and evaluation measures. This study also examines how feature selection and data preprocessing affect classification precision and computational effectiveness. This study provides useful information on the advantages and disadvantages of various machine learning algorithms for detecting cyberbullying through experimentation and comparative research. The results of this study can help practitioners and researchers choose the best methods for particular applications and support ongoing efforts to make the Internet safer.
Stern Flow Hydrodynamics around a Self-propelled Maneuvering VLCC Ship
Authors: Marcu Oana , Robe-Voinea Elena-Gratiela
Published: August 2024

The present research explores the stern flow hydrodynamics around a maneuvering ship. Utilizing Computational Fluid Dynamics (CFD) techniques, several flow scenarios including different drift angles and propulsion configurations are modeled for the benchmark ship KRISO Very Large Crude Carrier 2 (KVLCC2). The analysis depicts all vortical structures that appear in the propeller operating area, explaining their formation and evolution. Also, the mutual interactions between the turbulent flow and the propulsion unit are observed and examined. The detailed outcome is intended to provide valuable insights for both new ship design and retrofits, aiming to advance new and sustainable engineering practices.
A Research on Passenger Carrying Capacity of an Innovative Electric Traction Power Supply System based on ROCS of 750 V DC MRT
Authors: Thai Nguyen , Doan Van Dong
Published: August 2024

This article presents the results of a study on the feasibility of a Rigid Overhead Conductor-rail System (ROCS) for a Mass Rapid Transit (MRT) system using 750 V DC power based on a carrying capacity transport-supply voltage level relationship. In particular, peak load conditions often cause serious problems of voltage drops occurring along the contact line, affecting the reliability, flexibility, system safety, and efficiency performance of the MRT system. The potential at the pantograph of a train on the segment of power supply depends significantly on the structure of the traction power supply network, contact network type, and voltage level. Recently, there have been studies on the dynamics of ROCSs under the impact of train motion, thereby applying the design to several railway systems in the world in specific conditions such as tunnels, stations, or viaducts. To consolidate the advantages of this trend, this paper studies the operating voltage of an ROCS in a full-line MRT system with a voltage level of 750 V DC belonging to the third rail. Matlab R2017b/Railway Systems is a reliable software for simulating and analyzing the necessary data. The results exhibit the feasibility of the designed ROCS. The system has a passenger carrying capacity of up to 90,000 passengers per hour per direction (p/h/d) under both normal and fault conditions. In this case, this capacity is achieved with a single-end feed at a distance of 2 km from a Traction Power Station (TPS), with the minimum feeder voltage at the pantograph point being 532.7200 V. The lowest operational feeder voltage of the system is 523.6667 V, supplied from a double-end feed at a distance of up to 5 km from the TPS.
A Secure Framework based On Hybrid Cryptographic Scheme and Trusted Routing to Enhance the QoS of a WSN
Authors: Sirajuddin Mohammad , Ravela Chittibabu , Rama Krishna S. , Ahamed Shaik Khaleel , Basha S. Karimulla , Jubair Basha N. Md.
Published: August 2024

Achieving Quality of Service (QoS) in Wireless Sensor Networks (WSNs) is challenging, due to their dynamic nature, and many parameters must be taken into account. The main objective of this work is to propose a hybrid cryptographic system with trust-based routing to improve the QoS. This study considers ways to improve QoS while maintaining security. To enhance the performance of the WSN, a framework that uses a hybrid cryptographic system based on a logistic map and the trust-based routing protocol CTBSR that can recognize and counteract a variety of security threats is presented. The findings of this study support the claim that the proposed framework ensures better security than the existing approaches in terms of confidentiality, integrity, and authentication. The performance of the framework introduced is evaluated by employing the NS2 simulator.
A Hybrid Genetic Algorithm Approach based on Patient Classification to Optimize Home Health Care Scheduling and Routing
Authors: Zaghdoud Radhia , Rhaiem Olfa Ben , Amara Marwa , Mesghouni Khaled , Galet Shahad
Published: August 2024

This study aims to solve the multi-objective problem of home healthcare scheduling and routing. The former’s objectives are to upgrade the travel distance, the workload balance, and the waiting time of caregivers. A novel approach was proposed based on patient and caregiver clustering with the K-means++ algorithm in the first step and a hybrid genetic algorithm to optimize the global operation in the second step. The problem was solved regarding the deterministic and the uncertain aspect. The uncertain parameter investigated is the number of patients. A numeric study was conducted to prove the performance of the recommended approach using the Solomon Benchmark.
Predictors of Blockchain Technology Acceptance in Medical Imaging: The Mediating Role of Initial Trust
Authors: Al-Sulami Zainab Amin , Ali Nor’ashikin , Ramli Rohaini
Published: August 2024

Blockchain technology (BCT) is an emerging technology that has been used mainly in supply chain and financial technology. However, the use of this technology in Medical Imaging (MI) is still limited. This study investigates the acceptability of BCT in MI in public hospitals in Iraq. Based on relevant theories, the study proposed that Effort Expectancy (EE), Performance Expectancy (PE), Social Influence (SI), and Facilitating Condition (FC) significantly affect the acceptability of BCT in MI. Similarly, EE, PE, SI, and FC are expected to affect Initial Trust (IT), which in turn is proposed to mediate the effect of EE, PE, SI, and FC on the acceptability of BCT in MI. Data were collected from 136 doctors from public hospitals in Iraq. The results indicated that EE, PE, and SI positively affected the acceptability of BCT in MI. EE and PE positively affected IT. Furthermore, IT positively affected the acceptability of BCT in MI and mediated the effect of EE and PE. The study offers valuable insights for both theoretical and practical implementations, can guide future research, and informs strategies for the effective acceptability of BCT in MI in public hospitals.
Automatic Call of CPO Toolpaths without Uncut Regions for 2.5 D Pocket Milling
Authors: Bahloul Elhachemi , Guerraiche Khelifa
Published: August 2024

In order to achieve the automatic call of any toolpath generation in 2.5 D pocket milling, new tool paths with offset parallel to the contour for any concave or convex polygonal shape are proposed in this article. Focus is given on several methods for addressing issues related to trajectory generation: the disappearance of edges when transitioning from one contour to another, the residual between passes, and the center of the pocket. A few selected test cases are presented for validation. The obtained results reveal that the approach introduced offers automatic toolpath generation for any polygonal shape and ensures efficient machining simulation without the appearance of material residues between passes in the corners or at the center of the pocket.
Machine Learning Baseline Energy Model (MLBEM) to Evaluate Prediction Performances in Building Energy Consumption
Authors: Mustapa Rijalul Fahmi , Hairuddin Muhammad Asraf , Mohd Nordin Atiqah Hamizah , Dahlan Nofri Yenita , Yassin Ihsan Mohd , Dalila Khirul Ashar Nur
Published: August 2024

Electric Energy Consumption (EEC) prediction for building operations can be performed using a Baseline Energy Model (BEM), which is vital to ensure the efficiency of the EEC estimates with its respective independent variables. However, developing the BEM to represent the relationship between independent variables can be a complex task due to the EEC variability in an educational building that differs during its operation period. The best-suited BEM must be continuously improvised to achieve good modeling with accurate and reliable predictions that capture the building operations’ current dynamics. This study aims to conduct a comparative performance assessment between deep learning, machine learning, and statistical models to develop the BEM and, therefore, predict the EEC of the building for 24, 48, 72, and 96 hours, while considering the operation of the lecture weeks and the associated number of students and staff. The hours and temperature are considered as independent variables to be tested with residual error evaluations, whilst the correlation coefficient, coefficient of determination, and training time are also taken into account. Three models with different categories involving Long Short-Term Memory (LSTM), Support Vector Regression (SVR), and AutoRegressive Integrated Moving Average with Exogenous inputs (ARIMAX) were compared, concluding that SVR was the best and can be used as a universal model in the Machine Learning Baseline Energy Model (MLBEM) studies. Accurate EEC prediction will offer a huge advantage for building operators to properly monitor, plan, and manage the EEC, hence avoiding excessive utility bills.
An MLP-CNN Model for Real-time Health Monitoring and Intervention
Authors: Nizamuddin Mohammad Khaja , Raziuddin Syed , Farheen Mohammed , Atheeq C. , Sultana Ruhiat
Published: August 2024

The use of Artificial Intelligence (AI) in healthcare, particularly in real-time health monitoring and predictive interventions for chronic diseases, has many benefits but also many drawbacks. Existing health risk prediction algorithms face accuracy issues and, due to the wide variety of health profiles, general algorithm applicability is problematic. The proposed model solves this issue by using an advanced AI framework to improve the accuracy of the prediction of Chronic Kidney Disease (CKD) and eliminate false positives. Our hybrid Deep Learning (DL) method blends a Multi-Layer Perceptron (MLP) and a Convolutional Neural Network (CNN), thus including real-time feedback to help the system learn from its predictions and results. The proposed system solves a major problem in this area and sets a new benchmark for AI applications in healthcare by directly addressing prediction accuracy. It offers more tailored, accurate, and responsive chronic disease management, improving patient outcomes and healthcare resource efficiency.