bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Social Capital in Village Owned Business Entities (BUMDes) on Village Development (Case Study in Pujonkidul Village, Pujon District, Malang Regency)
Authors: AKBAR Rona Rio , MARYUNANI Maryunani , SASONGKO Sasongko
Published: February 2023

This study aims to determine what social capital affects the management of BUMDes for village development and to find the elements of social capital to help solve existing problems. By using qualitative research methods, this study seeks to explore the elements and roles of existing social capital and then analyze how this social capital plays a role in solving the problems faced. The results of research and observations of all elements of social capital, namely trust, network, norm, and reciprocal, are all contained in the management of BUMDes. However, the most dominant is the network of all existing elements, thanks to the breadth of relationships and networks. This study also proves that the solution to the problems that exist in the parking business unit, namely the problem of irregular parking by visitors due to the available parking is no longer able to accommodate the vehicles of visitors to the rice field cafe on certain days, so reciprocal is the solution to this problem. Mutual benefit between residents and parking unit managers. Then from the side of trust, the existence of mutual trust between the villagers and the manager of the rice field cafe will strengthen the kinship so that no more problems arise.
The Nexus Between Environmental Management Accounting Practices and Financial Sustainability of Cement and Mining Companies in South Africa
Authors: NYAHUNA Thomas , DOORASAMY Mishelle
Published: February 2023

The main purpose of the study is to investigate the relationship between environmental management accounting practices (EMAP) and financial performance of South African cement and mining companies. To attain the major objective of the research, three hypotheses were tested based on data from 45 JSE-listed cement and mining companies from 2010 to 2021. Multiple regression analysis with the assistance of IBM SPSS Statistics 24was also used to test the hypotheses. The study found that two accounting measures namely return on assets and net profit margin had no significant relationship with EMAP. However, the study also revealed that one accounting based measure namely return on equity had a positive and significant relationship with EMAP. This signifies that EMA is still at its primary stages in South Africa. In addition, the results also suggest that EMA is important to accomplish sustainability. The results provide managers with empirical evidence of EMAP that increases financial sustainability in the context of an emerging economy such as South Africa.
An Examination of Adolescent Girls' and Young Women's Entrepreneurial Knowledge in South Africa: Longitudinal Study
Authors: MVUNABANDI Jean Damascene , NOMLALA Bomi Cyril , GADZIKWA Lawrence
Published: February 2023

Motivated by lack of empirical research on entrepreneurial knowledge training among adolescent girls and young women in South Africa and elsewhere, this article examined the entrepreneurial knowledge among 3584 adolescent girls and young women from four provinces, namely KwaZulu Natal, Mpumalanga, Eastern Cape and Western Cape in South Africa. This study adopted quantitative and descriptive research approach. Secondary data collected using questionnaire survey during entrepreneurial mindset and skills training from July-October 2021 by the large anonymised not for profit organisation based in South Africa was used for data analysis. Robustness analysis was entirely performed using descriptive statistics using SPSS version 28.0. The findings from the empirical part of this research statistically proved the adolescent girls and young women improved their knowledge entrepreneurially after training that is evident in most extent literature. This article contributes to the current body of knowledge as it filled in the gap and contributed significantly to the entrepreneurial mindset skill and knowledge improvement among adolescent girls and young women in South Africa.
The Role of Strategic Management Accounting for Startups in Implementing Sustainable Development Goals in PT Oesodo Alam Mandiri
Authors: RAMADHAN Yanuar , SETIYAWATI Erna , SARI Ratna Dewi , IZA Maria , ALAWIYAH Noviyanti
Published: February 2023

PT Oesodo Alam Mandiri (PT OAM) is a company engaged in the partnership business that specifically provides delicious and contemporary herbal products through booths or cafes and the like by using the herbal medicine partnership business model in the form of a business opportunity. This study aims to analyze and find out how PT OAM's management strategy accounting can contribute to the implementation of the Sustainable Development Goals (SDGs) in Indonesia. The method used in this observation is a literature study by finding and using relevant theoretical references that serve as the basis and reference for finding solutions to cases or problems found. The results showed that SDGs no. 8 and 3 can be achieved by establishing a herbal medicine partnership strategy by collaborating with the Bekasi City Government to reduce the unemployment rate through the MSME program
Participer sans protester. Les logiques de l'engagement situé au sein du mouvement Reclaim the City au Cap
Authors: De Barros Margaux
Published: February 2023

Pourquoi une grande partie des résidents de l'occupation de Woodstock au Cap, régie par le mouvement social Reclaim the City, se tiennent-ils à l'écart des activités militantes, pourtant obligatoires, du mouvement ? À rebours d'une analyse dichotomique « actif » versus « passif », je mets en évidence l'adoption par ces habitants d'une attitude médiane, l'« engagement situé », limité à l'espace de l'occupation. À travers la restitution des trajectoires de certains d'entre eux, j'explore la façon dont la réparation de sphères de vie mises à mal par l'instabilité résidentielle, d'une part, la socialisation aux idées conservatrices portées par le parti au pouvoir dans la municipalité, d'autre part, constituent des entraves à un engagement intense en faveur d'un mouvement aux idées ancrées à gauche. Je resitue par ailleurs les subjectivités des habitants dans les conditions interactionnelles de voisinage. Les liens fragilisés par la promiscuité peuvent dégrader les rapports de militantisme et décourager un engagement poussé au sein du groupe. Toutefois, l'engagement situé est rendu possible grâce à des ajustements du militantisme qui permettent aux résidents d'éviter les sanctions et de préserver des relations de voisinage relativement apaisées.
L'israélisation de la diaspora juive. Le cas de Sar-El, volontariat civil en Israël
Authors: Partouche Maëlle
Published: February 2023

En quoi Sar El, programme de volontariat civil dans l'armée israélienne, joue-t-il un double rôle d'offre et de demande dans les relations entre la diaspora juive et l'État israélien. Répondre à cette question suppose d'envisager Sar-El comme un cas pratique d'israélisation de la diaspora par Israël, c'est-à-dire comme une entreprise de captation des juifs « de l'étranger » par un État autoproclamé centre du monde juif, tout en saisissant son inscription dans le « continuum d'engagements » des juifs restés en diaspora. Ce qui se joue dans la mise en œuvre et le succès de ce programme interroge la situation contemporaine des juifs en France et l'évolution du sionisme dans le contexte français. Plus largement, l'élaboration de tels programmes doit être appréhendée comme s'inscrivant dans le processus historique d'auto-ajustement de l'axiomatique de l'État gardien développé par D. Trom.
L'invention d'un marché : économie politique de la biométrie électorale en Afrique
Authors: Debos Marielle , Desgranges Guillaume
Published: February 2023

La biométrie électorale se développe en Afrique depuis les années 2000, et plus de la moitié des pays l'utilisent désormais pour l'identification des électeurs. Notre recherche vise à comprendre comment et par qui ce marché improbable a été inventé. Elle est fondée sur l'association de deux méthodologies  : d'une part, la création d'une base de données des technologies électorales utilisées dans les différents pays et des entreprises qui les vendent, d'autre part, une enquête qualitative par entretiens et observation ethnographique. Nous montrons que le marché de la biométrie électorale est façonné autant par la recherche de profit que par les savoirs, savoir-faire et positionnements normatifs d'une grande variété d'acteurs  : des bailleurs et professionnels internationaux de la démocratie au personnel politique des pays africains. En adoptant une approche d'économie politique, nous mettons également en évidence la dimension postcoloniale de ce marché, en particulier dans l'ancien empire français.
Combining NSP- and CPTu-based Nkt to evaluate undrained shear strength
Authors: Quirós Gerardo W , Peters Patricia M , Gan Kuat C
Published: February 2023

A procedure for estimating reliable ranges of Nkt for direct simple shear (DSS)-based and anisotropically consolidated triaxial compression (CAUC)-based undrained shear strength is presented. The procedure is based on a combination of three Normalized Soil Parameter (NSP) methods and two CPTu (piezocone penetrometer) methods and are related to the ratio of net cone resistance to hydrostatic effective vertical stress. The NSP and CPTu data used were acquired from seven sites: these sites have stress histories ranging from very underconsolidated to very highly overconsolidated. The stratigraphies of the seven sites consist of clays that are moderately plastic to highly plastic. This proposed procedure was then applied to 22 published sites with a wide range of fine-grained soil types and index properties. The procedure yielded very consistent and reasonable envelopes of Nkt, which in turn, provide sound DSS-based strength profiles as well as CAUC-based strength profiles. The proposed procedure also clearly demonstrates that the range for Nkt factors is not limited to 15 to 20 for normally consolidated to lightly overconsolidated cohesive sediments, which is frequently employed by practitioners.
Deep learning-based small object detection: A survey
Authors: Feng Qihan , Xu Xinzheng , Wang Zhixiao
Published: February 2023

Small object detection (SOD) is significant for many real-world applications, including criminal investigation, autonomous driving and remote sensing images. SOD has been one of the most challenging tasks in computer vision due to its low resolution and noise representation. With the development of deep learning, it has been introduced to boost the performance of SOD. In this paper, focusing on the difficulties of SOD, we analyze the deep learning-based SOD research papers from four perspectives, including boosting the resolution of input features, scale-aware training, incorporating contextual information and data augmentation. We also review the literature on crucial SOD tasks, including small face detection, small pedestrian detection and aerial image object detection. In addition, we conduct a thorough performance evaluation of generic SOD algorithms and methods for crucial SOD tasks on four well-known small object datasets. Our experimental results show that network configuring to boost the resolution of input features can enable significant performance gains on WIDER FACE and Tiny Person. Finally, several potential directions for future research in the area of SOD are provided.
Predicting model of mild and severe types of COVID-19 patients using Thymus CT radiomics model: A preliminary study
Authors: An Peng , Li Xiumei , Qin Ping , Ye YingJian , Zhang Junyan , Guo Hongyan , Duan Peng , He Zhibing , Song Ping , Li Mingqun , Wang Jinsong , Hu Yan , Feng Guoyan , Lin Yong
Published: February 2023

Objective

To predict COVID-19 severity by building a prediction model based on the clinical manifestations and radiomic features of the thymus in COVID-19 patients.

Method

We retrospectively analyzed the clinical and radiological data from 217 confirmed cases of COVID-19 admitted to Xiangyang NO.1 People's Hospital and Jiangsu Hospital of Chinese Medicine from December 2019 to April 2022 (including 118 mild cases and 99 severe cases). The data were split into the training and test sets at a 7:3 ratio. The cases in the training set were compared in terms of clinical data and radiomic parameters of the lasso regression model. Several models for severity prediction were established based on the clinical and radiomic features of the COVID-19 patients. The DeLong test and decision curve analysis (DCA) were used to compare the performances of several models. Finally, the prediction results were verified on the test set.

Result

For the training set, the univariate analysis showed that BMI, diarrhea, thymic steatosis, anorexia, headache, findings on the chest CT scan, platelets, LDH, AST and radiomic features of the thymus were significantly different between the two groups of patients (P < 0.05). The combination model based on the clinical and radiomic features of COVID-19 patients had the highest predictive value for COVID-19 severity [AUC: 0.967 (OR 0.0115, 95%CI: 0.925-0.989)] vs. the clinical feature-based model [AUC: 0.772 (OR 0.0387, 95%CI: 0.697-0.836), P < 0.05], laboratory-based model [AUC: 0.687 (OR 0.0423, 95%CI: 0.608-0.760), P < 0.05] and model based on CT radiomics [AUC: 0.895 (OR 0.0261, 95%CI: 0.835-0.938), P < 0.05]. DCA also confirmed the high clinical net benefits of the combination model. The nomogram drawn based on the combination model could help differentiate between the mild and severe cases of COVID-19 at an early stage. The predictions from different models were verified on the test set.

Conclusion

Severe cases of COVID-19 had a higher level of thymic involution. The thymic differentiation in radiomic features was related to disease progression. The combination model based on the radiomic features of the thymus could better promote early clinical intervention of COVID-19 and increase the cure rate.
Analysis of Monkeypox viral infection with human to animal transmission via a fractional and Fractal-fractional operators with power law kernel
Authors: Alzubaidi Alia M. , Othman Hakeem A. , Ullah Saif , Ahmad Nisar , Alam Mohammad Mahtab
Published: February 2023

Monkeypox (MPX) is a global public health concern. This infectious disease affects people all over the world, not just those in West and Central Africa. Various approaches have been used to study epidemiology, the source of infection, and patterns of transmission of MPX. In this article, we analyze the dynamics of MPX using a fractional mathematical model with a power law kernel. The human-to-animal transmission is considered in the model formulation. The fractional model is further reformulated via a generalized fractal-fractional differential operator in the Caputo sense. The basic mathematical including the existence and uniqueness of both fractional and fractal-fractional problems are provided using fixed points theorems. A numerical scheme for the proposed model is obtained using an efficient iterative method. Moreover, detailed simulation results are shown for different fractional orders in the first stage. Finally, a number of graphical results of fractal-fractional MPX transmission models are presented showing the combined effect of fractal and fractional orders on model dynamics. The resulting simulations conclude that the new fractal-fractional operator added more biological insight into the dynamics of illness.
A hierarchical age-structured model of optimal vermin management by contraception
Authors: Liu Rong , Zhang Fengqin
Published: February 2023

Taking the reproduction law of vermin into consideration, we formulate a hierarchical age-structured model to describe the optimal management of vermin by contraception control. It is shown that the model is well-posed, and the solution has a separable form. The existence of optimal management policy is established via a minimizing sequence and the use of compactness, while the structure of optimal strategy is obtained by using an adjoint system and normal cones. To show the compactness, we use the Fréchet-Kolmogorov theorem and its generalization. To construct the adjoint system, we give some continuity results. Finally, an illustrative example is given.
Impact Analysis of Felt Need-Based Adolescent Reproductive and Sexual Health Module for Late Adolescent Girls in an Urban Slum
Authors: Verma Mayuri , Gupta Arun , Adhya Saibal , Kapoor Suraj , Ekambaram TKM , Kour Amrindar Jeet
Published: February 2023

ABSTRACT

Introduction:

A timely and accurate intervention regarding reproductive and sexual health in adolescent age group is expected to enhance their knowledge, change their attitudes, and strengthen their decision-making skills regarding their own reproductive health. This study was undertaken to assess the impact of felt need-based adolescent reproductive and sexual health education module, on knowledge, attitude, and practices of their menstrual hygiene.

Materials and Methods:

It is an interventional quantitative study done in 206 late adolescent girls residing at an urban slum. Focus Group Discussion was held in group of 8–12 girls to assess felt needs regarding puberty and menstrual knowledge. Baseline knowledge, attitude, and practices were assessed through a questionnaire. Analysis of menstrual hygiene practices was done after 3 months of health education intervention. A one-way repeated measures ANOVA was conducted to compare the effect of health education on knowledge score. Three paired sample t-tests were used to make post hoc comparisons.

Results:

Mean age of girls was 16.10 years, with majority from Hindu religion. Sanitary pad usage was 91.26%. Restrictions in attending religious events were observed in 96.12% and 84.47% attended school during menses. Mother’s education and facility of sanitary latrine in house were significantly associated with menstrual hygiene practices (P < 0.05). ANOVA test to compare the effect of health education on knowledge score was significant, Wilks Lambda = 0.171, F (2,188) = 456.271, and P < 0.001. Maulchy’s test for sphericity was insignificant.

Conclusion:

Sanitary pad is being used by large majority of adolescent girls, in urban slum setting now. Menstrual hygiene practices were better in daughters of more educated mothers and those who had sanitary latrine in house. Number of girls having good knowledge about puberty and menstruation increased significantly after health education intervention. Although the knowledge increased drastically after the education sessions, the girls could not retain all of it, indicating reinforcement of knowledge is a must.
A Generalized Data-Driven Modelling for COVID-19 Pandemic Outbreak: Jordan Case Study
Authors:   Princess Sumaya University for Technology. Amman, Jordan. 2American University of Madaba. Amman, Jordan, Salameh Walid A. , Surakhi Ola M. , Alhaol Ibrahim Abu , Fung Pak Lun , AlKhanafseh Mohammad , Hussein Tareq
Published: February 2023

— The explosion of the COVID-19 pandemic shows the limitations of the existing healthcare system in handling health emergencies. Innovative technologies like artificial intelligence and mathematical modelling can play an essential role in effective planning operations for fighting coronavirus pandemic. In this paper, a comparison between the mathematical model performance for forecasting the number of positive cases in Jordan and three data-driven models is performed to provide more insight on the appropriate model that can be utilized for COVID-19 disease spreading analysis. Our finding shows that both types of models can assess disease-spreading research. Including more factors in the forecasting process can increase the complexity of mathematical model analysis. On the other hand, the datadriven models and mechanisms will be more appropriate for this purpose. However, much work is still needed to capture more factors in the modelling process and provide a reliable solution for stopping this pandemic.
Abstractive Text Summary with Transformer on Youtube Video Subtitle
Authors:   Computer Science Department, School of Computer Science, Bina Nusantara University, Jakarta Indonesia 11480, Atipa Juan Lee , Javin Javin , Bryan Fernando , Yesmaya Violitta , Wongso Rini
Published: February 2023

Time limitation is one of the most important factors when consuming media. Longer duration makes it harder for users to watch the entirety of the video. Text summarization could be a way for users to acquire information swiftly and concisely. However, the extent to which the summary of the information made has really approached the main core of the information to be conveyed. In this study using YouTube video subtitles as the data that will be used to get a summary of the core information from the video. Consequently, this research focuses on abstractive summarization utilizing several Transformer models namely T5, BART, and PEGASUS, and using the video subtitle dataset to create a summary. The text data from the video subtitle is used as the main source of information in the learning process of the model, ultimately enhancing the model’s ability on this specific summarization task. In evaluating the models’ results, ROUGE is employed, specifically ROUGE-1, ROUGE-2, and ROUGE-L.
Durian Farm Threats Identification through Convolution Neural Networks and Multimedia Mobile Development
Authors:   Multimedia Signal Processing Focus Group, Multimedia Department, Faculty Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, Yusoff Aiman , Kamarudin Noraziahtulhidayu , Al-Emad Nabil Ali , Sapuan Khusairi
Published: February 2023

— The difficulties to drive away the durian farm threatens animals such as wild boars, monkeys, foxes, and squirrels during nighttime often experienced by durian farmers. Therefore, the Pro Durian application is proposed that allows farmers to identify durian threats through a camera phone with an alert feature activation when the system detects an animal to drive away those animals. The application implements a deep learning algorithm of Convolutional Neural Network (CNN)-YOLO3in order to receive the best output results in identifying the different datasets of durian farm threats. The classification accuracies reached 80% in detecting the animal’s images. Keywords— Durian Farm, Recognition Image, TensorFlow lite, Android Studio, Convolution Neural Network
Adoption of More-than-voice Technology: The Role of Country Affiliation
Authors:   College of Business Administration, Prince Mohammad Bin Fahd University, Al Khobar, Saudi Arabia, Hossain Muhammad Muazzem
Published: February 2023

—Plethora of uses of mobile phones exist across the globe. The use of mobile phones beyond voice calls is known as the more-than-voice (MTV) technology. The widespread use of MTV technology is evident among the bottom of pyramid (BoP) around the world. The BoP represents a significant portion of the world population that not only can afford MTV technology but also can serve as a huge consumer base for services based on this technology. This study examines the factors affecting the acceptance of MTV technology by the BoP users and investigates whether their country affiliation plays a differing role in the adoption of the technology in the Indian subcontinent. Data were obtained from the Teleuse@BOP4 study. Partial least square (PLS) was performed to test the research model. The findings suggest that the perceived usefulness, ease of use, facilitating conditions, acumen to use, and propensity to use are the significant predictors of the adoption of the MTV technology. The findings also suggest that country affiliation plays a significant moderating role in the relationships between facilitating conditions and intention, and propensity to use and intention. This study then provides the practical and academic implications of both significant and insignificant findings. Keywords—More-than-voice technology, MTV technology, MTV services, consumer acceptance, technology adoption, country affiliation.
Critical Factors in user Preferences for Internet Service Provider: A Factor Analysis Approach
Authors:   Information Systems Management Department, Binus Graduate Program – Master of Information Systems Management, Bina Nusantara University, Jl. Kebon Jeruk Raya no 27 Kebon Jeruk, Jakarta 11530, Sari Fransiska Dian , Oktavia Tanty
Published: February 2023

This research is motivated by the increasingly sharp development of internet use. Almost every aspect is supported by technology, making us increasingly unable to live without the internet. Using the internet with a WiFi network offers easy and fast communication. However, each user has their preferences in using a Wi-Fi network. The non-fulfillment of user preferences results in user turnover problems. Therefore, the purpose of the study is to find out what factors have the most influence on user preferences. The factors are service quality, cost, brand image, and promotion. The target of this research is Wi-Fi network users in Indonesia. In collecting data from users, a questionnaire is used which is distributed through social media. Before testing the hypothesis, conduct validity and reliability tests on the instrument used. The results can be more easily understood using the multiple linear regression analysis methods. After conducting research, it is known that the most critical factor in determining user preferences for Internet Service Providers (ISPs) is the quality of services provided. From these results, the Internet Service Provider (ISP) can improve all aspects according the factors to solve problems and increase business profits
A Defense System: Jamming Detection and Mitigation for Safety Applications in Vehicular Networks
Authors:   Graduate University of Science and Technology (GUST), Vietnam Academy of Science and Technology, Vietnam, Minh Huong Nguyen , Tung Tran Hoang , Nam Huynh Vinh , Giang Pham Thanh
Published: February 2023

The periodically exchanged basic safety messages (BSM) in vehicular networks have become a new attack target for jamming attacks that are easy to conduct in a vehicular environment. The detection and mitigation must be cordially integrated to provide acceptable communication latency under attacking conditions. This paper considers a comprehensive defense system detecting and mitigating jamming attacks. We analyze the impact of the jamming attack on BSMs on our initially proposed random channel surfing scheme coupling with a detection method. The detection method can hardly provide 100% accuracy, and this consequently delays the reaction. We study the defense system by a mathematical model which is validated by simulations in NS-3. The obtained results depict how the performance of the channel surfing scheme depends on its preinstalled detection method
Data Collection in WSNs using a Probability-Based Rendezvous Points Selection Algorithm
Authors:   Department of Computer Science, Zarqa University, Zarqa, Jordan, Samara Ghassan , Alazaidah Raed , Aljaidi Mohammad , Almatarneh Sattam , BaniMustafa Ahmed , Bulkrock Olla , Sweerki Nael , Hnaif Adnan A.
Published: February 2023

Wireless Sensor Networks are becoming more prevalent in various industries, including military operations and distant environmental monitoring. This is important because sensors are getting smarter, smaller, and less expensive. The energy hole problem in the WSN has been a major focus of recent research. The mobile sink is an efficient solution for the energy hole problem in a wireless sensor network. A mobile sink gets data from sensors by moving around the network often to avoid problems with hotspots or energy holes. It gets data from network nodes by traveling regularly and visiting a group of nodes known as rendezvous points (RPs). This research will present a probability-based RP selection (PRPS) technique for data collection in wireless sensor networks. To begin, a directed spanning tree is used to construct a tree that eliminates duplication in the data forwarding path. The proposed method is employed to compute the likelihood of RPs. Finally, using the shortest path technique, a mobile sink is constructed between these locations. The path provided is the best path that connects all of the RPs. The proposed approach improves the previous solutions by choosing the nodes with the most data packets as RPs. As a result, it extends network lifetime by lowering energy consumption and addressing the energy hole problem.
OCR-based Hybrid Image Text Summarizer using Luhn Algorithm with FinetuneTransformer Modelsfor Long Document
Authors:   Computer Education Department, ACLC College of Butuan, Butuan City, Philippines, Singco Van Zachary V. , Trillo Joel C. , Abalorio Cristopher C. , Bustillo James Cloyd M. , Bojocan Junell T. , Elape Michelle C.
Published: February 2023

The accessibility of an enormous number of image text documents on the internet has expanded the opportunities to develop a system for image text recognition with text summarization. Several approaches used in ATS in the literature are based on extractive and abstractive techniques; however, few implementations of the hybrid approach were observed. This paper employed state-of-the-art transformer models with the Luhn algorithm for extracted texts using Tesseract OCR. Nine models were generated and tested using the hybrid text summarization approach. Using ROUGE metrics, we compared the proposed system finetune abstractive models against existing abstractive models that use the same dataset Xsum. As a result, the finetune model got the highest ROUGE score during evaluation; in ROUGE-1 score was 57%, the ROUGE-2 score was 43%, and the ROUGE-L score was 42%. Furthermore, even when better algorithms and models were available for summarization, the Luhn algorithm and T5 finetune model provided significant results.
Wireless IoT Networks Security and Lightweight Encryption Schemes- Survey
Authors:   Faculty of Science and Engineering, Anglia Ruskin University, Chelmsford, UK, Qashou Akram , Hazzaa Firas , Yousef Sufian
Published: February 2023

— IoT networks suffered from different kinds of attacks. The main issue of IoT security is the limitation of its node’s energy ability to perform big tasks such as encryption. This paper provides a comprehensive overview of the dynamic landscape of lightweight cryptography research, particularly in the context of real-time traffic security and Internet of Things (IoT) networks. The aim of this research is to identify the gaps in IoT research efforts and draw up ways to address it. The objectives are highlighting the global collaboration and standardization initiatives that have shaped its development. Also, it emphasizes the importance of balancing cryptographic strength with practical considerations such as encryption latency, energy efficiency, and memory constraints, particularly crucial in the context of resource constrained IoT devices. Furthermore, it highlights innovative approaches proposed by researchers to enhance the security of cryptographic operations while minimizing overhead and ensuring compatibility with evolving wireless environments. It calls for sustained research efforts to address these challenges and foster the development of robust cryptographic solutions capable of meeting the stringent security requirements of modern digital ecosystems.
A Study on the Application of Advanced Acoustic Information Technology for the Completion of Autonomous Driving Vehicles
Authors:   Electronic Information Engineering IT Convergence SoongSil niv, 369, Sangdo-ro Dongjak-gu, Seoul Korea, Ahn Ik-Soo
Published: February 2023

Since Autonomous Driving Vehicles are directly related to human life, it is necessary to put the utmost effort into safe driving to the point of being almost perfect. Also, for the best safety, any technology should be borrowed, tested, and applied. In this paper, the method of applying sound information to the Autonomous Driving Vehicles research presented last time will be emphasized and specified. Since the sound information to be applied to Autonomous Driving Vehicles is vast, it must be made into big data and must be used in various and precise ways, so it must be made into IOT based on AI. Sound Information Technology must be equipped with technology that can perfectly judge changing conditions such as time, season, and weather depending on the location. Acoustic Information Technology can be largely divided into ES(Environmental Sounds) and TS(Things Sounds). Environmental Sound is to detect the conditions of the surrounding environment including the road or the ground on which the vehicle is traveling with sound information. Things Sounds is to detect fixed or moving Things around the vehicle with sound information. In the future, it is expected that various methods of Sound Information Technology will be able to contribute greatly to the achievement of the era of Free Driving vehicles, which is the completion stage of Autonomous Driving Vehicles.
Revolutionary Triangular Patch Antenna with Dumbbell-Shaped Defected Ground Structure for 5G at 3.7 GHz: A Disruptive Design Innovation
Authors:   Centre for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100, Durian Tunggal, Melaka, Malaysia, Othman Mohd Azlishah bin , Jaafar Abd Shukur bin , Manap Redzuan Abdul , Misran Mohamad Harris , Said Maizatul Alice Meor , Suhaimi Shadia , Hassan Nurmala Irdawaty
Published: February 2023

This research proposes the use of a triangularshaped printed antenna operating at 3.7 GHz as a Defected Ground Structure (DGS) for a 5G communication system. The design of triangular antenna is incorporates with a printed Dumbbell shaped DGS structure in order to reduce the cost of antenna fabrication. The aim is to improve service performance, effectiveness, and quality of 5G communication systems. The proposed antenna has been analyzed and found to have return losses of -28.73 dB at the resonant frequency of 3.73 GHz, and an antenna gain of 3.23 dB. The DGS design is expected to increase the performance and this antenna be a choice for 5G communication systems.
A New Observer-based Model- Reference Approach for Nonlinear Discrete-Time Systems with Application to Power Systems
Authors:   Electrical Engineering Department, Cairo University, Hassan M. F. , Aljuwaiser E.
Published: February 2023

In this paper, a novel observer-based modelreference technique is developed to control the performance of nonlinear discrete-time systems. Firstly, a linear or nonlinear model is chosen for which the dynamics are designed to satisfy the pre-specified performance behaviours of the nonlinear system as stated by the designer. The proposed approach is then used with the system to fulfil a point-by-point tracking of the pre-designed model trajectories. To achieve this goal, an observer is firstly used to predict the states and the output(s) at the next sampling point of the system to be controlled from the received set of measurements. The differences between the achieved predicted estimates and those of the model are then used to generate the necessary online closed-loop control actions to force the system trajectories to track those of the model at the next sampling instant of time, as desired. The stability of the closed-loop control system is investigated. To check the performance of the developed approach, it is then used to control the performance of a synchronous machine and a permanent magnet synchronous motor. The achieved results are presented to illustrate the effectiveness, simplicity, and applicability of the proposed design procedure
System Simulation Comparison of Sliding Mode and PID Controller for Buck Converter
Authors:   Department of Electrical, Electronics and Communications Engineering, American University of Ras Al Khaimah, Ras Al Khaimah, UAE, Getu Beza Negash , Attia Hussain A.
Published: February 2023

In this paper, the performance of the closed loop sliding mode controller (SMC) is compared with the conventional PID controller for DC-DC buck converter. We specifically address the comparison of the two controllers from system simulations point of view by first developing the system model of the DC-to-DC buck converter circuit and designing a suitable SMC controller.Using MATLAB/SIMULINK system simulations, the performance of the SMC controlled buck converter is compared with the PID controller in terms of the overshoot, rise time and settling time of the load voltage and currents. The simulation results demonstrated the high performance of the SMC controlled buck converter in accurately tracking the reference voltage, eliminating the overshoot, improving the settling time but with slower rise time as compared with the PID controller. The transient time response of the SMC controller can be further improved by tuning the system control parameters to attain improved rise time. Such SMC based buck converter can be used for the design of a stable direct current power supply for DC loads such as DC motors used for water pumps or other applications.
Antenna Array Performance in Microwave Imaging Technique for Brain Tumor Detection
Authors:   Faculty of Engineering Technology, Universiti Tun Hussein Onn Malaysia, 84600 Pagoh, Muar, Johor, Malaysia, Harun Nur Syahirah , Wahab Anisah Abd , Ramli Mimi Faisyalini , Ngadiron Zuraidah , Rahiman Mohd Hafiz Fazalul , Sun Jiangtao
Published: February 2023

Recent advancements in microwave tomography (MT) imaging studies have stimulated interest in antenna array development for medical imaging. An antenna and a model of the human head are required for the medical MT system, particularly in detecting brain tumors. Previous studies have shown that antenna arrays are more reliable as compared to a single element of patch antenna in detecting brain tumors. In this study, a single patch antenna is first designed to work at 3.2GHz using CST Studio software. To evaluate the effectiveness of antenna arrays in microwave imaging systems, the patch antenna is then improved into a 2x1 and 4x1 array. The gain, directivity, return loss (S11), Voltage Standing Wave Ratio (VSWR), and bandwidth are compared between single and arrays of antenna models. It has been proved that 2x1 and 4x1 antenna arrays resulted in higher performance. With a maximum gain of 7.11 dB, the 4x1 rectangle patch antenna has 11.3 dBi directivity, -13.88 dB return loss, and 91.1 MHz bandwidth, meanwhile single patch antenna has a gain of 3.34 dB, 5.68 dBi directivity, - 17.33 dB return loss, and 132 MHz bandwidth. Overall, a 4x1 patch antenna is made reliable and sensitive to be used in detecting brain tumors as higher gain and directivity may be useful to penetrate multilayer human head.
COVID Detection Using Chest X-ray Images & Deep Learning CNN Mechanism
Authors:   Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia, Aljahdali Hani Moaiteq
Published: February 2023

As we know that how rapidly is corona virus spreading, starting from China, to all over the world. There are more than 5 million suspected cases and almost 0.33 million deaths according to the statistics of world meterinfo, and there are limited test kits available in hospitals because of cases are increasing rapidly on the daily bases. So, it is compulsory to build an authentic automatic detection system which gives maximum high performance to check whether the patient is Covid-19 suspect or not as an alternative to slow down the spread of coronavirus among people.In this research, we have used deep learning’s (DL) Convolutional neural network (CNN) and ResNet models. With a critical analysis, we conclude that every ResNet layered model has the high performance with error rate less than 3% on approximately all kinds of datasets of chest Xray images whether it includes rib shadow & clivade or after segmentation. We have proposed a new solution for existing model and to enhance the ResNet model by applying layered architecture style by adding more layers to our ResNet which will help to minimize the error rate. Further, to boost the performance of ResNet by tune up the batch size and learning rate, we achieve the learning rate 0.00001 that has higher accuracy as compared to the other learning rates 0.1, 0.01, 0.001 and 0.0001. The proposed study is promising framework for the covid detection that assist us to deal the COVID decease
Tilapia Weight Estimation System Using 2D Computer Vision
Authors:   School of Information and Communications Technology, West Visayas State University-Lambunao Campus, Lambunao, Iloilo, Philippines, Garanganao Jojo C. , Ymalay Lea P. , Delima AllemarJhone P. , Arroyo Jan Carlo T.
Published: February 2023

This study aimed to develop a Tilapia Weight Estimation System using 2D Computer Vision, for the AgriAqua Research and Technology Center located at Nanga, Pototan, Iloilo, Philippines.A system estimated the weight of live tilapia, and images were captured in a free-swimming aquarium. The study established the relationship between the fish's shape and its mass in order to estimate the weight of the fish. The dataset used in the system is composed of several tilapia images acquired from specimens with weights ranging from approximately 120-250 grams. As part of the evaluation, this study determined the accuracy of three regression models: Linear, Multiple, and Polynomial regressions in estimating the weight of a freely-swimming Tilapia. In addition to the R2 and P-value, the models were also compared in terms of RMSE, MAE, MARE, MXAE, and MXRE. The system’s quality was also evaluated according to the standards for computer software set by ISO 25010 International Quality Standards
Numerical Application of Higher Order Linear Block Method for Solving Some Fourth Order Initial Value Problems
Authors: Raymond D. , Kyagya T. Y. , John S. , Lydia A.
Published: February 2023

The numerical application of higher order linear block method for the direct solution of fourth order initial value problems was proposed using the linear block algorithm, where the methods applied in block form. The method is zero-stabile, consistent and convergent when analyzing the properties of the method. The mathematical example solved using the method is effective, suitable, and acceptable for solving fourth order initial value problems. The method is also compared with existing work when solving similar systems of differential equation and obviously, the method performs better than those in literature and textual shown.
Effect of Pre-Test Drying Temperature on the Properties of Lateritic Soils.
Authors: Afolagboye Lekan Olatayo , Arije Zaccheaus Olajide , Talabi Abel Ojo , Owoyemi Olubunmi Oluwadare
Published: February 2023

The properties of residual soils, according to literature, are sensitive to the pre-test drying method given to the sample prior to testing. Similarly, residual soils such as laterites/lateritic soils are formed under various climatic conditions, hence they show different degrees of sensitivity to pretest drying method. This work is therefore carried out to elucidate the influence of pre-test drying temperature or method on the properties of three lateritic soils that developed over three different Pre-Cambrian basement complex rocks from Ado-Ekiti, SW, Nigeria. The soils were subjected to three pre-test drying temperature before conducting laboratory tests. The pre-test drying temperature considered in this study include air-drying, oven-drying at 60° C, and oven-drying at 110° C. Pre-test drying at 60° and 110° C caused particle aggregation (which reduced the soil surface are) and loss of cohesion. Consequently, this reduced the specific gravity, optimum moisture content, clay content, consistency limits, and unconfined compressive strength of the lateritic soils. The maximum dry density and sand content increased as the pre-test drying temperature increases. The pre-test drying temperature did not significantly change the plasticity classification of the soils, however, at higher pre-test temperature the soils become less plastic. The free swell index of the lateritic soils increased with increasing pre-test drying temperature (up to 60° C) before decreasing when the temperature rose to 110° C. This study has revealed the effect pre-test drying temperature may have on the properties of lateritic soils and these may produce  soil properties that may not likely indicate the actual field performance of the tested soils.
Robust M-estimators and Machine Learning Algorithms for Improving the Predictive Accuracy of Seaweed Contaminated Big Data
Authors: Ibidoja Olayemi Joshua , Shan Fam Pei , Mukhtar  , Sulaiman Jumat , Majahar Ali Majid Khan
Published: February 2023

A common problem in regression analysis using ordinary least squares (OLS) is the effect of outliers or contaminated data on the estimates of the parameters. A robust method that is not sensitive to outliers and can handle contaminated data is needed. In this study, the objective is to determine the significant parameters that determine the moisture content of the seaweed after drying and develop a hybrid model to reduce the outliers. The data were collected with sensors from the v-Groove Hybrid Solar Drier (v-GHSD) at Semporna, South-Eastern Coast of Sabah, Malaysia. After the second order interaction, we have 435 drying parameters, each parameter has 1914 observations. First, we used four machine learning algorithms, such as random forest, support vector machine, bagging and boosting to determine the significant parameters by selecting 15, 25, 35 and 45 parameters. Second, we developed the hybrid model using robust methods such as M. Bi-Square, M. Hampel and M. Huber. The results show that there is a significant improvement in the reduction of the number of outliers and better prediction using hybrid model for the contaminated seaweed big data. For the highest variable importance of 45 significant drying parameters of seaweed, the hybrid model bagging M Bi-square performs better because it has the lowest percentage of outliers of 4.08 %.