bluuebunny/crossref_metadata_2025 huggingface dataset:
Trust in Business: Evaluating the Effects of Product Quality, Corporate Reputation, and Service Excellence on Customer Trust
Authors:   Management Study Program, Atma Bhakti College of Economics, Indonesia, Rahmawati Leily , . Sutianingsih ,   Management Study Program, Atma Bhakti College of Economics, Indonesia
Published: August 2024

This study aims to determine the influence of product quality, company reputation and service quality on customer trust CV. Liwansu, Grobogan Regency. The respondents in this study are customers who have purchased products on the CV. Liwansu. This study uses a quantitative approach by surveying 97 respondents. The data analysis technique used is multiple linear regression analysis. The testing technique uses the help of the SPSS 25 system. The results of the hypothesis test (t test) show that first, the product quality variable has a significant effect on the customer trust variable. Both variables of company reputation have a significant effect on the variable of customer trust. The three service quality variables have a significant effect on customer trust variables.
A critical appraisal of the parole system and its compliance with section 165 of the Constitution
Authors: Wolf Loammi
Published: August 2024

In terms of state organisation under the Constitution of the Republic of South Africa, 1996, the administration of justice, which encompasses the powers of the judiciary and the prosecuting authority, is clearly demarcated from the executive. Section 165(5) of the Constitution explicitly states that an order or decision of a court ‘binds all persons to whom and organs of state to which it applies’. Sentencing is a judicial power, and the discretion to grant parole is also a judicial power. The legislature attempted to reform the 1959 parole system, which conferred parole powers upon executive state organs, with the Correctional Services Act 111 of 1998 but failed to align the granting of parole with the constitutional norms of ss 165 and 35(2) of the Constitution. Instead, the legislature conferred these powers upon executive state organs in contravention of s 165(4). In practice, the executive is therefore usurping judicial power, although s 165(3) proscribes any organ of state from interfering with the functioning of the courts. The granting of parole cannot be transformed into some kind of ‘administrative action’ of the executive taken under s 85(2) of the Constitution. The rights of detained sentenced offenders are protected by s 35(2) of the Constitution, which offers relief for unlawful detention. Section 33 upholds just administrative action and does not apply to criminal justice.
Book Review: Anton Fagan Aquilian Liability in the South African Law of Delict: A Textbook for Students (2020)
Authors: Zitzke Emile
Published: August 2024

None
Go-Native: Kinaray-a, Mobile Learning Application Using Adaptive Algorithm
Authors: Ninia Rose M. Etorcita
Published: August 2024

In Philippines’s education, a school or educational institution integrates the language a child is most familiar with like the mother tongue or native language into the classroom lesson along with the school’s lesson such as English. This is normally the language that the child speaks at home with their family. The Department of Education (DepEd) of the Philippines gets inspiration in its inclusion of Mother Tongue-Based Multilingual Education (MTB-MLE) as a feature of the Enhanced Basic Education Program. Thus, it mandated the use of the language that the students in Grade one to three are familiar with, their first language as medium of instruction to allow them to grasp basic concepts more easily. The Go-Native app has a learning path that could help the child learn Kinaray-a which is the mother tongue of Antique as fast as they could as it offers a child friendly learning environment. Specifically, the application has two learning styles or types: visual and auditory. Additionally, this mobile based application aims to reinforce the teaching of Kinaray-a as it the ability to generate Pre-Test to assess the initial understanding of the pupil and Post-Test to measure the development of learning. In order to meet the aforementioned feature, the application uses the Adaptive Algorithm.
The Necessity to Inculcate Moral Values to the Students
Authors: Dr. R. Annam  , Mrs. Manneeswari  , Mr. G. Chellapandian  , Mr. M. Vijaakumar  , Mrs. R. Sasikala
Published: August 2024

Moral principles and ethics are necessary for success in life. One truly needs to possess a great deal of character strength in order to succeed. Professionals have been created successfully, but not humans. Tradition and moral values have not received enough attention in the current educational system.  Virtues like honesty, integrity, responsibility, respect, and empathy should be highly valued. The curriculum ought to incorporate these principles. It is the duty of educators and other staff members at educational institutions to consistently model moral behavior for pupils by acting morally and interacting with them. As a result, since students are more likely to emulate and adopt the behaviors they see their teachers and other role models modelling, it is important to establish an environment in the classroom that values kindness, respect, empathy, and inclusivity for all students. These programs can foster the development of commendable qualities through organized activities, group discussions, and self-reflection exercises. Now Rather of instilling moral principles in their children, parents are more preoccupied with their education. The majority of them are aware of what their kids get up to when they're not home. The goal of social media development was to provide a platform for interaction between individuals from various socioeconomic and cultural backgrounds. But, unfortunately, the negative impacts on youth from social media are manifold compared to the positive outcomes. This paper focuses on the need to inculcate moral values among students.
Programmes and Policies for Tribal Development
Authors: Dr. Bhimappa Rangannavar  , Nagaraj Y  , Mr. Sunil Kumar  , Gayathiri M  , Hanamant F Nayik
Published: August 2024

This paper explores the programmes and policies designed for the development of tribal communities in India. It provides an in-depth analysis of historical contexts, current policies, challenges, and their effectiveness. The study observes key areas such as education, healthcare, economic development, and cultural preservation. Highlighting successful practices and identifying gaps, this paper suggests recommendations to enhance the socio-economic conditions of tribal populations, emphasizing the importance of inclusive and culturally sensitive methods.
Blending of the Human and the Non-Human in the Poems of Seamus Heaney and Alice Oswald: An Ecological Perspective
Authors: A. Judes Jalaja  , Dr. H. Jimsy Asha
Published: August 2024

This paper examines the complex interplay between the human and non-human world in the poetry of Seamus Heaney and Alice Oswald through an ecological lens. A close reading of Oswald's inventive approach to nature poetry and Heaney's close ties to the Irish landscape, shows how both writers transcend conventional lines between the human and non-human realms. Heaney's works frequently depicts a symbiotic relationship with nature, in which the natural world has a significant influence on how humans define their earthly existence. Oswald's poetry, on the other hand, emphasizes the agency and autonomy of the natural world while negating human-centric viewpoints. This paper examines how the poets employ themes, and poetic techniques, to communicate ecological interdependence and the ethical implications of this interconnection through close readings of a few select poems. The study emphasizes the significance of literary viewpoints in tackling environmental concerns and advances our understanding of ecological consciousness in contemporary poetry by the two prominent poets of the British Isles. Analyzing the poems as samples of Eco poetry would provide an insight into how poetry becomes an agent of creating ecoconsciousness.
Enhanced Automation, Operation, And Management of Rural Water Supply Systems Using IoT Technologies
Authors: Vignesh Kumar B  , Dr.Michael
Published: August 2024

Enhancing automation, operation, and management through the integration of Internet of Things (IoT) technology in rural water delivery systems presents a revolutionary approach. The application of Internet of Things-enabled sensors and devices for real-time water quality, flow rate, and system performance monitoring is examined in this research. The system can quickly identify and resolve problems like leaks, pollution, and equipment failures by utilizing data analytics, guaranteeing a dependable and secure water supply. Furthermore, automating regular upkeep and operational duties like pump control and filter cleaning minimizes errors, cuts down on human error, and saves operating expenses. By combining centralized control and decision-making, the operation management approach enhances response times and optimizes resource allocation. This creative strategy seeks to enhance the sustainability and efficiency of rural water supply systems, providing communities with a dependable and well-managed water resource.
Public management model for user satisfaction in health centers
Authors: Tapia Villalva Jose Tomas , Carbajal Llauce Cecilia Teresita de Jesus , Pluas Moran Galo Emmanuel , Machado Rosado Frida Veruchka , Salcedo Galarza Nataly Eleonor
Published: August 2024

This study evaluated the effectiveness of a management model in public health institutions, focused on improving user satisfaction and operational efficiency. Using a quantitative methodology, data from 125 administrative and health personnel evaluations were analyzed through surveys and performance metrics, focused on service quality, accessibility, equity, responsiveness, and financial performance. The results revealed that the evaluated criteria obtained mean scores above 4 on a scale of 1 to 5, with low standard deviations, highlighting a positive and consistent perception of the management model. Specifically, a significant improvement in emergency response capacity, efficient financial management, and a positive impact on the health of the population served was observed, demonstrating the implemented model's effectiveness and contribution to the general well-being and sustainability of the public health system.
The Idea of Spatiality in Adele: A Feminist Geography Approach
Authors: Maabich Omar
Published: August 2024

Feminism is a multidisciplinary field that addresses women’s issues and interests.  The field has extended its focus to cover major aspects of women’s lives rising from society, economy, culture, and politics to geography. Feminist geography examines women’s status, interaction, and significance in a place and space. Leila Slimani’s Adele (2019) is a masterpiece that presents a genuine mode of spatiality where the interconnectedness and interplay between the physical and the digital space navigates gender-related issues. This present article addresses the idea of spatiality in Adele, and how the interconnectedness between the physical, and the digital spaces provides a holistic feminist geographical lens to discuss gender roles, inequality, and social discrimination. The study portrays how the protagonist navigates between the two realms effortlessly while exploring how places and spaces are social and gendered constructions. Initially, the digital place helped Adele to escape from the domestics, the family, and the public space, but digital escapism collapsed as it gave more intricate and complexity to the multithemed feminist issues and mode of spatiality in the narrative.
Keywords. Domestic place, digital space, feminist geography, gender roles, interconnectedness, interplay, mode of spatiality, space.
HYBRID CLOUD-EDGE ARCHITECTURES FOR AI-DRIVEN APPLICATIONS: OPPORTUNITIES AND CHALLENGES
Authors: Hajari Venudhar Rao , Paripati Lohith , Shah Jigar , Prasad Nitin , Narukulla Narendra
Published: August 2024

IoT has seen an exponential rise in the number of devices, and actual-time processing of data has become necessary, making AI-driven applications adopt hybrid Cloud-edge designs. These systems are able to process and analyze data in an optimal way using the advantages of edge and cloud computing ; moreover, they are able to face problems associated with a prolonged delay in delivery and limited bandwidth as well as data vulnerability. The prospects of utilizing hybrid cloud-edge are discussed in this paper for handling improved network capacity for data handling, faster response time, optimal usage of resources, and enhanced security. It also considers the challenges of implementing and deploying these designs, chiefly in terms of addressing concerns with risk, data coordination, and compliance. This report has been written with the intent of tackling the possible challenges and engaging in relevant recommendations which may help in optimizing the use of such architectures.
Vehicle Tracking System Approaches: A Systematic Literature Review
Authors: Alhwety Rakan Nasir H , Elfadil Nazar
Published: August 2024

The efficiency, security, and privacy of vehicle tracking systems can be improved through the development of a sophisticated real-time tracking system, the implementation of security measures to safeguard vehicles and their cargo, and the proposal of innovative solutions and best practices. This research adopts a comprehensive approach, which includes an extensive review of existing literature, the design and implementation of the tracking system, and systematic evaluations of its impact on transportation and logistics. The findings of this study demonstrate that the advanced tracking system provides accurate and up-to-date information on vehicle locations and performance, while the integration of security measures enhances the protection of vehicles and cargo. Furthermore, this research identifies the current state of vehicle tracking technology, identifies areas for improvement, and offers recommendations to advance the field. Overall, this study contributes to the progress of vehicle tracking technology by offering practical solutions, promoting data privacy, and optimizing compatibility, while also providing valuable insights into the performance and significance of these systems in the realm of logistics and transportation.
DEVELOPMENT OF ELECTRONIC LOG BOOK SYSTEM FOR STUDENTS’ INDUSTRIAL WORK EXPERIENCE SCHEME (CASE STUDY: FEDERAL POLYTECHNIC ILE-OLUJI, ONDO STATE)
Authors: K. O Adekunle , M. Ganiyu , O.Y Enigbokan
Published: August 2024

The motivations and interests of students qualifying for the Students’ Industrial Work Experience Scheme (SIWES) have been found to vary, often based on their perceptions of the program's benefits and drawbacks. The importance of an electronic logbook for SIWES cannot be overstated, as it addresses the challenges and risks associated with traditional paper logbooks. This study proposes an electronic logbook system leveraging internet technologies, offering a significant improvement over the current method. This system facilitates the digital recording of daily activities and achievements during Industrial Training (IT) placements. It allows for easy storage and retrieval of IT reports via server queries. The system's is implemented using C#, Net Core as the frontend and SQL Server as the database.
Simple Sequence of Procedures to Build IRS
Authors: AlQadi Ziad
Published: August 2024

A simple and efficient sequence of procedures to build an image recognition system will be proposed, this system will be easily used to classify any image, with any type and size. A procedure to create the image features database will be introduced, this procedure will be based on local binary patterns method, it will decrease the features extraction time and create a unique features array for each image, and this array will be used as an identifier to recognize the associated image. The second procedure will use a feedforward artificial neural network, the architecture of this ANN will be proposed and trained, the optimal ANN which minimize the mean square error between the targets and the calculated outputs, this ANN will be saved to be used in the image classification procedure. Several images will be selected, the features of each image will be extracted and save to create the image features database. This database with the required targets will used to train the ANN; various approaches will be discussed in order to achieve the optimal ANN. The created optimal ANN then will be used as a classification tool to identify the image using its features.
Formulation and Evaluation of Antiplatelet Clopidogrel Tablet using β-cyclodextrin for Solubility Enhancement
Authors: Kumre Ritesh , Bais Nidhi , Jain Sachin Kumar , Vengurlekar Sudha
Published: August 2024

Cardiovascular diseases (CVDs) are a major cause of global morbidity and mortality, necessitating effective therapeutic strategies. Clopidogrel, an antiplatelet drug, is crucial for preventing thrombotic events but suffers from poor aqueous solubility, affecting its bioavailability. This study investigates the enhancement of clopidogrel's solubility through its inclusion in β-cyclodextrin complexes prepared by the solvent evaporation method. Saturation solubility studies demonstrated that the complexes significantly improved solubility, with values of 4.5 µg/ml for formulation F1, 7.7 µg/ml for F5, and 6.2 µg/ml for F9. Tablet formulations incorporating these complexes were evaluated for physicochemical properties, including angle of repose (21.56° to 49.85°), bulk density (0.48 to 0.694 g/cm³), tapped density (0.625 to 0.834 g/cm³), Carr’s Index (16.67% to 29.09%), and Hausner’s ratio (1.2 to 1.44). Hardness ranged from 4.34 ± 0.26 kg/cm² to 6.75 ± 0.25 kg/cm², with friability between 0.2% and 0.5%. Disintegration times varied from 42 to 58 seconds. In-vitro drug release studies in 0.1 N HCl revealed that formulation F9 achieved a release of 44.89% at 2 minutes, 67.71% at 4 minutes, 84.13% at 6 minutes, and 93.21% at 8 minutes. These findings suggest that β-cyclodextrin significantly enhances clopidogrel’s solubility and dissolution, potentially improving its clinical efficacy and patient outcomes.
FORMULATION AND EVALUATION OF OPTHALMIC NOVEL IN-SITU GEL CONTAINING GANCYCLOVIR FOR THE TREATMENT OF HERPES SIMPLEX KERATITIS BY USING NATURAL GELLING AGENT
Authors: Singh Alisha , Vengurlekar Sudha , Jain Sachin Kumar
Published: August 2024

The present research work deals with the formulation and evaluation of in-situ gelling system based on sol-to-gel transition for ophthalmic delivery of an antiviral agent Ganciclovir, to overcome the problems of poor bioavailability and therapeutic response exhibited by conventional formulation Ganciclovir is an antiviral medication primarily used to treat infections caused by certain types of viruses, particularly cytomegalovirus (CMV). It was formulated as ocular in situ gel forming eye drop are using polymers such as Guar gum as a gelling agent in combination of suitable preservatives. It is a newer approach to improve easy to eye instillation residence time and enhance bioavailability, prolonged and sustained drug release. Also important in the ease of administration afforded and the decrease frequency of administration resulting in the better patient compliance and acceptance.
Synthesis of Mutual Prodrug of Mefenamic Acid and Fluroquinolones
Authors: Lovanshi Kavita , Choury Bharti , Ranjan Sanjeev
Published: August 2024

The development of mutual prodrugs is an innovative approach in medicinal chemistry aimed at enhancing the therapeutic efficacy and minimizing the adverse effects of individual drugs. This review focuses on the synthesis and pharmacological evaluation of a mutual prodrug combining mefenamic acid, a nonsteroidal anti-inflammatory drug (NSAID), and fluoroquinolones, a class of broad-spectrum antibiotics. The rationale behind this combination stems from the potential to synergistically enhance anti-inflammatory and antibacterial activities while reducing the gastrointestinal and other systemic side effects commonly associated with NSAIDs and fluoroquinolones. This paper provides an in-depth discussion on the chemical properties, synthesis routes, and mechanisms of action of mefenamic acid and fluoroquinolones. It further explores the design strategies for mutual prodrugs, highlighting the selection of suitable chemical linkers and the optimization of reaction conditions to achieve a stable and effective prodrug. The pharmacokinetic and pharmacodynamic benefits of this approach are evaluated through a review of in vitro and in vivo studies, comparing the mutual prodrug with its parent compounds. Moreover, the review addresses the challenges encountered in the synthesis and development of mutual prodrugs, including issues related to stability, bioavailability, and regulatory hurdles. The paper concludes with future perspectives on the potential of mutual prodrugs in drug development, emphasizing the need for further research to overcome current limitations and to fully realize the clinical benefits of this promising therapeutic strategy.
Assessing the Impact of Emerging Technologies on Teaching and Learning: A Review of Technology-Based Learning Environments
Authors: Clinton Nyakongo Mokaya , Ronoh Richard
Published: August 2024

There has been a change in the education dynamics due to new and emerging technologies. This has created a brand-new exciting possibility for improving teaching and learning process. This review paper is motivated by a desire to synthesize literature relating to the effect of these technologies on education, more specifically technology-enhanced learning environments. This paper provides insights into the pedagogical and learner engagement implications of new technologies, such as artificial intelligence (AI), virtual realities (VR) or mobile learning based on research. Together, the synthesis underscores opportunities and hurdles of such technology integration in educational contexts aiding guidance for educators, researchers, and policymakers to negotiate an evolving landscape of how we learn with technology.
Assessing Personnel Influences on Education Management Information System Outcomes in Nyanza Region, Kenya
Authors: Ariko Dr. Collins Oliver
Published: August 2024

Information systems are developed to enable organizations to utilize technology for effective management. The Ministry of Education (MOE) is committed to implementing the Education Management Information System (EMIS) to provide data for improved planning, policy formulation, and decision-making. Since 2004, the MOE has provided IT infrastructure, personnel training, and annual funding to District Education Officers (DEOs) to facilitate EMIS activities. Despite these efforts, an EMIS technical team survey revealed that data capture completion rates at district education offices have been low, causing delays in nationwide data processing, with Nyanza counties having the lowest completion rates. This study examined the influence of personnel factors on EMIS outcomes in the counties of Nyanza Region. Employing both correlation and descriptive survey designs, the study population included 36 District EMIS coordinators, 72 Data Capture Personnel, 36 DEOs, and the Regional EMIS Coordinator. Stratified sampling selected 29 District EMIS coordinators, 68 Data Capture Personnel, 29 DEOs, and 1 Provincial EMIS Coordinator. Data were collected using questionnaires and interview schedules. Regression results indicated that personnel factors contributed 16.9% to EMIS outcomes. Job design (beta = 0.317), gender (beta = 0.291), and age (beta = 0.223) were the best personnel predictors of EMIS outcomes. The study recommended that the MOE recruit officers specifically for EMIS activities rather than involving personnel with other commitments, and transfer the data capture process from DEOs to individual learning institutions to reduce the workload and the number of EMIS personnel at DEO offices.
A Thematic Analysis of Halaman Sidr’s Wooden Sculpture
Authors: Abdul Hamid Mohammad Fahmi , Ahmad Hisammudin , Meerangani Khairul Azhar , Hashim Siti Nurul Izza , Supah@ Supar Mohd Saharuddin , Sabu Mohd Shaharudin
Published: August 2024

In the Islamic spiritual tradition, Ulu al-Absar refers to an individual who has deep inner vision and spiritual wisdom. His observations are sourced from all the creations of Allah SWT in heaven and earth, to improve the intellectual, spiritual and physical competence of a human being. Thus, this study aims to analyze the implementation of the concept of Ulu al-Absar in the artwork of Halaman Sidr wooden sculpture. Through a qualitative approach that involves text analysis and the study of wooden sculpture, this study seeks to highlight the integration of the concept of Ulu al-Absar in the interpretation of the sculpture’s architecture. Halaman Sidr’s wooden sculpture was chosen as the subject of the study because it reflects a combination of modern aesthetics with deep spiritual symbolism and its connection with Sufism values. Analysis was done on the composition of the sculpture, the use of space, as well as the symbols applied in this work. The results of the study concluded that Halaman Sidr’s wooden sculpture art offers a new perspective related to the application of Islamic spiritual concepts in visual art. In addition, it is also able to promote a deeper appreciation of the art of sculpture in the spiritual and cultural context of Islam. This study also adds to the knowledge in the field of Islamic art and provides inspiration to artists to incorporate spiritual elements in their work.
Disambiguating Maize Policy Failure in Kenya, 2013 – 2024: A Political Economy Perspective
Authors: Kasera Odhiambo Alphonce , Osure Phennie Morghan , Oloo Bruno Charles , Odhiambo Owili Mathews , Salu Francis Odhiambo , Oguna Hemolike Omondi
Published: August 2024

This study conducts a political economy analysis of recent maize policies and programs in Kenya. It examines the persistent adoption of ineffective maize policies by the governments despite evident policy failures, which necessitate reconceptualization, reform or even termination. The research is based on desk review and policy content analysis, utilizing an interpretive methodology to present arguments and draw conclusions. Drawing on Bates’ (1981) political economy framework, the analysis unveils the political-economic dynamics shaping maize policies; concentrating on Uhuruto regime (2013-2022) and the radical policies implemented by current President Ruto during his first two years in office (2022-2024). Through four key analytical categories drawn from Bates conclusions, the paper interprets how the political contexts surrounding maize policy implementation hinder the achievement of maize food security. While existing research predominantly favors an ecological-economic-technical perspective, the study employs a political economy perspective to contextualize and explain the political motivations underpinning recent maize policy choices and the resulting persistent policy failures in Kenya. The study concludes that all maize-related decision-making and policy implementation are driven by political motivations aimed at maintaining the status quo of powerful political elites and their clients in key state-owned maize agencies. This provides their security, political survival through control of the hungry peasant masses and rent-seeking commercial maize enterprises dominating the market of agricultural factor of productions such as fertilizer dealers or companies. Study evidence shows that such a scenario is likely to continue stymying the transformation of Kenya from a food-and-feed-import-dependent country to a food-secure nation and a net food export country which it was before it experienced liberalization of agriculture. Political economy analysis thus provides a toolkit to situate the root of the country’s current maize challenges. The findings underscore the necessity of fundamental political transformation to facilitate effective maize policy outcomes. The empirical and theoretical recommendations provided in the paper shows how such a transformation may be attained.
Determinants of Job Stress among Fast Food Employees in Klang Valley, Malaysia
Authors: Ghazali Hazrina , Ying Chng Yee , Mansor Zuraina Dato’ , Othman Mohd Amar Ridham
Published: August 2024

The booming of fast-food industry in Malaysia has led to a concerning increase in job stress among fast-food employees. Hence, the purpose of this study was to identify the key determinants of job stress and its impact on fast-food workplaces. In this study, four variables were used: working environment, job insecurity, person-organization fit, and compensation and benefits. The study was conducted in fast-food restaurants in the Klang Valley area. The primary data for this study was collected through quantitative approach from fast-food employees. A total of 210 sets of self-administered questionnaires was distributed and 201 sets of questionnaires were valid with 95.7% of response. After that, all the data was analyzed through Statistical Package for the Social Sciences (SPSS) version 27. The result found that the working environment was the most influential factor contributing to job stress. Results also showed that 72.7% of respondents, perceived high levels of stress in the fast-food restaurants. It was expected that findings from this study could suggest the organizations’ top management to highlight factors that could contribute to job stress and strategize ways to overcome employees’ job stress in the long run.
Сравнение производительности PostgreSQL и ее расширения TimescaleDB
Authors: Платонова А. И.
Published: August 2024

В данной статье рассмотрена база данных PostgreSQL и ее расширение TimescaleDB. Целью данной работы является сравнение производительности баз данных при работе с большими данными. Так как в настоящее время при разработке приложений одним из первых вопросов, над которым задумывается разработчик, является выбор базы данных и время работы с ней, то данная тема остается актуальной. Для развертывания обеих баз данных использовано облачное хранилище, так как оно имеет ряд преимуществ перед развертыванием на локальной машине, и пользовательский интерфейс pgAdmin 4. Для проведения тестов сгенерирован тестовый набор данных, представляющий из себя временные ряды со значениями климатических показателей за 2011-2023 года. В статье описана структура тестовых данных, представлены параметры настройки баз данных и листинги SQL-запросов. Для каждой базы данных представлены результаты времени выполнения одного и того же запроса. Эти результаты представлены в виде гистограмм для каждого SQL-запроса, загрузки и выгрузки всего набора данных. После их анализа, представлена их интерпретация. В заключении предложены рекомендации по выбору базы данных под определенные цели.
Finite Element Analysis of Bellows Expansion Joint Under Large Deformation
Authors: Omenai Stanley
Published: August 2024

Purpose: A bellows expansion joint is a flexible connector made from a series of convolutions, also known as bellows, that can accommodate movements in a piping system. The movements can include axial compression and extension, lateral deflection, and angular rotation.
Methodology: Bellows expansion joints are used to absorb thermal expansion, reduce vibration, and compensate for misalignments in piping systems. They help to absorb tensile or compressive forces arising from expansions or contractions in the system. In this study, Finite Element Analysis (FEA) is performed on a bellows expansion joint within a piping system subjected to large deformations due to axial compression, axial tension, cyclic loading and bending loading. The deformation behaviour and stress distribution of the joint under the different loading scenarios is thoroughly investigated.
Findings: The analysis results provide significant insights into the deformation patterns, stress distribution, and strain energy within the bellows expansion joint under loading. The result of the Finite Element Analysis is validated by comparison with experimental data from literature.
Unique contribution to theory, policy and practice: A detailed 3D model of the multi-convolution bellows expansion joint is developed, and appropriate material properties assigned using Abaqus. The material model parameters are calibrated using data from literature. Non-linear static analysis is then conducted to simulate the joint's response under load.
Radius, diameter, domination number, order and minimum degree
Authors: Mafuta P.
Published: August 2024

Consider a simple graph G which is connected with given order, diameter, radius and minimum degree. Using set-theory and standard results, tight upper bounds on the domination number g (G) based on the aforementioned graph parameters are proven. The results bring to the literature new bounds on the domination number, apart from strengthening results by Henning and Mukwembi [Domination, radius and minimum degree, Discrete Applied Mathematics, 157 (2009), 2964-2968]. We show by construction that the results hold even if the graphs are highly connected. We consider only simple graphs.
Forecasting of international tourists visiting Taiwan for the purpose of leisure
Authors: Liang Yi-Hui
Published: August 2024

Forecasting is the basis of planning. Previous studies on international tourism forecasting have mostly examined international tourist arrivals. Few studies discuss international travelers for specific purposes. Tourists from Western countries are the main source of tourists for leisure purpose. Economic factors generally have a significant effect on the international tourist demand. Nevertheless in different settings, there will be different conclusions. Consequently, the study supposes the recurrent neural network with genetic algorithms and the ARIMAX model to forecast numbers of tourists to Taiwan from USA, U.K, Germany, and Australia for leisure, and analyzes economic factors. The findings can help the development of the Taiwan’ tourism industry.
Vintage intelligence : Leveraging artificial intelligence for wine production, marketing, distribution, and customer engagement
Authors: Goyal Anil Kumar , Maheshwari Alka , Vikas Sona
Published: August 2024

This study investigates AI’s diverse applications in the wine industry, enhancing production, marketing, distribution, and customer interaction. It explores AI’s role in vineyard management, market analysis, and logistics, using VOS viewer software to reveal interrelationships among key components. AI promises to revolutionize wine production, marketing, and distribution, ensuring efficiency and customer satisfaction. Embracing AI fosters industry competitiveness and adaptation to consumer trends. Understanding its benefits and challenges enables informed AI adoption, fostering innovation and industry growth.
Multi-disease detection system with X-ray images using deep learning techniques
Authors: Basha M. Suleman , Prasad K. Rajendra , Mouleeswaran S. K. , Poonia Ramesh Chandra , Sebastian Shiju
Published: August 2024

In the realm of medical diagnostics, advanced deep learning algorithms have become powerful tools for detecting and diagnosing diseases. This study introduces a groundbreaking Multi-Disease Detection System designed specifically for analyzing X-ray images. It focuses on detecting Alzheimer’s disease, brain tumors, COVID-19 infection, and pneumonia, marking a significant advancement in medical imaging analysis and clinical decision-making. The system utilizes CNN and RNN to attain unparalleled accuracy and reliability in disease detection. By processing MRI and CT scans for Alzheimer’s and brain tumor detection, and chest X-ray or CT images for COVID-19 and pneumonia detection, the framework identifies key features indicative of disease pathology. Through careful image preprocessing, noise is minimized, and features are enhanced to optimize CNN performance. Subsequently, RNNs analyze the temporal sequences of features, particularly crucial for diseases like COVID-19 with rapidly evolving symptoms. The system is trained and evaluated on a diverse dataset encompassing various disease stages and manifestations, demonstrating superior accuracy, sensitivity, specificity, and AUC-ROC metrics. This Multi-Disease Detection System represents a significant breakthrough in medical imaging, to take out healthcare specialists with a robust device for timely and accurate disease detection. By leveraging deep learning techniques, it not only improves patient outcomes but also transforms healthcare delivery, ushering in an era where early disease detection is commonplace.
Improved privacy protection technique for enhancing security of real-time video surveillance
Authors: Sivalakshmi Mallepogu , Prasad K. Rajendra , Bindu C. Shoba
Published: August 2024

This research presents an effective way for protecting privacy in video surveillance data security. This technique integrates numerous critical challenges in order to generate a public stream and a private remnant erroneous the proposed approach distorted the protected, vulnerable portion. The proposed technique is built around the following three primary concerns: recognizing information that is cognizant of privacy, safeguarding anonymity, and maintaining confidential data through video encoding. In the first stage, the Privacy Region Mask Separation approach is used to identify the portion that is susceptible to protection. The sensitive part is located using this method. Then, the Adaptive Silhouette-Blur Guided Privacy Protection Scheme (ASBGPPS) is considered for privacy protection. An improved version of the Coati optimization algorithm called SBGPPS and ICOA are both incorporated into it.. Lastly, the Storage-H.264/AVC approach is considered in order to accomplish the video encoding and secret sharing storage. Finally, we have completed the video restoration. In order to evaluate how well the proposed methodology works in comparison to more traditional methods, performance measurements are utilized.
Vocational education and candidate performance analyis
Authors: Öztürk Canan , Denizhan Selçuk , Gujrati Rashmi , Denizhan Berrin
Published: August 2024

Vocational education can create a reliable environment for both employees and employers. It allows companies to target niche markets, provide valuable content and networking opportunities. However, there is still a need to increase awareness and popularization of vocational education in industries. Vocational education is carried out by authorized institutions and is an activity that requires considerable cost and time. In this study, the factors affecting the exam performance of the candidates participating in the Vocational Qualification Certificate exams are examined. The research population consists of candidates who participated in the examination of the Bridge Crane Operator profession. Random sampling method was preferred in the selection of exams. 38-question survey was administered to 84 participants who took the exams. This analysis aims to increase awareness of the Professional Competence Certificate and to determine the factors affecting the exam performance of the candidates participating in the exam. By determining the factors, it is aimed to reduce the costs of repeating the exam after the failed exam and to prevent loss of time for both the institution conducting the exam and the candidate taking the exam. ANOVA analysis was used to measure the level of significance between demographic data and factors affecting exam performance.
Fingerprint preprocessing using FCN and U-net methods
Authors: Pan Ming-Sie , Fan Chao-Hsing , Yang Ching-Chao , Su Sheng-Gui , Cheng Yu-Hsin , Wei Nai-Chieh , Hsu Hsiang-Chen
Published: August 2024

This paper analyzes the importance of optimizing fingerprint images from the perspective of front-line forensics personnel. Due to defects such as fingerprint ridge blurring and fingerprint image overlap, it may cause delays in fingerprint identification and lead to misjudgments (false positives, false negatives) and other consequences. This paper simulated common fingerprint images (fuzzy feature points) at criminal cases, and captured, segmented, and reconstructed fingerprints. Two deep learning model architectures, U-net [1] and FCN [2], were applied to realize image segmentation and image reconstruction. The first task is fingerprint image segmentation, where the fused images are segmented into incomplete fingerprints. The second task is to reconstruct the complete fingerprint from the image obtained after segmenting the incomplete fingerprint. Field verification for fingerprint image reconstruction and separation on red envelope were carried out. Ethyl cyanoacrylate method is used to visualize paper latent fingerprints and would produce “white” fingerprints, which is not easily distinguished from the red background. The pre-processing of fingerprints on red paper background is the key to the accuracy of fingerprint recognition. U-net image processing technology demonstrates the contributions of the forensic personnel in processing fingerprint images are as follows: [1] Improve efficiency. [2] Reduce misjudgment.
Optimizing energy consumption in deep learning models using pruning and quantization techniques
Authors: Al-Alshaikh Halah A.
Published: August 2024

Within the past few a long time, the broad utilize of profound learning models has driven to huge enhancements in numerous regions. Be that as it may, their tall handling needs are still an issue, particularly in places with restricted assets. This think about tries to unravel these problems by proposing a better approach to utilize trimming and quantization together to form profound learning models utilize the slightest sum of energy conceivable. By carefully evacuating unnecessary links or parameters from the organize, pruning brings down the sum of work that should be done on the computer, and quantization reduces the model’s parameters to less exact representations, which assist brings down the sum of memory and work that should be done on the computer. By integrating these strategies, it conserves energy without compromising performance. In this paper, the test results demonstrate that the proposed strategy performs well with various deep learning models and datasets. Moreover this paper appears the qualities and shortcoming of the tradeoffs between show exactness and energy reserve funds, appearing how they may be utilized within the genuine world. Generally, this consider includes to the continuous work of making profound learning models that utilize less energy, which makes a difference with natural issues and makes it conceivable to utilize AI frameworks in places with restricted assets.
An optimization approach for real-time object detection in IoT devices through edge computing and deep learning
Authors: Poonia Ramesh Chandra , Almakki Riyad , Saudagar Abdul Khader Jilani , Altameem Abdullah , Albathan Mubarak
Published: August 2024

Real-time protest acknowledgment in IoT gadgets is vital for numerous employments, but it can be difficult to do since they do not have a part of computing control. To bargain with these issues, this ponder recommends a way to move forward things that employments edge computing and profound learning. By utilizing edge gadgets, handling is moved closer to the sources of information, which brings down delay and moves forward security. Convolutional neural networks (CNNs) are utilized to discover objects, but they got to be optimized some time recently they can be utilized on gadgets with restricted assets. Our strategy centers on diminishing the measure of the show, speeding up thinking, and utilizing less vitality. Edge computing and profound learning are utilized together to grant IoT gadgets the capacity to recognize objects in genuine time. This makes it conceivable for employments like observing, self-driving cars, and mechanical robotization. The recommended strategy precisely and rapidly finds objects, and comes about of tests appear that it works whereas diminishing the sum of work that ought to be done on central computers. By making adaptable and quick protest acknowledgment frameworks conceivable, this work makes a difference to create IoT situations more intelligent and more proficient.
A detailed examination of LSTM networks for large-scale text generation with optimizing sequence models
Authors: Poonia Ramesh Chandra , Almakki Riyad , Saudagar Abdul Khader Jilani , Altameem Abdullah , Albathan Mubarak
Published: August 2024

It discover long-range connections in direct information, Long Short-Term Memory (LSTM) systems have gotten to be valuable for making huge sums of content. We take a near see at LSTM systems in this think about, particularly how they can be utilized and moved forward for content era assignments. In this paper, we see into the structure of LSTM systems and appear their one of a kind capacity to memorize and keep in mind things over long arrangement of occasions. Our investigate moreover looks into the problems that come up after you attempt to prepare LSTM systems to make huge sums of content, such as over fitting and vanishing slants. To bargain with these problems, we see into distinctive optimization strategies, like dropout regularization and slope clipping, to form LSTM-based text creation models more steady and viable. In expansion, we see into ways to fine-tune hyper parameters to urge the most excellent comes about. We appear that LSTM systems can make consistent and valuable content in a assortment of settings by doing a parcel of tests on diverse content collections. These tests cover a wide extend of employments, such as dialect modelling, discussion era, and imaginative composing. Our finding about educate us a parcel approximately how to construct and progress LSTM-based grouping models for large-scale content era assignments. This opens the entryway to indeed more advance in AI and characteristic dialect preparing.
A Filter-Based Feature Selection for Robust Phishing Attack Detection using XGBoost
Authors: Isaac Dawandakpoye Ohwosoro
Published: August 2024

Phishing attacks are a pervasive cyber threat that has grown in sophistication and scale, presenting significant challenges to cybersecurity professionals. To effectively combat phishing, robust detection mechanisms are crucial, and machine learning has emerged as a powerful tool for this purpose. This study addresses the challenge of creating a fast and reliable framework to counter phishing attacks. We introduce a novel approach that integrates filter-based feature selection methods with the XGBoost algorithm. XGBoost is chosen for its high computational efficiency, outperforming other gradient boosting techniques by a factor of ten, while mutual information gain is used for rapid initial feature selection. Our proposed framework achieves outstanding performance, with an accuracy of 97.0%, precision of 96.3%, recall of 96.5%, F1-score of 96.6%, and ROC AUC score of 99.6%. These results demonstrate the framework's capability to effectively detect and mitigate phishing attacks, providing a timely and powerful tool for enhancing cybersecurity defenses
AI Teachers Using a VR/MR Environment for Greater Student Interaction and Immersion
Authors: F L.M. Escobedo
Published: August 2024

The transmission of knowledge has been a fundamental tool throughout the history of humankind, where each generation imparted and improved the knowledge and skills of the previous one. However, at certain times in history, some individuals attempted to monopolize this knowledge to gain advantages over their peers, thus restricting access to knowledge. As societies grew and diversified, it became evident that collaboration between individuals from different backgrounds and cultures accelerated and enhanced the expansion of knowledge. This process was further enhanced with the arrival of technological revolutions, such as the internet. Currently, artificial intelligence represents a new technological revolution that, if used properly, can produce better prepared individuals equipped with the best tools in history of humanity to expand and improve the knowledge acquired