bluuebunny/crossref_metadata_2025 huggingface dataset:
A Prediction Model of Gold Price Change Against US Dollar Based on BP Neural Network
Authors: Song Junrui , Xiao Fanzhen
Published: August 2024

This project predicts the trend of gold price change against the US dollar and provides a more scientific and effective basis for investment decisions. The whole system is divided into two aspects: data visualization and BP neural network model application. For visualization and analysis, the powerful drawing function of Matlab was used for perspective drawing, and line graphs were created to show the degree of fit of the predicted values with the accurate values and the trend of change. For the BP neural network, the price prediction code based on the BP neural network was written using Matlab, and a prediction accuracy of 0.92230 was achieved by calculating the mean square error. The research results of this project provide a powerful price prediction tool based on neural network modeling, which will bring investors more accurate and objective information about price trends and provide more reliable and clearer prediction results to improve the success rate of investment.
Research on the Motivation of Competition Situation Changes Based on the Performance Score and Momentum Scoring Model
Authors: Liu Pingxin , Tian Maoliang , Dang Chenzhe
Published: August 2024

Momentum in sports, particularly in tennis, refers to the perceived shift in performance and psychological advantage that can influence the outcome of a match. It encompasses both physical and psychological aspects and is often characterized by sequences of winning points, games, or sets. In tennis match, the flow of the match tends to change based on athlete’s individual ability, real-time status and other objective factors.In these factors, a growing number of matches have shown that the effect of momentum is particularly important. To explore the influence of momentum on the flow of the match,on the one hand,the paper establishes Player’s Performance Score Model and uses it to describe the flow of match.On the other hand, the paper establishes a Momentum Scoring Model to assess the impact of momentum on the outcome of the game.
A Comparative Study of Regression Models for Housing Price Prediction
Authors: Li Zizheng
Published: August 2024

The property market is closely related to the regional economy. This study focuses on exploring the problem of house price prediction in the property market. This paper aims to reveal the performance of extreme gradient boosted tree regression, ridge regression, decision tree, and random forest regression models in feature selection and data processing, and assess their effectiveness in house price prediction. Aspects compared include prediction accuracy, data required for fitting, and running time. The study shows that the random forest and decision tree regression models perform best. Although these two models require a certain amount of data, they are easily satisfied in the context of big data. Although the fit of the random forest regression model and the decision tree regression model is similar, the training time required for the random forest regression model is too long. Therefore, it is concluded that the decision tree regression model performs well on general real estate datasets and is a widely applicable regression model in the real estate domain. This study can provide a helpful reference for data analysis and forecasting in the real estate field and provide a basis and inspiration for further research in related fields.
Study of Interaction Interface of Vehicles for Automatic Driving
Authors: Meng Zhixin
Published: August 2024

With the rapid development of the vehicle and information industries, the traditional vehicle has been transformed from a simple travel tool to an intelligent vehicle with comprehensive functions, intelligence, and rich information. As a standard function of intelligent vehicles, automated driving will greatly reduce or even replace humans for vehicle control, and the human-machine interaction system pays more attention to displaying the driving status and prompting the driver in an intuitive way, to make the driver fully trust the vehicle and obtain safe driving experience. In this paper, I study the development and current application of the interaction interface of vehicles. The main study objective is HUD (Head-Up Display). By introducing different technologies of HUDs, the study describes the examples of interaction interface of HUDs, analyzes the pros and cons of the different applications, and thus presents the direct impression and typical futuristic experience of interaction interface of vehicles. The paper also discusses the human’s natural behavior while driving and related future technology advancement is developing, and the driving environment which is the most important topic for the whole industry. The paper analyzes the interaction requirements of automated driving vehicles and summarizes the development trend of the human-machine interaction system for automated driving, which results in better understanding of interaction interface of vehicles.
Advances in Weakly Supervised Object Detection: Leveraging Unlabeled Data for Enhanced Performance
Authors: Chen Hao , Lei Sicheng , Lyu Zhengliang , Zhang Naitian
Published: August 2024

Weakly supervised object detection represents a burgeoning field within the realm of computer vision, reflecting the growing interest in developing models that can effectively identify and classify objects with minimal labeled data. This paper offers a comprehensive classification of contemporary, state-of-the-art deep learning models tailored for weakly supervised target detection. The classification encompasses four principal categories: Multi-Instance Learning (MIL), Class Activation Mapping (CAM), Deep Weakly Supervised Learning leveraging Attention Mechanisms, and Weakly Supervised Object Detection employing Pseudo-labels. Each category represents a unique approach to the challenge of discerning and localizing objects with limited supervision, emphasizing different aspects of learning from sparse or imprecise annotations. Our analysis delves into the intricate methodologies and theoretical foundations underlying these models, offering insights into their practical applications and performance metrics. Furthermore, we explore the evolutionary trajectory of these techniques, highlighting their advancements and the pivotal role they play in advancing the frontiers of automated object detection in diverse and complex environments. This synthesis not only charts the current landscape of weakly supervised object detection but also paves the way for future research directions in this dynamic and rapidly evolving field.
Measurement of Conservation Value of Ancient Buildings from the Perspective of Climate Risk Based on the Entropy Weighting Method
Authors: Shen Xuhao , Luo Guangrui , Hu Chuanxia
Published: August 2024

Modern society is characterized by high levels of human activity and pollution, triggering numerous extreme weather events. This has resulted in numerous disaster losses, and ancient buildings of conservation value are often damaged by extreme weather. To mitigate the crisis caused by the increasingly severe climate risk to the protection of ancient buildings, this paper will measure the level of exposure of ancient buildings to climate risk this paper constructs a comprehensive evaluation index system that includes eight factors affecting the level of architectural protection from the aspects of history and culture, economic and social, and natural environment. On this basis, the Entropy Weighting Method and Delphi Method are used to establish a Building Conservation Model, and the weights of the subjective and objective factors are combined to prioritize the indicators, and the model is used to help regional leaders determine to what extent measures should be taken to protect buildings. In our model, the USA ranked first with a score of 0.116, followed by China with 0.005. This paper will provide a decision-making basis for the units responsible for the conservation of ancient buildings, and help them to identify and prevent climate risks to ancient buildings.
The Application of Artificial Intelligence in Education
Authors: Sun Xinyi
Published: August 2024

Artificial Intelligence has had a huge influence on various fields since its appearance. The main focus of this paper is on the revolutionary impact of artificial intelligence on education. The major applications in the field of education are personalized learning, adaptive learning, virtual reality technology and teaching assessment. Virtual reality mainly focuses on virtual classroom, virtual laboratory, and smart campus, while teaching assessment analyzes and exemplifies self-service grading as one of the key components. Artificial intelligence technology has changed the traditional teaching and learning system by providing new modes of operation, teaching methods, and grading systems. This paper addresses the drawbacks of artificial intelligence in education while also analyzing its benefits. Despite these challenges, Artificial intelligence plays an undeniable part in educational reform, it employ novel learning styles to satisfy students’ preferences and address multiple questions. Finally, the paper anticipates the future trajectories of artificial intelligence applications in education, and offering a comprehensive summary of the entire discussion.
Advanced Analytics for Smart Cities: Integrating Real-time Data and IoT
Authors: Krishna Pasupuleti Murali
Published: August 2024

Abstract: This chapter explores the critical role of advanced analytics and the integration of real-time data and IoT in the development and management of smart cities. It delves into the fundamentals of IoT technology and its applications in urban environments, focusing on how real-time data streams from connected devices enhance city operations. The chapter also examines advanced analytics techniques, including descriptive, predictive, and prescriptive analytics, and their applications in optimizing traffic management, environmental monitoring, public safety, and resource management. Additionally, it discusses the challenges of implementing these technologies, such as data privacy concerns, scalability issues, and infrastructural barriers, while highlighting future trends like edge computing, 5G networks, and AI-driven autonomous systems. The chapter concludes by reflecting on the transformative potential of these technologies in creating more efficient, sustainable, and resilient urban environments. Keywords: Smart Cities, Advanced Analytics, Internet of Things (IoT), Real-time Data, Data Integration, Edge Computing, 5G Networks, AI in Smart Cities, Traffic Management, Environmental Monitoring, Public Safety, Smart Utilities, Sustainability, Urban Resilience, Data Privacy and Security, Predictive Analytics, Prescriptive Analytics, Autonomous Systems, Urban Management and Future Trends in Smart Cities.
PENGARUH KUALITAS PELAYANAN TERHADAP KEPUASAN MASYARAKAT PADA KANTOR CAMAT AMUNTAI TENGAHKABUPATEN HULU SUNGAI UTARA
Authors: Syahrusiani Hj. , Hendrayani Hendrayani , Sarnubi Muhammad Said
Published: August 2024

Services at the Central Amuntai Sub-District Office, have not been maximized in providing a service, namely the lack of attention and ability of employees in the form of providing information to visitors, so that misunderstandings often occur, services are less precise, and lack of socialization / direction. Research Objectives to find out the influence and magnitude between service quality on community satisfaction. The research method used is Quantitative with associative type cause and effect and explains systematically. The data collection techniques used are observation, questionnaires and documentation. Data sources were taken using the Slovin formula with simple random sampling techniques totaling 75 respondents. The results showed that the results of the Service Quality variable (X) had a significant effect on the Community Satisfaction variable (Y) at the Central Amuntai Sub-District Office, HSU Regency. This can be seen from the level of satisfaction as evidenced by the simple linear regression analysis Y = 22.294 + 0.089 X, which means that every one increase in Service Quality has an effect of 0.089 on Community Satisfaction, so there is an influence between variable X on variable Y. Meanwhile, from the results of the t test calculation, namely the tcount of 2, 438 compared to the t table (db = 73) which is 2, 379 with a significant level of 0.01, this means that tcount> t table, Ha is accepted and Ho is rejected and Ha1 is accepted. means that there is a positive and significant influence between Service Quality on Community Satisfaction at the Central Amuntai Sub-District Office of Hulu Sungai Utara Regency. To the Head of the Central Amuntai Sub-District of Hulu Sungai Utara Regency, and service officers in order to further improve the ability of employees, provide information and periodic socialization to the community.
Pemanfaatan Digital Marketing Shopee dan Shopee Live sebagai Optimalisasi Pemasaran Fashion Muslimah “Gamaleea” dalam Menaikkan Omset Penjualan UMKM
Authors: Putri Synthia Sumartini , Almini Almini
Published: August 2024

The use of digital marketing is currently being greatly utilized by micro, small and medium enterprises (MSMEs). What micro, small and medium businesses use is Shopee Live or Shopee. With Shopee, it helps people meet household needs. Like the micro, small and medium Muslim fashion business "Gamaleea" utilizing the shopee or shopee live marketplace. Data collection techniques use observation, interviews and documentation. The results of the data that researchers found were that the Muslim fashion business "Gamaleea" focused on marketing using the Shopee marketplace or Shopee Live. Shopee live is useful for increasing sales in the Muslim fashion sector.
Exploring Childhood Trauma and Coping Mechanisms Through Ferenczi’s Trauma Theory
Authors: Ubaid Ullah Jan Talha , Hussain Rubina , Hizbullah Muhammad , Ur Rahman Saeed
Published: August 2024

This paper aims to achieve objectives to deepen the understanding of the psychological effects of childhood trauma, explore practical therapeutic approaches for addressing trauma, and provide insights into coping mechanisms. The significance of this research lies in its potential to offer strategies for recognizing and healing traumatic experiences in therapeutic settings. Grounded in Ferenczi’s trauma theory, this study analyzes the traumatic experiences of the protagonist in Pelzer's novel A Child Called 'It' (1995). By examining the protagonist's use of Ferenczi’s concept of “identification with the aggressor” and other coping techniques, the findings reveal the complex dynamics of trauma and its long-term consequences, highlighting the importance of therapeutic interventions in mitigating these effects.
Elaboration of a training plan in the technical management of the copoazú crop for producers of La Vereda de Balcanes in the municipality of Florencia, Caquetá
Authors: Calderón Trujillo Brayan Stiven , Sánchez Castillo Verenice
Published: August 2024

The production chain of Amazonian fruits, such as copoazú, is gaining relevance due to its food potential and its applications in various industries. In Colombia, especially in the department of Caquetá, copoazú is presented as a business opportunity that can contribute to economic and social development, particularly in areas affected by violence and poverty. This internship focuses on developing a training plan in the technical management of the copoazú crop for producers in the Balcanes district of the municipality of Florencia, Caquetá. This plan aims to improve ecological agriculture and provide farmers with technical knowledge that will allow them to increase their productivity and improve their quality of life. The training plan will include learning modules that will address the specific needs and requirements of Copoazú farmers. A qualitative approach of a descriptive nature will be used, applying techniques such as surveys and interviews with six farmers selected for convenience. This methodology will allow for the collection of detailed data on participants' perceptions and knowledge, facilitating the design of more effective educational strategies. The study also considers the international context of copoazú cultivation, highlighting the lack of technical assistance and training in producing countries such as Bolivia and Peru. In Colombia, although copoazú has high economic and nutritional potential, producers face challenges related to technical assistance and market integration. The importance of promoting sustainable agriculture is emphasized throughout the document, aligning with the Sustainable Development Goals, such as "zero hunger", "responsible production and consumption" and "climate action". The implementation of agroecological practices and the strengthening of farmers' organizational capacity are essential to ensure sustainable development in the Amazon region. In conclusion, this internship work seeks to establish a sustainable agricultural program in the Balcanes village, optimizing copoazú crops and improving the living conditions of farmers through a technical training plan adapted to their needs and the local context.
E-government and Environmental Governance: Case Study Cuba
Authors: González Someillán Gabrielle
Published: August 2024

E-government has emerged as a key component in the evolution of public administration into the digital age. This paper examines the intersection between e-government, governance, and the environment. It explores the ways in which information and communication technologies (ICTs) can strengthen environmental governance and facilitate informed decision-making in environmental public policy. In addition, the case study Cuba, where the National Environmental Information System was developed to facilitate the collection, analysis and dissemination of environmental data in real time, with the objective of informing citizens and decision makers, is analyzed. This specific case illustrates how e-government can improve transparency, citizen participation and collaboration between governmental and non-governmental actors by promoting efficient, sustainable environmental initiatives with lasting impact
Artificial Intelligence in Psychological Diagnosis and Intervention
Authors: Águila Ramírez Lipsary
Published: August 2024

The integration of artificial intelligence (AI) in the field of psychology is significantly transforming the diagnosis and intervention of mental disorders. Deep learning techniques enable the analysis of large volumes of data, such as neuroimages and electroencephalograms (EEG), to identify and diagnose psychiatric conditions with greater precision. These technologies also facilitate early detection of risk factors by analyzing data from social networks and electronic medical records, enabling personalized interventions. AI-based chatbots and mobile applications democratize access to psychological therapy, providing real-time support and improving the management of conditions such as anxiety and depression. Additionally, AI optimizes administrative tasks and enhances the training of new clinicians through learning platforms and virtual simulators, contributing to better preparedness and efficiency in the mental healthcare system. These innovations not only improve the quality of diagnosis and treatment but also enable more proactive and patient-centered care
Comparative Study of AI Code Generation Tools: Quality Assessment and Performance Analysis
Authors: Florez Muñoz Michael Alexander , Jaramillo De La Torre Juan Camilo , Pareja López Stefany , Herrera Stiven , Candela Uribe Christian Andrés
Published: August 2024

Artificial intelligence (AI) code generation tools are crucial in software development, processing natural language to improve programming efficiency. Their increasing integration in various industries highlights their potential to transform the way programmers approach and execute software projects. The present research was conducted with the purpose of determining the accuracy and quality of code generated by artificial intelligence (AI) tools. The study began with a systematic mapping of the literature to identify applicable AI tools. Databases such as ACM, Engineering Source, Academic Search Ultimate, IEEE Xplore and Scopus were consulted, from which 621 papers were initially extracted. After applying inclusion criteria, such as English-language papers in computing areas published between 2020 and 2024, 113 resources were selected. A further screening process reduced this number to 44 papers, which identified 11 AI tools for code generation. The method used was a comparative study in which ten programming exercises of varying levels of difficulty were designed and the results obtained from 4 of them are presented. The identified tools generated code for these exercises in different programming languages. The quality of the generated code was evaluated using the SonarQube static analyzer, considering aspects such as safety, reliability and maintainability. The results showed significant variations in code quality among the AI tools. Bing as a code generation tool showed slightly superior performance compared to others, although none stood out as a noticeably superior AI. In conclusion, the research evidenced that, although AI tools for code generation are promising, they still require a pilot to reach their full potential, giving evidence that there is still a long way to go.
Classification of tomato ripeness in the agricultural industry using a computer vision system
Authors: Valencia Buitrago Mateo , Torres Vargas Olga Lucía
Published: August 2024

Machine vision systems (SVA) occupy an important place in the field of food and agriculture, these techniques are performed in situ, are efficient, non-invasive, time-saving and more economical than traditional techniques. Tomatoes (Solanum lycopersicum) are extensively cultivated throughout the world, are essential in the agricultural and culinary fields and are recognized for their beneficial contributions to health. Lack of knowledge about fruit maturity, proper harvesting and postharvest handling are factors responsible for large postharvest losses. Therefore, the objective of this research was the construction of a VAS that allows establishing relationships between color and maturity stage of the Chonto Roble F1 tomato. The VAS built is composed of hardware and software duly synchronized through the application of computer vision algorithms in Python 3.9 software that allow it to perform the acquisition and segmentation of the image and present the user with the color coordinates in the CIEL*a*b* system. Finally, color measurements were performed on tomato samples at different stages of ripening in the VAS and a HunterLab ColorQuest XE (EHL) spectrophotometer. The results obtained indicated that there are no significant differences in both measurement systems for L* values, the changes produced in b* and a* were statistically significant for tomato samples. The results obtained indicated the potential use of the constructed VAS for the determination of the degree of maturity of tomatoes in real time, in a non-invasive and low-cost way.
Artificial Intelligence as a tool for analysis in Social Sciences: methods and applications
Authors: Hernández-Lugo Marena de la C.
Published: August 2024

Artificial Intelligence (AI) transforms the social sciences by providing new methodologies and tools for data analysis. This article was based on a comprehensive literature review that analyzed the role of artificial intelligence as an analytical tool in the social sciences. It was observed that the ability of AI to process text, images, and audio in an integrated manner allows researchers to address complex problems with greater accuracy and efficiency. Multimodal tools facilitate the analysis of large volumes of data, the interpretation of financial documents, and the evaluation of facial expressions, which improves decision making in social research. Specialized databases offer access to a wide range of AI tools that optimize tasks such as literature review, data collection and visualization of results. In addition, safety and ethics in the use of AI are key priorities, with the creation of alliances and regulatory frameworks that ensure responsible and safe development of these technologies. Initiatives such as the AI Safety Alliance and the European Union's Artificial Intelligence Act set global standards for the ethical and safe use of AI, safeguarding both individuals and society at large.
Employee Perspectives on Professional Growth: A Qualitative Study of Human Resource Development Initiatives
Authors: Sirojudin Muhammad , Wijoyo Tuwuh Adhistyo
Published: August 2024

This research examines the perspectives and experiences of workers about Human Resource Development (HRD) programs in order to determine the aspects that influence engagement, satisfaction, and overall effectiveness. Employing a qualitative methodology, the study included semi-structured interviews and focus groups with personnel from several departments. The results indicate that HRD programs are most efficient when they are congruent with individuals' specific career objectives and professional requirements, and when they have sufficient organizational resources and management support. The identification of challenges such as program rigidity and lack of relevance emphasizes the need for HRD methods that are more flexible and responsive. The research highlights the need of customizing HRD programs to cater to the varied requirements of employees and adjusting to rapid changes in the work environment. The findings provide practical and effective guidance for firms to improve their HRD processes and give stronger support for employee development. Further investigation is recommended to examine the incorporation of emerging technologies in HRD and evaluate their influence on employee engagement and development.
Comparative Analysis Of The Financial Performance Of Pt. Sarana Tower Nusantara Tbk (Towr) With Pt. Telekomunikasi Indonesia Tbk For The Period 2021-2022
Authors: Widiyastuti Iin , Rahayu Fransisca Tuti , Rahayu Pidha Tri
Published: August 2024

This study aims to determine the financial condition of two companies by calculating the comparative analysis of the financial statements of PT Sarana Menara Nusantara Tbk with PT Telekomunikasi Indonesia Tbk using the calculation of financial ratios. The ratios used are liquidity ratio, solvency ratio, profitability ratio, activity ratio, and market ratio. This research is a comparative research using literature study. The type of data in this study is secondary data, namely the company's financial statements for the 2021-2022 period. Data analysis is carried out using predetermined formulas for each ratio. The results showed that the liquidity ratio, activity ratio, solvency ratio, profitability ratio, and market ratio of PT Telekomunikasi Indonesia Tbk were superior to PT Sarana Menara Nusantara Tbk. This finding indicates that PT Telekomunikasi Indonesia Tbk has better overall financial performance during the period. This study provides important insights for investors and company management in making strategic decisions based on comprehensive financial ratio analysis. In addition, this study emphasizes the importance of periodic evaluation of financial performance to identify the strengths and weaknesses of the company.
Job Satisfaction Gen-Z: A Systematic Literature Review
Authors: Anggapradja Indra Taruna , Marianti Maria Merry , Deti Regina
Published: August 2024

The study examines the importance of human resource management (HRM) in attracting, retaining, and managing employee performance. It highlights the role of HRM in organizing compensation, benefits, and creating a positive work environment to improve job satisfaction and productivity. The research focuses on Generation Z’s preferences for job satisfaction, including flexibility, work-life balance, and meaningful work. It discusses how managers must adapt to retain young employees and invest in their development and well-being. Utilizing bibliometric analysis and PRISMA guidelines, the study analyzes scientific publications to understand the factors influencing job satisfaction among Generation Z. The study concludes that job satisfaction is crucial for employee retention and creating a positive workplace culture. It suggests that businesses must adapt to the changing needs of Generation Z by focusing on employee satisfaction to improve performance and reduce turnover
Recovery from early-season chilling stress : a cas study in the maize leaf growth zone
Authors:   , Lainé Cindy
Published: August 2024

Maize (Zea mays), a globally significant staple crop, is highly sensitive to chilling stress (0-15°C). Based on the experience of breeders, maize's ability to recover from cold stress plays a pivotal role in the plant's subsequent growth and final yield, especially in regions like Europe, where cold spells are typically transient. In contrast to the direct response to low temperatures, the recovery of maize leaf growth after a transient exposure has been hardly studied. Based on this, the aim of my PhD research became to unravel the mechanisms of recovery of maize leaf growth after chilling stress.
A Study of Fuzhou’s Undergraduate Behavioural Intentions to Use Tablet Personal Computer as Replacement of Textbook
Authors: Fan Haiyang , Ahmad Rohizan , Chen Tet-Khuan
Published: August 2024

Under the background of education informatization, the traditional classroom teaching mode and student learning style are quietly changing. Based on paper textbooks can no longer adapt to the current educational concept. In order to measure Fuzhou's undergraduate’s acceptance of new information technology, this paper used Unified Theory of Acceptance and Use of Technology (UTAUT) model to explore the intention of Fuzhou's undergraduates to use tablet personal computer instead of textbook. Total of 300 respondents which selected from 6 universities were collected using simple random sampling. Correlation Test show that Performance Expectancy (r=0.421, p<0.01), Effort Expectancy (r=0.387, p<0.01), Social Influence (r=0.582, p<0.01), Attitude of Using Technology (r=0.634, p<0.01), Facilitating Condition (r=0.587, p<0.01), Self-Efficacy(r=0.635, p<0.01) were significantly related to Fuzhou’s Undergraduate Behavioral Intentions to use Tablet personal computer as Replacement of Textbook. From the multiple regression model, F (7, 292) = 59.261, 57.7% variance of the Fuzhou’s undergraduate behavioral intention to use tablet PC as replacement of textbook was explained by five predictors, namely: Effort Expectancy, Social Influence, Attitude of Using Technology, Facilitating Condition, and Self-Efficacy. Implication and limitation also discussed.
Saltwater Anglers toward Marine Environmental Threats Using Multilayer Perceptron Neural Network Framework
Authors: Chi Yeong Nain , Chi Jennifer
Published: August 2024

The data for this study extracted from the 2013 National Saltwater Angler Survey is to understand saltwater recreational anglers’ concerns to the threats of marine environment and to identify groups exhibiting common patterns of response. Concerns of marine environmental threats from these participants were examined through factor analysis which identified three reliable factors. Cluster analysis was employed to identify three prominent groups. The multilayer perceptron neural network was utilized as a predictive model in deciding saltwater recreational anglers’ perceptions toward marine environmental threats. In the architectural point of view, it showed a 13-6-3 neural network construction. The results revealed that “overfishing in commercial fisheries” contributed most in the neural network model construction, followed by “industrial pollution”, “oil and gas extraction”, “marine habitats loss or degradation”, “climate change”, and so forth. Results of this study may provide insight regarding the concerns of marine environmental threats from saltwater recreational anglers as an indicator of potential participation and behavior of saltwater recreational fisheries management.
Machine Learning Application in Car Insurance Direct Marketing
Authors: Cheng Xiaotian
Published: August 2024

Direct marketing such as telemarketing or mailing is an important method for companies to boost their business. Identifying the right proportion of target market could largely cut operational expense and improve efficiency.  In this research, a secondary dataset from a car insurance company will be used to study this problem of market targeting. Basing on existing literature study, three classifiers are picked, Naïve Bayesian, Decision Tree, and Neural Network. Some literature researches on each of the algorithm are conducted. Later modelling experiments are performed to predict whether the final customer will purchase the insurance or not.
Secured E-Examination System with Continuous Authentication to Prevent Cheating
Authors: Amkamaran Keerrthanan , Kasmin Intan Farahana , Zainal Abidin Zety Marlia , Vasudavan Hemalata
Published: August 2024

The growth of technologies over the years has been tremendous as it is significant to improve and adapt the education system based on the new norm. Besides, EExamination is getting popular among higher-education institutes in new norm. As a result, standard cheating detection approaches will no longer be completely effective in preventing cheating during exams. Therefore, this research proposes a solution to prevent students from cheating in their examination through the help of Artificial Intelligence and Continuous Authentication. To provide scientifically sound results, a sampling size of 200 respondents which consist of Lecturers and Proctors will be taking part in a survey. They will be sorted out by using the stratified sampling method. As a conclusion, this research could convince many higher education institutes to switch their physical examination to E-Examination which also avoid the possibility of spreading the infection of COVID-19
ACJS: “Anti-Crypto Jacking System” Security Development
Authors: Rafeequ Ahmed Mabrook , Kasmin Intan Farahana , Zainal Abidin Zety Marlia , Vasudavan Hemalata
Published: August 2024

Computer users globally are common targets for attackers, including for the rising threat of crypto jacking. The threat on illegal crypto mining, has been ongoing since 2017, and it has done devastating levels of damage to users and organization’s devices all around the world. Few solutions had been developed by various communities to mitigate the threat. However, there has not been a solution brought whereby a single software is able to automate the steps and processes to remove crypto jacking threat from user devices, till date. The aim of this research is to propose a single software based automated solution to eliminate the threat of crypto jacking from its users, through means of system analysis and threat removal approach by automation. At the initial stage of research, numerous surveys, analysis, and literature review will be carried out. From here, a prototype of the proposed systematic solution will be developed with the results harvest in the former stage. Finally, the proposed application will be promoted to computer users, as a step to ensure secure computer usage, and to eliminate crypto jacking.
Modern Electoral System in Malaysia using E-Voting with the Implementation of Blockchain Technology
Authors: Tong Samantha Yap Xin , Kasmin Intan Farahana , Amin Salmiah , Zainal Nur Khairunnisha
Published: August 2024

Since its independence, the electoral system in Malaysia has always been unchanged, whereby voters are asked to be present at the polling station to cast their votes. This has unfortunately led to an accumulation of countless limitations that pertains to the current voting system such as inefficiency, lack of trust and transparency, high budget for each election, etc. The time for a change may be near, and this research paper aims to propose an E-Voting system which incorporates Blockchain technology for the Malaysian electoral system. Blockchain technology is known for its security, reliability, and anonymity. The flow of this study follows a mixture of both quantitative and qualitative methodology and the selection of respondents through two separate sampling methods- stratified sampling and judgement sampling, for the citizens of Malaysia and researchers & experts in the technologies behind the proposed system.
AI Stroke Detection and Emergency Response System
Authors: Xavier Joel Francis , Kasmin Intan Farahana , Zainal Abidin Zety Marlia , Vasudavan Hemalata
Published: August 2024

Deaths caused by stroke from patients failed to seek help increases. Most of them don’t even realize they have a stroke attack in the first place. Before a stroke takes place, an arrythmia of the heartbeat takes place beforehand. Detecting that can bring awareness to an individual beforehand and overcome a stroke attack that leads to death. This research paper has the aim to propose an AI device that immediately alerts the medical authorities before a stroke attack takes place. For the target population, mainly consists of Vascular Neurologists, patients that went through stroke attacks and Telemedicine engineers. The population will be sampled using stratified sampling and dividing them into subgroups. Besides, the data collection method used is the survey approach. In conclusion, it is possible that AI Stroke Detection system which is wearable can be used in telemedicine to provide real-time monitoring and healthcare. For future recommendations, special optimized healthcare plans can be implemented in the system to suggest the patients to change their current lifestyle to a healthy one depending on their medical background.
Using Analytics to Improve Healthcare in Public Hospitals in Asia
Authors: Ying Fen Ah Hui , Hong Duy Nguyen
Published: August 2024

Big data analytics is advantageous for businesses, but implementing BDA to leverage profitability is an essential problem facing practitioners. Even though previous studies have investigated the effect that BDA has on business development, there's an absence of investigation, which describes the whole intricacy of BDA implementations. Evaluation of how and under what conditions BDA achieve organizational performance from a holistic viewpoint is lacking in the current literature. To extend the theoretical viewpoint from the standard views to the configuration concept, we've created a conceptual design of BDA achievement, which seeks to explore how BDA features communicate with complementary organizational energy and organizational abilities in several configuration treatments, leading to better quality of treatment in healthcare organizations. To evaluate this particular unit, we use fuzzy set qualitative relative analysis to analyze multi source details acquired from a survey, as well as databases maintained by the Centres for Medicaid and Medicare Services. Our results suggest that BDA, when given by yourself, isn't enough to obtain the outcome, but is a synergy result where BDA features, analytical personnel's abilities combined with organizational energy, as well as helpful function, can boost readmission fees and patient satisfaction in healthcare organizations.
INFLUENCE OF ENGLISH LANGUAGE WORDS IN TAMIL FILM SONG LYRICS CORPUS: A MACHINE LEARNING APPROACH
Authors: Vijayarangan Sabananthan , Russell Freya , Ginige Tilak , Green Iain
Published: August 2024

The use of English words in Tamil lyrics has significantly increased in recent years due to globalisation, Western cultural exposure, and the evolution of the Tamil music industry. Traditionally, Tamil lyrics used pure Tamil words, which were well-received in the early 1960s. However, the younger generation's exposure to Western influences and English-speaking media has led to a greater incorporation of English words in Tamil lyrics, reflecting broader cultural and societal changes. This blending of languages has made it difficult to classify the language of these compositions accurately.
To address this, this study proposes a machine learning model to handle code-switching and multilingual text for identifying English words in Tamil lyrics. The objectives include testing the hypothesis that modern lyrics contain more English words than earlier compositions and using an unsupervised machine learning algorithm to cluster lyricists based on their use of English and other foreign language elements. By leveraging natural language processing (NLP) methods and machine learning techniques, the study aims to analyse language usage patterns in Tamil lyrics and explore the relationship between language, culture, and society in contemporary music.
Small Object Detection in Autonomous Cars Using a Deep Learning
Authors: Chaturvedee Adarsh , Al-Shabandar Raghad , Mohammed Ammar H.
Published: August 2024

In computer vision, object detection plays a vital role in ensuring the safety of a self-driving car. The most notable example of this continuing exploration and enhancement in the field is the Google Self-Driving Car Project, currently known as Waymo. Although many prior studies have utilised several object detection models to improve the efficiency of autonomous cars, each comes with its own set of challenges. The major challenge in the development of self-driving cars is latency. The latency refers to the delay between the processing of input data captured from the camera and the decision taken by the machine learning algorithm to move and direct the car on a safe road. To address these issues, we propose a MobileNet SSD framework by hyperlinking MobileNet with SSD, making it sufficient for real-time applications. The model utilises two types of sparable convolutions, namely spatial separable convolutions and stepwise sparable convolutions. The result demonstrates the efficiency of our proposed MobileNet SSD model in reducing computational costs and decreasing latency.
Antibacterial activity of Mitragyna speciosa Korth. leaves
Authors: Niyomdecha Muhammad , Muandao Kittisak , Sanongkiet Sucharat , Jaramornburapong Chanjira
Published: August 2024

The crude extracts of red vein kratom leaves (hexane, dichloromethane, ethyl acetate, ethanol, and 50% acetic acid) and mitragynine were tested for antibacterial activity against gram-positive Staphylococcus aureus and gram-negative Escherichia coli using the disk diffusion method. The minimum inhibitory concentration (MIC) values against S. aureus and E. coli were determined. The acetic acid crude extract was effective against both S. aureus and E. coli with an inhibition zone of 5.52±0.44 and 4.65±1.02 mm, at a minimum concentration of 6 and 9 mg/mL, respectively. Mitragynine was active against S. aureus with an inhibition zone of 4.35±0.68 mm and a MIC of 6 mg/mL.
Review of improvements in upper limb function with balance training and adjunct intervention in stroke survivors
Authors: Goh Candace Xiao Huey , Ahmedy Fatimah , Yin Khin Nyein
Published: August 2024

Balance is one of the main factors influencing the ability to walk. Various rehabilitation strategies have been developed to help stroke survivors regain functional ability. However, limited evidence is available on the effects of balance training on improving upper limb function. The goal of this review was to summarize the most recent research on the benefits of balance training and adjunct intervention for upper limb function in stroke survivors. Using the search phrases “stroke” AND “balance training” AND “hand function", the PubMed and Scopus databases were used to find relevant articles. Only those published in English were chosen, while the study included randomized controlled trials held between 2012 and 2021 involving stroke survivors aged 18 and above who underwent balance training. Dissertations, case studies, and review articles were excluded. Overall, 28 of 237 articles were eligible after screening based on the eligibility criteria. Ten articles were selected for the review. The intervention and control groups had 156 and 154 participants, respectively. Core muscle exercises; adjunct interventions such as virtual reality, action observation, and resistance training; and comparisons with combination therapy were among the main types of balance training. The Fugl-Meyer assessment upper extremity and Wolf motor function test were the primary outcome measures used to evaluate upper limb function. Of the ten trials chosen, six utilized combination therapy and demonstrated noticeable improvements in upper limb function.
USAHA HOTEL GRAND KEISHA YOGYAKARTA DALAM MENINGKATKAN GERAKAN GO GREEN
Authors: Nur Afifah Adila , Anandita Arnes , Indriastuti Wahyu Ari
Published: August 2024

Penelitian ini dilatarbelakangi oleh adanya global warming atau pemanasan global akibat perubahan iklim. Hal ini sangat berdampak buruk bagi kondisi bumi dan makhluk hidup di dalamnya, termasuk manusia. Fenomena ini sangat memungkinkan menjadi sebuah fenomena yang menjadi awal kerusakan bumi ini, apabila tidak segera dibenahi. Untuk itu, sebagai manusia harus tahu dampak yang akan dirasakan jika fenomena ini terus menerus terjadi. Dampak tersebut diantaranya perubahan iklim yang ekstrim dan meningkatnya permukaan air laut. Selain berdampak pada alam, ternyata pemanasan global juga berbahaya bagi internal manusia. Hal ini dikarenakan perubahan iklim yang membuat daya tahan tubuh manusia semakin berkurang. Di lain sisi, perubahan iklim juga akan mendatangkan berbagai penyakit. Dengan adanya kegiatan go green ini, tujuannya adalah membuat masyarakat mulai tergerak untuk melakukan hal-hal yang dapat mengurangi terjadinya pemanasan global, sekaligus kembali menjadi kelestarian lingkungan.
Tujuan dari penelitian ini adalah untuk mengetahui apa saja upaya Hotel Grand Keisha Yogyakarta dalam meningkatkan gerakan go green untuk menjaga kelestarian lingkungan. Penelitian ini merupakan penelitian kualitatif. Metode yang digunakan dalam penelitian ini adalah metode deskriptif. Data primer diperoleh langsung dari sumber yang relevan terutama staf karyawan Hotel Grand Keisha Yogyakarta. Data sekunder dari referensi yang ada di Hotel Grand Keisha Yogyakarta berupa sejarah singkat perusahaan, struktur organisasi dan fasilitas hotel.
Hasil dari penelitian ini menunjukkan usaha Hotel Grand Keisha Yogyakarta dalam meningkatkan gerakan go green untuk menjaga kelestarian lingkungan adalah dengan adanya beberapa program atau kebijakan baru di hotel mengenai gerakan go green. Hal tersebut dibuktikan berdasarkan pengamatan langsung peneliti dan hasil analisis data. Dalam penelitian ini disimpulkan bahwa usaha Hotel Grand Keisha Yogyakarta dalam meningkatkan gerakan go green adalah mengedukasi tamu untuk ikut serta dalam menjaga bumi dengan gerakan go green, memaksimalkan promosi di media sosial, serta memberikan pemahaman terhadap staf karyawan dan trainee.
PENERAPAN STANDARD HYGIENE SANITASI DAN KESELAMATAN KERJA FOOD AND BEVERAGE SERVICE DEPARTMENT SHERATON TAOYUAN HOTEL TAIWAN
Authors: Pratiwi Novita , Trimo Legowo Juni , Anandita Arnes
Published: August 2024

Penelitian ini bertujuan untuk memberikan gambaran tentang penerapan standarisasi hygiene sanitasi dan keselamatan kerja di Food and Baverage Service Departement Sheraton Taoyuan Hotel Taiwan. Pokok permasalahan pada penelitian ini adalah bagaimana pengaruh dalam penerapan standarisasi hygiene sanitasi dan keselamatan kerja di Food and Baverage Service Department pada Sheraton Taoyuan Hotel Taiwan. Penelitian ini menggunakan metode kualitatif untuk menjawab dari rumusan masalah yang telah ditetapkan dan teknik yang digunakan dalam penelitian ini adalah wawancara dengan Food and Baverage Service Staff seperti Food and Baverage Director, Restaurant Manager, Restaurant Supervisor, dan Restaurant Captain. Selain itu, penelitian ini dilakukan dengan pengamatan secara langsung tentang penerapan standard hygiene sanitasi dan keselamatan kerja di Food and Baverage Service Department Sheraton Taoyuan Hotel Taiwan.
Kesimpulan yang dapat diambil pada penelitian ini adalah penerapan standard hygiene sanitasi dan keselamatan kerja merupakan cara efektif dan efisien yang digunakan untuk mengukur seberapa keseriusan pihak hotel untuk menjaga kesehatan dan keselamatan para karyawan dan tamu hotel. Hal ini dilakukan untuk menghindari risiko yang dapat membahayakan diri mereka sendiri atau orang lain.