bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimizing Research Article Structure and Style: Best Practices for Ensuring Clarity and Impact in Scholarly Publications
Authors: Imran Aiman , Ghufran Fazal , Shah Tahir , Ahmad Bilal , Anwar Amjad
Published: August 2024

Composing a scholarly article involves diligent work and calls for clear expression, systematic organization, and a deep knowledge of the topic. The study at hand explores ways how to write a research article. The paper also looks into how one can present results comprising tables, figures, and narratives coherently. It further provides a detailed account of the key aspects that should be observed while writing a research article, with a view of giving proper guidance on how to use the suggested techniques to analyze data and relate them to the research questions, and give proper and logical conclusions. By gathering words from many research and scholarly articles, the researchers have examined the best steps for writing any academic article. Using the CARS model, the researchers examine ways and moves that help set the steps for writing the gap for an article. The methodology section provides a detailed look at article structure and style, as well as practices for ensuring clarity, rigor, and impact in scholarly publications. The analysis and discussion section is answered, which helps the researchers understand how to situate their research findings within the existing literature. The analysis of the study shows that the study will help set researchers on the course necessary to produce important, relevant, and admirable research papers that generate a good scholarly impact on their disciplines and in the practical field of life. Improving the presentation and organization of research articles is mandatory for readers` understanding, promoting a thorough approach and increasing their impact on the readers. Future recommendations point out areas for continued research and possible places for further study.
Impact of Climate Change-Induced Flood on Women’s Life: A Case Study of 2022 Flood in District Nowshera, Khyber Pakhtunkhwa, Pakistan
Authors: Gul Shehla , Khan Nigar , Nisar Shehla , Ali Zahid , Ullah Ubaid
Published: August 2024

This study highlights the difficulties women faced during and after the 2022 climate change induced floods in district Nowshera, examining their impacts on women's health, social lives, and personal lives. A mixed-methods approach was used, combining qualitative and quantitative data. Quantitative data was collected through 50 close-ended questionnaires using a multi-stage sampling method from women over 18 who experienced the 2022 flood. Qualitative data was gathered through focus group discussions and interviews. The results show that floods severely jeopardize women's personal lives, social lives, and physical and mental health. There was a noticeable rise in waterborne infections, reproductive issues, and mental health disorders such as depression and anxiety. Socially, floods exacerbate existing gender disparities in the workforce, increase burdens, and lead to exploitation in the disaster's aftermath. Personally, women experience loss of livelihoods, long-term displacement, and disruption of daily routines, all hindering personal growth and economic stability. The research emphasizes the necessity of gender-responsive disaster management strategies that cater to women's unique needs. It calls for greater access to mental health services, programs designed to support women's economic recovery, and improved healthcare access. Rebuilding women's social networks and enhancing resilience against future floods require community-based interventions and empowerment initiatives. Integrating gender perspectives into disaster preparedness, response, and recovery efforts is essential to address these impacts holistically. This study underscores the importance of inclusive policies and practices to mitigate the negative effects of flooding on women and to foster their resilience and overall well-being.
Analysis of Socio-Economic Conditions of Working Women and the Role of Built Environment to Enhance Quality of Life in Islamabad
Authors: Mukhtar Kashif , Shujat Bhatti Omer , Aziz Iqbal Muzafar , Qasim Zainab
Published: August 2024

This research study was conducted to study the socio-economic conditions of the working women who work in the industrial sector in Islamabad and its surroundings, along with the impacts of the built environment on improving their quality of life indoors. For evaluation of the research problem, the ten factories in the Industrial area of Islamabad were selected as a population. Out of them, 150 women workers were selected as a sample for this study. For data collection, questionnaires and interview schedules were used, and after collection, the raw data was analyzed, constructed in tabulated form and narrated for better understanding. The study demonstrates that 46.0% of respondents had 35 to 50 years of age recorded with 55.33% matric education level, 68.67% of they reported married group and 50.6% of them had up to 5 years of job experience with designation 55.33% of women workers recorded with supporting group (class four) which is followed by clerical (38.67%) and officer (6.0%). The data on the relation between machines and social life showed that machines had both kinds of impacts on women workers in industries. In some places, they think that they do not do not utilize their strengths. It was also concluded that the built indoor spaces and aspects of privacy in the work environment play a vital role in enhancing the spaces for privacy and enabling higher user satisfaction in the case of women in the workforce through the architectural design of these spaces.
Effect of Personal and Organizational Factors on Female Teachers’ Job Performance in Elementary Schools
Authors: Meharunisa  , Muhammad Zafar Jam , Ullah Naeem , Mazhar Ayesha
Published: August 2024

The study aimed to analyze the “effect of personal factors and organizational factors on female teachers’ job performance in elementary schools.” The study was survey and descriptive. The QUAN-qual. method was used. The explanatory sequential technique was adopted. The cluster random sampling techniques were used for data collection. The questionnaire was developed for data collection from public sector head teachers and elementary school teachers. The validity of the questionnaire was ensured through expert opinion, and the reliability was calculated through SPSS-24 using Cronbach Alpha. Findings showed that 77% of female teachers perform dual responsibilities of household work that affect their job performance in the public sector. The mean score of 4.05 and SD 1.01 supported. Moreover, 70% of respondents agreed that female teachers’ families are unsatisfied with their jobs due to work pressure, affecting their job performance. The mean score of 3.82 and SD 1.105 supported. The majority of respondents agreed to increase salaries and to provide learning material. The study recommended that the problems of female teachers in the public sector be resolved on a priority basis.
Investigating Socio-Emotional Competence, Sleep Quality, and Work-Life Balance Among Medical Students
Authors: Nadeem Zainab , Luqman Khan Muhammad , Atta Naheed
Published: August 2024

The present study explores the interrelationships between social-emotional competence, work-life balance, and sleep quality among medical students. The study is critical because it explores the depressing factors of medical students. This research was conducted on samples of 200 Faisalabad medical university and independent medical university students. Using a cross-sectional design, data were collected via self-report questionnaires, including the social-emotional competence scale, the work-life balance scale, and the Pittsburgh sleep quality index (PSQI). Various statistical analyses, such as descriptive statistics, correlation analysis, and regression modelling, were used to analyze the data. The results revealed significant correlations between the variables, indicating that higher socio-emotional competence was associated with better work-life balance and sleep quality. Findings highlight the importance of developing targeted interventions to enhance social-emotional skills, promote work-life balance, and improve sleep hygiene among medical students. This study contributes to the growing body of literature on medical student well-being and provides actionable insights for creating more balanced and supportive learning environments for medical institutions.
Importance of social research in advertising and marketing
Authors: Camelo Mendez Nicole Rocio , Guerrero Rodriguez Maria Paula , Urbano Marta Julian Andres , Garcia Rojas Maribel
Published: August 2024

If you were asked what do you understand by advertising? Probably the first thing that would come to mind would be a commercial for your favorite brand, or maybe the advertisements you see every day around the place where you live, and mention that advertising is basically the promotion of a product in a creative way. and that is attractive to the public; Although the above does not differ in large proportions from what advertising is, it has a background that encompasses not only the colors or the jingle of a commercial that caught your attention. In reality, advertising is a process that mixes from the economic studies of its ally marketing, the spontaneity and creativity of design, to the investigation of society and its evolution. Next, we will mention the importance of the aforementioned sciences and studies in advertising; focusing on the influence that social studies have on the production of advertising strategies and pieces, connecting design and creativity, along with marketing.
Ladrill Market Dynamics And Economic Growth : Evidence From Emerging Markets
Authors: Natsir Imron , Zainuddin Yusran , Sari Yolanda , Zainudin La Ode
Published: August 2024

Labor market dynamics and economic growth are two key components that are interrelated in determining the stability and economic progress of a country. In emerging markets, significant changes in the labor market can affect the overall economic growth path. This research analyzes the relationship between labor market dynamics and economic growth in emerging markets. Using a literature study method, this study collected data from various secondary sources including academic journals, policy reports and relevant case studies during the period 2000-2023. Thematic analysis is used to explore labor market indicators such as the labor force participation rate, unemployment rate, and real wages, and their relationship to Gross Domestic Product (GDP) growth. The research results show that increasing labor force participation and decreasing unemployment rates significantly contribute to economic growth in emerging markets. Additionally, increases in real wages were found to have a positive effect on labor productivity and economic competitiveness. These findings highlight the importance of inclusive and sustainable labor market policies to promote stable economic growth in developing countries. Policy implications and further recommendations are discussed to support effective decision making by policy makers.
Analysis of Competency Development at PT Unilever Indonesia Tbk from 2020 to 2023
Authors: Rahayu Pidha Tri
Published: August 2024

This study analyzes the competency development at PT Unilever Indonesia Tbk during the period from 2020 to 2023. The data used are sourced from the company's Sustainability Report. The analysis covers the competency development programs provided, the number of employees participating, and the impact of training on employee performance. The results indicate that Unilever consistently increased its investment in human resources (HR) for competency programs, with a focus on developing technical and leadership skills, and continually evolving competency development patterns with the introduction of new training programs.
Estrategias metodológicas para mejorar el comportamiento en niños de 4 A 5 años
Authors: Vargas Caicedo Cristhian Joaquín , Ayo Ríos Erika Denisse
Published: August 2024

El estudio tuvo como objetivo general promover un ambiente educativo positivo que favoreciera el desarrollo integral de los niños en términos de habilidades socioemocionales, cognitivas y de comportamiento. Para lograrlo, se identificaron conductas problemáticas en niños de 4 y 5 años y se diseñaron e implementaron estrategias metodológicas basadas en enfoques pedagógicos y psicológicos. La metodología adoptó un enfoque mixto, combinando métodos cuantitativos y cualitativos. Se utilizaron entrevistas abiertas, cuestionarios y encuestas para recolectar datos de docentes, padres de familia y estudiantes del centro infantil “Mitad Del Mundo”. Este enfoque permitió una comprensión más completa de los factores que afectaban el comportamiento de los niños y la efectividad de diferentes estrategias metodológicas. Entre las principales conclusiones, se destacó que las estrategias metodológicas individualizadas fueron cruciales para mejorar el comportamiento en los niños. La investigación resaltó la importancia de la colaboración entre escuela y familia, y la necesidad de capacitar a docentes y padres en técnicas de modificación de conducta. Además, se subrayó la efectividad de la gamificación y la educación emocional en la mejora del comportamiento infantil. La disposición positiva de padres y docentes hacia la capacitación en nuevas metodologías representó una oportunidad valiosa para fortalecer el entorno educativo y familiar.
Electrólisis como estrategia para reducir el consumo de combustible y gases, mediante un sistema alternativo de hidrógeno
Authors: Marcillo Fabricio , Ramírez Ponce Josthyn Iván , Begnini Lucía
Published: August 2024

El objetivo del estudio fue evaluar la efectividad de la electrólisis del agua para reducir el consumo de combustible y las emisiones de gases contaminantes mediante la integración de hidrógeno en motores de combustión interna. Se utilizó una revisión sistemática de la literatura para recopilar y analizar estudios previos sobre el uso de electrólisis para la producción de hidrógeno, seleccionando artículos científicos y técnicos de bases de datos académicas con términos clave relacionados con electrólisis, producción de hidrógeno y eficiencia energética. Además, se realizaron pruebas experimentales en un motor Aveo Family 1.5 L, midiendo el consumo de combustible y las emisiones antes y después de instalar el sistema de hidrógeno. Los resultados mostraron que la implementación del sistema de electrólisis resultó en un ahorro de combustible del 5%, mejorando la eficiencia del motor de 9.5 a 9.97 kilómetros por litro, y redujo las emisiones de gases contaminantes. Estos hallazgos sugieren que el hidrógeno mejora la eficiencia del combustible y contribuye a la sostenibilidad ambiental. Sin embargo, se identificaron desafíos significativos en infraestructura y almacenamiento para la adopción a gran escala de tecnologías basadas en hidrógeno, destacando el potencial del hidrógeno como vector energético y su aplicabilidad en diversos sectores más allá del automotriz.
A Comparison of Data Mining Algorithms for Liver Disease Prediction on Imbalanced Data
Authors: Arbain Ain Najwa , Balakrishnan B. Yushalinie Pillay
Published: August 2024

Liver is one of the most important organs in the human body but due to unhealthy lifestyle and excessive alcohol intake, liver disease has been increasing at an alarming rate globally hence it calls for an immediate attention to predict the disease before it is too late. However, medical data is often associated to be imbalanced and complex. Hence, the aim of this project is to investigate the data mining algorithm to predict liver disease on imbalanced data through random sampling. Results are compared and analysed based on accuracy and ROC index. K-Nearest Neighbour (k-NN) outperforms the other algorithms such as Logistic Regression, AutoNeural and Random Forest with the accuracy of 99.794%. As a conclusion, the model proposed in this research is performing better than past researchers conducted on Andhra Pradesh liver disease dataset.
High Level Mission Assignment Optimization
Authors: Gal Oren
Published: August 2024

Our research deals with Weapon-Target Assignment (WTA) problem which is a combinatorial optimization one that known to be NP-complete. The WTA is an optimization problem focus on setting the best assignment of weapons to targets, to minimizing the total expected value of the surviving targets. In this paper, we compared different methods of Z3 and Simulated Annealing (SA) to solve the WTA problem and suggest a novel algorithm based on Deep Q Networks (DQN) method. The main advantage of the DQN algorithm since we can learn in advance what is the optimal action for every space in short amount of time. Moreover, in real time the actual assignment of weapon can be done in a lot shorter amount of time then in the SA algorithm and the Z3 as can be seen in the results presented in this paper.
Predicting Growth and Trends of COVID-19 by Implementing Machine Learning Algorithms
Authors: Vistro Daniel Mago , Farooq Muhammad Shoaib , Rehman Attique Ur , Aftab Muhammad Omer
Published: August 2024

Artificial Intelligence has absolutely revolutionized the world in which we live, and with the passing of time it advances exponentially. The applications of AI are tremendous like healthcare and medical solutions, disease diagnostics, agriculture, developing security infrastructures, Autonomous vehicles, intelligent systems, industrial manufacturing, robotics and so much more. COVID19 is a deadly virus that started from china in 2019 and started to spread rapidly and within time spread throughout various countries of world and in 2020 the world went to a huge pandemic and many lives were lost due to this deadly virus causing to a major health hazard. Moreover, in 2021 many countries experience other new forms of the Covid19 that are faster to spread and more deadly. The spread and growth need to me monitored and evaluated to control the spread.  The paper states the proposed methodology to evaluate insights of the growth rate or number of cases along with the death rate of COVID19 to getter better visualization to impose lockdown and area evacuation for population safety. Moreover, the technique will help to evaluate the trend to get better insights for behavior analysis of COVID19. This study would aid policymakers in taking the required steps in advance, such as preparing isolation wards, ensuring the supply of drugs and paramedical staff, deciding partial or complete lockdown strategies, recruiting volunteers, and developing economic strategies. Out of all techniques, Random Forest algorithm outstands others with the highest accuracy of 87.28% with precision and recall of 89% and 85% respectively.
The Effects of Fragmentation of Government Services Against Cybercrimes
Authors: Sing Yap Chee , Abd Rahman Nor Azlina , Yusof Yusnita
Published: August 2024

The rapid advancement of technologies is not without its downfall as it allows attackers to develop and carry out increasingly sophisticated scam tactics over the internet, making them hard or impossible to trace. The government is aware of this and has set out effort to reduce its effects, but the services designed to do so are fragmented due to each departments establishing their own portal over co-developing a centralized one. This paper documents the effects of the fragmentation on its effectiveness and attempts to suggest a more optimal platform based on the response of participants.
Study of AIOT in Detecting Social Engineering Attacks: Phishing and Identity Theft
Authors: Siddiqui Ateefa Rehan , Abd Rahman Nor Azlina , Shajaratuddur Harun Khalida
Published: August 2024

With the advancement of technology, the Internet is becoming ubiquitous and available to everybody. There is a plethora of websites that provide various advantages. Despite their large quantity, not all these websites are genuine. Phishing sites are websites that trick people into serving their objectives. Phishing assaults, which have been around for ages and are still a huge issue today, pose a severe threat to the cyber world. Attackers are using a variety of innovative and inventive tactics to carry out phishing assaults, which are on the rise. Web browsing’s pervasiveness in our everyday lives, however, is not without security hazards. This standard web browsing habit, along with web users’ poor situational awareness of cyber dangers, exposes them to Phishing, malware, and profiling, among other hazards. Furthermore, phishing assaults are frequently used as an attack vector or the first stage in a more complex attack in today’s security climate. The usual method of comparing websites by using a blacklist and a whitelist is ineffective. As attackers have gotten more sophisticated in concealing and redirecting URLs, they may now fool users into phishing attacks without being caught. These Phishing attacks are used to commit all sorts of criminal activities like identity theft, whether in the form of Document theft, financial fraud, or medical fraud.   As   a   result,   new   methodologies on machine learning algorithms (ML) are required to detect these phishing websites.
Filling The Gap of Attacker Behavior Analysis in Organizing and Understanding CTF Games Among Students
Authors: Kamsin Intan Farahana , Jebbr Thana , Amin Salmiah , Zainal Nur Khairunnisha
Published: August 2024

CTF games are gaining popularity in educating young cybersecurity students to train them in cyber-attack and defence. This research aims to propose an effective IoT solution to solve issues that arise from the absence of attacker behaviour analysis (ABA) in organizing and analysing CTF games as a part of students cybersecurity education. This study follows a quantitative methodology and respondents are selected by purposive judgemental sampling method to acquire knowledgeable APU students. ABA is more than relevant to cyber defence research and can positively contribute to more effective and successful CTF events.
Implementation of One-Time Password in Online Banking System Among Malaysian Bank Users to Reduce Cyber Fraud
Authors: Yi Poh Xin , Kasmin Intan Farahana , Amin Salmiah , Zainal Nur Khairunnisha
Published: August 2024

Security is a critical concern for online banking applications, and it may be accomplished via a variety of Internet technologies. This study suggests an application with increased security and efficiency to fight the fear of being scammed to reduce the threat of phishing and validate the user's identity. To increase security, one-time passwords (OTP) are used to circumvent the flaws of standard password-based systems. The report application employs basic random sampling and attempts to create stronger technology to improve the online banking system and give a platform for Malaysian banks and bank customers to build partnerships. A set of questionnaires is used to obtain raw data from a random sample of 200 Malaysian bank users from various backgrounds to examine their preferences and opinions on the use of the e-payment application. The community has benefited from the adoption of a new comprehensive application.
Securing Healthcare System with the Blockchain Technology
Authors: Ken We’rn Adriena Lim , Kasmin Intan Farahana , Amin Salmiah , Zainal Nur Khairunnisha
Published: August 2024

In the event of a cyberattack, it might cause care to be disrupted owing to software breakdowns. The inability of healthcare workers to deliver proper care may be hampered by the loss of access to health records. This proposal reviews previous studies and discusses what the current healthcare system looks like, blockchain technology, and other similar systems to understand what can be learned and drawn from. The aim of this research is to implement Blockchain Technology to the healthcare industry in Malaysia to enhance the cybersecurity of the healthcare system, thereby reducing the number of cyber-attacks in the healthcare sector. This study utilizes a quantitative methodology, with respondents chosen using complex probability stratified sampling method to gather data. Aside from that, this proposal describes how surveys and case study evaluations aid in the identification of various system specifications.
Implementation of Self-service Petrol Stations based RFID Technology
Authors: Qian Lee Zi , Kasmin Intan Farahana , Amin Salmiah , Zainal Nur Khairunnisha
Published: August 2024

Present-day, everything is digital. The entire fuel pump has a design capable of displaying the tasks of operating the pump, driving the display, measuring the flow rate, and turning off the pump. However, most petrol stations still operate manually with labor. Cash is still acceptable at the counter to fill petrol. Thus, this paper proposes the automation of petrol bunks using RFID technology as an intelligent solution to this phenomenon. Stratified sampling and questionnaires will be used to gather the information for this research. In the end, the petrol stations are expected to minimize labor by applying RFID technology. The technology for automating petrol pumps also expected less time to operate, more efficient, and deployed anywhere. It is also recommended to enhance the system's security in future research.
An application to Raise Cyber Security Awareness Among Organization Employees
Authors: Wai Hong Yen , Kasmin Intan Farahana , Zainal Abidin Zety Marlia , Vasudavan Hemalata
Published: August 2024

The cyber security attacks incidents have been growing rapidly all around the globe recently due to the growth of internet users, especially since the covid-19 pandemic started. This has caused financial and intellectual properties losses to many organizations. The aim of this research is to come up with an application which helps the organizations to combat cyber security incidents due to the lack of cyber security awareness of employees. A survey will be distributed to the target employees in the organizations selected using cluster sampling. The proposed application has included a few important features such as artificial intelligence, hands-on training with guidance, as well as the capability for the user to socialize within the application. Future recommendation of adding an admin panel to the application has also been covered.
Cybersecurity Awareness Among Teenagers and Children Using Self-Learning System
Authors: Parimalam Summetha , Kasmin Intan Farahana , Zainal Abidin Zety Marlia , Vasudavan Hemalata
Published: August 2024

This study is to research on solutions to create awareness among teenagers and children through independent learning. The cybersecurity threats faced by teenagers and children has been increasing. Research have been conducted to study the current cyber security issues that children and teenager face as well as current solutions available to educate them on cybersecurity issues. The pros and cons of current available system and ideas to innovate the current system to provide better exposure on cybersecurity awareness have been studied. Probability sampling technique with stratified sampling technique have been suggested to study the data obtained through survey forms. The results from this research will be used to design a self-learning cybersecurity education system for children and teenagers. This will ensure that healthy internet behaviors among children and teenagers from the Gen Z will be aided.
Evaluating the Effectiveness of Gamification to Increase Cybersecurity Awareness among Students
Authors: Jr Maluda Amos Alban , Kasmin Intan Farahana , Zainal Abidin Zety Marlia , Vasudavan Hemalata
Published: August 2024

Cybersecurity is a field that is in constant motion due to the nature of cyberthreats which are always finding ways to abuse vulnerable victims. The victims are not discriminated which means that even youths are being targeted – to take advantage of their lack of awareness in cybersecurity. To counter this, there are some efforts to increase awareness through gamification. This is because games are fun, interactive, and appealing to the youths, which can help motivate them to put in effort to learn. Therefore, this paper aims to create a solution that can evaluate the effectiveness of this gamification process. There will be target users that will be sampled with the proper method to choose the right respondents to get data from them through a data collection method. In the end, with this paper – the potential of gamification to meet educational objectives can be uncovered.
Password Generator and Storage
Authors: Qian Goh Wei , Kasmin Intan Farahana , Zainal Abidin Zety Marlia , Vasudavan Hemalata
Published: August 2024

In the era of social web, most of the people have their own social media account, and some even have multiple accounts. They need to maintain each of the username and password, which is not easy for everyone. So, they will use the same username and password or select the very weak password to remember easily. To solve this serious problem, this research proposes a system that can generate and store the password. The users only need to remember one master password to manage all passwords. This gives users more confidence to create strong passwords and change passwords frequently without forgetting. This research will use stratified methods for sampling and questionnaires for data collection. In conclusion, the system will allow users to use social media in a safer environment. In future recommendation, we hope that in the future most social media will adopt biometric passwords instead of current text passwords.
Review and Comparative Analysis of Routing Protocols in Network
Authors: Vistro Daniel Mago , Mahmood Ishtiaque , Rehman Attique Ur , Javed Farwa
Published: August 2024

In network correspondence, directing is the way toward moving information across network between various end gadgets. In the network of Local and Wide Area communication is an important aspect. Routings is considered as a significant interaction in network correspondence Router works with routing protocols. Different router used different routing protocols that is used for data communication. Various conventions have various qualities that makes them fit to accomplish efficient communication. According to this different routing protocol is used. The information gets across various organization geographies and various conventions working inside and outside a self-sufficient framework handles this information. Different types of protocols are used in routing procedure. The paper purpose is the give a comprehensive analysis on different types of routing protocols. In this paper, OSPF, RIP, BGP are concerned to be discussed.
RANSOMWARE: TOOL DETECTION VULNERABILITIES AND DEFENSE
Authors: Nivesse Charles Antonin , Abd Rahman Nor Azlina , Shajaratuddur Harun Khalida
Published: August 2024

Ransomware is a type of harmful software that steals personal data. Ransomware infections may be catastrophic to a person or a company, and recovery can be a complex process that may necessitate the assistance of a competent data recovery specialist. In this paper, we will investigate the instruments utilized by authorities to combat ransomware attacks. Several different types of detection tools are employed, and many of them have flaws. Traditional detection systems will find it more difficult to identify malware as it evolves, and updated models of ransomware families behave differently than their predecessors. Following a risk assessment of those tools' possible weaknesses, a business continuity and disaster recovery strategy against ransomware attacks is established. Finally, enhancements to organizational structural and functional security models employing AI-assisted detection methods are offered.
Straper: Implementation to an Online Project Collaboration Application with Project Management Tools
Authors: Jun Tam Kai , Ramiah Sathiapriya
Published: August 2024

Straper is an online collaboration application that provides project management features for the Agile project team. This paper focuses on the implementation of Straper including technical investigation, system and architecture design and system testing. Trello, Jira and Slack are chosen as the similar systems for comparison and establish the design document. There are 12 software requirements of Straper are listed out along with their package version. In the architecture design, several components are integrated to enhance the system performance and scalability including Redis Pub/Sub server, SeaweedFS and load balancer. A complete ERD is created to demonstrate the data structure in MySQL database. The implementation result of Straper for main pages are shown with description. A complete unit testing and user acceptance testing are conducted by inviting four experts from the software industry. The result of testing is satisfied and all the requirements are fulfilled.
EFTS: An Encryption File Transfer System Applying Advanced Encryption Standard (AES) Algorithm
Authors: Mahdi Omar Mahdi Eldood , Juremi Julia
Published: August 2024

Since the start of the Covid19 pandemic, most of the work has been done online, including teaching, consulting, and exchanging confidential data between coworkers. Transferring data over the internet, on the other hand, is always risky. Some data can be lost or delivered to the wrong person by mistake. When a worker types in an email address to send a confidential attachment, they might type in a letter or a number by mistake that will send the email to another person. If the data ends up in the wrong hands, the company can suffer a significant loss. Therefore, an encryption is important incase an unauthorized user obtains access to the data, they will be unable to read it due to encryption. It secures sensitive data as well as increases the reliability of client-server communication. EFTS is an encryption file transfer system, developed to ensure safe and secure data transferring over the internet and to reduce the impact cased to the companies in case of a human error.
Malware and Type of Cyber Attacks Targeting Healthcare Industry In the current era, technology has evolved into many industries. As the technology gets upgraded from time to time, the vulnerability of hardware and software do still exist and without prope
Authors: Thiruchelvam Vinesh , Jegatheswaran Reshiwaran , Vistro Daniel Mago
Published: August 2024

In the current era, technology has evolved into many industries. As the technology gets upgraded from time to time, the vulnerability of hardware and software do still exist and without proper action it may convert the vulnerability into a key for cybercriminals. Malware attack is the term that is usually being used to address attacks that are made towards individual computers. There are new types of malware attacks. These attacks are being made either to steal information or for ransom.  Sometimes the attackers would just want to access the computer to gather credential and crucial information. On the other hand, there is also attackers who would want to make money whereby they would encrypt personal files or the computer and demand the individual to pay them a ransom in order to revert their actions.
Implementation of Machine Learning to Automate the Phishing Websites Detection
Authors: Tandri Angeline , Kasmin Intan Farahana , Zainal Abidin Zety Marlia , Vasudavan Hemalata
Published: August 2024

The number of gadgets linked to the internet has increased dramatically in recent years. In comparison to other types of cyber-attacks, phishing has become the most popular in cyberspace because it leverages human flaws rather than technology vulnerabilities. In phishing assault, an internet user is duped into providing personal information, such as login credentials or credit card information, by an apparently trustworthy organization. Many researchers have recently proposed alternative ways to phishing assaults. However, they are still reliant on user engagement to progress. Therefore, this research aims at studying on how Machine learning may be used to automate the identification of phishing websites. This research will use the stratified sampling method which is applied for 150 users raging from normal users, organizations’ IT team, as well as the browser team by distributing the Online Survey. In addition, three random participants are selected to attend the interview session to validate the reliability of the online survey result. At the end of this research, an automatic detection tool is developed to achieve the aim. Furthermore, this research motivates the future work in terms of adding more functional features and also the available platforms.
Ensuring Success With Analytics in Banks and Financial Services Firms
Authors: Liu Chih-hung Mien , Meng Xie Ching Kung , Schneider Jürgen Tobias
Published: August 2024

Purpose: Big data analytics is a recently available state of the art technology with prospective company influence. Nevertheless, the roadmap for the successful implementation of its as well as the road to exploiting its essential value remains unclear. This particular analysis seeks to make a much deeper understanding of the enablers facilitating BDA implementation in the banking.
Design/Methodology/Approach: We use an integrated approach that incorporates Delphi review, interpretive structural modeling, and fuzzy MICMAC strategy to determine the interactions between enablers, which determine the achievements of BDA implementation. Our strategy uses experts' understanding and gains a novel insight into the underlying causal relations regarding enablers, linguistic analysis of the mutual impacts among variables, and including 2 innovative methods for visualizing the outcomes.
 
Findings: Our findings highlight the primary key role of enabling elements, which includes skilled and technical workforce, financial assistance, infrastructure readiness, and choosing proper major data solutions. These factors have significant driving impacts on various other enablers in a hierarchical design. The results give reliable, easy and robust insights into the characteristics of BDA implementation in banking and monetary service as an entire program, while demonstrating possible influences of all interconnected important elements.
 
Originality/Value: This analysis explores the primary key enablers for effective BDA implementation in the banking and monetary service sector. More to the point, it reveals the interrelationships of elements by calculating operating and dependence degrees. This specific exploration provides managers with an obvious strategic path toward good BDA implementation.
Implementation of Enterprise-Wide Analytics and Data Science Systems Affect Performance of Software-Based Companies
Authors: Steiberg Yosef Elazaro , Mizrachi Miriam Aleen
Published: August 2024

Big data analytics has emerged as a crucial part of review for each practitioner and academic. Despite rising possible value of BDA, many scientific studies have been performed to explore the outcome of BDA on firm efficiency. In this particular study in progress, based on the difficulties of BDA dimensions, we suggest the BDA capability dimensions consistent with the IT capability idea. BDA infrastructure capability, BDA control capability, BDA personnel capability, as well as relational BDA ability deliver the general BDA Capability idea. The study, by employing powerful capability, proposes that BDA capability impacts firm fiscal and industry performance by mediated impact of functional results. The study through vital BDA ability, as well as the effect of its on firm performance, can be used as a roadmap and load up the gap between managers' expectation of BDA and what's emerged of BDA implementation.
Analytics Can Facilitate Innovative Financial Services for Consumers in Developed Countries
Authors: Sepp Kaapo Aadelheide , Ciobanu Vasilos Ionut
Published: August 2024

Of late, the financial services industry is quickly moving far from the conventional paradigm on the complicated digital means of offering and the client. Both the facets of the fiscal service sector, The financial service providers and the customers, are going through a digital evolution. Particularly, the banking industry has evolved from a journal of financial assets and ledger entry paradigm to information and analytics driven banking operations, which subsumes online and traditional client behavior. This particular paper covers different scenarios in development, finance services, and insurance, where big data analytics is turning out to be of paramount importance and a catalyst for change. The article additionally highlights the possible benefits of new technologies, like Internet of Things, Blockchain, Robotics and Chatbots.
Smart Manufacturing with Analytics, Machine Learning and IoTs
Authors: Donga Pham Quangu , Liu Ngoc Min-hau
Published: August 2024

With all the improvement of Internet of Things, and cloud computing solutions, the quantity of information from manufacturing methods is growing quickly. With substantial manufacturing details, achievements beyond expectations are produced to the product design, manufacturing, and keep procedure. Big data analytics were a primary know-how to encourage smart manufacturing methods. To be able to completely report BDA for intelligent production systems, this particular paper offers an extensive review of associated topics such as for instance the idea of big data, unit driven and information driven methodologies. The framework, key technologies, development, and programs of BDA for smart manufacturing methods are talked about. The opportunities and challenges for future investigation are highlighted. By means of this work, it's hoped to spark new concepts in the energy to notice the BDA for smart manufacturing methods.
Implementation of Machine Learning to Automate the Phishing Websites Detection
Authors: Tandri Angeline , Kamsin Intan Farahana , Abidin Zety Marlia Zainal , Vasudavan Hemalata
Published: August 2024

The number of gadgets linked to the internet has increased dramatically in recent years. In comparison to other types of cyber-attacks, phishing has become the most popular in cyberspace because it leverages human flaws rather than technology vulnerabilities. In phishing assault, an internet user is duped into providing personal information, such as login credentials or credit card information, by an apparently trustworthy organization. Many researchers have recently proposed alternative ways to phishing assaults. However, they are still reliant on user engagement to progress. Therefore, this research aims at studying on how Machine learning may be used to automate the identification of phishing websites. This research will use the stratified sampling method which is applied for 150 users raging from normal users, organizations’ IT team, as well as the browser team by distributing the Online Survey. In addition, three random participants are selected to attend the interview session to validate the reliability of the online survey result. At the end of this research, an automatic detection tool is developed to achieve the aim. Furthermore, this research motivates the future work in terms of adding more functional features and also the available platforms.
Data Science & Machine Learning Methods for Detecting Credit Card Fraud
Authors: Haddab Daniella Maya
Published: August 2024

Abstract- Credit Card fraud is the physical loss of a credit card or the loss of sensitive information. For detection there are many machine learning algorithms that can be used. The research demonstrates several algorithms that may be utilized for determining transactions as fraud or genuine. The data set utilized in credit Card Fraud Detection was used in the study. The SMOTE technique was utilized for oversampling because the dataset was extremely imbalanced. Furthermore, feature selection was carried out as well as the set was split into 2 components, test data as well as training data. The algorithms employed in this investigation were Logistic Regression, Naive Bayes, Random Forest, and Multilayer Perceptron. The results demonstrate that each algorithm could be utilized with high accuracy for fraud detection of credit cards. For the detection of additional irregularities, the proposed model could be used.
How Retail Industry Can Leverage Social Media Analytics to Drive Consumer Loyalty
Authors: Smith Deoindre Izaak , Yakuve Christina Aliana , O’brian Braydan Ciaran
Published: August 2024

Social media has turned into a part of living for a bigger part of individuals worldwide. Companies also are using it, to easily and instantly produce as well as share info with the buyers and get gained from this seamless interaction. As a consequence of the increased both social networking platforms as well as subscribers, the want to monitor, extract, analyse and report the information being developed on these platforms has additionally increased for all the Businesses. Existing labor identifies the social media analytics progression as well as online list application; it identifies the various phases of the SMA procedure with the integration of theirs on the online list approach, difficulties, and options. SMA metrics for customer life cycle are talked about. A comparative analysis continues to be offered for various SMA programs to determine the utility of theirs to the internet retail.
Systematic Literature Review of Mixed Variables Classification
Authors: Ngu Penny , Hamid Hashibah
Published: August 2024

Classification is one of the most popular approaches that had been used in a variety of fields. There are a lot of classification methods that are applicable to classify objects into their respective groups. Among the classification methods, the location model and smoothed location model received attention when the data consists of mixed continuous and categorical variables. In this paper, classification, location model and smoothed location model are screened from the Scopus and Science Direct websites for review purposes. A total of 70 articles were chosen through the systematic review processes based on the related studies’ topics. The studies had been reviewed and discussed under the topic of classification, location model and smoothed location model in different data situations. The systematic literature review has many benefits compared to traditional literature review. The systematic review process is able to provide a defined review process and fundamental priorities that can manage research bias easily. Based on the reviews, smoothed location model outperforms the other classification techniques in terms of classification performance. However, there are not many articles that particularly discuss the application of the location model and smoothed location model in mixed variables classification. Therefore, smoothed location model is suggested to be considered in the future work for mixed variables classification situation.