Volume 12 | Issue 5 |

 Abstract

In the competitive job market, selecting the right candidate for a given position is crucial for organizational success.Traditional human-based hiring processes can be time-consuming, subjective and prone to biases. Machine learning (ML) has emerged as a promising tool to streamline and enhance the recruitment process, particularly in the realm of personality prediction. This paper explores the application of ML for personality prediction in job applicant screening, aiming to automate initial candidate assessment and reduce the burden on HR personnel. By discussing various feature extraction techniques and ML algorithms for personality prediction, emphasizing the importance of data quality and ethical considerations. The potential benefits of ML-based personality prediction in job screening include improved efficiency, reduced biases, and enhanced decision-making. However, challenges remain in ensuring fairness, transparency, and accountability in the implementation of these algorithms. Further research is warranted to refine ML models, address ethical concerns, and establish clear guidelines for responsible use in the hiring process.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Personality Prediction

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Evaluation as a dynamic system produces information that affordable conclusions are derived via stakeholders for decision making that expectedly effect on college students' studying consequences. The facts mining method while extracting useful, legitimate patterns from better schooling database environment contribute to proactively ensuring students maximize their academic output. This paper develops a technique by the derivation of overall performance prediction signs to deploying a simple student performance assessment and tracking machine inside a teaching and gaining knowledge of environment via specifically specializing in overall performance tracking of college students' continuous assessment (assessments) and exam ratings as a way to predict their very last achievement reputation upon commencement. based totally on various records mining techniques (DMT) and the utility of device mastering methods, regulations are derived that permit the type of college students of their predicted lessons. The deployment of the prototyped answer, integrates measuring, 'recycling' and reporting procedures inside the new gadget to optimize prediction accuracy. from the traditional measurement and evaluation strategies to the usage of DMT which employs diverse intrusive facts penetration and investigation strategies to isolate vital implicit or hidden statistics. because of the reality that numerous new technologies have contributed and generated massive explicit information, causing implicit understanding to be unobserved and stacked away inside large amounts of records. the primary attribute of records mining is that it subsumes knowledge Discovery (KD) which in step with [2] is a nontrivial process of figuring out valid, novel, probably useful and in the end comprehensible styles in statistics procedures, thereby contributing to predicting trends of results by using profiling overall performance attributes that helps effective selections making. This paper deploys idea and exercise of records mining because it relates to student overall performance and monitoring partner diploma application in a community university. Technological tendencies and new programming strategies have stepped forward expertise and use of artificial Intelligence (AI). This paper profiled students from actual and partly behavioral factors. The factual profile content material consisting of gender, date of birth, race and others like distinctive check effects from the college each semester obtained from the pupil information. performance profiling is dependent upon motivation, attitudes, peer influence, curriculum and by the ongoing real-time tracking of pupil's overall performance the use of a easy rapid response device and as [5] cited predicts successfully which student may want some attention or reinforcements in the course of their education.. The model evolved facilitates reap a measurable scholar development monitoring manner that offers consequences speedy and meets a larger instructional aim benefiting stakeholders in the educational gadget and the wider network.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

DM, DMT, KD, Decision rules, Assessment, performance monitoring, Stakeholders

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract Teaching as a profession has changed the very attitude and perception of the role of future educators in our society. Teacher trainees irrespective of whether they are studying in an undergraduate or postgraduate degree in teaching, require various skills to be able to become facilitators in the future. The present study has been conducted with an aim of finding correlation between demographic variables of age, marital status, type of institute and working status with the aspect of well-being. A total of 134 trainee teachers, from both types of institutes (government and private),were administered the Ryff scale on psychological well-being. Findings were calculated using ANOVA and t-test within the groups and between the groups on different demographics. One significant finding was t-test 0.040 indicating high well-being among trainees of a graduate teacher training programme as compared to trainees in an undergraduate teacher training programme, indicating that exposure and experiences in life contribute towards wellbeing. Findings on ANOVA revealed significant mean differences in two dimensions of wellbeing which are Autonomy, Personal Growth and overall well-being scores among trainees irrespective of their training programmes. However findings on the sample distribution indicate no significant correlation between wellbeing and age. Wellbeing needs to be looked at from psychological demographics like family life, social support and self-awareness that can bring about the much required change in the future educators.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Wellbeing, trainee teachers, female, training institutes.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The accumulation of excess body fat causes obesity, a complicated multifactorial disease with detrimental effects on health. The rate of obesity is still rising, leading to an unparalleled crisis that doesn't appear to be abating anytime soon. Elevated body mass index (BMI) is associated with a significant reduction in life expectancy and quality of life due to its role as a risk factor for noncommunicable diseases such diabetes, cardiovascular diseases, and musculoskeletal problems. Long-term energy imbalance between calories taken and calories burned is the primary cause of obesity. Here, we examine the molecular underpinnings of obesity in an effort to offer practical therapeutic approaches for achieving a healthy body weight through both nature and nurture.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Obesity,genetics,modifiable,genetics,causes,pathophysiology

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Creative Commons Attribution 4.0 and The Open Definition

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The period of the COVID-19 pandemic impacted education, especially on early childhood education aged 5-6 years. This study aims to determine the influence of pandemic situation on developing language aspects of children aged 5-6 years. Since spring 2020, parents have been working from home and children have been home from daycare and school. Parents are experiencing stress in an attempt to satisfy the demands of work, family, and COVID-19 concerns. Due to the fact that children have been home from daycare and school, parents have the sole responsibility of caring for and teaching their children until schools are able to fully and effectively meet the needs of educating students in an adapted format. This impacted different developmental areas of young children like social, cognitive language etc. Research provides a wealth of information regarding influence of COVID-19 pandemic on language development. Charnery et al. (2021) reported that the language development of children can be negatively affected and there may be language developmental delays due to the pandemic period. With this view present review study mainly focuses on the studies which revealed influence of COVID-19 pandemic on language development among preschool children.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

COVID-19, Pre School, language development, Pandemic

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Worldwide agricultural production and food security are being threatened by insects. Conventional approaches to controlling insect pests frequently include the use of chemical pesticides, which can have negative consequences on both the environment and human health. This research study outlines a development project that aims to create an agricultural self-powered intelligent insect collector-killer that is outfitted with multiple wavelength light technology in response to these difficulties. The system provides an efficient way to develop the self-powered mechanism utilising clever algorithms and renewable energy sources, the system targets specific insect pests with the least amount of damage to the ecosystem and beneficial organisms. These techniques, along with contemporary technologies, have enormous potential for quickly detecting and monitoring dangerous pests and placing them under quarantine. The paper discusses the primary attributes, purposes, and potential consequences of this cutting-edge farming instrument.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Agriculture, Environmental Concerns, Natural resources, Insect-Pest population, Self -Powered Insect Trap, Automated trap, Multiple Wavelength light.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Text-to-Image and Text-to-Video AI generation models represent groundbreaking technologies that leverage deep learning and natural language processing (NLP) to produce images and videos from textual descriptions. This paper delves into the most advanced methods in the realms of Text-to-Image and Text-to-Video AI generation. It offers a comprehensive survey of the current literature and analyzes various approaches applied in multiple studies. This includes data preprocessing techniques, types of neural networks, and the evaluation metrics utilized in this field. Moreover, the paper explores the challenges and limitations associated with Text-to-Image and Text-to-Video AI generation and outlines potential directions for future research. These models hold significant promise for applications across diverse domains such as video production, content creation, and digital marketing.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

artificial intelligence, deep learning, natural language processing (NLP), large language model, AI text-to-image generation, AI text-to-video generation, DALL-E, CogView, Imagen, NUWA, Phenaki, GODIVA.

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Creative Commons Attribution 4.0 and The Open Definition

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This study explores e-trikes as pollution-free city transport, assessing their urban commuting performance. Petrol tricycles contribute to air and noise pollution due to the combustion of fossil fuels in their engines, emitting greenhouse gases and pollutants such as carbon dioxide, nitrogen oxides, and particulate matter, which can harm both the environment and human health. Petrol tricycles rely on gasoline as fuel, derived from non-renewable fossil fuels. We designed a tricycle with a 650W motor and 24V battery for eco-friendly short to medium city trips. Switching to electric drive maintains performance and ensures comfortable rides. With around a 16km range per charge, they meet urban mobility needs while championing sustainability. Besides eco-benefits, e-trikes prioritize passenger comfort and safety through smart design and stability. Extensive testing covers energy efficiency, range, and reliability, confirming e-trikes as a viable alternative to gas vehicles. Integrating e-trikes into city transit could dramatically cut pollution and boost air quality, fostering healthier urban environments. This study advocates for e-trikes to lead green mobility efforts and shape future urban transport. Key components include a PMDC motor, Battery, Charge controller, and Throttle.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Electric tricycle, pollution reduction, eco-friendly, reliability, green mobility.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Cyberattacks on people, companies, and organizations have grown in frequency. Cybercriminals are constantly searching for efficient ways to infect targets with malware in order to initiate an attack. Millions of people use images every day all throughout the world, and the majority of users think pictures to be secure for usage, however some kinds of pictures have the potential to carry a malware payload and execute detrimental acts. The main reason JPEG is the most widely used image format is because of its lossy compression. It's applied almost everyone, from small businesses to major corporations, and is present on nearly all devices (on digital cameras, cellphones, social networking, websites, etc.). Due of their reputation for being innocuous, enormous JPEG images have a lot of potential for misuse. With the increasing prevalence of digital imagery in our daily lives, the security risks associated with image formats such as JPEG (Joint Photographic Experts Group) have become more pronounced. Malware authors are utilizing the inherent vulnerabilities in image files to conceal and disseminate malicious code, posing significant threats to individuals and organizations alike. This project aims to develop an effective malware detection system specifically tailored for JPEG images. The proposed system employs a multi-layered approach combining traditional signature-based detection methods with advanced machine learning algorithms. By analyzing the structural properties and content of JPEG files, the system can identify anomalies indicative of malicious intent. Furthermore, deep learning techniques will be utilized to train the system on a diverse dataset of both benign and malicious JPEG images, enhancing its ability to accurately detect previously unseen threats. Key components of the system include feature extraction modules, signature databases, and a robust classification engine capable of real-time scanning and detection. Additionally, the project will explore techniques for image steganography detection to uncover hidden payloads within JPEG files. Through the development and implementation of this malware detection system, users can safeguard their digital assets against evolving threats in the form of malicious JPEG images, ensuring the integrity and security of their data in an increasingly interconnected world.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

JPEG, Automatic Interpretation, Image Processing, Artificial Intelligence, Malware Detection, CNN, Deep learning.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

: Our project involves simple design of motorized handle attachment mechanism for manual wheelchair for better mobility on road. The hand bike consists of electric Hub motor, rechargeable battery, a controller electric throttle, and mechanical brakes. The design is simple, and is affordable for middle class peoples. The mechanism is designed to be safe, light weight and aesthetic look. This electric motorized handle attachment can be easily detachable from wheelchair. This explains how an electric hand bike is made within limited budget for handicapped people

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Chair, BLDC Hub motor, PWM circuit, Mild steel frame, Rechargeable battery.

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Creative Commons Attribution 4.0 and The Open Definition