Volume 12 | Issue 5 |

 Abstract

In today's rapidly evolving job market, recruitment processes are undergoing significant transformations driven by technological advancements and changing workplace dynamics. The emergence of virtual interviews, alongside traditional in-person interviews, presents recruiters and organizations with new opportunities and challenges in identifying and assessing talent. However, there exists a gap in understanding how interviewees perceive and experience these different interview formats, with most published research focusing on employers' viewpoints. Therefore, the overarching goal of this study was to fill this gap by examining the preferences, perceptions, and experiences of interviewees participating in virtual and in-person interviews. This study delves into the comparative analysis of contemporary virtual interviewing practices and traditional in-person interviews from the perspective of interviewees.

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Key Words: workplace dynamics, interviews

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This paper presents the design and implementation of a news aggregator mobile app developed using Java and PHP, featuring an integrated admin panel for efficient content management and user engagement monitoring. The app consolidates news from various sources, offering a personalized and streamlined reading experience for users. Java was used for the mobile app development to leverage its robustness and performance capabilities, while PHP was utilized for backend services, including data management and API integration. The admin panel provides comprehensive control over content, user data, and system settings, facilitating effective administration. The development process followed a user-centered design approach, with iterative testing to ensure functionality and usability. Results indicate the app's effectiveness in delivering relevant news and the admin panel's efficiency in managing operations, demonstrating the potential to enhance modern news consumption.

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News Aggregator, Mobile App, Admin Panel, Java, PHP, API Integration, User Experience, Content Management.

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In many developing nations, the use of steel as a construction reinforcement is steadily rising. However, due to cost and availability considerations, there's a growing need to find suitable replacements for steel. In cases where steel production falls short of meeting demand, having a viable alternative that rivals steel's qualities becomes imperative. Bamboo emerges as a promising alternative to steel in small-scale construction and affordable housing, especially in countries like India, due to its abundance and durability. It can effectively serve as a substitute for steel in reinforcement, offering commendable tensile resistance, a crucial requirement for such applications. The inherent strength of bamboo, stemming from its natural tubular structure that withstands wind forces well, makes it a viable option. Addressing bamboo's weaknesses and promoting its innovative use as a steel replacement presents a valuable opportunity. This research intends to perform a literature analysis to evaluate the practicality of utilizing bamboo as a reinforcing material in concrete constructions, while significant investigation has been carried out on the strength attributes of metal-reinforced concrete, comprehensive knowledge on bamboo-reinforced concrete is insufficient. Hence, this research seeks to offer preliminary understanding of the strength features and behavior of bamboo reinforced concrete, particularly in addressing challenges related to affordable shelters.

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Strengthening Material, Bamboo, mechanical properties, strength

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The landscape of banking has undergone a transformative paradigm shift with the advent and widespread adoption of digital technologies. This study conducts a comprehensive investigation into financial fraud, aiming to elucidate the root causes, assess existing tools, and propose effective strategies for safeguarding financial systems. In a contemporary landscape marked by technological advancements, financial fraud's prevalence substantially threatens global financial stability. The study delves into the multifaceted factors contributing to financial fraud, evaluating the efficacy of current tools, and proposing innovative measures to fortify the resilience of financial systems. examines the rapid development of digital banking and how it has affected conventional banking positions in significant ways. Along with streamlining banking procedures, these developments have opened the door for new customer-focused services, improved security measures, and more individualized financial experiences. Digital banking has emerged as a force for change, transforming consumer interactions, operational strategies, and the financial ecosystem, as technology advances. The impact on customer behavior and expectations is also a focal point, as the convenience of digital banking services has shifted consumer preferences and raised the bar for user experience standards. Financial institutions are now compelled to innovate continually, adapting to a landscape where digital channels play a central role in delivering financial products and services.. The paper is structured to unfold a nuanced understanding of the problem, offering actionable recommendations to preserve trust and integrity in financial ecosystems. Data breaches can result in financial fines and erode consumer confidence (Ponemon Institute, 2020). Ransomware assaults may essentially hinder bookkeeping exercises, including administration conveyance and monetary exchanges (Jartelius, 2020). Insider gambles arise when workers purposefully or inadvertently reveal touchy monetary data (Le and Zincir Heywood, 2019). Bookkeeping firms should have network protection techniques to lessen risk. This article checks out at ideas and best practices for expanding information assurance.

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Financial Frauds, BFSI, AI, ML, ATM banking, Mobile Banking, Internet Banking

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In our comprehensive agricultural project, we tackle the pivotal challenge of crop yield prediction by leveraging advanced machine learning methodologies. Our innovative approach integrates soil image recognition and a range of pertinent parameters to forecast the most suitable plant types for specific soil conditions. To establish robust predictive models, we have deployed baseline algorithms such as Random Forest (RF) for building crop yield prediction model and Convolutional Neural Networks (CNN) for soil image recognition model, enhancing our predictive capabilities and enabling more accurate insights.We have developed a sophisticated computer vision-based soil type recognition model, enabling seamless input of soil data through image processing. This user-friendly interface streamlines data acquisition and analysis processes, ensuring accessibility for farmers and policymakers alike to provide them with the optimal crop to be selected to maximize the yield and profit. Through this multifaceted approach, our project aims to empower agricultural stakeholders with invaluable insights, facilitating informed decision-making and fostering sustainable practices in agriculture.

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Machine Learning, CNN, Random Forest, Feature Engineering, Computer Vision.

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This research is motivated by teacher performance Darulgoh Wadda'wah Islamic Boarding School. The aim of this research is to determine the influence of the relationship betweencompetence and organizational citizenship behaviour can have an impact on teacher performance is moderated by the organizational culture of Pondok Pesantren Darulgoh Wadda'wah (Dalwah, Bangil, Pasuruan). Grand theory This research is theoreticalTheory of Planned Behavior (TPB). The sampling technique uses a formulaslovinwith an error rate of 5%. The sample in this study was 232 teacher respondents Darulgoh Wadda'wah Islamic Boarding School through an independent survey. This research instrument uses a questionnaire and is analyzed using SEM analysis, the analytical tool for this research isSmart PLS version 3.0. These analytical tools are used to analyzeouter model, inner model and hypothesis testing with usep-value. The research results show a direct influence of competenceinfluentialsignificantly against to performance of Darulgoh Wadda'wah Islamic Boarding School teachers. Connection organizational citizenship behaviour influentialsignificantly against to performance of Darulgoh Wadda'wah Islamic Boarding School teachers. The results of this research indicate that there is an influence of the moderating variable, namely organizational culture, on relationshipscompetence dan organizational citizenship behaviour against against performance of Darulgoh Wadda'wah Islamic Boarding School teachers. This research shows that practice competence, organizational citizenship behaviour and organizational culture plays an important role in encouraging the performance of Darulgoh Wadda'wah Islamic Boarding School teachers.

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Competence, Organizational Citizenship Behavior, Organizational Culture and Teacher Performance

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Urban infrastructure has undergone a transformation thanks to the Internet of Things (IoT), and one important use that has improved urban transportation is smart parking systems. An Internet of Things (IoT)-based smart parking system that aims to reduce the problems related to parking in cities is examined in this abstract. The system uses internet and sensor technologies to track parking space availability in real time. Parking spots may be easily located and reserved by drivers using an easy-to-use smartphone application that provides real-time information. By optimizing parking space utilization, data analytics integration lowers emissions and traffic. Administrators can also make educated decisions about urban planning thanks to the system's insights regarding parking habits. In addition to improving user convenience, this Internet of Things (IoT)-based Smart Parking solution helps to build smarter, more sustainable urban settings.

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Urban infrastructure, Internet of Things (IoT), smart parking systems, urban transportation, parking problems, real-time tracking, sensor technologies, parking space availability, smartphone application, real-time information, parking spot reservation, parking space optimization, emissions reduction, traffic reduction, urban planning, parking habits, user convenience, sustainable urban settings, data analytics, smart city initiatives.

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The Soil and Water Assessment Tool (SWAT) is a comprehensive, river basin scale model developed to quantify the impact of land management practices in large, complex watersheds. SWAT has been widely adopted for assessing hydrology, sedimentation, and agricultural chemical yields in diverse landscapes under varying management policies. This review synthesizes over three decades of research involving SWAT, highlighting its development, applications, challenges, and future research directions. The discussion is framed around its utility in addressing emerging environmental issues, enhancing model accuracy, and integrating with other technological advances. The Soil and Water Assessment Tool (SWAT) is a well-regarded eco-hydrological model that has seen widespread application in watersheds worldwide. This review focuses on more than two decades (2002-2022) of SWAT studies across watersheds, where a total of 260 articles were identified since the model's initial application in this region in 2002. Remarkably, 62% of these studies were conducted in Greece, Italy, or Spain, and 86% of the reviewed papers were published in the last decade, highlighting a significant uptick in research activity. The primary aim of most studies was to evaluate SWAT's suitability for specific Mediterranean catchments. Many of these studies included detailed calibration and validation processes and reported on model performance outcomes. In the Mediterranean context, SWAT has predominantly been used for assessing water resources in terms of both quantity and quality, and for evaluating the hydrological and environmental impacts of land use and climate change. However, there is a growing trend toward using SWAT for multiple purposes, demonstrating the model's adaptability. Numerous studies have effectively employed SWAT alongside other tools and techniques, showcasing its versatility. Additionally, several studies have undertaken constructive comparisons of responses across Mediterranean watersheds or between SWAT and other modeling approaches.

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SWAT ANALSIS , LULC BHIMA WATERSHED

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Water contamination has long been a source of worry in the environmental community. Most bodies of water, such as rivers, lakes, and streams, are extremely contaminated. Floating wastes are a significant cause of pollution. To remove the floating garbage, machines have been devised. Any such machine may necessitate the use of some form of power, which is once again uneconomical. As a result, we decided to design a machine that would be simple and inexpensive, as well as not require any external power source. Given that a moving river or stream creates water heads at various points along its route of flow, it was determined to employ the available heads to generate hydropower that could be used to power a suitably built machine. The requirement for human labor to remove garbage might endanger the individual. As a result, a robot that cleans garbage from the water independently can have a substantial influence on pollution control. However, properly developing such a robot is a difficult challenge. The design and analysis of a river cleaning robot are presented in this work. The mechanism is intended to perform various functions such as collecting floating garbage, underwater inspection, and so on. The robot is made up of a frame, a cylinder hull, thrusters, and large waste disposal arms.

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ECO-AQUA CLEAN:WATER POLLUTION SOLUTION

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Cyber threats continue to proliferate Virtual Private Networks (VPNs) have become a ubiquitous tool for securing online communications. However, the widespread use of VPNs has inadvertently led to an increase in malicious actors exploiting VPN servers as gateways for launching attacks, posing a significant challenge for effective threat detection and mitigation. This abstract introduces a groundbreaking approach named Stealth Tracking designed to identify and thwart attacks originating from VPN servers. Stealth Tracking employs an innovative combination of advanced machine learning algorithms and network traffic analysis techniques to detect anomalous patterns indicative of malicious activities, while minimizing false positives. This paper details the comprehensive methodology of Stealth Tracking, covering aspects such as data collection, feature extraction, model training, and real-time monitoring, essential for the successful implementation of this approach. The experimental results presented in this paper showcase the efficacy of Stealth Tracking in accurately detecting and mitigating attacks originating from VPN servers. By enhancing cyber security measures, Stealth Tracking provides a valuable tool for organizations and individuals relying on VPN technology to secure their online communications. This proposed approach contributes to a more robust defense against evolving cyber threats in an increasingly interconnected digital landscape.

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Cyber threats continue to proliferate Virtual Private Networks (VPNs) have become a ubiquitous tool for securing online communications. However, the widespread use of VPNs has inadvertently led to an increase in malicious actors exploiting VPN servers as gateways for launching attacks, posing a significant challenge for effective threat detection and mitigation. This abstract introduces a groundbreaking approach named Stealth Tracking designed to identify and thwart attacks originating from VPN

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