bluuebunny/crossref_metadata_2025 huggingface dataset:
ENHANCING MARITIME SAFETY USING UNDERWATER COMMUNICATION AND IOT
Authors: K. Mohammed Younus , M. Sivaselvaraj , M. Selvakumar , K. Sivanesh , S. Tamilselvan
Published: August 2024

This project proposes an innovative approach utilizing underwater data transfer to enhance the safety and well-being of fishermen navigating through challenging marine environments. By testing various types of agents to precisely alter experimental water coefficients, the project aims to transmit real-time information about fishermen's organic conditions and interactions to a tracking station. This is achieved through separate transmitter and receiver modules deployed in the water. The fluctuating atmospheric conditions of the ocean pose significant challenges for marine navigators, often leading to health complications such as uncontrollable heart rate fluctuations, particularly during deep dives. To address these challenges, the proposed system integrates GPS coordinates, air pressure sensors, and air humidity sensors to monitor fishermen's health status while navigating. The system facilitates two-way communication between the ground station and sea navigators, enabling prompt response and assistance in case of emergencies. By leveraging this technology, the project aims to mitigate risks and potentially save the lives of numerous fishermen navigating hazardous waters.
INNOVATIVE SOLUTIONS SAFEGUARDING CROPS AND WILDLIFE WITH INTELLIGENT SURVEILLANCE
Authors: G. Mohanavel , V Mariselvam , S Kannan , K Mohanraj , E Nikilkumar .
Published: August 2024

In agriculture, the delicate balance between safeguarding crops and protecting wildlife presents a significant challenge. Traditional methods often involve reactive measures, leading to crop damage and wildlife disturbance. However, emerging technologies offer innovative solutions through intelligent surveillance systems. These systems leverage advanced technologies like predictive analytics and AI algorithms to monitor fields and wells proactively. By deploying such intelligent surveillance systems, it becomes possible to protect crops from wildlife damage while ensuring the safety of animals. Intelligent surveillance systems are revolutionizing agricultural practices by providing real-time monitoring and analysis capabilities. By integrating predictive analytics, these systems can anticipate potential threats to crops and wildlife based on historical data, weather patterns, and environmental factors. AI algorithms enhance the accuracy and efficiency of monitoring by identifying and differentiating between benign and harmful activities. With this proactive approach, farmers can implement timely interventions to mitigate risks, such as deploying deterrents or adjusting irrigation schedules, thereby minimizing crop damage while minimizing harm to wildlife populations. Furthermore, the integration of intelligent surveillance systems with IoT (Internet of Things) devices offers seamless connectivity and control. Sensors embedded in fields and wells can relay data to centralized platforms, enabling remote monitoring and management. This not only enhances efficiency but also reduces the need for physical presence, thereby minimizing disruptions to wildlife habitats. Additionally, the data collected from these systems can be analyzed to gain insights into wildlife behavior and habitat usage, facilitating informed decision-making for conservation efforts. The implementation of intelligent surveillance systems represents a proactive and sustainable approach to safeguarding both crops and wildlife in agricultural landscapes.
PREDICTIVE MAINTENANCE UNLEASHING APPLICATIONS OF MACHINE LEARNING: A COMPREHENSIVE EXPLORATION
Authors: Agarwal Vishnu , Sabir Mohammad , Mishra Surbhi , Sen Rahul
Published: August 2024

The integration of industrial artificial intelligence (AI), smart sensing, and the Internet of Things (IoT) has revolutionized data utilization in various sectors. Predictive maintenance (PDM) emerges as a pivotal strategy, leveraging data from diverse manufacturing and sensing sources to anticipate equipment failures. This paper presents a comprehensive overview of the application of machine learning (ML) techniques in PDM, categorizing advancements based on ML algorithms and data acquisition equipment. Through highlighting significant contributions and ongoing pilot projects, this review provides valuable insights for optimizing maintenance strategies and enhancing equipment performance and longevity.
DESIGN AND IMPLEMENTATION OF AUTOMATIC TRANSFORMER OVERLOAD PROTECTION SYSTEM
Authors: Rathore Arvind Singh , Lohar Anchal , Lohar Ashok , Patel Keya , Yadav Aman
Published: August 2024

Load sharing provides sufficient protection to distribution transformer under overloaded conditions. Due to overload on transformer, the efficiency drops and windings get overheated and may burn. By sharing a load current on transformer for each phase the transformer was protected. Therefore, the objective of this study was to protect transformers from overloaded conditions by sharing the load. Because of the differences in our college level studies and industry level requirements, we are allotted a project to get knowledge about the on goings at industries. I did the mini project that covered up a practical knowledge of what I have studied so far in books. I did experience an exposure to various electronics devices and equipment’s which I would not have able to get easily anywhere else. In electric power distribution, an automatic overload protection System Is a circuit breaker equipped with a mechanism that can automatically close the breaker after it has been opened due to a fault. Automatic overload protection systems are used in coordinated protection schemes for overhead line power distribution circuits.
SMART LIGHTING SYSTEM FOR REDUCES THE ENERGY CONSUMPTION
Authors: Rathore Arvind Singh , Ameta Jitendra Kumar , Saxena Aayush , Paneri Garvit , Sahu Rohit
Published: August 2024

- Advanced light scape controlling system is a simple yet powerful concept, which uses transistor as a switch. By using this system manual works are 100% removed. It automatically switches ON light when the sunlight goes below the visible region of our eyes. This is done by a sensor called Light Dependent Resistor (LDR) which senses the light like our eyes. It automatically switches OFF lights whenever the sunlight comes, visible to our eyes. By using this system energy consumption is also reduced because nowadays the manually operated streetlights are not switched off even when the sunlight comes and switched on earlier before sunset. In this project, there is no need for manual operation like ON time and OFF time setting. This project clearly demonstrates the working of transistors in saturation region and cut-off region. The working of relay is also known.
INTERNET OF THINGS INTEGRATING INTO THE AUTOMOTIVE SECTOR: INCREASING ACCESSIBILITY OR EFFECTIVENESS
Authors: Sheikh Anisha , Banu Nargis
Published: August 2024

Unlike the Industrial Internet of Things (IoT) which links all the equipment in an industry that processes data, this study article takes a more comprehensive approach. to incorporate IoT with mechanical systems. The automotive sector is witnessing a significant transition towards more intelligent, efficient, and connected cars with the introduction of the Internet of Things (IoT). This study examines how IoT is revolutionizing the automotive industry, highlighting its uses, advantages, difficulties, and potential. The automobile industry is utilizing the Internet of Things (IoT) to transform not just the performance and user experience of vehicles, but also to make transportation networks safer, more environmentally friendly, and more efficient. To completely achieve this technological integration, however, a number of issues must be resolved, such as data security, privacy concerns, and infrastructure requirements.
INSTANT LANGUAGE TRANSLATION APP
Authors: Kothari Nitin , Jain Chandra Prakash , Soni Dipesh , Kumar Avinash , Dadheech Anshumaan , Sharma Himanshu
Published: August 2024

The Real-Time Language Translation App is a solution aimed at addressing to the frequently found problem of language barriers in global communication. This app, which bridges linguistic gaps in communication between individuals and organizations, is based on state-of-the-art language processing technologies. The app provides instantaneous and accurate translations for conversations, documents, and various forms of by communication by utilizing artificial intelligence and natural language processing to translate spoken and written text in real-time. The Real-Time Language Translation App fundamentally represents the idea of an inclusive and networked world in which communication barriers between languages are no longer a barrier to comprehension and cooperation. Globalization and multiculturalism have made today's society more interconnected, and being able to communicate effectively across linguistic boundaries is crucial for promoting understanding amongst people. The app's innovative approach to language translation is based on modern innovations that make it possible to instantly and smoothly translate text and speech between several languages. By utilizing advanced algorithms, the application effectively interprets both written and spoken language, maintaining context and meaning while offering translations instantaneously. This feature is especially helpful in situations like business negotiations, international conferences, or emergency situations where quick communication is crucial.
BIG DATA AND DATA ANALYTICS APPROACHES: NAVIGATING THE SEAS OF INFORMATION
Authors: Seth Bhaskar , Kavdia Amisha , Sharma Preeti
Published: August 2024

In the current era of digitally enabled world, the expansion of data has become universal, giving rise to the concepts of big data and Data Analytics. This review paper provides a comprehensive view of these interconnected concepts, significance, objectives, implications, and methodologies. Big data refers to the massive volume of data generated from various sources whereas Data Analytics encircle the processes and techniques which are used to extract valuable insights from the massive data. The significance lies in their evolutionary potential for businesses and organizations. By leveraging this power businesses can grow and gain actionable insights. The objective of framing this review paper is to explore the implications for different industries and sectors. We'll look at what's being done now, what problems exist, and where we can go from here.
A COMPARATIVE STUDY OF AC AND DC MICROGRID SYSTEM WITH DISTRIBUTED ENERGY RESOURCES
Authors: Kumar Pradeep , Pawar Rajneesh
Published: August 2024

In this paper modern systematic literature analysis of AC and DC microgrids (MG) in combination with renewable energy sources (RESs) as distributed generations units (DG), loads and battery bank to store electricity. A review on the different DG units arrangements consisting distribution networks of the low voltage AC and DC using numerous applications of microgrid systems in the perspective of current and the future customer apparatus energy market is broadly deliberated. Based on the techno-economic and ecological advantages of the renewable energy-based DG units, a detailed comparison of AC and DC microgrid systems is done. This paper also explores the possibility, controlling and energy management schemes of the both microgrid systems depending upon the most recent research findings. Eventually, the protection and the power management techniques in microgrid systems are discussed and delivered in detail. Out of this literature analysis, it could be evidenced that both type of microgrid systems consisting multiconverter gadgets are inherently conceivable for the upcoming energy systems to attain the consistency, better power supply and efficiency.
THE DEVELOPMENT OF A WEB-BASED ROAD ACCIDENT DATA MANAGE SYSTEM USING GIS IN UDAIPUR CITY
Authors: Jangeed Denis , Ramawat Dharmendra , Khan Asif
Published: August 2024

This project aims to develop a comprehensive web-based road accident data management system tailored for Udaipur City, Rajasthan, India, utilizing GIS technology. With increasing urbanization and traffic congestion, effective management of road accident data becomes paramount for improving road safety measures. The system will offer tools for efficient collection, storage, analysis, and visualization of accident data, empowering authorities to make evidence-based decisions. Following a structured methodology encompassing data collection, system design, development, testing, and implementation, the project holds great promise for reducing accident rates and enhancing public safety in Udaipur City. Similarly, a user-friendly accident data management system has been developed for selected locations of Surat City, Gujarat, India, utilizing GIS technology. Designed to be accessible to those unfamiliar with computers, the system facilitates accident data reporting and statistical analysis, aligning with Indian Roads Congress guidelines. By highlighting the necessity of GIS database and user-friendly systems for effective transportation planning, design, and administration, this initiative underscores the importance of data-driven decision-making in enhancing road safety measures
SENSOR BASED SMART TRAFFIC LIGHT CONTROL SYSTEM
Authors: Jangeed Denis , Mohammad Idrish , Patel Jitendra
Published: August 2024

The Smart traffic light control system (STLCS) is a pioneering initiative aimed at addressing the complex challenges inherent in contemporary urban traffic management. As cities worldwide grapple with escalating issues such as traffic congestion, safety hazards, and environmental degradation, the urgency for innovative solutions has never been more pronounced. The STLCS offers a multifaceted approach, harnessing the power of state-of-the-art technologies such as sensor-based cameras, intelligent traffic lights, and sophisticated real-time data analytics. Central to the functionality of the STLCS are the foundational technologies it employs. Arduino boards serve as the backbone for data acquisition, seamlessly interfacing with a myriad of sensors and data sources dispersed throughout the traffic network. The Raspberry Pi emerges as the cerebral cortex of the system, tasked with processing vast volumes of data, executing complex algorithms, and making informed decisions in real time. Meanwhile, smart LED traffic lights, dynamically responsive to the ebb and flow of traffic conditions, act as the visible manifestation of the system's intelligence, orchestrating traffic flow with precision and finesse. The methodology underpinning the STLCS entails a meticulous process encompassing the installation, calibration, and optimization of sensor arrays and camera networks at strategic vantage points across the urban landscape. Concurrently, a robust suite of algorithms is developed and implemented to translate raw sensor data into actionable insights, informing adaptive traffic signal control strategies. Continuous monitoring, iterative refinement, and rigorous validation protocols underpin the evolution of the STLCS, ensuring its efficacy and reliability in real-world deployment scenarios. Preliminary testing of the STLCS has yielded encouraging results, with demonstrable improvements in traffic flow dynamics observed in controlled simulation environments. However, the journey towards widespread adoption and seamless integration into existing urban infrastructures necessitates further validation through extensive real-world testing and iterative refinement cycles.
CLOUD COMPUTING: A LATENCY AND BANDWIDTH COST OPTIMIZATION PERSPECTIVE
Authors: Agrawal Himangi , Gupta Tanya
Published: August 2024

Cloud providers are forced to run numerous datacenters throughout the world to host their cloud services due to end-user latency and regulatory requirements. Request allocation, the process of allocating each user request to the best data center to benefit cloud providers, is an emerging issue under such geo-distributed architecture. Nevertheless, previous request allocation solutions have serious drawbacks: They either only optimize benefits for one party (providers or users, for example) or neglect some important but realistic factors (various per-unit bandwidth costs among datacenters and heterogeneous latency requirements of different users) when optimizing benefits for both parties. The challenge of ensuring end user’s latency requirements while minimizing the overall bandwidth cost is discussed in this paper. In order to meet latency constraints and reduce operating costs, it is critical to optimize user request allocation as cloud services continue to expand across diverse geographical regions. The problem of effectively allocating incoming requests in a geo-distributed cloud environment is discussed in this paper. The principal aim is to achieve equilibrium between cost minimization and adherence to predetermined latency constraints, thereby guaranteeing responsive services for users, regardless of their geographical location. The suggested method makes use of intelligent load balancing, dynamic resource scaling, and predictive models to optimize inter-region data transfer while adaptively allocating requests. To assess resource provisioning and data transfer costs, cost models are integrated, which enhances overall costeffectiveness. Metrics like reliability, scalability, cost efficiency, and latency adherence are used to assess how effective the system is. The findings are intended to contribute to a more responsive and economical cloud infrastructure by offering insights into improving the performance of geo-distributed cloud services.
COMPUTATION OF THERMODYNAMICAL PARAMETERS OF BMGS ON BASIS OF TAYLOR’S SERIES EXPANSION
Authors: Gaur Jitendra , Mishra R. K. , . Vivek , . Sunita , Dalal Anita
Published: August 2024

The BMGs are the materials of interest of present and future scientific interest as these materials show good structural and functional applications and hence viewed as important metallic materials due to their exceptional properties of great strength at room temperature and high flexibility at high temperature. As a result, there is a race to study the thermodynamical properties of Bulk Metallic Glasses (BMGs). The Taylor series expansion is a mathematical tool used to represent a function as an infinite sum of terms calculated from the values of its derivatives at a specific point. However, the success of a Taylor series expansion depends on the behavior of the function and the range of temperatures one is interested in. In the context of thermodynamics and material science, Taylor series expansions can be used to approximate thermodynamic properties or expressions. In the present study, Taylor’s series expansion is used to compute the thermodynamical parameters of some selected undercooled melts characterized under the class of BMGs.
UNVEILING THE DYNAMICS OF MOBILE AD HOC NETWORKING (MANET)
Authors: Seth Shilpa , . Pooja , Mittal Manisha , Dutta Rashmi
Published: August 2024

This abstract provides a thorough examination of Mobile Ad Hoc Networking (MANET), highlighting its decentralized structure, dynamic topology, and routing complexities. It emphasizes MANET's crucial role in modern communication systems and explores challenges such as limited bandwidth, energy constraints, node mobility, and security risks. Various routing protocols and innovative solutions tailored to address MANET's unique challenges are discussed, with a focus on its integration into military operations, disaster management, vehicular networks, IoT, and smart cities. By exploring MANET fundamentals, challenges, solutions, and applications, this abstract offers a comprehensive understanding of its evolving landscape. It underscores MANET's adaptability and resilience in environments lacking traditional infrastructure, demonstrating its importance in scenarios requiring rapid deployment and reliable communication. This concise exploration aims to contribute to the ongoing dialogue on advancing MANET technology for diverse operational contexts and realworld applications.
EXPLORING SIMPLE LOAD BALANCING TECHNIQUES FOR IMPROVED CLOUD PERFORMANCE
Authors: Mittal Manisha , Dutta Rashmi , Seth Shilpa , . Pooja
Published: August 2024

The paradigm of cloud computing is one in which users receive resources like computation power warehousing and applications as a service over the internet. It provides common assets, information, software and other measures based on the requirement of the client at a particular time. Service needs to be improved as cloud computing expands rapidly and required computing attracts more users. Good load balancing techniques are required for efficient resource management. Load adjusting in distributed computing is a basic module for conveying approaching organization traffic or computational responsibilities across different servers or assets to guarantee ideal asset usage, expand throughput, limit reaction time and keep up with framework soundness. It is essential for enhancing cloud-based applications and services performance, scalability and dependability.
A REVIEW: BI-DIRECTIONAL DC-DC CONVERTER TOPOLOGIES
Authors: Sharma Piyush , Palwalia Dheeraj Kumar , Sharma Ashok Kumar
Published: August 2024

- Bidirectional DC-DC power converters are increasingly being used in a wide range of applications that require power flow in both forward and reverse directions. These applications encompass various fields such as energy storage systems, uninterruptible power supplies, electric vehicles, and renewable energy systems, among others. The objective of this paper is to meticulously evaluate these converters from both a topological and control scheme perspective. In terms of topology, these converters can be classified into two main categories: non-isolated and isolated configurations. The non-isolated category is further divided into eight distinct groups, each accompanied by their respective schematics and a summary table. Similarly, the isolated configuration category is also divided into eight groups, each with their own schematics and summary table. This comprehensive categorization provides a comprehensive overview of the various converter topologies. In summary, this paper provides a comprehensive review of bidirectional DC-DC power converters, focusing on their topologies. By categorizing the converters into non-isolated and isolated configurations, and thoroughly analyzing their respective schematics and summary tables, the paper offers a holistic understanding of the subject matter.
OPTIMUM OVERCURRENT RELAY’S COORDINATION USING MULTIPLE STANDARD RELAYS CHARACTERISTICS
Authors: Shah Preet , Godwal Shanker D. , Chatterjee Soumesh , Nimje Akhilesh A.
Published: August 2024

Relay Coordination is very crucial task as it required coordination of primary and backup relays. in past various authors have proposed modification in standard overcurrent relays characteristic, modification in objective function to achieve optimum results of operating time of primary as well as backup relays. In this paper, considering normal inverse, very inverse and extremely inverse standard relays characteristic, optimized results are obtained using PSO, GA, HAS. Further these results have been validated on radial distribution system.
STEERING INTO THE FUTURE: EXPLORING THE POTENTIAL OF FOUR-WHEEL CONTROL SYSTEMS
Authors: Sharma Deepti Mehta , Choubisa Nitin , Singhal Pratik , Singh Prabhjot
Published: August 2024

Nowadays, most existing vehicles use the two-wheel steering system to control the movement of the vehicle whether it is a front-wheel drive, rear-wheel drive, or all-wheel drive. But due to the awareness of safety, four-wheel steering vehicles are being used increasingly, since they are also known for their high performance and stability. In standard two-wheel steering vehicles, the rear wheels do not play any role in association with the steering and follow the path of the front wheels. In four-wheeled steering, the wheels can be rotated either left or right as per the requirements. The rear wheels can be rotated in the same direction as the front or in the opposite direction. The four-wheel system is designed to function in 3 modes namely, in-phase rotation, counter-phase rotation, and zero rotation. The steering systems are designed to give the best control designed for the vehicle. The vehicles are designed with steering control to the front wheels or in certain cases steering control is given to the rear wheels. The dual axle steering system shows the working of the different motions of wheels concerning various turning arrangements. The machine consists of 3 different steering arrangements i.e., neutral phase, negative phase & positive phase. In the neutral phase only the front wheels either run in the right or left direction and the rear wheel is the follower of the front wheels. In the negative phase, both front and rear axles move in the opposite direction relative to each other. In the positive phase, both the axle front and rear move in the same direction relative to each other. Here we need to lift the shifter and place it into the respective slot for the required motion.
ADVANCED APPLICATIONS AND FUTURE TRENDS OF AR/VR GLASSES
Authors: Kothari Nitin , Jain Chandra Prakash , Kabra Deepti , Aswani Chetna , Khichi Hiya
Published: August 2024

Augmented Reality (AR) and Virtual Reality (VR) technologies have undergone remarkable transformations, paving the way for innovative AR/VR glasses. These devices bridge the digital with the physical world, enhancing user engagement across various sectors including education, healthcare, entertainment, and industry. This paper delves into the technological underpinnings, prevalent applications, challenges, and prospective directions of AR/VR glasses, offering insights into their transformative potential and the evolutionary trajectory of immersive technologies.
RECOGNIZING SPEECH SYSTEM: AN INDEPTH EXAMINATION OF IDEAS ALONG WITH WORKINGS
Authors: Tailor Ritu , Sharma Surbhi
Published: August 2024

Nowadays, speech recognition systems make use of a wide range of multidisciplinary technologies, including unifying statistical frameworks, signal processing, natural language processing, and pattern recognition. Applications for these systems are numerous and include signal processing issues among many other things. The aim of this study is to introduce the fundamentals of speech recognition systems, including their development and recent improvements that have been applied to improve their accuracy and robustness. This paper provides a thorough analysis of the mechanism, obstacles, and strategies for overcoming them. It ends with a prediction that, as technology advances, the world will undoubtedly see dramatic changes in the not-too-distant future.
BEYOND SILICON: EMERGING MATERIALS AND TECHNOLOGIES IN SEMICONDUCTOR INNOVATION
Authors: Sharma Sunil , Chouhan Yashi Singh , Soni Rajdeep , Sharma Bhoomika
Published: August 2024

As the semiconductor industry approaches the physical limits of silicon-based technologies, the quest for alternative materials and innovative technologies has become paramount to continuing Moore's Law and addressing the growing demands for computing power and energy efficiency. This paper explores the frontier of semiconductor innovation, highlighting the emergence of novel materials and technologies poised to transcend the limitations of traditional silicon. The paper examines the properties and potential of materials such as graphene, transition metal di-chalcogenides (TMDCs), and topological insulators, alongside advancements in device architectures like quantum dots and spintronic. The methodology combines a systematic review of recent literature with comparative analysis of material properties, device performance, and scalability challenges. The integration of these emerging materials with current semiconductor manufacturing ecosystems is also discussed. Findings indicate that these materials offer significant advantages over silicon, including higher electron mobility, flexibility, transparency, and superior thermal properties, which could revolutionize the semiconductor industry by enabling faster, smaller, and more energy-efficient devices. These materials are showcasing their potential to enhance computational capabilities, sensor sensitivity, and connectivity for a wide range of applications, from wearable electronics to quantum computing. However, challenges related to synthesis, large-scale production, and integration into current systems persist. Addressing these hurdles requires interdisciplinary research and collaboration between academia, industry, and regulatory bodies to develop standardized methods for material synthesis, characterization, and device fabrication. The implications of findings extend beyond the semiconductor industry, offering insights into the future of electronics, telecommunications, and computing. As we stand on the brink of a new era in semiconductor technology, this paper calls for increased investment in research and development, policy support, and international cooperation to harness the full potential of these emerging materials and technologies, ensuring a sustainable and innovative future for the global semiconductor market.
PARAMETRIC INFLUENCES ON MECHANICAL TRAITS IN SELECTIVE LASER MELTING OF AlSi10Mg
Authors: Sharma Purushottam , Bhardwaj Tarun , Gangil Namrata , Singh Dinesh Kumar
Published: August 2024

The objective of this review is to present a thorough evaluation of the existing knowledge concerning the processing of AlSi10Mg Aluminum alloy by using Selective Laser Melting (SLM). The manufacturing of complex and intricate components has been significantly influenced by additive manufacturing in a wide range of industries, with SLM becoming increasingly popular owing to its numerous advantages. This review explores key characteristics of AlSi10Mg alloy components made by SLM. In this review, the impacts of various process parameters, post-processing treatments, and heat treatments on the mechanical characteristics of AlSi10Mg alloy components are comprehensively elaborated.
A REVIEW: AN IMPROVED LLC RESONANT INVERTER FOR INDUCTION FREQUENCY USING DIFFERENT ELECTRICAL APPLICATIONS
Authors: Jain Chandra Prakash , Paneri Prachi , Rathore Suhani , Yadav Prashant
Published: August 2024

In this paper, A simple power-control scheme for high frequency an LLC resonant inverter with asymmetrical control technique is proposed. The aim is to control the output power for high-temperature applications like steel melting, brazing, and hardening, where the load parameters and resonant frequency vary substantially throughout the system operation. The operating frequency is controlled using phase locked loop to track for the resonant frequency. The output power is controlled by adjusting the switch duty cycle. The LLC resonant tank is designed with a matching transformer in between the series inductor and paralleled LC resonant tank. The important advantage of the proposed topology is the short-circuit protection of the transformer and the induction coil. The validity of the proposed method is verified through computer simulation using MATLAB.
ENHANCING PERFORMANCE AND RELIABILITY OF HYBRID PV-WIND ENERGY CONVERSION SYSTEM USING FAULT ANALYSIS AND MITIGATION TECHNIQUE WITH ANN BASED DVR
Authors: Chouhan Meenakshi , Parikh Kapil , Baharni Prakash
Published: August 2024

- The major problem in renewable energy system is that the variation in power generation from time to time because of the intermittent nature of the renewable sources. In this paper presents a fault analysis, classification, and mitigation technique for a hybrid grid-connected photovoltaic (PV) wind energy conversion system (WECS) using Artificial Neural Network (ANN) based Dynamic Voltage Restorer (DVR). The proposed system aims to improve the performance and reliability of the hybrid energy conversion system during fault conditions. The study uses simulation to evaluate the effectiveness of the proposed fault analysis, classification, and mitigation technique in detecting and mitigating various types of faults in the hybrid system, such as voltage sag, voltage swell, symmetrical and asymmetrical faults. The results show that the proposed system is effective in detecting and classifying the faults accurately and mitigating them using DVR. The ANN-based fault classification algorithm provides high accuracy in identifying different types of faults, and the DVR is capable of quickly restoring the system's voltage to its nominal level. The study concludes that the proposed fault analysis, classification, and mitigation technique can significantly improve the reliability and performance of the hybrid PV-WECS system during fault conditions.
COMPARATIVE PERFORMANCE EVALUATION OF PSO-TUNED ANFIS MPPT ALGORITHM & GA-TUNED ANFIS MPPT ALGORITHM FOR SOLAR ENERGY CONVERSION SYSTEM
Authors: Prajapati Girraj , Parikh Kapil , Baharni Prakash
Published: August 2024

This paper introduces the development and performance evaluation of an Adaptive Neuro-Fuzzy Inference System (ANFIS) based MPPT controller designed for a DC-to-DC converter. The proposed system comprises a 2.0 kW PV array, a DC-to-DC boost converter, and a load. Leveraging the advantages of both neural and fuzzy networks, the proposed algorithm aims to optimize solar photovoltaic system parameters through the integration of an adaptive neuro-fuzzy inference system (ANFIS) controller, employing Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). The comparison between PSO and GA-based optimization techniques is conducted using MATLAB/SIMULINK software, with a focus on enhancing the converter's performance. The primary objective is to determine whether the GA-tuned ANFIS MPPT algorithm outperforms in terms of tracking Maximum Power Point (MPP), tracking accuracy, and steady-state oscillation—critical parameters for solar energy conversion systems. Simulation results indicate that, across a broad range of input irradiance levels, the GA-tuned ANFIS MPPT algorithm demonstrates superior performance in tracking MPP, accuracy, and steady-state oscillation compared to the PSO-tuned ANFIS MPPT algorithm under various operating conditions.
UPGRADING CYBERSECURITY: INVESTIGATING THE SECURITY BENEFITS OF CLOUD COMPUTING
Authors: Shriwas Rakhi , Sen Rahul Kumar , Agrawal Vishnu , Chouhan Jitendra Singh , Tege Saurbh
Published: August 2024

Cloud computing has revolutionized the landscape of cybersecurity, offering a myriad of advantages over traditional on-premises systems. This abstract explores the security benefits of cloud computing, highlighting its role in enhancing data protection, scalability, disaster recovery, proactive threat detection, centralized management, cost-effectiveness, and continuous updates. By leveraging the cloud, organizations can bolster their security posture, mitigate risks, and ensure business continuity in the face of evolving cyber threats.
ENHANCING SECURITY AND RESILIENCE IN SMART GRIDS THROUGH QUANTUM KEY DISTRIBUTION: CHALLENGES AND OPPORTUNITIES
Authors: Kaur Manpreet , Mishra Shweta
Published: August 2024

Smart grids offer many advantages, but they also come with some risks, especially regarding network security and privacy. This study aims to investigate the privacy and security of existing smart grid systems and to give a cross-section of the latest findings in the field of secure data aggregation and authentication for smart grids. The study focuses on addressing the challenges posed by malicious tampering and unauthorized access to metering data by exploring innovative approaches to ensure the integrity and confidentiality of data through a process termed "secure aggregate" and that the result of secure aggregations is authenticated in a manner that is both scalable and effective using Quantum Key Distribution. A software prototype has been developed to facilitate machine-to-machine authentication because this cryptographic key can be used and machine connections can be verified. This can contribute to the protection of essential infrastructure, the creation of a continuous threat detection feedback system, and the foundations of this technology are essential conditions for increasing the ability of systems to authenticate users.
Examining Intercage Transmission of Chlamydia muridarum: Impact of Barrier Husbandry and Cage Sanitization
Authors: Palillo Michael B , Mishkin Noah , Aydin Mert , Mourino Anthony , Ricart Arbona Rodolfo J , Lipman Neil S
Published: August 2024

Chlamydia muridarum (Cm) has reemerged as a prevalent bacterial contaminant of academic research mouse colonies. A study was conducted to assess the effectiveness of husbandry and cage sanitization methods in preventing intercage transmission of Cm. To assess intercage transmission during cage change, a cage housing 2 Cm-free Swiss Webster (SW; Tac:SW) sentinel mice was placed randomly on each of 12 individually ventilated cage racks, housing cages with Cm-shedding mice, located in one of 2 animal holding rooms. Husbandry staff blinded to the study cages changed all cages in the animal holding rooms weekly using a microisolation cage technique. PCR testing performed at 180 d postplacement confirmed all mice remained negative for Cm. To assess the effectiveness of cage sanitization to eliminate Cm, we investigated transmission of Cm to a naive Cm-free SW and NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ (NSG) mouse cohoused for 7 d (repeated weekly for 4 wk) in cages assigned to one of 3 groups (n = 10 pairs of mice/group). Cages that previously housed 2 Cm-shedding BALB/c mice were either washed in a tunnel washer (82.2 °C [180 °F] final rinse for an average of 16 s per run; n = 10) with and without postwashing autoclaving (121 °C for 20 min; n = 10), or were untreated (bedding change only; n = 10). Pre- and postsanitization swabs of each cage were assayed for Cm by PCR. All pretreatment swabs tested positive, while posttreatment swabs from all cages (excluding bedding change) tested negative. All SW and NSG mice, irrespective of group, remained negative for Cm as determined by PCR. These findings suggest that infectious Cm does not persist in untreated cages or after mechanical washing with and without autoclaving. Collectively, these findings suggest that neither our husbandry protocols nor inadequate cage sanitization methods likely contributed to the observed prevalence of Cm in contemporary research mouse colonies.
ANALISIS KESELAMATAN DAN KESEHATAN KERJA (K3) MENGGUNAKAN METODE HAZARD ANALYSIS (STUDI KASUS PADA PROYEK PEMBANGUNAN RUMAH SAKIT KORPRI KOTA SAMARINDA)
Authors: Acthree Dede , Haryanto Budi , P. Arifin Triana Sharly
Published: August 2024

Dalam dunia konstruksi tidak luput dengan adanya perhatian terhadap keselamatan dan kesehatan kerja (K3). Dalam suatu pekerjaan konstruksi terdapat banyak sekali unsur bahaya yang dapat membahayakan pekerja. Identifikasi keselamatan dan kesehatan kerja dilakukan menggunakan metode hazard analysis yaitu HIRA dan HAZOP. Pengumpulan data dilakukan dengan menggunakan data primer dan data sekunder yaitu data primer yang mencakup wawancara kepada safety officer, menyebarkan kuesioner ke pekerja hingga project manager, dan hasil pengamatan langsung di lapangan. Sedangkan data sekunder mencakup struktur organisasi perusahaan. Berdasarkan hasil terdapat 34 variabel resiko yang telah diidentifikasi dan dilakukan uji validitas terdapat 6 variabel resiko yang tidak valid sehingga dari 34 variabel resiko yang telah diidentifikasi hanya 28 variabel resiko yang valid. Kemudian dilakukan uji reliabilitas dan hasilnya 28 variabel resiko konsisten dan didapat nilai reliabilitas 0,886 yang memiliki reliabilitas tinggi. Hazard analysis dengan metode HIRA terdapat 2 variabel resiko yang paling tinggi dengan kategori extreme yaitu pada variabel B1 dan C1. Hazard analysis dengan metode HAZOP terdapat beberapa penyebab yang disebabkan dari potensi bahaya yaitu tidak adanya pelatihan dan pengarahan tentang K3, minimnya staff HSE pada proyek, minimnya pemberian sanksi yang tegas, minimnya anggaran dana untuk APD, tidak menggunakan APD, mengabaikan SOP, pekerja tidak memahami SOP.
ANALISIS ELEMEN STRUKTUR BALOK DAN KOLOM BETON BERTULANG (STUDI KASUS GEDUNG DEALER HONDA ASTRA KOTA SAMARINDA)
Authors: Ariani Indra , Aditya Muhammad Rangga , Jamal Mardewi
Published: August 2024

Perencanaan struktur merupakan hal yang penting dalam suatu konstruksi bangunan ditinjau dari segi kekuatan, keamanan dan keekonomiannya. Struktur bangunan secara keseluruhan terdiri dari struktur atas berupa lantai, balok, kolom, dinding dan atap; sedangkan struktur bawah terdiri dari pondasi dan balok sloof. Elemen struktur terpenting dalam struktur adalah kolom dan balok sehingga dimensi yang direncanakan dan penggunaan tulangan pada kolom dan balok perlu diketahui agar sesuai dengan persyaratan dalam kategori aman. Studi yang dilakukan dengan menganalisis tulangan balok dan kolom menurut SNI-2847-2019 berdasarkan persyaratan beton struktural untuk bangunan gedung. Kesimpulan dari penelitian yaitu tulangan utama pada balok dengan dimensi penampang 600 x 300 (tulangan atas 7D19; tulangan bawah 4D19) dan kolom dimensi 600 x 600 (tulangan utama 20D19) telah memenuhi persyaratan yang ditentukan. Adapun tulangan geser pada balok dimensi 600 x 300 (sengkang tumpuan D10-100 dan sengkang lapangan D10-150) dan kolom dengan dimensi 600 x 600 (tumpuan sengkang D10-100 dan sengkang lapangan D10-150) serta pengait D10-300 telah memenuhi persyaratan yang ditentukan.
ANALISA KUAT TEKAN BETON MENGGUNAKAN METODE COMPRESSION TEST DAN HAMMER TEST MENGGUNAKAN AGREGAT HALUS PASIR TENGGARONG
Authors: Alifsyah A.R Muhammad , Jamal Mardewi , P. Arifin Triana Sharly
Published: August 2024

Beton merupakan suatu bahan komposit yang dihasilkan dari pencampuran bahan-bahan agregat halus, agregat kasar, air, semen atau bahan lain yang berfungsi sebagai bahan pengikat hidrolis, dengan atau tanpa menggunakan bahan tambahan. Kuat tekan beban beton adalah besarnya beban per satuan luas yang menyebabkan benda uji beton hancur bila dibebani dengan gaya tekan tertentu yang dihasilkan oleh mesin tekan. Pada penelitian ini bertujuan untuk mengetahui kuat tekan beton yang dihasilkan dari metode compression test dan hammer test menggunakan agregat halus Pasir Tenggarong. Benda uji yang digunakan pada penelitian ini ada 2 jenis yaitu silinder berdiameter 15 cm dan tinggi 30 cm, kubus berukuran 15 cm X 15 cm X 15 cm dengan total 16 buah sampel benda uji yang dibagi menjadi 8 sampel untuk silinder dan 8 sampel untuk kubus, dengan sampel direndam/curing selama 28 hari. Hasil penelitian yang didapat untuk metode compression test benda uji kubus nilai tertingginya yaitu 307,73 kg/cm2 dan nilai terendahnya yaitu 269,20 kg/cm2 sedangkan untuk benda uji silinder nilai tertingginya yaitu 293,28 kg/cm2 dan nilai terendahnya yaitu 253,26 kg/cm2. Lalu untuk metode hammer test benda uji kubus nilai tertingginya yaitu 193,74 kg/cm2 dan nilai terendahnya yaitu 142,76 kg/cm2 sedangkan untuk benda uji silinder nilai tertingginya yaitu 203,94 kg/cm2 dan nilai terendahnya yaitu 122,36 kg/cm2. Yang terakhir nilai persentase hammer test terhadap compression test untuk benda uji kubus nilai tertingginya 70,08% dan terendahnya 51,55% sedangkan benda uji silinder nilai tertingginya 69,54% dan terendahnya 46,48%.
ANALISIS JALUR PEJALAN KAKI DAN AREA PARKIR UNTUK MENINGKATKAN KINERJA JALAN (STUDI KASUS: JALAN PRAMUKA)
Authors: Fakhrur Rozi Muhammad Arief , Alkas M. Jazir , Widiastuti Masayu
Published: August 2024

Jalan Pramuka menjadi akses penting bagi masyarakat Kota Samarinda karena menghubungkan berbagai lokasi perguruan tinggi, yaitu Universitas Mulawarman, Universitas Widya Gama Mahakam, IKIP PGRI Kalimantan Timur, dan STMIK Widya Cipta Dharma. Lokasi yang berdekatan dengan perguruan tinggi menjadikan Jalan Pramuka sebagai kawasan tempat tinggal mahasiswa, dan secara bertahap menjadi area komersial. Aktivitas komersial ini menimbulkan permasalahan lalu lintas yaitu hambatan samping yang disebabkan oleh pejalan kaki, kendaraan parkir badan jalan, kendaraan melambat, dan keluar masuk kendaraan. Pada analisis ini digunakan metode survei perhitungan jumlah hambatan samping, jumlah pejalan kaki, jumlah kendaraan parkir badan jalan, dan volume lalu lintas harian. Survei dilakukan selama 3 hari dengan durasi per hari selama 16 jam, dimulai dari pukul 06.00 hingga 22.00. Survei dilaksanakan pada hari Minggu, Senin, dan Selasa. Setelah seluruh data survei didapatkan maka digunakan analisis berdasarkan MKJI untuk mengetahui kinerja jalan, kemudian analisa kebutuhan parkir untuk mengetahui besaran jumlah area parkir yang dibutuhkan, dan analisa pedestrian untuk mendesain trotoar di Jalan Pramuka berdasarkan volume pejalan kaki. Hasil survei menunjukkan bahwa kebutuhan parkir di sepanjang Jalan Pramuka untuk sepeda motor (MC) adalah 186 petak, dan kendaraan ringan (LV) sebesar 36 petak, sedangkan untuk trotoar lebar minimum yang dibutuhkan adalah sebesar 1.54 meter per sisi. Berdasarkan data tersebut maka perencanaan dilakukan dengan menyediakan 2 area parkir yang berada di kedua ujung Jalan pramuka dengan kapasitas parkir kendaraan parkir (LV) 52 petak, sepeda motor (MC) 215 petak, untuk perencanaan trotoar direncanakan memiliki lebar 2 meter di sepanjang Jalan Pramuka, dilengkapi dengan fasilitas pemandu tunanetra (Guiding Block), bollard untuk menghalangi kendaraan memasuki trotoar, dan Teras Pramuka sebagai wadah relokasi pedagang kaki lima yang sebelumnya berjualan di bahu jalan, dipindahkan dalam 1 kawasan PKL yang berada terhubung dengan area parkir, sehingga tidak menimbulkan hambatan samping.
ANALISIS RISIKO K3 MENGGUNAKAN PENDEKATAN HIRADC DAN METODE JSA (STUDI KASUS : PROYEK PEMBANGUNAN GEDUNG BPKAD SAMARINDA)
Authors: Supriyadi Wulan Faradila , P. Arifin Triana Sharly , Abdi Fachriza Noor
Published: August 2024

Pelaksanaan pekerjaan konstruksi terdiri dari berbagai tahapan pekerjaan dan melibatkan banyak unsur. Hal ini menyebabkan kegiatan konstruksi memiliki risiko kecelakaan lebih tinggi. Oleh karena itu perlu diterapkan K3 yang baik pada setiap proyek konstruksi dan salah satu bentuk pengendaliannya adalah dengan sistem manajemen K3. Penelitian ini bertujuan untuk mengetahui jenis dan level risiko dalam proyek pembangunan gedung BPKAD Samarinda. Serta membandingkan penerapan pengendalian risiko di lapangan dengan rencana kerja K3.Penelitian ini menggunakan metode Hazard Identification, Risk Assesment and Determining Control  (HIRADC) dan Job Safety Analysis (JSA). Pengumpulan data dilakukan dengan penyebaran kuesioner tertutup dan kuesioner terbuka, hasil kuesioner tertutup diolah menggunakan SPSS dan hasil kuesioner terbuka diolah menggunakan triangulasi. Selanjutnya dilakukan analisis risiko menggunakan severity index dan matriks risiko. Selanjutnya dengan menggunakan metode HIRADC dan JSA akan diketahui level risiko tertinggi pekerjaan dan dapat  ditentukan rekomendasi pengendalian risiko. Tahapan terakhir dalam penelitian ini adalah mengetahui perbandingan penerapan pengendalian risiko di lapangan dengan dokumen RKK3.Hasil dari analisis risiko terdapat 4 pekerjaan dengan level risiko tinggi yaitu pekerjaan kolom dengan 3 level risiko extreme, acp dan kaca dengan 2 level risiko extreme, dan drainase dengan 2 level risiko extreme, sedang balok dan pelat lantai dengan 1 level risiko extreme. Berdasarkan hasil analisis kuesioner terbuka,  didapatkan rekomendasi pengendalian risiko dengan menggunakan Alat Pelindung diri (APD), dilakukan pengecekan, dll. Untuk penerapan pengendalian risiko terhadap proyek secara umum telah dilaksanakan sesuai dengan dokumen RKK3, namun untuk penerapan pemakaian APD terhadap pekerja masih banyak pekerja yang belum menaati peraturan.