Micro grid systems have emerged as a promising solution for integrating renewable energy sources and enhancing the overall reliability and efficiency of power distribution. The design and stability analysis of converter topologies play a crucial role in ensuring the seamless operation of micro grids. This research focuses on the development and optimization of converter topologies through advanced control techniques to enhance the stability and performance of micro grid systems. Special attention is given to the challenges associated with the integration of renewable energy sources, such as variable output and intermittent nature. A novel converter topology is proposed to address these challenges, leveraging advanced power electronics and control methodologies. The stability analysis is conducted using optimal control techniques to ensure robust and reliable operation of the micro grid. Mathematical models and simulation tools are employed to assess the dynamic behavior of the proposed converter topology under various operating change in load conditions. The research explores the potential of micro grid system with the converter topology to enhance the micro grid's overall stability and response to load variations. The results of the stability analysis highlight the improvements achieved in terms of system response, efficiency, and reliability.

The IoT is transforming healthcare by enabling extensive connectivity between medical professionals, equipment, staff, and patients, facilitating real-time monitoring. While the network's scale and diversity offer advantages for data exchange, they also pose challenges for privacy and security, particularly with sensitive medical information. To address this, deep learning-based cryptographic and biometric systems are utilized for authentication and anomaly detection in medical systems. However, power constraints on network sensors necessitate efficient security schemes. Thus, the authors propose a novel framework, the deep Inception-ResNetV2 with privacy preservation, to secure data transmission while minimizing encryption and decryption time. Implementing this method reduces the network's burden, saving time and costs in communication. Compared to alternatives like private biometric-based authentication, this model demonstrates superior performance. URN:NBN:sciencein.jist.2024.v12.805

This study focuses on investigating the prevalence of cervical vertigo, delving into the existing knowledge about how frequently it occurs and its distribution across different populations. In ACS Medical College and Hospital, Abitha Modern Physio Center in Kolathur, Blossom Rehabilitation Clinic in Kolathur, and F.O.R Ortho and Neuro Specialty Hospital, a six-month cross-sectional observational study was carried out. The investigation was carried out from January 2023 to June 2023. 244 people in the age range of 40 to 60 made up the sample for the study. Utilizing the vertigo symptom scale, the prevalence was gathered. 244 participants categorized by age, gender, BMI to investigate the prevalence of dizziness. From the statistical data it is clearly stated that female subjects were more affected than men. 41 - 60 Years age group were identified more with complaint. The BMI Classification showed that more of the affected people were overweight. Percentage distribution of dizziness in the Overall Participants using vertigo symptom scale, much of the participants had mild and moderate dizziness. Prevalence of cervical vertigo on different populations were demonstrated in this study. This study sheds light on the prevalence of dizziness across different age groups, gender disparities, and its relationship with BMI classification. The findings contribute to a better understanding distribution of dizziness. URN:NBN:sciencein.jist.2024.v12.797

Today, a growing number of applications are transitioning to the cloud due to its numerous benefits and userfriendly nature. Data plays a pivotal role in the migration, and its security is of paramount importance. Database forensics is a field dedicated to investigating malicious activities carried out by attackers, whether they occur on the front-end or back-end. These activities can be traced through the analysis of various database logs, with network details aiding in the identification of the attacker. In this paper, the authors explore the activity indicators by examining and analysing activity logs, database logs and network packets. Cloud forensics presents the digital investigation for the detection of cyber crimes on cloud. This could include data breaches or identity thefts or modification of databases and attacks on the application server and webserver.

This paper presents a performance study of cold-formed steel (CFS) structural frames subjected to lateral loading. The study focuses on performance based on the experimental and numerical study of cold formed steel structural frames, investigating strength and stiffness. The cold-formed steel frame consists of three storey structural frames that are made with cold-formed steel channel sections of columns and beam elements. The study involves analytical investigation via ANSYS workbench software. It was used to perform FE analysis and examine the factors influencing the failure of the frame. The result showed that the column made with lipped channel revealed stiffness higher than column made with normal cold formed steel. Moreover, increasing the thickness of structural elements leads the better lateral force resisting capacity of the frame. URN:NBN:sciencein.jist.2024.v12.791

This paper reports a Fog-based health monitoring systems framework to enable the real-time tracking and analysis of users' health data and associated events. This framework encompasses a broad spectrum, including medical, environmental, meteorological, and location-based information, with the overarching goal of addressing the escalating threat posed by different pathogens, mainly the rapidly spreading chikungunya virus (CHV) worldwide. The chikungunya virus, transmitted by Aedes aegypti and Aedes albopictis mosquitoes, raises significant public health concerns. The paper outlines three potential modes of virus transmission: 1) infection from infectious female mosquitoes, 2) transmission to healthy female mosquitoes from infected individuals, and 3) contagious female mosquitoes laying infectious eggs. In response to the challenges in identifying and preventing chikungunya virus outbreaks, the paper introduces strategic measures. Key objectives include establishing a Fog-based system that leverages user health symptoms and environmental factors for remote CHV diagnosis, delivering instant diagnostic and emergency notifications to users for timely responses, computing metrics from Social Network Analysis (SNA) graphs to depict virus contraction or transmission likelihood, generating warning messages for government and medical organizations to contain outbreaks, and safeguarding users' sensitive information against unauthorized access. In essence, the designed Fog-based health monitoring approaches seek to achieve comprehensive real-time monitoring and analysis, providing a systematic framework for CHV diagnosis, notification, and containment.

monitoring, and controlling various process parameters is a practice that has been prevalent in the manufacturing industry for the past few decades. Numerous measurement instruments which are available in the industry suit only a particular application requirement. Thus, multiplexing of a measurement device has many advantages over a single parameter measurement device. Wireless connectivity with the application infrastructure has always been desirable since the advent of IoT. This paper showcases the design process for the development of such a multiplexed measurement system, that will be compatible with a wide range of applications, with minimal installation space and cost, and which can communicate with the IoT network with the help of a LoRa module. LoRa, a wireless modulation method, enables low-power devices to communicate across long distances and low bit rates. The design of industrial measurement with LoRA interface aims to be a portable stand-alone embedded system, with an attractive and easily interpretable Graphical User Interface (GUI).

The utilization of microbial laccase for the biological delignification of biomass is regarded as an environmentally sustainable procedure. Present study aimed to optimize the process parameters to achieve improved laccase production. Mustard oil cake was utilized as a solid substrate, and Aspergillus nidulans was employed as the fungal strain for the production of Laccase enzyme. To optimize the different physical and chemical factors for laccase production, specifically moisture content, incubation time, nutrient pH, incubation temperature, salt concentration, and additional carbon and nitrogen sources were considered. Additionally, response surface methodology was employed to optimize both the media and process parameters. The highest observed enzyme activity was 6.99 U/mL under optimum conditions. Experimental data showed that moisture content of 100% (w/v), incubation temperature of 28°C, pH range of 5-6, 6% MgSO4 (w/v) and ammonium chloride when used as supplementary salts in the production medium resulted in the maximum production of laccase. The production medium was incubated for a duration of 96 hours once optimized. To maximize laccase production, this study optimized the different media components using conventional OFAT method and further optimized the critical parameters using the response surface methodology (RSM).