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Design And Development Of Artificial Intelligence Based Knowledge Management System For Managing Software Security Vulnerabilities
Software development practices play a signifcant role in building the world s future. It is the place where exciting technological evolution begins in the world. Exploration of critical challenges in the area of software development plays a signifcant role in fueling the pace of technological progression in the industry. This work focuses on exploring important areas of software development practices and problems faced by the industry. Understanding the critical parts of the software system development eco-system and the stakeholders associated with those will be important. Customers of software development teams, the software development industry and knowledge newlinesources, and the software development internal eco-system are the broad focus areas of study. Leveraging the data already spread across the eco-system and facilitating easy newlineaccess to practitioners as and when there is a need will be one of the primary focuses. newlineThe software development landscape module, customer landscape module, and industry landscape module are the key modules that will be explored in this work. The core aspiration of the work will be to integrate all the possible data across the industry newlineand process the same and make it easily accessible to the practitioners as and when they are needed. The process also makes the data smarter and more insightful over time. -
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Design and Development of Artificial Intelligence Knowledge Processing System for Optimizing Security of Software System
Software security vulnerabilities are significant for the software development industry. Exploration is conducted for software development industry landscape, software development eco-system landscape, and software system customer landscape. The focus is to explore the data sources that can provide the software development team with insights to act upon the security vulnerabilities proactively. Across these modules of software landscape, customer landscape, and industry landscape, data sources are leveraged using artificial intelligence approaches to identify the security insights. The focus is also on building a smart knowledge management system that integrates the information processed across modules into a central system. This central intelligence system can be further leveraged to manage software development activities proactively. In this exploration, machine learning and deep learning approaches are devised to model the data and learn from across the modules. Architecture for all the modules and their integration is also proposed. Work helps to envision a smart system for Artificial Intelligence-based knowledge management for managing software security vulnerabilities. 2023, Crown. -
Design and development of cognitive improvement through virtual reality based treatment using mathematical model
Virtual reality (VR) used in rehabilitation has the potential to enhance the quality of life for individuals with various medical conditions. As a result of this novel approach, there has been an increase in the number of individuals who are now giving their attention and actively engaging in rehabilitation programmes. This study aims to assess the effectiveness and advantages of virtual reality-based rehabilitation programmes in comparison to traditional educational methods for enhancing and strengthening talents. The creative capacity of VR was assessed through a study involving 50 participants who are going through regular traditional therepy methods. Virtual reality therapy enhances cognitive functions. As a result of the changes, there was a 30-40% increase in growth using proposed mathamatical model compared to traditional methods. The study revealed that the use of virtual reality-based personalised rehabilitation resulted in enhanced cognitive function and improved retention of knowledge among the participants. 2024, Taru Publications. All rights reserved. -
Design and Development of Dual Fuzzy Technique to Optimize Job Scheduling and Execution Time in Cloud Environment
Cloud computing is a type of computing that relies on sharing a pool of computing resources, rather than deploying local or personal hardware and software. It enables convenient, on-demand network access to a shared pool of configurable computing re- sources (e.g., applications, storage, networks, services, and servers) that can be swiftly provisioned and released with minimal management control or through the interaction of the cloud service provider. The increasing demand for computing resources in the cloud has made elasticity an important issue in the cloud. The availability of extending the resources pool for the user provides an effective alternative to deploying applications with high scalability and processing requirements. Providing a satisfactory Quality of Service (QoS) is an important objective in cloud data centers. The QoS is measured in terms of response time, job completion time and reliability. If the user jobs cannot be executed in high load and the job is crashed, it will enormously increase the response time and also push up the job completion time. Also due to load, the jobs may be still in the waiting queue and could not find a resource to execute. In such a situation, the user notices a big response delay and it will affect the QoS. Towards ensuring QoS, this research proposes the following solution - Dual Fuzzy Load Balancing for jobs. Dual Fuzzy Load Balancing balances the load in the data center with an overall goal of reduction of response and execution time for tasks. The proposed solutions were simulated in the Cloudsim simulator and performance metrics in terms of job response time, job completion time, resource utilization, a number of SLA violations, and along with the cost comparison to the existing algorithms of Load Balancing. The proposed solutions are also implemented in a real cloud environment and the effectiveness of the solution is evaluated. -
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Design and development of load balancing algorithm for enhance cloud computing performance
Software Applications have taken a leadership position in the field of Information Technology to reduce the human workload. In the case of distributed applications, the scalability of the application is a matter of newlineconcern in the present dynamic scenario. The fast developments in computing resources have reduced the cost of hardware and increased the processing capability of the system remarkably. Still, hosting a distributed newlineapplication in a higher end system is not recommended due to many reasons. Firstly, when there is a massive demand in the usage of the application which is beyond the limit of the system, there is no way to scale newlineit. The second reason is that when the system usage of the application is minimal, the entire infrastructure dedicated to the targeted application will remain idle. newlineDue to the wide acceptability of the industry on cloud computing, the variety of applications are designed to target the cloud platform which is one of the challenges for efficient load balancing in the cloud newlineenvironment. A fair distribution of workload among the available resources is mandatory to improve the efficiency of the cloud platform. To share the workload, a useful load balancing strategy, as well as a timely invocation of the plan, is essential. Invocation of the approach known as triggering policy can be different in centralised and distributed scenarios. Since cloud applications are running in a distributed situation, through this research newlinework, the researcher puts forward a complete framework for balancing load in different types of the request generated in Infrastructure as a Service (IaaS) platform. newlineAs a progressive model, this research work continuously focuses on improving the performance of the load balancer in the IaaS platform. Since the cloud data centres are spread across the globe, a centralised monitoring system to monitor and analyse the resource utilisation in different data newlinecentres is an essential requirement to see the load fluctuations in different clusters. -
Design and Development of Mobile Robot Manipulator for Patient Service During Pandemic Situations
Time and manpower are important constraints for completing large-scale tasks in this rapidly growing civilization. In most of the regular and often carried out works, such as welding, painting, assembly, container filling, and so on, automation is playing a vital part in reducing human effort. One of the key and most commonly performed activities is picking and placing projects from source to destination. Constant monitoring of patient bodily indicators such as temperature, pulse rate, and oxygen level and service of the patients becomes challenging in the current pandemic condition to the nurses and medical staffs. In consideration to this, a mobile robot with an integrated robotic arm has been designed and developed which can be available for service of patients continuously alongside monitoring them in general ward as well as in ICU of hospitals. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Design and Development of Multi-Sensor ADEP for Bore Wells Integrated with IoT Enabled Monitoring Framework
Typically, about 51% of the groundwater satisfies the drinking water worldwide and is regarded as the major source for the purpose of irrigation. Moreover, the monitoring and assessment of groundwater over bore wells is essential to identify the effect of seasonal changes, precipitations, and the extraction of water. Hence, there is a need to design a depth sensor probe for bore wells so as to analyze/monitor the quality of underground water thereby estimating any geophysical variations like landslides/earthquakes. Once the depth sensor probe is designed, the data is collected over wireless sensor network (WSN) medium and is stored in cloud for further monitoring and analyzing purposes. WSN is the major promising technologies that offer the real-time monitoring opportunities for geographical areas. The wireless medium in turn senses and gathers data like rainfall, movement, vibration, moisture, hydrological and geological aspects of soil that helps in better understanding of landslide or earthquake disasters. In this paper, the design and development of geophysical sensor probe for the deep bore well so as to monitor and collect the data like geological and hydrological conditions. The data collected is then transmitted by wireless network to analyze the geological changes which can cause natural disaster and water quality assessment. 2023 The Authors. Published by AnaPub Publications. This is an open access article under the CC BY-NC-ND license. (http://creativecommons.org/licenses/by-nc-nd/4.0/) -
Design and Development of Teaching and Learning Tool Using Sign Language Translator to Enhance the Learning Skills for Students With Hearing and Verbal Impairment
This research paper presents a system designed for the students with verbal and hearing impairments by enabling realtime Sign-to-Text and Text-to-Sign Language conversion, with a specific focus on the Indian Sign Language (ISL). The proposed study aligns to the United Nations Sustainable Development Goal (SDG) of Quality Education. The system leverages cutting-edge technologies, MediaPipe for holistic key point extraction encompassing hand and facial movements, and Long Short-Term Memory (LSTM) architecture powered by TensorFlow and Keras for accurate sign language interpretation. This comprehensive approach ensures nuanced aspects of sign language, such as facial expressions and hand movements, are faithfully represented. On the receiving end, the system excels at Text-to-Sign Language conversion, allowing non-sign language users to interact naturally with sign language users through textual input transformed into sign language animations and Sign-to-Text conversion where the information from the sign language users is converted to text which ensures smooth communication. A user-friendly web application, developed using HTML, CSS, and JavaScript, enhances accessibility and intuitive usage for realtime communication. This research represents a significant advancement in assistive technology, promoting inclusivity and communication accessibility. It underlines the transformative potential of innovation infostering a more connected and inclusive world for all, regardless of their hearing abilities 2024 IEEE. -
Design and Development of Terahertz Medical Screening Devices
This paper highlights the prospect of design and development of a terahertz medical screening system, giving an overview of existing devices, systems, for THz spectroscopy and imaging of biological samples (e.g., cell, tissue imaging or screening). Considering the non-ionizing nature of THz waves along with its reasonable soft-tissue sensitivity, terahertz instrumentation has opened up possibilities for medical screening devices. Some THz imaging systems presently use raster scanning for calculation of image region of interest. Here, a particular system is proposed as a medical screening device and factors like signal-to-noise ratio, image resolution, image contrast, etc., have been described and correlated with relevant clinical results for exploring possible prospects in medical applications of terahertz waves. 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Design and Evaluation of Wi-Fi Offloading Mechanism in Heterogeneous Networks
In recent years, WiFi offloading provides a potential solution for improving ad hoc network performance along with cellular network. This paper reviews the different offloading techniques that are implemented in various applications. In disaster management applications, the cellular network is not optimal for existing case studies because the lack of infrastructure. MANET Wi-Fi offloading (MWO) is one of the potential solutions for offloading cellular traffic. This word combines the cellular network with mobile ad hoc network by implementing the technique of Wi-Fi offloading. Based on the applications requirements the offloading techniques implemented into mobile-to-mobile (M-M), mobile-to-cellular (M-C), mobile-to-AP (M-AP). It serves more reliability, congestion eliminated, increasing data rate, and high network performance. The authors also identified the issue while implementing the offloading techniques in network. Finally, this paper achieved the better performance results compared to existing approaches implemented in disaster management. Copyright 2021, IGI Global. -
Design and Fabrication of Differential Thermal Analyser for Thermal Characterization of Materials
Thermal analysis techniques are widely used in both industrial and scientific domains to understand the changes in structural and chemical composition of materials. The structural and chemical composition of most of the materials undergoes changes when heated. Using various thermal analysis techniques such changes are monitored in various atmospheres of interest. Through these analytical experimental techniques the physical properties of the substance can be studied as a function of temperature. These techniques can be used to characterize, qualitatively and quantitatively a huge range of materials over a substantial temperature range. Results from the thermal analysis instruments can be obtained quickly and henceforth it has wide variety of applications. These thermal methods find widespread use for both quality control and research applications on polymers, pharmaceutical preparations, clay, minerals, metals and alloys. Differential thermal analysis is one of the thermal analysis methods, which records the difference in temperature (??T) between a substance and an inert reference material as a function of furnace temperature or time. Any transformation ?? change in specific heat or an enthalpy of transition ?? can be detected by Differential Thermal Analyser (DTA). The automated DTA is available readily from various manufacturers but it is expensive. Therefore researchers usually prefer to design and build their own instruments as per the individual requirements of experiments under various specialized conditions. Furnace, sample holder, controlled heating source, low noise-high gain amplifier and differential recorder are the main units of a differential thermal analyser. In the present work, we have made an attempt to design and fabricate a low cost differential thermal analyser for the thermal analysis of materials. -
Design and genome engineering of microbial cell factories for efficient conversion of lignocellulose to fuel
The gradually increasing need for fossil fuels demands renewable biofuel substitutes. This has fascinated an increasing investigation to design innovative energy fuels that have comparable Physico-chemical and combustion characteristics with fossil-derived fuels. The efficient microbes for bioenergy synthesis desire the proficiency to consume a large quantity of carbon substrate, transfer various carbohydrates through efficient metabolic pathways, capability to withstand inhibitory components and other degradation compounds, and improve metabolic fluxes to synthesize target compounds. Metabolically engineered microbes could be an efficient methodology for synthesizing biofuel from cellulosic biomass by cautiously manipulating enzymes and metabolic pathways. This review offers a comprehensive perspective on the trends and advances in metabolic and genetic engineering technologies for advanced biofuel synthesis by applying various heterologous hosts. Probable technologies include enzyme engineering, heterologous expression of multiple genes, CRISPR-Cas technologies for genome editing, and cell surface display. 2022 Elsevier Ltd -
Design and Implementation Bidirectional DC-AC Converter for Energy Storage System
This article proposes a bidirectional single-phase dc-ac converter with triple port converter (T-PC) for application of energy storage. This proposed converter provides three ports such as ac port, dc port, and dc bus port to achieve three power interfacing ports. For the direct conversion process, dc port is directly connected to T-PC, and direct power will be exchanged between energy storage device (ESD) and grid when the ESD voltage peak amplitude is lower than the ac voltage. Thus, a dc-dc converter downstream power process gets reduced, and power loss is decreased considerably. Due to multilevel characteristics, switching losses in the T-PC can be reduced. The efficiency of the overall bidirectional dc-ac conversion process can be increased significantly. The circuit model, working principle, and modulation control of T-PC-based bidirectional dc-ac conversion concepts are analyzed. A 1.5-kW test-bench model is developed and its effectiveness is verified to find the merits of suggested conversion. 2021 IEEE. -
Design and implementation of a universal converter for microgrid applications using approximate dynamic programming and artificial neural networks
This paper introduces a novel design for a universal DC-DC and DC-AC converter tailored for DC/AC microgrid applications using Approximate Dynamic Programming and Artificial Neural Networks (ADP-ANN). The proposed converter is engineered to operate efficiently with both low-power battery and single-phase AC supply, utilizing identical side terminals and switches for both chopper and inverter configurations. This innovation reduces component redundancy and enhances operational versatility. The converter's design emphasizes minimal switch usage while ensuring efficient conversion to meet diverse load requirements from battery or AC sources. A conceptual example illustrates the design's principles, and comprehensive analyses compare the converter's performance across various operational modes. A test bench model, rated at 3000W, demonstrates the converter's efficacy in all five operational modes with AC/DC inputs. Experimental results confirm the system's robustness and adaptability, leveraging ADP-ANN for optimal performance. The paper concludes by outlining potential applications, including microgrids, electric vehicles, and renewable energy systems, highlighting the converter's key advantages such as reduced complexity, increased efficiency, and broad applicability. The Author(s) 2024. -
Design and Implementation of Active Clamp Flyback Converter for High-Power Applications
This paper proposes a solar-powered isolated DCDC converter for high-power applications. The main aim of this paper is to achieve voltage regulation in the output side of the converter and to integrate a lossless active clamp flyback circuit (LACF) to compensate for the high-voltage issues that arise from one-stage DCDC converters. Hardware is developed with a power rating of 2 kW to test the performance of the proposed circuit. The circuit is designed using low-voltage devices and features such as soft switching and regeneration due to the LACF, which enhances efficiency. A novel luminous control algorithm is presented to improve the converter performance. The proposed circuits performance and feasibility are compared with existing converter parameters, such as the number of components in the circuit, voltage rating, and regeneration. 2023 by the authors. -
Design and implementation of Adaptive PI control based dynamic voltage restorer for solar based grid integration
This paper introduces an innovative approach to address voltage fluctuations in solar-based grid integration by implementing an adaptive PI control-based Dynamic Voltage Restorer (DVR). This DVR is engineered to counteract voltage disruptions resulting from grid disturbances and the intermittent nature of solar energy generation. To achieve optimal performance in diverse operating conditions, the adaptive PI controller dynamically adjusts its parameters, adapting to changes in load and solar generation. The system is realized on a digital signal processor (DSP) and evaluated within a laboratory-scale solar-based grid integration setup. The findings reveal that the proposed system effectively mitigates voltage fluctuations, ensuring a stable integration of solar energy into the grid. The adaptive PI control-based DVR outperforms traditional PI control-based DVRs, particularly when dealing with variable solar energy generation. This approach holds significant potential for practical applications in solar-based grid integration systems. 2024 IEEE. -
Design and Implementation of an Optimized Mask RCNN Model for Liver Tumour Prediction and Segmentation
Segmentation of liver tumour is a tedious job due to their large variation in location and closeness to nearby organs. In this research, a novel Mask RCNN prototype is developed which uses ResNet-50 model. The architecture utilizes the masked location of convolution neural network to precisely detect liver tumours by recognizing liver sites to deal with changes in liver and CT snaps with distinct metrics. The preprocessed CT scans are subjected to ResNet-50 model. The data samples used here comprises 130 instances recorded from several clinical sites that are publicly available on the LiTS weblink. The designed model upon deployment generates a promising outcome thereby obtaining a DSC of 0.97%. Thus, we can conclude that the developed model is capable enough to accurately assess liver tumours and thus help patients in early diagnosis. 2023 IEEE. -
Design and implementation of dual-leg generic converter for DC/AC grid integration
A newly designed generic photo-voltaic (PV) DC-DC/DC-AC converter is for direct current (DC) grid or single-phase alternating current (AC) grid integration. Main concept of the proposed converter is universal power conversion, and the same converter is used for DC-DC/DC-AC applications which also aiming for minimum redundancy because the proposed converter can be able to produce DC and AC output from the fixed/variable DC source. The proposed converter is designed with single-stage dual leg topology, with a designed filter, and protection circuits are connected in output/grid side. The proposed circuit is compared with existing topologies, and comparative analyses are made in both chopper (DC-DC) and inverter (DC-AC) modes for universal or generic operation. Real-time implementation of the proposed model is prepared for the power rating of 3.5 KW during inverter mode and 4 KW when same circuit working in chopper mode. Hardware results are obtained from the model from both chopper and inverter modes. Finally, correct applications, advantages, and future work are concluded in the last section. 2023 John Wiley & Sons Ltd.