Authors - Bimal Patel, Jalpesh Vasa, Ravi Patel, Martin Parmar, Krunal Maheriya Abstract - Software robustness, a vital component of software quality, encompasses key attributes such as reliability, usability, efficiency, maintainability, and portability. This paper offers a comprehensive overview of these attributes and examines the role of optimization tools in enhancing software robustness. Reliability, which ensures a system’s consistent dependability, is achieved through techniques like redundancy, error handling, and extensive testing. Usability, focusing on the user experience, is improved through user-centered design, usability testing, and heuristic evaluation. Efficiency targets the optimal use of system resources such as CPU and memory, with performance profiling, load testing, and code optimization techniques helping identify and resolve bottlenecks. Maintainability, ensuring that systems can be easily modified or updated, is enhanced through modularity, code readability, and design patterns that simplify future changes. Portability, which allows software to operate across diverse platforms, is achieved through cross-platform frameworks and containerization technologies such as Docker and Kubernetes. Optimization tools, including profilers, load testing tools, static code analyzers, and dependency management tools, play a critical role in maintaining software robustness. These tools help identify performance issues, ensure resource efficiency, and improve code quality. By leveraging these tools, developers and project managers can build more reliable, efficient, and maintainable software systems. This paper serves as a valuable resource for improving the overall quality, resilience, and portability of software products.
Authors - Siddhesh Joshi, Manoj Naidu, Athrva Kulkarni, Sahil Kadam, Nilesh P. Sable, Pranjal Pandit Abstract - Artificial Intelligence (AI) is a new type of experience that uses computer-generated content to augment the Real World (RW). An emerging type of experience known as augmented reality (AR) involves adding computer generated content to the real world (RW) that is connected to certain places and/or activities. AR is starting to show up in audio-visual media (news, entertainment, sports, etc.) and is starting to make a real and exciting appearance in other areas of lives (e-commerce, travel, marketing, etc.) [2]. This paper proposes the development of a marker-based AR system that overlays interactive 3D models of industrial machinery onto real-world views. The proposed project will be based on Unity software, which will make it feasible to present complex industrial equipment and move away from typical product manuals that are only text-laden. Users can intuitively see and interact with different parts of their machinery during maintenance, troubleshooting, or training through the AR-based system. This will probably ensure more user interaction with less learning time for a technical operation and is, therefore, most beneficial for the industries that heavily depend on machineries' setups and maintenance. This paper describes methodology, and the probable effects of the marker-based AR digitizing product manuals with first-hand observation in the future of digital documentation across industrial life.
Authors - Ashita C. Kolla, Dattatray G. Takale, Parikshit N. Mahalle, Bipin Sule, Gopal Deshmukh Abstract - The research paper mainly focuses on algorithmic bias in facial recognition technology using parameters like race and hairstyle. It involves a CNN model following the pre-processing step of the data and custom annotation. It further talks about advanced methods for dataset balancing, such as normalization and sampling, along with detailed annotations involving characteristics of different races and hairstyles. Compared to other models, the CNN model contains powerful feature extraction methods and other bias mitigation methods such as adversarial training and annotation to enhance the chance of predictions. The results reveal that the model has made significant progress with good performance and lesser bias. This study helps the industry develop more reliable FRT systems with effective strategies for reducing bias and maintaining accuracy. These advancements are important for applications in various industries, where unbiased facial recognition is important for fairness and effectiveness.
Authors - Shrivardhansinh Jadeja, Bimal Patel, Jalpesh Vasa Abstract - The evolution of software development methodologies has profoundly influenced the gaming industry, marking a transition from traditional approaches to agile frameworks that emphasize flexibility and responsiveness. Traditional methodologies often struggled to meet the rapidly changing demands of game design and player expectations, leading to extended development cycles and reduced competitiveness. In contrast, agile methodologies have emerged as a viable solution, focusing on iterative development, continuous feedback, and collaboration among cross-functional teams. This paradigm shift has enabled companies like Riot Games to significantly enhance operational efficiency and swiftly respond to market dynamics. This research paper investigates Riot Games' agile transformation as a case study, illustrating how the adoption of agile practices has fortified its competitive advantage over alternative players in the gaming sector. By examining Riot's innovative team structures, leadership models, and iterative development processes, this study elucidates the critical role of agility in fostering creativity, improving product quality, and accelerating time-to-market. The findings highlight the necessity of embracing agile methodologies not only for individual organizations but also for the broader gaming industry seeking sustainability and growth in an increasingly competitive landscape. Ultimately, this paper offers valuable insights into how agile transformation can act as a catalyst for success in game development, providing a framework for other companies aiming to enhance their competitive positioning.
Authors - Rashmy Moray, Sejal Vaishav, Sangam Dey, Sridevi Chennamsetti, Harsha Thorve Abstract - This paper investigates the impact of behavioural biases, specifically Loss Aversion, Regret Aversion, Reference Dependence, and Risk Perception on algorithmic trading using the framework of Prospect Theory. Using structured questionnaire, the Primary data was collected from the traders who use algorithm. Statistical tool, SmartPLS was employed to assess the endogenous factors and the behavioural biases that influence the intention to trade using algorithms. The findings indicate that Risk Perception and Reference Dependence significantly impact trading intent, whereas Loss Aversion and Regret Aversion do not show a significant influence on trading intent. This advocates that the systematic and emotion-free nature of algorithmic trading minimizes the effects of certain emotional biases. The study contributes profound understanding of behavioural biases of traders adopting algorithm offer distinctive path for future scope of research.
Authors - Padmanabh khunt, Martin Parmar, Het Khatusuriya, Mrugendra Rahevar, Bimal Patel, Krunal Maheriya Abstract - The smart garage system presented in this paper incorporates advanced security and remote-control functionalities to enhance the user experience and ensure secure access. The implementation of a One-Time Password (OTP) authentication mechanism provides an additional layer of security, effectively preventing unauthorized access to the garage. Central to the system are ESP32 microcontrollers, which facilitate reliable and efficient communication between the keypad, relay module, and the mobile application. Utilizing LoRa communication, the system achieves long-range wireless connectivity, enabling seamless interaction between ESP32 microcontrollers even in areas with limited network coverage. The mobile application, developed using React Native, offers a user-friendly interface for homeowners, featuring login/signup options, direct garage door control, and OTP generation for secure access. A robust server backend, built with Node.js and supported by a MongoDB database, ensures efficient management of user data, including login credentials and generated OTPs. Furthermore, an admin panel is integrated to enhance user administration and access control capabilities. This comprehensive smart garage system not only improves security but also provides convenience and reliability for modern homeowners.
