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Article In Press
Title: A COMPREHENSIVE REVIEW OF ROBOTIC ARMS: DESIGN, CONTROL, AND APPLICATIONS
Author: Magar Prathmesh*, Kale Suraj, Prof. Surwase S. S.
Keyword: Robotic Manipulator, Arduino UNO, Degree of Freedom, End Effector, Servo motor, Kinematics, Prototype Design, Mechatronics.
Page No: 117-121
Abstract: In this paper to the discusses the develope of the robotic manipulator, commonly referred to as a robotic arm, which is designed to replicate gripping and movement actions. The arm consists the series of rigid the segments called links, connected in a sequence to form the complete structure. The manipulator is controlled using an Arduino UNO and is suitable for tasks in hazardous environments, such as material handling or industrial operations. To analyze the torque requirements, a prototype in the robotic arm built and tested through simulated tasks. The paper also explores potential applications of a robotic manipulator with 6 degrees of freedom, focusing on functionality the end effector as the primary interface for interaction. Keywords: Robotic Manipulator, Arduino UNO, Degree of Freedom, End Effector, Servo motor, Kinematics, Prototype Design, Mechatronics. Download PDF


Title: EFFECTIVE PEOPLE COUNTING IN LIBRARY SYSTEMS USING DEEP LEARNING TECHNIQUES
Author: Saw Mya Nandar and Hlaing Htake Khaung Tin
Keyword: People counting, library, deep neural network, CNNs, image processing.
Page No: 122-132
Abstract: People counting is important for managing library spaces effectively and supporting decisions related to resource allocation, space utilization, and improvement of user experience. Traditional approac hes to counting individuals are inaccurate and not scalable, particularly in complex scenarios such as in libraries, where occlusions, light conditions, and spatial arrangements may be very different. In this paper, a deep learning-based approach is presented for accurate real-time people counting in library systems. In this paper, a deep neural network model is proposed based on CNNs and some advanced image processing techniques. It is trained and tested on a dataset tailored to library environments, showing the robustness against environmental challenges there. The experimental results demonstrate that the system reaches an average accuracy of 96.07%, an MAE of 1, and a very strong F1 score of 92.2%, outperforming conventional methods. These findings underpin the capability of deep learning for high-performance and scalable people counting in library systems, thereby offering enhanced management and user experience. Keyword: People counting, library, deep neural network, CNNs, image processing. Download PDF


Title: STUDY THE IMPACT OF SUPPLY CHAIN DECISIONS ON OVERALL ENVIRONMENTAL PERFORMANCE
Author: Dr Dharmendra Kr Dubey*, Dr. Chetna Choudhary, Mahendra Pratap Yadav, Mithilesh Kumar Singh and Mritunjay Kumar
Keyword: Supply Chain Management, Environmental Performance, Decision
Page No: 133-136
Abstract: As environmental awareness and regulatory demands continue to rise, the choices made within supply chains have a significant impact on an organization's ecological footprint. This study explores how v arious strategic and operational decisions—such as selecting suppliers, choosing transportation methods, planning inventory, and sourcing strategies—affect critical environmental performance indicators like carbon emissions, resource utilization, waste production, and energy usage. By analyzing cases from diverse industries along with existing theoretical literature, this research demonstrates that environmentally optimized supply chains not only mitigate negative ecological effects but also result in cost savings, lower risks, and increased brand reputation. Additionally, digital technologies, lifecycle assessment methods, and sustainability metrics empower companies to make more eco-efficient choices. The findings emphasize the importance for firms to integrate environmental considerations into their supply chain design and decision-making processes in alignment with global sustainability goals and regulations. This paper enhances our understanding of how supply chain management intersects with environmental sustainability while providing valuable insights for both researchers and practitioners in the field. Keywords: Supply Chain Management, Environmental Performance, Decision Download PDF


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