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Latest Trends in Visual Manipulation and Navigation in Robotics Miftahul Amri, Muhammad; Areche, Franklin Ore; Ratnakar Naik, Amar
Journal of Novel Engineering Science and Technology Vol. 2 No. 01 (2023): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v2i01.253

Abstract

In recent decades, the term Robot has become more and more popular. A robot can be defined as a machine that is specifically built to complete certain tasks to help human-being. In order to successfully accomplish its task, the robot needs to receive input data and process it. Then, the processed data is used for manipulator-actions decision-making. The input data can vary from sound, temperature, vibration, touch, vision, etc. Among those input data, vision is arguably one of the most challenging data. This is because vision often needs detailed and complicated preprocessing before it can be used. In addition, vision data size is relatively larger compared to the other type of input data, making it more challenging to process considering the computational resources. In this paper, current research and future development trend of robotic vision were reviewed and discussed. Further, challenges and potential issues about robot vision, such as safety and privacy concerns, were also discussed.
Artificial Intelligence and Organizational Culture: Navigating Contextual Shifts in Structure, Ethics, and Behavior Areche, Franklin Ore; Ofluoglu, Gokhan
Journal of Organizational and Human Resource Development Strategies Vol. 2 No. 02 (2025): Journal of Organizational and Human Resource Development Strategies
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/ohds.v2i02.1062

Abstract

This article explores the transformative impact of Artificial Intelligence (AI) on organizational culture. With the increasing integration of AI technologies into business operations, organizational dynamics, decision-making structures, and cultural norms are experiencing significant shifts. This qualitative-descriptive study reviews the literature and synthesizes empirical and theoretical perspectives on how AI reshapes organizational culture, focusing on decentralization, transparency, digitalization, and employee-manager relations. The article also highlights the role of deep learning and artificial neural networks as key technological drivers of this cultural evolution. The results underline the need for adaptive organizational models that integrate AI ethically and strategically.