Zahari Taha – författare

Research Paper (undergraduate) from the year 2011 in the subject Business economics - Business Management, Corporate Governance, grade: PhD candidate, The University of Malaya (Department of Engineering Design and Manufacture, Faculty of Engineering), course: Technology, Management, language: English, abstract: The number of small and medium enterprises (SMEs), especially those involved with research and development (R&D) programs and employed virtual teams to create the greatest competitive advantage from limited labor are increasing. Global and localized virtual R&D teams are believed to have high potential for the growth of SMEs. Due to the fast-growing complexity of new products coupled with new emerging opportunities of virtual teams, a collaborative approach is believed to be the future trend. This research explores the effectiveness of virtuality in SMEs' virtual R&D teams. Online questionnaires were emailed to Malaysian manufacturing SMEs and 74 usable questionnaires were received, representing a 20.8 percent return rate. In order to avoid biases which may result from pre-suggested answers, a series of open-ended questions were retrieved from the experts. This study was focused on analyzing an open-ended question, whereby four main themes were extracted from the experts' recommendations regarding the effectiveness of virtual teams for the growth and performance of SMEs. The findings of this study would be useful to product design managers of SMEs in order to realize the key advantages and significance of virtual R&D teams during the new product development (NPD) process. This in turn, leads to increased effectiveness in new product development's procedure.

Scientific Essay from the year 2011 in the subject Leadership and Human Resources - Miscellaneous, The University of Malaya (Faculty of Engineering), language: English, abstract: In this paper, we present our more than two years research experiences on virtual R&D teams in small and medium-sized enterprises (SMEs) and draws conclusions, giving special attention to the structure of virtual teams required to support education-industry collaboration. We report the relevant results of an online survey study. The online questionnaire was emailed by using a simple random sampling method to 947 manufacturing SMEs. The findings of this study show that SMEs in Malaysia and Iran are willing to use virtual teams for collaboration and the platform for industry-education collaboration is ready and distance between team members or differences in time zones, are not barriers to industry-education collaborations.

This short book provides a concise study of the mechanics of head impact in a soccer heading manoeuvre. It describes the development and validation of finite element models of soccer ball and human head, as well as the simulation of brain dynamics after ball-to-head impact. In addition, it also presents a computational study of the efficacy of wearing protective headgear in mitigating the risk of concussion due to heading in soccer.

This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. The sport of archery is often associated with a myriad of performance indicators namely bio-physiological, psychological, anthropometric as well as physical fitness. Traditionally, the determination of potential archers is carried out by means of conventional statistical techniques. Nonetheless, such methods often fall short in associating non-linear relationships between the variables. This book explores the notion of machine learning that is capable of mitigating the aforesaid issue. This book is valuable for coaches and managers in identifying potential archers during talent identification programs.​

This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. The sport of archery is often associated with a myriad of performance indicators namely bio-physiological, psychological, anthropometric as well as physical fitness. Traditionally, the determination of potential archers is carried out by means of conventional statistical techniques. Nonetheless, such methods often fall short in associating non-linear relationships between the variables. This book explores the notion of machine learning that is capable of mitigating the aforesaid issue. This book is valuable for coaches and managers in identifying potential archers during talent identification programs.​

This book gathers the Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications (RITA 2018). Reflecting the conference’s main theme, “Robotics and Machine Intelligence: Building Blocks for Industry 4.0,” it features relevant and current research investigations into various aspects of these building blocks. The areas covered include: Instrumentation and Control, Automation, Autonomous Systems, Biomechatronics and Rehabilitation Engineering, Intelligent Systems, Machine Learning, Robotics, Sensors and Actuators, and Machine Vision, as well as Signal and Image Processing. A valuable asset, the book offers researchers and practitioners a timely overview of the latest advances in robot intelligence technology and its applications.

This book gathers the Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications (RITA 2018). Reflecting the conference’s main theme, “Robotics and Machine Intelligence: Building Blocks for Industry 4.0,” it features relevant and current research investigations into various aspects of these building blocks. The areas covered include: Instrumentation and Control, Automation, Autonomous Systems, Biomechatronics and Rehabilitation Engineering, Intelligent Systems, Machine Learning, Robotics, Sensors and Actuators, and Machine Vision, as well as Signal and Image Processing. A valuable asset, the book offers researchers and practitioners a timely overview of the latest advances in robot intelligence technology and its applications.

This book gathers the Proceedings of the 6th International Conference on Robot Intelligence Technology and Applications (RITA 2018).

This book highlights the fundamental association between aquaculture and engineering in classifying fish hunger behaviour by means of machine learning techniques. Understanding the underlying factors that affect fish growth is essential, since they have implications for higher productivity in fish farms. Computer vision and machine learning techniques make it possible to quantify the subjective perception of hunger behaviour and so allow food to be provided as necessary. The book analyses the conceptual framework of motion tracking, feeding schedule and prediction classifiers in order to classify the hunger state, and proposes a system comprising an automated feeder system, image-processing module, as well as machine learning classifiers. Furthermore, the system substitutes conventional, complex modelling techniques with a robust, artificial intelligence approach. The findings presented are of interest to researchers, fish farmers, and aquaculture technologist wanting to gain insights into the productivity of fish and fish behaviour.