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Mass production of individualized products becomes essential for delivering personalized customer experience in the Industrial Revolution 4.0 era. Developing seamless value chain integration between enterprises, such as suppliers, retailers, and manufacturers, to achieve mass production of individualized products is challenging. This paper proposes a method of asset integration and asset data channeling between enterprises in a value chain, namely Asset Administration System (AAdSys), designed based on RAMI 4.0. A use case that involves PEC application and OMIS manufacturing line for full automation of individualized mixed juice production is developed. The use case demonstrates how data channeling between a retailer and a manufacturer using AAdSys can be done.

Digital disruption creates a lot of new entrepreneurship opportunities, affecting existing businesses at a very fast pace. Therefore using traditional classroom method to teach entrepreneurship to only business schools students no longer applicable. Students in the 21st century should be trained via project-based learning by leveraging the strength of the members from multi-disciplines. This research proposes a model on how entrepreneurship education (EE) could be introduced into university undergraduate programs across faculties towards entrepreneurial and commercialization pathway. The model has been developed and tested within 2 years, with few hundreds of computing and information technology students, supported by other faculties, related centers and representatives from the industry. It is believed that project-based learning does not only affect students’ attitudes to be more industry-relevant and stimulate entrepreneurial intention, but also creating actual start-up and commercialization opportunities.

Learner centred design (LCD)focuses on creating an e-learning system that can fulfil individual needs through personalization, nevertheless ther e are still many technical challenges. Besides, losing balanced focus on both of the learners and the instructorsdoes not help to create a successfule-learning system. User-centred design helps to improve the usability of a system as it integrates requirements and user interface designs based on users’ needs. The findings of this research prove that even the users are provided with the same LMS, not everyone has the same perception s or tolerance levels of the seven design factors that may cause frustrations to the users, and not everyone has the same satisfaction level of navigation experience and interface design.It is important for the LMS developers to understand that the variations between roles, genders, experiences and ages exist and should not be i gnored when designing the system.

To build a personalized e-learning system that can deliver adaptive learning content based on student’s cognitive effort and efficiency, it is important to develop a construct that can help measuring perceived mental state, such as stress and cognitive load. The construct must be able to be quantified, computerized and automated. Our research investigates how mouse and keyboard dynamics analyses could be used to detect cognitive stress, which is induced by high mental arithmetic demand with time pressure, without using intrusive and expensive equipment. The research findings suggest that when task demand increased, task error, task duration, passive attempt, stress perception and mouse idle duration may increase, while mouse speed, left mouse click and keystroke speed decreased. The significant effects of task demand and time pressure on mouse and keystroke behaviours suggest that stress evaluation from these input devices is potentially useful for designing an adaptive e-learning system.

Much research has been done to detect human emotion using various computational methods, such as physiological measures and facial expression recognition. These methods are effective but they could be expensive or intrusive as special setups of equipment are needed. Some researchers have utilized nonintrusive methods by using mouse or keyboard analyses and presented comparable effectiveness in detecting human emotion. This paper investigates how both keyboard and mouse features can be combined to detect human stress, particularly cognitive stress induced by time pressure and mental arithmetic problems. The results show that the complexity of the mental arithmetic problem and time pressure affect user behaviour, mouse behaviour and keyboard behaviour significantly. This indicates that automatic analysis of human stress from keyboard and mouse input is potentially useful for providing adaptation in interactive systems such as an e-learning system.