Kuo-Pao Tsai’s research while affiliated with National Tsing Hua University and other places

Music has become a part of many people's lives. Early adopters used to buy tapes or CDs to listen to music, which were difficult to preserve and easily damaged. With the digital transfor-mation of the industry, users nowadays can listen to various genres/styles of music online through digital music platforms at any time. As the types and styles of music are numerous, some digital music platforms have begun to consider providing more diverse ways of delivering music listening services. For example, various music classification systems allows users to easily find all albums by the same singer; different styles of music streaming services save users time in searching for songs of the same type; and the ability to share playlists allows users to share their listening playlists with family and friends. This service model increases peer discussion topics and exposure to albums, songs, and singers. The study summarizes the driving factors influencing the adoption of digital music subscription services using expert interviews and literature reviews. The study outlines four adoption-driving dimensions (service benefits, service efficiency, behavioral attribution, and adoption intention) and 16 evaluation criteria. Besides, this study integrates Desire and Satisfaction Analysis (DSA) and Network Relation Map (NRM) to propose a DSA-NRM analysis to evaluate the adoption strategy and optimal development path for digital music subscription services. Based on the four quadrants of music subscription services, this study proposes four selected strategies (attention strategy, sustainment strategy, adjustment strategy, and focus strategy). The research results show that the SB (service benefits) aspect has high desire and low satisfaction and can adopt selected strategy D (focus Strategy). The AI (adoption intention) aspect is an aspect with intense desire and low satisfaction and can use strategy C (adjustment strategy) chosen. The AI (adoption intention) aspect can dominate other aspects, and the SE (service effectiveness) can be dominated by different aspects.

Background: Individuals with visual impairment currently rely on walking sticks and guide dogs for mobility. However, both tools require the user to have a mental map of the area and cannot help the user establish detailed information about their surroundings, including weather, location, and businesses. Purpose and Methods: This study designed a navigation and recommendation system with context awareness for individuals with visual impairment. The study used Process for Agent Societies Specification and Implementation (PASSI), which is a multiagent development methodology that follows the Foundation for Intelligent Physical Agents framework. The model used the Agent Unified Modeling Language (AUML). Results: The developed system contains a context awareness module and a multiagent system. The context awareness module collects data on user context through sensors and constructs a user profile. The user profile is transferred to the multiagent system for service recommendations. The multiagent system has four agents: a consultant agent, search agent, combination agent, and dispatch agent and integrates machine and deep learning. AUML tools were used to describe the implementation and structure of the system through use-case graphics and kit, sequence, class, and status diagrams. Conclusions: The developed system understands the needs of the user through the context awareness module and finds services that best meet the user's needs through the agent recommendation mechanism. The system can be used on Android phones and tablets and improves the ease with which individuals with visual impairment can obtain the services they need.