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For this study, we constructed the following three case scenarios based on the Taiwanese government's energy policy: a normal scenario, the 2008 “Sustainable Energy Policy Convention” scenario, and the 2011 “New Energy Policy” scenario. We then employed a long-term Generation Expansion Planning (GEP) optimization model to compare the three case scenarios' energy mix for power generation for the next a15 years to further explore their possible impact on the electricity sector. The results provide a reference for forming future energy policies and developing strategic responses.

The impact of climate change and the pressure of environmental awareness have caused the concepts of energy conservation, carbon reduction, and the sustainable engagement of a production model involving green ecology to become common development goals in power utilities worldwide. This study examines the recycling application framework of microalgal carbon fixation developed by Taipower, which has been used for the past decade, and evaluates the framework using a social survey on the social acceptability of the biotech skincare products that were exploited by microalgal carbon fixation. Research results show that Taipower’s engagement in carbon fixation using microalgae is practicable in reducing carbon, providing an additional production model of circular economy to power business development. The application of microalgal carbon fixation is projected to have numerous benefits, such as tangible profit benefit through future mass production, the intangible benefit from the image of enterprise environmental protection, and the benefit through social promotion. Therefore, focus on the sustainable development of microalgal carbon fixation is worthwhile. This study provides a guideline for future development of the recycling application of microalgal carbon fixation at Taipower and other power utilities.

The Dietary intervention is one of the major components of therapy for patients with chronic kidney disease (CKD), aiming to minimize uremic symptoms and to provide optimal nutritional status. For slowing the progression of renal failure, dietary protein restriction has been recommended for patients with CKD. However, receiving lower doses of this dietary intervention reduces its effectiveness and results in usage attrition and patient dropout. Therefore, dietary compliance has become a well-recognized challenge to the development of effective dietary protein restriction interventions. Using a food journaling app to log dietary intake has been shown to benefit people and health researchers. We hypothesized that using a food journaling app affects patients' dietary compliance (the first hypothesis), and indirectly improves health outcomes because of the increased compliance (the second hypothesis). We conducted a 12-week dietary protein restriction intervention. Twenty recruited participants were required to eat low-protein meals (0.6 g/kg ideal body weight/day), and self-report their dietary intake by using a food journaling app. Thirteen of 20 participants completed the dietary protein restriction intervention, and their health outcomes were measured according to changes in blood urea nitrogen, serum creatinine, albumin, and glycated hemoglobin compared with those who dropped out. The empirical results support the first hypothesis and show that using the food journaling app can significantly increase the dietary compliance, but the results regarding the second hypothesis were not significant.

Enhanced index investing involves tracking a benchmark index closely and using risk-controlled strategies to add modest value to the index. The typical approaches to construction of such portfolios involve subjective management judgments. A new approach to enhanced indexing instead formulates the problem as a dual-criteria goal programming problem. Unlike the traditional approaches, which require a fund manager to buy and sell stocks actively in order to improve returns, the proposed approach is based on the passive management of a small number of stocks. Empirical results from tests in the Taiwan stock market suggest the new approach incurs lower transaction costs and produces sustainable risk-controlled enhanced returns.

Recently, target analysis combined with database technology and data mining has been widely used in industries such as marketing, finance, insurance, telecommunications, advertising, and e-commerce. Because of the unique complexities of user behavior in electricity demand, examples of target analysis applications have yet to be seen. Considering the industry’s urgent need to enhance the efficiency of electricity demand-side management, this study aims to build a mining analysis model for potential target users of interruptible load that both fully reflects consumer behavior characteristics and serves as a rule for static comparisons. The results of a data mining analysis of the Taiwan Power Company (Taipower)’s interruptible loads 1 to 6 show that the number of potential target users is 1669, which is 21% of the original mining population. Additionally, the target users who were classified to have “the most potential” for all categories of interruptible load only accounted for 0.76% of the total mining population (= 59/7814), verifying the mining effects.

In this chapter, we want to determine the factors and risks that affect the viable business model for pervasive healthcare systems - with an emphasis on sleep treatment devices. We used a hybrid analysis utilizing, i) Porter’s Five Forces, to determine the competitive advantages of the pervasive healthcare industry and ii) Delta Model, to determine the three strategic options related to customer bonding and adaptive processes which support these options. We have found that with the hybrid analysis pervasive healthcare industry will be highly competitive and strive to meet customer needs making it the next big trend in the medical industry overall. In particular, the ability to customize accordingly to the patients individual conditions is a key differentiator in such an industry. In addition, the major players and value chain of the sleep treatment industry are illustrated.

A blog has the potential to change the way we perceive information and make friends. Using the value, semantic, and social model of the blogger, this work analyzes the user interfaces and user profile for a proactive recommendation. Retrieving the personal value inclination, article topic semantic, and interactive social network of the bloggers, this study has tried to step toward a blog recommendation system. Related works, analysis model, system architecture, application UI and discussion are presented.