Key factors of adopting energy management systems in building sector in Taiwan

It is no doubt the world is experiencing global warming and human emission causes distinct climate change. According to the analysis from International Energy Agency, the over consumed nature resources from power, industry, transport and building sectors are off the major factors reflecting on the essential greenhouse gases to life. As moving onto the smart technology and smart grid development, recent studies indicate that using the advanced energy management systems is critical to improve power efficiency, energy saving, and reduce greenhouse gas emission. This study relies on a systematic literature review and expert opinion to identify the critical factors of adoption building energy management system. Finally, a framework is presented to evaluate the introduction of energy management systems in the construction field in order to achieve zero carbon ready buildings

How and When Review Length and Emotional Intensity Influence Review Helpfulness: Empirical Evidence from Epinions.com

Although longer reviews are generally considered more helpful, no research has investigated whether “the more the better” also applies to the expression of emotions. This paper explores the distinct effects of review length and emotional intensity. We propose that, in contrast to review length, the intensity of emotions has a negative effect on review helpfulness, and that this effect only applies to positive emotions. Additionally, drawing on elaboration likelihood model and the literature on the social functions of emotions, we predict that the respective effects of review length and emotional intensity are moderated by reviewer trustworthiness and the difficulty of reading review content. To test these hypotheses, we collected a rich data set from Epinions.com - a leading provider of consumer reviews. Our findings reveal the importance of taking the intensity of emotions into consideration when evaluating review helpfulness, and the results carry important practical implications

Acute aortic dissection mimicking as ureteral calculus

AbstractAcute aortic dissection is an uncommon but life-threatening emergency, which is often missed in up to 38% of patients on initial evaluation, and in up to 28% of patients the diagnosis is made at autopsy. Painless aortic dissection has been reported, but is relatively uncommon. The mortality rates are estimated at 50% by 48 hours and increase by 1% per hour if undiagnosed. We report a case of atypical aortic dissection who presented to ER with subtle unspecific renal colicky like pain as a primary symptom, which had made the prompt diagnosis very challenging and difficult

The Role Of The CEO, Executive Team, And Workforce Metrics Of A Small University In The U.S.

The Role of the CEO, Executive Team, and Workforce Metrics of a small University in the U.S. is not just a question of academic standards. The 21st century requirements of education involve a wider set of attributes, equipping the young with social and organizational skills to cope with adult life inside and outside the workplace (Barber, 2001). It is necessary to describe the importance of aligning clear strategic priorities with workforce metric of a small university in the U.S. In addition, effective strategy execution requires a new partnership between the CEO, the workforce, and a small university’s HR function. Therefore, providing insights into the execution challenge, with examples of how a small university has developed workforce and HR strategies to drive strategy execution efforts, and offering suggestions about workforce metrics might enhance the success in strategy execution

Weakly-supervised Caricature Face Parsing through Domain Adaptation

A caricature is an artistic form of a person's picture in which certain striking characteristics are abstracted or exaggerated in order to create a humor or sarcasm effect. For numerous caricature related applications such as attribute recognition and caricature editing, face parsing is an essential pre-processing step that provides a complete facial structure understanding. However, current state-of-the-art face parsing methods require large amounts of labeled data on the pixel-level and such process for caricature is tedious and labor-intensive. For real photos, there are numerous labeled datasets for face parsing. Thus, we formulate caricature face parsing as a domain adaptation problem, where real photos play the role of the source domain, adapting to the target caricatures. Specifically, we first leverage a spatial transformer based network to enable shape domain shifts. A feed-forward style transfer network is then utilized to capture texture-level domain gaps. With these two steps, we synthesize face caricatures from real photos, and thus we can use parsing ground truths of the original photos to learn the parsing model. Experimental results on the synthetic and real caricatures demonstrate the effectiveness of the proposed domain adaptation algorithm. Code is available at: https://github.com/ZJULearning/CariFaceParsing .Comment: Accepted in ICIP 2019, code and model are available at https://github.com/ZJULearning/CariFaceParsin

Alternative Ingredient Recommendation: A Co-occurrence and Ingredient Category Importance Based Approach

As many people will refer to a recipe when cooking, there are several recipe-sharing websites that include lots of recipes and make recipes easier to access than before. However, there is often the case that we could not get all the ingredients listed on the recipe. Prior research on alternative ingredient substitution has built a recommendation system considering the suitability of a recommended ingredient with the remained ingredients. In this paper, in addition to suitability, we also take the diversity of the ingredient categories and the novelty of new combination of ingredients into account. Besides, we combine suitability with novelty as an index, to see whether our method could help find out a new combination of ingredients that is possibly to be a new dish. Our evaluation results show that our proposed method attains a comparable or even better performance on each perspective