Zhejiang Gongshang University

About: Zhejiang Gongshang University is a education organization based out in Hangzhou, China. It is known for research contribution in the topics: Adsorption & Supply chain. The organization has 8258 authors who have published 7670 publications receiving 90296 citations. The organization is also known as: Zhèjiāng Gōngshāng Dàxué.

Personalized Services Recommendation Based on Context-Aware QoS Prediction

Abstract: With the increase of published Web services, it has become a great challenge to recommend service consumers the best services with regard to the quality of services (QoS). Collaborative filtering is often employed to predict the QoS of a specific service to a certain consumer. However, in existing collaborative filtering based service recommendation approaches, the context under which consumers submit a recommendation request is seldom taken into account when filtering similar recommenders and their corresponding experience. In this paper, we propose a new method dubbed CASR (Context-Aware Services Recommendation) by referring to previous service invocation experiences under similar context with the current consumer, which is of great importance in the personalized service recommendation system. First, the proposed algorithm clusters the service invocation records according to the similarity on context properties and selects the cluster that is most similar to the context of current consumer. Then it predicts the QoS of an unused service for current consumer based on the filtered recommendation records by Bayesian inference. Experimental results demonstrate that the proposed approach can significantly improve the accuracy of QoS prediction and service recommendation.

Effects of Food-Additive-Information on Consumers' Willingness to Accept Food with Additives.

Abstract: This study tested whether information on positive food additives and negative food additives had an effect on consumers’ risk perception and their willingness to accept (WTA) food with additives. Consumers’ WTA was examined via a random nth-price auction of exchanging freshly squeezed orange juice without additives for orange juice with additives. Results show that consumers’ WTA differs with the order in which information was provided. Consumers are generally more sensitive to negative than positive information on additives. Female, middle-educated consumers are more susceptible to additive information and their WTA is more likely to change, while postgraduate-educated consumers are less sensitive to additive information. Consumers with higher food-safety satisfaction have lower WTA than those who are not satisfied with food safety. However, their satisfaction is easily affected by the negative-information intervention. Interestingly, consumers with relatively good knowledge of additives had higher WTA than those with no such knowledge. This study provides insight on how to establish effective food-safety-risk communication. Government and non-government agencies need to timely and accurately eliminate food-safety scares through the daily communication and disclosure of food-safety information, as well as prevent the misguidance of negative food safety-risk information.

Fuji Apple Storage Time Predictive Method Using Electronic Nose

Abstract: An electronic nose-based Fuji apple storage time prediction method is investigated in this paper. A home-made electronic nose with eight metal oxide semiconductors gas sensor array was used to measure the apples stored at room temperature. Principal component analysis cannot discriminate all samples. Stochastic resonance signal-to-noise ratio spectrum distinguishes fresh, medium, and aged apples successfully. The prediction model is developed based on signal-to-noise ratio maximums. In validating experiments, results show that the predicting accuracy of this model is 84.62 %. This method takes some advantages including fast detection, easy operation, high accuracy, and good repeatability.