As a main new business model of Internet plus foreign trade, cross-border e-commerce has become an important way and breakthrough for China creating new foreign trade requirements in Internet economy. Cross-border supply chain management is one of the most important supports for cross-border e-commerce. Compared with domestic e-commerce, the supply chain of cross-border e-commerce faces more risks. In order to effectively identify and avoid the operational risks in the cross-border e-commerce supply chain, this article firstly analyzes the cross-border e-commerce supply chain risks from the operation process of the cross-border e-commerce supply chain. The risks include product selection management risks, cross-border transaction risks, and customs clearance risks that exist in the operation of cross-border e-commerce. Secondly, the cross-border e-commerce supply chain risk evaluation index system is established based on the risk elements. Finally, the risk evaluation is carried out through the FUZZY-ISM evaluation method, and the internal connection of each risk factor and the risk generation mechanism are revealed through structural model analysis, which provides a theoretical reference for cross-border e-commerce enterprise supply chain risk management.
Nowadays, people are suffering from various psychological problems such as insomnia, melancholia, anxiety, oppression, etc., but the current psychological counseling service system can not meet the increasing requirement. In this paper, we propose a new online psychological counseling framework, Psycare, which comes up with several significant features: (1)Automatic self-help in mind to customers with support of the accumulation of rich psychological data and a powerful data analysis system; (2) Seamless integration of mobile and the web, by which the customers' psychological changes are easily to be captured and recorded; (3)Multi-dimensional psychological screening by experts and intelligent module; (4)Personalization, tracking the whole process of therapy of each customer, which makes the new model as the user's personal mental coach. We have implemented Psycare, and after its deployment, we get more and more positive feedbacks from its clients.
As the development and progress of the society, human beings are suffering from pressure while working, studying, and living. Many researches have been done on cognitive behavior therapy to solve this problem. In this paper, we introduce our mental health self-help system which applies machine learning to cognitive-behavior therapy. Accord ing to the randomized controlled user study, our system is proven effective to reduce users' depressive disorders.
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