In every field of engineering, testing is a fundamental step for the validation of design, being the most direct way to verify that a product meets its specifications. If the desired performance is not achieved, testing should identify all the causes of malfunctioning and indicate suitable corrective actions. Different algorithms relying on the symbolic approach have been presented in the past by the authors and in this work noteworthy improvements on these algorithms are proposed. However, how the testability is designed to maintain devices during its lifetime is discussed lack at present. Furthermore, this problem concerns needing more times on testing and fault diagnosis, and wasting more manpower and material resources. Especially in the army devices field, it is very important that maintenance and indemnificatory are advanced. In this paper, the parameters in testability design for fault detection and diagnosis will be given. The detailed contents of testability will be proposed, including the dividing of circuit module in equipment, technology material needed for detection and requirement of specifications used for testing.

Personalized service systems are an effective way to help users obtain recommendations for unseen items, within the enormous volume of information available based on their preferences. The most commonly used personalized service system methods are collaborative filtering, content-based filtering, and hybrid filtering. Unfortunately, each method has its drawbacks. This paper proposes a new method which unified partition-based collaborative filtering and meta-information filtering. In partition-based collaborative filtering the user-item rating matrix can be partitioned into low-dimensional dense matrices using a matrix clustering algorithm. Recommendations are generated based on these low-dimensional matrices. Additionally, the very low ratings problem can be solved using meta-information filtering. The unified method is applied to a digital resource management system. The experimental results show the high efficiency and good performance of the new approach.