The authors propose an adaptive face recognition algorithm based on the discrete cosine transform (DCT) coefficients approach. For the database's establishment, the face images are pre‐processed with colour transform, hair cutting, and background removing to eliminate non‐face information. The recognised kernel applied the weights of DCT coefficient distribution with the entire image transformation, to avoid position mismatch and reduce the light effect. The key coefficients of DCT are chosen from the training database by maximum variance. The fast search mode can reject 90% weak candidates with few coefficients to fasten the processing speed. The significant coefficients weighting methods are used to enhance face features. Only using 50 coefficients per picture, the recognition rate can achieve 95% for ORL face database testing. For real‐time recognition, camera imaging is processed with algorithms using C‐programming based on Windows system. The recognition rate can achieve 95% and the speed is about nine frames per second for real‐time recognition in practice.

Summary Various functional units (FUs) have been designed in modern embedded processors to perform different functions when running an application. Traditionally, compilers did not take this characteristic into account to reduce the temperature of a processor during execution. For many applications, the occurrences of different instructions are not the same after they are compiled. As a consequence, the temperature of the processor is very high, arising from the major heating contribution of the special structure of the active functional unit, and thus, the system will suffer severe damage. Consequently, to remedy this hurdle, this paper provides a solution by shifting the loading from heavy‐loading FUs to light‐loading FUs. Our approach first identifies all the FUs that can exchange the loading among themselves and then presents a thermal model for these exchangeable FUs to estimate the temperature impact on shifting loading. Finally, the loading shifting has been performed by transforming code under the consideration of limited performance loss without hardware cost. The result shows that our approach can reduce the temperature to a small cost of performance degradation and code expansion. Copyright © 2014 John Wiley & Sons, Ltd.

Various functional units (FUs) have been designed in modern embedded processors to perform different functions when running an application. For many applications the occurrences of different instructions are not the same after they are compiled. As a consequence, the temperature of the processor is very high arising from the major heating contribution of the special structure active functional unit and thus the system will suffer severe damage. Thus, to remedy this hurdle, this paper provides a solution by shifting the loading from heavy-loading FUs to light-loading FUs. Our approach first identifies all FUs that can exchange the loading among them and then presents a thermal model for these exchangeable FUs to estimate the temperature impact on shifting loading. Finally, the loading shifting has been performed by transforming code under the consideration of limited performance loss without hardware cost. The result shows that our approach can reduce the temperature at the small cost of performance degradation and code expansion.

With the rapid increase of multimedia technology [1], [2], the support of network traffic has become an important issue. Thus many protocols have been developed to address this issue in different network layers such as Real Time Streaming Protocol (RTSP) [3], Smooth Streaming [4] in application layer, and Real time Protocol (RTP) in transport layer. The common characteristic of these protocols is the requirement of data smoothing to support modern application like intelligent home and vehicular network. In addition, smart phone and wireless sensor network(WSN) [5] do not support all protocols, indeed, they may only support Transmission Control Protocol(TCP) or User Data gram Protocol(UDP). This implies that the network bandwidth will nor be good enough to play high quality multimedia streaming and support complicated network structure. In this paper, we present a smooth data streaming approach on application layer to reduce packet retransmission and improve performance. The proposed approach can provide smooth data streaming and reduce response time with the aid of data caching or data compression without increase the complexity of network protocol. In order to decrease the development complexity arising from UDP, instead, we implement the proposed approach based on TCP. We also analyze the impact of this work and discuss challenges in TCP in this paper. The result shows that the proposed approach can stabilize smooth data transmission and improve performance by 20% to 35% for benchmarks.

In a multidatabase system, the participating databases are autonomous. The schemas of these databases may be different in various ways, while the same information is represented. A global query issued against the global database needs to be translated to a proper form before it can be executed in a local database. Since data requested by a query (or a part of a query) is sometimes available in multiple sites, the site (database) that processes the query with the least cost is the desired query processing site. The authors study the effect of differences in schemas on the cost of query processing in a multidatabase environment. They first classify schema conflicts to different types. For each type of conflict, they show how much more or less complex a translated query can become in comparison with the originally user-issued global query. Based on this observation, they propose an analytical method that considers the conflicts between local databases and finds the database(s) that renders the least execution cost in processing a global query. This research introduces a new level of query optimization (termed the schema-level optimization) in multidatabase environments. The results provide a new dimension of enhancement for the capability of a query optimizer in multidatabase systems.