On-demand learning for a wireless campus

The current Internet and wireless networks are harsh environments for transporting high-bandwidth multimedia data. We examine the technical issues involved, and describe an end-to-end solution to support a Web-based learn-on-demand system that operates in a wireless campus environment.     

Radiometric sensor for temperature control of food processing

This paper describes a novel planar antenna sensor created for the purpose of noninvasive temperature measurements using microwave radiometry. In order to improve radiometric measurements in industrial applications, a new generation of sensors is introduced, composed of a metallic sheet. Simulations based upon the method of moments is used both to design and to determine their electromagnetic performances. This paper also describes a radiometric device using these sensors to measure and control the temperature of food products during deep freezing processes. The results and discussions are presented.     

A fuzzy logic based-method for prognostic decision making in breast and prostate cancers

Accurate and reliable decision making in oncological prognosis can help in the planning of suitable surgery and therapy, and generally, improve patient management through the different stages of the disease. In recent years, several prognostic markers have been used as indicators of disease progression in oncology. However, the rapid increase in the discovery of novel prognostic markers resulting from the development in medical technology, has dictated the need for developing reliable methods for extracting clinically significant markers where complex and nonlinear interactions between these markers naturally exist. The aim of this paper is to investigate the fuzzy k-nearest neighbor (FK-NN) classifier as a fuzzy logic method that provides a certainty degree for prognostic decision and assessment of the markers, and to compare it with: 1) logistic regression as a statistical method and 2) multilayer feedforward backpropagation neural networks an artificial neural-network tool, the latter two techniques having been widely used for oncological prognosis. In order to achieve this aim, breast and prostate cancer data sets are considered as benchmarks for this analysis. The overall results obtained indicate that the FK-NN-based method yields the highest predictive accuracy, and that it has produced a more reliable prognostic marker model than both the statistical and artificial neural-network-based methods.     

Exposed Die-Top Encapsulation Molding for an Improved High- Performance Flip Chip BGA Package

The recent advancement in high- performance semiconductor packages has been driven by the need for higher pin count and superior heat dissipation. A one-piece cavity lid flip chip ball grid array (BGA) package with high pin count and targeted reliability has emerged as a popular choice. The flip chip technology can accommodate an I/O count of more than five hundreds500, and the die junction temperature can be reduced to a minimum level by a metal heat spreader attachment. None the less, greater expectations on these high-performance packages arose such as better substrate real estate utilization for multiple chips, ease in handling for thinner core substrates, and improved board- level solder joint reliability. A new design of the flip chip BGA package has been looked into for meeting such requirements. By encapsulating the flip chip with molding compound leaving the die top exposed, a planar top surface can be formed. A, and a flat lid can then be mounted on the planar mold/die top surface. In this manner the direct interaction of the metal lid with the substrate can be removed. The new package is thus less rigid under thermal loading and solder joint reliability enhancement is expected. This paper discusses the process development of the new package and its advantages for improved solder joint fatigue life, and being a multichip package and thin core substrate options. Finite-element simulations have been employed for the study of its structural integrity, thermal, and electrical performances. Detailed package and board-level reliability test results will also be reported     

Switched-Current Filters Revisited: Square-Root Domain Sampled-Data Filters

In this brief, the well-known switched-current (SI) filtering technique is revisited using the concept of the square-root domain (SRD) filtering. It is proved that SI filters are a subclass of the SRD filters, where sampled-data signal processing is performed. This is achieved by considering typical lossless and lossy SRD sampled-data integrator configurations, using a set of complementary SRD operators which are based on the quadratic I-V relationship of MOS transistor operated in the saturation. Circuit examples are given, where linear-domain integrator and third-order filter configurations were derived using appropriate SRD sampled-data building blocks     

基于USB总线的虚拟频谱分析仪设计

文章详细介绍了基于USB总线的虚拟频谱分析仪的设计过程。该仪器使用嵌入式混合处理器MC56F8323来实现动态信号的实时采集、频谱分析和数字滤波等功能。处理结果由USB2．0接口芯片CY7C68013上传至PC机．以完成数据显示、存储、绘制图形等功能。其中，CY7C68013工作于Slave FIFO模式，以实现与MC56F8323间的数据传输。该系统可同时对两路动态信号进行实时谱分析，每路采样频率高选500kHz。     

Routing Correlated Data with Fusion Cost in Wireless Sensor Networks

In this paper, we propose a routing algorithm called minimum fusion Steiner tree (MFST) for energy efficient data gathering with aggregation (fusion) in wireless sensor networks. Different from existing schemes, MFST not only optimizes over the data transmission cost, but also incorporates the cost for data fusion, which can be significant for emerging sensor networks with vectorial data and/or security requirements. By employing a randomized algorithm that allows fusion points to be chosen according to the nodes' data amounts, MFST achieves an approximation ratio of 5/4log(k + 1), where k denotes the number of source nodes, to the optimal solution for extremely general system setups, provided that fusion cost and data aggregation are nondecreasing against the total input data. Consequently, in contrast to algorithms that only excel in full or nonaggregation scenarios without considering fusion cost, MFST can thrive in a wide range of applications