Scalable Model of On-Wafer Interconnects for High-Speed CMOS ICs

This paper describes the development of an equivalent circuit model of on-wafer interconnects for high-speed CMOS integrated circuits. By strategically cascading two-pi blocks together, the lumped model can characterize the distributed effects. Besides, the elaborately proposed model characterizes the frequency-variant characteristics with frequency-independent components. Thus, the model can be easily plugged into commercial computer-aided design tools. By adopting a newly invented optimization algorithm, namely, particle swarm optimization (PSO), the model parameters are extracted and formulated as empirical expressions. Therein, with each set of the geometrical parameters, the interconnect behaviors can be accurately predicted. The accuracy of the model is validated by comparisons with the on-wafer measurements up to 30 GHz. Moreover, the scalability of the proposed model is also discussed     

Thermal resistance analysis and validation of flip chip PBGA packages

This work proposes a finite element numerical methodology to predict the thermal resistance of both flip chip-plastic ball grid array (FC-PBGA) with a bare die and FC-PBGA with a metal cap. The 3D finite element model was initially constructed to simulate the thermal resistance of FC-PBGA. A thermal resistance experiment was performed to verify the FEM results, following the construction of specimens of FC-PBGA with a bare die and with an aluminum cap, using six-layered substrate. The verified finite element model was employed to determine the thermal resistance of FC-PBGA with a copper cap using four-layered and six-layered substrates. Experimental results demonstrated that FC-PBGA with a metal cap improves thermal performance by 35% over with a bare die. FC-PBGA with a copper cap slightly improves thermal performance from 2% to 2.8% over that of FC-PBGA with an aluminum cap. The thermal resistance of FC-PBGA with a four-layered substrate is reduced by 4.0% to 5.9% from that of FC-PBGA with a six-layered substrate, since the four-layered substrate contains less metal. The finite element numerical results negligibly differ from the experimental results by 6% to 8.1%. A finite element numerical methodology is here proposed to predict the thermal resistance of FC-PBGA. The methodology is effective in researching and developing new products or improving existing packages.     

Application of marching cubes algorithm in visualization of mineral deposits

An implementation scheme of the marching cubes (MC) algorithm was presented for the visualization of mineral deposits. The basic principles, processes and pitfalls of the MC algorithm were discussed. The asymptotic decider algorithm was employed to solve the ambiguity problem associated with the MC algorithm. The implementation scheme was applied to model and reconstruct the surfaces of mineral deposits, using the geological data obtained from an iron mine in China. Experimental results demonstrate the ability of the implementation scheme to solve the ambiguity problem, and illustrate the effectiveness and efficiency of the MC algorithm in the visualization of mineral deposits.     

Progressive Simplification of Tetrahedral Meshes Preserving All Isosurface Topologies

In this paper, we propose a novel technique for constructing multiple levels of a tetrahedral volume dataset whilepreserving the topologies of all isosurfaces embedded in the data. Our simplification technique has two majorphases. In the segmentation phase, we segment the volume data into topological‐equivalence regions, that is, thesub‐volumes within each of which all isosurfaces have the same topology. In the simplification phase, we simplifyeach topological‐equivalence region independently, one by one, by collapsing edges from the smallest to the largesterrors (within the user‐specified error tolerance, for a given error metrics), and ensure that we do not collapseedges that may cause an isosurface‐topology change. We also avoid creating a tetrahedral cell of negative volume(i.e., avoid the fold‐over problem). In this way, we guarantee to preserve all isosurface topologies in the entiresimplification process, with a controlled geometric error bound. Our method also involves several additionalnovel ideas, including using the Morse theory and the implicit fully augmented contour tree, identifying typesof edges that are not allowed to be collapsed, and developing efficient techniques to avoid many unnecessary orexpensive checkings, all in an integrated manner. The experiments show that all the resulting isosurfaces preservethe topologies, and have good accuracies in their geometric shapes. Moreover, we obtain nice data‐reductionrates, with competitively fast running times.     

Identifying managers who need ethics training in using IT at work

This paper identifies managers who require ethics training in using IT at work. The identification of these managers is mainly based on studying the impact of their individual characteristics on a set of seven ethical issues and attitudes, which translated into IT ethical scenarios. This paper proposes a canonical model by treating individual characteristics of managers as predictor variables and considering information describing their beliefs on those seven ethical issues and attitudes as explained variables. A questionnaire survey was used for data collection and 249 managers participated in this study. The results show that the significant explained variables are based on a combination of six ethical events of accountability, conflict of interest, disclosure, personal conduct, protection of privacy, and social responsibility. The significant predictor variables are based on a combination of four individual characteristics of age, educational level, organizational level, and working experience. Discussion on the implication of the results and recommendations for remedial action are also provided in this paper.     

A new kernel-based fuzzy clustering approach: support vector clustering with cell growing

In this paper, the support vector clustering is extended to an adaptive cell growing model which maps data points to a high dimensional feature space through a desired kernel function. This generalized model is called multiple spheres support vector clustering, which essentially identifies dense regions in the original space by finding their corresponding spheres with minimal radius in the feature space. A multisphere clustering algorithm based on adaptive cluster cell growing method is developed, whereby it is possible to obtain the grade of memberships, as well as cluster prototypes in partition. The effectiveness of the proposed algorithm is demonstrated for the problem of arbitrary cluster shapes and for prototype identification in an actual application to a handwritten digit data set.     

Query optimization in multidatabase systems considering schemaconflicts

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     

Knowledge-based system for railway scheduling

In this paper, we describe a Knowledge-Based railway scheduling system (called RSS) for Taiwan Railway Administration's (TRA) railway scheduling operations. In our approach, the scheduling process is divided into two levels: global scheduling and local scheduling. In global scheduling, an initial train diagram is established by the Global Scheduler according to the master scheduling plan without considering conflicts. In local scheduling, scheduling conflicts are repaired by Local Scheduler. An embedded knowledge base provides advice for conflict resolution. Since cycles may exist among a sequence of repairs during the repair process, we also propose a cycle detection and resolution scheme in this paper. Through a graphic user interface, the user can interact with the Automatic Scheduler to solve the large-scale complex train scheduling problem in a cooperative and flexible fashion.     

Fast image retrieval using color-spatial information

In this paper, we present an image retrieval system that employs both the color and spatial information of images to facilitate the retrieval process. The basic unit used in our technique is a single-colored cluster, which bounds a homogeneous region of that color in an image. Two clusters from two images are similar if they are of the same color and overlap in the image space. The number of clusters that can be extracted from an image can be very large, and it affects the accuracy of retrieval. We study the effect of the number of clusters on retrieval effectiveness to determine an appropriate value for “optimal' performance. To facilitate efficient retrieval, we also propose a multi-tier indexing mechanism called the Sequenced Multi-Attribute Tree (SMAT). We implemented a two-tier SMAT, where the first layer is used to prune away clusters that are of different colors, while the second layer discriminates clusters of different spatial locality. We conducted an experimental study on an image database consisting of 12,000 images. Our results show the effectiveness of the proposed color-spatial approach, and the efficiency of the proposed indexing mechanism. Received August 1, 1997 / Accepted December 9, 1997     

Genetic algorithms combined with discriminant analysis for key variable identification

Many trouble-shooting problems in process industries are related to key variable identification for classifications. The contribution charts, based on principal component analysis (PCA), can be applied for this purpose. Genetic algorithms (GAs) have been proposed recently for many applications including variable selection for multivariate calibration, molecular modeling, regression analysis, model identification, curve fitting, and classification. In this paper, GAs are incorporated with Fisher discriminant analysis (FDA) for key variable identification. GAs are used as an optimization tool to determine variables that maximize the FDA classification success rate for two given data sets. GA/FDA is a proposed solution for the variable selection problem in discriminant analysis. The Tennessee Eastman process (TEP) simulator was used to generate the data sets to evaluate the correctness of the key variable selection using GA/FDA, and the T² and Q statistic contribution charts. GA/FDA correctly identifies the key variables for the TEP case studies that were tested. For one case study where the correlation changes in two data sets, the contribution charts incorrectly suggest that the operating conditions are similar. On the other hand, GA/FDA not only determines that the operating conditions are different, but also identifies the key variables for the change. For another case study where many key variables are responsible for the changes in the two data sets, the contribution charts only identifies a fraction of the key variables, while GA/FDA correctly identifies all of the key variables. GA/FDA is a promising technique for key variable identification, as is evidenced in successful applications at The Dow Chemical Company.