Distributed Artificial Intelligence in manufacturing systems control

This research uses a Distributed Artificial Intelligence (DAI) framework to efficiently utilize the infrastructure available for process planning in a batch processing PWB assembly facility. The DAI approach decomposes the entire production control task into several sub-tasks. Then, the sub-tasks are implemented by the basic elements of the DAI system called ‘intelligent agents’. By working collectively, the intelligent agents of the DAI system can arrive at a solution for the problem. The DAI system initially proposes all possible solutions generated by the intelligent agents. Then, a fuzzy coordination technique is utilized to evaluate the solutions and to find the most appropriate one for shopfloor implementation. Using inputs such as the short-term production plan, design data, shopfloor observation data, and CAD information, the DAI system provides applicable production plans with ranks for the feasibility of current assembly activities.     

Simulation based alternatives for overall process improvement at the cardiac catheterization lab

Cardiac catheterization is one of the critical procedures in patient care. It is pertinent for all process related issues in this department to be handled with due priority. This research is a cross-functional effort with a leading hospital that was in its planning stage to implement an overall process improvement at its cardiac catheterization lab department. It has been determined that significant process delays exist in this department. One of the identified key factors to process improvement was to reduce patient turnaround time. Process mapping was used to study the system and identify potential sources of delays in the system. A set of qualitative recommendations were put forward. These recommendations, include the reduction of wait time of outpatients and inpatients and the reduction of non-value-added times such as transfer time of patients, were evaluated using a discrete event simulation approach. The simulation study shows that the daily operating hours at the catheterization lab could be reduced, aiding to reallocate staff for discharging other duties, as the hospital may require.     

An integrated algorithm for text recognition: comparison with a cascaded algorithm

The use of diverse knowledge sources in text recognition and in correction of letter substitution errors in words of text is considered. Three knowledge sources are defined: channel characteristics as probabilities that observed letters are corruptions of other letters, bottom-up context as letter conditional probabilities (when the previous letters of the word are known), and top-down context as a lexicon. Two algorithms, one based on integrating the knowledge sources in a single step and the other based on sequentially cascading bottom-up and top-down processes, are compared in terms of computational/storage requirements and results of experimentation.     

Experiments in Text Recognition with Binary n-Gram and Viterbi Algorithms

The binary n-gram and Viterbi algorithms have been suggested as alternative approaches to contextual postprocessing for text produced by a noisy channel such as an optical character recognizer. This correspondence describes the underlying theory of each approach in unified terminology, and presents new implementation algorithms for each approach. In particular, a storage efficient data structure is proposed for the binary n-gram algorithm and a recursive formulation is given for the Viterbi algorithm. Results of extensive experiments with each algorithm are described.     

Boundary detection in multidimensions

The development of image processing algorithms for time-varying imagery and computerized tomography data calls for generalization of the concepts of adjacency, connectivity, boundary, etc., to three and four-dimensional discrete spaces. This paper defines these basic concepts in unified terminology and presents algorithms for a boundary detection task in multidimensional space. The performance of these algorithms is discussed with respect to theoretical maximum complexity, and is illustrated with simulated computerized tomography data.     

Evidence of low-symmetry phases in pressure-dependent Raman spectroscopic study of BaTiO<Subscript>3</Subscript>

In the earlier pressure-dependent Raman spectroscopic studies, it has been reported that BaTiO₃ undergoes a tetragonal to cubic phase transition above ~ 2 GPa, whereas pressure-dependent X-ray absorption, X-ray diffuse scattering studies and pair distribution function studies have reported the presence of a low-symmetry rhombohedral phase above ~ 2.3 GPa. In this report, we present our pressure-dependent Raman spectroscopic studies on polycrystalline BaTiO₃ which shows that it first undergoes a transition from tetragonal to orthorhombic/rhombohedral phase above ~ 2.6 GPa and then finally goes to the cubic phase above 8.4 GPa. Pressure-dependent synchrotron X-ray diffraction (SXRD) studies have also been carried out that provided rate of change of volume as a function of pressure resulting in bulk modulus of 215 ± 9 GPa.     

Process development for ball grid array assembly using a design of experiments approach

The focus of this work was to develop a robust assembly process for low and high input/output (I/O) ball grid arrays (BGAs). The test vehicles considered had a wide variety of components including full and perimeter array BGAs, and ultrafine pitch peripheral leaded devices. Experimental design techniques were applied in order to identify, screen, and control the parameters that affect the stencil printing process. The factors that affect the process were screened using Tagu-chi-based methodology. These significant factors and their interactions were then further analysed using full factorial designs. The volume and the quality of the solder paste deposits were considered as the response variables. Response surface plots were developed to provide process windows for paste deposition. Process capability studies were performed to evaluate the capability of the solder paste deposition process. Boards were assembled using optimal settings obtained from the experiments. No process-induced defects were found, and 100% yield was obtained.     

Optimal placement of known symbols for slowly varying frequency-selective channels

The problem of placing known symbols in a data stream for a slowly varying frequency-selective channel is considered from an information-theoretic perspective. Given the amount of redundancy associated with known symbols, placement schemes that minimize the outage probability are derived by assuming that the transmitted codewords consist of packets that are constrained to have the same known symbol placement. Under the assumption that each known symbol cluster is at least as large as /spl alpha/ /spl ges/ 2L + 1 (where L is the channel order), we show that the optimal placement is obtained by arranging the known symbols into as many clusters as possible and placing them such that the unknown symbol blocks are as equal as possible. It is shown that the optimal placement of known symbol clusters does not depend on the probability density of the channel. Numerical examples are used to illustrate the ideas and potential gains of using optimal known symbol placement.     

Sensitivity and Coding of Opportunistic ALOHA in Sensor Networks with Mobile Access

We consider a distributed medium access protocol, Opportunistic ALOHA, for reachback in sensor networks with mobile access points (AP). We briefly discuss some properties of the protocol, like throughput and transmission control for an orthogonal CDMA physical layer. We then consider the incorporation of necessary side information like location into the transmission control and numerically demonstrate the loss in throughput in the absence of such information. Through simulations, we discuss the robustness and sensitivity of the protocol under various modeling errors and propose strategies to allow for errors in estimation of some parameters without reduction in the throughput. For networks, where the sensors are allowed to collaborate, we consider three coding schemes for reliable transmission: spreading code independent, spreading code dependent transmission and coding across sensors. These schemes are compared in terms of achievable rates and random coding error exponents. The coding across sensors scheme has comparable achievable rates to the spreading code dependent scheme, but requires the additional transmission of sensor ID. However, the scheme does not require the mobile AP to send data through the beacon unlike the other two schemes. The use of these coding schemes to overcome sensitivity is demonstrated through simulations. Parvathinathan Venkitasubramaniam was born in India in 1981. He received his B.Tech. degree from the department of Electrical Engineering, Indian Institute of Technology, Madras in 2002. He joined the School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, in 2002 and he is working toward his Ph.D. degree. He is a recipient of the 2004 Leonard G. Abraham Award (with S. Adireddy and L. Tong) from the IEEE Communications Society. His research interests include random-access protocols,sensor networks, and information theory. Srihari Adireddy was born in India in 1977. He received the B.Tech. degree from the Department of Electrical Engineering, Indian Institute of Technology, Madras, and M.S. and Ph. D. degrees from the School of Electrical and Computer Engineering, Cornell University, Ithaca, NY in 2001 and 2003 respectively. Currently, he is working at Silicon Laboratories, Austin, TX. He is a recipient of the 2004 Leonard G. Abraham Award (with P. Venkitasubramaniam and L. Tong) from the IEEE Communications Society. His research interests include signal processing, information theory, and random-access protocols. Lang Tong received the B.E. degree from Tsinghua University, Beijing, China, in 1985, and M.S. and Ph.D. degrees in electrical engineering in 1987 and 1990, respectively, from the University of Notre Dame, Notre Dame, Indiana. He was a Postdoctoral Research Affiliate at the Information Systems Laboratory, Stanford University in 1991. Currently, he is a Professor in the School of Electrical and Computer Engineering, Cornell University, Ithaca, New York. Dr. Tong received Young Investigator Award rom the Office of Naval Research in 1996, and the Outstanding Young Author Award from the IEEE Circuits and Systems Society in 1991, the 2004 IEEE Signal Processing Society Best Paper Award (with M. Dong), the 2004 Leonard G. Abraham Prize Paper Award from the IEEE Communications Society (with P. Venkitasubramaniam and S. Adireddy). His areas of interest include statistical signal processing, adaptive receiver design for communication systems, signal processing for communication networks, and information theory.     

GDKAT: A goal-driven knowledge acquisition tool for knowledge base development

While knowledge-based systems are being used extensively to assist in making decisions, a critical factor that affects their performance and reliability is the quantity and quality of the knowledge bases. Knowledge acquisition requires the design and development of an in-depth comprehension of knowledge modeling and of applicable domain. Many knowledge acquisition tools have been developed to support knowledge base development. However, a weakness that is revealed in these tools is the domain-dependent and complex acquisition process. Domain dependence limits the applicable areas and the complex acquisition process makes the tool difficult to use. In this paper, we present a goal-driven knowledge acquisition tool (GDKAT) that helps elicit and store experts' declarative and procedural knowledge in knowledge bases for a user-defined domain. The designed tool is implemented using the object-oriented design methodology under C++ Windows environment. An example that is used to demonstrate the GDKAT is also delineated. While the application domain for the example presented is reflow soldering in surface mount printed circuit board assembly, the GDKAT can be used to develop knowledge bases for other domains also.