Development of Test Procedure For CMOS Operational Amplifier Application Circuits

The integrated circuit (IC) is an ultra-small and fragile electrical system. A chip is basically an IC placed in a protective black plastic casing. The only contact the outside world has with the IC is through the chips input-output and power supply pins. ICs are also prone to damage and to locate damages inside a chip requires special probing techniques. These techniques are incorporated from the beginning of the design stage of a chip. Design for Testability (DFT) is a method applied to the design stage of chips such that electrical testing of the chips at the end of the production stage is greatly simplified. For a chip manufacturer, DFT helps cut production cost by shortening the time to test finished chips w hich eventually decreases the time to market the chip. Built-In Self Test (BIST) chips, an outcome of DFT, are ICs designed with extended circuitry dedicated to test its electrical behavior which eventually could inform a manufacturer w here damage has occurred. The testing circuitry inside a BIST chip is complimented by a test pattern, which is a special signal that executes the actual testing. The main objective of this study is to develop a test procedure to test CMOS Operational Amplifier (Op-Amp) application circuits. The focus in the development of the testing procedure is to find a suitable test pattern. The study conducted results in the success of developing the said test procedure. The development of the test procedure is aided by a powerful computer software from Tanner Research Inc. called Tanner Tools. It is used for circuit simulation and development of a mask layout for an Op-Amp. The major findings of this thesis is that a faulty Op-Amp application circuit behaves differently from a faultless Op-Amp application circuit. From this finding a test pattern can be derived by comparing between faulty and faultless Op-Amp application circuit behavior through simulation. The only disadvantage of the test pattern is that it could only detect damages in the Op-Amp if the damages occurs only one at any given time. Thus it can be argued that in relation to DFT for an Op-Amp application circuit, it is not impossible for damages to be pin-pointed using the developed procedure

Nonintrusive eye gaze tracking using a single eye image

This paper proposes an Eye Gaze Tracking (EGT) technique using a single eye image that can be easily calibrated and mapped for Human Computer Interaction (HCI). The technique employs both geometric and trigonometric relationships to find a user's Point of Regard, followed by calculating user-dependent variables for final mapping onto a user interface (UI). Experimental results show acceptable accuracy with minimal focal errors

Approximately Counting Embeddings into Random Graphs

Let H be a graph, and let C_H(G) be the number of (subgraph isomorphic) copies of H contained in a graph G. We investigate the fundamental problem of estimating C_H(G). Previous results cover only a few specific instances of this general problem, for example, the case when H has degree at most one (monomer-dimer problem). In this paper, we present the first general subcase of the subgraph isomorphism counting problem which is almost always efficiently approximable. The results rely on a new graph decomposition technique. Informally, the decomposition is a labeling of the vertices such that every edge is between vertices with different labels and for every vertex all neighbors with a higher label have identical labels. The labeling implicitly generates a sequence of bipartite graphs which permits us to break the problem of counting embeddings of large subgraphs into that of counting embeddings of small subgraphs. Using this method, we present a simple randomized algorithm for the counting problem. For all decomposable graphs H and all graphs G, the algorithm is an unbiased estimator. Furthermore, for all graphs H having a decomposition where each of the bipartite graphs generated is small and almost all graphs G, the algorithm is a fully polynomial randomized approximation scheme. We show that the graph classes of H for which we obtain a fully polynomial randomized approximation scheme for almost all G includes graphs of degree at most two, bounded-degree forests, bounded-length grid graphs, subdivision of bounded-degree graphs, and major subclasses of outerplanar graphs, series-parallel graphs and planar graphs, whereas unbounded-length grid graphs are excluded.Comment: Earlier version appeared in Random 2008. Fixed an typo in Definition 3.

Soccer event detection via collaborative multimodal feature analysis and candidate ranking

This paper presents a framework for soccer event detection through collaborative analysis of the textual, visual and aural modalities. The basic notion is to decompose a match video into smaller segments until ultimately the desired eventful segment is identified. Simple features are considered namely the minute-by-minute reports from sports websites (i.e. text), the semantic shot classes of far and closeup-views (i.e. visual), and the low-level features of pitch and log-energy (i.e. audio). The framework demonstrates that despite considering simple features, and by averting the use of labeled training examples, event detection can be achieved at very high accuracy. Experiments conducted on ~30-hours of soccer video show very promising results for the detection of goals, penalties, yellow cards and red cards

Goal event detection in soccer videos via collaborative multimodal analysis

Detecting semantic events in sports video is crucial for video indexing and retrieval. Most existing works have exclusively relied on video content features, namely, directly available and extractable data from the visual and/or aural channels. Sole reliance on such data however, can be problematic due to the high-level semantic nature of video and the difficulty to properly align detected events with their exact time of occurrences. This paper proposes a framework for soccer goal event detection through collaborative analysis of multimodal features. Unlike previous approaches, the visual and aural contents are not directly scrutinized. Instead, an external textual source (i.e., minute-by-minute reports from sports websites) is used to initially localize the event search space. This step is vital as the event search space can significantly be reduced. This also makes further visual and aural analysis more efficient since excessive and unnecessary non-eventful segments are discarded, culminating in the accurate identification of the actual goal event segment. Experiments conducted on thirteen soccer matches are very promising with high accuracy rates being reported

A feasibility study of an interactive shared single display groupware in resource constrained schools, Sarawak

One pressing issue in resource constrained schools is the lack of access to computer facilities for learning. A single display groupware (SDG) is explored in this paper to provide an alternative solution for this limitation where it allows multiple users to work concurrently on a single computer display. This study aims to investigate the feasibility of SDG as an educational approach in resource constrained schools. The prototype SDG system RimbaIlmu, is designed and developed. Quantitative evaluations are carried out where the results indicate its feasibility in students’ engagement and learning performance, while overcoming technical constraints. Limitation of the SDG is also presented with the intent of guiding future improvements

Human action recognition using time delay input radial basis function networks

This paper presents a fast, vision-based method for the problem of human action representation and recognition. The first problem is addressed by constructing an action descriptor from spatiotemporal data of action silhouettes based on appearance and motion features. For action classification, a new Radial Basis Function Network (RBF), called Time Delay Input Radial Basis Function Network (TDIRBF) is proposed by introducing time delay units to the RBF in a novel approach. A TDIRBF offers a few desirable features such as an easier learning process and more flexibility. The representational power and speed of the proposed method were explored using a publicly available dataset. Based on experimental results, implemented in MATLAB and on standard PCs, the average time for constructing a feature vector for a high-resolution video was just about 20 ms/frame (or 50 fps) and the classifier speed was above 15 fps. Furthermore, the proposed approach demonstrated good performance in terms of both execution time and overall performance (a new performance measure that combines accuracy and speed into one metric)