Device reliability under electrical stress and photo response of oxide TFTs

Abstract— The stability of oxide TFTs has been the main focus of this research and is probably the most crucial requirement for the successful application to flat‐panel displays. Although the high Fermi level of oxide semiconductors makes TFTs basically stable under electrical stress, the device reliability under diverse variations of electrical stress is affected by materials such as active semiconductors and gate insulators, processes for the formation of back/front channels and passivation layers, and device configurations among other things. How these factors affect the device reliability have been investigated and a review of the stability is presented. In addition, several categories of the light instability of oxide TFTs is presented and the origin is discussed.     

A passive auto-focus camera control system

This paper presents a passive auto-focus camera control system which can easily achieve the function of auto-focus with no necessary of any active component (e.g., infrared or ultrasonic sensor) in comparison with the conventional active focus system. To implement the technique we developed, the hardware system including the adjustable lens with CMOS sensor and servo motor, an 8051 image capture micro-controller, a field programmable gate array (FPGA) sharpness measurement circuit, a pulse width modulation (PWM) controller, and a personal digital assistant (PDA) image displayer was constructed. The discrete wavelet transformation (DWT), the morphology edge enhancement sharpness measurement algorithms, and the self-organizing map (SOM) neural network were used in developing the control mechanism of the system. Compared with other passive auto-focus methods, the method we proposed has the advantages of lower computational complexity and easier hardware implementation.     

Analysis of pressure-driven electrokinetic flows in hydrophobic microchannels with slip-dependent zeta potential

The present study is an analysis of pressure-driven electrokinetic flows in hydrophobic microchannels with emphasis on the slip effects under coupling of interfacial electric and fluid slippage phenomena. Commonly used linear model with slip-independent zeta potential and the nonlinear model at limiting (high-K) condition with slip-dependent zeta potential are solved analytically. Then, numerical solutions of the electrokinetic flow model with zeta potential varying with slip length are analyzed. Different from the general notion of “the more hydrophobic the channel wall, the higher the flowrate,” the results with slip-independent and slip-dependent zeta potentials both disclose that flowrate becomes insensitive to the wall hydrophobicity or fluid slippage at sufficiently large slip lengths. Boundary slip not only assists fluid motion but also enhances counter-ions transport in EDL and, thus, results in strong streaming potential as well as electrokinetic retardation. With slip-dependent zeta potential considered, flowrate varies non-monotonically with increasing slip length due to competition of the favorable and adverse effects with more complicated interactions. The influence of the slip on the electrokinetic flow is eventually nullified at large slip lengths for balance of the counter effects, and the flowrate becomes insensitive to further hydrophobicity of the microchannel. The occurrence of maximum, minimum, and insensitivity on the flowrate-slip curves can be premature at a higher zeta potential and/or larger electrokinetic separation distance.     

Kinematics, pattern recognition, and motion control of mask-panel alignment system

Kinematics, pattern recognition, and motion control methods are investigated as an integrated approach for a mask-panel visual alignment system, which consists of the vision system to extract the mask-panel misalignment and the stage control system to compensate for it. First, a 4PPR alignment mechanism is considered and the inverse kinematic solution is found out to define the relationship between the mask-panel misalignment and the displacements of active joints. Then, a fast alignment mark recognition algorithm is proposed in terms of the geometric template matching (GTM), which is specific to simply shaped patterns but computationally much efficient compared with general correlation-based matchings. Finally, the kinematic solution and the developed vision algorithm are incorporated to implement a two-stage position-based visual servo, where both original fine images and reduced coarse ones are utilized together and the GTM plays a crucial role in achieving a near real-time visual feedback. Experimental results are shown to demonstrate the effectiveness of the GTM-based two-stage alignment control.     

Coupled-task scheduling on a single machine subject to a fixed-job-sequence

This paper investigates single-machine coupled-task scheduling where each job has two tasks separated by an exact delay. The objective of this study is to schedule the tasks to minimize the makespan subject to a given job sequence. We introduce several intriguing properties of the fixed-job-sequence problem under study. While the complexity status of the studied problem remains open, an O(n²) algorithm is proposed to construct a feasible schedule attaining the minimum makespan for a given permutation of 2n tasks abiding by the fixed-job-sequence constraint. We investigate several polynomially solvable cases of the fixed-job-sequence problem and present a complexity graph of the problem.     

An interactive concept map approach to supporting mobile learning activities for natural science courses

Mobile and wireless communication technologies not only enable anytime and anywhere learning, but also provide the opportunity to develop learning environments that combine real-world and digital-world resources. Nevertheless, researchers have indicated that, without effective tools for helping students organize their observations in the field, the mobile learning performance could be disappointing. To cope with this problem, this study proposes an interactive concept map-oriented approach for supporting mobile learning activities. An experiment has been conducted on an elementary school natural science course to evaluate the effectiveness of the proposed method. The experimental results show that the proposed approach not only enhances learning attitudes, but also improves the learning achievements of the students.     

On fuzzy renewal processes for fuzzy random variables and extended theorems

In this paper, we construct fuzzy renewal processes involving fuzzy random variables. We first extend the renewal processes to the fuzzy renewal processes where interarrival times, rewards, and stopping times are all fuzzy random variables. According to these fuzzy renewal processes, we then extend some theorems of renewal processes to those in fuzzy renewal processes. These are elementary renewal theorem, asymptotic expected average reward, and Wald's equation. In each part, we also give examples for applications. © 2010 Wiley Periodicals, Inc.     

Adaptive hybrid error correction model for video streaming over wireless networks

The Hybrid ARQ (HARQ) mechanism is the well-known error packet recovery solution composed of the Automation Repeat reQuest (ARQ) mechanism and the Forward Error Correction (FEC) mechanism. However, the HARQ mechanism neither retransmits the packet to the receiver in time when the packet cannot be recovered by the FEC scheme nor dynamically adjusts the number of FEC redundant packets according to network conditions. In this paper, the Adaptive Hybrid Error Correction Model (AHECM) is proposed to improve the HARQ mechanism. The AHECM can limit the packet retransmission delay to the most tolerable end-to-end delay. Besides, the AHECM can find the appropriate FEC parameter to avoid network congestion and reduce the number of FEC redundant packets by predicting the effective packet loss rate. Meanwhile, when the end-to-end delay requirement can be met, the AHECM will only retransmit the necessary number of redundant FEC packets to receiver in comparison with legacy HARQ mechanisms. Furthermore, the AHECM can use an Unequal Error Protection to protect important multimedia frames against channel errors of wireless networks. Besides, the AHECM uses the Markov model to estimate the burst bit error condition over wireless networks. The AHECM is evaluated by several metrics such as the effective packet loss rate, the error recovery efficiency, the decodable frame rate, and the peak signal to noise ratio to verify the efficiency in delivering video streaming over wireless networks.     

A new weighted approach to imbalanced data classification problem via support vector machine with quadratic cost function

In this paper, a new weighted approach on Lagrangian support vector machine for imbalanced data classification problem is proposed. The weight parameters are embedded in the Lagrangian SVM formulation. The training method for weighted Lagrangian SVM is presented and its convergence is proven. The weighted Lagrangian SVM classifier is tested and compared with some other SVMs using synthetic and real data to show its effectiveness and feasibility.     

Personalized top-k skyline queries in high-dimensional space

As data of an unprecedented scale are becoming accessible, it becomes more and more important to help each user identify the ideal results of a manageable size. As such a mechanism, skyline queries have recently attracted a lot of attention for its intuitive query formulation. This intuitiveness, however, has a side effect of retrieving too many results, especially for high-dimensional data. This paper is to support personalized skyline queries as identifying “truly interesting” objects based on user-specific preference and retrieval size k. In particular, we abstract personalized skyline ranking as a dynamic search over skyline subspaces guided by user-specific preference. We then develop a novel algorithm navigating on a compressed structure itself, to reduce the storage overhead. Furthermore, we also develop novel techniques to interleave cube construction with navigation for some scenarios without a priori structure. Finally, we extend the proposed techniques for user-specific preferences including equivalence preference. Our extensive evaluation results validate the effectiveness and efficiency of the proposed algorithms on both real-life and synthetic data.