A timing controller embedded driver IC with 3.24‐Gbps eDP interface for chip‐on‐glass TFT‐LCD applications

This paper presents a timing controller embedded driver (TED) IC with 3.24‐Gbps embedded display port (eDP), which is implemented using a 45‐nm high‐voltage CMOS process for the chip‐on‐glass (COG) TFT‐LCD applications. The proposed TED‐IC employs the input offset calibration scheme, the zero‐adjustable equalizer, and the phase locked loop‐based bang‐bang clock and data recovery to enhance the maximum data rate. Also, the proposed TED‐IC provides efficient power management by supporting advanced link power management feature of eDP standard v1.4. Additionally, the smart charge sharing is proposed to reduce the dynamic power consumption of output buffers. Measured result demonstrates the maximum data rate of 3.24 Gbps from a 1.1 V supply voltage with a 7.9‐inch QXGA 60‐Hz COG‐LCD prototype panel and 44% power saving from the display system.     

Video-based weathering gallery

We present a simple and effective method for constructing a gallery that consists of weathering effect elements called time-dependent appearance manifolds (TDAMs). Since TDAMs are computed from sample video clips showing dynamic weathering phenomena, they represent very smooth changes in the appearance of weathered pixels over time. Once a gallery with a variety of weathering effects is prepared, users can interactively choose and apply the predefined effects onto the surface of 3D graphic models and then finally assign the most appropriate one. This video-based weathering method can be implemented with very simple algorithms and it supports predictable, intuitive, and natural effects. Our system allows users to produce photorealistic augmented videos that include 3D graphic models weathered by our method. Moreover, users can easily enhance the realism of the augmented videos by manipulating rendering parameters such as the degree of weathering, texturing, lighting, and shadowing through user-friendly graphical user interfaces (GUIs).     

A secure image encryption scheme based on chaotic maps and affine transformation

Due to the interesting nonlinear dynamic properties of chaotic maps, recently chaos-based encryption algorithms have gained much attention in cryptographic communities. However, many encryption schemes do not fulfil the minimum key space requirement, which is an essential concern in many secure data applications. In this paper, an efficient chaos-based image encryption scheme with higher key space is presented. Even with a single round of encryption, a significantly larger key space can be achieved. The proposed scheme removes correlation among image pixels via random chaotic sequences, simply by XOR and addition operations. In order to resist against numerous attacks, we apply the affine transformation to get the final ciphertext image. The security of the proposed scheme is proved through histogram, contrast, PSNR, entropy, correlation, key space, key sensitivity and differential attack analysis. Many significant properties of chaotic maps, sensitivity to initial condition and control parameters, structure and attack complexity, make the anticipated scheme very reliable, practical and robust in various secure communication applications.     

A novel part-based approach to mean-shift algorithm for visual tracking

Visual tracking is one of the most important problems considered in computer vision. To improve the performance of the visual tracking, a part-based approach will be a good solution. In this paper, a novel method of visual tracking algorithm named part-based mean-shift (PBMS) algorithm is presented. In the proposed PBMS, unlike the standard mean-shift (MS), the target object is divided into multiple parts and the target is tracked by tracking each individual part and combining the results. For the part-based visual tracking, the objective function in the MS is modified such that the target object is represented as a combination of the parts and iterative optimization solution is presented. Further, the proposed PBMS provides a systematic and analytic way to determine the scale of the bounding box for the target from the perspective of the objective function optimization. Simulation is conducted with several benchmark problems and the result shows that the proposed PBMS outperforms the standard MS.

     

Predicting Attitudes Toward Knowledge Sharing by E-Mail: An Empirical Study

Social influence factors in sharing knowledge by e-mail are important issues in developing and understanding successful knowledge management systems and human–computer interaction. This article investigates important factors in shaping attitudes toward knowledge sharing by e-mail, based on social influence theory and self-determination theory. An empirical test of the proposed model using an online survey was conducted with a sample of undergraduate college students who use group e-mails for class assignments (n?=?566). All social influence factors significantly influenced attitudes toward knowledge sharing by e-mail (R ² = .57). Information systems researchers and practitioners will be able to more fully understand the roles of social influence factors in developing and designing knowledge management.     

Key-dependent 3D model hashing for authentication using heat kernel signature

Multimedia-based hashing is considered an important technique for achieving authentication and copy detection in digital contents. However, 3D model hashing has not been as widely used as image or video hashing. In this study, we develop a robust 3D mesh-model hashing scheme based on a heat kernel signature (HKS) that can describe a multi-scale shape curve and is robust against isometric modifications. We further discuss the robustness, uniqueness, security, and spaciousness of the method for 3D model hashing. In the proposed hashing scheme, we calculate the local and global HKS coefficients of vertices through time scales and 2D cell coefficients by clustering HKS coefficients with variable bin sizes based on an estimated L² risk function, and generate the binary hash through binarization of the intermediate hash values by combining the cell values and the random values. In addition, we use two parameters, bin center points and cell amplitudes, which are obtained through an iterative refinement process, to improve the robustness, uniqueness, security, and spaciousness further, and combine them in a hash with a key. By evaluating the robustness, uniqueness, and spaciousness experimentally, and through a security analysis based on the differential entropy, we verify that our hashing scheme outperforms conventional hashing schemes.     

Fault tolerant authenticated quantum direct communication immune to collective noises

This study proposes two new coding functions for GHZ states and GHZ-like states, respectively. Based on these coding functions, two fault tolerant authenticated quantum direct communication (AQDC) protocols are proposed. Each of which is robust under one kind of collective noises: collective-dephasing noise and collective-rotation noise, respectively. Moreover, the proposed AQDC protocols enable a sender to send a secure as well as authenticated message to a receiver within only one step quantum transmission without using the classical channels.     

Robust fuzzy stabilization of dithered chaotic systems using island-based random optimization algorithm

Applying dither to highly nonlinear systems may suppress chaotic phenomena, but dynamic performance, such as convergence rate and disturbance attenuation, is usually not guaranteed. This paper presents a dithered H_∞ robust fuzzy control scheme to stabilize chaotic systems that ensures disturbance attenuation bounds. In the proposed scheme, Takagi-Sugeno (T-S) fuzzy linear models are used to describe the relaxed models of the dithered chaotic system, and fuzzy controllers are designed based on an extension to the concept of parallel distributed compensation (PDC). Sufficient condition for the existence of the H_∞ robust fuzzy controllers is presented in terms of a novel linear matrix inequalities (LMI) form which takes full consideration of modeling error and disturbances, but cannot be solved by the standard procedures. In order to solve the LMI problem and to identify the chaotic systems as T-S fuzzy modes, we propose a compound optimization strategy called the island-based random-walk algorithm (IRA). The algorithm is composed of a set of communicating random-walk optimization procedures concatenated with the down-hill simplex method. The design procedure and validity of the proposed scheme is demonstrated via numerical simulation of the dithered fuzzy control of a chaotic system.     

Rainbow Product Ranking for Upgrading E-Commerce

Online product ranking is complicated by conflicting attributes. The authors propose a rainbow ranking system to solve this problem in e-commerce. This approach extends eBay's one-to-one shopping paradigm to a flexible one with many-to-many transactions. The system demonstrates a 50 to 70 percent transaction increase over skyline and eBay ranking methods. Buyers are allowed personalized selections of commodity products, whereas sellers benefit from both wholesale and retailing online. The rainbow scheme thus creates a win-win situation for both buyers and sellers in widened e-commerce marketplaces.     

Robust background maintenance by estimating global intensity level changes for dynamic scenes

The maintenance of relevant backgrounds under various scene changes is very crucial to detect foregrounds robustly. We propose a background maintenance method for dynamic scenes including global intensity level changes caused by changes of illumination conditions and camera settings. If the global level of the intensity changes abruptly, the conventional background models cannot discriminate true foreground pixels from the background. The proposed method adaptively modifies the background model by estimating the level changes. Because there are changes caused by moving objects as well as global intensity level changes, we estimate the dominant level change over the whole image regions by mean shift. Then, the problem caused by saturated pixels are handled by an additional scheme. In the experiments for dynamic scenes, our proposed method outperforms previous methods by adaptive background maintenance and handling of saturated pixels.