The reliability of a connector depends on the contact force generated by the spring in the terminal of a connector. The springs are commonly formed by stamping from a strip of spring material. Therefore, the prediction of the force — displacement relation by the finite element (FE) method is very important for the design of terminals. For simulation, an accurate model of stress-strain (s-s) responses of the materials is required. When the materials are deformed in the forward and then the reverse directions, almost all spring materials show different s-s responses between the two directions, due to the Bauschinger effect. This phenomenon makes simulation difficult because the s-s response depends on the prior deformation of the material. Hence, the measurement of the s-s response is the elementary process, by cyclic tension and compression testing in which materials deform elastically and plastically. Then, the s-s responses should be described accurately by mathematical models for FE simulation. In this paper, the authors compare the experimental s-s responses of copper-based materials with conventional mathematical models and the Yoshida-Uemori model, which is a constitutive model having high capability of describing the elastic and plastic behavior of cyclic deformation. The calculated s-s responses only by Yoshida-Uemori model were in very good agreement with the corresponding experimental results. Therefore, the use of this model for FE simulation would be recommended for a more accurate prediction of force-displacement relation of the spring.

We propose a current mode sense amplifier that uses a current-mirror to increase the bitline sensing current, which dominates the sensing speed. A comparison of the sensing delay shows that the proposed sense amplifier can provide about 12.6∼15.4% improvement depending on different bitline loads in sensing speed over original WTA scheme.

We experimentally investigate and analyze faults in optical fiber connections with refractive index matching material that have incorrectly cleaved fiber ends. We explain that incorrectly cleaved fiber ends, which are not ideal because they are uneven and not perpendicular to the fiber axis, are caused by defective optical fiber cleavers. We discover that the optical performance of field installable connections using incorrectly cleaved fiber ends might change greatly. We also infer that the significant change in insertion and return losses might be attributed to partially air-filled gaps by using scatter diagrams of measured insertion and return losses. Our experiment results reveal that the optical performance might deteriorate to more than 40dB in terms of insertion loss and less than 30dB in terms of return loss.

Based on sample-pair refinement and local optimization, this paper proposes a high-accuracy and quick matting algorithm. First, in order to gather foreground/background samples effectively, we shoot rays in hybrid (gradient and uniform) directions. This strategy utilizes the prior knowledge to adjust the directions for effective searching. Second, we refine sample-pairs of pixels by taking into account neighbors'. Both high confidence sample-pairs and usable foreground/background components are utilized and thus more accurate and smoother matting results are achieved. Third, to reduce the computational cost of sample-pair selection in coarse matting, this paper proposes an adaptive sample clustering approach. Most redundant samples are eliminated adaptively, where the computational cost decreases significantly. Finally, we convert fine matting into a de-noising problem, which is optimized by minimizing the observation and state errors iteratively and locally. This leads to less space and time complexity compared with global optimization. Experiments demonstrate that we outperform other state-of-the-art methods in local matting both on accuracy and efficiency.

As a network evolves following initial deployment, its service functions remain diversified through the openness of the network functions. This indicates that appropriate simplification of the service functions is essential if the evolving network is to achieve the required scalability of service processing and service management. While the screening of service functions is basically performed by network users and the market, several service functions will be automatically simplified based on the growth of the evolving network. This paper verifies the simplification of service functions resulting from the evolution of the network itself. First, the principles that serve as the basis for simplifying the service functions are explained using several practical examples. Next, a simulation model is proposed to verify the simplification of service functions in terms of the priority control function for path routing and load balancing among multiple paths. From the results of the simulation, this study clarifies that the anticipated simplification of service functions is actually realizable and the service performance requirements can be reduced as the network evolves after deployment. When the simplification of service functions can improve network quality, it accelerates the evolution of the network and increases the operator's revenue.

In this paper, we propose a novel layered scalable- multiple description coding (LS-MDC) which offers the benefits of both scalable video coding and multiple description coding for robust video transmission over packet lossy networks. In the proposed LS-MDC method, multiple descriptions including base layer, enhancement layers, and their corresponding FEC parity data are allocated into two network paths of a path diversity system. Unlike the conventional approaches, the source base/enhancement data and their own parities in the proposed method are not transmitted together but are transferred over different paths. Therefore, the effect of burst packet losses can be effectively reduced for the descriptions. Furthermore, in order to minimize the overall distortion for the LS-MDC system and exploit the benefits of path diversity, we also propose an optimal rate allocation scheme that can adaptively control the transmission rate as well as the channel coding rate for media senders. Experiments show that the proposed method provides much better peak signal-to-noise ratio (PSNR) than conventional MDC techniques.

The authors previously conducted the observation of microstructures and three-dimensional SEM on fretting wear phenomena at tin-plated contacts. In this study, we report the fretting characteristics of dissimilar metal contacts by studying the relation between the contact resistance behaviors and micro structural changes of gold and tin-plated fretting contacts, through surface SEM observations and cross sectional SEM and AES analysis.

In this paper, we propose the Perceptual Shape Decomposition (PSD) to detect fingers for a Kinect-based hand gesture recognition system. The PSD is formulated as a discrete optimization problem by removing all negative minima with minimum cost. Experiments show that our PSD is perceptually relevant and robust against distortion and hand variations, and thus improves the recognition system performance.

This paper presents the opportunity-based software rejuvenation policy and the optimization problem of software rejuvenation trigger time maximizing the system performance index. Our model is based on a basic semi-Markov software rejuvenation model by Dohi et al. 2000 under the environment where possible time, called opportunity, to execute software rejuvenation is limited. In the paper, we consider two stochastic point processes; renewal process and Markovian arrival process to represent the opportunity process. In particular, we derive the existence condition of the optimal trigger time under the two point processes analytically. In numerical examples, we illustrate the optimal design of the rejuvenation trigger schedule based on empirical data.

Clustering methods are divided into hierarchical clustering, partitioning clustering, and more. K-Means is a method of partitioning clustering. We improve the performance of a K-Means, selecting the initial centers of a cluster through a calculation rather than using random selecting. This method maximizes the distance among the initial centers of clusters. Subsequently, the centers are distributed evenly and the results are more accurate than for initial cluster centers selected at random. This is time-consuming, but it can reduce the total clustering time by minimizing allocation and recalculation. Compared with the standard algorithm, F-Measure is more accurate by 5.1%.

Segmenting indicated objects from natural color images remains a challenging problem for researches of image processing. In this paper, a novel level set approach is presented, to address this issue. In this segmentation algorithm, a contour that lies inside a particular region of the concerned object is first initialized by a user. The level set model is then applied, to extract the object of arbitrary shape and size containing this initial region. Constrained on the position of the initial contour, our proposed framework combines two particular energy terms, namely local and global energy, in its energy functional, to control movement of the contour toward object boundaries. These energy terms are mainly based on graph partitioning active contour models and Bhattacharyya flow, respectively. Its flow describes dissimilarities, measuring correlative relationships between the region of interest and surroundings. The experimental results obtained from our image collection show that the suggested method yields accurate and good performance, or better than a number of segmentation algorithms, when applied to various natural images.

Spectral subtraction (SS) is an additive noise removal method which is derived in an extensive framework. In spectral subtraction, it is assumed that speech and noise spectra follow Gaussian distributions and are independent with each other. Hence, noisy speech also follows a Gaussian distribution. Spectral subtraction formula is obtained by maximizing the likelihood of noisy speech distribution with respect to its variance. However, it is well known that noisy speech observed in real situations often follows a heavy-tailed distribution, not a Gaussian distribution. In this paper, we introduce a q-Gaussian distribution in the non-extensive statistics to represent the distribution of noisy speech and derive a new spectral subtraction method based on it. We found that the q-Gaussian distribution fits the noisy speech distribution better than the Gaussian distribution does. Our speech recognition experiments using the Aurora-2 database showed that the proposed method, q-spectral subtraction (q-SS), outperformed the conventional SS method.

We propose a non-photorealistic rendering method for generating moire-picture-like color images from color photographs. The proposed method is performed in two steps. First, images with a staircasing effect are generated by a bilateral filter. Second, moire patterns are generated with an improved bilateral filter called an anti-bilateral filter. The characteristic of the anti-bilateral filter is to emphasize gradual boundaries.

This paper presents a fine-grain bit-serial reconfigurable VLSI architecture using multiple-valued switch blocks and binary logic modules. Multiple-valued signaling is utilized to implement a compact switch block. A binary-controlled current-steering technique is introduced, utilizing a programmable three-level differential-pair circuit to implement a high-performance low-power arbitrary two-variable binary function, and increase the noise margins in comparison with the quaternary-controlled differential-pair circuit. A current-source sharing technique between a series-gating differential-pair circuit and a current-mode D-latch is proposed to reduce the current source count and improve the speed. It is demonstrated that the power consumption and the delay of the proposed multiple-valued cell based on the binary-controlled current-steering technique and the current-source-sharing technique are reduced to 63% and 72%, respectively, in comparison with those of a previous multiple-valued cell.

A procedural terrain generation method is presented in this paper. It uses a user-drawn sketch map, which is a raster image with lines and polygons painted by different colors to represent sketches of different terrain features, as input to control the placement of terrain features. Some simple parameters which can be easily understood and adjusted by users are used to control the generation process. To further automatically generate terrains, a mechanism that automatically generates sketches is also put forward. The method is implemented in a PC, and experiments show that terrains are generated efficiently. This method provides users a controllable way to generate terrains.

In classical routing protocols, geographical distances/locations are typically used as the metric to select the best route, under the assumption that shorter distances exhibit lower energy consumption and nodes within the communication range of the sender can receive packets with a certain success probability. However, in underwater acoustic sensor networks (UASNs), sound propagation in the ocean medium is more complex than that in the air due to many factors, including sound speed variations and the interaction of sound waves with the sea surface and floor, causing the sound rays to bend. Therefore, propagation of sound is anisotropic in water, and may cause a phenomenon called shadow zone where nodes in the communication range of the sender cannot hear any signal. This renders conventional routing protocols no longer energy-efficient. In this paper, we make use of the ray-model to account for the environment-dependent behavior of the underwater channel, re-define nodes' one-hop neighbors based on signal attenuation rather than geographical distance, and design a distributed energy-efficient routing protocol for UASNs. Results show that our ray-model-based routing policy consistently outperforms the shortest path policy, and performs very close to the optimal one in several scenarios.

The topic of retrieving videos containing a desired person from a dataset just using the content of faces without any help of textual information has many interesting applications like video surveillance, social network, video mining, etc. However, traditional face matching against a huge number of detected faces leads to an unacceptable response time and may also reduce the accuracy due to the large variations in facial expressions, poses, lighting, etc. Therefore, in this paper we propose a novel method to generate discriminative “signatures” for efficiently retrieving the videos containing the same person with a query. In this research, the signature is defined as a compact, discriminative and reduced dimensionality representation, which is generated from a set of high-dimensional feature vectors of an individual. The desired videos are retrieved based on the similarities between the signature of the query and those of individuals in the database. In particular, we make the following contributions. Firstly, we give an algorithm of two directional linear discriminant analysis with maximum correntropy criterion (2DLDA-MCC) as an extension to our recently proposed maximum correntropy criterion based linear discriminant analysis (LDA-MCC). Both algorithms are robust to outliers and noise. Secondly, we present an approach for transferring a set of exemplars to a fixed-length signature using LDA-MCC and 2DLDA-MCC, resulting in two kinds of signatures that are called 1D signature and 2D signature. Finally, a novel video retrieval scheme is given based on the signatures, which has low storage requirement and can achieve a fast search. Evaluations on a large dataset of videos show reliable measurement of similarities by using the proposed signatures to represent the identities generated from videos. Experimental results also demonstrate that the proposed video retrieval scheme has the potential to substantially reduce the response time and slightly increase the mean average precision of retrieval.

A specification for digital cinema systems which deal with movies digitally from production to delivery as well as projection on the screens is recommended by DCI (Digital Cinema Initiative), and the systems based on this specification have already been developed and installed in theaters. The parameters of the systems that play an important role in determining image quality include image resolution, quantization bit depth, color space, gamma characteristics, and data compression methods. This paper comparatively discusses a relation between required bit depth and gamma quantization using both of a human visual system for grayscale images and two color difference models for color images. The required bit depth obtained from a contrast sensitivity function against grayscale images monotonically decreases as the gamma value increases, while it has a minimum value when the gamma is 2.9 to 3.0 from both of the CIE 1976 L* a* b* and CIEDE2000 color difference models. It is also shown that the bit depth derived from the contrast sensitivity function is one bit greater than that derived from the color difference models at the gamma value of 2.6. Moreover, a comparison between the color differences computed with the CIE 1976 L* a* b* and CIEDE2000 leads to a same result from the view point of the required bit depth for digital cinema systems.

Managing the configurations of complex systems consisting of various components requires the combined efforts by multiple domain experts. These experts have extensive knowledge about different components in the system they need to manage but little understanding of the issues outside their individual areas of expertise. As a result, the configuration constraints, changes, and procedures specified by those involved in the management of a complex system are often interrelated with one another without being noticed, and their integration into a coherent procedure for configuration represents a major challenge. The method of synthesizing the configuration procedure introduced in this paper addresses this challenge using a combination of formal specification and model finding techniques. We express the knowledge on system management with this method, which is provided by domain experts as first-order logic formulas in the Alloy specification language, and combine it with system-configuration information and the resulting specification. We then employ the Alloy Analyzer to find a system model that satisfies all the formulas in this specification. The model obtained corresponds to a procedure for system configurations that satisfies all expert-specified constraints. In order to reduce the resources needed in the procedure synthesis, we reduce the length of procedures to be synthesized by defining and using intermediate goal states to divide operation procedures into shorter steps. Finally, we evaluate our method through a case study on a procedure to consolidate virtual machines.

Reprogramming for wireless sensor networks is essential to upload new code or to alter the functionality of existing code. To overcome the weakness of the centralized approach of the traditional solutions, He et al. proposed the notion of distributed reprogramming where multiple authorized network users are able to reprogram sensor nodes without involving the base station. They also gave a novel distributed reprogramming protocol called SDRP by using identity-based signature, and provided a comprehensive security analysis for their protocol. In this letter, unfortunately, we demonstrate that SDRP is insecure as the protocol fails to satisfy the property of authenticity and integrity of code images, the most important security requirement of a secure reprogramming protocol.