This paper describes a technique for overcoming the model shrinkage problem in automatic speech recognition (ASR), which allows application developers and users to control the model size with less degradation of accuracy. Recently, models for ASR systems tend to be large and this can constitute a bottleneck for developers and users without special knowledge of ASR with respect to introducing the ASR function. Specifically, discriminative language models (DLMs) are usually designed in a high-dimensional parameter space, although DLMs have gained increasing attention as an approach for improving recognition accuracy. Our proposed method can be applied to linear models including DLMs, in which the score of an input sample is given by the inner product of its features and the model parameters, but our proposed method can shrink models in an easy computation by obtaining simple statistics, which are square sums of feature values appearing in a data set. Our experimental results show that our proposed method can shrink a DLM with little degradation in accuracy and perform properly whether or not the data for obtaining the statistics are the same as the data for training the model.

Small-world is a common property existing in many real-life social, technological and biological networks. Small-world networks distinguish themselves from others by their high clustering coefficient and short average path length. In the past dozen years, many probabilistic small-world networks and some deterministic small-world networks have been proposed utilizing various mechanisms. In this Letter, we propose a new deterministic small-world network model by first constructing a binary-tree structure and then adding links between each pair of brother nodes and links between each grandfather node and its four grandson nodes. Furthermore, we give the analytic solutions to several topological characteristics, which shows that the proposed model is a small-world network.

Information diffusion analysis in social networks is of significance since it enables us to deeply understand dynamic social interactions among users. In this paper, we introduce approaches to discovering information diffusion process in social networks based on process mining. Process mining techniques are applied from three perspectives: social network analysis, process discovery and community recognition. We then present experimental results by using a real-life social network data. The proposed techniques are expected to employ as new analytical tools in online social networks such as blog and wikis for company marketers, politicians, news reporters and online writers.

Speaker change detection involves the identification of the time indices of an audio stream, where the identity of the speaker changes. This paper proposes novel measures for speaker change detection over the centroid model, which divides the feature space into non-overlapping clusters for effective speaker-change comparison. The centroid model is a computationally-efficient variant of the widely-used mixture-distribution based background models for speaker recognition. Experiments on both synthetic and real-world data were performed; the results show that the proposed approach yields promising results compared with the conventional statistical measures.

With more digital home appliances and network devices having OSGi as the software management platform, the power-saving capability of the OSGi platform has become a critical issue. This paper is aimed at improving the power-efficiency of the OSGi platform, i.e. reducing the energy consumption with minimum performance degradation. The key to this study is an efficient power-saving technique which exploits the runtime information already available in a Java virtual machine (JVM), the base software of the OSGi platform, to best determine the timing of performing DVFS (Dynamic Voltage and Frequency Scaling). This, technically, involves a phase detection scheme that identifies the memory phase of the OSGi-enabled device/server in a correct and almost effortless way. The overhead of the power-saving procedure is thus minimized, and the system performance is well maintained. We have implemented and evaluated the proposed power-saving approach on an OSGi server, where the Apache Felix OSGi implementation and the DaCapo benchmarks were applied. The results show that this approach can achieve real power-efficiency for the OSGi platform, in which the power consumption is significantly reduced and the performance remains highly competitive, compared with the other power-saving techniques.

The impact of co-channel deployment of femtocells on existing macro-cellular systems is investigated considering the use of techniques to resolve the loud neighbor problem. There are several approaches to this aim, for example, femtocell power control, interference coordination, and opening access to femtocells. Of these, coordinated scheduling, including power control, and their impact will be the main focus of this work. In the context of 3GPP-LTE, we examine under various operational scenarios the performance in terms of the average and 5% worst user throughput, a useful measure of fairness among users, both for femto and macro cells. Although recent studies have shown that co-channel femtocell has a minor impact on the macrocell performance in average sense, a non-negligible percentage of users may lose their opportunity to get satisfactory data service and, hence, we focus more on the 5% worst users.

Recent advance in digital storage technology has enabled us to archive a large volume of video data. Thanks to this trend, we have archived more than 1,800 hours of video data from a daily Japanese news show in the last ten years. When considering the effective use of such a large news video archive, we assumed that analysis of its chronological and semantic structure becomes important. We also consider that providing the users with the development of news topics is more important to help their understanding of current affairs, rather than providing a list of relevant news stories as in most of the current news video retrieval systems. Therefore, in this paper, we propose a structuring method for a news video archive, together with an interface that visualizes the structure, so that users could track the development of news topics according to their interest, efficiently. The proposed news video structure, namely the “topic thread structure”, is obtained as a result of an analysis of the chronological and semantic relation between news stories. Meanwhile, the proposed interface, namely “mediaWalker II”, allows users to track the development of news topics along the topic thread structure, and at the same time watch the video footage corresponding to each news story. Analyses on the topic thread structures obtained by applying the proposed method to actual news video footages revealed interesting and comprehensible relations between news topics in the real world. At the same time, analyses on their size quantified the efficiency of tracking a user's topic-of-interest based on the proposed topic thread structure. We consider this as a first step towards facilitating video authoring by users based on existing contents in a large-scale news video archive.

This paper describes the application of two attractive categories of topic modeling techniques to the problem of spoken document retrieval (SDR), viz. document topic model (DTM) and word topic model (WTM). Apart from using the conventional unsupervised training strategy, we explore a supervised training strategy for estimating these topic models, imagining a scenario that user query logs along with click-through information of relevant documents can be utilized to build an SDR system. This attempt has the potential to associate relevant documents with queries even if they do not share any of the query words, thereby improving on retrieval quality over the baseline system. Likewise, we also study a novel use of pseudo-supervised training to associate relevant documents with queries through a pseudo-feedback procedure. Moreover, in order to lessen SDR performance degradation caused by imperfect speech recognition, we investigate leveraging different levels of index features for topic modeling, including words, syllable-level units, and their combination. We provide a series of experiments conducted on the TDT (TDT-2 and TDT-3) Chinese SDR collections. The empirical results show that the methods deduced from our proposed modeling framework are very effective when compared with a few existing retrieval approaches.

In this paper, we analyze the key factors underlying the implementation, evaluation, and optimization of image processing and computer vision algorithms on embedded GPU using OpenGL ES 2.0 shader model. First, we present the characteristics of the embedded GPU and its inherent advantage when compared to embedded CPU. Additionally, we propose techniques to achieve increased performance with optimized shader design. To show the effectiveness of the proposed techniques, we employ cartoon-style non-photorealistic rendering (NPR), speeded-up robust feature (SURF) detection, and stereo matching as our example algorithms. Performance is evaluated in terms of the execution time and speed-up achieved in comparison with the implementation on embedded CPU.

The fringe field effects of nano-electromechanical (NEM) nonvolatile memory cells have been investigated analytically for the accurate evaluation of NEM memory cells. As the beam width is scaled down, fringe field effect becomes more severe. It has been observed that pull-in, release and hysteresis voltage decrease more than our prediction. Also, the fringe field on cell characteristics has been discussed.

As an add-on device option for the ultra-low power CMOS technology, the double-gated vertical-channel Tunnel Field-Effect Transistors (TFETs) of different source configurations are comparatively studied from the perspectives of fabrication and current drivability. While the top-source design where the source of the device is placed on the top of the fin makes the fabrication and source engineering much easier, it is more susceptible to parasitic resistance issue. The bottom-source design is difficult to engineer the tunneling barrier and may require a special replacement technique. Examples of the schemes to engineer the tunneling barrier for the bottom-source TFET are suggested. A TCAD simulation study on the bottom-source devices shows that both the parasitic resistance of source region and the current enhancement mechanism by field coupling need be carefully considered in designing the source.

Non-homogeneous Poisson processes (NHPPs) have gained much popularity in actual software testing phases to estimate the software reliability, the number of remaining faults in software and the software release timing. In this paper, we propose a new modeling approach for the NHPP-based software reliability models (SRMs) to describe the stochastic behavior of software fault-detection processes. The fundamental idea is to apply the equilibrium distribution to the fault-detection time distribution in NHPP-based modeling. We also develop efficient parameter estimation procedures for the proposed NHPP-based SRMs. Through numerical experiments, it can be concluded that the proposed NHPP-based SRMs outperform the existing ones in many data sets from the perspective of goodness-of-fit and prediction performance.

A simple image compression scheme is presented for various types of images, which include color/grayscale images, color-quantized images, and bilevel images such as document and digital halftone images. It is a bitplane coding composed of a new context modeling and adaptive binary arithmetic coding. A target bit to be encoded is conditioned by the estimates of the neighboring pixels including non-causal locations. Several functionalities are also integrated. They are arbitrary shaped ROI transmission, selective tile partitioning, accuracy scalability, and others. The proposed bitplane codec is competitive with JPEG-LS in lossless compression of 8-bit grayscale and 24-bit color images. The proposed codec is close to JBIG2 in bilevel image compression. It outperforms the existing standards in compression of 8-bit color-quantized images.

In this paper, we propose a new low power nonvolatile counter unit based on Magnetic Tunnel Junction (MTJ) with fine-grained power gating. The proposed counter unit consists of only a single latch with two MTJs. We verify the basic operation and estimate the power consumption of the proposed counter unit. The operating power consumption of the proposed nonvolatile counter unit is smaller than the conventional one below 140 kHz. The power of the proposed unit is 74.6% smaller than the conventional one at low frequency.

This paper introduces a new problem of maximizing communication performance while sustaining communication connection for a specified time without battery energy depletion on wireless sensor networks. As a solution to the problem, this paper proposes a communication scheme that maximizes the transmission rates of packets from sender sensors to destination sensors while guaranteeing the given connection time. The proposed scheme is designed to work for wireless sensors with multiple radio transmission ranges.

With the purpose of improving the performance of next generation wireless networks, cooperative relaying (CoR) and network coding (NC) are promising techniques. The number of time slots required for NC in bidirectional transmission is less than that required for CoR, and hence, NC can achieve higher throughput performance than CoR. However, the disadvantage of NC is that asymmetric traffic ratio conditions might cause a significant decrease in the bidirectional throughput. In contrast, CoR is robust to asymmetric traffic ratio conditions. In this paper, in order to improve the throughput of NC even under asymmetric traffic ratio conditions, we propose an opportunistic scheduling scheme for hybrid NC and CoR. In the proposed scheduling scheme, the transmission protocol with best throughput performance can be adaptively selected based on instantaneous channel state information. Computer simulation results reveal that the proposed scheduling scheme not only achieve higher throughput than the conventional scheduling scheme but is also robust against asymmetric traffic ratio conditions. By adjusting the scheduler's parameter, the proposed scheduling scheme can provide a tradeoff between the throughput and the traffic ratio. Moreover, in certain cases, maximizing the throughput of NC and guaranteeing the offered traffic ratio can be achieved at the same time.

Most of the IP mobility management schemes based on the IETF's MIPv6 may not be suitable for delay-sensitive vehicular applications since there will be frequent service disruptions as the moving vehicles frequently change their points of wireless network attachment. This paper presents a fast IP mobility management scheme for vehicular networks where multiple wireless network interfaces are used to perform fast handovers without handover latency or packet loss. In order to do this, the IETF standard HMIPv6 has been extended, where multiple simultaneous tunnels between the HMIPv6 mobility anchor point (MAP) and the mobile gateway are dynamically constructed. We have designed the architecture for a mobile gateway for supporting multiple tunnels, the structure of the extension MAP (E-MAP), and the signaling procedure to achieve fast IP handover in vehicular networks. Both mathematical analysis and simulation have been done for performance evaluation. The results show that the proposed scheme is superior to HMIPv6 and MIPv6 with regard to handover latency and packet loss as the vehicle moves between different wireless network cells at high speed.

In this paper, the authors focus on upstream transmission in TDMA-based IEEE 802.16j and propose two time slot assignment algorithms to decrease end-to-end transmission latency. One of the proposed algorithms assigns time slots considering the hop count from a gateway node, and the other takes the path from the relay node to the gateway node into account. In addition, a restriction in assigning time slots is introduced to reduce the delay at each relay node. The algorithms with the restriction assign later time slots considering the time slot order of links connecting a relay node. The performance of the proposed algorithms is evaluated through simulation experiments from the viewpoints of frame size and end-to-end transmission latency, and it is confirmed that the proposed algorithms achieve small transmission latency regardless of packet generation rate in the network, and decrease the transmission latency by up to 70% compared with the existing algorithm.