This paper proposes an iterative maximum a posteriori (MAP) receiver for orthogonal frequency division multiplexing (OFDM) mobile communications under fast-fading conditions. The previous work in [21] developed a MAP receiver based on the expectation-maximization (EM) algorithm employing the differential model, which can allow correlated time-variation of channel impulse responses. In order to make such a MAP receiver more robust against time-variant channels, this paper proposes two new message-passing algorithms derived from factor graphs; subcarrier removal and partial turbo processing. The subcarrier removal estimates the channel frequency response by using all subcarriers other than the targeted subcarrier. Such channel estimate can be efficiently calculated by removing information on the targeted subcarrier from the estimate of the original EM algorithm that uses all the subcarriers. This modification can avoid the repetitive use of incorrectly detected signals for the channel estimation. On the other hand, the partial turbo processing performs symbol-by-symbol channel decoding by using a symbol interleaver. Owing to this process, the current channel estimate, which is more accurate due to the decoding gain, can be used as the initial channel estimate for the next symbol. Computer simulations under fast multipath fading conditions demonstrate that the subcarrier removal and the partial turbo processing can improve the error floor and the convergence speed, respectively, compared to the conventional MAP receiver.

Switch-and-stay combining (SSC) is a simple diversity technique where a single radio frequency (RF) chain is connected to one of several antenna branches and stays there if the channel quality is satisfied or otherwise switches to a new branch. Compared with Selection Combining (SC), SSC requires less overhead in channel estimation and antenna selection feedback. In this paper, we analyze the performance of SSC in a time-correlated flat fading channel and with causal channel state information. We derive the general expressions for the distribution of the output signal-to-noise ratio (SNR), outage rate and average bit error rate (ABER) and then the analytical results are compared with the simulation results under the Jakes Rayleigh fading channel. Our results show that (1) For slowly varying channels, L branch SSC can achieve the full diversity order and the same outage rate as SC; (2) Increasing the number of antenna branches can improve the performance of SSC, however, the gain from adding antennas diminishes quickly as the channel variation speed increases. Moreover, to avoid the complexity in optimizing the fixed threshold, we also propose a simple adaptive SSC scheme which has almost the same ABER as the SSC with optimized fixed threshold.

Clickstreams in users' navigation logs have various data which are related to users' web surfing. Those are visit counts, stay times, product types, etc. When we observe these data, we can divide clickstreams into sub-clickstreams so that the pages in a sub-clickstream share more contexts with each other than with the pages in other sub-clickstreams. In this paper, we propose a method which extracts more informative rules from clickstreams for web page recommendation based on genetic programming and association rules. First, we split clickstreams into sub-clickstreams by contexts for generating more informative rules. In order to split clickstreams in consideration of context, we extract six features from users' navigation logs. A set of split rules is generated by combining those features through genetic programming, and then informative rules for recommendation are extracted with the association rule mining algorithm. Through experiments, we verify that the proposed method is more effective than the other methods in various conditions.

Classification based on predictive association rules (CPAR) is a widely used associative classification method. Despite its efficiency, the analysis results obtained by CPAR will be influenced by missing values in the data sets, and thus it is not always possible to correctly analyze the classification results. In this letter, we improve CPAR to deal with the problem of missing data. The effectiveness of the proposed method is demonstrated using various classification examples.

Although there have been enormous investments into English education all around the world, not many differences have been made to change the English instruction style. Considering the shortcomings for the current teaching-learning methodology, we have been investigating advanced computer-assisted language learning (CALL) systems. This paper aims at summarizing a set of POSTECH approaches including theories, technologies, systems, and field studies and providing relevant pointers. On top of the state-of-the-art technologies of spoken dialog system, a variety of adaptations have been applied to overcome some problems caused by numerous errors and variations naturally produced by non-native speakers. Furthermore, a number of methods have been developed for generating educational feedback that help learners develop to be proficient. Integrating these efforts resulted in intelligent educational robots – Mero and Engkey – and virtual 3D language learning games, Pomy. To verify the effects of our approaches on students' communicative abilities, we have conducted a field study at an elementary school in Korea. The results showed that our CALL approaches can be enjoyable and fruitful activities for students. Although the results of this study bring us a step closer to understanding computer-based education, more studies are needed to consolidate the findings.

The Liquid-crystal display (LCD) overdrive technique has been utilized to reduce motion blur on a display via a reduction in the response time. However, to measure the variation of the pixel amplitudes, it is necessary to store the previous frame using a large frame memory. To downscale the frame memory, block truncation coding (BTC) is commonly employed due to the simplicity of its implementation, even if some visual artifacts may occur for image blocks with high frequency components. In this paper, we present a multimode-multilevel BTC (MBTC) technique that improves performance while maintaining simplicity. To improve the visual quality, we uniquely determine the quantization level and coding mode of each block according to the distribution of the luminance and chrominance amplitudes. For a compression ratio of 6:1, the proposed method demonstrates higher coding efficiency and overdrive performance by up to 3.81 dB in the PSNR compared to other methods.

A receiver architecture and a digital IQ imbalance compensation method for dual-carrier reception are newly proposed. The impact of IQ imbalance on the baseband signal is mathematically analyzed. Based on the analysis, IQ imbalance parameters are estimated and the coupling effect of IQ imbalance is compensated using digital baseband processing alone. Simulation results show that the proposed IQ imbalance compensation successfully removes IQ imbalance. The deviation from the ideal performance is less than 1 dB when it is applied to the 3GPP-LTE carrier aggregation.

This paper presents an efficient algorithm, NEAR, that allows sensor nodes to acquire their off-duty eligibility. Any node only needs to calculate the coverage degrees of the intersections on its sensing boundary, and cooperates with its neighbors to know if it is redundant or not. The computing complexity of NEAR is only O(nlogn).

Clustering technology is very important in ad hoc networks and sensor networks from the view point of reducing the traffic load and energy consumption. In this paper, we propose a new structure formation mechanism as a tool for clustering. It meets the key clustering requirements including the use of an autonomous decentralized algorithm and a consideration of the situation of individual nodes. The proposed mechanism follows the framework of autonomous decentralized control based on local interaction, in which the behavior of the whole system is indirectly controlled by appropriately designing the autonomous actions of the subsystems. As an application example, we demonstrate autonomous decentralized clustering for a two-dimensional lattice network model, and the characteristics and adaptability of the proposed method are shown. In particular, the clusters produced can reflect the environmental situation of each node given by the initial condition.

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.

The proposed scheduling scheme minimizes the mean power consumption of real-time tasks with probabilistic computation amounts while meeting their deadlines. Our study formally solves the minimization problem under finitely discrete clock frequencies with irregular power consumptions, whereas state-of-the-arts studies did under infinitely continuous clock frequencies with regular power consumptions.

Chemical sensors are one of the oldest fields of research closely related to the semiconductor technology. From the Ion-Sensitive Field-Effect Transistors (ISFET) in the 70's, through Micro-Electro-Mechanical-System (MEMS) sensors from the end of the 80's, chemical sensors are combining in the 90's MEMS technology with LSI intelligence to devise more selective, sensitive and autonomous devices to analyse complex mixtures. A brief history of chemical sensors from the ISFET to the nowadays LSI integrated sensors is first detailed. Then the states-of-the-art of LSI integrated chemical sensors and their wide range of applications are discussed. Finally the authors propose a brand-new usage of integrated wireless MEMS sensors for remote surveillance of chemical substances, such as food-industry or pharmaceutical products, that are stored in closed environment like a bottle, for a long period. In such environment, in-situ analyse is necessary, and electrical cables, for energy supply or data transfer, cannot be used. Thanks to integrated MEMS, an autonomous long-term in-situ quality deterioration tracking system is possible.

In this paper, we survey the state of the art of the secure key exchange method that is secured by the laws of classical statistical physics, and involves the Kirchhoff's law and the generalized Johnson noise equation, too. We discuss the major characteristics and advantages of these schemes especially in comparison with quantum encryption, and analyze some of the technical challenges of its implementation, too. Finally, we outline some ideas about how to use already existing and currently used wire lines, such as power lines, phone lines, internet lines to implement unconditionally secure information networks.

The future wireless mobile communication networks are expected to provide seamless wireless access and data exchange to mobile users. In particular, it is expected that the demand for ubiquitous data exchange between mobile users will increase with the widespread use of various wireless applications of the intelligent transportation system (ITS) and intelligent vehicles. Mobile ad hoc networks (MANETs) are one of the representative research areas pursuing the technology needed to satisfy the increasing mobile communication requirements. However, most of the works on MANET systems do not take into account the continuous and dynamic changes of nodal mobility to accommodate system design and performance evaluation. The mobility of nodes limits the reliability of communication between the source and the destination node since a link between two continuously moving nodes is established only when one node enters the transmission range of the other. To alleviate this problem, mobile relay has been studied. In particular, it is shown that relay selection is an efficient way to support nodal mobility in MANET systems. In this paper, we propose a mobility-based relay selection algorithm for the MANET environment. Firstly, we define the lifetime as the maximum link duration for which the link between two nodes remains active. Therefore, the lifetime indicates the reliability of the relay link which measures its capability to successfully support relayed communication when requested by the source node. Furthermore, we consider a series of realistic scenarios according to the randomness of nodal mobility. Thus, the proposed algorithm can be easily applied in practical MANET systems by choosing the appropriate node mobility behavior. The numerical results show that the improved reliability of the proposed algorithm's relayed communication is achieved with a proper number of mobile relay nodes rather than with the conventional selection algorithm. Lastly, we show that random mobility of the individual nodes enhances reliability of the network in a sparse network environment.

We recently determined the values of intrinsic spin-orbit (SO) parameters for In0.52Al0.48As/In0.53Ga0.47As(10 nm)/In0.52Al0.48As (InGaAs/InAlAs) quantum wells (QW), lattice-matched to (001) InP, from the weak localization/antilocalization analysis of the low-temperature magneto-conductivity measurements [1]. We have then studied the subband energy spectra for the InGaAs/InAlAs double QW system from beatings in the Shubnikov de Haas (SdH) oscillations. The basic properties obtained here for the double QW system provides useful information for realizing nonmagnetic spin-filter devices based on the spin-orbit interaction [2].

Applying Distributed Video Coding (DVC) to mobile devices that have limited computation and power resources can be a very challenging problem due to its high-complexity decoding. To address this, this paper proposes a DVC bitstream organizer. The proposed DVC bitstream organizer reduces the complexity associated with repetitive channel decoding and SI generation in a flexible manner. It allows users to choose a means of minimizing the computational complexity of the DVC decoder according to their preferences and the device's resource limitations. An experiment shows that the proposed method increases decoding speeds by up to 25 times.

In this paper, we propose a 1-cycle high-performance 3D bufferless router with a 3-stage permutation network. The proposed router utilizes the 3-stage permutation network instead of the serialized switch allocator and 77 crossbar to achieve the frequency of 1.25 GHz in TSMC 65 nm technology. Compared with the other two 3D bufferless routers, the proposed router occupies less area and consumes less power consumption. Simulation results under both synthetic and application workloads illustrate that the proposed router achieves less average packet latency than the other two 3D bufferless routers.

A transmission control protocol (TCP) using an additive increase multiplicative decrease (AIMD) algorithm for congestion control plays a leading role in advanced Internet services. However, the AIMD method shows only low link utilization in lossy networks with long delay such as satellite networks. This is because the cwnd dynamics of TCP are reduced by long propagation delay, and TCP uses an inadequate congestion control algorithm, which does not distinguish packet loss from wireless errors from that due to congestion of the wireless networks. To overcome these problems, we propose an exponential recovery (ER) TCP that uses the exponential recovery function for rapidly occupying available bandwidth during a congestion avoidance period, and an adaptive congestion window decrease scheme using timestamp base available bandwidth estimation (TABE) to cope with wireless channel errors. We simulate the proposed ER-TCP under various test scenarios using the ns-2 network simulator to verify its performance enhancement. Simulation results show that the proposal is a more suitable TCP than the several TCP variants under long delay and heavy loss probability environments of satellite networks.

In this study, a precoding scheme based on QR-decomposition is proposed for mitigating the inter-carrier-interference (ICI) in orthogonal-frequency-division-multiplexing (OFDM) systems. The proposed approach first subjects the ICI matrix to QR decomposition so that the ICI effect is transformed into its spectrally causal equivalent. With this causality, the precoding can then be conducted based on the resultant spectrally causal matrix. In addition, by using the stationary property of the ICI factors, in conjunction with zero padding, we implement the QR-based precoding in a segmentation manner which can significantly alleviate the computational complexity imposed by QR decomposition while eliminating ICI within each segment. This study also analyzes the residue interference power induced by the segmentation. The residue interference power is then accordingly used to determine the order of zero padding. Computer simulations support the validity of the proposed approach.