A secure and efficient route discovery protocol is proposed for ad hoc networks, where only one-way hash functions are used to authenticate nodes in the ROUTE REQUEST, while additional public-key cryptography is used to guard against active attackers disguising a node in the ROUTE REPLY.

A new Elastic-Block Matching Algorithm using bilinear space warping is proposed. In this scheme a convex quadrilateral, which minimizes a distortion measure against the current square block, is searched to compensate the shape deformation caused by a rigid body's 3 dimensional depth motion or rotation. The proposed algorithm gives a remarkable improvement in motion-compensated prediction compared with the conventional algorithm.

In this letter, we propose a novel speech enhancement algorithm based on data-driven residual gain estimation. The entire system consists of two stages. At the first stage, a conventional speech enhancement algorithm enhances the input signal while estimating several signal-to-noise ratio (SNR)-related parameters. The residual gain, which is estimated by a data-driven method, is applied to further enhance the signal at the second stage. A number of experimental results show that the proposed speech enhancement algorithm outperforms the conventional speech enhancement technique based on soft decision and the data-driven approach using SNR grid look-up table.

Three synchronization issues, i.e., phase, frequency, and symbol time, have to be properly controlled to achieve distributed beamforming gain. In orthogonal frequency division multiplexing (OFDM) systems, frequency offset in cooperating signals is more important than other synchronization issues since it results in SNR degradation as well as inter-carrier interference (ICI). In this paper, the impact of frequency offset in distributed beamforming is analyzed for OFDM systems. ICI resulting from frequency offset between cooperating signals is also investigated and approximated. Performance degradation due to frequency offset is shown with various numbers of cooperating signals and offset values. We show that frequency offset between cooperating signals is critical in OFDM systems since it leads to interference from the other subcarriers as well as power loss in the desired signal.

To understand the characteristics of a multimedia service, such as the large volume of data transfer and real-time constraints, it is necessary to have a performance evaluation tool for an HDD. Our HDD simulator is running on a PC operated on FreeBSD UNIX OS. We first investigate the seek time and the sustained rate of HDDs and then evaluate the performance of an HDD for an experimental VOD system. Applying the experimental results, we find the bottleneck of an HDD, and then suggest what HDDs are to be selected for a VOD system.

Every time-series has its own linear trend, the directionality of a time-series, and removing the linear trend is crucial to get more intuitive matching results. Supporting the linear detrending in subsequence matching is a challenging problem due to the huge number of all possible subsequences. In this paper we define this problem as the linear detrending subsequence matching and propose its efficient index-based solution. To this end, we first present a notion of LD-windows (LD means linear detrending). Using the LD-windows we then present a lower bounding theorem for the index-based matching solution and show its correctness. We next propose the index building and subsequence matching algorithms. We finally show the superiority of the index-based solution.

Most of commercial websites provide customers with menu-driven navigation and keyword search. However, these inconvenient interfaces increase the number of mouse clicks and decrease customers' interest in surfing the websites. To resolve the problem, we propose an information retrieval assistant using a natural language interface in online sales domains. The information retrieval assistant has a client-server structure; a system connector and a NLP (natural language processing) server. The NLP server performs a linguistic analysis of users' queries with the help of coordinated NLP agents that are based on shallow NLP techniques. After receiving the results of the linguistic analysis from the NLP server, the system connector interacts with outer information provision systems such as conventional information retrieval systems and relational database management systems according to the analysis results. Owing to the client-server structure, we can easily add other information provision systems to the information retrieval assistant with trivial modifications of the NLP server. In addition, the information retrieval assistant guarantees fast responses because it uses shallow NLP techniques. In the preliminary experiment, as compared to the menu-driven system, we found that the information retrieval assistant could reduce the bothersome tasks such as menu selecting and mouse clicking because it provides a convenient natural language interface.

The Ubiquitous sensor network (USN) node is required to operate for several months with limited system resources such as memory and power. The typical USN node is in the active state for less than 1% of its several month lifetime and waits in the inactive state for the remaining 99% of its lifetime. This paper suggests a power adjustment dual priority scheduler (PA-DPS) that offers low power consumption while meeting the USN requirements by estimating power consumption in the USN node. PA-DPS has been designed based on the event-driven approach and the dual-priority scheduling structure, which has been conventionally suggested in the real-time system field. From experimental results, PA-DPS reduced the inactive mode current up to 40% under the 1% duty cycle.

We consider a problem of global asymptotic stabilization of a class of feedforward nonlinear systems that have the unknown linear growth rate and unknown input delay. The proposed output feedback controller employs a dynamic gain which is tuned adaptively by monitoring the output value. As a result, a priori knowledge on the linear growth rate and delay size are not required in controller design, which is a clear benefit over the existing results.

IEEE 802.11ac uses DL MU-MIMO and channelization for very high throughput. We propose a new algorithm for adaptive channelization in DL MU-MIMO WLANs. The proposed scheme can enhance the throughput efficiency for DL MU-MIMO transmission by adaptively applying the channelization scheme according to data size and MCS. Moreover, our proposal can reduce the overhead due to the exchange of control frames for DL MU-MIMO transmission in WLANs. A performance evaluation shows that the proposed scheme is superior to IEEE 802.11ac WLAN.

An Anomaly detection sensor, to detect an abnormal use of system resources or an abnormal behavior of authorized users, uses various measures and decides on the basis of threshold value. However, it has high false alarm rate, and it make it hard to merchandise. Also, it is not easy to have a threshold which is suitable for installation environment. In this paper, we propose a method to automatic generation of proper threshold of each sensor, and the threshold is applied for an integrated decision. Also, we propose a computing method for a correlation of heterogeneous detection sensors. As we use the correlation to integrate and decide the opinions of each sensor, false positive can be greatly reduced.

In this letter, we present useful features accounting for pronunciation prominence and propose a classification technique for prominence detection. A set of phone-specific features are extracted based on a forced alignment of the test pronunciation provided by a speech recognition system. These features are then applied to the traditional classifiers such as the support vector machine (SVM), artificial neural network (ANN) and adaptive boosting (Adaboost) for detecting the place of prominence.

In this paper, a new algorithm for the optimal training sequence with respect to sequence length in 1-dimensional cluster-based sequence equalizers (1-D CBSE) is presented. The proposed method not only removes the step of random training sequence selection but also shortens the length of the selected training sequences. The superiority of the new method is demonstrated by presenting several simulation results of quadrature phase shift keying (QPSK) signaling schemes and related analyses.

This paper discusses an efficient implementation of fault-tolerant digital filters based on the residue number system. In this implementation, a compact residue arithmetic module named the pulse-train residue arithmetic circuit" is effectively employed as the basic module, and an efficient error detection/correction algorithm in which error detections is performed in each basic module and error correction is performed based on the parallelism of residue arithmetic is also employed. Two design methods of fault-tolerant digital filters are newly proposed. In one method the error correcting circuit is imposed in series to the non-redundant system, and in the other the one is imposed in parallel. The prior has an advantage of compact hardware, and the latter has an advantage of high-speed operation. Following the proposed method, a 2nd-order recursive fault-tolerant digital filter with 3 digits is practically implemented, and its fault-tolerant ability is proved by noise injection testing. It is found that the hardware of our digital filter is 70% of the one based on the conventional tripple modular redundancy (TMR), and the mission time improving factor of our digital filter is 150% of the one of the TMR system.

In this letter, we propose a novel approach to human activity recognition. We present a class of features that are robust to the tilt of the attached sensor module and a state transition model suitable for HMM-based activity recognition. In addition, postprocessing techniques are applied to stabilize the recognition results. The proposed approach shows significant improvements in recognition experiments over a variety of human activity DB.

This paper proposed an automated segmentation algorithm for MR brain images through the complementary use of T1-weighted, T2-weighted, and PD images. The proposed segmentation algorithm is composed of 3 steps. The first step involves the extraction of cerebrum images by placing a cerebrum mask over the three input images. In the second step, outstanding clusters that represent the inner tissues of the cerebrum are chosen from among the 3-dimensional (3D) clusters. The 3D clusters are determined by intersecting densely distributed parts of a 2D histogram in 3D space formed using three optimal scale images. The optimal scale image results from applying scale-space filtering to each 2D histogram and a searching graph structure. As a result, the optimal scale image can accurately describe the shape of the densely distributed pixel parts in the 2D histogram. In the final step, the cerebrum images are segmented by the FCM (Fuzzy c-means) algorithm using the outstanding cluster center value as the initial center value. The ability of the proposed segmentation algorithm to calculate the cluster center value accurately then compensates for the current limitation of the FCM algorithm, which is unduly restricted by the initial center value used. In addition, the proposed algorithm, which includes a multi spectral analysis, can achieve better segmentation results than a single spectral analysis.

We propose a fault-tolerant routing algorithm for 2D meshes. Our routing algorithm can tolerate any number of concave fault regions. It is based on xy-routing and uses the concept of the fault ring/chain composed of fault-free elements surrounding faults. Three virtual channels per physical link are used for deadlock-free routing on a fault ring. Four virtual channels are needed for a fault chain. For a concave fault ring, fault-free nodes in the concave region have been deactivated to avoid deadlock in the previous algorithms, which results in excessive loss of the computational power. Our algorithm ensures deadlock-freedom by restricting the virtual channel usage in the concave region, and it minimizes the loss of the computational power. We also extend the proposed routing scheme for adaptive fault-tolerant routing. The adaptive version requires the same number of virtual channels as the deterministic one.

In this paper, a preprocessing approach to improving the quality of the music on a mobile phone using Enhanced variable rate codec (EVRC) is presented. Our approach works well on music signals considerably reducing the number of time-clipped frames.

In this letter, we propose a novel approach to speech enhancement, which incorporates a new criterion based on residual noise shaping. In the proposed approach, our goal is to make the residual noise perceptually comfortable instead of making it less audible. A predetermined `comfort noise' is provided as a target for the spectral shaping. Based on some assumptions, the resulting spectral gain function turns out to be a slight modification of the Wiener filter while requiring very low computational complexity. Subjective listening test shows that the proposed algorithm outperforms the conventional spectral enhancement technique based on soft decision and the noise suppression implemented in IS-893 Selectable Mode Vocoder.

Acoustic data transmission is a technique which embeds data in a sound wave imperceptibly and detects it at a receiver. The data are embedded in an original audio signal and transmitted through the air by playing back the data-embedded audio using a loudspeaker. At the receiver, the data are extracted from the received audio signal captured by a microphone. In our previous work, we proposed an acoustic data transmission system designed based on phase modification of the modulated complex lapped transform (MCLT) coefficients. In this paper, we propose the spectral magnitude adjustment (SMA) technique which not only enhances the quality of the data-embedded audio signal but also improves the transmission performance of the system.