In this paper, the planar subarray structure to be optimized by using random search method for large active array antenna is presented. Although MPSL of the optimized subarray structure is 1.09dB higher, G/T of the optimized subarray structure is 2.07dB higher than the reference subarray structure.

The literature presents a digitized pension system based on a consortium blockchain, with the aim of overcoming existing pension system challenges such as multiparty collaboration, manual intervention, high turnaround time, cost transparency, auditability, etc. In addition, the adoption of hyperledger fabric and the introduction of smart contracts aim to transform multi-organizational workflow into a synchronized, automated, modular, and error-free procedure.

This paper proposes a fault-resilient ROS platform supporting rapid fault detection and recovery. The platform employs heartbeat-based fault detection and node replication-based recovery. Our prototype implementation on top of the ROS Melodic shows a great performance in evaluations with a Nvidia development board and an inverted pendulum device.

Two simple and high performance multichannel distributed queue dual bus (MDQDB) protocols based on the wavelength division multiplexing (WDM) network technology are proposed, and the network architecture and operations are presented. To be suited for a high speed network, they inherit the advantages of the DQDB protocol such as node simplicity, network flexibility and distributed operations of individual nodes. The network capacity can also be greatly increased with marginal increase of node complexity. Simulation has been done to estimate the performances such as throughput and average access delays for individual nodes. The influence of the bandwidth balancing mechanism on the two protocols is considered at medium, high, and overload conditions. We also investigate the fairness characteristics in asymptotic conditions for various initial states.

MEMS storage devices are new non-volatile secondary storages that have outstanding advantages over magnetic disks. MEMS storage devices, however, are much different from magnetic disks in the structure and access characteristics in the following ways. They have thousands of heads called probe tips and provide the following two major access facilities: (1) flexibility : freely selecting a set of probe tips for accessing data, (2) parallelism: simultaneously reading and writing data with the set of probe tips selected. Due to these characteristics, it is nontrivial to find data placements that fully utilize the capability of MEMS storage devices. In this paper, we propose a simple logical model called the Region-Sector (RS) model that abstracts major characteristics affecting data retrieval performance, such as flexibility and parallelism, from the physical MEMS storage model. We also suggest heuristic data placement strategies based on the RS model. To show the usability of the RS model, we derive new data placements for relational data and two-dimensional spatial data by using these strategies. Experimental results show that the proposed data placements improve the data retrieval performance by up to 4.7 times for relational data and by up to 18.7 times for two-dimensional spatial data of approximately 320 Mbytes compared with those of existing data placements. Further, these improvements are expected to be more marked as the database size grows.

We propose an effective 2d image based end-to-end deep learning model for malware detection by introducing a black & white embedding to reserve bit information and adapting the convolution architecture. Experimental results show that our proposed scheme can achieve superior performance in both of training and testing data sets compared to well-known image recognition deep learning models (VGG and ResNet).

Internal user threats such as information leakage or system destruction can cause significant damage to the organization, however it is very difficult to prevent or detect this attack in advance. In this paper, we propose an anomaly-based insider threat detection method with local features and global statistics over the assumption that a user shows different patterns from regular behaviors during harmful actions. We experimentally show that our detection mechanism can achieve superior performance compared to the state of the art approaches for CMU CERT dataset.

To implement a fast and reliable question-answering system in Korean, we propose a two-pass answer indexer using co-occurrence information between answer candidates and adjacent content words. The two-pass indexer scans documents twice for obtaining local scores and global scores. Then, the two-pass indexer calculates the degrees of association between answer candidates and co-occurring content words. Using this technique, the proposed QA system shortens the response time and enhances the precision.

The objective is to generate a suboptimal weight vector for an adaptive array system operating in a multipath fading CDMA (Code Division Multiple Access) channel. The total computational load of the proposed procedure is about including the update of autocovariance matrix as well as the weight update itself, where N is the number of antenna elements. The performance of the proposed array system is shown in terms of BER (Bit Error Rate), allowable capacity, and convergence rate in practical CDMA signal environments such as IS95 and IS2000 1X.

A 12 Gb/s 10-level pulse amplitude modulation (PAM) serial-link transmitter was implemented using a 0.18 µm CMOS process. The proposed 10-PAM transmitter achieves a channel efficiency of 4 bit/symbol by dual-mode amplitude modulations using 10 differential-mode levels and 3 common-mode levels. The measured maximum data-rate was 12 Gb/s over 0.7-m cable and 2-cm printed circuit board (PCB) traces. The entire transmitter consumes 432 mW such that the figure of merit of the transmitter is 36 pJ/bit. The present work demonstrates the greater channel efficiency of 4 bit/symbol than the currently reported multi-level PAM transmitters.

In this paper, we propose new approaches to speech enhancement based on soft decision. In order to enhance the statistical reliability in estimating speech activity, we introduce the concept of a global speech absence probability (GSAP). First, we compute the conventional speech absence probability (SAP) and then modify it according to the newly proposed GSAP. The modification is made in such a way that the SAP has the same value of GSAP in the case of speech absence while it is maintained to its original value when the speech is present. Moreover, for improving the performance of the SAP's at voice tails (transition periods from speech to silence), we revise the SAP's using a hang-over scheme based on the hidden Markov model (HMM). In addition, we suggest a robust noise update algorithm in which the noise power is estimated not only in the periods of speech absence but also during speech activity based on soft decision. Also, for improving the SAP determination and noise update routines, we present a new signal to noise ratio (SNR) concept which is called the predicted SNR in this paper. Moreover, we demonstrate that the discrete cosine transform (DCT) enhances the accuracy of the SAP estimation. A number of tests show that the proposed method which is called the speech enhancement based on soft decision (SESD) algorithm yields better performance than the conventional approaches.

Nonnegative matrix factorization (NMF) is an unsupervised technique to represent nonnegative data as linear combinations of nonnegative bases, which has shown impressive performance for source separation. However, its source separation performance degrades when one signal can also be described well with the bases for the interfering source signals. In this paper, we propose a discriminative NMF (DNMF) algorithm which exploits the reconstruction error for the interfering signals as well as the target signal based on target bases. The objective function for training the bases is constructed so as to yield high reconstruction error for the interfering source signals while guaranteeing low reconstruction error for the target source signals. Experiments show that the proposed method outperformed the standard NMF and another DNMF method in terms of both the perceptual evaluation of speech quality score and signal-to-distortion ratio in various noisy environments.

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.