• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.1-11
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• 2006

In this paper, we propose a new register file architecture called the Register File Extension for Multi-words or Long-word Operation (RFEMLO) to accelerate both symmetric and asymmetric cryptographic algorithms. Based on the idea that most of cryptographic algorithms heavily use multi-words or long-word operations, RFEMLO allows multiple contiguous registers to be specified as a single operand. Thus, a single instruction can specify a SIMD-style multi-word operation or a long-word operation. RFEMLO can be applied to general purpose processors by adding instruction set for multi-words or long-word operands and functional units for additional instruction set. To evaluate the performance of RFEMLO, we use Simplescalar/ARM 3.0 (with gcc 2.95.2) and run detailed simulations on various symmetric and asymmetric cryptographic algorithms. By applying RFEMLO, we could get maximum 62% and 70% reductions in the total instruction count of symmetric and asymmetric cryptographic algorithms respectively. Also, performance results show that a speedup of 1.4 to 2.6 can be obtained in symmetric cryptographic algorithms and a speedup of 2.5 to 3.3 can be obtained for asymmetric cryptographic algorithms when we apply RFEMLO to a processor with an in-order pipeline. We also found that RFEMLO can effectively improve the performance of these cryptographic algorithms with much less cost compared to issue-width increase available in Superscalar implementations. Moreover, the RFEMLO can also be applied to Superscalar processor, leading to additional 83% and 138% performance gain in symmetric and asymmetric cryptographic algorithms.

• Bulletin of the Korean Chemical Society
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• v.32 no.1
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• pp.201-207
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• 2011

Peroxisome proliferator-activated receptors (PPARs) are members of nuclear receptors and their activation induces regulation of fatty acid storage and glucose metabolism. Therefore, the $PPAR\gamma$ is a major target for the treatment of type 2 diabetes mellitus. In order to generate pharmacophore model, 1080 known agonists database was constructed and a training set was selected. The Hypo7, selected from 10 hypotheses, contains four features: three hydrogen-bond acceptors (HBA) and one general hydrophobic (HY). This pharmacophore model was validated by using 862 test set compounds with a correlation coefficient of 0.903 between actual and estimated activity. Secondly, CatScramble method was used to verify the model. Hence, the validated Hypo7 was utilized for searching new lead compounds over 238,819 and 54,620 chemical structures in NCI and Maybridge database, respectively. Then the leads were selected by screening based on the pharmacophore model, predictive activity, and Lipinski's rules. Candidates were obtained and subsequently the binding affinities to $PPAR\gamma$ were investigated by the molecular docking simulations. Finally the best two compounds were presented and would be useful to treat type 2 diabetes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.532-538
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• 2003

In this paper we have investigated a novel approach applying low-density parity-check coding to a COFDM-CDMA system, which operates in a multi-path fading mobile channel. Developed as a linear-block channel coder, the LDPC code is known for a superior signal reception capability in AWGN and/or flat fading channels with respect to increased encoding rates, however, its performance degrades when the communication channel becomes multi-path fading. For a typical multi-path fading mobile channel with a SNR of 16㏈ or lower. in order to obtain a BER lower than 1 out of 10000, the LDPC code with encoding rates below 1:3 requires not only the inherent parity check information but also the piloting information for refreshing front-end equalizer taps of COFDM-CDMA, periodically. For instance, while the 1:3-rate LDPC coded transmission symbol is consisted of data bits and parity-check bits in 1 to 3 proportion, on the other hand, in the proposed method the same rate LDPC transmission symbol contains data bits, parity check bits, and pilot bits in 1 to 2 to 1 proportion, respectively. The included pilot bits are effective not only for channel estimation and channel equalization but for symbol decoding by assisting the parity-check bits, hence, improving SNR vs BER performance over the conventional 1:3-rate LDPC code. The proposed system performance has been verified using computer simulations in multi-path, Rayleigh fading channels, and the results show us that the proposed method out-performs the general LDPC channel coding methods in terms of SNR vs BER measurements.

• Journal of Periodontal and Implant Science
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• v.36 no.2
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• pp.531-554
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• 2006

Oral implants must fulfill certain criteria arising from special demands of function, which include biocompatibility, adequate mechanical strength, optimum soft and hard tissue integration, and transmission of functional forces to bone within physiological limits. And one of the critical elements influencing the long-term uncompromise functioning of oral implants is load distribution at the implant- bone interface, Factors that affect the load transfer at the bone-implant interface include the type of loading, material properties of the implant and prosthesis, implant geometry, surface structure, quality and quantity of the surrounding bone, and nature of the bone-implant interface. To understand the biomechanical behavior of dental implants, validation of stress and strain measurements is required. The finite element analysis (FEA) has been applied to the dental implant field to predict stress distribution patterns in the implant-bone interface by comparison of various implant designs. This method offers the advantage of solving complex structural problems by dividing them into smaller and simpler interrelated sections by using mathematical techniques. The purpose of this study was to evaluate the stresses induced around the implants in bone using FEA, A 3D FEA computer software (SOLIDWORKS 2004, DASSO SYSTEM, France) was used for the analysis of clinical simulations. Two types (external and internal) of implants of 4.1 mm diameter, 12.0 mm length were buried in 4 types of bone modeled. Vertical and oblique forces of lOON were applied on the center of the abutment, and the values of von Mises equivalent stress at the implant-bone interface were computed. The results showed that von Mises stresses at the marginal. bone were higher under oblique load than under vertical load, and the stresses were higher at the lingual marginal bone than at the buccal marginal bone under oblique load. Under vertical and oblique load, the stress in type I, II, III bone was found to be the highest at the marginal bone and the lowest at the bone around apical portions of implant. Higher stresses occurred at the top of the crestal region and lower stresses occurred near the tip of the implant with greater thickness of the cortical shell while high stresses surrounded the fixture apex for type N. The stresses in the crestal region were higher in Model 2 than in Model 1, the stresses near the tip of the implant were higher in Model 1 than Model 2, and Model 2 showed more effective stress distribution than Model.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.10
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• pp.523-532
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• 2003

Video on Demand(VOD) services cause high resource consumption in a video seuer, because multimedia are characterized by continuous playback, a high bandwidth requirement, and long playback duration. Patching has been proposed to save the network I/O bandwidth of a video server. To achieve true VOD, patching uses multicasting to share video streams, thereby providing immediate VOD services to users without any service latency. A communication channel is used to either multicast the entire video as a regular channel or multicast only the leading portion of a video as a Patching channel. This paper Proposes a buffering patching technique that divides regular channels, as used in patching, into sub-regular channels and regular channels to shorten the holding time of the channels. In the proposed technique, the last portion of video data, corresponding to the size of the buffering window, is not transferred by sub-regular channels, but rather downloaded and buffered in the user buffer from the latest regular channel. When simulations were performed to compare the performance of the proposed technique with that of conventional patching, the results indicated that the proposed technique was superior in terms of the defection rate, average service latency, and fairness, although the amount of video data buffered at each user station was higher than that with patching.

• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1546-1553
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• 2015

In cognitive radio technology, the overall capacity of communications systems can be improved without allocating additional bands by allowing secondary system to utilize the band when a primary system who has right to use the band does not utilize it. Therefore, spectrum sensing to determine the existence of primary system is utmost important in the cognitive radio technology. In this work, we consider a novel cooperative spectrum sensing in cognitive cellular systems. Especially, we consider the case in which heterogeneous primary systems coexist, i.e., heterogenous transmission power and sensing requirement of primary system, such that only portion of users in cognitive cellular systems are able to detect the primary system. In this case, we propose new cooperative spectrum sensing with multiple sensing stages to properly detect the existence of primary systems in this kind of situations. Moreover, we analyze the performance of conventional cooperative spectrum sensing schemes such as OR-rule, AND-rule and MAJORITY-rule under the existence of heterogeneous primary systems. Finally, we investigate the performance of the proposed scheme through computer based simulations and show that the existence of primary systems can be determined accurately by using our proposed scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.527-533
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• 2018

Recently, the device-to-device (D2D) communication has been conceived as the key technology for the next-generation mobile communication systems. The neighbor discovery in which the nearby users are found, is essential for the proper operation of the D2D communication. In this paper, we propose new neighbor discovery scheme based on deep learning technology which has gained a lot of attention recently. In the proposed scheme, the neighboring users can be found using the uplink pilot transmission of users only, unlike conventional neighbor discovery schemes in which direct pilot communication among users is required, such that the signaling overhead can be greatly reduced in our proposed scheme. Moreover, the neighbors with different proximity can also be classified accordingly which enables more accurate neighbor discovery compared to the conventional schemes. The performance of our proposed scheme is verified through the tensorflow-based computer simulations.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.5
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• pp.438-447
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• 2004

A new multilevel PWM inverter using a half-bridge and full-bridge cells is proposed for the use of stand-alone photovoltaic inverters. The configuration of the proposed multilevel PWM inverter is based on a prior 11-level shaped PWM inverter. Among three full-bridge cells employed in the prior inverter, one cell is substituted by a half-bridge cell. Owing to this simple alteration, the proposed inverter has three promising merits. First it increases the number of output voltage levels resulted in high quality output voltages. Second, it reduces two power switching devices by means of employing a half-bridge cell. Third, it reduces power imposed on a transformer connected with the half-bridge unit. That is to say, most power is transferred to loads via cascaded transformers connected with low switching inverters, which are used to synthesize the fundamental output voltage levels whereas the output of a transformer linked to a high switching inverter is used to improve the final output voltage waves; thus, it is desirable in the point of the improvement of the system efficiency. By comparing to the prior 11-level PWM inverter, it assesses the performance of the proposed inverter as a stand-alone photovoltaic inverter. The validity of the proposed inverter is verified by computer-aided simulations and experimental results.