• Journal of KIISE:Computer Systems and Theory
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• v.33 no.3
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• pp.178-192
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• 2006

The buffer overflow attack is the single most dominant and lethal form of security exploits as evidenced by recent worm outbreaks such as Code Red and SQL Stammer. In this paper, we propose microarchitectural techniques that can detect and recover from such malicious code attacks. The idea is that the buffer overflow attacks usually exhibit abnormal behaviors in the system. This kind of unusual signs can be easily detected by checking the safety of memory references at runtime, avoiding the potential data or control corruptions made by such attacks. Both the hardware cost and the performance penalty of enforcing the safety guards are negligible. In addition, we propose a more aggressive technique called corruption recovery buffer (CRB), which can further increase the level of security. Combined with the safety guards, the CRB can be used to save suspicious writes made by an attack and can restore the original architecture state before the attack. By performing detailed execution-driven simulations on the programs selected from SPEC CPU2000 benchmark, we evaluate the effectiveness of the proposed microarchitectural techniques. Experimental data shows that enforcing a single safety guard can reduce the number of system failures substantially by protecting the stack against return address corruptions made by the attacks. Furthermore, a small 1KB CRB can nullify additional data corruptions made by stack smashing attacks with only less than 2% performance penalty.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.8
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• pp.321-328
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• 2014

In this paper, we present a MapReduce-based mobility pattern mining system which can predict efficiently the next place of mobile users. It learns the mobility pattern model of each user, represented by Hidden Markov Models(HMM), from a large-scale trajectory dataset, and then predicts the next place for the user to visit by applying the learned models to the current trajectory. Our system consists of two parts: the back-end part, in which the mobility pattern models are learned for individual users, and the front-end part, where the next place for a certain user to visit is predicted based on the mobility pattern models. While the back-end part comprises of three distinct MapReduce modules for POI extraction, trajectory transformation, and mobility pattern model learning, the front-end part has two different modules for candidate route generation and next place prediction. Map and reduce functions of each module in our system were designed to utilize the underlying Hadoop infrastructure enough to maximize the parallel processing. We performed experiments to evaluate the performance of the proposed system by using a large-scale open benchmark dataset, GeoLife, and then could make sure of high performance of our system as results of the experiments.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.1
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• pp.51-58
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• 2007

This paper presented an adaptive pipeline architecture for a high-performance and low-power asynchronous processor. The proposed pipeline architecture employed a stage-skipping and a stage-combining scheme. The stage-skipping scheme can skip the operation of a bubble stage that is not used pipeline stage in an instruction execution. In the stage-combining scheme, two consecutive stages can be joined to form one stage if the latter stage is empty. The proposed pipeline architecture could reduce the processing time and power consumption. The proposed architecture supports multi-processing in the EX stage that executes parallel 4 instructions. We designed an asynchronous microprocessor to estimate the efficiency of the proposed pipeline architecture that was synthesized to a gate level design using a $0.35-{\mu}m$ CMOS standard cell library. We evaluated the performance of the target processor using SPEC2000 benchmark programs. The proposed architecture showed about 2.3 times higher speed than the asynchronous counterpart, AMULET3i. As a result, the proposed pipeline schemes and architecture can be used for asynchronous high-speed processor design

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.2
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• pp.181-190
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• 2007

The linkage framework of surface geometric modeling based on the NURBS and shell finite element analysis is developed in this study. In the geometrically exact shell finite element analysis, the accuracy of the analysis strongly depends upon the accurate computation of the surface geometric quantities. Therefore if we obtain the necessary geometric quantities from the NVRBS surface equation, it's possible to construct the effective linkage framework of surface modeling in the CAD systems and shell finite element analysis using geometrically exact shell finite element. Besides, the linkage framework can be applied to the analysis of general and complex surfaces as well as simple surfaces. In this study, the shell surfaces are generated by interpolating given set of data points based on the NURBS surfaces. These data points usually can be obtained from surface scanning. But the representations of the generated NURBS surface are not same to one another. The accuracy depends on the chosen parameterization methods used in NURBS. Therefore, it is needed to select the suitable parameterization method according to the geometry of the surfaces. To verify the performance and accuracy of our developed linkage framework, we solve several well-known benchmark problems and assess the performance of the developed method.

• Proceedings of the KSMRM Conference
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• 2003.10a
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• pp.103-105
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• 2003

After fifteen years of development, Magnetic Resonance (MR) technology for human imaging and spectroscopy is reaching a refined state with FDA approved 3T clinical products from Siemens, GE, and Philips. Broker has cleared CE approval with a 4T system. Varian supports a 4T system platform as well. Shielded magnets are standard at 3T from GE, Oxford, Magnex, and IGC. A shielded 4T whole body magnet is available from Oxford. Stronger switched gradients and dynamic shim coils, desired at any field, areespecially useful at higher static magnetic fields B0. In addition to the higher currents required for higher resolution slice or volume selection afforded by higher SNR, whole body gradient coils will be driven at increasing slew rates to meet the needs of new cardiac applications and other requirements. For example 3T and 4T systems are now being equipped with 2kV, 500A gradient coils and amplifiers capable of generating 4G/cm in 200msec, over a 67+/-cm bore diameter. High field EPI applications require oscillation rates at 1 kHz and higher. To achieve a benchmark 0.2 ppm shim over a 30cm sphere in a high field magnet, at least four stages of shimming need to be considered. 1) A good high field magnet will be built to a homogeneity spec. falling in the range of 100 to 150 ppm over this 30cm spherical "sweet spot" 2) Most modern high field magnets will also have superconducting shim coils capable of finding 1.5 ppm by their adjustment during system installation. 3) Passive ferro-magnetic shimming combined with 4) active, high order room temperature shim coils (as many as five orders are now being recommended) will accomplish 0.2 ppm over the 30cm sphere, and 0.1 ppm over a human brain in even the highest field magnets for human studies. Safety concerns for strong, fast gradients at any B0 field include acoustic noise and peripheral nerve stimulation. One or more of the mechanical decoupling methods may lead to quieter gradients. Patient positioning relative to asymmetric or short gradient coils may limit peripheral nerve stimulation at higher slew rates. Gradient designs combining a short coil for local speed and strength with a longer coil for coverage are being developed for 3T systems. Local gradients give another approach to maximizing performance over a limited region while keeping within the physiologically imposed dB0/dt performance limits.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.10
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• pp.69-77
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• 1998

This paper presents a new efficient and stable multilevel partitioning algorithm for VLSI circuit design. The performance of multilevel partitioning algorithms that are proposed to enhance the performance of previous iterative-improvement partitioning algorithms for large scale circuits, depend on choice of construction methods for partition hierarchy. As the most of previous multilevel partitioning algorithms forces experimental constraints on the process of hierarchy construction, the stability of their performances goes down. The lack of stability causes the large variation of partition results during multiple runs. In this paper, we minimize the use of experimental constraints and propose a new method for constructing partition hierarchy. The proposed method clusters the cells with the connection status of the circuit. After constructing the partition hierarchy, a partition improvement algorithm, HYIP$^{[11]}$ using hybrid bucket structure, unclusters the hierachy to get partition results. The experimental results on ACM/SIGDA benchmark circuits show improvement up to 10-40% in minimum outsize over the previous algorithm $^{[3] [4] [5] [8] [10]}$. Also our technique outperforms ML$^{[10]}$ represented multilevel partition method by about 5% and 20% for minimum and average custsize, respectively. In addition, the results of our algorithm with 10 runs are better than ML algorithm with 100 runs.

• 한국노년학
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• v.40 no.2
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• pp.359-377
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• 2020

The purpose of this study is to examine the direction of the elderly theatre by analyzing an example of the elderly theatre program which is attempted in a way of the welfare of senior citizens in terms of cultural support. To this end, the 'Hoechun Circus' composed of elderly women in Dangjin, South Chungcheong Province, was investigated and analyzed. Research methods uses a case study, performance theory, and peer review strategies to increase the validity of the study. The results of the study are as follows: Firstly, the elderly women intended to communicate with children and adolescents through performance; Secondly, they wanted to communicate with other physically uncomfortable elderly people; Thirdly, they also attempted to communicate with young or middle-aged as well as all residents; Fourthly, they experienced a new genre of theatre to identify themselves in a different ways and enhance their sense of accomplishment and spent their old age pleasantly and informally. Based on these findings, the following suggestions were made. First, we should expand the theatre programs of senior citizens which benchmark the 'Hoechun Circus'. Second, various cases of elderly theater should be studied and policy research to support such elderly theatre is necessary. Besides, educational courses to train elderly theatre experts should also be developed. Third, it should also seek ways for the program to move beyond regional limits and interact with organizations at home and abroad. Fourth, there is room to explore new ways in the field of theater therapy, and the development of sociodrama or psychodrama programs can be an alternative.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.171-189
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• 2022

Online reviews play an essential role in the consumer's purchasing decision-making process, and thus, providing helpful and reliable reviews is essential to consumers. Previous online review helpfulness prediction studies mainly predicted review helpfulness based on the consistency of text and rating information of online reviews. However, there is a limitation in that representation capacity or review text and rating interaction. We propose a CNN-RHP model that effectively learns the interaction between review text and rating information to improve the limitations of previous studies. Multi-channel CNNs were applied to extract the semantic representation of the review text. We also converted rating into independent high-dimensional embedding vectors representing the same dimension as the text vector. The consistency between the review text and the rating information is learned based on element-wise operations between the review text and the star rating vector. To evaluate the performance of the proposed CNN-RHP model in this study, we used online reviews collected from Amazom.com. Experimental results show that the CNN-RHP model indicates excellent performance compared to several benchmark models. The results of this study can provide practical implications when providing services related to review helpfulness on online e-commerce platforms.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.147-157
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• 2022

The backward-facing step (BFS) is a benchmark geometry for analyzing flow separation occurred at the edge and resulting development of shear layer and recirculation zone that are occupied by turbulent flow. It is important to accurately reproduce and analyze the mean flow and turbulence statistics of such flows to design physically stable and performance assurance structure. We carried out 3D RANS computations with widely used, two representative turbulence models, k-ω SST and RNG k-ε, to reproduce BFS flow at the Reynolds number of 23,000 and the Froude number of 0.22. The performance of RANS computations is evaluated by comparing numerical results with an experimental measurement. Both RANS computations with two turbulence models appear to reasonably well reproduce mean flow in the shear layer and recirculation zone, while RNG k-ε computation results in about 5% larger velocity between the outer edge of boundary layer and the free surface above the recirculation zone than k-ω SST computation and experiment. Both turbulence models underestimate the shear stress distribution experimentally observed just downstream of the sharp edge of BFS, while shear stresses computed in the boundary layer downstream of reattachment point are agree reasonably well with experimental measurement. RNG k-ε modeling reproduces better shear stress distribution along the bottom boundary layer, but overestimates shear shear stress in the approaching boundary layer and above the bottom boundary layer downstream of the BFS.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.17-25
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• 2023

In this paper, we propose a model that can perform human pose estimation through a MobileViT-based model with fewer parameters and faster estimation. The based model demonstrates lightweight performance through a structure that combines features of convolutional neural networks with features of Vision Transformer. Transformer, which is a major mechanism in this study, has become more influential as its based models perform better than convolutional neural network-based models in the field of computer vision. Similarly, in the field of human pose estimation, Vision Transformer-based ViTPose maintains the best performance in all human pose estimation benchmarks such as COCO, OCHuman, and MPII. However, because Vision Transformer has a heavy model structure with a large number of parameters and requires a relatively large amount of computation, it costs users a lot to train the model. Accordingly, the based model overcame the insufficient Inductive Bias calculation problem, which requires a large amount of computation by Vision Transformer, with Local Representation through a convolutional neural network structure. Finally, the proposed model obtained a mean average precision of 0.694 on the MS COCO benchmark with 3.28 GFLOPs and 9.72 million parameters, which are 1/5 and 1/9 the number compared to ViTPose, respectively.