• The KIPS Transactions:PartC
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• v.13C no.4 s.107
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• pp.397-404
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• 2006

Successful software attacks require both injecting malicious code into a program's address space and altering the program's flow control to the injected code. Code section can not be changed at program's runtime, so malicious code must be injected into data section. Detoured flow control into data section is a signal of software attack. We propose a new software attack detection method which verify the target address of CALL, JMP, RET instructions, which alter program's flow control, and detect a software attack when the address is not in code section. Proposed method can detect all change of flow control related data, not only program's return address but also function pointer, buffer of longjmp() function and old base pointer, so it can detect the more attacks.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.15-21
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• 2000

The Intelligent Manufacturing Systems (IMS) Rapid Product Development (RPD) Project is an international partnership formed to build a pre-competitive research and development program that will address the integration of new technologies in manufacturing and provide an infrastructure for industry to cooperate much more closely in the product development cycle. In this explanatory paper, a research trend of the RPD project is briefly presented, together with its background and state-of-the-art, focusing on objectives and target results of its sub-projects which include rapid development of functional parts and tools, validation and reverse engineering, and information logistic system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1744-1760
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• 2021

Since correlation filter appeared in the field of object tracking, it plays an increasingly vital role due to its excellent performance. Although many sophisticated trackers have been successfully applied to track the object accurately, very few of them attaches importance to the scale and rotation estimation. In order to address the above limitation, we propose a novel method combined with Fourier-Mellin transform and confidence evaluation strategy for robust object tracking. In the first place, we construct a correlation filter to locate the target object precisely. Then, a log-polar technique is used in the Fourier-Mellin transform to cope with the rotation and scale changes. In order to achieve subpixel accuracy, we come up with an efficient surface fitting mechanism to obtain the optimal calculation result. In addition, we introduce a confidence evaluation strategy modeled on the output response, which can decrease the impact of image noise and perform as a criterion to evaluate the target model stability. Experimental experiments on OTB100 demonstrate that the proposed algorithm achieves superior capability in success plots and precision plots of OPE, which is 10.8% points and 8.6% points than those of KCF. Besides, our method performs favorably against the others in terms of SRE and TRE validation schemes, which shows the superiority of our proposed algorithm in scale and rotation evaluation.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.1
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• pp.92-99
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• 2005

In this paper, we present a high-level design methodology applied on a network system-on-a-chip(SOC) using SystemC. The main target of our approach is to get optimum performance parameters for high network address translation(NAT) throughput. The Fast Ethernet media access controller(MAC) and its direct memory access(DMA) controller are modeled with SystemC in transaction level. They are calibrated through the cycle-based measurement of the operation of the real Verilog register transfer language(RTL). The NAT throughput of the model is within $\pm$10% error compared to the output of the real evaluation board. Simulation speed of the model is more than 100 times laster than the RTL. The validated models are used for intensive architecture exploration to find the performance bottleneck in the NAT router.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.5
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• pp.631-636
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• 2019

Over the last decade, many researchers have investigated a number of vision-based construction object detection algorithms for the purpose of construction site monitoring. However, previous methods require the ground truth labeling, which is a process of manually marking types and locations of target objects from training image data, and thus a large amount of time and effort is being wasted. To address this drawback, this paper proposes a vision-based construction object detection framework that employs an active learning technique while reducing manual labeling efforts. For the validation, the research team performed experiments using an open construction benchmark dataset. The results showed that the method was able to successfully detect construction objects that have various visual characteristics, and also indicated that it is possible to develop the high performance of an object detection model using smaller amount of training data and less iterative training steps compared to the previous approaches. The findings of this study can be used to reduce the manual labeling processes and minimize the time and costs required to build a training database.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.35 no.2
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• pp.65-71
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• 2022

Recently, multi-material structural topology optimization is more critical because it provides reasonable solution to weight reduction challenges and can as well provide effective conceptual design. For conventional multi-material topology optimization (MMTO), the number of design variable increases when the number of candidate materials increases, and accordingly, a significant increase in computational time occurs. Therefore, MMTO with a single design variable, such as the phase section method (PSM) was proposed. This research is focused on improving the PSM, considering three major limitations: the composition ratio does not represent the area or volume ratio, design variables are not sufficiently concentrated to target values, and certain materials are created less than they are required. To address such limitations, the redefined composition ratio and adjusted parameters for better convergence are proposed. The validation of proposed modifications is verified via two- and three-dimensional numerical examples.