• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.9
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• pp.2483-2504
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• 2023

Most existing low-light enhancement algorithms either use a large number of training parameters or lack generalization to real-world scenarios. This paper presents a novel lightweight and robust pixel-wise polynomial approximation-based deep network for low-light image enhancement. For mapping the low-light image to the enhanced image, pixel-wise higher-order polynomials are employed. A deep convolution network is used to estimate the coefficients of these higher-order polynomials. The proposed network uses multiple branches to estimate pixel values based on different receptive fields. With a smaller receptive field, the first branch enhanced local features, the second and third branches focused on medium-level features, and the last branch enhanced global features. The low-light image is downsampled by the factor of 2b-1 (b is the branch number) and fed as input to each branch. After combining the outputs of each branch, the final enhanced image is obtained. A comprehensive evaluation of our proposed network on six publicly available no-reference test datasets shows that it outperforms state-of-the-art methods on both quantitative and qualitative measures.

• 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.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.265-270
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• 2013

Strength design for a lightweight bicycle frame made of carbon/epoxy composite laminates was studied using Tsai-Wu's failure criterion. For the design of bicycle frames, reducing the weight of the frame is of great importance. Furthermore, the frame should satisfy the required strength under specific loading cases. In accordance with the European EN 14764 standard for bicycle frames, three loading cases-pedaling, vertical, and level loadings-were investigated in this study. Because of the anisotropic characteristics of composite materials, it is important to decide the appropriate stacking sequence and the number of layers to be used in the composite bicycle frame. From finite element analysis results, the most suitable stacking sequence of the fiber orientation and the number of layers were determined. The stacking sequences of $[0]_{8n}$, $[90]_{8n}$, $[0/90]_{2ns}$, $[{\pm}45]_{2ns}$, $[0/{\pm}45/90]_{ns}$ (n = 1, 2, 3, 4) were used in the analysis. The results indicated that the $[0/{\pm}45/90]_{3s}$ lay-up model was suitable for a composite bicycle frame. Furthermore, the weakest point and layer were investigated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.193-200
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• 2023

Cryptanalysis can be performed by various techniques such as known plaintext attack, differential attack, side-channel analysis, and the like. Recently, many studies have been conducted on cryptanalysis using deep learning. A known-plaintext attack is a technique that uses a known plaintext and ciphertext pair to find a key. In this paper, we use deep learning technology to perform a known-plaintext attack against S-PRESENT, a reduced version of the lightweight block cipher PRESENT. This paper is significant in that it is the first known-plaintext attack based on deep learning performed on a reduced lightweight block cipher. For cryptanalysis, MLP (Multi-Layer Perceptron) and 1D and 2D CNN(Convolutional Neural Network) models are used and optimized, and the performance of the three models is compared. It showed the highest performance in 2D convolutional neural networks, but it was possible to attack only up to some key spaces. From this, it can be seen that the known-plaintext attack through the MLP model and the convolutional neural network is limited in attackable key bits.

• Journal of Industrial Convergence
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• v.22 no.4
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• pp.21-29
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• 2024

This study analyzed the difficulty of scoring in different match situations in relation to which competitor scored first. The study analyzed the data from the 2022 Guadalajara World Taekwondo Championships. The analysis was performed for two separate weight classes: lightweight and heavyweight. Four game content variables were used: whether the athlete scored first, attack type, attack area, and game situation. Descriptive statistics, the Rasch model, and discrimination function questions were applied for data processing. SPSS and Winsteps were used for the statistical analysis, and the statistical significance level was set at 0.05. Consequently, in the lightweight class, the scoring frequency of the first scorer was high for all the game variables. In the heavyweight class, the scoring frequency for the first scorer was high for the attack type and attack area. By contrast, those who did not score first were more frequently found to be in a loss situation. By analyzing the scoring difficulties in different match situations based on whether the competitor scored first, the athletes who scored first in attack type most easily scored first. In losing situations, the athletes who scored first in attack area scored most easily, whereas those who did not score first scored most easily in body and match situations. For the heavyweight class, those who scored first in terms of attack type, counter-attack, and attack area scored the most easily while winning in body and match situations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.700-713
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• 2015

It is critical to design energy-efficient routing protocols for battery-limited mobile ad hoc networks, especially in which the energy-consuming MIMO techniques are employed. However, there are several challenges in such a design: first, it is difficult to characterize the energy consumption of a MIMO-based link; second, without a careful design, the broadcasted RREP packets, which are used in most energy-efficient routing protocols, could flood over the networks, and the destination node cannot decide when to reply the communication request; third, due to node mobility and persistent channel degradation, the selected route paths would break down frequently and hence the protocol overhead is increased further. To address these issues, in this paper, a novel Greedy Energy-Efficient Routing (GEER) protocol is proposed: (a) a generalized energy consumption model for the MIMO-based link, considering the trade-off between multiplexing and diversity gains, is derived to minimize link energy consumption and obtain the optimal transmit model; (b) a simple greedy route discovery algorithm and a novel adaptive reply strategy are adopted to speed up path setup with a reduced establishment overhead; (c) a lightweight route maintenance mechanism is introduced to adaptively rebuild the broken links. Extensive simulation results show that, in comparison with the conventional solutions, the proposed GEER protocol can significantly reduce the energy consumption by up to 68.74%.

• Journal of KIISE
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• v.44 no.3
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• pp.332-337
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• 2017

When using IFC data consisting of STEP schema based on the EXPRESS language, it is not easy for collaborating project stakeholders to share BIM modeling shape information. The IFC viewer application must be installed on the desktop PC to review the BIM modeling shape information defined within the IFC, because the IFC viewer application not only parse STEP structure information model but also process the 3D feature construction for a 3D visualization. Therefore, we propose a lightweight data structure design for web visualization by parsing IFC data and constructing 3D modeling data. Our experimental results show the weight reduction of IFC data is about 40% of original file size and the web visualization is able to see the same quality with all web browsers which support WebGL on PCs and smartphones. If applied research is conducted about the web visualization based on IFC data of the last construction phase, it could be utilized in various fields ranging from the facility maintenance to indoor location-based services.

• Journal of KIBIM
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• v.6 no.2
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• pp.39-46
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• 2016

While institutional matters such as improvement on Basic Guidelines for Construction Safety are greatly concerned to reduce falling accidents at construction sites, there are short of studies on how to practically predict accident signs at construction sites and to preemptively prevent them. As one of existing accident prevention methods, it was attempted to build the early warning system based on standardized accident scenarios to control the situations. However, the investment cost was too high depending on the site situation, and it did not help construction workers directly since it was developed to mainly provide support operational work support to safety managers. In the long run, it would be possible to develop the augmented reality based accident prevention method from the worker perspective by extracting product information from BIM, visually rendering it along with site installation materials term and comparing it with the site situation. However, to make this method effective, the BIM model should be implemented first and the technology that can promptly process site situations should be introduced. Accordingly, it is necessary to identify risk signs through lightweight image processing to promptly respond only with currently available resources. In this study, it was intended to propose the system concept that identified potential risk factors of falling accidents by histogram equalization, which was known as the fastest image processing method presently, used visual words, which could enhance model classification by wording image records, to determine the risk factors and notified them to the work manager.

• Journal of Korea Multimedia Society
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• v.12 no.4
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• pp.550-558
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• 2009

In ubiquitous environment, more small, lightweight, cheap and movable device is used than one device used in wired network environment. Multimedia service which is anytime, anywhere, is provided by device. However, it does not ensure the fair use of multimedia contents and causes damage to the contents providers because of illegal copy and distribution and indiscriminate use of digital contents. For solving this problems, DRM is applied to wired network but it has the problems does not protect stored license and manage license completely because of depending on simple protection such as device authentication and cryptographic algorithm. This paper proposes the license management model using digital forensic and DRM that prevents contents and licenses from distributing illegally and also enables the creation of evidence for legal countermeasure and the protection of license in whole life cycle.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.12
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• pp.1045-1055
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• 2013

It is true that the dependency on import is currently high in case of the safety checkup system of domestic airplanes, and it is at the point of time that localization of HUMS for small airplanes is required. In this study, the design factors were selected for the lightweight of HUMS for small airplanes by using Pro-Engineer which is a design tool and Abaqus. 9 models were made through experiment plans with Taguchi method for this, and the each model for weight lightening was selected through vibration analysis and shock analysis while in operation with experiment profile values. After fabricating HUMS, it was verified that as a result of experiment with the same profile values as the analysis, there was similarity between the analyzed values and values of the experiment. As a result of performing weight lightening which is the purpose of the study, electronic performance for small airplanes is assured and a design plan reducing 15 % weight compared to the targeted weight was deduced. Besides, it could be verified that the light weight model satisfied the maximum allowable displacement value of PCB[printed circuit board] and accordingly satisfied electronic properties of HUMS. In this study, the reliability of a product was certified through the result of an experiment on ground. If the reliability of HUMS were verified through a test flight in the future, it is considered that it would make a big contribution to localization of aerospace electronic equipment.