• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.473-476
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• 2007

Location determination of mobile user via RSSI approach has received ample attention from researchers lately. However, it remains a challenging issue due to the complexities of RSSI signal propagation characteristics, which are easily exacerbated by the mobility of user. Hence, a segmentation-based linear spline interpolation method is proposed to cater for the dynamic fluctuation pattern of radio signal in complex environment. This optimization algorithm is proposed in addition to the current radiolocation's (CC2431, Chipcon, Norway) algorithm, which runs on IEEE802.15.4 standard. The enhancement algorithm involves four phases. First phase consists of calibration model in which RSSI values at different static locations are collected and processed to obtain the mean and standard deviation value for the predefined distance. RSSI smoothing algorithm is proposed to minimize the dynamic fluctuation of radio signal received from each reference node when the user is moving. Distances are computed using the segmentation formula obtain in the first phase. In situation where RSSI value falls in more than one segment, the ambiguity of distance is solved by probability approach. The distance probability distribution function(pdf) for each distances are computed and distance with the highest pdf at a particular RSSI is the estimated distance. Finally, with the distances obtained from each reference node, an iterative trilateration algorithm is used for position estimation. Experiment results obtained position the proposed algorithm as a viable alternative for location tracking.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.1
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• pp.13-20
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• 2022

Aircraft weight is an important factor affecting performance and fuel efficiency. In the conceptual design stage of the aircraft, the process of balancing cost and weight is performed using empirical formulas such as fuel consumption cost per weight in estimating element weight. In addition, when an airline operates an aircraft, it promotes fuel efficiency improvement, fuel saving and carbon reduction through weight management activities. The relationship between changes in aircraft weight and changes in fuel consumption is called the cost of weight, and the cost of weight is used to evaluate the effect of adding or reducing weight to an aircraft on fuel consumption. In this study, the problems of the existing cost of weight calculation method are identified, and a new cost of weight calculation method is introduced to solve the problem. Using Breguet's Range Formula and actual flight data of the A350-900 aircraft, two weight costs are calculated based on take-off weight and landing weight. In conclusion, it was suggested that it is reasonable to use the cost of weight based on the take-off weight and the landing weight for other purposes. In particular, the cost of weight based on the landing weight can be used as an empirical formula for estimating element weight and optimizing cost and weight in the conceptual design stage of similar aircraft.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.363-372
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• 2022

Since the recent COVID-19 Pandemic, the ransomware fandom has intensified along with the expansion of remote work. Currently, anti-virus vaccine companies are trying to respond to ransomware, but traditional file signature-based static analysis can be neutralized in the face of diversification, obfuscation, variants, or the emergence of new ransomware. Various studies are being conducted for such ransomware detection, and detection studies using signature-based static analysis and behavior-based dynamic analysis can be seen as the main research type at present. In this paper, the frequency of ".text Section" Opcode and the Native API used in practice was extracted, and the association between feature information selected using K-means Clustering algorithm, Cosine Similarity, and Pearson correlation coefficient was analyzed. In addition, Through experiments to classify and detect worms among other malware types and Cerber-type ransomware, it was verified that the selected feature information was specialized in detecting specific ransomware (Cerber). As a result of combining the finally selected feature information through the above verification and applying it to machine learning and performing hyper parameter optimization, the detection rate was up to 93.3%.

• Journal of Broadcast Engineering
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• v.27 no.1
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• pp.3-12
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• 2022

Image deblurring aims to remove image blur, which can be generated while shooting the pictures by the movement of objects, camera shake, blurring of focus, and so forth. With the rise in popularity of smartphones, it is common to carry portable digital cameras daily, so image deblurring techniques have become more significant recently. Originally, image deblurring techniques have been studied using traditional optimization techniques. Then with the recent attention on deep learning, deblurring methods based on convolutional neural networks have been actively proposed. However, most of them have been developed while focusing on better performance. Therefore, it is not easy to use in real situations due to the speed of their algorithms. To tackle this problem, we propose a novel deep learning-based deblurring algorithm that can be operated in real-time on HD resolution. In addition, we improved the training and inference process and could increase the performance of our model without any significant effect on the speed and the speed without any significant effect on the performance. As a result, our algorithm achieves real-time performance by processing 33.74 frames per second at 1280×720 resolution. Furthermore, it shows excellent performance compared to its speed with a PSNR of 29.78 and SSIM of 0.9287 with the GoPro dataset.

• Journal of Internet Computing and Services
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• v.25 no.4
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• pp.23-37
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• 2024

Digital twin is an M&S (Modeling and Simulation) technology designed to solve or optimize problems in the real world by replicating physical objects in the real world as virtual objects in the digital world and predicting phenomena that may occur in the future through simulation. Digital twins have been elaborately designed and utilized based on data collected to achieve specific purposes in large-scale environments such as cities and industrial facilities. In order to apply this digital twin technology to real life and expand it into user-customized service technology, practical but sensitive issues such as personal information protection and personalization of simulations must be resolved. To solve this problem, this paper proposes a federated learning-based accelerated client training method (FACTS) for personalized digital twins. The basic approach is to use a cluster-driven federated learning training procedure to protect personal information while simultaneously selecting a training model similar to the user and training it adaptively. As a result of experiments under various statistically heterogeneous conditions, FACTS was found to be superior to the existing FL method in terms of training speed and resource efficiency.

• Journal of Korea Water Resources Association
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• v.32 no.5
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• pp.579-591
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• 1999

The operation of a reservoir system is necessary for establishing the operation rule as well as designing the reservoirs for water resources planning or management. Increasingly complex water resource systems require more advanced operation techniques. As a result, various techniques have been introduced and applied until now. In this study Linear Tracking model based on optimal control theory is applied to the operation of the largest scale multi-reservoir system in the Han river and its applicability proved. This system normally supplies the water resources required downstream for hydro-power and plays a role in satisfying the water demand of the Capital region. For the optimal use of the water resources the Linear Tracking model is designed with the objective to maximize the hydro-power energy subject to the water supply demand. The multi-reservoir system includes the seven main reservoirs in IIan river such as Hwachon, Soyanggang, Chunchon, Uiam, Cheongpyong, Chungju and Paldang. These reservoirs have been monthly operated for the past 21 years. Operation results are analyzed with respect to both hydro"power energy and water supply. Additionally the efficiency of the technique is assessed.sessed.

• Progress in Medical Physics
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• v.21 no.3
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• pp.261-273
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• 2010

For the use of Indirect-conversion CMOS (complementary metal-oxide-semiconductor) detectors for digital x-ray radiography and their better designs, we have theoretically evaluated the spatial-frequency-dependent detective quantum efficiency (DQE) using the cascaded linear-systems transfer theory. In order to validate the developed model, the DQE was experimentally determined by the measured modulation-transfer function (MTF) and noise-power spectrum, and the estimated incident x-ray fluence under the mammography beam quality of W/Al. From the comparison between the theoretical and experimental DQEs, the overall tendencies were well agreed. Based on the developed model, we have investigated the DQEs values with respect to various design parameters of the CMOS x-ray detector such as phosphor quantum efficiency, Swank noise, photodiode quantum efficiency and the MTF of various scintillator screens. This theoretical approach is very useful tool for the understanding of the developed imaging systems as well as helpful for the better design or optimization for new development.

• Applied Chemistry for Engineering
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• v.26 no.6
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• pp.730-736
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• 2015

Cyclotrimethylene trinitramine (RDX) is a high explosive commonly used for military applications. Submicronization of RDX particles has been a critical issue in order to alleviate the unintended and accidental stimuli toward safer and more powerful performances. The purpose of this study is to optimize experimental variables for drowning-out crystallization applied to produce submicron RDX particles. Effects of RDX concentration, anti-solvent temperature and anti-solvent mass were analyzed by the central composite rotatable design. The adjusted determination coefficient of regression model was calculated to be 0.9984 having the p-value less than 0.01. Response surface plots based on the central composite rotatable design determined the optimum conditions such as RDX concentration of 3 wt%, anti-solvent temperature of $0.2^{\circ}C$ and anti-solvent mass of 266 g. The optimum and experimental diameters of RDX particles were measured to be $0.53{\mu}m$ and $0.53{\mu}m$, respectively. The regression model satisfactorily predicts the average diameter of RDX particles prepared by drowning-out crystallization. Structure of RDX crystals was found to be ${\alpha}$-form by X-ray diffraction analysis and FT-IR spectroscopy.

• Korean journal of food and cookery science
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• v.31 no.2
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• pp.175-184
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• 2015

The purpose of this study was to determine the optimal mixing ratio of Agaricus blazei Murill powder and butter in the preparation of cookies. The experimental design utilized herein was based on central composite design for response surface methodology, which included 10 experimental points, including 2 replicates for Agaricus blazei Murill and butter. The physical, mechanical, and sensory properties of the test were measured, and these values were applied to the mathematical models. A canonical form and perturbation plot showed the influence of each ingredient on the final mixed product. The spread ratio increased significantly with an increase in Agaricus blazei Murill powder and butter (p<0.05). The response surface methodology was applied to evaluate the effect of Agaricus blazei Murill powder and butter on cookie moisture and color (L, a) (p<0.001). Sensory evaluation showed significant values for color (p<0.05), flavor (p<0.05), texture (p<0.05) and overall quality (p<0.01) in the predicted model. The optimum formulation by numerical and graphical methods was calculated as follows: Agaricus blazei Murill powder 3.63 g, butter 55.37 g.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.533-538
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• 2013

The damage caused by Recent frequently occurring locality torrential rains is increasing rapidly. In case of densely populated metropolitan area, casualties and property damage is a serious due to landslides and debris flows and floods. Therefore, the importance of predictions about the torrential is increasing. Precipitation characteristic of the bad weather in Korea is divided into typhoons and torrential rains. This seems to vary depending on the duration and area. Rainfall is difficult to predict because regional precipitation is large volatility and nonlinear. In this paper, Very short-term precipitation forecasting pattern model is implemented using KLAPS data used by Korea Meteorological Administration. we designed very short term precipitation forecasting pattern model using GA-based RBFNNs. the structural and parametric values such as the number of Inputs, polynomial type,number of fcm cluster, and fuzzification coefficient are optimized by GA optimization algorithm.