• Korean Security Journal
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• no.14
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• pp.367-388
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• 2007

Some of individuals working at various fields of security guard are given the legal right to use a gun to cope with expected risks and crimes. Not only in Korea but also throughout the world, a pistol is being used as a device for the workers of security guard such as the army, the police and intelligence agencies to keep the law and social order. A pistol, which is regarded as the last safety measure of security guard, is easy to carry but, because of its short barrel for high portability, its hit ratio and long-range shooting performance are much lower than ordinary guns. Despite such weak points, a pistol can be a great tool because of its high portability and if the users make steady efforts to improve their skills and, for this reason, it has been being used widely until now. National agency workers' pistol shooting skills depend on several important factors, but for the fast and accurate shooting, the mot important factor is how to aim at the target. Because it takes a relatively longer time to align the sight on the target, the change of the sight alignment method is expected to improve pistol shooting skills a lot. In Korea, however, most of national agency training centers teach the basic aiming method that crosses the foresight and the backsight and aligns the crossing to the target. That is, they teach the sight alignment method for fixed targets. Some agencies in Korea and foreign countries that have used guns more frequently and longer than us are teaching different sight alignment methods as well. Representative ones of them are aiming only with the foresight and pointing shooting. These aiming methods are expected to produce good results against moving targets. While the basic sight alignment method has to cross the foresight and the backsight and then to align the crossing to the target, so takes a longer time than other aiming methods, the other two aiming methods are expected to be effective in fields where both swiftness and accuracy are require. Because domestic agencies are teaching mainly the basic sight alignment method, the present study purposed to examine the effects of different aiming methods on shooting records and ultimately to contribute to national agency workers' operation. For this purpose, we selected 20 policemen from local police commandos under the National Police Agency who were accustomed to pistol shooting and measured their pistol shooting. According to the results, the pointed shooting method showed the best record in 5m short.range shooting. As to hit ratio in 15m shooting, which is relatively long.range for pistol shooting, the basic aiming method showed the best record, but the results of statistical analysis showed that pointed shooting is most superior. Of course, the results were obtained from a group who were used to and skillful in pistol shooting, but they are considered meaningful in that all the police and national agency workers should have such high shooting skills.

• The KIPS Transactions:PartA
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• v.12A no.5 s.95
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• pp.413-420
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• 2005

The Newton-Raphson iterative algorithm for finding a floating point reciprocal square mot calculates it by performing a fixed number of multiplications. In this paper, a variable latency Newton-Raphson's reciprocal square root algorithm is proposed that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the rediprocal square root of a floating point number F, the algorithm repeats the following operations: '$X_{i+1}=\frac{{X_i}(3-e_r-{FX_i}^2)}{2}$, $i\in{0,1,2,{\ldots}n-1}$' with the initial value is '$X_0=\frac{1}{\sqrt{F}}{\pm}e_0$'. The bits to the right of p fractional bits in intermediate multiplication results are truncated and this truncation error is less than '$e_r=2^{-p}$'. The value of p is 28 for the single precision floating point, and 58 for the double precision floating point. Let '$X_i=\frac{1}{\sqrt{F}}{\pm}e_i$, there is '$X_{i+1}=\frac{1}{\sqrt{F}}-e_{i+1}$, where '$e_{i+1}{<}\frac{3{\sqrt{F}}{{e_i}^2}}{2}{\mp}\frac{{Fe_i}^3}{2}+2e_r$'. If '$|\frac{\sqrt{3-e_r-{FX_i}^2}}{2}-1|<2^{\frac{\sqrt{-p}{2}}}$' is true, '$e_{i+1}<8e_r$' is less than the smallest number which is representable by floating point number. So, $X_{i+1}$ is approximate to '$\frac{1}{\sqrt{F}}$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications Per an operation is derived from many reciprocal square root tables ($X_0=\frac{1}{\sqrt{F}}{\pm}e_0$) with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal square root unit. Also, it can be used to construct optimized approximate reciprocal square root tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia, scientific computing, etc.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.9
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• pp.251-258
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• 2020

This study investigated the effect of Zardaverine supplementation in freezing extender, on kinetic characteristics of post-thawed boar sperm. Cryopreservation of boar sperm is an important technique of assisted reproductive technology and genetic resource banking. Although this technique is particularly useful, freeze-thaw cycles associated with sperm cryopreservation significantly reduce sperm quality. Semen from mature Duroc boars were collected and cryopreserved in freezing extenders (LEY) treated with varying concentrations of Zardaverine (0, 20, 50, 75, 100 𝜇M). The time-dependent kinetic characteristics of post-thawed spermatozoa were determined after thawing by applying computer-assisted sperm analysis (CASA). We observed that the motility immediately after thawing was significantly higher in 20 𝜇M stocks than in control (0 𝜇M) and the other treatments (p<0.05). Curvilinear velocity (VCL) in 0 𝜇M and 20 𝜇M stocks were significantly higher than the other treatment groups, except 75 𝜇M (p<0.05). Higher average path velocity (VAP) was obtained at 20 𝜇M as compared to 100 𝜇M, whereas amplitude of head lateral displacement (ALH) was significantly higher at 20 𝜇M than 50 𝜇M and 100 𝜇M (p<0.05). No differences were obtained for Straight-line velocity (VSL) and Linearity (LIN). In conclusion, our results indicate that Zardaverine improves the motility, VCL, VAP, and ALH of post-thawed boar sperm.

• Food Science and Preservation
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• v.13 no.6
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• pp.720-725
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• 2006

This study was conducted to investigate extracting solution effect on the chemical compositions in different parts of Korean mountain Ginseng. Water, 80% EtOH and 80% MeOH are used as extraction solutions, and extracting conditions were 2 hr at $85^{\circ}C$ in water bath. The Brix(%) of the extract were ranged from $0.42{\sim}22.58%$, 80% EtOH extract for leaf is the highest level as 22.58%. The pH ranges of the extracts were $4.43{\sim}7.41$ and brown color of the extract was the highest with 1.803 in 80% EtOH extract for leaf, respectively. In case of hunter's color value of the extract, L value is the highest with 24.35 in 80% EtOH extract of seed, a and b value were the highest with 0.41 in 100% water extract of leaf and 3.69 in 80% MeOH extract of stem. Sucrose is the major free sugar of the extinct it highest content with 3673 mg% in 80% MeOH extract of mot and fructose is the highest with 1897 mg% in 80% MeOH extract of leaf, Major organic acids are identified as malic, tartaric and citric acid, and total organic acid content is the highest with 5,254 mg% in 80% MeOH extract of leaf and 1,527 mg% in 80% EtOH extract of leaf, The extracted major minerals ate P and K, P content highest with 15,563 ppm in 100% water extract of stem, K is 4,952 ppm in 80% MeOH extract of leaf, and Ca is the highest with 3,052 ppm in 1011% water extract of leaf. These results suggest that extracting solvent (80% MeOH) is concerned with the extract preparation of Korea Mountain Ginseng.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.