• Proceedings of the Korean Information Science Society Conference
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• 2006.06c
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• pp.274-276
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• 2006

e-seal은 RFID(Radio Frequency IDentification) 기술을 사용하여 원격에서 자동으로 봉인상태를 확인할 수 있는 컨테이너 봉인 장치를 말한다. RFID의 특징상 반도체 칩에 기록된 정보를 제 삼자가 쉽게 판독 및 변조할 수 있다는 취약점으로 인하여 활성화되지 못하고 있는 실정이다. ISO에서는 RFID의 취약점을 보안하기 위한 표준작업(ISO 18185)을 진행 중이다. 이 중, ISO 18185-4는 e-seal에 저장되는 자료나 리더와의 RF통신에서 데이터 보호를 위한 표준이다. 이와 관련된 연구로는 인증 프로토콜과 ISO 18185-4를 위한 보고서로 제출된 보안 프로토콜이 있다. 제안된 e-seal 보안 프로토콜을 적용하기 위해서는 e-seal과 리더 간의 데이터를 암/복호화할 키가 필요하지만, 키 서버를 통해 전달받은 마스터 키를 데이터 암/복호화 키로 바로 사용하는 것은 보안 상의 문제점을 야기할 수 있기 때문에 PRF(Pseudo Random Function)을 이용하여 마스터 키로부터 MTK(Mutual Transient Key)를 유도하고, MTK를 암/복호화 키로 사용해야 한다. 기존의 PRF는 일방향 해시 함수(MD5, SHA 등)를 기반으로 하는 HMAC[2. 3]을 일반적으로 사용하였다. 그러나 일방향 해시 함수는 e-seal과 같은 제한된 자원을 갖는 환경에 적합하지 않다. 따라서, 본 논문에서는 e-seal 보안 프로토콜을 위한 효율적인 PRF을 제안한다. 기존의 일방향 해시 함수 기반이 아닌 블록 암호화 알고리즘을 기반으로 하는 MAC을 이용하여 PRF을 보다 효율적으로 구현하였고, 블록 암호화 알고리즘은 AES를 선택 합성체 $GF((2^4)^2)$을 통해 하드웨어 모듈을 최적화 하였다. AES를 기반으로 하는 MAC은 HMAC에 비해 면적 및 처리율에서 뛰어난 결과를 보여주었다.<0.01).이상의 연구 결과, cook-chill생산 시 녹차 추출물의 첨가가 미생물적 품질유지에 효과가 있다고 사료되는 바 본 연구결과를 기초로 급식소에서 음식 생산 시 녹차 추출물 및 천연 항균성 물질 첨가에 따른 미생물적 품질 및 관능적 품질검사를 통한 레시피 개발에 관한 지속적인 연구가 수행되어야 하겠다.다.다리다보니 점심시간을 활용할 수 없게 되는 문제점에 대한 재검토가 필요하다. 따라서 차후 학교급식의 안전성 확보를 위한 급식환경 개선의 일환으로 식당공간 확보 시 신속한 시간 내에 급식이 가능하도록 넓은 공간과 쾌적한 환경의 식당 조성에 대해 관심을 기울여야 할 것으로 사료된다. 이상 여부를 반영하는 임상증상의 빈도가 높은 청소년기 남녀 중학생의 경우 아침과 저녁의 결식빈도 및 외식과 간식의 빈도가 높았고, 아침식사의 질과 체형만족도가 낮은 것으로 나타나 청소년의 건강과 식습관 및 체형만족도가 상호 관련성이 높은 것으로 나타났다. 따라서 본 연구 결과는 성장기 청소년의 건강 유지를 위하여 바람직한 식습관의 중요성을 재인식할 수 있었으며, 올바른 식습관 확립을 위한 영양교육의 중요성이 재확인되었다.경제적일 것으로 판단된다.er 90 % of good relative dynamic modulus of elasticity due to fineness of formation caused by the increase of the unit powder content and the improvement of flowability, without regard to the replacement of crushed stone fines. Therefore, it can be said that the usage of crushed stone fines can control the strength of super flowing concrete by replacement and re

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.11-19
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• 2021

An abnormal object refers to a person, an object, or a mechanical device that performs abnormal and unusual behavior and needs observation or supervision. In order to detect this through artificial intelligence algorithm without continuous human intervention, a method of observing the specificity of temporal features using optical flow technique is widely used. In this study, an abnormal situation is identified by learning an algorithm that translates an input image frame to an optical flow image using a Generative Adversarial Network (GAN). In particular, we propose a technique that improves the pre-processing process to exclude unnecessary outliers and the post-processing process to increase the accuracy of identification in the test dataset after learning to improve the performance of the model's abnormal behavior identification. UCSD Pedestrian and UMN Unusual Crowd Activity were used as training datasets to detect abnormal behavior. For the proposed method, the frame-level AUC 0.9450 and EER 0.1317 were shown in the UCSD Ped2 dataset, which shows performance improvement compared to the models in the previous studies.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.692-703
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• 2021

Recently, with the development of computer graphics technology, research on technology for expressing real objects as more realistic virtual graphics is being actively conducted. Point cloud is a technology that uses numerous points, including 2D spatial coordinates and color information, to represent 3D objects, and they require huge data storage and high-performance computing devices to provide various services. Video-based Point Cloud Compression (V-PCC) technology is currently being studied by the international standard organization MPEG, which is a projection based method that projects point cloud into 2D plane, and then compresses them using 2D video codecs. V-PCC technology compresses point cloud objects using 2D images such as Occupancy map, Geometry image, Attribute image, and other auxiliary information that includes the relationship between 2D plane and 3D space. When increasing the density of point cloud or expanding an object, 3D calculation is generally used, but there are limitations in that the calculation method is complicated, requires a lot of time, and it is difficult to determine the correct location of a new point. This paper proposes a method to generate additional points at more accurate locations with less computation by applying 2D interpolation to the image on which the point cloud is projected, in the V-PCC technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.368-374
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• 2020

Journaling file systems (JFS) manage changes of file systems not yet committed in a data structure known as a journal to restore the file system in the event of an unexpected failure. Extra write operations required for journaling negatively affect the performance of JFS. The high-performance and byte-addressable non-volatile memory (NVM) was expected to easily mitigate these performance problems by providing NVM space as journal storage. However, even with such non-volatile memory technologies, performance problems still arise due to scalability problems inherent in processing transactions of JFS. To solve this problem, we proposes a technique for processing file system transactions for scalable performance. To this end, lock-free data structures are used and multiple I/O requests are allowed to simultaneously be processed on high-performance storage devices with multiple I/O channels. We evaluate the file system with the proposed technique by comparing the original ext4 file system and the recent proposed NVM-based journaling file system on a multi-core server, and experimental results show that our file system has better performance (up-to 2.9/2.3 times) than the original ext4 file system and the recent NVM-based journaling file system, respectively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.5
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• pp.1102-1107
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• 2004

Fingerprint Recognition System is made up of Off-line treatment and On-line treatment; the one is registering all the information of there trieving features which are retrieved in the digitalized fingerprint getting out of the analog fingerprint through the fingerprint acquisition device and the other is the treatment making the decision whether the users are approved to be accessed to the system or not with matching them with the fingerprint features which are retrieved and database from the input fingerprint when the users are approaching the system to use. In matching between On-line and Off-line treatment, the most important thing is which features we are going to use as the standard. Therefore, we have been using “Delta” and “Core” as this standard until now, but there might have been some deficits not to exist in every person when we set them up as the standards. In order to handle the users who do not have those features, we are still using the matching method which enables us to make up of the spanning tree or the triangulation with the relations of the spanned feature. However, there are some overheads of the time on these methods and it is not sure whether they make the correct matching or not. Therefore, I would like to represent the more correct matching algorism in this paper which has not only better matching rate but also lower mismatching rate compared to the present matching algorism by selecting the line segment connecting two minutiae on the same ridge and furrow structures as the reference point.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.1-9
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• 2016

This paper was studied in two ways with respect to the information received from the video signal separation technique of PPI Scop radar device. The proposed technique consists in generating an image signal through the video signal separation and synthesis, symbol generation, the residual image signal generation process. This technology can greatly improve the operating convenience with improved ease of discrimination, screen readability for the operator in analyzing radar information. The first proposed method was constructed for high-speed FPGA-based information processing systems for high speed operation stability of the system. The second proposed method was implemented intelligent algorithms and a software algorithm function curve associated resources.This was required to meet the constraints on the radar information, analysis system. Existing radar systems have not the frame data analysis unit image. However, this study was designed to image data stored in the frame-by-frame analysis of radar images with express information MPEG4 video. Key research content is to highlight the key observations expresses the target, the object-specific monitoring information to the positive image processing algorithm and the function curve delays. For high-definition video, high-speed to implement data analysis and expressing a variety of information was applied to the ARM Processor Support in Pro ASIC3.

• Journal of Korean Society of Transportation
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• v.27 no.5
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• pp.97-111
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• 2009

Image-based traffic information collection systems have entered widespread adoption and use in many countries since these systems are not only capable of replacing existing loop-based detectors which have limitations in management and administration, but are also capable of providing and managing a wide variety of traffic related information. In addition, these systems are expanding rapidly in terms of purpose and scope of use. Currently, the utilization of image processing technology in the field of traffic accident management is limited to installing surveillance cameras on locations where traffic accidents are expected to occur and digitalizing of recorded data. Accurately recording the sequence of situations around a traffic accident in a signal intersection and then objectively and clearly analyzing how such accident occurred is more urgent and important than anything else in resolving a traffic accident. Therefore, in this research, we intend to present a technology capable of overcoming problems in which advanced existing technologies exhibited limitations in handling real-time due to large data capacity such as object separation of vehicles and tracking, which pose difficulties due to environmental diversities and changes at a signal intersection with complex traffic situations, as pointed out by many past researches while presenting and implementing an active and environmentally adaptive methodology capable of effectively reducing false detection situations which frequently occur even with the Gaussian complex model analytical method which has been considered the best among well-known environmental obstacle reduction methods. To prove that the technology developed by this research has performance advantage over existing automatic traffic accident recording systems, a test was performed by entering image data from an actually operating crossroad online in real-time. The test results were compared with the performance of other existing technologies.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.10
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• pp.473-478
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• 2017

Drones require altitude holding in order to achieve flight objectives. The altitude holding of the drone is to repeat the operation of raising or lowering the drone according to the altitude information being measured in real-time. When the drones are maintained altitude, the drone's altitude will continue to change due to external factors such as imbalance in thrust due to difference in motor speed or wind. Therefore, in order to maintain the altitude of drone, we have to exactly measure the continuously changing altitude of the drone. Generally, the acceleration sensor is used for measuring the height of the drones. In this method, there is a problem that the measured value due to the integration error accumulates, and the drone's vibration is recognized by the altitude change. To solve the difficulty of the altitude measurement, commercial drones and existing studies are used for altitude measurement together with acceleration sensors by adding other sensors. However, most of the additional sensors have a limitation on the measurement distance and when the sensors are used together, the calculation processing of the sensor values increases and the altitude measurement speed is delayed. Therefore, it is necessary to accurately measure the altitude of the drone without considering additional sensors or devices. In this paper, we propose a measurement algorithm that improves general altitude measurement method using acceleration sensor and show that accuracy of altitude holding and altitude measurement is improved as a result of applying this algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.213-224
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• 2009

This paper presents a new algorithm for estimating a driver's physical condition using real-time vision system and performs experimentation for real facial image data. The system relies on a face recognition to robustly track the center points and sizes of person's two pupils, and two side edge points of the mouth. The face recognition constitutes the color statistics by YUV color space together with geometrical model of a typical face. The system can classify the rotation in all viewing directions, to detect eye/mouth occlusion, eye blinking and eye closure, and to recover the three dimensional gaze of the eyes. These are utilized to determine the carelessness and drowsiness of the driver. Finally, experimental results have demonstrated the validity and the applicability of the proposed method for the estimation of a driver's physical condition.