• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.873-879
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• 2023

This study explored the use of artificial intelligence(AI) to detect foreign bodies in chest X-ray images. Medical imaging, especially chest X-rays, plays a crucial role in diagnosing diseases such as pneumonia and lung cancer. With the increase in imaging tests, AI has become an important tool for efficient and fast diagnosis. However, images can contain foreign objects, including everyday jewelry like buttons and bra wires, which can interfere with accurate readings. In this study, we developed an AI algorithm that accurately identifies these foreign objects and processed the National Institutes of Health chest X-ray dataset based on the YOLOv8 model. The results showed high detection performance with accuracy, precision, recall, and F1-score all close to 0.91. Despite the excellent performance of AI, the study solved the problem that foreign objects in the image can distort the reading results, emphasizing the innovative role of AI in radiology and its reliability based on accuracy, which is essential for clinical implementation.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.89-96
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• 2023

In this paper, we propose a GPU-based method for real-time processing of dynamic re-meshing required for tearing cloth. Thin shell materials are used in various fields such as physics-based simulation/animation, games, and virtual reality. Tearing the fabric requires dynamically updating the geometry and connectivity, making the process complex and computationally intensive. This process needs to be fast, especially when dealing with interactive content. Most methods perform re-meshing through low-resolution simulations to maintain real-time, or rely on an already segmented pattern, which is not considered dynamic re-meshing, and the quality of the torn pattern is low. In this paper, we propose a new GPU-optimized dynamic re-meshing algorithm that enables real-time processing of high-resolution fabric tears. The method proposed in this paper can be used for virtual surgical simulation and physics-based modeling in games and virtual environments that require real-time, as it allows dynamic re-meshing rather than pre-split meshes.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1307-1312
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• 2023

In this paper, we propose a hybrid camera system that combines cameras with different focal lengths and LiDAR (Light Detection and Ranging) sensors to address the core components of autonomous driving perception technology, which include object recognition and distance measurement. We extract objects within the scene and generate precise location and distance information for these objects using the proposed hybrid camera system. Initially, we employ the YOLO7 algorithm, widely utilized in the field of autonomous driving due to its advantages of fast computation, high accuracy, and real-time processing, for object recognition within the scene. Subsequently, we use multi-focal cameras to create depth maps to generate object positions and distance information. To enhance distance accuracy, we integrate the 3D distance information obtained from LiDAR sensors with the generated depth maps. In this paper, we introduce not only an autonomous vehicle platform capable of more accurately perceiving its surroundings during operation based on the proposed hybrid camera system, but also provide precise 3D spatial location and distance information. We anticipate that this will improve the safety and efficiency of autonomous vehicles.

• The Journal of the Acoustical Society of Korea
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• v.25 no.2
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• pp.61-71
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• 2006

An MP3 encoder chip has been designed and fabricated with the hardware and software co-design concepts. In the aspect of the software. the calculation cycles of the distortion control loop. which requires most of the calculation cycles in MP3 encoding procedure. have been reduced to $67\%$ of the original algorithm through the 'scale factor Pre-calculation'. By using a floating Point 32 bit DSP core and designing the FFT block with the hardware. we can get the additional reduction of the calculation cycles in addition to the software optimization. The designed chip has been verified using HW emulation and fabricated via 0.25um CMOS technology The fabricated chip has the size of $6.2{\time}6.2mm^2$ and operates normally on the test board in the qualitative and quantitative aspect.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.59-71
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• 2012

PKI-based public key scheme is outstanding in terms of authenticity and privacy. Nevertheless its application brings big burden due to the certificate/key management. It is difficult to apply it to limited computing devices in WSN because of its high encryption complexity. The Bilinear Pairing emerged from the original IBE to eliminate the certificate, is a future significant cryptosystem as based on the DDH(Decisional DH) algorithm which is significant in terms of computation and secure enough for authentication, as well as secure and faster. The practical EC Weil Pairing presents that its encryption algorithm is simple and it satisfies IND/NM security constraints against CCA. The Random Oracle Model based IBE PKG is appropriate to the structure of our target system with one secret file server in the operational perspective. Our work proposes modification of the Weil Pairing as proper to the closed network for secret file distribution[2]. First we proposed the improved one computing both encryption and message/user authentication as fast as O(DES) level, in which our scheme satisfies privacy, authenticity and integrity. Secondly as using the public key ID as effective as PKI, our improved IBE variant reduces the key exposure risk.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.4
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• pp.26-41
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• 2012

It is necessary to manage, forecast and prepare agricultural production based on accurate and up-to-date information in order to cope with the climate change and its impacts such as global warming, floods and droughts. This study examined the applicability as well as challenges of the object-based image analysis method for developing a land cover image classification algorithm, which can support the fast thematic mapping of wide agricultural areas on a regional scale. In order to test the applicability of RapidEye's multi-temporal spectral information for differentiating agricultural land cover types, the integration of other GIS data was minimized. Under this circumstance, the land cover classification accuracy at the study area of Kimje ($1300km^2$) was 80.3%. The geometric resolution of RapidEye, 6.5m showed the possibility to derive the spatial features of agricultural land use generally cultivated on a small scale in Korea. The object-based image analysis method can realize the expert knowledge in various ways during the classification process, so that the application of spectral image information can be optimized. An additional advantage is that the already developed classification algorithm can be stored, edited with variables in detail with regard to analytical purpose, and may be applied to other images as well as other regions. However, the segmentation process, which is fundamental for the object-based image classification, often cannot be explained quantitatively. Therefore, it is necessary to draw the best results based on expert's empirical and scientific knowledge.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.153-162
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• 2013

This paper proposes the most simple method for optimal solution of the transshipment problem. Usually the transshipment problem is solved by direct linear programming or TSM (Transportation Simplex Method). The method using TSM has two steps. First it is to get a initial solution using NCM, LCM, or VAM, second to refine the initial solution using MOD or SSM. However the steps is complex and difficult. The proposed method applies the method that transforms transshipment problem to transportation problem. In the proposed method it simply selects the minimum cost of rows about transportation problem, and then it applies the method that assigns a transported volume as an ascending sort of the costs of rows about the selected costs. Our method makes to be very fast got the initial value. Also we uses the method that controls assignment volume, if a heavy item of cost is assigned to a transported volume and it has a condition to be able to transform to more lower cost. The proposed algorithm simply got the optimal solution with applying to 11 transshipment problem.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.107-114
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• 2019

In this paper, the P-wave multiple detection system for the fast and accurate earthquake early warning nearby the epicenter was developed. The developed systems were installed in five selected public buildings for the validation. During the monitoring, a magnitude 2.3 earthquake occurred in Pohang on 26 September 2019. P-wave initial detection algorithms were operated in three out of four systems installed in Pohang area and recorded as seismic events. At the nearest station, 5.5 km from the epicenter, P-wave signal was detected 1.2 seconds after the earthquake, and S-wave was reached 1.02 seconds after the P-wave reached, providing some alarm time. The maximum accelerations recorded in three different stations were 6.28 gal, 6.1 gal, and 5.3 gal, respectively. The alarm algorithm did not work, due to the high threshold of the maximum ground acceleration (25.1 gal) to operate it. If continuous monitoring and analysis are to be carried out in the future, the developed system could use a highly effective earthquake warning system suitable for the domestic situation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4717-4737
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• 2017

Today, smart grids, smart homes, smart water networks, and intelligent transportation, are infrastructure systems that connect our world more than we ever thought possible and are associated with a single concept, the Internet of Things (IoT). The number of devices connected to the IoT and hence the number of traffic flow increases continuously, as well as the emergence of new applications. Although cutting-edge hardware technology can be employed to achieve a fast implementation to handle this huge data streams, there will always be a limit on size of traffic supported by a given architecture. However, recent cloud-based big data technologies fortunately offer an ideal environment to handle this issue. Moreover, the ever-increasing high volume of traffic created on demand presents great challenges for flow management. As a solution, flow aggregation decreases the number of flows needed to be processed by the network. The previous works in the literature prove that most of aggregation strategies designed for smart grids aim at optimizing system operation performance. They consider a common identifier to aggregate traffic on each device, having its independent static aggregation policy. In this paper, we propose a dynamic approach to aggregate flows based on traffic characteristics and device preferences. Our algorithm runs on a big data platform to provide an end-to-end network visibility of flows, which performs high-speed and high-volume computations to identify the clusters of similar flows and aggregate massive number of mice flows into a few meta-flows. Compared with existing solutions, our approach dynamically aggregates large number of such small flows into fewer flows, based on traffic characteristics and access node preferences. Using this approach, we alleviate the problem of processing a large amount of micro flows, and also significantly improve the accuracy of meeting the access node QoS demands. We conducted experiments, using a dataset of up to 100,000 flows, and studied the performance of our algorithm analytically. The experimental results are presented to show the promising effectiveness and scalability of our proposed approach.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.1-9
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• 2008

As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.