• Transactions on Semiconductor Engineering
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• v.1 no.1
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• pp.1-8
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• 2023

This paper presents the design and implementation of Crystals-Kyber, a next-generation postquantum cryptography, as a hardware accelerator on an FPGA using High-Level Synthesis (HLS). We optimized the Crystals-Kyber algorithm using various directives provided by Vitis HLS, configured the AXI interface, and designed a hardware accelerator that can be implemented on an FPGA. Then, we used Vivado tool to design the IP block and implement it on the ZYNQ ZCU106 FPGA. Finally, the video was recorded and H.264 compressed with Python code in the PYNQ framework, and the video encryption and decryption were accelerated using Crystals-Kyber hardware accelerator implemented on the FPGA.

• Journal of Biomedical Engineering Research
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• v.21 no.5
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• pp.441-448
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• 2000

방출단층영상 재구성을 위한 최대우도 기대값최대화(maximum likelihood expectation maximization, MLEM) 방법은 영상 획득과정을 통계학적으로 모델링하여 영상을 재구성한다. MLEM은 일반적으로 사용하여 여과후역투사(filtered backprojection)방법에 비해 많은 장점을 가지고 있으나 반복횟수 증가에 따른 발산과 재구성 시간이 오래 걸리는 단점을 가지고 있다. 이 논문에서는 이러한 단점을 보완하기 위해 계산시간을 현저히 단축시킨 배열된부분집합 기대값최대화(ordered subsets expectation maximization. OSEM)에 Gibbs 선행치인 membrance (MM) 또는 thin plate(TP)을 첨가한 OSEM-MAP (maximum a posteriori)을 구현함으로써 알고리즘의 안정성 및 재구성된 영상의 질을 향상시키고자 g나다. 실험에서 알고리즘의 수렴시간을 가속화하기 위해 투사 데이터를 16개의 부분집합으로 분할하여 반복연산을 수행하였으며, 알고리즘의 성능을 비교하기 위해 소프트웨어 모형(원숭이 뇌 자가방사선, 수학적심장흉부)을 사용한 영상재구성 결과를 제곱오차로 비교하였다. 또한 알고리즘의 사용 가능성을 평가하기 위해 물리모형을 사용하여 PET 기기로부터 획득한 실제 투사 데이터를 사용하였다.

• Journal of the Korean earth science society
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• v.42 no.3
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• pp.247-263
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• 2021

Climate change has been accelerating in coastal waters recently; therefore, the importance of coastal environmental monitoring is also increasing. Chlorophyll-a concentration, an important marine variable, in the surface layer of the global ocean has been retrieved for decades through various ocean color satellites and utilized in various research fields. However, the commonly used chlorophyll-a concentration algorithm is only suitable for application in clear water and cannot be applied to turbid waters because significant errors are caused by differences in their distinct components and optical properties. In addition, designing a standard algorithm for coastal waters is difficult because of differences in various optical characteristics depending on the coastal area. To overcome this problem, various algorithms have been developed and used considering the components and the variations in the optical properties of coastal waters with high turbidity. Chlorophyll-a concentration retrieval algorithms can be categorized into empirical algorithms, semi-analytic algorithms, and machine learning algorithms. These algorithms mainly use the blue-green band ratio based on the reflective spectrum of sea water as the basic form. In constrast, algorithms developed for turbid water utilizes the green-red band ratio, the red-near-infrared band ratio, and the inherent optical properties to compensate for the effect of dissolved organisms and suspended sediments in coastal area. Reliable retrieval of satellite chlorophyll-a concentration from turbid waters is essential for monitoring the coastal environment and understanding changes in the marine ecosystem. Therefore, this study summarizes the pre-existing algorithms that have been utilized for monitoring turbid Case 2 water and presents the problems associated with the mornitoring and study of seas around the Korean Peninsula. We also summarize the prospective for future ocean color satellites, which can yield more accurate and diverse results regarding the ecological environment with the development of multi-spectral and hyperspectral sensors.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.185-195
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• 2018

As machines have been automated in the field of industries in recent years, it is a paramount importance to manage and maintain the automation machines. When a fault occurs in sensors attached to the machine, the machine may malfunction and further, a huge damage will be caused in the process line. To prevent the situation, the fault of sensors should be monitored, diagnosed and classified in a proper way. In the paper, we propose a sensor fault detection scheme based on SVM and CNN to detect and classify typical sensor errors such as erratic, drift, hard-over, spike, and stuck faults. Time-domain statistical features are utilized for the learning and testing in the proposed scheme, and the genetic algorithm is utilized to select the subset of optimal features. To classify multiple sensor faults, a multi-layer SVM is utilized, and ensemble technique is used for CNN. As a result, the SVM that utilizes a subset of features selected by the genetic algorithm provides better performance than the SVM that utilizes all the features. However, the performance of CNN is superior to that of the SVM.

• Investigative Magnetic Resonance Imaging
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• v.6 no.2
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• pp.137-146
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• 2002

Purpose : This paper introduces an improved classification approach which adopts a deterministic relaxation method and an agglomerative clustering technique for the classification of MRI using neural network. The proposed approach can solve the problems of convergency to local optima and computational burden caused by a large number of input patterns when a neural network is used for image classification. Materials and methods : Application of Hopfield neural network has been solving various optimization problems. However, major problem of mapping an image classification problem into a neural network is that network is opt to converge to local optima and its convergency toward the global solution with a standard stochastic relaxation spends much time. Therefore, to avoid local solutions and to achieve fast convergency toward a global optimization, we adopt MFA to a Hopfield network during the classification. MFA replaces the stochastic nature of simulated annealing method with a set of deterministic update rules that act on the average value of the variable. By minimizing averages, it is possible to converge to an equilibrium state considerably faster than standard simulated annealing method. Moreover, the proposed agglomerative clustering algorithm which determines the underlying clusters of the image provides initial input values of Hopfield neural network. Results : The proposed approach which uses agglomerative clustering and deterministic relaxation approach resolves the problem of local optimization and achieves fast convergency toward a global optimization when a neural network is used for MRI classification. Conclusion : In this paper, we introduce a new paradigm to classify MRI using clustering analysis and deterministic relaxation for neural network to improve the classification results.

• Spatial Information Research
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• v.2 no.1
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• pp.3-14
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• 1994

The external diseconomy has been accelerated by the megaspatial structure of metropolis such as Seoul Capital Region(below SCR), Korea in which the more than 10 million populations inhabit. The main course for It could be elaborated by the overconcentration of the urban and regional function of various kinds. The study is performed to analyze quantitatively the status quo of the region as described above and proceed into forecasting the future population trend, the land use at location for the increment of regional population and to set the location of new towns in Seoul Capital Region System projected by the methods in computer algorithm of descriptive models such as the simple and multiple regress ion analysis models, the gravity model and the facility location on a plane model analysis. The goal and object ive of the metropolitan planning are to decentralize the regional growth management to the optimum degree, which will not hinder the economic growth of the region, but the result of the study is that we can not discourage the functional concentration of Seoul Capital Region and, we have to provide the region with the appropriate new towns.

• Journal of the Korea Computer Graphics Society
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• v.6 no.1
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• pp.29-36
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• 2000

In this work, we propose ZF-buffer algorithm in order to accelerate the intersection test of ray-tracing algorithm. ZF-buffer is used in the preprocessing of ray-tracing and records the pointer that points to a parent face of a depth value(z value) of an object determined in Z-buffer. As a result, the face which intersects with the first ray can be determined easily by using the pointer stored in F-buffer. Though ZF-buffer and vista-buffer resemble each other, the difference between the two methods is that what ZF-buffer records is not bounding volume but the pointer of a displayable face. We applied the ZF-buffer algorithm for the first ray to Utah teapot which consists of 9216 polygons. By comparing the elapse time of our method with vista-buffer algorithm, we can acquire improvement in speed that it is 3 times faster than vista-buffer algorithm. We expanded our algorithm to the second ray.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.451-457
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• 2014

Recently, the land degradation and pasture erosion in Tuv, located around Ulaanbaatar of Mongolia, have been increasing sharply due to escalating developments of mining sectors, well as the density of populations. Because of that, we have chosen the urban and mining area of Tuv for our study target. During the study, the temporal changes of land cover in Tuv, Mongolia were observed by the Landsat TM/+ETM satellite images from 2001 to 2009 that provided the fundamental dataset to apply NDVI and K-Mean algorithm of Unsupervised Classification and Maximum likelihood classification(MLC) of Supervised Classification in order to conclude in land cover change analyzation. The result of our study implies that the growth of mining area, the climate change, and the density of population led the land degradation to desertification.

• Journal of Korea Multimedia Society
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• v.14 no.8
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• pp.981-991
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• 2011

MIP(Maximum Intensity Projection) is a volume rendering technique which is essential for the medical imaging system. MIP rendering based on the ray casting method produces high quality images but takes a long time. Our aim is improvement of the rendering speed using GPGPU(General-purpose computing on Graphic Process Unit) technique. In this paper, we present the ray casting algorithm based on CUDA(an acronym for Compute Unified Device Architecture) which is a programming language for GPGPU and we suggest new acceleration methods for CUDA. In detail, we propose the block based space leaping which skips unnecessary regions of volume data for CUDA, the bisection method which is a fast method to find a block edge, and the initial value estimation method which improves the probability of space leaping. Due to the proposed methods, we noticeably improve the rendering speed without image quality degradation.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.28-34
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• 2018

This paper is composed of a passenger management system using a temperature sensing module, a PIR sensor module for detecting movement inside a room, and a smart breath sensing module for determining a sleeping state. An embedded sensor module and a communication system integrated the sensing part and the algorithm driving part. As the aging society is accelerating and becoming more upgraded, the social cost of Silver Care increases, and in order to protect privacy, it is necessary to reduce costs by developing efficient smart silver care devices. The proposed non - image human body detection IOT sensor system is implemented by hardware and software and has superior performance compared with conventional image monitoring method.