• ETRI Journal
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• v.38 no.1
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• pp.100-111
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• 2016

This paper presents a low-complexity channel-adaptive reconfigurable $4{\times}4$ QR-decomposition and M-algorithm-based maximum likelihood detection (QRM-MLD) multiple-input and multiple-output (MIMO) detector. Two novel design approaches for low-power QRM-MLD hardware are proposed in this work. First, an approximate survivor metric (ASM) generation technique is presented to achieve considerable computational complexity reduction with minor BER degradation. A reconfigurable QRM-MLD MIMO detector (where the M-value represents the number of survival branches in a stage) for dynamically adapting to time-varying channels is also proposed in this work. The proposed reconfigurable QRM-MLD MIMO detector is implemented using a Samsung 65 nm CMOS process. The experimental results show that our ASM-based QRM-MLD MIMO detector shows a maximum throughput of 288 Mbps with a normalized power efficiency of 10.18 Mbps/mW in the case of $4{\times}4$ MIMO with 64-QAM. Under time-varying channel conditions, the proposed reconfigurable MIMO detector also achieves average power savings of up to 35% while maintaining a required BER performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.395-400
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• 2011

In this paper, we propose an study of the facial emotion recognition considering the dynamical variation of emotional state in facial image sequences. The proposed system consists of two main step: facial image based emotional feature extraction and emotional state classification/recognition. At first, we propose a method for extracting and analyzing the emotional feature region using a combination of Active Shape Model (ASM) and Facial Action Units (FAUs). And then, it is proposed that emotional state classification and recognition method based on Hidden Markov Model (HMM) type of dynamic Bayesian network. Also, we adopt a Harmony Search (HS) algorithm based heuristic optimization procedure in a parameter learning of HMM in order to classify the emotional state more accurately. By using all these methods, we construct the emotion recognition system based on variations of the dynamic facial image sequence and make an attempt at improvement of the recognition performance.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.1
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• pp.141-150
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• 2013

This study proposes technology using Active Shape Model to track the object separating it by depth-sensors. Unlike the common visual camera, the depth-sensor is not affected by the intensity of illumination, and therefore a more robust object can be extracted. The proposed algorithm removes the horizontal component from the information of the initial depth map and separates the object using the vertical component. In addition, it is also a more efficient morphology, and labeling to perform image correction and object extraction. By applying Active Shape Model to the information of an extracted object, it can track the object more robustly. Active Shape Model has a robust feature-to-object occlusion phenomenon. In comparison to visual camera-based object tracking algorithms, the proposed technology, using the existing depth of the sensor, is more efficient and robust at object tracking. Experimental results, show that the proposed ASM-based algorithm using depth sensor can robustly track objects in real-time.

• Membrane and Water Treatment
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• v.9 no.3
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• pp.155-162
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• 2018

Process modeling with activated sludge models (ASMs) is useful for the design and operational improvement of biological nutrient removal (BNR) processes. Effective utilization of ASMs requires the influent fraction analysis (IFA) of the wastewater treatment plant (WWTP). However, this is difficult due to the time and cost involved in the design and operation steps, thereby declining the simulation reliability. Harmony Search (HS) algorithm was utilized herein to determine the relationships between composite variables and state variables of the model IWA ASM1. Influent fraction analysis was used in estimating fractions of the state variables of the WWTP influent and its application to 9 wastewater treatment processes in South Korea. The results of influent $S_s$ and $Xs+X_{BH}$, which are the most sensitive variables for design of activated sludge process, are estimated within the error ranges of 8.9-14.2% and 3.8-6.4%, respectively. Utilizing the chemical oxygen demand (COD) fraction analysis for influent wastewater, it was possible to predict the concentrations of treated organic matter and nitrogen in 9 full scale BNR processes with high accuracy. In addition, the results of daily influent fraction analysis (D-IFA) method were superior to those of the constant influent fraction analysis (C-IFA) method.

• Journal of Korea Multimedia Society
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• v.14 no.11
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• pp.1373-1382
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• 2011

In this study, we propose an automated smile analysis system for self smile training. The proposed system detects the face area from the input image with the AdaBoost algorithm, followed by identifying facial features based on the face shape model generated by using an ASM(active shpae model). Once facial features are identified, the lip line and teeth area necessary for smile analysis are detected. It is necessary to judge the relationship between the lip line and teeth for smiling degree analysis, and to this end, the second differentiation of the teeth image is carried out, and then individual the teeth areas are identified by means of histogram projection on the vertical axis and horizontal axis. An analysis of the lip line and individual the teeth areas allows for an automated analysis of smiling degree of users, enabling users to check their smiling degree on a real time basis. The developed system in this study exhibited an error of 8.6% or below, compared to previous smile analysis results released by dental clinics for smile training, and it is expected to be used directly by users for smile training.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2283-2291
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• 1999

Most of collaborative applications use the Server-Client paradigm where all requests of clients will be delivered first to server and that server distributes again the requests to the rest of clients. This server-oriented operation and data transmission mechanism always presents end-to-end communications between the server and clients that can notably decrease the overall performance of applications. In this paper, we propose a new design approach to inhibit the inefficiency of applications using active networking concepts. We propose the ASM service that offers an application-specific in-network multicast functions, the AMTC service and its tree algorithm that builds anon-core based shared tree for multicast. These proposed services locate in active nodes performing its services as part of the overall system to improve the performance of collaborative applications.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.5
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• pp.1158-1174
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• 1988

A numerical technique is developed for the solution of fully developed turbulent recirculating flow in the passage of variable area using the non-orthogonal coordinate transformation. In the numerical analysis, primitive pressure-velocity finite difference equations were solved by SIMPLER algorithm with 2-equation turbulence model and algebraic stress model (ASM). QUICK scheme on the differencing of convective terms which is free from the inaccuracies of numerical diffusion has been applied to the variable grids and the results compared with those from HYBRID scheme. In order to test the effect of streamline curvatures on turbulent diffusion Lee and Choi streamline curvature correction model which has been obtained by modifying the Leschziner and Rodi's model is testes. The ASM was also employed and the results are compared to those from another turbulence model. The results show that difference of convective differencing schemes and turbulence models give significant differences in the prediction of velocity fields in the expansion region and outlet region of the combustor, however show little differences in the parallel flow region.

• Journal of Biomedical Engineering Research
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• v.25 no.3
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• pp.189-194
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• 2004

Pixel values of contrast enhanced computed tomography (CE-CT) images are randomly changed. Also, the middle liver part has a problem to segregate the liver structure because of similar gray-level values of a pancreas in the abdomen. In this paper, an automatic liver segmentation method using a partial histogram threshold (PHT) algorithm is proposed for overcoming randomness of CE-CT images and removing the pancreas. After histogram transformation, adaptive multi-modal threshold is used to find the range of gray-level values of the liver structure. Also, the PHT algorithm is performed for removing the pancreas. Then, morphological filtering is processed for removing of unnecessary objects and smoothing of the boundary. Four CE-CT slices of eight patients were selected to evaluate the proposed method. As the average of normalized average area of the automatic segmented method II (ASM II) using the PHT and manual segmented method (MSM) are 0.1671 and 0.1711, these two method shows very small differences. Also, the average area error rate between the ASM II and MSM is 6.8339 ％. From the results of experiments, the proposed method has similar performance as the MSM by medical Doctor.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.105-108
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• 1997

In this paper, we developed a portable electrical ventilator that could be controlled by the microcontroller. Control algorithm of motor drive t programmed with ASM96 assembly language software. We evaluated the system by measuring the parameters such as motor speed, feedback gain and overall specification.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.854-857
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• 2022

본 논문에서는 기존 이미지를 통해 위상 홀로그램을 생성하는 네트워크를 학습 및 최적화하여, 기존에 사용하는 알고리즘 방식인 GS 알고리즘(Gerchberg-Saxton algorithm)을 대체하는 것을 목표로 한다. GS는 반복 최적화 기법으로 한 장의 이미지에서 위상 홀로그램을 생성하는데 많은 시간이 걸리지만, 심층 학습 기반으로 학습된 모델을 통해 위상 홀로그램을 생성할 경우, 반복 최적화 과정 없이 짧은 시간 안에 위상 홀로그램을 생성할 수 있다. GS와 심층 학습 기반으로 각각 생성한 위상 홀로그램을 ASM(Angular Spectrum Method)을 통해 수치적으로 재복원하여 PSNR로 원본 이미지와 비교한 결과, 심층 학습 기반으로 생성한 위상 홀로그램에서 더 좋은 화질의 이미지를 짧은 시간 안에 얻을 수 있었다.