• Journal of the Korean housing association
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• v.14 no.2
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• pp.63-75
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• 2003

The planning of access area, so called "core" plays an important role of planning for multifamily housing, especially multistory housing. For all possibility of various planning and design, this area has been mostly planned and designed in uniformity. And only few attempts have so far been made in studying core, on the contrary to the unit plan or plotplan. It is keenly needed to develop various skills of planning and design in this sector. The purpose of this study is to find out the usable elements of planning and design, those are correspondent to normative targets. For this end, most possible core types are classified in to three categories: circulation types in the housing block, axis types to the entrance of housing units and number of accessed housing units. And then, sizable developments for norm of core have been effectuating in view of function, relationships both with housing unit and block. Based on this classification of types and listed norm, several European examples are analyzed and evaluated by merits and demerits of their respective core types. In addition to this analysis, some adequate planning conditions, positive vs. negative types of core, and detailed planning elements are prepared with regard to the norm of core. It is noteworthy that a variety of possible core planning cases are available by means of combination of lower categories in the classified core types. It is expected that this study will render service for some helpful planning and design guide in the practice

• Fire Science and Engineering
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• v.23 no.5
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• pp.9-16
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• 2009

Chemical products have had an favorable influence on our everyday life, and contributed very much to the development of human culture. According to the rapid change of industry and the development of scientific technique the using chemical products are increasing more and more. Chemical products can have any hazardous property such as flammability or explosiveness. There are occurring many accidents in the international trade due to the different classification and labelling of chemicals produced in various countries. The main purpose of this work is the development of global standard test methods for the chemicals, and the classification and labelling in building block approach by means of the basic technical data. Oxidizing solids, combustible solids, spontaneously combustible materials, water-prohibitive materials, flammable liquids, self-reactive materials and oxidizing liquids have been classification The first Experiment have tested Oxidizing solids of third five. The results have been classified according to the hazard material safety regulation and the UN regulation, and summarized in a data-base.

• Journal of Sensor Science and Technology
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• v.29 no.1
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• pp.19-26
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• 2020

Electrocardiogram (ECG) classification has become an essential task of modern day wearable devices, and can be used to detect cardiovascular diseases. State-of-the-art Artificial Intelligence (AI)-based ECG classifiers have been designed using various artificial neural networks (ANNs). Despite their high accuracy, ANNs require significant computational resources and power. Herein, three different ANNs have been compared: multilayer perceptron (MLP), convolutional neural network (CNN), and spiking neural network (SNN) only for the ECG classification. The ANN model has been developed in Python and Theano, trained on a central processing unit (CPU) platform, and deployed on a PYNQ-Z2 FPGA board to validate the model using a Jupyter notebook. Meanwhile, the hardware accelerator is designed with Overlay, which is a hardware library on PYNQ. For classification, the MIT-BIH dataset obtained from the Physionet library is used. The resulting ANN system can accurately classify four ECG types: normal, atrial premature contraction, left bundle branch block, and premature ventricular contraction. The performance of the ECG classifier models is evaluated based on accuracy and power. Among the three AI algorithms, the SNN requires the lowest power consumption of 0.226 W on-chip, followed by MLP (1.677 W), and CNN (2.266 W). However, the highest accuracy is achieved by the CNN (95%), followed by MLP (76%) and SNN (90%).

• Journal of Intelligence and Information Systems
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• v.12 no.1
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• pp.33-41
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• 2006

This paper presents a method that automatically recognizes products into model type, which it flows with the conveyor belt. The specific interlaced image are occurred by moving image when we use the NTSC based camera. It is impossible to process interlaced images, so a suitable post-processing is required. For the purpose of this processing, after it remove interlaced images using de-interlacing method, it leads rectangle region of object by thresholding. And then, after rectangle region is separated into several blocks through edge detection, we calculate pixel numbers per each block, re-classify using its average, and classify products into model type. Through experiments, we know that the proposed method represent high classification ratio.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.93-96
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• 2000

In this paper, we suggest a feature points selection method using block-based watershed segmentation and polygon approximation for preprocessing of MPEG-4 mesh generation. 2D natural image is segmented by 8$\times$8 or 4$\times$4 block classification method and watershed algorithm. As this result, pixels on the watershed lines represent scene's interior feature and this lines are shapes of closed contour. Continuous pixels on the watershed lines are selected out feature points using Polygon approximation and post processing.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.27-35
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• 2021

NAND flash memory-based SSD needs an internal software, Flash Translation Layer(FTL) to provide traditional block device interface to the host because of its physical constraints, such as erase-before-write and large erase block. However, because useful host-side information cannot be delivered to FTL through the narrow block device interface, SSDs suffer from a variety of problems such as increasing garbage collection overhead, large tail-latency, and unpredictable I/O latency. Otherwise, the new type of SSD, open-channel SSD exposes the internal structure of SSD to the host so that underlying NAND flash memory can be managed directly by the host-level FTL. Especially, I/O data classification by using host-side information can achieve the reduction of garbage collection overhead. In this paper, we propose a new scheme to reduce garbage collection overhead of open-channel SSD by separating the journal from other file data for the journaling filesystem. Because journal has different lifespan with other file data, the Write Amplification Factor (WAF) caused by garbage collection can be reduced. The proposed scheme is implemented by modifying the host-level FTL of Linux and evaluated with both Fio and Filebench. According to the experiment results, the proposed scheme improves I/O performance by 46%~50% while reducing the WAF of open-channel SSDs by more than 33% compared to the previous one.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.325-327
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• 2004

ECG limb lead II signal widely used to diagnosis heart diseases and it is essential to detect ECG events (onsets, offsets and peaks of the QRS complex P wave and T wave) and extract them from ECG signal for heart diseases diagnoses. However, it is very difficult to develop standardized feature extraction formulas since ECG signals are varying on patients and disease types. In this paper, simple feature extraction method from normal and abnormal types of ECG signals is proposed. As a signal features, heart rate, PR interval, QRS interval, QT interval, interval between S wave and baseline, and T wave types are extracted. To show the validity of proposed method, Right Bundle Branch Block (RBBB), Left Bundle Branch Block (LBBB), Sinus Bradycardia, and Sinus Tachycardia data from MIT-BIH arrhythmia database are used for feature extraction and the extraction results showed higher extraction capability compare to conventional formula based extraction method.

• Proceedings of the KSR Conference
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• 2005.05a
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• pp.550-555
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• 2005

In this research, safety requirements for guard rail, buffer stop, car stop scotch block, protection device, fire protection facilities, safety siding, escape facilities and inundation protection facilities are studied to establish a standard. First, various kinds of guard rails and their construction methods are investigated. Researches on the level difference of main track and guard rail, joint, length, and fastening force of guard rail are done. Second, the classification of buffer stop and car stop scotch block and its characteristics are examined, and the impact force, speed limit and capacity of buffer stop are summarized. Details of protection device, fire protection facilities, safety siding, escape facilities and inundation protection facilities are also investigated. From this fundamental research results, basic data on the safety facilities of railroad system are established.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.9B
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• pp.1292-1298
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• 2001

본 논문에서는 공간 영역에서의 블록 분류 (block classification)와 순방향 신경망 필터(feedforward neural network filter)를 이용한 블록 기반 부호화에서의 적응적 블록화 현상 제거 알고리듬을 제안하였다. 제안한 방법에서는 각 블록 경계를 인접 블록간의 통계적 특성을 이용하여 평탄 영역과 에지 영역으로 분류한 후, 각 영역에 대하여 블록화 현상이 발생하였다고 분류된 클래스에 대하여 적응적인 블록간 필터링을 수행한다. 즉, 평탄 영역으로 분류된 영역 중 블록화 현상이 발생한 영역은 오류 역전파 학습 알고리듬 (error backpropagation learning algorithm)에 의하여 학습된 2계층 (2-layer) 신경망 필터를 이용하여 블록화 현상을 제거하고, 복잡한 영역으로 분류된 영역 중 블록화 현상이 발생한 영역은 에지 성분을 보존하기 위하여 선형 내삽을 이용하여 블록간 인접 화소의 밝기 값만을 조정함으로써 블록화 현상을 제거한다. 모의 실험 결과를 통하여 제안한 방법이 객관적 화질 및 주관적 화질 측면에서 기존의 방법보다 그 성능이 우수함을 확인하였다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.560-567
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• 1998

This paper concerned about a imputed color printed material image in camera to decrease noise and distortion by processing median filtering with input image to identical condition. Also this paper proposed the way of compares a normal printed material with an abnormal printed material color tone with trained a learning of the error back-propagation to block classification by extracting five place from identical block(3${\times}$3) of color printed material R, G, B value. As a representative algorithm of multi-layer perceptron the error Back-propagation technique used to solve complex problems. However, the Error Back-propagation is algorithm which basically used a gradient descent method which can be converged to local minimum and the Back Propagation train include problems, and that may converge in a local minimum rather than get a global minimum. The network structure appropriate for a given problem. In this paper, a good result is obtained by improve initial condition and adjust th number of hidden layer to solve the problem of real time process, learning and train.