• Title/Summary/Keyword: 이미지정보

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A Strategy To Reduce Network Traffic Using Two-layered Cache Servers for Continuous Media Data on the Wide Area Network (이중 캐쉬 서버를 사용한 실시간 데이터의 좡대역 네트워크 대역폭 감소 정책)

  • Park, Yong-Woon;Beak, Kun-Hyo;Chung, Ki-Dong
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.10
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    • pp.3262-3271
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    • 2000
  • Continuous media objects, due to large volume and real-time consiraints in their delivery,are likely to consume much network andwidth Generally, proxy servers are used to hold the fiequently requested objects so as to reduce the network traffic to the central server but most of them are designed for text and image dae that they do not go well with continuous media data. So, in this paper, we propose a two-layered network cache management policy for continuous media object delivery on the wide area networks. With the proposed cache management scheme,in cach LAN, there exists one LAN cache and each LAN is further devided into a group of sub-LANs, each of which also has its own sub-LAN eache. Further, each object is also partitioned into two parts the front-end and rear-end partition. they can be loaded in the same cache or separately in different network caches according to their access frequencics. By doing so, cache replacement overhead could be educed as compared to the case of the full size daa allocation and replacement , this eventually reduces the backbone network traffic to the origin server.

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Balanced Scorecard using System Dynamics for Evaluating IT Investment (IT 투자 평가를 위한 시스템 다이나믹스를 활용한 밸런스스코어카드)

  • Baek, Sung-Won;Ju, Jung-Eun;Koo, Sang-Hoe
    • Journal of Intelligence and Information Systems
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    • v.14 no.1
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    • pp.19-34
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    • 2008
  • IT investment is usually very costly and takes a long time to get the results out of investment. However, most of currently available evaluation methods for IT investment are based upon short-term effects, hence their results are not fully trustworthy. In addition, those methods commonly consider only financial aspects such as ROI. For more reliable evaluation, it is necessary to consider non-financial factors such as system utilization, customer satisfaction, public relations, and so on, as well as financial factors. In this research, we propose an evaluation method that can evaluate both financial and non-financial aspects on a long-term base. For this purpose, we employed the research results developed in System dynamics and Balanced scorecard. System dynamics is useful in analyzing long term behavior of a given system, and Balanced scorecard is useful for evaluating both financial and non-financial aspects. We demonstrated the usefulness of our method by applying it to the evaluation of RFID (Radio Frequency Identification) investment in a distribution and retail industry. From this application, we found that RFID investment may not be rewarding in the short term, but is sure to be returning the income relative to its investment in the long run.

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Damage Detection and Classification System for Sewer Inspection using Convolutional Neural Networks based on Deep Learning (CNN을 이용한 딥러닝 기반 하수관 손상 탐지 분류 시스템)

  • Hassan, Syed Ibrahim;Dang, Lien-Minh;Im, Su-hyeon;Min, Kyung-bok;Nam, Jun-young;Moon, Hyeon-joon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.3
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    • pp.451-457
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    • 2018
  • We propose an automatic detection and classification system of sewer damage database based on artificial intelligence and deep learning. In order to optimize the performance, we implemented a robust system against various environmental variations such as illumination and shadow changes. In our proposed system, a crack detection and damage classification method using a deep learning based Convolutional Neural Network (CNN) is implemented. For optimal results, 9,941 CCTV images with $256{\times}256$ pixel resolution were used for machine learning on the damaged area based on the CNN model. As a result, the recognition rate of 98.76% was obtained. Total of 646 images of $720{\times}480$ pixel resolution were extracted from various sewage DB for performance evaluation. Proposed system presents the optimal recognition rate for the automatic detection and classification of damage in the sewer DB constructed in various environments.

2.5D Mapping Module and 3D Cloth Simulation System (2.5D Mapping 모듈과 3D 의복 시뮬레이션 시스템)

  • Kim Ju-Ri;Kim Young-Un;Joung Suck-Tae;Jung Sung-Tae
    • The KIPS Transactions:PartA
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    • v.13A no.4 s.101
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    • pp.371-380
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    • 2006
  • This paper utilizing model picture of finished clothes in fashion design field various material (textile fabrics) doing Draping directly can invent new design, and do not produce direction sample or poetic theme width and confirm clothes work to simulation. Also, construct database about model and material image and embodied system that can confirm Mapping result by real time. And propose clothes simulation system to dress to 3D human body model of imagination because using several cloth pieces first by process to do so that can do simulation dressing abstracted poetic theme width to 3D model here. Proposed system creates 3D model who put clothes by physical simulation that do fetters to mass-spring model after read 3D human body model file and 2D foundation pattern file. System of this treatise examines collision between triangle that compose human body model for realistic simulation and triangle that compose clothes and achieved reaction processing. Because number of triangle to compose human body is very much, this collision examination and reaction processing need much times. To solve this problem, treatise that see could create realistic picture by method to diminish collision public prosecutor and reaction processing number, and could dress clothes to imagination human body model within water plant taking advantage of Octree space sharing techniques.

Scheduling System using CSP leer Effective Assignment of Repair Warrant Job (효율적인 A/S작업 배정을 위한 CSP기반의 스케줄링 시스템)

  • 심명수;조근식
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2000.11a
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    • pp.247-256
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    • 2000
  • 오늘날의 기업은 상품을 판매하는 것 뿐만 아니라 기업의 신용과 이미지를 위해 그 상품에 대한 사후처리(After Service) 업무에 많은 투자를 하고 있다. 이러한 양질의 사후서비스를 고객에게 공급하기 위해서는 많은 인력을 합리적으로 관리해야 하고 요청되는 고장수리 서비스 업무를 빠르게 해결하기 위해서는 업무를 인력들에게 합리적으로 배정을 하고 회사의 비용을 최소화하면서 정해진 시간에 요청된 작업을 처리하기 위해서는 인력들에게 작업을 배정하고 스케줄링하는 문제가 발생된다. 본 논문에서는 이러한 문제를 해결하기 위해 화학계기의 A/S 작업을 인력에게 합리적으로 배정하는 스케줄링 시스템에 관한 연구이다. 먼저 스케줄링 모델을 HP 사의 화학분석 및 시스템을 판매, 유지보수 해 주는 "영진과학(주)"회사의 작업 스케줄을 분석하여 필요한 도메인과 고객서비스전략과 인력관리전략에서 제약조건을 추출하였고 여기에 스케줄링 문제를 해결하기 위한 방법으로 제약만족문제(CSP) 해결기법인 도메인 여과기법을 적용하였다. 도메인 여과기법은 제약조건에 의해 변수가 갖는 도메인의 불필요한 부분을 여과하는 것으로 제약조건과 관련되어 있는 변수의 도메인이 축소되는 것이다. 또한, 스케줄링을 하는데에 있어서 비용적인 측면에서의 스케줄링방법과 고객 만족도에서의 스케줄링 방법을 비교하여 가장 이상적인 해를 찾는데 트래이드오프(Trade-off)를 이용하여 최적의 해를 구했으며 실험을 통해 인력에게 더욱 효율적으로 작업들을 배정 할 수 있었고 또한, 정해진 시간에 많은 작업을 처리 할 수 있었으며 작업을 처리하는데 있어 소요되는 비용을 감소하는 결과를 얻을 수 있었다. 검증하였다.를, 지지도(support), 신뢰도(confidence), 리프트(lift), 컨빅션(conviction)등의 관계를 통해 다양한 방법으로 모색해본다. 이 연구에서 제안하는 이러한 개념계층상의 흥미로운 부분의 탐색은, 전자 상거래에서의 CRM(Customer Relationship Management)나 틈새시장(niche market) 마케팅 등에 적용가능하리라 여겨진다.선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity

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Automated Construction Progress Management Using Computer Vision-based CNN Model and BIM (이미지 기반 기계 학습과 BIM을 활용한 자동화된 시공 진도 관리 - 합성곱 신경망 모델(CNN)과 실내측위기술, 4D BIM을 기반으로 -)

  • Rho, Juhee;Park, Moonseo;Lee, Hyun-Soo
    • Korean Journal of Construction Engineering and Management
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    • v.21 no.5
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    • pp.11-19
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    • 2020
  • A daily progress monitoring and further schedule management of a construction project have a significant impact on the construction manager's decision making in schedule change and controlling field operation. However, a current site monitoring method highly relies on the manually recorded daily-log book by the person in charge of the work. For this reason, it is difficult to take a detached view and sometimes human error such as omission of contents may occur. In order to resolve these problems, previous researches have developed automated site monitoring method with the object recognition-based visualization or BIM data creation. Despite of the research results along with the related technology development, there are limitations in application targeting the practical construction projects due to the constraints in the experimental methods that assume the fixed equipment at a specific location. To overcome these limitations, some smart devices carried by the field workers can be employed as a medium for data creation. Specifically, the extracted information from the site picture by object recognition technology of CNN model, and positional information by GIPS are applied to update 4D BIM data. A standard CNN model is developed and BIM data modification experiments are conducted with the collected data to validate the research suggestion. Based on the experimental results, it is confirmed that the methods and performance are applicable to the construction site management and further it is expected to contribute speedy and precise data creation with the application of automated progress monitoring methods.

Design of Synchronous 256-bit OTP Memory (동기식 256-bit OTP 메모리 설계)

  • Li, Long-Zhen;Kim, Tae-Hoon;Shim, Oe-Yong;Park, Mu-Hun;Ha, Pan-Bong;Kim, Young-Hee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.7
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    • pp.1227-1234
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    • 2008
  • In this paper is designed a 256-bit synchronous OTP(one-time programmable) memory required in application fields such as automobile appliance power ICs, display ICs, and CMOS image sensors. A 256-bit synchronous memory cell consists of NMOS capacitor as antifuse and access transistor without a high-voltage blocking transistor. A gate bias voltage circuit for the additional blocking transistor is removed since logic supply voltage VDD(=1.5V) and external program voltage VPPE(=5.5V) are used instead of conventional three supply voltages. And loading current of cell to be programmed increases according to RON(on resistance) of the antifuse and process variation in case of the voltage driving without current constraint in programming. Therefore, there is a problem that program voltage can be increased relatively due to resistive voltage drop on supply voltage VPP. And so loading current can be made to flow constantly by using the current driving method instead of the voltage driving counterpart in programming. Therefore, program voltage VPP can be lowered from 5.9V to 5.5V when measurement is done on the manufactured wafer. And the sens amplifier circuit is simplified by using the sens amplifier of clocked inverter type instead of the conventional current sent amplifier. The synchronous OTP of 256 bits is designed with Magnachip $0.13{\mu}m$ CMOS process. The layout area if $298.4{\times}314{\mu}m2$.

A Design of Digital CMOS X-ray Image Sensor with $32{\times}32$ Pixel Array Using Photon Counting Type (포톤 계수 방식의 $32{\times}32$ 픽셀 어레이를 갖는 디지털 CMOS X-ray 이미지 센서 설계)

  • Sung, Kwan-Young;Kim, Tae-Ho;Hwang, Yoon-Geum;Jeon, Sung-Chae;Jin, Seung-Oh;Huh, Young;Ha, Pan-Bong;Park, Mu-Hun;Kim, Young-Hee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.7
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    • pp.1235-1242
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    • 2008
  • In this paper, x-ray image sensor of photon counting type having a $32{\times}32$ pixel array is designed with $0.18{\mu}m$ triple-well CMOS process. Each pixel of the designed image sensor has an area of loot $100{\times}100\;{\mu}m2$ and is composed of about 400 transistors. It has an open pad of an area of $50{\times}50{\mu}m2$ of CSA(charge Sensitive Amplifier) with x-ray detector through a bump bonding. To reduce layout size, self-biased folded cascode CMOS OP amp is used instead of folded cascode OP amp with voltage bias circuit at each single-pixel CSA, and 15-bit LFSR(Linear Feedback Shift Register) counter clock generator is proposed to remove short pulse which occurs from the clock before and after it enters the counting mode. And it is designed that sensor data can be read out of the sensor column by column using a column address decoder to reduce the maximum current of the CMOS x-ray image sensor in the readout mode.

Implementation of Efficient Container Number Recognition System at Automatic Transfer Crane in Container Terminal Yard (항만 야드 자동화크레인(ATC)에서 효율적인 컨테이너번호 인식시스템 개발)

  • Hong, Dong-Hee
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.9
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    • pp.57-65
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    • 2010
  • This paper describes the method of efficient container number recognition in colored container image with number plate at ATC(Automatic Transfer Crane) in container terminal yard. At the Sinseondae terminal gate in Busan, the container number recognition system is installed by "intelligent port-logistics system technology development", that is government research and development project. It is the method that it sets up the tunnel structure inside camera on the gate and it recognizes the container number in order to recognize the export container cargo automatically. However, as the automation equipment is introduced to the container terminal and the unmanned of a task is gradually accomplished, the container number recognition system for the confirmation of the object of work is required at ATC in container terminal yard. Therefore, the container number recognition system fitted for it is necessary for ATC in container terminal yard in which there are many intrusive of the character recognition through image including a sunlight, rain, snow, shadow, and etc. unlike the gate. In this paper, hardware components of the camera, illumination, and sensor lamp were altered and software elements of an algorithm were changed. that is, the difference of the brightness of the surrounding environment, and etc. were regulated for recognize a container number. Through this, a shadow problem, and etc. that it is thickly below hung with the sunlight or the cargo equipment were solved and the recognition time was shortened and the recognition rate was raised.

Hybrid All-Reduce Strategy with Layer Overlapping for Reducing Communication Overhead in Distributed Deep Learning (분산 딥러닝에서 통신 오버헤드를 줄이기 위해 레이어를 오버래핑하는 하이브리드 올-리듀스 기법)

  • Kim, Daehyun;Yeo, Sangho;Oh, Sangyoon
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.7
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    • pp.191-198
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    • 2021
  • Since the size of training dataset become large and the model is getting deeper to achieve high accuracy in deep learning, the deep neural network training requires a lot of computation and it takes too much time with a single node. Therefore, distributed deep learning is proposed to reduce the training time by distributing computation across multiple nodes. In this study, we propose hybrid allreduce strategy that considers the characteristics of each layer and communication and computational overlapping technique for synchronization of distributed deep learning. Since the convolution layer has fewer parameters than the fully-connected layer as well as it is located at the upper, only short overlapping time is allowed. Thus, butterfly allreduce is used to synchronize the convolution layer. On the other hand, fully-connecter layer is synchronized using ring all-reduce. The empirical experiment results on PyTorch with our proposed scheme shows that the proposed method reduced the training time by up to 33% compared to the baseline PyTorch.