• Title/Summary/Keyword: automatic identification

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GENESIS: An Automatic Signature-generating Method for Detecting Internet Disk P2P Application Traffic (GENESIS: Internet Disk P2P 트래픽 탐지를 위한 시그너춰 자동 생성 방안)

  • Lee, Byung-Joon;Yoon, Seung-Hyun;Lee, Young-Seok
    • Journal of KIISE:Information Networking
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    • v.34 no.4
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    • pp.246-255
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    • 2007
  • Due to the bandwidth-consuming characteristics of the heavy-hitter P2P applications, it has become critical to have the capability of pinpointing and mitigating P2P traffic. Traditional port-based classification scheme is no more adequate for this purpose because of newer P2P applications, which incorporating port-hopping techniques or disguising themselves as HTTP-based Internet disk services. Alternatively, packet filtering scheme based on payload signatures suggests more practical and accurate solution for this problem. Moreover, it can be easily deployed on existing IDSes. However, it is significantly difficult to maintain up-to-date signatures of P2P applications. Hence, the automatic signature generation method is essential and will be useful for successful signature-based traffic identification. In this paper, we suggest an automatic signature generation method for Internet disk P2P applications and provide an experimental results on CNU campus network.

A Study on the System Development for Automatic Webtoon Download and Feature Registration (웹툰 저작물 자동 수집 및 특징점 등록 시스템 개발에 관한 연구)

  • Yoon, Hee-Don;Kim, Tae-Hyun;Kang, Ho-Gab;Cho, Seong-Hwan
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.17 no.2
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    • pp.25-31
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    • 2017
  • This paper aims to develope the technology for monitoring and identifying webtoon works that are being illegally distributed through the web-hard, torrent and overseas websites. The technology is to effectively prevent the illegal distribution and protect the copyrights of the webtoon works, leading to create a healthy market. This paper deals with the technology for (a) automatic collection of webtoon works from the webtoon service sites, (b) extraction of the features from the images of the collected webtoon works, and (c) registers them in the feature database. For these purposes, the required system performance and features were analyzed and the structures of webtoon service sites were examined, through which the system for automatic registration of webtoon works and features was developed. The system can work for the early stage blockage of illegal distributions of webtoon works which occur during the period from webtoon posting to feature registration.

The Hangul 4 State Bar Code System for the Automatic processing of Mail Items (우편물 자동처리를 위한 한글 4 State 바코드 시스템)

  • Park, Moon-Sung;Song, Jae-Gwan;Woo, Dong-Chin
    • The Transactions of the Korea Information Processing Society
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    • v.7 no.1
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    • pp.146-155
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    • 2000
  • This paper describes a 4-state bar code called HANGUL 4 ST that has been specifically designed for automatic processing of the letter mails, A HANGUL 4 ST bar code is a necessary data base that is applied data capture and data carrier with it all the information necessary for sorting, the amount capture for transportation of mail items, and valued-added services such as indicia, tracking and trace. The 4-state bar code information contents are composed of a postal code, delivery point, customer information including customer identification number and name, and parity bits for error detect and correct. The data density capability of HANGUL 4 St allows all useful sorting data and customer data to be encoded on one label. This supports better automatic processing in mail items, higher level of customer service and more efficient operation.

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Automatic False-Alarm Labeling for Sensor Data

  • Adi, Taufik Nur;Bae, Hyerim;Wahid, Nur Ahmad
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.2
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    • pp.139-147
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    • 2019
  • A false alarm, which is an incorrect report of an emergency, could trigger an unnecessary action. The predictive maintenance framework developed in our previous work has a feature whereby a machine alarm is triggered based on sensor data evaluation. The sensor data evaluator performs three essential evaluation steps. First, it evaluates each sensor data value based on its threshold (lower and upper bound) and labels the data value as "alarm" when the threshold is exceeded. Second, it calculates the duration of the occurrence of the alarm. Finally, in the third step, a domain expert is required to assess the results from the previous two steps and to determine, thereby, whether the alarm is true or false. There are drawbacks of the current evaluation method. It suffers from a high false-alarm ratio, and moreover, given the vast amount of sensor data to be assessed by the domain expert, the process of evaluation is prolonged and inefficient. In this paper, we propose a method for automatic false-alarm labeling that mimics how the domain expert determines false alarms. The domain expert determines false alarms by evaluating two critical factors, specifically the duration of alarm occurrence and identification of anomalies before or while the alarm occurs. In our proposed method, Hierarchical Temporal Memory (HTM) is utilized to detect anomalies. It is an unsupervised approach that is suitable to our main data characteristic, which is the lack of an example of the normal form of sensor data. The result shows that the technique is effective for automatic labeling of false alarms in sensor data.

Rule Acquisition Using Ontology Based on Graph Search (그래프 탐색을 이용한 웹으로부터의 온톨로지 기반 규칙습득)

  • Park, Sangun;Lee, Jae Kyu;Kang, Juyoung
    • Journal of Intelligence and Information Systems
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    • v.12 no.3
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    • pp.95-110
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    • 2006
  • To enhance the rule-based reasoning capability of Semantic Web, the XRML (eXtensible Rule Markup Language) approach embraces the meta-information necessary for the extraction of explicit rules from Web pages and its maintenance. To effectuate the automatic identification of rules from unstructured texts, this research develops a framework of using rule ontology. The ontology can be acquired from a similar site first, and then can be used for multiple sites in the same domain. The procedure of ontology-based rule identification is regarded as a graph search problem with incomplete nodes, and an A* algorithm is devised to solve the problem. The procedure is demonstrated with the domain of shipping rates and return policy comparison portal, which needs rule based reasoning capability to answer the customer's inquiries. An example ontology is created from Amazon.com, and is applied to the many online retailers in the same domain. The experimental result shows a high performance of this approach.

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Automatic Identification of the OMR Answer Marking Using Smart Phone (스마트폰을 이용한 OMR 답안 마킹 자동 인식)

  • Noh, Duck-Soo;Kim, Jin-Ho
    • The Journal of the Korea Contents Association
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    • v.16 no.9
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    • pp.694-701
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    • 2016
  • The smart phone application to provide auto identification and answer explanation of multiple choice answer for each OMR answer item in the test paper different from ordinary OMR test by using smart phone is very useful in terms of a self learning and a smart learning. In this paper, smart phone application of OMR mark identification for each question item in test paper is proposed. QR code for each OMR answer is provided for the encrypted correct answer and the reference location of multiple choice answer rectangle location. The OMR answer region is extracted and the marked answer is identified in each question of test paper, in order to compare between the marking answer and the correct answer. Experimental result of smart phone application of the proposed algorithm for the OMR answer images with various size and direction shows excellent recognition performance.

Automatic Person Identification using Multiple Cues

  • Swangpol, Danuwat;Chalidabhongse, Thanarat
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1202-1205
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    • 2005
  • This paper describes a method for vision-based person identification that can detect, track, and recognize person from video using multiple cues: height and dressing colors. The method does not require constrained target's pose or fully frontal face image to identify the person. First, the system, which is connected to a pan-tilt-zoom camera, detects target using motion detection and human cardboard model. The system keeps tracking the moving target while it is trying to identify whether it is a human and identify who it is among the registered persons in the database. To segment the moving target from the background scene, we employ a version of background subtraction technique and some spatial filtering. Once the target is segmented, we then align the target with the generic human cardboard model to verify whether the detected target is a human. If the target is identified as a human, the card board model is also used to segment the body parts to obtain some salient features such as head, torso, and legs. The whole body silhouette is also analyzed to obtain the target's shape information such as height and slimness. We then use these multiple cues (at present, we uses shirt color, trousers color, and body height) to recognize the target using a supervised self-organization process. We preliminary tested the system on a set of 5 subjects with multiple clothes. The recognition rate is 100% if the person is wearing the clothes that were learned before. In case a person wears new dresses the system fail to identify. This means height is not enough to classify persons. We plan to extend the work by adding more cues such as skin color, and face recognition by utilizing the zoom capability of the camera to obtain high resolution view of face; then, evaluate the system with more subjects.

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Feature information fusion using multiple neural networks and target identification application of FLIR image (다중 신경회로망을 이용한 특징정보 융합과 적외선영상에서의 표적식별에의 응용)

  • 선선구;박현욱
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.4
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    • pp.266-274
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    • 2003
  • Distance Fourier descriptors of local target boundary and feature information fusion using multiple MLPs (Multilayer perceptrons) are proposed. They are used to identify nonoccluded and partially occluded targets in natural FLIR (forward-looking infrared) images. After segmenting a target, radial Fourier descriptors as global shape features are defined from the target boundary. A target boundary is partitioned into four local boundaries to extract local shape features. In a local boundary, a distance function is defined from boundary points and a line between two extreme points. Distance Fourier descriptors as local shape features are defined by using distance function. One global feature vector and four local feature vectors are used as input data for multiple MLPs to determine final identification result of the target. In the experiments, we show that the proposed method is superior to the traditional feature sets with respect to the identification performance.

Cold Storage Management System using RFID Deployment Simulator for Optimized Business Process (최적화된 비즈니스 프로세스를 위한 RFID 배치 시뮬레이터 기반의 냉동창고 관리 시스템)

  • Baek, Sun-Jae;Moon, Mi-Kyeong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.6
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    • pp.1453-1459
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    • 2010
  • Recently, the aim of cold storage warehouse is not only to provide preservation of the quality of perishable foods but also to use state-of-the-art information systems to rapidly move products across the cold chain. An RFID (Radio Frequency Identification) is an automatic identification method that detects signals from mobile objects, and tracks and traces movement of the objects. RFID can be used to turn a cold storage warehouses into a real-time system. In this paper, we develop an cold storage management system to support the optimized business processes with RFID system. First of all, business processes in the cold storage warehouse are analyzed. Then design factors which should be considered for incorporating RFID are defined. Design values which set to the design factors can be extracted from using RFID deployment simulator. as a result, the design values make RFID to be efficiently integrated to existing business processes.

Bacteriological Characteristics of Unidentified Vibrio sp., Hemolysin Producer Isolates front Brackish Water -1. Bacteriological Characteristics of Vibrio sp., D9 (V. kumkang) Similar to V. mimicus (기수에서 분리된 용혈독소를 생산하는 미분류 Vibrio sp.의 세균학적 특징 -1. V. mimicus와 유사한 Vibrio sp. D9의 세균학적 특성)

  • KIM Young-Man;OH Hee-Kyung
    • Korean Journal of Fisheries and Aquatic Sciences
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    • v.33 no.6
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    • pp.585-590
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    • 2000
  • A hemolysin producing strain was isolated from Kum rivet estuary located in west part of Korea. In the process of identification the isolated strain was similar to V. mimicus but did not show characteristics of known Vibrio species; therefore, the strain was designated as Vibrio sp. D9 ( V. kumkang) tentatively and further identification study was carried out by comparing its bacteriological characteristics, Morphologically Vibrio sp. D9 was a typical straight roe with a polar flagellium. Among known Vibrio species no identical strains were found when using automatic bacteria identification system ($MicioLog^(TM)$system, release 4.0, Biolog Inc., USA) which evaluated the ability of metabolizing 95 kinds of carbon and nitrogen sources. Vibrio sp. D9 showed 18 and 13 different responses as compared to V. mimicus and V. cholerae, respectively. Clear hemolysis zones were observed with the strain against human and sheep blood agar plate, Hemolytic toxicity was confirmed by strong vascular permeability and fatal toxicity against mouse was also observed. Thus the strain was a pathogenic vibrio. Growth conditions for Vibrio sp. D9 were salinity of $0{\~}5.0{\%}$, pH of $6.4{\~}9.8$, temperature of $15{\~}41^{\circ}C$, respectively.

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