• Journal of Computing Science and Engineering
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• 제7권4호
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• pp.251-262
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• 2013

Bad smells are usually related to program source code, arising from bad design and programming practices. Refactoring activities are often motivated by the detection of bad smells. With the increasing adoption of Design-by-Contract (DBC) methodologies in formal software development, evidence of bad design practices can similarly be found in programs that combine actual production code with interface contracts. These contracts can be written in languages, such as the Java Modeling Language (JML), an extension to the Java syntax. This paper presents a catalog of bad smells that appear during DBC practice, considering JML as the language for specifying contracts. These smells are described over JML constructs, although several can appear in other DBC languages. The catalog contains 6 DBC smells. We evaluate the recurrence of DBC smells in two ways: first by describing a small study with graduate student projects, and second by counting occurrences of smells in contracts from the JML models application programming interface (API). This API contains classes with more than 1,600 lines in contracts. Along with the documented smells, suggestions are provided for minimizing the impact or even removing a bad smell. It is believed that initiatives towards the cataloging of bad smells are useful for establishing good design practices in DBC.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.131-133
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• 1993

In the power system state estimation, the J(x)-index test and normalized residuals $r_N$ have been used to detect the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network model using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional methods and simulation results show the good performance in the bad data identification based on the neural network under sample power system.

• 한국컴퓨터정보학회논문지
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• 제23권1호
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• pp.25-32
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• 2018

In this paper, we propose an edge detection algorithm for auto focus of infrared camera. We designed and implemented the edge detection of infrared image by using a spatial filter on FPGA. The infrared camera should be designed to minimize the image processing time and usage of hardware resource because these days surveillance systems should have the fast response and be low size, weight and power. we applied the $3{\times}3$ mask filter which has an advantage of minimizing the usage of memory and the propagation delay to process filtering. When we applied Laplacian filter to extract contour data from an image, not only edge components but also noise components of the image were extracted by the filter. These noise components make it difficult to determine the focus state. Also a bad pixel of infrared detector causes a problem in detecting the edge components. So we propose an adaptive edge detection filter that is a method to extract only edge components except noise components of an image by analyzing a variance of pixel data in $3{\times}3$ memory area. And we can detect the bad pixel and replace it with neighboring normal pixel value when we store a pixel in $3{\times}3$ memory area for filtering calculation. The experimental result proves that the proposed method is effective to implement the edge detection for auto focus in infrared camera.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
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• pp.716-718
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• 2004

The false alarm data in intrusion detection systems are divided into false positive and false negative. The false positive makes bad effects on the performance of intrusion detection system. And the false negative makes bad effects on the efficiency of intrusion detection system. Recently, the most of works have been studied the data mining technique for analysis of alert data. However, the false alarm data not only increase data volume but also change patterns of alert data along the time line. Therefore, we need a tool that can analyze patterns that change characteristics when we look for new patterns. In this paper, we focus on the false positives and present a framework for analysis of false alarm pattern from the alert data. In this work, we also apply incremental data mining techniques to analyze patterns of false alarms among alert data that are incremental over the time. Finally, we achieved flexibility by using dynamic support threshold, because the volume of alert data as well as included false alarms increases irregular.

• 한국정보통신학회논문지
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• 제4권1호
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• pp.139-144
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• 2000

본 연구에서는 제철소의 원료운송라인의 가장 핵심인 콘베이어 벨트의 사행을 신뢰성 있게 감지할 수 있는 콘베이어 벨트 사행 감시장치를 개발하는 것이다. 원료생산 라인은 먼지 및 습도 진동 등, 외부에 완전히 노출되어 있어 계측 환경이 대단히 열악하므로 기존의 감지방식은 신뢰성을 갖기가 어렵다. 이러한 문제를 해결하기 위하여 가격이 저렴하고 열악한 환경에서도 잘 동작할 수 있는 적외선 센서어레이와 원칩 마이크로프로세서를 이용한 적외선 사행감지 시스템을 개발하였으며, 실험을 통해 동작의 신뢰성을 확인하였다.

• 한국산학기술학회논문지
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• 제13권11호
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• pp.5471-5478
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• 2012

본 논문에서는 SURF 알고리즘을 이용하여 PCB에 발생하는 불량 중 한 형태인 쇼트-서킷 불량을 탐지하는 기술을 제안한다. 제안하는 방법의 기본적인 절차는 SURF를 이용하여 샘플 영상과 입력된 영상에서 특징점 추출, 특징점 매칭 및 매칭 결과를 이용한 원근변환 수행, 검사 위치 관심영역 추출, 이진화 및 쇼트-서킷 추출, 결과 검증 순이다. 본 논문에서 제안하는 방식은 수작업으로 진행되는 후 공정의 특징 상, 검사하고자 하는 PCB의 놓여진 위치와 각도가 균일하지 않고 제각각으로 놓여 있는 경우에도 강건하게 쇼트-서킷 불량을 탐지하는 것에 중점을 두고 있다. 이 방법은 PCB가 놓여진 위치와 각도가 다양한 경우에도 불량을 탐지할 수 있음을 보이며, 탐지율 및 탐지시간 관점에서 기존의 수작업으로 검사하는 경우보다 우수함을 실험을 통하여 보인다.

• 조명전기설비학회논문지
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• 제17권3호
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• pp.103-109
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• 2003

전력계통의 자동화에 있어 측정되는 데이터의 정확성은 기본적으로 확립되어야 할 요건이다. 측정된 데이터는 통신 장애나 기기 자체의 오동작으로 인해 오차를 포함할 수 있으며, 이러한 오차는 상태추정에 의해 줄어들 수 있으나, 잘못 측정된 일부 값에 의해 상태추정의 전반적인 신뢰도가 저하될 수 있다. 본 논문에서는 가중최소 상태추정과 카이스퀘어 이론에 근거한 잘못 측정된 데이터의 검출 알고리즘이 제안되었으며, 이를 국내 154kV 변전소에 적용하였다. C 언어와 비쥬얼 베이직을 사용하여 GUI 환경의 시뮬레이터를 개발하였으며, 다른 운용 시스템과의 연계를 고려하여 TCP/IP 프로토콜을 탑재하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 A
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• pp.130-132
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• 1996

The squirrel cage rotors for induction motors may have several faults such as broken bars, bad spots in the end ring and abnormal skew caused by improper processing. These faults have bad effect on the performance of the induction motor. In this paper, these fault detection method is proposed, then the effects on the performance of the motor is analyzed using FEM.

• 한국전기전자재료학회:학술대회논문집
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• 한국전기전자재료학회 2008년도 춘계학술대회 논문집 센서 박막재료연구회 및 광주 전남지부
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• pp.54-57
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• 2008

A new modular Lateral Information Propagation Networks can be implemented in a IC chip with the circuit VLSI technology for detection of bad materials. The proposed modular architecture is propagated the neural network through inter module connections. For such inter module connections, the host(computer or logic) mediates the exchange of information among modules. Also border nodes in each module have capacitors for temporarily retaining the information from outer modules. For detecting of Faulty Insulator, $4\;{\times}\;4$ neural network modules has been designed and simulation of interpolation with the designed networks has been done.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.116-118
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• 2000

The modern power system including lots of measuring devices and controller is large and complex total information system. A Lot of data and system information are transmitted to operators, and analysing these information and system management is very important. Recently, GUI(Graphic Users Interface) is emphasized as a method that operators carry out their duties, effectively. In this paper. a simulator that can show state estimation and detection of bad measuring devices is introduced for domestic 154kV/22.9kV distribution substations. C language and Visual Basic is used for this simulator. and TCP/IP is adopted to consider connection with a Power system.