• 한국컴퓨터정보학회논문지
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• 제22권3호
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• pp.69-79
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• 2017

In this paper, we propose our four-phase life cycle of P2P botnet with corresponding detection methods and the future direction for more effective P2P botnet detection. Our proposals are based on the intensive analysis that compares existing P2P botnet detection schemes in different points of view such as life cycle of P2P botnet, machine learning methods for data mining based detection, composition of data sets, and performance matrix. Our proposed life cycle model composed of linear sequence stages suggests to utilize features in the vulnerable phase rather than the entire life cycle. In addition, we suggest the hybrid detection scheme with data mining based method and our proposed life cycle, and present the improved composition of experimental data sets through analysing the limitations of previous works.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.1050-1053
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• 1995

A stock removal cycle is developed as a programming tool of the CNC lathe. This cycle support the easiness and swifness of a part program generation in the shopfloor. The cycle contains the function of tool path generation of rough/finish cutting, of avoidance air-cut for non-cylindrical (die-casted, forged) workpiece, and of the tool collisopn detection/aviodance. Consequently the intelligent stock removal cycle results in improving the productivity and safety of CNC lathe.

• International journal of advanced smart convergence
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• 제13권2호
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• pp.195-204
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• 2024

In this paper, we investigate the comparative performance of two leading object detection architectures, YOLOv7 and Detection Transformer (DETR), across varying levels of data augmentation using CycleGAN. Our experiments focus on chest scan images within the context of biomedical informatics, specifically targeting the detection of abnormalities. The study reveals that YOLOv7 consistently outperforms DETR across all levels of augmented data, maintaining better performance even with 75% augmented data. Additionally, YOLOv7 demonstrates significantly faster convergence, requiring approximately 30 epochs compared to DETR's 300 epochs. These findings underscore the superiority of YOLOv7 for object detection tasks, especially in scenarios with limited data and when rapid convergence is essential. Our results provide valuable insights for researchers and practitioners in the field of computer vision, highlighting the effectiveness of YOLOv7 and the importance of data augmentation in improving model performance and efficiency.

• 한국정밀공학회지
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• 제22권3호
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• pp.170-178
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• 2005

The purpose of this study is to develop a gait-event detection system, which is necessary for the cycle-to-cycle FES control of locomotion. Proposed gait event detection system consists of a signal measurement part and gait event detection part. The signal measurement was composed of the sensors and the LabVIEW program for the data acquisition and synchronization of the sensor signals. We also used a video camera and a motion capture system to get the reference gait events. Machine learning technique with ANN (artificial neural network) was adopted for automatic detection of gait events. 2 cycles of reference gait events were used as the teacher signals for ANN training and the remnants ($2\sim5$ cycles) were used fur the evaluation of the performance in gait-event detection. 14 combinations of sensor signals were used in the training and evaluation of ANN to examine the relationship between the number of sensors and the gait-event detection performance. The best combinations with minimum errors of event-detection time were 1) goniometer, foot-switch and 2) goniometer, foot-switch, accelerometer x(anterior-posterior) component. It is expected that the result of this study will be useful in the design of cycle-to-cycle FES controller.

• Journal of Positioning, Navigation, and Timing
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• 제6권4호
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• pp.181-194
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• 2017

In recent years, research has been actively conducted on the navigation in an indoor environment where Global Navigation Satellite System signals are unavailable. Among them, a study performed indoor navigation by integrating pseudolite carrier and Inertial Measurement Unit (IMU) sensor. However, in this case, there was no solution for the cycle slip occurring in the carrier. In another study, cycle slip detection and compensation were performed by integrating Global Positioning System (GPS) and IMU in an outdoor environment. However, in an indoor environment, cycle slip occurs more easily and frequently, and thus the occurrence of half cycle slip also increases. Accordingly, cycle slip detection based on 1 cycle unit has limitations. Therefore, in the present study, the aforementioned problems were resolved by performing indoor navigation through the integration of pseudolite and ultra-low-cost IMU embedded in a smartphone and by performing half cycle slip detection and compensation based on this. In addition, it was verified through the actual implementation of real-time navigation.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.2
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• pp.91-96
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• 2006

Presently, cycle-slip detection is done between adjacent two points in many cycle-slip methods. Inherently, it is simple wavelet analysis. A new idea is put forward that the number of difference point can adjust by a parameter factor; we study this method to smooth raw data and detect cycle-slip with wavelet analysis. Taking CHAMP satellite data for example, we get some significant conclusions. It is showed that it is valid to detect cycle-slip in GPS phase measurement based on this wavelet function, and it is helpful to improve the precision of GPS data pre-processing and positioning.

• 한국정보과학회논문지:시스템및이론
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• 제32권2호
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• pp.49-54
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• 2005

본 논문에서는 즉시 할당 상태와 함께 단일 자원, 단일 요청의 가정 하에서 다중처리 시스템에서 사이클을 발생 즉시 발견함으로써 지연 없는 교차상태의 발견 방법을 소개한다. 기존의 방법과는 달리 제시된 방법은 n과 m으로 프로세스와 자원의 수론 나타낼 때 사이클의 발견에 O(1), 대기나 자원의 반납시에 O(n.m)의 시간을 요한다. 따라서 n과 m의 크기에 상관없이 교착상태를 발생 즉시 알 수 있으며, 이점이 다중처리 시스템의 특성과 잘 조화될 수 있음을 보였다. 교착상태와 연관된 응용환경에서 이러한 발견의 예측성과 비 지연성은 매우 유용할 것이다.

• 대한전기학회논문지:시스템및제어부문D
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• 제55권5호
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• pp.248-253
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• 2006

The purpose of this study is to develop a portable gait-event detection system which is necessary for the cycle-to-cycle FES(functional electrical stimulation) control of locomotion. To make the system portable, we made following modifications in the gait signal measurement system. That is, 1) to make the system wireless using Bluetooth communication, 2) to make the system small-sized and battery-powered by using low power consumption ${\mu}$ P(ATmega8535L). The gait-events were analyzed in off-line at the main computer using ANN(Artificial Neural Network). The Proposed system showed no mis-detection of the gait-events of normal subject and hemiplegia subjects. The performance of the system was better than the previous wired-system.

• 한국항행학회논문지
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• 제17권6호
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• pp.593-599
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• 2013

본 논문은 차량 환경에서 GPS 반송파 기반 위치 결정을 위한 반송파 불연속 측정치 검출에 대한 내용을 다룬다. 반송파 기반 위치 결정 방식에 있어서 위치 정확도의 신뢰도를 확보하기 위해서는 반송파 불연속 측정치를 검출해야 한다. 반송파 불연속 측정치를 검출하는 방식에는 여러 연구가 있지만 본 연구에서는 차분된 반송파 측정치와 저가의 관성센서를 이용해 추정한 차분된 반송파의 차이를 모니터링 값으로 설정함으로써 GPS 불연속 측정치를 검출한다. 저가의 불연속 측정치 검출 알고리즘을 개발하는 것을 목표로 설계된 불연속 측정치 검출 성능 만족을 위한 관성센서 성능 범위를 도출한다. 이를 통해 적절한 가격과 성능의 관성센서 선택이 가능하다. 선정된 관성센서가 설계치를 만족하는지를 검증하기 위하여 회전 테이블 실험을 진행하였다. 결과적으로 실험치가 설계된 불연속 측정치 검출 성능을 보수적으로 만족하는 검출 성능을 보였다.

• 한국측량학회지
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• 제40권4호
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• pp.359-364
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• 2022

원격탐사 영상의 변화탐지는 카메라의 광학적 요인, 계절적 요인, 토지피복 특성에 의해 오류가 발생한다. 본 연구에서는 CycleGAN (Cycle Generative Adversarial Network) 방법을 사용하여 촬영 각도에 따른 영상 내 건물 기울기를 모의 조정하였고, 이렇게 모의한 영상을 변화탐지에 활용하여 탐지 정확도 향상에 기여하도록 하였다. CycleGAN 기반으로 두 개 시기 영상 중 한 시기 영상을 기준으로 건물의 기울기를 다른 한 영상 내 건물에 유사하게 모의하였고 원 영상과 건물 기울기에 대한 오류를 비교 분석하였다. 실험자료로는 서로 다른 시기에 다른 각도로 촬영되었고, 건물이 밀집한 도시지역을 포함한 Kompsat-3A 고해상도 위성영상을 사용하였다. 실험 결과, 영상 내 건물 영역에 대하여 두 영상의 건물에 의한 오탐지 화소 수가 원 영상에서는 12,632개, CycleGAN 기반 모의 영상에서는 1,730개로 약 7배 감소하는 것으로 나타났다. 따라서, 제안 방법이 건물 기울기로 인한 탐지오류를 감소시킬 수 있음을 확인하였다.