• The KIPS Transactions:PartC
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• v.10C no.1
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• pp.39-44
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• 2003

The network performance gets down during congestion periods to solve the problem effectively. A RED(Random Earl Detection) algorithm of the queue management algorithm is proposed and IETF recommends it as a queue management. A RED algorithm controls a congestion aspect dynamically. In analyzing parameters when static value of parameter is set in the gateway cannot be handled the status of current network traffic properly We propose the Effective RED algorithm to solve with the weakness of RED In this algorithm the maximum drop probability decides to accept or drop the interning packets, is adjusted dynamically on the current queue state for controlling the congestion phase effectively in the gateway. This algorithm is confirmed by computer simulation using the NS(Network Simulator)-2.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.10b
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• pp.1447-1450
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• 2001

최근 라우터에서는 정체를 회피하고 전송률을 향상시키기 위한 능동적 큐 관리와 패킷 스케줄링에 대한 많은 논의가 이루어지고 있다. 본 논문은 라우터에서의 전송률 향상을 위한 Randrom Early Detectio(RED) 알고리즘과 최근까지 변형된 RED 알고리즘들의 특징을 살펴보고, RED 라우터에 적용하여 실제로 종단 호스트(End-to-end)에서 전송 받는 패킷의 양을 향상하기 위한 선별적 처리 알고리즘을 제안한다.

• Journal of KIISE:Information Networking
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• v.31 no.1
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• pp.70-80
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• 2004

In order to reduce the increasing packet loss rates caused by an exponential increase in network traffic, the IETF(Internet Engineering Task Force) is considering the deployment of active queue management techniques such as RED(Random Early Detection). But, RED configuration has been a problem since its first proposal. This problem is that proposed configuration is only good for the particular traffic conditions studied, but may have detrimental effects if used in other conditions. While active queue management in routers and gateways can potentially reduce packet loss rates in the Internet, this paper has demonstrated the inherent weakness of current techniques and shows that they are unstable for tile various traffic conditions. The inherent problem with these queue management algorithms is that they all use static parameter setting. In this paper, in order to solve this problem, a new active queue management algorithm called SQM(Stabilized Queue Management) is proposed. This paper shows that it is easy to parameterize SQM algorithm to perform well under different congestion scenarios. This algorithm can effectively reduce packet loss while maintaining high link utilizations and is good for the various traffic conditions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6B
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• pp.605-614
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• 2009

Existing Internet services were almost supported by the best effort service such as the data transmission service and were allowed the transmission delay and packet loss. However, recent Internet multimedia services such as Internet phone, Internet broadcasting are required a real-time processing and high bandwidth. Therefore, many studies for providing Internet QoS are performed at IETF (Internet Engineering Task Force). As the buffer management mechanism among IP QoS methods, active queue management method such as RED (Random Early Detection) algorithm has proposed. However, RED algorithm has a limitation of usage of an average buffer length and unfairness. So, many algorithms proposed as the modified algorithm of RED. But these modified algorithms also have difficulties to satisfy the requirements of various Internet user QoS. Therefore, in this paper we propose the QoS adaptive AQM (Active Queue Management) algorithm for the multimedia services that request various QoS requirements and present a performance evaluation by the simulations using the ns-2.

• Journal of KIISE:Information Networking
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• v.30 no.3
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• pp.437-447
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• 2003

In order to reduce the increasing packet loss rates caused by an exponential increase in network traffic, the IETF(Internet Engineering Task Force) is considering the deployment of active queue management techniques such as RED(Random Early Detection) algorithm. However, RED algorithm simple but does not protect traffic from high-bandwidth flows, which include not only flows that fail to use end-to-end congestion control such as UDP flow, but also short round-trip time TCP flows. In this paper, in order to solve this problem, we propose a simple fairness queue management scheme, called AFQM(Approximate Fair Queue Management) algorithm, that discriminate against the flows which submit more packets/sec than is allowed by their fair share. By doing this, the scheme aims to approximate the fair queueing policy Since it is a small overhead and easy to implement, AFQM algorithm controls unresponsive or misbehaving flows with a minimum overhead.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.11B
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• pp.1289-1295
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• 2009

Premature ventricular contractions are the most common of all arrhythmias and may cause more serious situation like ventricular fibrillation and ventricular tachycardia in some patients. Therefore, the detection of this arrhythmia becomes crucial in the early diagnosis and prevention of possible life threatening cardiac diseases. Particularly, in the healthcare system that must continuously monitor people's situation, it is necessary to process ECG signal in realtime. In other words, design of algorithm that exactly detects R wave using minimal computation and classifies PVC is needed. So, R wave detection algorithm based adaptive threshold and window for the classification of PVC is presented in this paper. For this purpose, ECG signals are first processed by the usual preprocessing method and R wave was detected and adaptive window through R-R interval is used for efficiency of the detection. The performance of R wave detection and PVC classification is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate 99.33%, 88.86% accuracy respectively for R wave detection and PVC classification.

• Journal of the Institute of Convergence Signal Processing
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• v.23 no.4
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• pp.256-263
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• 2022

Skin cancer is one of the most common diseases in the world, and the incidence rate in Korea has increased by about 100% over the past five years. In the United States, more than 5 million people are diagnosed with skin cancer every year. Skin cancer mainly occurs when skin tissue is damaged for a long time due to exposure to ultraviolet rays. Melanoma, a malignant tumor of skin cancer, is similar in appearance to Atypical melanocytic nevus occurring on the skin, making it difficult for the general public to be aware of it unless secondary signs occur. In this paper, we propose a skin cancer lesion edge detection algorithm and a deep learning model, CRNN, which performs skin cancer lesion classification for early detection and classification of these skin cancers. As a result of the experiment, when using the contour detection algorithm proposed in this paper, the classification accuracy was the highest at 97%. For the Canny algorithm, 78% was shown, 55% for Sobel, and 46% for Laplacian.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.763-768
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• 2006

The two-for-one(TFO) twister is precision machinery that twists fibers rapidly under constant tension. Since the quality of the twisted yarn is directly deteriorated by faults of the twister, such as the distortion of the spinning axis, bearing abrasion, and tension irregularity, it is important to detect faults of the TFO twister at an early stage. In this research, a new algorithm is proposed to detect faults of the TFO twister and their causes, by measuring the vibrations of the TFO twister and obtaining frequency components with a FFT algorithm. The TFO twister with faults showed increased vibrations and each fault generated vibrations at different frequencies. By analyzing changes of characteristics of vibrations, we can determine faulty twisters. The proposed fault detection algorithm can be implemented cheaply with a signal processor chip. It can be used to find when to repair a faulty TFO twister without much loss of yam on-line.

• Journal of Sensor Science and Technology
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• v.13 no.1
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• pp.56-65
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• 2004

In this paper, we proposed the detection algorithm of microcalcification based on region growing method with contrast and edge sharpness in digital X-ray mammographic images. We extracted the local maximum pixel and watershed regions by using watershed algorithm. Then, we used the mean slope between local maximum and neighborhood pixels to extract microcalcification candidate pixels among local maximum pixels. During increasing threshold value to grow microcalcification region, at the maximum threshold value of the contrast and edge sharpness, the microcalcification area is decided. The regions of which area of grown candidate microcalfication region is larger than that of watershed region are excluded from microcalcifications. We showed the diagnosis algorithm can be used to aid diagnostic-radiologist in the early detection breast cancer.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.121.1-121
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• 2001

Congestion control is a critical issue in TCP networks, Recently, active queue management (AQM) was proposed for congestion control at routers. The random early detection RED algorithm is widely known in the AQM algorithms, We present an adaptive nonlinear RED (NRED) algorithm, which has nonlinear drop probability profile. The proposed algorithm enhanced the performance of the RED algorithm by the self-parameterization based on the traffic load Furthermore, the proposed algorithm can effectively adapt itself between he RED and the drop-tail queue management by adopting proper nonlinearity in the drop probability profile. Through simulation, we show the effectiveness of the proposed algorithm comparing with the drop-tail and the original RED algorithm.