• 제목/요약/키워드: trend algorithm

검색결과 428건 처리시간 0.023초

Detection of the Ultrasonic Signals due to Partial Discharges in a 154kV Transformer

  • Kweon, Dong-Jin;Chin, Sang-Bum;Kwak, Hee-Ro
    • KIEE International Transactions on Electrophysics and Applications
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    • 제2C권6호
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    • pp.297-303
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    • 2002
  • We have developed an on-line ultrasonic detector to monitor partial discharge in an operating transformer. The ultrasonic sensor has 150[KHz] resonance frequency and contains a pre-amplifier with 60[㏈] gain. The on-line ultrasonic detector has 50~300[KHz] frequency band-pass filter to remove electrical and mechanical noises from the transformer. This detector has an ultrasonic signal discrimination algorithm which discriminates ultrasonic signals due to partial discharge in a transformer. A moving average method of ultrasonic signal number was employed to effectively monitor the increasing trend of the partial discharge. This paper describes an experience of partial discharge detection in a 154[㎸] operating transformer using an ultrasonic detector. With regards to gas analysis in oil, C2H2 gas was produced with a warning level in this transformer We detected ultrasonic signals on the transformer steel wall, and estimated the position of partial discharge. With further inspection, we found carbonized marks due to partial discharge on the supporting bolt which fastens the windings.

Analyzing Clustered and Interval-Censored Data based on the Semiparametric Frailty Model

  • Kim, Jin-Heum;Kim, Youn-Nam
    • 응용통계연구
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    • 제25권5호
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    • pp.707-718
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    • 2012
  • We propose a semi-parametric model to analyze clustered and interval-censored data; in addition, we plugged-in a gamma frailty to the model to measure the association of members within the same cluster. We propose an estimation procedure based on EM algorithm. Simulation results showed that our estimation procedure may result in unbiased estimates. The standard error is smaller than expected and provides conservative results to estimate the coverage rate; however, this trend gradually disappeared as the number of members in the same cluster increased. In addition, our proposed method was illustrated with data taken from diabetic retinopathy studies to evaluate the effectiveness of laser photocoagulation in delaying or preventing the onset of blindness in individuals with diabetic retinopathy.

Fast 3D Mesh Compression Using Shared Vertex Analysis

  • Jang, Euee-Seon;Lee, Seung-Wook;Koo, Bon-Ki;Kim, Dai-Yong;Son, Kyoung-Soo
    • ETRI Journal
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    • 제32권1호
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    • pp.163-165
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    • 2010
  • A trend in 3D mesh compression is codec design with low computational complexity which preserves the input vertex and face order. However, this added information increases the complexity. We present a fast 3D mesh compression method that compresses the redundant shared vertex information between neighboring faces using simple first-order differential coding followed by fast entropy coding with a fixed length prefix. Our algorithm is feasible for low complexity designs and maintains the order, which is now part of the MPEG-4 scalable complexity 3D mesh compression standard. The proposed algorithm is 30 times faster than MPEG-4 3D mesh coding extension.

한국형 Market Simulator 개발(II) (Development of Korean Market Simulator (II))

  • 허진;강동주;국경수;김태현;이정호;문영환
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 하계학술대회 논문집 A
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    • pp.655-657
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    • 2003
  • Power system deregulation has become a worldwide trend which introduces competition in electric power system in order to realize efficient electricity production and investment. In this regards, it is very important to develop an electricity market simulator so that it is to analyze competitive market and train market operators and market participants. In this paper, we implement the algorithm of determining market clearing price as the first module of unique market simulator. The adopted and suggested algorithm is verified by modelling a simple market with a commercial market simulator(PLEXOS).

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Assessment of Premature Ventricular Contraction Arrhythmia by K-means Clustering Algorithm

  • Kim, Kyeong-Seop
    • 한국컴퓨터정보학회논문지
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    • 제22권5호
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    • pp.65-72
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    • 2017
  • Premature Ventricular Contraction(PVC) arrhythmia is most common abnormal-heart rhythm that may increase mortal risk of a cardiac patient. Thus, it is very important issue to identify the specular portraits of PVC pattern especially from the patient. In this paper, we propose a new method to extract the characteristics of PVC pattern by applying K-means machine learning algorithm on Heart Rate Variability depicted in Poinecare plot. For the quantitative analysis to distinguish the trend of cluster patterns between normal sinus rhythm and PVC beat, the Euclidean distance measure was sought between the clusters. Experimental simulations on MIT-BIH arrhythmia database draw the fact that the distance measure on the cluster is valid for differentiating the pattern-traits of PVC beats. Therefore, we proposed a method that can offer the simple remedy to identify the attributes of PVC beats in terms of K-means clusters especially in the long-period Electrocardiogram(ECG).

A New Algorithm for Automated Modeling of Seasonal Time Series Using Box-Jenkins Techniques

  • Song, Qiang;Esogbue, Augustine O.
    • Industrial Engineering and Management Systems
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    • 제7권1호
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    • pp.9-22
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    • 2008
  • As an extension of a previous work by the authors (Song and Esogbue, 2006), a new algorithm for automated modeling of nonstationary seasonal time series is presented in this paper. Issues relative to the methodology for building automatically seasonal time series models and periodic time series models are addressed. This is achieved by inspecting the trend, estimating the seasonality, determining the orders of the model, and estimating the parameters. As in our previous work, the major instruments used in the model identification process are correlograms of the modeling errors while the least square method is used for parameter estimation. We provide numerical illustrations of the performance of the new algorithms with respect to building both seasonal time series and periodic time series models. Additionally, we consider forecasting and exercise the models on some sample time series problems found in the literature as well as real life problems drawn from the retail industry. In each instance, the models are built automatically avoiding the necessity of any human intervention.

Display System Design Based On The Abstraction Hierarchy

  • Sohn, Kwang-Young;Shin, Hyun-Kook
    • Nuclear Engineering and Technology
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    • 제28권3호
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    • pp.339-348
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    • 1996
  • Plant monitoring algorithm developments seem to be saturated which means that display system to show the results from the algorithm should be the well-defined and interactive tools for operator's diagnosing, controlling, restoring the abnormal plant situations. On the other hand, very little generalized display design concepts and evaluations are available. Events that are unfamiliar to operators and that has not been anticipated by designers may cause great threats to the nuclear power plant system safety operation. The abstraction hierarchy, considered most popular display design methodology but not generalized for nuclear power plant design space, has ken proposed as a representation frame work that can be adopted to design interfaces and supports operators in diagnosing overlooked events that should have been considered to operate plant safely. However most practical plant display systems do not fully stick to this design concept but partially rely on their philosophy from design experiences. Abstraction hierarchy display design concept will be do scribed and the trend of Advanced Control Room(ACR) CRT design will also be presented with the conventional display for the several type of plants. Consequently this complementary material should be of interest to designer and regulators concerned with nuclear power plant.

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INERTIAL PICARD NORMAL S-ITERATION PROCESS

  • Dashputre, Samir;Padmavati, Padmavati;Sakure, Kavita
    • Nonlinear Functional Analysis and Applications
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    • 제26권5호
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    • pp.995-1009
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    • 2021
  • Many iterative algorithms like that Picard, Mann, Ishikawa and S-iteration are very useful to elucidate the fixed point problems of a nonlinear operators in various topological spaces. The recent trend for elucidate the fixed point via inertial iterative algorithm, in which next iterative depends on more than one previous terms. The purpose of the paper is to establish convergence theorems of new inertial Picard normal S-iteration algorithm for nonexpansive mapping in Hilbert spaces. The comparison of convergence of InerNSP and InerPNSP is done with InerSP (introduced by Phon-on et al. [25]) and MSP (introduced by Suparatulatorn et al. [27]) via numerical example.

SVC 멀티캐스트 메커니즘에 관한 설계 (A Design of SVC Multicast Mechanism)

  • 고휘;이형옥;곽용완;남지승
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2011년도 추계학술발표대회
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    • pp.573-576
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    • 2011
  • Research on 4A(Any-time, Any-where, Any-device, Any-contents) services for the next-generation multimedia services is developed with the trend of the integration of wire and wireless networks and the convergence of telecommunications and broadcasting. In this paper we proposed a design of SVC(Scalable Video Coding) overlay multicast mechanism which can provide typical next-generation multimedia services such as SVC streaming. A novel overlay multicast algorithm called ACK-Flow tree optimization algorithm is proposed to guarantee SVC streaming with high efficiency.

Ensuring Data Confidentiality and Privacy in the Cloud using Non-Deterministic Cryptographic Scheme

  • John Kwao Dawson;Frimpong Twum;James Benjamin Hayfron Acquah;Yaw Missah
    • International Journal of Computer Science & Network Security
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    • 제23권7호
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    • pp.49-60
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    • 2023
  • The amount of data generated by electronic systems through e-commerce, social networks, and data computation has risen. However, the security of data has always been a challenge. The problem is not with the quantity of data but how to secure the data by ensuring its confidentiality and privacy. Though there are several research on cloud data security, this study proposes a security scheme with the lowest execution time. The approach employs a non-linear time complexity to achieve data confidentiality and privacy. A symmetric algorithm dubbed the Non-Deterministic Cryptographic Scheme (NCS) is proposed to address the increased execution time of existing cryptographic schemes. NCS has linear time complexity with a low and unpredicted trend of execution times. It achieves confidentiality and privacy of data on the cloud by converting the plaintext into Ciphertext with a small number of iterations thereby decreasing the execution time but with high security. The algorithm is based on Good Prime Numbers, Linear Congruential Generator (LGC), Sliding Window Algorithm (SWA), and XOR gate. For the implementation in C, thirty different execution times were performed and their average was taken. A comparative analysis of the NCS was performed against AES, DES, and RSA algorithms based on key sizes of 128kb, 256kb, and 512kb using the dataset from Kaggle. The results showed the proposed NCS execution times were lower in comparison to AES, which had better execution time than DES with RSA having the longest. Contrary, to existing knowledge that execution time is relative to data size, the results obtained from the experiment indicated otherwise for the proposed NCS algorithm. With data sizes of 128kb, 256kb, and 512kb, the execution times in milliseconds were 38, 711, and 378 respectively. This validates the NCS as a Non-Deterministic Cryptographic Algorithm. The study findings hence are in support of the argument that data size does not determine the execution.