• Title/Summary/Keyword: pattern search method

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An Efficient Search Strategy of Anti-Submarine Helicopter based on Multi-Static Operation in Furthest-On-Circles (확장형 탐색구역에서 Multi-Static 운용 기반 대잠헬기의 탐색에 관한 연구)

  • Kim, Changhyun;Oh, Rahgeun;Kim, Sunhyo;Choi, Jeewoong;Ma, Jungmok
    • Journal of the Korea Institute of Military Science and Technology
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    • v.21 no.6
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    • pp.877-885
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    • 2018
  • The anti-submarine helicopter is the most effective weapon system in anti-submarine warfare. Recently changes in the introduction of the anti-submarine warfare sonar system are expected to operate multi-static sonar equipment of the anti-submarine helicopter. Therefore, it is required to study the operational concept of multi-static of anti-submarine helicopter. This paper studies on the optimal search of multi-static based on anti-submarine helicopter considering Furthest On Circles(FOC). First, the deployment of the sensors of the anti-submarine helicopter is optimized using genetic algorithms. Then, the optimized model is extended to consider FOC. Finally, the proposed model is verified by comparing pattern-deployment the search method in Korean Navy.

Statistical Radial Basis Function Model for Pattern Classification (패턴분류를 위한 통계적 RBF 모델)

  • Choi Jun-Hyeog;Rim Kee-Wook;Lee Jung-Hyun
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.41 no.1
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    • pp.1-8
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    • 2004
  • According to the development of the Internet and the pervasion of Data Base, it is not easy to search for necessary information from the huge amounts of data. In order to do efficient analysis of a large amounts of data, this paper proposes a method for pattern classification based on the effective strategy for dimension reduction for narrowing down the whole data to what users wants to search for. To analyze data effectively, Radial Basis Function Networks based on VC-dimension of Support Vector Machine, a model of statistical teaming, is proposed in this paper. The model of Radial Basis Function Networks currently used performed the preprocessing of Perceptron model whereas the model proposed in this paper, performing independent analysis on VD-dimension, classifies each datum putting precise labels on it. The comparison and estimation of various models by using Machine Learning Data shows that the model proposed in this paper proves to be more efficient than various sorts of algorithm previously used.

An Efficient Search Method for High Confidence Association Rules Using CP(Confidence Pattern)-Tree Structure (CP-Tree구조를 이용한 높은 신뢰도를 갖는 연관 규칙의 효율적 탐색 방법)

  • 송한규;김재련
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.25 no.1
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    • pp.1-8
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    • 2002
  • The traditional approaches of association rule mining have relied on high support condition to find interesting rules. However, in some application such as analyzing the web page link and discovering some unusual combinations of some factors that have always caused some disease, we are interested in rules with high confidence that have very low support or need not have high support. In these cases, the traditional algorithms are not suitable since it relies on first satisfying high support. In this paper, we propose a new model, CP(Confidence Pattern)-Tree, to identify high confidence rule between 2-items without support constraint. constraint. In addition, we discuss confidence association rule between two more items without support constraint.

A Method to Generate Test Patterns for Scan Designed Logic Circuits under Logic Value Constraints (논리값 제약을 갖는 스캔 설계 회로에서의 자동 시험 패턴 생성)

  • Eun Sei Park
    • Journal of the Korean Institute of Telematics and Electronics A
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    • v.31A no.2
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    • pp.94-103
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    • 1994
  • In testing for practical scan disigned logic circuits, there may exist logic value constraints on some part of primary inputs due to various requirements on design and test. This paper presents a logic value system called taboo logic values which targets the test pattern generation of logic circuits under logic value constraints. The taboo logic system represents the logic value constraints and identifies additional logic value constraints through the implication of the tqaboo logic values using a taboo logic calculus. Those identified logic value constraints will guide the search during the test pattern generation of avoid the unfruitful searches and to identify redundant faults due to the logic value constraints very quickly. Finally, experimental results on ISCAS85 benchmark circuits will demonstrate the efficiency of the taboo logic values.

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Planning ESS Managemt Pattern Algorithm for Saving Energy Through Predicting the Amount of Photovoltaic Generation

  • Shin, Seung-Uk;Park, Jeong-Min;Moon, Eun-A
    • Journal of Integrative Natural Science
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    • v.12 no.1
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    • pp.20-23
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    • 2019
  • Demand response is usually operated through using the power rates and incentives. Demand management based on power charges is the most rational and efficient demand management method, and such methods include rolling base charges with peak time, sliding scaling charges depending on time, sliding scaling charges depending on seasons, and nighttime power charges. Search for other methods to stimulate resources on demand by actively deriving the demand reaction of loads to increase the energy efficiency of loads. In this paper, ESS algorithm for saving energy based on predicting the amount of solar power generation that can be used for buildings with small loads not under electrical grid.

AN EFFICIENT DENSITY BASED ANT COLONY APPROACH ON WEB DOCUMENT CLUSTERING

  • M. REKA
    • Journal of applied mathematics & informatics
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    • v.41 no.6
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    • pp.1327-1339
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    • 2023
  • World Wide Web (WWW) use has been increasing recently due to users needing more information. Lately, there has been a growing trend in the document information available to end users through the internet. The web's document search process is essential to find relevant documents for user queries.As the number of general web pages increases, it becomes increasingly challenging for users to find records that are appropriate to their interests. However, using existing Document Information Retrieval (DIR) approaches is time-consuming for large document collections. To alleviate the problem, this novel presents Spatial Clustering Ranking Pattern (SCRP) based Density Ant Colony Information Retrieval (DACIR) for user queries based DIR. The proposed first stage is the Term Frequency Weight (TFW) technique to identify the query weightage-based frequency. Based on the weight score, they are grouped and ranked using the proposed Spatial Clustering Ranking Pattern (SCRP) technique. Finally, based on ranking, select the most relevant information retrieves the document using DACIR algorithm.The proposed method outperforms traditional information retrieval methods regarding the quality of returned objects while performing significantly better in run time.

A Parametric Study of Displacement Measurements Using Digital Image Correlation Method

  • Ha, Kuen-Dong
    • Journal of Mechanical Science and Technology
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    • v.14 no.5
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    • pp.518-529
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    • 2000
  • A detailed and thorough parametric study of digital image correlation method is presented. A theoretical background and development of the method were introduced and the effects of various parameters on the determination of displacement outputs from the raw original and deformed image information were examined. Use of the normalized correlation coefficient, the use of 20 to 40 pixels for a searching window side, 6 variables searching, bi-cubic spline sub pixel interpolations and the use of coarse-fine search are some of the key choices among the results of parametric studies. The displacement outputs can be further processed with two dimensional curve fitting for the data noise reduction as well as displacement gradient calculation.

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Vehicle Detection in Aerial Images Based on Hyper Feature Map in Deep Convolutional Network

  • Shen, Jiaquan;Liu, Ningzhong;Sun, Han;Tao, Xiaoli;Li, Qiangyi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.4
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    • pp.1989-2011
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    • 2019
  • Vehicle detection based on aerial images is an interesting and challenging research topic. Most of the traditional vehicle detection methods are based on the sliding window search algorithm, but these methods are not sufficient for the extraction of object features, and accompanied with heavy computational costs. Recent studies have shown that convolutional neural network algorithm has made a significant progress in computer vision, especially Faster R-CNN. However, this algorithm mainly detects objects in natural scenes, it is not suitable for detecting small object in aerial view. In this paper, an accurate and effective vehicle detection algorithm based on Faster R-CNN is proposed. Our method fuse a hyperactive feature map network with Eltwise model and Concat model, which is more conducive to the extraction of small object features. Moreover, setting suitable anchor boxes based on the size of the object is used in our model, which also effectively improves the performance of the detection. We evaluate the detection performance of our method on the Munich dataset and our collected dataset, with improvements in accuracy and effectivity compared with other methods. Our model achieves 82.2% in recall rate and 90.2% accuracy rate on Munich dataset, which has increased by 2.5 and 1.3 percentage points respectively over the state-of-the-art methods.

Mining Maximal Frequent Contiguous Sequences in Biological Data Sequences

  • Kang, Tae-Ho;Yoo, Jae-Soo;Kim, Hak-Yong;Lee, Byoung-Yup
    • International Journal of Contents
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    • v.3 no.2
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    • pp.18-24
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    • 2007
  • Biological sequences such as DNA and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of more than hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological datasets with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with a fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. The experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

Development of Localization and Pose Compensation for Mobile Robot using Magnetic Landmarks (마그네틱 랜드마크를 이용한 모바일 로봇의 위치 인식 및 위치 보정 기술의 개발)

  • Kim, Bum-Soo;Choi, Byung-June;You, Won-Suk;Moon, Hyung-Pil;Koo, Ja-Choon;Choi, Hyouk-Ryeol
    • The Journal of Korea Robotics Society
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    • v.5 no.3
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    • pp.186-196
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    • 2010
  • In this paper, we present a global localization and position error compensation method in a known indoor environment using magnet hall sensors. In previous our researches, it was possible to compensate the pose errors of $x_e$, $y_e$, ${\theta}_e$ correctly on the surface of indoor environment with magnets sets by regularly arrange the magnets sets of identical pattern. To improve the proposed method, new strategy that can realize the global localization by changing arrangement of magnet pole is presented in this paper. Total six patterns of the magnets set form the unique landmarks. Therefore, the virtual map can be built by using the six landmarks randomly. The robots search a pattern of magnets set by rotating, and obtain the current global pose information by comparing the measured neighboring patterns with the map information that is saved in advance. We provide experimental results to show the effectiveness of the proposed method for a differential drive wheeled mobile robot.