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Efficient LDPC-Based, Threaded Layered Space-Time-Frequency System with Iterative Receiver

  • Hu, Junfeng;Zhang, Hailin;Yang, Yuan
    • ETRI Journal
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    • v.30 no.6
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    • pp.807-817
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    • 2008
  • We present a low-density parity-check (LDPC)-based, threaded layered space-time-frequency system with emphasis on the iterative receiver design. First, the unbiased minimum mean-squared-error iterative-tree-search (U-MMSE-ITS) detector, which is known to be one of the most efficient multi-input multi-output (MIMO) detectors available, is improved by augmentation of the partial-length paths and by the addition of one-bit complement sequences. Compared with the U-MMSE-ITS detector, the improved detector provides better detection performance with lower complexity. Furthermore, the improved detector is robust to arbitrary MIMO channels and to any antenna configurations. Second, based on the structure of the iterative receiver, we present a low-complexity belief-propagation (BP) decoding algorithm for LDPC-codes. This BP decoder not only has low computing complexity but also converges very fast (5 iterations is sufficient). With the efficient receiver employing the improved detector and the low-complexity BP decoder, the proposed system is a promising solution to high-data-rate transmission over selective-fading channels.

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An Object Recognition Method Based on Depth Information for an Indoor Mobile Robot (실내 이동로봇을 위한 거리 정보 기반 물체 인식 방법)

  • Park, Jungkil;Park, Jaebyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.10
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    • pp.958-964
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    • 2015
  • In this paper, an object recognition method based on the depth information from the RGB-D camera, Xtion, is proposed for an indoor mobile robot. First, the RANdom SAmple Consensus (RANSAC) algorithm is applied to the point cloud obtained from the RGB-D camera to detect and remove the floor points. Next, the removed point cloud is classified by the k-means clustering method as each object's point cloud, and the normal vector of each point is obtained by using the k-d tree search. The obtained normal vectors are classified by the trained multi-layer perceptron as 18 classes and used as features for object recognition. To distinguish an object from another object, the similarity between them is measured by using Levenshtein distance. To verify the effectiveness and feasibility of the proposed object recognition method, the experiments are carried out with several similar boxes.

A performance improvement methodology of web document clustering using FDC-TCT (FDC-TCT를 이용한 웹 문서 클러스터링 성능 개선 기법)

  • Ko, Suc-Bum;Youn, Sung-Dae
    • The KIPS Transactions:PartD
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    • v.12D no.4 s.100
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    • pp.637-646
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    • 2005
  • There are various problems while applying classification or clustering algorithm in that document classification which requires post processing or classification after getting as a web search result due to my keyword. Among those, two problems are severe. The first problem is the need to categorize the document with the help of the expert. And, the second problem is the long processing time the document classification takes. Therefore we propose a new method of web document clustering which can dramatically decrease the number of times to calculate a document similarity using the Transitive Closure Tree(TCT) and which is able to speed up the processing without loosing the precision. We also compare the effectivity of the proposed method with those existing algorithms and present the experimental results.

Video Indexing using Motion vector and brightness features (움직임 벡터와 빛의 특징을 이용한 비디오 인덱스)

  • 이재현;조진선
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.4
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    • pp.27-34
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    • 1998
  • In this paper we present a method for automatic motion vector and brightness based video indexing and retrieval. We extract a representational frame from each shot and compute some motion vector and brightness based features. For each R-frame we compute the optical flow field; motion vector features are then derived from this flow field, BMA(block matching algorithm) is used to find motion vectors and Brightness features are related to the cut detection of method brightness histogram. A video database provided contents based access to video. This is achieved by organizing or indexing video data based on some set of features. In this paper the index of features is based on a B+ search tree. It consists of internal and leaf nodes stores in a direct access a storage device. This paper defines the problem of video indexing based on video data models.

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Hardware design of the MPEG-2 AAC Decoder Module (MPEG-2 AAC 복호화기 모들의 하드웨어 설계)

  • 우광희;김수현;홍민철;차형태
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.1
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    • pp.113-118
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    • 2001
  • In this paper, we implement modules of the MPEG-2 AAC decoder using VHDL. Tools of Huffman decoder, inverse quantizer and high-density filter bank which are necessary for the AAC decoder. We designed the high speed Huffman decoder using the method of octal tree search algorithm, and reduced computational time of filter bank using IFFT. Also, we use table of computation result for an exponential calculation of Inverse quantizer in fixed-point hardware, and reduced the size of table using linear interpolation. Modules implemented by hardware through optimization work in real time at low clock frequency are possible to reduce the system size.

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Content-based Image Retrieval System (내용기반 영상검색 시스템)

  • Yoo, Hun-Woo;Jang, Dong-Sik;Jung, She-Hwan;Park, Jin-Hyung;Song, Kwang-Seop
    • Journal of Korean Institute of Industrial Engineers
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    • v.26 no.4
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    • pp.363-375
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    • 2000
  • In this paper we propose a content-based image retrieval method that can search large image databases efficiently by color, texture, and shape content. Quantized RGB histograms and the dominant triple (hue, saturation, and value), which are extracted from quantized HSV joint histogram in the local image region, are used for representing global/local color information in the image. Entropy and maximum entry from co-occurrence matrices are used for texture information and edge angle histogram is used for representing shape information. Relevance feedback approach, which has coupled proposed features, is used for obtaining better retrieval accuracy. Simulation results illustrate the above method provides 77.5 percent precision rate without relevance feedback and increased precision rate using relevance feedback for overall queries. We also present a new indexing method that supports fast retrieval in large image databases. Tree structures constructed by k-means algorithm, along with the idea of triangle inequality, eliminate candidate images for similarity calculation between query image and each database image. We find that the proposed method reduces calculation up to average 92.9 percent of the images from direct comparison.

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Metaheuristic-reinforced neural network for predicting the compressive strength of concrete

  • Hu, Pan;Moradi, Zohre;Ali, H. Elhosiny;Foong, Loke Kok
    • Smart Structures and Systems
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    • v.30 no.2
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    • pp.195-207
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    • 2022
  • Computational drawbacks associated with regular predictive models have motivated engineers to use hybrid techniques in dealing with complex engineering tasks like simulating the compressive strength of concrete (CSC). This study evaluates the efficiency of tree potential metaheuristic schemes, namely shuffled complex evolution (SCE), multi-verse optimizer (MVO), and beetle antennae search (BAS) for optimizing the performance of a multi-layer perceptron (MLP) system. The models are fed by the information of 1030 concrete specimens (where the amount of cement, blast furnace slag (BFS), fly ash (FA1), water, superplasticizer (SP), coarse aggregate (CA), and fine aggregate (FA2) are taken as independent factors). The results of the ensembles are compared to unreinforced MLP to examine improvements resulted from the incorporation of the SCE, MVO, and BAS. It was shown that these algorithms can considerably enhance the training and prediction accuracy of the MLP. Overall, the proposed models are capable of presenting an early, inexpensive, and reliable prediction of the CSC. Due to the higher accuracy of the BAS-based model, a predictive formula is extracted from this algorithm.

Mining Maximal Frequent Contiguous Sequences in Biological Data Sequences (생물학적 데이터 서열들에서 빈번한 최대길이 연속 서열 마이닝)

  • Kang, Tae-Ho;Yoo, Jae-Soo
    • The KIPS Transactions:PartD
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    • v.15D no.2
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    • pp.155-162
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    • 2008
  • Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of 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 dataset 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 the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.

Proposal of USN Configuratation and Routing Scheme Inside a Ship (선박 내 센서 노드 구성 및 라우팅 제안)

  • Lee, Seong Ro;Jeong, Min-A;Kim, Yeongeun;Min, Sang-Won
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.8
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    • pp.660-666
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    • 2014
  • In this paper, we consider a classification criteria of sensor nodes based on equipment function, and propose a routing search algorithm between node when an IP-USN is applied inside a ship. whereas a tree-type routing algorithm is applied to the limited mobile enviroment, such as engine room or machine room, a mesh-type routing alogrithm is to free mobile enviroment, such as passager corridor liviing quarters or restanrats areas. For mesh-type routing, it is necessary to maintain a seamless route path between a sink node and sensor nodes for which we consider a novel message exchange periodically. We proposed a new message, RDES message, which is issued periodically to update the topology of sensor node and check a connectivity between nodes.

An Empirical Study on the Quality Reliability of the Start-up performance of the Fixed Wing Aircraft at low temperature (고정익 항공기 저온 시동 성능의 품질 신뢰성 향상에 관한 실증적 연구)

  • Kim, DW;Jeong, SH
    • Journal of Korean Society for Quality Management
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    • v.46 no.1
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    • pp.169-188
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    • 2018
  • Purpose: The purpose of this study is to analyze low-temperature starting performance of the light attacker and to search and improve the aircraft system including battery and Battery Charge and Control Unit(BCCU). Methods: In order to improve the starting up performance of the light attacker at low-temp, various deficiency cause were derived and analyzed using Fault Tree Analysis method. As a result, it was confirmed there were drawbacks in the charging and discharging mechanism of the battery. The inactivation of the battery's electrolyte at low-temp and the premature termination of the battery charge were the main cause. After long error and trial, we improved these problems by improving performance of battery and optimizing the charging algorithm of BCCU. Results: It was confirmed that the problems of starting up failures were solved through the combined performance test of the battery and BCCU, the ground test using the aircraft system and the operation test conducted by Korea Airforce operating unit for 3 months in winter. Conclusion: This study showed that the improvement of quality reliability was achieved and thus the start-up performance issue of the light attacker has been resolved at low temperature. And it is expected that the design methodologies of temperature-affected electrical system of aircraft will contribute to the development of the aircraft industry in the future.