• Title/Summary/Keyword: multiple-decision method

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Iterative Phase estimation based on Turbo code (터보부호를 이용한 반복 위상 추정기법)

  • Ryu, Joong-Gon;Heo, Jun
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.43 no.12 s.354
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    • pp.1-8
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    • 2006
  • In this paper, we propose carrier phase synchronization algorithm which are base on turbo coded system for DVB-RCS. There have been two categories of phase estimator, single estimator outside turbo code decoder and multiple estimators inside turbo code decoder. In single estimator, we use the estimation algorithm that ML(Maximum Likelihood) and LMS(Least Mean Square), also three different soft decision methods are proposed. Multiple estimator apply PSP(Per Survivor Processing) algorithm additionally. We compared performance between single estimator and Multiple estimator in AWGN channel. We presented the two methods of PSP algorithm for performance elevation. First is the Bi-directional channel estimation and second is binding method.

Optimum Turbo Equalization Method based on Layered Space Time Codes in Underwater Communications (MIMO 수중통신에서 최적의 터보 등화 기법)

  • Kim, Tae-Hun;Jung, Ji-Won
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.5
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    • pp.1042-1050
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    • 2014
  • The performance of underwater acoustic(UWA) communication system is sensitive to the Inter-Symbol Interference(ISI) due to delay spread develop of multipath signal propagation. And due to limited frequency using acoustic wave, UWA is a low transmission rate. Thus, it is necessary technique of Space-time code, equalizer and channel code to improve transmission speed and eliminate ISI. In this paper, UWA communication system were analyzed by simulation using these techniques. In the result of simulation, the proposed Turbo Equalization method based on layered Space Time Codes has improved performance compared to conventional UWA communication.

Data anomaly detection for structural health monitoring of bridges using shapelet transform

  • Arul, Monica;Kareem, Ahsan
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.93-103
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    • 2022
  • With the wider availability of sensor technology through easily affordable sensor devices, several Structural Health Monitoring (SHM) systems are deployed to monitor vital civil infrastructure. The continuous monitoring provides valuable information about the health of the structure that can help provide a decision support system for retrofits and other structural modifications. However, when the sensors are exposed to harsh environmental conditions, the data measured by the SHM systems tend to be affected by multiple anomalies caused by faulty or broken sensors. Given a deluge of high-dimensional data collected continuously over time, research into using machine learning methods to detect anomalies are a topic of great interest to the SHM community. This paper contributes to this effort by proposing a relatively new time series representation named "Shapelet Transform" in combination with a Random Forest classifier to autonomously identify anomalies in SHM data. The shapelet transform is a unique time series representation based solely on the shape of the time series data. Considering the individual characteristics unique to every anomaly, the application of this transform yields a new shape-based feature representation that can be combined with any standard machine learning algorithm to detect anomalous data with no manual intervention. For the present study, the anomaly detection framework consists of three steps: identifying unique shapes from anomalous data, using these shapes to transform the SHM data into a local-shape space and training machine learning algorithms on this transformed data to identify anomalies. The efficacy of this method is demonstrated by the identification of anomalies in acceleration data from an SHM system installed on a long-span bridge in China. The results show that multiple data anomalies in SHM data can be automatically detected with high accuracy using the proposed method.

OLAP4R: A Top-K Recommendation System for OLAP Sessions

  • Yuan, Youwei;Chen, Weixin;Han, Guangjie;Jia, Gangyong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.6
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    • pp.2963-2978
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    • 2017
  • The Top-K query is currently played a key role in a wide range of road network, decision making and quantitative financial research. In this paper, a Top-K recommendation algorithm is proposed to solve the cold-start problem and a tag generating method is put forward to enhance the semantic understanding of the OLAP session. In addition, a recommendation system for OLAP sessions called "OLAP4R" is designed using collaborative filtering technique aiming at guiding the user to find the ultimate goals by interactive queries. OLAP4R utilizes a mixed system architecture consisting of multiple functional modules, which have a high extension capability to support additional functions. This system structure allows the user to configure multi-dimensional hierarchies and desirable measures to analyze the specific requirement and gives recommendations with forthright responses. Experimental results show that our method has raised 20% recall of the recommendations comparing the traditional collaborative filtering and a visualization tag of the recommended sessions will be provided with modified changes for the user to understand.

Multiple-Shot Person Re-identification by Features Learned from Third-party Image Sets

  • Zhao, Yanna;Wang, Lei;Zhao, Xu;Liu, Yuncai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.2
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    • pp.775-792
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    • 2015
  • Person re-identification is an important and challenging task in computer vision with numerous real world applications. Despite significant progress has been made in the past few years, person re-identification remains an unsolved problem. This paper presents a novel appearance-based approach to person re-identification. The approach exploits region covariance matrix and color histograms to capture the statistical properties and chromatic information of each object. Robustness against low resolution, viewpoint changes and pose variations is achieved by a novel signature, that is, the combination of Log Covariance Matrix feature and HSV histogram (LCMH). In order to further improve re-identification performance, third-party image sets are utilized as a common reference to sufficiently represent any image set with the same type. Distinctive and reliable features for a given image set are extracted through decision boundary between the specific set and a third-party image set supervised by max-margin criteria. This method enables the usage of an existing dataset to represent new image data without time-consuming data collection and annotation. Comparisons with state-of-the-art methods carried out on benchmark datasets demonstrate promising performance of our method.

Design of Mixed Integer Linear Programming Model for Transportation Planning (혼합 정수 선형 계획법을 이용한 수송 계획 모델 설계)

  • Park, Yong Kuk;Lee, Min Goo;Jung, Kyung Kwon;Won, Young-Jin
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.11
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    • pp.166-174
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    • 2016
  • In this paper, we developed a mixed-integer linear programming model for transportation planning of athletes in sports events. The transportation planning of athletes involves finding the lowest-cost and fastest-time plan for distributing athletes from multiple accommodation to stadium. The decision variables associate with the number of driving events, and the total transportation cost is the objective function that needs to be minimized. The proposed method uses mixed integer linear programming to solve transportation problem, thus the global optimality is guaranteed. In order to verify the effectiveness of proposed method, we performed simulation and built the sports event management service platform (SEMSP) for transportation planning.

An Optimization Approach to the Construction of a Sequence of Benchmark Targets in DEA-Based Benchmarking (DEA 기반 벤치마킹에서의 효율성 개선 경로 선정을 위한 최적화 접근법에 관한 연구)

  • Park, Jaehun;Lim, Sungmook;Bae, Hyerim
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.6
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    • pp.628-641
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    • 2014
  • Stepwise efficiency improvement in data envelopment analysis (DEA)-based benchmarking is a realistic and effective method by which inefficient decision making units (DMUs) can choose benchmarks in a stepwise manner and, thereby, effect gradual performance improvement. Most of the previous research relevant to stepwise efficiency improvement has focused primarily on how to stratify DMUs into multiple layers and how to select immediate benchmark targets in leading levels for lagging-level DMUs. It can be said that the sequence of benchmark targets was constructed in a myopic way, which can limit its effectiveness. To address this issue, this paper proposes an optimization approach to the construction of a sequence of benchmarks in DEA-based benchmarking, wherein two optimization criteria are employed : similarity of input-output use patterns, and proximity of input-output use levels between DMUs. To illustrate the proposed method, we applied it to the benchmarking of 23 national universities in South Korea.

A Combined DEA-BSC methodology for evaluating organizational efficiency (DEA와 BSC 기법을 이용한 조직 효율성 비교에 대한 연구)

  • Kim Bum-Soo;Chang Tai-Woo;Shin Ki-Tae;Park Jin-Woo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.28 no.2
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    • pp.18-26
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    • 2005
  • The balanced scorecard(BSC) overcomes the limit of traditional financial statement that focuses on only financial performance. BSC is widely used in government and industry because of the clear representation of the relationship and logic between the key performance indicators(KPI) of 4 perspectives - financial, customer, internal process, and loaming and growth. However, traditional BSC does not consider evaluating the difference between the results measured by BSC. By using relatively small number of inputs and outputs In comparing decision-making units, data envelopment analysis(DEA) can aggregate multiple performance measures. In this research, we propose a methodology named CDB(Combined DEA and BSC) to evaluate the performance of organization considering financial and non-financial perspectives. CDB uses KPI of cause-and-effect relationship on BSC as inputs and outputs of DEA method. In addition, this research proposes a method of converting the KPI of BSC to the input and output variables of DEA, and enhancing discrimination power using the limit number of variables. We illustrate the methodology by giving an example of evaluating aquisition-unit efficiency in a supply chain.

A Study on the Sound Quality of Passenger Cars (자동차 실내 소음의 음질 연구)

  • 김정우;최종대;허정기;변언섭
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1998.04a
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    • pp.94-101
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    • 1998
  • This paper presents the psychoacoustic analyses on the vehicle interior, noise generated when accelerating. Following the objective quantification for vehicle noises of different classes, the subjective decision process by the jury test is adopted to interrelate these results based on two different approaches. In particular, the paired comparison method is employed in assessing the sound quality in terms of the quietness, the powerfulness, and the pleasantness of the human auditory sensation. Special attention is paid to the physical interpretation of psychoacoutic parameters and their interrelation to the subjective assessment scores. In order to ensure the integrity of statistics of the survey, various tests are performed. The results show that the consistency of the "quiet" sensation is far higher than that of the "powerful" and the "pleasant" sensations. Also, it is found that the most significant parameter determining these feelings turns out to be the inherent loudness of the noise instead of the conventional indicators such as the weighted sound pressure level. It may be concluded that the psychoacoustic analysis offers more realistic evaluation for vehicle noise and assists the improvement of NVH more efficiently.ement of NVH more efficiently.

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An interactive and iterative control panel layout

  • 박성준;정의승;조항준
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1994.04a
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    • pp.103-111
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    • 1994
  • An interactive and iterative design method based on the constraint satisfaction problem (CSP) technique was developed to generate an ergonomically sound layout of a control panel. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constraints, and generate an optimal or, at least, a "satisfactory" solution through iterative interactions with the designer. The existing panel design and layout methods are mostly based on the optimization of single objective function formulated to reflect and trade off all ergonomic design objectives which are largely different in their nature. In fact, the problem of seeking an ergonomically sound panel design should be viewed as a multiple objective optimization problem. Furthermore, most of the design objectives should be understood as constraints rather than objectives to be optimized. Hence, a constraint satisfaction approach is proposed in this study as a framework for the panel designer to search through the design decision space effectively and make various design decisions iteratively. In order to apply the constraint satisfaction approach to the panel design procedure, the ergonomic principles such as frequency-of-use, importance, functional grouping, and sequence-of-use are formalized as CSP terms. With this formalization, a prototype system was implemented and applied to panel layout problems. The results clearly showed the effectiveness of the proposed approach since it permits designers to consider and iteratively evaluate various design constraints and ergonomic principles, and, therefore, aids the panel designer to come up with an ergonomically sound control panel layout.