• Title/Summary/Keyword: Hard Decision

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Solving the test resource allocation using variable group genetic algorithm (가변 그룹 유전자알고리즘 기반의 시험자원할당 문제 해결)

  • Mun, Chang-min
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.8
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    • pp.1415-1421
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    • 2016
  • There are considerable concern on the methods for the efficient utilization of the test-resources as increasing of the number of the tests for functionality and performance verification of weapon systems. Furthermore, with an increase in the complexity of the resource assignment the decision support is required. Test resource allocation is basically the same problems as conventional NP-hard FJSP(Flexible Job Shop Problem), therefore empirical test resource allocation method that has been used in many decades is limited in the time performance. Although research has been conducted applying the genetic algorithm to the FJSP, it is limited in the test resource allocation domain in which more than one machine is necessary for a single operation. In this paper, a variable group genetic algorithm is proposed. The algorithm is expected to improve the test plan efficiency by automating and optimizing the existing manual based allocation. The simulation result shows that the algorithm could be applicable to the test plan.

A Study on FTN Decoding Method for High Throughput Satellite Communication (고전송율 위성통신을 위한 FTN 신호 복호 기법 연구)

  • Kwon, Hae-Chan;Jung, Ji-Won
    • Journal of Navigation and Port Research
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    • v.38 no.3
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    • pp.211-216
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    • 2014
  • In this paper, high throughput method is studied to provide floating objects with broadband service as ship by using satellite. In recent, satellite broadcastings standard is based on DVB-S3 for communication service using wireless device on navigation communication by satellite. LDPC codes are iterative coding algorithm proposed in DVB-S3. In this paper, FTN technique is applied to LDPC codes with 8-PSK modulation and then present the method to alleviate performance degradation due to FTN through BICM-ID. BICM-ID is the method to improve performance by calculating a new LLR from hard-decision value of decoder output. DVB-S2 system with 8-PSK modulation and FTN technique based on iterative decoding had a better performance than DVB-S2 with 8-PSK modulation and FTN technique over Gaussian channels.

An Improved Combining of Hard Decisions for Cooperative Spectrum Sensing in Cognitive Radio Systems (무선인지 시스템에서 협력 스팩트럼 센싱 성능 향상을 위한 경판정 결합 기법)

  • Shin, Oh-Soon;Shin, Yo-An
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.2A
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    • pp.132-138
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    • 2009
  • Cognitive radio is considered as a promising solution to scarce spectrum problem. The primary object of cognitive radio is to increase spectral efficiency, while causing limited interference to primary users who are using the spectrum. Hence, an essential part of cognitive radio systems is spectrum sensing which determines whether a particular spectrum is occupied or not by a primary user at a particular time. However, sensing decision of each individual secondary user alone may not be reliable enough due to shadowing and multipath fading of wireless channels. The so called hidden terminal problem makes the problem even worse, possibly yielding undesired interference to the primary users. Recently, cooperative spectrum sensing is emerging as a remedy to these problems of individual sensing. Cooperative sensing allows a group of secondary users to share local sensing information to extract a global decision with high fidelity. In this paper, we investigate a cooperative spectrum sensing algorithm based on hard decisions of local sensing outcomes. Specifically, we propose an effective scheme for combining local decisions by introducing weighting factors that reflect reliability of the corresponding secondary user. Through computer simulations, the performance of the proposed combining scheme is compared with that of the conventional scheme without weighting factors in various environments.

A Soft Demapping Method for 64-APSK in the DVB-S3 System (DVB-S3 시스템의 64-APSK 방식에 대한 연판정 비트 검출 기법)

  • Li, Guowen;Zhang, Meixiang;Kim, Sooyoung
    • Journal of Satellite, Information and Communications
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    • v.9 no.2
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    • pp.23-27
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    • 2014
  • In this paper, we propose a soft demapping method for 64-ary APSK in the DVB-S3 system. The proposed method in this paper uses the hard decision threshold (HDT) line for each constituent bit in a symbol, and calculates the soft bit information with the distance between the HDT line and the detected symbol. If the HDT lines are defined in a simple manner, the complexity to estimate soft information can be largely reduced compared with the maximum likelihood detection (MLD) which has an exponential complexity. By considering this, we first derive HDT lines for each constituent bit for a 64-APSK symbol, and propose a method to calculate soft bit information. We simulate the BER performance of the proposed scheme by using a turbo codes which requires soft-input-soft-output information, and compare it that of the MLD. The result show that the proposed scheme produces approximating performance to MLD with largely reduced complexity.

An Iterative Soft-Decision Decoding Algorithm of Block Codes Using Reliability Values (신뢰도 값을 이용한 블록 부호의 반복적 연판정 복호 알고리즘)

  • Shim, Yong-Geol
    • The KIPS Transactions:PartC
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    • v.11C no.1
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    • pp.75-80
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    • 2004
  • An iterative soft-decision decoding algorithm of block codes is proposed. With careful examinations of the first hard-decision decoding result, the candidate codewords are efficiently searched for. An approach to reducing decoding complexity and lowering error probability is to select a small number of candidate codewords. With high probability, we include the codewords which are at the short distance from the received signal. The decoder then computes the distance to each of the candidate codewords and selects the codeword which is the closest. We can search for the candidate codewords which make the error patterns contain the bits with small reliability values. Also, we can reduce the cases that we select the same candidate codeword already searched for. Computer simulation results are presented for (23,12) Golay code. They show that decoding complexity is considerably reduced and the block error probability is lowered.

The Impact of Performance Information Use and Decision Making on Organization Performance (성과정보 활용행태 및 의사결정 행태가 조직성과에 미치는 영향)

  • Cho, Munseok;Her, Dahye;Eom, Young Ho
    • Journal of Convergence for Information Technology
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    • v.10 no.4
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    • pp.55-64
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    • 2020
  • This research empirically explores the relationship between types of performance information use, decision making behaviors and performance of government organizations. We measured two types of using performance information, relevance of performance index, variety of performance information, and levels of manager intervention by surveying performance managers of each government ministry or agency and also measured performance by using performance reports. The results of fuzzy-set qualitative comparative analysis suggest that hard use and soft use have impact on performance by combining with characteristics of performance information and managers decision-making by intervening performance management processes.

A Development of Wireless Sensor Networks for Collaborative Sensor Fusion Based Speaker Gender Classification (협동 센서 융합 기반 화자 성별 분류를 위한 무선 센서네트워크 개발)

  • Kwon, Ho-Min
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.2
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    • pp.113-118
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    • 2011
  • In this paper, we develop a speaker gender classification technique using collaborative sensor fusion for use in a wireless sensor network. The distributed sensor nodes remove the unwanted input data using the BER(Band Energy Ration) based voice activity detection, process only the relevant data, and transmit the hard labeled decisions to the fusion center where a global decision fusion is carried out. This takes advantages of power consumption and network resource management. The Bayesian sensor fusion and the global weighting decision fusion methods are proposed to achieve the gender classification. As the number of the sensor nodes varies, the Bayesian sensor fusion yields the best classification accuracy using the optimal operating points of the ROC(Receiver Operating Characteristic) curves_ For the weights used in the global decision fusion, the BER and MCL(Mutual Confidence Level) are employed to effectively combined at the fusion center. The simulation results show that as the number of the sensor nodes increases, the classification accuracy was even more improved in the low SNR(Signal to Noise Ration) condition.

Object oriented simulation in a CIM environment

  • 김종수
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1991.10a
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    • pp.67-76
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    • 1991
  • For several years, graduate students and faculty of the Engineering Systems Research Center at U.C., Berkeley have been studying new methods of planning and scheduling in a computer integrated manufacturing environment, with particular emphasis on large scale integrated circuit fabrication. One part of this work, focusing on short interval scheduling, uses simulation models as a primary research tool. We have built two versions of the same basic model (programmed in C) to study two different problems (one deals with machine down time and the other with setup times). These have proven to be efficient for studying particular problems, but are difficult and time consuming to modify. We are convinced that our research will be more effective: (1) if it were easier to build special purpose models tailored to the research question at hand; and (2) if we had better interfaces to graphics output. Commercially available factory simulators are inadequate for this research for a variety of reasons. Existing packages such as SIMKIT, SLAM, SIMAN and EXCELL have their own weaknesses. Typically, they are hard to develop and to modify. They do not allow for adding new dispatching decisions or release decision. Also, it is hard to add more machines to existing environment or change the route the product flows. For these various reasons, we had developed a new simulation package having flexibility and modularity. In this paper, based on experiences gained in the application of object oriented programming, we discuss unique features of the simulator developed in OOPS and ways to take advantage of features in developing and using manufacturing simulation software written in the OOPS

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Spatial Compare Filter Based Real-Time dead Pixel Correction Method for Infrared Camera

  • Moon, Kil-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.21 no.12
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    • pp.35-41
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    • 2016
  • In this paper, we propose a new real-time dead pixel detection method based on spatial compare filtering, which are usually used in the small target detection. Actually, the soft dead and the small target are cast in the same mold. Our proposed method detect and remove the dead pixels as applying the spatial compare filtering, into the pixel outputs of a detector after the non-uniformity correction. Therefore, we proposed method can effectively detect and replace the dead pixels regardless of the non-uniformity correction performance. In infrared camera, there are usually many dead detector pixels which produce abnormal output caused by manufactural process or operational environment. There are two kind of dead pixel. one is hard dead pixel which electronically generate abnormal outputs and other is soft dead pixel which changed and generated abnormal outputs by the planning process. Infrared camera have to perform non-uniformity correction because of structural and material properties of infrared detector. The hard dead pixels whose offset values obtained by non-uniformity correction are much larger or smaller than the average can be detected easily as dead pixels. However, some dead pixels(soft dead pixel) can remain, because of the difficulty of uncleared decision whether normal pixel or abnormal pixel.

Real-time Fall Accident Prediction using Random Forest in IoT Environment (사물인터넷 환경에서 랜덤포레스트를 이용한 실시간 낙상 사고 예측)

  • Chan-Woo Bang;Bong-Hyun Kim
    • Journal of Internet of Things and Convergence
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    • v.10 no.4
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    • pp.27-33
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    • 2024
  • As of 2023, the number of accident victims in the domestic construction industry is 26,829, ranking second only to other businesses (service industries). The accident types of casualties in all industries were falls (29,229 people), followed by falls (14,357 people). Based on the above data, this study attaches sensors to hard hats and insoles to predict fall accidents that frequently occur at construction sites, and proposes smart safety equipment that applies a random forest algorithm based on the data collected through this. The random forest model can determine fall accidents in real time with high accuracy by generating multiple decision trees and combining the predictions of each tree. This model classifies whether a worker has had a fall accident and the type of behavior through data collected from the MPU-6050 sensor attached to the hard hat. Fall accidents that are primarily determined from hard hats are secondarily predicted through sensors attached to the insole, thereby increasing prediction accuracy. It is expected that this will enable rapid response in the event of an accident, thereby reducing worker deaths and accidents.