• Title/Summary/Keyword: Multi-objectives

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Knee-driven many-objective sine-cosine algorithm

  • Hongxia, Zhao;Yongjie, Wang;Maolin, Li
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.2
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    • pp.335-352
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    • 2023
  • When solving multi-objective optimization problems, the blindness of the evolution direction of the population gradually emerges with the increase in the number of objectives, and there are also problems of convergence and diversity that are difficult to balance. The many- objective optimization problem makes some classic multi-objective optimization algorithms face challenges due to the huge objective space. The sine cosine algorithm is a new type of natural simulation optimization algorithm, which uses the sine and cosine mathematical model to solve the optimization problem. In this paper, a knee-driven many-objective sine-cosine algorithm (MaSCA-KD) is proposed. First, the Latin hypercube population initialization strategy is used to generate the initial population, in order to ensure that the population is evenly distributed in the decision space. Secondly, special points in the population, such as nadir point and knee points, are adopted to increase selection pressure and guide population evolution. In the process of environmental selection, the diversity of the population is promoted through diversity criteria. Through the above strategies, the balance of population convergence and diversity is achieved. Experimental research on the WFG series of benchmark problems shows that the MaSCA-KD algorithm has a certain degree of competitiveness compared with the existing algorithms. The algorithm has good performance and can be used as an alternative tool for many-objective optimization problems.

Depth tracking of occluded ships based on SIFT feature matching

  • Yadong Liu;Yuesheng Liu;Ziyang Zhong;Yang Chen;Jinfeng Xia;Yunjie Chen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.4
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    • pp.1066-1079
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    • 2023
  • Multi-target tracking based on the detector is a very hot and important research topic in target tracking. It mainly includes two closely related processes, namely target detection and target tracking. Where target detection is responsible for detecting the exact position of the target, while target tracking monitors the temporal and spatial changes of the target. With the improvement of the detector, the tracking performance has reached a new level. The problem that always exists in the research of target tracking is the problem that occurs again after the target is occluded during tracking. Based on this question, this paper proposes a DeepSORT model based on SIFT features to improve ship tracking. Unlike previous feature extraction networks, SIFT algorithm does not require the characteristics of pre-training learning objectives and can be used in ship tracking quickly. At the same time, we improve and test the matching method of our model to find a balance between tracking accuracy and tracking speed. Experiments show that the model can get more ideal results.

Weight Adjustment Scheme Based on Hop Count in Q-routing for Software Defined Networks-enabled Wireless Sensor Networks

  • Godfrey, Daniel;Jang, Jinsoo;Kim, Ki-Il
    • Journal of information and communication convergence engineering
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    • v.20 no.1
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    • pp.22-30
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    • 2022
  • The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

Nutrient regime, N:P ratios and suspended solids as key factors influencing fish tolerance, trophic compositions, and stream ecosystem health

  • Kim, Seon-Young;An, Kwang-Guk
    • Journal of Ecology and Environment
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    • v.38 no.4
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    • pp.505-515
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    • 2015
  • The objectives of this study were to determine the effects of stream nutrient regime, N:P ratios and suspended solids on fish tolerance/trophic compositions and stream ecosystem health, based on multi-metric model, during 2008-2013. Also, stream ecosystem health was evaluated in relation to chlorophyll-a (CHL) as a measure of algal productivity or indicators of trophic state to water chemical parameters. Total number of sampled fish species were 50 and showed a decreasing trend from 2008 to 2013. The minnow of Zacco platypus, based on the catch per unit effort (CPUE), was the most dominant species (25.9%) among the all species. Spatial heterogeneity was evident in the fish tolerance guilds that showed the dominance of sensitive species (89%) in the headwaters (S1) and the dominance of tolerant species (57%) in the urban. These conditions were directly influenced by concentrations of nutrients and organic matter (COD). The N:P ratios, as a barometer of water pollution, had a negative linear function (R2 = 0.40, P < 0.01) with CHL, and the ratios had an important role in changes of COD concentration (R2 = 0.40, P < 0.01). Under the circumstances, the N:P ratio directly influenced the relative proportions of fish trophic/tolerance compositions. According to the regression analysis of omnivore (Om) and insectivore sp. (In) on total nitrogen and total phosphorus, nitrogen had no significant influences (P > 0.05) to the two compositions, but phosphorus influenced directly the two guilds [slope (a) = -32.3, R2 = 0.25, P < 0.01 in the In; a = 40.7, R2 = 0.19, P < 0.01 in the Om]. Such water chemistry and fish trophic guilds determined the stream ecosystem health, based on the multi-metric fish model.

A Study for Storage Reallocation of Multipurpose Reservoir(I) - Flood Control Storage Analysis (다목적댐 용량 재할당에 대한 연구(I)- 치수용량 분석)

  • Yi, Jae-Eung;Kwon, Yong-Ik;Yoon, Young-Nam;Ahn, Tae-Jin
    • Journal of Korea Water Resources Association
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    • v.37 no.4
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    • pp.273-281
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    • 2004
  • Generally, reservoir storage is allocated according to planned purposes established before construction and operating policies are established through release control. The established reservoir allocation is hardly changed unless the special cases such as raising dam or changed purposes occur It Is, however, likely that public needs and objectives can be changed as time go on, the study for multipurpose reservoir storage reallocation is performed as an alternative to reflect these. In this study, flood control analysis is performed for several alternatives of reallocation for the Daechung multi-purpose reservoir in Geum river. As a result, it is confirmed that flood control capability is not decreased compared to single operation of Daechung reservoir for the same flood condition even if conservation level of Daechung multi-purpose reservoir is increased.

Data Cleaning and Integration of Multi-year Dietary Survey in the Korea National Health and Nutrition Examination Survey (KNHANES) using Database Normalization Theory (데이터베이스 정규화 이론을 이용한 국민건강영양조사 중 다년도 식이조사 자료 정제 및 통합)

  • Kwon, Namji;Suh, Jihye;Lee, Hunjoo
    • Journal of Environmental Health Sciences
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    • v.43 no.4
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    • pp.298-306
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    • 2017
  • Objectives: Since 1998, the Korea National Health and Nutrition Examination Survey (KNHANES) has been conducted in order to investigate the health and nutritional status of Koreans. The food intake data of individuals in the KNHANES has also been utilized as source dataset for risk assessment of chemicals via food. To improve the reliability of intake estimation and prevent missing data for less-responded foods, the structure of integrated long-standing datasets is significant. However, it is difficult to merge multi-year survey datasets due to ineffective cleaning processes for handling extensive numbers of codes for each food item along with changes in dietary habits over time. Therefore, this study aims at 1) cleaning the process of abnormal data 2) generation of integrated long-standing raw data, and 3) contributing to the production of consistent dietary exposure factors. Methods: Codebooks, the guideline book, and raw intake data from KNHANES V and VI were used for analysis. The violation of the primary key constraint and the $1^{st}-3rd$ normal form in relational database theory were tested for the codebook and the structure of the raw data, respectively. Afterwards, the cleaning process was executed for the raw data by using these integrated codes. Results: Duplication of key records and abnormality in table structures were observed. However, after adjusting according to the suggested method above, the codes were corrected and integrated codes were newly created. Finally, we were able to clean the raw data provided by respondents to the KNHANES survey. Conclusion: The results of this study will contribute to the integration of the multi-year datasets and help improve the data production system by clarifying, testing, and verifying the primary key, integrity of the code, and primitive data structure according to the database normalization theory in the national health data.

Effects of Jungsongouhyul Herbal Acupuncture(JSO) Multi-treatment for Whiplash Injury by Traffic Accident (중성어혈약침(中性瘀血藥鍼) 복합치료(複合治療)가 교통사고로 인한 경추 편타손상에 미치는 영향)

  • Seol, Hyun;Song, Beom-Ryong;Sin, Min-Seop;Yook, Tae-Han
    • Journal of Pharmacopuncture
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    • v.8 no.1
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    • pp.59-65
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    • 2005
  • Objectives : To examine the effects of JSO multi-treatment for whiplash injury patients by traffic accident. Interventions : Nonrandomized, Nonblinded compartson of the JSO+Acupuncture and Acupuncture Treatment. Main Outcome Measures : Subjective evaluation was followed by Clinical Grade and VAS after 5 times treatments. The SPSS 10.0 for windows was used to analyze the date and the Wilcoxon signed rank test and Mann-Whitney U-testwere used to verify the results. Results : The following results were obtained ; 1. Clinical Grade of the JSO+Acupuncture treatment was centralized to Gr II(50%) before treatment. After 5 times treatments, it was centralized to Gr I(58.3%). Also Clinical Grade was significantly changed from GR ll to Gr I(p<0.0002). 2. Clinical Grade of the Acupuncture treatment was centralize(d) to Gr II(54.2%) before treament. After 5 times treament, it was tend to cenualize to Gr I(50%). But Clinical Grade was still remained at Gr II(p<0.001) 3. VAS of change between JSO+Acupuncture and Acupuncture treatment, Vas of JSO+Acupuncture was significantly decreased (p<0.003). C onclusion : It is suggested that JSO multi-treatment has development-effectiveness on whiplash injury patients by traffic accident.

Factors Affecting Public Prejudice and Social Distance on Mental Illness: Analysis of Contextual Effect by Multi-level Analysis

  • Jang, Hyeon-Gap;Lim, Jun-Tae;Oh, Ju-Hwan;Lee, Seon-Young;Kim, Yong-Ik;Lee, Jin-Seok
    • Journal of Preventive Medicine and Public Health
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    • v.45 no.2
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    • pp.90-97
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    • 2012
  • Objectives: While there have been many quantitative studies on the public's attitude towards mental illnesses, it is hard to find quantitative study which focused on the contextual effect on the public's attitude. The purpose of this study was to identify factors that affect the public's beliefs and attitudes including contextual effects. Methods: We analyzed survey on the public's beliefs and attitudes towards mental illness in Korea with multi-level analysis. We analyzed the public's beliefs and attitudes in terms of prejudice as an intermediate outcome and social distance as a final outcome. Then, we focused on the associations of factors, which were individual and regional socioeconomic factors, familiarity, and knowledge based on the comparison of the intermediate and final outcomes. Results: Prejudice was not explained by regional variables but was only correlated with individual factors. Prejudice increased with age and decreased by high education level. However, social distance controlling for prejudice increased in females, in people with a high education level, and in regions with a high education level and a high proportion of the old. Therefore, social distance without controlling for prejudice increased in females, in the elderly, in highly educated people, and in regions with a high education and aged community. Conclusions: The result of the multi-level analysis for the regional variables suggests that social distance for mental illness are not only determined by individual factors but also influenced by the surroundings so that it could be tackled sufficiently with appropriate considering of the relevant regional context with individual characteristics.

Application of Model-Based Systems Engineering to Large-Scale Multi-Disciplinary Systems Development (모델기반 시스템공학을 응용한 대형복합기술 시스템 개발)

  • Park, Joong-Yong;Park, Young-Won
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.8
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    • pp.689-696
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    • 2001
  • Large-scale Multi-disciplinary Systems(LMS) such as transportation, aerospace, defense etc. are complex systems in which there are many subsystems, interfaces, functions and demanding performance requirements. Because many contractors participate in the development, it is necessary to apply methods of sharing common objectives and communicating design status effectively among all of the stakeholders. The processes and methods of systems engineering which includes system requirement analysis; functional analysis; architecting; system analysis; interface control; and system specification development provide a success-oriented disciplined approach to the project. This paper shows not only the methodology and the results of model-based systems engineering to Automated Guided Transit(AGT) system as one of LMS systems, but also propose the extension of the model-based tool to help manage a project by linking WBS (Work Breakdown Structure), work organization, and PBS (Product Breakdown Structure). In performing the model-based functional analysis, the focus was on the operation concept of an example rail system at the top-level and the propulsion/braking function, a key function of the modern automated rail system. The model-based behavior analysis approach that applies a discrete-event simulation method facilitates the system functional definition and the test and verification activities. The first application of computer-aided tool, RDD-100, in the railway industry demonstrates the capability to model product design knowledge and decisions concerning key issues such as the rationale for architecting the top-level system. The model-based product design knowledge will be essential in integrating the follow-on life-cycle phase activities. production through operation and support, over the life of the AGT system. Additionally, when a new generation train system is required, the reuse of the model-based database can increase the system design productivity and effectiveness significantly.

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Control of Smart Base-isolated Benchmark Building using Fuzzy Supervisory Control (퍼지관리제어기법을 이용한 스마트 면진 벤치마크 건물의 제어)

  • Kim, Hyun-Su;Roschke P. N.
    • Journal of the Earthquake Engineering Society of Korea
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    • v.9 no.4 s.44
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    • pp.55-66
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    • 2005
  • The effectiveness of fuzzy supervisory control technique for the control of seismic responses of smart base isolation system is investigated in this study. To this end, first generation base isolated building benchmark problem is employed for the numerical simulation. The benchmark structure under consideration is an eight-story base isolated building having irregular plan and is equipped with low-damping elastometric bearings and magnetorheological (MR) dampers for seismic protection. Lower level fuzzy logic controllers (FLC) for far-fault or near-fault earthquakes are developed in order to effectively control base isolated building using multi-objective genetic algorithm. Four objectives, i.e. reduction of peak structural acceleration, peak base drift, RMS structural acceleration and RMS base drift, are used in multi-objective optimization process. When earthquakes are applied to benchmark building, each of low level FLCs provides different command voltage and supervisory fuzzy controller combines two command voltages io one based on fuzzy inference system in real time. Results from the numerical simulations demonstrate that base drift as well as superstructure responses can be effectively reduced using the proposed supervisory fuzzy control technique.