• Journal of KIISE:Software and Applications
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• v.34 no.11
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• pp.991-1000
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• 2007

A new robust approach to detect vehicles in a single frame of traffic scenes is presented. The method is based on the multi-level shadow classification, which has been shown to have the capability of extracting correct shadow shapes regardless of the operating conditions. The rationale of this classification is supported by the fact that shadow regions underneath vehicles usually exhibit darker gray level regardless of the vehicle brightness and illuminating conditions. Classified shadows provide string clues on the presence of vehicles. Unlike other schemes, neither background nor temporal information is utilized; thereby the performance is robust to the abrupt change of weather and the traffic congestion. By a simple evidential reasoning, the shadow evidences are combined with bright evidences to locate correct position of vehicles. Experimental results show the missing rate ranges form 0.9% to 7.2%, while the false alarm rate is below 4% for six traffic scenes sets under different operating conditions. The processing speed for more than 70 frames per second could be obtained for nominal image size, which makes the real-time implementation of measuring the traffic parameters possible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.11
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• pp.2945-2965
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• 2023

The laser inertial measurement unit is a precision device widely used in rocket navigation system and other equipment, and its quality is directly related to navigation accuracy. In the quality evaluation of laser inertial measurement unit, there is inevitably uncertainty in the index input information. First, the input numerical information is in interval form. Second, the index input grade and the quality evaluation result grade are given according to different national standards. So, it is a key step to transform the interval information input by the index into the data form consistent with the evaluation result grade. In the case of uncertain input, this paper puts forward a method based on probability distribution to solve the problem of asymmetry between the reference grade given by the index and the evaluation result grade when evaluating the quality of laser inertial measurement unit. By mapping the numerical relationship between the designated reference level and the evaluation reference level of the index information under different distributions, the index evidence symmetrical with the evaluation reference level is given. After the uncertain input information is transformed into evidence of interval degree distribution by this method, the information fusion of interval degree distribution evidence is carried out by interval evidential reasoning algorithm, and the evaluation result is obtained by projection covariance matrix adaptive evolution strategy optimization. Taking a five-meter redundant laser inertial measurement unit as an example, the applicability and effectiveness of this method are verified.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2006.11a
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• pp.277-280
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• 2006

Most real world design evaluation and risk-based decision support combine quantitative and qualitative (linguistic) variables. Decision-making based on conventional mathematics that combines qualitative and quantitative concepts always exhibit difficulty in modelling actual problems. The successful selection process for choosing a design/procurement proposal is based on a high degree of technical integrity, safety levels and low costs in construction, corrective measures, maintenance, operation, inspection and preventive measures. However, the objectives of maximising the degree of technical performance, maximising the safety levels and minimising the costs incurred are usually in conflict, and the evaluation of the technical performance, safety and costs is always associated with uncertainties, especially for a novel system at the initial concept design stage. In this paper, a design-decision support framework using a composite structure methodology grounded in approximate reasoning approach and evidential reasoning method is suggested for design evaluation of machinery space of a ship engine room at the initial stages. It is a Multiple Attribute Decision-Making (MADM) or Multiple Criteria Decision Making (MCDM) framework, which provides a juxtaposition of cost, safety and technical performance of a system during evaluation to assist decision makers in selecting the winning design/procurement proposal that best satisfies the requirement in hand. An illustrative example is used to demonstrate the application of the proposed framework.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.192-194
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• 1995

An improved filter for tracking a maneuvering target is presented. The proposed filter consists of two kalman filters based on different dynamic models and double decision logic. The use of double decision logic for the maneuver onset and ending detection leads to reduction in estimation error. This decision rule is based on evidence theory, Dempster-Shafer theory, which is extended in order to be applicable in the tracking problem. Simulation results show that the proposed filter performs better than IMM at a lower computational load.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.11
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• pp.1401-1409
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• 1999

In this paper, a conceptual framework of a new concept of protectability is proposed, which indicates the protection level of the system. Evaluation attributes have been identified and a hierarchical evaluation model has been established. Dempster-Shafer Theory of Evidence is applied in combining multiple uncertain judgements to produce an aggregated evaluation.

• ETRI Journal
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• v.39 no.4
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• pp.592-604
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• 2017

Intrusion detection is very important for network situation awareness. While a few methods have been proposed to detect network intrusion, they cannot directly and effectively utilize semi-quantitative information consisting of expert knowledge and quantitative data. Hence, this paper proposes a new detection model based on a directed acyclic graph (DAG) and a belief rule base (BRB). In the proposed model, called DAG-BRB, the DAG is employed to construct a multi-layered BRB model that can avoid explosion of combinations of rule number because of a large number of types of intrusion. To obtain the optimal parameters of the DAG-BRB model, an improved constraint covariance matrix adaption evolution strategy (CMA-ES) is developed that can effectively solve the constraint problem in the BRB. A case study was used to test the efficiency of the proposed DAG-BRB. The results showed that compared with other detection models, the DAG-BRB model has a higher detection rate and can be used in real networks.

• Journal of the Korean Society for information Management
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• v.8 no.1
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• pp.100-116
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• 1991

In this study, a retrieval system taking advantage of term relationship in a specific domain and also of evidential reasoning as tools for measuring relevance is implemented. For this experiment, techincal memoranda documented in Electronics and Telecommunications Research Institute (ETRI) served as a sample document file. Sample knowledge base was prepared by extracting terms and term relations pertaining to telecommunications from INSPEC thesaurus. Relations between terms were represented by numerical values according to types of term relations. Relationship between a query and a document was measured according to Dempster-Shafer theory of evidence. As a result of this experiment, a more comprehensive search was made by expanding search terms utilizing term relations. Measure of relevance represented by reflecting term relations, and search results were listed in a descending order of relevance.

• Smart Structures and Systems
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• v.23 no.3
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• pp.279-293
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• 2019

To ensure high quality data being used for data mining or feature extraction in the bridge structural health monitoring (SHM) system, a practical sensor fault diagnosis methodology has been developed based on the similarity of symmetric structure responses. First, the similarity of symmetric response is discussed using field monitoring data from different sensor types. All the sensors are initially paired and sensor faults are then detected pair by pair to achieve the multi-fault diagnosis of sensor systems. To resolve the coupling response issue between structural damage and sensor fault, the similarity for the target zone (where the studied sensor pair is located) is assessed to determine whether the localized structural damage or sensor fault results in the dissimilarity of the studied sensor pair. If the suspected sensor pair is detected with at least one sensor being faulty, field test could be implemented to support the regression analysis based on the monitoring and field test data for sensor fault isolation and reconstruction. Finally, a case study is adopted to demonstrate the effectiveness of the proposed methodology. As a result, Dasarathy's information fusion model is adopted for multi-sensor information fusion. Euclidean distance is selected as the index to assess the similarity. In conclusion, the proposed method is practical for actual engineering which ensures the reliability of further analysis based on monitoring data.

• Journal of the Daesoon Academy of Sciences
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• v.28
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• pp.103-131
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• 2017

As the establishment of self-identity is based on 'Relationships of Mutual Beneficence,' the formation of 'Relationships of Mutual Beneficence' is the only road to the security and confirmation of self-existence. But given that our ordinary life almost entirely consists of actions objectifying others, the formation of 'Relationships of Mutual Beneficence' is by no means easy. The formation of 'Relationships of Mutual Beneficence' should be based on morality, controlling self-desire, and not objectifying others. Philosophy based on a priori reasoning describes self-control over selfdesire as the domination of the body through a priori reasoning. But this practical philosophy cannot present a self-evidential internal motivation behind moral actions. Due to this, the application of moral order given by a priori reasoning in response to reality is likely to be reinterpreted on basis of self-interest. With regards to this, the 'propensity towards sympathy' is given as new moral norm. The 'propensity towards sympathy' as emotion is direct and consistent given that feeling occurs prior to thinking. The 'propensity towards sympathy' is intuitive in the sense that it is an instinctual response preceeding a reasoned judgment. The 'propensity towards sympathy,' as a natural moral emotion, is self-validating given that all human beings know it and practice it. But previous studies on the 'propensity towards sympathy' have an obvious limitation because they adopt phenomenological approaches to the 'propensity towards sympathy' which eschew the investigation of morality. Though they present the 'propensity towards sympathy' as a natural emotion based on body rather than reason, they do not philosophically explain the 'propensity towards sympathy.' Thus the 'propensity towards sympathy' as a natural moral emotion is likely to be interpreted as a subjective and relative moral norm. This paper philosophically explains that the 'propensity towards sympathy' is a universal moral norm on the basis of Merleau-Ponty's 'flesh.' 'Flesh' is formed as the entanglement between oneself and others and presents the 'propensity towards sympathy' as its philosophical basis. In other words, 'flesh' formed as the mixture or entanglement between oneself and others is the material foundation upon which one can activate the 'propensity towards sympathy.' This paper's approach to the 'propensity of sympathy' can be desribed as a phenomenological approach to the 'propensity towards sympathy' as a universal moral norm.