• International journal of advanced smart convergence
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• 제9권1호
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• pp.193-201
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• 2020

The main objective of this study is to investigate the impact of additional modalities on the performance of emotion recognition using speech, facial expression and physiological measurements. In order to compare different approaches, we designed a feature-based recognition system as a benchmark which carries out linear supervised classification followed by the leave-one-out cross-validation. For the classification of four emotions, it turned out that bimodal fusion in our experiment improves recognition accuracy of unimodal approach, while the performance of trimodal fusion varies strongly depending on the individual. Furthermore, we experienced extremely high disparity between single class recognition rates, while we could not observe a best performing single modality in our experiment. Based on these observations, we developed a novel fusion method, called parametric decision fusion (PDF), which lies in building emotion-specific classifiers and exploits advantage of a parametrized decision process. By using the PDF scheme we achieved 16% improvement in accuracy of subject-dependent recognition and 10% for subject-independent recognition compared to the best unimodal results.

• 대한산업공학회지
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• 제1권2호
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• pp.27-38
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• 1975

This paper explores a quantitative decision-making system for planning production, inventories and work-force in a multi-item production system. The Multi-item Parametric Decision Rule (MPDR) model, which assumes the existence of two types of linear feed-back rules, one for work-force level and one for production rates, is basically an extension of the existing method of Parametric Production Planning (PPP) proposed by C.H. Jones. The MPDR model, however, explicitly considers the effect of manufacturing progress and other factors such as employee turn-over, difference in work-days between month etc., and it also provides decision rules for production rates of individual items. First, the cost relations of the production system are estimated in terms of mathematical functions, and then decision rules for work-force level and production rates of individual items are establised based upon the estimated objective cost function. Finally, a direct search technique is used to find a set of parameters which minimizes the total cost of the objective function over a specified planning horizon, given estimates of future demands and initial values of inventories and work-force level. As a case problem, a hypothetical decision rule is developed for a particular firm (truck assembly factory).

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권2호
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• pp.71-76
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• 2011

The problem of decision making under imprecise environments are widely spread in real life decision situations. We present a method of object recognition from imprecise multi observer data, which extends the work of Roy and Maji [J Compu. Appl. Math. 203(2007) 412-418] to generalized intuitionistic fuzzy soft set theory. The method involves the construction of a comparison table from a generalized intuitionistic fuzzy soft set in a parametric sense for decision making.

• Wind and Structures
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• 제31권3호
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• pp.241-253
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• 2020

The inerter-based vibration absorber (IVA) is an enhanced variation of Tuned Mass Damper (TMD). The parametric optimization of absorbers in the previous research mainly considered only two decision variables, namely frequency ratio and damping ratio, and aimed to minimize peak displacement and acceleration individually under the excitation of the across-wind load. This paper extends these efforts by minimizing two conflicting objectives simultaneously, i.e., the extreme displacement and acceleration at the top floor, under the constraint of the physical mass. Six decision variables are optimized by adopting a constrained multi-objective evolutionary algorithm (CMOEA), i.e., NSGA-II, under fluctuating across- and along-wind loads, respectively. After obtaining a set of optimal individuals, a decision-making approach is employed to select one solution which corresponds to a Tuned Mass Damper Inerter/Tuned Inerter Damper (TMDI/TID). The optimization procedure is applied to parametric optimization of TMDI/TID installed in a 340-meter-high building under wind loads. The case study indicates that the optimally-designed TID outperforms TMDI and TMD in terms of wind-induced vibration mitigation under different wind directions, and the better results are obtained by the CMOEA than those optimized by other formulae. The optimal TID is proven to be robust against variations in the mass and damping of the host structure, and mitigation effects on acceleration responses are observed to be better than displacement control under different wind directions.

• 한국CDE학회논문집
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• 제3권3호
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• pp.168-176
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• 1998

This paper deals with an application on the mould machining of air intake hose product by using 3-dimensional parametric modeling techniques. The detailed domain is the 3-dimensional product with similar shapes and different sizes which needs too much working time for preparation of modeling or machining due to making a trial and errors repeatedly. Decision making rules for selection of modeling order and technique, and for calculation of cutting conditions, and for determination of sequence and method concerning machining operations are required by interview of expert engineers in the field. The developed expert system of modeling and machining is programmed by using a user programming language under the CAD/CAM software of the Personal Designer. The developed system that aids a mould engineer who is working in the modeling and machining section which deal with air intake hose product provides strong and useful capabilities.

• 산업경영시스템학회지
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• 제39권1호
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• pp.47-55
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• 2016

As one of recent issues in the information and communication industry, internet of things has attracted attention to provide intelligent infrastructure services which connect and share data and information between real and virtual world. According to the development of these internet of things technologies, types of machines, telecommunication devices, and terminals are increasing tremendously. In this situation, connectivity and interoperability between internet of things components are important issues to build a hyper connected society. To visualize this society, it is important to set up and develop information and communication technology (ICT) standards among stakeholders. However, under limited budget and human resources, it is essential to rank standardization work items for setting standards with respect to efficiency. The purpose of this study is to provide a method for setting standardization strategies within group decision making. As a multi-criteria group decision making tool, analytic hierarchy process (AHP) is adopted and applied to determine the priorities of setting work items. The proposed method first defines decision making problem with objective, criteria, and alternatives which produces a hierarchy consisting of upper and lower criteria. Then, pairwise comparisons of academy and public sector experts are performed with respect to their relative meaning and importance. Individual surveys of expert groups are collected and summarized to determine relative criteria importance measures. Furthermore, to deliver reliable importance criteria measures, differences between academy and public sector expert groups are compared and tested using Mann-Whitney non-parametric test. The results are illustrated for useful guidelines to practical group decision making in standardization strategy establishments.

• 한국지능시스템학회논문지
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• 제11권3호
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• pp.231-240
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• 2001

Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

• 산업경영시스템학회지
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• 제37권4호
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• pp.239-244
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• 2014

The conventional clustering approaches are mostly based on minimizing total dissimilarity of input and output. However, the clustering approach may not be helpful in some cases of clustering decision making units (DMUs) with production feature converting multiple inputs into multiple outputs because it does not care converting functions. Data envelopment analysis (DEA) has been widely applied for efficiency estimation of such DMUs since it has non-parametric characteristics. We propose a new clustering method to identify groups of DMUs that are similar in terms of their input-output profiles. A real world example is given to explain the use and effectiveness of the proposed method. And we calculate similarity value between its result and the result of a conventional clustering method applied to the example. After the efficiency value was added to input of K-means algorithm, we calculate new similarity value and compare it with the previous one.

• 한국실내디자인학회논문집
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• 제25권6호
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• pp.70-78
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• 2016

This paper aims to describe a case study of parametric interior design based on BIM (Building Information Modeling). As the practical use of BIM-based design grows, its influence expands into the field of interior architecture design. BIM makes possible to check various design plan, reach decision making in an effective way, and change design plan in an efficient method. Therefore, BIM is also promising field in interior architecture design. However, compared to other fields in architecture, engineering, and construction (AEC) industry, there have been less research and projects on BIM in the field of interior architecture. For increasing the feasibility of adapting BIM in interior architecture design, this paper describes a case study-projecting images for designing interior panels using parametric modeling. This process needs elaborate, delicate, and precise steps for harmonious output. For continuous use of building, users look forward to the design which variable and changeable according to user's preference and environment. Therefore, demand for parametric design in the interior design part such as panel pattern design for various decoration is growing. Treated process in this paper deals with an advanced phase which much effective in decreasing time consumption and useless part of process. Finally, this paper suggests the possibility of using BIM in the interior design process and field where BIM can be applied.

• 국제학술발표논문집
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• The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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• pp.176-181
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• 2011

A role of cost modeler is that of facilitating design process by the systematic application of cost factors so as to maintain sensible and economic relationships between cost, quantity, utility and appearance. These relationships help to achieve the client's requirements within an agreed budget. The purpose of this study is to develop a parametric cost estimating model for the early design stage by using the multi-dimensional system of OLAP (On-line Analytical Processing) based on the case of quantity data related to architectural design features. The parametric cost estimating models have been adopted to support decision making in the early design stage. These models typically use a similar instance or a pattern of historical case. In order to effectively use this type of data model, it is required to set data classification and prediction methods. One of the methods is to find the similar class in line with attribute selection measure in the multi-dimensional data model. Therefore, this research is to analyze the relevance attribute influenced by architectural design features with the subject of case-based quantity data used for the parametric cost estimating model. The relevance attributes can be analyzed by Analytical Characterization. It helps determine what attributes to be included in the OLAP multi-dimension.