• Journal of Ethics
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• 제82호
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• pp.73-125
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• 2011

This article aims to search for moral educational implication of J. D. Greene's recent neuro-scientific approaches to deontological ethics. Recently new technique in neuroscience such as fMRI is applied to moral and social psychological concepts or terms, and 'affective primacy' and 'automaticity' principles are highlighted as basic concepts of the new paradigm. When these principles are introduced to ethical theories, it makes rooms of new and different interpretations of them. J. D. Greene et al. claim that deontological moral judgments or theories are just a kind of post hoc rationalization for intuitions or emotions by ways of neuroscientific findings and evolutionary interpretation. For example, Kant's categorical imperative in which a maxim should be universalizable to be as a principle, might be a product of moral intuition. Firstly this article tries to search for intellectual backgrounds of the social intuitionalism where Greens' thought originates. Secondly, this article tries to collect and summarize his arguments about moral dilemma responses, personal-impersonal dilemma catergorizing hypothesis, fMRI data interpretations by ways of evolutionary theory, cultural and social psychological theories, application to deontological and consequential theories, and his suggestion that deontological ethics shoud be rejected as a normative ethical thought and consequentialism be a promising theory etc. Thirdly, this tries to analyse and critically exam those aspects and argumentation, especially from viewpoints of the ethicists whose various strategies seek to defeat Greene's claims. Fourthly, this article criticizes that his arguments make a few critical mistakes in methodology and data interpretation. Last, this article seeks to find its implications for moral education in korea, in which in spite of incomplete argumentation of his neuroscientific approach to morality, neuroethics needs to be introduced as a new approach and educational content, and critical materials as well.

• Journal of Electrical Engineering and Technology
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• 제12권2호
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• pp.612-620
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• 2017

Relay coordination in power system is a complex problem and so far, meta-heuristic algorithms and other methods as an alternative approach may not properly deal with large scale relay coordination due to their huge time consuming computation. In some cases the relay coordination could be unachievable. As the urgency for a proper approach is essential, in this paper an innovative and simple relay coordination method is introduced that is able to be applied on optimization algorithms for relay protection coordination. The objective function equation of operating time of relays are divided into two separate functions with less constraints. As the analytical results show here, this equivalent method has a remarkable speed with high accuracy to coordinate directional relays. Two distribution systems including directional overcurrent relays are studied in DigSILENT software and the collected data are examined in MATLAB. The relay settings of this method are compared with particle swarm optimization and genetic algorithm. The analytical results show the correctness of this mathematical and practical approach. This fast coordination method has a proper velocity of convergence with low iteration that can be used in large scale systems in practice and also to provide a feasible solution for protection coordination in smart grids as online or offline protection coordination.

• The Journal of Asian Finance, Economics and Business
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• 제3권1호
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• pp.33-41
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• 2016

Essences, needs and features of formation of national innovative development model of Kazakhstan are proved on the basis of analysis of various research approaches to realization of the modernization that exist in the world economic theory. For studying the problems of innovative development of the country, there was a need for the formulation of a number of definitions, disclosure of their contents, changing the approaches to reform, as well as adjusting their targets. In the article the general scientific research methods used dialectic, abstraction, systemic and situational approach, empirical and theoretical and analytical methods, and logic modeling. The proposed approach to the implementation of innovative development based on the use of evolutionary and institutional approaches to the study of the problems of implementing an effective innovation policy. This approach is intended to contribute to the development of a forward strategy of modernization, innovative development and higher competitiveness of the national economy. The study proved the causes and features of the implementation of innovative development model in Kazakhstan.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제27권6호
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• pp.1020-1027
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• 2003

A traditional mold design has been conducted by an experience-based trial and error, whereby the mold designer would decide the gate locations and processing conditions based on the caring characteristics and its functional requirements. The paper suggests an optimal gate location and processing conditions in the injection molding using a global search method referred to as micro genetic algorithm( ${\mu}$ GA). ${\mu}$ GA yields the optimal solution with a small size of population without respect to design variables for saving time that is needed to calculate the fitness of many individuals. Due to the reason, the paper uses a commercial analysis package of injection molding(CAPA) to analysis a state of flux. In addition to that, axiomatic approach .is applied in the beginning of design. It is a useful method to draw a well-organized and reasonable idea to handle a problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권12호
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• pp.3117-3132
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• 2012

The tree topology in multicast systems has high transmission efficiency, low latency, but poor resilience to node failures. In our work, some nodes are selected as backbone nodes to construct a tree-like core overlay. Backbone nodes are reliable enough and have strong upload capacity as well, which is helpful to overcome the shortcomings of tree topology. The core overlay is organized into a spanning tree while the whole overlay is of mesh-like topology. This paper focuses on improving the performance of the application-layer multicast overlay by optimizing the core overlay which is periodically adjusted with the proposed optimization algorithm. Our approach is to construct the overlay tree based on the out-degree weighted reliability where the reliability of a node is weighted by its upload bandwidth (out-degree). There is no illegal solution during the evolution which ensures the evolution efficiency. Simulation results show that the proposed approach greatly enhances the reliability of the tree-like core overlay systems and achieves shorter delay simultaneously. Its reliability performance is better than the reliability-first algorithm and its delay is very close to that of the degree-first algorithm. The complexity of the proposed algorithm is acceptable for application. Therefore the proposed approach is efficient for the topology optimization of a real multicast overlay.

• The Journal of the Korea Contents Association
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• 제15권7호
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• pp.21-29
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• 2015

This paper proposes a novel two-tier optimization approach for decision making in many-objective problems. Because the Pareto-optimal solution ratio increases exponentially with an increasing number of objectives, simply finding the Pareto-optimal solutions is not sufficient for decision making in many-objective problems. In other words, it is necessary to discriminate the more preferable solutions from the other solutions. In the proposed approach, user preference-oriented as well as diverse Pareto-optimal solutions can be obtained as candidate solutions by introducing an additional tier of optimization. The second tier of optimization employs the corresponding secondary objectives, global evaluation and crowding distance, which were proposed in previous works, to represent the users preference to a solution and the crowdedness around a solution, respectively. To demonstrate the effectiveness of the proposed approach, decision making for some benchmark functions is conducted, and the outcomes with and without the proposed approach are compared. The experimental results demonstrate that the decisions are successfully made with consideration of the users preference through the proposed approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권5호
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• pp.2277-2298
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• 2019

Adaptive learning in e-learning has garnered researchers' interest. In it, learning resources could be recommended automatically to achieve a personalized learning experience. There are various ways to realize it. One of the realistic ways is adaptive learning path recommendation, in which learning resources are provided according to learners' requirements. This paper summarizes existing works and proposes an innovative approach. Firstly, a learner-centred concept map is created using graph theory based on the features of the learners and concepts. Then, the approach generates a linear concept sequence from the concept map using the proposed traversal algorithm. Finally, Learning Objects (LOs), which are the smallest concrete units that make up a learning path, are organized based on the concept sequences. In order to realize this step, we model it as a multi-objective combinatorial optimization problem, and an improved immune algorithm (IIA) is proposed to solve it. In the experimental stage, a series of simulated experiments are conducted on nine datasets with different levels of complexity. The results show that the proposed algorithm increases the computational efficiency and effectiveness. Moreover, an empirical study is carried out to validate the proposed approach from a pedagogical view. Compared with a self-selection based approach and the other evolutionary algorithm based approaches, the proposed approach produces better outcomes in terms of learners' homework, final exam grades and satisfaction.

• Journal of the Korean Geographical Society
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• 제40권4호
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• pp.387-401
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• 2005

This research reviews how tourism geography studies in Anglo-American tradition have evolved since 1930s. The purposes of the research are two fold. One is to analyze the change of tourism geographies research trends in terms of research approach and major research themes. The other is to bring out the lessons from the research results for the development of Korean tourism geographies research. For these purposes, the selected papers and texts have been analyzed according to four research approaches: (1) empiricist approach, (2) positivist approach, (3) humanist approach, and (4) critical social theory approach. The major research themes are the explanation of destination through descriptive research in empiricist approach, spatial analysis and evolutionary research in positivist approach, tourist behaviour and place identity in humanist approach, and tourism and consumption in critical social theory approach. It is expected that the development of Anglo-American tourism geographies study will continue in the future because of the growth of tourism industry, the close relation of tourism and geography in nature, and the active contribution of tourism geographers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권2호
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• pp.326-354
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• 2014

In this paper, a new green clustering algorithm is proposed to be as a first approach in the framework of an energy efficient strategy for centralized enterprise high-density WLANs. Traditionally, in order to maintain the network coverage, all the APs within the WLAN have to be powered-on. Nevertheless, the new algorithm can power-off a large proportion of APs while the coverage is maintained as its always-on counterpart. The two main components of the new approach are the faster procedure based on K-means and the more accurate procedure based on Evolutionary Algorithm (EA), respectively. The two procedures are processes in parallel for different designed requirements and there is information interaction in between. In order to implement the new algorithm, EA is applied to handle the optimization of multiple objectives. Moreover, we adapt the method for selection and recombination, and then introduce a new operator for mutation. This paper also presents simulations in scenarios modeled with ray-tracing method and FDTD technique, and the results show that about 67% to 90% of energy consumption can be saved while it is able to maintain the original network coverage during periods when few users are online or the traffic load is low.

• Journal of Electrical Engineering and Technology
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• 제2권4호
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• pp.413-419
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• 2007

The optimal power flow (OPF) problem was introduced by Carpentier in 1962 as a network constrained economic dispatch problem. Since then, it has been intensively studied and widely used in power system operation and planning. In the past few decades, many stochastic optimization methods such as Genetic Algorithm (GA), Evolutionary Programming (EP), and Particle Swarm Optimization (PSO) have been applied to solve the OPF problem. In particular, PSO is a newly proposed population based stochastic optimization algorithm. The main idea behind it is based on the food-searching behavior of birds and fish. Compared with other stochastic optimization methods, PSO has comparable or even superior search performance for some hard optimization problems in real power systems. Nowadays, some modifications such as breeding and selection operators are considered to make the PSO superior and robust. In this paper, we propose the Modified PSO (MPSO), in which the mutation operator of GA is incorporated into the conventional PSO to improve the search performance. To verify the optimal solution searching ability, the proposed approach has been evaluated on an IEEE 3D-bus test system. The results showed that performance of the proposed approach is better than that of the standard PSO.