• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.3
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• pp.215-222
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• 2021

As the importance of human-computer interaction (Human Computer Interface) technology grows and research on HCI is progressing, it is inferred about the research emotion inference or the computer reaction according to the user's intention, not the computer reaction by the standard input of the user. Stress is an unavoidable result of modern human civilization, and it is a complex phenomenon, and depending on whether or not there is control, human activity ability can be seriously changed. In this paper, we propose an intelligent emotional recommendation system using music as a way to relieve stress after measuring heart rate variability (HRV) and acceleration photoplethymogram (APG) increased through stress as part of human-computer interaction. The differential evolution algorithm was used to extract reliable data by acquiring and recognizing the user's biometric information, that is, the stress index, and emotional inference was made through the semantic web based on the obtained stress index step by step. In addition, by searching and recommending a music list that matches the stress index and changes in emotion, an emotional recommendation system suitable for the user's biometric information was implemented as an application.

• Journal of Gifted/Talented Education
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• v.13 no.3
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• pp.1-17
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• 2003

Development and evaluation of distance learning for the gifted students in science and mathematics In this study, we developed and administrated the distance learning for the gifted students in science and mathematics, and analysed their responses. To do this, four types of teaching programs - lectures using program for distance learning, practice activities using simulation program, tasks solving programs based on discussions, and problem solving activities - were developed and students responses were analysed in eight area - stimulus, difficulties, structure, learning circumstances, involvement, interaction, learning outcomes, comparison with other learning -. As results, it was found that many students responded positively and thought programs helped their creativity, logical thinking, intelligent ability, and information searching ability. Students preferred practice activities based on appropriate guidances to lectures providing detailed explanations. And interaction could be stimulated by inducing discussion.

• Smart Structures and Systems
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• v.17 no.6
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• pp.957-980
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• 2016

Structural damage detection (SDD) is a challenging task in the field of structural health monitoring (SHM). As an exploring attempt to the SDD problem, a hybrid self-adaptive Firefly-Nelder-Mead (SA-FNM) algorithm is proposed for the SDD problem in this study. First of all, the basic principle of firefly algorithm (FA) is introduced. The Nelder-Mead (NM) algorithm is incorporated into FA for improving the local searching ability. A new strategy for exchanging the information in the firefly group is introduced into the SA-FNM for reducing the computation cost. A random walk strategy for the best firefly and a self-adaptive control strategy of three key parameters, such as light absorption, randomization parameter and critical distance, are proposed for preferably balancing the exploitation and exploration ability of the SA-FNM. The computing performance of the SA-FNM is evaluated and compared with the basic FA by three benchmark functions. Secondly, the SDD problem is mathematically converted into a constrained optimization problem, which is then hopefully solved by the SA-FNM algorithm. A multi-step method is proposed for finding the minimum fitness with a big probability. In order to assess the accuracy and the feasibility of the proposed method, a two-storey rigid frame structure without considering the finite element model (FEM) error and a steel beam with considering the model error are taken examples for numerical simulations. Finally, a series of experimental studies on damage detection of a steel beam with four damage patterns are performed in laboratory. The illustrated results show that the proposed method can accurately identify the structural damage. Some valuable conclusions are made and related issues are discussed as well.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.98-107
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• 2015

Hierarchical constraints and constraint satisfaction were analyzed in order to solve the problem of conflict detection in collaborative design. The constraints were divided into two sets: one set consisted of known constraints and the other of unknown constraints. The constraints of the two sets were detected with corresponding methods. The set of the known constraints was detected using an interval propagation algorithm, a back propagation (BP) neural network was proposed to detect the set with the unknown constraints. An immune algorithm (IA) was utilized to optimize the weights and the thresholds of the BP neural network, and the steps were designed for the optimization process. The results of the simulation indicated that the BP neural network that was optimized by IA has a better performance in terms of convergent speed and global searching ability than a genetic algorithm. The constraints were described using the eXtensible Markup Language (XML) for computers to be able to automatically recognize and establish the constraint network. The implementation of the conflict detection system was designed based on constraint satisfaction. A wind planetary gear train is taken as an example of collaborative design with a conflict detection system.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.747-752
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• 2011

HMMs (Hidden Markov Models) are widely used for biological signal, such as EEG (electroencephalogram) sequence, analysis because of their ability to incorporate sequential information in their structure. A recent trends of research are going after the biological interpretable HMMs, and we need to control the complexity of the HMM so that it has good generalization performance. So, an automatic means of optimizing the structure of HMMs would be highly desirable. In this paper, we described a procedure of classification of motor imagery EEG signals using HMM. The motor imagery related EEG signals recorded from subjects performing left, right hand and foots motor imagery. And the proposed a method that was focus on the validation of the HSA (Harmony Search Algorithm) based optimization for HMM. Harmony search algorithm is sufficiently adaptable to allow incorporation of other techniques. A HMM training strategy using HSA is proposed, and it is tested on finding optimized structure for the pattern recognition of EEG sequence. The proposed HSA-HMM can performs global searching without initial parameter setting, local optima, and solution divergence.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.249-274
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• 1998

It is the analyses of replies showed n the questionnaire consisted of four kinds of matters to see level of knowledge among SELIS (SEoul Women's University Library and Information System) OPAC users of keyword/boolean search. The result of this analyses is : in SELIS search, users who prefer keyword search than any other, who satisfy work of retrieval by means of boolean operator, and who think it easier, show lusher level of knowledge than those who deny it in the questionnaire. Knowledges Presented in the survey are ; characteristics of keyword search, single or double keys, using boolean operator in keyword, knowledge of index, knowledge of stop list, uncontrolled term. keyword search technique, right truncation, correct application of boolean logic operator, and selecting major subject in keyword browsing. The above mentioned knowledges will work as important factors n keyword/boolean search, OPAC. For successful search it requires conceptional knowledge of information retrieval processing, or inquiry word transformation how to search required information, and semantic ability to get result questioned In the given system, when and how to apply the characteristics of the system, and scientific record for user's inquiry, or fundamental computer technology and syntax knowledge to make search word in detail. But so far now important knowledge considered as user's online index search, has been emphasized on knowledge of scientific record, and has been lag of semantic and conceptional knowledge. So, it is recommendable for online index user to train to concentrate semantic knowledge, syntax ability, and conceptional knowledge, rather than scientific technique too much.

• PNF and Movement
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• v.14 no.3
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• pp.157-176
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• 2016

Purpose: The purpose of this study was to share an experience about processes and lessons learned to execute evidence-based practice (EBP) in neurological physical therapy. Methods: The most important thing in applying EBP to practice is to search, find, and appraise the existing evidence. Many evidence databases are available, such as CENTRAL, PEDro, PUBMED, and EMBASE. However, the knowledge represented in these databases is not always perfect. The practice model is a set of processes to resolve client problems. Therapists should make hypothesis-focused decisions through EBP. Integrating clinical reasoning and evidence is most important when it comes to the execution of EBP. Results: The process of EBP consisted of following: coming up with clinical questions, followed by searching for, appraising, evaluating, and integrating evidence. To integrate EBP into practice, it is necessary to consider clinical expertise, patient value and preferences, as well as research wth the best evidence. We provided an example of a clinical case with a stroke patient to show how this process and framework concerning clinical reasoning through evidences can be integrateds. During this process, we also utilized information technology to improve EBP ability. Conclusion: We should recognize what manner of information is needed to resolve eash patient's problem, and we should search for this information efficiently. Then, we should judge the value of the information obtained as it applies, to the clinical setting.

• Journal of KIISE
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• v.45 no.1
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• pp.53-60
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• 2018

This study describes a spatial web object retrieval system using Spark, an in - memory based distributed processing system. Development of social networks has created massive amounts of spatial web objects, and retrieval and analysis of data is difficult by using exist spatial web object retrieval systems. Recently, development of distributed processing systems supports the ability to analyze and retrieve large amounts of data quickly. Therefore, a method is promoted to search a large-capacity spatial web object by using the distributed processing system. Data is processed in block units, and one of these blocks is converted to RDD and processed in Spark. Regarding the discussed method, we propose a system in which each RDD consists of spatial web object index for the included data, dividing the entire spatial region into non-overlapping spatial regions, and allocating one divided region to one RDD. We propose a system that can efficiently use the distributed processing system by dividing space and increasing efficiency of searching the divided space. Additionally by comparing QP-tree with R-tree, we confirm that the proposed system is better for searching the spatial web objects; QP-tree builds index with both spatial and words information while R-tree build index only with spatial information.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.725-730
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• 2006

Recently Web services have become a key technology which is indispensable for e-business. Due to its ability to provide the desired information or service regardless of time and place, integrating current application systems within a single business or between multiple businesses with standardized technologies are realized using the open network and Internet. However, the current Web Services Retrieval Systems, based on text oriented search are incapable of providing reliable search results by perceiving the similarity or interrelation between the various terms. Currently there are no web services retrieval models containing such semantic web functions. This research work is purported for solving such problems by designing and implementing an extended Semantic Web Services Retrieval Model that is capable of searching for general web documents, UDDI and semantic web documents. Execution result is proposed in this paper and its efficiency and accuracy are verified through it.

• Journal of The Korean Association of Information Education
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• v.11 no.1
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• pp.29-38
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• 2007

Computer programming in computer education draws much attention recently. Encouraged by the increased tendency of acquiring logical ability and creativity through learning, various attempts have been made to develop them through learning computer programming in the area of computer education as well. The fact that a computer program is the representation of a computer algorithm expressed in a computer language makes us realize that the devise of a logical method for a solution - i.e., the design of an algorithm - is the key to the solution of a problem. Recognizing the importance of computer algorithm would lead us to such a point that systematic investigations for directional establishment for algorithm education are necessary. We observe that researches on teaching computer algorithm have concentrated mostly on specific problems such as sorting and searching, which can be characterized as problem-dependent and individual. In this paper, the idea of conceptual algorithm is stated from the standpoint of conceptual types of problem-solving methods which are considered as problem-independent and collective. A novice approach to algorithm education based on the characteristics of types of conceptual algorithms is proposed for the purpose of developing systematic, problem-independent, algorithmic problem-solving capabilities of learners, which is widely different from the current methods of individual and problem-dependent algorithm education.