• Journal of the Korean Society for Precision Engineering
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• v.14 no.12
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• pp.24-29
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• 1997

Recently, Genetic Algorithm(GA), which is a stochastic direct search strategy that mimics the process of genetic evolution, is widely adapted into a search procedure for structural optimization. Contrast to traditional optimal design techniques which use design sensitivity analysis results, GA is very simple in their algorithms and there is no need of continuity of functions(or functionals) any more in GA. So, they can be easily applicable to wide area of design optimization problems. Also, owing to multi-point search procedure, they have higher porbability of convergence to global optimum compared to traditional techniques which take one-point search method. The methods consist of three genetics opera- tions named selection, crossover and mutation. In this study, a method of finding the omtimum size and topology of drilling machine is proposed by using the GA, For rapid converge to optimum, elitist survival model,roulette wheel selection with limited candidates, and multi-point shuffle cross-over method are adapted. And pseudo object function, which is the combined form of object function and penalty function, is used to include constraints into fitness function. GA shows good results of weight reducing effect and convergency in optimal design of drilling machine.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.213-219
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• 2023

In recent years, popularity of deep learning (DL) is increased due to its ability to extract features from Hyperspectral images. A lack of discrimination power in the features produced by traditional machine learning algorithms has resulted in poor classification results. It's also a study topic to find out how to get excellent classification results with limited samples without getting overfitting issues in hyperspectral images (HSIs). These issues can be addressed by utilising a new learning network structure developed in this study.EfficientNet-B4-Based Convolutional network (EN-B4), which is why it is critical to maintain a constant ratio between the dimensions of network resolution, width, and depth in order to achieve a balance. The weight of the proposed model is optimized by Search and Rescue Operations (SRO), which is inspired by the explorations carried out by humans during search and rescue processes. Tests were conducted on two datasets to verify the efficacy of EN-B4, with Indian Pines (IP) and the University of Pavia (UP) dataset. Experiments show that EN-B4 outperforms other state-of-the-art approaches in terms of classification accuracy.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.6
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• pp.530-538
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• 2014

The weight estimation of floating offshore structures such as FPSO, TLP, semi-Submersibles, Floating Offshore Wind Turbines etc. in the preliminary design, is one of important measures of both construction cost and basic performance. Through both literature investigation and internet search, the weight data of floating offshore structures such as FPSO and TLP was collected. In this study, the weight estimation model was suggested for FPSO. The weight estimation model using non-linear regression analysis was established by fixing independent variables based on this data and the multiple regression analysis was introduced into the weight estimation model. Its reliability was within 4% of error rate.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.42-47
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• 2010

Many contests by micro mouse was celebrated of which maze search algorithms performance are compared. That is used in various forms based on left(right) weight method, euclidean algorithm method, hill climbing method. However we feel uncomfortable to test algorithms performance through direct development of programs or hardwares as no software platform to test in maze search algorithms. In this research we develop of a platform for maze search algorithms that is easily to produce various forms of maze that are hard to be realized by hardware, to apply algorithms, and evaluate the seek time, operation count, steps and performance. The platform is consist of main layer, interface layer, user layer which has merit to apply and replace easily algorithms. We verified that the maze search algorithm can be applied even in the development and experiment of algorithm by evaluating and analyzing its performance through the experiment of platform.

• Journal of KIISE:Databases
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• v.36 no.1
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• pp.22-29
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• 2009

The World Wide Web has emerged as largest media which provides even a single user to market their products and publish desired information; on the other hand the user can access what kind of information abundantly enough as well. As a result web holds large amount of related information distributed over multiple web pages. The current search engines search for all the entered keywords in a single webpage and rank the resulting set of web pages as an answer to the user query. But this approach fails to retrieve the pair of web pages which contains more relevant information for users search. We introduce a new search paradigm which gives different weights to the query keywords according to their order of appearance. We propose a new arc weight measure that assigns more relevance to the pair of web pages with alternate keywords present so that the pair of web pages which contains related but distributed information can be presented to the user. Our measure proved to be effective on the similarity search in which the experimentation represented the e~arc ranking measure outperforming the conventional ones.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.5-5
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• 2003

The purple acid phosphatases comprise a family of binuclear metal-containing enzymes. The metal centre contains one ferric ion and one divalent metal ion. Spectroscopic studies of the monomeric, ${\sim}$36 kDa mammalian purple acid phosphatases reveal the presence of an Fe(III)Fe(II) centre in which the metals are weakly antiferromagnetically coupled, whereas the dimeric, ${\sim}$110 000 kDa plant enzymes contain either Fe(III)Zn(II) or Fe(III)Mn(II). The three dimensional structures of the red kidney bean and pig enzymes show very similar arrangements of the metal ligands but some significant differences beyond the immediate vicinity of the metals. In addition to the catalytic domain, the plant enzyme contains a second domain of unknown function. A search of sequence databases was undertaken using a sequence pattern which includes the conserved metal-binding residues in the plant and animal enzymes. The search revealed the presence in plants of a 'mammalian-type' low molecular weight purple acid phosphatase, a high molecular weight form in some fungi, and a homologue in some bacteria. The catalytic mechanism of the enzyme has been investigated with a view to understanding the marked difference in specificity between the Fe-Mn sweet potato enzyme, which exhibits highly efficient catalysis towards both activated and unactivated phosphate esters, and other PAPs, which hydrolyse only activated esters. Comparison of the active site structures of the enzymes reveal some interesting differences between them which may account for the difference. The implications fur understanding the physiological functions of the enzymes will be discussed.

• Herbal Formula Science
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• v.22 no.2
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• pp.45-54
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• 2014

Objectives : The main objective of this study is to classify herbal components to 4 groups which are similar to Gunsinjwasa grades by using herbal composition ratio of prescription. Another objective is to design the searching system which compares prescriptions and improves efficiency with 4 groups like Gunsinjwasa grades. Methods : This study was proceeded with Acess 2007 on Microsoft Windows 7 and we created composition ratio based on weight by using prescriptions of Donguibogam, Uihagipmun and Banghakhabpyun. We could make comparison and searching method of prescriptions. Results : We could search using composition ratio degree of herbs which composes prescription. And the similarity comparison of prescription was possible with value from 0 to 10. Conclusions : We could increase the accuracy of the searching prescriptions and comparison with putting into the information about composition degree and composition ratio of herbs which compose a prescription.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.57 no.3
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• pp.185-193
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• 2021

This study was conducted to evaluate the performance of the octopus pot according to mesh sizes. Entering behavior of Octopus minor and bait (Macrophthalmus japonicus) escape rate on the mesh sizes of the pots were investigated for six times in indoor tank. The sea trials for evaluating the performance of Octopus minor pot to different mesh sizes (22, 20 and 18 mm) were conducted for six times from 2017 to 2018 in the coastal sea of Deukyang Bay, the Republic of Korea. Behavior patterns of contact pot to leaved pot were more frequent than contact pot to bait search. When the octopus contacted to the pot, there was no clear search behavior to distinguish the mesh sizes. Total catch of 46% was accounted for 18 mm pots, followed by 34% at 20 mm and 20% at 22 mm (P < 0.05). Catch per unit effort was calculated as 30 g/pot at 22 mm, 44 g/pot at 20 mm and 59 g/pot at 18 mm. As a result of evaluating 50% selection of mantle length and weight on the mesh sizes, mantle length (mm) and weight (g) were 84.6 and 147.8 in 22 mm, followed by 20 and 18 mm.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.12-18
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• 2011

In this paper, we proposed Interval Type-2 polynomial Radial Basis Function Neural Networks. In the receptive filed of hidden layer, Interval Type-2 fuzzy set is used. The characteristic of Interval Type-2 fuzzy set has Footprint Of Uncertainly(FOU), which denotes a certain level of robustness in the presence of un-known information when compared with the type-1 fuzzy set. In order to improve the performance of proposed model, we used the linear polynomial function as connection weight of network. The parameters such as center values of receptive field, constant deviation, and connection weight between hidden layer and output layer are optimized by Conjugate Gradient Method(CGM) and Space Search Evolutionary Algorithm(SSEA). The proposed model is applied to gas furnace dataset and its result are compared with those reported in the previous studies.