• KIEAE Journal
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• v.15 no.2
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• pp.27-35
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• 2015

Purpose: Healthcare is on the whole a personal and critical service that consumer's use, whereas hospitalization is as a rule painful, because nature nurtures and Sun Light Luminosity for healthcare settings is considered healing. The performance and design of climate responsive buildings such as AKU requires a detailed study of attributes of climate both at micro as well as macro level. The therapeutic value of contact with nature through window view, greenery and landscape is calculated there. Method: A two prong strategy is been devised for this article, at micro level three typical morphologies are analysed by creating same environment of neighboring building on sun shading chart, radiation and temperature range. Since the analysis of local climate helps to determine the design strategies for hospital Healing Environment which is suitable for Karachi climate; in order to track the macro climatic behaviour, a considerable analysis of psychometrics chart for AKU Karachi are designed on Climate Consultant (CC) and analysed by Machine Learning. Climate Consultant proposes different design strategies suitable for Karachi. And on the other hand time wise illumination sources for clinical area which are then measured on psychrometric chart- according to singular space: multi patient admission, secondly: acute ambulatory ward, and tertiary: multi windowed space according to the mushrabiyah and sky light pattern. Result: Our findings support the hypothesis that windowed wall is 75-80% more healing wall; an accelerated evidence was found for healing at macro level if the form of the hospital is designed according to the climatologically preferences, whereas at micro level: the light resource becomes the staff attentiveness determinant. In Conclusion evidence was provided that the actual form of luminosity results consequently in satisfaction while light entering from several set of windows and other sources might be valued if design according to the healing environment. The data added on the sun shading chart to calculate rays entraining into space in patient room equal to 124416.21 Watts/ meter $m^2$ is calculated as precise healing rate-and is confirmed by questionnaire from patients belonging from each clinical stage having different illnesses.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.73-81
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• 2015

The paper proposes a prototype selection method and evaluates the generalization performance of standard algorithms and prototype based classification learning. The proposed prototype classifier defines multidimensional spheres with variable radii within class areas and generates a small set of training data. The nearest-neighbor classifier uses the new training set for predicting the class of test data. By decomposing bias and variance of the mean expected error value, we compare the generalization errors of k-nearest neighbor, Bayesian classifier, prototype selection using fixed radius and the proposed prototype selection method. In experiments, the bias-variance changing trends of the proposed prototype classifier are similar to those of nearest neighbor classifiers with all training data and the prototype selection rates are under 27.0% on average.

• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.853-862
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• 2003

Many more use e-mail purely on a personal basis and the pool of e-mail users is growing daily. Also, the amount of mails, which are transmitted in electronic commerce, is getting more and more. Because of its convenience, a mass of spam mails is flooding everyday. And yet automated techniques for learning to filter e-mail have yet to significantly affect the e-mail market. This paper suggests Web Mail Filtering Agent for Personalized Classification, which automatically manages mails adjusting to the user. It is based on web mail, which can be logged in any time, any place and has no limitation in any system. In case new mails are received, it first makes some personal rules in use of the result of observation ; and based on the personal rules, it automatically classifies the mails into categories according to the contents of mails and saves the classified mails in the relevant folders or deletes the unnecessary mails and spam mails. And, we applied Bayesian Algorithm using Dynamic Threshold for our system's accuracy.

• Journal of Korean Elementary Science Education
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• v.24 no.3
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• pp.214-225
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• 2005

The purpose of this study was to examine the content relevance of the 7th national primary science curriculum and textbooks. To fulfill the purpose of the study, we 1) analyzed the 7th national science curriculum of Korea, Californian science standards, the national science curriculum of England and Japan, and current Korean and Japanese science textbooks, 2) conducted a nationwide survey to gather opinions from students, teachers, and professors of teachers colleges about the relevance of the science curriculum and textbooks. Main findings of this study are as follows: First, the science contents at each grade level should be determined by the students' characteristics, not by an equal portion rule among physics, chemistry, biology and earth science. Second, the excessive overlapping and repetition of contents due to the spiral curriculum should be avoid. Third, the number of topics at each grade level should be reduced, and the similar topics and themes should be integrated for students' deeper understanding. Fourth, the number of science concepts and activities should be reduced to an appropriate level considering the time allotment for science classes, teachers workload, laboratory conditions, etc. Fifth, differentiated curriculum, such as in-depth and supplementary course, should be described not in science contents, but in teaching and learning strategy.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.2
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• pp.181-189
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• 2013

In this paper, we introduce the fuzzy neural network based on the individual input space to design the pattern recognizer. The proposed networks configure the network by individually dividing each input space. The premise part of the networks is independently composed of the fuzzy partition of individual input spaces and the consequence part of the networks is represented by polynomial functions. The learning of fuzzy neural networks is realized by adjusting connection weights of the neurons in the consequent part of the fuzzy rules and it follows a back-propagation algorithm. In addition, in order to optimize the parameters of the proposed network, we use real-coded genetic algorithms. Finally, we design the optimized pattern recognizer using the experimental data for pattern recognition.

• Journal of Korean Library and Information Science Society
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• v.6
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• pp.53-103
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• 1979

Kyujang-gak was an institution established by the King Jungjo's order to enshrine and edit the royal writings and autographs, and to help the revival of learning with more active services in collection, control, and use of the important materials. Furthermore, it was aimed in its establishment to promote the settlement of an innovative and ideal Royal Regime. In this paper, the Outer Kyujang-gak(外奎章閣) of Kangwha Magistracy(江華府), which was one of the lower branches of the Kyujanggak(奎章閣), will be treated, especially about its details of establishment, location, functions, the characteristics and value of its collection. After the Japanese invasion of Korea in 1592, the Historical Deposit Library(史庫) was established at the Kangwha Magistracy to take custody of the royal writings and autographs. An Annex(別庫) was built near by the Historical Deposit Library to enlarge the space in the reign of the King Hyojong. These spaces, however, become insufficient as the amount of materials deposited expanded, and custody for them was also not successful. Therefore, at the April of the 6th year of the King Jungjo's rule, the Outer Kyujang-gak was built at the east of the Temporary Palace(行宮) within Kangwha Magistracy, where the royal materials were deposited. This Outer Kynjang-gak was also called 'Kangdo Oe-gak(江都外閣)', 'Kyujang Oe-gak(奎章外閣)' or 'Simdo Oe-gak(心都外閣)', and its major function was to take custody of the materials and to hand them down to the next generations forever. The Kandwha Magistrate(江華留守) was responsible for the management of the Outer Kyujang-gak. Regular events for the book keeping were enshrinement, inventory and airing. In the 6th year in the reign of the King Jungjo, 4,892 volumes consisting of 762 titles were moved here from the Bon-gmodang(奉謨堂), the Seoseo(西序) in Main Palace, the Annex(別庫), the Deposit Library(史庫) mentioned above, the Kaegsa(客舍) and Chaeg-go(冊庫) within Kangwha Magistracy. By the end of the Joseon Dynasty, through fourteen times of addition altogether, the number of collection enshrined here reached 6,400 volumes consisting of 1,212 titles. The significance of this Outer Kyujang-gak established at the Kangwha Magistracy is in the point that this was one of the most important deopsit libraries of the Joseon Dynasty.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.170-171
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• 2013

In aspect of HCI(Human Computer Interaction) gameplay is the procedure to solve the problem that gamers encounter in order to generate or discover a new rule to achieve gamers' goal. The goal of this research is to investigate the structure and understand the gameplay in aspect of affordance from ecological psychology rather than the traditional problem solving theory. This research selects 'World of Warcraft' as MMORPG(Massively Multiplayer Online Role Playing Game). Five expert gamers participated in this experiment. We record all gameplay using audio and video device. We conducted protocol analysis as qualitative method based on the verbal report and action protocol during game playing. As result, gameplay based on affordance includes selection and relation. We found that subjects selected one thing at once with attention. Moreover, we found that there were two behaviors : exploratory action and performatory action. We believe that learning, utilization, and transformation for affordance appear. The result of this research imply to suggest design guideline for game design methodology when designers develop game.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12A
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• pp.1181-1187
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• 2010

This paper proposes a mobile AI (Artificial Intelligence) conducting decision-making in the game through education for intelligent character on the basis of Neural Network. Neural Network is learned through the input/output value of the algorithm which defines the game rule and the problem solving method. The learned character is able to perceive the circumstances and make proper action. In this paper, the mobile AI using Neural Network has been step-by-step designed, and a simple game has been materialized for its functional experiment. In this game, the goal, the character, and obstacles exist on regular 2D space, and the character, evading obstacles, has to move where the goal is. The mobile AI can achieve its goals in changing environment by learning the solution to several problems through the algorithm defined in each experiment. The defined algorithm and Neural Network are designed to make the input/output system the same. As the experimental results, the suggested mobile AI showed that it could perceive the circumstances to conduct action and to complete its mission. If mobile AI learns the defined algorithm even in the game of complex structure, its Neural Network will be able to show proper results even in the changing environment.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.6
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• pp.551-558
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• 2013

A support vector machine (SVM) is a very powerful classification algorithm when a set of training data, each marked as belonging to one of several categories, is given. Therefore, SVM techniques have been used as one of the diagnostic tools in machine learning as well as in pattern recognition. In this paper, we present the results of classifying ball bearing fault types and severities using SVM with an optimized feature set based on the minimum distance rule. A feature set as an input for SVM includes twelve time-domain and nine frequency-domain features that are extracted from the measured vibration signals and their decomposed details and approximations with discrete wavelet transform. The vibration signals were obtained from a test rig to simulate various bearing fault conditions.

• Journal of Biosystems Engineering
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• v.19 no.2
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• pp.124-137
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• 1994

Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.