• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.47-67
• /
• 2017

Steel plate faults is one of important factors to affect the quality and price of the steel plates. So far many steelmakers generally have used visual inspection method that could be based on an inspector's intuition or experience. Specifically, the inspector checks the steel plate faults by looking the surface of the steel plates. However, the accuracy of this method is critically low that it can cause errors above 30% in judgment. Therefore, accurate steel plate faults diagnosis system has been continuously required in the industry. In order to meet the needs, this study proposed a new steel plate faults diagnosis system using Simultaneous MTS (S-MTS), which is an advanced Mahalanobis Taguchi System (MTS) algorithm, to classify various surface defects of the steel plates. MTS has generally been used to solve binary classification problems in various fields, but MTS was not used for multiclass classification due to its low accuracy. The reason is that only one mahalanobis space is established in the MTS. In contrast, S-MTS is suitable for multi-class classification. That is, S-MTS establishes individual mahalanobis space for each class. 'Simultaneous' implies comparing mahalanobis distances at the same time. The proposed steel plate faults diagnosis system was developed in four main stages. In the first stage, after various reference groups and related variables are defined, data of the steel plate faults is collected and used to establish the individual mahalanobis space per the reference groups and construct the full measurement scale. In the second stage, the mahalanobis distances of test groups is calculated based on the established mahalanobis spaces of the reference groups. Then, appropriateness of the spaces is verified by examining the separability of the mahalanobis diatances. In the third stage, orthogonal arrays and Signal-to-Noise (SN) ratio of dynamic type are applied for variable optimization. Also, Overall SN ratio gain is derived from the SN ratio and SN ratio gain. If the derived overall SN ratio gain is negative, it means that the variable should be removed. However, the variable with the positive gain may be considered as worth keeping. Finally, in the fourth stage, the measurement scale that is composed of selected useful variables is reconstructed. Next, an experimental test should be implemented to verify the ability of multi-class classification and thus the accuracy of the classification is acquired. If the accuracy is acceptable, this diagnosis system can be used for future applications. Also, this study compared the accuracy of the proposed steel plate faults diagnosis system with that of other popular classification algorithms including Decision Tree, Multi Perception Neural Network (MLPNN), Logistic Regression (LR), Support Vector Machine (SVM), Tree Bagger Random Forest, Grid Search (GS), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The steel plates faults dataset used in the study is taken from the University of California at Irvine (UCI) machine learning repository. As a result, the proposed steel plate faults diagnosis system based on S-MTS shows 90.79% of classification accuracy. The accuracy of the proposed diagnosis system is 6-27% higher than MLPNN, LR, GS, GA and PSO. Based on the fact that the accuracy of commercial systems is only about 75-80%, it means that the proposed system has enough classification performance to be applied in the industry. In addition, the proposed system can reduce the number of measurement sensors that are installed in the fields because of variable optimization process. These results show that the proposed system not only can have a good ability on the steel plate faults diagnosis but also reduce operation and maintenance cost. For our future work, it will be applied in the fields to validate actual effectiveness of the proposed system and plan to improve the accuracy based on the results.

• Journal of Science of Art and Design
• /
• v.11
• /
• pp.221-249
• /
• 2007

Today, photography is facing to the crisis of identity and dilemma of ontology from the digital imaging process in the new technology form. It is very important points to say rethinking of the traditional photographic medium, that has changed the way we view the world and ourselves is perhaps an understatement and that photography has transformed our essential understanding of reality. Now, no longer are photographic images regarded as the true automatic recording, innocent evidence and the mirror to the reality. Rather, photography constructs the world for our entertainment, helping to create the comforting illusions by which we live. The recognition that photographs are not constructions and reflections of reality, is the basis for the actual presence within the contemporary photographic world. It is shock. This thesis's aim is to look for the problems of photographic identity and ontological crisis that is controlling and regulating digital photographic imagery, allowing the reproduction of the electronic simulations era. Photography loses its special aesthetic status and becomes no more true information and, exclusively evidence by traditional film and paper that appeared both as a technological accuracy and as a medium-specific aesthetic. The result, photography is facing two crises, one is the photographic ontology(the introduction of computerized digital images) and the other is photographic epistemology(having to do broader changes in ethics, knowledge and culture). Taken together, these crises apparently threaten us with the death of photography, with the 'end' of photography and the culture it sustains. The thesis's meaning is to look into the dilemma of photography's ontology and epistemology, especially, automatical index and digital codes from its origin, meaning, and identity as the technological medium. Thus, in particular, thesis focuses on the analog imagery presence, from the nature in the material world, and the digital imagery presence from the cultural situations in our society. And also thesis's aim is to examine the main issues of the history of photography has been concentrated on the ontological arguments since the discovery of photography in 1839. Photography has never been only one static technology form. Rather, its nearly two centuries of technological development have been marked by numerous, competing of technological innovation and self revolution from the dual aspects. This thesis examines recent account of photography by the analysis of the medium's concept, meaning, identity between film base image and digital base image from the aspects of photographic ontology and epistemology. Thus, the structure of thesis is fairy straightforward to examine what appear to be two opposing view of photographic conditions and ontological situations. Thesis' view contrasts that figure out the value of photography according to its fundamental characteristic as a medium. Also, it seeks a possible solution to the dilemma of photographic ontology through the medium's origin from the early years of the nineteenth century to the raising questions about the different meaning(analog/digital) of photography, now. Finally, this thesis emphasizes and concludes that the photographic ontological crisis reflects to the paradoxical dynamic structure, that unsolved the origins of the medium, itself. Moreover, even photography is not single identity of the photographic ontology, and also can not be understood as having a static identity or singular status from the dynamic field of technologies, practices, and images.

• Journal of Intelligence and Information Systems
• /
• v.20 no.4
• /
• pp.89-105
• /
• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• The Journal of Korean Society for Radiation Therapy
• /
• v.24 no.2
• /
• pp.123-135
• /
• 2012

Purpose: It is essential to minimize the movement of tumor due to respiratory movement at the time of respiration controlled radiotherapy of non-small cell lung cancer patient. Accordingly, this Study aims to evaluate the usefulness of restricted respiratory period by comparing and analyzing the treatment plans that apply free and restricted respiration period respectively. Materials and Methods: After having conducted training on 9 non-small cell lung cancer patients (tumor n=10) from April to December 2011 by using 'signal monitored-breathing (guided- breathing)' method for the 'free respiratory period' measured on the basis of the regular respiratory period of the patents and 'restricted respiratory period' that was intentionally reduced, total of 10 CT images for each of the respiration phases were acquired by carrying out 4D CT for treatment planning purpose by using RPM and 4-dimensional computed tomography simulator. Visual gross tumor volume (GTV) and internal target volume (ITV) that each of the observer 1 and observer 2 has set were measured and compared on the CT image of each respiratory interval. Moreover, the amplitude of movement of tumor was measured by measuring the center of mass (COM) at the phase of 0% which is the end-inspiration (EI) and at the phase of 50% which is the end-exhalation (EE). In addition, both observers established treatment plan that applied the 2 respiratory periods, and mean dose to normal lung (MDTNL) was compared and analyzed through dose-volume histogram (DVH). Moreover, normal tissue complication probability (NTCP) of the normal lung volume was compared by using dose-volume histogram analysis program (DVH analyzer v.1) and statistical analysis was performed in order to carry out quantitative evaluation of the measured data. Results: As the result of the analysis of the treatment plan that applied the 'restricted respiratory period' of the observer 1 and observer 2, there was reduction rate of 38.75% in the 3-dimensional direction movement of the tumor in comparison to the 'free respiratory period' in the case of the observer 1, while there reduction rate was 41.10% in the case of the observer 2. The results of measurement and comparison of the volumes, GTV and ITV, there was reduction rate of $14.96{\pm}9.44%$ for observer 1 and $19.86{\pm}10.62%$ for observer 2 in the case of GTV, while there was reduction rate of $8.91{\pm}5.91%$ for observer 1 and $15.52{\pm}9.01%$ for observer 2 in the case of ITV. The results of analysis and comparison of MDTNL and NTCP illustrated the reduction rate of MDTNL $3.98{\pm}5.62%$ for observer 1 and $7.62{\pm}10.29%$ for observer 2 in the case of MDTNL, while there was reduction rate of $21.70{\pm}28.27%$ for observer 1 and $37.83{\pm}49.93%$ for observer 2 in the case of NTCP. In addition, the results of analysis of correlation between the resultant values of the 2 observers, while there was significant difference between the observers for the 'free respiratory period', there was no significantly different reduction rates between the observers for 'restricted respiratory period. Conclusion: It was possible to verify the usefulness and appropriateness of 'restricted respiratory period' at the time of respiration controlled radiotherapy on non-small cell lung cancer patient as the treatment plan that applied 'restricted respiratory period' illustrated relative reduction in the evaluation factors in comparison to the 'free respiratory period.

• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.35 no.3
• /
• pp.41-66
• /
• 2017

The purpose of this research is to empirically trace the junctures of Yigye-gugok managed by Gwan-am Hong Gyeong-mo, a grandson of Yigye Hong Yang-ho who originally designed Yigye-gugok, while reviewing the features of the forms and patterns of gugok. The results of the research are as follows. 1. Ui-dong was part of the domain of the capital during the Chosun dynasty, which also is located in the city of Seoul as a matter of administrative zone. Likewisely, Yigye-gugok is taken as a special meaning for it was one and only gugok. Starting with Mangyeong Waterfall as the $1^{st}$ gok, Yigye follows through the $2^{nd}$ gok of Jeokchwibyeong Rock, the $3^{rd}$ gok of Chanunbong Peak, the $4^{th}$ gok of Jinuigang Rock, the $5^{th}$ gok of Okkyeongdae Rock, the $6^{th}$ gok of Wolyeongdam Pond, the $7^{th}$ gok of Tagyeongam Rock, the $8^{th}$ gok of Myeongoktan Stream, and the $9^{th}$ gok of Jaeganjeong Pavilion. Of these, Mangyeong Waterfall, Chanunbong Peak, and Okkyeongdae Rock are distinct for their locations in as much as their features, while estimated locations for Jinuigang Rock, Wolyeongdam Pond, Myeongoktan Stream, and Jaeganjeong Pavilion were discovered. However, Jeokchwibyeong Rock and Tagyeongam Rock demonstrated multiple locations in close resemblance to documentary literatures within secretive proximity, whereas geography, scenery, and sighted objects were considered to evaluate the 1st estimated location. Through these endeavored, it was possible to identify the shipping routes and structures for the total distance of 2.1km running from the $1^{st}$ gok to the $9^{th}$ gok, which nears Gwanam's description of 5ri(里), or approximately 1.96km for gugok. 2. Set towards the end of the $18^{th}$ century, Yigye-gugok originated from a series of work shaping the space of Hong Yang-ho's tomb into a space for the family. Comparing Yigye-gugok to other gugoks, numerous differences are apparent from beyond the rather more general format such as adjoining the $8^{th}$ gok while paving through the lower directions from the upper directions of the water. This gives rises to the interpretation such that Yigye-gugok was positioned to separate the doman of the family from those of the other families in power, thereby taking over Ui-dong. Yet, the aspect of the possession of the space lends itself to the determination that the location positioned at the $8^{th}$ gok above Mangyeongpok Waterfall representing Wooyi-dong was a consequence of the centrifugal space creation efforts. 3. While writings and poetic works were manufactured in such large quantities in Yigye-gugok whose products of setters and managers seemed intended towards gugok-do and letters carved on the rocks among others, there is yet a tremendous lack of visual media in the same respect. 'Yigye-gugok Daejacheop' Specimens of Handwriting offers the traces of Gwanam's attempts to engrave gakja at the food of Yigye-gugok. This research was able to ascertain that 'Yigye-gugok Daejacheop' Specimens of Handwriting was a product of Hong Yang-ho's collections maintained under the auspices of the National Central Museum, which are renowned for Song Shi-yeol's penmanship.

• Journal of Intelligence and Information Systems
• /
• v.24 no.3
• /
• pp.1-19
• /
• 2018

Large amount of data is now available for research and business sectors to extract knowledge from it. This data can be in the form of unstructured data such as audio, text, and image data and can be analyzed by deep learning methodology. Deep learning is now widely used for various estimation, classification, and prediction problems. Especially, fashion business adopts deep learning techniques for apparel recognition, apparel search and retrieval engine, and automatic product recommendation. The core model of these applications is the image classification using Convolutional Neural Networks (CNN). CNN is made up of neurons which learn parameters such as weights while inputs come through and reach outputs. CNN has layer structure which is best suited for image classification as it is comprised of convolutional layer for generating feature maps, pooling layer for reducing the dimensionality of feature maps, and fully-connected layer for classifying the extracted features. However, most of the classification models have been trained using online product image, which is taken under controlled situation such as apparel image itself or professional model wearing apparel. This image may not be an effective way to train the classification model considering the situation when one might want to classify street fashion image or walking image, which is taken in uncontrolled situation and involves people's movement and unexpected pose. Therefore, we propose to train the model with runway apparel image dataset which captures mobility. This will allow the classification model to be trained with far more variable data and enhance the adaptation with diverse query image. To achieve both convergence and generalization of the model, we apply Transfer Learning on our training network. As Transfer Learning in CNN is composed of pre-training and fine-tuning stages, we divide the training step into two. First, we pre-train our architecture with large-scale dataset, ImageNet dataset, which consists of 1.2 million images with 1000 categories including animals, plants, activities, materials, instrumentations, scenes, and foods. We use GoogLeNet for our main architecture as it has achieved great accuracy with efficiency in ImageNet Large Scale Visual Recognition Challenge (ILSVRC). Second, we fine-tune the network with our own runway image dataset. For the runway image dataset, we could not find any previously and publicly made dataset, so we collect the dataset from Google Image Search attaining 2426 images of 32 major fashion brands including Anna Molinari, Balenciaga, Balmain, Brioni, Burberry, Celine, Chanel, Chloe, Christian Dior, Cividini, Dolce and Gabbana, Emilio Pucci, Ermenegildo, Fendi, Giuliana Teso, Gucci, Issey Miyake, Kenzo, Leonard, Louis Vuitton, Marc Jacobs, Marni, Max Mara, Missoni, Moschino, Ralph Lauren, Roberto Cavalli, Sonia Rykiel, Stella McCartney, Valentino, Versace, and Yve Saint Laurent. We perform 10-folded experiments to consider the random generation of training data, and our proposed model has achieved accuracy of 67.2% on final test. Our research suggests several advantages over previous related studies as to our best knowledge, there haven't been any previous studies which trained the network for apparel image classification based on runway image dataset. We suggest the idea of training model with image capturing all the possible postures, which is denoted as mobility, by using our own runway apparel image dataset. Moreover, by applying Transfer Learning and using checkpoint and parameters provided by Tensorflow Slim, we could save time spent on training the classification model as taking 6 minutes per experiment to train the classifier. This model can be used in many business applications where the query image can be runway image, product image, or street fashion image. To be specific, runway query image can be used for mobile application service during fashion week to facilitate brand search, street style query image can be classified during fashion editorial task to classify and label the brand or style, and website query image can be processed by e-commerce multi-complex service providing item information or recommending similar item.

• Journal of Korean Academy of Nursing
• /
• v.2 no.1
• /
• pp.3-33
• /
• 1971

Nursing of today has as one of its objectives the solving of problems related to human needs arising from the demands of a rapidly changing society. This nursing objective, I believe, can he attained by the appropriate application of scientific principles in the giving of comprehensive nursing care. Comprehensive nursing care may be defined as nursing care which meets all of the patient's needs. the needs of patients are said to fall into five broad categories: physical needs, psychological needs, environmental needs, socio-economic needs, and teaching needs. Most people who become ill have adjustment problems related to their new situation. Because patient teaching is one of the most important functions of professional nursing, the success of this teaching may be used as a gauge for evaluating comprehensive nursing care. This represents a challenge foe the future. A questionnaire consisting of 67 items was distributed to 200 professional nurses working ill direct patient care at Yonsei University Medical Center in Seoul, Korea. 160 (80,0%) nurses of the total sample returned completed questionnaires 81 (50.6%) nurses were graduates of 3 fear diploma courser 79 (49.4%) nurses were graduates of 4 year collegiate nursing schools in Korea 141 (88,1%) nurses had under 5 years of clinical experience in a medical center, while 19 (11.9%) nurses had more than 5years of clinical experience. Three hypotheses were tested: 1. “Nurses had high levels of concept and knowledge toward patient teaching”-This was demonstrated by the use of a statistical method, the mean average. 2. “Nurses graduating from collegiate programs and diploma school programs of nursing show differences in concepts and knowledge toward patient teaching”-This was demonstrated by a statistical method, the mean average, although the results showed little difference between the two groups. 3. “Nurses having different amounts of clinical experience showed differences in concepts and knowledge toward patient teaching”-This was demonstrated by the use of a statistical method, the mean average. 2. “Nurses graduating from collegiate programs and diploma school programs of nursing show differences in concepts and knowledge toward patient teaching”-This was demonstrated by a statistical method, the mean average, although the results showed little difference between the two groups. 3. “Nurses having different amounts of clinical experience showed differences in concepts and knowledge toward patient teaching”-This was demonstrated by the use of the T-test. Conclusions of this study are as follow: Before attempting the explanation, of the results, the questionnaire will he explained. The questionnaire contained 67 questions divided into 9 sections. These sections were: concept, content, time, prior preparation, method, purpose, condition, evaluation, and recommendations for patient teaching. 1. The nurse's concept of patient teaching: Most of the nurses had high levels of concepts and knowledge toward patient teaching. Though nursing service was task-centered at the turn of the century, the emphasis today is put on patient-centered nursing. But we find some of the nurses (39.4%) still are task-centered. After, patient teaching, only a few of the nurses (14.4%) checked this as “normal teaching.”It seems therefore that patient teaching is often done unconsciously. Accordingly it would he desirable to have correct concepts and knowledge of teaching taught in schools of nursing. 2. Contents of patient teaching: Most nurses (97.5%) had good information about content of patient teaching. They teach their patients during admission about their diseases, tests, treatments, and before discharge give nurses instruction about simple nursing care, personal hygiene, special diets, rest and sleep, elimination etc. 3. Time of patient teaching: Teaching can be accomplished even if there is no time set aside specifically for it. -a large part of the nurse's teaching can be done while she is giving nursing care. If she believes she has to wait for time free from other activities, she may miss many teaching opportunities. But generally proper time for patient teaching is in the midmorning or midafternoon since one and a half or two hours required. Nurses meet their patients in all stages of health: often tile patient is in a condition in which learning is impossible-pain, mental confusion, debilitation, loss of sensory perception, fear and anxiety-any of these conditions may preclude the possibility of successful teaching. 4. Prior preparation for patient teaching: The teaching aids, nurses use are charts (53.1%), periodicals (23.8%), and books (7.0%) Some of the respondents (28.1%) reported that they had had good preparation for the teaching which they were doing, others (27.5%) reported adequate preparation, and others (43.8%) reported that their preparation for teaching was inadequate. If nurses have advance preparation for normal teaching and are aware of their objectives in teaching patients, they can do effective teaching. 5. Method of patient teaching: The methods of individual patient teaching, the nurses in this study used, were conversation (55.6%) and individual discussion (19.2%) . And the methods of group patient teaching they used were demonstration (42.3%) and lecture (26.2%) They should also he prepared to use pamphlet and simple audio-visual aids for their teaching. 6. Purposes of patient teaching: The purposes of patient teaching is to help the patient recover completely, but the majority of the respondents (40.6%) don't know this. So it is necessary for them to understand correctly the purpose of patient teaching and nursing care. 7. Condition of patient teaching: The majority of respondents (75.0%) reported there were some troubles in teaching uncooperative patients. It would seem that the nurse's leaching would be improved if, in her preparation, she was given a better understanding of the patient and communication skills. The majority of respondents in the total group, felt teaching is their responsibility and they should teach their patient's family as well as the patient. The place for teaching is most often at the patient's bedside (95.6%) but the conference room (3.1%) is also used. It is important that privacy be provided in learning situations with involve personal matters. 8. Evaluation of patient teaching: The majority of respondents (76.3%,) felt leaching is a highly systematic and organized function requiring special preparation in a college or university, they have the idea that teaching is a continuous and ever-present activity of all people throughout their lives. The suggestion mentioned the most frequently for improving preparation was a course in patient teaching included in the basic nursing program. 9. Recommendations: 1) It is recommended, that in clinical nursing, patient teaching be emphasized. 2) It is recommended, that insertive education the concepts and purposes of patient teaching he renewed for all nurses. In addition to this new knowledge, methods and materials which can be applied to patient teaching should be given also. 3) It is recommended, in group patient teaching, we try to embark on team teaching.

• Journal of Intelligence and Information Systems
• /
• v.24 no.2
• /
• pp.85-109
• /
• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Journal of Oral Medicine and Pain
• /
• v.33 no.3
• /
• pp.279-294
• /
• 2008

This study aimed to make an analysis of the occlusion in the state of muscle fatigue produced by excessive mouth opening and clenching during the dental treatment to control the dental pain and to evaluate the sensory nerve in the muscle pain state. Most of the reasons why patients visit the dental office result in pain-either conceivably the dental origin pain or the non-dental origin pain. The dental offices have many therapeutic actions to produce the masticatory muscle fatigue for the treatment. Dental treatment with long minutes of mouth opening can cause some headaches, masticatory muscle pain and mouth opening difficulties. Patients with mastication problems who visits a dental office to alleviate pain run against another unexpected pain with other aspects. This study uses T-scan II system(Tekscan Co., USA) for the evaluation on the occlusal pattern in the experimental muscle fatigue after clenching, opening the mouth excessively and chewing gum. The occlusal contact pattern is analyzed by the contact timing, namely first, intercuspal, maximum and end point of contact. This inspection was performed at frequencies of 2000Hz, 250 Hz and 5 Hz before and after each experimental muscle pain was produced to 24 subjects who had normal occlusion without the orthodontic treatment or a wide range of the prosthesis by using $neurometer^{\circledR}$ CPT/C(Neurotron, Inc. Baltimore, Maryland, USA). The measuring sites were mandibular nerve experimental muscle fatigue respectively. This study could obtain the following results after the assessment of occlusion and sensory nerve of the experimental muscle fatigue. 1. There were the fastest expression after the excessive mouth opening in muscle fatigue and after tooth clenching in muscle pain. In the visual analog scale that records the subjective level, there was the highest scale after the clenching in the muscle fatigue in jumping off the point of pain. 2. Tooth contact time, contact force, relative contact force on the point of the first contact had no difference, and there were decreases in the contact force after the excessive mouth opening on intercuspal position point, after the excessive mouth opening and the gum chewing on the point of the maximum, and in the contact time after all the experimental muscle fatigue state on the point of the end contact. 3. There was no statistic significance in the current perception threshold before and after the experimental muscle fatigue. 4. There was no significant difference in the contact number, the maximal contact number on the point of the first contact, and the contact number after the mouth opening and gum chewing on the point of the intercuspal position and the contact number after the experimental muscle fatigue on the maximum point, and showed significant decreases. In conclusion, it was found that the occlusal pattern can cause the changes on the case of the clinical muscle weakness by intra-external oral events. It was important that the sedulous attention to details is required during dental treatment in case of excessive mouth opening, mastication and clenching.

• Journal of Dairy Science and Biotechnology
• /
• v.34 no.2
• /
• pp.99-116
• /
• 2016

We herein performed animal safety assessment in accordance with Good Laboratory Practice (GLP) regulations with the aim of developing sialic acid from glycomacropeptide (hereafter referred to as "GMP") as an index ingredient and functional component in functional foods. GMP is a type of whey protein derived from milk and a safe food, with multiple functions, such as antiviral activity. A test substance was produced containing 7% (w/w) sialic acid and mostly-hydrolyzed whey protein (hereafter referred to as "7%-GNANA") by enzymatic treatment of substrate GMP. The maximum intake test dose level was selected based on 5,000 mg/kg/day dose set for male NOEL (no-observed-effect-level) and female NOAEL (no-observed-adverse-effect-level) determined by a dose-range finding (DRF) test (GLP Center of Catholic University of Daegu, Report No. 15-NREO-001) that was previously conducted with the same test substance. To evaluate the toxicity of a repeated oral dose of the test substance in connection with the previous DRF study, 1,250, 2,500, and 5,000 mg/kg of the substance were administered by a probe into the stomachs of 6-week-old SPF Sprague-Dawley male and female rats for 90 d. Each test group consisted of 10 male and 10 female rats. To determine the toxicity index, all parameters, such as observation of common signs; measurements of body weight and food consumption; ophthalmic examination; urinalysis, electrolyte, hematological, and serum biochemical examination; measurement of organ weights during autopsy; and visual and histopathological examinations were conducted according to GLP standards. After evaluating the results based on the test toxicity assessment criteria, it was determined that NOAEL of the test substance, 7%-GNANA, was 5,000 mg/kg/day, for both male and female rats. No animal death was noted in any of the test groups, including the control group, during the study period, and there was no significant difference associated with test substance, as compared with the control group, with respect to general symptoms, body weight changes, food consumption, ophthalmic examination, urinalysis, hematological and serum biochemical examination, and electrolyte and blood coagulation tests during the administration period (P<0.05). As assessed by the effects of the test substance on organ weights, food consumption, autopsy, and histopathological safety, change in kidney weight as an indicator of male NOAEL revealed up to 20% kidney weight increase in the high-dose group (5,000 mg/kg/day) compared with the change in the control group. However, it was concluded that this effect of the test substance was minor. In the case of female rats, reduction of food consumption, increase of kidney weight, and decrease of thymus weight were observed in the high-dose group. The kidney weight increased by 10.2% (left) and 8.9% (right) in the high-dose group, with a slight dose-dependency compared with that of the control group. It was observed that the thymus weight decreased by 25.3% in the high-dose group, but it was a minor test substance-associated effect. During the autopsy, botryoid tumor was detected on the ribs of one subject in the high-dose group, but we concluded that the tumor has been caused by a naturally occurring (non-test) substance. Histopathological examination revealed lesions on the kidney, liver, spleen, and other organs in the low-dose test group. Since these lesions were considered a separate phenomenon, or naturally occurring and associated with aging, it was checked whether any target organ showed clear symptoms caused by the test substance. In conclusion, different concentrations of the test substance were fed to rats and, consequently, it was verified that only a minor effect was associated with the test substance in the high-dose (5,000 mg/kg/day) group of both male and female rats, without any other significant effects associated with the test substance. Therefore, it was concluded that NOAEL of 7%-GNANA (product name: Helicobactrol) with male and female rats as test animals was 5,000 mg/kg/day, and it thus was determined that the substance is safe for the ultimate use as an ingredient of health functional foods.