• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.57-71
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• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

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

• Science of Emotion and Sensibility
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• v.11 no.4
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• pp.461-480
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• 2008

There are innumerable studies on technology adoption and usage continuance; most examine cognitive factors while affective factors or the feelings of users are left relatively unexplored. Although attitude and user satisfaction are factors commonly considered in Information Systems(IS) research, they represent only some aspects of feelings. In contrast, researchers in diverse fields have begun to note the importance of feelings in understanding and predicting human behavior. Feelings are anticipated to be essential particularly in the context of modern applications, such as mobile internet(M-internet) services, where users are not simply technology users but also service consumers. Drawing on the support of consumer research, social psychology and computer science, this study proposes a balanced cognition-affect model of IS continuance. Prior works in relation to IS research have already considered the emotional factors. The common factors are enjoyment, anxiety, affect and satisfaction. The main difference in our study is that the factors that we used are the primary dimensions of affect according to Circumplex Model of Affect. The horizontal axis of the model represents the pleasure dimension and the vertical represents the arousal dimension. Other emotional factors such as enjoyment and anxiety can be viewed as a combination of these two dimensions, and they can be placed in the vector space formed by these two primary dimensions. Affect has been defined as the enjoyment a person derives from using computers. Satisfaction has different conceptualizations. It has been conceptualized as judgment based on the expectation disconfirmation theory. Thus, while prior works considered the direct and indirect effects of "feeling-related constructs"(enjoyment and anxiety) on usage behavior, our study proposes effects of "feeling-based constructs"(pleasure and arousal). The balanced cognition-affect model is tested in a survey of, M-internet service users. The results establish the validity of the model.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.85-92
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• 2017

As accessibility toward traditional cultural contents drops compared to its increase in production, the need for higher accessibility for continued management and research to exist. For this, this paper introduces an image classifier model for traditional images based on artificial neural networks, which converts the input image's features into a vector space and by utilizing a RNN based model it recognizes and compares the details of the input which enables the classification of traditional images. This enables the classifiers to classify similarly looking traditional images more precisely by focusing on the details. For the training of this model, a wide range of images were arranged and collected based on the format of the Korean information culture field, which contributes to other researches related to the fields of using traditional cultural images. Also, this research contributes to the further activation of demand, supply, and researches related to traditional culture.

• Tunnel and Underground Space
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• v.13 no.3
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• pp.187-195
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• 2003

This case study which is to make 2-Dimension earth's crust structures clearly is about the great boring-hole blasting to provide ground vibration source of the reflected wave research on the Korean Peninsula earth's crust structures research. For this study we've done blasting twice-500 ㎏/charge per delay, 1,000 ㎏/charge per delay, and the specifications of blasting are the following - dia.: 300 ㎜, boring-depth : 100m, besides, we used the explosives and electric detonators which have sufficient detonating velocity and very excellent safety, capacity of detonating, accurate delay time. We charged explosives into steel pipe with bulk type to avoid dead pressure by ground water. And then we tested about pipe airtight and blasting to certificate which has no problem by using on this study. In the results, we succeeded each blasting in Seosan, Youngdong. For the Peak Sum Vector(PSV) around the blasting at the main points, its real measured PSV is higher 180 % than estimated PSV with USBM. In this study we can't to be analysis of vibration velocity, but to be key providing vibration source.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.1
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• pp.19-29
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• 2000

Because the previous simulation tool for attitude control of satellite was designed for the modeling of rigid body and PD controller, the attitude error can be made more than the limitation value for keeping for communication link, and then the communication link can be lost at moving of satellite. So, for rapid attitude restoration and design of stable and modernized controller, the modelling of rigid body and flexible body structure for moving GEO and LEO satellites were performed. Also the minimum time controller is designed for the rapid restoration of attitude error at communication broken and to minimize the disconnection period from ground communication system during the satellite stationkeeping. The linear regulator is designed using the space state vector that is better than accuracy and stability of PD controller. Firstly the simulation was performed for comparison of the rigid and stability of PD controller. Firstly the simulation was performed for comparison of the rigid and flexible models using PD controller and the case of the pitch angle changing by ground command, and the case of the periodic north-south stationkeeping are performed for the analysis of response characteristics of each controller when the attitude is changed. As a result, the flexible body model represents more sililar results of real situation than the rigid body model. The minimum time controller can restore 7 times rapidly than PD controller for its lost attitude. The linear regulator has several merits for capability of adaptation against the external disturbance, stability and response time. In future, we can check the estimated results using this satellite model and controller for real operation. Futhermore the development of new controller and training can be supported.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.36 no.3
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• pp.257-265
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• 2000

Brushless DC(BLDC) motors are widely used as AC servo motors in factory automation fields because of their quick instantaneous mobility, good energy saving efficiency and easiness of design for control system comparing with induction motors. Recently, a Two-Degree-of-Freedom(2DOF) PI control law has been adopted to some application parts to accomplish an advanced speed control of BLDC motors. The method can treat the two conflicting performances, minimum tracking errors versus reference inputs without large overshoot and rejection of some disturbances including modeling errors, independently. However, the method can not design the optimal system which is able to minimize tracking errors and energy consumption simultaneously. In this paper, a 2DOF integral type optimal servo control method is investigated to promote the speed control performances of BLDC motors considering energy consumption. In order to applicate the method to the speed servo system of the BLDC motor, the motor is modeled in the state space using the vector control and decoupling technique. To verify the validity of the suggested method, some simulations and experiments are performed.

• Parasites, Hosts and Diseases
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• v.58 no.3
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• pp.267-278
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• 2020

The heterogeneity and complexity of malaria involves political and natural environments, socioeconomic development, cross-border movement, and vector biology; factors that cannot be changed in a short time. This study aimed to assess the impact of economic growth and cross-border movement, toward elimination of malaria in Yunnan Province during its pre-elimination phase. Malaria data during 2011-2016 were extracted from 18 counties of Yunnan and from 7 villages, 11 displaced person camps of the Kachin Special Region II of Myanmar. Data of per-capita gross domestic product (GDP) were obtained from Yunnan Bureau of Statistics. Data were analyzed and mapped to determine spatiotemporal heterogeneity at county and village levels. There were a total 2,117 malaria cases with 85.2% imported cases; most imported cases came from Myanmar (78.5%). Along the demarcation line, malaria incidence rates in villages/camps in Myanmar were significantly higher than those of the neighboring villages in China. The spatial and temporal trends suggested that increasing per-capita GDP may have an indirect effect on the reduction of malaria cases when observed at macro level; however, malaria persists owing to complex, multi-faceted factors including poverty at individual level and cross-border movement of the workforce. In moving toward malaria elimination, despite economic growth, cooperative efforts with neighboring countries are critical to interrupt local transmission and prevent reintroduction of malaria via imported cases. Cross-border workers should be educated in preventive measures through effective behavior change communication, and investment is needed in active surveillance systems and novel diagnostic and treatment services during the elimination phase.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.28-38
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• 2005

According to the recent development of measurement system utilizing one or a set of boreholes, visualization of the explored underground became to be a major issue. It induced even the introduction of monitoring apparatuses on the borehole wall with multi-function tool, but the usage of these was often limited by where is unfavorable rock condition and a few of engineers can approach. And so, a portable type of borehole camera with only the essential function has been investigated and a few of commercial models about this is recently being applied into the field condition. This paper was based on the monitoring results obtained using a commercial model by Dr. Nakagawa. Discontinuities in rock mass were the topic for the visualization, and it was studied how can visualize their three dimensional distribution and what a numerical formulation is needed and how to understand the visualization result. The numerical formulation was based on the geometric correlation between the dip direction / dip of discontinuous plane and the trend / plunge of borehole, a set of the equation of a plane was induced. As field application of this into two places, it is found that the above visualization methodology will be especially an useful geotechlical tool for analyzing the local distribution of discontinuities.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.425-438
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• 2012

In this paper, We propose Augmented Reality (AR) System for the interaction between user's hand motion and virtual object motion based on computer vision. The previous AR system provides inconvenience to user because the users have to control the marker and the sensor like a tracker. We solved the problem through hand motion and provide the convenience to the user. Also the motion of virtual object using a physical phenomenon gives a reality. The proposed system obtains geometrical information by the marker and hand. The system environments like virtual space of moving virtual ball and bricks are made by using the geometrical information and user's hand motion is obtained from the hand's information with extracted feature point through the taping hand. And it registers a virtual plane stably by getting movement of the feature points. The movement of the virtual ball basically is parabolic motion with a parabolic equation. When the collision occurs either the planes or the bricks, we show movement of the virtual ball with ball position and normal vector of plane and the ball position is faulted. So we showed corrected ball position through experiment. and we proved that this system can replaced the marker system to compare to jitter of augmented virtual object and progress speed with it.