• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.47-55
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• 2015

Recently, the environment of a hospital information system is a trend to combine various SMART technologies. Accordingly, various smart devices, such as a smart phone, Tablet PC is utilized in the medical information system. Also, these environments consist of various applications executing on heterogeneous sensors, devices, systems and networks. In these hospital information system environment, applying a security service by traditional access control method cause a problems. Most of the existing security system uses the access control list structure. It is only permitted access defined by an access control matrix such as client name, service object method name. The major problem with the static approach cannot quickly adapt to changed situations. Hence, we needs to new security mechanisms which provides more flexible and can be easily adapted to various environments with very different security requirements. In addition, for addressing the changing of service medical treatment of the patient, the researching is needed. In this paper, we suggest a dynamic approach to medical information systems in smart mobile environments. We focus on how to access medical information systems according to dynamic access control methods based on the existence of the hospital's information system environments. The physical environments consist of a mobile x-ray imaging devices, dedicated mobile/general smart devices, PACS, EMR server and authorization server. The software environment was developed based on the .Net Framework for synchronization and monitoring services based on mobile X-ray imaging equipment Windows7 OS. And dedicated a smart device application, we implemented a dynamic access services through JSP and Java SDK is based on the Android OS. PACS and mobile X-ray image devices in hospital, medical information between the dedicated smart devices are based on the DICOM medical image standard information. In addition, EMR information is based on H7. In order to providing dynamic access control service, we classify the context of the patients according to conditions of bio-information such as oxygen saturation, heart rate, BP and body temperature etc. It shows event trace diagrams which divided into two parts like general situation, emergency situation. And, we designed the dynamic approach of the medical care information by authentication method. The authentication Information are contained ID/PWD, the roles, position and working hours, emergency certification codes for emergency patients. General situations of dynamic access control method may have access to medical information by the value of the authentication information. In the case of an emergency, was to have access to medical information by an emergency code, without the authentication information. And, we constructed the medical information integration database scheme that is consist medical information, patient, medical staff and medical image information according to medical information standards.y Finally, we show the usefulness of the dynamic access application service based on the smart devices for execution results of the proposed system according to patient contexts such as general and emergency situation. Especially, the proposed systems are providing effective medical information services with smart devices in emergency situation by dynamic access control methods. As results, we expect the proposed systems to be useful for u-hospital information systems and services.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.133-146
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• 2013

While the use of internet is routine nowadays, users receive and share information through a variety of media. Through the use of internet, information delivery media is diversifying from traditional media of one-way communication, such as newspaper, TV, and radio, into media of two-way communication. In contrast of traditional media, blogs enable individuals to directly upload and share news, which can be considered to have a differential speed of information diffusion than news media that convey information unilaterally. Therefore this Study focused on the difference between online news and social media blogs. Moreover, there are variations in the speed of information diffusion because that information closely related to one person boosts communications between individuals. We believe that users' standard of evaluation would change based on the types of information. As well, the speed of information diffusion would change based on the level of proximity. Therefore, the purpose of this study is to examine the differences in information diffusion based on the types of media. And then information is segmentalized and an examination is done to see how information diffusion differentiates based on the types of information. This study used the Bass diffusion model, which has been frequently used because this model has higher explanatory power than other models by explaining diffusion of market through innovation effect and imitation effect. Also this model has been applied a lot in other information diffusion related studies. The Bass diffusion model includes an innovation effect and an imitation effect. Innovation effect measures the early-stage impact, while the imitation effect measures the impact of word of mouth at the later stage. According to Mahajan et al. (2000), Innovation effect is emphasized by usefulness and ease-of-use, as well Imitation effect is emphasized by subjective norm and word-of-mouth. Also, according to Lee et al. (2011), Innovation effect is emphasized by mass communication. According to Moore and Benbasat (1996), Innovation effect is emphasized by relative advantage. Because Imitation effect is adopted by within-group influences and Innovation effects is adopted by product's or service's innovation. Therefore, ours study compared online news and social media blogs to examine the differences between media. We also choose different types of information including entertainment related information "Psy Gentelman", Current affair news "Earthquake in Sichuan, China", and product related information "Galaxy S4" in order to examine the variations on information diffusion. We considered that users' information proximity alters based on the types of information. Hence, we chose the three types of information mentioned above, which have different level of proximity from users' standpoint, in order to examine the flow of information diffusion. The first conclusion of this study is that different media has similar effect on information diffusion, even the types of media of information provider are different. Information diffusion has only been distinguished by a disparity between proximity of information. Second, information diffusions differ based on types of information. From the standpoint of users, product and entertainment related information has high imitation effect because of word of mouth. On the other hand, imitation effect dominates innovation effect on Current affair news. From the results of this study, the flow changes of information diffusion is examined and be applied to practical use. This study has some limitations, and those limitations would be able to provide opportunities and suggestions for future research. Presenting the difference of Information diffusion according to media and proximity has difficulties for generalization of theory due to small sample size. Therefore, if further studies adopt to a request for an increase of sample size and media diversity, difference of the information diffusion according to media type and information proximity could be understood more detailed.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.63-82
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• 2016

Individuals gather information online to resolve problems in their daily lives and make various decisions about the purchase of products or services. With the revolutionary development of information technology, Web 2.0 has allowed more people to easily generate and use online reviews such that the volume of information is rapidly increasing, and the usefulness and significance of analyzing the unstructured data have also increased. This paper presents an analysis on the lexical features of expert product reviews to determine their influence on consumers' purchasing decisions. The focus was on how unstructured data can be organized and used in diverse contexts through text mining. In addition, diverse lexical features of expert reviews of contents provided by a third-party review site were extracted and defined. Expert reviews are defined as evaluations by people who have expert knowledge about specific products or services in newspapers or magazines; this type of review is also called a critic review. Consumers who purchased products before the widespread use of the Internet were able to access expert reviews through newspapers or magazines; thus, they were not able to access many of them. Recently, however, major media also now provide online services so that people can more easily and affordably access expert reviews compared to the past. The reason why diverse reviews from experts in several fields are important is that there is an information asymmetry where some information is not shared among consumers and sellers. The information asymmetry can be resolved with information provided by third parties with expertise to consumers. Then, consumers can read expert reviews and make purchasing decisions by considering the abundant information on products or services. Therefore, expert reviews play an important role in consumers' purchasing decisions and the performance of companies across diverse industries. If the influence of qualitative data such as reviews or assessment after the purchase of products can be separately identified from the quantitative data resources, such as the actual quality of products or price, it is possible to identify which aspects of product reviews hamper or promote product sales. Previous studies have focused on the characteristics of the experts themselves, such as the expertise and credibility of sources regarding expert reviews; however, these studies did not suggest the influence of the linguistic features of experts' product reviews on consumers' overall evaluation. However, this study focused on experts' recommendations and evaluations to reveal the lexical features of expert reviews and whether such features influence consumers' overall evaluations and purchasing decisions. Real expert product reviews were analyzed based on the suggested methodology, and five lexical features of expert reviews were ultimately determined. Specifically, the "review depth" (i.e., degree of detail of the expert's product analysis), and "lack of assurance" (i.e., degree of confidence that the expert has in the evaluation) have statistically significant effects on consumers' product evaluations. In contrast, the "positive polarity" (i.e., the degree of positivity of an expert's evaluations) has an insignificant effect, while the "negative polarity" (i.e., the degree of negativity of an expert's evaluations) has a significant negative effect on consumers' product evaluations. Finally, the "social orientation" (i.e., the degree of how many social expressions experts include in their reviews) does not have a significant effect on consumers' product evaluations. In summary, the lexical properties of the product reviews were defined according to each relevant factor. Then, the influence of each linguistic factor of expert reviews on the consumers' final evaluations was tested. In addition, a test was performed on whether each linguistic factor influencing consumers' product evaluations differs depending on the lexical features. The results of these analyses should provide guidelines on how individuals process massive volumes of unstructured data depending on lexical features in various contexts and how companies can use this mechanism from their perspective. This paper provides several theoretical and practical contributions, such as the proposal of a new methodology and its application to real data.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.83-98
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• 2015

Many TV viewers use mainly portal sites in order to retrieve information related to broadcast while watching TV. However retrieving information that people wanted needs a lot of time to retrieve the information because current internet presents too much information which is not required. Consequentially, this process can't satisfy users who want to consume information immediately. Interactive video is being actively investigated to solve this problem. An interactive video provides clickable objects, areas or hotspots to interact with users. When users click object on the interactive video, they can see additional information, related to video, instantly. The following shows the three basic procedures to make an interactive video using interactive video authoring tool: (1) Create an augmented object; (2) Set an object's area and time to be displayed on the video; (3) Set an interactive action which is related to pages or hyperlink; However users who use existing authoring tools such as Popcorn Maker and Zentrick spend a lot of time in step (2). If users use wireWAX then they can save sufficient time to set object's location and time to be displayed because wireWAX uses vision based annotation method. But they need to wait for time to detect and track object. Therefore, it is required to reduce the process time in step (2) using benefits of manual annotation method and vision-based annotation method effectively. This paper proposes a novel annotation method allows annotator to easily annotate based on face area. For proposing new annotation method, this paper presents two steps: pre-processing step and annotation step. The pre-processing is necessary because system detects shots for users who want to find contents of video easily. Pre-processing step is as follow: 1) Extract shots using color histogram based shot boundary detection method from frames of video; 2) Make shot clusters using similarities of shots and aligns as shot sequences; and 3) Detect and track faces from all shots of shot sequence metadata and save into the shot sequence metadata with each shot. After pre-processing, user can annotates object as follow: 1) Annotator selects a shot sequence, and then selects keyframe of shot in the shot sequence; 2) Annotator annotates objects on the relative position of the actor's face on the selected keyframe. Then same objects will be annotated automatically until the end of shot sequence which has detected face area; and 3) User assigns additional information to the annotated object. In addition, this paper designs the feedback model in order to compensate the defects which are wrong aligned shots, wrong detected faces problem and inaccurate location problem might occur after object annotation. Furthermore, users can use interpolation method to interpolate position of objects which is deleted by feedback. After feedback user can save annotated object data to the interactive object metadata. Finally, this paper shows interactive video authoring system implemented for verifying performance of proposed annotation method which uses presented models. In the experiment presents analysis of object annotation time, and user evaluation. First, result of object annotation average time shows our proposed tool is 2 times faster than existing authoring tools for object annotation. Sometimes, annotation time of proposed tool took longer than existing authoring tools, because wrong shots are detected in the pre-processing. The usefulness and convenience of the system were measured through the user evaluation which was aimed at users who have experienced in interactive video authoring system. Recruited 19 experts evaluates of 11 questions which is out of CSUQ(Computer System Usability Questionnaire). CSUQ is designed by IBM for evaluating system. Through the user evaluation, showed that proposed tool is useful for authoring interactive video than about 10% of the other interactive video authoring systems.

• Science of Emotion and Sensibility
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• v.21 no.4
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• pp.25-36
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• 2018

Nowadays, it is hard to imagine one's life without smart phones or the internet. Furthermore, not only do people form groups offline, but also online. Based on the cognitive dissonance theory, there have been many studies about how an offline group's initiation affects attitudes toward the group. However, there has not been a study about how an online group's initiation can affect attitudes toward the group. Therefore, this study aims to find out how cognitive dissonance aroused by initiation affects the attitudes toward the online community, which represents groups that are formed online. In addition, this study examined how perceived similarity affects changes in attitude aroused by cognitive dissonance. Participants were assigned to a group in three ways as follows: without a registration process, with a simple registration process, and/or with a complex registration process. Perceived similarity was calculated by the difference between the current body mass index (BMI) and the target BMI of the participant. Attitudes toward the online group were measured by perceived source credibility, perceived information quality, satisfaction, information usefulness, and continuance intention. Contrary to the cognitive dissonance theory, the results showed that when applied to offline social groups, there were conflicting results. There were cases where there was no difference in the evaluation between initiation conditions. However, other cases showed that groups with the most complex registration process were found to have the worst evaluation. People were more favorable toward the group when the perceived similarity was larger. Interestingly, people who had higher perceived similarity had more positive attitudes toward the groups that had been assigned with a registration process compared to the group formed without a registration process. Conversely, people with lower perceived similarity had more positive attitudes toward the group when there was no initiation process. Online communities may use the results of this study to design more suitable registration processes for their communities.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.109-125
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• 2019

As interest on intelligent search engines increases, various studies have been conducted to extract and utilize the features related to products intelligencely. In particular, when users search for goods in e-commerce search engines, the 'color' of a product is an important feature that describes the product. Therefore, it is necessary to deal with the synonyms of color terms in order to produce accurate results to user's color-related queries. Previous studies have suggested dictionary-based approach to process synonyms for color features. However, the dictionary-based approach has a limitation that it cannot handle unregistered color-related terms in user queries. In order to overcome the limitation of the conventional methods, this research proposes a model which extracts RGB values from an internet search engine in real time, and outputs similar color names based on designated color information. At first, a color term dictionary was constructed which includes color names and R, G, B values of each color from Korean color standard digital palette program and the Wikipedia color list for the basic color search. The dictionary has been made more robust by adding 138 color names converted from English color names to foreign words in Korean, and with corresponding RGB values. Therefore, the fininal color dictionary includes a total of 671 color names and corresponding RGB values. The method proposed in this research starts by searching for a specific color which a user searched for. Then, the presence of the searched color in the built-in color dictionary is checked. If there exists the color in the dictionary, the RGB values of the color in the dictioanry are used as reference values of the retrieved color. If the searched color does not exist in the dictionary, the top-5 Google image search results of the searched color are crawled and average RGB values are extracted in certain middle area of each image. To extract the RGB values in images, a variety of different ways was attempted since there are limits to simply obtain the average of the RGB values of the center area of images. As a result, clustering RGB values in image's certain area and making average value of the cluster with the highest density as the reference values showed the best performance. Based on the reference RGB values of the searched color, the RGB values of all the colors in the color dictionary constructed aforetime are compared. Then a color list is created with colors within the range of ${\pm}50$ for each R value, G value, and B value. Finally, using the Euclidean distance between the above results and the reference RGB values of the searched color, the color with the highest similarity from up to five colors becomes the final outcome. In order to evaluate the usefulness of the proposed method, we performed an experiment. In the experiment, 300 color names and corresponding color RGB values by the questionnaires were obtained. They are used to compare the RGB values obtained from four different methods including the proposed method. The average euclidean distance of CIE-Lab using our method was about 13.85, which showed a relatively low distance compared to 3088 for the case using synonym dictionary only and 30.38 for the case using the dictionary with Korean synonym website WordNet. The case which didn't use clustering method of the proposed method showed 13.88 of average euclidean distance, which implies the DBSCAN clustering of the proposed method can reduce the Euclidean distance. This research suggests a new color synonym processing method based on RGB values that combines the dictionary method with the real time synonym processing method for new color names. This method enables to get rid of the limit of the dictionary-based approach which is a conventional synonym processing method. This research can contribute to improve the intelligence of e-commerce search systems especially on the color searching feature.