• Broadcasting and Media Magazine
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• v.11 no.4
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• pp.104-117
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• 2006

In this Paper, we analyze the application of Interactive Data Broadcasting in DMB(Digital Multimedia Broadcasting) in the accordance with convergence of service and technology. With the acceleration of digital convergence in the Ubiquitous period substantial development of digital media technology and convergence of broadcasting and telecommunication industry are being witnessed. Consequently these results gave rise to newly combined-products such as DMB(Digital Multimedia Broadcasting), WCDMA(Wide-band code division multiple access), Wibro(Wireless Broadband Internet), IP-TV (Internet protocol TV) and HSDPA(High speed downlink packet access). The preparatory stage for the implementation of Interactive Data Broadcasting Service will be reached by the end of December, 2006. DMB is the first result of a successful convergence service between Broadcasting and Telecommunication in new media era. Multimedia technology and services are the core elements of DMB. The Data Broadcasting will not only offer various services of interactive information such News, Weather, Broadcasting Program etc, but also be linked with characteristic function of mobile phone such as calling and SMS(Short Message Service) via Return Channel.

• Asia pacific journal of information systems
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• v.21 no.2
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• pp.89-116
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• 2011

In collaborative tagging systems such as Delicious.com and Flickr.com, users assign keywords or tags to their uploaded resources, such as bookmarks and pictures, for their future use or sharing purposes. The collection of resources and tags generated by a user is called a personomy, and the collection of all personomies constitutes the folksonomy. The most significant need of the folksonomy users Is to efficiently find useful resources or experts on specific topics. An excellent ranking algorithm would assign higher ranking to more useful resources or experts. What resources are considered useful In a folksonomic system? Does a standard superior to frequency or freshness exist? The resource recommended by more users with mere expertise should be worthy of attention. This ranking paradigm can be implemented through a graph-based ranking algorithm. Two well-known representatives of such a paradigm are Page Rank by Google and HITS(Hypertext Induced Topic Selection) by Kleinberg. Both Page Rank and HITS assign a higher evaluation score to pages linked to more higher-scored pages. HITS differs from PageRank in that it utilizes two kinds of scores: authority and hub scores. The ranking objects of these pages are limited to Web pages, whereas the ranking objects of a folksonomic system are somewhat heterogeneous(i.e., users, resources, and tags). Therefore, uniform application of the voting notion of PageRank and HITS based on the links to a folksonomy would be unreasonable, In a folksonomic system, each link corresponding to a property can have an opposite direction, depending on whether the property is an active or a passive voice. The current research stems from the Idea that a graph-based ranking algorithm could be applied to the folksonomic system using the concept of mutual Interactions between entitles, rather than the voting notion of PageRank or HITS. The concept of mutual interactions, proposed for ranking the Semantic Web resources, enables the calculation of importance scores of various resources unaffected by link directions. The weights of a property representing the mutual interaction between classes are assigned depending on the relative significance of the property to the resource importance of each class. This class-oriented approach is based on the fact that, in the Semantic Web, there are many heterogeneous classes; thus, applying a different appraisal standard for each class is more reasonable. This is similar to the evaluation method of humans, where different items are assigned specific weights, which are then summed up to determine the weighted average. We can check for missing properties more easily with this approach than with other predicate-oriented approaches. A user of a tagging system usually assigns more than one tags to the same resource, and there can be more than one tags with the same subjectivity and objectivity. In the case that many users assign similar tags to the same resource, grading the users differently depending on the assignment order becomes necessary. This idea comes from the studies in psychology wherein expertise involves the ability to select the most relevant information for achieving a goal. An expert should be someone who not only has a large collection of documents annotated with a particular tag, but also tends to add documents of high quality to his/her collections. Such documents are identified by the number, as well as the expertise, of users who have the same documents in their collections. In other words, there is a relationship of mutual reinforcement between the expertise of a user and the quality of a document. In addition, there is a need to rank entities related more closely to a certain entity. Considering the property of social media that ensures the popularity of a topic is temporary, recent data should have more weight than old data. We propose a comprehensive folksonomy ranking framework in which all these considerations are dealt with and that can be easily customized to each folksonomy site for ranking purposes. To examine the validity of our ranking algorithm and show the mechanism of adjusting property, time, and expertise weights, we first use a dataset designed for analyzing the effect of each ranking factor independently. We then show the ranking results of a real folksonomy site, with the ranking factors combined. Because the ground truth of a given dataset is not known when it comes to ranking, we inject simulated data whose ranking results can be predicted into the real dataset and compare the ranking results of our algorithm with that of a previous HITS-based algorithm. Our semantic ranking algorithm based on the concept of mutual interaction seems to be preferable to the HITS-based algorithm as a flexible folksonomy ranking framework. Some concrete points of difference are as follows. First, with the time concept applied to the property weights, our algorithm shows superior performance in lowering the scores of older data and raising the scores of newer data. Second, applying the time concept to the expertise weights, as well as to the property weights, our algorithm controls the conflicting influence of expertise weights and enhances overall consistency of time-valued ranking. The expertise weights of the previous study can act as an obstacle to the time-valued ranking because the number of followers increases as time goes on. Third, many new properties and classes can be included in our framework. The previous HITS-based algorithm, based on the voting notion, loses ground in the situation where the domain consists of more than two classes, or where other important properties, such as "sent through twitter" or "registered as a friend," are added to the domain. Forth, there is a big difference in the calculation time and memory use between the two kinds of algorithms. While the matrix multiplication of two matrices, has to be executed twice for the previous HITS-based algorithm, this is unnecessary with our algorithm. In our ranking framework, various folksonomy ranking policies can be expressed with the ranking factors combined and our approach can work, even if the folksonomy site is not implemented with Semantic Web languages. Above all, the time weight proposed in this paper will be applicable to various domains, including social media, where time value is considered important.

• The Journal of Korean Society for Radiation Therapy
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• v.31 no.1
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• pp.51-56
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• 2019

Purpose: The usefulness of using single-electron radiation for secondary radiotherapy of breast cancer patients after surgery is assessed and the use of a combine of different energy. Methods and materials : In this study, 40 patients (group A) using energy 6 MeV and 9 MeV, and 19 patients (group B) using a combine of 9 MeV and 12 MeV were studied among 59 patients who performed secondary care using combine electronic radiation. Each patient in each group, 6 MeV, 9 MeV, Combine(6 MeV / 9 MeV) and 9 MeV, 12 MeV, Combine (9 MeV / 12 MeV) were developed in different ways, and the maximum doses delivered to the original hospital, D95, D5, and $V_3$, $V_5$, $V_{10}$ were compared. Result: The D95 mean value of Group A treatment plan was $785.33{\pm}225.37cGy$, $1121.79{\pm}87.02cGy$ at 9 MeV, and $1010.98{\pm}111.17cGy$ at 6 MeV / 9 MeV, and the mean value at 6 MeV / 9 MeV was most appropriate for the dose. The mean values of the low dose area $V_3$ and $V_5$ in the lung of the breast direction being treated were $3.24{\pm}3.49%$ and $0.72{\pm}1.55%$ at 6 MeV, the highest 9 MeV at $7.25{\pm}4.59%$, $3.07{\pm}2.64%$, the lowest at 6 MeV. Maximum and average lung dose was $727.78{\pm}137.27cGy$ at 6 MeV / 9 MeV, $49.16{\pm}24.44cGy$, highest 9 MeV at $998.97{\pm}114.35cGy$, $85.33{\pm}41.18cGy$, and lowest 6 MeV at $387.78{\pm}208.88cGy$, $9.27{\pm}6.60cGy$. The value of $V_{10}$ was all close to zero. Group B appeared in the pattern of Group A. Conclusion: Relative differences in low-dose areas of the lungs $V_3$ and $V_5$ were seen and were most effective in the dose transfer of tumor bed in the application of combined energy. It is thought that the method of using electronic energy in further radiation treatments for breast cancer is a more effective way to use the energy effect of limiting energy resources, and that if you think about it again, it could be a little more beneficial radiation treatment for patients.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• Korean Journal of Soil Science and Fertilizer
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• v.37 no.5
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• pp.304-314
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• 2004

The objective of this study was to investigate the effect of organic materials (compost, straw, green manure, pig manure, seed production oil cake, and industrial by products including municipal sewage sludge, industrial sewage sludge, leather processing sludge, and alcohol fermentation processing sludge) on physical properties of soils in seven paddy and four upland fields with differential soil textures, sandy loam, loam, or clay loam, etc. The investigated physical parameters were bulk density (BD), air permeability (AP), macroporosity, hardness, shear resistance, frictional resistance, water stability aggregate (WSA), and Middleton's dispersion ratio. Except for coarse sandy loam field with weak structure, a decrease in BD and shear resistance, and an increase in macroporosity and AP in plots with applying organic materials compared to plots without applying organic materials appeared. In upland fields, the positive effect of organic materials on WSA, BD, and air permeability was higher than in paddy fields. The combined plot of NPK and compost had lower BD, hardness, and shear resistance, and higher macroporosity and WSA than plot with compost. Green manure had higher positive effect on physical properties of soils compared to other organic materials and the extent of positive effect had no significant correlation with soil organic matter content. Of industrial byproducts applied in coarse sandy loam soil under upland condition, municipal sewage sludge and pig manure compost had higher effect on increase of WSA than leather processing sludge and alcohol fermentation processing sludge. Unlike WSA, there were no significant differences between industrial byproduct types in other physical properties. in silty clay loam soil under the upland condition, straw had more positive effect on soil physical parameters than hairy vetch and pig manure. Therefore, different organic materials had differently active effect on physical parameters depending on types of soil and land use. Especially, it could be thought that well-decomposed organic materials have the advantage of an increase in organic matter content, while coarse organic materials of an increase in WSA.

• Korean Journal of Soil Science and Fertilizer
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• v.19 no.4
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• pp.283-289
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• 1986

To establish a suitability grouping system of paddy soils for multiple cropping of rice with other upland crops, the study was carried out after a few basic experiments. In succession to the results on basic experiment prior, the suitability system proposed and the results of application mentioned in this report were summarized as follows; 1. The factors of soil properties in the system were productivities represented by soil texture and drainage class, as well as salinity of surface and sub-soil pH of chemical properties were considered together with slope, warmth index, ground water table, parent materials etc. of soil physical or environmental conditions. The weights of the factors were combined with multiplicatively and additively so as the total marks of ideal soil to be 100. The system was composed with 5 suitability classes; over 91 mark is class I, under 60 mark class V, and each 10 point interval between classes. The limiting factors "P" (in the case that Physical properties or Productivity marks under 24), "S" (Surface slope less than 15) and "C" (Chemical condition below 15) etc. were appended up to two kinds to the classes except a part of soils in class I. 2. The areas where the warmth index exceed 110 in Yeongnam were 19% for class I, 22.7% for class II, 44.7% for class III, 11.5% for class IV, and 2.1% for class V. The rates in class I and II were slightly more than those of the whole country. 3. The points of each soil gained by the system had a positive correlation ($r=.922^{**}$) with the potential productivities.

• Journal of the Korean Society of Food Science and Nutrition
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• v.46 no.3
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• pp.298-305
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• 2017

Atopic dermatitis is a chronic, relapsing inflammatory skin disease. This study aimed to investigate the therapeutic benefits of Aronia melanocarpa (AM) and Moringa oleifera seed extract (MO) on experimental atopic dermatitis. We examined the effects of AM or MO and their combination on 2,4-dinitrochlorobenzene (DNCB)-induced atopic dermatitis in BALB/c mice as well as tumor necrosis factor $(TNF)-{\alpha}$ and interferon $(IFN)-{\gamma}-stimulated$ HaCaT keratinocytes. Mice were orally treated with extract during repeated application of DNCB to shaved dorsal skin. Our results show that treatment with AM and MO in combination reduced histological manifestations such as epidermal hyperplasia and inflammatory cell infiltration. Furthermore, it significantly decreased skin thickness and serum immunoglobulin E (IgE) level compared to the AM or MO alone treated group. Combined extract of AM and MO suppressed expression of $TNF-{\alpha}/IFN-{\gamma}-induced$ T helper 2 (Th2) chemokines such as thymus and activation-regulated chemokine and macrophage-derived chemokine. To sum up, combination of AM and MO suppressed the inflammatory response and serum IgE as an indicator of several allergic diseases in DNCB-induced experimental atopic dermatitis and Th2 chemokine expression in HaCaT cells. This result suggests that combination of AM and MO could be a valuable strategy to improve atopic dermatitis.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.

• Journal of Oral Medicine and Pain
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• v.30 no.4
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• pp.457-464
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• 2005

The purpose of our study was to investigate whether the intrapulpal temperature during cavity preparation of enamel or dentin with Er:YAG laser still remained in range of safety for dental pulp protection when combined with appropriate water flow rate. The effect of different pulse repetition rates at the same pulse energy during ablation was evaluated as well. Caries-free, restoration-free extracted human molar teeth were prepared for the specimen and divided two experimental groups of enamel and dentin. Each group comprised 5 specimens and each of tooth specimens were embedded into a resin block each and measuring probe was placed on the irradiated pulpal walls. For experiments of dentin ablation, enamel layers were prepared to produce dentin specimen with a same dentin thickness of 2 mm. A pulse energy of Er:YAG laser was set to 300 mJ and three different pulse repetition rates of 20 Hz, 15 Hz and 10 Hz were employed. Laser beam was delivered with 3 seconds and less per application over enamel and dentin surfaces constant sized by $3\;mm{\times}2\;mm$ and water spray added during irradiation was a rate of 1.6 ml/min. Temperature change induced by Er:YAG laser irradiation was monitored and recorded While enamel was ablated, there was no significant difference of temperature related to pulse repetition rates(p=0.358) and temperature change at any pulse repetition rate was negligible. Significant statistical difference in temperature changes during cavity preparation in dentin existed among three different pulse groups(p=0.001). While temperature rise was noticeable when the dentinal wall was perforated, actual change of temperature due to Er:YAG laser irradiation was not enough to compromise safety of dental pulp when irradiation was conjugated with appropriate water spray. Conclusively, it can be said that cavity preparation on enamel or dentin with an Er:YAG laser is performed safely without pulp damage if appropriate volume of water is sprayed properly over the irradiated site.

• Journal of the Korea Concrete Institute
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• v.26 no.2
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• pp.151-157
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• 2014

Since recently developed Ultra-High-Performance-Concrete (UHPC) provides very high strength, stiffness, and durability, many studies have been made on the application of the UHPC to bridge decks. Due to high strength and stiffness of UHPC bridge deck, the structural contribution of top flange of steel girder composite to UHPC deck would be much lower than that of conventional concrete deck. At this point of view, this study proposes a inverted-T shaped steel girder composite to UHPC deck. This girder requires a new type of shear connector because conventional shear connectors are welded on top flange. This study also proposes three different types of shear connectors, and evaluate their ultimate strength via push-out static test. The first one is a stud shear connector welded directly to the web of the girder in the transverse direction. The second one is a puzzle-strip type shear connector developed by the European Commission, and the last one is the combination of the stud and the puzzle-strip shear connectors. Experimental results showed that the ultimate strength of the transverse stud was 26% larger than that given in the AASHTO LRFD Bridge Design Specifications, but a splitting crack observed in the UHPC deck was so severe that another measure needs to be developed to prevent the splitting crack. The ultimate strength of the puzzle-strip specimen was 40% larger than that evaluated by the equation of European Commission. The specimens combined with stud and puzzle-strip shear connectors provided less strength than arithmetical sum of those. Based on the experimental observations, there appears to be no advantage of combining transverse stud and puzzle-strip shear connectors.