Recent interests in data mining result from the expansion of the amount of business data and the growing business needs for extracting valuable knowledge from the data and then utilizing it for decision making process. In particular, recent advances in association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from the voluminous transactional data. Certainly, one of the major purposes of association rule mining is to utilize acquired knowledge in providing marketing strategies such as cross-selling, sales promotion, and shelf-space allocation. In spite of the potential applicability of association rule mining, unfortunately, it is not often the case that the marketing mix acquired from data mining leads to the realized profit. The main difficulty of mining-based profit realization can be found in the fact that tremendous numbers of patterns are discovered by the association rule mining. Due to the many patterns, data mining experts should perform additional mining of the results of initial mining in order to extract only actionable and profitable knowledge, which exhausts much time and costs. In the literature, a number of interestingness measures have been devised for estimating discovered patterns. Most of the measures can be directly calculated from what is known as a contingency table, which summarizes the sales frequencies of exclusive items or itemsets. A contingency table can provide brief insights into the relationship between two or more itemsets of concern. However, it is important to note that some useful information concerning sales transactions may be lost when a contingency table is constructed. For instance, information regarding the size of each market basket(i.e., the number of items in each transaction) cannot be described in a contingency table. It is natural that a larger basket has a tendency to consist of more sales patterns. Therefore, if two itemsets are sold together in a very large basket, it can be expected that the basket contains two or more patterns and that the two itemsets belong to mutually different patterns. Therefore, we should classify frequent itemset into two categories, inter-pattern co-occurrence and intra-pattern co-occurrence, and investigate the effect of the market basket size on the two categories. This notion implies that any interestingness measures for association rules should consider not only the total frequency of target itemsets but also the size of each basket. There have been many attempts on analyzing various interestingness measures in the literature. Most of them have conducted qualitative comparison among various measures. The studies proposed desirable properties of interestingness measures and then surveyed how many properties are obeyed by each measure. However, relatively few attentions have been made on evaluating how well the patterns discovered by each measure are regarded to be valuable in the real world. In this paper, attempts are made to propose two notions regarding association rule measures. First, a quantitative criterion for estimating accuracy of association rule measures is presented. According to this criterion, a measure can be considered to be accurate if it assigns high scores to meaningful patterns that actually exist and low scores to arbitrary patterns that co-occur by coincidence. Next, complementary measures are presented to improve the accuracy of traditional association rule measures. By adopting the factor of market basket size, the devised measures attempt to discriminate the co-occurrence of itemsets in a small basket from another co-occurrence in a large basket. Intensive computer simulations under various workloads were performed in order to analyze the accuracy of various interestingness measures including traditional measures and the proposed measures.
This paper empirically examines factors that potentially influence the success of a Web-based semantic search engine. A research model has been proposed that shows the impact of quality-related factors upon the effectiveness of a semantic search engine, based on DeLone and McLean's(2003) information systems success model. An empirical study has been conducted to test hypotheses formulated around the research model, and statistical methods were applied to analyze gathered data and draw conclusions. Implications for academics and practitioners are offered based on the findings of the study. The proposed model includes three quality dimensions of a Web-based semantic search engine-namely, information quality, system quality and service quality. These three dimensions each have measures designed to collectively assess the respective dimension. The model is intended to examine the relationship between measures of these quality dimensions and measures of two dependent constructs, including individuals' net benefit and user satisfaction. Individuals' net benefit was measured by the extent to which the user's information needs were adequately met, whereas user satisfaction was measured by a combination of the perceived satisfaction with search results and the perceived satisfaction with the overall system. A total of 23 hypotheses have been formulated around the model, and a questionnaire survey has been conducted using a functional semantic search website created by KT and Hakia, so as to collect data to validate the model. Copies of a questionnaire form were handed out in person to 160 research associates and employees working in the area of designing and developing semantic search engines. Those who received the form, 148 respondents returned valid responses. The survey form asked respondents to use the given website to answer questions concerning the system. The results of the empirical study have indicated that, of the three quality dimensions, information quality was found to have the strongest association with the effectiveness of a Web-based semantic search engine. This finding is consistent with the observation in the literature that the aspects of the information quality should serve as a basis for evaluating the search outcomes from a semantic search engine. Measures under the information quality dimension that have a positive effect on informational gratification and user satisfaction were found to be recall and currency. Under the system quality dimension, response time and interactivity, were positively related to informational gratification. On the other hand, only one measure under the service quality dimension, reliability was found to have a positive relationship with user satisfaction. The results were based on the seven hypotheses that have been accepted. One may wonder why 15 out of the 23 hypotheses have been rejected and question the theoretical soundness of the model. However, the correlations between independent variables and dependent variables came out to be fairly high. This suggests that the structural equation model yielded results inconsistent with those of coefficient analysis, because the structural equation model intends to examine the relationship among independent variables as well as the relationship between independent variables and dependent variables. The findings offer some useful implications for owners of a semantic search engine, as far as the design and maintenance of the website is concerned. First, the system should be designed to respond to the user's query as fast as possible. Also it should be designed to support the search process by recommending, revising, and choosing a search query, so as to maximize users' interactions with the system. Second, the system should present search results with maximum recall and currency to effectively meet the users' expectations. Third, it should be capable of providing online services in a reliable and trustworthy manner. Finally, effective increase in user satisfaction requires the improvement of quality factors associated with a semantic search engine, which would in turn help increase the informational gratification for users. The proposed model can serve as a useful framework for measuring the success of a Web-based semantic search engine. Applying the search engine success framework to the measurement of search engine effectiveness has the potential to provide an outline of what areas of a semantic search engine needs improvement, in order to better meet information needs of users. Further research will be needed to make this idea a reality.
Recently, due to various environmental problems, blast tracks in tunnel are replaced with concrete tracks, but they have more adverse effects on noise than blast tracks so that additional noise measures are needed. Among these measures, sound-absorbing blocks start to be used due to its easy and quick installation. However, the performance of sound absorption blocks need to be verified under real environmental and operational conditions. In this paper, interior noise levels in KTX train cruising in Dalseong tunnel are measured before and after the installation of sound-absorbing blocks and the measured data are analyzed and compared. Additionally, noise reduction are estimated by modeling the high speed train, the tunnel and absorption blocks. Measurement devices and methods are used according to ISO 3381 and the equivalent sound pressure levels during the cruising time inside the tunnel are computed. In addition to overall SPLs(Sound Pressure Levels), 1/3-octave-band levels are also analyzed to account for the frequency characteristics of sound absorption and equipment noise in a cabin. In addition, to consider the effects of train cruising speeds and environmental conditions on the measurements, the measured data are corrected by using those measured during the train-passing through the tunnels located before and behind the Dalseong tunnel. Analysis of measured results showed that the maximum noise reduction of 6.8 dB (A) can be achieved for the local region where the sound-absorbing blocks are installed. Finally, through the comparison of predicted 1/3-octave band SPLs for the KTX interior noise with the measurements, the understanding of noise reduction mechanism due to sound-absorbing blocks is enhanced.
While Korean GAAP had detailed regulations for the measurement and disclosure of operating income in the past, K-IFRS did not provide specific rules for operating income until 2011. Some firms that adopted K-IFRS before 2011 did not disclose or calculated operating income in an inconsistent manner although operating income is usually considered as one of the core information items to assess firm valuation. Inconsistency in firms' treatment of operating income invoked much criticism from diverse users of financial statement. The Korean Accounting Institute (KAI hereafter) revised the K-IFRS rules relevant to operating income in September 2010 in response to the voices raised by the business community, whereby the operating income number is allowed to be calculated in conformity with the previous K-GAAP. This study was motivated by the revision of K-IFRS and aims to provide a clue on the validity of such policy decision. To achieve the research objective, we test the relative value relevance of the alternative operating income numbers under K-IFRS versus K-GAAP. Our main findings are as follows. The value relevance of operating income reported before K-IFRS is proved to be higher than after K-IFRS. K-IFRS operating income adjusted to the previous K-GAAP has greater explanatory power for market values relative to one calculated under the K-IFRS regime. In an additional analysis, the sample was decomposed according to whether the operating income under K-IFRS is greater than under K-GAAP. The difference in the value relevance of K-IFRS versus K-GAAP operating income is significant only in the subsample consisting of firms which reports higher operating income under K-IFRS compared to K-GAAP. Also, the firms which would have reported negative operating income on a consecutive basis are more likely to have chosen K-IFRS, resulting in higher numbers than otherwise. It is likely that firms facing the threat of delisting due to consecutive operating loss reporting are more likely to have adopted K-IFRS disclosure rules by which they could report higher operating income numbers. To sum up, these results corroborate the limitation inherent in the K-IFRS regarding operating income disclosures. This paper suggests that the recent revision of K-IFRS implemented by KAI is likely to mitigate some of afore-mentioned limitations effectively.
In this paper through Honam high-speed railroad which is planned with the north and south axis, we will verify the feasibility of the coordinate conversion using railroad control points after regarding current planned-railroad as the linear central axises. From analysis, distortion of Y axis varies 21cm to 40cm diminishing to a gentle straight line, distortion of X axis varies 14cm to 29cm. Through a revision, the deviation value between the coordinates were 6mm to 9mm and it satisfied the allowable error of national geographic information institute which is following ITRF (International Terrestrial Reference Frame) and cadastral boundary survey(10cm). consequently the coordinate conversion is possible using railroad control points as common control points.
In this paper, we analyze the effect of the depth perception, volume perception and visual discomfort according to the change of the quality of the depth image and the depth of the major object. For the analysis, a 2D image was converted to eighteen 3D images using depth images generated based on the different depth position of a major object and background, which were represented in three detail levels. The subjective test was carried out using eighteen 3D images so that the degrees of the depth perception, volume perception and visual discomfort recognized by the subjects were investigated according to the change in the depth position of the major object and the quality of depth map. The absolute depth position of a major object and the relative depth difference between background and the major object were adjusted in three levels, respectively. The details of the depth map was also represented in three levels. Experimental results showed that the quality of the depth image differently affected the depth perception, volume perception and visual discomfort according to the absolute and relative depth position of the major object. In the case of the cardboard depth image, it severely damaged the volume perception regardless of the depth position of the major object. Especially, the depth perception was also more severely deteriorated by the cardboard depth image as the major object was located inside the screen than outside the screen. Furthermore, the subjects did not felt the difference of the depth perception, volume perception and visual comport from the 3D images generated by the detail depth map and by the rough depth map. As a result, it was analyzed that the excessively detail depth map was not necessary for enhancement of the stereoscopic perception in the 2D-to-3D conversion.
Kim, Jung Wook;Park, Se Yun;Jo, Young Jun;Park, Jong Yeop
The Korean Journal of Nuclear Medicine Technology
/
v.16
no.2
/
pp.25-28
/
2012
Purpose : It is important to reduce radiation dose associated with computed tomography (CT) scanning to as low as reasonably achievable (ALARA). With Dose Modulation Technic, user select a desired image quality and the system adapts tube current to obtain the desired image quality with greater radiation dose efficiency. In this paper, we presents a comprehensive description of fundamentals, clinical applications and radiation dose benefits of Dose Modulation Technic depending on Body Mass Index(BMI). Materials and Methods : In this study, 149 patients were examined(The mean age : $58{\pm}12.4$ years old). Biograph True Point 40 (Siemens, USA) and Gemini TF 64 (Philips. Cleveland) were used for equipment. When we used Care Dose 4D (Siemens, USA) and D-dom (Philips, Cleveland), we measured dose reduction and Computed Tomography Dose Index (CTDI) depending on BMI. Then we analyze data using SPSS Ver.18. Results : When we used Care Dose 4D, p-value is considered statistically significant by groups with the result that we compared Care Dose 4D with D-dom. On the other hand, p-value isn't considered statistically significant by groups using D-dom. Conclusion : Dose modulation based on the projection angle didn't affect degree of obesity. And When using Care Dose 4D, dose reduction rate in the normal patients were higher than the obese. In this study, there are errors on somato type. So I think more research have to be done. Then application of Dose Modulation technic can help in maintaining acceptable image quality while reducing radiation dose by 20-60% in most instances.
With the development of the 4th industrial, research is being conducted to prevent diseases and reduce damage in various fields of science and technology such as medicine, health, and bio. As a result, artificial intelligence technology has been introduced and researched for image analysis of radiological examinations. In this paper, we will directly apply a deep learning model for classification and detection of pneumonia using chest X-ray images, and evaluate whether the deep learning model of the Inception series is a useful model for detecting pneumonia. As the experimental material, a chest X-ray image data set provided and shared free of charge by Kaggle was used, and out of the total 3,470 chest X-ray image data, it was classified into 1,870 training data sets, 1,100 validation data sets, and 500 test data sets. I did. As a result of the experiment, the result of metric evaluation of the Inception V3 deep learning model was 94.80% for accuracy, 97.24% for precision, 94.00% for recall, and 95.59 for F1 score. In addition, the accuracy of the final epoch for Inception V3 deep learning modeling was 94.91% for learning modeling and 89.68% for verification modeling for pneumonia detection and classification of chest X-ray images. For the evaluation of the loss function value, the learning modeling was 1.127% and the validation modeling was 4.603%. As a result, it was evaluated that the Inception V3 deep learning model is a very excellent deep learning model in extracting and classifying features of chest image data, and its learning state is also very good. As a result of matrix accuracy evaluation for test modeling, the accuracy of 96% for normal chest X-ray image data and 97% for pneumonia chest X-ray image data was proven. The deep learning model of the Inception series is considered to be a useful deep learning model for classification of chest diseases, and it is expected that it can also play an auxiliary role of human resources, so it is considered that it will be a solution to the problem of insufficient medical personnel. In the future, this study is expected to be presented as basic data for similar studies in the case of similar studies on the diagnosis of pneumonia using deep learning.
This study is aimed to analyze problems of police budgetary execution and to suggest better ways for establishing effective budget implementation as well as legitimacy of securing budget in the field of police work. For this purpose, this paper analyzed the annual reports on police budgetary execution, from 2009 to 2012, conducted by National Assembly Budget Office. In result, most parts of the police budgetary execution were not satisfied with the audit standard, and especially in terms of management of budgetary execution, it showed 40% in inappropriateness. In addition, excessive and underestimate appropriation in the police budgetary execution, which happened frequently in other offices, was recorded on the second place. 10% of the amount of budget was executed for ordinance violence. Given results analyzed from each division, Transportation Division occupied 40% of the amount of related problems and all of types in the field did not meet the audit standard, thus it is required to manage budgetary execution effectively. In terms of Public Safety Division, the problem was related to budgetary allocation prior to execution, such as overlap in other works, excessive and underestimate appropriation, and inappropriate business plans. Director General for Planning and Coordination did not meet the standard of law system maintenance, Given the light of the result of analyzing programs, traffic safety and securing communication was the most problematic and support for police administration, crime prevention and protecting the disadvantaged, educating professional police officers, and establishment of policing infrastructure were required to be reformed in sequence. In order to resolve these problems, it is demanded to check budgetary execution and the process in business plans on a regular basis. Additionally, in case of using budget in inappropriate parts, tough penality including reduction of budget in related to the local police should be implemented to increase the importance of budgetary execution. Moreover, because of the fact that a part of problem of budgetary execution was originally caused by the budgetary allocation, it is advised to allocate police budget using the budget proposal of National Finance Act and Ministry of Strategy and Finance.
Korea Forest Service has supplied 76 industrial wood pellet boilers from 2011 to 2015 through subsidy programs. Since carbon monoxide (CO) and nitrogen oxides ($NO_x$) generated during boiler combustion are substances that lead to death in the case of acute poisoning, it is very important to reduce emissions. Therefore, the CO and $NO_x$ emission values of 63 boilers excluding the hot air blower and some boilers initially supplied were analyzed. The emission factor was also calculated from the measured exhaust gas concentration (based on exhaust gas $O_2$ concentration of 12%). The average value of CO emitted from industrial wood pellet boilers was 49 ppm and it was confirmed that the CO concentration was decreasing as the years passed. The emission factor of CO was 0.73 g/kg. The average value of $NO_x$ emitted from industrial wood pellet boilers was 67 ppm and the emission factor of $NO_x$ was 1.63 g/kg. Unlike CO, there was no tendency to decrease according to the installation year. Both CO and $NO_x$ measurements met the limits of the Ministry of Environment. These $NO_x$ emission factors were compared with the $NO_x$ emission factors produced by certified low $NO_x$ burners. The $NO_x$ emission factor of industrial wood pellet boilers was about 1.9 times that of certified low $NO_x$ LNG combustors and about 0.92 times that of coal combustion.
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