• Journal of Industrial Convergence
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• v.21 no.9
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• pp.41-48
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• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

• Journal of Korean Society of Environmental Engineers
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• v.39 no.8
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• pp.449-455
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• 2017

Process input data including material and energy, process output data including product, co-product and its environmental emissions of the reference and target processes were collected and analyzed to evaluate the process performance. Environmentally problematic input/environmental emissions of the manufacturing processes were identified using these data. Significant process inputs contributing to each of the environmental emissions were identified using multiple regression analysis between the process inputs and environmental emissions. Optimum combination of the end-of-pipe technologies for treating the environmental emissions considering economic aspects was made using the linear programming technique. The cement manufacturing processes in Korea and the EU producing same type of cement were chosen for the case study. Environmentally problematic input/environmental emissions of the domestic cement manufacturing processes include coal, dust, and $SO_x$. Multiple regression analysis among the process inputs and environmental emissions revealed that $CO_2$ emission was influenced most by coal, followed by the input raw materials and gypsum. $SO_x$ emission was influenced by coal, and dust emission by gypsum followed by raw material. Optimization of the end-of-pipe technologies treating dust showed that a combination of 100% of the electro precipitator and 2.4% of the fiber filter gives the lowest cost. The $SO_x$ case showed that a combination of 100% of the dry addition process and 25.88% of the wet scrubber gives the lowest cost. Salient feature of this research is that it proposed a method for identifying environmentally problematic input/environmental emissions of the manufacturing processes, in particular, cement manufacturing process. Another feature is that it showed a method for selecting the optimum combination of the end-of-pipe treatment technologies.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.139-155
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• 2009

For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.123-132
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• 2013

As the smartphones are equipped with various sensors such as the accelerometer, GPS, gravity sensor, gyros, ambient light sensor, proximity sensor, and so on, there have been many research works on making use of these sensors to create valuable applications. Human activity recognition is one such application that is motivated by various welfare applications such as the support for the elderly, measurement of calorie consumption, analysis of lifestyles, analysis of exercise patterns, and so on. One of the challenges faced when using the smartphone sensors for activity recognition is that the number of sensors used should be minimized to save the battery power. When the number of sensors used are restricted, it is difficult to realize a highly accurate activity recognizer or a classifier because it is hard to distinguish between subtly different activities relying on only limited information. The difficulty gets especially severe when the number of different activity classes to be distinguished is very large. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we take to dealing with this ten-class problem is to use the ensemble of nested dichotomy (END) method that transforms a multi-class problem into multiple two-class problems. END builds a committee of binary classifiers in a nested fashion using a binary tree. At the root of the binary tree, the set of all the classes are split into two subsets of classes by using a binary classifier. At a child node of the tree, a subset of classes is again split into two smaller subsets by using another binary classifier. Continuing in this way, we can obtain a binary tree where each leaf node contains a single class. This binary tree can be viewed as a nested dichotomy that can make multi-class predictions. Depending on how a set of classes are split into two subsets at each node, the final tree that we obtain can be different. Since there can be some classes that are correlated, a particular tree may perform better than the others. However, we can hardly identify the best tree without deep domain knowledge. The END method copes with this problem by building multiple dichotomy trees randomly during learning, and then combining the predictions made by each tree during classification. The END method is generally known to perform well even when the base learner is unable to model complex decision boundaries As the base classifier at each node of the dichotomy, we have used another ensemble classifier called the random forest. A random forest is built by repeatedly generating a decision tree each time with a different random subset of features using a bootstrap sample. By combining bagging with random feature subset selection, a random forest enjoys the advantage of having more diverse ensemble members than a simple bagging. As an overall result, our ensemble of nested dichotomy can actually be seen as a committee of committees of decision trees that can deal with a multi-class problem with high accuracy. The ten classes of activities that we distinguish in this paper are 'Sitting', 'Standing', 'Walking', 'Running', 'Walking Uphill', 'Walking Downhill', 'Running Uphill', 'Running Downhill', 'Falling', and 'Hobbling'. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window of the last 2 seconds, etc. For experiments to compare the performance of END with those of other methods, the accelerometer data has been collected at every 0.1 second for 2 minutes for each activity from 5 volunteers. Among these 5,900 ($=5{\times}(60{\times}2-2)/0.1$) data collected for each activity (the data for the first 2 seconds are trashed because they do not have time window data), 4,700 have been used for training and the rest for testing. Although 'Walking Uphill' is often confused with some other similar activities, END has been found to classify all of the ten activities with a fairly high accuracy of 98.4%. On the other hand, the accuracies achieved by a decision tree, a k-nearest neighbor, and a one-versus-rest support vector machine have been observed as 97.6%, 96.5%, and 97.6%, respectively.

• Korean Journal of Health Education and Promotion
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• v.18 no.2
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• pp.45-63
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• 2001

The objective of this study is to give basic materials for selection and improvement of contents of safety education, which is substantially helpful to elementary students, by analysis of contents of safety education in some subjects and assessment of the needs of elementary students for safety education. For this purpose, this study was analyzed the contents of safety education in five subjects for elementary school and conducted the survey of 883 students in some elementary schools in Seoul from April 7 to 22, 2000. The results were as follows; 1. As a result of analysis of the proportion of contents regarding safety-related education in some subjects, Physical Education occupied the highest proportion (14.09％), and that was followed by Practical Subject (9.55％) and Moral Education (9.34％). However, the proportions in Social Study and Natural Science were very low, 1.85％ and 1.31％ each. In total lines of these five subjects, the numbers of line regarding safety education was contained by 5.78％. 2. Analyzing the proportion of domains of safety education in five textbooks, the Meaning of Safety and Basic Principles occupied the highest portion (29.5％), and that was followed by the Home Safety (24.0％), the Safety in School (17.1％), and the Play and Leisure Safety (14.0％). The Coping with Accidents and First Aid, the Safety from Fire and Explosion, and the Traffic Safety occupied relatively low portion, 6.9％, 5.7％, and 2.8％ each. 3. As a result of analysis of the proportion of the safety education domain in each subject, the Meaning of Safety and Basic Principles occupied the highest portion (23.6％) in Moral Education, the Home Safety (12.7％) in Practical Subject, and the Play and Leisure Safety (10.9％) in Physical Education. 4. Most of the participants in this survey experienced the Home Accidents (71.1％). And also, they experienced the Play and Leisure Accidents (57.9％), the Accidents in School (49.7％), the Traffic Accidents (45.3％), and the Fire and Explosion Accidents (24.7％) in order. 5. In the average proportion of the needs of participants for safety education in each domain, the Coping with Accidents and First Aid has the highest point (4.05). And, that was followed by the Home safety (3.79), the Safety from Fire and Explosion (3.73), the Meaning of Safety and Basic Principles (3.65), the Play and Leisure Safety (3.50), the Safety in School (3.37), and the Traffic Safety (3.35). The average proportion of the needs for safety education of total domains was 3.66. 6. In the needs for safety education regarding the feature of participants, it showed higher scores in female students than male ones (p〈0.001), in lower grader than higher grader (p〈0.05), and in the students born to wealth than those born poor (p〈0.05). Also, the children who recognize the necessity of safety education showed higher scores of the needs for safety education (p〈0.001). And it also showed the same results of high score to the children whose parents did the safety education (p〈0.00l) and to the children and their parents who have the higher degree of practicing safety (p〈0.001), and these differences were statistically significant. 7. In the extent of preference for methods of safety education, it showed high score to the Field Learning, followed by the Audio- Visual Education, the Discussion, and the Instruction of teacher. In the extent of preference for subjects regarding the contents of safety education by each domain, it showed high score to the subject of Safety for 4 domains - the Meaning of Safety and Basic Principles, the Traffic Safety, the Safety from Fire and Explosion, and the Coping with Accidents and First Aid. And also, they preferred Moral Education for 2 domains - the Home safety and the Safety in School, and Physical Education for a domain of the Play and Leisure Safety. 8. While 27 of 36 detail items was contained the contents of safety education, the proportion of needs of participants for safety education showed more than average 3.00 score in 34 of 36 detail items. However, none of 9 detail items was included in five textbooks. Also, 2 detail items - the Coping with Disasters and the Safety from Poisoning - were included together 2 parts; One part had the higher ranked 7 items acquired by analysis of the needs, and the other had the higher ranked 7 items acquired by analysis of the contents. But, except those 2 items, none of items were matched with each part.

• Journal of Yeungnam Medical Science
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• v.6 no.2
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• pp.159-172
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• 1989

This study was conducted to compare the date on knowledge, attitude and motivation toward blood donation between donors and nondonors. The study population included 622 donors and 322 nondonors who visited the mobile blood donation car of Taegu Red Cross Blood Center and participated the group appointed blood donation campaign managed by the center from March 1 to March 31, 1989. The donors and nondonors were questioned above mentioned items with a formulated questionnaire. Among the general characteristics of the subjects in the study, male predominace(84.1% in donors and 73.6% in nondonors) in young age group (16-24 years) was the outstanding feature. As a medium of information about blood donation, "television" was playing a dominant role(donors ; 75.2%, nondonors ; 78.9%), while "magazine"played more important roles among donors. Of the donors, 70.6% and of the nondonors, 58.1% replied that they had ever been induced to donate blood (p<0.01). Major inducers were friend and personnel of mobile blood donation vehicle. On the measuring of knowledge level, the average rates of correct answer was higher in donors (62.6%) than in nondonors (54.1%) (p<0.01). Higher the education level was presented, higher the knowledge level (p<0.05). There have been noticeable difference between donors and nondonors in blood replying the questionnaire set to measure their attitude toward blood donation. especially in the items such as "impression toward blood", "selection of transfusion blood source" and "view on the situation of blood shortage." The major motivation toward blood donation of the groups were "possible future need" and "altruism or humanitarian interest". The major reasons for not donating blood in both groups were "fear of the needle" and around to visit to mobile car or center."

• Journal of the Korean Society of Food Science and Nutrition
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• v.31 no.6
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• pp.1134-1141
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• 2002

Adhesion of leukocytes to the activated vascular endothelium and their subsequent recruitment/migration into the artery wall are key features in the pathogenesis of atherosclerosis and inflammatory diseases. These features have been mediated by cell adhesion molecules including vascular cell adhesion molecule-1 (VCAM-1) and in tracellular cell adhesion molecule-1 (ICAM-1). This study examined whether flavonoids inhibit the pro-inflammatory cytokine TNF-$\alpha$-induced monocyte adhesion via a modulation of the protein expression of VCAM-1 and ICAM-1 of human umbilical vein endothelial cells (HUVECs). TNF-$\alpha$ markedly increased the adhesion of THP-1 monocytes to endothelial cells and induced the expression of VCAM-1, ICAM-1 and E-selectin proteins in HUVECs. Micromolar concentrations of the flavones luteolin and apigenin and the flavonol quercetin near completely blocked the monocyte adhesion to the activated endothelial cells and the induction of these adhesion molecules. However, equimicromolar catechins of (-)epigallocatechin gallate and (+)catechin, the flavonol myr- icetin and the flavanones of naringin and hesperidin had no effect on TNF-$\alpha$-activated monocyte adhesion. (-)Epigallocatechin gallate, (+) catechin, and naringin did not attenuate the TNF-$\alpha$ induction of these adhesion molecules. Furthermore, culture with luteolin and apigenin strongly blocked the expression of TNF-$\alpha$-induced VCAM-1 mRNA and modestly attenuated ICAM-1 mRNA. Quercetin modestly decreased the TNF-$\alpha$-activated VCAM-1 and ICAM-1 mRNAs. These results demonstrate that flavonoids classified as flavones and flavonols may inhibit monocyte adhesion to the TNF-$\alpha$-activated endothelium, most likely due to a blockade of expression of functional adhesion molecules down-regulated at the transcriptional level, indicating a definite linkage between the chemical structure of flavonoids and the expression of cell adhesion molecules. Furthermore, the antiathero-genic feature of flavonoids appears to be independent of their antioxidant activity.

• Korean Journal of Psychosomatic Medicine
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• v.27 no.2
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• pp.101-110
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• 2019

Objectives : It is not clear which clinical variables are most closely associated with delirium in the Intensive Care Unit (ICU). By comparing clinical data of ICU delirium and non-delirium patients, we sought to identify variables that most effectively differentiate delirium from non-delirium. Methods : Medical records of 6,386 ICU patients were reviewed. Random Subset Feature Selection and Principal Component Analysis were utilized to select a set of clinical variables with the highest discriminatory capacity. Statistical analyses were employed to determine the separation capacity of two models-one using just the selected few clinical variables and the other using all clinical variables associated with delirium. Results : There was a significant difference between delirium and non-delirium individuals across 32 clinical variables. Richmond Agitation Sedation Scale (RASS), urinary catheterization, vascular catheterization, Hamilton Anxiety Rating Scale (HAM-A), Blood urea nitrogen, and Acute Physiology and Chronic Health Examination II most effectively differentiated delirium from non-delirium. Multivariable logistic regression analysis showed that, with the exception of vascular catheterization, these clinical variables were independent risk factors associated with delirium. Separation capacity of the logistic regression model using just 6 clinical variables was measured with Receiver Operating Characteristic curve, with Area Under the Curve (AUC) of 0.818. Same analyses were performed using all 32 clinical variables;the AUC was 0.881, denoting a very high separation capacity. Conclusions : The six aforementioned variables most effectively separate delirium from non-delirium. This highlights the importance of close monitoring of patients who received invasive medical procedures and were rated with very low RASS and HAM-A scores.

• Economic and Environmental Geology
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• v.18 no.4
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• pp.343-355
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• 1985

Spectral reflectivity and microhardness were measured quantitatively on polished surfaces of a selection of bireflecting minerals obtained from several well known metallic deposits. Incremental errors are much higher than decremental errors and errors were found to be lowest in the spectral region close to the green wavelength ($544m{\mu}$). The characteristics of the spectral profile are significant in their control of white light color. The covellite and graphite have reflectivity profiles similar in shape for each principal direction, showing noticeable difference in magnitude between the profiles: The spectral reflectivity of covellite parallel to the extraordinary vibration is higher (R$$\simeq_-$$10%) than that parallel to the ordinary vibration and graphite shows opposite feature. Reflectivity of the enargite and famatinite cut parallel to the cleavage plane is always higher (R$$\simeq_-$$5%) than that of the section cut normal. The optical symmetry of 5 bireflecting minerals was determined by noting the variation in reflectivity at $544m{\mu}$. The data indicate that covellite is optically uniaxial positive and graphite is optically uniaxial negative. The Rm values for enargite and famatinite are clearly closer to the minimum value for the mineral ($R_1$) than to the maximum value ($R_2$) : the minerals can be recognized as optically biaxial positive. Enargite and famatinite cut parallel to cleavage have much higher hardness values (HV=> $200kg/mm^2$) than those cut normal to cleavage. Vickers indentations exhibit characteristic features for all the bireflecting mineral species studied. Broad radicle groupings of the mineral species can be made with regard to the reflectivity microhardness numbers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.11
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• pp.3514-3523
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• 2009

Before 1990's, Korea had only few colleges that had film and film related majors. As Korean film industry started its marvelous improvement in both commercial and artistic phase, many colleges were interested in this new academic field. They hurried up to launch this new and profitable major; as a result, Korea now has more than hundred colleges and universities that has film related majors. Each college enumerates numbers of academic courses that may look reasonable; they have almost every course a fine film school should provide such as film theory, production, and performance in film. Lots of film schools offer lots of film courses; and they look alike. One unique thing in film major is its vast sub fields and categories. After you decide to study film, you have to select what specific field in film you want to study. Studying film theory and film production can be as different as majoring physics and physical education. The problem Korean colleges are dealing with is that there are too much film schools, and moreover those colleges have similar curriculums that just look like a department store that sells everything. One suggestion is specializing its curriculum in which the school can take advantages using their special conditions. San Francisco Art Institute is one of United States well known private film schools, but many people remember this school as a specialized film school in experimental film. San Francisco where this school is located has had many liberal and experimental artists as the city has been supporting and offering them an environment they can concentrate their work. Naturally, the school has world famous faculty members in experimental film, and students who want to study and make experimental film come to this school from all over the world because they know this school would be the best to study experimental film. There are many film schools in metro Los Angeles area; since its location near Hollywood, no wonder these schools concentrate on film producing and film production. They take advantage of their geographical location to hire film industry professional and to focus on commercial feature film productions. What we can do now to adjust the curriculum in film and film related major in Korean colleges is to adapt new standards in this changed film industry. One school can emphasize digital production while another school focuses on digital intermediate process. But if one school tries to both fields or all fields of film major just like we have done so far, the school could not take care of all the equipment and the faculty that the fields would need. Korean film schools should devide the field in film major and concentrate what they selected. Selection and concentration can be and should be applied in Korean film schools.