• 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.

• Korean Journal of Radiology
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• v.22 no.5
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• pp.770-781
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• 2021

Objective: Chemical exchange-dependent saturation transfer (CEST) MRI is sensitive for detecting solid-like proteins and may detect changes in the levels of mobile proteins and peptides in tissues. The objective of this study was to evaluate the characteristics of chemical exchange proton pools using the CEST MRI technique in patients with dementia. Materials and Methods: Our institutional review board approved this cross-sectional prospective study and informed consent was obtained from all participants. This study included 41 subjects (19 with dementia and 22 without dementia). Complete CEST data of the brain were obtained using a three-dimensional gradient and spin-echo sequence to map CEST indices, such as amide, amine, hydroxyl, and magnetization transfer ratio asymmetry (MTR_asym) values, using six-pool Lorentzian fitting. Statistical analyses of CEST indices were performed to evaluate group comparisons, their correlations with gray matter volume (GMV) and Mini-Mental State Examination (MMSE) scores, and receiver operating characteristic (ROC) curves. Results: Amine signals (0.029 for non-dementia, 0.046 for dementia, p = 0.011 at hippocampus) and MTR_asym values at 3 ppm (0.748 for non-dementia, 1.138 for dementia, p = 0.022 at hippocampus), and 3.5 ppm (0.463 for non-dementia, 0.875 for dementia, p = 0.029 at hippocampus) were significantly higher in the dementia group than in the non-dementia group. Most CEST indices were not significantly correlated with GMV; however, except amide, most indices were significantly correlated with the MMSE scores. The classification power of most CEST indices was lower than that of GMV but adding one of the CEST indices in GMV improved the classification between the subject groups. The largest improvement was seen in the MTR_asym values at 2 ppm in the anterior cingulate (area under the ROC curve = 0.981), with a sensitivity of 100 and a specificity of 90.91. Conclusion: CEST MRI potentially allows noninvasive image alterations in the Alzheimer's disease brain without injecting isotopes for monitoring different disease states and may provide a new imaging biomarker in the future.

• Journal of Korean Dental Hygiene Science
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• v.1 no.2
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• pp.41-52
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• 2018

The purpose of this study was to examine the state of oral prophylaxis practice among dental hygiene students and their awareness of musculoskeletal diseases in an effort to provide some information on how to strengthen education on treatment posture to manage musculoskeletal diseases and how to raise awareness of musculoskeletal diseases. From November 2 to 13, 2016, a self-administered survey was conducted on 653 sophomores, juniors and seniors with an experience of oral prophylaxis practice. SPSS version 20.0 for Windows was employed to analyze the collected data. The findings of the study were as follows: 1. The largest group that accounted for 37.4% responded that the total number of students undergoing oral prophylaxis practice during a semester was four to six. The biggest group that represented 65.4% answered that the required practice time per student was one to fewer than three hours. 76.0% continued to be in the repeated same posture. 2. As for the posture of patients, supine position was most common for the maxillary sinus, which accounted for 82.2%. And semi-upright position was most common for the mandibular sinus, which represented 49.6%. 3. In regard to the burden of oral prophylaxis practice, 33.9% considered the required for the practice appropriate. 42.3% took the repeated long-lasting posture, and 53.5% were under physical pressure. 55.4% suffered from mental pressure and stress. 4. The most dominant musculoskeletal area that they experienced pain after oral prophylaxis practice was neck with 52.5%; waist with 48.2, shoulders/wrists/hands with 45.5, back with 10.3, buttocks with 4.1, elbows with 2.3, legs with 2.1, ankles/feet with 0.8 and knees with 0.6%. 5. Concerning the maintenance of repeated treatment postures and pain experience, the students who continued to be in the repeated same position underwent more pain than the others who didn't on the shoulders(2.92±1.05), in the waist(3.02±1.01), buttocks(1.75±0.92), elbows(1.55±0.79) and ankles/foot(2.52±1.25). The differences were statistically significant(p<.05, p<.01). 6. As to educational experience on treatment posture and musculoskeletal diseases, 88.8% received education on treatment posture; 87.9%, on what position should be taken in times of cooperation; 46.9%, on musculoskeletal diseases; 51.9%, on carpal tunnel syndrome; 42.3%, on varicose vein. The students who replied education on occupational diseases was necessary accounted for 89.6%. 7. The students who experienced treatment posture education were better aware of the causes of musculoskeletal diseases(3.23±3.00), ways for preventing the diseases(3.33±.834) and how to stretch the body(3.63±.858). The differences were statistically significant(p<.05, p<.001). 8. The students who experienced education on occupational diseases heard more about musculoskeletal diseases(3.27±.965), were better cognizant of the causes of the diseases(3.45±.847), were better aware of how to prevent them(3.55±.805) and found themselves to know how to stretch to prevent the diseases (3.73±.826). The differences were statistically significant(p<.001).

• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.3
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• pp.46-58
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• 2024

The purpose of this study is to understand the current status of the pet plant kit industry and determine the priorities for support policies to revitalize the industry. SWOT analysis assessed the industry's current state, and the Analytic Hierarchy Process (AHP) was used with industry professionals to prioritize support policies. The SWOT analysis results indicated that SO strategies involve leveraging government support policies to enhance marketing and developing eco-friendly DIY products. WO strategies include launching advertising campaigns to increase market recognition and establishing strategic partnerships to expand distribution. ST strategies focus on strengthening price competitiveness and proposing unique values, while WT strategies involve improving production processes and enhancing product quality based on consumer feedback. The AHP analysis identified 3 top-level and 12 sub-level evaluation items, with data collected from 17 expert surveys. The results showed the 'entry phase' (0.482), 'activation phase' (0.397), and 'advanced phase' (0.121) were prioritized, with 'organizing seminars' (0.181) as the most crucial subcategory and 'support for kit development' (0.020) as the least. The pet plant kit industry is in its early stages, and appropriate policy incubation can help activate the garden industry. This study provides foundational information on the industry's needs for activation.

• Journal of Digital Convergence
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• v.22 no.1
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• pp.1-14
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• 2024

In order to improve the effectiveness of carbon neutrality in Jeju Special Self-Governing Province, this study identifies the current state of social environmental education through literature research, excluding school environmental education being implemented in elementary, middle, and high schools in the province, and identifies shortcomings or problems. The purpose is to establish a plan to systematically and integratedly operate social environmental education, and the derived plan can be used as a guide to change environmental awareness and induce eco-friendly behavior to improve the effectiveness of carbon neutrality. As a result of the study, Jeju Special Self-Governing Province established a consultative body with environmental education institutions, organizations and expert groups operating dispersed throughout the province through the substantial operation and support of the environmental education center currently being entrusted, to identify the current status and develop content necessary for establishing environmental education policies, establishing a platform to enable information sharing, role division, regular communication, empathy, and policy feedback, and on-site environmental education centered on the field to stimulate emotions and personalize environmental problems so that environmental problems can be properly recognized. Emphasizing the necessity.

• Journal of Animal Science and Technology
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• v.66 no.1
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• pp.135-144
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• 2024

The objective of this study was to investigate the influence of feeding frequency on a sow's reproductive performance and stress response during gestation. A total of twenty multiparous sows (Yorkshire × Landrace) were used in a completely randomized design based on their parity, body weight (BW), and backfat thickness (BFT), and the sows were allotted to two different feeding systems: 1) once daily feeding (OF) and 2) twice daily feeding (TF) in corn-soybean meal based diets. The gestation diet was formulated to contain 3,265 kcal of metabolizable energy (ME) / kg, 12.90% of crude protein (CP), and 0.75 % of total lysine. The lactation diet was formulated to contain 3,265 kcal of ME / kg, 16.80% of CP, and 1.08% of total lysine and provided ad libitum during lactation. In gestation, sow BFT and BF changes were not affected by feeding frequency, but higher BW and BW gain from day 35 to 90 and day 35 to 110 were observed in OF sow (p < 0.10). In lactation, feeding frequency did not influence on BW, BW gain, BFT, BF changes, average daily feed intake, and wean-to-estrus interval. Also, there were no differences in litter size, litter weight and piglet weight in lactating sows. OF sows had higher (p < 0.05; p < 0.10) protein, solid-not-fat, and total solid concentrations in colostrum compared to TF sows, while OF sows had a lower (p < 0.05) lactose concentration in colostrum compared to TF sows. Sows in OF showed significantly lower average daily water consumption (ADWC) from day 35 to 110 of gestation (p < 0.05). While there were no significant differences in stereotypic behaviors and salivary cortisol levels during gestation between treatments, the OF sows showed less time spending on the activity at day 105 (p < 0.05). In conclusion, reduced feeding frequency increased BW gain during gestation, decreased activation time, and changed the colostrum composition. This information may contribute to the understanding of the physiological and behavioral change of gestating sows by manipulating feeding frequency.

• The Journal of Bigdata
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• v.9 no.1
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• pp.153-168
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• 2024

In summer, as chillers are considered the main energy consumer of building, the efficient chiller operation is considered important. However, it is difficult to operate chillers to meet the cooling demand of the building as the demand fluctuates with various factors like the internal, external environment and behavior of the occupants and as chiller's constraint cause the current operation constrains operation in future. To address these problems, this study proposes a multi-chiller operation model based on deep reinforcement learning considering the minimum up-time of the chiller. The proposed model learns the value of the chiller operations according to the state composed of metrological and cooling system information and determines operation that minimizes the difference between the supply load and the cooling demand among feasible operations. The practical applicability was improved by applying the training algorithm considering the minimum up-time constraint and Experiments results using the actual data from a Korean university confirmed that the proposed model complies with the chiller constraints and outperforms the existing chiller operation logic of the university in terms of differences from the building cooling demand.

• Journal of Society of Preventive Korean Medicine
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• v.28 no.2
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• pp.55-65
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• 2024

Background : Tuberculosis (TB) remains a significant public health issue worldwide, particularly among healthcare workers (HCWs) at high risk of exposure. Latent tuberculosis infection (LTBI) is a state where individuals are infected with Mycobacterium tuberculosis but do not show clinical symptoms. Early detection and treatment of LTBI are crucial to prevent progression to active TB. This study aimed to investigate the prevalence and risk factors of LTBI among Korean Medicine (KM) workers in Seoul, South Korea. Methods : This study analyzed 368 adults aged 19 and over working in Korean medicine institutions in Seoul by September 2023. Participants underwent a tuberculin skin test (TST) and completed a survey collecting demographic information, occupation, work duration, smoking status, BCG vaccination, TB history, and comorbidities. Data were analyzed using descriptive statistics and chi-square tests, with significance set at p < 0.05. Results : The average age of participants was 43.1 years, with an LTBI prevalence rate of 3.5%. Significant risk factors included age and history of TB, Older age and a history of TB were associated with higher LTBI positivity. Conclusion : The study identified the prevalence and risk factors of LTBI among Korean medicine workers in Seoul. The findings highlight the need for targeted LTBI screening and preventive measures, especially for older workers and those with a history of TB. While the prevalence was lower than in other healthcare settings, the results emphasize the importance of regular LTBI testing and prevention education for KM workers. Future large-scale studies are needed to confirm these findings and further understand the relationship between various risk factors and LTBI in KM settings.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.57-79
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• 2016

It is a rising trend that the number of users using one of the social media channels, the Social Network Service, so called the SNS, is getting increased. As per to this social trend, more companies have interest in this networking platform and start to invest their funds in it. It has received much attention as a tool spreading and expanding the message that a company wants to deliver to its customers and has been recognized as an important channel in terms of the relationship marketing with them. The environment of media that is radically changing these days makes possible for companies to approach their customers in various ways. Particularly, the social network service, which has been developed rapidly, provides the environment that customers can freely talk about products. For companies, it also works as a channel that gives customized information to customers. To succeed in the online environment, companies need to not only build the relationship between companies and customers but focus on the relationship between customers as well. In response to the online environment with the continuous development of technology, companies have tirelessly made the novel marketing strategy. Especially, as the one-to-one marketing to customers become available, it is more important for companies to maintain the relationship marketing with their customers. Among many SNS, Facebook, which many companies use as a communication channel, provides a fan page service for each company that supports its business. Facebook fan page is the platform that the event, information and announcement can be shared with customers using texts, videos, and pictures. Companies open their own fan pages in order to inform their companies and businesses. Such page functions as the websites of companies and has a characteristic of their brand communities such as blogs as well. As Facebook has become the major communication medium with customers, companies recognize its importance as the effective marketing channel, but they still need to investigate their business performances by using Facebook. Although there are infinite potentials in Facebook fan page that even has a function as a community between users, which other platforms do not, it is incomplete to regard companies' Facebook fan pages as communities and analyze them. In this study, it explores the relationship among customers through the network of the Facebook fan page users. The previous studies on a company's Facebook fan page were focused on finding out the effective operational direction by analyzing the use state of the company. However, in this study, it draws out the structural variable of the network, which customer committment can be measured by applying the social network analysis methodology and investigates the influence of the structural characteristics of network on the business performance of companies in an empirical way. Through each company's Facebook fan page, the network of users who engaged in the communication with each company is exploited and it is the one-mode undirected binary network that respectively regards users and the relationship of them in terms of their marketing activities as the node and link. In this network, it draws out the structural variable of network that can explain the customer commitment, who pressed "like," made comments and shared the Facebook marketing message, of each company by calculating density, global clustering coefficient, mean geodesic distance, diameter. By exploiting companies' historical performance such as net income and Tobin's Q indicator as the result variables, this study investigates influence on companies' business performances. For this purpose, it collects the network data on the subjects of 54 companies among KOSPI-listed companies, which have posted more than 100 articles on their Facebook fan pages during the data collection period. Then it draws out the network indicator of each company. The indicator related to companies' performances is calculated, based on the posted value on DART website of the Financial Supervisory Service. From the academic perspective, this study suggests a new approach through the social network analysis methodology to researchers who attempt to study the business-purpose utilization of the social media channel. From the practical perspective, this study proposes the more substantive marketing performance measurements to companies performing marketing activities through the social media and it is expected that it will bring a foundation of establishing smart business strategies by using the network indicators.