• Journal of Korean Society of Water and Wastewater
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• v.37 no.6
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• pp.311-324
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• 2023

As an advanced study on the method of calculating the target revenue water ratio of local waterworks through the leakage component analysis method proposed by Kim et al. (2022), this study developed a model to calculate the achievable revenue water ratio within the specified project cost, the required project cost to achieve the specified target revenue water ratio, and the economically appropriate target revenue water ratio level by considering the leakage reduction cost and leakage reduction benefit for each revenue water ratio improvement strategy, and conducted an applicability evaluation of the developed model using actual field data. The procedure for calculating the target revenue water ratio of local waterworks considering economics proposed in this study consists of three stages: physical data linkage model construction, leakage component analysis, and economic analysis, and the applicability was evaluated for Zone H with branch type and the Zone M network type. As a result of the application, it was calculated that approximately 32.5 billion won would be required to achieve the target revenue water ratio of 70% in the Zone H, and approximately KRW 10.5 billion would be required to achieve the target revenue water ratio of 75% in the Zone M. If the business scale of Zones H and M was corrected to 10,000 m³/day of water usage, the required project cost for a 1% improvement in the revenue water ratio of Zone H was calculated to be 0.7642 billion won and 0.4715 billion won for Zone M.

• The Journal of the Convergence on Culture Technology
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• v.10 no.6
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• pp.869-874
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• 2024

The spread of various digital devices, the development of communication and network technologies, and the spread of personal media services have led to an explosive increase in the production and distribution of multimedia content. Recognition and search of multimedia data such as images and videos requires a content-based recognition and search method that analyzes and quantifies the physical characteristics of the data and compares them. In content-based search of images, color and shape become important visual features. In this paper, a method to describe and search the spatial distribution of color regardless of image rotation using the complex color model to intergrate color and shape features is proposed. It was confirmed through experiments that by applying a rotation-invariant shape descriptor to a complex color image converted according to a complex color model, color-shape could be expressed and recognized regardless of rotation.

• Journal of Digital Forensics
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• v.13 no.4
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• pp.231-244
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• 2019

Digital evidence is crucial to issues that require not only cybercrime but also to prove the facts of the cyber environment. While digital evidence has traditionally been collected from physically specific media, it is often impossible to specify the physical location of the data as cloud and distributed processing technologies evolve, requiring a ways of collecting data remotely. However, existing procedures or rules for collecting data from remote locations only emphasize fundamental conditions such as integrity and audit tracking, but there are many ambiguity when applied to actual collection. In addition, the threat of falsification that occurs when collecting data from remote locations was not considered. In this paper, we propose a framework that can ensure the reliability of the collection environment and the reliability of the network to show that it has not been falsified and that data that exists remotely has been collected as it was originally. It also implements this framework as a virtual environment and collects digital evidence from remote locations through case studies to discuss its effectiveness.

• The Journal of Korean Obstetrics and Gynecology
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• v.37 no.3
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• pp.63-84
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• 2024

Objectives: This study aims to understand the stress patterns and coping behaviors of women with infertility and to improve existing infertility stress assessment tools to develop a tool suited for Korean society. Methods: The study involved 10 women diagnosed with primary or secondary infertility. Data were collected through surveys and in-depth interviews. Participants were recruited voluntarily, and snowball sampling was used for additional recruitment. Data collection occurred from September 2023 to April 2024. Data analysis included Spearman's rank correlation, Mann-Whitney U test, and Kruskal-Wallis test. Interview results were analyzed using text mining and network analysis with Python 3.12. Results: There was a significant correlation between IVF/ICSI treatment and resilience scores, with non-IVF/ICSI groups showing higher resilience scores. Existing infertility stress assessment tools were generally useful but had limitations, such as discomfort with religious expressions and fixed gender roles, as well as issues with the number of items and response scales. Text mining of interview responses revealed key stress-related keywords including worry, depression, burden, pregnancy outcome, and health. Main stressors included uncertainty about pregnancy outcomes, physical discomfort during treatments, economic burdens, and emotional reactions from family and social relationships. Conclusions: This study identified the stress patterns of women with infertility through interviews. It showed the need for a new assessment tool to evaluate and support the complex stressors experienced by these women. Developing a comprehensive tool is essential for better understanding and managing the various stress factors faced by infertile women.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.7
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• pp.1726-1748
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• 2024

Trajectory planning is vital for autonomous systems like robotics and UAVs, as it determines optimal, safe paths considering physical limitations, environmental factors, and agent interactions. Recent advancements in trajectory planning and future location prediction stem from rapid progress in machine learning and optimization algorithms. In this paper, we proposed a novel framework for Spatial-temporal transformer-based feed-forward neural networks (STTFFNs). From the traffic flow local area point of view, skip-gram model is trained on trajectory data to generate embeddings that capture the high-level features of different trajectories. These embeddings can then be used as input to a transformer-based trajectory planning model, which can generate trajectories for new objects based on the embeddings of similar trajectories in the training data. In the next step, distant regions, we embedded feedforward network is responsible for generating the distant trajectories by taking as input a set of features that represent the object's current state and historical data. One advantage of using feedforward networks for distant trajectory planning is their ability to capture long-term dependencies in the data. In the final step of forecasting for future locations, the encoder and decoder are crucial parts of the proposed technique. Spatial destinations are encoded utilizing location-based social networks(LBSN) based on visiting semantic locations. The model has been specially trained to forecast future locations using precise longitude and latitude values. Following rigorous testing on two real-world datasets, Porto and Manhattan, it was discovered that the model outperformed a prediction accuracy of 8.7% previous state-of-the-art methods.

• Korean Journal of Materials Research
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• v.34 no.9
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• pp.439-447
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• 2024

Organic-inorganic hybrid coating films have been used to increase the transmittance and enhance the physical properties of plastic substrates. Sol-gel organic-inorganic thin films were fabricated on polymethylmethacrylate (PMMA) substrates using a dip coater. Metal alkoxide precursor tetraethylsilicate (TEOS) and alkoxy silanes including decyltrimethoxysilane (DTMS), 3-glycidoxypropyltrimethoxysilane (GPTMS), phenyltrimethoxysilane (PTMS), 3-(trimethoxysilyl)propyl methacrylate (TMSPM) and vinyltrimethoxysilane (VTMS) were used to synthesize sol-gel hybrid coating solutions. Sol-gel synthesis was confirmed by the results of FT-IR. Cross-linking of the Si-O-Si network during synthesis of the sol-gel reaction was confirmed. The effects of each alkoxy silane on the coating film properties were investigated. All of the organic-inorganic hybrid coatings showed improved transmittance of over 90 %. The surface hardness of all coating films on the PMMA substrate was measured to be 4H or higher and the average thickness of the coating films was measured to be about 500 nm. Notably, the TEOS/DTMS coating film showed excellent hydrophobic properties, of about 97°.

• The Journal of Sustainable Design and Educational Environment Research
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• v.23 no.3
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• pp.36-51
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• 2024

School facilities play are crucial in improving educational outcomes not only by serving as physical infrastructure to achieve the goals of school education but also by positively influencing the satisfaction of school users (e.g., teachers and students) and students' academic achievement and emotional development. Consequently, the importance of school facilities has been consistently emphasized. This study aims to explore the research trends of school spaces within the field of educational facilities to identify the future role and research directions of school spaces. Therefore, content and network text analyses were conducted on 531 studies published from 2001 to 2022 that are related to school spaces in the Korean Educational Facilities Society and Korean Educational Green Environment Research Institute. Further, quantitative changes, target contributions, research methods, and shifts in key words and themes were analyzed. The results suggest the need for expanding research subjects, improving the educational environment by reflecting characteristics and needs of each educational stage, broadening the use of research methodologies, and expanding research on school safety to further contribute to the development of research on school spaces.

• Journal of Distribution Science
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• v.9 no.3
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• pp.83-94
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• 2011

Most domestic companies, with the exclusion of major firms, are reluctant to implement a supply chain management (SCM) network into their operations. Most small- and medium-sized enterprises are not even aware of SCM. Due to the inherent total-systems efficiency of SCM, it coordinates domestic manufacturers, subcontractors, distributors, and physical distributors and cuts down on cost of inventory control, as well as demand management. Furthermore, a lack of SCM causes a decrease in competitiveness for domestic companies. The reason lies in the fundamentality of SCM, which is the characteristic of information sharing, process innovation throughout SCM, and the vast range of problems the SCM management tool is able to address. This study suggests the contemplation and reformation of the current SCM situation by analyzing the SCM strategic plan, discourses and logical discussions on the topic, and a successful case for adapting SCM; hence, the study plans to productively "process" SCM. First, it is necessary to contemplate the theoretical background of SCM before discussing how to successfully process SCM. I will describe the concept and background of SCM in Chapter 2, with a definition of SCM, types of SCM promotional activities, fields of SCM, necessity of applying SCM, and the effects of SCM. All of the defects in currently processing SCM will be introduced in Chapter 3. Discussion items include the following: the Bullwhip Effect; the breakdown in supply chain and sales networks due to e-business; the issue that even though the key to a successful SCM is cooperation between the production and distribution company, during the process of SCM, the companies, many times, put their profits first, resulting in a possible defect in demands estimation. Furthermore, the problems of processing SCM in a domestic distribution-production company concern Information Technology; for example, the new system introduced to the company is not compatible with the pre-existing document architecture. Second, for effective management, distribution and production companies should cooperate and enhance their partnership in the aspect of the corporation; however, in reality, this seldom occurs. Third, in the aspect of the work process, introducing SCM could provoke corporations during the integration of the distribution-production process. Fourth, to increase the achievement of the SCM strategy process, they need to set up a cross-functional team; however, many times, business partners lack the cooperation and business-information sharing tools necessary to effect the transition to SCM. Chapter 4 will address an SCM strategic plan and a case study of LG Electronics. The purpose of the strategic plan, strategic plans for types of business, adopting SCM in a distribution company, and the global supply chain process of LG Electronics will be introduced. The conclusion of the study is located in Chapter 5, which addresses the issue of the fierce competition that companies currently face in the global market environment and their increased investment in SCM, in order to better cope with short product life cycle and high customer expectations. The SCM management system has evolved through the adaptation of improved information, communication, and transportation technologies; now, it demands the utilization of various strategic resources. The introduction of SCM provides benefits to the management of a network of interconnected businesses by securing customer loyalty with cost and time savings, derived through the consolidation of many distribution systems; additionally, SCM helps enterprises form a wide range of marketing strategies. Thus, we could conclude that not only the distributors but all types of businesses should adopt the systems approach to supply chain strategies. SCM deals with the basic stream of distribution and increases the value of a company by replacing physical distribution with information. By the company obtaining and sharing ready information, it is able to create customer satisfaction at the end point of delivery to the consumer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.8
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• pp.392-402
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• 2019

The purpose of this study is to determine the factors that predict happiness among aged males and females who live alone, and we focused on their satisfaction with their socio-physical environment, their social network, regular participation in social activities, their subjective health status and if they suffer from depression. A total of 2,76 people were the subjects of this study, their average age was 65 years old, they lived alone and all of them were selected from the '2017 Community Health Survey' data. The data was analyzed utilizing the Chi-square test, the Mann-Whitney test and multivariate logistic regression analysis. The subjects were 605 males (21.86%) and 2,163 females (78.14%). For the result of this study, the significant predictive factors of happiness for aged males living alone were monthly income (OR=2.363, 95% CI=1.473-3.791), basic livelihood rights (OR=1.903, 95% CI=1.144-3.167), trusting their neighbors (OR=2.018, 95% CI=1.263-3.225), religious activities (OR=2.098, 95% CI=1.314-3.349), subjective health (OR=2.753, 95% CI=1.217-6.228), and depression (OR=0.852, 95% CI=0.803-0.905). The significant predictive factors of happiness for aged females living alone were income (OR=2.407 95% CI=1.362-4.253), basic livelihood rights (OR=1.350, 95% CI=1.019-1.788), contact with friends (OR=1.879, 95% CI=1.323-2.669), religious activities (OR=1.372, 95% CI=1.124-1.676), recreation/leisure activities (OR=1.608, 95% CI=1.161-2.228), subjective health (OR=5.327, 95% CI=1.347-21.070), and depression (OR=0.864, 95% CI=0.840-0.890). In conclusion, programs to enhance happiness should be developed with considering the characteristics affecting the happiness of aged Korean males and females who live alone.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.127-148
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• 2020

The data center is a physical environment facility for accommodating computer systems and related components, and is an essential foundation technology for next-generation core industries such as big data, smart factories, wearables, and smart homes. In particular, with the growth of cloud computing, the proportional expansion of the data center infrastructure is inevitable. Monitoring the health of these data center facilities is a way to maintain and manage the system and prevent failure. If a failure occurs in some elements of the facility, it may affect not only the relevant equipment but also other connected equipment, and may cause enormous damage. In particular, IT facilities are irregular due to interdependence and it is difficult to know the cause. In the previous study predicting failure in data center, failure was predicted by looking at a single server as a single state without assuming that the devices were mixed. Therefore, in this study, data center failures were classified into failures occurring inside the server (Outage A) and failures occurring outside the server (Outage B), and focused on analyzing complex failures occurring within the server. Server external failures include power, cooling, user errors, etc. Since such failures can be prevented in the early stages of data center facility construction, various solutions are being developed. On the other hand, the cause of the failure occurring in the server is difficult to determine, and adequate prevention has not yet been achieved. In particular, this is the reason why server failures do not occur singularly, cause other server failures, or receive something that causes failures from other servers. In other words, while the existing studies assumed that it was a single server that did not affect the servers and analyzed the failure, in this study, the failure occurred on the assumption that it had an effect between servers. In order to define the complex failure situation in the data center, failure history data for each equipment existing in the data center was used. There are four major failures considered in this study: Network Node Down, Server Down, Windows Activation Services Down, and Database Management System Service Down. The failures that occur for each device are sorted in chronological order, and when a failure occurs in a specific equipment, if a failure occurs in a specific equipment within 5 minutes from the time of occurrence, it is defined that the failure occurs simultaneously. After configuring the sequence for the devices that have failed at the same time, 5 devices that frequently occur simultaneously within the configured sequence were selected, and the case where the selected devices failed at the same time was confirmed through visualization. Since the server resource information collected for failure analysis is in units of time series and has flow, we used Long Short-term Memory (LSTM), a deep learning algorithm that can predict the next state through the previous state. In addition, unlike a single server, the Hierarchical Attention Network deep learning model structure was used in consideration of the fact that the level of multiple failures for each server is different. This algorithm is a method of increasing the prediction accuracy by giving weight to the server as the impact on the failure increases. The study began with defining the type of failure and selecting the analysis target. In the first experiment, the same collected data was assumed as a single server state and a multiple server state, and compared and analyzed. The second experiment improved the prediction accuracy in the case of a complex server by optimizing each server threshold. In the first experiment, which assumed each of a single server and multiple servers, in the case of a single server, it was predicted that three of the five servers did not have a failure even though the actual failure occurred. However, assuming multiple servers, all five servers were predicted to have failed. As a result of the experiment, the hypothesis that there is an effect between servers is proven. As a result of this study, it was confirmed that the prediction performance was superior when the multiple servers were assumed than when the single server was assumed. In particular, applying the Hierarchical Attention Network algorithm, assuming that the effects of each server will be different, played a role in improving the analysis effect. In addition, by applying a different threshold for each server, the prediction accuracy could be improved. This study showed that failures that are difficult to determine the cause can be predicted through historical data, and a model that can predict failures occurring in servers in data centers is presented. It is expected that the occurrence of disability can be prevented in advance using the results of this study.