• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.1-9
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• 2022

In this paper, we propose the Deep Learning-Based Companion Animal Abnormal Behavior Detection Service, which using video and sensor data. Due to the recent increase in households with companion animals, the pet tech industry with artificial intelligence is growing in the existing food and medical-oriented companion animal market. In this study, companion animal behavior was classified and abnormal behavior was detected based on a deep learning model using various data for health management of companion animals through artificial intelligence. Video data and sensor data of companion animals are collected using CCTV and the manufactured pet wearable device, and used as input data for the model. Image data was processed by combining the YOLO(You Only Look Once) model and DeepLabCut for extracting joint coordinates to detect companion animal objects for behavior classification. Also, in order to process sensor data, GAT(Graph Attention Network), which can identify the correlation and characteristics of each sensor, was used.

• Journal of Industrial Convergence
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• v.21 no.4
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• pp.1-12
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• 2023

The era of digital transformation is rapidly emerging in industries and academia, including finance and logistics, and the consulting market for digital transformation is also growing. According to previous studies, the need for digital transformation is also mentioned in consulting institutions. In this process, the role of consultants should be changed according to the times, and customer relationship management and attitude toward customers are emphasized. However, consulting research has the point that research on this has not been studied in depth. Therefore, the purpose of this study is to develop an element of attitude focusing on consultant attitudes in the field of digital transformation. As a result of research using literature analysis and modified Delphi techniques, 'customer orientation', achievement orientation', professional dignity', 'maintenance of expertise', and 'ethics' were found to be key attitude factors. This study is meaningful in that consultant attitude elements in the digital transformation field were explored and developed by verifying content validity, and consultants in the digital transformation field can recognize the importance of attitude and use it as a basic tool for capacity improvement.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.1
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• pp.17-31
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• 2009

The importance of software has been growing rapidly owing to the development of various Internet and e-business applications. The traditional approaches to software evaluation are based on the development process perspective, and their major concerns are no strongly related to use or customer-oriented evaluation of software. According to resource-based theory, company's resource is consisted of human, technology, market value, and finance. Customer satisfaction improved by product satisfaction and service satisfaction. Based on the previous studies the factors of human resources, technology, customer satisfaction are selected to evaluate software company's competence This research suggests the factor effecting on sales performance. And then statistical methods are used for verifying relationship between the factor and sales performance.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.563-570
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• 2022

Industrialized and modular construction is a growing construction technique that can transfer a large portion of the construction process to off-site fabrication yards. This method of construction often involves the fabrication, pre-assembly, and transportation of massive and long volumetric modules. The module weight keeps increasing as the modules become more complete (with infill) to minimize the work at the site and, as higher productivity can be achieved at the fabrication shop. Thus, a volumetric module delivery gets more challenging and risky. Despite its importance, past research paid relatively insufficient attention to the problem related to the lifting of heavy modules. This can be a complex and time-consuming problem with multiple lifting for transportation-and-installation operations both in fabrication yard and jobsite, and require complex crane operations (sometimes, more than one crane) due to crane load capacity and load balance/stability. This study investigates this problem by focusing on the structural perspective of lifting such long volumetric modules through simulation studies. Various scenarios of lifting a weighty module from the top using four lifting cables attached to crane hooks (either a single crane or double crane) are simulated in SAP software. The simulations account for various factors pertaining to structural indices, e.g., bending stress and deflection, to identify a proper method of module lifting from a structural point of view. The method can identify differences in structural indices allowing identification of structural efficiency and safety levels during lifting, which further allows the selection of the number of cranes and location of lifting points.

• Journal of Information Technology Services
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• v.22 no.2
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• pp.23-40
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• 2023

Despite the growing interest and normative discussions on AI ethics, there is a lack of discussion on policy instruments that are necessary for companies to develop AI-based services in compliance with ethical principles. Thus, the purpose of this study is to explore policy instruments that can encourage companies to voluntarily comply with and adopt AI ethical standards and self-checklists. The study reviews previous research and similar cases on AI ethics, conducts interviews with AI-related companies, and analyzes the data using AHP to derive action plans. In terms of desirability and feasibility, Research findings show that policy instruments that induce companies to ethically develop AI-based services should be prioritized, while regulatory instruments require a cautious approach. It was also found that a consulting support policy consisting of experts in various fields who can support the use of AI ethics, and support for the development of solutions that adhere to AI ethical standards are necessary as incentive policies. Additionally, the participation and agreement of various stakeholders in the process of establishing AI ethical standards are crucial, and policy instruments need to be continuously supplemented through implementation and feedback. This study is significant as it presents the necessary policy instruments for companies to develop ethical AI-based services through an analytical methodology, moving beyond discursive discussions on AI ethical principles. Further analysis on the effectiveness of policy instruments linked to AI ethical principles is necessary for establishing ethical AI-based service development.

• Membrane Journal
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• v.32 no.1
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• pp.33-42
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• 2022

Growing industrialization leads to severe water pollution. Organic effluents from pharmaceuticals and textile industries released in wastewater adversely affect the environment and human health. Presence of antibiotics used for antibacterial treatment in wastewater leads to the growth of drug resistance bacteria, which is very harmful for human being. Various small organic molecules are used for the preparation of organic dye molecules in the textile industries. These molecules hardly degrade, which is present in the wastewater effluents from printing and dyeing industries. In order to address these problems, photoactive catalyst is embedded in the membrane and wastewater are passed through it. Through this process, organic molecules are photodegraded and at the same time, the degraded compounds are separated by the membrane. Titanium dioxide (TiO₂) is a semiconductor which behave as excellent photocatalyst. Photocatalytic ability is enhanced by the making its composite with other transition metal oxide and incorporated into polymeric membrane. In this review, the degradation of dye and drug molecules by photocatalytic membrane are discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.2
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• pp.102-108
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• 2023

Recently in Korea, YouTube stock channels increased rapidly due to the high social interest in the stock market during the COVID-19 period. Accordingly, the role of new media channels such as YouTube is attracting attention in the process of generating and disseminating market information. Nevertheless, prior studies on the market forecasting power of YouTube stock channels remain insignificant. In this study, the market forecasting power of the information from the YouTube stock channel was examined and compared with traditional news media. To measure information from each YouTube stock channel and news media, positive and negative opinions were extracted. As a result of the analysis, opinion in channels operated by media outlets were found to be leading indicators of KOSPI market returns among YouTube stock channels. The prediction accuracy by using logistic regression model show 74%. On the other hand, Sampro TV, a popular YouTube stock channel, and the traditional news media simply reported the market situation of the day or instead showed a tendency to lag behind the market. This study is differentiated from previous studies in that it verified the market predictive power of the information provided by the YouTube stock channel, which has recently shown a growing trend in Korea. In the future, the results of advanced analysis can be confirmed by expanding the research results for individual stocks.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.269-274
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• 2021

With the development of artificial intelligence, society is moving to a different world. As a result, amid growing interest in artificial intelligence education, research on how to teach artificial intelligence is also being conducted more actively in Korea. However, a lot of research is being conducted around the upper grades of elementary school, and curriculum and programs for the lower grades are insufficient. Therefore, this study developed an artificial intelligence program for lower grades. Among them, it was developed focusing on artificial intelligence image recognition. It compares image recognition methods of people, animals, and computers, identifies the characteristics of fallen leaves, and helps them understand the image recognition process of artificial intelligence by classifying them according to the characteristics of fallen leaves. I hope this program will help elementary school students understand the image recognition principle of artificial intelligence in the future.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.59-67
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• 2021

The development of AI technology has brought about a big change in our lives. As AI's influence grows from life to society to the economy, the importance of education on AI and data is also growing. In particular, the OECD Education Research Report and various domestic information and curriculum studies address data literacy and present it as an essential competency. Looking at domestic and international studies, one can see that the definition of data literacy differs in its specific content and scope from researchers to researchers. Thus, the definition of major research related to data literacy was analyzed from various angles and derived from various angles. In key studies, Word2vec natural language processing methods, along with word frequency analysis used to define data literacy, are used to analyze semantic similarities and nominate them based on content elements of curriculum research to derive the definition of 'understanding and using data to process information'. Based on the definition of data literacy derived from this study, we hope that the contents will be revised and supplemented, and more research will be conducted to provide a good foundation for educational research that develops students' future capabilities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.323-325
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• 2021

The size of the delivery market in Korea is growing year by year. In recent years, the growth rate has skyrocketed due to the aftermath of the coronavirus. Looking at the domestic delivery market's volume trend in 2020, about 3.4 billion boxes increased by 21% compared to about 2.8 billion boxes last year. In addition, sales amounted to 7.5 trillion won, an increase of about 19% compared to 6.3 trillion won a year earlier. As the delivery market grows, the proportion of courier damage relief is also occurring at a considerable rate. About 33% of 1,000 people have experienced delivery accidents, and about 41% of the week have experienced damage or damage. In this paper, a deep learning model capable of detecting a parcel was created to detect a damaged parcel. A system that can check the performance of this model and detect and classify parcels during the delivery process using a real-time detection camera was studied.