• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.2
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• Advances in pediatric surgery
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• v.14 no.1
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• pp.37-47
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• 2008

Recently, the survival rates of extremely low-birth-weight (ELBW) infants have improved with the development of neonatal intensive care. However, these infants were susceptible to intestinal perforation due to prematurity, fluid restriction, and injection of indomethacin, etc. Because of the risks of transportation, anesthesia and surgery itself, peritoneal drainage has been compared with laparotomy. Through our experience, we investigate the usefulness of peritoneal drainage retrospectively. From 1997 to 2007, six ELBW (M:F=5:1) underwent primary peritoneal drainage for intestinal perforation. Their median birth weight was 685g (405~870) and gestational age was $25^{+1}$ weeks ($24^{+3}{\sim}27^{+0}$). We noticed the intestinal perforation at median 10.5 days (8~18) after birth, and placed Penrose drain or Jackson-Pratt drain through right lower quadrant incision under local anesthesia. The cause of intestinal perforation was necrotizing enterocolitis in one patient, but that of the others was not clear. Three patients who showed normal platelet count and stable vital signs recovered uneventfully. Two patients (birth weight less than 500g) who showed unstable vital signs and low platelet count (12,000 / $mm^3$ to 30,000 / $mm^3$)expired despite aggressive resuscitation. One patient required laparotomy due to persistent intestinal obstruction after drain removal and survived. Our experience shows that peritoneal drainage was an acceptable treatment for ELBW infants and the prognosis was related to vital sign and platelet count at the time of intestinal perforation, and birth weight.

• Journal of the HCI Society of Korea
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• v.13 no.2
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• pp.31-44
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• 2018

In the IoT environment, various things could be connected. Those connected things learn and operate themselves, by acquiring data. As human being, they have self-learning and self-operating systems. In the field of IoT study, therefore, the key issue is to design communication system connecting both of the two different types of subjects, human being(user) and the things. With the advent of the IoT environment, much research has been done in the field of UI design. It can be seen that research has been conducted to take complex factors into account through keywords such as multi-modality and interusability. However, the existing UI design method has limitations in structuring or testing interaction between things and users of IoT environment. Therefore, this paper suggests a new UI prototyping method. In this paper, the major analysis and studies are as follows: (1) defined what is the behavior process of the things (2) analyzed the existing IoT product (3) built a new framework driving personality types (4) extracted three representative personality models (5) applied the three models to the smart home service and tested UI prototyping. It is meaningful with that this study can confirm user experience (UX) about IoT service in a more comprehensive way. Moreover, the concept of the personality of things will be utilized as a tool for establishing the identity of artificial intelligence (AI) services in the future.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.189-199
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• 2023

This study aimed to identify the development direction of Arduino-based boards relating to artificial intelligence based on social awareness identified using big data analytical methods. For the purpose, big data were extracted through the Textom website, focusing on keywords that included 'Arduino + artificial intelligence' and 'Arduino + AI', and these data were refined and analyzed using the Textom website and the UNICET program. In this study, big data analyses, including frequency analysis, TF-IDF analysis, Degree Centrality analysis, N-gram analysis, and CONCOR analysis, were performed. The analyses' results confirmed that keywords relating to education and coding education, keywords relating to making and experience based on Arduino, and keywords relating to programs were the main keywords used in Arduino- and artificial intelligence-related Internet documents, and clusters were formed based on these keywords confirmed. The social awareness of Arduino and artificial intelligence was evaluated, and the direction of board development was identified based on this social awareness. This study is meaningful in that it identified various factors of board development based on the general public's social awareness, which was evaluated using a big data analysis method. This study may serve as a point of reference for future researchers or developers wishing to understand user needs using big data analysis methods.

• The Journal of Society for e-Business Studies
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• v.27 no.1
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• pp.29-41
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• 2022

Since the first sale of a banner advertisement in 1995, electronic commerce has become a new transaction channel for consumers. With more than 20 years of its history, electronic commerce has become an important consumption channel for everyone and inexperience is no more a reason that discourages the consumption through this channel. The great expansion of this channel is now a formidable thereat to traditional channels. However, products with high asset specificity and complexity are still having difficulty to be traded over the online channel where the experience of the products for a consumer is limited. Especially, variations of the same product's quality depending on how pre-owners used the product and high complexity to describe the quality of the products prevent used goods from being traded over e-channels. Added to that, the information asymmetry between sellers and buyers for used goods makes the establishment of market transaction difficult. Considering the challenges, the current case study discusses thredUP, a clothing resale platform company. In this paper, we study how the company could overcome those limitations in this toughest resale market through the use of AI for dynamic pricing and standarized product quality ratings. In addition, we also hope to provide readers with the opportunity to understand the secondhand industries and its market, and see where it is heading for in the future.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.

• Journal of Korean Academy of Nursing
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• v.5 no.1
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• pp.59-69
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• 1975

Author studied on various psychiatric nursing problems applying with the test of questionnaire to the 376 nurses who are attending at 13 general hospitals and one mental hospital in Korea from Apr. 1, 1974 to July 30. 1974. The results obtained were ai follows: 1. 13.095 of nonpsychiatric registered nurses wanted the psychiatric service for their most attractive assignment and this was the 3rd in order next to the general surgical and operating room. Among the psychiatric nurses, the popularity toward psychiatric ward was 31. 0% and they were 26.0%at the private general hospitals and 6, 0% in national public hospitals. 2, The feelings or attitudes of disgust and apprehension on nursing care of the patients at-flirted with infectious diseases were the highest responses (38.5%) and these 1.ends were also appeared in 6.9% of psychiatric nurses. 3. 85.5% of nonpsychiatric registered nurses have had received course lectures on psychiatric nursing and nursing care training on the psychiatric ward at their school of nursing. 38.0% of psychiatric nurses had received post graduate psychiatric nursing and they were higher in national public hospitals (27.0% ) than in private general hospitals (11.0%). 4. The responses of satisfaction and security on their employment were almost similar patterns between nonpsychiatric registered nurses and psychiatric nurses. But among the psychiatric nurses. they were more satisfied at private general hospitals (33.0%) than that of national public hospitals (10.0%). 5. Almost the half of the nurses (50.8%) were employed by the hospitals without considering their past educational or clinical experience or career. Among the psychiatric nurses, who were employed by hospitals without considering their past experience or career were 35.0% in national public hospitals and 12.0% in private hospitals. On the contrary, the nurses who were employed by their wishes fore more higher (26.0%) in private general hospitals than national public hospitals (2.0%). 6. The nurses who thought their employment was fit for their aptitude were 48.6% in nonpsychiatric registered nurses and 51.0% in psychiatric nurses. Among the psychiatric nurses, this response was higher in private general hospitals (34.0%) than the national public hospitals (17.0%). 7. Responses on wort loadings of nurses showed almost same patterns between nonpsychiatric registered nurses and psychiatric nurses. But. among the psychiatric nurses who felt much heavier than the nurses of other part were 24.0% in national public hospitals and 8.0% in private general hospitals. 8. 92.6% of nurses felt that the psychiatric nurses should have post graduate training in psychiatric nursing prior to their assignment. 9. 96.0% of nurses agreed to the risk coverage on the payment for the nurses assigned to the psychiatric ward and the ward for infection diseases.

• Advances in pediatric surgery
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• v.9 no.1
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• pp.6-11
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• 2003

This study reviews 14 years' experience treating esophageal atresia with special emphasis on the clinical profile and outcome. From May 1989 to February 2003, 65 cases of esophageal atresia (EA) were treated at Asan Medical Center. Boys outnumbered girls 2.4 to 1. Prematutity and low birth weight were 27.7% and 38.5%. Esophageal atresia with distal tracheoesophageal fistula (TEF) was the most common type (87.7%), followed by pure EA and H type fistula. Forty-six patients (70.8%) had one or more associated anomalies, cardiac malformations were the most common. Duodenal atresia was found in 7 cases. There were 6 patients (9.2 %) with VATER cluster. VACTERL cluster was present in 18 patients (27.7%), one of who fulfilled the complete syndrome. Waterston group A, B and C made up 21.5%, 40.0% and 38.5% of the total group. Surgical treatment was attempted in 63 patients and deferred in 2 who had severe associated malformations. For EA with distal TEF, primary esophago esophagostomy was carried out in 51 cases, and division of TEF and gastrostomy in 4 cases and no operation in 2 cases. For pure EA, colonic graft was done in 2 after gastrostomy and esophagostomy, and esophago esophagostomy was performed in 2 after gastrostomy. Two patients with pure EA are waiting for the second operation after gastrostomy. Division of TEF was carried out in 2 cases with H type TEF. The overall survival rate was 76.9%, and survival by Waterston classification was 100% in group A, 80.8% in B and 60.0% in C. Thorough workup for associated anomalies, interdepartmental approach and more careful surgical decision and technique are required to improve the outcome of EA.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.147-157
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• 2017

Recently, ICT Retail Convergence(IRC) has been rapidly increasing to improve consumer satisfaction and consumer experience. In this paper, we aim to diagnose IRC from consumers' point of view by reviewing the present status and value of IRC according to consumer purchase decision making process. Based on the previous studies in retail industry, we classified IRC into 4 types: Experience-specific tech(Virtual Reality and Augmented Reality); Information-specific tech(Artificial Intelligence and Big Data); Location-based tech(Radio Frequency Identification and Beacon); Payment-related tech(Fin-tech and Biometrics). Next, we found that there is a difference in value provided to consumers according to the type of technology, analysing the value by consumer purchase decision making process. This study can be useful to introduce IRC for improving consumer satisfaction as well as ICT and Retail. Also, it can be basic data for future technology studies with a consumer perspective.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.80-93
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• 2022

This study is a study on a methodology that can extract various factors that affect purchase and use of products/services from the consumer's point of view through previous studies, and analyze the types and tendencies of consumers according to age and gender. To this end, we quantify factors in terms of general personal propensity, consumption influence, consumption decision, etc. to check the consistency of data, and based on these studies, we conduct research to suggest and prove data analysis methodologies of consumer types that are meaningful from the perspectives of startups and SMEs. did As a result, it was confirmed through cross-validation that there is a correlation between the three main factors assumed for data analysis from the consumer's point of view, the general tendency, the general consumption tendency, and the factors influencing the consumption decision. verified. This study presented a data analysis methodology and a framework for consumer data analysis from the consumer's point of view. In the current data analysis trend, where digital infrastructure develops exponentially and seeks ways to project individual preferences, this data analysis perspective can be a valid insight.