• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.3
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• pp.141-156
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• 2023

Due to the unprecedented worldwide pandemic of the new Covid-19 infection, business trends of companies have changed significantly. Therefore, it is strongly required to monitor the rapid changes of innovation trends to design and plan future businesses. Since the pandemic, many studies have attempted to analyze business changes, but they are limited to specific industries and are insufficient in terms of data objectivity. In response, this study aims to analyze business trends after Covid-19 using Crunchbase, a global startup data. The data is collected and preprocessed every two years from 2018 to 2021 to compare the business trends. To capture the major trends, a network analysis is conducted for the industry groups and industry information based on the co-occurrence. To analyze the minor trends, LDA-based topic modelling and word2vec-based clustering is used. As a result, e-commerce, education, delivery, game and entertainment industries are promising based on their technological advances, showing extension and diversification of industry boundaries as well as digitalization and servitization of business contents. This study is expected to help venture capitalists and entrepreneurs to understand the rapid changes under the impact of Covid-19 and to make right decisions for the future.

• Information Systems Review
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• v.23 no.3
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• pp.127-158
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• 2021

Many online travel agencies (OTAs) provide average ratings and time-relevant information or the most recently posted reviews regarding hotels to satisfy customers. To identify these two factors' relative influence on behavioral decision-making processes, we conducted two studies: (1) an experimental research design to explore the relative influence of the two on online review consumption and (2) an empirical approach to examine their relative impact on online review generation. The results show that when review posters observe an inconsistency between average ratings and recent reviews, they tend to deviate from the recent reviews regardless of the overall direction (reactance behavior). Meanwhile, review consumers tend to conform to the opinions presented in recent reviews (herding behavior). Additionally, in both cases, the effects are amplified in case of a negative aberration. Based on the findings, this study provides theoretical and practical implications regarding the relative influences of average rating and recently posted reviews and their different impacts on online review consumption and generation.

• Information Systems Review
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• v.23 no.1
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• pp.45-68
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• 2021

As the influence of online reviews on consumer decision-making increases, concerns about review manipulation are also increasing. Fake reviews or review manipulations are emerging as an important problem by posting untrue reviews in order to increase sales volume, causing the consumer's reverse choice, and acting at a high cost to the society as a whole. Most of the related prior studies have focused on predicting review manipulation through data mining methods, and research from a consumer perspective is insufficient. However, since the possibility of manipulation of reviews perceived by consumers can affect the usefulness of reviews, it can provide important implications for online word-of-mouth management regardless of whether it is false or not. Therefore, in this study, we analyzed whether there is a difference between the review evaluated by the consumer as being manipulated and the general review, and verified whether the manipulated review negatively affects the review usefulness. For empirical analysis, 34,711 online book reviews on the LibraryThing website were analyzed using multilevel logistic regression analysis and Poisson regression analysis. As a result of the analysis, it was found that there were differences in product level, reviewer level, and review level factors between reviews that consumers perceived as being manipulated and reviews that were not. In addition, manipulated reviews have been shown to negatively affect review usefulness.

• Information Systems Review
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• v.23 no.1
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• pp.69-91
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• 2021

Credit Bureaus in Korea commonly use financial transaction information of the past and present time for calculating an individual's credit scores. Compared to other rating factors, the repayment history information accounts for a larger weights on credit scores. Accordingly, despite full redemption of overdue payments, late payment history is reflected negatively for the assessment of credit scores for certain period of the time. An individual with debt delinquency can be classified into two groups; (1) the individuals who have faithfully paid off theirs overdue debts(Normal Repayment), and (2) those who have not and as differences of creditworthiness between these two groups do exist, it needs to grant relatively higher credit scores to the former individuals with normal repayment. This study is designed to analyze the factors of normal repayment of Korean financial debt delinquents based on credit information of personal loan, overdue payments, redemption from Korea Credit Information Services. As a result of the analysis, the number of overdue and the type of personal loan and delinquency were identified as significant variables affecting normal repayment and among applied methodologies, neural network models suggested the highest classification accuracy. The findings of this study are expected to improve the performance of individual credit scoring model by identifying the factors affecting normal repayment of a financial debt delinquent.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.1
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• pp.85-93
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• 2024

The monitoring of environmental information (e.g. noise, dust, vibration, temperature, humidity) is crucial to the safe and sustainable operation of a construction site. However, commercial sensors exhibit certain drawbacks when applied on-site. First, the installation cost is prohibitively high. Second, these sensors have been engineered without considering the rugged and harsh conditions of a construction site, resulting in error-prone sensing. Third, construction sites are compelled to allocate additional resources in terms of manpower, expenses, and physical spaces to accommodate individual sensors. This research developed an integrated sensing module to measure the environmental information in construction site. The sensing module slashes the installation cost to 3.3%, is robust enough to harsh and outdoor sites, and consolidates multiple sensors into a single unit. The sensing module also supports GPS, LTE, and real-time sensing. The evaluation showed remarkable results including 97.5% accuracy and 99.9% precision in noise measurement, an 89.7% accuracy in dust measurement, and a 93.5% reliability in data transmission. This research empowers the collection of substantial volumes and high-quality environmental data from construction sites, providing invaluable support to decision-making process. These encompass objective regulatory compliance checking, simulations of environmental data dispersion, and the development of environmental mitigation strategies.

• Korean Journal of Head & Neck Oncology
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• v.39 no.2
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• pp.13-17
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• 2023

Diffuse large B cell lymphoma (DLBCL) is main subtype of primary thyroid lymphoma and can be histologically transformed from a low-grade B-cell lymphoma. The characteristics and treatment guidelines of these particular DLBCL have not been fully established. The mainstay of treatment of primary thyroid DLBCL is multimodality treatment with chemotherapy and radiotherapy. Meanwhile, surgery can be considered only for diagnosis or alleviation of airway compressive symptoms. A 57-year-old female visited our outpatient clinic for recently enlarged long-held anterior neck mass. A thyroid mass compressing the airway and esophagus was identified on imaging, which was diagnosed as MALT lymphoma by excisional biopsy. After staging, the patient underwent total thyroidectomy with regional lymph node dissection for treatment of stage IIE MALT lymphoma and relieving airway compromise symptoms. The final diagnosis was DLBCL transformed from MALT Lymphoma, and chemotherapy was additionally performed. We report this rare experience with a review of literature.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.430-436
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• 2023

Study on Changes in Vessel Traffic Services Due to Introduction of Maritime Autonomous Surface ShipsThe development of technologies related to Maritime Autonomous Surface Ships (MASS) has been actively progressing since the mid-2010s, focusing on themes such as collision avoidance, route planning, digital twin, and communication technologies. On the other hand, research on land-based infrastructure connected with MASS, such as logistics systems, port facilities, and vessel traffic services, has relatively received less attention. This study analyzed impact of emergence of MASS on existing vessel traffic service operations and proposed changes in control operations to prepare for its impact. To do this, current vessel traffic service operations were analyzed and elements of MASS technology that could affect vessel traffic control were identified. A survey was conducted among vessel traffic controllers to identify items related to the control of MASS. Results analyzed using the AHP method showed that preparation for emergency response and communication methods with MASS were the most important. Based on this, we were able to derive detailed plans for basic MASS control procedures and emergency response procedures based on data communication within maritime traffic control areas. MASS control procedures proposed in this study are expected to be used as a solution to resolve issues related to traffic safety of MASS in coastal areas.

• Information Systems Review
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• v.22 no.4
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• pp.21-39
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• 2020

Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data

• Journal of Physiology & Pathology in Korean Medicine
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• v.37 no.6
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• pp.172-177
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• 2023

In order to deduce the pathogenic factor(PF) diagnosis logic of underlying in pattern identification of Korean medicine, 2,072 cases of DSOM(Diagnosis System of Oriental Medicine) data from May 2005 to April 2022 were collected and analyzed by means of decision tree model(DTM). The entire data were divided into training data and validation data at a ratio of 7:3. The CHAID algorithm was used for analysis of DTM, and then validity was tested by applying the validation data. The decision rules of items and pathways determined from the diagnosis data of Qi Deficiency, Blood Deficiency, Yin Deficiency and Yang Deficiency Pathogenic Factor of DSOM were as follows. Qi Deficiency PF had 7 decision rules and used 5 questions: Q124, Q116a, Q119, Q119a, Q55. The primary indicators(PI) were 'lack of energy' and 'weary of talking'. Blood deficiency PF had 7 decision rules and used 6 questions: Q113, Q84, Q85, Q114, Q129, Q130. The PI were 'numbness in the limbs', 'dizziness when standing up', and 'frequent cramps'. Yin deficiency PF had 3 decision rules and used 2 questions: Q144 and Q56. The PI were 'subjective heat sensation from the afternoon to night' and 'heat sensation in the limbs'. Yang deficiency PF had 3 decision rules and used 3 questions: Q55, Q10, and Q102. The PI were 'sweating even with small movements' and 'lack of energy'. Conclusively, these rules and symptom information to decide the Qi·Blood·Yin·Yang Deficiency PF would be helpful for Korean medicine diagnostics.

• Information Systems Review
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• v.22 no.2
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• pp.101-120
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• 2020

This study investigates the effects of privacy psychological characteristics of B2C logistics services users on their willingness to comply with their logistics companies' information protection policy. Using cognitive valence theory as a theoretical framework, this study proposes a research model to examine the relationships between users' logistics security knowledge, privacy trust, privacy risk, privacy concern, and their willingness of information protection policy compliance. To test the proposed model, we conducted a survey from actual users of logistics services and collected valid 151 samples. We analyzed the data using a structural equation modeling software. The empirical results show that logistics security knowledge positively affects privacy trust; privacy concern positively influences privacy risk; privacy trust, privacy risk, and privacy concern positively influence behavioral willingness of compliance. However, logistics security knowledge does not affect behavioral willingness of compliance. The results of the study provide several contributions to the literature of B2C logistics services domain and managerial implications to logistics services companies.