• Korean Journal of Artificial Intelligence
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• v.9 no.1
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• pp.9-14
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• 2021

This paper predicted a model that indicates whether to buy a car based on primary health insurance customer data. Currently, automobiles are being used to land transportation and living, and the scope of use and equipment is expanding. This rapid increase in automobiles has caused automobile insurance to emerge as an essential business target for insurance companies. Therefore, if the car insurance sales are predicted and sold using the information of existing health insurance customers, it can generate continuous profits in the insurance company's operating performance. Therefore, this paper aims to analyze existing customer characteristics and implement a predictive model to activate advertisements for customers interested in such auto insurance. The goal of this study is to maximize the profits of insurance companies by devising communication strategies that can optimize business models and profits for customers. This study was conducted through the Microsoft Azure program, and an automobile insurance purchase prediction model was implemented using Health Insurance Cross-sell Prediction data. The program algorithm uses Two-Class Logistic Regression and Two-Class Boosted Decision Tree at the same time to compare two models and predict and compare the results. According to the results of this study, when the Threshold is 0.3, the AUC is 0.837, and the accuracy is 0.833, which has high accuracy. Therefore, the result was that customers with health insurance could induce a positive reaction to auto insurance purchases.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.31-42
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• 2021

Several studies have been conducted on market orientation over the last three decades. However, the majority of previous research focused exclusively on an internal vision that conceives the market orientation from an organizational perspective, considering the market orientation as a strictly perceived culture or behavior by company's staff (managers and employees) .This study aims to emphasize the importance of analyzing the market orientation from a dual perspective by investigating simultaneously the perceptions of customers and those of managers. It examines the perceptual gap or perceptual congruence of market orientation between customers and managers. A survey is conducted with Tunisian bank managers and B to B customers to measure their market orientation perception. The results should reveal level of manager's market orientation in Tunisian banks compared to customers' perceptions. The perception gaps of market orientation between managers and customers named congruence is highlighted and categorized. This study provides some contributions to fill the gap emerging from the one-sidedness of market orientation evaluation and gives a dyadic vision of market orientation that helps managers in their continuous learning about markets and sensing customers' needs and expectations. Market orientation level between the two groups is evaluated to give some managerial recommendations.

• Smart Structures and Systems
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• v.29 no.4
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• pp.599-616
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• 2022

Bridge displacement contains vital information for bridge condition and performance. Due to the limits of direct displacement measurement methods, the indirect displacement reconstruction methods based on the strain or acceleration data are also developed in engineering applications. There are still some deficiencies of the displacement reconstruction methods based on strain or acceleration in practice. This paper proposed a novel method based on long short-term memory (LSTM) networks to reconstruct the bridge dynamic displacements with the strain and acceleration data source. The LSTM networks with three hidden layers are utilized to map the relationships between the measured responses and the bridge displacement. To achieve the data fusion, the input strain and acceleration data need to be preprocessed by normalization and then the corresponding dynamic displacement responses can be reconstructed by the LSTM networks. In the numerical simulation, the errors of the displacement reconstruction are below 9% for different load cases, and the proposed method is robust when the input strain and acceleration data contains additive noise. The hyper-parameter effect is analyzed and the displacement reconstruction accuracies of different machine learning methods are compared. For experimental verification, the errors are below 6% for the simply supported beam and continuous beam cases. Both the numerical and experimental results indicate that the proposed data fusion method can accurately reconstruct the displacement.

• International Journal of Knowledge Content Development & Technology
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• v.12 no.4
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• pp.41-65
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• 2022

This study would understand the overall perception of our society about public libraries, analyzing the texts related to public libraries, utilizing the semantic connection network & sentiment analysis. For this purpose, this study collected data from the last five years with keywords, 'Library' and 'Lifelong Learning Center' from January 1, 2016 through November 30, 2020 through the blogs and cafés of major domestic portal sites. With the collected data, text mining, centrality of keywords, network structure, structural equipotentiality, and sensitivity analyses were conducted. As a result of the analysis, First, 'reading' and 'book' were identified as representative keywords that form the social perception of public libraries. Second, it turned out that there were keywords related to the use of the library and the untact service due to the recent spread of COVID-19. Third, in seeking a plan for the development of public libraries through the keywords drawn to have positive meanings, it is necessary to create continuous services that can form a new image of the library, breaking away from the existing fixed role and image of the library and increase the convenience of use. Fourth, facilities and facilities for library services were recognized from a neutral point of view. Fifth, the spread of infectious diseases, social distancing, and temporary closure and closure of libraries are negatively related to public libraries, and awareness of librarians has been identified as negative keywords.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.293-298
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• 2023

The military is facing a continuous decrease in personnel, and in order to cope with potential accidents and challenges in operations, efforts are being made to reduce the direct involvement of personnel by utilizing the latest technologies. Recently, the use of various sensors related to Manned-Unmanned Teaming and artificial intelligence technologies has gained attention, emphasizing the need for flexible utilization methods. In this paper, we propose four dataset construction methods that can be used for effective training of robots that can be deployed in military operations, utilizing not only RGB image data but also data acquired from IR image sensors. Since there is no publicly available dataset that combines RGB and IR image data, we directly acquired the dataset within buildings. The input values were constructed by combining RGB and IR image sensor data, taking into account the field of view, resolution, and channel values of both sensors. We compared the proposed method with conventional RGB image data classification training using the same learning model. By employing the proposed image data fusion method, we observed improved stability in training loss and approximately 3% higher accuracy.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.2
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• pp.41-50
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• 2023

Gait analysis is an important tool in the clinical management of cerebral palsy, allowing for the assessment of condition severity, identification of potential gait abnormalities, planning and evaluation of interventions, and providing a baseline for future comparisons. However, traditional methods of gait analysis are costly and time-consuming, leading to a need for a more convenient and continuous method. This paper proposes a method for analyzing the posture of cerebral palsy patients using only smartphone videos and deep learning models, including a ResNet-based image tilt correction, AlphaPose for human pose estimation, and SmoothNet for temporal smoothing. The indicators employed in medical practice, such as the imbalance angles of shoulder and pelvis and the joint angles of spine-thighs, knees and ankles, were precisely examined. The proposed system surpassed pose estimation alone, reducing the mean absolute error for imbalance angles in frontal videos from 4.196° to 2.971° and for joint angles in sagittal videos from 5.889° to 5.442°.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.122-122
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• 2021

전 세계적인 기후변화로 인해 태풍과 집중호우의 빈도와 규모가 증가하고 있으며 그로 인해 수재해 대응과 수자원 관리에 많은 어려움이 따른다. 댐 운영은 이러한 수자원 관리의 중요한 요소이며 정확한 댐 유입량의 예측은 효율적인 댐 운영과 관리의 필수적인 부분이다. 최근에는 여러 분야에서 활용되고 있는 딥러닝 모델을 활용하여 댐 유입량 예측에 관한 다수의 연구들이 수행되고 있다. 특히, 수문 시계열의 장기적인 특성과 비선형적인 관계를 고려하기 위해 연속형 모의를 기반으로 하는 딥러닝 모델의 적용 및 평가와 관련 연구의 필요성이 대두되고 있다. 본 연구에서는 연속형 모의를 기반으로 하는 딥러닝 모델을 활용하여 댐 유입량 예측을 수행하고자 하며 이의 적용성을 평가하고자 한다. 적용 대상 지역으로는 안동댐 상류 유역을 선정하였으며 2006년부터 2020년까지의 시 단위 강우 및 댐 유입량 자료를 활용하였다. 선행시간(1~6시간)별 예측 유입량과 관측 유입량의 비교를 통한 정량적 평가를 수행하였다. 또한 입력 자료에 대한 과거 기간, 모델 구성, 손실함수 등에 대한 조건별 평가를 통해 예측 정확도의 변화에 대한 분석을 수행하였다. 본 연구결과를 통해, 딥러닝 기반의 댐 유입량 예측 정확도에 대한 향상과 실시간 예측을 위한 딥러닝 모델의 활용성 증대에 기여할 것으로 기대된다. 향후, 강우 예보 자료를 연계한 딥러닝 기반의 실시간 댐 유입량 예측 기법을 제안하고 이의 활용성을 평가하고자 한다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.294-296
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• 2022

Atherosclerosis is a chronic vascular inflammatory disease in which plaque builds up in the arteries and impairs blood flow. This can lead to heart disease and stroke. Since most people do not have any symptoms until the artery is severely narrowed, early detection of atherosclerosis is critical. In this paper, in order to effectively detect atherosclerotic lesions in tube-shaped blood vessels, polar conversion is applied to MRI images based on the vessel center. We then propose a SE-LSTMNet model using continuous signal information for each angle of a polar coordinate image. The trained model showed classification performance of 0.9194 accuracy, 0.9370 sensitivity, 0.8796 specificity, 0.8700 F1 score, and 0.9719 AUC on the validation data.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.31-36
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• 2023

The purpose of this study is to provide basic data for developing strategies to maintain a stable and happy middle-aged and mature years. We want a happy life during middle and old age. However, most middle-aged and older adults are a continuous process of self-regulation, learning stress coping skills to maintain balance and integration throughout their lives, control their emotions, and effectively regulate their living environments. To effectively cope with the crises experienced in middle and old age, to discover and pursue one's own unique meaning in life, and to enjoy a stable and vibrant middle and old age without experiencing difficulties between happiness and unhappiness, we continuously learn the core of the meaning of life. The purpose of this study is to present data.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.270-280
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• 2024

This study aims to explore innovative measures for community policing activities of the Korean police in the context of the newly implemented autonomous police system and the increasing demand for community-oriented policing. By conducting an in-depth analysis of advanced community policing practices in the United States, Japan, and the United Kingdom, this research identifies key characteristics such as resident participation, communication, scientific crime analysis, and customized policing services. The study reveals the need for the Korean police to establish a collaborative governance system that actively involves residents, strengthen scientific policing capabilities utilizing advanced technologies, and provide policing services tailored to local characteristics. Organizational and personnel management reforms, including the substantiation of the local police officer system and the establishment of an institutional foundation for resident participation, are proposed. Furthermore, this study emphasizes the importance of developing a creative community policing model suitable for the Korean context, rather than directly transplanting overseas practices. Continuous research and efforts to build a new policing paradigm that reflects the changing social environment and policing demands are suggested. Ultimately, the success of community policing lies in the active participation and cooperation of all members of society, including the police, government, local communities, and residents.