• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.128-133
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• 2021

Currently, autonomous vehicle markets are commercializing a third-level autonomous vehicle, but there is a possibility that an accident may occur even during fully autonomous driving due to stability issues. In fact, autonomous vehicles have recorded 81 accidents. This is because, unlike level 3, autonomous vehicles after level 4 have to judge and respond to emergency situations by themselves. Therefore, this paper proposes a vehicle crisis detection system(VCDS) that collects and stores information outside the vehicle through CNN, and uses the stored information and vehicle sensor data to output the crisis situation of the vehicle as a number between 0 and 1. The VCDS consists of two modules. The vehicle external situation collection module collects surrounding vehicle and pedestrian data using a CNN-based neural network model. The vehicle crisis situation determination module detects a crisis situation in the vehicle by using the output of the vehicle external situation collection module and the vehicle internal sensor data. As a result of the experiment, the average operation time of VESCM was 55ms, R-CNN was 74ms, and CNN was 101ms. In particular, R-CNN shows similar computation time to VESCM when the number of pedestrians is small, but it takes more computation time than VESCM as the number of pedestrians increases. On average, VESCM had 25.68% faster computation time than R-CNN and 45.54% faster than CNN, and the accuracy of all three models did not decrease below 80% and showed high accuracy.

• Journal of Aerospace System Engineering
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• v.16 no.4
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• pp.95-108
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• 2022

Airworthiness certification is critical, in ensuring the flight safety of military aircraft for development tests and production operations. The MIL-HDBK-516C, latest airworthiness certification document, handles the field of flying qualities in Chapter 6 (flight technology), and refers to specific chapters of MIL-STD-1797B, which is the specification document for developing military aircraft. Since the MIL-STD-1797B released in 2006 by the U.S. Department of Defense is not disclosed to other countries, the Chapter 6 (flight technology) of MIL-HDBK-516B Expanded, the former certification standards pursuant to flying qualities, has to be applied to military aircraft being developed in the Republic of Korea. However the requirements of Chapter 6 of MIL-HDBK-516B Expanded comprise unclear sentences, because of contents from various development specifications. Also, clarification is needed in that the same requirements have to be verified in different criteria. In this paper, the results of this study present an effective verification method, for acquiring the airworthiness certification in field of flying qualities based on MIL-HDBK-516B Expanded.

• Journal of Internet Computing and Services
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• v.23 no.3
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• pp.87-95
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• 2022

Recently, with the development of smart technology, in medical information platform, patient's biometric data is measured in real time and accumulated into database, and it is possible to determine the patient's emergency situations. Medical staff can easily access patient information after simple authentication using a mobile terminal. However, in accessing medical information using the mobile terminal, it is necessary to study authentication in consideration of the patient situations and mobile terminal. In this paper, we studied on medical information platforms based on big data processing and edge computing for supporting automatic authentication in emergency situations. The automatic authentication system that we had studied is an authentication system that simultaneously performs user authentication and mobile terminal authentication in emergency situations, and grants upper-level access rights to certified medical staff and mobile terminal. Big data processing and analysis techniques were applied to the proposed platform in order to determine emergency situations in consideration of patient conditions such as high blood pressure and diabetes. To quickly determine the patient's emergency situations, edge computing was placed in front of the medical information server so that the edge computing determine patient's situations instead of the medical information server. The medical information server derived emergency situation decision values using the input patient's information and accumulated biometric data, and transmit them to the edge computing to determine patient-customized emergency situation. In conclusion, the proposed medical information platform considers the patient's conditions and determine quick emergency situations through big data processing and edge computing, and enables rapid authentication in emergency situations through automatic authentication, and protects patient's information by granting access rights according to the patient situations and the role of the medical staff.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.339-346
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• 2022

Recently, the resource depletion and climate change problem caused by the massive usage of fossil fuels for electric power generation has become a critical issue worldwide. According to this issue, interest in renewable energy resources that can replace fossil fuels is increasing. Especially, photovoltaic power has gaining much attention because there is no risk of resource exhaustion compared to other energy resources and there are low restrictions on installation of photovoltaic system. In order to use the power generated by the photovoltaic system efficiently, a more accurate photovoltaic power forecasting model is required. So far, even though many machine learning and deep learning-based photovoltaic power forecasting models have been proposed, they showed limited success in terms of interpretability. Deep learning-based forecasting models have the disadvantage of being difficult to explain how the forecasting results are derived. To solve this problem, many studies are being conducted on explainable artificial intelligence technique. The reliability of the model can be secured if it is possible to interpret how the model derives the results. Also, the model can be improved to increase the forecasting accuracy based on the analysis results. Therefore, in this paper, we propose an explainable photovoltaic power forecasting scheme based on BiLSTM (Bidirectional Long Short-Term Memory) and SHAP (SHapley Additive exPlanations).

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.43-53
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• 2023

In this detailed and comprehensive study, our primary focus has been placed on accurately gauging the number of visitors and their real-time locations in commercial spaces. Particularly, in a real cafe, using security cameras, we have developed a system that can offer live updates on available seating and predict future congestion levels. By employing YOLO, a real-time object detection and tracking algorithm, the number of visitors and their respective locations in real-time are also monitored. This information is then used to update a cafe's indoor map, thereby enabling users to easily identify available seating. Moreover, we developed a model that predicts the congestion of a cafe in real time. The sophisticated model, designed to learn visitor count and movement patterns over diverse time intervals, is based on Long Short Term Memory (LSTM) to address the vanishing gradient problem and Sequence-to-Sequence (Seq2Seq) for processing data with temporal relationships. This innovative system has the potential to significantly improve cafe management efficiency and customer satisfaction by delivering reliable predictions of cafe congestion to all users. Our groundbreaking research not only demonstrates the effectiveness and utility of indoor location tracking technology implemented through security cameras but also proposes potential applications in other commercial spaces.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.419-430
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• 2023

Currently, NFTs have no dominant application except for the proof of ownership for digital content, and it also have small liquidity problem, which makes their price difficult to predict. Real estate usually has very high barriers to investment due to its high pricing. Real estate can be converted into NFTs and also divided into small value fungible tokens (FTs), and it can increase the the volume of the investor community due to more liquidity and better accessibility. In this document, we implement and design a system that allows ordinary users can invest on high priced real estate utilizing Black Litterman (BL) model-based Portfolio investment interface. To this end, we target a set of real estates pegged as collateral and issue NFT for the collateral using blockchain. We use oracle to get the current real estate information and to monitor varying real estate prices. After tokenizing real estate into NFTs, we divide the NFTs into easily accessible price FTs, thereby, we can lower prices and provide large liquidity with price volatility limited. In addition, we also implemented BL based asset portfolio interface for effective portfolio composition for investing in multiple of real estates with small investments. Using BL model, investors can fix the asset portfolio. We implemented the whole system using Solidity smart contracts on Flask web framework with public data portals as oracle interfaces.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.3
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• pp.206-214
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• 2023

Fish school monitoring technology is utilized for various purposes, such as boat fishing and resource surveys. With advancements in information and communication technology, this technology has expanded its application to remote areas. Its significance has grown in fishing sites, particularly for improving the efficiency and cost-effectiveness of set-net fishing. Set-net fishing gears are not limited to coastal areas, but are also installed in inland and remote sea regions. Consequently, fishermen require technology that allows them to quickly transmit information about approaching fish schools and enables them to perform long-term monitoring. The development of remote monitoring technology for set-net fish schools must consider crucial design factors such as communication range, transmission speed, power consumption of information modules, and operational expenses. In this study, we developed a low-power remote monitoring module for set-net fish school based on WCDMA. The module was specifically designed to minimize power consumption, allowing for communication over long distances and extended operation times in set-net fishing applications. Furthermore, we developed a web server software application that enables remote access to fish schools and provides real-time weather information. The performance of the developed module was evaluated through set-net fishing site application and experiments with moving ships on the sea. The experimental results demonstrated that the remote monitoring system, consisting of the developed low-power remote monitoring module for set-net fish school based on WCDMA and a fish finder, had an average power consumption of 4.6 W, a maximum communication range of 22.84 km, and a data transmission and reception rate of 98.79%. The maximum fish school information transmission and reception rate was 97.26%

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.433-435
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• 2022

In this paper, we introduce a computing resource standard metadata schema design plan for registering, retrieving, and managing computing resources used for research data analysis and utilization in the Korea Research Data Commons(KRDC). KRDC is a joint utilization system of research data and computing resources to maximize the sharing and utilization of research data. Computing resources refer to all resources in the computing environment, such as analysis infrastructure and analysis software, necessary to analyze and utilize research data used in the entire research process. The standard metadata schema for KRDC computing resource management is designed by considering common attributes for computing resource management and other attributes according to each computing resource feature. The standard metadata schema for computing resource management consists of a computing resource metadata schema and a computing resource provider metadata schema. In addition, the metadata schema of computing resources and providers was designed as a service schema and a system schema group according to their characteristics. The standard metadata schema designed in this paper is used for computing resource registration, retrieval, management, and workflow services for computing resource providers and computing resource users through the KRDC web service, and is designed in a scalable form for various computing resource links.

• Therapeutic Science for Rehabilitation
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• v.12 no.2
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• pp.55-68
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• 2023

Objective : This study aims to analyze the effects of visual perception intervention by systematically reviewing the studies that applied visual perception intervention to children with cerebral palsy. Methods : The databases used were PubMed, EMbase, Science Direct, ProQuest, Koreanstudies Information Service System (KISS), Research Information Sharing Service (RISS), and the National Assembly Library. The keywords used were cerebral palsy, CP, and visual perception. According to the PRISMA flowchart, 10 studies were selected from among studies published from January 1, 2012 to March 30, 2022. The quality level of the selected studies, the demographic characteristics of study participants, the effectiveness of interventions, area and strategies of intervention, assessment tools to measure the effectiveness of interventions, and risk of bias were analyzed. Results : All selected studies confirmed that visual perception intervention was effective in improving visual perception function. In addition, positive results were shown in upper extremity function, activities of daily living, posture control, goal achievement, and psychosocial areas as well as visual perception function. The eye-hand coordination area was intervened in all studies. Conclusion : In visual perception intervention, It is necessary to evaluate the visual perception function by area, and apply systematically graded customized interventions for each individual.

• The Korean Journal of Nuclear Medicine Technology
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• v.27 no.1
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• pp.47-54
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• 2023

Purpose PET-CT imaging require an appropriate quality assurance system to achieve high efficiency and reliability. Quality control is essential for improving the quality of care and patient safety. Currently, there are performance evaluation methods of UN2-1994 and UN2-2001 proposed by NEMA and IEC for PET-CT image evaluation. In this study, we compare phantom images with the same experiments before and after PET-CT 3D normalization and well counter correction and evaluate the usefulness of quality control. Materials and methods Discovery 690 (General Electric Healthcare, USA) PET-CT equiptment was used to perform 3D normalization and well counter correction as recommended by GE Healthcare. Based on the recovery coefficients for the six spheres of the NEMA IEC Body Phantom recommended by the EARL. 20kBq/㎖ of ¹⁸F was injected into the sphere of the phantom and 2kBq/㎖ of ¹⁸F was injected into the body of phantom. PET-CT scan was performed with a radioacitivity ratio of 10:1. Images were reconstructed by appliying TOF+PSF+TOF, OSEM+PSF, OSEM and Gaussian filter 4.0, 4.5, 5.0, 5.5, 6.0, 6,5 mm with matrix size 128×128, slice thickness 3.75 mm, iteration 2, subset 16 conditions. The PET image was attenuation corrected using the CT images and analyzed using software program AW 4.7 (General Electric Healthcare, USA). The ROI was set to fit 6 spheres in the CT image, RC (Recovery Coefficient) was measured after fusion of PET and CT. Statistical analysis was performed wilcoxon signed rank test using R. Results Overall, after the quality control items were performed, the recovery coefficient of the phantom image increased and measured. Recovery coefficient according to the image reconstruction increased in the order TOF+PSF, TOF, OSEM+PSF, before and after quality control, RCmax increased by OSEM 0.13, OSEM+PSF 0.16, TOF 0.16, TOF+PSF 0.15 and RCmean increased by OSEM 0.09, OSEM+PSF 0.09, TOF 0.106, TOF+PSF 0.10. Both groups showed a statistically significant difference in Wilcoxon signed rank test results (P value<0.001). Conclusion PET-CT system require quality assurance to achieve high efficiency and reliability. Standardized intervals and procedures should be followed for quality control. We hope that this study will be a good opportunity to think about the importance of quality control in PET-CT