• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.127-136
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• 2023

Gyeonggi Province has established a bus information system to provide real-time bus arrival information, aiming to make bus usage convenient for its residents. While the Gyeonggi bus information system is becoming more advanced through the application of IT technology, there are still information-vulnerable groups finding it difficult to use. In particular, the elderly have a low level of digital information literacy and habe difficulty using it. In this regard, this study aims to address the information usage disparity among the elderly in public transportation by utilizing expert in-depth survey methodology known as the Delphi technique. The study classified the policy initiatives that Gyeonggi Province should undertake into three categories: user education and expanded promotion, technological development and dissemination, and providing convenient usage environment. Through two rounds of surveys, the study assessed the priority of ten specific sub-tasks within these categories. Additionally, it gathered opinions on the effectiveness and feasibility of each item. The results yielded prioritization and evaluation of effectiveness and feasibility for nine sub-tasks. Based on these outcomes, the study proposed future projects that Gyeonggi Province should implement to address the information disparity among the elderly, offering a comprehensive approach to bridge the gap.

• Journal of the Korean Society of Radiology
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• v.17 no.6
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• pp.911-917
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• 2023

The method of observing nodular changes on the liver surface using clinical ultrasonography is useful for diagnosing cirrhosis. However, the speckle noise that inevitably occurs in ultrasound images makes it difficult to identify changes in the liver surface and echo patterns, which has a negative impact on the diagnosis of cirrhosis. The purpose of this study is to model the median modified Wiener filter (MMWF), which can efficiently reduce noise in cirrhotic ultrasound images, and confirm its applicability. Ultrasound images were acquired using an ACR phantom and an actual cirrhotic patient, and the proposed MMWF algorithm and conventional noise reduction algorithm were applied to each image. Coefficient of variation (COV) and edge rise distance (ERD) were used as quantitative image quality evaluation factors for the acquired ultrasound images. We confirmed that the MMWF algorithm improved both COV and ERD values compared to the conventional noise reduction algorithm in both ACR phantom and real ultrasound images of cirrhotic patients. In conclusion, the proposed MMWF algorithm is expected to contribute to improving the diagnosis rate of cirrhosis patients by reducing the noise level and improving spatial resolution at the same time.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.81-89
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• 2023

In modern society, blind people face difficulties in navigating common environments such as sidewalks, elevators, and crosswalks. Research has been conducted to alleviate these inconveniences for the visually impaired through the use of visual and audio aids. However, such research often encounters limitations when it comes to practical implementation due to the high cost of wearable devices, high-performance CCTV systems, and voice sensors. In this paper, we propose an artificial intelligence fusion algorithm that utilizes low-cost video sensors integrated into smartphones to help blind people safely navigate their surroundings during walking. The proposed algorithm combines motion capture and object detection algorithms to detect moving people and various obstacles encountered during walking. We employed the MediaPipe library for motion capture to model and detect surrounding pedestrians during motion. Additionally, we used object detection algorithms to model and detect various obstacles that can occur during walking on sidewalks. Through experimentation, we validated the performance of the artificial intelligence fusion algorithm, achieving accuracy of 0.92, precision of 0.91, recall of 0.99, and an F1 score of 0.95. This research can assist blind people in navigating through obstacles such as bollards, shared scooters, and vehicles encountered during walking, thereby enhancing their mobility and safety.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1195-1210
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• 2023

Coastal debris has emerged as a salient issue due to its adverse effects on coastal aesthetics, ecological systems, and human health. In pursuit of effective countermeasures, the present study delineated the construction of a specialized image dataset for coastal debris detection and embarked on a comparative analysis between two paramount real-time object detection algorithms, YOLOv8 and RT-DETR. Rigorous assessments of robustness under multifarious conditions were instituted, subjecting the models to assorted distortion paradigms. YOLOv8 manifested a detection accuracy with a mean Average Precision (mAP) value ranging from 0.927 to 0.945 and an operational speed between 65 and 135 Frames Per Second (FPS). Conversely, RT-DETR yielded an mAP value bracket of 0.917 to 0.918 with a detection velocity spanning 40 to 53 FPS. While RT-DETR exhibited enhanced robustness against color distortions, YOLOv8 surpassed resilience under other evaluative criteria. The implications derived from this investigation are poised to furnish pivotal directives for algorithmic selection in the practical deployment of marine debris monitoring systems.

• Journal of Venture Innovation
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• v.6 no.1
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• pp.59-73
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• 2023

In the era of the 4th Industrial Revolution, manufacturing is the implementation of smart factories through digital transformation, and refers to consumer-centered intelligent factories that combine next-generation digital new technologies and manufacturing technologies beyond the existing factory automation level. In order to successfully settle such a smart factory, it is necessary to train professionals. However, education for smart factories is difficult to have actual field mechanical facilities or overall production processes. Therefore, there is a need for a system that can visualize and control the flow and process of logistics at the actual production site. In this paper, the logistics flow of the actual site was implemented as a small FMS, a physical system, and the production process was implemented as a digital system. In real-time synchronization of the physical system and the digital system, the location of AGV and materials, and the process state can be monitored to see the flow of logistics and process processes at the actual manufacturing site. The developed digital twin system can be used as an effective educational system for training manpower in smart factories.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.743-754
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• 2023

The global occurrence of myriad natural disasters and incidents, catalyzed by climate change and extreme meteorological conditions, has engendered substantial human and material losses. International organizations such as the International Charter have established an enduring collaborative framework for real-time coordination to provide high-resolution satellite imagery and geospatial information. These resources are instrumental in the management of large-scale disaster scenarios and the expeditious execution of recovery operations. At the national level, the operational deployment of advanced National Earth Observation Satellites, controlled by National Geographic Information Institute, has not only catalyzed the advancement of geospatial data but has also contributed to the provisioning of damage analysis data for significant domestic and international disaster events. This special edition of the National Disaster Management Research Institute delineates the contemporary landscape of major disaster incidents in the year 2023 and elucidates the strategic blueprint of the government's national disaster safety system reform. Additionally, it encapsulates the most recent research accomplishments in the domains of artificial satellite systems, information and communication technology, and spatial information utilization, which are paramount in the institution's disaster situation management and analysis efforts. Furthermore, the publication encompasses the most recent research findings relevant to data collection, processing, and analysis pertaining to disaster cause and damage extent. These findings are especially pertinent to the institute's on-site investigation initiatives and are informed by cutting-edge technologies, including drone-based mapping and LiDAR observation, as evidenced by a case study involving the 2023 landslide damage resulting from concentrated heavy rainfall.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.17-27
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• 2023

Today, as AI (Artificial Intelligence) technology develops and its practicality increases, it is widely used in various application fields in real life. At this time, the AI model is basically learned based on various statistical properties of the learning data and then distributed to the system, but unexpected changes in the data in a rapidly changing data situation cause a decrease in the model's performance. In particular, as it becomes important to find drift signals of deployed models in order to respond to new and unknown attacks that are constantly created in the security field, the need for lifecycle management of the entire model is gradually emerging. In general, it can be detected through performance changes in the model's accuracy and error rate (loss), but there are limitations in the usage environment in that an actual label for the model prediction result is required, and the detection of the point where the actual drift occurs is uncertain. there is. This is because the model's error rate is greatly influenced by various external environmental factors, model selection and parameter settings, and new input data, so it is necessary to precisely determine when actual drift in the data occurs based only on the corresponding value. There are limits to this. Therefore, this paper proposes a method to detect when actual drift occurs through an Anomaly analysis technique based on XAI (eXplainable Artificial Intelligence). As a result of testing a classification model that detects DGA (Domain Generation Algorithm), anomaly scores were extracted through the SHAP(Shapley Additive exPlanations) Value of the data after distribution, and as a result, it was confirmed that efficient drift point detection was possible.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.823-835
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• 2023

Recently, due to the increase in abnormal climate, rainfall intensity is increasing and drought periods are continuing. These environmental changes lead to prolonged drought conditions and difficulties in real-time recognition. In general, drought can be judged by the amount of precipitation and the number of days without rainfall. In determining the impact of drought, it is divided into meteorological drought, agricultural drought, and hydrological drought and evaluation is made using the drought index, but environmental drought evaluation is insufficient. The river water quality managed through the total water pollution cap system is vulnerable to the effects of such drought. In this study, we aim to determine the drought impact on river water quality and quantify the impact of prolonged drought on water quality. The impact of rain-free days and accumulated precipitation on river water quality was quantitatively evaluated. The Load Duration Curve (LDC), which is used to evaluate the water quality of rivers, was used to evaluate water pollution occurring at specific times. It has been observed that when the number of consecutive rainless days exceeds 14 days, the target water quality in the mid-basin is exceeded in over 60% of cases. The cumulative rainfall is set at 28 days as the criteria, with an annual average rainfall of 3%, which is 32.1 mm or less. It has been noted that changes in water quality in rivers occur when there are 14 or more rainless days and the cumulative rainfall over 28 days is 32.1 mm or less in the Gamcheon Mid-basin. Based on the results of this study, it aims to quantify the drought impact and contribute to the development of a drought water quality index for future environmental droughts.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1001-1006
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• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• Journal of the Korean Applied Science and Technology
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• v.40 no.5
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• pp.965-976
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• 2023

Reynoutria japonica is a perennate plant belonging to Polygonaceae and grows wild in East Asia containing Korea. Roots of Reynoutria japonica (R. japonica), part of roots of Reynoutria japonica, has been used for anti-inflammation and antispasmodics and contains emodin as active compound. Epidermis of skin is crucial roles to defense our body against stimulants, harmful substance and prevent water loss. In this study, we examined the effect of R. japonica and emodin, its active compound, on skin-barrier and moisturizing on HaCaT cells. First, antioxidant effect of R. japonica was prominent by scavenging ABTS⁺ radicals. Next, we conducted real time PCR and expression of filaggrin mRNA which is crucial role in differentiation of keratinocyte increased by R. japonica and emodin dose-dependently. In addition, R. japonica and emodin significantly elevated the expression of HAS-2 mRNA which play a role in hyaluronic acid synthesis on HaCaT cells. Taken together, R. japonica containing emodin, as active compound has potential as a cosmetic material for enhancing the function of skin-barrier and moisturizing in epidermis.