• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1130-1135
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• 2022

In Seoul, about 75,000 CCTVs are installed in 25 district offices. Each ward office has built a control center for CCTV control and is performing 24-hour CCTV video control for the safety of citizens. Seoul Metropolitan Government is building a smart city integrated platform that is safe for citizens by providing CCTV images of the ward office to enable rapid response to emergency/emergency situations by signing an MOU with related organizations. In this paper, when an incident occurs at the Seoul Metropolitan Government Office, the escape route is predicted by discriminating people and vehicles using the AI DNN-based Template Matching technology, MLP algorithm and CNN-based YOLO SPP DNN model for CCTV images. In addition, it is designed to automatically disseminate image information and situation information to adjacent ward offices when vehicles and people escape from the competent ward office. The escape route prediction and tracking system using artificial intelligence can expand the smart city integrated platform nationwide.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.359-373
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• 2022

The new crown pneumonia (COVID-19) has become a global epidemic. The disease has spread to most countries and poses a challenge to the healthcare system. Contact tracing technology is an effective way for public health to deal with diseases. Many experts have studied traditional contact tracing and developed digital contact tracking. In order to better understand the field of contact tracking, it is necessary to analyze the development of contact tracking in the field of computer science by bibliometrics. The purpose of this research is to use literature statistics and topic analysis to characterize the research literature of contact tracking in the field of computer science, to gain an in-depth understanding of the literature development status of contact tracking and the trend of hot topics over the past decade. In order to achieve the aforementioned goals, we conducted a bibliometric study in this paper. The study uses data collected from the Scopus database. Which contains more than 10,000 articles, including more than 2,000 in the field of computer science. For popular trends, we use VOSviewer for visual analysis. The number of contact tracking documents published annually in the computer field is increasing. At present, there are 200 to 300 papers published in the field of computer science each year, and the number of uncited papers is relatively small. Through the visual analysis of the paper, we found that the hot topic of contact tracking has changed from the past "mathematical model," "biological model," and "algorithm" to the current "digital contact tracking," "privacy," and "mobile application" and other topics. Contact tracking is currently a hot research topic. By selecting the most cited papers, we can display high-quality literature in contact tracking and characterize the development trend of the entire field through topic analysis. This is useful for students and researchers new to field of contact tracking ai well as for presenting our results to other subjects. Especially when comprehensive research cannot be conducted due to time constraints or lack of precise research questions, our research analysis can provide value for it.

• Journal of Korea Multimedia Society
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• v.25 no.8
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• pp.1224-1232
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• 2022

Whole body bone scan is the most frequently performed nuclear medicine imaging to evaluate bone metastasis in cancer patients. We evaluated the performance of a VGG16-based transfer learning classifier for bone scan images in which metastatic bone lesion was present. A total of 1,000 bone scans in 1,000 cancer patients (500 patients with bone metastasis, 500 patients without bone metastasis) were evaluated. Bone scans were labeled with abnormal/normal for bone metastasis using medical reports and image review. Subsequently, gradient-weighted class activation maps (Grad-CAMs) were generated for explainable AI. The proposed model showed AUROC 0.96 and F1-Score 0.90, indicating that it outperforms to VGG16, ResNet50, Xception, DenseNet121 and InceptionV3. Grad-CAM visualized that the proposed model focuses on hot uptakes, which are indicating active bone lesions, for classification of whole body bone scan images with bone metastases.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.96-101
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• 2023

In this work, an energy harvester (EH) on the rotating shaft has been proposed for a wireless sensor system (WSS) applications. The EH was designed and implemented to the shaft with a diameter of 20 cm to continuously power a wireless sensor system (WSS). The rotor has coils wound in pairs on seven U-shaped cores attached to the shaft. The stator consists of eight pairs of magnets attached to eight I-cores and they are fixed to an outer fixture. The generated power of the EH was investigated as function of the air gap between the rotor and stator, the number of turn of coils, and shaft speed. The fabricated EH produced power up to 2.87 W at 300 rpm and the 3 mm air gap.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.71-76
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• 2023

In this paper, a humidity sensor using a microstrip patch antenna(MPA) and polyvinyl alcohol(PVA) is studied. PVA is a polymer material whose permittivity changes with humidity, and a rectangular slot is added to the radiating edge of the MPA, which is sensitive to changes in electric field, in order to increase the sensitivity to changes in relative permittivity. After thinly coating the area around the radiating edge with the rectangular slot of the MPA fabricated on a 0.76 mm-thick RF-35 substrate with PVA, the changes in the resonant frequency and magnitude of the MPA's input reflection coefficient are measured when relative humidity is adjusted from 40% to 80% in 10% increments at a temperature of 25 degrees using a temperature and humidity chamber. Experiment results show that when the relative humidity increases from 40% to 80%, the resonance frequency of the antenna' input reflection coefficient decreases from 2.447 GHz to 2.418 GHz, whereas the magnitude increases from -7.112 dB to -3.428 dB.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.63-70
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• 2023

In this work, a capacitive wireless power transfer (C-WPT) system is presented for wireless sensor system (WSS) applications in marine propulsion shafts. For a single Q factor on both sides of the coupling capacitor and reactive power removal from the circuit, a double-sided LCLC converter and transformers topology are designed to drive the rotary C-WPT system for WSS on the shaft. Parallel-connected parallel plate rotating capacitors with a capacitance of 170 pF are designed and implemented for the C-WPT system on a snow rotating shaft. In the experimental results, the C-WPT system achieved a transmission efficiency of 66.67% with 7.8 W output power at 3 mm distance and 1 MHz operating frequency. Therefore, it was proved that the fabricated C-WPT system can supply power to the WSS of the rotating shaft.

• Smart Structures and Systems
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• v.31 no.4
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• pp.335-349
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• 2023

Bridges constantly undergo deterioration and damage, the most common ones being concrete damage and exposed rebar. Periodic inspection of bridges to identify damages can aid in their quick remediation. Likewise, identifying components can provide context for damage assessment and help gauge a bridge's state of interaction with its surroundings. Current inspection techniques rely on manual site visits, which can be time-consuming and costly. More recently, robotic inspection assisted by autonomous data analytics based on Computer Vision (CV) and Artificial Intelligence (AI) has been viewed as a suitable alternative to manual inspection because of its efficiency and accuracy. To aid research in this avenue, this study performs a comparative assessment of different architectures, loss functions, and ensembling strategies for the autonomous segmentation of bridge components and damages. The experiments lead to several interesting discoveries. Nested Reg-UNet architecture is found to outperform five other state-of-the-art architectures in both damage and component segmentation tasks. The architecture is built by combining a Nested UNet style dense configuration with a pretrained RegNet encoder. In terms of the mean Intersection over Union (mIoU) metric, the Nested Reg-UNet architecture provides an improvement of 2.86% on the damage segmentation task and 1.66% on the component segmentation task compared to the state-of-the-art UNet architecture. Furthermore, it is demonstrated that incorporating the Lovasz-Softmax loss function to counter class imbalance can boost performance by 3.44% in the component segmentation task over the most employed alternative, weighted Cross Entropy (wCE). Finally, weighted softmax ensembling is found to be quite effective when used synchronously with the Nested Reg-UNet architecture by providing mIoU improvement of 0.74% in the component segmentation task and 1.14% in the damage segmentation task over a single-architecture baseline. Overall, the best mIoU of 92.50% for the component segmentation task and 84.19% for the damage segmentation task validate the feasibility of these techniques for autonomous bridge component and damage segmentation using RGB images.

• Journal of Platform Technology
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• v.11 no.3
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• pp.45-55
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• 2023

This paper presents a model that supports decision-makers in the Korean film industry to maximize the success of online movies. To achieve this, we collected historical box office movies and clustered them into types to propose a model predicting each type's online box office performance. We considered various features to identify factors contributing to movie success and reduced feature dimensionality for computational efficiency. We systematically classified the movies into types and predicted each type's online box office performance while analyzing the contributing factors. We used automated machine learning (AutoML) techniques to automatically propose and select machine learning algorithms optimized for the problem, allowing for easy experimentation and selection of multiple algorithms. This approach is expected to provide a foundation for informed decision-making and contribute to better performance in the film industry.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.97-110
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• 2023

In this study, we propose a technique to automatically generate transfer documents using sensor data from livestock manure transfer systems. The research involves analyzing sensor data and applying machine learning techniques to derive optimized outcomes for livestock manure transfer documents. By comparing and contrasting with existing documents, we present a method for automatic document generation. Specifically, we propose the utilization of Gradient Boosting, a machine learning algorithm. The objective of this research is to enhance the efficiency of livestock manure and liquid byproduct management. Currently, stakeholders including producers, transporters, and processors manually input data into the livestock manure transfer management system during the disposal of manure and liquid byproducts. This manual process consumes additional labor, leads to data inconsistency, and complicates the management of distribution and treatment. Therefore, the aim of this study is to leverage data to automatically generate transfer documents, thereby increasing the efficiency of livestock manure and liquid byproduct management. By utilizing sensor data from livestock manure and liquid byproduct transport vehicles and employing machine learning algorithms, we establish a system that automates the validation of transfer documents, reducing the burden on producers, transporters, and processors. This efficient management system is anticipated to create a transparent environment for the distribution and treatment of livestock manure and liquid byproducts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.228-231
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• 2022

Most CCTVs operated by public institutions for crime prevention and parking enforcement are located on roads. The angle of these CCTV's view is often changed for various reasons, such as bolt loosening by vibration or shocking by vehicles and workers, etc. In order to effectively provide AI services based on the collected images, the service target area(ROI, Region Of Interest) must be provided without interruption within the image. This is also related to the viewpoint of effective operation of computing power for image analysis. This study explains how to maximize the application of artificial intelligence technology by setting the ROI based on the marker on the road, setting the image analysis to be possible only within the area, and studying the process of finding the ROI.