• Journal of Information Processing Systems
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• v.19 no.3
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• pp.394-406
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• 2023

In this study, a real-time surveillance system using Internet of Things technology is proposed for vaccine cold chains. This system fully visualizes vaccine transport and storage. It comprises a 4G gateway module, lowpower and low-cost wireless temperature and humidity collection module (WTHCM), cloud service software platform, and phone app. The WTHCM is installed in freezers or truck-mounted cold chain cabinets to collect the temperature and humidity information of the vaccine storage environment. It then transmits the collected data to a gateway module in the radiofrequency_physical layer (RF_PHY). The RF_PHY is an interface for calling the bottom 2.4-GHz transceiver, which can realize a more flexible communication mode. The gateway module can simultaneously receive data from multiple acquisition terminals, process the received data depending on the protocol, and transmit the collated data to the cloud server platform via 4G or Wi-Fi. The cloud server platform primarily provides data storage, chart views, short-message warnings, and other functions. The phone app is designed to help users view and print temperature and humidity data concerning the transportation and storage of vaccines anytime and anywhere. Thus, this system provides a new vaccine management model for ensuring the safety and reliability of vaccines to a greater extent.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.6_3
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• pp.1243-1249
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• 2023

The Public Data Act mandates that every public institution must make efforts to facilitate convenient access to public data for all and take necessary measures to universally expand the right to use such data. Furthermore, it specifies that the head of a public institution must provide the data held and managed by that institution to the citizens. The Construction Project Information Disclosure Service aims to increase the utilization of data within the Construction CALS System, creating new added value by disclosing information and fostering communication. This service seeks to enhance public interest and transparency, support the creation of new businesses based on construction project data, and stimulate related industries. Since 2019, a total of 26 types of information have been disclosed through this service. As the volume of disclosed information continues to increase, there has been a consistent demand for reducing burden on data providers and enhancing user functionality. This study analyzes the current status of the Construction CALS Information Disclosure System to identify its existing challenges. Subsequently, it establishes a systematic approach to the data opening process and proposes enhancements to information disclosure and search functionalities for addressing these challenges.

• The Korean Journal of Nuclear Medicine Technology
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• v.28 no.1
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• pp.35-40
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• 2024

Purpose: To improve the image quality in positron emission tomography (PET), the attenuation correction technique based on the computed tomography (CT) data is important process. However, the artifact is caused by metal material during PET/CT scan, and the image quality is degraded. Therefore, the purpose of this study was to evaluate image quality according to with and without iterative metal artifact reduction (iMAR) algorithm using customized 3D printing phantom. Materials and Methods: The Hoffman and Derenzo phantoms were designed. To protect the gamma ray transmission and express the metal portion, lead substance was located to the surface. The SiPM based PET/CT was used for acquisition of PET images according to application with and without iMAR algorithm. The quantitative methods were used by signal to noise ratio (SNR), coefficient of variation (COV), and contrast to noise ratio (CNR). Results and Discussion: The results shows that the image quality applying iMAR algorithm was higher 1.15, 1.19, and 1.11 times than image quality without iMAR algorithm for SNR, COV, and CNR. Conclusion: In conclusion, the iMAR algorithm was useful for improvement of image quality by reducing the metal artifact lesion.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.37 no.3
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• pp.241-252
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• 2024

With the recent development of emerging technologies, information acquisition and delivery between users has been actively conducted, and inorganic thin film transfer technology that effectively transfers various materials and devices is being studied to develop flexible electronic devices accordingly. This is aimed at innovative structural changes and functional improvement of electronic devices in the era of the Internet of Things (IoT). In particular, advanced technologies such as microLEDs are used to realize high-resolution flexible displays, and the possibility of heterogeneous integrated technologies can be presented by precisely transferring materials to substrates through various transfer process. This paper introduced physical, chemical, and self-assembly transfer methods based on inorganic thin film materials to implement heterogeneous integrated flexible semiconductor systems and introduces the results of application studies of semiconductor devices obtained through different transfer technologies. These studies are expected to bring about innovative changes in the field of smart devices, medical technology, and user interfaces in the future.

• The Journal of Korea Robotics Society
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• v.19 no.2
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• pp.203-212
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• 2024

Simultaneous motion is essential in the activities of daily living (ADL). For motion intention recognition, surface electromyogram (sEMG) and corresponding motion label is necessary. However, this process is time-consuming and it may increase the burden of the user. Therefore, we propose a simultaneous motion recognition framework using data augmentation based on muscle activation model. The model consists of multiple point sources to be optimized while the number of point sources and their initial parameters are automatically determined. From the experimental results, it is shown that the framework has generated the data which are similar to the real one. This aspect is quantified with the following two metrics: structural similarity index measure (SSIM) and mean squared error (MSE). Furthermore, with k-nearest neighbor (k-NN) or support vector machine (SVM), the classification accuracy is also enhanced with the proposed framework. From these results, it can be concluded that the generalization property of the training data is enhanced and the classification accuracy is increased accordingly. We expect that this framework reduces the burden of the user from the excessive and time-consuming data acquisition.

• Restorative Dentistry and Endodontics
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• v.49 no.1
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• pp.1.1-1.18
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• 2024

The implementation of imaging methods that enable sensitive and specific observation of anatomical structures has been a constant in the evolution of endodontic therapy. Cone-beam computed tomography (CBCT) enables 3-dimensional (3D) spatial anatomical navigation in the 3 volumetric planes (sagittal, coronal and axial) which translates into great accuracy for the identification of endodontic pathologies/conditions. CBCT interpretation consists of 2 main components: (i) the generation of specific tasks of the image and (ii) the subsequent interpretation report. A systematic and reproducible method to review CBCT scans can improve the accuracy of the interpretation process, translating into greater precision in terms of diagnosis and planning of endodontic clinical procedures. MEDLINE (PubMed), Web of Science, Google Scholar, Embase and Scopus were searched from inception to March 2023. This narrative review addresses the theoretical concepts, elements of interpretation and applications of the CBCT scan in endodontics. In addition, the contents and rationale for reporting 3D endodontic imaging are discussed.

• BMB Reports
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• v.57 no.1
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• pp.40-49
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• 2024

Prokaryotes encode clustered regularly interspaced short palindromic repeat (CRISPR) arrays and CRISPR-associated (Cas) genes as an adaptive immune machinery. CRISPR-Cas systems effectively protect hosts from the invasion of foreign enemies, such as bacteriophages and plasmids. During a process called 'adaptation', non-self-nucleic acid fragments are acquired as spacers between repeats in the host CRISPR array, to establish immunological memory. The highly conserved Cas1-Cas2 complexes function as molecular recorders to integrate spacers in a time course manner, which can subsequently be expressed as crRNAs complexed with Cas effector proteins for the RNA-guided interference pathways. In some of the RNA-targeting type III systems, Cas1 proteins are fused with reverse transcriptase (RT), indicating that RT-Cas1-Cas2 complexes can acquire RNA transcripts for spacer acquisition. In this review, we summarize current studies that focus on the molecular structure and function of the RT-fused Cas1-Cas2 integrase, and its potential applications as a directional RNA-recording tool in cells. Furthermore, we highlight outstanding questions for RT-Cas1-Cas2 studies and future directions for RNA-recording CRISPR technologies.

• International Journal of Computer Science & Network Security
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• v.24 no.1
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• pp.1-8
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• 2024

In contemporary education, the rapid advancement of digital technologies elevates demands for integrating the latest tools into the learning process. Mathematical analysis, as a discipline, benefits from computer mathematics in distance education, enhancing practical aspects and enabling individualized learning. This article addresses the integration of the Maple computer mathematics system into higher education, specifically in teaching "Mathematical Analysis." Emphasizing its role in distance learning, computer mathematics optimizes the educational environment, reducing the time required for knowledge acquisition. The article showcases the application of Maple in finding extremum points and introduces an educational software simulator, enabling students to practice the method. The simulator, developed within Maple, facilitates self-checking and enhances the study of functions. Conclusions drawn from the study highlight the positive impact of these tools on distance education, affirming Maple's role in enhancing professional training and information culture among higher education students.

• Korean Journal of Construction Engineering and Management
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• v.25 no.2
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• pp.69-80
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• 2024

Currently rebar spacing inspection is carried out by human inspectors who heavily rely on their individual experience, lacking a guarantee of objectivity and accuracy in the inspection process. In addition, if incorrectly placed rebars are identified, the inspector need to correct them. Recently, laser scanning and AR technologies have been widely used because of their merits of measurement accuracy and visualization. This study proposes a technology for rebar spacing inspection and fixing by combining laser scanning and AR technology. First, scan data acquisition of rebar layers is performed and the raw scan data is processed. Second, AR-based visualization and fixing are performed by comparing the design model with the model generated from the scan data. To verify the developed technique, performance comparison test is conducted by comparing with existing drawing-based method in terms of inspection time, error detection rate, cognitive load, and situational awareness ability. It is found from the result of the experiment that the AR-based rebar inspection and fixing technology is faster than the drawing-based method, but there was no significant difference between the two groups in error identification rate, cognitive load, and situational awareness ability. Based on the experimental results, the proposed AR-based rebar spacing inspection and fixing technology is expected to be highly useful throughout the construction industry.

• Korean Journal of Artificial Intelligence
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• v.12 no.3
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• pp.1-7
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• 2024

In this paper, we propose an innovative super-resolution technique to address the issue of reduced accuracy in license plate recognition caused by low-resolution images. Conventional vehicle license plate recognition systems have relied on images obtained from fixed surveillance cameras for traffic detection to perform vehicle detection, tracking, and license plate recognition. However, during this process, image quality degradation occurred due to the physical distance between the camera and the vehicle, vehicle movement, and external environmental factors such as weather and lighting conditions. In particular, the acquisition of low-resolution images due to camera performance limitations has been a major cause of significantly reduced accuracy in license plate recognition. To solve this problem, we propose a Single Image Super-Resolution (SISR) model with a parallel structure that combines Multi-Scale and Attention Mechanism. This model is capable of effectively extracting features at various scales and focusing on important areas. Specifically, it generates feature maps of various sizes through a multi-branch structure and emphasizes the key features of license plates using an Attention Mechanism. Experimental results show that the proposed model demonstrates significantly improved recognition accuracy compared to existing vehicle license plate super-resolution methods using Bicubic Interpolation.