• Journal of Microbiology and Biotechnology
• /
• v.31 no.12
• /
• pp.1709-1715
• /
• 2021

Outbreaks of food poisoning due to the consumption of norovirus-contaminated shellfish continue to occur. Male-specific (F+) coliphage has been suggested as an indicator of viral species due to the association with animal and human wastes. Here, we compared two methods, the double agar overlay and the quantitative real-time PCR (RT-PCR)-based method, for evaluating the applicability of F+ coliphage-based detection technique in microbial contamination tracking of shellfish samples. The RT-PCR-based method showed 1.6-39 times higher coliphage PFU values from spiked shellfish samples, in relation to the double agar overlay method. These differences indicated that the RT-PCR-based technique can detect both intact viruses and non-particle-protected viral DNA/RNA, suggesting that the RT-PCR based method could be a more efficient tool for tracking microbial contamination in shellfish. However, the virome information on F+ coliphage-contaminated oyster samples revealed that the high specificity of the RT-PCR- based method has a limitation in microbial contamination tracking due to the genomic diversity of F+ coliphages. Further research on the development of appropriate primer sets for microbial contamination tracking is therefore necessary. This study provides preliminary insight that should be examined in the search for suitable microbial contamination tracking methods to control the sanitation of shellfish and related seawater.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.3
• /
• pp.63-69
• /
• 2022

In this paper, we propose a new GPU-based framework for quickly calculating adaptive and continuous SDF(Signed distance fields), and examine cases related to rendering/collision processing using them. The quadtree constructed from the triangle mesh is transferred to the GPU memory, and the Euclidean distance to the triangle is processed in parallel for each thread by using it to find the shortest continuous distance without discontinuity in the adaptive grid space. In this process, it is shown through experiments that the cut-off view of the adaptive distance field, the distance value inquiry at a specific location, real-time raytracing, and collision handling can be performed quickly and efficiently. Using the proposed method, the adaptive sign distance field can be calculated quickly in about 1 second even on a high polygon mesh, so it is a method that can be fully utilized not only for rigid bodies but also for deformable bodies. It shows the stability of the algorithm through various experimental results whether it can accurately sample and represent distance values in various models.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.16 no.6
• /
• pp.1323-1328
• /
• 2021

In this paper, we present a medical electric scooter sharing platform for the transportation vulnerable who are experiencing difficulties and inconveniences in moving. The proposed medical electric scooter sharing platform for the transportation vulnerable includes basic mobile rental, return, and functions that incorporate the IOT technology of the currently operating personal mobility sharing platform. The safety function has been strengthened. The medical electric scooter sharing platform for the transportation vulnerable stores driving data on the server in real time through GPS, and strengthens the alarm and call function in advance of an accident to enable rapid SOS processing. By making the quick contact and responding to the situation, people with disabilities can drive safely and comfortably.

• Journal of Information Technology Services
• /
• v.21 no.2
• /
• pp.97-107
• /
• 2022

Recently, interest in smart factories is increasing. Investments to improve intelligence/automation are also being made continuously in manufacturing plants. Facility automation based on sensor data collection is now essential. In addition, we are operating our factories based on data generated in all areas of production, including production management, facility operation, and quality management, and an integrated standard information system. When producing LCD polarizer products, it is most important to link trace information between data generated by individual production processes. All systems involved in production must ensure that there is no data loss and data integrity is ensured. The large-capacity data collected from individual systems is composed of key values linked to each other. A real-time quality analysis processing system based on connected integrated system data is required. In this study, large-capacity data collection, storage, integration and loss prevention methods were presented for optimization of LCD polarizer production. The identification Risk model of inspection products can be added, and the applicable product model is designed to be continuously expanded. A quality inspection and analysis system that maximizes the yield rate was designed by using the final inspection image of the product using big data technology. In the case of products that are predefined as analysable products, it is designed to be verified with the big data knn analysis model, and individual analysis results are continuously applied to the actual production site to operate in a virtuous cycle structure. Production Optimization was performed by applying it to the currently produced LCD polarizer production line.

• Journal of Veterinary Science
• /
• v.23 no.4
• /
• pp.56.1-56.17
• /
• 2022

Background: At the therapeutic doses, diclofenac sodium (DFS) has few toxic side effects on mammals. On the other hand, DFS exhibits potent toxicity against birds and the mechanisms remain ambiguous. Objectives: This paper was designed to probe the toxicity of DFS exposure on the hepatic proteome of broiler chickens. Methods: Twenty 30-day-old broiler chickens were randomized evenly into two groups (n = 10). DFS was administered orally at 10mg/kg body weight in group A, while the chickens in group B were perfused with saline as a control. Histopathological observations, serum biochemical examinations, and quantitative real-time polymerase chain reaction were performed to assess the liver injury induced by DFS. Proteomics analysis of the liver samples was conducted using isobaric tags for relative and absolute quantification (iTRAQ) technology. Results: Ultimately, 201 differentially expressed proteins (DEPs) were obtained, of which 47 were up regulated, and 154 were down regulated. The Gene Ontology classification and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted to screen target DEPs associated with DFS hepatotoxicity. The regulatory relationships between DEPs and signaling pathways were embodied via a protein-protein interaction network. The results showed that the DEPs enriched in multiple pathways, which might be related to the hepatotoxicity of DFS, were "protein processing in endoplasmic reticulum," "retinol metabolism," and "glycine, serine, and threonine metabolism." Conclusions: The hepatotoxicity of DFS on broiler chickens might be achieved by inducing the apoptosis of hepatocytes and affecting the metabolism of retinol and purine. The present study could provide molecular insights into the hepatotoxicity of DFS on broiler chickens.

• Journal of Biomedical Engineering Research
• /
• v.43 no.5
• /
• pp.361-368
• /
• 2022

The purpose of this study was to develop a hand rehabilitation training system for hemiplegic patients. We also tried to find out five hand postures (WF: Wrist Flexion, WE: Wrist Extension, BG: Ball Grip, HG: Hook Grip, RE: Rest) in real-time using multi-channel EMG-based deep learning. We performed a pre-processing method that converts to Spider Chart image data for the classification of hand movement from five test subjects (total 1,500 data sets) using Convolution Neural Networks (CNN) deep learning with an 8-channel armband. As a result of this study, the recognition accuracy was 92% for WF, 94% for WE, 76% for BG, 82% for HG, and 88% for RE. Also, ten physical therapists participated for the usability evaluation. The questionnaire consisted of 7 items of acceptance, interest, and satisfaction, and the mean and standard deviation were calculated by dividing each into a 5-point scale. As a result, high scores were obtained in immersion and interest in game (4.6±0.43), convenience of the device (4.9±0.30), and satisfaction after treatment (4.1±0.48). On the other hand, Conformity of intention for treatment (3.90±0.49) was relatively low. This is thought to be because the game play may be difficult depending on the degree of spasticity of the hemiplegic patient, and compensation may occur in patient with weakened target muscles. Therefore, it is necessary to develop a rehabilitation program suitable for the degree of disability of the patient.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.10
• /
• pp.1432-1440
• /
• 2022

Recently, as Virtual Desktop Infrastructure(VDI) is widely used not only in office work environments but also in workloads that use high-spec multi-core-based applications, the requirements for real-time and stability of VDI are increasing. Accordingly, the display protocol used for remote access in VDI and performance optimization of virtual machines have also become more important. In this paper, we propose two ways to configure desktop virtualization for multi-core-based application operation. First, we propose a codec configuration of a display protocol with optimal performance in a high load situation due to multi-processing. Second, we propose a virtual CPU scheduling optimization method to reduce scheduling delay in case of CPU contention between virtual machines. As a result of the test, it was confirmed that the H.264 codec of Blast Extreme showed the best and stable frame, and the scheduling performance of the virtual CPU was improved through scheduling optimization.

• Korean Journal of Remote Sensing
• /
• v.38 no.5_3
• /
• pp.819-834
• /
• 2022

Artificial Intelligence (AI) techniques have been effectively used for image classification, object detection, and image segmentation. Along with the recent advancement of computing power, deep learning models can build deeper and thicker networks and achieve better performance by creating more appropriate feature maps based on effective activation functions and optimizer algorithms. This review paper examined technical and academic trends of Convolutional Neural Network (CNN) and Transformer models that are emerging techniques in remote sensing and suggested their utilization strategies and development directions. A timely supply of satellite images and real-time processing for deep learning to cope with disaster monitoring will be required for future work. In addition, a big data platform dedicated to satellite images should be developed and integrated with drone and Closed-circuit Television (CCTV) images.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.10
• /
• pp.1447-1452
• /
• 2022

Seoul Special City, one of the world's top 10 cities and Metro City, has traditional urban manufacturing industries such as printing, sewing, and mechanical metals. Small business owners in these manufacturing clusters have developed in the form of mutual assistance. Due to the nature of the agglomeration site, each process is handled by an individual company. It is difficult for relatively small business owners to prepare order processing services that provide real-time logistics movement information between processes. This paper collects and analyzes existing logistics data for smooth order and delivery of small business owners in package manufacturing and special printing fields We design an artificial intelligence Fulfillment Service Platform system with CRNN, k-NN, and ID3 Decision Tree Algorithm. Through this study, it is expected that it will greatly contribute to increasing sales and improving capabilities by allowing small business owners in integrated areas to use individual orders and delivery customized services through the Cloud network.

• Journal of Animal Science and Technology
• /
• v.63 no.6
• /
• pp.1453-1463
• /
• 2021

Feeding is the most important behavior that represents the health and welfare of weanling pigs. The early detection of feed refusal is crucial for the control of disease in the initial stages and the detection of empty feeders for adding feed in a timely manner. This paper proposes a real-time technique for the detection and recognition of small pigs using a deep-leaning-based method. The proposed model focuses on detecting pigs on a feeder in a feeding position. Conventional methods detect pigs and then classify them into different behavior gestures. In contrast, in the proposed method, these two tasks are combined into a single process to detect only feeding behavior to increase the speed of detection. Considering the significant differences between pig behaviors at different sizes, adaptive adjustments are introduced into a you-only-look-once (YOLO) model, including an angle optimization strategy between the head and body for detecting a head in a feeder. According to experimental results, this method can detect the feeding behavior of pigs and screen non-feeding positions with 95.66%, 94.22%, and 96.56% average precision (AP) at an intersection over union (IoU) threshold of 0.5 for YOLOv3, YOLOv4, and an additional layer and with the proposed activation function, respectively. Drinking behavior was detected with 86.86%, 89.16%, and 86.41% AP at a 0.5 IoU threshold for YOLOv3, YOLOv4, and the proposed activation function, respectively. In terms of detection and classification, the results of our study demonstrate that the proposed method yields higher precision and recall compared to conventional methods.