• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2367-2371
• /
• 2003

A new instrument for early detection of Alzheimer's disease is constructed from the investigative items with both the investigation of living environment, and the functional tests of the sense, the physiology, and the left and right brains. This paper describes the indexes obtained from the results of test using a new instrument for early detection of Alzheimer's disease. The indexes for early detection of Alzheimer's disease were obtained from the investigations of the living environment and the social adaptability, the functional tests of the sight and the hearing in the five senses, and the functional tests of left hemispheres in brain.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2362-2366
• /
• 2003

The paper describes a new instrument for early detection of Alzheimer's disease. A new instrument for early detection of Alzheimer's disease is constructed on both the questionnaire for the investigation of living environment, and the lists for the functional tests of the sense, the physiology, and the left and right brains. When the medical doctor has made a diagnosis of Alzheimer's disease, the demented patient does not recover the indication adding available treatments. Then, the indication of a patient only takes a turn for the worse. For the demented patient can be kept his/her life style, Alzheimer's disease can make an early detection using a new instrument before a diagnosis of the dementia. And the indication of a demented patient can be delayed by the available medical treatments.

• Korean Journal of Veterinary Research
• /
• v.54 no.2
• /
• pp.113-115
• /
• 2014

Salmonella are causative agents of gastroenteritis and systemic disease in animals. The invA gene was selected as a target sequence of loop-mediated isothermal amplification (LAMP) assay for diagnosis of Salmonella infection. The detection limits for broth dilution, spiked feces and enrichment were $10^4$, $10^5$ and $10^2$ CFUs/mL, respectively. The LAMP assay developed in the present study may be a reliable method for detection of Salmonella spp. in pig feces.

• Journal of Veterinary Science
• /
• v.19 no.6
• /
• pp.855-857
• /
• 2018

Porcine parvovirus 7 (PPV7) was first detected in Korean pig farms in 2017. The detection rate of PPV7 DNA was 24.0% (30/125) in aborted pig fetuses and 74.9% (262/350) in finishing pigs, suggesting that PPV7 has circulated among Korean domestic pig farms. Phylogenetic analysis based on capsid protein amino acid sequences demonstrated that the nine isolated Korean strains (PPV-KA1-3 and PPV-KF1-6) were closely related to the previously reported USA and Chinese PPV7 strains. In addition, the Korean strains exhibit genetic diversity with both insertion and deletion mutations. This study contributes to the understanding of the molecular epidemiology of PPV7 in Korea.

• Journal of Bone Metabolism
• /
• v.25 no.4
• /
• pp.213-217
• /
• 2018

Patients with gastrointestinal disease (GI) are at risk for osteopenia or osteoporosis, which can lead to fractures. Although these patients may be at risk from a young age, gastroenterologists often overlook this fact in practice. There are well-known GI diseases associated with osteopenia and osteoporosis, such as the post-gastrectomy state, inflammatory bowel disease (IBD), and celiac disease. As there is an increase in the prevalence of IBD patients, newly diagnosed celiac disease in adulthood, and gastric cancer survivors following gastrectomy, bone disease in these patients becomes an important issue. Here, we have discussed osteoporosis and fractures in GI disease, especially in the postgastrectomy state, IBD, and celiac disease. Although the pathogenesis of bone loss in each disease has not been fully identified, we have confirmed that the prevalence of osteoporosis and fractures in each of these diseases is high. There are scarce studies comparing the prevalence of osteoporosis or osteoporotic fractures in GI disease patients with studies in postmenopausal women, and specific guidelines for their management in each disease have not been established. Intensive surveillance and management are needed to ensure that these patients attain peak bone mass for age and sex to prevent fractures.

• Journal of Korea Multimedia Society
• /
• v.25 no.11
• /
• pp.1653-1671
• /
• 2022

Crop diseases affect crop production, more than 30 billion USD globally. We proposed a classification study of crop species and diseases using deep learning algorithms for corn, cucumber, pepper, and strawberry. Our study has three steps of species classification, disease detection, and disease classification, which is noteworthy for using captured images without additional processes. We designed deep learning approach of deep learning convolutional neural networks based on Mask R-CNN model to classify crop species. Inception and Resnet models were presented for disease detection and classification sequentially. For classification, we trained Mask R-CNN network and achieved loss value of 0.72 for crop species classification and segmentation. For disease detection, InceptionV3 and ResNet101-V2 models were trained for nodes of crop species on 1,500 images of normal and diseased labels, resulting in the accuracies of 0.984, 0.969, 0.956, and 0.962 for corn, cucumber, pepper, and strawberry by InceptionV3 model with higher accuracy and AUC. For disease classification, InceptionV3 and ResNet 101-V2 models were trained for nodes of crop species on 1,500 images of diseased label, resulting in the accuracies of 0.995 and 0.992 for corn and cucumber by ResNet101 with higher accuracy and AUC whereas 0.940 and 0.988 for pepper and strawberry by Inception.

• Journal of Veterinary Science
• /
• v.23 no.5
• /
• pp.32.1-32.11
• /
• 2022

Background: Classical swine fever (CSF) is a severe infectious disease of pigs that causes significant economic losses to the swine industry. Objectives: This study developed a solid-phase blocking enzyme-linked immunosorbent assay (spbELISA) method for the specific detection of antibodies against the CSF virus (CSFV) in porcine serum samples. Methods: A spbELISA method was developed based on the recombinant E2 expressed in Escherichia coli. The specificity of this established spbELISA method was evaluated using reference serum samples positive for antibodies against other common infectious diseases. The stability and sensitivity were evaluated using an accelerated thermostability test. Results: The spbELISA successfully detected the antibody levels in swine vaccinated with the C-strain of CSFV. In addition, the detection ability of spbELISA for CSFV antibodies was compared with that of other commercial ELISA kits and validated using an indirect immunofluorescence assay. The results suggested that the spbELISA provides an alternative, stable, and rapid serological detection method suitable for the large-scale screening of CSFV serum antibodies. Conclusions: The spbELISA has practical applications in assessing the vaccination status of large pig herds.

• Transactions on Electrical and Electronic Materials
• /
• v.15 no.4
• /
• pp.230-234
• /
• 2014

Automatic detection of disease helps medical institutions that are introducing digital images to read images rapidly and accurately, and is thus applicable to lesion diagnosis and treatment. The aim of this study was to apply a symmetry contribution algorithm to unsharp mask filter-applied MR images and propose an analysis technique to automatically recognize brain tumor and edema. We extracted the skull region and drawed outline of the skull in database of images obtained at P University Hospital and detected an axis of symmetry with cerebral characteristics. A symmetry contribution algorithm was then applied to the images around the axis of symmetry to observe intensity changes in pixels and detect disease areas. When we did not use the unsharp mask filter, a brain tumor was detected in 60 of a total of 95 MR images. The disease detection rate for the brain was 63.16%. However, when we used the unsharp mask filter, the tumor was detected in 87 of a total of 95 MR images, with a disease detection rate of 91.58%. When the unsharp mask filter was used in the pre-process stage, the disease detection rate for the brain was higher than when it was not used. We confirmed that unsharp mask filter can be used to rapidly and accurately to read many MR images stored in a database.

• Smart Media Journal
• /
• v.11 no.4
• /
• pp.38-45
• /
• 2022

Object detection models have become the current tool of choice for plant disease detection in precision agriculture. Most existing research improves the performance by ameliorating networks and optimizing the loss function. However, the data-centric part of a whole project also needs more investigation. In this paper, we proposed a systematic strategy with three different annotation methods for plant disease detection: local, semi-global, and global label. Experimental results on our paprika disease dataset show that a single class annotation with semi-global boxes may improve accuracy. In addition, we also studied the noise factor during the labeling process. An ablation study shows that annotation noise within 10% is acceptable for keeping good performance. Overall, this data-centric numerical analysis helps us to understand the significance of annotation methods, which provides practitioners a way to obtain higher performance and reduce annotation costs on plant disease detection tasks. Our work encourages researchers to pay more attention to label quality and the essential issues of labeling methods.

• The Plant Pathology Journal
• /
• v.36 no.5
• /
• pp.459-467
• /
• 2020

Areca palm yellow leaf (AYL) disease caused by the 16SrI group phytoplasma is a serious threat to the development of the Areca palm industry in China. The 16S rRNA gene sequence was utilized to establish a rapid and efficient detection system efficient for the 16SrI-B subgroup AYL phytoplasma in China by loop-mediated isothermal amplification (LAMP). The results showed that two sets of LAMP detection primers, 16SrDNA-2 and 16SrDNA-3, were efficient for 16SrI-B subgroup AYL phytoplasma in China, with positive results appearing under reaction conditions of 64℃ for 40 min. The lowest detection limit for the two LAMP detection assays was the same at 200 ag/μl, namely approximately 53 copies/μl of the target fragments. Phytoplasma was detected in all AYL disease samples from Baoting, Tunchang, and Wanning counties in Hainan province using the two sets of LAMP primers 16SrDNA-2 and 16SrDNA-3, whereas no phytoplasma was detected in the negative control. The LAMP method established in this study with comparatively high sensitivity and stability, provides reliable results that could be visually detected, making it suitable for application and research in rapid diagnosis of AYL disease, detection of seedlings with the pathogen and breeding of disease-resistant Areca palm varieties.