• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.10
• /
• pp.1462-1468
• /
• 2022

Among the data used for the diagnosis of calf disease, feces play an important role in disease diagnosis. In the image of calf feces, the health status can be known by the shape, color, and texture. For the fecal image that can identify the health status, data of 207 normal calves and 158 calves with diarrhea were pre-processed according to fecal status and used. In this paper, images of fecal variables are detected among the collected calf data and images are trained by applying GLCM-CNN, which combines the properties of CNN and GLCM, on a dataset containing disease symptoms using convolutional network technology. There was a significant difference between CNN's 89.9% accuracy and GLCM-CNN, which showed 91.7% accuracy, and GLCM-CNN showed a high accuracy of 1.8%.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.7
• /
• pp.956-962
• /
• 2022

Diffuse thyroid disease has ambiguous diagnostic criteria and many errors occur according to the subjective diagnosis of skilled practitioners. If image processing technology is applied to ultrasound images, quantitative data is extracted, and applied to a computer auxiliary diagnostic system, more accurate and political diagnosis is possible. In this paper, 19 parameters were extracted by applying the Gray level co-occurrence matrix (GLCM) algorithm to ultrasound images classified as normal, mild, and moderate in patients with thyroid disease. Using these parameters, an artificial neural network (ANN) was applied to analyze diffuse thyroid ultrasound images. The final classification rate using ANN was 96.9%. Using the results of the study, it is expected that errors caused by visual reading in the diagnosis of thyroid diseases can be reduced and used as a secondary means of diagnosing diffuse thyroid diseases.

• Imaging Science in Dentistry
• /
• v.52 no.4
• /
• pp.399-408
• /
• 2022

Purpose: The purpose of this study was to compare volume measurements obtained using 2 image software packages on Digital Imaging and Communications in Medicine (DICOM) images acquired from 1 multidetector computed tomography and 5 cone-beam computed tomography devices, using different protocols for physical volume measurements. Materials and Methods: Four pieces of bovine leg were prepared. Marrow was removed from 3 pieces, leaving cortical bone exposed. The resulting space of 1 piece was filled with water, another was filled with propylene glycol, and the third was left unfilled. The marrow in the fourth sample was left fully intact. Volume measurements were obtained after importing DICOM images into the Dolphin Imaging 11.95 and ITK-SNAP software programs. Data were analyzed using 3-way analysis of variance with a generalized linear model to determine the effects of voxel size, software, and content on percentage mean volume differences between tomographic protocols. A significance level of 0.05 was used. Results: The intraclass correlation coefficients for intraobserver and interobserver reliability were, respectively, 0.915 and 0.764 for the Dolphin software and 0.894 and 0.766 for the ITK-SNAP software. Three sources of statistically significant variation were identified: the interaction between software and content (P=0.001), the main effect of content (P=0.014), and the main effect of software (P=0.001). Voxel size was not associated with statistically significant differences in volume measurements. Conclusion: Both content and software influenced the accuracy of volume measurements, especially when the content had gray values similar to those of the adjacent tissues.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.3
• /
• pp.916-937
• /
• 2023

Most of the existing Distributed Denial-of-Service mitigation schemes in Software-Defined Networking are only implemented in the network domain managed by a single controller. In fact, the zombies for attackers to launch large-scale DDoS attacks are actually not in the same network domain. Therefore, abnormal traffic of DDoS attack will affect multiple paths and network domains. A single defense method is difficult to deal with large-scale DDoS attacks. The cooperative defense of multiple domains becomes an important means to effectively solve cross-domain DDoS attacks. We propose an efficient multi-domain DDoS cooperative defense mechanism by integrating blockchain and SDN architecture. It includes attack traceability, inter-domain information sharing and attack mitigation. In order to reduce the length of the marking path and shorten the traceability time, we propose an AS-level packet traceability method called ASPM. We propose an information sharing method across multiple domains based on blockchain and smart contract. It effectively solves the impact of DDoS illegal traffic on multiple domains. According to the traceability results, we designed a DDoS attack mitigation method by replacing the ACL list with the IP address black/gray list. The experimental results show that our ASPM traceability method requires less data packets, high traceability precision and low overhead. And blockchain-based inter-domain sharing scheme has low cost, high scalability and high security. Attack mitigation measures can prevent illegal data flow in a timely and efficient manner.

• Imaging Science in Dentistry
• /
• v.53 no.1
• /
• pp.21-26
• /
• 2023

Purpose: A fully digital approach to oral prosthodontic rehabilitation requires the possibility of combining (i.e., registering) digital documentation from different sources. This becomes more complex in an edentulous jaw, as fixed dental markers to perform reliable registration are lacking. This validation study aimed to evaluate the reproducibility of 1) intraoral scanning and 2) soft tissue-based registration of an intraoral scan with a cone-beam computed tomography (CBCT) scan for a fully edentulous upper jaw. Materials and Methods: Two observers independently performed intraoral scans of the upper jaw in 14 fully edentulous patients. The palatal vault of both surface models was aligned, and the inter-observer variability was assessed by calculating the mean inter-surface distance at the level of the alveolar crest. Additionally, a CBCT scan of all patients was obtained and a soft tissue surface model was generated using patient-specific gray values. This CBCT soft tissue model was registered with the intraoral scans of both observers, and the intraclass correlation coefficient(ICC) was calculated to evaluate the reproducibility of the registration method. Results: The mean inter-observer deviation when performing an intraoral scan of the fully edentulous upper jaw was 0.10±0.09 mm. The inter-observer agreement for the soft tissue-based registration method was excellent(ICC=0.94; 95% confidence interval, 0.81-0.98). Conclusion: Even when teeth are lacking, intraoral scanning of the jaw and soft tissue-based registration of an intraoral scan with a CBCT scan can be performed with a high degree of precision.

• Korean Journal of Remote Sensing
• /
• v.40 no.1
• /
• pp.93-101
• /
• 2024

Accurate field crop classification is essential for various agricultural applications, yet existing methods face challenges due to diverse crop types and complex field conditions. This study aimed to address these issues by combining support vector machine (SVM) models with multi-seasonal unmanned aerial vehicle (UAV) images, texture information extracted from Gray Level Co-occurrence Matrix (GLCM), and RGB spectral data. Twelve high-resolution UAV image captures spanned March-October 2021, while field surveys on three dates provided ground truth data. We focused on data from August (-A), September (-S), and October (-O) images and trained four support vector classifier (SVC) models (SVC-A, SVC-S, SVC-O, SVC-AS) using visual bands and eight GLCM features. Farm maps provided by the Ministry of Agriculture, Food and Rural Affairs proved efficient for open-field crop identification and served as a reference for accuracy comparison. Our analysis showcased the significant impact of hyperparameter tuning (C and gamma) on SVM model performance, requiring careful optimization for each scenario. Importantly, we identified models exhibiting distinct high-accuracy zones, with SVC-O trained on October data achieving the highest overall and individual crop classification accuracy. This success likely stems from its ability to capture distinct texture information from mature crops.Incorporating GLCM features proved highly effective for all models,significantly boosting classification accuracy.Among these features, homogeneity, entropy, and correlation consistently demonstrated the most impactful contribution. However, balancing accuracy with computational efficiency and feature selection remains crucial for practical application. Performance analysis revealed that SVC-O achieved exceptional results in overall and individual crop classification, while soybeans and rice were consistently classified well by all models. Challenges were encountered with cabbage due to its early growth stage and low field cover density. The study demonstrates the potential of utilizing farm maps and GLCM features in conjunction with SVM models for accurate field crop classification. Careful parameter tuning and model selection based on specific scenarios are key for optimizing performance in real-world applications.

• Korean journal of applied entomology
• /
• v.46 no.1 s.145
• /
• pp.63-69
• /
• 2007

This study was conducted to examine the problems that would arise in our cropping systems when introducing Gain Threshold (GT) which is an important element in determining Economic Injury Level (EIL). Cain Threshold (GT) can be defined as the amount of damage (=yield loss) to justify management, and calculated by dividing the management costs by the market crop price. GTs for some pests in rice, soybean, and greenhouse vegetable crops cultivation were estimated and also compared with those in foreign countries. GTs and percentage of yield loss equivalent to them were estimated to be 4.6-6.1kg/10a/season and 1.0-1.3% for brown planthopper, white-backed planthopper, rice water weevil, and sheath blight, whereas for rice blast in rice cultivation were 12.7kg/10a/season and 2.7%. In soybean cultivation, the values for bean bug were 6.2 kg/10a/season and 3.6%. GTs and percentage of yield loss estimated for melon thrips, whitefly, and downy mildew in cucumber cultivation were 10.0-12.6kg/10a/week, 1.4-1.7%, and the values for two spotted mite and gray mildew in strawberry cultivation were 3.1-3.5kg/10a/week, 1.3-1.5%, and the values for American leaf minor, whitefly, and gray mold in tomato were 8.4-9.7kg/10a/week, 1.7-1.9%. Overall GTs in our cropping systems were so low compared to those in foreign countries, which meant that the low GTs might yield the low EILs. Therefore, we could suggest that prior to direct introduction of GTs calculated from current cultivation systems in developing EILs it is necessary to seriously consider reasonable values of GTs or the yield loss equivalents to them.

• Korean Journal of Remote Sensing
• /
• v.36 no.5_2
• /
• pp.989-1006
• /
• 2020

Building change monitoring based on building detection is one of the most important fields in terms of monitoring artificial structures using high-resolution multi-temporal images such as CAS500-1 and 2, which are scheduled to be launched. However, not only the various shapes and sizes of buildings located on the surface of the Earth, but also the shadows or trees around them make it difficult to detect the buildings accurately. Also, a large number of misdetection are caused by relief displacement according to the azimuth and elevation angles of the platform. In this study, object-based building detection was performed using the azimuth angle of the Sun and the corresponding main direction of shadows to improve the results of building change detection. After that, the platform's azimuth and elevation angles were used to detect changed buildings. The object-based segmentation was performed on a high-resolution imagery, and then shadow objects were classified through the shadow intensity, and feature information such as rectangular fit, Gray-Level Co-occurrence Matrix (GLCM) homogeneity and area of each object were calculated for building candidate detection. Then, the final buildings were detected using the direction and distance relationship between the center of building candidate object and its shadow according to the azimuth angle of the Sun. A total of three methods were proposed for the building change detection between building objects detected in each image: simple overlay between objects, comparison of the object sizes according to the elevation angle of the platform, and consideration of direction between objects according to the azimuth angle of the platform. In this study, residential area was selected as study area using high-resolution imagery acquired from KOMPSAT-3 and Unmanned Aerial Vehicle (UAV). Experimental results have shown that F1-scores of building detection results detected using feature information were 0.488 and 0.696 respectively in KOMPSAT-3 image and UAV image, whereas F1-scores of building detection results considering shadows were 0.876 and 0.867, respectively, indicating that the accuracy of building detection method considering shadows is higher. Also among the three proposed building change detection methods, the F1-score of the consideration of direction between objects according to the azimuth angles was the highest at 0.891.

• Journal of the Korean Society of Radiology
• /
• v.15 no.4
• /
• pp.463-472
• /
• 2021

Demand for examinations using transvaginal transducer with high frequencies is increasing to observe pelvic organs in gynecological ultrasound tests. However, the quality control of the replacement probe in clinical trials is not properly implemented and the evaluation criteria have not been established. Therefore, 58 transvaginal transducers and 20 convex transducers were applied to the ATS-539 ultrasound phantom for 20 ultrasound devices currently in clinical use to obtain their respective images and measure them quantitatively and qualitatively. For quantitative measurements, vertical measurement, horizontal measurement, and focal zone and qualitative measurements, dead zone, axial·lateral resolution, sensitivity, functional resolution, gray scale·dynamic range were performed. Quantitative statistical analysis showed significant differences between the two transducers in the lateral measurement and local area (p<0.05). qualitative comparative analysis showed differences in sensitivity and functional resolution. This occurs due to the difference in frequency between transducers and the transducer's injection geometry. Based on the above experiments, the tolerance for horizontal measurement is raised to 10% (±8 mm), the tolerance for sensitivity is observed up to 6 cm deep, which is 12 cm deep,which is the level of the third quartile (75%). The permissible range of functional resolution is up to 6 (12 cm), 6 (12 cm), 11 (11 cm), 9 (9 cm), 6 (6 cm) target, which is the level of the third quartile (75%). It is considered reasonable to adjust the depth of targets in gray scale·dynamic range to measure at a depth of 2 cm, which is 50% of the depth of 4 cm. As above, the criteria for evaluating the quality of transvaginal transducer for use in the past have been proposed and it is expected that this study will be used as a basic data for the production of phantom exclusively for transvaginal transducer in the future.

• The Journal of Korean Physical Therapy
• /
• v.18 no.2
• /
• pp.59-65
• /
• 2006

Purpose: The purpose of this study to investigate the effect of TENS and electroacupuncture (EA) on injured muscle recovery and to compare the difference between TENS and EA. Methods: 18 S-D rats were produced surgically for crush injury on Extensor digitorum. TENS and EA stimulation were applied on acu-point that Zusanli (ST36) and Taijun (Liv3) of each hindlimb as approximitely 2Hz for 15 minutes. The rats were sacrificed on 1, 3, 7 post operation day, and the spinal level was immunohistochmical stainied. Results: The expression of NT-3 on the spinal level related with injured muscle between Ex-1 group and Ex-2, there is no significant difference. But between Con and Ex-1/Ex-2, there was little difference. In the same indivudual, we confirmed more NT-3 expression on the same side of injured muscle than on another side of gray matter in posterior horn. Conclusion: There is no difference, which is more effective to recover of injured muscle, between EA and TENS on injured muscle.