• Journal of Interdisciplinary Genomics
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• v.5 no.2
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• pp.24-28
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• 2023

Chromosomal microarray (CMA) is primarily recommended for detecting clinically significant copy number variants (CNVs) in the genetic diagnosis of developmental delay, intellectual disability, autism, and congenital malformations. Prenatal CMA is recommended when a fetus has major congenital malformations. The main principles of CMA can be divided into array comparative genomic hybridization and single-nucleotide polymorphism arrays. In the current CMA platforms, these two principles are combined, and detection of genetic abnormalities including CNVs and absence of heterozygosity is facilitated. In this review, I described practical assessment of CMA testing regarding to laboratory management of CMA, interpretation of CNVs, and special considerations for comprehensive genetic counseling.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.147-155
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• 2024

Currently, the 4th Industrial Revolution, like other revolutions, is bringing great change and new life to humanity, and in particular, the demand for and use of drones, which can be applied by combining various technologies such as big data, artificial intelligence, and information and communications technology, is increasing. Recently, it has been widely used to carry out dangerous military operations and missions, such as the Russia-Ukraine war and North Korea's reconnaissance against South Korea, and as the demand for and use of drones increases, concerns about the safety and security of drones are growing. Currently, a variety of research is being conducted, such as detection of wireless communication abnormalities and sensor data abnormalities related to drones, but research on real-time detection of threats using radio frequency characteristic data is insufficient. Therefore, in this paper, we conduct a study to determine whether the characteristic data is normal or abnormal signal data by collecting radio frequency signal characteristic data generated while the drone communicates with the ground control system while performing a mission in a HITL(Hardware In The Loop) simulation environment similar to the real environment. proceeded. In addition, we propose an unsupervised learning-based threat detection system and optimal threshold that can detect threat signals in real time while a drone is performing a mission.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.109-117
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• 2022

This paper proposes a method for detecting flight anomalies of drones through the difference between the command of flight controller (FC) and the navigation solution. If the drones make a flight normally, control errors generated by the difference between the desired control command of FC and the navigation solution should converge to zero. However, there is a risk of sudden change or divergence of control errors when the FC control feedback loop preset for the normal flight encounters interferences such as strong winds or navigation sensor abnormalities. In this paper, we propose the method with a deep neural network model that predicts the control error in the normal flight so that the abnormal flight state can be detected. The performance of proposed method was evaluated using the real-world flight data. The results showed that the method effectively detects anomalies in various situation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.636-638
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• 2022

This paper is a study to apply CNN(Convolution Neural Network) to fundus images for identifying glaucoma. Fundus images are evaluated in the field of medical diagnosis detection, which are diagnosing of blood vessels and nerve tissues, retina damage, various cardiovascular diseases and dementia. For the experiment, using normal image set and glaucoma image set, two types of image set are classifed by using AlexNet. The result performs that glaucoma with abnormalities are activated and characterized in feature map.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.313-316
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• 2022

In this paper, we implement a system that detects abnormalities in the charging data transmitted from the charger during the charging process of electric vehicles and controls them remotely. Using classification algorithms such as logistic regression, KNN, SVM, and decision trees, to do this, an analysis model is created that judges the data received from the charger as normal and abnormal. In addition, a model is created to determine the cause of the abnormality using the existing charging data based on the analysis of the type of charger abnormality. Finally, it is solved using unsupervised learning method to find new patterns of abnormal data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2037-2042
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• 2017

The manufacturing facility is generally operated by a pre-set program under the existing factory automation system. On the other hand, the manufacturing facility must decide how to operate autonomously in Industry 4.0. Determining the operation mode of the production facility itself means, for example, that it detects the abnormality such as the deterioration of the facility at the shop-floor, prediction of the occurrence of the problem, detection of the defect of the product, In this paper, we propose a manufacturing process modeling using a queue for detection of manufacturing process abnormalities at the shop-floor, and detect abnormalities in the modeling using SVM, one of the machine learning techniques. The queue was used for M / D / 1 and the conveyor belt manufacturing system was modeled based on ${\mu}$, ${\lambda}$, and ${\rho}$. SVM was used to detect anomalous signs through changes in ${\rho}$.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.7343-7350
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• 2015

Genetic changes associated with acute lymphoblastic leukemia (ALL) provide very important diagnostic and prognostic information with a direct impact on patient management. Detection of chromosome abnormalities by conventional cytogenetics combined with fluorescence in situ hybridization (FISH) play a very significant role in assessing risk stratification. Identification of specific chromosome abnormalities has led to the recognition of genetic subgroups based on reciprocal translocations, deletions and modal number in B or T-cell ALL. In the last twelve years 102 newly diagnosed childhood/adult ALL bone marrow samples were analysed for chromosomal abnormalities with conventional G-banding, and FISH (selected cases) using specific probes in our hospital. G-banded karyotype analysis found clonal numerical and/or structural chromosomal aberrations in 74.2% of cases. Patients with pseudodiploidy represented the most frequent group (38.7%) followed by high hyperdiploidy group (12.9%), low hyperdiploidy group (9.7%), hypodiploidy (<46) group (9.7%) and high hypertriploidy group (3.2%). The highest observed numerical chromosomal alteration was high hyperdiploidy (12.9%) with abnormal karyotypes while abnormal 12p (7.5%) was the highest observed structural abnormality followed by t(12;21)(p13.3;q22) resulting in ETV6/RUNX1 fusion (5.4%) and t(9;22)(q34.1;q11.2) resulting in BCR/ABL1 fusion (4.3%). Interestingly, we identified 16 cases with rare and complex structural aberrations. Application of the FISH technique produced major improvements in the sensitivity and accuracy of cytogenetic analysis with ALL patients. In conclusion it confirmed heterogeneity of ALL by identifying various recurrent chromosomal aberrations along with non-specific rearrangements and their association with specific immunophenotypes. This study pool is representative of paediatric/adult ALL patients in Oman.

• Journal of the korean academy of Pediatric Dentistry
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• v.26 no.1
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• pp.146-150
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• 1999

With the improved cure rates for childhood malignant conditions in the past decade, late effects of cancer therapy must be recognized to minimize their impact on the quality of life in long-term survivors. Chemoradiation therapy is a major part of pediatric oncology treatment and is implicated in causing tooth agenesis, microdontia, root shortening, early apical closure, and coronal hypocalcification. Dental development may be affected by illness, trauma, chemotherapy, or radiation therapy at any point prior to complete maturation. Treatment given during the first 3.5 years of life was more likely to affect the dental lamina and crown formation and result in a small tooth. Dental treatment affected by chemoradiation damage to developing teeth includes orthodontic tooth movement, prosthetic abutment consideration, periodontal health, space maintenance, requirement for home fluoride regimens to protect hypomineralized teeth, and enodontic procedures. Dental abnormalities are common in patients treated for cancer, and these children require aggressive dental follow-up. Meticulous surveillance may facilitate detection of abnormalities, enabling the dental practitioner to intervene earlier in promoting a more aggressive regimen of oral care, thus reducing the morbidity associated with dental sequelae of oncotherapy, specifically periodontal disease and malocclusion. In this case, we report microdontia of all permanent second premolar and second molar in an 8 year old boy treated with chemotherapeutic agents during period of active dental development(14 months to 38 months of age).

• Proceedings of the Korean Society of Developmental Biology Conference
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• 1998.07a
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• pp.12-18
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• 1998

Tremendous progress has been made over the past quarter-century studying the genetics of gametogenesis and the resulting gametes and embryos. Studies merging molecular techniques and conventional cytogenetics are now beginning to bridge the gap between what we have learned about the meiotic process in males and females and what we know of the mitotic chromosomes of zygotes. Numerical abnormalities in sperm, oocytes and embryo can now diagnosed by fluorescence in situ hybridization (FISH). "At risk" couples can, therefore, have only unaffected embryos replaced in the sterus and avoid the possibility of terminating a pregnancy that might only be diagnosed as affected later gestation. Single-cell genetic analysis has also provided powerful tools for studying genetic defects arising during early human development. Recent studies of sperms, oocytes and cleavage-stage human embryos have revealed an unexpectedly high incidence. These genetic abnormalities are likely to contribute to early pregnancy loss and have important implications for improving pregnancy rates in infertile couples by assisted reproduction. The widespread use of preimplantation genetic diagnosis (PGD) awaits further documentatio of safety and accuracy. Other issues also must be addressed. First, the ethical issues regarding germ cell and embryo screening must be addressed including what diseases are serious enough to warrant the procedure. Another concern is the use of this technology for non-genetic disorders such as gender selection. Finally, the experimental nature of these procedure must continually be discussed with patients, and long-term follow-up studies must be undertaken. Development of more accurate and less expensive assays coupled with improved assisted reproductive technology success rates may make PGD a more widely use clinical tool. The future awaits these development.velopment.

• Imaging Science in Dentistry
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• v.49 no.3
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• pp.191-199
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• 2019

Purpose: To compare the diagnostic ability of undergraduate dental students to detect maxillary sinus abnormalities in panoramic radiographs(PR) and cone-beam computed tomography (CBCT). Materials and Methods: This was a retrospective study based on the evaluation of PR and CBCT images. A pilot study was conducted to determine the number of students eligible to participate in the study. The images were evaluated by 2 students, and 280 maxillary sinuses were assessed using the following categories: normal, mucosal thickening, sinus polyp, antral pseudocyst, nonspecific opacification, periostitis, antrolith, and antrolith associated with mucosal thickening. The reference standard was established by the consensus of 2 oral radiologists based on the CBCT images. The kappa test, receiver operating characteristic curves, and 1-way analysis of variance with the Tukey-Kramer post-hoc test were employed. Results: Intraobserver and interobserver reliability showed agreement ranging from substantial (0.809) to almost perfect (0.922). The agreement between the students' evaluations and the reference standard was reasonable (0.258) for PR and substantial(0.692) for CBCT. Comparisons of values of sensitivity, specificity, and accuracy showed that CBCT was significantly better(P<0.05). Conclusion: CBCT was better than PR for the detection of maxillary sinus abnormalities by dental students. However, CBCT should only be requested after a careful analysis of PR by students and more experienced professionals.