• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.85-90
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• 2022

In modern conditions of the development of public relations, there is a continuous development of technologies. This not only reflects the convenience of service users, and new technology but also contributes to the emergence of new disputes to protect the rights of stakeholders. Therefore, it is urgent to study the distinctions between the jurisdiction of commercial, civil and administrative courts in resolving IT disputes. The work aims to study the peculiarities of delimitation of the jurisdiction of commercial, civil, and administrative courts through the prism of IT measurement. The research methodology consists of such methods as a historical, comparative-legal, formal-logical, empirical, method of analogy, method of synthesis, method of analysis, and systematic method. Examining the specifics of delimiting the jurisdiction of commercial, civil, and administrative courts through the IT dimension, it was concluded that there is a problem in determining the jurisdiction of the court. In addition, the judicial practice on this issue is quite variable, which negatively affects the predictability of technology in resolving potential disputes. In this regard, the criterion models for distinguishing between commercial, administrative, and civil proceedings according to the legal classification of the parties, as well as the nature of the claim are identified. This separation will contribute to a more accurate application of legal norms and methods of application of administrative norms and reduce the number of cases of improper proceedings.

• Korean Journal of Biological Psychiatry
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• v.25 no.2
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• pp.38-43
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• 2018

Objectives Dopamine dysregulation has been regarded as one of the core pathologies in patients with schizophrenia. Since dopamine synthesis capacity has found to be inconsistent in patients with schizophrenia, current classification of patients based on clinical symptoms cannot reflect the neurochemical heterogeneity of the disease. Here we performed new subtyping of patients with first-episode psychosis (FEP) through biotype-based cluster analysis. We specifically suggested basal ganglia structural changes as a biotype, which deeply involves in the dopaminergic circuit. Methods Forty FEP and 40 demographically matched healthy participants underwent 3T T1 MRI. Whole brain parcellation was conducted, and volumes of total 6 regions of basal ganglia have been extracted as features for cluster analysis. We used K-means clustering, and external validation was conducted with Positive and Negative Syndrome Scale (PANSS). Results K-means clustering divided 40 FEP subjects into 2 clusters. Cluster 1 (n = 25) showed substantial volume decrease in 4 regions of basal ganglia compared to Cluster 2 (n = 15). Cluster 1 showed higher positive scales of PANSS compared with Cluster 2 (F = 2.333, p = 0.025). Compared to healthy controls, Cluster 1 showed smaller volumes in 4 regions, whereas Cluster 2 showed larger volumes in 3 regions. Conclusions Two subgroups have been found by cluster analysis, which showed a distinct difference in volume patterns of basal ganglia structures and positive symptom severity. The result possibly reflects the neurobiological heterogeneity of schizophrenia. Thus, the current study supports the importance of paradigm shift toward biotype-based diagnosis, instead of phenotype, for future precision psychiatry.

• Journal of Korean Neurosurgical Society
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• v.63 no.3
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• pp.386-396
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• 2020

Objective : To generate synthetic spine magnetic resonance (MR) images from spine computed tomography (CT) using generative adversarial networks (GANs), as well as to determine the similarities between synthesized and real MR images. Methods : GANs were trained to transform spine CT image slices into spine magnetic resonance T2 weighted (MRT2) axial image slices by combining adversarial loss and voxel-wise loss. Experiments were performed using 280 pairs of lumbar spine CT scans and MRT2 images. The MRT2 images were then synthesized from 15 other spine CT scans. To evaluate whether the synthetic MR images were realistic, two radiologists, two spine surgeons, and two residents blindly classified the real and synthetic MRT2 images. Two experienced radiologists then evaluated the similarities between subdivisions of the real and synthetic MRT2 images. Quantitative analysis of the synthetic MRT2 images was performed using the mean absolute error (MAE) and peak signal-to-noise ratio (PSNR). Results : The mean overall similarity of the synthetic MRT2 images evaluated by radiologists was 80.2%. In the blind classification of the real MRT2 images, the failure rate ranged from 0% to 40%. The MAE value of each image ranged from 13.75 to 34.24 pixels (mean, 21.19 pixels), and the PSNR of each image ranged from 61.96 to 68.16 dB (mean, 64.92 dB). Conclusion : This was the first study to apply GANs to synthesize spine MR images from CT images. Despite the small dataset of 280 pairs, the synthetic MR images were relatively well implemented. Synthesis of medical images using GANs is a new paradigm of artificial intelligence application in medical imaging. We expect that synthesis of MR images from spine CT images using GANs will improve the diagnostic usefulness of CT. To better inform the clinical applications of this technique, further studies are needed involving a large dataset, a variety of pathologies, and other MR sequence of the lumbar spine.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.287-294
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• 2021

Modern small farms are important link components in the structure of the world agro-industrial complex. It ensures the food and nutritional sustainability of the country exclusively at the local regional level. The purpose of the research is to examine the role of farming in ensuring nutritional security and food stability based on the analysis of the Food Sustainability Index (FSI). Research methods: modeling, abstraction, analogy, analysis, synthesis, formalization, logical abstraction, theoretical cognition, systematization and classification, abstract-logical, etc. Results. Having analyzed the Food Sustainability Index for 2018, it has been established that there is a lack of a clear relationship between the pace of economic development and the level of food and nutritional sustainability. In addition, this study has identified the countries with the largest number of small farms, as well as the number of farms within the region. The correlation between the size of the farm and the area of agricultural land that it cultivates has been determined. The problems faced by small farms in the process of their activity have been analyzed. The programs implemented in the field of agro-industrial complex development by international profile institutions have been systematized. Particularly, the regional structure of agricultural development programs under the guidance of IFAD is defined, as well as the areas to which they are directed. Specific measures taken by governments to stimulate the development of small farms have been outlined. Reasonable conclusions have been formed based on the study. The direction of future research is seen in the assessment of the export potential of small farms in terms of range, volume of export deliveries and geographical direction of movement of their products.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.334-342
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• 2022

Nowadays, as we can notice on social media, most users choose to use more than one language in their online postings. Thus, social media analytics needs reviewing as code-switching analytics instead of traditional analytics. This paper aims to present evidence comparable to the accuracy of code-switching analytics techniques in analysing the mood state of social media users. We conducted a systematic literature review (SLR) to study the social media analytics that examined the effectiveness of code-switching analytics techniques. One primary question and three sub-questions have been raised for this purpose. The study investigates the computational models used to detect and measures emotional well-being. The study primarily focuses on online postings text, including the extended text analysis, analysing and predicting using past experiences, and classifying the mood upon analysis. We used thirty-two (32) papers for our evidence synthesis and identified four main task classifications that can be used potentially in code-switching analytics. The tasks include determining analytics algorithms, classification techniques, mood classes, and analytics flow. Results showed that CNN-BiLSTM was the machine learning algorithm that affected code-switching analytics accuracy the most with 83.21%. In addition, the analytics accuracy when using the code-mixing emotion corpus could enhance by about 20% compared to when performing with one language. Our meta-analyses showed that code-mixing emotion corpus was effective in improving the mood analytics accuracy level. This SLR result has pointed to two apparent gaps in the research field: i) lack of studies that focus on Malay-English code-mixing analytics and ii) lack of studies investigating various mood classes via the code-mixing approach.

• Korean small business review
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• v.41 no.1
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• pp.97-129
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• 2019

The concepts of entrepreneurship are very various. So many researchers are confused or not sure of the concepts of entrepreneurship. Some entrepreneurship researches has defined the entrepreneurship as 'self-employment. This study try to set a comprehensive conceptual model of concepts of entrepreneurship through classification of word and phrase with job analysis and competence model. Several concepts of entrepreneurship which important prior researchers, had defined are analysed into 'subject', 'object', 'verb', 'goal and behavioral results' with content analysis. Also, Several concepts of entrepreneur which important prior researchers had defined, are analysed into 'individual psychological traits', 'competence and ability', 'motive', and 'function or job (business).' This study suggests a integrated conceptual model of entrepreneurship based on analysed results.

• Parasites, Hosts and Diseases
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• v.54 no.6
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• pp.751-758
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• 2016

This study aimed at constructing a draft genome of the adult female worm Toxocara canis using next-generation sequencing (NGS) and de novo assembly, as well as to find new genes after annotation using functional genomics tools. Using an NGS machine, we produced DNA read data of T. canis. The de novo assembly of the read data was performed using SOAPdenovo. RNA read data were assembled using Trinity. Structural annotation, homology search, functional annotation, classification of protein domains, and KEGG pathway analysis were carried out. Besides them, recently developed tools such as MAKER, PASA, Evidence Modeler, and Blast2GO were used. The scaffold DNA was obtained, the N50 was 108,950 bp, and the overall length was 341,776,187 bp. The N50 of the transcriptome was 940 bp, and its length was 53,046,952 bp. The GC content of the entire genome was 39.3%. The total number of genes was 20,178, and the total number of protein sequences was 22,358. Of the 22,358 protein sequences, 4,992 were newly observed in T. canis. Following proteins previously unknown were found: E3 ubiquitin-protein ligase cbl-b and antigen T-cell receptor, zeta chain for T-cell and B-cell regulation; endoprotease bli-4 for cuticle metabolism; mucin 12Ea and polymorphic mucin variant C6/1/40r2.1 for mucin production; tropomodulin-family protein and ryanodine receptor calcium release channels for muscle movement. We were able to find new hypothetical polypeptides sequences unique to T. canis, and the findings of this study are capable of serving as a basis for extending our biological understanding of T. canis.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.18 no.2
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• pp.123-129
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• 2007

Objectives: Autism is a complex neurodevelopmental spectrum disorder with a strong genetic component. Previous neurochemical and genetic studies have suggested the possible involvement of the serotonin system in autism. Tryptophan 2,3-dioxygenase(TDO2) is the rate-limiting enzyme in the catabolism of tryptophan, which is the precursor of serotonin synthesis. The aim of this study was to investigate the association between the TDO2 gene and autism spectrum disorders(ASD) in a Korean population. Methods: The patients were diagnosed with ASD on the basis of the DSM-IV diagnostic classification outlined in the Korean version of the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. The present study included the detection of four single nucleotide polymorphisms(SNPs) in the TDO2 gene(rs2292536, rs6856558, rs6830072, rs6830800) and the family-based association analysis of the single nucleotide polymorphisms in Korean ASD trios using a transmission disequilibrium test(TDT) and haplotype analysis. The family trios of 136 probands were included in analysis. 87.5% were male and 86.0% were diagnosed with autism. The mean age of the probands was $78.5{\pm}35.8$ months(range: 26-264 months). Results: Two SNPs showed no polymorphism, and there was no significant difference in transmission in the other two SNPs. We also could not find any significant transmission in the haplotype analysis(p>.05). Conclusion: We could not find any significant statistical association between the transmission of SNPs in the TDO2 gene and ASD in a Korean population. This result may not support the possible involvement of the TDO2 gene in the development of ASD, and further exploration might be needed to investigate other plausible SNP sites.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.14 no.1
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• pp.16-25
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• 2003

Background and Objectives : Electroglottography(EGG) is a non-invasive method of monitoring the vocal cord vibration by measuring the variation of physiological impedance across the vocal folds through the neck skin. It reveals especially the vocal fold contact area and is widely used for basic laryngeal researches, voice analysis and synthesis. The purpose of this study is to investigate the effectiveness of EGG parameters in differential diagnosis of laryngeal cancer. Materials and Methods : The author investigated 10 laryngeal cancer and 25 benign laryngeal disease patients who visited at the Department of Otolaryngology, Pusan National University Hospital. The EGG equipment was devised in the author's Department. Among various parameters of EGG, closed quotient(CQ), speed quotient(SQ), speed index(SI), Jitter, Shimmer, Fo were determined by an analysis program made with MATLAB 6.5$^{\circledR}$(Mathwork, Inc.). In order to differentiate various laryngeal diseases from pathologic voice signals, the author has used the electroglottographic parameters using the neural network of multilayer perceptron structure. Results : SQ, SI, Jitter and Shimmer values except those of CQ and Fo showed remarkable differences between benign and malignant laryngeal disease groups. From the artificial neural network, the percentage of differentiating the laryngeal cancer was over 80% in SQ, SI, Jitter, Shimmer except for CQ and Fo. These results indicated that it is possible to discriminate the benign and malignant laryngeal diseases by EGG parameters using the artificial neural network. Conclusion : If parameters of EGG which can reveal for the pathology of laryngeal diseases are additionally developed and the current classification algorithm is improved, the discrimination of laryngeal cancer will become much more accurate.

• Journal of Life Science
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• v.27 no.9
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• pp.1040-1046
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• 2017

We describe the isolation and characterization of six different intestinal microorganisms from the digestive tract of the cricket Gryllus bimaculatus. Based on 16S rRNA gene sequences, we obtained six isolates belonging to four different genera: Staphylococcus, Bacillus, Citrobacter, and Proteus. All the isolates were resistant to ampicillin. Ampicillin is an irreversible inhibitor of the enzymeetranspeptidase, which is needed to make bacterial cell walls. None of the isolates were resistant to kanamycin, which binds to the 30S subunit of the bacterial ribosome and then inhibits total protein synthesis. Gram staining was conducted, in addition to morphological classification under a microscope. Four grampositive isolates and two gram-negative isolates were detected. The gram-positive isolates were GL1 (round shaped, 2 am in diameter), GL2 (rod shaped, $2.5{\mu}m$ in length), GL3 (rod shaped, $2{\mu}m$ in length), and GL4 (round shaped, $1.5{\mu}m$ in diameter). The gram-negative isolates were GL5 (rod shaped, $2{\mu}m$ in length) and GL6 (rod-shaped, $2.5{\mu}m$ in length). Notably, two of the isolates, GL2 and GL4, secreted specific extracellular proteins. These were determined by MALDI-TOF-MS spectral analysis to be a 87 kDa collagenase, 56 kDa hypothetical protein, and 200 kDa hypothetical protein. The six isolates in this study could be used for various biotechnological applications and pest management, both in the field and in greenhouse systems. In addition, it would be interesting to determine the relationship between these isolates and their host.