• Journal of Korean Neurosurgical Society
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• v.62 no.2
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• pp.193-200
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• 2019

Objective : Endovascular treatment (EVT) outcomes for acute M2 segment of middle cerebral artery occlusion remains unclear because most results are obtained from patients with large artery occlusion in the anterior circulation. The objective of this study was to assess procedural outcomes for acute M2 occlusion and compare outcomes according to thrombus location (M1 vs. M2). Methods : A systematic review was performed for online literature published from January 2004 to December 2016. Primary outcome was successful recanalization rate and symptomatic intracranial hemorrhage (S-ICH) after the procedure. A fixed effect model was used if heterogeneity was less than 50%. Results : Eight articles were included. EVT showed successful recanalization rate of 69.1% (95% confidence interval [CI], 54.9-80.4%) and S-ICH rate of 6.1% (95% CI, 4.5-8.3%). The rates of good clinical outcome at 3 months and mortality were 59.4% (95% CI, 49.9-68.2%) and 14.9% (95% CI, 11.4-19.3%), respectively. According to thrombus location (M1 vs. M2), successful recanalization (odds ratio [OR], 1.539; 95% CI, 0.293-8.092; p=0.610) and S-ICH (OR, 1.313; 95% CI, 0.603-2.861; p=0.493) did not differ significantly. Good clinical outcome was more evident in M2 occlusion after EVT than that in M1 occlusion (OR, 1.639; 95% CI, 1.135-2.368; p=0.008). However, mortality did not differ significantly according to thrombus location (OR, 0.788; 95% CI, 0.486-1.276; p=0.332). Conclusion : EVT seems to be technically feasible for acute M2 occlusion. Direct comparative studies between EVT and medical treatment are needed further to find specific beneficiary group after EVT in patient with M2 occlusion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1321-1329
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• 2019

With the development of social information networks, the marketing methods are also changing in various ways. Unlike successful marketing methods based on existing celebrities and financial support, Influencer-based marketing is a big trend and very famous. In this paper, we first extract influencer features from more than 54 YouTube channels using the multi-dimensional qualitative analysis based on the meta information and comment data analysis of YouTube, model representative themes to maximize a personalized video satisfaction. Plus, the purpose of this study is to provide supplementary means for the successful promotion and marketing by creating and distributing videos of new items by referring to the existing Influencer features. For that we assume all comments of various videos for each channel as each document, TF-IDF (Term Frequency and Inverse Document Frequency) and LDA (Latent Dirichlet Allocation) algorithms are applied to maximize performance of the proposed scheme. Based on the performance evaluation, we proved the proposed scheme is better than other schemes.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.43-52
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• 2021

In weapon assignment studies to defend against threats such as ballistic missiles and long range artillery, threat assessment was partially lacking in analysis of various threat attributes, and considering the threat characteristics of warheads, which are difficult to judge in the early flight stages, it is very important to apply more reliable optimal solutions than approximate solution using LP model, Meta heuristics Genetic Algorithm, Tabu search and Particle swarm optimization etc. Our studies suggest Generic Rule based threat evaluation and weapon assignment algorithm in the basis of various attributes of threats. First job of studies analyzes information on Various attributes such as the type of target, Flight trajectory and flight time, range and intercept altitude of the intercept system, etc. Second job of studies propose Rule based threat evaluation and weapon assignment algorithm were applied to obtain a more reliable solution by reflection the importance of the interception system. It analyzes ballistic missiles and long-range artillery was assigned to multiple intercept system by real time threat assessment reflecting various threat information. The results of this study are provided reliable solution for Weapon Assignment problem as well as considered to be applicable to establishing a missile and long range artillery defense system.

• Imaging Science in Dentistry
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• v.52 no.2
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• pp.141-153
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• 2022

Purpose: This study aimed to identify the prevalence and extension of the anterior loop (AL) of the mental nerve in different populations and according to different cone-beam computed tomography (CBCT) imaging settings. Materials and Methods: Medline/PubMed, Embase, Scopus, Web of Science, and ProQuest were searched. The main inclusion criterion was ALs evaluated in CBCT images. The quality of studies was assessed with the Joanna Briggs Institute risk of bias checklist. Subgroup analyses were conducted for sex, side, continent, voxel size, field of view, and type of CBCT-reconstruction images with a random-effects model. Results: Sixty-three studies with 13,743 participants (27,075 hemimandibles) were included. An AL was found in 40.6% (95% CI: 32.8%-48.9%, P<0.05) of participants and 36.0% (95% CI: 27.5%-45.5%, P<0.05) of hemimandibles, in 34.9% (95% CI: 25.1%-46.2%, P<0.05) of males and 34.5% (95% CI: 23.5%-47.4%, P<0.05) of females. The average length of ALs was 2.39 mm (95% CI: 2.07-2.70 mm, P<0.05). Their extension was 2.13 mm (95% CI: 1.54-2.73 mm, P<0.05) in males and 1.85 mm (95% CI: 1.35-2.36 mm, P<0.05) in females. Significant differences were observed regarding the prevalence and length of ALs among continents and for its measured length on different CBCT-reconstruction images, but not between other subgroups. Conclusion: AL was a relatively common finding. The voxel size and fields of view of CBCT devices were adequate for assessing AL; however, a 2-mm safety margin from anatomical structures(such as the AL) could be recommended to be considered when using CBCT imaging.

• Archives of Plastic Surgery
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• v.48 no.4
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• pp.361-365
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• 2021

Background Pain in the postoperative body contouring patient has traditionally been managed with narcotic medication. In an effort to minimize side effects and prevent addiction, plastic surgeons are searching for novel ways to provide adequate analgesia, one of which is nerve blocks. This study was conducted with a meta-analysis that evaluates the efficacy of these blocks for patients who undergo breast surgery. Methods A search of the PubMed/MEDLINE database for articles including the terms "post-operative analgesia" OR "postoperative pain management" AND "in plastic surgery" OR "in cosmetic surgery" OR "in elective surgery" in February 2019 generated five studies on elective breast augmentation and reduction mammoplasty that reported pain scores and quantities of opioids consumed. Independent samples t-tests, one-way analysis of variance, and a random effects model were implemented for evaluation. Results A total of 317 patients were identified as having undergone body contouring of the breast, about half of which received a nerve block. Pain scores on a 1-10 scale and opioid dose-equivalents were calculated. Those who were blocked had an average score of 2.40 compared to 3.64 for those who did not (P<0.001), and required an average of 5.20 less narcotic doses (P<0.001). Pain relief following subpectoral augmentation was best achieved with type-II blocks as opposed to type-I and type-II with serratus plane (P<0.001). Conclusions The opioid epidemic has extended to all surgical specialties. Implementation of a nerve block seems to be an efficacious and cost-effective mechanism to not only help with post-operative pain, but also lower the need for narcotics, especially in subpectoral augmentation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4531-4544
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• 2021

Because the traditional network information security vulnerability risk assessment method does not set the weight, it is easy for security personnel to fail to evaluate the value of information security vulnerability risk according to the calculation value of network centrality, resulting in poor evaluation effect. Therefore, based on the network security data element feature system, this study designed a quantitative assessment method of network information security vulnerability detection risk under single transmission state. In the case of single transmission state, the multi-dimensional analysis of network information security vulnerability is carried out by using the analysis model. On this basis, the weight is set, and the intrinsic attribute value of information security vulnerability is quantified by using the qualitative method. In order to comprehensively evaluate information security vulnerability, the efficacy coefficient method is used to transform information security vulnerability associated risk, and the information security vulnerability risk value is obtained, so as to realize the quantitative evaluation of network information security vulnerability detection under single transmission state. The calculated values of network centrality of the traditional method and the proposed method are tested respectively, and the evaluation of the two methods is evaluated according to the calculated results. The experimental results show that the proposed method can be used to calculate the network centrality value in the complex information security vulnerability space network, and the output evaluation result has a high signal-to-noise ratio, and the evaluation effect is obviously better than the traditional method.

• Biomolecules & Therapeutics
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• v.31 no.2
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• pp.161-167
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• 2023

Despite the various medications used in clinics, the efforts to develop more effective treatments for depression continue to increase in the past decades mainly because of the treatment-resistant population, and the testing of several hypotheses- and target-based treatments. Undesirable side effects and unresponsiveness to current medications fuel the drive to solve this top global health problem. In this study, we focused on neuroinflammatory response-mediated depression which represents a cluster of depression etiology both in animal models and humans. Several meta-analyses reported that proinflammatory cytokines such as interleukin 6 (IL-6) and tumor necrosis factor-α (TNF-α) were increased in major depressive disorder patients. Inflammatory mediators implicated in depression include type-I interferon and inflammasome pathways. To elucidate the molecular mechanisms of neuroinflammatory cascades underlying the pathophysiology of depression, we introduced hycanthone, an antischistosomal drug, to check whether it can counteract depressive-like behaviors in vivo and normalize the inflammation-induced changes in vitro. Lipopolysaccharide (LPS) treatment increased proinflammatory cytokine expression in the murine microglial cells as well as the stimulation of type I interferon-related pathways that are directly or indirectly regulated by Janus kinase-signal transducer and activator of transcription (JAK-STAT) activation. Hycanthone treatment attenuated those changes possibly by inhibiting the JAK-STAT pathway and inflammasome activation. Hycanthone also ameliorated depressive-like behaviors by LPS. Taken together, we suggest that the inhibitory action of hycanthone against the interferon pathway leading to attenuation of depressive-like behaviors can be a novel therapeutic mechanism for treating depression.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.4
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• pp.193-202
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• 2023

In recent years, the outstanding performance of large language models (LLMs) trained on extensive datasets has become a hot topic. Since studies on LLMs are available on open-source approaches, the ecosystem is expanding rapidly. Models that are task-specific, lightweight, and high-performing are being actively disseminated using additional training techniques using pre-trained LLMs as foundation models. On the other hand, the performance of LLMs for Korean is subpar because English comprises a significant proportion of the training dataset of existing LLMs. Therefore, research is being carried out on Korean-specific LLMs that allow for further learning with Korean language data. This paper identifies trends of open source based LLMs and introduces research on Korean specific large language models; moreover, the applications and limitations of large language models are described.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.50-53
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• 2022

In order to detect an object in yolv5, a process of annotating location information on an existing image is required when learning an image. The most representative method is to draw a bounding box on an image to store location information as meta information. However, if the boundary of the object is ambiguous, it will be difficult to make a bounding box. A representative example would be to classify parts that are not fire and parts that are fire. Therefore, in this paper, images of 100 samples judged to have caught fire were learned by varying the number of boxes. The results showed better fire detection performance in the model where the bounding box was trained by annotating it with three boxes by segmenting it slightly more than annotating it with one box by holding the edge as large as possible during annotating it with one box.

• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.1
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• pp.97-113
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• 2023

This study investigates the effect of consumers' trust in communication with online fashion mall avatars on performance expectancy and re-use intention. For the empirical study, 207 adults were surveyed using a 5-point Likert scale, and the results were analyzed with SPSS 21.0. The analysis reveals the following results. First, the factor analysis of trust in communication with the avatar, performance expectancy, and re-use intention revealed cognitive and affective trust as subfactors of the trust in communication with the avatar, while purchase choice expectations and performance expectancy were identified as subfactors of performance expectancy for the avatar. A total of five factors, including re-use intention, were recognized. Second, the trust in communication with online fashion mall avatars significantly positively affected performance expectancy for the avatar. Among the subfactors, cognitive trust was determined to have a greater influence on purchase choice expectations than affective trust. Third, the performance expectancy for the online fashion mall avatar significantly positively affected re-use intention. Notably, the subfactor performance expectancy had a greater influence than purchase choice expectations. Finally, trust in communication with online fashion mall avatars significantly positively affected re-use intention. Accordingly, the sub-factor cognitive trust had a greater influence on re-use intention than affective trust. The results of this study are academically significant in that they empirically test the influence relationship between trust in communication, performance expectancy, and re-use intention, considering the personal characteristics of online fashion mall avatars on consumers using the Meta-UTAUT model in the fashion field.