• 한국자원식물학회지
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• 제35권6호
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• pp.785-795
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• 2022

Traditional germplasms are unsuitable for mechanized production, limiting adzuki bean production. The creation of cultivars that can be harvested by mechanized means is an urgent task for breeders. The bottom pod height (BPH), lodging resistance, and synchronous maturing of adzuki beans are critical factors for the reduction of losses due to mechanized harvesting. In this study, 14 traits of 806 adzuki bean accessions were analyzed. All growth stages and the yield, lodging score, and synchronous maturing correlated negatively with the BPH. These negative correlations reflect the increased difficulty of breeding to simultaneously satisfy the needs for no lodging, high synchronous maturing rates, BPHs > 10 cm, and high yield. We screened three germplasms with no lodging, high synchronous maturing rates, and BPHs > 10 cm that were used as mechanization-adapted breeding material for crossing with high-yield cultivars. Agronomic trait diversity in adzuki beans was also examined in this study. Principal component and cluster analyses were conducted for 806 germplasms resulting in three clusters with the yield and three growth stage traits serving as the main discriminating factors. Cluster 1 included high-yield germplasms with the number of pods per plant and the number of seeds per pod being the major discriminant factors. Cluster 2 included germplasms with long growth periods and large 100-seed weights while cluster 3 contained germplasms with high BPHs. In general, the characteristics that make mechanical harvesting feasible and those assessed in this study could be utilized to choose and enhance adzuki beans production.

• 대한방사선기술학회지:방사선기술과학
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• 제46권4호
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• pp.277-285
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• 2023

In this study, pneumonia identification networks with the small number of layers were constructed by using chest X-ray images. The networks had similar trainable-parameters, and the performance of the trained models was quantitatively evaluated with the modification of the network architectures. A total of 6 networks were constructed: convolutional neural network (CNN), VGGNet, GoogleNet, residual network with identity blocks, ResNet with bottleneck blocks and ResNet with identity and bottleneck blocks. Trainable parameters for the 6 networks were set in a range of 273,921-294,817 by adjusting the output channels of convolution layers. The network training was implemented with binary cross entropy (BCE) loss function, sigmoid activation function, adaptive moment estimation (Adam) optimizer and 100 epochs. The performance of the trained models was evaluated in terms of training time, accuracy, precision, recall, specificity and F1-score. The results showed that the trained models with the small number of layers precisely detect pneumonia from chest X-ray images. In particular, the overall quantitative performance of the trained models based on the ResNets was above 0.9, and the performance levels were similar or superior to those based on the CNN, VGGNet and GoogleNet. Also, the residual blocks affected the performance of the trained models based on the ResNets. Therefore, in this study, we demonstrated that the object detection networks with the small number of layers are suitable for detecting pneumonia using chest X-ray images. And, the trained models based on the ResNets can be optimized by applying appropriate residual-blocks.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.289-301
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• 2023

Due to the development and dissemination of modern technology, anyone can easily communicate using services such as social network service (SNS) through a personal computer (PC) or smartphone. The development of these technologies has caused many beneficial effects. At the same time, bad effects also occurred, one of which was the spam problem. Spam refers to unwanted or rejected information received by unspecified users. The continuous exposure of such information to service users creates inconvenience in the user's use of the service, and if filtering is not performed correctly, the quality of service deteriorates. Recently, spammers are creating more malicious spam by distorting the image of spam text so that optical character recognition (OCR)-based spam filters cannot easily detect it. Fortunately, the level of transformation of image spam circulated on social media is not serious yet. However, in the mail system, spammers (the person who sends spam) showed various modifications to the spam image for neutralizing OCR, and therefore, the same situation can happen with spam images on social media. Spammers have been shown to interfere with OCR reading through geometric transformations such as image distortion, noise addition, and blurring. Various techniques have been studied to filter image spam, but at the same time, methods of interfering with image spam identification using obfuscated images are also continuously developing. In this paper, we propose a deep learning-based spam image detection model to improve the existing OCR-based spam image detection performance and compensate for vulnerabilities. The proposed model extracts text features and image features from the image using four sub-models. First, the OCR-based text model extracts the text-related features, whether the image contains spam words, and the word embedding vector from the input image. Then, the convolution neural network-based image model extracts image obfuscation and image feature vectors from the input image. The extracted feature is determined whether it is a spam image by the final spam image classifier. As a result of evaluating the F1-score of the proposed model, the performance was about 14 points higher than the OCR-based spam image detection performance.

• Genomics & Informatics
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• 제21권3호
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• pp.38.1-38.8
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• 2023

Non-small cell lung cancer (NSCLC) is an important cause of cancer-associated deaths worldwide. Therefore, the exact molecular mechanisms of NSCLC are unidentified. The present investigation aims to identify the miRNAs with predictive value in NSCLC. The two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed miRNAs (DEmiRNA) and mRNAs (DEmRNA) were selected from the normalized data. Next, miRNA-mRNA interactions were determined. Then, co-expression network analysis was completed using the WGCNA package in R software. The co-expression network between DEmiRNAs and DEmRNAs was calculated to prioritize the miRNAs. Next, the enrichment analysis was performed for DEmiRNA and DEmRNA. Finally, the drug-gene interaction network was constructed by importing the gene list to dgidb database. A total of 3,033 differentially expressed genes and 58 DEmiRNA were recognized from two datasets. The co-expression network analysis was utilized to build a gene co- expression network. Next, four modules were selected based on the Z_summary score. In the next step, a bipartite miRNA-gene network was constructed and hub miRNAs (let-7a-2-3p, let-7d-5p, let-7b-5p, let-7a-5p, and let-7b-3p) were selected. Finally, a drug-gene network was constructed while SUNITINIB, MEDROXYPROGESTERONE ACETATE, DOFETILIDE, HALOPERIDOL, and CALCITRIOL drugs were recognized as a beneficial drug in NSCLC. The hub miRNAs and repurposed drugs may act a vital role in NSCLC progression and treatment, respectively; however, these results must validate in further clinical and experimental assessments.

• 보건행정학회지
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• 제33권4호
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• pp.440-449
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• 2023

Background: This study aimed to analyze the prehospital process and reperfusion therapy process of acute ischemic stroke in Busan metropolitan area and examine the impact of living arrangement on the early management and functional outcomes of acute ischemic stroke (AIS). Methods: The patients who diagnosed with AIS and received reperfusion therapy at the Busan Regional Cardiovascular Center between September 2020 and May 2023 were selected. We investigated the patients' hospital arrival time (onset to door time) and utilization of 119 emergency ambulance services. Additionally, various time matrices related to reperfusion therapy after hospital were examined, along with the functional outcome at the 90-day after treatment. Results: Among the 753 AIS patients who underwent reperfusion therapy, 166 individuals (22.1%) were living alone. AIS patients living alone experienced significant delays in symptom detection (p<0.05) and hospital arrival compared to AIS patients with cohabitants (370.1 minutes vs. 210.2 minutes, p<0.001). There were no significant differences between the two groups in terms of 119 ambulance utilization and time metrics related with the reperfusion therapy. Independent predictors of prognosis in AIS patients were found to be age above 70, National Institutes of Health Stroke Scale score at admission, tissue plasminogen activator, living alone (odds ratio [OR], 1.785; 95% confidence interval [CI], 1.155-2.760) and interhospital transfer (OR, 1.898; 95% CI, 1.152-3.127). Delay in identification of AIS was shown significant correlation (OR, 2.440; 95% CI, 1.070-5.561) at living alone patients. Conclusion: This study revealed that AIS patients living alone in the Busan metropolitan region, requiring endovascular treatment, face challenges in the pre-hospital phase, which significantly impact their prognosis.

• International Journal of Computer Science & Network Security
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• 제24권6호
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• pp.8-16
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• 2024

Communication with the deaf has always been crucial. Deaf and hard-of-hearing persons can now express their thoughts and opinions to teachers through sign language, which has become a universal language and a very effective tool. This helps to improve their education. This facilitates and simplifies the referral procedure between them and the teachers. There are various bodily movements used in sign language, including those of arms, legs, and face. Pure expressiveness, proximity, and shared interests are examples of nonverbal physical communication that is distinct from gestures that convey a particular message. The meanings of gestures vary depending on your social or cultural background and are quite unique. Sign language prediction recognition is a highly popular and Research is ongoing in this area, and the SVM has shown value. Research in a number of fields where SVMs struggle has encouraged the development of numerous applications, such as SVM for enormous data sets, SVM for multi-classification, and SVM for unbalanced data sets.Without a precise diagnosis of the signs, right control measures cannot be applied when they are needed. One of the methods that is frequently utilized for the identification and categorization of sign languages is image processing. African Buffalo Optimization using Support Vector Machine (ABO+SVM) classification technology is used in this work to help identify and categorize peoples' sign languages. Segmentation by K-means clustering is used to first identify the sign region, after which color and texture features are extracted. The accuracy, sensitivity, Precision, specificity, and F1-score of the proposed system African Buffalo Optimization using Support Vector Machine (ABOSVM) are validated against the existing classifiers SVM, CNN, and PSO+ANN.

• Hip & pelvis
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• 제36권2호
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• pp.135-143
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• 2024

Purpose: Hip fractures are associated with increased mortality. The identification of risk factors of mortality could improve patient care. The aim of the study was to identify risk factors of mortality after surgery for a hip fracture and construct a mortality model. Materials and Methods: A cohort study was conducted on patients with hip fractures at two institutions. Five hundred and ninety-seven patients with hip fractures that were treated in the tertiary hospital, and another 147 patients that were treated in a secondary hospital. The perioperative data were collected from medical charts and interviews. Functional Assessment Measure score, Short Form-12 and mortality were recorded at 12 months. Patients and surgery variables that were associated with increased mortality were used to develop a mortality model. Results: Mortality for the whole cohort was 19.4% at one year. From the variables tested only age >80 years, American Society of Anesthesiologists category, time to surgery (>48 hours), Charlson comorbidity index, sex, use of anti-coagulants, and body mass index <25 kg/m² were associated with increased mortality and used to construct the mortality model. The area under the curve for the prediction model was 0.814. Functional outcome at one year was similar to preoperative status, even though their level of physical function dropped after the hip surgery and slowly recovered. Conclusion: The mortality prediction model that was developed in this study calculates the risk of death at one year for patients with hip fractures, is simple, and could detect high risk patients that need special management.

• 대한영상의학회지
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• 제85권1호
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• pp.138-146
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• 2024

목적 카메라형 휴대형 X선 장치를 이용하여 촬영한 흉부 X선 사진의 영상품질을 기존 이동형 디지털 X선 장치로 촬영한 영상과 비교하여 임상에서 사용 가능한지 평가하고자 하였다. 대상과 방법 2020년 9월부터 2021년 5월까지 응급실에 내원한 환자 중 기관내 삽관, 중심정맥관, 비위관 등을 삽입한 86명의 환자를 대상으로 하였다. 환자들은 기구 삽입 전 기존 이동형 디지털 X선 장치, 기구 삽입 후 카메라형 휴대형 X선 장치를 이용하여 각각 흉부 영상을 촬영하였다. 두 명의 영상의학과 의사가 얻어진 두 영상을 삽입기구의 식별에 대하여 5점 척도, 전반적인 영상 품질에 대하여 20점 만점으로 평가하였다. 결과 카메라형 휴대형 X선 장치로 삽입한 기구의 식별에 대한 평가는 4.67 ± 0.71점이었다. 전반적인 영상품질에 대한 평가는 기존 이동형 디지털 X선 장치와 카메라형 휴대형 X선 장치가 각각 19.70 ± 0.72점과 15.02 ± 3.31점(p < 0.001)이었고, 호흡 및 움직임 관련 인공물, 기관 및 기관지, 폐혈관, 심장 뒤 혈관, 흉추 추간판 공간, 횡격막 하 혈관, 횡격막 관찰의 세부항목에서 카메라형 X선 장치의 점수가 통계적으로 유의하게 점수가 낮았다(횡격막 관찰 세부항목 p = 0.013, 그 외 세부항목 p < 0.001). 결론 카메라형 휴대형 X선 장치는 흉부X선 사진에서 삽입 기구의 평가를 목적으로 사용하는 것은 가능하나 영상의 품질 저하가 있으므로 일반적인 진단 목적의 사용에는 주의를 요한다.

• 지능정보연구
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• 제27권3호
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• pp.57-73
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• 2021

ICT 인프라의 이상탐지를 통한 유지보수와 장애 예방이 중요해지고 있다. 장애 예방을 위해서 이상탐지에 대한 관심이 높아지고 있으며, 지금까지의 다양한 이상탐지 기법 중 최근 연구들에서는 딥러닝을 활용하고 있으며 오토인코더를 활용한 모델을 제안하고 있다. 이는 오토인코더가 다차원 다변량에 대해서도 효과적으로 처리가 가능하다는 것이다. 한편 학습 시에는 많은 컴퓨터 자원이 소모되지만 추론과정에서는 연산을 빠르게 수행할 수 있어 실시간 스트리밍 서비스가 가능하다. 본 연구에서는 기존 연구들과 달리 오토인코더에 2가지 요소를 가미하여 이상탐지의 성능을 높이고자 하였다. 먼저 다차원 데이터가 가지고 있는 속성별 특징을 최대한 부각하여 활용하기 위해 멀티모달 개념을 적용한 멀티모달 오토인코더를 적용하였다. CPU, Memory, network 등 서로 연관이 있는 지표들을 묶어 5개의 모달로 구성하여 학습 성능을 높이고자 하였다. 또한, 시계열 데이터의 특징을 데이터의 차원을 늘리지 않고 효과적으로 학습하기 위하여 조건부 오토인코더(conditional autoencoder) 구조를 활용하는 조건부 멀티모달 오토인코더(Conditional Multimodal Autoencoder, CMAE)를 제안하였다. 제안한 CAME 모델은 비교 실험을 통해 검증했으며, 기존 연구들에서 많이 활용된 오토인코더와 비교하여 AUC, Accuracy, Precision, Recall, F1-score의 성능 평가를 진행한 결과 유니모달 오토인코더(UAE)와 멀티모달 오토인코더(Multimodal Autoencoder, MAE)의 성능을 상회하는 결과를 얻어 이상탐지에 있어 효과적이라는 것을 확인하였다.

• 초등상담연구
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• 제5권1호
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• pp.227-253
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• 2006

It seems common for students living at a small county and islands to experience psychological conflicts and be unaccustomed in the peer society because they are not familiar with peer interaction and social skills. This is a case study of L (hereinafter called L) who was grown up in the sheltered school at a small county. L was psychologically disturbed because he couldn't get along well in the transferred school. It is the reason why he had lived in the sheltered school at a small county, so he had not enough exposure to interact with peer and social skills. Sometimes he was obstinate irrationally and when he had trouble with friends, he threw something out or went out of school and tricked juniors dangerously. The fact of disperse with families, parent's indifference, and hate of older brother made L to have ill feeling against family. He had low motivation and low self confident in learning because of short attention time and accumulated poor learning progress. In this study, he was evaluated at various area, such as, intelligent, affective, personal and inter-personal, before counselling. To evaluated the effect of the counselling, K-WISC-III, KPRC, sentence filling test, social adaptation ability test, etc, were administered right after the counselling was over and 8 weeks later. For specific information gathering and analysing, observation diary and deepen counselling were accomplished by homeroom teacher, his mother, and his peers. To correct his problematic behaviors, 13 counseling sessions were accomplished for 6 months and those counselling sessions were recorded and analysed definitely. Followings are the result of this case study. First, he was recovered from the anxiety of inter-personal interaction and he started to interact with peers. The result of sac scale score of KPRC profile was lower than before as much as average student after counseling and 8 weeks later. This reveals that the distress against interpersonal relation have settled. Especially, through the result of sentence filing test, he seemed to feel attachment to peers and be positive, active in the relation of peer. For instance, he was active in the open class lesson and interacted well with peers. It could be said that he overcame the psychological distress comparing with previous time. Second, he could apologize to his peer and juniors for his fault. His attitude were well shown in the letter from an old friend at the sheltered school, average KPRC profiling score comparing with previous counseling time, and remarkable decrease of attack scale score of teacher and peer. Third, his view toward family turn out positive. He recognized his situation that he lived apart from family and even worried about his parent's financial difficulty. Through solving the confliction with his older brother, he could acquire the feeling of family reunion. Fourth, his learning motivation and self-confidence were increased. He confirmed his future positively and he might be judged more attentive because his intelligence index was higher than before as much as average student. With the main goal of this study, verification for effectiveness of counseling. understanding and helping problematic students such as L who lives at a small county and island through investigation of their real situation and problems with the method of counseling and socio-cultural analysis is worthwhile. Identification of ideal relationship with peer is related with positive self-conception, harmonic social adaptation and development of child. It is time to investigate easy adaptive in classroom and well-organised program to acquire general social skills for sheltered school students at a small county and islands.