• International Journal of Computer Science & Network Security
• /
• v.23 no.2
• /
• pp.203-209
• /
• 2023

The paper brings across data that is utilized in the Bring Your Own Device (BYOD) status collected between February and April of 2021 across Saudi Arabia. The data set was collected using questionnaires established through online mechanisms for the respondents. In the questionnaire, personal details included five questions while seven questions addressed the working model of personal mobile devices. Six questions addressed the awareness of employees bring your own device awareness for employees comprised seven questions and two questions addressed the benefits of business achievements. In the identification of suitable respondents for the research, two approaches were applied. The research demanded that the respondents be Saudi Arabian nationals and have attained 18 years. Snowball and purposive techniques were applied in the collection of information from a wide area of Saudi Arabia while employing social media approaches that include the use of WhatsApp and emails in the collection of data. The approach ensured the collection of data from 857 respondents used in the identification of the status as well as issues across the BYOD environment and accompanying solutions. The data was also used in the provision of awareness in the community through short-term courses, cyber security training and awareness programs. The results of the research are therefore applicable to the context of the Saudi Arabian country that is currently facing issues in dealing with the application of personal devices in the work environment.

• The Journal of Churna Manual Medicine for Spine and Nerves
• /
• v.17 no.2
• /
• pp.131-139
• /
• 2022

Objectives This study aimed to analyze the medical utilization of low back pain (LBP) patients after back surgery and estimate the medical costs of Korean and Western medicine collaborative treatment, odds ratio, and hazard ratio between the two groups using the 2019 Health Insurance Review and Assessment Service-National Patient Sample (HIRA-NPS-2019). Methods Data management and descriptive analysis, logistic regression, and survival analysis were conducted for defining and estimating the LBP patients after back surgery in the NPS 2019 dataset. Results A total of 216,424 patients out of 991,189 were identified as having LBP. Among the patients with LBP, 1,734 were treated with surgery while 214,690 were not. Among those who had surgery, 937 were treated with conventional treatments only and 797 underwent Korean medicine treatments. The odds ratio of the logistic regression analysis was 0.7129, suggesting that Korean medical treatment experience group had a 28.7% lower risk of reoperation than the Western medical treatments only group. The hazard ratio of the survival analysis was 0.9145; thus, the risk probability of reoperation was estimated to be approximately 8.55% lower. The 50% risk of reoperation was 69 days (0.5044) for the conventional group, and 97 days (0.5008) for the Korean medical group in the survival analysis using the Kaplan-Meier graph. Conclusions These results could be utilized in future studies in conducting economic evaluation for estimating cost-effectiveness of Western medicine and Korean medicine treatment compared to Western medicine alone in LBP patients after back surgery in a South Korean perspective. mended and should be applied while taking the necessary precautions.

• Journal of Biomedical Engineering Research
• /
• v.44 no.3
• /
• pp.211-217
• /
• 2023

Recently, many studies have introduced artificial intelligence systems in the surgical process to reduce the incidence and mortality of complications in patients. Bleeding is a major cause of operative mortality and complications. However, there have been few studies conducted on detecting bleeding in surgical videos. To advance the development of deep learning models for detecting intraoperative hemorrhage, three models have been trained and compared; such as, YOLOv5, RetinaNet50, and RetinaNet101. We collected 1,016 bleeding images extracted from five surgical videos. The ground truths were labeled based on agreement from two specialists. To train and evaluate models, we divided the datasets into training data, validation data, and test data. For training, 812 images (80%) were selected from the dataset. Another 102 images (10%) were used for evaluation and the remaining 102 images (10%) were used as the evaluation data. The three main metrics used to evaluate performance are precision, recall, and false positive per image (FPPI). Based on the evaluation metrics, RetinaNet101 achieved the best detection results out of the three models (Precision rate of 0.99±0.01, Recall rate of 0.93±0.02, and FPPI of 0.01±0.01). The information on the bleeding detected in surgical videos can be quickly transmitted to the operating room, improving patient outcomes.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.1
• /
• pp.216-238
• /
• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2021.05a
• /
• pp.282-284
• /
• 2021

최근 4차 산업혁명으로 의료빅데이터 기반으로 한 AI 기술이 급속도로 발전하고 있다. 특히, 의료영상을 기반으로 병변을 탐색, 분활 및 정량화 그리고 자동진단 및 예측 관련된 기술이 AI 제품으로 출시되고 있다. AI 기술개발은 많은 학습데이터가 요구되며, 임상검증에 단일기관에서 2개 이상 기관의 검증이 요구되고 있다. 그러나 아직까지도 단일기관에서 학습용 데이터와 테스트, 검증용 데이터를 달리하여 기술개발에 활용하고 있다. 본 논문은 AI 기술개발에 필요한 영상데이터에 대한 표준화된 데이터셋 변환 및 관리를 위한 시스템에 대해 기술한다. 다기관 데이터를 수집하기 위해서는 각 기관의 의료영상 데이터 수집 및 저장하는 기준이 명확하지 않아 표준화 작업이 필요하다. 제안한 시스템은 기관 또는 다기관 연구 그룹의 의료영상데이터를 표준화하여 저장할 수 있을 뿐만 아니라 의료영상 뷰어 및 의료영상 리스트를 통해 연구자가 원하는 의료영상 데이터 셋을 검색하여 다양한 데이터셋으로 제공할 수 있기 때문에 수집 및 변환 그리고 관리까지 지원할 수 있는 시스템으로 영상기반의 머신러닝 연구에 활력을 불어넣을 수 있을 것으로 기대하고 있다.

• Journal of Animal Science and Technology
• /
• v.65 no.3
• /
• pp.588-595
• /
• 2023

The aim of this study was to investigate the effects of heat stress on milk traits in South Korea using comprehensive data (dairy production and climate). The dataset for this study comprised 1,498,232 test-day records for milk yield, fat- and protein-corrected milk, fat yield, protein yield, milk urea nitrogen (MUN), and somatic cell score (SCS) from 215,276 Holstein cows (primiparous: n = 122,087; multiparous: n = 93,189) in 2,419 South Korean dairy herds. Data were collected from July 2017 to April 2020 through the Dairy Cattle Improvement Program, and merged with meteorological data from 600 automatic weather stations through the Korea Meteorological Administration. The segmented regression model was used to estimate the effects of the temperature-humidity index (THI) on milk traits and elucidate the break point (BP) of the THI. To acquire the least-squares mean of milk traits, the generalized linear model was applied using fixed effects (region, calving year, calving month, parity, days in milk, and THI). For all parameters, the BP of THI was observed; in particular, milk production parameters dramatically decreased after a specific BP of THI (p < 0.05). In contrast, MUN and SCS drastically increased when THI exceeded BP in all cows (p < 0.05) and primiparous cows (p < 0.05), respectively. Dairy cows in South Korea exhibited negative effects on milk traits (decrease in milk performance, increase in MUN, and SCS) when the THI exceeded 70; therefore, detailed feeding management is required to prevent heat stress in dairy cows.

• Smart Structures and Systems
• /
• v.32 no.1
• /
• pp.23-35
• /
• 2023

Steel bolted joint is an important part of steel structure, and its damage directly affects the bearing capacity and durability of steel structure. Currently, the existing research mainly focuses on the identification of corroded bolts and corroded bolts respectively, and there are few studies on multiple states. A detection framework of corroded and loosened bolts is proposed in this study, and the innovations can be summarized as follows: (i) Vision Transformer (ViT) is introduced to replace the third and fourth C3 module of you-only-look-once version 5s (YOLOv5s) algorithm, which increases the attention weights of feature channels and the feature extraction capability. (ii) Three states of the steel bolts are considered, including corroded bolt, bolt missing and clean bolt. (iii) Line segment detector (LSD) is introduced for bolt rotation angle calculation, which realizes bolt looseness detection. The improved YOLOv5s model was validated on the dataset, and the mean average precision (mAP) was increased from 0.902 to 0.952. In terms of a lab-scale joint, the performance of the LSD algorithm and the Hough transform was compared from different perspective angles. The error value of bolt loosening angle of the LSD algorithm is controlled within 1.09%, less than 8.91% of the Hough transform. Furthermore, the proposed framework was applied to fullscale joints of a steel bridge in China. Synthetic images of loosened bolts were successfully identified and the multiple states were well detected. Therefore, the proposed framework can be alternative of monitoring steel bolted joints for management department.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.16 no.6
• /
• pp.369-377
• /
• 2023

In the industrial manufacturing sector, quality control is pivotal for minimizing defect rates; inadequate management can result in additional costs and production delays. This study underscores the significance of detecting texture defects in manufactured goods and proposes a more precise defect detection technique. While the DFR(Deep Feature Reconstruction) model adopted an approach based on feature map amalgamation and reconstruction, it had inherent limitations. Consequently, we incorporated a new loss function using statistical methodologies, integrated a skip connection structure, and conducted parameter tuning to overcome constraints. When this enhanced model was applied to the texture category of the MVTec-AD dataset, it recorded a 2.3% higher Defect Segmentation AUC compared to previous methods, and the overall defect detection performance was improved. These findings attest to the significant contribution of the proposed method in defect detection through the reconstruction of feature map combinations.

• Information Systems Review
• /
• v.22 no.1
• /
• pp.91-111
• /
• 2020

E-book markets are currently moving through a period of disequilibrium as new pricing structures (i.e., flat-fee subscriptions) are rapidly embraced by major vendors. On the basis of a novel dataset, we investigate how the availability of "all-you-can-read" pricing programs influences consumers' tariff choice and contract renewal behaviors. Consistent with the rational choice framework, the findings suggest that most e-book consumers significantly gain from subscription-based tariffs. Power readers prefer flat-fee subscriptions, and those that have economically benefited renew their subscription. However, we also find some other intriguing results. Among the three subscription designs examined, the 1-week plan affords consumers more economic benefits than do 1-day or 1-month programs. Finally, iOS users are more inclined to select subscription models than are Android users because of the absence of in-app purchase functionalities for the former. The unavailability of in-app purchase affects tariff choices and transaction patterns as it increases transaction costs.

• Information Systems Review
• /
• v.22 no.3
• /
• pp.81-97
• /
• 2020

Recent trends in sentiment analysis have been focused on applying single label classification approaches. However, when considering the fact that a review comment by one person is usually composed of several topics or aspects, it would be better to classify sentiments for those aspects respectively. This paper has two purposes. First, based on the fact that there are various aspects in one sentence, aspect mining is performed to classify the emotions by each aspect. Second, we apply the multiple label classification method to analyze two or more dependent variables (output values) at once. To prove our proposed approach's validity, online review comments about musical performances were garnered from domestic online platform, and the multi-label classification approach was applied to the dataset. Results were promising, and potentials of our proposed approach were discussed.