• Clinical Pain
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• v.18 no.2
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• pp.92-96
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• 2019

Torticollis is an abnormal, asymmetric head or neck position which usually caused by imbalance of paracervical muscles. The traumatic torticollis can be caused by following events; atlantoaxial rotatory subluxation, atlantoaxial dislocation, cervical vertebral fractures, and injury to the cervical musculature. Especially, acute traumatic atlantoaxial rotatory subluxation usually presents limitation of cervical range of motion without pain or neurologic deficit. We report a case of a 58 year-old man who developed the acute atlantoaxial rotatory subluxation right after the chiropractic therapy, which induced the limitation of cervical range of motion to 52.5% of normal range. The magnetic resonance image revealed the facture of the odontoid process and the partial injury in transverse ligaments of the atlas. He underwent intramuscular botulinum toxin injection and 10 days of continuous cervical traction 15 hours a day using a 5 kg weight. The range of the cervical motion restored up to 90.2% of normal range.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.5
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• pp.37-49
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• 2023

The drought risk has been increasing recently due to climate change causing the extreme climate to be more frequent. In order to supply agricultural water stably under drought, it is necessary to operate an agricultural reservoir in response to drought. To this end, it is crucial to establish appropriate drought response operation rules considering weather conditions and reservoir status. In the reservoir operation simulation, the supply amount differs from the actual reservoir supply for many reasons, including maintaining water levels for supply and accommodating farmers' requests. So, for a more realistic reservoir operation simulation, it is necessary to reflect the reservoir operation rules of the actual water management site. Therefore, in this study, through a survey, the standards for limitation of agricultural water supply applied to agricultural reservoirs in Korea were investigated, and the criteria for drought response reservoir operation (DRO) were established based on the survey. Then, the DRO was applied to the irrigation period for nine subject reservoirs. The applicability was evaluated by comparing the DRO result to the operation result of HOMWRS (Hydrological Operation Model for Water Resources System). The reservoir drought index, storage rate, and daily supply were compared for evaluation. From the result, DRO showed more stable operation results in most cases against drought as it has fewer days of water supply limitation and a somewhat reservoir storage rate which can be utilized for prolonged drought.

• Land and Housing Review
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• v.14 no.4
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• pp.95-102
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• 2023

Numerous investigations have explored the integration of machine leaning algorithms with high-resolution drone image for object detection in urban settings. However, a prevalent limitation in vehicle extraction studies involves the reliance on bounding boxes rather than instance segmentation. This limitation hinders the precise determination of vehicle direction and exact boundaries. Instance segmentation, while providing detailed object boundaries, necessitates labour intensive labelling for individual objects, prompting the need for research on automating unsupervised instance segmentation in vehicle extraction. In this study, a novel approach was proposed for vehicle extraction utilizing unsupervised SVM classification applied to vehicle bounding boxes in drone images. The method aims to address the challenges associated with bounding box-based approaches and provide a more accurate representation of vehicle boundaries. The study showed promising results, demonstrating an 89% accuracy in vehicle extraction. Notably, the proposed technique proved effective even when dealing with significant variations in spectral characteristics within the vehicles. This research contributes to advancing the field by offering a viable solution for automatic and unsupervised instance segmentation in the context of vehicle extraction from image.

• Journal of Biomedical Engineering Research
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• v.45 no.2
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• pp.90-94
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• 2024

Diagnosing wounds presents a significant challenge in clinical settings due to its complexity and the subjective assessments by clinicians. Wound deep learning algorithms quantitatively assess wounds, overcoming these challenges. However, a limitation in existing research is reliance on specific datasets. To address this limitation, we created a comprehensive dataset by combining open dataset with self-produced dataset to enhance clinical applicability. In the annotation process, machine learning based on Gradient Vector Flow (GVF) was utilized to improve objectivity and efficiency over time. Furthermore, the deep learning model was equipped U-net with residual blocks. Significant improvements were observed using the input dataset with images cropped to contain only the wound region of interest (ROI), as opposed to original sized dataset. As a result, the Dice score remarkably increased from 0.80 using the original dataset to 0.89 using the wound ROI crop dataset. This study highlights the need for diverse research using comprehensive datasets. In future study, we aim to further enhance and diversify our dataset to encompass different environments and ethnicities.

• Physical Therapy Korea
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• v.31 no.1
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• pp.72-78
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• 2024

Background: Limitations of shoulder range of motion (ROM), particularly shoulder internal rotation (SIR), are commonly associated with musculoskeletal disorders in both the general population and athletes. The limitation can result in connective tissue lesions such as superior labrum tears and symptoms such as rotator cuff tears and shoulder impingement syndrome. Maintaining the center of rotation of the glenohumeral joint during SIR can be challenging due to the compensatory scapulothoracic movement and anterior displacement of the humeral head. Therefore, observing the path of the instantaneous center of rotation (PICR) using the olecranon as a marker during SIR may provide valuable insights into understanding the dynamics of the shoulder joint. Objects: The aim of the study was to compare the displacement of the olecranon to measure the rotation control of the humeral head during SIR in individuals with and without restricted SIR ROM. Methods: Twenty-four participants with and without restricted SIR ROM participated in this study. The displacement of olecranon was measured during the shoulder internal rotation control test (SIRCT) using a Kinovea (ver. 0.8.15, Kinovea), the 2-dimensional marker tracking analysis system. An independent t-test was used to compare the horizontal and vertical displacement of the olecranon marker between individuals with and without restricted SIR ROM. The statistical significance was set at p < 0.05. Results: Vertical displacement of the olecranon was significantly greater in the restricted SIR group than in the control group (p < 0.05). However, no significant difference was observed in the horizontal displacement of the olecranon (p > 0.05). Conclusion: The findings of this study indicated that individuals with restricted SIR ROM had significantly greater vertical displacement of the olecranon. The results suggest that the limitation of SIR ROM may lead to difficulty in rotation control of the humeral head.

• Journal of Science Education
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• v.48 no.1
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• pp.63-73
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• 2024

Knowing the learner's image of a subject-related occupation is good data for determining the direction of a teacher's teaching and learning. Existing drawing image analysis tools have the limitation that it takes a long time to analyze images and drawings of a scientist's appearance. The semantic differential method is a widely used method to analyze images of specific objects. However, research using the semantic differential method has the limitation of failing to reflect terms or factors that change over time by using the adjective pairs used in the initial study as they were in accordance with the research content. In this study, we use the semantic differential method to develop a tool to measure middle school students' scientist image and apply it to middle school students to discuss educational implications regarding the usefulness of measuring scientist image.

• Information Systems Review
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• v.19 no.1
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• pp.49-74
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• 2017

The development of smart devices has affected employees' working environments and their lives. However, using smart devices is causing employees to experience technostress. This study aims to investigate the effects of technostress in using smart devices on usage intention in an organization. Moreover, the study investigates the effect of employees' stress-coping methods on the intention to use smart devices. This study posits familiarity, use innovativeness, role ambiguity, system vulnerability, technological limitation, and ubiquity as the antecedents of technostress. Data collected from 317 users who have experience in using smart devices in organizations are empirically tested against a research model using the PLS graph. Analysis results show that role ambiguity, system vulnerability, and technological limitation significantly influence technostress. Moreover, users take up emotion-focused coping behaviors because of technostress. Emotion-focused coping behaviors affect usage intention in organizations. However, technostress and problem-focused coping behaviors do not directly affect usage intention in organizations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.6
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• pp.1692-1705
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• 2024

In this paper, we present a method that integrates a Grammar Transducer as an external language model to enhance the accuracy of the pre-trained Korean End-to-end (E2E) Automatic Speech Recognition (ASR) model. The E2E ASR model utilizes the Connectionist Temporal Classification (CTC) loss function to derive hypothesis sentences from input audio. However, this method reveals a limitation inherent in the CTC approach, as it fails to capture language information from transcript data directly. To overcome this limitation, we propose a fusion approach that combines a clause-level n-gram language model, transformed into a Weighted Finite-State Transducer (WFST), with the E2E ASR model. This approach enhances the model's accuracy and allows for domain adaptation using just additional text data, avoiding the need for further intensive training of the extensive pre-trained ASR model. This is particularly advantageous for Korean, characterized as a low-resource language, which confronts a significant challenge due to limited resources of speech data and available ASR models. Initially, we validate the efficacy of training the n-gram model at the clause-level by contrasting its inference accuracy with that of the E2E ASR model when merged with language models trained on smaller lexical units. We then demonstrate that our approach achieves enhanced domain adaptation accuracy compared to Shallow Fusion, a previously devised method for merging an external language model with an E2E ASR model without necessitating additional training.

• Tuberculosis and Respiratory Diseases
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• v.87 no.2
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• pp.165-175
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• 2024

Background: The prevalence of small airway dysfunction (SAD) in patients with chronic obstructive pulmonary disease (COPD) across different ethnicities is poorly understood. This study aimed to estimate the prevalence of SAD in stable COPD patients. Methods: We conducted a cross-sectional study of 196 consecutive stable COPD patients. We measured pre- and post-bronchodilator (BD) lung function and respiratory impedance. The severity of COPD and lung function abnormalities was graded in accordance with the Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. SAD was defined as either difference in whole-breath resistance at 5 and 19 Hz > upper limit of normal or respiratory system reactance at 5 Hz < lower limit of normal. Results: The cohort consisted of 95.9% men, with an average age of 66.3 years. The mean forced expiratory volume 1 second (FEV₁) % predicted was 56.4%. The median COPD assessment test (CAT) scores were 14. The prevalence of post-BD SAD across the GOLD grades 1 to 4 was 14.3%, 51.1%, 91%, and 100%, respectively. The post-BD SAD and expiratory flow limitation at tidal breath (EFL_T) were present in 62.8% (95% confidence interval [CI], 56.1 to 69.9) and 28.1% (95% CI, 21.9 to 34.2), respectively. COPD patients with SAD had higher CAT scores (15.5 vs. 12.8, p<0.01); poor lung function (FEV₁% predicted 46.6% vs. 72.8%, p<0.01); lower diffusion capacity for CO (4.8 mmol/min/kPa vs. 5.6 mmol/min/kPa, p<0.01); hyperinflation (ratio of residual volume to total lung capacity % predicted: 159.7% vs. 129%, p<0.01), and shorter 6-minute walk distance (367.5 m vs. 390 m, p=0.02). Conclusion: SAD is present across all severities of COPD. The prevalence of SAD increases with disease severity. SAD is associated with poor lung function and higher symptom burden. Severe SAD is indicated by the presence of EFL_T.

• Journal of Platform Technology
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• v.12 no.1
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• pp.151-163
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• 2024

The Privacy Impact Assessment, PIPA in Korea refers to the process of analyzing risk factors and identifying improvements that must be carried out by organizations that operate personal information files as stipulated in Article 33 of the Personal Information Protection Act, PIPA and Article 35 of the Enforcement Decree of the PIPA. There are two main limitations of the PIA in Korea. The first limitation is that the targets of the PIA are limited to public institutions and organizations that are legally equivalent to public institutions, and the second limitation is that only organizations with adequate manpower, facilities, and other necessary requirements which are regulated upon the Enforcement Decree of the PIPA can conduct a PIA. This paper proposes to develop a preliminary diagnostic tool that can be performed by private companies, small and medium-sized venture companies, and small businesses in the era of rapidly developing data in recent years and presents an analysis of specific assessment factors. The results of this study are provided in the form of a self-checklist, which is expected to serve as a pre-diagnostic tool for the PIA that can be easily accessed by the general public. It is also expected to contribute to strengthening privacy protection and achieving legal compliance at the national level.