• Clinical Psychopharmacology and Neuroscience
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• v.16 no.4
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• pp.449-460
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• 2018

Objective: Prior functional magnetic resonance imaging (fMRI) work has revealed that children/adolescents with disruptive behavior disorders (DBDs) show dysfunctional reward/non-reward processing of non-social reinforcements in the context of instrumental learning tasks. Neural responsiveness to social reinforcements during instrumental learning, despite the importance of this for socialization, has not yet been previously investigated. Methods: Twenty-nine healthy children/adolescents and 19 children/adolescents with DBDs performed the fMRI social/non-social reinforcement learning task. Participants responded to random fractal image stimuli and received social and non-social rewards/non-rewards according to their accuracy. Results: Children/adolescents with DBDs showed significantly reduced responses within the caudate and posterior cingulate cortex (PCC) to non-social (financial) rewards and social non-rewards (the distress of others). Connectivity analyses revealed that children/adolescents with DBDs have decreased positive functional connectivity between the ventral striatum (VST) and the ventromedial prefrontal cortex (vmPFC) seeds and the lateral frontal cortex in response to reward relative to non-reward, irrespective of its sociality. In addition, they showed decreased positive connectivity between the vmPFC seed and the amygdala in response to non-reward relative to reward. Conclusion: These data indicate compromised reinforcement processing of both non-social rewards and social non-rewards in children/adolescents with DBDs within core regions for instrumental learning and reinforcement-based decision-making (caudate and PCC). In addition, children/adolescents with DBDs show dysfunctional interactions between the VST, vmPFC, and lateral frontal cortex in response to rewarded instrumental actions potentially reflecting disruptions in attention to rewarded stimuli.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.33 no.1
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• pp.2-15
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• 2022

Objectives: Children with attention-deficit/hyperactivity disorder (ADHD) tend to be noisy and violate rules with their disruptive behaviors, resulting in greater difficulties with off-task behaviors and being at risk for social refusal. The visual activity schedule (VAS) intervention program is a frequently used method to teach multiple skills involving on-task, use of schedules, transition behaviors, social initiation, independent play skills, classroom skills, and academic skills. The current systematic review aimed to examine the efficacy of using VAS intervention in reducing problem behaviors in children with ADHD between 5 and 12 years of age. Methods: Systematic searches were conducted using two electronic databases (PubMed and Scopus) to identify relevant studies published in English between 2010 and 2020. Four studies met the inclusion criteria: two studies examined the effect of schedule-based tasks and the use of an iPad on classroom skills, while the other two examined randomized clinical trials (RCTs) of psychosocial treatment for ADHD inattentive type and a cross-sectional study examined the impact of the group size on task behavior and work productivity in children with ADHD. Results: The findings indicate that the interventions used in all four studies could lead to increased satisfaction among participants and parents, as well as a reduction in problem behavior. In terms of the research indicators, the RCT had low quality, while the others were of high quality. Conclusion: A larger number of studies and the ADHD clinical population would help to increase the generalizability of future reviews of treatments in this context.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.29-49
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• 2022

Consumers are now no longer satisfied with using a single channel to shop and then desire a smooth and consistent purchasing experience across channels. By integrating different channels and services, an omni-channel strategy allows consumers to choose their preferred channel to complete their shopping tasks. Therefore, large retailers in China have recently been transforming into omni-channel retail formats to secure their competitive advantage. To better implement this strategy and optimize its effectiveness, it is important to understand how consumers respond to the quality of channel integration. Based on social exchange theory (SET), the main purposes of this study are to explore the impact of channel integration quality on consumer engagement in the Chinese omni-channel retailing environment and to further examine whether there is a moderating effect of consumer empowerment on this relationship. To test this research model, we collected data from 330 respondents by conducting an online questionnaire in China. The results indicated that the two dimensions of channel integration (breadth of channel-service choice and transparency of channel-service configuration) positively affected two dimensions of customer engagement (conscious attention and enthusiastic participation), respectively. The findings also show that consumer empowerment only positively moderates the relationship between breadth of channel service choice and conscious attention, whereas it negatively moderates the relationship between transparency of channel-service configuration and conscious attention/enthusiastic participation. Given these results, this study deepens our understanding of the impact of the quality of channel integration on customer engagement in the context of omni-channel retailing in China and sheds light on how retailers can attract consumers with different levels of empowerment.

• Smart Structures and Systems
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• v.31 no.4
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• pp.351-363
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• 2023

Visual structural inspections are an inseparable part of post-earthquake damage assessments. With unmanned aerial vehicles (UAVs) establishing a new frontier in visual inspections, there are major computational challenges in processing the collected massive amounts of high-resolution visual data. We propose twin deep learning models that can provide accurate high-resolution structural components and damage segmentation masks efficiently. The traditional approach to cope with high memory computational demands is to either uniformly downsample the raw images at the price of losing fine local details or cropping smaller parts of the images leading to a loss of global contextual information. Therefore, our twin models comprising Trainable Resizing for high-resolution Segmentation Network (TRS-Net) and DmgFormer approaches the global and local semantics from different perspectives. TRS-Net is a compound, high-resolution segmentation architecture equipped with learnable downsampler and upsampler modules to minimize information loss for optimal performance and efficiency. DmgFormer utilizes a transformer backbone and a convolutional decoder head with skip connections on a grid of crops aiming for high precision learning without downsizing. An augmented inference technique is used to boost performance further and reduce the possible loss of context due to grid cropping. Comprehensive experiments have been performed on the 3D physics-based graphics models (PBGMs) synthetic environments in the QuakeCity dataset. The proposed framework is evaluated using several metrics on three segmentation tasks: component type, component damage state, and global damage (crack, rebar, spalling). The models were developed as part of the 2^nd International Competition for Structural Health Monitoring.

• 재활복지
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• v.14 no.3
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• pp.95-119
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• 2010

This study aims to develope participation scale of people with disabilities according to the International classification of Functioning, Disability, and Health(ICF). ICF includes a component for classifying and qualifying participation of individuals in the context of their environments. The participation scale were developed using 7 times with different focus groups using the ICIDH-2 as a contextual framework. Candidate 41 items were developed based on the 8 participation components and put into a survey format. Finally, purposeful sample of 363 people with mobility limitations was conducted survey. As a result of survey, participation scale is composed of 38 items that are placed in 7 domains used in the activity/participation component of the ICF: holisitc health; communication; mobility; domestic life; interpersonal interactions and relationships; social and economic life; civic life. This scale does not include the domains of learning and applying knowledge, general tasks and demands, recreation and leisure but more focuses on social and civic life.

• The Journal of the Acoustical Society of Korea
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• v.25 no.7
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• pp.312-318
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• 2006

The conventional lip-synch system has a two-step process, speech segmentation and recognition. However, the difficulty of speech segmentation procedure and the inaccuracy of training data set due to the segmentation lead to a significant Performance degradation in the system. To cope with that, the connected vowel recognition method using Head-Body-Tail (HBT) model is proposed. The HBT model which is appropriate for handling relatively small sized vocabulary tasks reflects co-articulation effect efficiently. Moreover the 7 vowels are merged into 3 classes having similar lip shape while the system is optimized by employing a class dependent SCHMM structure. Additionally in both end sides of each word which has large variations, 8 components Gaussian mixture model is directly used to improve the ability of representation. Though the proposed method reveals similar performance with respect to the CHMM based on the HBT structure. the number of parameters is reduced by 33.92%. This reduction makes it a computationally efficient method enabling real time operation.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.4
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• pp.701-708
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• 2024

The advent of transformer architectures in deep learning has been a major breakthrough in natural language processing research. Object name recognition is a branch of natural language processing and is an important research area for tasks such as information retrieval. It is also important in the biomedical field, but the lack of Korean biomedical corpora for training has limited the development of Korean clinical research using AI. In this study, we built a new biomedical corpus for Korean biomedical entity name recognition and selected language models pre-trained on a large Korean corpus for transfer learning. We compared the name recognition performance of the selected language models by F1-score and the recognition rate by tag, and analyzed the errors. In terms of recognition performance, KlueRoBERTa showed relatively good performance. The error analysis of the tagging process shows that the recognition performance of Disease is excellent, but Body and Treatment are relatively low. This is due to over-segmentation and under-segmentation that fails to properly categorize entity names based on context, and it will be necessary to build a more precise morphological analyzer and a rich lexicon to compensate for the incorrect tagging.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.573-578
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• 2008

Recently, we should control various devices such as TV, audio, DVD player, video player, and set-top box simultaneously to manipulate home theater system. To execute the function the user want in this situation, user should know functions and positions of the buttons in several remote controllers. Normally, people feel difficult due to these realistic problems. Besides, the number of the devices that we can control shall increase, and people will confuse more if the ubiquitous home environment is realized. Therefore, user adaptive interface that provides the summarized functions is required. Moreover there can be a lot of mobile and stationary controller devices in ubiquitous computing environment, so user interface should be adaptive in selecting the functions that user wants and in adjusting the features of UI to fit in specific controller. To implement the user and controller adaptive interface, we modeled the ubiquitous home environment and used modeled context and device information. We have used Bayesian network to get the degree of necessity in each situation. Behavior selection network uses predicted user situation and the degree of necessity, and it selects necessary functions in current situation. Selected functions are used to construct adaptive interface for each controller using presentation template. For experiments, we have implemented ubiquitous home environment and generated controller usage log in this environment. We have confirmed the BN predicted user requirements effectively as evaluating the inferred results of controller necessity based on generated scenario. Finally, comparing the adaptive home UI with the fixed one to 14 subjects, we confirmed that the generated adaptive UI was more useful for general tasks than fixed UI.

• Journal of Korea Entertainment Industry Association
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• v.14 no.7
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• pp.599-608
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• 2020

This study aims to investigate the performance and satisfaction of occupational therapists at the Dementia Relief Center for health care of the elderly in local communities, and to provide basic data necessary for role establishment by checking occupational therapists' tasks according to the priority. The subjects of this study were occupational therapists in dementia care centers in the Honam area and Gwangju Metropolitan City, who were surveyed via mail and e-mail. The survey had a total of 54 items covering the general characteristics of the therapists and current state of the centers (n=8), performance and satisfaction with the service areas and task content of the centers (n=45), and tasks that were considered important (one short-answer question). It was found that occupational therapists at the Dementia Relief Center were mainly carrying out the "Dementia Prevention Management Projects", which provided the programs for the patients, and they showed the highest satisfaction. Although the 'MMSE-DS' is occupational therapists' own area with high performance and satisfaction, it was not assigned to the occupational therapists at the Dementia Relief Center, indicating that the role was insufficient. The tasks related "administrative works and strengthening community capacities" showed low performance and satisfaction, but they are essential for the operation of the Dementia Relief Center and the management of the patients, so the plans to increase the occupational therapists' performance should be established. The categories of projects that occupational therapists consider important were also consistent with those they had to perform. It means the occupational therapists at the Dementia Relief Center recognized their unique roles. In this context, to establish the role of occupational therapist at the Dementia Relief Center, it is necessary to amend the operating guidelines based on the performance, satisfaction, and priorities of the projects, and to develop the curriculums and programs that can improve the tasks with insufficient performance and low satisfaction.

• The Korean Journal of Archival Studies
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• no.48
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• pp.45-92
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• 2016

Corporations report their economical, environmental, social influences and achievements through sustainability reports. Apart from the financial reports, which are subject to legal restrictions, sustainability reports inform non financial achievements of a corporation, thus the reliability of the information is solely dependent on the corporation itself. The current sustainability reports are of types that cannot include proof or source of the index data, thus they are tended to be regarded as means of publicity. The reliability of the reports is often questioned. This research applied the concept of Evidence-Based Accountability, which will allow the confirmation of accountability through records including contents and context of the tasks. Evidence-Based Accountability means producing and accumulating witness records of actions, then managing the records as usable information and use them as accountability information. Index data from sustainability reports of domestic corporations and web based reports of Vodafone was reviewed. Measures to link task records as proof of index data was studied. To make this possible, record production and acquisition system was redesigned in order to secure required records as evidence. Linked build-up of SR system and RMS was proposed. The proposed system will allow collection and management of records as SR accountability information, and provide the data when necessary. Also, corporate infrastructure was proposed. This infrastructure will build a professional records management system in stages, through organizational system and regulations. Cooperation of staff in this infrastructure will support reliable corporate accountability.