• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.3
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• pp.161-173
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• 2020

This study analyzed local imbalances in the supply and demand of emergency medical services in Busan using the 119 emergency activity reports of the Busan Fire & Disaster Headquarters. The data for EMS activity reports in 2017 was converted into Jimgyegu units. The spatial distribution of the indicators representing the local imbalance of emergency demand and supply (number of reports, number of reports relative to the population, average coefficient of variation and outlier of on-site arrival time, and number of dispatches outside the jurisdiction) was analyzed using Hotspot analysis of GIS spatial statistics analysis. As a result of the analysis, the hot spot area and the cold spot area where both supply and demand of emergency services are concentrated were clearly distinguished. This means that the supply and demand of emergency services in Busan are locally unbalanced. In particular, there was a difference in the demand and supply of emergency services in the original downtown and its surrounding areas, and in the outskirts of Busan.

• The Research Journal of the Costume Culture
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• v.21 no.2
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• pp.220-233
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• 2013

This study examined regarding the moderating effect of length of relationship in the relationship among the antecedent variables (i.e., specific investment, opportunistic behavior, communication, uncertainty, interdependence, power imbalance, shared value, and flexibility) of trust and commitment, trust and commitment and firm performance and relationship satisfaction. A total of 128 apparel manufacturers participated in this study. Flexibility exerted the most positive effect on trust in short-term relationship, followed by specific investment. And opportunistic behavior was found to exert negative effect on trust. Commitment was found to be most negatively affected by power imbalance, followed by interdependence. Trust was shown to be significantly affected by communication, shared value and flexibility in short-term relationship. In the case of long-term relationship, commitment was shown to be significantly affected by uncertainty, interdependence, power imbalance and flexibility. Firm performance was positively affected by both trust and commitment. As for the effect of trust and commitment on relationship satisfaction, relationship satisfaction was also affected by both trust and commitment. In case the length of relationship, firm performance was affected by both trust and commitment. As for the effect of trust and commitment on relationship satisfaction, relationship satisfaction was also affected by both trust and commitment. The result of this research provides valuable data for making a concrete suggestion regarding the strategy for improving trust and commitment for the sake of the desirable relationship between apparel manufacturers and contractors.

• Safety and Health at Work
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• v.8 no.1
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• pp.77-83
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• 2017

Background: In contemporary China, most parents are dual-earner couples and there is only one child in the family. We aimed to examine the associations of parents' work stress with suicidal ideation among the corresponding adolescent. We further hypothesized that low parental support experienced by adolescents may mediate the associations. Methods: Cross-sectional data from school students and their working parents were used, with 907 families from Kunming City, China. Stress at work was measured by the effort-reward imbalance questionnaire. Perceived parental support was assessed by an item on parental empathy and their willingness to communicate with the adolescent. Suicidal ideation was considered positive if students reported thoughts about suicide every month or more frequently during the previous 6 months. Logistic regression was used to examine the associations. Results: We observed that parents' work stress was positively associated with low parental support, which was in turn associated with adolescent suicidal ideation. The odds ratio for parents' work stress and adolescent suicidal ideation was 2.91 (95% confidence interval: 1.53-5.53), and this association was markedly attenuated to 2.24 (95% confidence interval: 1.15-4.36) after additional adjustment for parental support. Notably, mothers' work stress levels exerted stronger effects on children's suicidal ideation than those of fathers. Conclusion: Parents' work stress (particularly mother's work stress) was strongly associated with adolescent's suicidal ideation, and the association was partially mediated by low parental support. These results need to be replicated and extended in prospective investigations within and beyond China, in order to explore potential causal pathways as a basis of preventive action.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.440-448
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• 2022

Recently, due to the introduction of distributed energy resources, the optimal resource allocation problem of the power network is more and more important, and the distributed resource allocation method is required to process huge amount of data in large-scale power networks. In the optimal resource allocation problem, many studies have been conducted on the case when the supply-demand balance is satisfied due to the limitation of the generation capacity of each generator, but the studies considering the supply-demand imbalance, that total demand exceeds the maximum generation capacity, have rarely been considered. In this paper, we propose the consensus-based distributed algorithm for the optimal resource allocation of power network considering the supply-demand imbalance condition as well as the supply-demand balance condition. The proposed distributed algorithm is designed to allocate the optimal resources when the supply-demand balance condition is satisfied, and to measure the amount of required resources when the supply-demand is imbalanced. Finally, we conduct the simulations to verify the performance of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2429-2449
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• 2018

Dynamic data possession verification is a common requirement in cloud storage systems. After the client outsources its data to the cloud, it needs to not only check the integrity of its data but also verify whether the update is executed correctly. Previous researches have proposed various schemes based on Merkle Hash Tree (MHT) and implemented some initial improvements to prevent the tree imbalance. This paper tries to take one step further: Is there still any problems remained for optimization? In this paper, we study how to raise the efficiency of data dynamics by improving the parts of query and rebalancing, using a new data structure called Rank-Based Merkle AVL Tree (RB-MAT). Furthermore, we fill the gap of verifying multiple update operations at the same time, which is the novel batch updating scheme. The experimental results show that our efficient scheme has better efficiency than those of existing methods.

• Journal of Broadcast Engineering
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• v.17 no.5
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• pp.742-755
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• 2012

In this paper, we propose a parallel deblocking algorithm to resolve workload imbalance when the deblocking filter of high efficiency video coding (HEVC) decoder is parallelized. In HEVC, the deblocking filter which is one of the in-loop filters conducts two-step filtering on vertical edges first and horizontal edges later. The deblocking filtering can be conducted with high-speed through data-level parallelism because there is no dependency between adjacent edges for deblocking filtering processes. However, workloads would be imbalanced among regions even though the same amount of data for each region is allocated, which causes performance loss of decoder parallelization. In this paper, we solve the problem for workload imbalance by predicting the complexity of deblocking filtering with coding unit (CU) depth information at a coding tree block (CTB) and by allocating the same amount of workload to each core. Experimental results show that the proposed method achieves average time saving (ATS) by 64.3%, compared to single core-based deblocking filtering and also achieves ATS by 6.7% on average and 13.5% on maximum, compared to the conventional uniform data-level parallelism.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.7
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• pp.1457-1467
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• 2015

Depending on the type of Tx-Rx pairs, VHF Data Exchange System (VDES) for maritime communication is expected to employ the different frequency channels. Load imbalance between the different channels turns out to be a critical problem for the multi-hop communication using Ad-hoc Self-Organizing TDMA (ASO-TDMA) MAC protocol, which has been proposed to provide the connectivity between land station and remote ship stations. In order to handle the inter-channel load imbalance problem, we consider a model of the stochastic geomety in this paper. After analyzing the spatial reuse efficiency in each hop region by the given model, we show that the resource utility can be maximized by balancing the inter-channel traffic load with optimal resource allocation in each hop region.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.4
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• pp.135-142
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• 2023

Recently, many companies are using public cloud services or building their own data center because digital transformation is expanding. The software-defined storage is a key solution for storing data on the cloud platform and its use is expanding worldwide. Software-defined storage has the advantage of being able to virtualize and use all storage resources as a single storage device and supporting flexible scale-out. On the other hand, since the size of an object is variable, an imbalance occurs in the use of the disk and may cause a failure. In this study, a method of redistributing objects by optimizing disk weights based on storage state information was proposed to solve the imbalance problem of disk use, and the experimental results were presented. As a result of the experiment, it was confirmed that the maximum utilization rate of the disk decreased by 10% from 89% to 79%. Failures can be prevented, and more data can be stored by optimizing the use of disk.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.15-25
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• 2024

For effective analysis of animal ecosystems, technology that can automatically identify the current status of animal habitats is crucial. Specifically, animal sound classification, which identifies species based on their sounds, is gaining great attention where video-based discrimination is impractical. Traditional studies have relied on a single deep learning model to classify animal sounds. However, sounds collected in outdoor settings often include substantial background noise, complicating the task for a single model. In addition, data imbalance among species may lead to biased model training. To address these challenges, in this paper, we propose an animal sound classification scheme that combines predictions from multiple models using Focal Loss, which adjusts penalties based on class data volume. Experiments on public datasets have demonstrated that our scheme can improve recall by up to 22.6% compared to an average of single models.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.47-55
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• 2024

We spend a lot of time in indoor space, and the space has a huge impact on our lives. Interior design plays a significant role to make an indoor space attractive and functional. However, it should consider a lot of complex elements such as color, pattern, and material etc. With the increasing demand for interior design, there is a growing need for technologies that analyze these design elements accurately and efficiently. To address this need, this study suggests a deep learning-based design analysis system. The proposed system consists of a semantic segmentation model that classifies spatial components and an image classification model that classifies attributes such as color, pattern, and material from the segmented components. Semantic segmentation model was trained using a dataset of 30000 personal indoor interior images collected for research, and during inference, the model separate the input image pixel into 34 categories. And experiments were conducted with various backbones in order to obtain the optimal performance of the deep learning model for the collected interior dataset. Finally, the model achieved good performance of 89.05% and 0.5768 in terms of accuracy and mean intersection over union (mIoU). In classification part convolutional neural network (CNN) model which has recorded high performance in other image recognition tasks was used. To improve the performance of the classification model we suggests an approach that how to handle data that has data imbalance and vulnerable to light intensity. Using our methods, we achieve satisfactory results in classifying interior design component attributes. In this paper, we propose indoor space design analysis system that automatically analyzes and classifies the attributes of indoor images using a deep learning-based model. This analysis system, used as a core module in the A.I interior recommendation service, can help users pursuing self-interior design to complete their designs more easily and efficiently.