• 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.

• Journal of Haehwa Medicine
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• v.18 no.2
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• pp.13-20
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• 2009

Objectives : In order to investigate change of isokinetic trunk muscle strength according to decrease of body composition analysis parameter after obesity treatment. Methods : 2 obese patients have been treated with oriental medical obese treatment for 1 month. One patient got the exercise treatment, another didn't. Before and after treatment, the segmental bioelectrical impedance analysis, isokinetic trunk muscle strength test were performed. Then we analyzed the relationship of data. Results : After obesity treatment, BMI(Body Mass Index), PBF(Percentage of Body Fat), WHR(Waist Hip Ratio) were decreased in all patient and LBM(Lean Body Mass) was increased. In non-exercise patient, Ext.PT(extension Peak Torque) was decreased and Flex.PT(flexion Peak Torque) was increased. In exercise patient showed the opposite results. E/F ratio became more imbalance. Conclusions: Ext.PT was decreased in non-exercise patient but increased in exercise patient. And the trunk muscle strength became imbalance in both patients, right after the treatment. So trunk muscle exercise should be carried out and it is necessary to do long term study.

• Journal of Nutrition and Health
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• v.30 no.3
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• pp.326-335
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• 1997

In the Health Promotion Law proclaimed on January 1995, nutritional improvement at national level was emphasized and designated as one of the jobs to be carried out by local governmnets. With such a situational necessity, we conducted a dietary survey along with an anthropometric measurement, biochemical assessment and questionnaire analysis on general characteristics of the students from 3 junior higher schools in Seoul area. About 300 students had participated in the study and the data from only 139 students, 28 boys and 111 girls, with complete report of dietary intake were subjected to analysis, comparison and discussion. Fasting blood samples were drawn and analyzed for hemoglobin, hematocrit and total cholesterol. Dietary intake was monitored by 1-day 24hr recall +2-day food record. In general, the average intake of nutrients for most of the subjects were above RDA for korean of that age except for 2 nutrients namely, vitamin A and calcium, of which average intake corresponded to 46-69% of RDA. In addition to this kind of nutritional imbalance, there were several other factors of nutritional problems such as skipping breakfast, overeating at dinner and frequent eating of snacks. As the best countermeasure for these kinds of nutritional problems, more detailed campaign and prractical nutrition education for these adolescents are necessary. Only through proper education and guidance for them, the healthy and intellectual man power could be guaranteed for the forthcoming 21st century.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.1
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• pp.19-30
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• 2015

A static synchronous compensator (STATCOM) applied to rapidly changing, highly unbalanced loads such as electric arc furnaces (EAFs), requires both positive-sequence and negative-sequence current control, which indicates fast response characteristics and can be controlled independently. Furthermore, a delta-connected STATCOM with cascaded H-bridge configuration accompanying multiple separate DC-sides, should have high performance zero-sequence current control to suppress a phase-to-phase imbalance in DC-side voltages when compensating for unbalanced load. In this paper, actual EAF data is analyzed to reflect on the design of current controllers and a pioneering zero-sequence current controller with a superb transient performance is devised, which generates an imaginary -axis component from the presumed response of forwarded reference. Via simulation and experiments, the performance of the positive, negative, and zero-sequence current control of a cascaded H-bridge STATCOM for EAF is verified.

• Journal of Technology Innovation
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• v.16 no.2
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• pp.201-223
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• 2008

This paper studies the supply and demand of Industrial Technology Labor-force(ITL) and analyzes the determinate of ITL shortage in Korean manufacturing. We classified the industry into four categories-high technology industries, medium-high technology industries, medium-low technology industries and low technology industries-based on its R&D intensity like OECD. For the empirical analyses we use a survey data collected from 5,703 enterprises. The key findings are as follows: Firstly, a large majority of ITL is engaged in more technology-intensive industries but the categories that are exposed to more serious labor-force shortage problem are medium-high technology industries and low technology industries. Secondly, in the terms of supply factor, the ITL shortage problems are mainly due to the avoidance of ITL jobs. And the demand point, the reason is that the most of ITL are not researchers but production managers. Thirdly, the cause of imbalance between supply and demand of ITL are different by the technological categories. For example, in the high technology industries, the supply factors, such as average wage and turnover rate played more important role in the imbalance. But in the low technology industries the demand factors, such as per capita sales and the ratio of ITL in all employees were relatively much more important. Based on the findings, we discovered some political meanings such as the necessity to plan various policies to resolve the shortage problem of ITL according to the technological categories, etc.

• Journal of Home Health Care Nursing
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• v.27 no.2
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• pp.137-145
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• 2020

Purpose: This study aimed to identify the training system and current status of home health nurses and to examine ways to retain sufficient number of advanced practice nurses (APNs) in the home health nursing field. Methods: This study analyzed the adequacy of the supply of home health nurse by reviewing the existing research literature and statistical data. Results: Discussions on how to revitalize the home care business have been ongoing since the beginning of 2001. However, despite home health nurses being oversupplied, discussions on the adequacy of supply have always been excluded from the focus of revitalization. The recent expansion of the home care business has resulted in a shortage of workforce, which can be inked not only to the continuous reduction of the designated quota of programs but also to the regional imbalance of educational institutions. The serious imbalance between supply and demand has caused fears that the home care business would drastically reduce. Conclusion: It is necessary to not only increase designated quotas for APNs programs but also integrate those programs of the similar curricula, thus lowering supply shortages in home health nurses.