• International journal of advanced smart convergence
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• v.8 no.3
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• pp.145-150
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• 2019

Due to the development of science and technology and the emergence of new industries, the environmental change of the digital contents industry is rapidly progressing. The scope of technological development in the digital contents industry is affecting not only the entertainment industry but also various industries. Recently, with the development of digital convergence using realistic content, games, video, and VR have provided new opportunities for the growth of the content industry. The researcher determined that a new education system would need to be changed as the digital contents industry developed. For this purpose, an AHP questionnaire was conducted for experts with a high basic understanding of the education platform based on previous studies. We proposed a platform model for human resource development as an education system that meets the demand of digital contents industry. The education system for nurturing talents needed by future society should include elements that can interest the learning of users. The platform should not be approached from a system point of view, but should be developed from the content and user's point of view, considering the platform's original purpose.

• Journal of KIBIM
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• v.10 no.3
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• pp.43-53
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• 2020

BIM-based Cloud platform gained popularity coupled with the convergence of Fourth Industrial Revolution technology. However, most of the previous work has not guaranteed sufficient efficiency to meet user requirements according to BIM service. Furthermore, the Cloud environment is only used as a server and it does not consider cloud characteristics. For the processing of High Capacity Data like BIM and using seamless BIM service, Resource management technology is required in the cloud environment. In this paper, to solve the problems, we propose a BIM platform for BaaS and an efficient resource allocation scheme. We also proved the efficiency of resource for the proposed scheme by using existing schemes. By doing this, the proposed scheme looks forward to accelerating the growth of the BaaS through improving the user experience and resource efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1258-1275
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• 2023

Cloud computing is a new technology that has adapted to the traditional way of service providing. Service providers are responsible for managing the allocation of resources. Selecting suitable containers and bandwidth for job scheduling has been a challenging task for the service providers. There are several existing systems that have introduced many algorithms for resource allocation. To overcome these challenges, the proposed system introduces an Optimized Task Scheduling Algorithm with Deep Learning (OTS-DL). When a job is assigned to a Cloud Service Provider (CSP), the containers are allocated automatically. The article segregates the containers as' Long-Term Container (LTC)' and 'Short-Term Container (STC)' for resource allocation. The system leverages an 'Optimized Task Scheduling Algorithm' to maximize the resource utilisation that initially inquires for micro-task and macro-task dependencies. The bottleneck task is chosen and acted upon accordingly. Further, the system initializes a 'Deep Learning' (DL) for implementing all the progressive steps of job scheduling in the cloud. Further, to overcome container attacks and errors, the system formulates a Container Convergence (Fault Tolerance) theory with high-level security. The results demonstrate that the used optimization algorithm is more effective for implementing a complete resource allocation and solving the large-scale optimization problem of resource allocation and security issues.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.39-55
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• 2006

• ETRI Journal
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• v.37 no.2
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• pp.262-272
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• 2015

In particular, for a practical mobile robot team to perform such a task as that of carrying out a search and rescue mission in a disaster area, the network connectivity and localization have to be guaranteed even in an environment where the network infrastructure is destroyed or a Global Positioning System is unavailable. This paper proposes the new collective intelligence network management architecture of multiple mobile robots supporting seamless network connectivity and cooperative localization. The proposed architecture includes a resource manager that makes the robots move around and not disconnect from the network link by considering the strength of the network signal and link quality. The location manager in the architecture supports localizing robots seamlessly by finding the relative locations of the robots as they move from a global outdoor environment to a local indoor position. The proposed schemes assuring network connectivity and localization were validated through numerical simulations and applied to a search and rescue robot team.

• Journal of Internet Computing and Services
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• v.22 no.5
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• pp.27-33
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• 2021

With the broad adoption of the Internet of Things (IoT) in a variety of scenarios and application services, management and orchestration entities require upgrading the traditional architecture and develop intelligent models with ultra-reliable methods. In a heterogeneous network environment, mission-critical IoT applications are significant to consider. With erroneous priorities and high failure rates, catastrophic losses in terms of human lives, great business assets, and privacy leakage will occur in emergent scenarios. In this paper, an efficient resource slicing scheme for optimizing federated learning in software-defined IoT (SDIoT) is proposed. The decentralized support vector regression (SVR) based controllers predict the IoT slices via packet inspection data during peak hour central congestion to achieve a time-sensitive condition. In off-peak hour intervals, a centralized deep neural networks (DNN) model is used within computation-intensive aspects on fine-grained slicing and remodified decentralized controller outputs. With known slice and prioritization, federated learning communications iteratively process through the adjusted resources by virtual network functions forwarding graph (VNFFG) descriptor set up in software-defined networking (SDN) and network functions virtualization (NFV) enabled architecture. To demonstrate the theoretical approach, Mininet emulator was conducted to evaluate between reference and proposed schemes by capturing the key Quality of Service (QoS) performance metrics.

• Proceedings of the Korea Information Processing Society Conference
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• 2024.05a
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• pp.774-776
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• 2024

The effective implementation of advanced speech recognition (ASR) systems necessitates the deployment of sophisticated keyword spotting models that are both responsive and resource-efficient. The initial local detection of user interactions is crucial as it allows for the selective transmission of audio data to cloud services, thereby reducing operational costs and mitigating privacy risks associated with continuous data streaming. In this paper, we address these needs and propose utilizing the Whisper-Tiny model with fine-tuning process to specifically recognize keywords from google speech dataset which includes 65000 audio clips of keyword commands. By adapting the model's encoder and appending a lightweight classification head, we ensure that it operates within the limited resource constraints of local devices. The proposed model achieves the notable test accuracy of 92.94%. This architecture demonstrates the efficiency as on-device model with stringent resources leading to enhanced accessibility in everyday speech recognition applications.

• Journal of Wetlands Research
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• v.17 no.4
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• pp.407-413
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• 2015

As the number of applications containing nanomaterials increase, aquatic ecosystem exposure to nanoparticles (NPs) is unavoidable. In this study, we carried out toxicity assessment to Au-nanoparticles(NPs) of Rana dybowskii eggs and tadpoles. Toxicity was recorded hatching rate, body condition(Snout-tail length, STL), and behavioral sensitivity. Behavioral sensitivity was analyzed to anti-predator behavior using Ethovision XT 9. Au-NPs did not show any toxicity of hatching rate and STL. But, Tadpoles exposed to Au-NPs decrease behavioral sensitivity of stimuli. This study has value of environmental toxicity evaluation because these results show the new way of toxicity assessment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.753-759
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• 2014

This study aim to arrange ISD from the competency context and from the Dual major base of junior colleges related to Dept. of Administrative Professional. By analysing the curricula of the Korean capital area junior colleges of secretarial service, extracted some ability factor and classified it on the basis of NCS and competency grouping. From this, the basic direction of Standardizing Competency can be determined and it applied to develop ISD. Thus the Multi ground base of ISD can be constructed which served on developing a convergence human resource. It may give an implication and practical methodology for the junior colleges of secretarial service related Dept. to make a framework for developing a multi ground based ISD which can be designed from the multiple competency and from more than two complex major.

• Journal of the Korea Convergence Society
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• v.12 no.9
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• pp.169-178
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• 2021

It is the post-corona era that we will soon face. It is time to achieve the original purpose of job training for health and welfare personnel operated by the Korea Human Resource Development Institute for Health and Welfare and to innovate change to maintain educational consistency. This study reviewed literatures to find alternatives for efficient and effective curriculum operation by integrating contents of health and welfare job education. Through this, we decided to check the possibility of building an open platform and suggest it as a sufficient alternative. It is expected that the establishment of the open platform for job education in the health and welfare sector will enable the education accessibility and the management of the learning management system of the subjects. Above all, it will contribute to the duplication of the education experts and the efficiency of the budget.