• Advanced Industrial SCIence
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• v.2 no.3
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• pp.8-14
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• 2023

The majority of IoT devices already employ AIoT, however there are still numerous issues that need to be resolved before AI applications can be deployed. In order to more effectively distribute IoT edge resources, this paper propose a machine learning-based approach to managing IoT edge resources. The suggested method constantly improves the allocation of IoT resources by identifying IoT edge resource trends using machine learning. IoT resources that have been optimized make use of machine learning convolution to reliably sustain IoT edge resources that are always changing. By storing each machine learning-based IoT edge resource as a hash value alongside the resource of the previous pattern, the suggested approach effectively verifies the resource as an attack pattern in a distributed AIoT context. Experimental results evaluate energy efficiency in three different test scenarios to verify the integrity of IoT Edge resources to see if they work well in complex environments with heterogeneous computational hardware.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.7
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• pp.219-230
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• 2014

In the cloud computing environment, cloud service users purchase and use the virtualized resources from cloud resource providers on a pay as you go manner. Typically, there are two billing plans for computing resource allocation adopted by large cloud resource providers such as Amazon, Gogrid, and Microsoft, on-demand and reserved plans. Reserved Virtual Machine(VM) instance is provided to users based on the lengthy allocation with the cheaper price than the one of on-demand VM instance which is based on shortly allocation. With the proper mixture allocation of reserved and on-demand VM corresponding to users' requests, cloud service providers are able to reduce the resource allocation cost. To do this, prior researches about VM allocation scheme have been focused on the optimization approach with the users' request prediction techniques. However, it is difficult to predict the expected demands exactly because there are various cloud service users and the their request patterns are heavily fluctuated in reality. Moreover, the previous optimization processing techniques might require unacceptable huge time so it is hard to apply them to the current cloud computing system. In this paper, we propose the cloud brokering system with the adaptive VM allocation schemes called A3R(Adaptive 3 Resource allocation schemes) that do not need any optimization processes and kinds of prediction techniques. By using A3R, the VM instances are allocated to users in response to their service demands adaptively. We demonstrate that our proposed schemes are able to reduce the resource use cost significantly while maintaining the acceptable Quality of Service(QoS) of cloud service users through the evaluation results.

• Journal of Technology Innovation
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• v.4 no.1
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• pp.185-207
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• 1996

It is frequently pointed out that the Korean economy, with its scarce natural resources, would never have been able to achieve current levels of economic development without the massive provision of well-educated, hardworking human resources. Throughout the industrialization process ,full-fledged deployment and mobilization of qualified human resources have been the foundation to industrial policy and S&T policy. This paper describes the development of S&T human resources in Korea using various statistics including educational enrollment rates, unemployment rates, the allocation of researchers and R&D expenditures among sectors of performance, educational composition of employment within and across industries, technical human resource shortage rates, relative wage levels of SMEs, and composition of labor force by age-group and gender. While analyzing S&T human resources development, this paper discusses issues such as the mismatched demand and supply of skill and knowledge levels of the highly educated, the unbalanced distribution of S&T human resources between sectors, and the low utilization of the female and aged labor force. This paper suggests that the policy maker applies a hybrid of quantitative and qualitative policies to reduce the mismatches of supply and demand of skill and knowledge levels for each labor market categorized according to supply side.

• Journal of IKEEE
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• v.22 no.2
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• pp.281-288
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• 2018

In this paper, we propose an intelligent face recognition and tracking system that distributes GPU resources using CUDA. The proposed system consists of five steps such as GPU allocation algorithm that distributes GPU resources in optimal state, face area detection and face recognition using deep learning, real time face tracking, and PTZ camera control. The GPU allocation algorithm that distributes multi-GPU resources optimally distributes the GPU resources flexibly according to the activation level of the GPU, unlike the method of allocating the GPU to the thread fixedly. Thus, there is a feature that enables stable and efficient use of multiple GPUs. In order to evaluate the performance of the proposed system, we compared the proposed system with the non - distributed system. As a result, the system which did not allocate the resource showed unstable operation, but the proposed system showed stable resource utilization because it was operated stably. Thus, the utility of the proposed system has been demonstrated.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.375-381
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• 2012

If a mobile station requests a channel allocation in its mobile networks, the switching center assigns a channel to a mobile station that belongs to each base station. There are three kinds of channel allocation schemes; a fixed channel allocation, a dynamic channel allocation and a hybrid combination of these two forms. In assigning a good frequency, it is our intention to provide quality service to our customers as well as to use resources efficiently. This paper proposes methods of assigning frequencies that minimize interference between channels and that also minimize the amount of searching time involved. In this paper, we propose an algorithm to per specific equipment, regardless of the number of channels that can be used as a general-purpose system, such as base stations, control stations, central office model is proposed, the existing operators manner similar to the fixed channel allocation based statistics and assigned when the conventional method and the improved method is proposed. Different ways and compared via simulations to verify the effectiveness of the proposed approach.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.2
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• pp.159-166
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• 2020

In this paper, we propose a heterogenous mission allocation technique for multi-UAV system based on discrete event modeling. We model a series of heterogenous mission creation, mission allocation, UAV departure, mission completion, and UAV maintenance and repair process as a mathematical discrete event model. Based on the proposed model, we then optimize the number of UAVs required to operate in a given scenario. To validate the optimized number of UAVs, the simulations are executed repeatedly, and their results are analyzed. The proposed mission allocation technique can be used to efficiently utilize limited UAV resources, and allow the human operator to establish an optimal mission plan.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3524-3542
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• 2017

In a single-source and multi-relay amplify-forward (AF) cooperative network, the outage probability and the power allocation are two key factors to influence the performance of an entire system. In this paper, an optimized AF relay selection by an exclusive method and near optimal power allocation (NOPA) is proposed for both good outage probability and power efficiency. Given the same power at the source and the relay nodes, a threshold for selecting the relay nodes is deduced and employed to minimize the average outage probability. It mainly excludes the relay nodes with much higher thresholds over the aforementioned threshold and thus the remainders of the relay nodes participate in cooperative forwarding efficiently. So the proposed scheme can improve the utility of the resources in the cooperative multi-relay system, as well as reduce the computational complexity. In addition, based on the proposed scheme, a NOPA is also suggested to approach sub-optimal power efficiency with low complexity. Simulation results show that the proposed scheme obtains about 2.1dB and 5.8dB performance gain at outage probability of $10^{-4}$, when compared with the all-relay-forward (6 participated relays) and the single-relay-forward schemes. Furthermore, it obtains the minimum outage probability among all selective relay schemes with the same number of the relays. Meanwhile, it approaches closely to the optimal exhaustive scheme, thus reduce much complexity. Moreover, the proposed NOPA scheme achieves better outage probability than those of the equal power allocation schemes. Therefore, the proposed scheme can obtain good outage probability, low computational complexity and high power efficiency, which makes it pragmatic efficiently in the single-source and multi-relay AF based cooperative networks.

• The KIPS Transactions:PartA
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• v.8A no.3
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• pp.279-286
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• 2001

This paper proposes a low power resource allocation and scheduling algorithm that minimized power consumption such as DSP circuit in high-level synthesis process. In this paper, we have used list-scheduling method for low power design in scheduling step. Also, it increase possibility to reuse input through resource sharing when assign resource. After scheduling, the resources allocation uses the power function in consideration of the result of calculating average hamming distances and switching activity between two input. First, it obtain switching activity about input value after calculate average hamming distances between two operator and find power value make use of bit pattern of the input value. Resource allocation process assign operator to minimize average hamming distance and power dissipation on all occasions which is allocated at each control step according to increase control step. As comparing the existed method, the execution time becomes fast according to number of operator and be most numberous control step. And in case of power that consume, there is decrease effect from 6% to 8% to be small.

• Journal of Korean Society on Water Environment
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• v.26 no.1
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• pp.168-176
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• 2010

This study proposes the improvement of the present Total Maximum Daily Load (TMDL) management system of MOE (Ministry of Environment). The margin of safety (MOS) is calculated by a method using standard error and a method using variability and uncertainty. The allocation of pollutant loads are calculated using three methods, equal load reduction method, equal percent removal method and method using equity standards. This study applied the improved TMDL management system to the Anyangcheon watershed. Since MOS varies from 12% to 44% due to the high variability of measured and simulated data, it must not be ignored in the TMDL. The method using equity standards is the most proper in this application since the others produced unrealistic allocations. Area, runoff, water use quantity, population and budget are considered for equity standards. This study shows that this allocation method can be also applicable for the administrative units as well as the sub-watersheds. Finally, Hydrologic Simulation Program-FORTRAN (HSPF) with the allocated pollutant load was used to confirm whether it satisfy the water quality standard or not. This study will be helpful to improve the MOS and allocation system TMDL in the future.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.12A
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• pp.1191-1199
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• 2008

We propose the Staggered-zone Resource Allocation (SRA) in order to relax throughput decrease problems by the co-channel interference of the cell boundary users at the cellular OFDMA system using frequency reuse factor K=1 and analyze the throughput improvement. The proposed algorithm allocates the resources to the users in compliance with resource allocation rule which is planned in order to minimize co-channel interference between cells without any additional information. The resource allocation method in the SRA lines up the users in pathloss order as descending series, and then allocates from pre-determined resource allocation region where decides differently in each cell. This algorithm prevents the co-channel interferences of the cell boundary user to be caused by using same resource simultaneously and equalizes interference to the users in the cell.