• The Transactions of the Korean Institute of Electrical Engineers P
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• v.63 no.4
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• pp.283-289
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• 2014

A Fresnel lens is an optical component which can be used as a cost-effective, lightweight alternative to conventional continuous surface optics. Fresnel lens solar concentrators continue to fulfill a market requirement as a system component in high volume cost effective Concentrating Photovoltaic (CPV) electricity generation. The basic principles of the fresnel lens are reviewed and some practical examples are described. To investigate the performance space of the Fresnel lens, a fast simulation method which is a hybrid between raytracing and analytical computation is employed to generate a cache of simulation data. Injection molders are warming up to the idea of cycling their tool surface temperature during the molding cycle rather than keeping it constant. Heat and cool process are now also finding that raising the mold wall temperature above the resin's glass-transition or crystalline melting temperature during the filling stage and product performance in applications from automotive to packaging to optics. This paper deals with the suitability of Fresnel lenses of imaging and non-imaging designs for solar energy concentration. The concentration fresnel lens confirmed machinability and optical transmittance and roughness measure through manufactured the prototype.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.1
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• pp.1-10
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• 2010

Recently heterogeneous storage system such as hybrid hard disk drive (H-HDD) combining flash memory and magnetic disk is launched, according as the read performance of NAND flash memory is enhanced as similar to that of hard disk drive (HDD) and the power consumption of NAND flash memory is reduced less than that of HDD. However, the read and write operations of NAND flash memory are slower than those of rotational disk. Besides, serious overheads are incurred on CPU and main memory in the case that intensive write requests to flash memory are repeatedly occurred. In this paper, we propose the Least Frequently Used-Hot scheme that replaces the data blocks whose reference frequency of read operation is low and update frequency of write operation is high, and the data flushing scheme that rearranges the data blocks into the multi-zone of the rotation disk. Experimental results show that the execution time of the proposed method is 38% faster than those of conventional LRU and LFU block replacement schemes in I/O performance aspect and the proposed method increases the life span of Non-Volatile Cache 40% higher than those of conventional LRU, LFU, FIFO block replacement schemes.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11B
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• pp.1607-1617
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• 2010

In this paper we propose MA-CBRP, mesh adaptive algorithm for wireless mesh networks. MA-CBRP is a hybrid algorithm based on ad-hoc CBRP protocol. In MA-CBRP, the mesh router periodically sends the ANN message as like Hello-message in CBRP. ANN message allows to all clients periodically store a route towards the mesh-router and renewal information in their routing cache. While CBRP periodically reply Hello-message, MA-CBRP does not reply to achieve less overhead. After receiving ANN message, mesh client send JOIN message to mesh router when the route towards mesh router changed. at the same time Register the entry to mesh router, it can achieve to reduce overhead of control the route and shorten the time to find route. consequently, MA-CBRP shows 7% reduced overhead and shortened time to find route than CBRP with regardless of clients number.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.