• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.140-146
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• 2023

Resource allocation is one of the top challenges in Internet of Things (IoT) networks. This is due to the scarcity of computing, energy and communication resources in IoT devices. As a result, IoT devices that are not using efficient algorithms for resource allocation may cause applications to fail and devices to get shut down. Owing to this challenge, this paper proposes a novel algorithm for managing computing resources in IoT network. The fog computing devices are placed near the network edge and IoT devices send their large tasks to them for computing. The goal of the algorithm is to conserve energy of both IoT nodes and the fog nodes such that all tasks are computed within a deadline. A bi-partite graph-based algorithm is proposed for stable matching of tasks and fog node computing units. The output of the algorithm is a stable mapping between the IoT tasks and fog computing units. Simulation results are conducted to evaluate the performance of the proposed algorithm which proves the improvement in terms of energy efficiency and task delay.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.319-325
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• 2023

In this study, we proposed a method for hyperparameter optimization in the building and training of a deep learning model designed to process point cloud data collected by a millimeter-wave radar system. The primary aim of this study is to facilitate the deployment of a baseline model in resource-constrained IoT devices. We evaluated a RadHAR baseline deep learning model trained on a public dataset composed of point clouds representing five distinct human activities. Additionally, we introduced a coarse-to-fine hyperparameter optimization procedure, showing substantial potential to enhance model efficiency without compromising predictive performance. Experimental results show the feasibility of significantly reducing model size without adversely impacting performance. Specifically, the optimized model demonstrated a 3.3% improvement in classification accuracy despite a 16.8% reduction in number of parameters compared th the baseline model. In conclusion, this research offers valuable insights for the development of deep learning models for resource-constrained IoT devices, underscoring the potential of hyperparameter optimization and model size reduction strategies. This work contributes to enhancing the practicality and usability of deep learning models in real-world environments, where high levels of accuracy and efficiency in data processing and classification tasks are required.

• Korean Journal of Agricultural Science
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• v.51 no.1
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• pp.53-61
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• 2024

A total of 180 21-day-old weaning pigs ([Yorkshire × Landrace] × Duroc) with an initial body weight of 6.44 ± 0.01 kg were randomly assigned to 9 treatments for evaluating the effects of replacing dietary inorganic copper (Cu) and zinc (Zn) with glycine (Gly) or methionine (Met)-chelated Cu and Zn on growth performance and nutrient digestibility. The experimental period was 35 days. There were four replicated pens per treatment, with five pigs (three males and two females) per pen. Dietary treatments consisted of a basal diet (CON), in which the sources of Cu and Zn were in inorganic form. The inorganic Cu and Zn in the basal diet were replaced by glycine-chelated (GC) and methionine-chelated (MC) Cu and Zn by 30, 50, 70, or 100% to form the GC1, GC2, GC3, GC4, or MC1, MC2, MC3, MC4 groups. The 100% replacement of dietary inorganic Cu and Zn with GC or MC increased (p < 0.05) average daily gain, average daily feed intake, and gain-to-feed ratio. The complete replacement of dietary inorganic Cu and Zn with GC or MC led to enhanced (p < 0.05) digestibility of dry matter, nitrogen, Cu and Zn. Thus, the replacement of inorganic Cu and Zn with GC or MC can improve the growth efficiency and nutrient utilization of weaning pigs.

• Environmental and Resource Economics Review
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• v.26 no.2
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• pp.205-227
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• 2017

Today, the global environment has so many serious problems such as global warming, ecological destruction and air pollution. Now China is the second largest carbon emissions country in the world. In this paper, we estimated the ratio of GDP per unit of carbon emissions for each of 30 provinces in China, and then also estimated the carbon emission efficiency of 30 provinces and analyzed the factors that affecting them. There are differences in carbon emission efficiency among different provinces, and carbon emission efficiency is relatively high in Hainan Province, Beijing, and Tianjin. In the regression results of the factors affecting the carbon emission efficiency, when the proportion of service industries is higher, the efficiency is higher. Also, when the higher the proportion of heavy industry and the higher the proportion of coal consumption are estimated to be worse.

• Environmental and Resource Economics Review
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• v.18 no.2
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• pp.191-215
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• 2009

In the real world, there exist various products in terms of price and quality, and it can be expected that a product with lower price and higher quality than others is better. Hence efficiency of consumption behaviour can be measured by the level of goodness in terms of price and quality attributes of that product. The purpose of this research is to define consumption efficiency in terms of price and quality, and to measure consumption efficiency of IT and electronic products in South Korea. From the results, many consumers have purchased inefficient products m air-conditioner, TV, digital camera, MP3 player, computer markets. On the other hand, consumers have purchase efficient products in refrigerator and washing machine markets relatively. In addition, we analyze the relationship of consumption efficiency, information channel, and electric power consumption. This research may provide meaningful information for consumer's behaviour by measuring consumption efficiency quantitatively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5264-5281
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• 2017

Multihop relay-based cellular networks are attracting much interest because of their throughput enhancement, coverage extension, and low infrastructure cost. In these networks, relay stations (RSs) between a base station (BS) and mobile stations (MSs) drastically increase the overall spectral efficiency, with improved channel quality for MSs located at the cell edge or in shadow areas, and enhanced throughput of MSs in hot spots. These relay-based networks require an advanced radio resource management scheme because the optimal amount of radio resource for a BS-to-RS link should be allocated according to the MS channel quality and distribution, considering the interference among RSs and neighbor BSs. In this paper, we propose optimal resource planning algorithms that maximize the overall utility of relay-based networks under a proportional fair scheduling policy. In the first phase, we determine an optimal scheduling policy for distributing BS-to-RS link resources to RSs. In the second phase, we determine the optimal amount of the BS-to-RS link resources using the results of the first phase. The proposed algorithms efficiently calculate the optimal amount of resource without exhaustive searches, and their accuracy is verified by comparison with simulation results, in which the algorithms show a perfect match with simulations.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.229-240
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• 2021

As the environment and rivalry of Regional Agricultural Cooperatives(RACs) becomes more unfavorable, the pressures to enhance organizational performance are strenghthened. Existing studies suggest efficiency improvement through resource sharing(RS) to fix the issue. In this context, I intend to find if RS still increases organizational performance in another form of organization on the basis of 132 business units(BUs) of 45 RACS. According to empirical results, resource similarity between BUs and resource level of BU increases RS respectively, and RS increases BU's performance. The RS also has mediating effects on similarity and resource level into performance. But the overall resource level of RAC has no influence on RS and there is no mediating effect. My contribution is to confirm the efficacy of RS in half-profit organization and to verify determinants and performance implications of RS.

• Environmental and Resource Economics Review
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• v.12 no.1
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• pp.29-48
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• 2003

The Steel Industry has made a significant contribution to the increase of energy use in Korea. This paper presents a method for development energy efficiency indicator in the steel industry based on the decomposing approach. This paper develops a logically consistent method for decomposing a change in energy consumption into the effects of three factors structural change, energy intensity and output level. Numerical illustration of the method is given using 1992~2001 data for energy consumption in a virtual works. The most dominant factor is revealed to be the output effect. The energy intensity for the steel industry has increased and the effect of such a growth was relatively strongly reflected in the decomposition analysis. The structural effect turned out to be also important during the periods.

• Bulletin of the Korean Chemical Society
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• v.32 no.8
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• pp.2599-2606
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• 2011

The fluorescence of ethidium bound to DNA, poly[d(A-T)$_2$], and poly[d(G-C)$_2$] at a [ethidium]/[DNA] ratio of 0.005 was quenched by porphyrins when both ethidium and the porphyrins simultaneously bound to the same polynucleotide. The quenching was tested using the "inner sphere" and the "Forster resonance energy transfer" (FRET) models, with the latter found to contribute, at least in part, to the quenching. Meso-tetrakis(N-methylpyridinium-4-yl)porphyrin (TMPyP) exhibited a higher quenching and FRET efficiency than cis-bis(N-methylpyridinium-4-yl)porphyrin (BMPyP) for all of the tested DNA and polynucleotides, demonstrating that energy transfer efficiency is affected by the number of positive charges of porphyrins.

• Journal of Information Technology Applications and Management
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• v.9 no.3
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• pp.47-56
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• 2002

A variety of enterprises have Implemented ERP system on the promises of feasible strategic benefits. The objectives of this study are (1) to classily and analyze the motives and critical success factors o the enterprises'ERP system adoptions, and (2) to measure their impacts on the business performance. The data for this research were collected from 43 cases in Korea that have operated ERP system for more than 6 months after the implementation. This study results reveals that the Information strategic planning and business strategy establishment prior to ERP adoption and the demands of field people activate as critical triggers In the larger firms Among the six critical success factors, training was statistically significant for all of four performance measures control, cost reduction, quality and service, and work efficiency. And other findings are furnished. Also the larger company group In the sales volume has shown the higher performance except work efficiency.