• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.654-665
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• 2017

It is major strategy for SMEs to cooperate with other companies or Public Research Institutes(PRIs) as the essential technology is getting more complicated and technological life cycle is getting short. However, It is not easy to perform a proper cooperation with SMEs for PRIs, because they are accustomed to support SMEs in the short run. In addition, previous studies also have mainly focussed on finding determinants of performance as a consequence of temporary cooperation instead of long-term relationships among companies. Therefore this study analyzed which satisfaction is more effective to maintain the long-term cooperative relationship between PRIs and SMEs. As a result, it has found that when SMEs satisfy from quality of input like manpower supports R&D and context of the support program over the output like technological or economical performance, they intend to continue cooperation with PRIs. And this paper shows that the performance has mediated effect rather direct effect on long-term cooperation intention. In light of all the above, to cooperate with SMEs effectively, it will be suggested that PRIs enhance quality of support process and contents instead of quantity of support based on one-time cooperation.

• Journal of Broadcast Engineering
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• v.16 no.1
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• pp.1-13
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• 2011

In this paper, we propose an adaptive in-loop filter to improve the coding efficiency. Recently, there are post-filter hint SEI and block-based adaptive filter control (BAFC) methods based on the Wiener filter which can minimize the mean square error between the input image and the decoded image in video coding standards. However, since the post-filter hint SEI is applied only to the output image, it cannot reduce the prediction errors of the subsequent frames. Because BAFC is also conducted with a deblocking filter, independently, it has a problem of high computational complexity on the encoder and decoder sides. In this paper, we propose the low-complexity adaptive in-loop filter (LCALF) which has lower computational complexity by using H.264/AVC deblocking filter, adaptively, as well as shows better performance than the conventional method. In the experimental results, the computational complexity of the proposed method is reduced about 22% than the conventional method. Furthermore, the coding efficiency of the proposed method is about 1% better than the BAFC.

• Journal of IKEEE
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• v.22 no.3
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• pp.638-644
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• 2018

In this paper, we develop a measurement system that uses 3D Scintillator and NaI(TI) Detector to 3-dimensionally identify the location of multiple radiation sources in moving vehicle loads. The radiation measurement system consists of radiation measurement (plastic scintillator), 2-channel Pulse Counter Board, nuclide analysis (NaI(TI) detector) and 1 channel MCA Board. The source locator algorithm calculates the coordinate value of the ratio of the CPS value($1/r^2$) of the source according to the angle(${\theta}$) in inverse proportion to the square of the distance(X, Y) through the SVM classification. The coordinate values are input every predetermined period of the spectrum, and after analyzing the spectrum per unit cycle, the position of the nuclide at the time is calculated by determining whether or not the nuclide is present in the remaining part except for the background area. As a result of the position discrimination test, the error within the international standard of ${\pm}1m$ was shown. Thus, the utility of the proposed system has been demonstrated.

• Journal of the Korean Institute of Gas
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• v.16 no.1
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• pp.39-45
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• 2012

While the natural gas supply industry has continuously been growing, its potential hazard has also risen since the natural gas facilities essentially require installations that carry highly flammable and pressurized gas close to the populated areas, posing a serious consequence of significant property damage as well as human casualties in the event of accident. Therefore Quantitative Risk Assessment (QAR) has been recognized as a appropriate method to reduce the risk as far as possible, considering the reality of unachievable zero-risk. However, it is hard to perform effective QRA on hundreds of gas facilities because of insufficient number of expert and long-term analysis. In this paper, we suggest a conceptual QRA system framework to support more efficient risk analysis in gas supply facilities. In this system, the experts make questionnaires and internal calculation formula needed in accident frequency/consequence analysis of the facility through pre-analysis on the point of analysis, called incident point, and general users locate the point on the map and input the value required by the questionnaire to obtain the risk. Ultimately, this is suggested based on the idea that the specialization is available in QRA analysis process and the validity of the system is verified through actual system construction and application.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.10
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• pp.1189-1193
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• 2012

The Miniaturized Fingerprint Imager (MFI) is a slim optical mouse that can be used as an input device for application to wireless portable personnel communication devices such as smartphones. In this study, we have fabricated key optical components of an MFI, including the illumination optical components and imaging lens. An LED beam-shaping lens consisting of an aspheric lens and a Fresnel facet was successfully machined using a diamond turning machine (DTM). A customized V-shaped groove for beam path banding was fabricated by the bulk micromachining of silicon that was coated with aluminum using the shadow effect in thermal evaporation. The imaging lens and arrayed multilevel Fresnel lenses were fabricated by electron beam lithography and FAB etching, respectively. The proposed optical components are extremely compact and have high optical efficiency; therefore, they are applicable to ultraslim optical systems.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.2D
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• pp.217-225
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• 2011

Currently our country has very serious problems of traffic congestion and urban environment due to increasing automobile ownership. Recently, our concern about environmentally sustainable transportation and green transportation is increasing, so the government is pushing ahead the policy of bicycle using activation. So it is needed to develop a model to analyze the service level of bicycle roads more realistically. In this study, a neuro-fuzzy inference model to analyze the service level of bicycle roads was built selecting the width of bicycle roads, the number of conflicts during cycling and pedestrian volume, which have fuzzy characteristics, as input variables. The predictability of the model was evaluated comparing the surveyed and the estimated. The values of the statistics, $R^2$, MAE and MSE were 0.987, 0.142, 0.032. Therefore, It may be judged that the explainability of the model is very high. The service levels of bicyle roads estimated by the model are 1~3 steps lower than KHCM assessments. The reason may be explained that the model estimates the service level considering the width of bicycle roads and the number of conflicts simultaneously besides pedestrian volume.

• Korean Journal of Medicinal Crop Science
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• v.2 no.1
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• pp.14-19
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• 1994

Elephant food(Amorphophallus konjac K.) have been utilized its tubers in workedmaterials for a health and diet food. The author supposed that it was increased the area of cultivation and demand. This experiments were conducted to select the proper covering material during winter in order to increase yield of tubers and decrease input by 2 year's continuous cultivation, also to verified ability of seed germination and to measured efficiency of photosynthesis of plant. The proper covering materials for wintering were rice straw and rice hull. These materials were covered at 5 cm thick and at field was promoted according to emergence appearing after winter. The yields were 5,790kg /10a at 4,730kg /10a, respectively. Yield increase was 120% and 80% than that of control. The seeds collected at August 22 were germinated about 84 percent, and it was not necessary to treatment of low temperature or germination-accelerated chemicals. The widest leaf area was ranged $1,218-1,438cm^2$ at October 20 and was varied. The efficiency of photosynthesis was highest at 65-95 days after leaf emergence. The line of broad leaf and high photosynthetic efficiency per unit area was greater compare with yield. Therefore, it was supposed that these characteristics will use a marker for selection for high-yielding lines.

• Journal of Technology Innovation
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• v.17 no.2
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• pp.131-158
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• 2009

We examine the effects of environmental or organizational factors on the performance of TLOs(technology transfer offices) in the PRIs(Public research institutes) using SFA(Stochastic Frontier Analysis), a technique for estimating the efficiency of DMUs(decision making units). In SFA, independent variables are assumed to determine the efficient production technique(production frontier) or affect the efficiency of DMUs. Previous researchs show that input variables such as number of personnel, R&D expenditure affect the production frontier while environmental or organizational variables affect the efficiency. We tried to estimate various types of models to find out whether environmental or organizational variables affect output variables differently from the previous research. Main empirical findings are as follows. First, R&D expenditure tends to increase all output variables considered. Second, environmental factors such as type of institutions and location of institutions affect the level of outputs. Third, organizational factors such as reward system for technology transfer also appear to affect the output variables. Fourth, environmental or organizational variables affect the production frontier directly rather than affect the efficiency of DMUs. Lastly, the efficiency of each DMU appear to be 1 or near to 1. Since almost all DMUs are equally efficient, it may not be effective to evaluate technology transfer activities of PRIs by efficiency criteria. We believe that this research should be complemented by additional data. More general types of production function need to be considered, and new techniques with concepts like output distance functions need to be developed to analyse multiple outputs simultaneously.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.