• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2726-2728
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• 2001

This paper describes an optimal synthesis method of binary neural network(BNN) for an approximation problem of a circular region using a newly proposed learning algorithm[7] Our object is to minimize the number of connections and neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm(NETLA) for the multilayer BNN. The synthesis method in the NETLA is based on the extension principle of Expanded and Truncated Learning(ETL) and is based on Expanded Sum of Product (ESP) as one of the boolean expression techniques. And it has an ability to optimize the given BNN in the binary space without any iterative training as the conventional Error Back Propagation(EBP) algorithm[6] If all the true and false patterns are only given, the connection weights and the threshold values can be immediately determined by an optimal synthesis method of the NETLA without any tedious learning. Futhermore, the number of the required neurons in hidden layer can be reduced and the fast learning of BNN can be realized. The superiority of this NETLA to other algorithms was proved by the approximation problem of one circular region.

• Korean Journal of Veterinary Research
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• v.23 no.1
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• pp.111-117
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• 1983

In the present study, the optimal electric current and induction time of the acupuncture anesthesia were determined and the clinical signs during and after the acupuncture anesthesia were observed in 90 Korean native dogs. The results were summarized as fellows. 1. Optimal electric current was 11-13 Hz at 1.0 volt initially with gradual increase up to 22-26 Hz at 5.0-6.0 volts after 5 minutes. 2. The induction time was 7-20 minutes in all cased; 55.8% out of them showed the induction time of 7-10 minutes. 3. No differences were found in the analgesic effect and clinical signs between ages and between body weights. There were individual differences in the induction time and the optimal electric current. The respiratory and pulse rates were lower at 5 minutes after the removal of the needles than 5 minutes before attachment of needles to the electrodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5819-5840
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• 2018

Considering the topology of hierarchical tree structure, each cluster in WSNs is faced with various attacks launched by malicious nodes, which include network eavesdropping, channel interference and data tampering. The existing intrusion detection algorithm does not take into consideration the resource constraints of cluster heads and sensor nodes. Due to application requirements, sensor nodes in WSNs are deployed with approximately uncorrelated security weights. In our study, a novel and versatile intrusion detection system (IDS) for the optimal defense strategy is primarily introduced. Given the flexibility that wireless communication provides, it is unreasonable to expect malicious nodes will demonstrate a fixed behavior over time. Instead, malicious nodes can dynamically update the attack strategy in response to the IDS in each game stage. Thus, a multi-stage intrusion detection game (MIDG) based on Bayesian rules is proposed. In order to formulate the solution of MIDG, an in-depth analysis on the Bayesian equilibrium is performed iteratively. Depending on the MIDG theoretical analysis, the optimal behaviors of rational attackers and defenders are derived and calculated accurately. The numerical experimental results validate the effectiveness and robustness of the proposed scheme.

• Smart Structures and Systems
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• v.20 no.1
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• pp.61-74
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• 2017

One of the most reliable and simplest tools for structural vibration control in civil engineering is Tuned Mass Damper, TMD. Provided that the frequency and damping parameters of these dampers are tuned appropriately, they can reduce the vibrations of the structure through their generated inertia forces, as they vibrate continuously. To achieve the optimal parameters of TMD, many different methods have been provided so far. In old approaches, some formulas have been offered based on simplifying models and their applied loadings while novel procedures need to model structures completely in order to obtain TMD parameters. In this paper, with regard to the nonlinear decision-making of fuzzy systems and their enough ability to cope with different unreliability, a method is proposed. Furthermore, by taking advantage of both old and new methods a fuzzy system is designed to be operational and reduce uncertainties related to models and applied loads. To design fuzzy system, it is required to gain data on structures and optimum parameters of TMDs corresponding to these structures. This information is obtained through modeling MDOF systems with various numbers of stories subjected to far and near field earthquakes. The design of the fuzzy systems is performed by three methods: look-up table, the data space grid-partitioning, and clustering. After that, rule weights of Mamdani fuzzy system using the look-up table are optimized through genetic algorithm and rule weights of Sugeno fuzzy system designed based on grid-partitioning methods and clustering data are optimized through ANFIS (Adaptive Neuro-Fuzzy Inference System). By comparing these methods, it is observed that the fuzzy system technique based on data clustering has an efficient function to predict the optimal parameters of TMDs. In this method, average of errors in estimating frequency and damping ratio is close to zero. Also, standard deviation of frequency errors and damping ratio errors decrease by 78% and 4.1% respectively in comparison with the look-up table method. While, this reductions compared to the grid partitioning method are 2.2% and 1.8% respectively. In this research, TMD parameters are estimated for a 15-degree of freedom structure based on designed fuzzy system and are compared to parameters obtained from the genetic algorithm and empirical relations. The progress up to 1.9% and 2% under far-field earthquakes and 0.4% and 2.2% under near-field earthquakes is obtained in decreasing respectively roof maximum displacement and its RMS ratio through fuzzy system method compared to those obtained by empirical relations.

• Korean Journal of Remote Sensing
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• v.35 no.3
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• pp.375-387
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• 2019

The use of drone-based hyperspectral image offers considerable advantages in high resolution remote sensing applications. The primary objective of this study was to select the optimal bands based on hyperspectral image for the estimation yield of the chinese cabbage. The hyperspectral narrow bands were acquired over 403.36 to 995.19 nm using a 3.97 nm wide, 150 bands, drone-based hyperspectral imaging sensor. Fresh weight data were obtained from 2,031 sample for each field survey. Normalized difference vegetation indices were computed using red, red-edge and near-infrared bands and their relationship with quantitative each fresh weights were established and compared. As a result, predominant proportion of fresh weights are best estimated using data from three narrow bands, in order of importance, centered around 697.29 nm (red band), 717.15 nm (red-edge band) and 808.51 nm (near-infrared band). The study determined three spectral bands that provide optimal chinese cabbage productivity in the visible and near-infrared portion of the spectrum.

• Journal of Bio-Environment Control
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• v.28 no.2
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• pp.104-109
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• 2019

The crops recommended for the plant factory system are diverse. The importance of planting density in the plant factory is being recognized. The objective of this study was to determine the optimal planting density for growth and quality of kohlrabi in a closed-type plant factory system. The kohlrabi was grown under fluorescent lamps and nutrient film technique system. The growth and quality of kohlrabi were investigated under four different planting densities ($22plants/m^2(15{\times}30cm)$, $27plants/m^2(15{\times}25cm)$, and $33plants/m^2(15{\times}20cm)$). There were no significant interactions between Shoot fresh and dry weights per plant or bulb stem fresh and dry weights per plant and planting density. Shoot fresh and dry weight per area or bulb stem fresh and dry weight per area were the highest at $33plants/m^2$. There were no significant interactions between plant height, leaf area, photosynthetic rate, hardness, and chlorophyll content and planting density. Significant differences in Bulb stem height and diameter, and brix were observed. Bulb stem height and diameter and brix of kohlrabi were the highest at $22plants/m^2$. Based on our results, we conclude that the optimal planting density is $33plants/m^2$ for growth of kohlrabi, however, the optimal planting density is $22plants/m^2$ for quality of kohlrabi in a closed-type plant factory system.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.2
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• pp.68-74
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• 2005

In deadline scheduling, jobs have deadlines by which they are completed. The scheduling algorithm determines which jobs are executed at each time. Then only the completed jobs contribute to the throughput or gain of the algorithm. The jobs have arbitrary weights and the gain of the algorithm is given as the sum of weights of the completed jobs. The goal of the scheduling algorithm is to maximize its gain. In this paper, we consider online non-preemptive scheduling, where jobs arrive online and the scheduling algorithm has no information about jobs arriving ahead. Also the jobs cannot be preempted or rejected while they are executed. For this problem, we obtain lower bounds for any online algorithms and also we propose an optimal online algorithm meeting the lower bounds.

• Journal of Navigation and Port Research
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• v.35 no.7
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• pp.605-611
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• 2011

In this paper, practical problems for current feeder service between Busan port and west coast of Japan were extracted through in depth interviews with Japanese feeder vessel companies, shippers, and port authority based upon which major criteria (elements) for improvement of the feeder network are structured in hierarchic order and weighed relative importance through AHP method. From the questionnaire answered by Korean and Japanese port users and experts the weights of criteria were calculated and the shipping service was ranked the first by both parties with 0.235 and 0.217, respectively. The port service and support system ranked the second and the third, whereas the port marketing was shown to be the lowest of all. Considering the overall weights, the increase in a port loading and unloading speed of port service was followed by provision of dedicated deck for feeder vessel of port facilities for Korean respondents. Therefore, speed up of the port operations and providing docks for feeder vessel are to be firstly provided for more efficient feeder operations, which would be the basis for the construction of optimal transportation network.

• Journal of KIISE
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• v.43 no.11
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• pp.1270-1274
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• 2016

Logistic regression is widely used for predicting and estimating the relationship among variables. We propose a new logistic regression model, the value weighted logistic regression, which comprises of a fine-grained weighting method, and assigns adapted weights to each feature value. This gradient approach obtains the optimal weights of feature values. Experiments were conducted on several data sets from the UCI machine learning repository, and the results revealed that the proposed method achieves meaningful improvement in the prediction accuracy.

• Journal of Hydrogen and New Energy
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• v.20 no.1
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• pp.79-85
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• 2009

In this paper, we investigated impact factors by brainstorming and survey research and calculated the weights of them using the Analytic Hierarchy Process(AHP) method in order to evaluate alternatives for supplying Liquefied Natural Gas(LNG). AHP is a useful method for evaluating multi-criteria decision making problems. We selected 3 criteria and 9 sub-criteria. According to the result in this study, the most important sub-criterion is the Government's Policy, and the second is the Province's Policy. The other side, the lowest important sub-criterion is the Investment Cost. This study may provide basic data to select the optimal alternative for supplying LNG.