• Journal of Korean Society of Transportation
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• v.20 no.1
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• pp.65-76
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• 2002

This study is realized using fuzzy evaluation and AHP(the analytic hierarchy process) for the optimum search of traffic route and estimated by the quantitative analysis in the vague subjective judgement. It is different from classical route search and noticed thinking method of human. Appraisal element, weight, appraisal value of route is extracted from basic of the opinion gathering fur the driving expert and example of route model was used for the finding of practice utility. Model assessment was performed attribute membership function making of estimate element, estimate value setting, weight define by the AHP, non additive presentation of weight according to $\lambda$-fuzzy measure, Choquet fuzzy integral.

• ETRI Journal
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• v.36 no.2
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• pp.317-320
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• 2014

A balanced RF duplexer with low interference in an extremely narrow bandgap is proposed. The Long-Term Evolution band-7 duplexer should be designed to prevent the co-existence problem with the WiFi band, whose fractional bandgap corresponds to only 0.7%. By implementing a hybrid bulk acoustic wave (BAW) structure, the temperature coefficient of frequency (TCF) value of the duplexer is successfully reduced and the suppressed interference for the narrow bandgap is performed. To achieve an RF duplexer with balanced Rx output topology, we also propose a novel balanced BAW Rx topology and RF circuit block. The novel balanced Rx filter is designed with both lattice- and ladder-type configurations to ensure excellent attenuation. The RF circuit block, which is located between the antenna and the Rx filter, is developed to simultaneously function as a balance-tounbalance transformer and a phase shift network. The size of the fabricated duplexer is as small as $2.0mm{\times}1.6mm$. The maximum insertion loss of the duplexer is as low as 2.4 dB in the Tx band, and the minimum attenuation in the WiFi band is as high as 36.8 dB. The TCF value is considerably lowered to $-16.9ppm/^{\circ}C$.

• Journal of Korea Multimedia Society
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• v.9 no.8
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• pp.1030-1036
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• 2006

The rapid proliferation of wireless networks and mobile computing applications has changed the landscape of network security. Anomaly detection is a pattern recognition task whose goal is to report the occurrence of abnormal or unknown behavior in a given system being monitored. This paper presents an efficient rough set based anomaly detection method that can effectively identify a group of especially harmful internal masqueraders in cellular mobile networks. Our scheme uses the trace data of wireless application layer by a user as feature value. Based on the feature values, the use pattern of a mobile's user can be captured by rough sets, and the abnormal behavior of the mobile can be also detected effectively by applying a roughness membership function considering weighted feature values. The performance of our scheme is evaluated by a simulation. Simulation results demonstrate that the anomalies are well detected by the method that assigns different weighted values to feature attributes depending on importance.

• Korean Institute of Interior Design Journal
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• no.13
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• pp.187-196
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• 1997

A Study on the Characteristics of the Modern Chair Design The features of the modern chair design results from the diverse life style unfolded as per the 20th century social structure and the change of the residential space, and new design has been being developed by the scientists and the artists in various fields through their cooperated work in a way. The field of the scientific or technical study and creation of arts can be developed where they can evoke the sympathy in the circumstances under which the various styles of both arts and science meet across, complement crash together, and grow up. The operation which can control in the network of such pluralistic sphere has been needed for a long period and it has been facing the needs from a time and society. The engineering furniture as the counterplan of the above has brought the value of materials into relief to the forms of human life by making the properties of matter the maximum value or changing it. It can be summarized as following characteristics in its materials and forms along as well as the 3 types (handycrafty, mechanical, and ecological expression) in process through the 20th century. 1. Characteristics in Materials elasticity of the chair as per the changes of the flexibility in the steel pipe development of systematic chair using the plasticity of the plywood, plastic, and wire lightweight due to the materials such as aluminum. 2. Formative characteristics formative simplicity for the increase of the function and the quality improvement such as sociality, productivity, environmental and aesthetic nature emphasis on the structure as per the architectural environment and tecniques pursuit of the forms as a container of the human body seeking for the formative values as the cultural symbols coping with the needs from thepluralistic social structure Furniture is not the makeup for convenience sake but most importantexpression as necessaries of our environments. It should identify itself always as per these kind of needs and also it should be able to used to keep the relation of such mutual division, otherwise the purchase of new furniture should be necessary according to every change of the existing situatiov. Our residence doesn't need the specific style but expresses only the properties of the dwellers.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.11
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• pp.76-88
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• 1998

While most of the research on reinforcement learning assumed a discrete control space, many of the real world control problems need to have continuous output. This can be achieved by using continuous mapping functions for the value and action functions of the reinforcement learning architecture. Two questions arise here however. One is what sort of function representation to use and the other is how to determine the amount of noise for search in action space. The ubiquitous neural network is used here to learn the value and policy functions. Next, the reinforcement predictor that is intended to predict the next reinforcement is introduced that also determines the amount of noise to add to the controller output. The proposed reinforcement learning architecture is found to have a sound on-line learning control performance especially at high-speed road following of high curvature road. Both computer simulation and actual experiments on a test vehicle have been performed and their efficiency and effectiveness has been verified.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2074-2093
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• 2022

RSA is known as one of the best techniques for securing secret information across an unsecured network. The private key which is one of private parameters is the aim for attackers. However, it is exceedingly impossible to derive this value without disclosing all unknown parameters. In fact, many methods to recover the private key were proposed, the performance of each algorithm is acceptable for the different cases. For example, Wiener's attack is extremely efficient when the private key is very small. On the other hand, Fermat's factoring can quickly break RSA when the difference between two large prime factors of the modulus is relatively small. In general, if all private parameters are not disclosed, attackers will be able to confirm that the private key is unquestionably inside the scope [3, n - 2], where n is the modulus. However, this scope has already been reduced by increasing the greatest lower bound to [d_il, n - 2], where d_il ≥ 3. The aim of this paper is to decrease the least upper bound to narrow the scope that the private key will remain within this boundary. After finishing the proposed method, the new scope of the private key can be allocated as [d_il, d_ir], where d_ir ≤ n - 2. In fact, if the private key is extremely close to the new greatest lower bound, it can be retrieved quickly by performing a brute force attack, in which d_ir is decreased until it is equal to the private key. The experimental results indicate that the proposed method is extremely effective when the difference between prime factors is close to each other and one of two following requirement holds: the first condition is that the multiplier of Euler totient function is very close to the public key's small value whereas the second condition is that the public key should be large whenever the multiplier is far enough.

• Korean Journal of Soil Science and Fertilizer
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• v.39 no.5
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• pp.259-267
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• 2006

Hydraulic conductivity is the rate of water flux on hydraulic gradient. The van Genuchten Mualem (VGM) model is frequently used for describing unsaturated state of soils, that is composed with the function of soil water potential and soil water content and requests various parameters. This study is to get the value of VGM parameters used Rosetta computer program based on neural network analysis method and to calculate VGM parameters. VGM parameters included Ko(effective saturated hydraulic conductivity), ${\theta}r$(residual soil water content), ${\theta}s$(saturated soil water content), L, n and m. The unsaturated hydraulic conductivity at 10 kPa was calculated by using Rosetta program. Unsaturated hydraulic conductivities of 17 soil series at 1, 3, 5, 7 kPa were also obtained by applying saturated hydraulic conductivity by disk tension infiltrometer based on Gardner and Wooding's equation. Water flow at the water potential of 3 kPa was very low except Namgye, Hagog, Baegsan, Sangju, Seogcheon, Yesan soil series. Unsaturated hydraulic conductivity at 1 kPa showed the highest value for Samgag soil series and was in order of Yesan, Hwabong, Hagog and Baegsan soil series. Those of Gacheon, Seocheon and Ugog soil series were very low. When the value by VGM was compared with the value by disc tension infiltrometer, there was a tendency with exponential function to soils without gravel but there was no tendency to soils including gravel. Conclusively, it would be limited that VGM model for unsaturated hydraulic conductivity analysis applies to Korean agricultural land including gravel and having steep slope, shallow soil depth.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.5_6
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• pp.202-213
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• 2007

A network is an important model widely used in natural and social science as well as engineering. To analyze these networks easily it is necessary that we should layout the features of networks visually. These Graph-Layout researches have been performed recently according to the development of the computer technology. Among them, the Scale-free Network that stands out in these days is widely used in analyzing and understanding the complicated situations in various fields. The Scale-free Network is featured in two points. The first, the number of link(Degree) shows the Power-function distribution. The second, the network has the hub that has multiple links. Consequently, it is important for us to represent the hub visually in Scale-free Network but the existing Graph-layout algorithms only represent clusters for the present. Therefor in this thesis we suggest Graph-layout algorithm that effectively presents the Scale-free network. The Hubity(hub+ity) repulsive force between hubs in suggested algorithm in this thesis is in inverse proportion to the distance, and if the degree of hubs increases in a times the Hubity repulsive force between hubs is ${\alpha}^{\gamma}$ times (${\gamma}$??is a connection line index). Also, if the algorithm has the counter that controls the force in proportion to the total node number and the total link number, The Hubity repulsive force is independent of the scale of a network. The proposed algorithm is compared with Graph-layout algorithm through an experiment. The experimental process is as follows: First of all, make out the hub that exists in the network or not. Check out the connection line index to recognize the existence of hub, and then if the value of connection line index is between 2 and 3, then conclude the Scale-free network that has a hub. And then use the suggested algorithm. In result, We validated that the proposed Graph-layout algorithm showed the Scale-free network more effectively than the existing cluster-centered algorithms[Noack, etc.].

• Korean Chemical Engineering Research
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• v.45 no.2
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• pp.133-142
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• 2007

As the environmental pollution caused by excessive uses of chemical fertilizers and pesticides is aggravated, organic farming using pasture and livestock manure is gaining an increased necessity. The application rate of the organic farming materials to the field is determined as a function of crops and soil types, weather and cultivation surroundings. When livestock manure is used for organic farming materials, the volatilization of ammonia from field-spread animal manure is a major source of atmospheric pollution and leads to a significant reduction in the fertilizer value of the manure. Therefore, an ammonia emission model should be presented to reduce the ammonia emission and to know appropriate application rate of manure. In this study, the ammonia emission rate from field-applied pig manure is predicted using an artificial neural network (ANN) method, where the Michaelis-Menten equation is employed for the ammonia emission rate model. Two model parameters (total loss of ammonia emission rate and time to reach the half of the total emission rate) of the model are predicted using a feedforward-backpropagation ANN on the basis of the ALFAM (Ammonia Loss from Field-applied Animal Manure) database in Europe. The relative importance among 15 input variables influencing ammonia loss is identified using the weight partitioning method. As a result, the ammonia emission is influenced mush by the weather and the manure state.

• Korean Journal of Cognitive Science
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• v.16 no.4
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• pp.369-386
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• 2005

Although Intelligent Tutoring System(ITS) offers individualized learning environment that overcome limited function of existent CAI, and consider many learners' variable, there is little development to be using at the sites of schools because of inefficiency of investment and absence of pedagogical content knowledge representation techniques. To solve these problem, we should study a method, which represents knowledge for ITS, and which reuses knowledge base. On the pedagogical content knowledge, the knowledge in education differs from knowledge in a general sense. In this paper, we shall primarily address the multi-complex structure of knowledge and explanation of learning vein using multi-complex structure. Multi-Complex, which is organized into nodes, clusters and uses by knowledge base. In addition, it grows a adaptive knowledge base by self-learning. Therefore, in this paper, we propose the 'Extended Neural Logic Network(X-Neuronet)', which is based on Neural Logic Network with logical inference and topological inflexibility in cognition structure, and includes pedagogical content knowledge and object-oriented conception, verify validity. X-Neuronet defines that a knowledge is directive combination with inertia and weights, and offers basic conceptions for expression, logic operator for operation and processing, node value and connection weight, propagation rule, learning algorithm.