• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.4
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• pp.154-160
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• 2003

This paper is proposed a ANN-based rotor position and speed estimation method for IPMSM by measuring the currents. Because the proposed estimator treats the estimated motor speed as the weights, it is possible to estimate motor speed to adapt back propagation algorithm with 2 layered neural network. The proposed control algorithm is applied to IPMSM drive system. The operating characteristics controlled by neural networks are examined in detail.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1471-1478
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• 2011

A typical standard of vehicular ad hoc networks, WAVE which consists of IEEE 1609.x Family standards and IEEE 802.11p standard, includes the multi-channel coordination and channel synchronization function to provide safety services or public services during a car is driven. Generally, the performance of data communication and networking technologies is evaluated by using simulation tools, such as ns-2, OPNET, OPNET++, etc. However, these tools doesn't provide the operations of WAVE protocol. Therefore, in this paper, we implement and verify WAVE simulation program based on ns-2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1285-1294
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• 1999

In this paper we consider the performance of TCP video traffic over ABR with Long-Range Dependent VBR traffic. As compressed coded video traffics are increasing rapidly over Internet, lots of studies are being done for transmitting those traffics efficiently using limited network resources. We consider here the transmitting video service over ABR service in ATM networks, especially satellite networks. CBR or VBR services are suggested in transmitting the video traffic in ATM Forum TM 4.0. But ABR service connection, which is considered as appropriate service for data traffic, can be established with a small amount of bandwidth, MCR (Minimum cell rate). Furthermore ABR service can control the source's transmitting rate using feedback mechanism. Using this feature ABR service can be used in some applications which can control their quality of services corresponding to network loads. Compressed video sources with MPEG-2 are used for Long-Range Dependent VBR traffic here. We model the compressed video source to resemble the MPEG-2 transport streams. These compressed video traffic streams are consisted of three different frames, I-frame, P-frame, and B-frame. So when a network are overloaded, we can control the quality of service using this traffic features. TCP Traffics over ABR need large buffers in ATM switch to satisfy their QoS with background VBR traffics, which have high deviations in bandwidth. Furthermore satellite ATM networks with large feedback delay need large buffers corresponding RTT delay. The performance comparisons among EFCI and ER switch (ERICA+) switches in the network circumstances described above were shown in this paper. We also considered the case with ON-OFF VBR traffics.

• Polymer(Korea)
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• v.38 no.5
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• pp.588-595
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• 2014

A semi-interpenetrating polymer network (semi-IPN) hydrogel composed of crosslinked chitosan and poly (acrylic acid-co-crotonic acid) was prepared in the presence of glutaraldehyde (GA) as a crosslinker. Fourier-transform infrared, thermogravimetric analysis and scanning electron microscopy were employed to confirm the structure of the semi-IPN hydrogel. The swelling capacity of hydrogel was shown to be affected by the monomers weight ratio, chitosan content, initiator and GA concentrations. The results also indicated that the semi-IPN hydrogel had different swelling capacity at various pHs. Additionally, the swelling behavior of the hydrogel was investigated in aqueous solutions of NaCl, $CaCl_2$, and $AlCl_3$.

• Journal of Information Technology Applications and Management
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• v.9 no.2
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• pp.1-16
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• 2002

Recently, neural network methods have been studied to find out more valuable information in data bases. But the supervised learning methods of neural networks have an overfitting problem, which leads to errors of target patterns. And the unsupervised learning methods can distort important information in the process of regularizing data. Thus they can't efficiently classify data, To solve the problems, this paper introduces a hybrid neural networks HACAB(Hybrid Algorithm combining a Competition learning model And BP Algorithm) combining a competition learning model and 8P algorithm. HACAB is designed for cases which there is no target patterns. HACAB makes target patterns by adopting a competition learning model and classifies input patterns using the target patterns by BP algorithm. HACAB is evaluated with random input patterns and Iris data In cases of no target patterns, HACAB can classify data more effectively than BP algorithm does.

• Journal of the Korean Institute of Telematics and Electronics
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• v.4 no.3
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• pp.2-8
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• 1967

A method is illustrated for minimizing the number of internal states in incompletely specified sequential networks. The starting point for minimizing technique in this paper is the set of maximal compatibility classes which covers the original flow table and the minimal covering can be obtained directly by employing three rules. The reduction techniques for prime implicant table or covering and closure table are not employed in this paper. Although the minimizing technique is applied to some specific problems, it is believed that the concepts are general in nature and can be applied to any type of incompletely specified flow tables.

• Journal of Communications and Networks
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• v.15 no.2
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• pp.179-190
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• 2013

Given the bandwidth assignment for dedicated short range communications for use in vehicular ad-hoc network (VANET) and the expected introduction of equipment in the next few years, we elaborate on how VANET can support infotainment services. We define an architectural model for the integration of VANETs and cellular networks, according to a push mode paradigm where VANETs are used primarily to disseminate service announcements and general interest messages. Cooperation with cellular network is addressed by comparing architecture alternatives. A set of information dissemination protocols for VANETs is compared via simulations on a real urban map. Some results from a lab testbed based on IEEE 802.11p boards are presented along with an application developed for Android operating system to demonstrate the concept of the paper.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.1
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• pp.28-36
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• 2007

Sensor networks are usually composed of tens or thousands of tiny devices with limited resources. Because of their limited resources, many researchers have studied on the energy management in the WSNs(Wireless Sensor Networks), especially taking into account communications efficiency. For effective data transmission and sensor fault detection in sensor network environment, a new remote monitoring system based on PCA(Principle Component Analysis) and AANN(Auto Associative Neural Network) is proposed. PCA and AANN have emerged as a useful tool for data compression and identification of abnormal data. Proposed system can be effectively applied to sensor network working in LEA2C(Low Energy Adaptive Connectionist Clustering) routing algorithms. To verify its applicability, some simulation studies on the data obtained from real WSNs are executed.

• Geomechanics and Engineering
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• v.1 no.4
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• pp.307-321
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• 2009

The paper employs a feed forward neural network with back-propagation algorithm for modeling time dependent swell in clays containing carbonate in the presence of sulfuric acid. The oedometer swell percent is estimated at a nominal surcharge pressure of 6.25 kPa to develop 612 data sets for modeling. The input parameters used in the network include time, sulfuric acid concentration, carbonate percentage, and liquid limit. Among the total data sets, 280 (46%) were assigned to training, 175 (29%) for testing and the remaining 157 data sets (25%) were relegated to cross validation. The network was programmed to process this information and predict the percent swell at any time, knowing the variable involved. The study demonstrates that it is possible to develop a general BPNN model that can predict time dependent swell with relatively high accuracy with observed data ($R^2$=0.9986). The obtained results are also compared with generated non-linear regression model.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.172-182
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• 2014

In this paper, we investigate the fundamental performance limits of the cooperative sensing using energy detection by considering the unlimited number of sensing nodes. Although a lot of cognitive radio research so far proposed various uses of energy detection because of its simplicity, the performance limits of energy detection have not been studied when a large number of sensing nodes exist. First, we show that when the sensing nodes see the independent and identically distributed channel conditions, then as the number of sensing nodes N goes to infinity, the OR rule of hard decision achieves zero of false alarm Pf for any given target probability of detection $\bar{P_d}$ irrespective of the non-zero received primary user signal to noise ratio ${\gamma}$. Second, we show that under the same condition, when the AND rule of hard decision is used, there exists a lower bound of $P_f$. Interestingly, however, for given $\bar{P_d}$, $P_f$ goes to 1 as N goes to infinity. Third, we show that when the soft decision is used, there exists a way of achieving 100% utilization of secondary user, i.e., the sensing time overhead ratio goes to zero so does $P_f$.We verify our analyses by performing extensive simulations of the proposed unlimited cooperative sensing. Finally, we suggest a way of incorporating the unlimited cooperative sensing into a practical cellular system such as long term evolutionadvanced by exploiting the existing frame structure of absolute blank subframe to implement the in-band sensing.