• Journal of Information Processing Systems
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• v.10 no.3
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• pp.459-470
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• 2014

In this paper, the average probability of the symbol error rate (SER) and throughput are studied in the presence of joint spectrum sensing and data transmission in a cognitive relay network, which is in the environment of an optimal power allocation strategy. In this investigation, the main component in calculating the secondary throughput is the inclusion of the spatial false alarms, in addition to the conventional false alarms. It has been shown that there exists an optimal secondary power amplification factor at which the probability of SER has a minimum value, whereas the throughput has a maximum value. We performed a Monte-Carlo simulation to validate the analytical results.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.10
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• pp.37-45
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• 1992

For a precise manipulator control in the presence of environmental uncertainties, it has long been recognized that the robot should be controlled in a task-referenced space. In this respect, an effective visual servo control system for robot manipulators based on neural networks is proposed. In the proposed control system, a Backpropagation neural network is used first to learn the mapping relationship between the robot's joint space and the video image space. However, in the real control loop, this network is not used in itself, but its first and second derivatives are used to generate servo commands for the robot. Second, and Adaline neural network is used to identify the approximately linear dynamics of the robot and also to generate the proper joint torque commands. Computer simulation has been performed demonstrating the proposed method's superior performance. Futrhermore, the proposed scheme can be effectively utilized in a robot skill acquisition system where the robot can be taught by watching a human behavioral task.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.3
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• pp.132-138
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• 2011

This paper presents an intelligent control approach for lateral position control of an autonomous four wheel steered snowplowing robotic vehicle. The vehicle is built for removing snow on the highway. Dynamics of the vehicle is derived and linearized for LQR control. Lateral position is controlled by the LQR method first, then the neural network control technique is introduced to improve tracking performances under the presence of load. The feasibility of using four wheel steering control is investigated by simulation studies of lateral position tracking of the Ford F-250 truck model. Performances of a LQR control method and a neural network control method under virtual snowplowing situation are compared.

• Computers and Concrete
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• v.30 no.3
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• pp.209-224
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• 2022

In this paper, the artificial neural network (ANN) is employed to predict the flexural behavior of reinforced concrete (RC) beams retrofitted with carbon fiber/epoxy composites modified by carbon nanotubes (CNTs). Multiple techniques are used to improve the accuracy of the ANN prediction, as the data represents a multivalued function. These techniques include static ANN modeling, ANN modeling with load history, and ANN modeling with double load history. The developed ANN models are used to predict the load-displacement profiles of beams retrofitted with either CFRP or CNTs modified CFRP, flexural capacity, and maximum displacement of the beams. The results demonstrate that the ANN is able to predict the flexural behavior of the retrofitted RC beams as well as the effect of each parameter including the type of the used epoxy and the presence of the CNTs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.295-296
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• 2021

In iris diagnostics, iris changes in its area on the iris map when abnormal changes in human tissues and organs occur in response to changes in color and iris structure. This makes it possible to determine the long-term condition in which an abnormal change has occurred, and to determine the presence or absence of a congenital illness. In this paper, we design a neural network algorithm that is displayed on the iris and classifies lesions by using a convolution neural network that has the advantage of advancing learning using images of various dip-running neural networks.

• Journal of information and communication convergence engineering
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• v.12 no.3
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• pp.135-139
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• 2014

Opportunistic routing was originally introduced in various multihop network environments to reduce the number of hops in such a way that, among the relays that decode the transmitted packet for the current hop, the one that is closest to the destination becomes the transmitter for the next hop. Unlike the conventional opportunistic routing case where there is a single active S-D pair, for an ad hoc network in the presence of fading, we investigate the performance of parallel opportunistic multihop routing that is simultaneously performed by many source-destination (S-D) pairs to maximize the opportunistic gain, thereby enabling us to obtain a logarithmic gain. We first analyze a cut-set upper bound on the throughput scaling law of the network. Second, computer simulations are performed to verify the performance of the existing opportunistic routing for finite network conditions and to show trends consistent with the analytical predictions in the scaling law. More specifically, we evaluate both power and delay with respect to the number of active S-D pairs and then, numerically show a net improvement in terms of the power-delay trade-off over the conventional multihop routing that does not consider the randomness of fading.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4701-4719
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• 2015

A Mobile Ad hoc Network (MANET) consists of mobile nodes which co-operate to forward each other's packets without the presence of any centralized authority. Due to this lack of centralized monitoring authority, MANETs have become vulnerable to various kinds of routing misbehaviour. Sometimes, nodes exhibit non-cooperating behaviour for conserving their own resources and exploiting others' by relaying their traffic. A node may even drop packets of other nodes in the guise of forwarding them. This paper proposes an efficient Reputation and Collaboration technique through route-request for handling such misbehaving nodes. It lays emphasis not only on direct observation but also considers the opinion of other nodes about misbehaving nodes in the network. Unlike existing schemes which generate separate messages for spreading second-hand information in the network, nodes purvey their opinion through route-request packet. Simulation studies reveal that the proposed scheme significantly improves the network performance by efficiently handling the misbehaving nodes in the network.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2144-2165
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• 2016

In a vehicular ad hoc network, the communication links are unsteady due to the rapidly changing topology, high mobility and traffic density in the urban environment. Most of the existing geographical routing protocols rely on the continuous transmission of beacon messages to update the neighbors' presence, leading to network congestion. Source-based approaches have been proven to be inefficient in the inherently unstable network. To this end, we propose an opportunistic beaconless packet forwarding approach based on a modified handshake mechanism for the urban vehicular environment. The protocol acts differently between intersections and at the intersection to find the next forwarder node toward the destination. The modified handshake mechanism contains link quality, forward progress and directional greedy metrics to determine the best relay node in the network. After designing the protocol, we compared its performance with existing routing protocols. The simulation results show the superior performance of the proposed protocol in terms of packet delay and data delivery ratio in realistic wireless channel conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5149-5173
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• 2016

Cooperative forwarding has shown a substantial network performance improvement compared to traditional routing in multi-hop wireless network. To further enhance the system throughput, especially in the presence of highly congested multiple cross traffic flows, a promising way is to incorporate the multi-radio multi-channel (MRMC) capability into cooperative forwarding. However, it requires to jointly address multiple issues. These include radio-channel assignment, routing metric computation, candidate relay set selection, candidate relay prioritization, data broadcasting over multi-radio multi-channel, and best relay selection using a coordination scheme. In this paper, we propose a simple and efficient cluster-based cooperative data forwarding (CCDF) which jointly addresses all these issues. We study the performance impact when the same candidate relay set is being used for multiple cross traffic flows in the network. The network simulation shows that the CCDF with MRMC not only retains the advantage of receiver diversity in cooperative forwarding but also minimizes the interference, which therefore further enhances the system throughput for the network with multiple cross traffic flows.