• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.15-18
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• 2008

WDM is an incredibly promising technique in which multiple channels are operated along a single fiber, providing the facilities of terabit per second bandwidth. Thus, the survivability of WDM networks becomes critical for the success of the next generation internet architecture. Despite the fact that the path-based proactive restoration scheme guarantees 100% restoration as it computes a backup light path while the primary light path is being set up, this method results in additional capacity consumption. In this paper, an ideal technique is proposed that modifies the active multi-backup paths method and results in a better restoration scheme. Based on a theoretical analysis, a new method is shown to reduce the number of hopes as well as the restoration time.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.700-705
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• 2006

This paper proposes a collision avoidance algorithm for two mobile robots with independent goals in a same workspace. Using skeleton map, an environment is presented as a graph consisting of nodes and arcs. Robots generate the shortest set of paths using the combination of objective functions of the two robots. Path for collision avoidance of a robot can be selected among three class; the shortest path, detour, paths with a waiting time at safety points around crossing points. Simulation results are presented to verify the efficiency of the proposed algorithms.

• The Journal of Korea Robotics Society
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• v.3 no.1
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• pp.1-8
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• 2008

Automatic parking assist system is one of the key technologies of the future automobiles. Control problem of a car-like vehicle is not easy due to the nonholonomic constraints. In this paper, a practical solution for planning a car-parking path is proposed according to the proposed motion space (M-space) approach. The M-space is the extension of the conventional configuration space (C-space). A collision-free, nonholonomic feasible path can be directly computed by the M-space conversion and a back-propagation of reachable regions from the goal. The proposed planning scheme provide not a single solution, but also a candidate solution set, therefore, optimization of the parking path can be easily carried out with respect to performance criteria such as safety, maneuvering, and so on. Presented simulation results clearly show that the proposed scheme provides various practical solutions.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.21-30
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• 2007

The inverse offset method (IOM) is widely used for generating cutter paths from the point-based surface where the surface is characterised by a set of surface points rather than parametric polynomial surface equations. In the IOM, cutter path planning is carried out by specifying the grid sizes, called the step-forward and step-interval distances respectively in the forward and transverse cutting directions. The step-forward distance causes the chordal deviation and the step-forward distance produces the cusp. The chordal deviation and cusp are also functions of local surface slopes and curvatures. As the slopes and curvatures vary over the surface, different step-forward and step-interval distances are appropriate in different areas for obtaining the machined surface accurately and efficiently. In this paper, the chordal deviation and cusp height are calculated in consideration with the surface slopes and curvatures, and their combined effect is used to estimate the machined surface error. An adaptive grid generation algorithm is proposed, which enables the IOM to generate cutter paths adaptively using different step-forward and step-interval distances in different regions rather than constant step-forward and step-interval distances for entire surface.

• Smart Media Journal
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• v.7 no.2
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• pp.9-14
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• 2018

The k-ary n-cube $Q^k_n$ is widely used in the design and implementation of parallel and distributed processing architectures. It consists of $k^n$ identical nodes, each node having degree 2n is connected through bidirectional, point-to-point communication channels to different neighbors. On $Q^k_n$ we would like to transmit packets from a source node to 2n destination nodes simultaneously along paths on this network, the $i^{th}$ packet will be transmitted along the $i^{th}$ path, where $0{\leq}i{\leq}2n-1$. In order for all packets to arrive at a destination node quickly and securely, we present an $O(n^3)$ routing algorithm on $Q^k_n$ for generating a set of one-to-many node-disjoint and nearly shortest paths, where each path is either shortest or nearly shortest and the total length of these paths is nearly minimum since the path is mainly determined by employing the Hungarian method.

• Journal of Integrative Natural Science
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• v.12 no.1
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• pp.14-19
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• 2019

In this paper, we propose a system for controlling the brightness of street lights by predicting pedestrian paths, identifying the position of pedestrians with motion sensing sensors and obtaining motion vectors based on past walking directions, then predicting pedestrian paths through the route prediction smart street lighting system. In addition, by using motion vector data, the pre-treatment process using linear interpolation method and the fuzzy system and neural network system were designed in parallel structure to increase efficiency and the rough set was used to correct errors. It is expected that the system proposed in this paper will be effective in securing the safety of pedestrians and reducing light pollution and energy by predicting the path of pedestrians in the detection of movement of pedestrians and in conjunction with smart street lightings.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.1-12
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• 2021

In this paper, we present a new architecture for semantic segmentation. Semantic segmentation aims at a pixel-wise classification which is important to fully understand images. Previous semantic segmentation networks use features of multi-layers in the encoder to predict final results. However, they do not contain various receptive fields in the multi-layers features, which easily lead to inaccurate results for boundaries between different classes and small objects. To solve this problem, we propose a multi-path feature fusion module that allows for features of each layers to contain various receptive fields by use of a set of dilated convolutions with different dilatation rates. Various experiments demonstrate that our method outperforms previous methods in terms of mean intersection over unit (mIoU).

• ETRI Journal
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• v.43 no.6
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• pp.1013-1023
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• 2021

In this study, we propose a practical path planning method that combines the A^* search algorithm and minimum snap trajectory generation. The A^* search algorithm determines a set of waypoints to avoid collisions with surrounding obstacles from a starting to a destination point. Only essential waypoints (waypoints necessary to generate smooth trajectories) are extracted from the waypoints determined by the A^* search algorithm, and an appropriate time between two adjacent waypoints is allocated. The waypoints so determined are connected by a smooth minimum snap trajectory, a dynamically executable trajectory for the quadrotor. If the generated trajectory is invalid, we methodically determine when intermediate waypoints are needed and how to insert the points to modify the trajectory. We verified the performance of the proposed method by various simulation experiments and a real-world experiment in a forested outdoor environment.

• Structural Engineering and Mechanics
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• v.81 no.6
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• pp.665-675
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• 2022

The safety problems of giant hydraulic structures such as dams caused by terrorist attacks, earthquakes, and wars often have an important impact on a country's economy and people's livelihood. For the national defense department, timely and effective assessment of damage to or impending damage to dams and other structures is an important issue related to the safety of people's lives and property. In the field of damage assessment and vulnerability analysis, it is usually necessary to give the damage assessment results within a few minutes to determine the physical damage (crack length, crater size, etc.) and functional damage (decreased power generation capacity, dam stability descent, etc.), so that other defense and security departments can take corresponding measures to control potential other hazards. Although traditional numerical calculation methods can accurately calculate the crack length and crater size under certain combat conditions, it usually takes a long time and is not suitable for rapid damage assessment. In order to solve similar problems, this article combines simulation calculation methods with machine learning technology interdisciplinary. First, the common concrete gravity dam shape was selected as the simulation calculation object, and XFEM (Extended Finite Element Method) was used to simulate and calculate 19 cracks with different initial positions. Then, an LSTM (Long-Short Term Memory) machine learning model was established. 15 crack paths were selected as the training set and others were set for test. At last, the LSTM model was trained by the training set, and the prediction results on the crack path were compared with the test set. The results show that this method can be used to predict the crack propagation path rapidly and accurately. In general, this article explores the application of machine learning related technologies in the field of mechanics. It has broad application prospects in the fields of damage assessment and vulnerability analysis.

• Journal of Information Processing Systems
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• v.7 no.2
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• pp.241-260
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• 2011

In earlier days, most of the data carried on communication networks was textual data requiring limited bandwidth. With the rise of multimedia and network technologies, the bandwidth requirements of data have increased considerably. If a network link at any time is not able to meet the minimum bandwidth requirement of data, data transmission at that path becomes difficult, which leads to network congestion. This causes delay in data transmission and might also lead to packet drops in the network. The retransmission of these lost packets would aggravate the situation and jam the network. In this paper, we aim at providing a solution to the problem of network congestion in mobile ad hoc networks [1, 2] by designing a protocol that performs routing intelligently and minimizes the delay in data transmission. Our Objective is to move the traffic away from the shortest path obtained by a suitable shortest path calculation algorithm to a less congested path so as to minimize the number of packet drops during data transmission and to avoid unnecessary delay. For this we have proposed a protocol named as Congestion Aware Selection Of Path With Efficient Routing (CASPER). Here, a router runs the shortest path algorithm after pruning those links that violate a given set of constraints. The proposed protocol has been compared with two link state protocols namely, OSPF [3, 4] and OLSR [5, 6, 7, 8].The results achieved show that our protocol performs better in terms of network throughput and transmission delay in case of bulky data transmission.