• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.1
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• pp.84-91
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• 2013

Ultrasonic flip-chip bonding needs a precise bonding tool which delivers ultrasonic energy into chip bumps effectively to use the selected resonance mode and frequency of the horn structure. The bonding tool is excited at the resonance frequency and the input and output ports should locate at the anti-nodal points of the resonance mode. In this study, we propose new design method with topology optimization for ultrasonic bonding tools. The SIMP(solid isotropic material with penalization) method is used to formulate topology optimization and OC(optimal criteria) algorithm is adopted for the update scheme. MAC(modal assurance criterion) tracking is used for the target frequency and mode. We fabricate two prototypes of ultrasonic tools which are based on 3D optimization models after reviewing 2D and 3D topology optimization results. The prototypes are satisfied with the ultrasonic frequency and vibration amplitude as the ultrasonic bonding tools.

• Journal of Electrical Engineering and Technology
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• v.12 no.4
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• pp.1519-1528
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• 2017

The paper proposes a well structured, component count waned single phase multilevel inverter (MLI) topology, which drives three different modules viz. Stipulation Based Sources Insertion (SBSI) module, Level Count Increasing (LCI) module and Inter-Linking H-Bridge (ILHB) module. The SBSI module confronts the number of basic sources needed in series/parallel to achieve required magnitude for any particular level. The LCI possesses an offsetting dc source and opuses to increase the number of levels and the ILHB module links the SBSI and LCI modules. A developed Hybrid Pulse Width Modulation (HPWM) strategy has PWM pulses for the switches of LCI module while the switches of the remaining two modules function at fundamental switching frequency. A fifteen level version of the proposed stipulation based sources insertion MLI (SBSIMLI) topology is simulated in MATLAB R2010a and a prototype of the similar specifications is constructed to validate the performance by experimental results. The comparison between the developed SBSIMLI topology and the competent topologies shows many interesting facts.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.1909-1928
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• 2020

Predicting human mobility has always been an important task in Location-based Social Network. Previous efforts fail to capture spatial dependence effectively, mainly reflected in weakening the location topology information. In this paper, we propose a neural network-based method which can capture spatial-temporal dependence to predict the next location of a person. Specifically, we involve a graph convolutional network (GCN) based on a seq2seq framework to capture the location topology information and temporal dependence, respectively. The encoder of the seq2seq framework first generates the hidden state and cell state of the historical trajectories. The GCN is then used to generate graph embeddings of the location topology graph. Finally, we predict future trajectories by aggregated temporal dependence and graph embeddings in the decoder. For evaluation, we leverage two real-world datasets, Foursquare and Gowalla. The experimental results demonstrate that our model has a better performance than the compared models.

• Journal of Communications and Networks
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• v.9 no.3
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• pp.282-295
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• 2007

Due to the nature that high datarate leads to shorter transmission range, the performance enhancement by high datarate 802.11 WLANs may be degraded when applying high datarate to an 802.11 based multihop ad hoc network. In this paper, we evaluate, through extensive simulations, the performance of multihop ad hoc networks at multiple transmission datarates, in terms of the number of hops between source and destination, throughput, end-to-end delay and packet loss. The study is conducted based on both stationary chain topology and mesh topologies with or without node mobility. From numerical results on network performance based on chain topology, we conclude that there is almost no benefit by applying the highest datarate when the chain length is 6 hops or more. With node mobility in mesh topology, the benefit of using high datarate diminishes at even shorter number of hops. To explore the main reasons for this behavior, analyses on multihop end-to-end throughput and network k-connectivity have been conducted later in the paper, and correspondingly an auto-rate adaptation algorithm has been proposed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.8
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• pp.2473-2489
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• 2022

Urban development has brought about the increasing saturation of urban traffic demand, and traffic congestion has become the primary problem in transportation. Roads are in a state of waiting in line or even congestion, which seriously affects people's enthusiasm and efficiency of travel. This paper mainly studies the discrete domain path planning method based on the flow data. Taking the traffic flow data based on the highway network structure as the research object, this paper uses the deep learning theory technology to complete the path weight determination process, optimizes the path planning algorithm, realizes the vehicle path planning application for the expressway, and carries on the deployment operation in the highway company. The path topology is constructed to transform the actual road information into abstract space that the machine can understand. An appropriate data structure is used for storage, and a path topology based on the modeling background of expressway is constructed to realize the mutual mapping between the two. Experiments show that the proposed method can further reduce the interpolation error, and the interpolation error in the case of random missing is smaller than that in the other two missing modes. In order to improve the real-time performance of vehicle path planning, the association features are selected, the path weights are calculated comprehensively, and the traditional path planning algorithm structure is optimized. It is of great significance for the sustainable development of cities.

• Steel and Composite Structures
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• v.44 no.5
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• pp.633-649
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• 2022

This paper is first implemented with the bending behavior of three-dimensional functionally graded (3DFG) plates in the framework of level set-based topology optimization (LS-based TO). Besides, due to the suitable properties of the current design domain, the thin-plate spline (TPS) is recognized as a RBF to construct the LS function. The overall mechanical properties of the 3DFG plate are assessed using a power-law distribution scheme via Mori-Tanaka micromechanical material model. The bending response is obtained using the first-order shear deformation theory (FSDT). The mixed interpolation of four elements of tensorial components (MITC4) is also implemented to overcome a well-known shear locking problem when the thickness becomes thinner. The Hamilton-Jacobi method is utilized in each iteration to enforce the necessary boundary conditions. The mathematical formulas are expressed in great detail for the LS-based TO using 3DFG materials. Several numerical examples are exhibited to verify the efficiency and reliability of the current methodology with the previously reported literature. Finally, the influences of FG materials in the optimized design are explained in detail to illustrate the behaviors of optimized structures.

• Journal of the Korean Society of Systems Engineering
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• v.20 no.spc1
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• pp.90-96
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• 2024

In this paper, we propose a technique to model high resolution seafloor topography with 1m intervals using actual water depth data near the east coast of the Korea with 1.6km distance intervals. Using a feature point extraction algorithm that harris corner based on deep learning, the location of the center of seafloor mountain was calculated and the surrounding topology was modeled. The modeled high-resolution seafloor topography based on deep learning was verified within 1.1m mean error between the actual warder dept data. And average error that result of calculating based on deep learning was reduced by 54.4% compared to the case that deep learning was not applied. The proposed algorithm is expected to generate high resolution underwater topology for the entire Korean peninsula and be used to establish a path plan for autonomous navigation of underwater vehicle.

• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.645-652
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• 2004

In this paper, we aggregate multi-links information between boundary nodes using the line segment scheme that aggregates topology in-formation within PG referring bandwidth and delay parameter. The proposed scheme can search multi-links efficiently using the depth priority method based on hop count instead of searching all links. To do this, we propose a modified line segment algorithm using two line segment method that represents two points which consist of delay-bandwidth pair to reduce topology information and provide a flexibility to the multi pie-links aggregation. And we apply it to current star topology aggregation. To evaluate performance of the proposed scheme, we compare/analyze the current method with the proposed scheme with respect to call success rate, access time and crankback rate. Through the simulation result analysis, the proposed star topology aggregation scheme presents the better performance than existing scheme.

• Bulletin of the Society of Naval Architects of Korea
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• v.35 no.3
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• pp.66-70
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• 1998

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.8
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• pp.49-58
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• 2016

In designing heterogeneous architecture based application-specific network-on-chips (NoCs), the opportunities of performance improvement would be expanded when applying asynchronous on-chip communication protocol. This is because the wire latency can be configured independently considering the wirelength of each link. In this paper, we develop the delay model of link-wire-length in asynchronous NoC and propose simulated annealing (SA) based floorplan-aware topology generation algorithm to optimize link-wirelengths. Incorporating the generated topology and the associated latency values across all links, we evaluate the performance using the floorplan-annotated sdf (standard delay format) file and RTL-synthesized gate-level netlist. Compared to TopGen, one of general topology generation algorithms, the experimental results show the reduction in latency by 13.7% and in execution time by 11.8% in average with regards to four applications.