• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.7 s.178
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• pp.1878-1884
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• 2000

In multibody dynamic analysis, one of the most important problems is to reduce computation times for real time simulation. In this paper, a symbolic computation method is implemented and tested for each dynamic analysis step. Applying symbolic formulations to the vehicle dynamics program AutoDyn7, the effectiveness of the symbolic computation method is verified.

• Transactions of the Korean Society of Mechanical Engineers
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• v.13 no.3
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• pp.500-507
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• 1989

The improvement of volumetric efficiency of air charging into combustion chamber is a primary requirement to obtain better mean effective pressure of an engine. Since parameters such as the air resistances in intake and exhaust flow passages, valve lift and valve timing influence greatly to the volumetric efficiency, it is very convenient and time saving if we can optimize these parameters by computation before we enter into long time fact finding engine tests. In this study we have developed a semi-empirical engine simulation program for the determinations of intake and exhaust valve timings, valve lifts, intake and exhaust port diameters in order to obtain highest volumetric efficiency. In this computation it requires only the measured variational pressures in intake and exhaust port. Using these variational pressures as an input data for our simulation program, we can calculate volumetric efficiency more accurately and can save computing time drastically. To confirm the validity of our simulation program we have made engine operation test in parallel and taken the experimental data. Comparing the computation result with the experimental data obtained through real engine test it has shown only the difference of 3%.

• Transactions of Materials Processing
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• v.7 no.5
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• pp.474-480
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• 1998

In the present study a domain decomposition scheme using the substructuring method is developed for the computational efficiency of the finite element analysis of metal forming processes. in order to avoid calculation of an inverse matrix during the substructuring procedure, the modified Cholesky decomposition method is implemented. As obtaining the data independence by the substructuring method the program is easily paralleized using the Parallel Virtual machine(PVM) library on a work-station cluster connected on networks. A numerical example for a simple upsetting is calculated and the speed-up ratio with respect to various number of subdomains and number of processors. The efficiency of the parallel computation is discussed by comparing the results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.23 no.4
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• pp.1024-1034
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• 1998

Most public cryptosystem widely used in communication network are based on the exponentiation-arithmetic. But, cryptosystem has to use bigger and bigger key parameter to attain an adequate level of security. This situation increases both computation and time delay. Montgomery, yang and Kawamura presented a method by using the pre-computation, intermediately computing and table look-up on modular reduction. Coster, Brickel and Lee persented also a method by using the pre-computation on exponentiation. This paper propose to reduce computation of exponentiation with spare prime. This method is to enhance computation efficiency in cryptosystem used discrete logarithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4081-4098
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• 2022

With the aim of tackling the contradiction between computation intensive industrial applications and resource-weak Edge Devices (EDs) in Industrial Internet of Things (IIoT), a novel computation task offloading scheme in SDIN-enabled MEC based IIoT is proposed in this paper. With the aim of reducing the task accomplished latency and energy consumption of EDs, a joint optimization method is proposed for optimizing the local CPU-cycle frequency, offloading decision, and wireless and computation resources allocation jointly. Based on the optimization, the task offloading problem is formulated into a Mixed Integer Nonlinear Programming (MINLP) problem which is a large-scale NP-hard problem. In order to solve this problem in an accessible time complexity, a sub-optimal algorithm GPCOA, which is based on hybrid evolutionary computation, is proposed. Outcomes of emulation revel that the proposed method outperforms other baseline methods, and the optimization result shows that the latency-related weight is efficient for reducing the task execution delay and improving the energy efficiency.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.188-196
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• 2022

Recently, neural architecture search (NAS) has received increasing attention as it can replace human experts in designing the architecture of neural networks for different tasks and has achieved remarkable results in many challenging tasks. In this study, a path-based computation neural architecture encoder (PCE) was proposed. Our PCE first encodes the computation of information on each path in a neural network, and then aggregates the encodings on all paths together through an attention mechanism, simulating the process of information computation along paths in a neural network and encoding the computation on the neural network instead of the structure of the graph, which is more consistent with the computational properties of neural networks. We performed an extensive comparison with eight encoding methods on two commonly used NAS search spaces (NAS-Bench-101 and NAS-Bench-201), which included a comparison of the predictive capabilities of performance predictors and search capabilities based on two search strategies (reinforcement learning-based and Bayesian optimization-based) when equipped with different encoders. Experimental evaluation shows that PCE is an efficient encoding method that effectively ranks and predicts neural architecture performance, thereby improving the search efficiency of neural architectures.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.9
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• pp.674-684
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• 2002

In order to decrease remarkably the computation time and storage used in the direct integration method without the loss of accuracy, authors suggest a new transient analysis algorithm. This algorithm is derived from the combination of three techniques, that is, the transfer technique of the transfer stiffness coefficient method, the modeling technique of the finite element method, and the numerical integration technique of the Newmark method. In this paper, the transient analysis algorithm of a frame structure is formulated by the proposed method. The accuracy and computation efficiency of the proposed method are demonstrated through the comparing with the computation results by the direct integration method for three computation models under various excitations.

• Smart Media Journal
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• v.12 no.3
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• pp.68-76
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• 2023

Emerging mobile edge computing (MEC) can be used in battery-constrained Internet of things (IoT). The execution latency of IoT applications can be improved by offloading computation-intensive tasks to an MEC server. Recently, the popularity of unmanned aerial vehicles (UAVs) has increased rapidly, and UAV-based MEC systems are receiving considerable attention. In this paper, we propose a dynamic computation offloading paradigm for UAV-based MEC systems, in which a UAV flies over an urban environment and provides edge services to IoT devices on the ground. Since most IoT devices are energy-constrained, we formulate our problem as a Markov decision process considering the energy level of the battery of each IoT device. We also use model-free Q-learning for time-critical tasks to maximize the system utility. According to our performance study, the proposed scheme can achieve desirable convergence properties and make intelligent offloading decisions.

• Journal of KIISE
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• v.42 no.6
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• pp.707-712
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• 2015

Mobile cloud computing is a technology that uses cloud services to overcome resource constrains of a mobile device, and it applies the computation offloading scheme to transfer a portion of a task which should be executed from a mobile device to the cloud. If the communication cost of the computation offloading is less than the computation cost of a mobile device, the mobile device commits a certain task to the cloud. The previous cost analysis models, which were used for separating functions running on a mobile device and functions transferring to the cloud, only considered the amount of data transfer and response time as the offloading cost. In this paper, we proposed a new task partitioning scheme that considers the frequency of function calls and data synchronization, during the cost estimation of the computation offloading. We also verified the energy efficiency of the proposed scheme by using experimental results.

• Journal of Korean Institute of Industrial Engineers
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• v.1 no.1
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• pp.67-71
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• 1975

This paper studies the efficiency of four algorithms in determining the shortest-route length between two specified nodes of a network in which every pair of nodes is connected by two nonnegative length arcs. The efficiency is measured in terms of number of additions and comparisons in computation of the shortest-route length. Also, each algorithm is programmed on the IBM 1130 for solving for example problems, and the computing time is measured for further efficiency comparisons.