• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.9 no.6
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• pp.761-767
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• 1998

The Perfectly Matched Layer(PML) provide good performance in absorption over a wide frequency range and is an appropriate ABC for waveguides with high dispersion. In this paper, a novel algorithm is proposed to improve the computational efficiency of the PML. In the input and output ports, the fields are decomposed into a series of modes, and then an appropriate ABC is applied to each mode. CPU time and memory storage requirements are greatly reduced, since the computational region is analyzed in one dimension. A WG-90 rectangular waveguide with a thick asymmetric iris is analyzed by Finite-Difference Time-Domain(FDTD) simulations with the conventional PML and the proposed one-dimensional (1-D) PML. Numerical results show that the computational efficiency is significantly improved by the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.9
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• pp.4512-4526
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• 2018

The Internet of Things (IoT) has become an emerging industry that is broadly used in many fields from industrial and agricultural manufacturing to home automation and hospitality industry. Because of the sheer number of connected devices transmitting valuable data, the IoT infrastructures have become a main target for cyber-criminals. One of the key challenges in protecting IoT devices is the lack of security measures by design. Although there are many hardware and software based security solutions (firewalls, honeypots, IPDS, anti-virus etc.) for information systems, most of these solutions cannot be applied to IoT devices because of the fact that IoT devices have limited computing resources (CPU, RAM,). In this paper, we propose a honeypot system called HoneyThing for modem/router devices (i.e. a kind of IoT device). HoneyThing emulates TR-069 protocol which is prevalent protocol used to remotely manage customer-premises equipment (CPE) devices, e.g. modems, routers. Honeything also serves an embedded web server simulating a few actual, critical vulnerabilities associated with the implementation of TR-069 protocol. To show effectiveness of the HoneyThing in capturing real world attacks, we have deployed it in the Internet. The obtained results are highly promising and facilitate to reveal network attacks targeting to CPE devices.

• Nuclear Engineering and Technology
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• v.55 no.9
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• pp.3485-3492
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• 2023

One of the major topic of tokamak research is the determination of the magnetic profile due to magnetic coil fields and plasma current by mean of data from magnetic probes. The most practical approach is to use the current filament method, which models the plasma column with multiple current carrying filaments and the total current of these filaments is equal to the plasma current. Determining the plasma boundary in Alvand-U tokamak is the main purpose of this paper. In order to determine the magnetic field profile and plasma boundary, information concerning the magnetic coils, their position, and current is required in the computing code. Then, the plasma shape is determined and finally the plasma boundary is extracted by the code. In the conducted research, we discuss how to determine the plasma boundary and the performance of the computing code for extraction of the plasma boundary. The developed algorithm shows to be effective by running it in the regular pc machine with characteristics of Intel (R) core (TM) i3-10100 CPU @3.60 GHz and 8.00 GB of RAM. Finally, we present results of a test run for computing code using a typical experimental pulse.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.49-56
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• 2023

Computer architecture serves as a link between application requirements and underlying technology capabilities such as technical, mathematical, medical, and business applications' computational and storage demands are constantly increasing. Machine learning these days grown and used in many fields and it performed better than traditional computing in applications that need to be implemented by using mathematical algorithms. A mathematical algorithm requires more extensive and quicker calculations, higher computer architecture specification, and takes longer execution time. Therefore, there is a need to improve the use of computer hardware such as CPU, memory, etc. optimization has a main role to reduce the execution time and improve the utilization of computer recourses. And for the importance of execution time in implementing machine learning supervised module linear regression, in this paper we focus on optimizing machine learning algorithms, for this purpose we write a (Diabetes prediction program) and applying on it a Practical Swarm Optimization (PSO) to reduce the execution time and improve the utilization of computer resources. Finally, a massive improvement in execution time were observed.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.4
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• pp.144-159
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• 2014

Techniques for making a single panoramic image using multiple pictures are widely studied in many areas such as computer vision, computer graphics, etc. The panorama image can be applied to various fields like virtual reality, robot vision areas which require wide-angled shots as an useful way to overcome the limitations such as picture-angle, resolutions, and internal informations of an image taken from a single camera. It is so much meaningful in a point that a panoramic image usually provides better immersion feeling than a plain image. Although there are many ways to build a panoramic image, most of them are using the way of extracting feature points and matching points of each images for making a single panoramic image. In addition, those methods use the RANSAC(RANdom SAmple Consensus) algorithm with matching points and the Homography matrix to transform the image. The SURF(Speeded Up Robust Features) algorithm which is used in this paper to extract featuring points uses an image's black and white informations and local spatial informations. The SURF is widely being used since it is very much robust at detecting image's size, view-point changes, and additionally, faster than the SIFT(Scale Invariant Features Transform) algorithm. The SURF has a shortcoming of making an error which results in decreasing the RANSAC algorithm's performance speed when extracting image's feature points. As a result, this may increase the CPU usage occupation rate. The error of detecting matching points may role as a critical reason for disqualifying panoramic image's accuracy and lucidity. In this paper, in order to minimize errors of extracting matching points, we used $3{\times}3$ region's RGB pixel values around the matching points' coordinates to perform intermediate filtering process for removing wrong matching points. We have also presented analysis and evaluation results relating to enhanced working speed for producing a panorama image, CPU usage rate, extracted matching points' decreasing rate and accuracy.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.1
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• pp.90-100
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• 2011

We present a parallel bi-conjugate gradient (Bi-CG) matrix solver for large scale Bio-FET simulations based on recent graphics processing units (GPUs) which can realize a large-scale parallel processing with very low cost. The proposed method is focused on solving the Poisson equation in a parallel way, which requires massive computational resources in not only semiconductor simulation, but also other various fields including computational fluid dynamics and heat transfer simulations. As a result, our solver is around 30 times faster than those with traditional methods based on single core CPU systems in solving the Possion equation in a 3D FDM (Finite Difference Method) scheme. The proposed method is implemented and tested based on NVIDIA's CUDA (Compute Unified Device Architecture) environment which enables general purpose parallel processing in GPUs. Unlike other similar GPU-based approaches which apply usually 32-bit single-precision floating point arithmetics, we use 64-bit double-precision operations for better convergence. Applications on the CUDA platform are rather easy to implement but very hard to get optimized performances. In this regard, we also discuss the optimization strategy of the proposed method.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.2
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• pp.67-74
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• 2013

Approximate string matching problems have been studied in diverse fields. Recently, fast approximate string matching algorithms are being used to reduce the time and costs for the next generation sequencing. To measure the amounts of errors between two strings, we use a distance function such as the edit distance. Given two strings X(|X| = m) and Y(|Y| = n) over an alphabet ${\Sigma}$, the edit distance between X and Y is the minimum number of edit operations to convert X into Y. The edit distance between X and Y can be computed using the well-known dynamic programming technique in O(mn) time and space. The edit distance also can be computed using the Four-Russians' algorithm whose preprocessing step runs in $O((3{\mid}{\Sigma}{\mid})^{2t}t^2)$ time and $O((3{\mid}{\Sigma}{\mid})^{2t}t)$ space and the computation step runs in O(mn/t) time and O(mn) space where t represents the size of the block. In this paper, we present a parallelized version of the computation step of the Four-Russians' algorithm. Our algorithm computes the edit distance between X and Y in O(m+n) time using m/t threads. Then we implemented both the sequential version and our parallelized version of the Four-Russians' algorithm using CUDA to compare the execution times. When t = 1 and t = 2, our algorithm runs about 10 times and 3 times faster than the sequential algorithm, respectively.

• Atmosphere
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• v.29 no.1
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• pp.87-103
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• 2019

This study introduces the overall characteristics of LOVECLIM version 1.3, the earth system model of intermediate complexity (EMIC), including the installation and operation processes by conducting two kinds of past climate simulation. First climate simulation is the equilibrium experiment during the mid-Holocene (6,000 BP), when orbital parameters were different compared to those at present. The overall accuracy of simulated global atmospheric fields by LOVECLIM is relatively lower than that in Coupled Model Intercomparison Project phase 5 (CMIP5) and Paleoclimate modelling Intercomparison Project phase 3 (PMIP3) simulations. However, surface temperature over the globe, the 800 hPa meridional wind over the mid-latitude coastal region, and the 200 hPa zonal wind from LOVECLIM show similar spatial distribution to those multi-model mean of CMIP5/PMIP3 climate models. Second one is the transient climate experiment from mid-Holocene to present. LOVECLIM well captures the major differences in surface temperature between preindustrial and mid-Holocene simulations by CMIP5/PMIP3 multi-model mean, even though it was performed with short integration time (i.e., about four days in a single CPU environment). In this way, although the earth system model of intermediate complexity has a limit due to its relatively low accuracy, it can be a very useful tool in the specific research area such as paleoclimate.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.12
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• pp.1403-1413
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• 2014

Structural optimization is widely accepted in industrial fields. Structural optimization pursues improved performance of the structures. Recently, structural optimization is actively utilized due to the well-developed commercial design software systems. Three popular commercial structural optimization systems are investigated and compared. They are MSC.Nastran, Genesis and OptiStruct. The performance of the systems is analyzed based on the quality of the optimum solution and the computational time. Linear static response size, shape and topology optimizations are explored and compared with some test examples. For fair comparison, the systems are run in the same environment and the optimization parameters affecting the performance are unified. The optimization results are analyzed and the performances and characteristics of each software system are discussed.

• Proceedings of the KOSOMBE Conference
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• v.1998 no.11
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• pp.317-318
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• 1998

The purpose of this study is to design and develop the circuit of the dual mode syringe pump. Syringe pump is used in intensive care unit, delivery room, pediatric room, operating theater and other fields of hospital at present. Normally the syringe pump delivers one medicine in one case, but in case of intensive care unit, it is necessary to deliver more than two kinds of medicines at a time. Therefore we have designed dual mode syringe pump. We used RISC type microcontroller, PIC17C44 as master controller, and PIC16C73 as slave cpu using for the low power consumption. The performance of system is evaluated by analysis of the linearity and accuracy which is the most important factors in application. While the proposed system shows a acceptable linearity and accuracy, a further research about reducing the errorr should be done.