• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2008.08a
• /
• pp.95-98
• /
• 2008

The vehicle has many technique change from The requirement of the safety the energy environment and convenience dimension is an enlargement toe. This is keeping changing the paradigm of the vehicle industry rapidly. The change to be technical such brought the intelligence of the former control device. And this organizes a sensor network among each systems and makes new traffic system. This paper a standard framework based on Sensor. We call it Vehicle Management System. The VMS used MOST network and It is able to make the stability of the component swap time or vehicle order the greatest.

• The KIPS Transactions:PartA
• /
• v.9A no.4
• /
• pp.405-412
• /
• 2002

The embedded system has less fast CPU and lower memory than PC(personal Computer) or Workstation system. Therefore embedded operating is system is designed to efficiently use the limited resource in the system. Virtual memory management or the embedded linux have a low efficiency when page fault is occurred to get a data from I/O device. Because a data is moving from the swap device to main memory. This paper suggests virtual memory compression algorithm for improving in virtual memory management and capacity of space. In this paper, we present a way to performance implement a virtual memory compression system that achieves significant improvement for the embedded system.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.10 no.4
• /
• pp.79-87
• /
• 2014

In this paper, we implemented the HearCAM platform with Raspberry PI B+ model which is an open source platform. Raspberry PI B+ model consists of dual step-down (buck) power supply with polarity protection circuit and hot-swap protection, Broadcom SoC BCM2835 running at 700MHz, 512MB RAM solered on top of the Broadcom chip, and PI camera serial connector. In this paper, we used the Google speech recognition engine for recognizing the voice characteristics, and implemented the pattern matching with OpenCV software, and extended the functionality of speech ability with SVOX TTS(Text-to-speech) as the matching result talking to the microphone of users. And therefore we implemented the functions of the HearCAM for identifying the voice and pattern characteristics of target image scanning with PI camera with gathering the temperature sensor data under IoT environment. we implemented the speech recognition, pattern matching, and temperature sensor data logging with Wi-Fi wireless communication. And then we directly designed and made the shape of HearCAM with 3D printing technology.

• Nuclear Engineering and Technology
• /
• v.54 no.10
• /
• pp.3888-3896
• /
• 2022

Nuclear data is the basis of reactor physics analysis. This paper aim at studying the influence of major evaluated nuclear data libraries, CENDL-3.2, ENDF/B-VIII.0, JEFF-3.3, and JENDL-4.0u, on the neutronics modelling of CEFR start-up tests. Results show these four libraries have a good performance and consistency in the modelling CEFR start-up tests. The JEFF-3.3 results exhibit only an 8 pcm k_eff difference with the measurement. The difference in criticality is decomposed by nuclide, which shows the large overestimation of CENDL-3.2 is mainly from the cross-section of ⁵²Cr. Except for few cases, the calculation results are within 1σ of measurement uncertainty in control rod worth, sodium void reactivity, temperature reactivity, and subassembly swap reactivity. In the evaluation of axial and radial reaction distribution, there are about 65% of relative errors that are less than 5% and 82% of relative errors that are less than 10%.

• Nuclear Engineering and Technology
• /
• v.54 no.10
• /
• pp.3897-3908
• /
• 2022

High-fidelity nuclear data libraries and neutronics simulation tools are essential for the development of fast reactors. The IAEA coordinated research project on "Neutronics Benchmark of CEFR Start-Up Tests" offers valuable data for the qualification of nuclear data libraries and neutronics codes. This paper focuses on the verification and validation of the CEFR start-up modelling using OpenMC Monte-Carlo code against the experimental measurements. The OpenMC simulation results agree well with the measurements in criticality, control rod worth, sodium void reactivity, temperature reactivity, subassembly swap reactivity, and reaction distribution. In feedback coefficient evaluations, an additional state method shows high consistency with lower uncertainty. Among 122 relative errors in the benchmark of the distribution of nuclear reaction, 104 errors are less than 10% and 84 errors are less than 5%. The results demonstrate the high reliability of OpenMC for its application in fast reactor simulations. In the companion paper, the influence of cross-section libraries is investigated using neutronics modelling in this paper.

• Journal of Broadcast Engineering
• /
• v.27 no.1
• /
• pp.13-19
• /
• 2022

Video Object Segmentation (VOS) task requires an amount of labeled sequence data, which limits the performance of the current VOS methods trained with public datasets. In this paper, we propose two effective data augmentation schemes for VOS. The first augmentation method is to swap the background segment to the background from another image, and the other method is to play the sequence in reverse. The two augmentation schemes for VOS enable the current VOS methods to robustly predict the segmentation labels and improve the performance of VOS.

• International Journal of Computer Science & Network Security
• /
• v.23 no.6
• /
• pp.193-201
• /
• 2023

In this paper, we consider the maximum scatter traveling salesman problem (MSTSP), a travelling salesman problem (TSP) variant. The problem aims to maximize the minimum length edge in a salesman's tour that travels each city only once in a network. It is a very complicated NP-hard problem, and hence, exact solutions can be found for small sized problems only. For large-sized problems, heuristic algorithms must be applied, and genetic algorithms (GAs) are found to be very successfully to deal with such problems. So, this paper develops a hybrid GA (HGA) for solving the problem. Our proposed HGA uses sequential sampling algorithm along with 2-opt search for initial population generation, sequential constructive crossover, adaptive mutation, randomly selected one of three local search approaches, and the partially mapped crossover along with swap mutation for perturbation procedure to find better quality solution to the MSTSP. Finally, the suggested HGA is compared with a state-of-art algorithm by solving some TSPLIB symmetric instances of many sizes. Our computational experience reveals that the suggested HGA is better. Further, we provide solutions to some asymmetric TSPLIB instances of many sizes.

• The Journal of Bigdata
• /
• v.7 no.2
• /
• pp.225-234
• /
• 2022

In this paper, we study the recent changes in the credit risk interconnectedness in Korea. Using the CDS spread data from November 2015 to August 2022, we estimate the network structure of sovereign and corporate credit risk. The results show that sovereign and corporate credit risks are interconnected significantly, particularly with respect to the banking sector where FX-related transactions are made. Since 2022 when the monetary policy has become contractionary, such credit risk interconnectedness seems to be strengthened because of greater common exposure.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.18 no.3
• /
• pp.201-207
• /
• 2018

There is no known polynomial time algorithm for random-type quadratic assignment problem(RQAP) that is a NP-complete problem. Therefore the heuristic or meta-heuristic approach are solve the approximated solution for the RQAP within polynomial time. This paper suggests polynomial time algorithm for random type quadratic assignment problem (QAP) with time complexity of $O(n^2)$. The proposed algorithm applies one-to-one matching strategy between ascending order of sum of distance for each location and descending order of sum of quantity for each facility. Then, swap the facilities for reflect the correlation of distances of locations and quantities of facilities. For the experimental data, this algorithm, in spite of $O(n^2)$ polynomial time algorithm, can be improve the solution than genetic algorithm a kind of metaheuristic method.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.10
• /
• pp.169-173
• /
• 2014

Nobody has yet been able to determine the optimal solution conclusively whether NP-complete problems are in fact solvable in polynomial time. Gu$\acute{e}$ret et al. tries to obtain the optimal solution using linear programming with $O(m^4)$ time complexity for barge loading problem a kind of bin packing problem that is classified as nondeterministic polynomial time (NP)-complete problem. On the other hand, this paper suggests the loading rule of profit priority rank algorithm with O(m log m) time complexity. This paper decides the profit priority rank firstly. Then, we obtain the initial loading result using the rule of loading the good has profit priority order. Finally, we balance the loading and capability of barge swap the goods of unloading in previously loading in case of under loading. As a result of experiments, this algorithm reduces the $O(m^4)$ of linear programming to O(m log m) time complexity for NP-complete barge loading problem.