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A Dynamic QoS Adjustment Enabled and Load-balancing-aware Service Composition Method for Multiple Requests

  • Wu, Xiaozhu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.891-910
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    • 2021
  • Previous QoS-aware service composition methods mainly focus on how to generate composite service with the optimal QoS efficiently for a single request. However, in the real application scenarios, there are multiple service requests and multiple service providers. It is more important to compose services with suboptimal QoS and maintain the load balance between services. To solve this problem, in this paper, we propose a service composition method, named as dynamically change and balancing composition method (DCBC). It assumes that the QoS of service is not static, and the services can adjust the value of QoS to gain more opportunities to be selected for composition. The method mainly includes two steps, which are the preprocessing step and the service selection step. In the preprocessing step, a backward global best QoS calculation is performed which regarding the static and dynamic QoS respectively; then guided by the global QoS, the feasible services can be selected efficiently in the service selection step. The experiments show that the DCBC method can not only improve the overall quality of composite services but also guarantee the fulfill ratio of requests and the load balance of services.

Solar Cyclic Modulation of Diurnal Variation in Cosmic Ray Intensity

  • Park, Eun Ho;Jung, Jongil;Oh, Suyeon;Evenson, Paul
    • Journal of Astronomy and Space Sciences
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    • v.35 no.4
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    • pp.219-225
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    • 2018
  • Cosmic rays are ions that move at relativistic speeds. They generate secondary cosmic rays by successive collisions with atmospheric particles, and then, the secondary particles reach the ground. The secondary particles are mainly neutrons and muons, and the neutrons are observed by the ground neutron monitor. This study compared the diurnal variation in cosmic ray intensity obtained via harmonic analysis and that obtained through the pile-up method, which was examined in a previous study. In addition, we analyzed the maximum phase of the diurnal variation using four neutron monitors with a cutoff rigidity below approximately 6 GV, located at similar longitudes to the Oulu and Rome neutron monitors. Expanding the data of solar cycles 20-24, we examined the time of the maximum cosmic ray intensity, that is, the maximum phase regarding the solar cyclic modulation. During solar cycles 20-24, the maximum phase derived by harmonic analysis showed no significant difference with that derived by the pile-up method. Thus, the pile-up method, a relatively straightforward process to analyze diurnal variation, could replace the complex harmonic analysis. In addition, the maximum phase at six neutron monitors shows the 22-year cyclic variation very clearly. The maximum phase tends to appear earlier and increase the width of the variation in solar cycles as the cutoff rigidity increases.

Markov Model-based Static Obstacle Map Estimation for Perception of Automated Driving (자율주행 인지를 위한 마코브 모델 기반의 정지 장애물 추정 연구)

  • Yoon, Jeongsik;Yi, Kyongsu
    • Journal of Auto-vehicle Safety Association
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    • v.11 no.2
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    • pp.29-34
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    • 2019
  • This paper presents a new method for construction of a static obstacle map. A static obstacle is important since it is utilized to path planning and decision. Several established approaches generate static obstacle map by grid method and counting algorithm. However, these approaches are occasionally ineffective since the density of LiDAR layer is low. Our approach solved this problem by applying probability theory. First, we converted all LiDAR point to Gaussian distribution to considers an uncertainty of LiDAR point. This Gaussian distribution represents likelihood of obstacle. Second, we modeled dynamic transition of a static obstacle map by adopting the Hidden Markov Model. Due to the dynamic characteristics of the vehicle in relation to the conditions of the next stage only, a more accurate map of the obstacles can be obtained using the Hidden Markov Model. Experimental data obtained from test driving demonstrates that our approach is suitable for mapping static obstacles. In addition, this result shows that our algorithm has an advantage in estimating not only static obstacles but also dynamic characteristics of moving target such as driving vehicles.

Shuffling of Elliptic Curve Cryptography Key on Device Payment

  • Kennedy, Chinyere Grace;Cho, Dongsub
    • Journal of Korea Multimedia Society
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    • v.22 no.4
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    • pp.463-471
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    • 2019
  • The growth of mobile technology particularly smartphone applications such as ticketing, access control, and making payments are on the increase. Elliptic Curve Cryptography (ECC)-based systems have also become widely available in the market offering various convenient services by bringing smartphones in proximity to ECC-enabled objects. When a system user attempts to establish a connection, the AIK sends hashes to a server that then verifies the values. ECC can be used with various operating systems in conjunction with other technologies such as biometric verification systems, smart cards, anti-virus programs, and firewalls. The use of Elliptic-curve cryptography ensures efficient verification and signing of security status verification reports which allows the system to take advantage of Trusted Computing Technologies. This paper proposes a device payment method based on ECC and Shuffling based on distributed key exchange. Our study focuses on the secure and efficient implementation of ECC in payment device. This novel approach is well secure against intruders and will prevent the unauthorized extraction of information from communication. It converts plaintext into ASCII value that leads to the point of curve, then after, it performs shuffling to encrypt and decrypt the data to generate secret shared key used by both sender and receiver.

Manufacturing process improvement of offshore plant: Process mining technique and case study

  • Shin, Sung-chul;Kim, Seon Yeob;Noh, Chun-Myoung;Lee, Soon-sup;Lee, Jae-chul
    • Ocean Systems Engineering
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    • v.9 no.3
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    • pp.329-347
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    • 2019
  • The shipbuilding industry is characterized by order production, and various processes are performed simultaneously in the construction of ships. Therefore, effective management of the production process and productivity improvement form important key factors in the industry. For decades, researchers and process managers have attempted to improve processes by using business process analysis (BPA). However, conventional BPA is time-consuming, expensive, and mainly based on subjective results generated by employees, which may not always correspond to the actual conditions. This paper proposes a method to improve the production process of offshore plant modules by analysing the process mining data obtained from the shipbuilding industry. Process mining uses information accumulated from the system-provided event logs to generate a process model and determine the values hidden within the process. The discovered process is visualized as a process model. Subsequently, alternatives are proposed by brainstorming problems (such as bottlenecks or idle time) in the process. The results of this study can aid in productivity improvement (idle time or bottleneck reduction in the production process) in conjunction with a six-sigma technique or ERP system. In future, it is necessary to study the standardization of the module production processes and development of the process monitoring system.

A Study on the Improvement in Productivity and Safetiness for Calcination Process of Automotive Catalyst by Using Design of Experiment (실험계획을 통한 자동차 촉매 소성 공정의 생산성 향상과 안정성 증대 연구)

  • Jung, Chule-kyou;Lee, Chang-Ho
    • Journal of the Korea Safety Management & Science
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    • v.21 no.1
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    • pp.17-23
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    • 2019
  • The diesel engine generate many pollutants such as PM(Particulate matter) and NOx(Nitrogen oxide). So the SCR(Selective catalytic reduction) must be required to meet the emission standard. The SCR catalyst market is growing rapidly, and the automobile markets using alternative energy sources are growing rapidly. This study deals with optimization of the calcination process the manufacturing process of SCR catalyst to be competitive. The calcination process is a bottleneck and it is required to optimize productivity and accept to be safety, But we cannot trade off anything in terms of safety. We applied DOE(Design of experiments) among many research methods performed in various fields. In order to achieve quality and productivity optimization. The dependent variables in the DOE were selected as NO Conversion(%). The independent variables were selected as the calcination temperature, soaking time and fan speed RPM. the CCD(Central composite designs) constructs response surface using the data onto experience and finds optimum levels within the fitted response surfaces. Our tests are our stability guarantee and efficient together with operation.

Deep Learning Based Gray Image Generation from 3D LiDAR Reflection Intensity (딥러닝 기반 3차원 라이다의 반사율 세기 신호를 이용한 흑백 영상 생성 기법)

  • Kim, Hyun-Koo;Yoo, Kook-Yeol;Park, Ju H.;Jung, Ho-Youl
    • IEMEK Journal of Embedded Systems and Applications
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    • v.14 no.1
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    • pp.1-9
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    • 2019
  • In this paper, we propose a method of generating a 2D gray image from LiDAR 3D reflection intensity. The proposed method uses the Fully Convolutional Network (FCN) to generate the gray image from 2D reflection intensity which is projected from LiDAR 3D intensity. Both encoder and decoder of FCN are configured with several convolution blocks in the symmetric fashion. Each convolution block consists of a convolution layer with $3{\times}3$ filter, batch normalization layer and activation function. The performance of the proposed method architecture is empirically evaluated by varying depths of convolution blocks. The well-known KITTI data set for various scenarios is used for training and performance evaluation. The simulation results show that the proposed method produces the improvements of 8.56 dB in peak signal-to-noise ratio and 0.33 in structural similarity index measure compared with conventional interpolation methods such as inverse distance weighted and nearest neighbor. The proposed method can be possibly used as an assistance tool in the night-time driving system for autonomous vehicles.

Application of Deep Learning to Solar Data: 2. Generation of Solar UV & EUV images from magnetograms

  • Park, Eunsu;Moon, Yong-Jae;Lee, Harim;Lim, Daye
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.1
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    • pp.81.3-81.3
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    • 2019
  • In this study, we apply conditional Generative Adversarial Network, which is one of the deep learning method, to the image-to-image translation from solar magentograms to solar UV and EUV images. For this, we train a model using pairs of SDO/AIA 9 wavelength UV and EUV images and their corresponding SDO/HMI line-of-sight magnetograms from 2011 to 2017 except August and September each year. We evaluate the model by comparing pairs of SDO/AIA images and corresponding generated ones in August and September. Our results from this study are as follows. First, we successfully generate SDO/AIA like solar UV and EUV images from SDO/HMI magnetograms. Second, our model has pixel-to-pixel correlation coefficients (CC) higher than 0.8 except 171. Third, our model slightly underestimates the pixel values in the view of Relative Error (RE), but the values are quite small. Fourth, considering CC and RE together, 1600 and 1700 photospheric UV line images, which have quite similar structures to the corresponding magnetogram, have the best results compared to other lines. This methodology can be applicable to many scientific fields that use several different filter images.

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Feasibility Study for Development of New Stationkeeping System (Flapping Foil을 적용한 위치유지시스템 개발을 위한 운동시험)

  • Yu, Young-Jae;Sim, Woo-Lim;Kumar, Rupesh;Kim, Dong-Ju;Shin, Hyun-Kyoung
    • Journal of Ocean Engineering and Technology
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    • v.33 no.2
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    • pp.189-195
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    • 2019
  • In this study, experiments with a floater using flapping foils were performed to develop a new station keeping system that can maintain its position in waves without mooring lines. The foils applied to this system generate thrust using wave energy. In this experiment, the motion of the floater was analyzed in three different wave periods. Sixteen foils were attached to the cylindrical floater. The thrust of each foil was controlled by changing its azimuth angle, and three cases were compared. Based on the previous data, we made more precise measurements and found an optimal model for stationkeeping under each wave condition. We verified the potential of this new stationkeeping system using flapping foils, and conclusions were drawn from the results.

The critical angle of seismic incidence of transmission tower-line system based on wavelet energy method

  • Tian, Li;Dong, Xu;Pan, Haiyang;He, Xiaoyu
    • Earthquakes and Structures
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    • v.17 no.4
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    • pp.387-398
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    • 2019
  • On the basis that ground motions may arrive at a structure from any horizontal direction and that different directions of seismic incidence would result in different structural dynamic responses, this paper focuses on orienting the crucial seismic incidence of transmission tower-line systems based on the wavelet energy method. A typical transmission tower-line system is chosen as the case study, and two finite element (FE) models are established in ABAQUS, with and without consideration of the interaction between the transmission towers and the transmission lines. The mode combination frequency is defined by considering the influence of the higher-order modes of the structure. Subsequently, wavelet transformation is performed to obtain the total effective energy input and the effective energy input rate corresponding to the mode combination frequency to further judge the critical angle of seismic incidence by comparing these two performance indexes under different seismic incidence angles. To validate this approach, finite element history analysis (FEHA) is imposed on both FE models to generate comparative data, and good agreement is found. The results demonstrate that the wavelet energy method can forecast the critical angle of seismic incidence of a transmission tower-line system with adequate accuracy, avoiding time-consuming and cumbersome computer analysis. The proposed approach can be used in future seismic design of transmission tower-line systems.