• Title/Summary/Keyword: meta power

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Robust design on the arrangement of a sail and control planes for improvement of underwater Vehicle's maneuverability

  • Wu, Sheng-Ju;Lin, Chun-Cheng;Liu, Tsung-Lung;Su, I-Hsuan
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.617-635
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    • 2020
  • The purpose of this study is to discuss how to improve the maneuverability of lifting and diving for underwater vehicle's vertical motion. Therefore, to solve these problems, applied the 3-D numerical simulation, Taguchi's Design of Experiment (DOE), and intelligent parameter design methods, etc. We planned four steps as follows: firstly, we applied the 2-D flow simulation with NACA series, and then through the Taguchi's dynamic method to analyze the sensitivity (β). Secondly, take the data of pitching torque and total resistance from the Taguchi orthogonal array (L9), the ignal-to-noise ratio (SNR), and analysis each factorial contribution by ANOVA. Thirdly, used Radial Basis Function Network (RBFN) method to train the non-linear meta-modeling and found out the best factorial combination by Particle Swarm Optimization (PSO) and Weighted Percentage Reduction of Quality Loss (WPRQL). Finally, the application of the above methods gives the global optimum for multi-quality characteristics and the robust design configuration, including L/D is 9.4:1, the foreplane on the hull (Bow-2), and position of the sail is 0.25 Ls from the bow. The result shows that the total quality is improved by 86.03% in comparison with the original design.

A Metaheuristic Approach Towards Enhancement of Network Lifetime in Wireless Sensor Networks

  • J. Samuel Manoharan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.4
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    • pp.1276-1295
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    • 2023
  • Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

A three-dimensional two-hemisphere model for unmanned aerial vehicle multiple-input multiple-output channels

  • Zixu Su;Wei Chen;Changzhen Li;Junyi Yu;Guojiao Gong;Zixin Wang
    • ETRI Journal
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    • v.45 no.5
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    • pp.768-780
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    • 2023
  • The application of unmanned aerial vehicles (UAVs) has recently attracted considerable interest in various areas. A three-dimensional multiple-input multiple-output concentric two-hemisphere model is proposed to characterize the scattering environment around a vehicle in an urban UAV-to-vehicle communication scenario. Multipath components of the model consisted of lineof-sight and single-bounced components. This study focused on the key parameters that determine the scatterer distribution. A time-variant process was used to analyze the nonstationarity of the proposed model. Vital statistical properties, such as the space-time-frequency correlation function, Doppler power spectral density, level-crossing rate, average fade duration, and channel capacity, were derived and analyzed. The results indicated that with an increase in the maximum scatter radius, the time correlation and level-crossing rate decreased, the frequency correlation function had a faster downward trend, and average fade duration increased. In addition, with the increase of concentration parameter, the time correlation, space correlation, and level-crossing rate increased, average fade duration decreased, and Doppler power spectral density became flatter. The proposed model was compared with current geometry-based stochastic models (GBSMs) and showed good consistency. In addition, we verified the nonstationarity in the temporal and spatial domains of the proposed model. These conclusions can be used as references in the design of more reasonable communication systems.

A SE Approach for Machine Learning Prediction of the Response of an NPP Undergoing CEA Ejection Accident

  • Ditsietsi Malale;Aya Diab
    • Journal of the Korean Society of Systems Engineering
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    • v.19 no.2
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    • pp.18-31
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    • 2023
  • Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

Implementation of Efficient and Reliable Flash File System (효율적이고 신뢰성 있는 플래시 파일시스템의 구현)

  • Jin, Jong-Won;Lee, Tae-Hoon;Lee, Seung-Hwan;Chung, Ki-Dong
    • Journal of Korea Multimedia Society
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    • v.11 no.5
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    • pp.651-660
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    • 2008
  • Flash memory is widely used in embedded systems because of its benefits such as non-volatile, shock resistant, and low power consumption. However, NAND flash memory suffers from out-place-update, limited erase cycles, and page based read/write operations. To solve these problems, YAFFS and RFFS, the flash memory file systems, are proposed. However YAFFS takes long time to mount the file system, because all the files are scattered all around flash memory. Thus YAFFS needs to fully scan the flash memory. To provide fast mounting, RFFS has been proposed. It stores all the block information, the addresses of block information and meta data to use them at mounting time. However additional operations for the meta data management are decreasing the performance of the system. This paper presents a new NAND flash file system called ERFFS (Efficient and Reliable Flash File System) which provides fast mounting and recovery with minimum mata data management. Based on the experimental results, ERFFS reduces the flash mount/recovery time and the file system overhead.

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A study of design the agent system for management and service of S&T information (학술정보 관리 및 유통을 위한 에이전트 시스템 설계에 관한 연구)

  • Lee, Seok-Hyoung;Yoon, Hee-Jun;Yoon, Hwa-Mook
    • Proceedings of the Korea Contents Association Conference
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    • 2006.05a
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    • pp.503-506
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    • 2006
  • In this paper, we suggest the Agent System for management and service of science and technology information that performs the collection, analyzing, processing and managing the information. Generally, any system can process the collection and service the information as usual method, but that mean can't be clear because of the data process method on different systems of hardware and software. So, it's very important point that the design and development of S&T information flow framework that can accept the various data, and we expect that the agent system adapted in framework guarantee the reduction of man power and process time and the enlarged system. Agent System consists of five multi agents, Resource Format Register Agent, Data Collector Agent, Data Analyzer Agent, Data Processor Agent and MetaDB Creator Agent. We describe the main roles and elements of agent systems.

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Effects of Electroencephalogram Biofeedback on Emotion Regulation and Brain Homeostasis of Late Adolescents in the COVID-19 Pandemic

  • Park, Wanju;Cho, Mina;Park, Shinjeong
    • Journal of Korean Academy of Nursing
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    • v.52 no.1
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    • pp.36-51
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    • 2022
  • Purpose: The purpose of this study was to examine the effects of electroencephalogram (EEG) biofeedback training for emotion regulation and brain homeostasis on anxiety about COVID-19 infection, impulsivity, anger rumination, meta-mood, and self-regulation ability of late adolescents in the prolonged COVID-19 pandemic situation. Methods: A non-equivalent control group pretest-posttest design was used. The participants included 55 late adolescents in the experimental and control groups. The variables were evaluated using quantitative EEG at pre-post time points in the experimental group. The experimental groups received 10 sessions using the three-band protocol for five weeks. The collected data were analyzed using the Shapiro-Wilk test, Wilcoxon rank sum test, Wilcoxon signed-rank test, t-test and paired t-test using the SAS 9.3 program. The collected EEG data used a frequency series power spectrum analysis method through fast Fourier transform. Results: Significant differences in emotion regulation between the two groups were observed in the anxiety about COVID-19 infection (W = 585.50, p = .002), mood repair of meta-mood (W = 889.50, p = .024), self-regulation ability (t = - 5.02, p < .001), self-regulation mode (t = - 4.74, p < .001), and volitional inhibition mode (t = - 2.61, p = .012). Neurofeedback training for brain homeostasis was effected on enhanced sensory-motor rhythm (S = 177.00, p < .001) and inhibited theta (S = - 166.00, p < .001). Conclusion: The results demonstrate the potential of EEG biofeedback training as an independent nursing intervention that can markedly improve anxiety, mood-repair, and self-regulation ability for emotional distress during the COVID-19 pandemic.

The Statistical Technique for Dosimetric Meta-Analysis at in-vivo and in-vitro Papers about Bioeffects of RF Electromagnetic Field (RF 전자기장 생체 영향 연구 문헌에서 노출량 메타분석을 위한 통계적 기법)

  • Choi, Sung-Ho;Kim, Nam
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.14 no.12
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    • pp.1311-1320
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    • 2003
  • This paper proposed the estimating method of electromagnetic dosimetric reliability at in-vivo and in-vitro experiments. For more accurate consequences of these researches, we have tried to find out any correlations among output power, power density and specific absorption rate(SAR) with the results of in-vivo, in-vitro tests and SAR reports of cellular phone and PDA. In the case of in-vivo tests, the power density has close statistical correlations with SAR value and in the event of in-vitro tests, the output power has considerable statistical correlations with SAR containing duty factor. We analysed the coefficient of determination to estimate the dosimeoic uncertainty. If we use this method before evaluating techniques of measurement and analysis at both in-vivo and in-vitro experiments, we will conduct more accurate reliability test.

Dual-Band Unequal Power-Divider Miniaturized by Metamaterial CRLH Phase-Shift Lines (메타 재질 구조 CRLH 전송선 기반 소형 이중 대역 비균등 전력분배기)

  • Eom, Da-Jeong;Kahng, Sung-Tek
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.23 no.9
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    • pp.1048-1057
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    • 2012
  • In this paper, a new compact dual-band unequal power divider is suggested. Instead of the quarter wavelength transmission line(TX-line)s for the branches of the conventional Wilkinson's power divider, we use composite right- and left-handed(CRLH) phase-shift lines and can reduce the physical length. With the non-linear dispersion of the meta-meterial, each branch in the proposed divider is designed to have $+90^{\circ}$ and $-90^{\circ}$ at $f_1$ and $f_2$ respectively. To validate the proposed method, the performances of the circuit and full-wave simulation results are shown with the CRLH dispersion curve. The measurement results are compared with the simulation results. Also, the size reduction effect by the proposed scheme is addressed.

Methodology for Extended Schema Representation in Database Integration

  • 김철호
    • Journal of the military operations research society of Korea
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    • v.23 no.2
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    • pp.85-102
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    • 1997
  • There have been several research efforts to support interoperability among multiple databases. In integrating multiple databases, we must resolve schema conflicts due to the heterogeneity in databases. To resolve these conflicts, not only meta-data for database schemas but also general knowledge expressing the real world meanings associated with the database schemas are required. This paper presents a uniform representation method for relational schema and general knowledge base that is composed, among other things, of concept hierarchy and thematic roles in relationship, using the knowledge representation language Lk. This representation method has a flexible descriptive power which facilitates concepts to be expressed at different levels of granularity and can describe knowledge expressed in Lk are used for input of the next step, such as conflict resolution and query processing of multiple database.

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