Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and *** resources are vital for all countries in terms of their economies and *** a result,selecting the optimal o...
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Renewable energy is created by renewable natural resources such as geothermal heat,sunlight,tides,rain,and *** resources are vital for all countries in terms of their economies and *** a result,selecting the optimal option for any country is critical in terms of energy *** country is nowadays planning to increase the share of renewable energy in their universal energy sources as a result of global *** the present work,the authors suggest fuzzy multi-characteristic decision-making approaches for renew-able energy source selection,and fuzzy set theory is a valuable methodology for dealing with uncertainty in the presence of incomplete or ambiguous *** study employed a hybrid method for order of preference by resemblance to an ideal solution based on fuzzy analytical network process-technique,which agrees with professional assessment scores to be linguistic phrases,fuzzy numbers,or crisp *** hybrid methodology is based on fuzzy set ideologies,which calculate alternatives in accordance with professional functional requirements using objective or subjective *** best-suited renewable energy alternative is discovered using the approach presented.
Now that the population is growing, the expenditure on basic needs of life is also increasing due to a lack of or less availability of resources. The economy consumed electricity is reaching peaks as its main fuel, co...
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The digital transformation process of power systems towards smart grids is resulting in improved reliability, efficiency and situational awareness at the expense of increased cybersecurity vulnerabilities. Given the a...
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The digital transformation process of power systems towards smart grids is resulting in improved reliability, efficiency and situational awareness at the expense of increased cybersecurity vulnerabilities. Given the availability of large volumes of smart grid data, machine learning-based methods are considered an effective way to improve cybersecurity posture. Despite the unquestionable merits of machine learning approaches for cybersecurity enhancement, they represent a component of the cyberattack surface that is vulnerable, in particular, to adversarial attacks. In this paper, we examine the robustness of autoencoder-based cyberattack detection systems in smart grids to adversarial attacks. A novel iterative-based method is first proposed to craft adversarial attack samples. Then, it is demonstrated that an attacker with white-box access to the autoencoder-based cyberattack detection systems can successfully craft evasive samples using the proposed method. The results indicate that naive initial adversarial seeds cannot be employed to craft successful adversarial attacks shedding insight on the complexity of designing adversarial attacks against autoencoder-based cyberattack detection systems in smart grids.
This paper presents a novel Substrate Integrated Waveguide (SIW) Cavity-Backed Slot Antenna (CBSA) to enable the next generation of communication and sensing infrastructure. The antenna achieves a bandwidth of 40%, wi...
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Research into Medicare fraud detection that utilizes machine learning methodologies is of great national interest due to the significant fiscal ramifications of this type of fraud. Our big data analysis pertains to th...
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The impact of orthopedic scaffolds on bone defect healing,particularly the late-stage bone remodeling process,is pivotal for the therapeutic *** study applies fadditively manufactured scaffolds composed of hydroxyapat...
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The impact of orthopedic scaffolds on bone defect healing,particularly the late-stage bone remodeling process,is pivotal for the therapeutic *** study applies fadditively manufactured scaffolds composed of hydroxyapatite-doped poly(lactide-co-glycolide)-b-poly(ethylene glycol)-b-poly(lactide-co-glycolide)(HAPELGA)with varying properties to treat rat calvarial defects,elucidating their significant role in bone remodeling by modulating physiological *** engineered two scaffolds with different polylactic acid(PLA)to polyglycolic acid(PGA)ratio(9/1 and 18/1)to vary in hydrophobicity,degradation rate,mechanical properties,and structural *** variations influenced physiological responses,including osteogenesis,angiogen-esis,and immune reactions,thereby guiding bone *** findings show that the HA-PELGA(18/1)scaffold,with a slower degradation rate,supported bulk bone formation due to a stable ***,the HA-PELGA(9/1)scaffold,with a faster degradation rate and more active interfaces,facilitated the formation of a thin bone layer and higher bone *** study demonstrates these degradable scaffolds help to promote bone healing and reveals how scaffold properties influence the bone remodeling process,offering a potential strategy to optimize scaffold design aiming at late-stage bone defect healing.
This research proposes a tagging antenna sensor for permittivity detection of solid materials based on a close quarter approach. The sensor is proposed to operate at a frequency of 2.53 GHz using a single port resonat...
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作者：
Butola, RajatLi, YimingKola, Sekhar ReddyNational Yang Ming Chiao Tung University
Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Institute of Pioneer Semiconductor Innovation
The Institute of Artificial Intelligence Innovation National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program The Institute of Communications Engineering the Institute of Biomedical Engineering Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan
In this work, a dynamic weighting-artificial neural network (DW-ANN) methodology is presented for quick and automated compact model (CM) generation. It takes advantage of both TCAD simulations for high accuracy and SP...
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In the context of modern services that use multiple Deep Neural Networks (DNNs), managing workloads on embedded devices presents unique challenges. These devices often incorporate diverse architectures, necessitating ...
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Active distribution network(ADN),as a typically cyber-physical system,develops with the evolution of Internet of Things(IoTs),which makes the network vulnerable to cybersecurity *** this paper,the eavesdropping attack...
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Active distribution network(ADN),as a typically cyber-physical system,develops with the evolution of Internet of Things(IoTs),which makes the network vulnerable to cybersecurity *** this paper,the eavesdropping attacks that lead to privacy breaches are addressed for the IoT-enabled ADN.A privacy-preserving energy management system(EMS)is proposed and empowered by secure data exchange protocols based on the homomorphic *** the information transmission among distributed generators and load customers in the EMS,private information including power usage and electricity bidding price can be effectively protected against eavesdropping *** correctness of the final solutions,e.g.,optimal market clearing price and unified power utilization ratio,can be deterministically *** simulation results demonstrate the effectiveness and the computational efficiency of the proposed homomorphically encrypted EMS.
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