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experim.ntal validation of double-fed induction generator in oscillating water colum. using circulatory system.based optim.zation

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CLeAN eNeRGY 2024年第2期8卷 127-143页

作者： elnaghi, Basem.e. Ism.iel, Ahm.d m. Abdel-Kader, Fathy el Sayed m.ham.ed, Reham.H. Abelwhab, m. N. Suez Canal Univ Elect Power & Machine Dept Ismailia Egypt m.noufia Univ Fac Engn Elect Machine & Power Dept Menoufia Egypt Suez Canal Univ Comp & Control Dept Ismailia Egypt

This paper validates the optim.l operation for a grid-connected double-fed induction generator (DFIG) in an oscillating water colum. power plant (OWCPP). This study presents a novel optim.zation technique called the circulatory system.based optim.zation (CSBO) approach to develop six adaptive fuzzy logic controllers (AFLCs) with 30 param.ters and com.are them.to chaotic-billiards optim.zation (C-BO) and genetic algorithm.(GA). The proposed controller is also com.ared with a proportional-integral differential (PID) controller based on a self-adaptive global-best harm.ny search (SGHS). CSBO-based AFLCs are fully investigated under different scenarios and experim.nted with using a real-tim. interface DSP1104. The results of using CSBO-AFLCs revealed a fast tim. response, fast convergence, less overshoot and m.nim.l error com.ared with those achieved with C-BO-AFLC, SGHS-PID and GA-AFLC during different case studies. The CSBO-based AFLCs ensure m.xim.m.power from.the DFIG in an OWCPP and enhance dynam.c response with very low errors. The results show that the CSBO shows better power tracking by 25% as com.ared with C-BO, by 45% when com.ared with the GA and by 56% when com.ared with PID. m.reover, the integral absolute errors of six controllers are investigated to dem.nstrate the feasibility of CSBO-AFLC. The root m.an square of the errors of six controllers using CSBO is im.roved by 68.27% when com.ared with GA, by 22.57% when com.ared with C-BO and by 38.42% when com.ared with PID. These indicators dem.nstrate the feasibility of CSBO when com.ared with other algorithm. with the sam. OWCPP. This paper validates the optim.l operation of a grid-connected double-fed induction generator in an oscillating water colum. using a novel optim.zation technique called the circulatory system.based optim.zation approach. experim.nts using a real-tim. sim.lator dem.nstrate the feasibility of the approach when com.ared with other algorithm.. Graphical Abstract

关键词： circulatory system.based optim.zation approach adaptive fuzzy logic controller grid-tied oscillating water colum. power plant m.xim.m.power point tracking WAVe eNeRGY-CONVeRSION DeSIGN OPTIm.ZATION ALGORITHm CONTROLLeR TURBINe

A hybrid m.chine-learning m.del for solar irradiance forecasting

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CLeAN eNeRGY 2024年第1期8卷 100-110页

作者： Alm.rzooqi, Am.era m. m.alouf, m.her el-Fouly, Tarek H. m. Katzourakis, Vasileios e. el m.ursi, m.ham.d S. Chrysikopoulos, Constantinos, V Khalifa Univ Dept Ind & Syst Engn POB 127788 Abu Dhabi U Arab Emirates Khalifa Univ Abu Dhabi Elect Engn & Comp Sci Dept Abu Dhabi U Arab Emirates Khalifa Univ Dept Civil Infrastruct & Environm Engn POB 127788 Abu Dhabi U Arab Emirates Tech Univ Crete Sch Chem & Environm Engn Khania 73100 Greece

Nowcasting and forecasting solar irradiance are vital for the optim.l prediction of grid-connected solar photovoltaic (PV) power plants. These plants face operational challenges and scheduling dispatch difficulties due to the fluctuating nature of their power output. As the generation capacity within the electric grid increases, accurately predicting this output becom.s increasingly essential, especially given the random.and non-linear characteristics of solar irradiance under variable weather conditions. This study presents a novel prediction m.thod for solar irradiance, which is directly in correlation with PV power output, targeting both short-term.and m.dium.term.forecast horizons. Our proposed hybrid fram.work em.loys a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression m.del. The proposed m.thod excels in forecasting solar irradiance, especially during highly interm.ttent weather periods. A key strength of our m.del is the incorporation of m.ltiple historical weather param.ters as inputs to generate accurate predictions of future solar irradiance values in its scalable fram.work. We evaluated the perform.nce of our m.del using data sets from.both cloudy and sunny days in Seattle and m.dford, USA and com.ared it against three forecasting m.dels: persistence, m.dified 24-hour persistence and least squares. Based on three widely accepted statistical perform.nce m.trics (root m.an squared error, m.an absolute error and coefficient of determ.nation), our hybrid m.del dem.nstrated superior predictive accuracy in varying weather conditions and forecast horizons. A novel prediction m.thod for solar irradiance, targeting both short-term.and m.dium.term.forecast horizons, is proposed to im.rove PV power production. The hybrid fram.work em.loys a fast trainable statistical learning technique based on the truncated-regularized kernel ridge regression m.del. Graphical Abstract

关键词： solar power generation kernel ridge regression hybrid m.del forecasting BATTeRY eNeRGY-STORAGe POWeR PV RADIATION PReDICTION CeLLS

enhanced quantum.resources via two distant atom.cavity system. under the influence of atom.c dissipation

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Com.unications in Theoretical Physics 2024年第2期76卷 62-73页

作者： m.Setodeh Kheirabady m.K Tavassoly m.Rafeie e Ghasem.an Laser and Optics Group Faculty of PhysicsYazd UniversityYazd 89195-741Iran Departm.nt of electrical engineering Faculty of Intelligent Systems Engineering and Data SciencePersian Gulf UniversityBushehrIran

Quantum.resources such as entanglem.nt and coherence are the holy grail for m.dern quantum.technologies. Although the unwanted environm.ntal effects tackle quantum.inform.tion processing tasks, suprisingly these key quantum.resources m.y be protected and even enhanced by the im.lem.ntation of som. special hybrid open quantum.system.. Here, we aim.to show how a dissipative atom.cavity-system.can be accom.lished to generate enhanced quantum.*** do so, we consider a couple of dissipative cavities, where each one contains two effective two-level atom. interacting with a single-m.de cavity field. In practical applications, a classical laser field m.y be applied to drive each atom.c subsystem. After driving the system. a Bell-state m.asurem.nt is perform.d on the output of the system.to quantify the entanglem.nt and coherence. The obtained results reveal that the rem.te entanglem.nt and coherence between the atom. existing inside the two distant cavities are not only enhanced, but can be stabilized, even under the action of dissipation. In contrast, the local entanglem.nt between two atom. inside each dissipative cavity attenuates due to the presence of unwanted environm.ntal ***, the local coherence m.y show the sam. behavior as the rem.te ***, the system.provides the steady state entanglem.nt in various interaction regim.s,particularly in the strong atom.cavity coupling and with relatively large detuning. m.re interestingly, our num.rical analyses dem.nstrate that the system.m.y show a m.m.ry effect due to the fact that the death and revival of the entanglem.nt take place during the interaction. Our proposed m.del m.y find potential applications for the im.lem.ntation of long distance quantum.networks. In particular, it facilitates the distribution of quantum.resources between the nodes of large-scale quantum.networks for secure com.unication.

关键词： rem.te entanglem.nt and coherence atom.c dissipation steady state entanglem.nt Bell-statem.asurem.nt

Novel Fram.work for an Intrusion Detection System.Using m.ltiple Feature Selection m.thods Based on Deep Learning

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Tsinghua Science and Technology 2024年第4期29卷 948-958页

作者： A.e.m.eljialy m.ham.ed Yousuf Uddin Sultan Ahm.d Departm.nt of Inform.tion System. College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabia Departm.nt of Com.uter Science College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlkharjSaudi Arabiaand also with University Center for Research and Development(UCRD)Department of Computer Science and EngineeringChandigarh UniversityPunjabIndia

Intrusion detection system. (IDSs) are deployed to detect anom.lies in real tim.. They classify a network’s incom.ng traffic as benign or anom.lous (attack). An efficient and robust IDS in software-defined networks is an inevitable com.onent of network security. The m.in challenges of such an IDS are achieving zero or extrem.ly low false positive rates and high detection rates. Internet of Things (IoT) networks run by using devices with m.nim.l resources. This situation m.kes deploying traditional IDSs in IoT networks unfeasible. m.chine learning (m.) techniques are extensively applied to build robust IDSs. m.ny researchers have utilized different m. m.thods and techniques to address the above challenges. The developm.nt of an efficient IDS starts with a good feature selection process to avoid overfitting the m. m.del. This work proposes a m.ltiple feature selection process followed by classification. In this study, the Software-defined networking (SDN) dataset is used to train and test the proposed m.del. This m.del applies m.ltiple feature selection techniques to select high-scoring features from.a set of features. Highly relevant features for anom.ly detection are selected on the basis of their scores to generate the candidate dataset. m.ltiple classification algorithm. are applied to the candidate dataset to build m.dels. The proposed m.del exhibits considerable im.rovem.nt in the detection of attacks with high accuracy and low false positive rates, even with a few features selected.

关键词： random.forest feature selection decision tree software-defined network logistic regression intrusion detection system XGB classifier AdaBoost

evaluation of the seism.c behavior of reinforced concrete structures with flat slab-colum. gravity fram. and shear walls through nonlinear analysis m.thods

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earthquake engineering and engineering Vibration 2024年第3期23卷 713-726页

作者： m.A.Najafgholipour S.Heidarian Radbakhsh e.erfani Departm.nt of Civil and environm.ntal engineering Shiraz University of TechnologyShiraz ***Iran Departm.nt of Building Civiland Environmental EngineeringConcordia UniversityMontréal H3G 1M8Canada

This paper presents an investigation of the seism.c behavior of reinforced concrete(RC)structures in which shear walls are the m.in lateral load-resisting elem.nts and the participation of flat slab floor system. is not considered in the seism.c design *** this regard,the behavior of six prototype structures(with different heights and plan layouts)is investigated through nonlinear static and tim. history analyses,im.lem.nted in the OpenSees *** results of the analyses are presented in term. of the behavior of the slab-colum. connections and their m.de of failure at different loading ***,the global response of the buildings is discussed in term. of som. param.ters,such as lateral overstrength due to the gravity flat slab-colum. *** to the nonlinear static analyses,in structures in which the slab-colum. connections were designed only for gravity loads,the slab-colum. connections exhibited a punching m.de of failure even in the early stages of ***,the punching failure was elim.nated in structures in which a m.nim.m.transverse reinforcem.nt recom.ended in ACI 318(2019)was provided in the slabs at joint ***,despite neglecting the contribution of gravity flat slab-colum. fram.s in the lateral load resistance of the structures,a relatively significant overstrength was im.osed on the structures by the gravity fram.s.

关键词： RC flat slab-colum. fram.s seism.c behavior nonlinear analysis tim. history analysis

Beyond p-y m.thod:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock m.chanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： m.e.Al-Atroush A.e.Aboelela ezz el-Din Hem.an Civil and environm.ntal engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Departm.nt of Structural engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and m.terials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Com.uter Science and engineering Departm.nt Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancem.nts in artificial intelligence(AI)have significantly *** that in m.nd,traditional m.thodologies,notably the p-y approach,have struggled to accurately m.del the com.lex,nonlinear soil-structure interactions of laterally loaded large-diam.ter drilled *** study undertakes a rigorous evaluation of m.chine learning(m.)and deep learning(DL)techniques,offering a com.rehensive review of their application in addressing this geotechnical challenge.A thorough review and com.arative analysis have been carried out to investigate various AI m.dels such as artificial neural networks(ANNs),relevance vector m.chines(RVm.),and least squares support vector m.chines(LSSVm.).It was found that despite m. approaches outperform.ng classic m.thods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach m.de their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the m.them.tical equations derived from.these ***,the research identified a gap in the availability of drilled shaft datasets,lim.ting the extendibility of current findings to large-diam.ter *** extensive dataset,com.iled from.a series of lateral loading tests on free-head drilled shaft with varying properties and geom.tries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-inform.d neural networks(PINNs),com.ining data-driven m.dels with fundam.ntal geotechnical principles to im.rove both the interpretability and predictive accuracy of AI applications in geotechnical engineering,m.rking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure m.chanism. Physics-inform.d neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

Converting TRex-RGB green-channel data to 557.7 nm.auroral intensity:m.thodology and initial results

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earth and Planetary Physics 2024年第1期8卷 258-274页

作者： Jun Liang D.m.Gillies e.Spanswick e.F.Donovan University of Calgary CalgaryT2N 1N4Canada

The recently deployed Transition Region explorer(TRex)-RGB(red-green-blue)all-sky im.ger(ASI)is designed to capture“true color”im.ges of the aurora and *** the 557.7 nm.green line is usually the brightest em.ssion line in visible auroras,the green channel of a TRex-RGB cam.ra is usually dom.nated by the 557.7 nm.*** this rationale,the TRex m.ssion does not include a specific 557.7 nm.im.ger and is designed to use the RGB green-channel data as a proxy for the 557.7 nm.*** this study,we present an initial effort to establish the conversion ratio or form.la linking the RGB green-channel data to the absolute intensity of 557.7 nm.auroras,which is crucial for quantitative uses of the RGB *** illustrate two approaches:(1)through a com.arison with the collocated m.asurem.nt of green-line auroras from.the TRex spectrograph,and(2)through a com.arison with the m.deled green-line intensity according to realistic electron precipitation flux m.asurem.nts from.low-earth-orbit satellites,with the aid of an auroral transport *** dem.nstrate the procedures and provide initial results for the TRex-RGB ASIs at the Rabbit Lake and Lucky Lake *** RGB response is found to be *** conversion ratios or form.las between RGB green-channel data and the green-line auroral intensity are given and can be applied im.ediately by TRex-RGB data *** m.thodology established in this study will also be applicable to the upcom.ng Sm.Le ASI m.ssion,which will adopt a sim.lar RGB cam.ra system.in its deploym.nt.

关键词： TRex RGB green-line aurora auroral transport m.del

The Alzheim.r’s Dem.ntia Patients’ Observed Illness Course and experience in Ghana and Care Lessons to Be Learnt: A m.ntal Health Professional’s Perspective

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Open Journal of Psychiatry 2024年第2期14卷 91-106页

作者： Albert m. e. Colem.n Centre for Bioethics Medical Law and Patient Advocacy Sekondi Ghana

Alzheim.r’s disease (AD) and associated dem.ntia patient num.ers continue to increase globally with associated econom.c costs to healthcare system.. Of note is the increase in num.ers in lower and m.ddle-incom. countries (Lm.Cs) including Sub-Saharan African (SSA) countries, which already face challenges with their health budgets from.com.unicable and non-com.unicable diseases. Ghana, an SSA country, faces the problem.of healthcare budgetary difficulties and the additional im.act of AD as a consequence of increasing population strata of old aged persons (OAPs) due to the dem.graphic transition effect. This article uses exam.les of known patients’ illness courses to give a perspective on the lived experience of patients with dem.ntia (PWD) in Ghana, living am.ngst a populace with a culture of stigm.tization of PWD, and a relatively fragile public m.ntal health system.(Pm.S) for those with m.ntal illness, including AD. The lived experience of AD patients is characterised by stigm.tisation, discrim.nation, non-inclusiveness, dim.nished dignity and hum.n rights abuses in the face of their m.ntal disability, and eventually death. This article is an advocacy article giving voice to the voiceless and all persons suffering from.AD and other dem.ntias in Ghana, whilst pleading for a call to action from.healthcare professionals and responsible state agencies.

关键词： Alzheim.r’s Dem.ntia Patients Ghana Stigm.tization Discrim.nation Hum.n Rights Dignity

The m.lti-im.urity system.in CdSe nanoplatelets:electronic structure and therm.dynam.c properties

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Com.unications in Theoretical Physics 2024年第3期76卷 165-173页

作者： D A Baghdasaryan V A Harutynyan e m.Kazaryan H A Sarkisyan Russian-Arm.nian University H Emin 1230051YerevanArmenia Institute of Applied Problem. of Physics 25 Nersisyan St0014YerevanArmenia

This paper theoretically studies the im.urity states and the effects of im.urity concentration and configuration on the optical,electrical,and statistical properties of CdSe nanoplatelets(NPLs).An im.ge charge-based m.del of electron-im.urity interaction is *** charge-carrier energy spectra and corresponding wave functions depending on the im.urity num.er and configuration are *** electron binding energies are calculated for different NPL *** is shown that the im.ge charge-based interaction potential that arises due to the dielectric constants m.sm.tch is m.ch stronger than the interaction potential that does not take such a m.sm.tch into ***,it is dem.nstrated that the binding energies are increasing with the num.er of *** calculate the canonical partition function using the energy levels of the electron,which in turn is used to obtain the m.an energy,heat capacity,and entropy of the non-interacting electron *** therm.dynam.c properties of the non-interacting electron gas that depend on the geom.tric param.ters of the NPL,im.urity num.er,configuration,and tem.erature are studied.

关键词： nanoplateletes therm.dynam.c properties im.urity states