Search results for: PERFORMANCE MODEL
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A Surrogate-Assisted Measurement Correction Method for Accurate and Low-Cost Monitoring of Particulate Matter Pollutants
PublicationAir pollution involves multiple health and economic challenges. Its accurate and low-cost monitoring is important for developing services dedicated to reduce the exposure of living beings to the pollution. Particulate matter (PM) measurement sensors belong to the key components that support operation of these systems. In this work, a modular, mobile Internet of Things sensor for PM measurements has been proposed. Due to a limited...
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Ionic liquid as morphology-directing agent of two-dimensional Bi2WO6: New insight into photocatalytic and antibacterial activity
PublicationAn efficient and durable utilization of light to drive photocatalytic reactions still requires the overcoming of barriers. Herein, two-dimensional (2D) ultrathin IL_Bi2WO6 (IL_BWO) photocatalysts were prepared for the first time via ionic liquid-assisted hydrothermal route by adjusting the amount of tetrabutylammonium chloride [TBA][Cl], synthesis temperature and duration. IL played the role of morphology-directing agent given...
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COMPARISON OF HEAT TRANSFER CHARACTERISTICS IN SURFACE COOLING WITH BOILING MICROJETS OF WATER, ETHANOL AND HFE7100
PublicationThe basis of microjet technology is to produce laminar jets which when impinging the surface have a very high kinetic energy at the stagnation point. Boundary layer is not formed in those conditions, while the area of film cooling has a very high turbulence resulting from a very high heat transfer coefficient. Applied technology of jet production can result with the size of jets ranging from 20 to 500μm in breadth and 20 to 100μm...
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier
PublicationIn recent years, a lot of attention has been paid to using radiology imaging to automatically find COVID-19. (1) Background: There are now a number of computer-aided diagnostic schemes that help radiologists and doctors perform diagnostic COVID-19 tests quickly, accurately, and consistently. (2) Methods: Using chest X-ray images, this study proposed a cutting-edge scheme for the automatic recognition of COVID-19 and pneumonia....
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Coarse-grained simulation - an efficient approach for studying motions of large proteins
PublicationOne of the most important challenges in performing Molecular Dynamics (MD) simulations of large protein complexes is to accommodate the model accuracy and the simulation timescale. Hitherto, for the most relevant dynamics of protein aggregates in an explicit aqueous environment, the timescale reachable for the all-atoms simulations is of hundreds of nanoseconds. This range is four to six orders of magnitude smaller than processes...
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The adaptive backstepping control of PMSM supplied by current source inverter for the field weakening region
PublicationThe sensorless control system of permanent magnet synchronous motor PMSM supplied by current source inverter for field weakening operation is presented in this paper. The adaptive backstepping control system and the backstepping speed observer are presented. The control system is based on multi-scalar variables. The control variables are: dc-link voltage and the output current vector pulsation. The control system was named voltage...
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Hydrodynamic cavitation based advanced oxidation processes: Studies on specific effects of inorganic acids on the degradation effectiveness of organic pollutants
PublicationThe use of cavitation in advanced oxidation processes (AOPs) to treat acidic effluents and process water has become a promising trend in the area of environmental protection. The pH value of effluents – often acidified using an inorganic acid, is one of the key parameters of optimization process. However, in the majority of cases the effect of kind of inorganic acid on the effectiveness of degradation is not studied. The present...
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Reliable Surrogate Modeling of Antenna Input Characteristics by Means of Domain Confinement and Principal Components
PublicationA reliable design of contemporary antenna structures necessarily involves full-wave electromagnetic (EM) analysis which is the only tool capable of accounting, for example, for element coupling or the effects of connectors. As EM simulations tend to be CPU-intensive, surrogate modeling allows for relieving the computational overhead of design tasks that require numerous analyses, for example, parametric optimization or uncertainty...
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Mathematical modelling and computer simulation of activated sludge systems.Second edition
PublicationMathematical Modelling and Computer Simulation of Activated Sludge Systems – Second Edition, provides, from the process engineering perspective, a comprehensive and up-to-date overview regarding various aspects of the mechanistic (“white box”) modelling and simulation of advanced activated sludge systems performing biological nutrient removal. In the new edition of the book, a special focus is given to nitrogen removal and an overview...
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Selected Technical Issues of Deep Neural Networks for Image Classification Purposes
PublicationIn recent years, deep learning and especially Deep Neural Networks (DNN) have obtained amazing performance on a variety of problems, in particular in classification or pattern recognition. Among many kinds of DNNs, the Convolutional Neural Networks (CNN) are most commonly used. However, due to their complexity, there are many problems related but not limited to optimizing network parameters, avoiding overfitting and ensuring good...
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Polynomial Chaos Expansion in Bio- and Structural Mechanics
PublicationThis thesis presents a probabilistic approach to modelling the mechanics of materials and structures where the modelled performance is influenced by uncertainty in the input parameters. The work is interdisciplinary and the methods described are applied to medical and civil engineering problems. The motivation for this work was the necessity of mechanics-based approaches in the modelling and simulation of implants used in the repair...
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Solvent dependency of carbon dioxide Henry's constant in aqueous solutions of choline chloride-ethylene glycol based deep eutectic solvent
PublicationThe Henry's constants of carbon dioxide absorbed in aqueous solutions of ethaline (choline chloride-ethylene glycol) were determined for temperatures ranging from 303.15 to 323.15 K based on solubility measurement at CO2 pressure ranging from 0 to 6 bar (0.6 MPa). These studies revealed that the Henry's constant increased with the increase of temperature. Data indicated the highest capacity of CO2 absorption is obtained for ethaline...
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Fast Design Closure of Compact Microwave Components by Means of Feature-Based Metamodels
PublicationPrecise tuning of geometry parameters is an important consideration in the design of modern microwave passive components. It is mandatory due to limitations of theoretical design methods unable to quantify certain phenomena that are important for the operation and performance of the devices (e.g., strong cross-coupling effects in miniaturized layouts). Consequently, the initial designs obtained using analytical or equivalent network...
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Simulation-Driven Antenna Modeling by Means of Response Features and Confined Domains of Reduced Dimensionality
PublicationIn recent years, the employment of full-wave electromagnetic (EM) simulation tools has become imperative in the antenna design mainly for reliability reasons. While the CPU cost of a single simulation is rarely an issue, the computational overhead associated with EM-driven tasks that require massive EM analyses may become a serious bottleneck. A widely used approach to lessen this cost is the employment of surrogate models, especially...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Polynomial Chaos Expansion in Bio-and Structural Mechanics
PublicationThis monograph presents a probabilistic approach to modelling the mechanics of materials and structures where the modelled performance is influenced by uncertainty in the input parameters. The work is interdisciplinary and the methods described are applied to medical and civil engineering problems. The motivation for this work was the necessity of mechanics-based approaches in the modelling and simulation of implants used in the...
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Seafloor Characterisation and Imaging Using Multibeam Sonar Data
PublicationThe approach to seafloor characterisation and imaging is presented. It relies on the combined, concurrent use of several techniques of multibeam sonar data processing. The first one is based on constructing the grey-level sonar images of seabed using the backscattering strength calculated for the echoes received in the consecutive beams. Then, the set of parameters describing the local region of sonar image is calculated. The second...
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Nested Space Mapping Technique for Design and Optimization of Complex Microwave Structures with Enhanced Functionality
PublicationIn this work, we discuss a robust simulation-driven methodology for rapid and reliable design of complex microwave/RF circuits with enhanced functionality. Our approach exploits nested space mapping (NSM) technology, which is dedicated to expedite simulation-driven design optimization of computationally demanding microwave structures with complex topologies. The enhanced func-tionality of the developed circuits is achieved by means...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Determination of the content of saccharides and ethanol in samples of fermented beverages
Open Research DataThe data set presents the results of measurements of the content of mono- and disaccharides: glucose, maltose, fructose and ethanol in samples of beverages fermented by high performance liquid chromatography (HPLC-RID).
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Modelling and Simulation of a New Variable Stiffness Holder for Milling of Flexible Details
PublicationModern industry expectations in terms of milling operations often demand the milling of the flexible details by using slender ball-end tools. This is a difficult task because of possible vibration occurrence. Due to existence of certain conditions (small depths of cutting, regeneration phenomena), cutting process may become unstable and self-excited chatter vibration may appear. Frequency of the chatter vibration is close to dominant...
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The evaluation of COD fractionation and modeling as a key factor for appropriate optimization and monitoring of modern cost-effective activated sludge systems
PublicationA study was conducted to characterize the raw wastewater entering a modern cost effective municipal WWTP in Poland using two approaches; 1) a combination of modeling and carbonaceous oxygen demand (COD) fractionation using respirometric test coupled with model estimation (RTME) and 2) flocculation/filtration COD fractionation method combined with BOD measurements (FF-BOD). It was observed that the particulate fractions of COD obtained...
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublicationThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Suppression of Supply Current Harmonics of 18-Pulse Diode Rectifier by Series Active Power Filter with LC Coupling
PublicationThe reported research aims at improving the quality of three-phase rectifier supply currents. An effective method consists of adding properly formed booster voltages to the fundamental supply voltages using a series active filter. In the proposed solution, the booster voltages are generated by three single-phase systems consisting of inverters, LC filters, and single-phase transformers. The application of LC couplings ensures low...
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Optimal Design of Transmitarray Antennas via Low-Cost Surrogate Modelling
PublicationOver the recent years, reflectarrays and transmitarrays have been drawing a considerable attention due to their attractive features, including a possibility of realizing high gain and pencil-like radiation patterns without the employment of complex feeding networks. Among the two, transmitarrays seem to be superior over reflectarrays in terms of achieving high radiation efficiency without the feed blockage. Notwithstanding, the...
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Reliable computationally-efficient behavioral modeling of microwave passives using deep learning surrogates in confined domains
PublicationThe importance of surrogate modeling techniques has been steadily growing over the recent years in high-frequency electronics, including microwave engineering. Fast metamodels are employed to speedup design processes, especially those conducted at the level of full-wave electromagnetic (EM) simulations. The surrogates enable massive system evaluations at nearly EM accuracy and negligible costs, which is invaluable in parameter...
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Probabilistic assessment of SMRFs with infill masonry walls incorporating nonlinear soil-structure interaction
PublicationInfill Masonry Walls (IMWs) are used in the perimeter of a building to separate the inner and outer space. IMWs may affect the lateral behavior of buildings, while they are different from those partition walls that separate two inner spaces. This study focused on the seismic vulnerability assessment of Steel Moment-Resisting Frames (SMRFs) assuming different placement of IMWs incorporating nonlinear Soil-Structure Interaction (SSI)....
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Reduced-cost optimization-based miniaturization of microwave passives by multi-resolution EM simulations for internet of things and space-limited applications
PublicationStringent performance specifications along with constraints imposed on physical dimensions, make the design of contemporary microwave components a truly onerous task. In recent years, the latter demand has been growing in importance, with the innovative application areas such as Internet of Things coming into play. The need to employ full-wave electromagnetic (EM) simu-lations for response evaluation, reliable yet CPU heavy, only...
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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublicationReflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using...
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Predicting the seismic collapse capacity of adjacent SMRFs retrofitted with fluid viscous dampers in pounding condition
PublicationSevere damages of adjacent structures due to structural pounding during earthquakes have emphasized the need to use some seismic retrofit strategy to enhance the structural performance. The purpose of this paper is to study the influence of using linear and nonlinear Fluid Viscous Dampers (FVDs) on the seismic collapse capacities of adjacent structures prone to pounding and proposing modification factors to modify the median...
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Optimization of carbamazepine photodegradation on defective TiO2-based magnetic photocatalyst
PublicationIn this work, carbamazepine (CBZ) degradation over defective Fe3O4@SiO2/d-TiO2/Pt photocatalyst was studied. Within the titania structure, Ti vacancies and Pt nanoparticles were introduced to enhance the photocatalyst’s light absorption and influence charge carriers’ mobility. For the carbamazepine degradation, process parameters, e.g., temperature, flux intensity, photocatalyst loading, aeration, pH, and addition of H2O2, were optimized...
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Theoretical examination of the fracture behavior of BC3 polycrystalline nanosheets: Effect of crack size and temperature
Publication2D carbon graphene nanostructures are elements of advanced materials and systems. This theoretical survey provides explanation to the mechanical and fracture behavior of mono- and polycrystalline BC3 nanosheets (denoted as MC- and PCBC3NS, respectively) as a function of temperature and the type of crack defects. The mechanical performance of PCBC3NS at elevated temperatures was monitored varying the number of grain boundaries (the...
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Mitigating the seismic pounding of multi-story buildings in series using linear and nonlinear fluid viscous dampers
PublicationSeismic-induced pounding between adjacent buildings may have serious consequences, ranging from minor damage up to total collapse. Therefore, researchers try to mitigate the pounding problem using different methods, such as coupling the adjacent buildings with stiff beams, connecting them by using viscoelastic links, and installing damping devices in each building individually. In the current paper, the effect of using linear and...
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Using Convolutional Neural Networks for Corneal Arcus Detection Towards Familial Hypercholesterolemia Screening
PublicationFamilial hypercholesterolemia (FH) is a highly undiagnosed disease. Among FH patients, the onset of premature coronary artery disease is 13 times higher than in the general population. Early diagnosis and treatment is essential to prevent cardiovascular diseases and their complications, and to prolong life. One of the clinical criteria of FH is the occurrence of a corneal arcus (CA) among patients, especially those under 45 years...
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Pose-Configurable Generic Tracking of Elongated Objects
PublicationElongated objects have various shapes and can shift, rotate, change scale, and be rigid or deform by flexing, articulating, and vibrating, with examples as varied as a glass bottle, a robotic arm, a surgical suture, a finger pair, a tram, and a guitar string. This generally makes tracking of poses of elongated objects very challenging. We describe a unified, configurable framework for tracking the pose of elongated objects, which...
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Integrated monitoring, control and security of Critical Infrastructure Systems
PublicationModern societies have reached a point where everyday life relies heavily on desired operation of critical infrastructures, in spite of accidental failures and/or deliberate attacks. The issue of desired performance operation of CIS at high security level receives considerable attention worldwide. The pioneering generic methodologies and methods are presented in the paper project for designing systems capable of achieving these...
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Design and Experimental Validation of a Metamaterial-Based Sensor for Microwave Imaging in Breast, Lung, and Brain Cancer Detection
PublicationThis study proposes an innovative geometry of a microstrip sensor for high-resolution microwave imaging (MWI). The main intended application of the sensor is early detection of breast, lung, and brain cancer. The proposed design consists of a microstrip patch antenna fed by a coplanar waveguide with a metamaterial layer-based lens implemented on the back side, and an artificial magnetic conductor (AMC) realized on as a separate...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Evaluation of the electrochemical performance of CPMD in ZICs with 3M ZnSO4 electrolyte
Open Research DataThese data contain the results of the electrochemical performance measurements of CPMD in ZICs with 3M ZnSO4 electrolyte, incl. CGD (galvanostatic charge-discharge ) curve and cycling stability of CPMD. Sample abbreviations (CPMD) are in agreement with the markings used in the linked publication.
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
PublicationRecent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Using Decisional DNA to Enhance Industrial and Manufacturing Design: Conceptual Approach
PublicationDuring recent years, manufacturing organizations are facing market changes such as the need for short product life cycles, technological advancement, intense pressure from competitors and the continuous customers’ expectation for high quality products at lower costs. In this scenario, knowledge and its associated engineering/management of every stage involved in the industrial design has become increasingly important for manufacturing...
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Deposition of phosphate coatings on titanium within scaffold structure
PublicationPurpose: Existing knowledge about the appearance, thickness, and chemical composition of phosphate coatings on titanium inside porous structures is insufficient. Such knowledge is important for the design and fabrication of porous implants. Methods: Metallic scaffolds were fabricated by selective laser melting of 316L stainless steel powder. Phosphate coatings were deposited on Ti sensors placed either outside the scaffolds or...
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The Technological Advancement of New Products, Product Newness and Market Information
PublicationThe purpose of this study is to propose product newness and obtaining market information as mediators of the relationship between the technological advancement of a new product and its commercial success. So far, little is known about the mediators of this relationship but knowledge about the factors that strengthen or weaken it is valid, both for the theory and practice of new product management. On the one hand, product newness...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Successive cytotoxicity control by evolutionary surface decorated electronic push-pull green ZnCr-LDH nanostructures: Drug delivery enlargement for targeted breast cancer chemotherapy
PublicationThe reason for the increasing bioavailability and biocompatibility of the porous nanomaterials in the presence of different (bio)molecules is still unknown. The role of difference functional groups and their interactions with the potential bioavailability and biocompatibility is of great importance. To investigate the potential contribution of the electronic effects (especially on the surface of the porous nanomaterials) on their...
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Globalized Parametric Optimization of Microwave Passive Components Using Simplex-Based Surrogates
PublicationOptimization-based parameter adjustment involving full-wave electromagnetic (EM) simulation models is a crucial stage of present-day microwave design process. In fact, rigorous optimization is the only reliable mean permitting to simultaneously handle multiple geometry/material parameters, objectives, and constraints. Unfortunately, EM-driven design is a computationally intensive endeavor. While local tuning is usually manageable,...
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Nonlinear Free and Forced Vibrations of a Hyperelastic Micro/Nanobeam Considering Strain Stiffening Effect
PublicationIn recent years, the static and dynamic response of micro/nanobeams made of hyperelasticity materials received great attention. In the majority of studies in this area, the strain-stiffing effect that plays a major role in many hyperelastic materials has not been investigated deeply. Moreover, the influence of the size effect and large rotation for such a beam that is important for the large deformation was not addressed. This...