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Wyniki wyszukiwania dla: deep learning, genetic algorithm, artificial neural networks, predictive maintenance, cost efficient maintenance
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Clonal selection algorithm for vehicle routing
PublikacjaOver the years several successful computing techniques have been inspired by biological mechanisms. Studies of the mechanisms that allow the immune systems of vertebratesto adapt and learn have resulted in a class of algorithms called artificial immune systems. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublikacjaTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
PublikacjaThe Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results...
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Knowledge sharing and knowledge hiding in light of the mistakes acceptance component of learning culture- knowledge culture and human capital implications
PublikacjaPurpose: This study examines the micromechanisms of how knowledge culture fosters human capital development. Method: An empirical model was developed using the structural equation modeling method (SEM) based on a sample of 321 Polish knowledge workers employed in different industries. Findings: This study provides direct empirical evidence that tacit knowledge sharing supports human capital, whereas tacit knowledge hiding does...
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MANAGING LEARNING PROCESS WITH E-LEARNING TOOL
PublikacjaThis article presents one possibility to employ Moodle, the free e-Leaning platform, to organize learning understood as a process. Behavioral approach and application to massive courses are assumed. A case study is presented, where the introduction of Moodle resulted in better student performance in homework
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Capacity efficient shared protection and fast restoration scheme in self-configured optical networks
PublikacjaW artykule zaproponowano nową koncepcję optymalizacji rozdziału zasobów dla przeżywalnych sieci rozległych, która gwarantuje szybkie odtwarzanie usług po wystąpieniu awarii. Wykazano, iż proponowany algorytm, wykorzystujący ideę wierzchołkowego kolorowania grafów, nie powoduje wydłużania ścieżek zabezpieczających - zjawiska charakterystycznego dla powszechnie stosowanych algorytmów optymalizacji. Udowodniono, iż powyższa cecha...
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Application of Feed Forward Neural Networks for Modeling of Heat Transfer Coefficient During Flow Condensation for Low and High Values of Saturation Temperatur
PublikacjaMost of the literature models for condensation heat transfer prediction are based on specific experimental parameters and are not general in nature for applications to fluids and non-experimental thermodynamic conditions. Nearly all correlations are created to predict data in normal HVAC conditions below 40°C. High temperature heat pumps operate at much higher parameters. This paper aims to create a general model for the calculation...
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Power System Stabilizer as a Part of a Generator MPC Adaptive Predictive Control System
PublikacjaIn this paper, a model predictive controller based on a generator model for prediction purposes is proposed to replace a standard generator controller with a stabilizer of a power system. Such a local controller utilizes an input-output model of the system taking into consideration not only a generator voltage Ug but also an additional, auxiliary signal (e.g., α, Pg, or ωg). This additional piece of information allows for taking...
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Study of various machine learning approaches for Sentinel-2 derived bathymetry
PublikacjaIn recent years precise and up-to-date information regarding seabed depth has become more and more important for companies and institutions that operate on coastlines. While direct, in-situ measurements are performed regularly, they are expensive, time-consuming and impractical to be performed in short time intervals. At the same time, an ever-increasing amount of satellite imaging data becomes available. With these images, it...
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Controlling computer by lip gestures employing neural network
PublikacjaResults of experiments regarding lip gesture recognition with an artificial neural network are discussed. The neural network module forms the core element of a multimodal human-computer interface called LipMouse. This solution allows a user to work on a computer using lip movements and gestures. A user face is detected in a video stream from a standard web camera using a cascade of boosted classifiers working with Haar-like features....
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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublikacjaSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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Deep learning based segmentation using full wavefield processing for delamination identification: A comparative study
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Analysis of Learning Outcomes in Medical Education with the Use of Fuzzy Logic
PublikacjaThe national curricula of the EU member states are structured around learning outcomes, selected according to Bloom’s Taxonomy. The authors of this paper claim that using Bloom’s Taxonomy to phrase learning outcomes in medical education in terms of students’ achievements is difficult and unclear. This paper presents an efficient method of assessing course learning outcomes using Fuzzy Logic.
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Photosensitization of TiO2 and SnO2 by Artificial Self-Assembling Mimics of the Natural Chlorosomal Bacteriochlorophylls
PublikacjaOf all known photosynthetic organisms, the green sulfur bacteria are able to survive under the lowest illumination conditions due to highly efficient photon management and exciton transport enabled by their special organelles, the chlorosomes, which consist mainly of self-assembled bacteriochlorophyll c, d, or e molecules. A challenging task is to mimic the principle of self-assembling chromophores in artificial light-harvesting...
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Application of deep eutectic solvents in bioanalysis
PublikacjaThe application of deep eutectic solvents (DESs) is sharply surging as a green alternative to conventional solvents due to their unique properties in terms of simplicity of preparation, designability and low cost. A great deal of attention has been paid to the application of these green solvents in analytical chemistry in recent years, and a lot of interesting work has been reported. This review summarizes the most relevant applications...
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Toward Intelligent Vehicle Intrusion Detection Using the Neural Knowledge DNA
PublikacjaIn this paper, we propose a novel intrusion detection approach using past driving experience and the neural knowledge DNA for in-vehicle information system security. The neural knowledge DNA is a novel knowledge representation method designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing systems. We examine our approach for classifying malicious vehicle control commands...
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An automatic selection of optimal recurrent neural network architecture for processes dynamics modelling purposes
PublikacjaA problem related to the development of algorithms designed to find the structure of artificial neural network used for behavioural (black-box) modelling of selected dynamic processes has been addressed in this paper. The research has included four original proposals of algorithms dedicated to neural network architecture search. Algorithms have been based on well-known optimisation techniques such as evolutionary algorithms and...
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How Much Does an e-Vote Cost? Cost Comparison per Vote in Multichannel Elections in Estonia
PublikacjaWe are presenting the results of the CoDE project in this paper, where we investigate the costs per vote of different voting channels in Estonian Local Elections (2017). The elections analyzed involve different processes for casting a vote: Early Voting at County Centers, Advance Voting at County Centers, Advance Voting at Ordinary Voting District Committees, Electronic Voting, Election Day Voting, and Home Voting. Our analysis...
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A predictive estimation based control strategy for a quasi-resonant dc-link inverter
PublikacjaIn this paper the predictive estimation based control strategy for a quasi-resonant dc link inverter (PQRDCLI) is developed. Instead of direct measurement of dc link input inverter current – its estimation with one step prediction is applied. The PQRDCLI fed induction motor, controlled with a predictive current estimation stabilized inverter output voltage slopes independently of load. Moreover, reduction of overvoltage spikes...
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Blended Learning Model for Computer Techniques for Students of Architecture
PublikacjaAbstract: The article summarizes two-year experience of implementing hybrid formula for teaching Computer Techniques at the Faculty of Architecture at the Gdansk University of Technology. Original educational e-materials, consisting of video clips, text and graphics instructions, as well as links to online resources are embedded in the university e-learning educational platform. The author discusses technical constraints associated...
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Energy consumption optimization in wastewater treatment plants: Machine learning for monitoring incineration of sewage sludge
PublikacjaBiomass management in terms of energy consumption optimization has become a recent challenge for developed countries. Nevertheless, the multiplicity of materials and operating parameters controlling energy consumption in wastewater treatment plants necessitates the need for sophisticated well-organized disciplines in order to minimize energy consumption and dissipation. Sewage sludge (SS) disposal management is the key stage of...
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Edge-Computing based Secure E-learning Platforms
PublikacjaImplementation of Information and Communication Technologies (ICT) in E-Learning environments have brought up dramatic changes in the current educational sector. Distance learning, online learning, and networked learning are few examples that promote educational interaction between students, lecturers and learning communities. Although being an efficient form of real learning resource, online electronic resources are subject to...
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Genetic and biochemical determinants of serum concentrations of monocyte chemoattractant protein-1, a potential neural tube defect risk factor
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Patch size setup and performance/cost trade-offs in multi-objective EM-driven antenna optimization using sequential domain patching
PublikacjaPurpose This paper aims to assess control parameter setup and its effect on computational cost and performance of deterministic procedures for multi-objective design optimization of expensive simulation models of antenna structures. Design/methodology/approach A deterministic algorithm for cost-efficient multi-objective optimization of antenna structures has been assessed. The algorithm constructs a patch connecting extreme Pareto-optimal...
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Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects
PublikacjaModern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimizationand model prediction. The effective utilization of ML techniques for the development and scaling up of renewable energy systemsneeds a high degree of accountability. However, most of the ML approaches currently in use are termed black box since their work isdifficult to comprehend. Explainable artificial intelligence (XAI)...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublikacjaThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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Genetic predisposition to inflammatory bowel disease
PublikacjaInflammatory bowel disease (IBD) is a chronic, incurable inflammatory disease of the digestive system. The two main disease entities included in the IBD are ulcerative colitis and Crohn's disease. According to epidemiological studies there are more and more new cases every year. In especially among the youngest patients with symptoms of malnutrition and growth inhibition to land up in hospitalwith cancer suspected. The purpose...
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Playback detection using machine learning with spectrogram features approach
PublikacjaThis paper presents 2D image processing approach to playback detection in automatic speaker verification (ASV) systems using spectrograms as speech signal representation. Three feature extraction and classification methods: histograms of oriented gradients (HOG) with support vector machines (SVM), HAAR wavelets with AdaBoost classifier and deep convolutional neural networks (CNN) were compared on different data partitions in respect...
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SELECTING A REPRESENTATIVE DATA SET OF THE REQUIRED SIZE USING THE AGENT-BASED POPULATION LEARNING ALGORITHM
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Reliable routing and resource allocation scheme for hybrid RF/FSO networks
PublikacjaSignificant success of wireless networks in the last decade has changed the paradigms of communication networks design. In particular, the growing interest in wireless mesh networks (WMNs) is observed. WMNs offer an attractive alternative to conventional cable infrastructures, especially in urban areas, where the cost of new installations is almost prohibitive. Unfortunately, the performance of WMNs is often limited by the cluttered...
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Supramolecular deep eutectic solvents and their applications
PublikacjaIn recent years, the growing awareness of the harmfulness of chemicals to the environment has resulted in the development of green and sustainable technologies. The compromise between economy and environmental requirements is based on the development of new efficient and green solutions. Supramolecular deep eutectic solvents (SUPRADESs), a new deep eutectic solvent (DES) subclass characterized by inclusion properties, are a fresh...
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Fast method for IEEE 802.16-2004 standard-based networks coverage measuring
PublikacjaThis paper presents the time and cost efficient method for measuring effective coverage of IEEE 802.16-2004 standard-based networks. This is done by performing a series of continuous measurements on the grid basis. Due to this kind of signal quality surveying, estimationof the probable coverage area can be made. It is significant that themethod is fast and is uses a standard customer equipment which makes it more accessible for...
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Quantitative Analysis of Biofilm Formed on Vascular Prostheses by Staphylococcus Epidermidis with Different ica and aap Genetic Status
PublikacjaOBJECTIVES: This study aims to examine biofilm formed on vascular prostheses by Staphylococcus epidermidis with different ica and aap genetic status, and to evaluate the effect of antibiotic-modified prostheses on bacterial colonization. METHODS: Biofilm formation was determined using fluorescence microscopy imaging. Quantitative analysis was conducted using the biofilm coverage ratio (BCR) calculations. RESULTS: Our investigations...
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The Neural Knowledge DNA Based Smart Internet of Things
PublikacjaABSTRACT The Internet of Things (IoT) has gained significant attention from industry as well as academia during the past decade. Smartness, however, remains a substantial challenge for IoT applications. Recent advances in networked sensor technologies, computing, and machine learning have made it possible for building new smart IoT applications. In this paper, we propose a novel approach: the Neural Knowledge DNA based Smart Internet...
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Machine learning-based seismic fragility and seismic vulnerability assessment of reinforced concrete structures
PublikacjaMany studies have been performed to put quantifying uncertainties into the seismic risk assessment of reinforced concrete (RC) buildings. This paper provides a risk-assessment support tool for purpose of retrofitting and potential design strategies of RC buildings. Machine Learning (ML) algorithms were developed in Python software by innovative methods of hyperparameter optimization, such as halving search, grid search, random...
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Efficient handover scheme for Mobile IPv4 over IEEE 802.11 networks with IEEE 802.21 triggers.
PublikacjaEfektywność przełączania jest bardzo istotnym parametrem, decydującym o pracy sieci bezprzewodowych, realizujacych usługi multimedialne na wysokim poziomie jakości. Użytkownicy takich sieci oczekują ciągłej obsługi podczas procesu przemieszczania się. Okazuje się, że istotnym źródlem opóźnień są nieefektywne procedury przełączania w warstwach drugiej i trzeciej, wynikający częściowo z postulatu o separacji funkcji realizowanych...
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A novel class-based protection algorithm providing fast service recovery in IP/WDM networks
PublikacjaW artykule rozważa się warstwową strukturę sieci IP-MPLS/WDM. Węzły sieci mają funkcjonalność zarówno optycznych krotnic transferowych (OXC), jak i routerów IP. Dowolne dwa routery IP mogą być ze sobą połączone poprzez logiczne łącze IP realizowane przez ścieżkę optyczną WDM. Zaproponowano metodę klasową doboru tras przeżywalnych zapewniającą szybkie odtwarzanie uszkodzonych strumieni ruchu zarówno w warstwie WDM jak i IP-MPLS....
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Dynamic unattended measurement based routing algorithm for diffServ architecture
PublikacjaDynamic routing is very important in terms of assuring QoS in today's packet networks especially for streaming and elastic services. Existing solutions dedicated to dynamic routing are often too complicated and seem to be not usable in real time traffic scenarios where transferred traffic may vary significantly. This was the main reason for research and new routing mechanism proposal which should apply to today's packet networks....
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Computer experiments with a parallel clonal selection algorithm for the graph coloring problem
PublikacjaArtificial immune systems (AIS) are algorithms that are based on the structure and mechanisms of the vertebrate immune system. Clonal selection is a process that allows lymphocytes to launch a quick response to known pathogens and to adapt to new, previously unencountered ones. This paper presents a parallel island model algorithm based on the clonal selection principles for solving the Graph Coloring Problem. The performance of...
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How Machine Learning Contributes to Solve Acoustical Problems
PublikacjaMachine learning is the process of learning functional relationships between measured signals (called percepts in the artificial intelligence literature) and some output of interest. In some cases, we wish to learn very specific relationships from signals such as identifying the language of a speaker (e.g. Zissman, 1996) which has direct applications such as in call center routing or performing a music information retrieval task...
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INVESTIGATION OF THE LOMBARD EFFECT BASED ON A MACHINE LEARNING APPROACH
PublikacjaThe Lombard effect is an involuntary increase in the speaker’s pitch, intensity, and duration in the presence of noise. It makes it possible to communicate in noisy environments more effectively. This study aims to investigate an efficient method for detecting the Lombard effect in uttered speech. The influence of interfering noise, room type, and the gender of the person on the detection process is examined. First, acoustic parameters...
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Experimental tests of reinforced concrete deep-beams
PublikacjaThe paper presents results of experimental research of the reinforced concrete deep beam with a spatial arrangement. Tested structural elements consist of the cantilever deep beam loaded on the height and transverse deep beam with hanging on it another one. The analysis includes crack morphology, effort of steel and load distribution. The article verified effectiveness of two different kind of reinforcement in both tested deep...
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Accurate Lightweight Calibration Methods for Mobile Low-Cost Particulate Matter Sensors
PublikacjaMonitoring air pollution is a critical step towards improving public health, particularly when it comes to identifying the primary air pollutants that can have an impact on human health. Among these pollutants, particulate matter (PM) with a diameter of up to 2.5 μ m (or PM2.5) is of particular concern, making it important to continuously and accurately monitor pollution related to PM. The emergence of mobile low-cost PM sensors...
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Experimental investigations and prediction of WEDMed surface of nitinol SMA using SinGAN and DenseNet deep learning model
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Artificial intelligence for software development — the present and the challenges for the future
PublikacjaSince the time when first CASE (Computer-Aided Software Engineering) methods and tools were developed, little has been done in the area of automated creation of code. CASE tools support a software engineer in creation the system structure, in defining interfaces and relationships between software modules and, after the code has been written, in performing testing tasks on different levels of detail. Writing code is still the task...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublikacjaThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Efficient Multi-Fidelity Design Optimization of Microwave Filters Using Adjoint Sensitivity
PublikacjaA simple and robust algorithm for computationally efficient design optimiza-tion of microwave filters is presented. Our approach exploits a trust-region (TR)-based algorithm that utilizes linear approximation of the filter response obtained using adjoint sensitivity. The algorithm is sequentially executed on a family of electromagnetic (EM)-simulated models of different fidelities, starting from a coarse-discretization one, and...
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Performance comparison of new modified gradient algorithm and Foy algorithm for iterative position calculation
PublikacjaIn the paper a new position calculation algorithm is presented. It is proposed for indoor environments and is called modified gradient algorithm. This algorithm is compared with well-known Foy algorithm. The comparative analysis is based on real distance measurements conducted in indoor environment.
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Social learning in cluster initiatives
PublikacjaPurpose – The purpose of the paper is to portray social learning in cluster initiatives (CIs), namely: 1) to explore, with the lens of the communities of practice (CoPs) theory, in what ways social learning occurs in CIs; 2) to discover how various CoPs emerge and evolve in CIs to facilitate a collective journey in their learning process. Subsequently, the authors address the research questions: In what ways does social learning...
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Grid-Forming Operation of Energy-Router Based on Model Predictive Control with Improved Dynamic Performance
PublikacjaThe focus of this study is on the grid-forming operation of the Energy Router (ER) based on Model Predictive Control (MPC). ER is regarded as a key component of microgrids. It is a converter that interfaces the microgrid (s) with the utility grid. The ER has a multiport structure and bidirectional energy flow control. The ER concept can be implemented in Nearly Zero-Energy Buildings (NZEB) to provide flexible energy control. A...