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Hybrid nanomaterials fabricated by the heterogeneous integration of 1D (carbon nanotubes) and 2D (graphene oxide) nanomaterials showed synergy in electrical and mechanical properties. Here, we reported the infiltration of carboxylic functionalized single-walled carbon nanotubes (C-SWNT) into free-standing graphene oxide (GO) paper for better electrical and mechanical properties than native GO. The stacking arrangement of GO sheets and its alteration in the presence of C-SWNT were comprehensively explored through scanning electron microscopy, X-ray photoelectron spectroscopy (XPS) and X-ray diffraction. The C-SWNTs bridges between different GO sheets produce a pathway for the flow of electrical charges and provide a tougher hybrid system. The nanoscopic surface potential map reveals a higher work function of the individual functionalised SWNTs than surrounded GO sheets showing efficient charge exchange. We observed the enhanced conductivity up to 50 times and capacitance up to 3.5 times of the hybrid structure than the GO-paper. The laminate of polystyrene composites provided higher elastic modulus and mechanical strength when hybrid paper is used, thus paving the way for the exploitation of hybrid filler formulation in designing polymer composites.

Hybrid microfluidic systems that are composed of multiple different types of substrates have been recognized as a versatile and superior platform, which can draw benefits from different substrates while avoiding their limitations. This review article introduces the recent innovations of different types of low-cost hybrid microfluidic devices, particularly focusing on cost-effective polymer- and paper-based hybrid microfluidic devices. In this article, the fabrication of these hybrid microfluidic devices is briefly described and summarized. We then highlight various hybrid microfluidic systems, including polydimethylsiloxane (PDMS)-based, thermoplastic-based, paper/polymer hybrid systems, as well as other emerging hybrid systems (such as thread-based). The special benefits of using these hybrid systems have been summarized accordingly. A broad range of biological and biomedical applications using these hybrid microfluidic devices are discussed in detail, including nucleic acid analysis, protein analysis, cellular analysis, 3D cell culture, organ-on-a-chip, and tissue engineering. The perspective trends of hybrid microfluidic systems involving the improvement of fabrication techniques and broader applications are also discussed at the end of the review.

Artificial Intelligence, Machine Learning, Fuzzy Logic, Neural Network, Genetic Algorithm and their hybrid systems play vital role in the medical sciences to diagnose various diseases efficiently in the patients. The problems related to the heart are widely comon in today’s world. The risk of heart failure develops due to the narrowness and blockage in the coronary arteries of the heart as excess cholesterol deposits in the arteries and blood vessels that results in fatigue, chest pain, dyspnoea, sleeping difficulties and depression. This research aims to explore diverse work done on FL and Hybrid-based techniques to identify the risk of heart disease among the patients. The present study reveals publications along with the strength, operating system, accuracy rate and other specifications used in the identification of heart disease based on FL and Hybrid-based approaches since 2010. This survey contributes motivation for research scholars to generate more innovative ideas and continue their research work in the respective field. Moreover, the future model for direct service of the patients from old age homes to the Intensive Care Unit through ambulance services is also presented in this paper.

In this study, an exoskeleton type robot-assisted rehabilitation system, called RehabRoby, is developed for rehabilitation purposes. A control architecture, which contains a high-level controller and a low-level controller, is designed so that RehabRoby can complete the given rehabilitation task in a desired and safe manner. A hybrid system modelling technique is used for the high-level controller. An admittance control with an inner robust position control loop is used for the low-level control of the RehabRoby. Real-time experiments are performed to evaluate the control architecture of the robot-assisted rehabilitation system, RehabRoby. Furthermore, the usability of RehabRoby is evaluated. Support Programme for Scientific and Technological Research ProjectsTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [TUBITAK-3501, 108E190] We gratefully acknowledge the help of Prof. Serap Inal and Prof. Sule Badilli Demirbas, who are in the Physiotherapy and Rehabilitation Department of the Faculty of Health Sciences Yeditepe University, for their valuable feedback concerning the task design. The study was supported by the Support Programme for Scientific and Technological Research Projects (TUBITAK-3501) under Grant 108E190.

Background Information related to patient medication is crucial for health care; however, up to 80% of the information resides solely in unstructured text. Manual extraction is difficult and time-consuming, and there is not a lot of research on natural language processing extracting medical information from unstructured text from French corpora. Objective We aimed to develop a system to extract medication-related information from clinical text written in French. Methods We developed a hybrid system combining an expert rule–based system, contextual word embedding (embedding for language model) trained on clinical notes, and a deep recurrent neural network (bidirectional long short term memory–conditional random field). The task consisted of extracting drug mentions and their related information (eg, dosage, frequency, duration, route, condition). We manually annotated 320 clinical notes from a French clinical data warehouse to train and evaluate the model. We compared the performance of our approach to those of standard approaches: rule-based or machine learning only and classic word embeddings. We evaluated the models using token-level recall, precision, and F-measure. Results The overall F-measure was 89.9% (precision 90.8; recall: 89.2) when combining expert rules and contextualized embeddings, compared to 88.1% (precision 89.5; recall 87.2) without expert rules or contextualized embeddings. The F-measures for each category were 95.3% for medication name, 64.4% for drug class mentions, 95.3% for dosage, 92.2% for frequency, 78.8% for duration, and 62.2% for condition of the intake. Conclusions Associating expert rules, deep contextualized embedding, and deep neural networks improved medication information extraction. Our results revealed a synergy when associating expert knowledge and latent knowledge.

The current study presents a detailed evaluation and comparison between two integrated anaerobic–aerobic systems for biological wastewater treatment under equal conditions in all aspects (wastewater characteristics, climatic conditions, reactor sizing, and even the measurement methods). The two examined systems are (i) a hybrid upflow anaerobic sludge blanket (hybrid UASB) coupled with integrated fixed-film activated sludge (IFAS) and (ii) a conventional UASB coupled with activated sludge (AS). The present comparative study aims to evaluate and assess the effect of adding carrier-filling media on the performance of the classical integrated UASB-AS. The two parallel pilot-scale systems, hybrid UASB-IFAS and UASB-AS, were installed and operated at a wastewater treatment plant. Three sets of experiments were conducted to examine the influence of the hydraulic retention time (HRT) on the consequent organic and hydraulic loads, temperature, and recirculation rate of the proposed systems. The main results showed that the two investigated systems had a comparably high efficiency for the removal of organic matters and ammonia. Moreover, a paired sample t-test indicated there was a statistically significant effect of the filling media, and the performance of the hybrid UASB-IFAS increased significantly compared with that of the UASB-AS system. An additional benefit of the filling media on the hybrid system was its high stability when changing the organic and hydraulic loads. The optimum HRT was 6 h, with a total chemical oxygen demand (TCOD) percentage removal of approximately 95% in both examined systems. Treatment of sewage under high and low temperatures indicated that increasing the temperature improved the efficiency of the overall process for both systems significantly.

The current experimental and theoretical study proposes forward osmosis (FO)-reverse osmosis (RO) (FR*) and FO-FO-RO (FFR) hybrid systems to combine concentration of cheese whey and Caspian seawater desalination. The powerful TF-PMM was used as a FO membrane. The impact of sales of concentrated cheese whey on reducing Caspian seawater desalination costs was studied. The results showed that the TF-PMM has good potential for concentration of cheese whey with a water flux of about 12.62 L/m2h. In terms of permeate concentration (Cp) and at low recovery rates (RR), the choice of FR* and FFR hybrid systems with 0.3 M NaCl as the draw solution (DS) should be the priority. At high RR, although the sensitivity of the type of system is reduced, the FR* system should not be used. The total power consumption (Est) for the FR*-30 % and FR*-50 % systems are lower than that of a single RO unit. In FR* hybrid system by increasing the RRFO1, the power consumption of the FO unit and also the Est decreased. Also, in the FFR system, by increasing the concentration of the DS, while increasing the Est, the power consumption portion of the FO unit decreased. The existence of a valuable by-product in the proposed hybrid systems increases the allowable limit of the cost of required equipment and other operating costs to achieve profitability and reach the break-even point. In the meantime, the FR*-50 % system generates the most revenue, and also the quality of produced freshwater from the FFR-50 %–0.3 M system is the highest.

Due to the high UHV AC/DC transmission line tower, the working voltage amplitude on the wire is large, causing lightning accidents. The paper first analyses the impact of lightning strike point on lightning overvoltage of 1000 kV UHV transformer substation and determines the research object of lightning intruding wave overvoltage. Second, the influence of the impact grounding resistance of transformer side lightning arrester and transmission line tower on invaded wave is analysed. Finally, the commutation failure of HVDC system was analysed, and the simulation tests were carried out by CIGER standard model in PSCAD and Simulink, valve voltage and valve current waveform can be used as a new basis for judgment. The conclusion shows that the analysis of UHV AC/DC hybrid system commutation failure should start from the DC system to study, and commutation failure directly related to the failure, operating conditions, and other factors.

Background Lignocellulosic biomass is one of the most promising alternatives for replacing mineral resources to overcome global warming, which has become the most important environmental issue in recent years. Furfural was listed by the National Renewable Energy Laboratory as one of the top 30 potential chemicals arising from biomass. However, the current production of furfural is energy intensive and uses inefficient technology. Thus, a hybrid purification process that combines extraction and distillation to produce furfural from lignocellulosic biomass was considered and investigated in detail to improve the process efficiency. This effective hybrid process depends on the extracting solvent, which was selected based on a comprehensive procedure that ranged from solvent screening to complete process design. Results Various solvents were first evaluated in terms of their extraction ability. Then, the most promising solvents were selected to study the separation feasibility. Eventually, processes that used the three best solvents (toluene, benzene, and butyl chloride) were designed and optimized in detail using Aspen Plus. Sustainability analysis was performed to evaluate these processes in terms of their energy requirements, total annual costs (TAC), and carbon dioxide (CO2) emissions. The results showed that butyl chloride was the most suitable solvent for the hybrid furfural process because it could save 44.7% of the TAC while reducing the CO2 emissions by 45.5% compared to the toluene process. In comparison with the traditional purification process using distillation, this suggested hybrid extraction/distillation process can save up to 19.2% of the TAC and reduce 58.3% total annual CO2 emissions. Furthermore, a sensitivity analysis of the feed composition and its effect on the performance of the proposed hybrid system was conducted. Conclusions Butyl chloride was found to be the most suitable solvent for the hybrid extraction/distillation process of furfural production. The proposed hybrid sequence was more favorable than the traditional distillation process when the methanol fraction of the feed stream was

The control of nitrite-oxidizing bacteria (NOB) challenges the implementation of partial nitritation and anammox (PN/A) processes under mainstream conditions. The aim of the present study was to understand how operating conditions impact microbial competition and the control of NOB in hybrid PN/A systems, where biofilm and flocs coexist. A hybrid PN/A moving-bed biofilm reactor (MBBR; also referred to as integrated fixed film activated sludge or IFAS) was operated at 15 °C on aerobically pre-treated municipal wastewater (23 mgNH4-N·L−1). Ammonium-oxidizing bacteria (AOB) and NOB were enriched primarily in the flocs, and anammox bacteria (AMX) in the biofilm. After decreasing the dissolved oxygen concentration (DO) from 1.2 to 0.17 mgO2·L−1 - with all other operating conditions unchanged - washout of NOB from the flocs was observed. The activity of the minor NOB fraction remaining in the biofilm was suppressed at low DO. As a result, low effluent NO3− concentrations (0.5 mgN·L−1) were consistently achieved at aerobic nitrogen removal rates (80 mgN·L−1·d−1) comparable to those of conventional treatment plants. A simple dynamic mathematical model, assuming perfect biomass segregation with AOB and NOB in the flocs and AMX in the biofilm, was able to qualitatively reproduce the selective washout of NOB from the flocs in response to the decrease in DO-setpoint. Similarly, numerical simulations indicated that flocs removal is an effective operational strategy to achieve the selective washout of NOB. The direct competition for NO2− between NOB and AMX - the latter retained in the biofilm and acting as a “NO2-sink” - was identified by the model as key mechanism leading to a difference in the actual growth rates of AOB and NOB (i.e., μNOB < μAOB in flocs) and allowing for the selective NOB washout. Experimental results and model predictions demonstrate the increased operational flexibility, in terms of variables that can be easily controlled by operators, offered by hybrid systems as compared to solely biofilm systems for the control of NOB in mainstream PN/A applications.HighlightsHybrid PN/A systems provide increased operational flexibility for NOB controlAOB and NOB enrich primarily in the flocs, and AMX in the biofilm (“NO2-sink”)AMX use NO2− allowing to differentiate AOB and NOB growth ratesA decrease in DO or an increase in floc removal leads to selective NOB washout from flocsThe activity of the minor NOB fraction in the biofilm is suppressed at limiting DO

Self-propelled micromotors are emerging as important tools that help us understand the fundamentals of motion at the microscale and the nanoscale. Development of the motors for various biomedical and environmental applications is being pursued. Multiple fabrication methods can be used to construct the geometries of different sizes of motors. Here, we present an overview of appropriate methods of fabrication according to both size and shape requirements and the concept of guiding the catalytic motors within the confines of wall. Micromotors have also been incorporated with biological systems for a new type of fabrication method for bioinspired hybrid motors using three-dimensional (3D) printing technology. The 3D printed hybrid and bioinspired motors can be propelled by using ultrasound or live cells, offering a more biocompatible approach when compared to traditional catalytic motors.

This paper presents a wearable biopatch prototype for body surface potential measurement. It combines three key technologies, including mixed-signal system on chip (SoC) technology, inkjet printing technology, and anisotropic conductive adhesive (ACA) bonding technology. An integral part of the biopatch is a low-power low-noise SoC. The SoC contains a tunable analog front end, a successive approximation register analog-to-digital converter, and a reconfigurable digital controller. The electrodes, interconnections, and interposer are implemented by inkjet-printing the silver ink precisely on a flexible substrate. The reliability of printed traces is evaluated by static bending tests. ACA is used to attach the SoC to the printed structures and form the flexible hybrid system. The biopatch prototype is light and thin with a physical size of 16 cm x 16 cm. Measurement results show that low-noise concurrent electrocardiogram signals from eight chest points have been successfully recorded using the implemented biopatch. QC 20130805. Updated from accepted to published.

As artificial intelligence becomes ubiquitous in our lives, so do the opportunities to combine machine and human intelligence to obtain more accurate and more resilient prediction models across a wide range of domains. Hybrid intelligence can be designed in many ways, depending on the role of the human and the algorithm in the hybrid system. This paper offers a brief taxonomy of hybrid intelligence, which describes possible relationships between human and machine intelligence for robust forecasting. In this taxonomy, biological intelligence represents one axis of variation, going from individual intelligence (one individual in isolation) to collective intelligence (several connected individuals). The second axis of variation represents increasingly sophisticated algorithms that can take into account more aspects of the forecasting system, from information to task to human problem-solvers. The novelty of the paper lies in the interpretation of recent studies in hybrid intelligence as precursors of a set of algorithms that are expected to be more prominent in the future. These algorithms promise to increase hybrid system’s resilience across a wide range of human errors and biases thanks to greater human-machine understanding. This work ends with a short overview for future research in this field.

International audience; This paper proposes a numerical approach to the stability analysis for a class of piecewise-affine systems with (possibly time-varying) parameter-dependent cells and dynamics. This class of model aims at allowing a better modelling of time-varying or parameter-varying nonlinearities of physical phenomena such as dry friction. We form the stability certification problem as the one of finding a Lyapunov function that is parameterised as a polynomial function of the variable parameter. The application of the well-known Lyapunov stability theorem together with the use of the generalised S-procedure reduces the problem to checking whether a certain set of matrices has the sum-of-squares property. The latter can be solved using well-documented numerical solvers, and we provide two examples of successful applications at the end of the paper.

MLD system is a type of hybrid system, which adopts the form of integer linear inequality including continuous variable and logical variable, which reflects both continuous and discrete dynamic characteristics by switching law. In this paper, the problem of optimal management of open laboratories in Colleges and universities is illustrated in the form of a class of advanced MLD system. By analyzing the main factors of laboratory consumption, the laboratory cost function is established. Taking the minimum cost as the objective function, it uses the random number of students in the laboratory to realize the energy-saving optimization management of the laboratory. At the end of this paper, a simulation example is used to analyze the process of MLD system used in laboratory optimization management, which shows hybrid dynamic characteristics, optimal management effect and ideal applicability.

The paper concerns the design analysis of a hybrid gas turbine power plant with a fuel cell (stack). The aim of this work was to find the most favourable variant of the medium capacity (approximately 10 MW) hybrid system. In the article, computational analysis of two variants of such a system was carried out. The analysis made it possible to calculate the capacity, efficiency of both variants and other parameters like the flue gas temperature. The paper shows that such hybrid cycles can theoretically achieve extremely high efficiency over 60%. The most favourable one was selected for further detailed thermodynamic and flow calculations. As part of this calculation, a multi-stage axial compressor, axial turbine, fuel cell (stack) and regenerative heat exchanger were designed. Then an analysis of the profitability of the installation was carried out, which showed that the current state of development of this technology and its cost make the project unprofitable. For several years, however, tendencies of decreasing prices of fuel cells have been observed, which allows the conclusion that hybrid systems will start to be created. This may apply to both stationary and marine applications. Hybrid solutions related to electrical power transmission, including fuel cells, are real and very promising for smaller car ferries and shorter ferry routes.

This paper deals with the problem of passivity analysis and passivity-based synthesis for continuous-time stochastic hybrid singular systems (SHSSs). First, a set of linear matrix inequalities for the stochastic admissibility and passivity, which is also known as the positive real lemma, is obtained for continuous-time SHSSs. The proposed condition successfully holds a necessary and sufficient condition for the positive realness of SHSSs, whereas the existing papers in the literature have been handled only sufficient conditions. Next, the passivity-based control synthesis problem is also considered based on the new positive real lemma. The passivity-based stabilization criterion for the closed-loop system with its mode-dependent state-feedback control is expressed in terms of matrix inequality. Thus, by introducing an additional slack matrix to the non-convex conditions, the feasible conditions for the control gain are obtained in terms of linear matrix inequalities. Finally, a numerical example is provided to show the effectiveness of the result.

In the present research, properties and performance of special effect printing inks were observed with the aim of obtaining a printed product with dual functional properties. Thermochromic liquid crystal-based printing ink (TLC) and UV-visible (daylight invisible) fluorescent inks (UVF), pure and as hybrid ink systems, were printed using a screen-printing technique on two types of uncoated paper substrates. Characterization of the paper substrates was performed, as well as detailed analysis of printed layers. Thickness, surface roughness, surface free energy, and adhesion parameters of printed layers were analysed. Spectral reflectance of pure UVF and TLC printing inks, as well as the spectral reflectance of the proposed hybrid ink systems were measured. The thermochromic effect of the TLC ink and hybrid systems was analysed. Microscopy was used to display the visual colour play effect and the effect of the fluorescence. Results of the measurements showed high compatibility of used materials in the proposed hybrid ink systems. Since the effect of luminescence and the colour play effect in the hybrid systems were preserved, it can be concluded that TLC/UVF hybrid ink systems can find their application in the development of functional packaging and in all other applications with special requirements for temperature monitoring and hidden information for different products.

The use of hybrid systems for electrification of remote areas has been increased dramatically in recent years, and the optimal sizing of these systems is a significant challenge for cost-effectiveness and reliability. This paper aims to propose a predictable planning framework that increases the renewable energy penetration (REP) rate and minimizes the annualized cost of the system (ACS) considering C O 2 emission and different loss of power supply probability (LPSP). Due to the unavailability of precise weather data in remote areas, an intelligent weather forecasting scheme is developed using an adaptive neuro-fuzzy process based on fuzzy c-means clustering technique to estimate the solar radiation, wind speed, and ambient temperature. This paper also examines various evolutionary algorithms and compare the collected result of the proposed Multi-Verse Optimizer (MVO) with other meta-heuristic methods in terms of total annualized cost with different LPSP, and REP amounts. Moreover, to assess the impact of wind speed, solar irradiation, the lifespan of battery energy storage systems, and the fuel price of diesel engine generators on optimal sizing problem, a sensitivity analysis is performed for different values of REP and LPSP. The effectiveness of the proposed approach is verified using a realistic case study in the Sistan & Balouchestan province of Iran. Simulation results illustrate that using photovoltaic panels, wind turbine generators, battery energy storage systems, and diesel engine generators (PV/WTG/BESS/DEG) is the most cost-effective strategy resulting in a 96.13% decrease of C O 2 emission compared to DEG system at R E P m i n = 97 % and L P S P m a x = 1 % . Moreover, the growth of fuel cost causes an increase in the production of renewable energy resources (RESs) and a decrease in the usage of diesel engine generators. Consequently, for L P S P m a x = 10 % and R E P m i n = 91 % , and 50% rise in the price of fuel, the number of DEG drops to zero, and the optimal number of PV and BESS increase from 311 and 172 to 411 and 228, respectively.

Combining wave energy converters (WECs) with a floating breakwater provides a potential approach to help develop commercial-scale wave power operations. This paper aims to design and optimize a three-dimensional floating breakwater integrated with a WEC array by developing a numerical model of a multi-floating-body coupled system based on potential flow theory with viscous correction in the frequency domain. By analyzing the wave surface elevations around the breakwater, the size of the breakwater was optimized and the optimal installation locations of the WECs were determined. Under the condition of coupled constraints and six degrees-of-freedom motion, the interactions between the WEC array and the breakwater were analyzed. Subsequently, the number of WECs and the distance between the WECs and the breakwater were optimized to maximize the wave energy conversion performance of the hybrid system. Results show that the wave focusing areas appear more frequently near the breakwater. These focusing areas significantly improve WEC power, and thus better wave energy conversion performance can be achieved when the WECs are placed close to the breakwater. The vertical forces on the breakwater significantly increase due to the presence of the WECs, however the horizontal forces are decreased. The findings of this paper provide guidance to design and optimize a hybrid WEC-breakwater system in practical engineering applications.

As promising solutions to various social and environmental issues, the generation and integration of renewable energy (RE) into microgrids (MGs) has recently increased due to the rapidly growing consumption of electric power. However, such integration can affect the stability and security of power systems due to its complexity and intermittency. Therefore, an optimal control approach is essential to ensure the efficiency, reliability, and quality of the delivered power. In addition, effective planning of policies for integrating MGs can help promote MG operations. However, outages may render these strategies inefficient and place the power system at risk. MGs are considered an ideal candidate for distributed power systems, given their capability to restore these systems rapidly after a physical or cyber-attack and create reliable protection systems. The energy management system (EMS) in an MG can operate controllable distributed energy resources and loads in real-time to generate a suitable short-term schedule for achieving some objectives. This paper presents a comprehensive review of MG elements, the different RE resources that comprise a hybrid system, and the various types of control, operating strategies, and goals in an EMS. A detailed explanation of the primary, secondary, and tertiary levels of MGs is also presented. This paper aims to contribute to the policies and regulations adopted by certain countries, their protection schemes, transactive markets, and load restoration in MGs.

For commercial applications, the durability and economy of the fuel cell hybrid system have become obstacles to be overcome, which are not only affected by the performance of core materials and components, but also closely related to the energy management strategy (EMS). This paper takes the 7.9 t fuel cell logistics vehicle as the research object, and designed the EMS from two levels of qualitative and quantitative analysis, which are the composite fuzzy control strategy optimized by genetic algorithm and Pontryagin’s minimum principle (PMP) optimized by objective function, respectively. The cost function was constructed and used as the optimization objective to prolong the life of the power system as much as possible on the premise of ensuring the fuel economy. The results indicate that the optimized PMP showed a comprehensive optimal performance, the hydrogen consumption was 3.481 kg/100 km, and the cost was 13.042 $/h. The major contribution lies in that this paper presents a method to evaluate the effect of different strategies on vehicle performance including fuel economy and durability of the fuel cell and battery. The comparison between the two totally different strategies helps to find a better and effective solution to reduce the lifetime cost.

The paper deals with the characteristics of three different types of power train hybridization of forest logging machines and with the benefits of reducing environmental impacts by comparing new technology with more conventional, older technology. New hybridization options that could be implemented in forestry machines are also discussed. The paper divides a hybrid solution into three classes based on the energy used in the system of hybridization. First is an electro-hybrid system that uses an electric motor and battery or different storage device. The second, a hydraulic hybrid system, is a solution with a hydraulic accumulator, hydraulic motor, and pump. The third system is a combination of the electro-hybrid and hydraulic-hybrid system. The current technical and technological development of hybrid drive systems, as well as their components, has led to significant improvements in drive performance and thus better performance of the new generation of forest vehicles. Improved energy efficiency using hybrid propulsion systems in forest vehicles would result in a significant reduction in greenhouse gas emissions and possibly lower maintenance costs.

Still a lot of Indonesia’s population lacks access to electricity, and a large number of those people live in remote areas or on islands. Traditionally, electrification of areas not yet connected to the main electricity grid and too remote for grid extension has mainly been achieved through installation of decentralized generation units with diesel generators. However, with decreased cost of renewable energy technologies, renewable hybrid mini-grid systems are becoming economically viable options in an ever-increasing number of places. This paper analyzes the economic viability of renewable hybrid mini-grid systems with solar Photo-Voltaic cells, batteries, and diesel generators in a typical un-electrified village in Indonesia employing local data. The analysis is conducted by utilizing HOMER simulation techniques to design the optimal renewable hybrid mini-grid systems and the economic viability assessment of the system is performed by comparing the levelized cost of energy of the system with that of the conventional diesel system under different financial scenarios. Further financial analyses, such as Internal Rate of Return and Net Present Value, are performed for the hybrid systems to investigate what kind of financial scenarios (debt/equity ratios) and public aid (international aid and government fund), would make the hybrid systems attractive to private investors. The analysis has clarified that even at the most conservative scenario with 100% equity finance, the levelized cost of energy of the renewable hybrid mini-grid system is lower than that of the diesel system. Further analysis has shown that grant finance that covers 35% of the total project cost could make the hybrid system a profitable investment project for private investors even in the most conservative scenario. The paper also demonstrates that the profitability of renewable hybrid mini-grid systems is highly affected by financial scenarios (debt/equity ratios) in comparison with that of diesel systems, concluding with policy recommendations.

The energy management strategy is the key to achieve fuel cell hybrid system operation with high-efficiency and low-energy cost. The widely used energy management strategies are established based on the fixed models of power sources energy consumption and efficiency. However, due to the gradual performance degradation of the fuel cell during the service period, some model parameters will change significantly and the fixed models will become increasingly inaccurate over time. Therefore, this paper established time-varying models of power sources energy consumption and efficiency by introducing the fuel cell degradation rate. On this basis, in order to reduce the energy consumption of the system, improve the fuel cell efficiency and relatively maintain the SOC level, a novel dual-mode energy management strategy, DMDEE, for hybrid vehicles was proposed. In order to improve the online operation speed of proposed energy management strategy, the optimal control rules were obtained by offline calculation first. Then through comparison experiments with other two energy management strategies, PMP and PF, it was verified that the proposed strategy can effectively reduce the system energy consumption and improve the efficiency of the fuel cell system, meanwhile could make the SOC regress after its deviating from ideal working area. In addition, the mode switching hysteresis control was also validated. Therefore, the effectiveness and superiority of the proposed energy management strategy in this paper has been verified.

Heat storage systems with multiple heat sources play an important role in consuming extra wind power. A reasonable scheduling strategy for a hybrid system with multiple heat and electric sources could provide greater economic benefits. However, the present scheduling methods primarily focus on extra wind power consumption alone. This paper aims to develop a coordinated dispatching method that targets the maximum extra wind power consumed and highest economic benefit of the hybrid energy system as the optimization objective. A two-step coordinated dispatching method is proposed, where the first step focuses on optimizing the extra wind power consumed by coordinating the consumption quota for different types of energy sources at the system level and distributes the consumption share for every unit within each type of energy source, thereby maximizing fuel savings and economic benefits in the second step. The effectiveness of the approach is demonstrated using simulation results for an electric-heat hybrid system. Compared with two existing dispatching methods, the scheduling strategy presented in this paper could consume more extra wind power and provide higher fuel savings and economic benefits.

This paper investigates the abnormal noise and vibration of a hybrid electric vehicle during the electric-only driving mode. The sources of the noise and vibration are first identified through the frequency analysis, and then several measures are implemented to reduce the noise and vibration level. The experimental results have identified the gear meshing in the compound planetary gear set is the main source of the noise and vibration. The theoretical analysis demonstrates that gear pairs of the short planet-small sun gear and short planet-long planet in the compound planetary gear set contribute to the main noise and vibration of the hybrid system in the electric-only driving mode. This research also shows that the gear-meshing noise level in the compound planetary gear set can be decreased significantly by matching the engagement parameters, such as meshing stiffness, tooth error, and pitch error. The observation results in this paper are able to provide a practical reference for improving the ride comfort of hybrid electric vehicles in the future study.

This paper deals with an optimal control problem for a linear system of first-order hyperbolic equations with a function on the right-hand side determined from controlled bilinear ordinary differential equations. These ordinary differential equations are linear with respect to state functions with controlled coefficients. Such problems arise in the simulation of some processes of chemical technology and population dynamics. Normally, general optimal control methods are used for these problems because of bilinear ordinary differential equations. In this paper, the problem is reduced to an optimal control problem for a system of ordinary differential equations. The reduction is based on non-classic exact increment formulas for the cost-functional. This treatment allows to use a number of efficient optimal control methods for the problem. An example illustrates the approach.

This paper studies set invariance and contractivity in hybrid systems modeled by hybrid inclusions using barrier functions. After introducing the notion of a multiple barrier functions, we investigate the tightest possible sufficient conditions to guarantee different forward invariance and contractivity notions of a closed set for hybrid systems with nonuniqueness of solutions and solutions terminating prematurely. More precisely, we consider forward (pre-)invariance of sets, which guarantees solutions to stay in a set, and (pre-)contractivity, which further requires solutions that reach the boundary of the set to evolve (continuously or discretely) towards its interior. Our conditions for forward invariance and contractivity involve infinitesimal conditions in terms of multiple barrier functions. Examples illustrate the results. Keywords: Forward invariance, contractivity, barrier functions, hybrid dynamical systems., Technical report accompanying the paper entitled: Sufficient conditions for forward invariance and contractivity in hybrid inclusions using barrier functions, submitted to Automatica, 2019

This paper presents the performance of a novel hybrid islanding detection method (IDM) for multi-single-phase photovoltaic (PV) inverters based on the combination of four active methods and three passive methods. Although islanding detection in PV multi-inverter systems has been widely researched, most islanding studies are focused on three-phase inverters, rather than single-phase ones. In this paper, different active and passive methods are used to detect the islanding of four paralleled single-phase PV inverters. By combining those methods synergistically, it reduces their weakness of each method, while combining their advantages. The novelty of the proposed system methodology consists of four paralleled single-phase inverters equipped with four different active methods, named Active Frequency Drift (AFD), Sandia Frequency Shift (SFS), Sliding Mode frequency Shift (SMS), and Sandia Voltage Shift (SVS) triggered by a block composed by three passive methods: voltage frequency protection (VFP), rate of change of frequency (ROCOF), and DC-link. This novel hybrid system is studied under different detailed scenarios, where it shows its performance and characteristics.

A recommendation system is a system that offers suggestions to users, leveraging specific data such as books, movies, songs, and other relevant information. Movie recommendation algorithms utilize the attributes of previously enjoyed films to predict the preferences of users and suggest similar movies they might enjoy. Businesses that gather ample customer data and strive to deliver top-notch recommendations can greatly benefit from these recommendation systems. When creating a movie recommendation system, multiple elements such as genre, cast, and even the director of the movie are taken into account. This paper introduces a hybrid movie recommendation system that utilizes a combination of weighted average and min-max scaler to assess movie ratings and popularity. Moreover, TF-IDF is utilized for transforming the data into vectors, while cosine similarity is employed to gauge the resemblance among these vectors. The recommender system is built using the Movies dataset. The results show the top-K recommendation for users as well as the proposed system can provide a prediction of rating for a particular movie.

Electric distribution systems face many issues, such as power outages, high power losses, voltage sags, and low voltage stability, which are caused by the intermittent nature of renewable power generation and the large changes in load demand. To deal with these issues, a distribution system has been designed using both short- and long-term energy storage systems such as superconducting magnetic energy storage (SMES) and pumped-hydro energy storage (PHES). The aim of this paper is to propose a metaheuristic-based optimization method to find the optimal size of a hybrid solar PV-biogas generator with SMES-PHES in the distribution system and conduct a financial analysis. This method is based on an efficient algorithm called the “enhanced whale optimization” algorithm (EWOA), along with the proposed objective functions and constraints of the system. The EWOA is employed to reduce the hybrid system’s life cycle cost (LCC) and improve its reliability, both of which serve as performance indicators for the distribution system. The proposed method for sizing a grid-connected hybrid solar PV-biogas generator with SMES-PHES is compared with other metaheuristic optimization techniques, including the African vulture optimization algorithm (AVOA), grey wolf optimization algorithm (GWO), and water cycle algorithm (WCA). The numerical results of the EWOA show that the combination of a hybrid solar PV-biogas generator with SMES-PHES can successfully reduce the LCC and increase reliability, making the distribution system work better.

In this paper, a robust current control of the hybrid renewable energy system (HRES), based on the PV-Wind system, is proposed. The HRES is connected to a multiport converter to synchronize the multi-source system with one DC-Bus. Due to their ability to integrate many renewable energy sources (RES) individually or simultaneously, multiport converters (MPC) are an innovative method suitable for renewable energy applications. Recently, many DC-DC converter designs and topologies have emerged to ensure the highest possible efficiency of hybrid RESs. The multiport converter is a typical coupling system with several modes of operation. Thus, the design of its controller become complicated. To stabilize the DC-Bus voltage, a battery has been added to the system. In this HRES configuration, all sources are connected in parallel via the multiport DC converter. We used the multiport DC converter to minimize the intermittent character of solar and wind and control the energy flow between the different power sources and the load, as well as to increase the performance of the system. The nonlinear robust control structure is based on Lyapunov approach to overcome the nonlinear model of the system to improve robustness and guarantees the asymptotic stability. The proposed control law is implemented and tested on dSPACE-DS1104. The results show the effectiveness and the feasibility of the proposed controller.

This paper presents a feasibility analysis of the technical, environmental, and economic sustainability of an existing mini-grid technology system in Nigeria. The study investigates the cost and other operational parameters of the Gbamu-Gbamu solar–battery–diesel hybrid mini-grid, specifically the 85 kWp solar PV installation in the Ijebu East Local Government area of Ogun state. Situated within the Owo forest in South-West Nigeria, the mini-grid aims to reduce the effects of global warming and promote sustainable technological development in rural communities by increasing energy access through renewable sources. To assess the system’s viability, this research utilized RETScreen Expert software to validate the techno-economic and environmental sustainability of the installed mini-grid solar–PV–battery–diesel system in the region. Climatic data for the study were obtained from the National Aeronautics and Space Administration (NASA). The results demonstrate that the system is economically feasible and environmentally viable, as indicated by the positive net present value (NPV) and an average monthly irradiance of 4.78 kW/h/m2. Furthermore, the system achieved a 92.9% reduction in GHG emissions, provided a reasonable payback period of four years, and enabled a yearly electricity export of 203 MWh. These findings highlight the system’s potential to enhance energy access and mitigate climate change.

No one denies the importance of renewable energy sources in modern power systems in terms of sustainability and environmental conservation. However, due to their reliance on environmental change, they are unreliable systems. This paper uses a Unified Power Flow Controller (UPFC) to enhance the reliability and performance of grid-tied renewable energy systems. This system consists of two renewable sources, namely photovoltaic cells (PV) and wind turbines (WTs). The UPFC was selected for its unique advantage in both active and reactive power control. The UPFC is controlled with an optimized Fractional Order Proportional–Integral–Derivative (FOPID) controller. The parameters of this controller were tuned using an Atomic Search Optimization (ASO) algorithm. Simulation results confirm the efficiency of the suggested controller in supporting the reliability and performance of the hybrid power system during some disturbance events including voltage sag, swell, and unbalanced loading. In addition, power quality can be improved through reducing the total harmonic distortion. It is worth mentioning that two maximum point tracking techniques had been included for the PV and WT systems separately. MATLAB/SIMULINK 2021a software was used to model the system.

Real world systems of interest often feature interactions between discrete and continuous dynamics. Various hybrid system formalisms have been used to model and analyze this combination of dynamics, ranging from mathematical descriptions, e.g., using impulsive differential equations and switching, to automata-theoretic and language-based approaches. This paper bridges two such formalisms by showing how various classes of switched systems can be modeled using the language of hybrid programs from differential dynamic logic (dL). The resulting models enable the formal specification and verification of switched systems using dL and its existing deductive verification tools such as KeYmaera X. Switched systems also provide a natural avenue for the generalization of dL's deductive proof theory for differential equations. The completeness results for switched system invariants proved in this paper enable effective safety verification of those systems in dL., Long version of paper at ADHS 2021 (7th IFAC Conference on Analysis and Design of Hybrid Systems, July 7-9, 2021)

Wireless charging provides continuous energy for wireless sensor networks. However, it is difficult to replenish enough energy for all sensor nodes with fixed charging alone, and even more unrealistic to charge a large number of nodes within a short time via mobile charging. In order to overcome the above weaknesses, this paper firstly puts forward a Master-Slave Charging mode for the WRSN (Wireless Rechargeable Sensor Network), where fixed charging is the master mode and mobile charging is the slave mode, respectively. However, Master-Slave Charging is a typical hybrid system involving discrete event decision and continuous energy transfer. Therefore, the Hybrid Cyber Petri net system is proposed to build a visual specification with mathematical expression of Master-Slave Charging. Moreover, wireless charging in the WRSN is modeled and evaluated from the perspective of a hybrid system for the first time. Furthermore, a greedy-genetic algorithm is proposed to obtain the deployment of fixed chargers and the path planning of a mobile charger, by maximizing the actual electric quantity of the master charging problem and minimizing the mobile charger&rsquo, s travelling path of the slave charging problem. Finally, the simulation results confirm and verify the Hybrid Cyber Petri net model for Master-Slave Charging. It is worth noting that the proposed model in this paper is highly adaptable to various charging modes in the WRSN.

We revisit a unique building system including a base-isolation, building-connection hybrid control system. The base-isolation system withstands pulse-type earthquake ground motions effectively and the building-connection system resists long-duration earthquake ground motions efficiently. A simple smart critical response evaluation method without nonlinear time-history response analysis is proposed for this hybrid building system under near-fault ground motions. An analytical expression of the maximum elastic-plastic deformation of a damped bilinear hysteretic single-degree-of-freedom (SDOF) model under critical double impulse as a representative of pulse-type ground motions derived in our previous paper plays an important role in the development of the simple critical response evaluation method. A two-step transformation procedure into an SDOF model is proposed. The first step is the transformation of the main base-isolated building into an SDOF system and the second step is the reduction of the connecting dampers supported on a sub building to a damper with a sophisticated compensation factor on an assumed rigid wall. The evaluation of damping coefficients with the consideration of yielding of the base-isolation story is a key step in this paper. Different from the previous work, the equivalent damping coefficient is derived depending on the response range before and after yielding of the base-isolation story. This treatment enhances the accuracy of the proposed method. The accuracy and reliability of the proposed response evaluation method is demonstrated by the time-history response analysis of the multi-degree-of-freedom (MDOF) model.

In this paper, we deal with an optimal harvesting problem for a periodic predator-prey hybrid system dependent on size-structure in a polluted environment. In other words, a size-dependent model in an environment with a small toxicant content has been established. The well-posedness of state system is proved by using the fixed point theorem. The necessary optimality conditions are derived by tangent-normal cone technique in nonlinear functional analysis. The existence of a unique optimal harvesting policy is verified via the Ekeland’s variational principle. The optimal harvesting problem has an optimal harvesting policy, which has a Bang-Bang structure and provides a threshold for the optimal harvesting problem. Using the optimization theories and methods in mathematics to control phenomena of life. The objective function represents the total economic profit from the harvested population. Some theoretical results obtained in this paper provide a scientific theoretical basis for the practical application of the model.

Fuzziness, as a way to express imprecision, or uncertainty, in computation is an important feature in a number of current application scenarios: from hybrid systems interfacing with sensor networks with error boundaries, to knowledge bases collecting data from often non-coincident human experts. Their abstraction in e.g. fuzzy transition systems led to a number of mathematical structures to model this sort of systems and reason about them. This paper adds two more elements to this family: two modal logics, framed as institutions, to reason about fuzzy transition systems and the corresponding processes. This paves the way to the development, in the second part of the paper, of an associated theory of structured specification for fuzzy computational systems., This work is financed by the ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation -COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT -Fundacao para a Ciencia e a Tecnologia within project POCI-01-0145-FEDER-029946 -PTDC/CCI-COM/29946/2017.

This paper proposes a digital model predictive controller (DMPC) for a multi-input multi-output (MIMO) DC-DC converter interfaced with renewable energy resources in a hybrid system. Such MIMO systems generally suffer from cross-regulation, which seriously impacts the stability and speed of response of the system. To solve the contemporary issues in a MIMO system, a controller is required to attenuate the cross-regulation. Therefore, this paper proposes a controller, which increases speed of response and maintains stable output by regulating the load voltage independently. The inductor current and the capacitor voltage of the proposed converter are considered as the controlling parameters. With the aid of Forward Euler’s procedure, the future values are computed for the instantaneous values of controlling parameters. Cost function defines the control action by the predicted values that describe the system performance and establish optimal condition at which the output of the system is required. This allows proper switching of the system, thereby helping to regulate the output voltages. Thus, for any variation in load, the DMPC ensures steady switching operation and minimization of cross-regulation. To prove the efficacy of proposed DMPC controller, simulations followed by the experimental results are executed on a hybrid system consisting of dual-input dual-output (DIDO) positive Super-Lift Luo converter (PSLLC) interfaced with photovoltaic renewable energy resource. The results thus obtained are compared with the conventional PID (proportional integrative derivative) controller for validation and prove that the DMPC controller is able to control the cross-regulation effectively.

Complex control structures are required for the operation of photovoltaic electrical energy systems. In this paper, a general review of the controllers used for photovoltaic systems is presented. This review is based on the most recent papers presented in the literature. The control architectures considered are complex hybrid systems that combine classical and modern techniques, such as artificial intelligence and statistical models. The main contribution of this paper is the synthesis of a generalized control structure and the identification of the latest trends. The main findings are summarized in the development of increasingly robust controllers for operation with improved efficiency, power quality, stability, safety, and economics.

International audience; Synchronization pertains to the property of interconnected systems according to which their dynamic behavior is coordinated in an appropriate sense. That is to say, some of their state variables, or functions of the latter for that matter, converge to each other. Synchronization may occur naturally or may be induced, controlled, and it may be present between two systems or among a large number. In the latter case, it is convenient to speak of a network of interconnected systems. Understanding synchronization, and how to control it, is an important paradigm as it is present in a variety of scenarios. These involve, e.g., networks of technological systems (robots and vehicles of different kinds), social networks (by which people exchange opinions and agree, or not), networks of biological systems (uni or pluricellular), etc. Owing to the context, the mathematical models to describe such networks and to define synchronization formally, varies dramatically. Ordinary continuous-time or discrete-time models for which modern control theory and Lyapunov stability theory are tailored result inappropriate to incorporate hybrid phenomena that intervene in the network. These may stem from sudden topology changes, the use of digital or intermittent control strategies, the presence of impacts in the intrinsic dynamics of the nodes, etc. In this invited paper, we give an overview of synchronization control problems, mostly of cooperative control of networks of autonomous vehicles (based on continuous-time models). For that matter, the first part of the paper focuses on the main contributions of [1]. Then, we give further perspectives on what we consider significant open problems on synchronization of hybrid systems and hybrid networks.

Solar energy has attracted the attention of researchers around the world due to its advantages. However, photovoltaic (PV) panels still have not attained the desired efficiency and economic mature. PV tracking techniques can play a vital role in improving the performance of the PV system. The aim of this paper is to evaluate and compare the technical and economic performance of grid-connected hybrid energy systems including PV and fuel cells (FC) by applying major types of PV tracking technique. The topology and design principles and technical description of hybrid system components are proposed in this paper. Moreover, this paper also introduces economic criteria, which are used to evaluate the economy of different PV tracking techniques and seek the optimal configuration of system components. In the case study, the results show that the vertical single axis tracker was ranked 1st in terms of highest PV generation, penetration of renewable energy to the grid, lowest CO2 emission, highest energy sold to the grid and lowest purchased, and lowest net present cost (NPC) and levelized cost of energy (LCOE). The study found that the optimal design of a grid-connected hybrid energy system (PV-FC) was by using a vertical single axis tracker which has the lowest NPC, LCOE.

Applications of renewable electricity in cities are mostly limited to photovoltaics, and they need other renewable sources, batteries, and the grid to guarantee reliability. This paper proposes a hybrid system, combining biomass and photovoltaics, to supply electricity to educational buildings. This system is reliable and provides at least 50% of electricity based on renewable sources. Buildings with small (&lt, 500 kW) installed power based on renewables, mainly biomass, are usually expensive. Besides, in urban areas, photovoltaic capacity is limited due to roof availability. This paper analyzes different configurations, meeting these constraints to obtain an economically feasible solution based on photovoltaic-biomass modelling of small size hybrid systems. The technology used for biomass energy valorization is a fluidized bed gasification power plant, which has been modelled with real data obtained from experimental tests and previous research projects. Thereby, real costs and electric efficiency are included in the model. The techno-economic feasibility analysis using HOMER software with metered real load curves from an educational building has been modelled. The results of the model show that hybrid renewable systems are very feasible in the scenario of 50% of electricity contribution, however, higher contribution (&gt, 70%) implies high electricity costs.

The present paper deals with the Life-Cycle Cost (LCC) of an offshore renewable energy farm that is currently a topic of interest for operators and investors. The LCC analysis refers to the Cost Breakdown Structure (CBS) considering all the phases of life span, and it has been carried out for floating offshore wind farms (FOWFs) and hybrid wind-wave farms (HWWFs). For HWWFs, this paper proposes a hybrid wind-wave energy system (HWWES), which provides the coupling of wave energy converter (WEC) with Tension Leg Platform (TLP) or Spar Buoy platform (SB). The LCC analysis has been carried out considering: (i) FOWF consisting of TLP floating platforms; (ii) FOWF consisting of a SB floating platforms; (iii) HWWF realized with the conceived hybrid system coupling the WEC with the TLP platform; (iv) HWWF realized with the conceived hybrid system coupling the WEC with SB platform. In addition to the LCC evaluation, the Levelized Cost of Energy (LCOE) analysis has also been carried out. The site chosen for the study is off the port of Brindisi, southern Italy. This work’s interest lies in having performed a LCC analysis for FOWF and HWWF in the Mediterranean that is an area of growing interest for offshore renewable energy, and obtained results have allowed making assessments on costs for offshore energy farms.

Recently, renewable energy resources (RESs) have been utilized to supply electricity to remote areas, instead of the conventional methods of electrical energy production. In this paper, the optimal design of a standalone hybrid RES comprising photovoltaic (PV), wind turbine (WT), and biomass sources as well as an energy storage system, such as a hydro-pumped storage system, is studied. The problem of the optimal sizing of the generating units in the proposed energy system is formulated as an optimization problem and the algorithms heap-based optimizer (HBO), grey wolf optimizer (GWO), and particle swarm optimization (PSO) are applied to achieve the optimal sizing of each component of the proposed grid-independent hybrid system. The optimization problem is formulated depending on the real-time meteorological data of the Ataka region on the Red Sea in Egypt. The main goal of the optimization process is to minimize the cost of energy (COE) and the loss of power supply probability (LPSP), while satisfying the constraints of system operation. The results clarify that the HBO algorithm succeeded in obtaining the best design for the selected RE system with the minimum COE of 0.2750 USD/kWh and a net present cost (NPC) of USD 8,055,051. So, the HBO algorithm has the most promising performance over the GWO algorithm in addressing this optimization problem.

Internet of things (IoT) becomes the most popular term in the recent advances in Healthcare devices. The healthcare data in the IoT process and structure is very sensitive and critical in terms of healthy and technical considerations. Outlier detection approaches are considered as principal tool or stage of any IoT system and are mainly categorized in statistical and probabilistic, clustering and classification-based outlier detection. Recently, fuzzy logic (FL) system is used in ensemble and cascade systems with other ML-based tools to enhance outlier detection performance but its limitation involves the false detection of outliers. In this paper, we propose a fuzzy logic system that uses the anomaly score of each point using local outlier factor (LOF), connectivity-based outlier factor (COF) and generalized LOF to eliminate the confusion in classifying points as outliers or inliers. Regarding human activity recognition (HAR) dataset, the FL achieved a value of 98.2 %. Compared to the performance of LOF, COF, and GLOF individually, the accuracy increased slightly, but the increase in precision and recall indicates an increase in correctly classified data and that neither true nor abnormal data is classified wrongly. The results show the increase in precision and recall which indicates an increase in correctly classified data. Thus, it can be confirmed that fuzzy logic with input of scores achieved the desired goal in terms of mitigating cases of false detection of anomalous data. By comparing the proposed ensemble of fuzzy logic and different types of local density scores in this study, the outcomes of fuzzy logic presents a new way of elaborating or fusing the different tools of the same purpose to enhance detection performance, Інтернет речей (IР) стає найпопулярнішим терміном в останніх досягненнях у сфері пристроїв охорони здоров’я. Дані охорони здоров’я в процесі та структурі IР є дуже чутливими та критичними з точки зору здоров’я та технічних міркувань. Підходи до виявлення викидів вважаються основним інструментом або етапом будь-якої системи IР і в основному поділяються на статистичне та ймовірнісне виявлення викидів на основі кластеризації та класифікації. Останнім часом система нечіткої логіки (НЛ) використовується в ансамблевих і каскадних системах з іншими інструментами на основі машинного навчання для підвищення продуктивності виявлення викидів, але її обмеження включає хибне виявлення викидів. У цій статті ми пропонуємо систему нечіткої логіки, яка використовує оцінку аномалії кожної точки з використанням локального викиду (ЛВ), викиду на основі зв’язності (ВОЗ) і узагальненого УЛВ, щоб усунути плутанину в класифікації точок як викидів або внутрішніх. Щодо набору даних розпізнавання діяльності людини (РДЛ), НЛ досягла значення 98,2 %. Порівняно з характеристиками ЛВ, ВОЗ і ГУЛВ окремо, точність дещо зросла, але збільшення точності та запам’ятовування вказує на збільшення правильно класифікованих даних і те, що ані правдиві, ані аномальні дані класифіковані неправильно. Результати демонструють підвищення точності та запам’ятовування, що вказує на збільшення правильно класифікованих даних. Таким чином, можна підтвердити, що нечітка логіка з введенням балів досягла бажаної мети з точки зору пом’якшення випадків помилкового виявлення аномальних даних. Порівнюючи запропонований ансамбль нечіткої логіки та різні типи оцінок локальної щільності в цьому дослідженні, результати нечіткої логіки представляють новий спосіб розробки або злиття різних інструментів однієї мети для підвищення ефективності виявлення

This paper, dedicated to controlled generalized batches Petri nets without discrete nodes, presents a method for computing a control trajectory for reaching a steady state from a given initial marking. A steady state is characterized by a state in which the marking and the firing flow vector are constant. By controlling the firing flow vector of transitions, the proposed control strategy is an event-based one and relies on an algorithm solving a linear programming problem. This new control strategy, called in this paper as maximal flow based ON/OFF control, exploits the maximal firing flows and reduces the delay of the transient behavior for reaching the steady state. A practical communication system is provided to illustrate the relevance of such a control strategy for Cyber-Physical Systems.