Search results for: double layered fuzzy graph

Authors: Sima Shakoorjavan, Mahdieh Eskafi, Dawid Stawski, Somaye Akbari

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In this study, poly (amidoamine) dendritic material (PAMAM) and poly (acrylic acid) (PAA) as polycation and polyanion were deposited on surface charged polylactide (PLA) nonwoven to study the relationship of dye absorption capacity of layered-PLA with the number of deposited layers. To produce negatively charged-PLA, acrylic acid (AA) was grafted on the PLA surface (PLA-g-AA) through a chemical redox reaction with the strong oxidizing agent. Spectroscopy analysis, water contact measurement, and FTIR-ATR analysis confirm the successful grafting of AA on the PLA surface through the chemical redox reaction method. In detail, an increase in dye absorption percentage by 19% and immediate absorption of water droplets ensured hydrophilicity of PLA-g-AA surface; and the presence of new carbonyl bond at 1530 cm-¹ and a wide peak of hydroxyl between 3680-3130 cm-¹ confirm AA grafting. In addition, PLA as linear polyester can undergo aminolysis, which is the cleavage of ester bonds and replacement with amid bonds when exposed to an aminolysis agent. Therefore, to produce positively charged PLA, PAMAM as amine-terminated dendritic material was introduced to PLA molecular chains at different conditions; (1) at 60 C for 0.5, 1, 1.5, 2 hours of aminolysis and (2) at room temperature (RT) for 1, 2, 3, and 4 hours of aminolysis. Weight changes and spectrophotometer measurements showed a maximum in weight gain graph and K/S value curve indicating the highest PAMAM attachment at 60 C for 1 hour and RT for 2 hours which is considered as an optimum condition. Also, the emerging new peak around 1650 cm-1 corresponding to N-H bending vibration and double wide peak at around 3670-3170 cm-1 corresponding to N-H stretching vibration confirm PAMAM attachment in selected optimum condition. In the following, regarding the initial surface charge of grafted-PLA, lbl deposition was performed and started with PAA or PAMAM. FTIR-ATR results confirm chemical changes in samples due to deposition of the first layer (PAA or PAMAM). Generally, spectroscopy analysis indicated that an increase in layer number costed dye absorption capacity. It can be due to the partial deposition of a new layer on the previously deposited layer; therefore, the available PAMAM at the first layer is more than the third layer. In detail, in the case of layer-PLA starting lbl with negatively charged, having PAMAM as the first top layer (PLA-g-AA/PAMAM) showed the highest dye absorption of both cationic and anionic model dye.

Keywords: surface modification, layer-by-layer technique, dendritic materials, PAMAM, dye absorption capacity, PLA nonwoven

Procedia PDF Downloads 81

Authors: I. Filikhin, B. Vlahovic

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We focus on a novel type of detection based on electron tunneling properties of double nanoscale structures in semiconductor materials. Semiconductor heterostructures as quantum wells (QWs), quantum dots (QDs), and quantum rings (QRs) may have energy level structure of several hundred of electron confinement states. The single electron spectra of the double quantum objects (DQW, DQD, and DQR) were studied in our previous works with relation to the electron localization and tunneling between the objects. The wave function of electron may be localized in one of the QDs or be delocalized when it is spread over the whole system. The localizing-delocalizing tunneling occurs when an electron transition between both states is possible. The tunneling properties of spectra differ strongly for “regular” and “chaotic” systems. We have shown that a small violation of the geometry drastically affects localization of electron. In particular, such violations lead to the elimination of the delocalized states of the system. The same symmetry violation effect happens if electrical or magnetic fields are applied. These phenomena could be used to propose a new type of detection based on the high sensitivity of charge transport between double nanostructures and small violations of the shapes. It may have significant technological implications.

Keywords: double quantum dots, single electron levels, tunneling, electron localizations

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Authors: Hend Alrasheed

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Due to their different properties that have led to avoid several limitations of classic client/server systems, there has been a great interest in the development and the improvement of different peer to peer systems. Understanding the properties of complex peer to peer networks is essential for their future improvements. It was shown that the performances of peer to peer protocols are directly related to their underlying topologies. Therefore, multiple efforts have analyzed the topologies of different peer to peer systems. This study presents an overview of major findings of close experimental analyses to different topologies of three unstructured peer to peer systems: BitTorrent, Gnutella, and FreeNet.

Keywords: peer to peer networks, network topology, graph diameter, clustering coefficient, small-world property, random graph, degree distribution

Procedia PDF Downloads 380

Authors: A. Sivakumar, S. S. Darun Prakash, P. Navaneethakrishnan

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In and around Erode District, it is estimated that more than 1250 chemical and allied textile processing fabric industries are affected, partially closed and shut off for various reasons such as poor management, poor supplier performance, lack of planning for productivity, fluctuation of output, poor investment, waste analysis, labor problems, capital/labor ratio, accumulation of stocks, poor maintenance of resources, deficiencies in the quality of fabric, low capacity utilization, age of plant and equipment, high investment and input but low throughput, poor research and development, lack of energy, workers’ fear of loss of jobs, work force mix and work ethic. The main objective of this work is to analyze the existing conditions in textile fabric sector, validate the break even of Total Productivity (TP), analyze, design and implement fuzzy sets and mathematical programming for improvement of productivity and quality dimensions in the fabric processing industry. It needs to be compatible with the reality of textile and fabric processing industries. The highly risk events from productivity and quality dimension were found by fuzzy systems and results are wrapped up among the textile fabric processing industry.

Keywords: break even point, fuzzy crisp data, fuzzy sets, productivity, productivity cycle, total productive maintenance

Procedia PDF Downloads 337

Authors: M. Caramihai, Irina Severin

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This paper deals with the design of an intelligent control structure for a bioprocess of Hansenula polymorpha yeast cultivation. The objective of the process control is to produce biomass in a desired physiological state. The work demonstrates that the designed Hybrid Control Techniques (HCT) are able to recognize specific evolution bioprocess trajectories using neural networks trained specifically for this purpose, in order to estimate the model parameters and to adjust the overall bioprocess evolution through an expert system and a fuzzy structure. The design of the control algorithm as well as its tuning through realistic simulations is presented. Taking into consideration the synergism of different paradigms like fuzzy logic, neural network, and symbolic artificial intelligence (AI), in this paper we present a real and fulfilled intelligent control architecture with application in bioprocess control.

Keywords: bioprocess, intelligent control, neural nets, fuzzy structure, hybrid techniques

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Authors: Mohammad Ali Alavidoost, Hossein Bozorgian

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Criterion-referenced tests (CRTs) are designed to measure student performance against a fixed set of predetermined criteria or learning standards. The reliability of such tests cannot be based on internal reliability. Threshold loss agreement is one way to calculate the reliability of CRTs. However, the selection of master and non-master in such agreement is determined by the threshold point. The problem is if the threshold point witnesses a minute change, the selection of master and non-master may have a drastic change, leading to the change in reliability results. Therefore, in this study, the Fuzzy logic approach is employed as a remedial procedure for data analysis to obviate the threshold point problem. Forty-one Iranian students were selected; the participants were all between 20 and 30 years old. A quantitative approach was used to address the research questions. In doing so, a quasi-experimental design was utilized since the selection of the participants was not randomized. Based on the Fuzzy logic approach, the threshold point would be more stable during the analysis, resulting in rather constant reliability results and more precise assessment.

Keywords: criterion-referenced tests, threshold loss agreement, threshold point, fuzzy logic approach

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Authors: Pranvera Shehaj

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Unlike any prior analysis on the withholding tax rates negotiated in tax treaties, this study looks at the treaty heterogeneity content, by investigating the impact of the residence country’s double tax relief method and of tax-sparing agreements, on the difference between developing countries’ domestic withholding taxes on dividends on one side, and treaty negotiated withholding taxes at source on portfolio dividends on the other side. Using a dyadic panel dataset of asymmetric double tax treaties between 2005 and 2019, this study suggests first that the difference between domestic and negotiated WHTs on portfolio dividends is higher when the OECD member uses the credit method, as compared to when it uses the exemption method. Second, results suggest that the inclusion of tax-sparing provisions vanishes the positive effect of the credit method at home on the difference between domestic and negotiated WHTs on portfolio dividends, incentivizing developing countries to negotiate higher withholding taxes.

Keywords: double tax treaties, asymmetric investments, withholding tax, dividends, double tax relief method, tax sparing

Procedia PDF Downloads 61

Authors: Mahmoud I. Syam

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Stratified double median ranked set sampling (SDMRSS) method is suggested for estimating the population mean. The SDMRSS is compared with the simple random sampling (SRS), stratified simple random sampling (SSRS), and stratified ranked set sampling (SRSS). It is shown that SDMRSS estimator is an unbiased of the population mean and more efficient than SRS, SSRS, and SRSS. Also, by SDMRSS, we can increase the efficiency of mean estimator for specific value of the sample size. SDMRSS is applied on real life examples, and the results of the example agreed the theoretical results.

Keywords: efficiency, double ranked set sampling, median ranked set sampling, ranked set sampling, stratified

Procedia PDF Downloads 246

Authors: R. S. Sheu, H. Usman, M. S. Lawal

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Takagi-Sugeno (T-S) fuzzy model based control of a load frequency deviation in a single machine with limit nonlinearity on power coefficient is presented in the paper. Two T-S fuzzy rules with only rotor angle variable as input in the premise part, and linear state space models in the consequent part involving characteristic matrices determined from limits set on the power coefficient constant are formulated, state feedback control gains for closed loop control was determined from the formulated Linear Matrix Inequality (LMI) with eigenvalue optimization scheme for asymptotic and exponential stability (speed of esponse). Numerical evaluation of the closed loop object was carried out in Matlab. Simulation results generated of both the open and closed loop system showed the effectiveness of the control scheme in maintaining load frequency stability.

Keywords: T-S fuzzy model, state feedback control, linear matrix inequality (LMI), frequency deviation control

Procedia PDF Downloads 396

Authors: Aouiche Abdelaziz, Soudani Mouhamed Salah, Aouiche El Moundhe

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The present paper addresses the utilization of Artificial Neural Networks (ANNs) and Fuzzy Inference Systems (FISs) for the identification and control of dynamical systems with some degree of uncertainty. Because ANNs and FISs have an inherent ability to approximate functions and to adapt to changes in input and parameters, they can be used to control systems too complex for linear controllers. In this work, we show how ANNs and FISs can be put in order to form nets that can learn from external data. In sequence, it is presented structures of inputs that can be used along with ANNs and FISs to model non-linear systems. Four systems were used to test the identification and control of the structures proposed. The results show the ANNs and FISs (Back Propagation Algorithm) used were efficient in modeling and controlling the non-linear plants.

Keywords: non-linear systems, fuzzy set Models, neural network, control law

Procedia PDF Downloads 211

Authors: Gabriele Borg, Alexei Debono, Charlie Abela

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There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.

Keywords: graph neural networks, traffic management, big data, mobile data patterns

Procedia PDF Downloads 127

Authors: Kaddari Faiza, Mazari Benyounes, Mihoub Youcef, Safa Ahmed

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Active filtering of electric power has now become a mature technology for reactive power and harmonic compensation caused by the proliferation of power electronics devices used for industrial, commercial and residential purposes. The aim of this study is to enhance the power quality by improving the performances of shunt active power filter in harmonic mitigation to obtain sinusoidal source currents with very weak ripples. A power circuit configuration and control scheme for shunt active power filter are described with an improved method for harmonics compensation using self-tuning-filter for harmonics identification and fuzzy logic control to generate reference current. Simulation results (using MATLAB/SIMULINK) illustrates the compensation characteristics of the proposed control strategy. Analysis of these results proves the feasibility and effectiveness of this method to improve the power quality and also show the performances of fuzzy logic control which provides flexibility, high precision and fast response. The total harmonic distortion (THD %) for the simulations found to be within the recommended imposed IEEE 519-1992 harmonic standard.

Keywords: Active Powers Filter (APF), Self-Tuning-Filter (STF), fuzzy logic control, hysteresis-band control

Procedia PDF Downloads 735

Authors: Vlado Ostovic

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An electric machine topology characterized by single tooth winding in both stator and rotor is presented. The proposed machine is capable of operating as a direct drive double fed wind generator (DDDF, D3F) because it requires no gearbox and only a reduced-size converter. A wind turbine drive built around a D3F generator is cheaper to manufacture, requires less maintenance, and has a higher energy yield than its conventional counterparts. The single tooth wound generator of a D3F turbine has superb volume utilization and lower stator I2R losses due to its extremely short-end windings. Both stator and rotor of a D3F generator can be manufactured in segments, which simplifies its assembly and transportation to the site, and makes production cheaper.

Keywords: direct drive, double fed generator, gearbox, permanent magnet generators, single tooth winding, wind power

Procedia PDF Downloads 189

Authors: Amadou Fall Dia, Maurras Ulbricht Togbe, Aliou Boly, Zakia Kazi Aoul, Elisabeth Metais

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Existing RDF (Resource Description Framework) Stream Processing (RSP) systems allow continuous processing of RDF data issued from different application domains such as weather station measuring phenomena, geolocation, IoT applications, drinking water distribution management, and so on. However, processing window phase often expires before finishing the entire session and RSP systems immediately delete data streams after each processed window. Such mechanism does not allow optimized exploitation of the RDF data streams as the most relevant and pertinent information of the data is often not used in a due time and almost impossible to be exploited for further analyzes. It should be better to keep the most informative part of data within streams while minimizing the memory storage space. In this work, we propose an RDF graph summarization system based on an explicit and implicit expressed needs through three main approaches: (1) an approach for user queries (SPARQL) in order to extract their needs and group them into a more global query, (2) an extension of the closeness centrality measure issued from Social Network Analysis (SNA) to determine the most informative parts of the graph and (3) an RDF graph summarization technique combining extracted user query needs and the extended centrality measure. Experiments and evaluations show efficient results in terms of memory space storage and the most expected approximate query results on summarized graphs compared to the source ones.

Keywords: centrality measures, RDF graphs summary, RDF graphs stream, SPARQL query

Procedia PDF Downloads 201

Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Xiguan Jiangfan Yang

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This study investigates the tea consumption based on the Double-Hurdle model. The results of a CHNS survey of 12,745 samples in China offer two preliminary insights: First, we can’t apply the conclusions we get by using all samples to the men or women subgroups. Second, men and women are impacted by different demographic not only on the intention to drink tea, but also on the quantities of tea consumed. These two findings suggest that appropriate and corresponding marketing strategies should be developed to targeting on the different groups of tea consumers.

Keywords: Chinese, CHNS, Double-Hurdle model, tea consumption

Procedia PDF Downloads 410

Authors: Yang Li, Xiaorong Guan, Cheng Xu

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In order to design a suitable control scheme for human extremity exoskeleton, the interaction force control scheme with traditional PI controller was presented, and the simulation study of the electromechanical system of the human extremity exoskeleton was carried out by using a MATLAB/Simulink module. By analyzing the simulation calculation results, it was shown that the traditional PI controller is not very suitable for every movement speed of human body. So, at last the fuzzy self-adaptive PI controller was presented to solve this problem. Eventually, the superiority and feasibility of the fuzzy self-adaptive PI controller was proved by the simulation results and experimental results.

Keywords: human extremity exoskeleton, interaction force control scheme, simulation study, fuzzy self-adaptive pi controller, man-machine coordinated walking, bear payload

Procedia PDF Downloads 361

Authors: Istvan Szilagyi, Marko Pavlovic, Paul Rouster

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Antioxidant enzymes are the most efficient defense systems against reactive oxygen species, which cause severe damage in living organisms and industrial products. However, their supplementation is problematic due to their high sensitivity to the environmental conditions. Immobilization on carrier nanoparticles is a promising research direction towards the improvement of their functional and colloidal stability. In that way, their applications in biomedical treatments and manufacturing processes in the food, textile and cosmetic industry can be extended. The main goal of the present research was to prepare and formulate antioxidant bionanocomposites composed of superoxide dismutase (SOD) enzyme, anionic clay (layered double hydroxide, LDH) nanoparticle and heparin (HEP) polyelectrolyte. To characterize the structure and the colloidal stability of the obtained compounds in suspension and solid state, electrophoresis, dynamic light scattering, transmission electron microscopy, spectrophotometry, thermogravimetry, X-ray diffraction, infrared and fluorescence spectroscopy were used as experimental techniques. LDH-SOD composite was synthesized by enzyme immobilization on the clay particles via electrostatic and hydrophobic interactions, which resulted in a strong adsorption of the SOD on the LDH surface, i.e., no enzyme leakage was observed once the material was suspended in aqueous solutions. However, the LDH-SOD showed only limited resistance against salt-induced aggregation and large irregularly shaped clusters formed during short term interval even at lower ionic strengths. Since sufficiently high colloidal stability is a key requirement in most of the applications mentioned above, the nanocomposite was coated with HEP polyelectrolyte to develop highly stable suspensions of primary LDH-SOD-HEP particles. HEP is a natural anticoagulant with one of the highest negative line charge density among the known macromolecules. The experimental results indicated that it strongly adsorbed on the oppositely charged LDH-SOD surface leading to charge inversion and to the formation of negatively charged LDH-SOD-HEP. The obtained hybrid materials formed stable suspension even under extreme conditions, where classical colloid chemistry theories predict rapid aggregation of the particles and unstable suspensions. Such a stabilization effect originated from electrostatic repulsion between the particles of the same sign of charge as well as from steric repulsion due to the osmotic pressure raised during the overlap of the polyelectrolyte chains adsorbed on the surface. In addition, the SOD enzyme kept its structural and functional integrity during the immobilization and coating processes and hence, the LDH-SOD-HEP bionanocomposite possessed excellent activity in decomposition of superoxide radical anions, as revealed in biochemical test reactions. In conclusion, due to the improved colloidal stability and the good efficiency in scavenging superoxide radical ions, the developed enzymatic system is a promising antioxidant candidate for biomedical or other manufacturing processes, wherever the aim is to decompose reactive oxygen species in suspensions.

Keywords: clay, enzyme, polyelectrolyte, formulation

Procedia PDF Downloads 266

Authors: Dmytro O. Plutenko, Alexei D. Kiselev, Mikhail V. Vasnetsov

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We present the results of our analytical and computational study of Laguerre-Gaussian (LG) beams scattering by spherical homogeneous isotropic particles located on the axis of the beam. We consider different types of scatterers (dielectric, metallic and double negative metamaterials) and different polarizations of the LG beams. A possibility to generate photonic nanojets using metallic and double negative metamaterial Mie scatterers is shown. We have studied the properties of such nonclassical nanojets and discovered new types of the nanojets characterized by zero on-axes magnetic (or electric) field with the electric (or magnetic) field polarized along the z-axis.

Keywords: double negative metamaterial, Laguerre-Gaussian beam, Mie scattering, optical vortices, photonic nanojets

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Authors: Bezhan Ghvaberidze

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A fuzzy multi-objective facility location-selection problem (FLSP) under uncertain and extreme environments based on possibility theory is developed. The model’s uncertain parameters in the q-rung orthopair fuzzy values are presented and transformed in the Dempster-Shaper’s belief structure environment. An objective function – distribution centers’ selection ranking index as an extension of Dempster’s extremal expectations under discrimination q-rung orthopair fuzzy information is constructed. Experts evaluate each humanitarian aid from distribution centers (HADC) against each of the uncertain factors. HADCs location problem is reduced to the bicriteria problem of partitioning the set of customers by the set of centers: (1) – Minimization of transportation costs; (2) – Maximization of centers’ selection ranking indexes. Partitioning type constraints are also constructed. For an illustration of the obtained results, a numerical example is created from the facility location-selection problem.

Keywords: FLSP, multi-objective combinatorial optimization problem, evidence theory, HADC, q-rung orthopair fuzzy set, possibility theory

Procedia PDF Downloads 119

Authors: Changho Han, Jaemin Lee, Li Hua, Seokkwon Jeong

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Design of membership function ranges in fuzzy logic control (FLC) is presented for robust control of a variable speed refrigeration system (VSRS). The criterion values of the membership function ranges can be carried out from the static experimental data, and two different values are offered to compare control performance. Some simulations and real experiments for the VSRS were conducted to verify the validity of the designed membership functions. The experimental results showed good agreement with the simulation results, and the error change rate and its sampling time strongly affected the control performance at transient state of the VSRS.

Keywords: variable speed refrigeration system, fuzzy logic control, membership function range, control performance

Procedia PDF Downloads 263

Authors: Ahmed Abbou

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This paper present a sensorless controller designed by the backstepping approach for the speed control of induction motor. In this strategy of control, we also combined the method Fuzzy MRAS to estimate the rotor speed and the observer type Luenburger to observe Rotor flux. The control model involves a division by the flux variable that may lead to unbounded solutions. Such a risk is avoided by basing the controller design on Lyapunov function that accounts for the model singularity. On the other hand, this mixed method gives better results in Sensorless operation and especially at low speed. The response time at 5% of the flux is 20ms while the error between the speed with sensor and the estimated speed remains in the range of ±0.8 rad/s for the rated functioning and ±1.5 rad/s for low speed.

Keywords: backstepping approach, fuzzy logic, induction motor, luenburger observer, sensorless MRAS

Procedia PDF Downloads 372

Authors: Pengcheng Quan, Shan Zhong

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Double ramp geometry is widely used in supersonic and hypersonic environments as it presents unique flow patterns for shock wave-boundary layer interaction studies as well as for two-dimensional inlets and deflected control surfaces for re-entry vehicles. Hence, the surface pressure distribution is critical for optimum design. Though when the model is wide enough on spanwise direction the flow can be regarded as a two-dimensional flow, in actual applications a finite width would normally cause some three-dimensional spillage effects. No research has been found addressed this problem, hence the primary interest of this study is to set up a liable surface pressure distribution on a double ramp with three-dimensional effects. Both numerical and experimental (pressure sensitive paints) are applied to obtain the pressure distribution; the results agree well except that the numerical computation doesn’t capture the Gortler vortices. The pressure variations on the spanwise planes are used to analyse the development of the Gortler vortices and the effects of three-dimensional spillage on the vortices. Results indicate that the three-dimensionl spillage effects not only enhance the developing of the Gortler vortice, but also increase the periodic distance between vortice pairs.

Keywords: spillage effects, pressure sensitive paints, hypersonic, double ramp

Procedia PDF Downloads 329

Authors: Nousheen Hashmi, Shoab Ahmad Khan

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Active collaboration among the green energy sources and the load demand leads to serious issues related to power quality and stability. The growing number of green energy resources and Distributed-Generators need newer strategies to be incorporated for their operations to keep the power energy stability among green energy resources and micro-grid/Utility Grid. This paper presents a novel technique for energy power management in Grid-Connected Photovoltaic with energy storage system under set of constraints including weather conditions, Load Shedding Hours, Peak pricing Hours by using rule-based fuzzy smart grid controller to schedule power coming from multiple Power sources (photovoltaic, grid, battery) under the above set of constraints. The technique fuzzifies all the inputs and establishes fuzzify rule set from fuzzy outputs before defuzzification. Simulations are run for 24 hours period and rule base power scheduler is developed. The proposed fuzzy controller control strategy is able to sense the continuous fluctuations in Photovoltaic power generation, Load Demands, Grid (load Shedding patterns) and Battery State of Charge in order to make correct and quick decisions.The suggested Fuzzy Rule-based scheduler can operate well with vague inputs thus doesn’t not require any exact numerical model and can handle nonlinearity. This technique provides a framework for the extension to handle multiple special cases for optimized working of the system.

Keywords: photovoltaic, power, fuzzy logic, distributed generators, state of charge, load shedding, membership functions

Procedia PDF Downloads 478

Authors: Mario M. Figueroa de la Cruz, Claudia I. Solorzano, Raul Acosta, Ignacio Funes

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This technological development project seeks to create a tool that allows companies, in need of implementing a Data Center, intelligently determining factors for allocating resources support cooling and power supply (UPS) in its conception. The results should show clearly the speed, robustness and reliability of a system designed for deployment in environments where they must manage and protect large volumes of data.

Keywords: telecommunications, data center, fuzzy logic, expert systems

Procedia PDF Downloads 343

Authors: Leyla Noroozbabaee, David Nickerson

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We introduce a modular, consistent, reusable bond graph model of the renal nephron’s proximal convoluted tubule (PCT), which can reproduce biological behaviour. In this work, we focus on ion and volume transport in the proximal convoluted tubule of the renal nephron. Modelling complex systems requires complex modelling problems to be broken down into manageable pieces. This can be enabled by developing models of subsystems that are subsequently coupled hierarchically. Because they are based on a graph structure. In the current work, we define two modular subsystems: the resistive module representing the membrane and the capacitive module representing solution compartments. Each module is analyzed based on thermodynamic processes, and all the subsystems are reintegrated into circuit theory in network thermodynamics. The epithelial transport system we introduce in the current study consists of five transport membranes and four solution compartments. Coupled dissipations in the system occur in the membrane subsystems and coupled free-energy increasing, or decreasing processes appear in solution compartment subsystems. These structural subsystems also consist of elementary thermodynamic processes: dissipations, free-energy change, and power conversions. We provide free and open access to the Python implementation to ensure our model is accessible, enabling the reader to explore the model through setting their simulations and reproducibility tests.

Keywords: Bond Graph, Epithelial Transport, Water Transport, Mathematical Modeling

Procedia PDF Downloads 86

Authors: Noureddine Henka, Sami Tazi, Mohamad Assaad

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The electrical grid is a highly intricate system designed to transfer electricity from production areas to consumption areas. The Transmission System Operator (TSO) is responsible for ensuring the efficient distribution of electricity and maintaining the grid's safety and quality. However, due to the increasing integration of intermittent renewable energy sources, there is a growing level of uncertainty, which requires a faster responsive approach. A potential solution involves the use of electrical segmentation, which involves creating coherence zones where electrical disturbances mainly remain within the zone. Indeed, by means of coherent electrical zones, it becomes possible to focus solely on the sub-zone, reducing the range of possibilities and aiding in managing uncertainty. It allows faster execution of operational processes and easier learning for supervised machine learning algorithms. Electrical segmentation can be applied to various applications, such as electrical control, minimizing electrical loss, and ensuring voltage stability. Since the electrical grid can be modeled as a graph, where the vertices represent electrical buses and the edges represent electrical lines, identifying coherent electrical zones can be seen as a clustering task on graphs, generally called community detection. Nevertheless, a critical criterion for the zones is their ability to remain resilient to the electrical evolution of the grid over time. This evolution is due to the constant changes in electricity generation and consumption, which are reflected in graph structure variations as well as line flow changes. One approach to creating a resilient segmentation is to design robust zones under various circumstances. This issue can be represented through a multiplex graph, where each layer represents a specific situation that may arise on the grid. Consequently, resilient segmentation can be achieved by conducting community detection on this multiplex graph. The multiplex graph is composed of multiple graphs, and all the layers share the same set of vertices. Our proposal involves a model that utilizes a unified representation to compute a flattening of all layers. This unified situation can be penalized to obtain (K) connected components representing the robust electrical segmentation clusters. We compare our robust segmentation to the segmentation based on a single reference situation. The robust segmentation proves its relevance by producing clusters with high intra-electrical perturbation and low variance of electrical perturbation. We saw through the experiences when robust electrical segmentation has a benefit and in which context.

Keywords: community detection, electrical segmentation, multiplex graph, power grid

Procedia PDF Downloads 78

Authors: Ryan B. Escorial, Elmer A. Maravillas, Chris Jordan G. Aliac

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This study presents a small-scale water pumping system utilizing a fuzzy logic inference system attached to a renewable energy source. The fuzzy logic controller was designed and simulated in MATLAB fuzzy logic toolbox to examine the properties and characteristics of the input and output variables. The result of the simulation was implemented in a microcontroller, together with sensors, modules, and photovoltaic cells. The study used a grand rapid variety of lettuce, organic substrates, and foliar for observation of the capability of the device to irrigate crops. Two plant boxes intended for manual and automated irrigation were prepared with each box having 48 heads of lettuce. The observation of the system took 22-31 days, which is one harvest period of the crop. Results showed a 22.55% increase in agricultural productivity compared to manual irrigation. Aside from reducing human effort, and time, the smart irrigation system could help lessen some of the shortcomings of manual irrigations. It could facilitate the economical utilization of water, reducing consumption by 25%. The use of renewable energy could also help farmers reduce the cost of production by minimizing the use of diesel and gasoline.

Keywords: fuzzy logic, intelligent system, precision agriculture, renewable energy

Procedia PDF Downloads 127

Authors: Asma Hanif, A. I. K. Butt, Shabir Ahmad, Rahim Ud Din, Mustafa Inc

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This paper is devoted to a study of the fuzzy fractional mathematical model reviewing the transmission dynamics of the infectious disease Covid-19. The proposed dynamical model consists of susceptible, exposed, symptomatic, asymptomatic, quarantine, hospitalized and recovered compartments. In this study, we deal with the fuzzy fractional model defined in Caputo’s sense. We show the positivity of state variables that all the state variables that represent different compartments of the model are positive. Using Gronwall inequality, we show that the solution of the model is bounded. Using the notion of the next-generation matrix, we find the basic reproduction number of the model. We demonstrate the local and global stability of the equilibrium point by using the concept of Castillo-Chavez and Lyapunov theory with the Lasalle invariant principle, respectively. We present the results that reveal the existence and uniqueness of the solution of the considered model through the fixed point theorem of Schauder and Banach. Using the fuzzy hybrid Laplace method, we acquire the approximate solution of the proposed model. The results are graphically presented via MATLAB-17.

Keywords: Caputo fractional derivative, existence and uniqueness, gronwall inequality, Lyapunov theory

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Authors: Joseph Gear, Yue Xu, Ernest Foo, Praveen Gauravaran, Zahra Jadidi, Leonie Simpson

Abstract:

Deep learning methods have been seeing an increasing application to the long-standing security research goal of automatic vulnerability detection for source code. Attention, however, must still be paid to the task of producing vector representations for source code (code embeddings) as input for these deep learning models. Graphical representations of code, most predominantly Abstract Syntax Trees and Code Property Graphs, have received some use in this task of late; however, for very large graphs representing very large code snip- pets, learning becomes prohibitively computationally expensive. This expense may be reduced by intelligently pruning this input to only vulnerability-relevant information; however, little research in this area has been performed. Additionally, most existing work comprehends code based solely on the structure of the graph at the expense of the information contained by the node in the graph. This paper proposes Semantic-enhanced Code Embedding for Vulnerability Discovery (SCEVD), a deep learning model which uses semantic-based feature selection for its vulnerability classification model. It uses information from the nodes as well as the structure of the code graph in order to select features which are most indicative of the presence or absence of vulnerabilities. This model is implemented and experimentally tested using the SARD Juliet vulnerability test suite to determine its efficacy. It is able to improve on existing code graph feature selection methods, as demonstrated by its improved ability to discover vulnerabilities.

Keywords: code representation, deep learning, source code semantics, vulnerability discovery

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