Polymer filament and its printability, which is strongly influenced by the rheological behavior, can represent a significant hurdle in translating fused deposition modeling (FDM) from the lab to the industrial or clinical settings. The... more
Polymer filament and its printability, which is strongly influenced by the rheological behavior, can represent a significant hurdle in translating fused deposition modeling (FDM) from the lab to the industrial or clinical settings. The aim of this study is to demonstrate the potential of machine learning (ML) approaches to speed up the development of polymer filaments for FDM. Four types of ML methods; artificial neural network, support vector regression, polynomial chaos expansion (PCE), and response surface model were used to predict the rheological behaivior of polybutylene succinate. In general, all four approaches presented significantly high correlation values with respect to the training and testing data stages. Remarkably, the PCE algorithm repeatedly provided the highest correlation for each response variable in both the training and testing stages. Noteworthy, variation differs between response variables rather than between algorithms. Taken together, these modeling approa...
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In this study, structural and techno-functional characteristics of an exopolysaccharide (EPS) produced by Lactobacillus kunkeei AK1 were determined. High-performance liquid chromatography (HPLC) analysis demonstrated that EPS AK1 was... more
In this study, structural and techno-functional characteristics of an exopolysaccharide (EPS) produced by Lactobacillus kunkeei AK1 were determined. High-performance liquid chromatography (HPLC) analysis demonstrated that EPS AK1 was composed of only glucose units. 1H and 13C Nuclear magnetic resonance (NMR) analysis revealed that EPS AK1 was a dextran type EPS containing 4.78% (1 → 4)-linked α-d-glucose branches. The molecular weight of EPS AK1 was determined to be 45 kDa by Gel Permeation Chromatography (GPC) analysis. A high level of thermal stability up to 280 °C was determined for dextran AK1 detected by Differential scanning calorimetry (DSC) and Thermogravimetric analysis (TGA). Dextran AK1 appeared as regular spheres with compact morphology and as irregular particles in the solution with no clear cross-linking between the chains of the polysaccharide observed by Scanning electron microscopy (SEM) and Atomic force microscopy (AFM) analysis, respectively. X-ray diffraction analysis (XRD) analysis demonstrated that dextran AK1 had a crystalline structure. A relatively strong antioxidant activity was observed for dextran AK1 determined by 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis-3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radical scavenging and cupric reducing antioxidant capacity (CUPRAC) tests. Finally, only a digestion ratio of 3.1% was observed for dextran AK1 following the in vitro simulated gastric digestion test.
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The objective of this paper is to evaluate energy and exergy efficiencies of a biogas cogeneration plant. The total and net energy efficiencies for this biogas cogeneration plant were calculated as 91% and 85%, while the total and net... more
The objective of this paper is to evaluate energy and exergy efficiencies of a biogas cogeneration plant. The total and net energy efficiencies for this biogas cogeneration plant were calculated as 91% and 85%, while the total and net exergy efficiencies were 55.5% and 51.7%, respectively. Electric and heat efficiencies and equivalent electrical efficiency of the plant were 37%, 48%, and 80%, respectively. The primary energy savings and relative primary energy savings were found as 264 kW and 22%, respectively. The relative CO2 emissions savings were calculated as 0.62286 kgCO2/h for the plant.
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For the nonlinear dynamic analyses of complex mechanical components, it is necessary to apply efficient modeling framework to reduce computational burden. The accurate surrogate model for approximating the nonlinear responses of several... more
For the nonlinear dynamic analyses of complex mechanical components, it is necessary to apply efficient modeling framework to reduce computational burden. The accurate surrogate model for approximating the nonlinear responses of several failures is a vital issue to provide robust and safe design conditions in complex engineering applications. In this paper, two different Modified multi-extremum Response Surface basis Models (MRSM) are proposed for dynamic nonlinear responses of failure capacities for turbine blisk responses. The proposed MRSM is established using two regression processes including regressed the input variables by linear or exponential basis functions in first calibrating phase and regressed the second-order polynomial basis function using inputs data provided by first stage in second calibrating procedure. A sensitivity analysis using MRSM is proposed to consider the variation of input variables on the nonlinear responses. In the sensitivity analysis procedure, the effects of input variables are evaluated using the calibrating results given from the first regressed process. To evaluate the performance of the proposed MRSM, three multi-extremum failure modes including radial deformation of compressor blisk, maximum strain, and stress of compressor blade and disk are considered. the prediction of MRSM of nonlinear responses for Thermal-fluid–structure system with dynamical nonlinear finite-element analyses is compared with response surface method (RSM) and artificial neural network (ANN). The predicted results of modeling approaches showed that the sensitivity analysis based on MRSM accurately provided the effective degree for input variables. The gas temperature has the highest effects on nonlinear responses of turbine blisk which is followed by angular speed and material density. The MRSM combined with basic exponential function performs better than other models, while the MRSM coupled with linear function is more accurate than ANN and RSM. The proposed MRSM models have illustrated the accurate and efficient framework for approximating dynamic structural analysis of complex components.
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Recently, the education system faced an unpredicted health pandemic (COVID-19) that led to quick actions by governments to transform education from traditional face-to-face learning to modern virtual/distance learning. Due to the... more
Recently, the education system faced an unpredicted health pandemic (COVID-19) that led to quick actions by governments to transform education from traditional face-to-face learning to modern virtual/distance learning. Due to the transition to a new education environment, learners needed special social care to improve their concentration and motivation for online learning in such a crucial crisis. In the current study, virtual learning is investigated to determine its impact on student’s motivation from teachers' perception. The influence of teachers on students’ motivation is examined by measuring the effects of teachers` gender, age, experiences, and levels of education. The current study also reflects on the influence of obstacles that face virtual education and their impact on student’s motivation. The current study is conducted at the Department of Education in Jeddah Region for teachers in middle and secondary schools. To answer the research questions and discuss their res...
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This study seems to be the first effort to determine the viscoelastic properties of dilute ovalbumin colloids using dynamic-light-scattering-based optical microrheology using carboxylated melamine microparticles as the tracer probe. A... more
This study seems to be the first effort to determine the viscoelastic properties of dilute ovalbumin colloids using dynamic-light-scattering-based optical microrheology using carboxylated melamine microparticles as the tracer probe. A generalized form of the Stokes–Einstein equation constructed based on Laplace transformation of the mean square displacement, 〈Δr 2(t)〉, was employed to compute the viscoelastic moduli (storage modulus, G′, and loss modulus, G″). 〈Δr 2(t)〉 was determined to increase with time by reaching a maximum plateau at a time between 10−3 and 10−1 s with no further increase, revealing the elastic nature of dilute ovalbumin colloids within the given time. On the other hand, ovalbumin colloids exhibited different viscoelastic properties at two different frequency ranges. The measurements and interpretation of data revealed that the technique used seems to ensure a fast and effective method for measuring the viscoelastic properties of ovalbumin colloids at very low ...
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A slimy-mucinous-type colony of EPS-producing Weissella cibaria PDER21 was isolated and identified. The monomer composition was glucose, showing that the EPS is a glucan type homopolysaccharide, The core structure of (1 → 6)-linked... more
A slimy-mucinous-type colony of EPS-producing Weissella cibaria PDER21 was isolated and identified. The monomer composition was glucose, showing that the EPS is a glucan type homopolysaccharide, The core structure of (1 → 6)-linked α-d-glucose units including (1 → 3)-linked α-d-glucose branches at a ratio of 93.4/6.6 was revealed by 1H and 13C NMR spectra and confirmed by FTIR analysis. The glucan showed a superior thermal stability with almost no degradation in structure up to 300 °C. XRD analysis revealed the amorphous structure while SEM analysis confirmed the layer-like morphology. The glucan had an antioxidant activity (89.5%), water-holding capacity (103.7%) and water solubility index (80.7%) values, suggesting that the glucan had a strong level of antioxidant properties; good water binding capacity and excellent solubility. The glucan PDER21 is a polysaccharide possessing a good combination of technical and functional attributes, suggesting a great deal of potential for use in the food industry.
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Poor air quality, particularly during the dry months, causes adverse health effects from exposure to carbon monoxide, ozone and suspended particles. Particulate matter with aero-dynamic diameters of less than 10 μm (PM 10 ) was measured... more
Poor air quality, particularly during the dry months, causes adverse health effects from exposure to carbon monoxide, ozone and suspended particles. Particulate matter with aero-dynamic diameters of less than 10 μm (PM 10 ) was measured over 24-h intervals at four core stations in and around Jeddah City, Saudi Arabia. The sampling zones were located to Abhor, Industrial area, Bani Malek and Stadium regions of the city. The atmospheric elements in the total suspended particulates (TSP), the PM 10 fractions came from different emission sources, such as soil, traffic, industry and suspended particles. The gases and particulate matters data were collected from Saudi Presidency of meteorology and environment center for the periods between; January 2009 an April 2002. Hence, the complete set includes 769 data for this study. The aim of this study is to analyze the main mechanisms of dust in Jeddah as well as the PM 10 concentration, and mainly draw attention to the complexity of dust beha...
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Abstract Lactic Acid Bacteria (LAB) from different niches can be responsible for the production of distinct exopolysaccharides (EPS) that might possess important structural and technological features. In this respect, the aim of this... more
Abstract Lactic Acid Bacteria (LAB) from different niches can be responsible for the production of distinct exopolysaccharides (EPS) that might possess important structural and technological features. In this respect, the aim of this study was to isolate an EPS producer LAB strain from bee pollen environment. Leuconostoc mesenteroides BI-20 with a slimy-mucoid colony morphology was identified from bee pollen and the structural, technological and functional characteristics of EPS produced by this strain were determined. EPS BI-20 was a highly branched dextran containing 20% (1 → 3)-linked α-D-glucose branches determined by 1H and 13C NMR analysis. The presence of (1 → 6)/(1 → 3)-linked α-D-glucose linkages in dextran BI-20 was also confirmed by FTIR analysis. Dextran BI-20, with a molecular weight of 1 × 108 Da, possessed strong thermal properties, amorphous nature and highly branched and fibrous microstructural characteristics determined by DSC, TGA, XRD and SEM analysis, respectively. In terms of functional roles, dextran BI-20 demonstrated strong antioxidant capacity detected by ABTS and CUPRAC tests. Finally, no digestion was observed in dextran BI-20 under simulated gastric conditions. Results of this study unveiled techno-functional characteristics of dextran BI-20 produced by a bee pollen isolate LAB strain.
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Abstract The accurate design-oriented model for concrete confined with fiber-reinforced polymer (FRP) is important to provide safe design of this composite system. In this paper, the response surface model (RSM) is coupled with support... more
Abstract The accurate design-oriented model for concrete confined with fiber-reinforced polymer (FRP) is important to provide safe design of this composite system. In this paper, the response surface model (RSM) is coupled with support vector regression (SVR) for developing a novel hybrid model, namely RSM-SVR, with the aim of predicting the ultimate condition of FRP-confined concrete. Predictions obtained by the proposed model were compared with those by six empirical models and two data-driven models of RSM and SVR for database containing 780-test column results with circular cross section. Statistical analysis reveals that the proposed RSM-SVR model predicts the compressive strength and corresponding axial strain of the concrete confined with FRPs more accurately in comparison with the existing models. The results also show that RSM-SVR and SVR models provide stable predictions of strength and strain enhancement ratios for lateral confining ratio of >1 while the other models exhibit chaotic model error. The high accuracy and stable predictions by the proposed model are achieved based on its high flexibility and robustness in capturing the effect of lateral confining pressure as the interaction between the concrete core and FRP jacket in comparison with the existing models.
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This study addresses the learning objectives and the student outcomes of industrial engineering students by examining them at three different levels: course level, program level, and graduate level. Three learning domains are developed... more
This study addresses the learning objectives and the student outcomes of industrial engineering students by examining them at three different levels: course level, program level, and graduate level. Three learning domains are developed and analyzed for this purpose to assess the performance of students during and after graduation. These domains are labeled as the house of cognitive learning, which shows the level of learning, its outcome elements, and the depth of understanding. In the higher education system, the correct assessment of student learning is always considered as a challenging task. The aim of this study was to develop an integrated integer-programming algorithm to accurately determine the learning level of students. The method incorporates quality control charts and statistical assessment tools to present the findings. In this study, level of learning is calculated as a learning index that presents the contribution of a course to the respective student outcomes. Moreov...
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In this work, response surface methodology and adaptive neuro-fuzzy inference system approaches were used to predict and model effect of extraction conditions of pectin from medlar fruit (Mespilus germanica L.). The pectin extracted at... more
In this work, response surface methodology and adaptive neuro-fuzzy inference system approaches were used to predict and model effect of extraction conditions of pectin from medlar fruit (Mespilus germanica L.). The pectin extracted at optimized conditions (89 °C, 4.83 h and 4.2 pH) could be classified as high methoxyl pectin. Sugar composition analysis showed that pectin was mainly composed of D-galacturonic acid, L-arabinose, L-rhamnose, D-galactose and D-glucose. Fourier Transform Infrared Spectroscopy, RAMAN and nuclear magnetic resonance spectra confirmed molecular structure, revealing presence of D-galacturonic acid backbone. X-ray diffraction patterns revealed an amorphous structure. Differential scanning calorimetry showed endothermic (123 °C) and exothermic peaks (192 °C). Thermogravimetric analysis revealed three decomposition regions, 50-225 °C, 225-400 °C and 400-600 °C. Steady and dynamic shear analyses revealed that pectin had a pseudo-plastic behavior with storage (G&...
Research Interests: Chemistry, Decomposition, Fuzzy Systems, Food Chemistry, Medicine, and 15 moreFuzzy Inference, Glucose, Differential scanning calorimetry, Fruit, Article, Fruits, EXTRACTION, Fuzzy System, Fourier transform infrared spectroscopy, Controlled Study, ANFIS Model, Fuzzy Neural Networks, Chemical Structure, Dynamic Mechanical Analysis, and Flow Kinetics
High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower... more
High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.
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ABSTRACT Biogas is produced by anaerobic (oxygen free) digestion of organic materials such as sewage sludge, animal waste, and municipal solid wastes (MSW). As sustainable clean energy carrier biogas is an important source of energy in... more
ABSTRACT Biogas is produced by anaerobic (oxygen free) digestion of organic materials such as sewage sludge, animal waste, and municipal solid wastes (MSW). As sustainable clean energy carrier biogas is an important source of energy in heat and electricity generation, it is one of the most promising renewable energy sources in the world. Biogas is produced from the anaerobic digestion (AD) of organic matter, such as manure, MSW, sewage sludge, biodegradable wastes, and agricultural slurry, under anaerobic conditions with the help of microorganism. Biogas is composed of methane (55–75%), carbon dioxide (25–45%), nitrogen (0–5%), hydrogen (0–1%), hydrogen sulfide (0–1%), and oxygen (0–2%). The sewage sludge contains mainly proteins, sugars, detergents, phenols, and lipids. Sewage sludge also includes toxic and hazardous organic and inorganic pollutants sources. The digestion of municipal sewage sludge (MSS) occurs in three basic steps: acidogen, methanogens, and methanogens. During a 30-day digestion period, 80–85% of the biogas is produced in the first 15–18 days. Higher yields were observed within the temperature range of 30–60°C and pH range of 5.5–8.5. The MSS contains low nitrogen and has carbon-to-nitrogen (C/N) ratios of around 40–70. The optimal C/N ratio for the AD should be between 25 and 35. C/N ratio of sludge in small-scale sewage plants is often low, so nitrogen can be added in an inorganic form (ammonia or in organic form) such as livestock manure, urea, or food wastes. Potential production capacity of a biogas plant with a digestion chamber size of 500 m3 was estimated as 20–36 × 103 Nm3 biogas production per year.
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The G20 countries are the locomotives of economic growth, representing 64% of the global population and including 4.7 billion inhabitants. As a monetary and market value index, real gross domestic product (GDP) is affected by several... more
The G20 countries are the locomotives of economic growth, representing 64% of the global population and including 4.7 billion inhabitants. As a monetary and market value index, real gross domestic product (GDP) is affected by several factors and reflects the economic development of countries. This study aimed to reveal the hidden economic patterns of G20 countries, study the complexity of related economic factors, and analyze the economic reactions taken by policymakers during the coronavirus disease of 2019 (COVID-19) pandemic recession (2019–2020). In this respect, this study employed data-mining techniques of nonparametric classification tree and hierarchical clustering approaches to consider factors such as GDP/capita, industrial production, government spending, COVID-19 cases/population, patient recovery, COVID-19 death cases, number of hospital beds/1000 people, and percentage of the vaccinated population to identify clusters for G20 countries. The clustering approach can help...
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A solid waste management system based on the 3R principle: reduce, reuse, and recycle. There are two major recycling methods for conversion of plastic wastes to synthetic fuels: (a) pyrolysis in absence and presence of catalyst and (b)... more
A solid waste management system based on the 3R principle: reduce, reuse, and recycle. There are two major recycling methods for conversion of plastic wastes to synthetic fuels: (a) pyrolysis in absence and presence of catalyst and (b) thermal and/or catalytic cracking. Pyrolysis is a complex series of chemical and thermal reactions to decompose or depolymerize organic material under oxygen-free conditions. The most affecting variables of plastic pyrolysis are catalyst type and shape, temperature, and residence time. Certain types of waste plastics such as polystyrene (PS), polyethylene (PE), and polypropylene (PP) are generally used in pyrolysis. The plastic wastes can be pyrolyzed into liquid, gas, and solid residue products. The pyrolysis of plastic wastes produces a whole spectrum of hydrocarbons including paraffins, olefins, naphthalenes, and aromatics. The total yields of paraffins and olefins of PE and PP wastes obtained by pyrolysis were higher than that of PS. The oil obtained from plastic pyrolysis could improve performance by modifying engine. The addition of catalyst in the pyrolysis can be a more efficient method to produce high valuable products with mainly gasoline-range hydrocarbons. The catalytic decomposition was produced much more light hydrocarbons than that of thermal decomposition. Especially, ZSM-5 with a smaller pore size, rather than that of zeolite Y was more cracked into light hydrocarbons such as C6-C12 hydrocarbons and gas products.
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Buyuk burokratik kurulumlar, bilgi ve bilgi teknolojilerinde gerceklestirilen kapsamli gelismelerden cok daha once olusturulmus ve kullanilmislardir. Bu burokratik organizasyonlar ilk kurulus donemlerinde oldugu gibi, gunumuzde de... more
Buyuk burokratik kurulumlar, bilgi ve bilgi teknolojilerinde gerceklestirilen kapsamli gelismelerden cok daha once olusturulmus ve kullanilmislardir. Bu burokratik organizasyonlar ilk kurulus donemlerinde oldugu gibi, gunumuzde de hiyerarsik ve merkeziyetci bir yapiya sahip olduklarindan kaynaklarini etkin olarak kullanamamaktadirlar ve dolayisiyla rekabetci degildirler. Bugunun modern bilgi sistemleri, daha dogru ve etkin kararlar verebildigi dusunulen merkeziyetci ust yonetimler yerine, sayica daha az fakat daha genis karar verme yetki ve sorumluluga sahip personele ve hiyerarsik olmayan girisimlere ihtiyac duymaktadirlar. Bu calismada, modern bir bilgi sistemi olusturulurken kuruluslarin rolu incelenmistir. Bir bilgi sistemi, kurumlarin yapisal olarak yeniden dizayni esas alinarak, gerceklestirilir. Cunku, bilgi sistemi sosyo-teknik bir entitedir, kurulusun hem teknik ve hemde sosyal unsurlarinin yeniden dizaynini gerektirir. Bu nedenle, degisim muhendisligi yaklasimi kapsaminda ...
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Timely and accurate detection of cardiovascular diseases (CVDs) is critically important to minimize the risk of a myocardial infarction. Relations between factors of CVDs are complex, ill-defined and nonlinear, justifying the use of... more
Timely and accurate detection of cardiovascular diseases (CVDs) is critically important to minimize the risk of a myocardial infarction. Relations between factors of CVDs are complex, ill-defined and nonlinear, justifying the use of artificial intelligence tools. These tools aid in predicting and classifying CVDs. In this article, we propose a methodology using machine learning (ML) approaches to predict, classify and improve the diagnostic accuracy of CVDs, including support vector regression (SVR), multivariate adaptive regression splines, the M5Tree model and neural networks for the training process. Moreover, adaptive neuro-fuzzy and statistical approaches, nearest neighbor/naive Bayes classifiers and adaptive neuro-fuzzy inference system (ANFIS) are used to predict seventeen CVD risk factors. Mixed-data transformation and classification methods are employed for categorical and continuous variables predicting CVD risk. We compare our hybrid models and existing ML techniques on a...
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Design and implementation of biological neural networks is a vital research field in the neuromorphic engineering. This paper presents LUT-based modeling of the Adaptive Exponential integrate-and-fire (ADEX) model using Nyquist frequency... more
Design and implementation of biological neural networks is a vital research field in the neuromorphic engineering. This paper presents LUT-based modeling of the Adaptive Exponential integrate-and-fire (ADEX) model using Nyquist frequency method. In this approach, a continuous term is converted to a discrete term by sampling factor. This new modeling is called N-LUT-ADEX (Nyquist-Look Up Table-ADEX) and is based on accurate sampling of the original ADEX model. Since in this modeling, the high-accuracy matching is achieved, it can exactly reproduce the spiking patterns, which have the same behaviors of the original neuron model. To confirm the N-LUT-ADEX neuron, the proposed model is realized on Virtex-II Field-Programmable Gate Array (FPGA) board for validating the final hardware. Hardware implementation results show the high degree of similarity between the proposed and original models. Furthermore, low-cost and high-speed attributes of our proposed neuron model will be validated. I...
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The Central Nervous System (CNS) is the part of the nervous system including the brain and spinal cord. The CNS is so named because the brain integrates the received information and influences the activity of different sections of the... more
The Central Nervous System (CNS) is the part of the nervous system including the brain and spinal cord. The CNS is so named because the brain integrates the received information and influences the activity of different sections of the bodies. The basic elements of this important organ are: neurons, synapses, and glias. Neuronal modeling approach and hardware realization design for the nervous system of the brain is an important issue in the case of reproducing the same biological neuronal behaviors. This work applies a quadratic-based modeling called Digital Spiking Silicon Neuron (DSSN) to propose a modified version of the neuronal model which is capable of imitating the basic behaviors of the original model. The proposed neuron is modeled based on the primary hyperbolic functions, which can be realized in high correlation state with the main model (original one). Really, if the high-cost terms of the original model, and its functions were removed, a low-error and high-performance ...
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The main required organ of the biological system is the Central Nervous System (CNS), which can influence the other basic organs in the human body. The basic elements of this important organ are neurons, synapses, and glias (such as... more
The main required organ of the biological system is the Central Nervous System (CNS), which can influence the other basic organs in the human body. The basic elements of this important organ are neurons, synapses, and glias (such as astrocytes, which are the highest percentage of glias in the human brain). Investigating, modeling, simulation, and hardware implementation (realization) of different parts of the CNS are important in case of achieving a comprehensive neuronal system that is capable of emulating all aspects of the real nervous system. This paper uses a basic neuron model called the Izhikevich neuronal model to achieve a high copy of the primary nervous block, which is capable of regenerating the behaviors of the human brain. The proposed approach can regenerate all aspects of the Izhikevich neuron in high similarity degree and performances. The new model is based on Look-Up Table (LUT) modeling of the mathematical neuromorphic systems, which can be realized in a high deg...