Search results for: online genetic control

Authors: Lari Kela

Abstract:

An adaptive Helmholtz resonator was designed and adapted to hydraulics. The resonator was controlled by open- and closed-loop controls so that 20 dB attenuation of the peak-to-peak value of the pulsating pressure was maintained. The closed-loop control was noted to be better, albeit it was slower because of its low pressure and temperature variation, which caused variation in the effective bulk modulus of the hydraulic system. Low-pressure hydraulics contains air, which affects the stiffness of the hydraulics, and temperature variation changes the viscosity of the oil. Thus, an open-loop control loses its efficiency if a condition such as temperature or the amount of air changes after calibration. The instability of the low-pressure hydraulic system reduced the operational frequency range of the Helmholtz resonator when compared with the results of an analytical model. Different dampers for hydraulics are presented. Then analytical models of a hydraulic pipe and a hydraulic pipe with a Helmholtz resonator are presented. The analytical models are based on the wave equation of sound pressure. Finally, control methods and the results of experiments are presented.

Keywords: adaptive, damper, hydraulics, pressure, pulsating

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Authors: Kee-Young Kwahk, Xi Ge, Jun-Hyung Park

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This study aims to examine the determinants of purchase intention in C2C e-commerce. Specifically the role of instant messaging in the C2C e-commerce contextis investigated. In addition to instant messaging, we brought in two antecedents of purchase intention - trust and customer satisfaction - to establish a theoretical research model. Structural equation modeling using LISREL was used to analyze the data.We discussed the research findings and suggested some implications for researchers and practitioners.

Keywords: E-commerce, Online marketing, C2C, Purchase Intention

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Authors: S. Nasri, G. H. Amin, A. Azimi

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The use of herbs to treat disease is accompanied with the history of human life. This research is aimed to study the anti-inflammatory and antinociceptive effects of hydroalcoholic extract of aerial parts of "Tanacetum balsamita balsamita". In the experimental studies 144 male mice are used. In the inflammatory test, animals were divided into six groups: Control, positive control (receiving Dexamethason at dose of 15mg/kg), and four experimental groups receiving Tanacetum balsamita balsamita hydroalcoholic extract at doses of 25, 50, 100 and 200mg/kg. Xylene was used to induce inflammation. Formalin was used to study the nociceptive effects. Animals were divided into six groups: control group, positive control group (receiving morphine) and four experimental groups receiving Tanacetum balsamita balsamita (Tb.) hydroalcoholic extract at doses of 25, 50, 100 and 200mg/kg. I.p. injection of drugs or normal saline was performed 30 minutes before test. The data were analyzed by using one way Variance analysis and Tukey post test. Aerial parts of Tanacetum balsamita balsamita hydroalcoholic extract decreased significantly inflammatory at dose of 200mg/kg (P<0/001) and caused a significant decrease and alleviated the nociception in both first and second phases at doses of 200mg/kg (p<0/001) and 100mg/kg (P<0/05). Tanacetum balsamita balsamita extract has the anti-inflammatory and anti-nociceptive effects which seems to be related with flavonoids especially Quercetin.

Keywords: Inflammation, nociception, Hydroalcoholic extract, aerial parts of Tanacetum balsamita balsamita L.

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Authors: Adel Hamad Rafa

Abstract:

This paper, proposes a control system for use with microgrid consiste of  multiple small scale embedded generation networks (SSEG networks) connected to the 33kV distribution network. The proposed controller controls power flow in the grid-connected mode of operation, enables voltage and frequency control when the SSEG networks are islanded, and resynchronises the SSEG networks with the utility before reconnecting them. The performance of the proposed controller has been tested in simulations using PSCAD.

Keywords: Microgrid, Small scale embedded generation, island mode, resynchronisation.

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Authors: Asaiel Alohaly

Abstract:

A theoretical framework for corporate governance is needed to bridge the gap between the corporate governance of private companies and State-Owned Enterprises (SOEs). The two dominant models, being shareholder and stakeholder, do not always address the specific requirements and challenges posed by ‘hybrid’ companies; namely, previously national bodies that have been privatised while the government retains significant control or holds a majority of shares. Thus, an exploratory theoretical study is needed to identify how ‘hybrid’ companies should be defined and why the state model should be acknowledged since it is the less conspicuous model in comparison with the shareholder and stakeholder models. This research focuses on the state model of corporate governance to understand the complex ownership, control pattern, goals, and corporate governance of these hybrid companies. The significance of this research lies in the fact that there is a limited available publication on the state model. This research argues for the state model, which proceeds from an understanding of the institutionally embedded characteristics of hybrid companies, where the government as a shareholder, is either a majority of the total shares, or has been granted power based on the rule of law; the company bylaws.

Keywords: Corporate governance, control, shareholders, state model.

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Authors: M. M. Hlakola, E. Golovins, D. V. Nicolae

Abstract:

The field of instrumentation electronics is undergoing an explosive growth, due to its wide range of applications. The proliferation of electrical devices in a close working proximity can negatively influence each other’s performance. The degradation in the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic interference originating in the General Purpose Interface Bus (GPIB) control-network of the AC-DC transfer measurement system. Remedial measures of reducing measurement errors and failure of range of industrial devices due to EMI have been explored. The ACDC transfer measurement system was analysed for the commonmode (CM) EMI effects. Further investigation of coupling path as well as much accurate identification of noise propagation mechanism has been outlined. To prevent the occurrence of common-mode (ground loops) which was identified between the GPIB system control circuit and the measurement circuit, a microcontroller-driven GPIB switching isolator device was designed, prototyped, programmed and validated. This mitigation technique has been explored to reduce EMI effectively.

Keywords: CM, EMI, GPIB, ground loops.

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Authors: S. Grouni, R. Ibtiouen, M. Kidouche, O. Touhami

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Induction machine models used for steady-state and transient analysis require machine parameters that are usually considered design parameters or data. The knowledge of induction machine parameters is very important for Indirect Field Oriented Control (IFOC). A mismatched set of parameters will degrade the response of speed and torque control. This paper presents an improvement approach on rotor time constant adaptation in IFOC for Induction Machines (IM). Our approach tends to improve the estimation accuracy of the fundamental model for flux estimation. Based on the reduced order of the IM model, the rotor fluxes and rotor time constant are estimated using only the stator currents and voltages. This reduced order model offers many advantages for real time identification parameters of the IM.

Keywords: Indirect Field Oriented Control (IFOC), InductionMachine (IM), Rotor Time Constant, Parameters ApproachAdaptation. Optimum rotor flux.

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Authors: Onder Turkmen, Musa Seymen, Sali Fidan, Mustafa Paksoy

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There is a requirement for registered edible seed pumpkin suitable for eating in Turkey. A total of 81 genotypes collected from the researchers in 2005 originated from Eskisehir, Konya, Nevsehir, Tekirdag, Sakarya, Kayseri and Kirsehir provinces were utilized. The used genetic materials were brought to S5 generation by the research groups among 2006 and 2010 years. In this research, S5 stage reached in the genotype given some of the morphological features, and selection of promising genotypes generated scale were made. Results showed that the A-1 (420), A-7 (410), A-8 (420), A-32 (420), B-17 (410), B-24 (410), B-25 (420), B-33 (400), C-24 (420), C-25 (410), C-26 (410) and C-30 (420) genotypes are expected to be promising varieties.

Keywords: Candidate cultivar, edible seed pumpkin, morphologic parameters, selection.

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Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, Multiobjective optimization, ZDT test functions, performance metrics.

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Authors: Saad M. Howladar, Mostafa M. Rady, Ashraf Sh. Osman

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Effects of bio-nitrogen fertilizer (bio-N), as a partial alternative to mineral-nitrogen fertilizer (mineral-N), on growth, yield and yield quality of broccoli plants were investigated. Bio-N was applied at 1, 2 or 3 doses in combination with 65% of the recommended dose of mineral-N (bio-N1, bio-N2 or bio-N3 + ⅔mineral-N). However, 100% of the recommended dose of mineral- N was applied as a control. Significant positive influences of the bio- N3 + ⅔mineral-N treatment were observed on growth traits, leaf contents of nitrogen, phosphorus, potassium, nitrate and nitrite, and yield quality when compared to the other two combined treatments. In contrast, there were no significant differences in these parameters between the bio-N3 + ⅔mineral-N and the control treatments, except for leaf contents of nitrate and nitrite. They showed lower contents in the bio-N3 + ⅔mineral-N treatment than the control. Therefore, we recommend using bio-N as a partial alternative to mineral-N for healthy nutrition.

Keywords: Bio-fertilization, broccoli, growth, nitrate, nitrite, yield quality.

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Authors: Mohamed A. Hammad, Dzul Azri Mohamed Noor, Syed Azhar Syed Sulaiman, Ahmed A. Khamis, Abeer Kharshid, Nor Azizah Aziz

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The effect of statins dose intensity (SDI) on glycemic control in patients with existing diabetes is unclear. Also, there are many contradictory findings were reported in the literature; thus, it is limiting the possibility to draw conclusions. This project was designed to compare the effect of SDI on glycated hemoglobin (HbA1c%) control in outpatients with Type 2 diabetes in the endocrine clinic at Hospital Pulau Pinang, Malaysia, between July 2015 and August 2016. A prospective cohort study was conducted, where records of 345 patients with Type 2 diabetes (Moderate-SDI group 289 patients and high-SDI cohort 56 patients) were reviewed to identify demographics and laboratory tests. The target of glycemic control (HbA1c < 7% for patient < 65 years, and < 8% for patient ≥ 65 years) was estimated, and the results were presented as descriptive statistics. From 289 moderate-SDI cohorts with a mean age of 57.3 ± 12.4 years, only 86 (29.8%) cases were shown to have controlled glycemia, while there were 203 (70.2%) cases with uncontrolled glycemia with confidence interval (CI) of 95% (6.2–10.8). On the other hand, the high-SDI group of 56 patients with Type 2 diabetes with a mean age 57.7±12.4 years is distributed among 11 (19.6%) patients with controlled diabetes, and 45 (80.4%) of them had uncontrolled glycemia, CI: 95% (7.1–11.9). The study has demonstrated that the relative risk (RR) of uncontrolled glycemia in patients with Type 2 diabetes that used high-SDI is 1.15, and the excessive relative risk (ERR) is 15%. The absolute risk (AR) is 10.2%, and the number needed to harm (NNH) is 10. Outpatients with Type 2 diabetes who use high-SDI of statin have a higher risk of uncontrolled glycemia than outpatients who had been treated with a moderate-SDI.

Keywords: Cohort study, diabetes control, dose intensity, HbA1c, Malaysia, statin, Type 2 diabetes mellitus, uncontrolled glycemia.

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Authors: Pinto F., Dario C., Selvaggi M., Vicenti A.

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Two group of kids (“Safflower cake" and “Control") were fed ad libitum with pelleted total mixed rations. After a 7-days adaptation period, the diet of the “Safflower cake" group were supplemented with 20% of safflower cake. The kids were slaughtered at 96 days of age. Dietary safflower cake did not affect the growth traits of kids. In addition, kids fed experimental diet showed a lower feed intake and consequently a better feed conversion ratio in comparison to the “Control" group. The use of safflower decreased the level of SFA and increased the level of MUFA in kid meat. The level of PUFA was higher in lipid extracted from animals feeding “Control“ diet even if the UFA level was lower. Furthermore, lipid extracted from animals feeding control diet contained more ω6 fatty acids in comparison to kids feeding experimental diet while the opposite trend was observed for the level of ω3 fatty acids. The ω6 to ω3 ratio was significantly affected by diet and in particular this ratio decreased in meat of kids fed experimental diet. Our results indicate that intramuscular fatty acid composition of kid meat can be improved from a human health perspective by inclusion of safflower cake in the diet.

Keywords: Cake, fatty acids, meat, safflower.

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Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of big data technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centres or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through VADER and RoBERTa model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and Term Frequency – Inverse Document Frequency (TFIDF) Vectorization and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide if the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: Counter vectorization, Convolutional Neural Network, Crawler, data technology, Long Short-Term Memory, LSTM, Web Scraping, sentiment analysis.

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Authors: Zunaira Asif, Zhi Chen

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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: Air pollution, linear programming, mining, optimization, treatment technologies.

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Authors: Mehdi Dehghan-Banadaky, Fridoon Niazi, Mohsen Ghiasvand

Abstract:

Sixteen female Holstein calves allocated in three treatments including: 1: control, 2: fed raw fiber concentrate (RFC) for 45 days and 3: fed RFC for 90 days. RFC supplement (Vitacel® 200) was added to milk immediately before feeding (10 g/L milk). Withers height and body weights of calves were measured monthly. Individual dry matter intake was recorded daily. Blood samples were taken monthly. The result showed that calves consumed RFC had significantly greater weaning and final body weight. Treatment effect on dry matter intake was not significant (p>0.05). Calves fed RFC had better feed efficiency. Withers height of calves fed RFC were taller than the control group (p<0.05). Plasma cholesterol and total proteins concentrations in calves fed RFC were less than control group. We conclude that feeding RFC for 45 or 90 days in suckling period caused to achieve better feed efficiency and higher growth performance in Holstein calves.

Keywords: Holstein calves, raw fiber concentrate, growth, blood metabolites.

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Authors: Ε. Giovanis

Abstract:

In this paper we present, propose and examine additional membership functions for the Smoothing Transition Autoregressive (STAR) models. More specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions. Because Smoothing Transition Autoregressive (STAR) models follow fuzzy logic approach, more fuzzy membership functions should be tested. Furthermore, fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation or genetic algorithm instead to nonlinear squares. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

Keywords: Forecast , Fuzzy membership functions, Smoothingtransition, Time-series

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: Metabolic network, gene knockout, flux balance analysis, microarray data, integration.

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Authors: C. Clements, M. Hasenohr, A. Anvar

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A glider is in essence an unpowered vehicle and in this project we designed and built an oceanic glider, designed to operate underwater. This Glider was designed to collect ocean data such as temperature, pressure and (in future measures physical dimensions of the operating environment) and output this data to an external source. Development of the Oceanic Glider required research into various actuation systems that control buoyancy, pitch and yaw and the dynamics of these systems. It also involved the design and manufacture of the Glider and the design and implementation of a controller that enabled the Glider to navigate and move in an appropriate manner.

Keywords: Ocean Glider, Robot, Automation, Command, Control, Navigation.

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Authors: Yazhi Huang, Jing Yang, Dingge Ying, Yan Zhang, Vorasuk Shotelersuk, Nattiya Hirankarn, Pak Chung Sham, Yu Lung Lau, Wanling Yang

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Human leukocyte antigen (HLA) typing from next generation sequencing (NGS) data has the potential for applications in clinical laboratories and population genetic studies. Here we introduce a novel technique for HLA typing from NGS data based on read-mapping using a comprehensive reference panel containing all known HLA alleles and de novo assembly of the gene-specific short reads. An accurate HLA typing at high-digit resolution was achieved when it was tested on publicly available NGS data, outperforming other newly-developed tools such as HLAminer and PHLAT.

Keywords: Human leukocyte antigens, next generation sequencing, whole exome sequencing, HLA typing.

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Authors: Seema Chopra, R. Mitra, Vijay Kumar

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A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.

Keywords: Fuzzy control, neuro-fuzzy techniques, fuzzy subtractive clustering, extraction of rules, and optimization of membership functions.

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Authors: Thair Sh. Mahmoud, Tang Sai Hong, Mohammed H. Marhaban

Abstract:

In this paper, Neuro-Fuzzy based Fuzzy Subtractive Clustering Method (FSCM) and Self Tuning Fuzzy PD-like Controller (STFPDC) were used to solve non-linearity and trajectory problems of pitch AND yaw angles of Twin Rotor MIMO system (TRMS). The control objective is to make the beams of TRMS reach a desired position quickly and accurately. The proposed method could achieve control objectives with simpler controller. To simplify the complexity of STFPDC, ANFIS based FSCM was used to simplify the controller and improve the response. The proposed controllers could achieve satisfactory objectives under different input signals. Simulation results under MATLAB/Simulink® proved the improvement of response and superiority of simplified STFPDC on Fuzzy Logic Controller (FLC).

Keywords: Fuzzy Subtractive Clustering Method, Neuro Fuzzy, Self Tuning Fuzzy Controller, and Twin Rotor MIMO System.

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor, when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics, and using the weighted sum-squared prediction error as the residual. The Recursive Orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. Several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature, and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control.

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Authors: N. Lassouaoui, L. Hamami, N. Nouali

Abstract:

The tracking allows to detect the tumor affections of cervical cancer, it is particularly complex and consuming time, because it consists in seeking some abnormal cells among a cluster of normal cells. In this paper, we present our proposed computer system for helping the doctors in tracking the cervical cancer. Knowing that the diagnosis of the malignancy is based in the set of atypical morphological details of all cells, herein, we present an unsupervised genetic algorithm for the separation of cell components since the diagnosis is doing by analysis of the core and the cytoplasm. We give also the various algorithms used for computing the morphological characteristics of cells (Ratio core/cytoplasm, cellular deformity, ...) necessary for the recognition of illness.

Keywords: Cervical cell, morphological analysis, recognition, segmentation.

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Authors: Amira, A. Goma, U. E. Mahrous

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Welfare may be considered to be a subjective experience; it has a biological function that is related to the fitness and survival of the animal accordingly, researches have suggested that welfare is compromised when the animal's evolutionary fitness is reduced. This study was carried out to explain the effect of some managerial stressors as handling and restraint on behavioral patterns and biochemical parameters of rats. A total of 24 (12 males & 12 females) Sprague-Dawley rats (12 months & 150-180g) were allotted into 3 groups, handled group (4 male & 4 female), restrained group (4 male & 4 female) and control group (4 males & 4 females). The obtained results revealed that time spent feeding, drinking, movement and cage exploration frequencies increased significantly in handled rats than other groups, while lying time and licking increased significantly in restrained rats than handled and controls. Moreover, social behavior decreased in both stressed groups than control. Triglycerides were significantly increased in handled rats than other groups, while total lipid, total protein and globulin significantly increased in both treated groups than control. Corticosterone increased in restrained and handled rats than control ones. Moreover, there was an increment in packed cell volume significantly in restrained rats than others. These deducted that if we want to study the effect of stress on animal welfare it is necessary to study the effect of such stressors on animal’s behavior and physiological responses.

Keywords: Behavior, handling, restraint, rat, welfare.

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Authors: Benmabrouk. Zaineb, Ben Hamed. Mouna, Lassad. Sbita

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This article deals to describe the simulation investigation of the digital phase locked loop implemented in software (SDPLL). SDPLL has been developed for speed drives of an induction motor in scalar strategy. A drive was implemented and simulation results are presented to verify the robustness against motor parameter variation and regulation speed.

Keywords: Induction motor, Software Digital Phase LockedLoop, Speed control, Simulation.

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Authors: Babesse Saad, Ameddah Djameleddine

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In this paper, a learning algorithm using neuronal networks to improve the roll stability and prevent the rollover in a single unit heavy vehicle is proposed. First, LQR control to keep balanced normalized rollovers, between front and rear axles, below the unity, then a data collected from this controller is used as a training basis of a neuronal regulator. The ANN controller is thereafter applied for the nonlinear side force model, and gives satisfactory results than the LQR one.

Keywords: Rollover, single unit heavy vehicle, neural networks, nonlinear side force.

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Authors: R. Gunabalan, S. Immanuel Prabakaran, J. Reegan, S. Ganesh

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This paper describes a software approach for modeling inverter fed induction motor drive using Laboratory Virtual Instrument Engineering Workbench (LabVIEW). The reason behind the selection of LabVIEW software is because of its strong graphical interface, flexibility of its programming language combined with built-in tools designed specifically for test, measurement and control. LabVIEW is generally used in most of the applications for data acquisition, test and control. In this paper, inverter and induction motor are modeled using LabVIEW toolkits. Simulation results are presented and are validated.

Keywords: Induction motor, LabVIEW, State model.

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Authors: Akbar H. Borzabadi, Omid S. Fard

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In this paper we introduce an approach via optimization methods to find approximate solutions for nonlinear Fredholm integral equations of the first kind. To this purpose, we consider two stages of approximation. First we convert the integral equation to a moment problem and then we modify the new problem to two classes of optimization problems, non-constraint optimization problems and optimal control problems. Finally numerical examples is proposed.

Keywords: Fredholm integral equation, Optimization method, Optimal control, Nonlinear and linear programming

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Authors: Alawode Kehinde O., Jubril Abimbola M. Komolafe Olusola A.

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This paper solves the environmental/ economic dispatch power system problem using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and its hybrid with a Convergence Accelerator Operator (CAO), called the NSGA-II/CAO. These multiobjective evolutionary algorithms were applied to the standard IEEE 30-bus six-generator test system. Several optimization runs were carried out on different cases of problem complexity. Different quality measure which compare the performance of the two solution techniques were considered. The results demonstrated that the inclusion of the CAO in the original NSGA-II improves its convergence while preserving the diversity properties of the solution set.

Keywords: optimal power flow, multiobjective power dispatch, evolutionary algorithm

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Authors: Pham Luu Trung Duong, Moonyong Lee

Abstract:

To increase precision and reliability of automatic control systems, we have to take into account of random factors affecting the control system. Thus, operational matrix technique is used for statistical analysis of first order plus time delay system with uniform random parameter. Examples with deterministic and stochastic disturbance are considered to demonstrate the validity of the method. Comparison with Monte Carlo method is made to show the computational effectiveness of the method.

Keywords: First order plus dead-time, Operational matrix, Statistical analysis, Walsh function.

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