Search results for: Stability and accuracy

Authors: F. M. Abu-Salem, M. H. Mahmoud, A. Y. Gibriel, M. H. El-Kalyoubi, A. A. Abou-Arab Arab

Abstract:

Soybean Natto powder was added to the burger in order to enhance the oxidative stability as well as decreases the microbial spoilage. The soybean bioactives compound (soybean Natto) as antioxidant and antimicrobial were added at level of 1, 2 and 3%. Chemical analysis and physical properties were affected by soybean Natto addition. All the tested soybean Natto additives showed strong antioxidant properties. The microbiological indicators were significantly (P < 0.05) affected by the addition of the soybean Natto. Decreasing trends of different extent were also observed in samples of the treatments for total viable counts, Coliform, Staphylococcus aureus, yeast and molds. Storage period was significantly (P < 0.05) affected on microbial counts in all samples Staphylococcus aureus were the most sensitive microbe followed by Coliform group of the sample containing soybean Natto. Sensory attributes were also performed, added soybean Natto exhibits beany flavor which was clear about samples of 3% soybean Natto.

Keywords: Antioxidant, antimicrobial, bioactive peptide, antioxidant peptides.

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Authors: Van Nhan Nguyen, Harald Holone

Abstract:

Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Traffic Control (ATC), such as air traffic control simulation and training, monitoring live operators for with the aim of safety improvements, air traffic controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this field. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air traffic control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as specific approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed.

Keywords: Automatic Speech Recognition, ASR, Air Traffic Control, ATC.

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Authors: Il Young Song, Du Yong Kim, Vladimir Shin

Abstract:

This paper reports on a receding horizon filtering for mobile robot systems with cross-correlated sensor noises and uncertainties. Also, the effect of uncertain parameters in the state of the tracking error model performance is considered. A distributed fusion receding horizon filter is proposed. The distributed fusion filtering algorithm represents the optimal linear combination of the local filters under the minimum mean square error criterion. The derivation of the error cross-covariances between the local receding horizon filters is the key of this paper. Simulation results of the tracking mobile robot-s motion demonstrate high accuracy and computational efficiency of the distributed fusion receding horizon filter.

Keywords: Distributed fusion, fusion formula, Kalman filter, multisensor, receding horizon, wheeled mobile robot

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Authors: Peña Aguilar Juan M., Valencia Luis, Pastrana Alberto, Nava Estefany, Martinez A., Vivanco M., Castañeda A.

Abstract:

This paper seeks to compare the innovation of Mexico from an economic and human perspective, with the seven most innovative countries according to the Global Innovation Index 2013, done by the World Intellectual Property Organization (WIPO). The above analysis suggests nine dimensions: Expenditure on R & D, intellectual property, appropriate environment to conduct business, economic stability, triple helix for R & D, ICT Infrastructure, education, human resources and quality of life. Each dimension is represented by an indicator which is later used to construct a radial graph that compares the innovative capacity of the countries analyzed. As a result, it is proposed a new indicator of innovation called The Area of Innovation. Observations are made from the results, and finally as a conclusion, those items or dimensions in which Mexico suffers lag in innovation are identify.

Keywords: Dimension, measure, innovation level, economy, radar chart.

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Authors: Rajab Abdullah Hokoma

Abstract:

Manufacturing, production and service industries within Libya have struggled with many problems during the past two decades due to many difficulties. These problems have created a negative impact on the productivity and utilization of many industries around the country. This paper studies the implementation levels of the manufacturing control systems known as Manufacturing Resource Planning (MRPII) being adapted within some Libyan industries. A survey methodology has been applied for this research, based on the survey analysis, the results pointed out that the system within these industries has a modest strategy towards most of the areas that are considered as being very crucial in implementing these systems successfully. The findings also show a variation within these implementation levels with a respect to the key-elements that related to MRPII, giving the highest levels in the emphasise on financial data accuracy. The paper has also identified limitations within the investigated manufacturing and managerial areas and has pointed to where senior managers should take immediate actions in order to achieve effective implementation of MRPII within their business area.

Keywords: Control, Industry, Manufacturing, Survey, System

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Authors: Meredith Stevenson, John E. Porter

Abstract:

Since the pioneering work of Zadeh, fuzzy set theory has been applied to a myriad of areas. Song and Chissom introduced the concept of fuzzy time series and applied some methods to the enrollments of the University of Alabama. In recent years, a number of techniques have been proposed for forecasting based on fuzzy set theory methods. These methods have either used enrollment numbers or differences of enrollments as the universe of discourse. We propose using the year to year percentage change as the universe of discourse. In this communication, the approach of Jilani, Burney, and Ardil is modified by using the year to year percentage change as the universe of discourse. We use enrollment figures for the University of Alabama to illustrate our proposed method. The proposed method results in better forecasting accuracy than existing models.

Keywords: Fuzzy forecasting, fuzzy time series, fuzzified enrollments, time-invariant model

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Authors: Robert Setekera, Luuk Tiemeijer, Ramses van der Toorn

Abstract:

In this paper an extensive verification of the extraction method (published earlier) that consistently accounts for self-heating and Early effect to accurately extract both base and thermal resistance of bipolar junction transistors is presented. The method verification is demonstrated on advanced RF SiGe HBTs were the extracted results for the thermal resistance are compared with those from another published method that ignores the effect of Early effect on internal base-emitter voltage and the extracted results of the base resistance are compared with those determined from noise measurements. A self-consistency of our method in the extracted base resistance and thermal resistance using compact model simulation results is also carried out in order to study the level of accuracy of the method.

Keywords: Avalanche, Base resistance, Bipolar transistor, Compact modeling, Early voltage, Thermal resistance, Self-heating, parameter extraction.

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Authors: V. V. Lyahov, V. M. Neshchadim

Abstract:

We offer a new technique for research of stability of current sheaths in space plasma taking into account the effect of polarization. At the beginning, the found perturbation of the distribution function is used for calculation of the dielectric permeability tensor, which simulates inhomogeneous medium of a current sheath. Further, we in the usual manner solve the system of Maxwell's equations closed with the material equation. The amplitudes of Fourier perturbations are considered to be exponentially decaying through the current sheath thickness. The dispersion equation follows from the nontrivial solution requirement for perturbations of the electromagnetic field. The resulting dispersion equation allows one to study the temporal and spatial characteristics of instability modes of the current sheath (within the limits of the proposed model) over a wide frequency range, including low frequencies.

Keywords: Current sheath, distribution function, effect of polarization, instability modes, low frequencies, perturbation of electromagnetic field dispersion equation, space plasma, tensor of dielectric permeability.

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Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu

Abstract:

Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.

Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.

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Authors: C.Kia, M.R.Arshad, A.H.Adom, P.A.Wilson

Abstract:

This paper presents recent work on the improvement of the robotics vision based control strategy for underwater pipeline tracking system. The study focuses on developing image processing algorithms and a fuzzy inference system for the analysis of the terrain. The main goal is to implement the supervisory fuzzy learning control technique to reduce the errors on navigation decision due to the pipeline occlusion problem. The system developed is capable of interpreting underwater images containing occluded pipeline, seabed and other unwanted noise. The algorithm proposed in previous work does not explore the cooperation between fuzzy controllers, knowledge and learnt data to improve the outputs for underwater pipeline tracking. Computer simulations and prototype simulations demonstrate the effectiveness of this approach. The system accuracy level has also been discussed.

Keywords: Fuzzy logic, Underwater target tracking, Autonomous underwater vehicles, Artificial intelligence, Simulations, Robot navigation, Vision system.

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Authors: Abdul Rauf, Muhammad Irfan, Muhammad Nadeem, Ishtiaq Ahmed, Hafiz Muhammad Nasir Iqbal

Abstract:

Rhizopus oligosporus was used in the present study for the production of protease enzyme under SSF. Sunflower meal was used as by-product of oil industry incorporated with organic salts was employed for the production of protease enzyme. The main purpose of the present was to study different parameters of protease productivity, its yields and to optimize basal fermentation conditions. The optimal conditions found for protease production using sunflower meal as a substrate in the present study were inoculum size (1%), substrate (Sunflower meal), substrate concentration (20 g), pH (3), cultivation period (72 h), incubation temperature (35oC), substrate to diluent-s ratio (1:2) and tween 81 (1 mL). The maximum production of protease in the presence of cheaper substrate at low concentration and stability at acidic pH, these characteristics make the strain and its enzymes useful in different industry.

Keywords: Acidic protease, Rhizopus oligosporus, Mediaoptimization, Solid state Fermentation

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Authors: N. Jinesh, K. Shankar

Abstract:

This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: Structural identification, PZT patches, inverse problem, particle swarm optimization.

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Authors: A. Pedišius, V. Janušas, A. Bertašienė

Abstract:

The paper depicts air velocity values, reproduced by laser Doppler anemometer (LDA) and ultrasonic anemometer (UA), relations with calculated ones from flow rate measurements using the gas meter which calibration uncertainty is ± (0.15 – 0.30) %. Investigation had been performed in channel installed in aerodynamical facility used as a part of national standard of air velocity. Relations defined in a research let us confirm the LDA and UA for air velocity reproduction to be the most advantageous measures. The results affirm ultrasonic anemometer to be reliable and favourable instrument for measurement of mean velocity or control of velocity stability in the velocity range of 0.05 m/s – 10 (15) m/s when the LDA used. The main aim of this research is to investigate low velocity regularities, starting from 0.05 m/s, including region of turbulent, laminar and transitional air flows. Theoretical and experimental results and brief analysis of it are given in the paper. Maximum and mean velocity relations for transitional air flow having unique distribution are represented. Transitional flow having distinctive and different from laminar and turbulent flow characteristics experimentally have not yet been analysed.

Keywords: Laser Doppler anemometer, ultrasonic anemometer, air flow velocities, transitional flow regime, measurement, uncertainty.

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Authors: H. F. A. Abdul Ghani, R. R. Porle

Abstract:

Speech to text in Malay language is a system that converts Malay speech into text. The Malay language recognition system is still limited, thus, this paper aims to investigate the performance of ten Malay words obtained from the online Malay news. The methodology consists of three stages, which are preprocessing, feature extraction, and speech classification. In preprocessing stage, the speech samples are filtered using pre emphasis. After that, feature extraction method is applied to the samples using Mel Frequency Cepstrum Coefficient (MFCC). Lastly, speech classification is performed using Feedforward Neural Network (FFNN). The accuracy of the classification is further investigated based on the hidden layer size. From experimentation, the classifier with 40 hidden neurons shows the highest classification rate which is 94%.  

Keywords: Feed-Forward Neural Network, FFNN, Malay speech recognition, Mel Frequency Cepstrum Coefficient, MFCC, speech-to-text.

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Authors: Hossein Esbati, Jalil Shirazi

Abstract:

In this paper, in order to categorize ORL database face pictures, principle Component Analysis (PCA) and Kernel Principal Component Analysis (KPCA) methods by using Elman neural network and Support Vector Machine (SVM) categorization methods are used. Elman network as a recurrent neural network is proposed for modeling storage systems and also it is used for reviewing the effect of using PCA numbers on system categorization precision rate and database pictures categorization time. Categorization stages are conducted with various components numbers and the obtained results of both Elman neural network categorization and support vector machine are compared. In optimum manner 97.41% recognition accuracy is obtained.

Keywords: Face recognition, Principal Component Analysis, Kernel Principal Component Analysis, Neural network, Support Vector Machine.

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Authors: Alexander Schulz, Ingrid Rottensteiner, Manfred Neumann, Michael Wehse, Johann Wassermann

Abstract:

Self-sensing estimates the air gap within an electro magnetic path by analyzing the bearing coil current and/or voltage waveform. The self-sensing concept presented in this paper has been developed within the research project “Active Magnetic Bearings with Supreme Reliability" and is used for position sensor fault detection. Within this new concept gap calculation is carried out by an alldigital analysis of the digitized coil current and voltage waveform. For analysis those time periods within the PWM period are used, which give the best results. Additionally, the concept allows the digital compensation of nonlinearities, for example magnetic saturation, without degrading signal quality. This increases the accuracy and robustness of the air gap estimation and additionally reduces phase delays. Beneath an overview about the developed concept first measurement results are presented which show the potential of this all-digital self-sensing concept.

Keywords: digital signal analysis, active magnetic bearing, reliability, fault detection.

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Authors: F. Onyango, Salim R. Wanjala, M. Ndege, L. Masu

Abstract:

Asphalt concrete pavements have a short life cycle, failing mainly due to temperature changes, traffic loading and ageing. Modified asphalt mixtures provide the technology to produce a bituminous binder with improved viscoelastic properties, which remain in balance over a wider temperature range and loading conditions. In this research, 60/70 penetration grade asphalt binder was modified by adding 2, 4, 6, 8 and 10 percent by weight of asphalt binder following the wet process and the mineral aggregate was modified by adding 1, 2, 3, 4 and 5 percent crumb rubber by volume of the mineral aggregate following the dry process. The LDPE modified asphalt binder rheological properties were evaluated. The laboratory results showed an increase in viscosity, softening point and stiffness of the binder. The modified asphalt was then used in preparing asphalt mixtures by Marshall Mix design procedure. The Marshall Stability values for mixes containing 2% crumb rubber and 4% LDPE were found to be 30% higher than the conventional asphalt concrete mix.

Keywords: Crumb rubber, dry process, low-density polyethylene, hot mix asphalt, wet process.

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Authors: O. Miraliyari, M.M. Najafizadeh, A.R. Rahmani, A. Momeni Hezaveh

Abstract:

This paper presents the buckling analysis of short and long functionally graded cylindrical shells under thermal and mechanical loads. The shell properties are assumed to vary continuously from the inner surface to the outer surface of the shell. The equilibrium and stability equations are derived using the total potential energy equations, Euler equations and first order shear deformation theory assumptions. The resulting equations are solved for simply supported boundary conditions. The critical temperature and pressure loads are calculated for both short and long cylindrical shells. Comparison studies show the effects of functionally graded index, loading type and shell geometry on critical buckling loads of short and long functionally graded cylindrical shells.

Keywords: Buckling, Functionally graded materials, Short and long cylindrical shell, Thermal and mechanical loads.

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Authors: V. Gomathi, Dr. K. Ramar, A. Santhiyaku Jeevakumar

Abstract:

Facial expression analysis plays a significant role for human computer interaction. Automatic analysis of human facial expression is still a challenging problem with many applications. In this paper, we propose neuro-fuzzy based automatic facial expression recognition system to recognize the human facial expressions like happy, fear, sad, angry, disgust and surprise. Initially facial image is segmented into three regions from which the uniform Local Binary Pattern (LBP) texture features distributions are extracted and represented as a histogram descriptor. The facial expressions are recognized using Multiple Adaptive Neuro Fuzzy Inference System (MANFIS). The proposed system designed and tested with JAFFE face database. The proposed model reports 94.29% of classification accuracy.

Keywords: Adaptive neuro-fuzzy inference system, Facialexpression, Local binary pattern, Uniform Histogram

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Authors: DongHoon Shin, Yunmook Nah, HoSeong Kim, Gang Shin Lee, Jae-Il Lee

Abstract:

The rapid advance of communication technology is evolving the network environment into the broadband convergence network. Likewise, the IT services operated in the individual network are also being quickly converged in the broadband convergence network environment. VoIP and IPTV are two examples of such new services. Efforts are being made to develop the video phone service, which is an advanced form of the voice-oriented VoIP service. However, the new IT services will be subject to stability and reliability vulnerabilities if the relevant security issues are not answered during the convergence of the existing IT services currently being operated in individual networks within the wider broadband network environment. To resolve such problems, this paper attempts to analyze the possible threats and identify the necessary security measures before the deployment of the new IT services. Furthermore, it measures the quality of the encryption algorithm application example to describe the appropriate algorithm in order to present security technology that will have no negative impact on the quality of the video phone service.

Keywords: BcN, Security Measures, Video Phone.

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Authors: Hiba Basim Alwan, Ku Ruhana Ku-Mahamud

Abstract:

A direction for ACO is to optimize continuous and mixed (discrete and continuous) variables in solving problems with various types of data. Support Vector Machine (SVM), which originates from the statistical approach, is a present day classification technique. The main problems of SVM are selecting feature subset and tuning the parameters. Discretizing the continuous value of the parameters is the most common approach in tuning SVM parameters. This process will result in loss of information which affects the classification accuracy. This paper presents two algorithms that can simultaneously tune SVM parameters and select the feature subset. The first algorithm, ACO_R-SVM, will tune SVM parameters, while the second IACO_MV-R-SVM algorithm will simultaneously tune SVM parameters and select the feature subset. Three benchmark UCI datasets were used in the experiments to validate the performance of the proposed algorithms. The results show that the proposed algorithms have good performances as compared to other approaches.

Keywords: Continuous ant colony optimization, incremental continuous ant colony, simultaneous optimization, support vector machine.

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Authors: Swadhin Ku. Mishra, Sidhartha Panda, Simanchala Padhy, C. Ardil

Abstract:

In this paper, real-coded genetic algorithm (RCGA) optimization technique has been applied for large-scale linear dynamic multi-input-multi-output (MIMO) system. The method is based on error minimization technique where the integral square error between the transient responses of original and reduced order models has been minimized by RCGA. The reduction procedure is simple computer oriented and the approach is comparable in quality with the other well-known reduction techniques. Also, the proposed method guarantees stability of the reduced model if the original high-order MIMO system is stable. The proposed approach of MIMO system order reduction is illustrated with the help of an example and the results are compared with the recently published other well-known reduction techniques to show its superiority.

Keywords: Multi-input-multi-output (MIMO) system.Modelorder reduction. Integral squared error (ISE). Real-coded geneticalgorithm

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Authors: Sannikumar Patel, Brian Nolan, Markus Hofmann, Philip Owende, Kunjan Patel

Abstract:

Sentiment analysis and opinion mining have become emerging topics of research in recent years but most of the work is focused on data in the English language. A comprehensive research and analysis are essential which considers multiple languages, machine translation techniques, and different classifiers. This paper presents, a comparative analysis of different approaches for multilingual sentiment analysis. These approaches are divided into two parts: one using classification of text without language translation and second using the translation of testing data to a target language, such as English, before classification. The presented research and results are useful for understanding whether machine translation should be used for multilingual sentiment analysis or building language specific sentiment classification systems is a better approach. The effects of language translation techniques, features, and accuracy of various classifiers for multilingual sentiment analysis is also discussed in this study.

Keywords: Cross-language analysis, machine learning, machine translation, sentiment analysis.

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Authors: Belkacem Laimouche

Abstract:

With the field of Artificial Intelligence (AI) experiencing exponential growth, fueled by technological advancements that pave the way for increasingly innovative and promising applications, there is an escalating need to develop rigorous methods for assessing their performance in pursuit of transparency and equity. This article proposes a metrology-inspired statistical framework for evaluating bias and explainability in AI systems. Drawing from the principles of metrology, we propose a pioneering approach, using a concrete example, to evaluate the accuracy and precision of AI models, as well as to quantify the sources of measurement uncertainty that can lead to bias in their predictions. Furthermore, we explore a statistical approach for evaluating the explainability of AI systems based on their ability to provide interpretable and transparent explanations of their predictions.

Keywords: Artificial intelligence, metrology, measurement uncertainty, prediction error, bias, machine learning algorithms, probabilistic models, inter-laboratory comparison, data analysis, data reliability, bias impact assessment, bias measurement.

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Authors: Bremananth R, Nithya B, Saipriya R

Abstract:

The proposed system identifies the species of the wood using the textural features present in its barks. Each species of a wood has its own unique patterns in its bark, which enabled the proposed system to identify it accurately. Automatic wood recognition system has not yet been well established mainly due to lack of research in this area and the difficulty in obtaining the wood database. In our work, a wood recognition system has been designed based on pre-processing techniques, feature extraction and by correlating the features of those wood species for their classification. Texture classification is a problem that has been studied and tested using different methods due to its valuable usage in various pattern recognition problems, such as wood recognition, rock classification. The most popular technique used for the textural classification is Gray-level Co-occurrence Matrices (GLCM). The features from the enhanced images are thus extracted using the GLCM is correlated, which determines the classification between the various wood species. The result thus obtained shows a high rate of recognition accuracy proving that the techniques used in suitable to be implemented for commercial purposes.

Keywords: Correlation, Grey Level Co-Occurrence Matrix, ProbabilityDensity Function, Wood Recognition.

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Authors: Abdur Rosyid, Mohamed El-Madany, Mohanad Alata

Abstract:

Due to simplicity and low cost, rotordynamic system is often modeled by using lumped parameters. Recently, finite elements have been used to model rotordynamic system as it offers higher accuracy. However, it involves high degrees of freedom. In some applications such as control design, this requires higher cost. For this reason, various model reduction methods have been proposed. This work demonstrates the quality of model reduction of rotor-bearing-support system through substructuring. The quality of the model reduction is evaluated by comparing some first natural frequencies, modal damping ratio, critical speeds, and response of both the full system and the reduced system. The simulation shows that the substructuring is proven adequate to reduce finite element rotor model in the frequency range of interest as long as the number and the location of master nodes are determined appropriately. However, the reduction is less accurate in an unstable or nearly-unstable system.

Keywords: Finite element model, rotordynamic system, model reduction, substructuring.

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Authors: Ashu Ahuja, Shiv Narayan, Jagdish Kumar

Abstract:

This paper realized the 2-DOF controller structure for first order with time delay systems. The co-prime factorization is used to design observer based controller K(s), representing one degree of freedom. The problem is based on H∞ norm of mixed sensitivity and aims to achieve stability, robustness and disturbance rejection. Then, the other degree of freedom, prefilter F(s), is formulated as fixed structure polynomial controller to meet open loop processing of reference model. This model matching problem is solved by minimizing integral square error between reference model and proposed model. The feedback controller and prefilter designs are posed as optimization problem and solved using Particle Swarm Optimization (PSO). To show the efficiency of the designed approach different variety of processes are taken and compared for analysis.

Keywords: 2-DOF, integral square error, mixed sensitivity function, observer based controller, particle swarm optimization, prefilter.

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Authors: Rouzbeh Ramezani, Renzo Di Felice

Abstract:

Nowadays, removal of CO₂ as one of the major contributors to global warming using alternative solvents with high CO₂ absorption efficiency, is an important industrial operation. In this study, three amines, including 2-methylpiperazine, potassium sarcosinate and potassium lysinate as potential additives, were added to the potassium carbonate solution as a base solvent for CO₂ capture. In order to study the absorption performance of CO₂ in terms of loading capacity of CO₂ and absorption rate, the absorption experiments in a blend of additives with potassium carbonate were carried out using the vapor-liquid equilibrium apparatus at a temperature of 313.15 K, CO₂ partial pressures ranging from 0 to 50 kPa and at mole fractions 0.2, 0.3, and 0.4. Furthermore, the performance of CO₂ absorption in these blend solutions was compared with pure monoethanolamine and with pure potassium carbonate. Finally, a correlation with good accuracy was developed using the nonlinear regression analysis in order to predict CO₂ loading capacity.

Keywords: Absorption rate, carbon dioxide, CO2 capture, global warming, loading capacity.

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Authors: Norziana Aminudin, Titik Khawa Abdul Rahman, Ismail Musirin

Abstract:

One of the factors to maintain system survivability is the adequate reactive power support to the system. Lack of reactive power support may cause undesirable voltage decay leading to total system instability. Thus, appropriate reactive power support scheme should be arranged in order to maintain system stability. The strength of a system capacity is normally denoted as system loadability. This paper presents the enhancement of system loadability through optimal reactive power planning technique using a newly developed optimization technique, termed as Multiagent Immune Evolutionary Programming (MAIEP). The concept of MAIEP is developed based on the combination of Multiagent System (MAS), Artificial Immune System (AIS) and Evolutionary Programming (EP). In realizing the effectiveness of the proposed technique, validation is conducted on the IEEE-26-Bus Reliability Test System. The results obtained from pre-optimization and post-optimization process were compared which eventually revealed the merit of MAIEP.

Keywords: Load margin, MAIEP, Maximum loading point, ORPP.

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Authors: Zeyneb Kurt, Oguzhan Yavuz

Abstract:

The feature of HIV genome is in a wide range because of it is highly heterogeneous. Hence, the infection ability of the virus changes related with different chemokine receptors. From this point, R5 and X4 HIV viruses use CCR5 and CXCR5 coreceptors respectively while R5X4 viruses can utilize both coreceptors. Recently, in Bioinformatics, R5X4 viruses have been studied to classify by using the coreceptors of HIV genome. The aim of this study is to develop the optimal Multilayer Perceptron (MLP) for high classification accuracy of HIV sub-type viruses. To accomplish this purpose, the unit number in hidden layer was incremented one by one, from one to a particular number. The statistical data of R5X4, R5 and X4 viruses was preprocessed by the signal processing methods. Accessible residues of these virus sequences were extracted and modeled by Auto-Regressive Model (AR) due to the dimension of residues is large and different from each other. Finally the pre-processed dataset was used to evolve MLP with various number of hidden units to determine R5X4 viruses. Furthermore, ROC analysis was used to figure out the optimal MLP structure.

Keywords: Multilayer Perceptron, Auto-Regressive Model, HIV, ROC Analysis

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