Search results for: Group process model

Authors: Khaled Abdalla Elraies, Shuaib Ahmed

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A large quantity of world-s oil reserves exists in carbonate reservoirs. Carbonate reservoirs are very sensitive to chemical enhanced oil recovery process because of containing large amount of calcite, dolomite and calcium sulfate minerals. These minerals cause major obstacles during alkali-surfactant-polymer (ASP) flooding. Alkali reacts with these minerals and form undesired precipitations which plug effective porous openings, reduce permeability and cause scale occurrence at the wellbore. In this paper, a new chemical combination consists of acrylic acid and alkali was used to minimize precipitation problem during ASP flooding. A series of fluid-fluid compatibility tests were performed using acrylic acid and different concentrations of alkaline. Two types of alkalis namely; sodium carbonate and sodium metaborate were screened. As a result, the combination of acrylic acid and sodium carbonate was not effective in preventing calcium and magnesium precipitations. However, acrylic acid and sodium metaborate showed promising results for keeping all solutions without any precipitations. The ratio of acrylic acid to sodium metaborate of 0.7:1.0 was found to be optimum for achieving a compatible solution for 30 days at 80oC.

Keywords: Fluid-fluid compatibility test, Carbonate reservoirs, Precipitations and ASP flooding.

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Authors: Wataru Nakamura, Tomoaki Hashimoto, Liang-Kuang Chen

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This paper provides a state estimation method for automatic control systems of nonlinear vehicle dynamics. A nonlinear tire model is employed to represent the realistic behavior of a vehicle. In general, all the state variables of control systems are not precisedly known, because those variables are observed through output sensors and limited parts of them might be only measurable. Hence, automatic control systems must incorporate some type of state estimation. It is needed to establish a state estimation method for nonlinear vehicle dynamics with restricted measurable state variables. For this purpose, unscented Kalman filter method is applied in this study for estimating the state variables of nonlinear vehicle dynamics. The objective of this paper is to propose a state estimation method using unscented Kalman filter for nonlinear vehicle dynamics. The effectiveness of the proposed method is verified by numerical simulations.

Keywords: State estimation, control systems, observer systems, unscented Kalman filter, nonlinear vehicle dynamics.

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Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.

Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks.

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Authors: Zhou Yu, Jiang Feng

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An adaptive Chinese hand-talking system is presented in this paper. By analyzing the 3 data collecting strategies for new users, the adaptation framework including supervised and unsupervised adaptation methods is proposed. For supervised adaptation, affinity propagation (AP) is used to extract exemplar subsets, and enhanced maximum a posteriori / vector field smoothing (eMAP/VFS) is proposed to pool the adaptation data among different models. For unsupervised adaptation, polynomial segment models (PSMs) are used to help hidden Markov models (HMMs) to accurately label the unlabeled data, then the "labeled" data together with signerindependent models are inputted to MAP algorithm to generate signer-adapted models. Experimental results show that the proposed framework can execute both supervised adaptation with small amount of labeled data and unsupervised adaptation with large amount of unlabeled data to tailor the original models, and both achieve improvements on the performance of recognition rate.

Keywords: sign language recognition, signer adaptation, eMAP/VFS, polynomial segment model.

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Authors: Jawairia Umar, Tanveer Hussain, Zulfiqar Ali, Muhammad Maqsood

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Different knitted structures and knitted parameters play a vital role in the stretch and recovery management of compression sportswear in addition to the materials use to generate this stretch and recovery behavior of the fabric. The present work was planned to predict the different performance indicators of a compression sportswear fabric with some ground parameters i.e. base yarn stitch length (polyester as base yarn and spandex as plating yarn involve to make a compression fabric) and linear density of the spandex which is a key material of any sportswear fabric. The prediction models were generated by response surface method for performance indicators such as stretch & recovery percentage, compression generated by the garment on body, total elongation on application of high power force and load generated on certain percentage extension in fabric. Certain physical properties of the fabric were also modeled using these two parameters.

Keywords: Compression, sportswear, stretch and recovery, statistical model, kikuhime.

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Authors: Toshihiko Sasama, Takahide Yanaka, Kazunori Sugahara, Hiroshi Masuyama

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In order to monitor for traffic traversal, sensors can be deployed to perform collaborative target detection. Such a sensor network achieves a certain level of detection performance with the associated costs of deployment and routing protocol. This paper addresses these two points of sensor deployment and routing algorithm in the situation where the absolute quantity of sensors or total energy becomes insufficient. This discussion on the best deployment system concluded that two kinds of deployments; Normal and Power law distributions, show 6 and 3 times longer than Random distribution in the duration of coverage, respectively. The other discussion on routing algorithm to achieve good performance in each deployment system was also addressed. This discussion concluded that, in place of the traditional algorithm, a new algorithm can extend the time of coverage duration by 4 times in a Normal distribution, and in the circumstance where every deployed sensor operates as a binary model.

Keywords: binary sensor, coverage rate, power energy consumption, routing algorithm, sensor deployment

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Authors: P. Kumsawat, N. Pimpru, K. Attakitmongcol, A.Srikaew

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In this paper, we proposed an efficient data compression strategy exploiting the multi-resolution characteristic of the wavelet transform. We have developed a sensor node called “Smart Sensor Node; SSN". The main goals of the SSN design are lightweight, minimal power consumption, modular design and robust circuitry. The SSN is made up of four basic components which are a sensing unit, a processing unit, a transceiver unit and a power unit. FiOStd evaluation board is chosen as the main controller of the SSN for its low costs and high performance. The software coding of the implementation was done using Simulink model and MATLAB programming language. The experimental results show that the proposed data compression technique yields recover signal with good quality. This technique can be applied to compress the collected data to reduce the data communication as well as the energy consumption of the sensor and so the lifetime of sensor node can be extended.

Keywords: Wireless sensor network, wavelet transform, data compression, ZigBee, skipped high-pass sub-band.

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Authors: Anju Shri, Parvinder S. Sandhu, Vikas Gupta, Sanyam Anand

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In literature, there are metrics for identifying the quality of reusable components but the framework that makes use of these metrics to precisely predict reusability of software components is still need to be worked out. These reusability metrics if identified in the design phase or even in the coding phase can help us to reduce the rework by improving quality of reuse of the software component and hence improve the productivity due to probabilistic increase in the reuse level. As CK metric suit is most widely used metrics for extraction of structural features of an object oriented (OO) software; So, in this study, tuned CK metric suit i.e. WMC, DIT, NOC, CBO and LCOM, is used to obtain the structural analysis of OO-based software components. An algorithm has been proposed in which the inputs can be given to K-Means Clustering system in form of tuned values of the OO software component and decision tree is formed for the 10-fold cross validation of data to evaluate the in terms of linguistic reusability value of the component. The developed reusability model has produced high precision results as desired.

Keywords: CK-Metric, Desicion Tree, Kmeans, Reusability.

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Authors: Wajid A. Chishty, Stephen D. Lepera, Uri Vandsburger

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Thermoacoustic instabilities in combustors have remained a topic of investigation for over a few decades due to the challenges it posses to the operation of low emission gas turbines. For combustors burning liquid fuel, understanding the cause-andeffect relationship between spray combustion dynamics and thermoacoustic oscillations is imperative for the successful development of any control methodology for its mitigation. The paper presents some very unique operating characteristics of a kerosene-fueled diffusion type combustor undergoing limit-cycle oscillations. Combustor stability limits were mapped using three different-sized injectors. The results show that combustor instability depends on the characteristics of the fuel spray. A simple analytic analysis is also reported in support of a plausible explanation for the unique combustor behavior. The study indicates that high amplitude acoustic pressure in the combustor may cause secondary breakdown of fuel droplets resulting in premixed pre-vaporized type burning of the diffusion type combustor.

Keywords: Secondary droplet breakup, Spray dynamics, Taylor Analogy Breakup Model, Thermoacoustic instabilities.

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Authors: Pei-Chun Lee, Sheng-Shih Wang, Pei-Hsuan Ku

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Many existing amusement parks have been operated with assistance of a variety of information and communications technologies to design friendly and efficient service systems for tourists. However, these systems leave various levels of decisions to tourists to make by themselves. This incurs pressure on tourists and thereby bringing negative experience in their tour. This paper proposes a smart amusement park system to offer each tourist the GPS-based customized plan without tourists making decisions by themselves. The proposed system consists of the mobile app subsystem, the central subsystem, and the detecting/counting subsystem. The mobile app subsystem interacts with the central subsystem. The central subsystem performs the necessary computing and database management of the proposed system. The detecting/counting subsystem aims to detect and compute the number of visitors to an attraction. Experimental results show that the proposed system can not only work well, but also provide an innovative business operating model for owners of amusement parks.

Keywords: Amusement park, location-based service (LBS), mobile app, tourist service.

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Authors: Noman Khan, B. S. Chowdhry, A.Q.K Rajput

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Integrated fiber-wireless (FiWi) access networks are a viable solution that can deliver the high profile quadruple play services. Passive optical networks (PON) networks integrated with wireless access networks provide ubiquitous characteristics for high bandwidth applications. Operation of PON improves by employing a variety of multiplexing techniques. One of it is time division/wavelength division multiplexed (TDM/WDM) architecture that improves the performance of optical-wireless access networks. This paper proposes a novel feedback-based TDM/WDM-PON architecture and introduces a model of integrated PON-FiWi networks. Feedback-based link architecture is an efficient solution to improves the performance of optical-line-terminal (OLT) and interlink optical-network-units (ONUs) communication. Furthermore, the feedback-based WDM/TDM-PON architecture is compared with existing architectures in terms of capacity of network throughput.

Keywords: Fiber-wireless (FiWi), Passive Optical Network (PON), TDM/WDM architecture

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Authors: Sharmina Begum, M. G. Rasul, Delwar Akbar

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Solid waste can be considered as an urban burden or as a valuable resource depending on how it is managed. To meet the rising demand for energy and to address environmental concerns, a conversion from conventional energy systems to renewable resources is essential. For the sustainability of human civilization, an environmentally sound and techno-economically feasible waste treatment method is very important to treat recyclable waste. Several technologies are available for realizing the potential of solid waste as an energy source, ranging from very simple systems for disposing of dry waste to more complex technologies capable of dealing with large amounts of industrial waste. There are three main pathways for conversion of waste material to energy: thermo chemical, biochemical and physicochemical. This paper investigates the thermo chemical conversion of solid waste for energy recovery. The processes, advantages and dis-advantages of various thermo chemical conversion processes are discussed and compared. Special attention is given to Gasification process as it provides better solutions regarding public acceptance, feedstock flexibility, near-zero emissions, efficiency and security. Finally this paper presents comparative statements of thermo chemical processes and introduces an integrated waste management system.

Keywords: Gasification, Incineration, Pyrolysis, Thermo chemical conversion.

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Authors: B. Singh, K. K. Agrawal, B. K. Nanda

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In built-up structures, one of the effective ways of dissipating unwanted vibration is to exploit the occurrence of slip at the interfaces of structural laminates. The present work focuses on the dynamic analysis of welded structures. A mathematical formulation has been developed for the mechanism of slip damping in layered and welded mild steel beams with unequal thickness subjected to both periodic and non-periodic forces. It is observed that a number of vital parameters such as; thickness ratio, pressure distribution characteristics, relative slip and kinematic co-efficient of friction at the interfaces, nature of exciting forces, length and thickness of the beam specimen govern the damping characteristics of these structures. Experimental verification has been carried out to validate the analysis and study the effect of these parameters. The developed damping model for the structure is found to be in fairly good agreement with the measured data. Finally, the results of the analysis are discussed and rationalized.

Keywords: Slip damping, tack welded joint, thickness ratio, inplane bending stress

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Authors: M. S. Razana, Z. W. Shafiuddin

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Internal auditing is one of the most important activities for organizations that implement information security management systems (ISMS). The purpose of internal audits is to ensure the ISMS implementation is in accordance to the ISO/IEC 27001 standard and the organization’s own requirements for its ISMS. Competent internal auditors are the main element that contributes to the effectiveness of internal auditing activities. To realize this need, CyberSecurity Malaysia is now in the process of becoming a certification body that certifies ISMS internal auditors. The certification scheme will assess the competence of internal auditors in generic knowledge and skills in management systems, and also in ISMS-specific knowledge and skills. The certification assessment is based on the ISO/IEC 19011 Guidelines for auditing management systems, ISO/IEC 27007 Guidelines for information security management systems auditing and ISO/IEC 27001 Information security management systems requirements. The certification scheme complies with the ISO/IEC 17024 General requirements for bodies operating certification systems of persons. Candidates who pass the exam will be certified as an ISMS Internal Auditor, whose competency will be evaluated every three years.

Keywords: ISMS internal audit, ISMS internal auditor, ISO/IEC 17024, Competence, Certification.

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Authors: Simeon Karafolas, Maciej Woźniak

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Mostly of public financing programs at national and regional level are funded from European Union sources. EU can participate directly to a national and regional program (example LEADER initiative, URBAN…) or indirectly by funding regional or national funds.Funds from European Union are provided from EU multiannual financial framework form which the annual budget is programmed. The adjusted program 2007-2013 of the EU considered commitments of almost 1 trillion Euros for the EU-28 countries. Provisions of the new program 2014-2020 consider commitments of more than 1 trillion Euros. Sustainable growth, divided to Cohesion and Competitiveness for Growth an Employment, is one of the two principal categories; the other is the preservation and management of natural resources.Through this financing process SMEs benefited of EU and public sources by receiving grants for their investments. Most of the financial instruments are available indirectly through the national financial intermediaries. Part of them is managed by the European Investment Fund.The paper focuses on the public financing to SMEs by examining case studies on divers forms of public help. It tries to distinguish the efficiency of the examined good practices and therefore try to have some conclusions on the possibility of application to other regions.

Keywords: DIFASS, financing, grants, SMEs.

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Authors: Sh. Yasini, M. B. Naghibi-Sistani, A. Karimpour

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This paper employs a new approach to regulate the blood glucose level of type I diabetic patient under an intensive insulin treatment. The closed-loop control scheme incorporates expert knowledge about treatment by using reinforcement learning theory to maintain the normoglycemic average of 80 mg/dl and the normal condition for free plasma insulin concentration in severe initial state. The insulin delivery rate is obtained off-line by using Qlearning algorithm, without requiring an explicit model of the environment dynamics. The implementation of the insulin delivery rate, therefore, requires simple function evaluation and minimal online computations. Controller performance is assessed in terms of its ability to reject the effect of meal disturbance and to overcome the variability in the glucose-insulin dynamics from patient to patient. Computer simulations are used to evaluate the effectiveness of the proposed technique and to show its superiority in controlling hyperglycemia over other existing algorithms

Keywords: Insulin Delivery rate, Q-learning algorithm, Reinforcement learning, Type I diabetes.

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Authors: Michaela Chovancova, Jakub Elcner

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Real bronchial tree is very complicated piping system. Analysis of flow and pressure losses in this system is very difficult. Due to the complex geometry and the very small size in the lower generations is examination by CFD possible only in the central part of bronchial tree. For specify the pressure losses of lower generations is necessary to provide a mathematical equation. Determination of mathematical formulas for calculation of pressure losses in the real lungs is time consuming and inefficient process due to its complexity and diversity. For these calculations is necessary to slightly simplify the geometry of lungs (same cross-section over the length of individual generation) or use one of the idealized models of lungs (Horsfield, Weibel). The article compares the values of pressure losses obtained from CFD simulation of air flow in the central part of the real bronchial tree with the values calculated in a slightly simplified real lungs by using a mathematical relationship derived from the Bernoulli and continuity equations. The aim of the article is to analyse the accuracy of the analytical method and its possibility of use for the calculation of pressure losses in lower generations, which is difficult to solve by numerical method due to the small geometry.

Keywords: Pressure gradient, airways resistance, real geometry of bronchial tree, breathing.

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Authors: C. Murat, T. Elifnaz

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Today, with globalization, human mobility has increased the interaction between countries significantly, and this contact has also increased the possibility of epidemics, although this contact has moved societies forward in terms of civilization. The coronavirus (COVID-19) epidemic, which caused the most loss of life from these epidemics, quickly swept the whole world with the effect of globalization. The coronavirus epidemic has affected the world economically as well as health problems. While some businesses around the world experienced an extraordinary increase in demand, some businesses temporarily stopped their activities or were forced to do so. Businesses affected by the crisis had to adapt to new legal regulations but had to make changes in matters such as working styles, human resources practices, and policies. One of the measures considered is the reduction of the workforce. The current COVID-19 crisis has created serious challenges for many organizations and has led to an unprecedented wave of termination notices. In this study, examples of companies that were affected by the pandemic process and changed their working policies after the pandemic were examined. This study aims to reveal the impact of the global COVID-19 epidemic on human resources policies and employees and how these situations will affect businesses in the future.

Keywords: COVID-19, human resource management, crisis management, business function.

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Authors: Kyogun Chang, Yoon Bok Lee

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Fault detection determines faultexistence and detecting time. This paper discusses two layered fault detection methods to enhance the reliability and safety. Two layered fault detection methods consist of fault detection methods of component level controllers and system level controllers. Component level controllers detect faults by using limit checking, model-based detection, and data-driven detection and system level controllers execute detection by stability analysis which can detect unknown changes. System level controllers compare detection results via stability with fault signals from lower level controllers. This paper addresses fault detection methods via stability and suggests fault detection criteria in nonlinear systems. The fault detection method applies tothe hybrid control unit of a military hybrid electric vehicleso that the hybrid control unit can detect faults of the traction motor.

Keywords: Two Layered Fault Detection, Stability Analysis, Fault-Tolerant Control

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Authors: Hojjat Saberinejad, Adel Hashiehbaf, Ehsan Afrasiabian

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Among the various cooling processes in industrial applications such as: electronic devices, heat exchangers, gas turbines, etc. Gas turbine blades cooling is the most challenging one. One of the most common practices is using ribbed wall because of the boundary layer excitation and therefore making the ultimate cooling. Vortex formation between rib and channel wall will result in a complicated behavior of flow regime. At the other hand, selecting the most efficient method for capturing the best results comparing to experimental works would be a fascinating issue. In this paper 4 common methods in turbulence modeling: standard k-e, rationalized k-e with enhanced wall boundary layer treatment, k-w and RSM (Reynolds stress model) are employed to a square ribbed channel to investigate the separation and thermal behavior of the flow in the channel. Finally all results from different methods which are used in this paper will be compared with experimental data available in literature to ensure the numerical method accuracy.

Keywords: boundary layer, turbulence, numerical method, rib cooling

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Authors: S. Cherif, M. Turki-Hadj Alouane

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In this paper, we propose a modified version of the Constant Modulus Algorithm (CMA) tailored for blind Decision Feedback Equalizer (DFE) of first order Markovian time varying channels. The proposed NonStationary CMA (NSCMA) is designed so that it explicitly takes into account the Markovian structure of the channel nonstationarity. Hence, unlike the classical CMA, the NSCMA is not blind with respect to the channel time variations. This greatly helps the equalizer in the case of realistic channels, and avoids frequent transmissions of training sequences. This paper develops a theoretical analysis of the steady state performance of the CMA and the NSCMA for DFEs within a time varying context. Therefore, approximate expressions of the mean square errors are derived. We prove that in the steady state, the NSCMA exhibits better performance than the classical CMA. These new results are confirmed by simulation. Through an experimental study, we demonstrate that the Bit Error Rate (BER) is reduced by the NSCMA-DFE, and the improvement of the BER achieved by the NSCMA-DFE is as significant as the channel time variations are severe.

Keywords: Time varying channel, Markov model, Blind DFE, CMA, NSCMA.

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Authors: H. Hosseini, M. Javadi, M. Moghiman, M. H. Ghodsi Rad

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Carbon disulfide is widely used for the production of viscose rayon, rubber, and other organic materials and it is a feedstock for the synthesis of sulfuric acid. The objective of this paper is to analyze possibilities for efficient production of CS2 from sour natural gas reformation (H2SMR) (2H2S+CH4 =CS2 +4H2) . Also, the effect of H2S to CH4 feed ratio and reaction temperature on carbon disulfide production is investigated numerically in a reforming reactor. The chemical reaction model is based on an assumed Probability Density Function (PDF) parameterized by the mean and variance of mixture fraction and β-PDF shape. The results show that the major factors influencing CS2 production are reactor temperature. The yield of carbon disulfide increases with increasing H2S to CH4 feed gas ratio (H2S/CH4≤4). Also the yield of C(s) increases with increasing temperature until the temperature reaches to 1000°K, and then due to increase of CS2 production and consumption of C(s), yield of C(s) drops with further increase in the temperature. The predicted CH4 and H2S conversion and yield of carbon disulfide are in good agreement with result of Huang and TRaissi.

Keywords: Carbon disulfide, sour natural gas, H2SMR, probability density function.

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Authors: Amir-Massoud Bidgoli, Mehdi Naseri Parsa

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In this paper a combined feature selection method is proposed which takes advantages of sample domain filtering, resampling and feature subset evaluation methods to reduce dimensions of huge datasets and select reliable features. This method utilizes both feature space and sample domain to improve the process of feature selection and uses a combination of Chi squared with Consistency attribute evaluation methods to seek reliable features. This method consists of two phases. The first phase filters and resamples the sample domain and the second phase adopts a hybrid procedure to find the optimal feature space by applying Chi squared, Consistency subset evaluation methods and genetic search. Experiments on various sized datasets from UCI Repository of Machine Learning databases show that the performance of five classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First Decision Tree and JRIP) improves simultaneously and the classification error for these classifiers decreases considerably. The experiments also show that this method outperforms other feature selection methods.

Keywords: feature selection, resampling, reliable features, Consistency Subset Evaluation.

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Authors: Li Shoutao, Gordon Lee

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Evolutionary robotics is concerned with the design of intelligent systems with life-like properties by means of simulated evolution. Approaches in evolutionary robotics can be categorized according to the control structures that represent the behavior and the parameters of the controller that undergo adaptation. The basic idea is to automatically synthesize behaviors that enable the robot to perform useful tasks in complex environments. The evolutionary algorithm searches through the space of parameterized controllers that map sensory perceptions to control actions, thus realizing a specific robotic behavior. Further, the evolutionary algorithm maintains and improves a population of candidate behaviors by means of selection, recombination and mutation. A fitness function evaluates the performance of the resulting behavior according to the robot-s task or mission. In this paper, the focus is in the use of genetic algorithms to solve a multi-objective optimization problem representing robot behaviors; in particular, the A-Compander Law is employed in selecting the weight of each objective during the optimization process. Results using an adaptive fitness function show that this approach can efficiently react to complex tasks under variable environments.

Keywords: adaptive fuzzy neural inference, evolutionary tuning

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Authors: F. Rahimi Dehgolan, S. E. Khadem, S. Bab, M. Najafee

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Nowadays, using rotating systems like shafts and disks in industrial machines have been increased constantly. Dynamic stability is one of the most important factors in designing rotating systems. In this study, linear frequencies and stability of a coupled continuous flexible rotor-disk-blades system are studied. The Euler-Bernoulli beam theory is utilized to model the blade and shaft. The equations of motion are extracted using the extended Hamilton principle. The equations of motion have been simplified using the Coleman and complex transformations method. The natural frequencies of the linear part of the system are extracted, and the effects of various system parameters on the natural frequencies and decay rates (stability condition) are clarified. It can be seen that the centrifugal stiffening effect applied to the blades is the most important parameter for stability of the considered rotating system. This result highlights the importance of considering this stiffing effect in blades equation.

Keywords: Rotating shaft, flexible blades, centrifugal stiffening, stability.

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Authors: R. B. Knudsen, O. T. Rasmussen, R. A. Alphinas

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The reason for conducting this research is to develop an algorithm that is capable of classifying news articles from the automobile industry, according to the competitive actions that they entail, with the use of Text Mining (TM) methods. It is needed to test how to properly preprocess the data for this research by preparing pipelines which fits each algorithm the best. The pipelines are tested along with nine different classification algorithms in the realm of regression, support vector machines, and neural networks. Preliminary testing for identifying the optimal pipelines and algorithms resulted in the selection of two algorithms with two different pipelines. The two algorithms are Logistic Regression (LR) and Artificial Neural Network (ANN). These algorithms are optimized further, where several parameters of each algorithm are tested. The best result is achieved with the ANN. The final model yields an accuracy of 0.79, a precision of 0.80, a recall of 0.78, and an F1 score of 0.76. By removing three of the classes that created noise, the final algorithm is capable of reaching an accuracy of 94%.

Keywords: Artificial neural network, competitive dynamics, logistic regression, text classification, text mining.

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Authors: Mohamed A. G. H. Abdalsadig, Amir Nourian, G. G. Nasr, Meisam Babaie

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Gas lift optimization is becoming more important now a day in petroleum industry. A proper lift optimization can reduce the operating cost, increase the net present value (NPV) and maximize the recovery from the asset. A widely accepted definition of gas lift optimization is to obtain the maximum output under specified operating conditions. In addition, gas lift, a costly and indispensable means to recover oil from high depth reservoir entails solving the gas lift optimization problems. Gas lift optimization is a continuous process; there are two levels of production optimization. The total field optimization involves optimizing the surface facilities and the injection rate that can be achieved by standard tools softwares. Well level optimization can be achieved by optimizing the well parameters such as point of injection, injection rate, and injection pressure. All these aspects have been investigated and presented in this study by using experimental data and PROSPER simulation program. The results show that the well head pressure has a large influence on the gas lift performance and also proved that smart gas lift valve can be used to improve gas lift performance by controlling gas injection from down hole. Obtaining the optimum gas injection rate is important because excessive gas injection reduces production rate and consequently increases the operation cost.

Keywords: Optimization, production rate, reservoir pressure effect, gas injection rate effect, gas injection pressure.

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Authors: S. Sarumathi, P. Ranjetha, C. Saraswathy, M. Vaishnavi, S. Geetha

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Clustering is an unsupervised learning technique for aggregating data objects into meaningful classes so that intra cluster similarity is maximized and inter cluster similarity is minimized in data mining. However, no single clustering algorithm proves to be the most effective in producing the best result. As a result, a new challenging technique known as the cluster ensemble approach has blossomed in order to determine the solution to this problem. For the cluster analysis issue, this new technique is a successful approach. The cluster ensemble's main goal is to combine similar clustering solutions in a way that achieves the precision while also improving the quality of individual data clustering. Because of the massive and rapid creation of new approaches in the field of data mining, the ongoing interest in inventing novel algorithms necessitates a thorough examination of current techniques and future innovation. This paper presents a comparative analysis of various cluster ensemble approaches, including their methodologies, formal working process, and standard accuracy and error rates. As a result, the society of clustering practitioners will benefit from this exploratory and clear research, which will aid in determining the most appropriate solution to the problem at hand.

Keywords: Clustering, cluster ensemble methods, consensus function, data mining, unsupervised learning.

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: Drought index, climatic projections, precipitation of the Uruguay River Basin, Standardized Precipitation Index.

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Authors: Mat Syai'in, Adi Soeprijanto, Takashi Hiyama

Abstract:

An optimal power flow (OPF) based on particle swarm optimization (PSO) was developed with more realistic generator security constraint using the capability curve instead of only Pmin/Pmax and Qmin/Qmax. Neural network (NN) was used in designing digital capability curve and the security check algorithm. The algorithm is very simple and flexible especially for representing non linear generation operation limit near steady state stability limit and under excitation operation area. In effort to avoid local optimal power flow solution, the particle swarm optimization was implemented with enough widespread initial population. The objective function used in the optimization process is electric production cost which is dominated by fuel cost. The proposed method was implemented at Java Bali 500 kV power systems contain of 7 generators and 20 buses. The simulation result shows that the combination of generator power output resulted from the proposed method was more economic compared with the result using conventional constraint but operated at more marginal operating point.

Keywords: Optimal Power Flow, Generator Capability Curve, Particle Swarm Optimization, Neural Network

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