Search results for: performance parameters

Authors: Thaniya Kaosol, Sirinthrar Wandee

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In this research, an aerobic composting method is studied to reuse organic waste from rubber factory waste as soil fertilizer and to study the effect of cellulolytic microbial activator (CMA) as the activator in the rubber factory waste composting. The performance of the composting process was monitored as a function of carbon and organic matter decomposition rate, temperature and moisture content. The results indicate that the rubber factory waste is best composted with water hyacinth and sludge than composted alone. In addition, the CMA is more affective when mixed with the rubber factory waste, water hyacinth and sludge since a good fertilizer is achieved. When adding CMA into the rubber factory waste composted alone, the finished product does not achieve a standard of fertilizer, especially the C/N ratio. Finally, the finished products of composting rubber factory waste and water hyacinth and sludge (both CMA and without CMA), can be an environmental friendly alternative to solve the disposal problems of rubber factory waste. Since the C/N ratio, pH, moisture content, temperature, and nutrients of the finished products are acceptable for agriculture use.

Keywords: composting, rubber waste, C/N ratio, sludge, cellulolytic microbial activator

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Authors: Jazaul Ikhsan, Masaharu Fujita

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Safety, river environment, and sediment utilization are the elements of the target of sediment management. As a change in an element by sediment management, may affect the other two elements, and the priority among three elements depends on stakeholders. It is necessary to develop a method to evaluate the effect of sediment management on each element and an integrated evaluation method for socio-economic effect. In this study, taking Mount Merapi basin as an investigation field, the method for an active volcanic basin was developed. An integrated evaluation method for sediment management was discussed from a socio-economic point on safety, environment, and sediment utilization and a case study of sediment management was evaluated by means of this method. To evaluate the effect of sediment management, some parameters on safety, utilization, and environment have been introduced. From a utilization point of view, job opportunity, additional income of local people, and tax income to local government were used to evaluate the effectiveness of sediment management. The risk degree of river infrastructure was used to describe the effect of sediment management on a safety aspect. To evaluate the effects of sediment management on environment, the mean diameter of grain size distribution of riverbed surface was used. On the coordinate system designating these elements, the direction of change in basin condition by sediment management can be predicted, so that the most preferable sediment management can be decided. The results indicate that the cases of sediment management tend to give the negative impacts on sediment utilization. However, these sediment managements will give positive impacts on safety and environment condition. Evaluation result from a social-economic point of view shows that the case study of sediment management reduces job opportunity and additional income for inhabitants as well as tax income for government. Therefore, it is necessary to make another policy for creating job opportunity for inhabitants to support these sediment managements.

Keywords: Merapi, sediment, management, evaluation

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Authors: Kittisak Kerdprasop, Nittaya Kerdprasop

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The problem of frequent pattern discovery is defined as the process of searching for patterns such as sets of features or items that appear in data frequently. Finding such frequent patterns has become an important data mining task because it reveals associations, correlations, and many other interesting relationships hidden in a database. Most of the proposed frequent pattern mining algorithms have been implemented with imperative programming languages. Such paradigm is inefficient when set of patterns is large and the frequent pattern is long. We suggest a high-level declarative style of programming apply to the problem of frequent pattern discovery. We consider two languages: Haskell and Prolog. Our intuitive idea is that the problem of finding frequent patterns should be efficiently and concisely implemented via a declarative paradigm since pattern matching is a fundamental feature supported by most functional languages and Prolog. Our frequent pattern mining implementation using the Haskell and Prolog languages confirms our hypothesis about conciseness of the program. The comparative performance studies on line-of-code, speed and memory usage of declarative versus imperative programming have been reported in the paper.

Keywords: Frequent pattern mining, functional programming, pattern matching, logic programming.

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Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

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Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr₂O₃), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr₂O₃, FeO, Al₂O₃ and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr₂O₃) was reduced at 1200 ⁰C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 ⁰C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: Apparent porosity, beneficiation, low grade chromite, refractory, spinel compounds, slag resistance.

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an ‘optimal’ value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: Cross Validation, Parameter Averaging, Parameter Selection, Regularization Parameter Search.

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Authors: Roy R. Gu, Mahesh Sahu, Xianggui Zhao

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Contour filter strips planted with perennial vegetation can be used to improve surface and ground water quality by reducing pollutant, such as NO3-N, and sediment outflow from cropland to a river or lake. Meanwhile, the filter strips of perennial grass with biofuel potentials also have economic benefits of producing ethanol. In this study, The Soil and Water Assessment Tool (SWAT) model was applied to the Walnut Creek Watershed to examine the effectiveness of contour strips in reducing NO3-N outflows from crop fields to the river or lake. Required input data include watershed topography, slope, soil type, land-use, management practices in the watershed and climate parameters (precipitation, maximum/minimum air temperature, solar radiation, wind speed and relative humidity). Numerical experiments were conducted to identify potential subbasins in the watershed that have high water quality impact, and to examine the effects of strip size and location on NO3-N reduction in the subbasins under various meteorological conditions (dry, average and wet). Variable sizes of contour strips (10%, 20%, 30% and 50%, respectively, of a subbasin area) planted with perennial switchgrass were selected for simulating the effects of strip size and location on stream water quality. Simulation results showed that a filter strip having 10%-50% of the subbasin area could lead to 55%- 90% NO3-N reduction in the subbasin during an average rainfall year. Strips occupying 10-20% of the subbasin area were found to be more efficient in reducing NO3-N when placed along the contour than that when placed along the river. The results of this study can assist in cost-benefit analysis and decision-making in best water resources management practices for environmental protection.

Keywords: modeling, SWAT, water quality, NO3-N, watershed.

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Authors: Yehia A. Eldrainy, Hossam S. Aly, Khalid M. Saqr, Mohammad Nazri Mohd Jaafar

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The central recirculation zone (CRZ) in a swirl stabilized gas turbine combustor has a dominant effect on the fuel air mixing process and flame stability. Most of state of the art swirlers share one disadvantage; the fixed swirl number for the same swirler configuration. Thus, in a mathematical sense, Reynolds number becomes the sole parameter for controlling the flow characteristics inside the combustor. As a result, at low load operation, the generated swirl is more likely to become feeble affecting the flame stabilization and mixing process. This paper introduces a new swirler concept which overcomes the mentioned weakness of the modern configurations. The new swirler introduces air tangentially and axially to the combustor through tangential vanes and an axial vanes respectively. Therefore, it provides different swirl numbers for the same configuration by regulating the ratio between the axial and tangential flow momenta. The swirler aerodynamic performance was investigated using four CFD simulations in order to demonstrate the impact of tangential to axial flow rate ratio on the CRZ. It was found that the length of the CRZ is directly proportional to the tangential to axial air flow rate ratio.

Keywords: Swirler, Gas turbine, CFD, Numerical simulation, Recirculation zone, Swirl number

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Authors: S. Padma, Dr. R. Lakshmipathi, K. Ramash Kumar, P. Nandagopal

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The power system network is becoming more complex nowadays and it is very difficult to maintain the stability of the system. Today-s enhancement of technology makes it possible to include new energy storage devices in the electric power system. In addition, with the aid of power electronic devices, it is possible to independently exchange active and reactive power flow with the utility grid. The main purpose of this paper proposes a Proportional – Integral (PI) control based 48 – pulse Inverter based Static Synchronous Series Compensator (SSSC) with and without Superconducting Magnetic Energy Storage (SMES) used for enhancing the transient stability and regulating power flow in automatic mode. Using a test power system through the dynamic simulation in Matlab/Simulink platform validates the performance of the proposed SSSC with and without SMES system.

Keywords: Flexible AC transmission system (FACTS), PIControl, Superconducting Magnetic Energy Storage (SMES), Static Synchronous Series Compensator (SSSC).

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Authors: Akhtar N, Khan BA, Khan MS, Mahmood T, Khan HMS, Iqbal M, Bashir S

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This study was designed to formulate, pharmaceutically evaluate a topical skin-care cream (w/o emulsion) of Aloe Vera versus its vehicle (Base) as control and determine their effects on Stratum Corneum (SC) water content and Transepidermal water loss (TEWL). Base containing no extract and a Formulation containing 3% concentrated extract of Aloe Vera was developed by entrapping in the inner aqueous phase of w/o emulsion (cream). Lemon oil was incorporated to improve the odor. Both the Base and Formulation were stored at 8°C ±0.1°C (in refrigerator), 25°C±0.1°C, 40°C±0.1°C and 40°C± 0.1°C with 75% RH (in incubator) for a period of 4 weeks to predict their stability. The evaluation parameters consisted of color, smell, type of emulsion, phase separation, electrical conductivity, centrifugation, liquefaction and pH. Both the Base and Formulation were applied to the cheeks of 21 healthy human volunteers for a period of 8 weeks Stratum corneum (SC) water content and Transepidermal water loss (TEWL) were monitored every week to measure any effect produced by these topical creams. The expected organoleptic stability of creams was achieved from 4 weeks in-vitro study period. Odor was disappeared with the passage of time due to volatilization of lemon oil. Both the Base and Formulation produced significant (p≤0.05) changes in TEWL with respect to time. SC water content was significantly (p≤0.05) increased by the Formulation while the Base has insignificant (p 0.05) effects on SC water content. The newly formulated cream of Aloe Vera, applied is suitable for improvement and quantitative monitoring of skin hydration level (SC water content/ moisturizing effects) and reducing TEWL in people with dry skin.

Keywords: Aloe Vera; Skin; Stratum corneum (SC) water content and Transepidermal water loss (TEWL).

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Authors: Ly. Benbahouche

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Currently, several soft switching topologies have been studied to achieve high power switching efficiency, reduced cost, improved reliability and reduced parasites. It is well known that improvement in power electronics systems always depend on advanced in power devices. The IGBT has been successfully used in a variety of switching applications such as motor drives and appliance control because of its superior characteristics.

The aim of this paper is focuses on simulation and explication of the internal dynamics of IGBTs behaviour under the most popular soft switching schemas that is Zero Current Switching (ZCS) environments.

The main purpose of this paper is to point out some mechanisms relating to current tail during the turn-off and examination of the response at turn-off with variation of temperature, inductance L, snubber capacitors Cs, and bus voltage in order to achieve an improved understanding of internal carrier dynamics. It is shown that the snubber capacitor, the inductance and even the temperature controls the magnitude and extent of the tail current, hence the turn-off time (switching speed of the device).

Moreover, it has also been demonstrated that the ZCS switching can be utilized efficiently to improve and reduce the power losses as well as the turn-off time. Furthermore, the turn-off loss in ZCS was found to depend on the time of switching of the device.

Keywords: PT-IGBT, ZCS, turn-off losses, dV/dt.

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Authors: Mansi Jhamb, R. K. Sharma, A. K. Gupta

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In the current scenario, with the increasing integration densities, most system-on-chip designs are partitioned into multiple clock domains. In this paper, an asynchronous FIFO (First-in First-out pipeline) design is employed as a data transfer interface between two independent clock domains. Since the clocks on the either sides of the FIFO run at a different speed, the task to ensure the correct data transmission through this FIFO is manually performed. Firstly an existing asynchronous FIFO design is discussed and simulated. Gate-level simulation results depicted the flaw in existing design. In order to solve this problem, a novel modified asynchronous FIFO design is proposed. The results obtained from proposed design are in perfect accordance with theoretical expectations. The proposed asynchronous FIFO design outperforms the existing design in terms of accuracy and speed. In order to evaluate the performance of the FIFO designs presented in this paper, the circuits were implemented in 0.24µ TSMC CMOS technology and simulated at 2.5V using HSpice (© Avant! Corporation). The layout design of the proposed FIFO is also presented.

Keywords: Asynchronous, Clock, CMOS, C-element, FIFO, Globally Asynchronous Locally Synchronous (GALS), HSpice.

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: Evolutionary Algorithms, Chemical Reaction Optimization, Traveling Salesman, Board Drilling.

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Authors: Fernanda M. Assef, Maria Teresinha A. Steiner

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The aim of this paper is to compare and discuss better classifier algorithm options for credit risk assessment by applying different Machine Learning techniques. Using records from a Brazilian financial institution, this study uses a database of 5,432 companies that are clients of the bank, where 2,600 clients are classified as non-defaulters, 1,551 are classified as defaulters and 1,281 are temporarily defaulters, meaning that the clients are overdue on their payments for up 180 days. For each case, a total of 15 attributes was considered for a one-against-all assessment using four different techniques: Artificial Neural Networks Multilayer Perceptron (ANN-MLP), Artificial Neural Networks Radial Basis Functions (ANN-RBF), Logistic Regression (LR) and finally Support Vector Machines (SVM). For each method, different parameters were analyzed in order to obtain different results when the best of each technique was compared. Initially the data were coded in thermometer code (numerical attributes) or dummy coding (for nominal attributes). The methods were then evaluated for each parameter and the best result of each technique was compared in terms of accuracy, false positives, false negatives, true positives and true negatives. This comparison showed that the best method, in terms of accuracy, was ANN-RBF (79.20% for non-defaulter classification, 97.74% for defaulters and 75.37% for the temporarily defaulter classification). However, the best accuracy does not always represent the best technique. For instance, on the classification of temporarily defaulters, this technique, in terms of false positives, was surpassed by SVM, which had the lowest rate (0.07%) of false positive classifications. All these intrinsic details are discussed considering the results found, and an overview of what was presented is shown in the conclusion of this study.

Keywords: Artificial Neural Networks, ANNs, classifier algorithms, credit risk assessment, logistic regression, machine learning, support vector machines.

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Authors: Liliana M. Marinelli, Cristina T. Varanese

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In the last few years, students from higher education have difficulties in grasping mathematical concepts which support physical matters, especially those in the first years of this education. Classical Physics teaching turns to be complex when students are not able to make use of mathematical tools which lead to the conceptual structure of Physics. When derivation and integration rules are not used or developed in parallel with other disciplines, the physical meaning that we attempt to convey turns to be complicated. Due to this fact, it could be of great use to see the Classical Mechanics from an axiomatic approach, where the correspondence rules give physical meaning, if we expect students to understand concepts clearly and accurately. Using the Minkowski point of view adapted to a two-dimensional space and time where vectors, matrices, and straight lines (worked from an affine space) give mathematical and physical rigorosity even when it is more abstract. An interesting option would be to develop the disciplinary contents from an axiomatic version which embraces the Classical Mechanics as a particular case of Relativistic Mechanics. The observation about the increase in the difficulties stated by students in the first years of education allows this idea to grow as a possible option to improve performance and understanding of the concepts of this subject.

Keywords: Axiom, classical physics, physical concepts, relativity.

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Authors: S. Boudali, A. M. Soliman, B. Abdulsalam, K. Ayed, D. E. Kerdal, S. Poncet

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This study investigates the potential of using crushed concrete as aggregates to produce green and sustainable concrete. Crushed concrete was sieved to powder fine recycled aggregate (PFRA) less than 80 µm and coarse recycled aggregates (CRA). Physical, mechanical, and microstructural properties for PFRA and CRA were evaluated. The effect of the additional rates of PFRA and CRA on strength development of recycled aggregate concrete (RAC) was investigated. Additionally, the characteristics of interfacial transition zone (ITZ) between cement paste and recycled aggregate were also examined. Results show that concrete mixtures made with 100% of CRA and 40% PFRA exhibited similar performance to that of the control mixture prepared with 100% natural aggregate (NA) and 40% natural pozzolan (NP). Moreover, concrete mixture incorporating recycled aggregate exhibited a slightly higher later compressive strength than that of the concrete with NA. This was confirmed by the very dense microstructure for concrete mixture incorporating recycled concrete aggregates compared to that of conventional concrete mixture.

Keywords: Compressive strength, recycled concrete aggregates, microstructure, interfacial transition zone, powder fine recycled aggregate.

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Authors: Ε. Giovanis

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The purpose of this paper is to present two different approaches of financial distress pre-warning models appropriate for risk supervisors, investors and policy makers. We examine a sample of the financial institutions and electronic companies of Taiwan Security Exchange (TSE) market from 2002 through 2008. We present a binary logistic regression with paned data analysis. With the pooled binary logistic regression we build a model including more variables in the regression than with random effects, while the in-sample and out-sample forecasting performance is higher in random effects estimation than in pooled regression. On the other hand we estimate an Adaptive Neuro-Fuzzy Inference System (ANFIS) with Gaussian and Generalized Bell (Gbell) functions and we find that ANFIS outperforms significant Logit regressions in both in-sample and out-of-sample periods, indicating that ANFIS is a more appropriate tool for financial risk managers and for the economic policy makers in central banks and national statistical services.

Keywords: ANFIS, Binary logistic regression, Financialdistress, Panel data

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Authors: Ibrahim Gomaa, Hoda M. O. Mokhtar

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Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Keywords: Continuous query processing, dynamic database, moving object, skyline queries.

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Authors: Bachir Bentouati, Lakhdar Chaib, Saliha Chettih, Gai-Ge Wang

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The problem of economic dispatch (ED) is the basic problem of power framework, its main goal is to find the most favorable generation dispatch to generate each unit, reduce the whole power generation cost, and meet all system limitations. A heuristic algorithm, recently developed called Stud Krill Herd (SKH), has been employed in this paper to treat non-convex ED problems. The proposed KH has been modified using Stud selection and crossover (SSC) operator, to enhance the solution quality and avoid local optima. We are demonstrated SKH effects in two case study systems composed of 13-unit and 40-unit test systems to verify its performance and applicability in solving the ED problems. In the above systems, SKH can successfully obtain the best fuel generator and distribute the load requirements for the online generators. The results showed that the use of the proposed SKH method could reduce the total cost of generation and optimize the fulfillment of the load requirements.

Keywords: Stud Krill Herd, economic dispatch, crossover, stud selection, valve-point effect.

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Authors: Joaquin Navarro Perales, Ana Lidia Franzoni Velázquez, Francisco Cervantes Pérez

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The Mexican educational system faces diverse challenges related with the quality and coverage of education. The development of Intelligent Tutoring Systems (ITS) may help to solve some of them by helping teachers to customize their classes according to the performance of the students in online courses. In this work, we propose the adaptation of a functional ITS based on Bloom’s taxonomy called Sistema de Apoyo Generalizado para la Enseñanza Individualizada (SAGE), to measure student’s metacognition and their emotional response based on Marzano’s taxonomy. The students and the system will share the control over the advance in the course, so they can improve their metacognitive skills. The system will not allow students to get access to subjects not mastered yet. The interaction between the system and the student will be implemented through Natural Language Processing techniques, thus avoiding the use of sensors to evaluate student’s response. The teacher will evaluate student’s knowledge utilization, which is equivalent to the last cognitive level in Marzano’s taxonomy.

Keywords: Intelligent tutoring systems, student modelling, metacognition, affective computing, natural language processing.

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Authors: T. Kumar, Achinta Bera, Ajay Mandal

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Use of microemulsion in enhanced oil recovery has become more attractive in recent years because of its high level of extraction efficiency. Experimental investigations have been made on characterization of microemulsions of oil-brinesurfactant/ cosurfactant system for its use in enhanced oil recovery (EOR). Sodium dodecyl sulfate, propan-1-ol and heptane were selected as surfactant, cosurfactant and oil respectively for preparation of microemulsion. The effects of salinity on the relative phase volumes and solubilization parameters have also been studied. As salinity changes from low to high value, phase transition takes place from Winsor I to Winsor II via Winsor III. Suitable microemulsion composition has been selected based on its stability and ability to reduce interfacial tension. A series of flooding experiments have been performed using the selected microemulsion. The flooding experiments were performed in a core flooding apparatus using uniform sand pack. The core holder was tightly packed with uniform sands (60-100 mesh) and saturated with brines of different salinities. It was flooded with the brine at 25 psig and the absolute permeability was calculated from the flow rate of the through sand pack. The sand pack was then flooded with the crude oil at 800 psig to irreducible water saturation. The initial water saturation was determined on the basis of mass balance. Waterflooding was conducted by placing the coreholder horizontally at a constant injection pressure at 200 pisg. After water flooding, when water-cut reached above 95%, around 0.5 pore volume (PV) of the above microemulsion slug was injected followed by chasing water. The experiments were repeated using different composition of microemulsion slug. The additional recoveries were calculated by material balance. Encouraging results with additional recovery more than 20% of original oil in place above the conventional water flooding have been observed.

Keywords: Microemulsion Flooding, Enhanced Oil Recovery, Phase Behavior, Optimal salinity

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Authors: Amin Sedighfar, M. R. Moniri

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Determination of state of charge (SOC) in today’s world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the SOC estimation algorithm is expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and all of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate. 

Keywords: Kalman filter, neural networks, state-of-charge, VRLA battery.

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Authors: Suvradip Mullick, Yuvraj K. Madhukar, Subhranshu Roy, Ashish K. Nath

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We present the development of a new underwater laser cutting process in which a water-jet has been used along with the laser beam to remove the molten material through kerf. The conventional underwater laser cutting usually utilizes a high pressure gas jet along with laser beam to create a dry condition in the cutting zone and also to eject out the molten material. This causes a lot of gas bubbles and turbulence in water, and produces aerosols and waste gas. This may cause contamination in the surrounding atmosphere while cutting radioactive components like burnt nuclear fuel. The water-jet assisted underwater laser cutting process produces much less turbulence and aerosols in the atmosphere. Some amount of water vapor bubbles is formed at the laser-metal-water interface; however, they tend to condense as they rise up through the surrounding water. We present the design and development of a water-jet assisted underwater laser cutting head and the parametric study of the cutting of AISI 304 stainless steel sheets with a 2 kW CW fiber laser. The cutting performance is similar to that of the gas assist laser cutting; however, the process efficiency is reduced due to heat convection by water-jet and laser beam scattering by vapor. This process may be attractive for underwater cutting of nuclear reactor components.

Keywords: Laser, underwater cutting, water-jet.

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Authors: Dawid Stawski, Silviya Halacheva, Dorota Zielińska

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The surface properties of many materials can be readily and predictably modified by the controlled deposition of thin layers containing appropriate functional groups and this research area is now a subject of widespread interest. The layer-by-layer (lbl) method involves depositing oppositely charged layers of polyelectrolytes onto the substrate material which are stabilized due to strong electrostatic forces between adjacent layers. This type of modification affords products that combine the properties of the original material with the superficial parameters of the new external layers. Through an appropriate selection of the deposited layers, the surface properties can be precisely controlled and readily adjusted in order to meet the requirements of the intended application. In the presented paper a variety of anionic (poly(acrylic acid)) and cationic (linear poly(ethylene imine), polymers were successfully deposited onto the polypropylene nonwoven using the lbl technique. The chemical structure of the surface before and after modification was confirmed by reflectance FTIR spectroscopy, volumetric analysis and selective dyeing tests. As a direct result of this work, new materials with greatly improved properties have been produced. For example, following a modification process significant changes in the electrostatic activity of a range of novel nanocomposite materials were observed. The deposition of polyelectrolyte nanolayers was found to strongly accelerate the loss of electrostatically generated charges and to increase considerably the thermal resistance properties of the modified fabric (the difference in T50% is over 20oC). From our results, a clear relationship between the type of polyelectrolyte layer deposited onto the flat fabric surface and the properties of the modified fabric was identified.

Keywords: Layer-by-layer technique, polypropylene nonwoven, surface modification, surface properties.

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Authors: Lokesh Tharani, R.P.Yadav

Abstract:

This paper presents the results related to the interference reduction technique in multistage multiuser detector for asynchronous DS-CDMA system. To meet the real-time requirements for asynchronous multiuser detection, a bit streaming, cascade architecture is used. An asynchronous multiuser detection involves block-based computations and matrix inversions. The paper covers iterative-based suboptimal schemes that have been studied to decrease the computational complexity, eliminate the need for matrix inversions, decreases the execution time, reduces the memory requirements and uses joint estimation and detection process that gives better performance than the independent parameter estimation method. The stages of the iteration use cascaded and bits processed in a streaming fashion. The simulation has been carried out for asynchronous DS-CDMA system by varying one parameter, i.e., number of users. The simulation result exhibits that system gives optimum bit error rate (BER) at 3rd stage for 15-users.

Keywords: Multi-user detection (MUD), multiple accessinterference (MAI), near-far effect, decision feedback detector, successive interference cancellation detector (SIC) and parallelinterference cancellation (PIC) detector.

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Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

Abstract:

In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: Linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control.

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Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

Abstract:

Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

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Authors: Miroslava Šidlovská, Ida Petrovičová, Tomáš Pilka, Branislav Kolena

Abstract:

Phthalates are ubiquitous environmental pollutants well known because of their endocrine disrupting activity in human organism. The aim of our study was, by biological monitoring, investigate exposure to phthalates of Roma ethnicity group i.e. children and adults from 5 families (n=29, average age 11.8 ± 7.6 years) living in western Slovakia. Additionally, we analysed some associations between anthropometric measures, questionnaire data i.e. socio-economic status, eating and drinking habits, practise of personal care products and household conditions in comparison with concentrations of phthalate metabolites. We used for analysis of urine samples high performance liquid chromatography and tandem mass spectrometry (HPLC-MS/MS) to determine concentrations of phthalate metabolites monoethyl phthalate (MEP), mono-n-butyl phthalate (MnBP), mono-iso-butyl phthalate (MiBP), mono(2-ethyl- 5-hydroxyhexyl) phthalate (5OH-MEHP), mono(2-ethyl-5-oxohexyl) phthalate (5oxo-MEHP) and mono(2-etylhexyl) phthalate (MEHP). Our results indicate that ethnicity, lower socioeconomic status and different housing conditions in Roma population can affect urinary concentration of phthalate metabolites.

Keywords: Biomonitoring, ethnicity, human exposure, phthalate metabolites.

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Authors: Prawal Sinha, Getachew Adamu

Abstract:

Heating is inevitable in any bearing operation. This leads to not only the thinning of the lubricant but also could lead to a thermal deformation of the bearing. The present work is an attempt to analyze the influence of thermal deformation on the thermohydrodynamic lubrication of infinitely long tilted pad slider rough bearings. As a consequence of heating the slider is deformed and is assumed to take a parabolic shape. Also the asperities expand leading to smaller effective film thickness. Two different types of surface roughness are considered: longitudinal roughness and transverse roughness. Christensen-s stochastic approach is used to derive the Reynolds-type equations. Density and viscosity are considered to be temperature dependent. The modified Reynolds equation, momentum equation, continuity equation and energy equation are decoupled and solved using finite difference method to yield various bearing characteristics. From the numerical simulations it is observed that the performance of the bearing is significantly affected by the thermal distortion of the slider and asperities and even the parallel sliders seem to carry some load.

Keywords: Thermal Deformation, Tilted pad slider bearing, longitudinal roughness, transverse roughness, load capacity

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Authors: Elison Eduardo Jardim Bierhals, Claudineia Brazil, Deivid Pires, Rafael Haag, Elton Gimenez Rossini

Abstract:

The objective of this work is to evaluate the results of solar radiation projections between 2006 and 2013 for the state of Rio Grande do Sul, Brazil. The projections are provided by the General Circulation Models (MCGs) belonging to the Coupled Model Intercomparison Phase 5 (CMIP5). In all, the results of the simulation of six models are evaluated, compared to monthly data, measured by a network of thirteen meteorological stations of the National Meteorological Institute (INMET). The performance of the models is evaluated by the Nash coefficient and the Bias. The results are presented in the form of tables, graphs and spatialization maps. The ACCESS1-0 RCP 4.5 model presented the best results for the solar radiation simulations, for the most optimistic scenario, in much of the state. The efficiency coefficients (CEF) were between 0.95 and 0.98. In the most pessimistic scenario, HADGen2-AO RCP 8.5 had the best accuracy among the analyzed models, presenting coefficients of efficiency between 0.94 and 0.98. From this validation, solar radiation projection maps were elaborated, indicating a seasonal increase of this climatic variable in some regions of the Brazilian territory, mainly in the spring.

Keywords: climate change, projections, solar radiation, validation.

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Authors: Petter Eklund, Jonathan Sjölund, Sandra Eriksson, Mats Leijon

Abstract:

The spoke type rotor can be used to obtain magnetic flux concentration in permanent magnet machines. This allows the air gap magnetic flux density to exceed the remanent flux density of the permanent magnets but gives problems with leakage fluxes in the magnetic circuit. The end leakage flux of one spoke type permanent magnet rotor design is studied through measurements and finite element simulations. The measurements are performed in the end regions of a 12 kW prototype generator for a vertical axis wind turbine. The simulations are made using three dimensional finite elements to calculate the magnetic field distribution in the end regions of the machine. Also two dimensional finite element simulations are performed and the impact of the two dimensional approximation is studied. It is found that the magnetic leakage flux in the end regions of the machine is equal to about 20% of the flux in the permanent magnets. The overestimation of the performance by the two dimensional approximation is quantified and a curve-fitted expression for its behavior is suggested.

Keywords: End effects, end leakage flux, permanent magnet machine, spoke type rotor.

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