Search results for: Minimum Energy and Under Actuator.

Authors: Eu Tteum Ha, Kwang Ryel Ryu

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As smartphones are equipped with various sensors, there have been many studies focused on using these sensors to create valuable applications. Human activity recognition is one such application motivated by various welfare applications, such as the support for the elderly, measurement of calorie consumption, lifestyle and exercise patterns analyses, and so on. One of the challenges one faces when using smartphone sensors for activity recognition is that the number of sensors should be minimized to save battery power. In this paper, we show that a fairly accurate classifier can be built that can distinguish ten different activities by using only a single sensor data, i.e., the smartphone accelerometer data. The approach that we adopt to deal with this twelve-class problem uses various methods. The features used for classifying these activities include not only the magnitude of acceleration vector at each time point, but also the maximum, the minimum, and the standard deviation of vector magnitude within a time window. The experiments compared the performance of four kinds of basic multi-class classifiers and the performance of four kinds of ensemble learning methods based on three kinds of basic multi-class classifiers. The results show that while the method with the highest accuracy is ECOC based on Random forest.

Keywords: Ensemble learning, activity recognition, smartphone accelerometer.

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Authors: Mohamed Omar

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Superelastic Shape Memory Alloy (SMA) is accepted when it used as connection in steel structures. The seismic behaviour of steel frames with SMA is being assessed in this study. Three eightstorey steel frames with different SMA systems are suggested, the first one of which is braced with diagonal bracing system, the second one is braced with nee bracing system while the last one is which the SMA is used as connection at the plastic hinge regions of beams. Nonlinear time history analyses of steel frames with SMA subjected to two different ground motion records have been performed using Seismostruct software. To evaluate the efficiency of suggested systems, the dynamic responses of the frames were compared. From the comparison results, it can be concluded that using SMA element is an effective way to improve the dynamic response of structures subjected to earthquake excitations. Implementing the SMA braces can lead to a reduction in residual roof displacement. The shape memory alloy is effective in reducing the maximum displacement at the frame top and it provides a large elastic deformation range. SMA connections are very effective in dissipating energy and reducing the total input energy of the whole frame under severe seismic ground motion. Using of the SMA connection system is more effective in controlling the reaction forces at the base frame than other bracing systems. Using SMA as bracing is more effective in reducing the displacements. The efficiency of SMA is dependant on the input wave motions and the construction system as well.

Keywords: Finite element analysis, seismic response, shapesmemory alloy, steel frame, superelasticity

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Authors: K. A. Sumitra Devi, N. P. Banashree, Annamma Abraham

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Partitioning is a critical area of VLSI CAD. In order to build complex digital logic circuits its often essential to sub-divide multi -million transistor design into manageable Pieces. This paper looks at the various partitioning techniques aspects of VLSI CAD, targeted at various applications. We proposed an evolutionary time-series model and a statistical glitch prediction system using a neural network with selection of global feature by making use of clustering method model, for partitioning a circuit. For evolutionary time-series model, we made use of genetic, memetic & neuro-memetic techniques. Our work focused in use of clustering methods - K-means & EM methodology. A comparative study is provided for all techniques to solve the problem of circuit partitioning pertaining to VLSI design. The performance of all approaches is compared using benchmark data provided by MCNC standard cell placement benchmark net lists. Analysis of the investigational results proved that the Neuro-memetic model achieves greater performance then other model in recognizing sub-circuits with minimum amount of interconnections between them.

Keywords: VLSI, circuit partitioning, memetic algorithm, genetic algorithm.

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Authors: K. Melouk, M. Dellakrachai

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Analytical formula for the optical gain based on a simple parabolic-band by introducing theoretical expressions for the quantized energy is presented. The model used in this treatment take into account the effects of intraband relaxation. It is shown, as a result, that the gain for the TE mode is larger than that for TM mode and the presence of acceptor impurity increase the peak gain.

Keywords: Laser, quantum well, semiconductor, InGaAsP.

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Authors: Yunos Zahri, Ab Hamid R. Susanty, Ahmad Mustaffa

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This paper explores the need for a national baseline study on understanding the level of cyber security situational awareness among primary and secondary school students in Malaysia. The online survey method was deployed to administer the data collection exercise. The target groups were divided into three categories: Group 1 (primary school aged 7-9 years old), Group 2 (primary school aged 10-12 years old), and Group 3 (secondary school aged 13-17 years old). A different questionnaire set was designed for each group. The survey topics/areas included Internet and digital citizenship knowledge. Respondents were randomly selected from rural and urban areas throughout all 14 states in Malaysia. A total of 9,158 respondents participated in the survey, with most states meeting the minimum sample size requirement to represent the country’s demographics. The findings and recommendations from this baseline study are fundamental to develop teaching modules required for children to understand the security risks and threats associated with the Internet throughout their years in school. Early exposure and education will help ensure healthy cyber habits among millennials in Malaysia.

Keywords: Cyber security awareness, cyber security education, cyber security, students.

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Authors: Behrouz Mosayebi Dehkordi

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Simultaneous effects of temperature, immersion time, salt concentration, sucrose concentration, pressure and convective dryer temperature on the combined osmotic dehydration - convective drying of edible button mushrooms were investigated. Experiments were designed according to Central Composite Design with six factors each at five different levels. Response Surface Methodology (RSM) was used to determine the optimum processing conditions that yield maximum water loss and rehydration ratio and minimum solid gain and shrinkage in osmotic-convective drying of edible button mushrooms. Applying surfaces profiler and contour plots optimum operation conditions were found to be temperature of 39 °C, immersion time of 164 min, salt concentration of 14%, sucrose concentration of 53%, pressure of 600 mbar and drying temperature of 40 °C. At these optimum conditions, water loss, solid gain, rehydration ratio and shrinkage were found to be 63.38 (g/100 g initial sample), 3.17 (g/100 g initial sample), 2.26 and 7.15%, respectively.

Keywords: Dehydration, Mushroom, Optimization, Osmotic, Response Surface Methodology

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Authors: Behrouz Mosayebi Dehkordi

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Simultaneous effects of temperature, immersion time, salt concentration, sucrose concentration, pressure and convective dryer temperature on the combined osmotic dehydration - convective drying of edible button mushrooms were investigated. Experiments were designed according to Central Composite Design with six factors each at five different levels. Response Surface Methodology (RSM) was used to determine the optimum processing conditions that yield maximum water loss and rehydration ratio and minimum solid gain and shrinkage in osmotic-convective drying of edible button mushrooms. Applying surfaces profiler and contour plots optimum operation conditions were found to be temperature of 39 °C, immersion time of 164 min, salt concentration of 14%, sucrose concentration of 53%, pressure of 600 mbar and drying temperature of 40 °C. At these optimum conditions, water loss, solid gain, rehydration ratio and shrinkage were found to be 63.38 (g/100 g initial sample), 3.17 (g/100 g initial sample), 2.26 and 7.15%, respectively.

Keywords: Dehydration, mushroom, optimization, osmotic, response surface methodology.

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Authors: R. Kamalakannan, N. Ravi Kumar

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The global energy consumption is increasing persistently and need for distributed power generation through renewable energy is essential. To meet the power requirements for consumers without any voltage fluctuations and losses, modeling and design of multilevel inverter with Flexible AC Transmission System (FACTS) capability is presented. The presented inverter is provided with 13-level cascaded H-bridge topology of Insulated Gate Bipolar Transistor (IGBTs) connected along with inbuilt Distributed Static Synchronous Compensators (DSTATCOM). The DSTATCOM device provides control of power factor stability at local feeder lines and the inverter eliminates Total Harmonic Distortion (THD). The 13-level inverter utilizes 52 switches of each H-bridge is fed with single DC sources separately and the Pulse Width Modulation (PWM) technique is used for switching IGBTs. The control strategy implemented for inverter transmits active power to grid as well as it maintains power factor to be stable with achievement of steady state power transmission. Significant outcome of this project is improvement of output voltage quality with steady state power transmission with low THD. Simulation of inverter with DSTATCOM is performed using MATLAB/Simulink environment. The scaled prototype model of proposed inverter is built and its results were validated with simulated results.

Keywords: FACTS devices, distributed-Static synchronous compensators, DSTATCOM, total harmonics elimination, modular multilevel converter.

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Authors: Fernando C. Monteiro, Vasco Cadavez

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This paper presents a method for the detection of OD in the retina which takes advantage of the powerful preprocessing techniques such as the contrast enhancement, Gabor wavelet transform for vessel segmentation, mathematical morphology and Earth Mover-s distance (EMD) as the matching process. The OD detection algorithm is based on matching the expected directional pattern of the retinal blood vessels. Vessel segmentation method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel-s feature vector. Feature vectors are composed of the pixel-s intensity and 2D Gabor wavelet transform responses taken at multiple scales. A simple matched filter is proposed to roughly match the direction of the vessels at the OD vicinity using the EMD. The minimum distance provides an estimate of the OD center coordinates. The method-s performance is evaluated on publicly available DRIVE and STARE databases. On the DRIVE database the OD center was detected correctly in all of the 40 images (100%) and on the STARE database the OD was detected correctly in 76 out of the 81 images, even in rather difficult pathological situations.

Keywords: Diabetic retinopathy, Earth Mover's distance, Gabor wavelets, optic disc detection, retinal images

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Authors: A. El Shahat, A. Keyhani, H. El Shewy

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High Speed PM Generators driven by micro-turbines are widely used in Smart Grid System. So, this paper proposes comparative study among six classical, optimized and genetic analytical design cases for 400 kW output power at tip speed 200 m/s. These six design trials of High Speed Permanent Magnet Synchronous Generators (HSPMSGs) are: Classical Sizing; Unconstrained optimization for total losses and its minimization; Constrained optimized total mass with bounded constraints are introduced in the problem formulation. Then a genetic algorithm is formulated for obtaining maximum efficiency and minimizing machine size. In the second genetic problem formulation, we attempt to obtain minimum mass, the machine sizing that is constrained by the non-linear constraint function of machine losses. Finally, an optimum torque per ampere genetic sizing is predicted. All results are simulated with MATLAB, Optimization Toolbox and its Genetic Algorithm. Finally, six analytical design examples comparisons are introduced with study of machines waveforms, THD and rotor losses.

Keywords: High Speed, Micro - Turbines, Optimization, PM Generators, Smart Grid, MATLAB.

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Authors: Sapan Mohan Saini

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We report the electronic structure and optical properties of NdF3 compound. Our calculations are based on density functional theory (DFT) using the full potential linearized augmented plane wave (FPLAPW) method with the inclusion of spin orbit coupling. We employed the local spin density approximation (LSDA) and Coulomb-corrected local spin density approximation, known for treating the highly correlated 4f electrons properly, is able to reproduce the correct insulating ground state. We find that the standard LSDA approach is incapable of correctly describing the electronic properties of such materials since it positions the f-bands incorrectly resulting in an incorrect metallic ground state. On the other hand, LSDA + U approximation, known for treating the highly correlated 4f electrons properly, is able to reproduce the correct insulating ground state. Interestingly, however, we do not find any significant differences in the optical properties calculated using LSDA, and LSDA + U suggesting that the 4f electrons do not play a decisive role in the optical properties of these compounds. The reflectivity for NdF3 compound stays low till 7 eV which is consistent with their large energy gaps. The calculated energy gaps are in good agreement with experiments. Our calculated reflectivity compares well with the experimental data and the results are analyzed in the light of band to band transitions.

Keywords: FPLAPW Method, optical properties, rare earthtrifluorides LSDA+U

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Authors: Cora Fernandez Dacosta, John A. Posada, Andrea Ramirez

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The biodegradable family of polymers polyhydroxyalkanoates is an interesting substitute for convectional fossil-based plastics. However, the manufacturing and environmental impacts associated with their production via intracellular bacterial fermentation are strongly dependent on the raw material used and on energy consumption during the extraction process, limiting their potential for commercialization. Industrial wastewater is studied in this paper as a promising alternative feedstock for waste valorization. Based on results from laboratory and pilot-scale experiments, a conceptual process design, techno-economic analysis and life cycle assessment are developed for the large-scale production of the most common type of polyhydroxyalkanoate, polyhydroxbutyrate. Intracellular polyhydroxybutyrate is obtained via fermentation of microbial community present in industrial wastewater and the downstream processing is based on chemical digestion with surfactant and hypochlorite. The economic potential and environmental performance results help identifying bottlenecks and best opportunities to scale-up the process prior to industrial implementation. The outcome of this research indicates that the fermentation of wastewater towards PHB presents advantages compared to traditional PHAs production from sugars because the null environmental burdens and financial costs of the raw material in the bioplastic production process. Nevertheless, process optimization is still required to compete with the petrochemicals counterparts.

Keywords: Circular economy, life cycle assessment, polyhydroxyalkanoates, waste valorization.

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Authors: M. Zeydan, G. Toğa

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This study deals with a multi-criteria optimization problem which has been transformed into a single objective optimization problem using Response Surface Methodology (RSM), Artificial Neural Network (ANN) and Grey Relational Analyses (GRA) approach. Grey-RSM and Grey-ANN are hybrid techniques which can be used for solving multi-criteria optimization problem. There have been two main purposes of this research as follows. 1. To determine optimum and robust fiber dyeing process conditions by using RSM and ANN based on GRA, 2. To obtain the best suitable model by comparing models developed by different methodologies. The design variables for fiber dyeing process in textile are temperature, time, softener, anti-static, material quantity, pH, retarder, and dispergator. The quality characteristics to be evaluated are nominal color consistency of fiber, maximum strength of fiber, minimum color of dyeing solution. GRA-RSM with exact level value, GRA-RSM with interval level value and GRA-ANN models were compared based on GRA output value and MSE (Mean Square Error) performance measurement of outputs with each other. As a result, GRA-ANN with interval value model seems to be suitable reducing the variation of dyeing process for GRA output value of the model.

Keywords: Artificial Neural Network, Grey Relational Analysis, Optimization, Response Surface Methodology

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Authors: R. Prakash, B. Meenakshipriya, R. Kumaravelan

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Fresh water is one of the resources which is getting depleted day by day. A wise method to address this issue is by the application of renewable energy-sun irradiation and by means of decentralized, cheap, energetically self-sufficient, robust and simple to operate plants, distillates can be obtained from sea, river or even sewage. Solar desalination is a technique used to desalinate water using solar energy. The present work deals with the comprehensive design and simulation of solar tracking system using LabVIEW, temperature and mass flow rate control of the solar desalination plant using LabVIEW and also analysis of single phase inverter circuit with LC filters for solar pumping system in MATLAB. The main objective of this work is to improve the performance of solar desalination system using automatic tracking system, output control using temperature and mass flow rate control system and also to reduce the harmonic distortion in the solar pumping system by means of LC filters. The simulation of single phase inverter was carried out using MATLAB and the output waveforms were analyzed. Simulations were performed for optimum output temperature control, which in turn controls the mass flow rate of water in the thermal collectors. Solar tracking system was accomplished using LABVIEW and was tested successfully. The thermal collectors are tracked in accordance with the sun’s irradiance levels, thereby increasing the efficiency of the thermal collectors.

Keywords: Desalination, Electro dialysis, LabVIEW, MATLAB, PWM inverter, Reverse osmosis.

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Authors: Yuan-Jye Tseng, Shin-Han Lin

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In this research, a mathematical model for integrated evaluation of green design and green manufacturing processes is presented. To design a product, there can be alternative options to design the detailed components to fulfill the same product requirement. In the design alternative cases, the components of the product can be designed with different materials and detailed specifications. If several design alternative cases are proposed, the different materials and specifications can affect the manufacturing processes. In this paper, a new concept for integrating green design and green manufacturing processes is presented. A green design can be determined based the manufacturing processes of the designed product by evaluating the green criteria including energy usage and environmental impact, in addition to the traditional criteria of manufacturing cost. With this concept, a mathematical model is developed to find the green design and the associated green manufacturing processes. In the mathematical model, the cost items include material cost, manufacturing cost, and green related cost. The green related cost items include energy cost and environmental cost. The objective is to find the decisions of green design and green manufacturing processes to achieve the minimized total cost. In practical applications, the decision-making can be made to select a good green design case and its green manufacturing processes. In this presentation, an example product is illustrated. It shows that the model is practical and useful for integrated evaluation of green design and green manufacturing processes.

Keywords: Supply chain management, green supply chain, green design, green manufacturing, mathematical model.

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Authors: Jesús Everardo Olguín Tiznado, Rafael García Martínez, Claudia Camargo Wilson, Juan Andrés López Barreras, Everardo Inzunza González, Javier Ordorica Villalvazo

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The response surface methodology (RSM) is a collection of mathematical and statistical techniques useful in the modeling and analysis of problems in which the dependent variable receives the influence of several independent variables, in order to determine which are the conditions under which should operate these variables to optimize a production process. The RSM estimated a regression model of first order, and sets the search direction using the method of maximum / minimum slope up / down MMS U/D. However, this method selects the step size intuitively, which can affect the efficiency of the RSM. This paper assesses how the step size affects the efficiency of this methodology. The numerical examples are carried out through Monte Carlo experiments, evaluating three response variables: efficiency gain function, the optimum distance and the number of iterations. The results in the simulation experiments showed that in response variables efficiency and gain function at the optimum distance were not affected by the step size, while the number of iterations is found that the efficiency if it is affected by the size of the step and function type of test used.

Keywords: RSM, dependent variable, independent variables, efficiency, simulation

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Authors: Abiodun M. Aibinu, Athaur Rahman Najeeb, Momoh J. E. Salami, Amir A. Shafie

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An alternative approach to the use of Discrete Fourier Transform (DFT) for Magnetic Resonance Imaging (MRI) reconstruction is the use of parametric modeling technique. This method is suitable for problems in which the image can be modeled by explicit known source functions with a few adjustable parameters. Despite the success reported in the use of modeling technique as an alternative MRI reconstruction technique, two important problems constitutes challenges to the applicability of this method, these are estimation of Model order and model coefficient determination. In this paper, five of the suggested method of evaluating the model order have been evaluated, these are: The Final Prediction Error (FPE), Akaike Information Criterion (AIC), Residual Variance (RV), Minimum Description Length (MDL) and Hannan and Quinn (HNQ) criterion. These criteria were evaluated on MRI data sets based on the method of Transient Error Reconstruction Algorithm (TERA). The result for each criterion is compared to result obtained by the use of a fixed order technique and three measures of similarity were evaluated. Result obtained shows that the use of MDL gives the highest measure of similarity to that use by a fixed order technique.

Keywords: Autoregressive Moving Average (ARMA), MagneticResonance Imaging (MRI), Parametric modeling, Transient Error.

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Authors: S. Jungsuttiwong, R. Tarsang, S. Pansay, T. Yakhantip, V. Promarak, T. Sudyoadsuk, T. Kaewin, S. Saengsuwan, S. Namuangrak

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In this paper, four carbazole-based D-D-π-A organic dyes code as CCT2A, CCT3A, CCT1PA and CCT2PA were reported. A series of these organic dyes containing identical donor and acceptor group but different π-system. The effect of replacing of thiophene by phenyl thiophene as π-system on the physical properties has been focused. The structural, energetic properties and absorption spectra were theoretically investigated by means of Density Functional Theory (DFT) and Time-Dependent Density Functional Theory (TD-DFT). The results show that nonplanar conformation due to steric hindrance in donor part (cabazolecarbazole unit) of dye molecule can prevent unfavorable dye aggregation. By means of the TD-DFT method, the absorption spectra were calculated by B3LYP and BHandHLYP to study the affect of hybrid functional on the excitation energy (Eg). The results revealed the increasing of thiophene units not only resulted in decreasing of Eg, but also found the shifting of absorption spectra to higher wavelength. TD-DFT/BHandHLYP calculated results are more strongly agreed with the experimental data than B3LYP functions. Furthermore, the adsorptions of CCT2A and CCT3A on the TiO2 anatase (101) surface were carried out by mean of the chemical periodic calculation. The result exhibit the strong adsorption energy. The calculated results provide our new organic dyes can be effectively used as dye for Dye Sensitized Solar Cell (DSC).

Keywords: Dye-Sensitized Solar cell, Carbarzole, TD-DFT, D-D-π-A organic dye

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Authors: Oriyomi M. Okeyinka, David A. Oloke, Jamal M. Khatib

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Large quantities of solid wastes being generated worldwide from sources such as household, domestic, industrial, commercial and construction demolition activities, leads to environmental concerns. Utilization of these wastes in making building construction materials can reduce the magnitude of the associated problems. When these waste products are used in place of other conventional materials, natural resources and energy are preserved and expensive and/or potentially harmful waste disposal is avoided. Recycling which is regarded as the third most preferred waste disposal option, with its numerous environmental benefits, stand as a viable option to offset the environmental impact associated with the construction industry. This paper reviews the results of laboratory tests and important research findings, and the potential of using these wastes in building construction materials with focus on sustainable development. Research gaps, which includes; the need to develop standard mix design for solid waste based building materials; the need to develop energy efficient method of processing solid waste use in concrete; the need to study the actual behavior or performance of such building materials in practical application and the limited real life application of such building materials have also been identified. A research is being proposed to develop an environmentally friendly, lightweight building block from recycled waste paper, without the use of cement, and with properties suitable for use as walling unit. This proposed research intends to incorporate, laboratory experimentation and modeling to address the identified research gaps.

Keywords: Recycling, solid waste, construction, building materials.

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Authors: M. H. Sedaghat, A. Zamani, S. Morshedi, R. Janamiri, M. Safdari, I. Mahdavi, A. Hosseini, A. Hatampour

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Although lots of experiments have been done in enhanced oil recovery, the number of experiments which consider the effects of local and global heterogeneity on efficiency of enhanced oil recovery based on the polymer-surfactant flooding is low and rarely done. In this research, we have done numerous experiments of water flooding and polymer-surfactant flooding on a five spot glass micromodel in different conditions such as different positions of layers. In these experiments, five different micromodels with three different pore structures are designed. Three models with different layer orientation, one homogenous model and one heterogeneous model are designed. In order to import the effect of heterogeneity of porous media, three types of pore structures are distributed accidentally and with equal ratio throughout heterogeneous micromodel network according to random normal distribution. The results show that maximum EOR recovery factor will happen in a situation where the layers are orthogonal to the path of mainstream and the minimum EOR recovery factor will happen in a situation where the model is heterogeneous. This experiments show that in polymer-surfactant flooding, with increase of angles of layers the EOR recovery factor will increase and this recovery factor is strongly affected by local heterogeneity around the injection zone.

Keywords: Layered Reservoir, Micromodel, Local Heterogeneity, Polymer-Surfactant Flooding, Enhanced Oil Recovery.

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Authors: G. Sekeroglu, M. Altan

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Working capital is identified as firm’s all current assets. Inventories which are one of the working capital elements are very important among current assets for firms. Because, profitability is an indicator for firms’ financial success is provided with minimum cost and optimum inventory quantity. So in this study, it is investigated as comparatively that the effect of inventory management on the profitability of Turkish firms which operated in weaving industry, eatables industry, wholesale and retail industry in between 2003 – 2012 years. Research data consist of profitability ratios and inventory turnovers ratio calculated by using balance sheets and income statements of firms which operated in Borsa Istanbul (BIST). In this research, the relationship between inventories and profitability is investigated by using SPSS-20 software with regression and correlation analysis. The results achieved from three industry departments which exist in study interpreted as comparatively. Accordingly, it is determined that there is a positive relationship between inventory management and profitability in eatables industry. However, it was founded that there is no relationship between inventory management and profitability in weaving industry and wholesale and retail industry.

Keywords: Profitability, regression analysis, inventory management, working capital.

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Authors: B. Janani, S. Thiruvenkadam

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In this work, the system evaluates the impact of considering a stochastic approach on the day ahead basis Unit Commitment. Comparisons between stochastic and deterministic Unit Commitment solutions are provided. The Unit Commitment model consists in the minimization of the total operation costs considering unit’s technical constraints like ramping rates, minimum up and down time. Load shedding and wind power spilling is acceptable, but at inflated operational costs. The evaluation process consists in the calculation of the optimal unit commitment and in verifying the fulfillment of the considered constraints. For the calculation of the optimal unit commitment, an algorithm based on the Benders Decomposition, namely on the Dual Dynamic Programming, was developed. Two approaches were considered on the construction of stochastic solutions. Data related to wind power outputs from two different operational days are considered on the analysis. Stochastic and deterministic solutions are compared based on the actual measured wind power output at the operational day. Through a technique capability of finding representative wind power scenarios and its probabilities, the system can analyze a more detailed process about the expected final operational cost.

Keywords: Benders’ decomposition, network constrained AC unit commitment, stochastic programming, wind power uncertainty.

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Authors: Ghada Salem, Nihal Kabel

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Objective: This in vitro study was carried out to assess the microleakage properties of nano-filled glass ionomer in comparison to resin-reinforced glass ionomers. Material and Methods: 40 deciduous molar teeth were included in this study. Class-II cavity was prepared in a standard form for all the specimens. The teeth were randomly distributed into two groups (20 per group) according to the restorative material used either nano-glass ionomer or Photac Fill glass ionomer restoration. All specimens were thermocycled for 1000 cycles between 5 and 55 °C. After that, the teeth were immersed in 2% methylene blue dye then sectioned and evaluated under a stereomicroscope. Microleakage was assessed using linear dye penetration and on a scale from zero to five. Results: Two way ANOVA test revealed a statistically significant lower degree of microleakage in both occlusal and gingival restorations (0.4±0.2), (0.9±0.1) for nano-filled glass ionomer group in comparison to resin modified glass ionomer (2.3±0.7), (2.4±0.5). No statistical difference was found between gingival and occlusal leakage regarding the effect of the measured site. Conclusion: Nano-filled glass ionomer shows superior sealing ability which enables this type of restoration to be used in minimum invasive treatment.

Keywords: Microleakage, nano-ionomer, resin-reinforced glass ionomer, proximal cavity preparation.

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Authors: J. B. Qin, X. H. Jiang, Y. T. Ge

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The growing awareness of global warming potential has internationally aroused interest and demand in reducing greenhouse gas emissions produced by human activity. Much national energy in the UK had been consumed in the residential sector mainly for space heating and domestic hot water production. Currently, gas boilers are mostly applied in the domestic water heating which contribute significantly to excessive CO₂ emissions and consumption of primary energy resources. The issues can be solved by popularizing heat pump systems that are attributable to higher performance efficiency than those of traditional gas boilers. Even so, the heat pump system performance can be further enhanced if the dissolved gases in its hot water circuit can be efficiently discharged.  To achieve this target, the bubble behaviors in the heat pump water heating system need to be extensively investigated. In this paper, by varying different experimental conditions, the effects of various heat pump hot water side parameters on gas microbubble diameters were measured and analyzed. Correspondingly, the effect of each parameter has been investigated. These include varied system pressures, water flow rates, saturation ratios and heat outputs. The results measurement showed that the water flow rate is the most significant parameter to influence on gas microbubble productions. The research outcomes can significantly contribute to the understanding of gas bubble behaviors at domestic heat pump water heating systems and thus the efficient way for the discharging of the associated dissolved gases.  

Keywords: Dissolved gases in water, heat pump, domestic water heating system, microbubble formation.

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Authors: Thomas V. Prevenslik

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Ovshinsky initiated scientific research in the field of amorphous and disordered materials that continues to this day. The Ovshinsky Effect where the resistance of thin GST films is significantly reduced upon the application of low voltage is of fundamental importance in phase-change - random access memory (PC-RAM) devices.GST stands for GdSbTe chalcogenide type glasses.However, the Ovshinsky Effect is not without controversy. Ovshinsky thought the resistance of GST films is reduced by the redistribution of charge carriers; whereas, others at that time including many PC-RAM researchers today argue that the GST resistance changes because the GST amorphous state is transformed to the crystalline state by melting, the heat supplied by external heaters. In this controversy, quantum mechanics (QM) asserts the heat capacity of GST films vanishes, and therefore melting cannot occur as the heat supplied cannot be conserved by an increase in GST film temperature.By precluding melting, QM re-opens the controversy between the melting and charge carrier mechanisms. Supporting analysis is presented to show that instead of increasing GST film temperature, conservation proceeds by the QED induced creation of photons within the GST film, the QED photons confined by TIR. QED stands for quantum electrodynamics and TIR for total internal reflection. The TIR confinement of QED photons is enhanced by the fact the absorbedheat energy absorbed in the GST film is concentrated in the TIR mode because of their high surface to volume ratio. The QED photons having Planck energy beyond the ultraviolet produce excitons by the photoelectric effect, the electrons and holes of which reduce the GST film resistance.

Keywords: Ovshinsky, phase change memory, PC-RAM, chalcogenide, quantummechanics, quantum electrodynamics.

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Authors: N. Manavizadeh, M. Hosseini, M. Rabbani

Abstract:

In the last decades to supply the various and different demands of clients, a lot of manufacturers trend to use the mixedmodel assembly line (MMAL) in their production lines, since this policy make possible to assemble various and different models of the equivalent goods on the same line with the MTO approach. In this article, we determine the sequence of (MMAL) line, with applying the kitting approach and planning of rest time for general workers to reduce the wastages, increase the workers effectiveness and apply the sector of lean production approach. This Multi-objective sequencing problem solved in small size with GAMS22.2 and PSO meta heuristic in 10 test problems and compare their results together and conclude that their results are very similar together, next we determine the important factors in computing the cost, which improving them cost reduced. Since this problem, is NPhard in large size, we use the particle swarm optimization (PSO) meta-heuristic for solving it. In large size we define some test problems to survey it-s performance and determine the important factors in calculating the cost, that by change or improved them production in minimum cost will be possible.

Keywords: Mixed-Model Assembly Line, particle swarmoptimization, Multi-objective sequencing problem, MTO system, kitto-assembly, rest time

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Authors: Jefrey Pilusa, Tumisang Seodigeng

Abstract:

This research discusses a South African case study for the potential of utilizing refuse-derived fuel (RDF) obtained from non-burn treatment of health care risk waste (HCRW) as potential feedstock for green energy production. This specific waste stream can be destroyed via non-burn treatment technology involving high-speed mechanical shredding followed by steam or chemical injection to disinfect the final product. The RDF obtained from this process is characterised by a low moisture, low ash, and high calorific value which means it can be potentially used as high-value solid fuel. Due to the raw feed of this RDF being classified as hazardous, the final RDF has been reported to be non-infectious and can blend with other combustible wastes such as rubber and plastic for waste to energy applications. This study evaluated non-burn treatment technology as a possible solution for on-site destruction of HCRW in South African private and public health care centres. Waste generation quantities were estimated based on the number of registered patient beds, theoretical bed occupancy. Time and motion study was conducted to evaluate the logistics viability of on-site treatment. Non-burn treatment technology for HCRW is a promising option for South Africa, and successful implementation of this method depends upon the initial capital investment, operational cost and environmental permitting of such technology; there are other influencing factors such as the size of the waste stream, product off-take price as well as product demand.

Keywords: Autoclave, disposal, fuel, incineration, medical waste.

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Authors: S. Anna Durai, E. Anna Saro

Abstract:

Image Compression using Artificial Neural Networks is a topic where research is being carried out in various directions towards achieving a generalized and economical network. Feedforward Networks using Back propagation Algorithm adopting the method of steepest descent for error minimization is popular and widely adopted and is directly applied to image compression. Various research works are directed towards achieving quick convergence of the network without loss of quality of the restored image. In general the images used for compression are of different types like dark image, high intensity image etc. When these images are compressed using Back-propagation Network, it takes longer time to converge. The reason for this is, the given image may contain a number of distinct gray levels with narrow difference with their neighborhood pixels. If the gray levels of the pixels in an image and their neighbors are mapped in such a way that the difference in the gray levels of the neighbors with the pixel is minimum, then compression ratio as well as the convergence of the network can be improved. To achieve this, a Cumulative distribution function is estimated for the image and it is used to map the image pixels. When the mapped image pixels are used, the Back-propagation Neural Network yields high compression ratio as well as it converges quickly.

Keywords: Back-propagation Neural Network, Cumulative Distribution Function, Correlation, Convergence.

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Authors: M. Khosravy-el-Hossani, Q. Dorosti

Abstract:

One of the important applications of gas turbines is their utilization for heat recovery steam generator in combine-cycle technology. Exhaust flow and energy are two key parameters for determining heat recovery steam generator performance which are mainly determined by the main gas turbine components performance data. For this reason a method was developed for determining the exhaust energy in the new edition of ASME PTC22. The result of this investigation shows that the method of standard has considerable error. Therefore in this paper a new method is presented for modifying of the performance calculation. The modified method is based on exhaust gas constituent analysis and combustion calculations. The case study presented here by two kind of General Electric gas turbine design data for validation of methodologies. The result shows that the modified method is more precise than the ASME PTC22 method. The exhaust flow calculation deviation from design data is 1.5-2 % by ASME PTC22 method so that the deviation regarding with modified method is 0.3-0.5%. Based on precision of analyzer instruments, the method can be suitable alternative for gas turbine standard performance test. In advance two methods are proposed based on known and unknown fuel in modified method procedure. The result of this paper shows that the difference between the two methods is below than %0.02. In according to reasonable esult of the second procedure (unknown fuel composition), the method can be applied to performance evaluation of gas turbine, so that the measuring cost and data gathering should be reduced.

Keywords: Gas turbine, Performance test code, Combined cycle.

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Authors: R. Vishnu Priya, A. Vadivel

Abstract:

Sequential pattern mining is a challenging task in data mining area with large applications. One among those applications is mining patterns from weblog. Recent times, weblog is highly dynamic and some of them may become absolute over time. In addition, users may frequently change the threshold value during the data mining process until acquiring required output or mining interesting rules. Some of the recently proposed algorithms for mining weblog, build the tree with two scans and always consume large time and space. In this paper, we build Revised PLWAP with Non-frequent Items (RePLNI-tree) with single scan for all items. While mining sequential patterns, the links related to the nonfrequent items are not considered. Hence, it is not required to delete or maintain the information of nodes while revising the tree for mining updated transactions. The algorithm supports both incremental and interactive mining. It is not required to re-compute the patterns each time, while weblog is updated or minimum support changed. The performance of the proposed tree is better, even the size of incremental database is more than 50% of existing one. For evaluation purpose, we have used the benchmark weblog dataset and found that the performance of proposed tree is encouraging compared to some of the recently proposed approaches.

Keywords: Sequential pattern mining, weblog, frequent and non-frequent items, incremental and interactive mining.

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