Search results for: evolutionary rate

Authors: Vishal Awasthi, Krishna Raj

Abstract:

Unwanted side effects because of spectral aliasing and spectral imaging during signal processing would be the major concern over the sampling rate alteration. Multirate-multistage implementation of digital filter could come about a large computational saving than single rate filter suitable for sample rate conversion. This implementation can further improve through high-level architectural transformation in circuit level. Reallocating registers and  relocating flip-flops across logic gates through retiming certainly a prominent sequential transformation technology, that optimize hardware circuits to achieve faster clocking speed without affecting the functionality. In this paper, we proposed an efficient compensated cascade Integrator comb (CIC) decimation filter structure that analyze the consequence of filter order variation which has a retimed FIR filter being compensator while using the cutset retiming technique and achieved an improvement in the passband droop by 14% to 39%, in computation time by 38.04%, 25.78%, 12.21%, 6.69% and 4.44% and reduction in path delay by 62.27%, 72%, 86.63%, 91.56% and 94.42% of 3, 6, 8, 12 and 24 order filter respectively than the non-retimed CIC compensation filter.

Keywords: Multirate Filtering, CIC decimation filter, Compensation theory, Retiming, Retiming algorithm, Filter order, Synchronous dataflow graph.

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Authors: Philip Rose, Markus Linke, David Busquets

Abstract:

The distinction between interlaminar and intralaminar fracture toughness is challenging. For loading mode I, the double cantilever beam specimens were often used for the interlaminar fracture toughness and the compact tension specimen for the intralaminar fracture toughness. For the analysis of interlaminar properties regarding energy release under different loading modes, the geometry of the DCB specimen can also be tested under three-point bending for Mode II characteristics. The same specimen can also be tested with defined superimposed loading conditions (mixed mode) using the Mixed Mode Bending test apparatus. However, this approach has not been applicable for intralaminar characteristics, as crack initiation in a single layer for laminates made out of prepreg, has not been feasible. The method presented in this work enables differentiation of interlaminar and intralaminar energy release rates in Mode II loading with nearly identical specimen geometry. With this, a practically identical energy release rate is observed in Mode II for the investigated material IM7/8552.

Keywords: Fibre reinforced plastics, end-notched flexure, energy release rate, fracture toughness, intralaminar, interlaminar.

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Authors: C. Recommandé, J.C. Blind, A. Clavel, R. Gourichon, V. Le Gal

Abstract:

Simulations are developed in this paper with usual DSGE model equations. The model is based on simplified version of Smets-Wouters equations in use at European Central Bank which implies 10 macro-economic variables: consumption, investment, wages, inflation, capital stock, interest rates, production, capital accumulation, labour and credit rate, and allows take into consideration the banking system. Throughout the simulations, this model will be used to evaluate the impact of rate shocks recounting the actions of the European Central Bank during 2008.

Keywords: CC-LM, Central Bank, DSGE, Liquidity Shock, Non-standard Intervention.

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

Abstract:

Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: Android, permissions combination, API calls, machine learning.

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Authors: Desmond B. Keenan

Abstract:

The clinical usefulness of heart rate variability is limited to the range of Holter monitoring software available. These software algorithms require a normal sinus rhythm to accurately acquire heart rate variability (HRV) measures in the frequency domain. Premature ventricular contractions (PVC) or more commonly referred to as ectopic beats, frequent in heart failure, hinder this analysis and introduce ambiguity. This investigation demonstrates an algorithm to automatically detect ectopic beats by analyzing discrete wavelet transform coefficients. Two techniques for filtering and replacing the ectopic beats from the RR signal are compared. One technique applies wavelet hard thresholding techniques and another applies linear interpolation to replace ectopic cycles. The results demonstrate through simulation, and signals acquired from a 24hr ambulatory recorder, that these techniques can accurately detect PVC-s and remove the noise and leakage effects produced by ectopic cycles retaining smooth spectra with the minimum of error.

Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, wavelets, ectopic beats, spectral analysis.

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Authors: L. Grinis, N. Lubashevsky, Y. Ostrovski

Abstract:

A jet pump is a type of pump that accelerates the flow of a secondary fluid (driven fluid) by introducing a motive fluid with high velocity into a converging-diverging nozzle. Jet pumps are also known as adductors or ejectors depending on the motivator phase. The ejector's motivator is of a gaseous nature, usually steam or air, while the educator's motivator is a liquid, usually water. Jet pumps are devices that use air bubbles and are widely used in wastewater treatment processes. In this work, we will discuss about the characteristics of the jet pump and the computational simulation of this device. To find the optimal angle and depth for the air pipe, so as to achieve the maximal air volumetric flow rate, an experimental apparatus was constructed to ascertain the best geometrical configuration for this new type of jet pump. By using 3D printing technology, a series of jet pumps was printed and tested whilst aspiring to maximize air flow rate dependent on angle and depth of the air pipe insertion. The experimental results show a major difference of up to 300% in performance between the different pumps (ratio of air flow rate to supplied power) where the optimal geometric model has an insertion angle of 60⁰ and air pipe insertion depth ending at the center of the mixing chamber. The differences between the pumps were further explained by using CFD for better understanding the reasons that affect the airflow rate. The validity of the computational simulation and the corresponding assumptions have been proved experimentally. The present research showed high degree of congruence with the results of the laboratory tests. This study demonstrates the potential of using of the jet pump in many practical applications.

Keywords: Air bubbles, CFD simulation, jet pump, practical applications.

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Authors: Suman Kumar Saha, Rajib Kar, Durbadal Mandal, S. P. Ghoshal

Abstract:

This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.

Keywords: IIR Filter, RGA, PSO, CRPSO, Evolutionary Optimization Techniques, Low Pass (LP) Filter, Magnitude Response, Pole-Zero Plot, Stability.

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Authors: S. Iijima, K. Nakayama, D. Kuchar, M. Kubota, H. Matsuda

Abstract:

Regenerative Thermal Oxidizer (RTO) is one of the best solutions for removal of Volatile Organic Compounds (VOC) from industrial processes. In the RTO, VOC in a raw gas are usually decomposed at 950-1300 K and the combustion heat of VOC is recovered by regenerative heat exchangers charged with ceramic honeycombs. The optimization of the treatment of VOC leads to the reduction of fuel addition to VOC decomposition, the minimization of CO2 emission and operating cost as well. In the present work, the thermal efficiency of the RTO was investigated experimentally in a pilot-scale RTO unit using toluene as a typical representative of VOC. As a result, it was recognized that the radiative heat transfer was dominant in the preheating process of a raw gas when the gas flow rate was relatively low. Further, it was found that a minimum heat exchanger volume to achieve self combustion of toluene without additional heating of the RTO by fuel combustion was dependent on both the flow rate of a raw gas and the concentration of toluene. The thermal efficiency calculated from fuel consumption and the decomposed toluene ratio, was found to have a maximum value of 0.95 at a raw gas mass flow rate of 1810 kg·h-1 and honeycombs height of 1.5m.

Keywords: Regenerative Heat Exchange, Self Combustion, Toluene, Volatile Organic Compounds.

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Authors: Dai Zhimei, Hua Chen

Abstract:

The exploration of urban spatial evolution is an important part of urban development research. Therefore, the evolutionary modern Yangzhou urban spatial texture was taken as the research object, and Spatial Syntax was used as the main research tool, this paper explored Yangzhou spatial evolution law and its driving factors from the urban street network scale, district scale and street scale. The study has concluded that at the urban scale, Yangzhou urban spatial evolution is the result of a variety of causes, including physical and geographical condition, policy and planning factors, and traffic conditions, and the evolution of space also has an impact on social, economic, environmental and cultural factors. At the district and street scales, changes in space will have a profound influence on the history of the city and the activities of people. At the end of the article, the matters needing attention during the evolution of urban space were summarized.

Keywords: Space Syntax, spatial texture, urban space, Yangzhou.

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Authors: Leena Sharma

Abstract:

Chemical reaction and diffusion are important phenomena in quantitative neurobiology and biophysics. The knowledge of the dynamics of calcium Ca²⁺ is very important in cellular physiology because Ca²⁺ binds to many proteins and regulates their activity and interactions Calcium waves propagate inside cells due to a regenerative mechanism known as calcium-induced calcium release. Buffer-mediated calcium diffusion in the cytosol plays a crucial role in the process. A mathematical model has been developed for calcium waves by assuming the buffers are in equilibrium with calcium i.e., the rapid buffering approximation for a one dimensional unsteady state case. This model incorporates important physical and physiological parameters like dissociation rate, diffusion rate, total buffer concentration and influx. The finite difference method has been employed to predict [Ca²⁺] and buffer concentration time course regardless of the calcium influx. The comparative studies of the effect of the rapid buffered diffusion and kinetic parameters of the model on the concentration time course have been performed.

Keywords: Calcium Profile, Rapid Buffering Approximation, Influx, Dissociation rate constant.

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Authors: M. Saravanan, J. Raja Murugadoss, V. Jayanthi

Abstract:

Optimal design of structure has a main role in reduction of material usage which leads to deduction in the final cost of construction projects. Evolutionary approaches are found to be more successful techniques for solving size and shape structural optimization problem since it uses a stochastic random search instead of a gradient search. By reviewing the recent literature works the problem found was the optimization of weight. A new meta-heuristic algorithm called as Cuckoo Search (CS) Algorithm has used for the optimization of the total weight of the truss structures. This paper has used set of 10 bars and 25 bars trusses for the testing purpose. The main objective of this work is to reduce the number of iterations, weight and the total time consumption. In order to demonstrate the effectiveness of the present method, minimum weight design of truss structures is performed and the results of the CS are compared with other algorithms.

Keywords: Cuckoo search algorithm, levy’s flight, meta-heuristic, optimal weight.

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Authors: Campbell Townsend, David Hamilton

Abstract:

Previous research has demonstrated that negative attitudes towards people with physical disabilities and obesity are predicted by a component of perceived vulnerability to disease; germ aversion. These findings have been suggested as illustrations of an evolved but over-active mechanism which promotes the avoidance of pathogen-carrying individuals. To date, this interpretation of attitude formation has not been explored with regard to people with intellectual disability, and no attempts have been made to examine possible mediating factors. This study examined attitudes in 333 adults and demonstrated that the moderate positive relationship between germ aversion and negative attitudes toward people with intellectual disability is fully mediated by social dominance orientation, a general preference for hierarchies and inequalities among social groups. These findings have implications for the design of programs which attempt to promote community acceptance and inclusion of people with disabilities.

Keywords: avoidance, evolutionary psychology, intellectual disability, prejudice

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Authors: Ghazy M.R. Assassa, Mona F. M. Mursi, Hatim A. Aboalsamh

Abstract:

Traditional principal components analysis (PCA) techniques for face recognition are based on batch-mode training using a pre-available image set. Real world applications require that the training set be dynamic of evolving nature where within the framework of continuous learning, new training images are continuously added to the original set; this would trigger a costly continuous re-computation of the eigen space representation via repeating an entire batch-based training that includes the old and new images. Incremental PCA methods allow adding new images and updating the PCA representation. In this paper, two incremental PCA approaches, CCIPCA and IPCA, are examined and compared. Besides, different learning and testing strategies are proposed and applied to the two algorithms. The results suggest that batch PCA is inferior to both incremental approaches, and that all CCIPCAs are practically equivalent.

Keywords: Candid covariance-free incremental principal components analysis (CCIPCA), face recognition, incremental principal components analysis (IPCA).

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Authors: Zuwairie Ibrahim, Yusei Tsuboi, Osamu Ono, Marzuki Khalid

Abstract:

Deoxyribonucleic Acid or DNA computing has emerged as an interdisciplinary field that draws together chemistry, molecular biology, computer science and mathematics. Thus, in this paper, the possibility of DNA-based computing to solve an absolute 1-center problem by molecular manipulations is presented. This is truly the first attempt to solve such a problem by DNA-based computing approach. Since, part of the procedures involve with shortest path computation, research works on DNA computing for shortest path Traveling Salesman Problem, in short, TSP are reviewed. These approaches are studied and only the appropriate one is adapted in designing the computation procedures. This DNA-based computation is designed in such a way that every path is encoded by oligonucleotides and the path-s length is directly proportional to the length of oligonucleotides. Using these properties, gel electrophoresis is performed in order to separate the respective DNA molecules according to their length. One expectation arise from this paper is that it is possible to verify the instance absolute 1-center problem using DNA computing by laboratory experiments.

Keywords: DNA computing, operation research, 1-center problem.

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Authors: Muhammad Rizwan Azhar, Emadadeen Ali

Abstract:

In this paper, periodic force operation of a wastewater treatment process has been studied for the improved process performance. A previously developed dynamic model for the process is used to conduct the performance analysis. The static version of the model was utilized first to determine the optimal productivity conditions for the process. Then, feed flow rate in terms of dilution rate i.e. (D) is transformed into sinusoidal function. Nonlinear model predictive control algorithm is utilized to regulate the amplitude and period of the sinusoidal function. The parameters of the feed cyclic functions are determined which resulted in improved productivity than the optimal productivity under steady state conditions. The improvement in productivity is found to be marginal and is satisfactory in substrate conversion compared to that of the optimal condition and to the steady state condition, which corresponds to the average value of the periodic function. Successful results were also obtained in the presence of modeling errors and external disturbances.

Keywords: Dilution rate, nonlinear model predictive control, sinusoidal function, wastewater treatment.

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Authors: J. K. Khare, Abhay Kumar Sharma, Ajay Tiwari, Amol A. Talankar

Abstract:

Powder metallurgy (P/M) is the only economic way to produce porous parts/products. P/M can produce near net shape parts hence reduces wastage of raw material and energy, avoids various machining operations. The most vital use of P/M is in production of metallic filters and self lubricating bush bearings and siding surfaces. The porosity of the part can be controlled by varying compaction pressure, sintering temperature and composition of metal powder mix. The present work is aimed for experimental analysis of friction and wear properties of self lubricating copper and tin bush bearing. Experimental results confirm that wear rate of sintered component is lesser for components having 10% tin by weight percentage. Wear rate increases for high tin percentage (experimented for 20% tin and 30% tin) at same sintering temperature. Experimental results also confirms that wear rate of sintered component is also dependent on sintering temperature, soaking period, composition of the preform, compacting pressure, powder particle shape and size. Interfacial friction between die and punch, between inter powder particles, between die face and powder particle depends on compaction pressure, powder particle size and shape, size and shape of component which decides size & shape of die & punch, material of die & punch and material of powder particles.

Keywords: Interfacial friction, porous bronze bearing, sintering temperature, wear rate.

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Authors: Seok Hong Min, Woo Young Jung, Tae Kwon Ha

Abstract:

Superplastic deformation and high temperature load relaxation behavior of coarse-grained iron aluminides with the composition of Fe-28 at.% Al have been investigated. A series of load relaxation and tensile tests were conducted at temperatures ranging from 600 to 850oC. The flow curves obtained from load relaxation tests were found to have a sigmoidal shape and to exhibit stress vs. strain rate data in a very wide strain rate range from 10-7/s to 10-2/s. Tensile tests have been conducted at various initial strain rates ranging from 3×10-5/s to 1×10-2/s. Maximum elongation of ~500 % was obtained at the initial strain rate of 3×10-5/s and the maximum strain rate sensitivity was found to be 0.68 at 850oC in binary Fe-28Al alloy. Microstructure observation through the optical microscopy (OM) and the electron back-scattered diffraction (EBSD) technique has been carried out on the deformed specimens and it has revealed the evidences for grain boundary migration and grain refinement to occur during superplastic deformation, suggesting the dynamic recrystallization mechanism. The addition of Cr by the amount of 5 at.% appeared to deteriorate the superplasticity of the binary iron aluminide. By applying the internal variable theory of structural superplasticity, the addition of Cr has been revealed to lower the contribution of the frictional resistance to dislocation glide during high temperature deformation of the Fe3Al alloy.

Keywords: Iron aluminide (Fe3Al), large grain size, structural superplasticity, dynamic recrystallization, chromium (Cr).

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Authors: Peter Odero Akuon

Abstract:

A rain cell ratio model is proposed that computes attenuation of the smallest rain cell which represents the maximum rain rate value i.e. the cell size when rainfall rate is exceeded 0.01% of the time, R_0.01 and predicts attenuation for other cells as the ratio with this maximum. This model incorporates the dependence of the path factor r on the ellipsoidal path variation of the Fresnel zone at different frequencies. In addition, the inhomogeneity of rainfall is modeled by a rain drop packing density factor. In order to derive the model, two empirical methods that can be used to find rain cell size distribution D_c are presented. Subsequently, attenuation measurements from different climatic zones for terrestrial radio links with frequencies F in the range 7-38 GHz are used to test the proposed model. Prediction results show that the path factor computed from the rain cell ratio technique has improved reliability when compared with other path factor and effective rain rate models, including the current ITU-R 530-15 model of 2013.

Keywords: Packing density of rain drops, prediction model, rain attenuation, rain cell ratio technique.

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Authors: S. A. Razavi Alavi, M. Torabi Angaji, Z. Gholami

Abstract:

In the process of polyethylene extrusion polymer material similar to powder or granule is under compression, melting and transmission operation and on base of special form, extrudate has been produced. Twin-screw extruders are applicable in industries because of their high capacity. The powder mixing with chemical additives and melting with thermal and mechanical energy in three zones (feed, compression and metering zone) and because of gear pump and screw's pressure, converting to final product in latest plate. Extruders with twin-screw and short distance between screws are better than other types because of their high capacity and good thermal and mechanical stress. In this paper, process of polyethylene extrusion and various tapes of extruders are studied. It is necessary to have an exact control on process to producing high quality products with safe operation and optimum energy consumption. The granule size is depending on granulator motor speed. Results show at constant feed rate a decrease in granule size was found whit Increase in motor speed. Relationships between HDPE feed rate and speed of granulator motor, main motor and gear pump are calculated following as: x = HDPE feed flow rate, yM = Main motor speed yM = (-3.6076e-3) x^4+ (0.24597) x^3+ (-5.49003) x^2+ (64.22092) x+61.66786 (1) x = HDPE feed flow rate, yG = Gear pump speed yG = (-2.4996e-3) x^4+ (0.18018) x^3+ (-4.22794) x^2+ (48.45536) x+18.78880 (2) x = HDPE feed flow rate, y = Granulator motor speed 10th Degree Polynomial Fit: y = a+bx+cx^2+dx^3... (3) a = 1.2751, b = 282.4655, c = -165.2098, d = 48.3106, e = -8.18715, f = 0.84997 g = -0.056094, h = 0.002358, i = -6.11816e-5 j = 8.919726e-7, k = -5.59050e-9

Keywords: Extrusion, Extruder, Granule, HDPE, Polymer, Twin-Screw extruder.

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Authors: Sabrina Gaito, Andrea Greppi, Giuliano Grossi

Abstract:

In this paper we present a technique to speed up ICA based on the idea of reducing the dimensionality of the data set preserving the quality of the results. In particular we refer to FastICA algorithm which uses the Kurtosis as statistical property to be maximized. By performing a particular Johnson-Lindenstrauss like projection of the data set, we find the minimum dimensionality reduction rate ¤ü, defined as the ratio between the size k of the reduced space and the original one d, which guarantees a narrow confidence interval of such estimator with high confidence level. The derived dimensionality reduction rate depends on a system control parameter β easily computed a priori on the basis of the observations only. Extensive simulations have been done on different sets of real world signals. They show that actually the dimensionality reduction is very high, it preserves the quality of the decomposition and impressively speeds up FastICA. On the other hand, a set of signals, on which the estimated reduction rate is greater than 1, exhibits bad decomposition results if reduced, thus validating the reliability of the parameter β. We are confident that our method will lead to a better approach to real time applications.

Keywords: Independent Component Analysis, FastICA algorithm, Higher-order statistics, Johnson-Lindenstrauss lemma.

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Authors: M. F. R. Zuthi, H. H. Ngo, W. S. Guo, S. S. Chen, N. C. Nguyen, L. J. Deng, T. D. C. Tran

Abstract:

Sustaining a desired rate of oxygen transfer for microbial activity is a matter of major concern for biological wastewater treatment (MBR). The study reported in the paper was aimed at assessing the effects of microbial products on the specific oxygen uptake rate (SOUR) in a conventional membrane bioreactor (CMBR) and that in a sponge submerged MBR (SSMBR). The production and progressive accumulation of soluble microbial products (SMP) and bound-extracellular polymeric substances (bEPS) were affecting the SOUR of the microorganisms which varied at different stages of operation of the MBR systems depending on the variable concentrations of the SMP/bEPS. The effect of bEPS on the SOUR was stronger in the SSMBR compared to that of the SMP, while relative high concentrations of SMP had adverse effects on the SOUR of the CMBR system. Of the different mathematical correlations analyzed in the study, logarithmic mathematical correlations could be established between SOUR and bEPS in SSMBR, and similar correlations could also be found between SOUR and SMP concentrations in the CMBR.

Keywords: Microbial products, Microbial activity, Specific oxygen uptake rate, Membrane bioreactor.

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Authors: L. Grinis, N. Lubashevsky, Y. Ostrovski

Abstract:

In wastewater treatment processes, aeration introduces air into a liquid. In these systems, air is introduced by different devices submerged in the wastewater. Smaller bubbles result in more bubble surface area per unit of volume and higher oxygen transfer efficiency. Jet pumps are devices that use air bubbles and are widely used in wastewater treatment processes. The principle of jet pumps is their ability to transfer energy of one fluid, called primary or motive, into a secondary fluid or gas. These pumps have no moving parts and are able to work in remote areas under extreme conditions. The objective of this work is to study experimentally the characteristics of the jet pump and the size of air bubbles in the laboratory water tank. The effect of flow rate ratio on pump performance is investigated in order to have a better understanding about pump behavior under various conditions, in order to determine the efficiency of receiving air bubbles different sizes. The experiments show that we should take care when increasing the flow rate ratio while seeking to decrease bubble size in the outlet flow. This study will help improve and extend the use of the jet pump in many practical applications.

Keywords: Jet pump, air bubbles size, retention time.

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Authors: Zohreh Orshesh

Abstract:

In this study, a 3D combustion chamber was simulated using FLUENT 6.32. Aim to obtain detailed information on combustion characteristics and _ nitrogen oxides in the furnace and the effect of oxygen enrichment in a combustion process. Oxygenenriched combustion is an effective way to reduce emissions. This paper analyzes NO emission, including thermal NO and prompt NO. Flow rate ratio of air to fuel is varied as 1.3, 3.2 and 5.1 and the oxygen enriched flow rates are 28, 54 and 68 lit/min. The 3D Reynolds Averaged Navier Stokes (RANS) equations with standard k-ε turbulence model are solved together by Fluent 6.32 software. First order upwind scheme is used to model governing equations and the SIMPLE algorithm is used as pressure velocity coupling. Results show that for AF=1.3, increase the oxygen flow rate of oxygen reduction in NO emissions is Lance. Moreover, in a fixed oxygen enrichment condition, increasing the air to fuel ratio will increase the temperature peak, but not the NO emission rate. As a result, oxygen enrichment can reduce the NO emission at this kind of furnace in low air to fuel rates.

Keywords: Combustion chamber, Oxygen enrichment, Reynolds Averaged Navier- Stokes, NO emission

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Authors: Hiroki Satou, Kayoko Yamamoto

Abstract:

This study aims to propose three evaluation methods to evaluate the Tokyo Cap and Trade Program when emissions trading is performed virtually among enterprises, focusing on carbon dioxide (CO2), which is the only emitted greenhouse gas that tends to increase. The first method clarifies the optimum reduction rate for the highest cost benefit, the second discusses emissions trading among enterprises through market trading, and the third verifies long-term emissions trading during the term of the plan (2010-2019), checking the validity of emissions trading partly using Geographic Information Systems (GIS). The findings of this study can be summarized in the following three points. 1. Since the total cost benefit is the greatest at a 44% reduction rate, it is possible to set it more highly than that of the Tokyo Cap and Trade Program to get more total cost benefit. 2. At a 44% reduction rate, among 320 enterprises, 8 purchasing enterprises and 245 sales enterprises gain profits from emissions trading, and 67 enterprises perform voluntary reduction without conducting emissions trading. Therefore, to further promote emissions trading, it is necessary to increase the sales volumes of emissions trading in addition to sales enterprises by increasing the number of purchasing enterprises. 3. Compared to short-term emissions trading, there are few enterprises which benefit in each year through the long-term emissions trading of the Tokyo Cap and Trade Program. Only 81 enterprises at the most can gain profits from emissions trading in FY 2019. Therefore, by setting the reduction rate more highly, it is necessary to increase the number of enterprises that participate in emissions trading and benefit from the restraint of CO2 emissions.

Keywords: Emissions Trading, Tokyo Cap and Trade Program, Carbon Dioxide (CO2), Global Warming, Geographic Information Systems (GIS)

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Authors: A. Ahadpour Shal, A. Ghadimi, A. Azadbar

Abstract:

In this paper a new method for increasing the speed of SAGCM-APD is proposed. Utilizing carrier rate equations in different regions of the structure, a circuit model for the structure is obtained. In this research, in addition to frequency response, the effect of added new charge layer on some transient parameters like slew-rate, rising and falling times have been considered. Finally, by trading-off among some physical parameters such as different layers widths and droppings, a noticeable decrease in breakdown voltage has been achieved. The results of simulation, illustrate some features of proposed structure improvement in comparison with conventional SAGCM-APD structures.

Keywords: Optical communication systems (OCS), Circuit modeling, breakdown voltage, SAGCM APD

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Authors: Mohammad Akbarpour, Reza Nasiri Mahalati, Caro Lucas

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The existence of many biological systems, especially human societies, is based on cooperative behavior [1, 2]. If natural selection favors selfish individuals, then what mechanism is at work that we see so many cooperative behaviors? One answer is the effect of network structure. On a graph, cooperators can evolve by forming network bunches [2, 3, 4]. In a research, Ohtsuki et al used the idea of iterated prisoners- dilemma on a graph to model an evolutionary game. They showed that the average number of neighbors plays an important role in determining whether cooperation is the ESS of the system or not [3]. In this paper, we are going to study the dynamics of evolution of cooperation in a social network. We show that during evolution, the ratio of cooperators among individuals with fewer neighbors to cooperators among other individuals is greater than unity. The extent to which the fitness function depends on the payoff of the game determines this ratio.

Keywords: Evolution of cooperation, Iterated prisoner's dilemma, Model dynamics, Social network structure, Intensity of selection.

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Authors: Mangesh R. Phate, V. H. Tatwawadi

Abstract:

This paper is intended to develop an artificial neural network (ANN) based model of material removal rate (MRR) in the turning of ferrous and nonferrous material in a Indian small-scale industry. MRR of the formulated model was proved with the testing data and artificial neural network (ANN) model was developed for the analysis and prediction of the relationship between inputs and output parameters during the turning of ferrous and nonferrous materials. The input parameters of this model are operator, work-piece, cutting process, cutting tool, machine and the environment.

The ANN model consists of a three layered feedforward back propagation neural network. The network is trained with pairs of independent/dependent datasets generated when machining ferrous and nonferrous material. A very good performance of the neural network, in terms of contract with experimental data, was achieved. The model may be used for the testing and forecast of the complex relationship between dependent and the independent parameters in turning operations.

Keywords: Field data based model, Artificial neural network, Simulation, Convectional Turning, Material removal rate.

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Authors: Pushpendra S. Bharti, S. Maheshwari

Abstract:

Electric discharge machining (EDM) is one of the most widely used non-conventional manufacturing process to shape difficult-to-cut materials. The process yield, in terms of material removal rate, surface roughness and tool wear rate, of EDM may considerably be improved by selecting the optimal combination(s) of process parameters. This paper employs Multi-response signal-to-noise (MRSN) ratio technique to find the optimal combination(s) of the process parameters during EDM of Inconel 718. Three cases v.i.z. high cutting efficiency, high surface finish, and normal machining have been taken and the optimal combinations of input parameters have been obtained for each case. Analysis of variance (ANOVA) has been employed to find the dominant parameter(s) in all three cases. The experimental verification of the obtained results has also been made. MRSN ratio technique found to be a simple and effective multi-objective optimization technique.

Keywords: EDM, material removal rate, multi-response signal-to-noise ratio, optimization, surface roughness.

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Authors: Bing Song, Kexi Han, Xuewei Lv

Abstract:

Titania slag is a high quality raw material containing titanium in the subsequent process of titanium pigment. The effects of cooling approaches of granulating, water cooling, and air cooling on chemical, phases, and acidolysis of Panzhihua titania slag were investigated. Compared to the original slag which was prepared by the conventional processing route, the results show that the titania slag undergoes oxidation of Ti³⁺during different cooling ways. The Ti₂O₃ content is 17.50% in the original slag, but it is 16.55% and 16.84% in water cooled and air-cooled slag, respectively. Especially, the Ti₂O₃ content in granulated slag is decreased about 27.6%. The content of Fe₂O₃ in granulated slag is approximately 2.86% also obviously higher than water (<0.5%) or air-cooled slag (<0.5%). Rutile in cooled titania slag was formed because of the oxidation of Ti³⁺. The rutile phase without a noticeable change in water cooled and air-cooled slag after the titania slag was cooled, but increased significantly in the granulated slag. The rate of sulfuric acid acidolysis of cooled slag is less than the original slag. The rate of acidolysis is 90.61% and 92.46% to the water-cooled slag and air-cooled slag, respectively. However, the rate of acidolysis of the granulated slag is less than that of industry slag about 20%, only 74.72%.

Keywords: Cooling approaches, titania slag, granulating, sulfuric acid acidolysis,

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Authors: Ryad Zemouri, Paul Ciprian Patic

Abstract:

An adaptive software reliability prediction model using evolutionary connectionist approach based on Recurrent Radial Basis Function architecture is proposed. Based on the currently available software failure time data, Fuzzy Min-Max algorithm is used to globally optimize the number of the k Gaussian nodes. The corresponding optimized neural network architecture is iteratively and dynamically reconfigured in real-time as new actual failure time data arrives. The performance of our proposed approach has been tested using sixteen real-time software failure data. Numerical results show that our proposed approach is robust across different software projects, and has a better performance with respect to next-steppredictability compared to existing neural network model for failure time prediction.

Keywords: Neural network, Prediction error, Recurrent RadialBasis Function Network, Reliability prediction.

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