Search results for: phase error accumulation methodology

Authors: Feng Wang, Shencheng Ni, Shuying Han, Shanhong You

Abstract:

With the development of optical communication, optical performance monitoring (OPM) has received more and more attentions. Since optical signal-to-noise ratio (OSNR) is directly related to bit error rate (BER), it is one of the important parameters in optical networks. Recently, artificial neural network (ANN) has been greatly developed. ANN has strong learning and generalization ability. In this paper, a method of OSNR monitoring based on delay-tap sampling (DTS) and ANN has been proposed. DTS technique is used to extract the eigenvalues of the signal. Then, the eigenvalues are input into the ANN to realize the OSNR monitoring. The experiments of 10 Gb/s non-return-to-zero (NRZ) on–off keying (OOK), 20 Gb/s pulse amplitude modulation (PAM4) and 20 Gb/s return-to-zero (RZ) differential phase-shift keying (DPSK) systems are demonstrated for the OSNR monitoring based on the proposed method. The experimental results show that the range of OSNR monitoring is from 15 to 30 dB and the root-mean-square errors (RMSEs) for 10 Gb/s NRZ-OOK, 20 Gb/s PAM4 and 20 Gb/s RZ-DPSK systems are 0.36 dB, 0.45 dB and 0.48 dB respectively. The impact of chromatic dispersion (CD) on the accuracy of OSNR monitoring is also investigated in the three experimental systems mentioned above.

Keywords: Artificial neural network, ANN, chromatic dispersion, delay-tap sampling, optical signal-to-noise ratio, OSNR.

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Authors: R. Clancy, M. Ahern, D. O’Sullivan, K. Bruton

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The manufacturing industry is currently undergoing a digital transformation as part of the mega-trend Industry 4.0. As part of this phase of the industrial revolution, traditional manufacturing processes are being combined with digital technologies to achieve smarter and more efficient production. To successfully digitally transform a manufacturing facility, the processes must first be digitized. This is the conversion of information from an analogue format to a digital format. The objective of this study was to explore the research area of digitizing manufacturing data as part of the worldwide paradigm, Industry 4.0. The formal methodology of a systematic mapping study was utilized to capture a representative sample of the research area and assess its current state. Specific research questions were defined to assess the key benefits and limitations associated with the digitization of manufacturing data. Research papers were classified according to the type of research and type of contribution to the research area. Upon analyzing 54 papers identified in this area, it was noted that 23 of the papers originated in Germany. This is an unsurprising finding as Industry 4.0 is originally a German strategy with supporting strong policy instruments being utilized in Germany to support its implementation. It was also found that the Fraunhofer Institute for Mechatronic Systems Design, in collaboration with the University of Paderborn in Germany, was the most frequent contributing Institution of the research papers with three papers published. The literature suggested future research directions and highlighted one specific gap in the area. There exists an unresolved gap between the data science experts and the manufacturing process experts in the industry. The data analytics expertise is not useful unless the manufacturing process information is utilized. A legitimate understanding of the data is crucial to perform accurate analytics and gain true, valuable insights into the manufacturing process. There lies a gap between the manufacturing operations and the information technology/data analytics departments within enterprises, which was borne out by the results of many of the case studies reviewed as part of this work. To test the concept of this gap existing, the researcher initiated an industrial case study in which they embedded themselves between the subject matter expert of the manufacturing process and the data scientist. Of the papers resulting from the systematic mapping study, 12 of the papers contributed a framework, another 12 of the papers were based on a case study, and 11 of the papers focused on theory. However, there were only three papers that contributed a methodology. This provides further evidence for the need for an industry-focused methodology for digitizing and analyzing manufacturing data, which will be developed in future research.

Keywords: Analytics, digitization, industry 4.0, manufacturing.

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Authors: E. Asadollahi-Yazdi, J. Gardan, P. Lafon

Abstract:

Nowadays, manufactures are encountered with production of different version of products due to quality, cost and time constraints. On the other hand, Additive Manufacturing (AM) as a production method based on CAD model disrupts the design and manufacturing cycle with new parameters. To consider these issues, the researchers utilized Design For Manufacturing (DFM) approach for AM but until now there is no integrated approach for design and manufacturing of product through the AM. So, this paper aims to provide a general methodology for managing the different production issues, as well as, support the interoperability with AM process and different Product Life Cycle Management tools. The problem is that the models of System Engineering which is used for managing complex systems cannot support the product evolution and its impact on the product life cycle. Therefore, it seems necessary to provide a general methodology for managing the product’s diversities which is created by using AM. This methodology must consider manufacture and assembly during product design as early as possible in the design stage. The latest approach of DFM, as a methodology to analyze the system comprehensively, integrates manufacturing constraints in the numerical model in upstream. So, DFM for AM is used to import the characteristics of AM into the design and manufacturing process of a hybrid product to manage the criteria coming from AM. Also, the research presents an integrated design method in order to take into account the knowledge of layers manufacturing technologies. For this purpose, the interface model based on the skin and skeleton concepts is provided, the usage and manufacturing skins are used to show the functional surface of the product. Also, the material flow and link between the skins are demonstrated by usage and manufacturing skeletons. Therefore, this integrated approach is a helpful methodology for designer and manufacturer in different decisions like material and process selection as well as, evaluation of product manufacturability.

Keywords: Additive manufacturing, 3D printing, design for manufacturing, integrated design, interoperability.

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Authors: Prathuang Usaborisut, Dithaporn Thungsotanon

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Soil compaction induced by a tractor towing trailer becomes a major problem associated to sugarcane productivity. Soil beneath the tractor’s tire is not only under compressing stress but also shearing stress. Therefore, in order to help to understand such effects on soil, this research aimed to determine stress state in soil and predict compaction of soil under a tractive tire. The octahedral stress ratios under the tires were higher than one and much higher under higher draft forces. Moreover, the ratio was increasing with increase of number of tire’s passage. Soil compaction model was developed using data acquired from triaxial tests. The model was then used to predict soil bulk density under tractive tire. The maximum error was about 4% at 15 cm depth under lower draft force and tended to increase with depth and draft force. At depth of 30 cm and under higher draft force, the maximum error was about 16%.

Keywords: Draft force, soil compaction model, stress state, tractive tire.

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Authors: Yohei Saika, Hiroki Sakaematsu, Shota Akiyama

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We investigated statistical performance of Bayesian inference using maximum entropy and MAP estimation for several models which approximated wave-fronts in remote sensing using SAR interferometry. Using Monte Carlo simulation for a set of wave-fronts generated by assumed true prior, we found that the method of maximum entropy realized the optimal performance around the Bayes-optimal conditions by using model of the true prior and the likelihood representing optical measurement due to the interferometer. Also, we found that the MAP estimation regarded as a deterministic limit of maximum entropy almost achieved the same performance as the Bayes-optimal solution for the set of wave-fronts. Then, we clarified that the MAP estimation perfectly carried out phase unwrapping without using prior information, and also that the MAP estimation realized accurate phase unwrapping using conjugate gradient (CG) method, if we assumed the model of the true prior appropriately.

Keywords: Bayesian inference using maximum entropy, MAP estimation using conjugate gradient method, SAR interferometry.

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Authors: Kevin Spencer G. Anglim, Zhenyu Zhang, Qingbin Gao

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Reusable launch vehicles (RLVs) present a more environmentally-friendly approach to accessing space when compared to traditional launch vehicles that are discarded after each flight. This paper studies the recyclable nature of RLVs by presenting a solution method for determining minimum-fuel optimal trajectories using principles from optimal control theory and particle swarm optimization (PSO). This problem is formulated as a minimum-landing error powered descent problem where it is desired to move the RLV from a fixed set of initial conditions to three different sets of terminal conditions. However, unlike other powered descent studies, this paper considers the highly nonlinear effects caused by atmospheric drag, which are often ignored for studies on the Moon or on Mars. Rather than optimizing the controls directly, the throttle control is assumed to be bang-off-bang with a predetermined thrust direction for each phase of flight. The PSO method is verified in a one-dimensional comparison study, and it is then applied to the two-dimensional cases, the results of which are illustrated.

Keywords: Minimum-fuel optimal trajectory, particle swarm optimization, reusable rocket, SpaceX.

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Authors: A. Lauvray, F. Poulhaon, P. Michaud, P. Joyot, E. Duc

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Additive Friction Stir Manufacturing, or AFSM, is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. There is still a lack in understanding of the physical phenomena taking place during the process. This research aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system due to pure friction. An analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable, due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes through a numerical modeling followed by an experimental validation to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, frictional heat generation, process

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Authors: Yilun Shang

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We study a long-range percolation model in the hierarchical lattice ΩN of order N where probability of connection between two nodes separated by distance k is of the form min{αβ−k, 1}, α ≥ 0 and β > 0. The parameter α is the percolation parameter, while β describes the long-range nature of the model. The ΩN is an example of so called ultrametric space, which has remarkable qualitative difference between Euclidean-type lattices. In this paper, we characterize the sizes of large clusters for this model along the line of some prior work. The proof involves a stationary embedding of ΩN into Z. The phase diagram of this long-range percolation is well understood.

Keywords: percolation, component, hierarchical lattice, phase transition.

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Authors: Prince Mugoya, Collins Oduor Ondiek, Patrick Kanyi Wamuyu

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Refugee Job Board Website is a web-based application that provides a platform for organizations to post jobs specifically for refugees. Organizations upload job opportunities and refugees can view them on the website. The website also allows refugees to input their skills and qualifications. The methodology used to develop this system is a waterfall (traditional) methodology. Software development tools include Brackets which will be used to code the website and PhpMyAdmin to store all the data in a database.

Keywords: Information technology, refugee, skills, utilization, economy, jobs.

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

Abstract:

A seizure prediction method is proposed by extracting global features using phase correlation between adjacent epochs for detecting relative changes and local features using fluctuation/ deviation within an epoch for determining fine changes of different EEG signals. A classifier and a regularization technique are applied for the reduction of false alarms and improvement of the overall prediction accuracy. The experiments show that the proposed method outperforms the state-of-the-art methods and provides high prediction accuracy (i.e., 97.70%) with low false alarm using EEG signals in different brain locations from a benchmark data set.

Keywords: Epilepsy, Seizure, Phase Correlation, Fluctuation, Deviation.

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Authors: A. I. Alateyah, H. N. Dhakal, Z. Y. Zhang

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The study of the effect of the processing parameters on the level of intercalation between the layered silicate and polymer of two different methodology took place. X-ray diffraction, Scanning Electron Microscopy, Energy Dispersive X-ray Spectrometry, and Transmission Electron Microscopy were utilized in order to examine the intercalation level of nanocomposites of both methodologies. It was found that drying the clay prior to mixing with the polymer, mixing time and speed, degassing time, and the curing method had major changes to the level of distribution of the nanocomposites structure. In methodology 1, the presence of aggregation layers was observed at only 2.5 wt.% clay loading whereas in methodology 2 the presence of aggregation layers was found at higher clay loading (i.e. 5 wt.%).

Keywords: Vinyl ester, nanocomposites, layered silicate, characterisations, aggregation layers, intercalation, exfoliation.

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Authors: J. Tonkonogij, A. Pedišius, A. Stankevičius

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The new semi-experimental method for simulation of the turbine flow meters rotation in the transitional flow has been developed. The method is based on the experimentally established exponential low of changing of dimensionless relative turbine gas meter rotation frequency and meter inertia time constant. For experimental evaluation of the meter time constant special facility has been developed. The facility ensures instant switching of turbine meter under test from one channel to the other channel with different flow rate and measuring the meter response. The developed method can be used for evaluation and predication of the turbine meters response and dynamic error in the transitional flow with any arbitrary law of flow rate changing. The examples of the method application are presented.

Keywords: Dynamic error, pulsing flow, numerical simulation, response, turbine gas meters.

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Authors: W. Devapriya, C. Nelson Kennedy Babu, T. Srihari

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Automatic License plate recognition (ALPR) is a technology which recognizes the registration plate or number plate or License plate of a vehicle. In this paper, an Indian vehicle number plate is mined and the characters are predicted in efficient manner. ALPR involves four major technique i) Pre-processing ii) License Plate Location Identification iii) Individual Character Segmentation iv) Character Recognition. The opening phase, named pre-processing helps to remove noises and enhances the quality of the image using the conception of Morphological Operation and Image subtraction. The second phase, the most puzzling stage ascertain the location of license plate using the protocol Canny Edge detection, dilation and erosion. In the third phase, each characters characterized by Connected Component Approach (CCA) and in the ending phase, each segmented characters are conceptualized using cross correlation template matching- a scheme specifically appropriate for fixed format. Major application of ALPR is Tolling collection, Border Control, Parking, Stolen cars, Enforcement, Access Control, Traffic control. The database consists of 500 car images taken under dissimilar lighting condition is used. The efficiency of the system is 97%. Our future focus is Indian Vehicle License Plate Validation (Whether License plate of a vehicle is as per Road transport and highway standard).

Keywords: Automatic License plate recognition, Character recognition, Number plate Recognition, Template matching, morphological operation, canny edge detection.

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Authors: Ehigiamusoe, Uyi Kizito

Abstract:

The paper examines the impact of money market on economic growth in Nigeria using data for the period 1980-2012. Econometrics techniques such as Ordinary Least Squares Method, Johanson’s Co-integration Test and Vector Error Correction Model were used to examine both the long-run and short-run relationship. Evidence from the study suggest that though a long-run relationship exists between money market and economic growth, but the present state of the Nigerian money market is significantly and negatively related to economic growth. The link between the money market and the real sector of the economy remains very weak. This implies that the market is not yet developed enough to produce the needed growth that will propel the Nigerian economy because of several challenges. It was therefore recommended that government should create the appropriate macroeconomic policies, legal framework and sustain the present reforms with a view to developing the market so as to promote productive activities, investments, and ultimately economic growth.

Keywords: Economic Growth, Investments, Money Market, Money Market Challenges, Money Market Instruments.

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Authors: Luciana C. Ramos, Leandro J. Sousa, Antônio Ferreira da Silva, Valéria Gomes Oliveira Falcão, Suzana T. Cunha Lima

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The commercial production of biodiesel using microalgae demands a high-energy input for harvesting biomass, making production economically unfeasible. Methods currently used involve mechanical, chemical, and biological procedures. In this work, a flocculation system is presented as a cost and energy effective process to increase biomass production of Phaeodactylum tricornutum. This diatom is the only species of the genus that present fast growth and lipid accumulation ability that are of great interest for biofuel production. The algae, selected from the Bank of Microalgae, Institute of Biology, Federal University of Bahia (Brazil), have been bred in tubular reactor with photoperiod of 12 h (clear/dark), providing luminance of about 35 μmol photons m^-2s^-1, and temperature of 22 °C. The medium used for growing cells was the Conway medium, with addition of silica. The seaweed growth curve was accompanied by cell count in Neubauer camera and by optical density in spectrophotometer, at 680 nm. The precipitation occurred at the end of the stationary phase of growth, 21 days after inoculation, using two methods: centrifugation at 5000 rpm for 5 min, and electro-flocculation at 19 EPD and 95 W. After precipitation, cells were frozen at -20 °C and, subsequently, lyophilized. Biomass obtained by electro-flocculation was approximately four times greater than the one achieved by centrifugation. The benefits of this method are that no addition of chemical flocculants is necessary and similar cultivation conditions can be used for the biodiesel production and pharmacological purposes. The results may contribute to improve biodiesel production costs using marine microalgae.

Keywords: Biomass, diatom, flocculation, microalgae.

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Authors: Jamal R. Elbergali

Abstract:

Multiple Input Multiple Output (MIMO) systems are wireless systems with multiple antenna elements at both ends of the link. Wireless communication systems demand high data rate and spectral efficiency with increased reliability. MIMO systems have been popular techniques to achieve these goals because increased data rate is possible through spatial multiplexing scheme and diversity. Spatial Multiplexing (SM) is used to achieve higher possible throughput than diversity. In this paper, we propose a Zero- Forcing (ZF) detection using a combination of Ordered Successive Interference Cancellation (OSIC) and Zero Forcing using Interference Cancellation (ZF-IC). The proposed method used an OSIC based on Signal to Noise Ratio (SNR) ordering to get the estimation of last symbol, then the estimated last symbol is considered to be an input to the ZF-IC. We analyze the Bit Error Rate (BER) performance of the proposed MIMO system over Rayleigh Fading Channel, using Binary Phase Shift Keying (BPSK) modulation scheme. The results show better performance than the previous methods.

Keywords: SNR, BER, BPSK, MIMO, Modulation, Zero forcing (ZF), OSIC, ZF-IC, Spatial Multiplexing (SM).

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Authors: R. Haoui

Abstract:

Hypersonic flows around spatial vehicles during their reentry phase in planetary atmospheres are characterized by intense aerothermodynamics phenomena. The aim of this work is to analyze high temperature flows around an axisymmetric blunt body taking into account chemical and vibrational non-equilibrium for air mixture species and the no slip condition at the wall. For this purpose, the Navier-Stokes equations system is resolved by the finite volume methodology to determine the flow parameters around the axisymmetric blunt body especially at the stagnation point and in the boundary layer along the wall of the blunt body. The code allows the capture of shock wave before a blunt body placed in hypersonic free stream. The numerical technique uses the Flux Vector Splitting method of Van Leer. CFL coefficient and mesh size level are selected to ensure the numerical convergence.

Keywords: Hypersonic flow, viscous flow, chemical kinetic, dissociation, finite volumes, frozen and non-equilibrium flow.

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Authors: M.R. Mustafa, M.H. Isa, R.B. Rezaur

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Prediction of highly non linear behavior of suspended sediment flow in rivers has prime importance in the field of water resources engineering. In this study the predictive performance of two Artificial Neural Networks (ANNs) namely, the Radial Basis Function (RBF) Network and the Multi Layer Feed Forward (MLFF) Network have been compared. Time series data of daily suspended sediment discharge and water discharge at Pari River was used for training and testing the networks. A number of statistical parameters i.e. root mean square error (RMSE), mean absolute error (MAE), coefficient of efficiency (CE) and coefficient of determination (R2) were used for performance evaluation of the models. Both the models produced satisfactory results and showed a good agreement between the predicted and observed data. The RBF network model provided slightly better results than the MLFF network model in predicting suspended sediment discharge.

Keywords: ANN, discharge, modeling, prediction, suspendedsediment,

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Authors: Peter Drotar, Juraj Gazda, Pavol Galajda, Dusan Kocur

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The study in this paper underlines the importance of correct joint selection of the spreading codes for uplink of multicarrier code division multiple access (MC-CDMA) at the transmitter side and detector at the receiver side in the presence of nonlinear distortion due to high power amplifier (HPA). The bit error rate (BER) of system for different spreading sequences (Walsh code, Gold code, orthogonal Gold code, Golay code and Zadoff-Chu code) and different kinds of receivers (minimum mean-square error receiver (MMSE-MUD) and microstatistic multi-user receiver (MSF-MUD)) is compared by means of simulations for MC-CDMA transmission system. Finally, the results of analysis will show, that the application of MSF-MUD in combination with Golay codes can outperform significantly the other tested spreading codes and receivers for all mostly used models of HPA.

Keywords: HPA, MC-CDMA, microstatistic filter, multi-user receivers, PAPR.

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Authors: Khaing Win Mar, Thinn Thu Naing

Abstract:

Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.

Keywords: Precipitation prediction, monthly precipitation, neural network models, Myanmar.

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Authors: Yin Yin Phyo, Tun Lin Naing

Abstract:

This paper investigated the simulation of two-phase interleaved boost converter (IBC) with free and open-source software Scilab/Xcos. By using interleaved method, it can reduce current stress on components, components size, input current ripple and output voltage ripple. The required mathematical model is obtained from the equivalent circuit of its different four modes of operation for simulation. The equivalent circuits are considered in continuous conduction mode (CCM). The average values of the system variables are derived from the state-space equation to find the equilibrium point. Scilab is now becoming more and more popular among students, engineers and scientists because it is open-source software and free of charge. It gives a great convenience because it has powerful computation and simulation function. The waveforms of output voltage, input current and inductors current are obtained by using Scilab/Xcos.

Keywords: Two-phase boost converter, continuous conduction mode, free and open-source, interleaved method, dynamic simulation.

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Authors: X. Vecino, J. M. Cruz, A. Moldes

Abstract:

The disposal and the treatment of sewage sludge is an expensive and environmentally complex problem. In this work, a lipopeptide biosurfactant extracted from corn steep liquor was used as ecofriendly and cost-competitive alternative for the mobilization and bioremediation of fluorene in sewage sludge. Results have demonstrated that this biosurfactant has the capability to mobilize fluorene to the aqueous phase, reducing the amount of fluorene in the sewage sludge from 484.4 mg/Kg up to 413.7 mg/Kg and 196.0 mg/Kg after 1 and 27 days respectively. Furthermore, once the fluorene was extracted the lipopeptide biosurfactant contained in the aqueous phase allowed the biodegradation, up to 40.5% of the initial concentration of this polycyclic aromatic hydrocarbon.

Keywords: Fluorene, lipopeptide biosurfactant, mobilization, sewage sludge.

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Authors: Joon-Hyung Kim, Him-Chan Lee, Jin-Hyuk Kim, Yong-Kab Lee, Young-Seok Choi

Abstract:

The crude oil in an oil well exists in various phases such as gas, seawater, and sand, as well as oil. Therefore, a phase separator is needed at the front of a single-phase pump for pressurization and transfer. On the other hand, the application of a multiphase pump can provide such advantages as simplification of the equipment structure and cost savings, because there is no need for a phase separation process. Therefore, the crude oil transfer method using a multiphase pump is being applied to recently developed oil wells. Due to this increase in demand, technical demands for the development of multiphase pumps are sharply increasing, but the progress of research into related technologies is insufficient, due to the nature of multiphase pumps that require high levels of skills. This study was conducted to verify the reliability of pump performance evaluation using numerical analysis, which is the basis of the development of a multiphase pump. For this study, a model was designed by selecting the specifications of this study. The performance of the designed model was evaluated through numerical analysis and experiment. The results of the performance evaluation were compared to verify the reliability of the result using numerical analysis.

Keywords: Multiphase pump, Numerical analysis, Experiment, Performance evaluation, Reliability verification.

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Authors: Anna Fredriksson Häägg, Charlotte Weil, Niklas Rönnberg

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Map-based dashboards are used for data exploration every day. The present study used an insight-based methodology for evaluating a map-based dashboard that presents research findings of water management and ecosystem services in the Amazon. In addition to analyzing the insights gained from using the dashboard, the evaluation method was compared to standardized questionnaires and task-based evaluations. The result suggests that the dashboard enabled the participants to gain domain-relevant, complex insights regarding the topic presented. Furthermore, the insight-based analysis highlighted unexpected insights and hypotheses regarding causes and potential adaptation strategies for remediation. Although time- and resource-consuming, the insight-based methodology was shown to have the potential of thoroughly analyzing how end users can utilize map-based dashboards for data exploration and decision making. Finally, the insight-based methodology is argued to evaluate tools in scenarios more similar to real-life usage, compared to task-based evaluation methods.

Keywords: Visual analytics, dashboard, insight-based evaluation, geographic visualization.

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Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom

Abstract:

The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. Previous work established that the Ward-style artificial neural network (ANN) is a suitable tool for developing such models. The current research focused on developing ANN models with reduced average prediction error by increasing the number of distinct observations used in training, adding additional input terms that describe the date of an observation, increasing the duration of prior weather data included in each observation, and reexamining the number of hidden nodes used in the network. Models were created to predict air temperature at hourly intervals from one to 12 hours ahead. Each ANN model, consisting of a network architecture and set of associated parameters, was evaluated by instantiating and training 30 networks and calculating the mean absolute error (MAE) of the resulting networks for some set of input patterns. The inclusion of seasonal input terms, up to 24 hours of prior weather information, and a larger number of processing nodes were some of the improvements that reduced average prediction error compared to previous research across all horizons. For example, the four-hour MAE of 1.40°C was 0.20°C, or 12.5%, less than the previous model. Prediction MAEs eight and 12 hours ahead improved by 0.17°C and 0.16°C, respectively, improvements of 7.4% and 5.9% over the existing model at these horizons. Networks instantiating the same model but with different initial random weights often led to different prediction errors. These results strongly suggest that ANN model developers should consider instantiating and training multiple networks with different initial weights to establish preferred model parameters.

Keywords: Decision support systems, frost protection, fruit, time-series prediction, weather modeling

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Authors: K. Shakeri, M. Mohebbi

Abstract:

In order to consider the effects of the higher modes in the pushover analysis, during the recent years several multi-modal pushover procedures have been presented. In these methods the response of the considered modes are combined by the square-rootof- sum-of-squares (SRSS) rule while application of the elastic modal combination rules in the inelastic phases is no longer valid. In this research the feasibility of defining an efficient alternative combination method is investigated. Two steel moment-frame buildings denoted SAC-9 and SAC-20 under ten earthquake records are considered. The nonlinear responses of the structures are estimated by the directed algebraic combination of the weighted responses of the separate modes. The weight of the each mode is defined so that the resulted response of the combination has a minimum error to the nonlinear time history analysis. The genetic algorithm (GA) is used to minimize the error and optimize the weight factors. The obtained optimal factors for each mode in different cases are compared together to find unique appropriate weight factors for each mode in all cases.

Keywords: Genetic Algorithm, Modal Pushover, Optimalweight.

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

Abstract:

The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: Data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse.

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Authors: Weiling Li, Wenqi Zhong, Baosheng Jin, Rui Xiao, Yong Lu, Tingting He

Abstract:

Experiments were performed in a three-phase bubble column to study variations of bubble rise velocities. The dynamic gas disengagement (DGD) technique and the fast response pressure transducers were utilized to investigate the bubble rise in the column. The superficial gas velocity of large bubbles and small bubbles, the rise velocities of larger and small bubble fractions were studied considering the effect of particle sizes. The results show that the superficial gas velocity associated with large bubbles linearly increase as superficial gas velocity increasing. Particle size has little effect on the both large and small bubble superficial gas velocities. The rise velocities of larger bubble fractions are larger than that of small bubble fractions, and it had different tendency at low and high superficial gas velocities when changing the particle sizes. The rise velocities of small bubble fractions increased and then had a decrease tendency when the particle size became greater.

Keywords: Bubble rise velocity, gas–liquid–solid, particle size effect, three–phase bubble column.

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Authors: Júlia Szőke

Abstract:

Negotiating across cultures needs consideration as different cultures have different norms, habits and behavioral patterns. The significance of cross-cultural negotiations lies in the fact that many business relationships have already failed due to the lack of cultural knowledge. Therefore, the paper deals with cross-cultural negotiations in case of Hungarian business negotiators. The aim of the paper is to introduce the findings of a two-phase research conducted among Hungarian business negotiators. In the first phase a qualitative research was conducted to reveal the importance of cultural differences in case of cross-cultural business negotiations from the viewpoint of Hungarian negotiators, whereas in the second phase a quantitative one was conducted to figure out whether cultural stereotypes affect the way how the respondents negotiate with people coming from different cultures. The research found out that in case of Hungarian negotiators it is mostly the lack of cultural knowledge that lurks behind the problems and miscommunication occurring during the negotiations. The research also revealed that stereotypes have an influence on the negotiation styles of Hungarian negotiators. The paper concludes that culture and cultural differences must be taken into consideration in case of cross-cultural negotiations so that problems and misunderstandings could be avoided.

Keywords: Business, culture, negotiations, stereotypes.

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Authors: M. Chandrasekaran, D. Devarasiddappa

Abstract:

Metal matrix composites have been increasingly used as materials for components in automotive and aerospace industries because of their improved properties compared with non-reinforced alloys. During machining the selection of appropriate machining parameters to produce job for desired surface roughness is of great concern considering the economy of manufacturing process. In this study, a surface roughness prediction model using fuzzy logic is developed for end milling of Al-SiCp metal matrix composite component using carbide end mill cutter. The surface roughness is modeled as a function of spindle speed (N), feed rate (f), depth of cut (d) and the SiCp percentage (S). The predicted values surface roughness is compared with experimental result. The model predicts average percentage error as 4.56% and mean square error as 0.0729. It is observed that surface roughness is most influenced by feed rate, spindle speed and SiC percentage. Depth of cut has least influence.

Keywords: End milling, fuzzy logic, metal matrix composites, surface roughness

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