Search results for: velocity prediction program

Authors: Takeru Furuawa, Kohei Takizawa, Daisuke Kuwahara, Shunjiro Shinohara

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In the field of a space propulsion, an electric propulsion system has been developed because its fuel efficiency is much higher than a conventional chemical one. However, the practical electric propulsion systems, e.g., an ion engine, have a problem of short lifetime due to a damage of generation and acceleration electrodes of the plasma. A helicon plasma thruster is proposed as a long-lifetime electric thruster which has non-direct contact electrodes. In this system, both generation and acceleration methods of a dense plasma are executed by antennas from the outside of a discharge tube. Development of the helicon plasma thruster has been conducting under the Helicon Electrodeless Advanced Thruster (HEAT) project. Our helicon plasma thruster has two important processes. First, we generate a dense source plasma using a helicon wave with an excitation frequency between an ion and an electron cyclotron frequencies, fci and fce, respectively, applied from the outside of a discharge using a radio frequency (RF) antenna. The helicon plasma source can provide a high-density (~1019 m-3), a high-ionization ratio (up to several tens of percent), and a high particle generation efficiency. Second, in order to achieve high thrust and specific impulse, we accelerate the dense plasma by the axial Lorentz force fz using the product of the induced azimuthal current jθ and the static radial magnetic field Br, shown as fz = jθ × Br. The HEAT project has proposed several kinds of electrodeless acceleration schemes, and in our particular case, a Rotating Magnetic Field (RMF) method has been extensively studied. The RMF scheme was originally developed as a concept to maintain the Field Reversed Configuration (FRC) in a magnetically confined fusion research. Here, RMF coils are expected to generate jθ due to a nonlinear effect shown below. First, the rotating magnetic field Bω is generated by two pairs of RMF coils with AC currents, which have a phase difference of 90 degrees between the pairs. Due to the Faraday’s law, an axial electric field is induced. Second, an axial current is generated by the effects of an electron-ion and an electron-neutral collisions through the Ohm’s law. Third, the azimuthal electric field is generated by the nonlinear term, and the retarding torque generated by the collision effects again. Then, azimuthal current jθ is generated as jθ = - nₑ er ∙ 2π fRMF. Finally, the axial Lorentz force fz for plasma acceleration is generated. Here, jθ is proportional to nₑ and frequency of RMF coil current fRMF, when Bω is fully penetrated into the plasma. Our previous study has achieved 19 % increase of ion velocity using the 5 MHz and 50 A of the RMF coil power supply. In this presentation, we will show the improvement of the ion velocity using the lower frequency and higher current supplied by RMF power supply. In conclusion, helicon high-density plasma production and electromagnetic acceleration by the RMF scheme with a concept of electrodeless condition have been successfully executed.

Keywords: electric propulsion, electrodeless thruster, helicon plasma, rotating magnetic field

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Authors: R. Andreola, O. A. A. Santos, L. M. M. Jorge

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An industrial system for the production of white liquor of a paper industry, Klabin Paraná Papé is, formed by ten reactors was modeled, simulated, and analyzed. The developed model considered possible water losses by evaporation and reaction, in addition to variations in volumetric flow of lime mud across the reactors due to composition variations. The model predictions agreed well with the process measurements at the plant and the results showed that the slaking reaction is nearly complete at the third causticizing reactor, while causticizing ends by the seventh reactor. Water loss due to slaking reaction and evaporation occurs more pronouncedly in the slaking reaction than in the final causticizing reactors; nevertheless, the lime mud flow remains nearly constant across the reactors.

Keywords: causticizing, lime, prediction, process

Procedia PDF Downloads 359

Authors: Haitham A. Hussein, Rozi Abdullah, Issa Saket, Md. Azlin

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The gravitational effect has been extensively applied to separate oil from water in water and wastewater treatment systems. The maximum oil globules removal efficiency is improved by obtaining the best flow uniformity in separator tanks. This study used 2D computational fluid dynamics (CFD) to investigate the effect of different inlet baffle positions inside the separator tank. Laboratory experiment has been conducted, and the measured velocity fields which were by Nortek Acoustic Doppler Velocimeter (ADV) are used to verify the CFD model. Computational investigation results indicated that the construction of an inlet baffle in a suitable location provides the minimum recirculation zone volume, creates the best flow uniformity, and dissipates kinetic energy in the oil and water separator tank. Useful formulas were predicted to design the oil and water separator tanks geometry based on an experimental model.

Keywords: oil/water separator tanks, inlet baffles, CFD, VOF

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Authors: Taha Zakaraia Abdel Wahid

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In the present study, a development of the papers is introduced. The behavior of the unsteady non-equilibrium distribution functions for a rarefied gas mixture under the effect of non-linear thermal radiation field is presented. For the best of our knowledge this is done for the first time at all. The distinction and comparisons between the unsteady perturbed and the unsteady equilibrium velocity distribution functions are illustrated. The equilibrium time for the rarefied gas mixture is determined for the first time. The non-equilibrium thermodynamic properties of the system is investigated. The results are applied to the Argon-Neon binary gas mixture, for various values of both of molar fraction parameters and radiation field intensity. 3D-Graphics illustrating the calculated variables are drawn to predict their behavior and the results are discussed.

Keywords: radiation field, binary gas mixture, exact solutions, travelling wave method, unsteady BGK model, irreversible thermodynamics

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Authors: A. C. Blaga, A. Cârlescu, M. Turnea, A. I. Galaction, D. Caşcaval

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The performance of an aerobic stirred bioreactor for fungal fermentation was analyzed on the basis of mixing time and oxygen mass transfer coefficient, by quantifying the influence of some specific geometrical and operational parameters of the bioreactor, as well as the rheological behavior of Penicillium chrysogenum broth (free mycelia and mycelia aggregates). The rheological properties of the fungus broth, controlled by the biomass concentration, its growth rate, and morphology strongly affect the performance of the bioreactor. Experimental data showed that for both morphological structures the accumulation of fungus biomass induces a significant increase of broths viscosity and modifies the rheological behavior. For lower P. chrysogenum concentrations (both morphological conformations), the mixing time initially increases with aeration rate, reaches a maximum value and decreases. This variation can be explained by the formation of small bubbles, due to the presence of solid phase which hinders the bubbles coalescence, the rising velocity of bubbles being reduced by the high apparent viscosity of fungus broths. By biomass accumulation, the variation of mixing time with aeration rate is gradually changed, the continuous reduction of mixing time with air input flow increase being obtained for 33.5 g/l d.w. P. chrysogenum. Owing to the superior apparent viscosity, which reduces considerably the relative contribution of mechanical agitation to the broths mixing, these phenomena are more pronounced for P. chrysogenum free mycelia. Due to the increase of broth apparent viscosity, the biomass accumulation induces two significant effects on oxygen transfer rate: the diminution of turbulence and perturbation of bubbles dispersion - coalescence equilibrium. The increase of P. chrysogenum free mycelia concentration leads to the decrease of kla values. Thus, for the considered variation domain of the main parameters taken into account, namely air superficial velocity from 8.36 10-4 to 5.02 10-3 m/s and specific power input from 100 to 500 W/m3, kla was reduced for 3.7 times for biomass concentration increase from 4 to 36.5 g/l d.w. The broth containing P. crysogenum mycelia aggregates exhibits a particular behavior from the point of view of oxygen transfer. Regardless of bioreactor operating conditions, the increase of biomass concentration leads initially to the increase of oxygen mass transfer rate, the phenomenon that can be explained by the interaction of pellets with bubbles. The results are in relation with the increase of apparent viscosity of broths corresponding to the variation of biomass concentration between the mentioned limits. Thus, the apparent viscosity of the suspension of fungus mycelia aggregates increased for 44.2 times and fungus free mycelia for 63.9 times for CX increase from 4 to 36.5 g/l d.w. By means of the experimental data, some mathematical correlations describing the influences of the considered factors on mixing time and kla have been proposed. The proposed correlations can be used in bioreactor performance evaluation, optimization, and scaling-up.

Keywords: biomass concentration, mixing time, oxygen mass transfer, P. chrysogenum broth, stirred bioreactor

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Authors: Jayanta K. Behera, Ashwini K. Sinha

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The study has pointed out the relationship of energetic particle precipitation (EPP) during high speed solar wind streams (HSS) to the ionization characteristics and subsequent NOx production in the polar atmosphere. Over the last few decades, it has been shown that production of NOx in the mesosphere region during the precipitation of charged particles (with energy range >30 KeV to 1 MeV) is directly related to the ozone loss in the polar middle atmosphere, extending from mesosphere to upper stratosphere. This study has dealt with the analysis of the interplanetary parameters such as interplanetary magnetic field (IMF), solar wind velocity (Vs), charged particle density (Ns), convection field enhancement (Ec) during such HSS events and their link to the rate of production of NOx in the mesosphere. Moreover, the analysis will be used to validate or, to modify the current ion-chemistry models which describe the ionization rate and NOx production in the polar atmosphere due to EPP.

Keywords: energetic particle precipitation (EPP), NOx, ozone depletion, polar vortex

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Authors: Bikram Jung Kunwar

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Forests have central roles in climate change. The conservation of forests sequestrates the carbon from the atmosphere and also regulates the carbon cycle. However, knowingly and unknowingly the world’s forests were deforested and degraded annually at the rate of 0.18% and emitted the carbon to the atmosphere. The IPCC reports claimed that the deforestation and forest degradation accounts 1/5th of total carbon emission, which is second position after fossil fuels. Since 1.6 billion people depend on varying degree on forests for their daily livelihood, not all deforestation are undesirable. Therefore, to conserve the forests and find the livelihood opportunities for forest surrounding people is prerequisites to address the climate change problems especially in developing countries, and also a growing concern to the forestry sector researchers, planners and policy makers. The study examines the role of community based forest management in carbon mitigation and adaptation taking the examples of Nepal’s community forestry program. In the program, the government hands over a part of national forests to the local communities with sole forest management authorities. However, the government itself retained the ownership rights of forestland. Local communities organized through a local institution called Community Forest User Group (CFUG) managed the forests. They also formed an operational plan with technical prescriptions and a constitution with forest management rules and regulations. The implementation results showed that the CFUGs are not only found effective to organize the local people and construct a local institution to forest conservation and management activities, but also they are able to collect a community fund from the sale of forest products and carried out various community development activities. These development activities have decisive roles to improve the livelihood of forest surrounding people and eventually to address the climate change problems.

Keywords: climate change, community forestry, local institution, Nepal

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Authors: Moch Agus Choiron

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Crash box design has been developed to obtain optimum energy absorption. In this study, two-segment crash box design with holes is investigated under oblique load. The deformation behavior and crash energy absorption are observed. The analysis was performed using finite element method. The crash test components were impactor, crash box, and fixed rigid base. Impactor and the fixed base material are modelled as a rigid, and crash box material as bilinear isotropic hardening. The models consist of 2 and 4 holes laid within ¼, ½ and ¾ from first segment length. 100 mm aluminum crash box and frontal crash velocity of 16 km/jam were selected. Based on simulation results, it can be concluded that 2 holes located at ¾ has the largest crash energy absorption. This behavior associated with deformation pattern, which produces higher number of folding than other models.

Keywords: crash Box, two-segments, holes configuration, oblique load, deformation pattern

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Authors: Andres Mejia-Ortiz, Catalina Lozada, German R. Santos, Rafael Angulo-Jaramillo, Bernardo Caicedo

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The interaction between atmospheric variables and soil properties is a determining factor when evaluating the flow of water through the soil. This interaction situation directly determines the behavior of the soil and greatly influences the changes that occur in it. The atmospheric variations such as changes in the relative humidity, air temperature, wind velocity and precipitation, are the external variables that reflect a greater incidence in the changes that are generated in the subsoil, as a consequence of the water flow in descending and ascending conditions. These environmental variations have a major importance in the study of the soil because the conditions of humidity and temperature in the soil surface depend on them. In addition, these variations control the thickness of the unsaturated zone and the position of the water table with respect to the surface. However, understanding the relationship between the atmosphere and the soil is a somewhat complex aspect. This is mainly due to the difficulty involved in estimating the changes that occur in the soil from climate changes; since this is a coupled process where act processes of mass transfer and heat. In this research, an experimental field was implemented to study in-situ the interaction between the atmosphere and the soft soils of the city of Bogota, Colombia. The soil under study consists of a 60 cm layer composed of two silts of similar characteristics at the surface and a deep soft clay deposit located under the silky material. It should be noted that the vegetal layer and organic matter were removed to avoid the evapotranspiration phenomenon. Instrumentation was carried on in situ through a field disposal of many measuring devices such as soil moisture sensors, thermocouples, relative humidity sensors, wind velocity sensor, among others; which allow registering the variations of both the atmospheric variables and the properties of the soil. With the information collected through field monitoring, the water balances were made using the Hydrus-1D software to determine the flow conditions that developed in the soil during the study. Also, the moisture profile for different periods and time intervals was determined by the balance supplied by Hydrus 1D; this profile was validated by experimental measurements. As a boundary condition, the actual evaporation rate was included using the semi-empirical equations proposed by different authors. In this study, it was obtained for the rainy periods a descending flow that was governed by the infiltration capacity of the soil. On the other hand, during dry periods. An increase in the actual evaporation of the soil induces an upward flow of water, increasing suction due to the decrease in moisture content. Also, cracks were developed accelerating the evaporation process. This work concerns to the study of soil-atmosphere interaction through the experimental field and it is a very useful tool since it allows considering all the factors and parameters of the soil in its natural state and real values of the different environmental conditions.

Keywords: field monitoring, soil-atmosphere, soft soils, soil-water balance

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Authors: N. Najafi, Laleh Maleknia , M. E. Olya

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An aqueous conductive ink of single-walled carbon nanotubes for inkjet printing was formulated. To prepare the homogeneous SWCNT ink in a size small enough not to block a commercial inkjet printer nozzle, we used a kinetic ball-milling process to disperse the SWCNTs in an aqueous suspension. When a patterned electrode was overlaid by repeated inkjet printings of the ink on various types of fabric, the fabric resistance decreased rapidly following a power law, reaching approximately 760 X/sq, which is the lowest value ever for a dozen printings. The Raman and Fourier transform infrared spectra revealed that the oxidation of the SWCNTs was the source of the doped impurities. This study proved also that the droplet ejection velocity can have an impact on the CNT distribution and consequently on the electrical performances of the ink.

Keywords: ink-jet printing, carbon nanotube, fabric ink, cotton fabric, raman spectroscopy, fourier transform infrared spectroscopy, dozen printings

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Authors: Sarah Faulkner, Patrick Faulkner, Caroline Ellison

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Improved mental and physical health, community connection, and increased life satisfaction has been strongly associated with bike riding for those with and without a disability. However, much evidence suggests that people living with a disability face increased barriers to engaging in cycling compared to members of the general population. People with an intellectual disability often live more sedentary and socially isolated lives that negatively impact their mental and physical health, as well as life satisfaction. This paper is based on preliminary findings from a three-year intervention cycling project funded by the South Australian Government. The cycling project was developed in partnership with community stakeholders that provided weekly instruction, training, and support to individuals living with intellectual disabilities to increase their capacity in cycling. This project aimed to support people living with intellectual disabilities to foster and facilitate improved physical and mental health, confidence, and independence and enhance social networking through their engagement in community cycling. The program applied principles of social role valorisation (SRV) theory as its guiding framework. Preliminary data collected is based on qualitative interviews with over 50 program participants, results from two participant wellness questionnaires, as well as a perceptually regulated exercise test administered throughout the project implementation. Preliminary findings are further supplemented with ethnographic analyses by the researchers who took a phenology of life experience approach. Preliminary findings of the program suggest a variety of social motivations behind participants' desire to learn cycling that acknowledges previous barriers to engagement and cycling’s role to address feelings of loneliness and social isolation. Meaningful health benefits can be achieved as demonstrated by increases in predicted V02 max measures, suggesting that physical intervention can not only improve physical health outcomes but also provide a variety of other social benefits. Initial engagement in the project has demonstrated an increase in participants' sense of confidence, well-being, and physical fitness. Implementation of the project in partnership with a variety of community stakeholders has identified a number of critical factors and processes necessary for future service replication, sustainability, and success. Findings from this intervention study contribute to the development of a knowledge base on how best to support individuals living with an intellectual disability to partake in bike riding and increase positive outcomes associated with their capacity building, social interaction, increased physical activity, physical health, and mental well-being. The initial findings of this study provide critical academic insights into the social and physical benefits of cycling for people living with a disability, as well as practical advice for future human service applications.

Keywords: cycling, disability, social inclusion, capacity building

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Authors: Joanna Grzybowska, Magdalena Igras, Mariusz Ziółko

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Association rule learning is an approach for discovering interesting relationships in large databases. The analysis of relations, invisible at first glance, is a source of new knowledge which can be subsequently used for prediction. We used this data mining technique (which is an automatic and objective method) to learn about interesting affects associations in a corpus of emergency phone calls. We also made an attempt to match revealed rules with their possible situational context. The corpus was collected and subjectively annotated by two researchers. Each of 3306 recordings contains information on emotion: (1) type (sadness, weariness, anxiety, surprise, stress, anger, frustration, calm, relief, compassion, contentment, amusement, joy) (2) valence (negative, neutral, or positive) (3) intensity (low, typical, alternating, high). Also, additional information, that is a clue to speaker’s emotional state, was annotated: speech rate (slow, normal, fast), characteristic vocabulary (filled pauses, repeated words) and conversation style (normal, chaotic). Exponentially many rules can be extracted from a set of items (an item is a previously annotated single information). To generate the rules in the form of an implication X → Y (where X and Y are frequent k-itemsets) the Apriori algorithm was used - it avoids performing needless computations. Then, two basic measures (Support and Confidence) and several additional symmetric and asymmetric objective measures (e.g. Laplace, Conviction, Interest Factor, Cosine, correlation coefficient) were calculated for each rule. Each applied interestingness measure revealed different rules - we selected some top rules for each measure. Owing to the specificity of the corpus (emergency situations), most of the strong rules contain only negative emotions. There are though strong rules including neutral or even positive emotions. Three examples of the strongest rules are: {sadness} → {anxiety}; {sadness, weariness, stress, frustration} → {anger}; {compassion} → {sadness}. Association rule learning revealed the strongest configurations of affects (as well as configurations of affects with affect-related information) in our emergency phone calls corpus. The acquired knowledge can be used for prediction to fulfill the emotional profile of a new caller. Furthermore, a rule-related possible context analysis may be a clue to the situation a caller is in.

Keywords: data mining, emergency phone calls, emotional profiles, rules

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Authors: Busra Mutlu Ipek, Merve Mutlu, Ahmet Mutlu

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Novel coronavirus COVID-19, which has recently influenced the world, poses a great threat to humanity. In order to overcome this challenging situation, scientists are working on developing effective vaccine against coronavirus. Many experts and researchers have also produced articles and done studies on this highly important subject. In this direction, this special topic was chosen for article to make a contribution to this area. The purpose of this article is to perform RNA sequence analysis of selected virus forms in the Coronaviridae family and predict/classify SARS-CoV-2 (COVID-19) from other selected complete genomes in coronaviridae family using proposed Artificial Neural Network(ANN) algorithm.

Keywords: Coronaviridae family, COVID-19, RNA sequencing, ANN, neural network

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Authors: Hariti Rafika, Fekih Malika, Saighi Mohamed

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During the period storage of liquefied natural gas, stability is necessarily affected by natural convection along the walls of the tank with thermal insulation is not perfectly efficient. In this paper, we present the numerical simulation of heat transfert by natural convection double diffusion,in unsteady laminar regime in a storage tank. The storage tank contains a liquefied natural gas (LNG) in its gaseous phase. Fluent, a commercial CFD package, based on the numerical finite volume method, is used to simulate the flow. The gas is just on the surface of the liquid phase. This numerical simulation allowed us to determine the temperature profiles, the stream function, the velocity vectors and the variation of the heat flux density in the vapor phase in the LNG storage tank volume. The results obtained for a general configuration, by numerical simulation were compared to those found in the literature.

Keywords: numerical simulation, natural convection, heat gains, storage tank, liquefied natural gas

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Authors: Lívia B. Meirelles, Erika C. A. N. Chrisman, Flávia B. de Andrade, Lilian C. M. de Oliveira

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True Boiling Point distillation (TBP) is one of the most common experimental techniques for the determination of petroleum properties. This curve provides information about the performance of petroleum in terms of its cuts. The experiment is performed in a few days. Techniques are used to determine the properties faster with a software that calculates the distillation curve when a little information about crude oil is known. In order to evaluate the accuracy of distillation curve prediction, eight points of the TBP curve and specific gravity curve (348 K and 523 K) were inserted into the HYSYS Oil Manager, and the extended curve was evaluated up to 748 K. The methods were able to predict the curve with the accuracy of 0.6%-9.2% error (Software X ASTM), 0.2%-5.1% error (Software X Spaltrohr).

Keywords: distillation curve, petroleum distillation, simulation, true boiling point curve

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Authors: Mounir Adal, Baalal Azeddine, Afifi Moulay Larbi

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Numerical analysis is a branch of mathematics devoted to the development of iterative matrix calculation techniques. We are searching for operations optimization as objective to calculate and solve systems of equations of order n with time and energy saving for computers that are conducted to calculate and analyze big data by solving matrix equations. Furthermore, this scientific discipline is producing results with a margin of error of approximation called rates. Thus, the results obtained from the numerical analysis techniques that are held on computer software such as MATLAB or Simulink offers a preliminary diagnosis of the situation of the environment or space targets. By this we can offer technical procedures needed for engineering or scientific studies exploitable by engineers for water.

Keywords: numerical analysis methods, obstacles solving, engineering, simulation, numerical modeling, iteration, computer, MATLAB, water, underground, velocity

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Authors: Darrol Stanley, Levan Efremidze, Jannie Rossouw

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We investigate the predictability of the USD/ZAR (South African Rand) exchange rate with sample entropy analytics for the period of 2004-2015. We calculate sample entropy based on the daily data of the exchange rate and conduct empirical implementation of several market timing rules based on these entropy signals. The dynamic investment portfolio based on entropy signals produces better risk adjusted performance than a buy and hold strategy. The returns are estimated on the portfolio values in U.S. dollars. These results are preliminary and do not yet account for reasonable transactions costs, although these are very small in currency markets.

Keywords: currency trading, entropy, market timing, risk factor model

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Authors: Ebraheem Al-Jouri, Youssef Abu-Ahmad, Ramasamy Srinivasan

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The parasitoid, Diadegma semiclausum (Hymenoptera: Ichneumonidae) is one of the most effective exotic parasitoids of diamondback moth (DBM), Plutella xylostella in the lowland areas of Homs, Syria. Molecular evolution studies are useful tools to shed light on the molecular bases of insect geographical spread and adaptation to new hosts and environment and for designing better control strategies. In this study, molecular evolution analysis was performed based on the 42 nuclear internal transcribed spacer-2 (ITS2) sequences representing the D. semiclausum and eight other Diadegma spp. from Syria and worldwide. Possible recombination events were identified by RDP4 program. Four potential recombinants of the American D. insulare and D. fenestrale (Jeju) were detected. After detecting and removing recombinant sequences, the ratio of non-synonymous (dN) to synonymous (dS) substitutions per site (dN/dS=ɷ) has been used to identify codon positions involved in adaptive processes. Bayesian techniques were applied to detect selective pressures at a codon level by using five different approaches including: fixed effects likelihood (FEL), internal fixed effects likelihood (IFEL), random effects method (REL), mixed effects model of evolution (MEME) and Program analysis of maximum liklehood (PAML). Among the 40 positively selected amino acids (aa) that differed significantly between clades of Diadegma species, three aa under positive selection were only identified in D. semiclausum. Additionally, all D. semiclausum branches tree were highly found under episodic diversifying selection (EDS) at p≤0.05. Our study provide evidence that both recombination and positive selection have contributed to the molecular diversity of Diadegma spp. and highlights the significant contribution of D. semiclausum in adaptive evolution and influence the fitness in the DBM parasitoid.

Keywords: diadegma sp, DBM, ITS2, phylogeny, recombination, dN/dS, evolution, positive selection

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Authors: Keunhong Chae, Seokho Yoon

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Recently, the global navigation satellite system (GNSS) such as Galileo and GPS is employing more satellites to provide a higher degree of accuracy for the location service, thus calling for a more efficient signaling scheme among the satellites used in the overall GNSS network. In that the network throughput is improved, the spatial diversity can be one of the efficient signaling schemes; however, it requires multiple antenna that could cause a significant increase in the complexity of the GNSS. Thus, a diversity scheme called the cooperative signaling was proposed, where the virtual multiple-input multiple-output (MIMO) signaling is realized with using only a single antenna in the transmit satellite of interest and with modeling the neighboring satellites as relay nodes. The main drawback of the cooperative signaling is that the relay nodes receive the transmitted signal at different time instants, i.e., they operate in an asynchronous way, and thus, the overall performance of the GNSS network could degrade severely. To tackle the problem, several modified cooperative signaling schemes were proposed; however, all of them are difficult to implement due to a signal decoding at the relay nodes. Although the implementation at the relay nodes could be simpler to some degree by employing the time-reversal and conjugation operations instead of the signal decoding, it would be more efficient if we could implement the operations of the relay nodes at the source node having more resources than the relay nodes. So, in this paper, we propose a novel cooperative signaling scheme, where the data signals are combined in a unique way at the source node, thus obviating the need of the complex operations such as signal decoding, time-reversal and conjugation at the relay nodes. The numerical results confirm that the proposed scheme provides the same performance in the cooperative diversity and the bit error rate (BER) as the conventional scheme, while reducing the complexity at the relay nodes significantly. Acknowledgment: This work was supported by the National GNSS Research Center program of Defense Acquisition Program Administration and Agency for Defense Development.

Keywords: global navigation satellite network, cooperative signaling, data combining, nodes

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Authors: Erkan Talay, Mustafa Yigit Yagci

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For the systems like sliding door, designers should predict not only strength but also dynamic behavior of the system and this prediction usually becomes more critical if design has radical changes refer to previous designs. Also, sometimes physical tests could cost more than expected, especially for rail geometry changes, since this geometry affects design of the body. The aim of the study is to observe and understand the dynamics of the sliding door in virtual environment. For this, multibody dynamic model of the sliding door was built and then affects of various parameters like rail geometry, roller diameters, or center of mass detected. Also, a design of experiment study was performed to observe interactions of these parameters.

Keywords: design of experiment, minimum closing effort, multibody simulation, sliding door

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Authors: Lican Wang, Rongqian Chen, Yancheng You, Ruofan Qiu

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In the applications of jet engine, open-jet wind tunnel and airframe, there wildly exists a shear layer formed by the velocity and temperature gradients between jet flow and surrounded medium. The presence of shear layer will refract and reflect the sound path that consequently influences the measurement results in far-field. To investigate and evaluate the shear layer effect, a gradient term suppression and filtering method is adopted to simulate sound propagation through a steady sheared flow in three dimensions. Two typical configurations are considered: one is an incompressible and cold jet flow in wind tunnel and the other is a compressible and hot jet flow in turbofan engine. A numerically linear microphone array is used to localize the position of given sound source. The localization error is presented and linearly fitted.

Keywords: aeroacoustic, linearized Euler equation, acoustic propagation, source localization

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Authors: Himanshu Payal, Sachin Maheshwari, Pushpendra S. Bharti

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Electrical discharge machining (EDM), a non-conventional machining process, finds wide applications for shaping difficult-to-cut alloys. Process modeling of EDM is required to exploit the process to the fullest. Process modeling of EDM is a challenging task owing to involvement of so many electrical and non-electrical parameters. This work is an attempt to model the EDM process using artificial neural network (ANN). Experiments were carried out on die-sinking EDM taking Inconel 825 as work material. ANN modeling has been performed using experimental data. The prediction ability of trained network has been verified experimentally. Results indicate that ANN can predict the values of performance measures of EDM satisfactorily.

Keywords: artificial neural network, EDM, metal removal rate, modeling, surface roughness

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Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Sittampalam Manoharan, Gary Chai, Sanaul Chowdhury, Andrew Golding

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The primary objective of this paper is to present a simplified approach to develop the structural deterioration model using traffic speed deflectometer data for flexible pavements. Maintaining assets to meet functional performance is not economical or sustainable in the long terms, and it would end up needing much more investments for road agencies and extra costs for road users. Performance models have to be included for structural and functional predicting capabilities, in order to assess the needs, and the time frame of those needs. As such structural modelling plays a vital role in the prediction of pavement performance. A structural condition is important for the prediction of remaining life and overall health of a road network and also major influence on the valuation of road pavement. Therefore, the structural deterioration model is a critical input into pavement management system for predicting pavement rehabilitation needs accurately. The Traffic Speed Deflectometer (TSD) is a vehicle-mounted Doppler laser system that is capable of continuously measuring the structural bearing capacity of a pavement whilst moving at traffic speeds. The device’s high accuracy, high speed, and continuous deflection profiles are useful for network-level applications such as predicting road rehabilitations needs and remaining structural service life. The methodology adopted in this model by utilizing time series TSD maximum deflection (D0) data in conjunction with rutting, rutting progression, pavement age, subgrade strength and equivalent standard axle (ESA) data. Then, regression analyses were undertaken to establish a correlation equation of structural deterioration as a function of rutting, pavement age, seal age and equivalent standard axle (ESA). This study developed a simple structural deterioration model which will enable to incorporate available TSD structural data in pavement management system for developing network-level pavement investment strategies. Therefore, the available funding can be used effectively to minimize the whole –of- life cost of the road asset and also improve pavement performance. This study will contribute to narrowing the knowledge gap in structural data usage in network level investment analysis and provide a simple methodology to use structural data effectively in investment decision-making process for road agencies to manage aging road assets.

Keywords: adjusted structural number (SNP), maximum deflection (D0), equant standard axle (ESA), traffic speed deflectometer (TSD)

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Authors: Amy Hodges, Deanna Rasmussen, Sherry Ward

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This paper examines the use of ePortfolios in a two-course sequence for ESL (English as a Second Language) students at an international branch campus in Doha, Qatar. ePortfolios support the transfer of language learning, but few have examined the sustainability of that transfer across an ESL program. Drawing upon surveys and interviews with students, we analyze three case studies that complicate previous research on metacognition, language learning, and ePortfolios. Our findings have implications for those involved in ESL programs and assessment of student writing.

Keywords: TESOL, electronic portfolios, assessment, technology

Procedia PDF Downloads 265

Authors: Mokrane Selma

Abstract:

The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

Procedia PDF Downloads 164

Authors: Golnush Masghati-Amoli, Paul Chin

Abstract:

Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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Authors: Chang He, Hiroshi Tamura, Hiroshi Katsuchi, Jiaqi Wang

Abstract:

In this study, the aim is to infer the slip limit (static friction limit) of contact interfaces in bolt friction joints by analyzing other bolt friction joints with the same contact surface but in a different shape. By using the Weibull distribution to deal with microelements on the contact surface statistically, the slip limit of a certain type of bolt joint was predicted from other types of bolt joint with the same contact surface. As a result, this research succeeded in predicting the slip limit of bolt joins with different numbers of contact surfaces and with different numbers of bolt rows.

Keywords: bolt joints, slip coefficient, finite element method, Weibull distribution

Procedia PDF Downloads 177

Authors: Min Wei

Abstract:

The traditional prediction methods of the forecast for tourism market are paid more attention to the accuracy of the forecasts, ignoring the results of the feasibility of forecasting and predicting operability, which had made it difficult to predict the results of scientific testing. With the application of Linear Regression Model, this paper attempts to construct a scientific evaluation system for predictive value, both to ensure the accuracy, stability of the predicted value, and to ensure the feasibility of forecasting and predicting the results of operation. The findings show is that a scientific evaluation system can implement the scientific concept of development, the harmonious development of man and nature co-ordinate.

Keywords: linear regression model, tourism market, forecast, tourism economics

Procedia PDF Downloads 335

Authors: Sudipto Sarkar, Anamika Paul

Abstract:

Pseudoplastic (n<1, n is the power index) fluids have great importance in food, pharmaceutical and chemical process industries which require a lot of attention. Unfortunately, due to its complex flow behavior inadequate research works can be found even in laminar flow regime. A practical problem is solved in the present research work by numerical simulation where we tried to control the vortex shedding from a square cylinder using a horizontal splitter plate placed at the downstream flow region. The position of the plate is at the centerline of the cylinder with varying distance from the cylinder to calculate the critical gap-ratio. If the plate is placed inside this critical gap, the vortex shedding from the cylinder suppressed completely. The Reynolds number considered here is in unsteady laminar vortex shedding regime, Re = 100 (Re = U∞a/ν, where U∞ is the free-stream velocity of the flow, a is the side of the cylinder and ν is the maximum value of kinematic viscosity of the fluid). Flow behavior has been studied for three different gap-ratios (G/a = 2, 2.25 and 2.5, where G is the gap between cylinder and plate) and for a fluid with three different flow behavior indices (n =1, 0.8 and 0.5). The flow domain is constructed using Gambit 2.2.30 and this software is also used to generate the mesh and to impose the boundary conditions. For G/a = 2, the domain size is considered as 37.5a × 16a with 316 × 208 grid points in the streamwise and flow-normal directions respectively after a thorough grid independent study. Fine and equal grid spacing is used close to the geometry to capture the vortices shed from the cylinder and the boundary layer developed over the flat plate. Away from the geometry meshes are unequal in size and stretched out. For other gap-ratios, proportionate domain size and total grid points are used with similar kind of mesh distribution. Velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition) at upper and lower domain boundary conditions are used for the simulation. Wall boundary condition (u = v = 0) is considered both on the cylinder and the splitter plate surfaces. Discretized forms of fully conservative 2-D unsteady Navier Stokes equations are then solved by Ansys Fluent 14.5. SIMPLE algorithm written in finite volume method is selected for this purpose which is a default solver inculcate in Fluent. The results obtained for Newtonian fluid flow agree well with previous works supporting Fluent’s usefulness in academic research. A thorough analysis of instantaneous and time-averaged flow fields are depicted both for Newtonian and pseudoplastic fluid flow. It has been observed that as the value of n reduces the stretching of shear layers also reduce and these layers try to roll up before the plate. For flow with high pseudoplasticity (n = 0.5) the nature of vortex shedding changes and the value of critical gap-ratio reduces. These are the remarkable findings for laminar periodic vortex shedding regime in pseudoplastic flow environment.

Keywords: CFD, pseudoplastic fluid flow, wake-boundary layer interactions, critical gap-ratio

Procedia PDF Downloads 112