Search results for: finite element models

Authors: Ana Paula Melchiors Stahlschmidt

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This paper discusses the role of music as a ludic activity and constituent element of voice in the construction and consolidation of the relationship of the baby and his/her mother or caretaker, evaluating its implications in his/her psychic structure and constitution as a subject. The work was based on the research developed as part of the author’s doctoral activities carried out from her insertion in a project of the Music Department of Federal University of Rio Grande do Sul - UFRGS, which objective was the development of musical activities with groups of babies from 0 to 24 months old and their caretakers. Observations, video recordings of the meetings, audio testemonies, and evaluation tools applied to group participants were used as instruments for this research. Information was collected on the participation of 195 babies, among which 8 were more focused on through interviews with their mothers or caretakers. These interviews were analyzed based on the referential of French Discourse Analysis, Psychoanalysis, Psychology of Development and Musical Education. The results of the research were complemented by other posterior experiences that the author developed with similar groups, in a context of a private clinic. The information collected allowed the observation of the ludic and structural functions of musical activities, when developed in a structured environment, as well as the importance of the musicality of the mother’s voice to the psychical structuring of the baby, allowing his/her insertion in the language and his/her constituition as a subject.

Keywords: music and babies, maternal voice, Psychoanalysis and music, psychology and music

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Authors: Wali Ullah, Muhammad Nishat

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The study investigates the extent to which the so called Nelson-Siegel model (DNS) and its extended version that accounts for time varying volatility (DNS-EGARCH) can optimally fit the yield curve and predict its future path in the context of an emerging economy. For the in-sample fit, both models fit the curve remarkably well even in the emerging markets. However, the DNS-EGARCH model fits the curve slightly better than the DNS. Moreover, both specifications of yield curve that are based on the Nelson-Siegel functional form outperform the benchmark VAR forecasts at all forecast horizons. The DNS-EGARCH comes with more precise forecasts than the DNS for the 6- and 12-month ahead forecasts, while the two have almost similar performance in terms of RMSE for the very short forecast horizons.

Keywords: yield curve, forecasting, emerging markets, Kalman filter, EGARCH

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Authors: Mustafa Col, Funda Gul Koc, Merve Yangaz, Eylem Subasi, Can Akbasoglu

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G38NiCrMo8-4-4 steel is widely used in mining industries, machine parts, gears due to its high strength and toughness properties. In this study, microstructure, wear and mechanical properties of G38NiCrMo8-4-4 steel modified with boron used in the mining industry were investigated. For this purpose, cast materials were alloyed by melting in an induction furnace to include boron with the rates of 0 ppm, 15 ppm, and 50 ppm (wt.) and were formed in the dimensions of 150x200x150 mm by casting into the sand mould. Homogenization heat treatment was applied to the specimens at 1150˚C for 7 hours. Then all specimens were austenitized at 930˚C for 1 hour, quenched in the polymer solution and tempered at 650˚C for 1 hour. Microstructures of the specimens were investigated by using light microscope and SEM to determine the effect of boron and heat treatment conditions. Changes in microstructure properties and material hardness were obtained due to increasing boron content and heat treatment conditions after microstructure investigations and hardness tests. Wear tests were carried out using a pin-on-disc tribometer under dry sliding conditions. Charpy V notch impact test was performed to determine the toughness properties of the specimens. Fracture and worn surfaces were investigated with scanning electron microscope (SEM). The results show that boron element has a positive effect on the hardness and wear properties of G38NiCrMo8-4-4 steel.

Keywords: G38NiCrMo8-4-4 steel, boron, heat treatment, microstructure, wear, mechanical properties

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Authors: Bryan Crompton, Daniel Giger, Tanay Mehta, Apurva Mody

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The task of classifying radio frequency (RF) signals has seen recent success in employing deep neural network models. In this work, we present a combined signal processing and machine learning approach to signal classification for cochannel anomalous signals. The power spectral density and cyclostationary signal processing features of a captured signal are computed and fed into a neural net to produce a classification decision. Our combined signal preprocessing and machine learning approach allows for simpler neural networks with fast training times and small computational resource requirements for inference with longer preprocessing time.

Keywords: signal processing, machine learning, cyclostationary signal processing, signal classification

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Authors: Naci Kalkan, Ihsan Dagtekin

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This research presents the design and analysis of solar air-conditioning systems particularly solar chimney which is a passive strategy for natural ventilation, and demonstrates the structures of these systems’ using Computational Fluid Dynamic (CFD) and finally compares the results with several examples, which have been studied experimentally and carried out previously. In order to improve the performance of solar chimney system, highly efficient sub-system components are considered for the design. The general purpose of the research is to understand how efficiently solar chimney systems generate cooling, and is to improve the efficient of such systems for integration with existing and future domestic buildings.

Keywords: active and passive solar technologies, solar cooling system, solar chimney, natural ventilation, cavity depth, CFD models for solar chimney

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Authors: Rajendra Kumar

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We study the Electronic spectral density of a double coupled quantum dots sandwich between superconducting leads, where one of the superconducting leads (QD1) are connected with left superconductor lead and (QD1) also connected right superconductor lead. (QD1) and (QD2) are coupling to each other. The electronic spectral density through a quantum dots between superconducting leads having s-wave symmetry of the superconducting order parameter. Such junction is called superconducting –quantum dot (S-QD-S) junction. For this purpose, we have considered a renormalized Anderson model that includes the double coupled of the superconducting leads with the quantum dots level and an attractive BCS-type effective interaction in superconducting leads. We employed the Green’s function technique to obtain superconducting order parameter with the BCS framework and Ambegaoker-Baratoff formalism to analyze the electronic spectral density through such (S-QD-S) junction. It has been pointed out that electronic spectral density through such a junction is dominated by the attractive the paring interaction in the leads, energy of the level on the dot with respect to Fermi energy and also on the coupling parameter of the two in an essential way. On the basis of numerical analysis we have compared the theoretical results of electronic spectral density with the recent transport existing theoretical analysis. QDs is the charging energy that may give rise to effects based on the interplay of Coulomb repulsion and superconducting correlations. It is, therefore, an interesting question to ask how the discrete level spectrum and the charging energy affect the DC and AC Josephson transport between two superconductors coupled via a QD. In the absence of a bias voltage, a finite DC current can be sustained in such an S-QD-S by the DC Josephson effect.

Keywords: quantum dots, S-QD-S junction, BCS superconductors, Anderson model

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Authors: T. Nozu, K. Hibi, T. Nishiie

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This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.

Keywords: deflagration, large eddy simulation, turbulent combustion, vented enclosure

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Authors: Vishnu Pratap Singh Kirar

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The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

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Authors: Carlos Escobar-del Pozo, César Ahumada-Monroy, Azael García-Rebolledo, Alberto Brambila-Solórzano, Gregorio Martínez-Sánchez, Luis Ortiz-Rincón

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Numerical simulations of flow in complex biological structures have gained considerable attention in the last years. However, the major issue is the validation of the results. The present work shows a Particle Image Velocimetry PIV flow visualization technique in complex biological structures, particularly in intracranial aneurysms. A methodology to reconstruct and generate a transparent model has been developed, as well as visualization and particle tracking techniques. The generated transparent models allow visualizing the flow patterns with a regular camera using the visualization techniques. The final goal is to use visualization as a tool to provide more information on the treatment and surgery decisions in aneurysms.

Keywords: aneurysms, PIV, flow visualization, particle tracking

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Authors: Balarabe Nkom, Adam P. R. Taylor, Craig Baguley

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Power Line Communications (PLC) is being employed in existing power systems, despite the infrastructure not being designed with PLC considerations in mind. Given that power transformers can last for decades, the distribution transformer in particular exists as a relic of un-optimized technology. To determine issues that may need to be addressed in subsequent designs of such transformers, it is essential to have a highly accurate transformer model for simulations and subsequent optimization for the PLC environment, with a view to increase data speed, throughput, and efficiency, while improving overall system stability and reliability. This paper reviews various methods currently available for creating transformer models and provides insights into the requirements of each for obtaining high accuracy. The review indicates that a combination of traditional analytical methods using a hybrid approach gives good accuracy at reasonable costs.

Keywords: distribution transformer, modelling, optimization, power line communications

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Authors: Kazuyoshi Mori, Keisuke Hashimoto

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In this paper, we consider the two-stage compensator designs of SISO plants. As an investigation of the characteristics of the two-stage compensator designs, which is not well investigated yet, of SISO plants, we implement three dimensional visualization systems of output signals and optimization system for SISO plants by the parametrization of stabilizing controllers based on the two-stage compensator design. The system runs on Mathematica by using “Three Dimensional Surface Plots,” so that the visualization can be interactively manipulated by users. In this paper, we use the discrete-time LTI system model. Even so, our approach is the factorization approach, so that the result can be applied to many linear models.

Keywords: linear systems, visualization, optimization, Mathematica

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Authors: Bandar Ali Al-Asbahi, Mohammad Hafizuddin Haji Jumali

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Forster energy transfer between poly (9,9'-di-n-octylfluorenyl-2,7-diyl) (PFO)/TiO2 nanoparticles (NPs) as a donor and Fluorol 7GA as an acceptor has been studied. The energy transfer parameters were calculated by using mathematical models. The dominant mechanism responsible for the energy transfer between the donor and acceptor molecules was Forster-type, as evidenced by large values of quenching rate constant, energy transfer rate constant and critical distance of energy transfer. Moreover, these composites which were used as an emissive layer in organic light emitting diodes, were investigated in terms of current density–voltage and electroluminescence spectra.

Keywords: energy transfer parameters, forster-type, electroluminescence, organic light emitting diodes

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Authors: Azeez Shaik, Amit Salvi, B. P. Gautham

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Fiber reinforced polymer resin composite materials are finding wide variety of applications in automotive and aerospace industry because of their high specific stiffness and specific strengths when compared to metals. New class of 2D and 3D textile and woven fabric composites offer excellent fracture toughens as they bridge the cracks formed during fracture. Due to complexity of their fiber architectures and its resulting composite microstructures, optimized design and analysis of these structures is very complicated. A traditional homogenization approach is typically used to analyze structures made up of these materials. This approach usually fails to predict damage initiation as well as damage propagation and ultimate failure of structure made up of woven and textile composites. This study demonstrates a methodology to analyze woven and textile composites by using the multi-level multi-scale modelling approach. In this approach, a geometric repetitive unit cell (RUC) is developed with all its constituents to develop a representative volume element (RVE) with all its constituents and their interaction modeled correctly. The structure is modeled based on the RUC/RVE and analyzed at different length scales with desired levels of fidelity incorporating the damage and failure. The results are passed across (up and down) the scales qualitatively as well as quantitatively from the perspective of material, configuration and architecture.

Keywords: cohesive zone, multi-scale modeling, rate dependency, RUC, woven textiles

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Authors: Winfred Okoe Addy, Jean Jacques Dominique Beraud

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Access control systems (ACs) are some of the most important components in safety areas. Inaccuracies of regulatory frameworks make personal policies and remedies more appropriate than standard models or protocols. This problem is exacerbated by the increasing complexity of software, such as integrated Big Data (BD) software for controlling large volumes of encrypted data and resources embedded in a dedicated BD production system. This paper proposes a general access control strategy system for the diffusion of Big Data domains since it is crucial to secure the data provided to data consumers (DC). We presented a general access control circulation strategy for the Big Data domain by describing the benefit of using designated access control for BD units and performance and taking into consideration the need for BD and AC system. We then presented a generic of Big Data access control system to improve the dissemination of Big Data.

Keywords: access control, security, Big Data, domain

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Authors: Revoti Prasad Bora, Nikita Katyal

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Promotion is a key element in the retail business. Thus, analysis of promotions to quantify their effectiveness in terms of Revenue and/or Margin is an essential activity in the retail industry. However, measuring the sales/revenue uplift is based on estimations, as the actual sales/revenue without the promotion is not present. Further, the presence of Halo and Cannibalization in a multiple parallel promotions’ scenario complicates the problem. Calculating Baseline by considering inter-brand/competitor items or using Halo and Cannibalization's impact on Revenue calculations by considering Baseline as an interpretation of items’ unit sales in neighboring nonpromotional weeks individually may not capture the overall Revenue uplift in the case of multiple parallel promotions. Hence, this paper proposes a Machine Learning based method for calculating the Revenue uplift by considering the Halo and Cannibalization impact on the Baseline and the Revenue. In the first section of the proposed methodology, Baseline of an item is calculated by incorporating the impact of the promotions on its related items. In the later section, the Revenue of an item is calculated by considering both Halo and Cannibalization impacts. Hence, this methodology enables correct calculation of the overall Revenue uplift due a given promotion.

Keywords: Halo, Cannibalization, promotion, Baseline, temporary price reduction, retail, elasticity, cross price elasticity, machine learning, random forest, linear regression

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Authors: Vishwas Goel, Kapil Surve, Somnath Basu

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In-situ alloying in steel during the electro-slag remelting (ESR) process has already been achieved by the addition of necessary ferroalloys into the electro-slag remelting mold. However, the use of commercially available ferroalloys during ESR processing is often found to be financially less favorable, in comparison with the conventional alloying techniques. However, a process of alloying steel with elements like chromium and manganese using the electro-slag remelting route is under development without any ferrochrome addition. The process utilizes in-situ reduction of refined mineral chromite (Cr₂O₃) and resultant enrichment of chromium in the steel ingot produced. It was established in course of this work that this process can become more advantageous over conventional alloying techniques, both economically and environmentally, for applications which inherently demand the use of the electro-slag remelting process, such as manufacturing of superalloys. A key advantage is the lower overall CO₂ footprint of this process relative to the conventional route of production, storage, and the addition of ferrochrome. In addition to experimentally validating the feasibility of the envisaged reactions, a mathematical model to simulate the reduction of chromium (III) oxide and transfer to chromium to the molten steel droplets was also developed as part of the current work. The developed model helps to correlate the amount of chromite input and the magnitude of chromium alloying that can be achieved through this process. Experiments are in progress to validate the predictions made by this model and to fine-tune its parameters.

Keywords: alloying element, chromite, electro-slag remelting, ferrochrome

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Authors: Panagiota Koliousi, Natasha Miaouli

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We compare product and labour market liberalization under the two trade union bargaining models: the Right-to-Manage (RTM) model and the Efficient Bargaining (EB) model. The vehicle is a dynamic general equilibrium (DGE) model that incorporates two types of agents (capitalists and workers), imperfectly competitive product and labour markets. The model is solved numerically employing common parameter values and data from the euro area. A key message is that product market deregulation is favourable under any labour market structure while opting for labour market deregulation one should provide special attention to the structure of the labour market such as the bargaining system of unions. If the prevailing way of bargaining is the RTM model then restructuring both markets is beneficial for all agents.

Keywords: market structure, structural reforms, trade unions, unemployment

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Authors: Balarabe Z. Ahmad, Anne-Lorène Vernay

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The emergence of electricity in Nigeria was dated back to 1896. The power plants have the potential to generate 12,522 MW of electric power. Whereas current dispatch is about 4,000 MW, access to electrification is about 60%, with consumption at 0.14 MWh/capita. The government embarked on energy reforms to mitigate energy poverty. The reform targeted the provision of electricity access to 75% of the population by 2020 and 90% by 2030. Growth of total electricity demand by a factor of 5 by 2035 had been projected. This means that Nigeria will require almost 530 TWh of electricity which can be delivered through generators with a capacity of 65 GW. Analogously, the geographical location of Nigeria has placed it in an advantageous position as the source of solar energy; the availability of a high sunshine belt is obvious in the country. The implication is that the far North, where energy poverty is high, equally has about twice the solar radiation as against southern Nigeria. Hence, the chance of generating solar electricity is 66% possible at 11850 x 103 GWh per year, which is one hundred times the current electricity consumption rate in the country. Harvesting these huge potentials may be a mirage if the entrepreneurs in the solar panel business are left with the conventional business models that are not uncertainty resilient. Currently, business entities in RE in Nigeria are uncertain of; accessing the national grid, purchasing potentials of cooperating organizations, currency fluctuation and interest rate increases. Uncertainties such as the security of projects and government policy are issues entrepreneurs must navigate to remain sustainable in the solar panel industry in Nigeria. The aim of this paper is to identify how entrepreneurial firms consider uncertainties in developing workable business models for commercializing solar energy projects in Nigeria. In an attempt to develop a novel business model, the paper investigated how entrepreneurial firms assess and navigate uncertainties. The roles of key stakeholders in helping entrepreneurs to manage uncertainties in the Nigeria RE sector were probed in the ongoing study. The study explored empirical uncertainties that are peculiar to RE entrepreneurs in Nigeria. A mixed-mode of research was embraced using qualitative data from face-to-face interviews conducted on the Solar Energy Entrepreneurs and the experts drawn from key stakeholders. Content analysis of the interview was done using Atlas. It is a nine qualitative tool. The result suggested that all stakeholders are required to synergize in developing an uncertainty resilient business model. It was opined that the RE entrepreneurs need modifications in the business recommendations encapsulated in the energy policy in Nigeria to strengthen their capability in delivering solar energy solutions to the yawning Nigerians.

Keywords: uncertainties, entrepreneurial, business model, solar-panel

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Authors: Hao Qu, Xiang Liu, Michael Crosby, Brian Kozak, Andreas K. Freund

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The outstanding performance of highly oriented pyrolytic graphite (HOPG) as an optical element for neutron beam conditioning is unequaled by any other crystalline material in the applications of monochromator, analyzer, and filter. This superiority stems from the favorable nuclear properties of carbon (small absorption and incoherent scattering cross-sections, big coherent scattering length) and the specific crystalline structure (small thermal diffuse scattering cross-section, layered crystal structure). The real crystal defect structure revealed by imaging techniques is correlated with the parameters used in the mosaic model (mosaic spread, mosaic block size, uniformity). The diffraction properties (rocking curve width as determined by both the intrinsic mosaic spread and the diffraction process, peak and integrated reflectivity, filter transmission) as a function of neutron wavelength or energy can be predicted with high accuracy and reliability by diffraction theory using empirical primary extinction coefficients extracted from a great amount of existing experimental data. The results of these calculations are given as graphs and tables permitting to optimize HOPG characteristics (mosaic spread, thickness, curvature) for any given experimental situation.

Keywords: neutron optics, pyrolytic graphite, mosaic spread, neutron scattering, monochromator, analyzer

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Authors: Kunal Tongaria, Abhishek Mangal, S. Mandal, Devendra Mohan

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The carbonation of concrete is a phenomenon which is a function of various interdependent parameters. Therefore, in spite of numerous literature and database, the useful generalization is not an easy task. These interdependent parameters can be grouped under the category of internal and external factors. This paper focuses on the internal parameters which govern and increase the probability of the ingress of deleterious substances into concrete. The mechanism of effects of internal parameters such as microstructure for with and without supplementary cementing materials (SCM), water/binder ratio, the age of concrete etc. has been discussed. This is followed by the comparison of various proposed mathematical models for the deterioration of concrete. Based on existing laboratory experiments as well as field results, this paper concludes the present understanding of mechanism, modeling and future research needs in this field.

Keywords: carbonation, diffusion coefficient, microstructure of concrete, reinforced concrete

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Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

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Authors: Mohamed Moustafa Mahmoud Sedky

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In line start permanent magnet synchronous motor, eccentricity is a common fault that can make it necessary to remove the motor from the production line. However, because the motor may be inaccessible, diagnosing the fault is not easy. This paper presents an FEM that identifies different models, static eccentricity, dynamic eccentricity, and mixed eccentricity, at no load and full load. The method overcomes the difficulty of applying FEMs to transient behavior. It simulates motor speed, torque and flux density distribution along the air gap for SE, DE, and ME. This paper represents the various effects of different eccentricities types on the transient performance.

Keywords: line start permanent magnet, synchronous machine, static eccentricity, dynamic eccentricity, mixed eccentricity

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Authors: George D. Hatzigeorgiou, Nikos G. Pnevmatikos

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This study examines the inelastic behavior of adjacent planar reinforced concrete (R.C.) frames subjected to strong ground motions. The investigation focuses on the effects of vertical ground motion on the seismic pounding. The examined structures are modeled and analyzed by RUAUMOKO dynamic nonlinear analysis program using reliable hysteretic models for both structural members and contact elements. It is found that the vertical ground motion mildly affects the seismic response of adjacent buildings subjected to structural pounding and, for this reason, it can be ignored from the displacement and interstorey drifts assessment. However, the structural damage is moderately affected by the vertical component of earthquakes.

Keywords: nonlinear seismic behavior, reinforced concrete structures, structural pounding, vertical ground motions

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Authors: Amin Banae Babazadeh

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In the contemporary world, NGOs are considered as important tool for motivating the community. So they committed their true mission and the promotion of civic participation and strengthen social identities. Functional characteristics of non-governmental organizations are the element to leverage the centers of political and social development of powerful governments since they are concrete and familiar with the problems of society and the operational strategies which would facilitate this process of mutual trust between the people and organizations. NGOs on the one hand offer reasonable solutions in line with approved organizations as agents to match between the facts and reality of society and on the other hand changes to a tool to have true political, social and economic behavior. However, the NGOs are active in the formulation of national relations and policy formulation in an organized and disciplined based on three main factors, i.e., resources, policies, and institutions. Organizations are not restricted to state administration in centralized system bodies and this process in the democratic system limits the accumulation of desires and expectations and at the end reaches to the desired place. Hence, this research will attempt to emphasis on field research (questionnaire) and according to the development evolution and role of NGOs analyze the effects of this center on youth. Therefore, the hypothesis is that there is a direct relationship between the Enlightenment and the effectiveness of policy towards NGOs and solving social damages.

Keywords: civic participation, community vulnerability, insightful, NGO, urmia

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Authors: Szymon Rutkowski, Tomasz Korbak

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We present a reinforcement-learning-based method of training neural machine translation models without parallel corpora. The standard encoder-decoder approach to machine translation suffers from two problems we aim to address. First, it needs parallel corpora, which are scarce, especially for low-resource languages. Second, it lacks psychological plausibility of learning procedure: learning a foreign language is about learning to communicate useful information, not merely learning to transduce from one language’s 'encoding' to another. We instead pose the problem of learning to translate as learning a policy in a communication game between two agents: the translator and the classifier. The classifier is trained beforehand on a natural language inference task (determining the entailment relation between a premise and a hypothesis) in the target language. The translator produces a sequence of actions that correspond to generating translations of both the hypothesis and premise, which are then passed to the classifier. The translator is rewarded for classifier’s performance on determining entailment between sentences translated by the translator to disciple’s native language. Translator’s performance thus reflects its ability to communicate useful information to the classifier. In effect, we train a machine translation model without the need for parallel corpora altogether. While similar reinforcement learning formulations for zero-shot translation were proposed before, there is a number of improvements we introduce. While prior research aimed at grounding the translation task in the physical world by evaluating agents on an image captioning task, we found that using a linguistic task is more sample-efficient. Natural language inference (also known as recognizing textual entailment) captures semantic properties of sentence pairs that are poorly correlated with semantic similarity, thus enforcing basic understanding of the role played by compositionality. It has been shown that models trained recognizing textual entailment produce high-quality general-purpose sentence embeddings transferrable to other tasks. We use stanford natural language inference (SNLI) dataset as well as its analogous datasets for French (XNLI) and Polish (CDSCorpus). Textual entailment corpora can be obtained relatively easily for any language, which makes our approach more extensible to low-resource languages than traditional approaches based on parallel corpora. We evaluated a number of reinforcement learning algorithms (including policy gradients and actor-critic) to solve the problem of translator’s policy optimization and found that our attempts yield some promising improvements over previous approaches to reinforcement-learning based zero-shot machine translation.

Keywords: agent-based language learning, low-resource translation, natural language inference, neural machine translation, reinforcement learning

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Authors: Taoufik Bettaieb, Sihem Soufi

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As a bioactive metalloid, silicon (Si) is an essential element for plant growth and development. It also plays a crucial role in enhancing plants’ resilience to different abiotic and biotic stresses. The morpho-physiological, biochemical, and molecular background of Si-mediated stress tolerance in plants were unraveled. Cold stress is a severe abiotic stress response to the decrease of plant growth and yield by affecting various physiological activities in plants. Several approaches have been used to alleviate the adverse effects generated from cold stress exposure, but the cost-effective, environmentally friendly, and defensible approach is the supply of silicon. Silicon has the ability to neutralize the harmful impacts of cold stress. Therefore, based on these hypotheses, this study was designed in order to investigate the morphological and physiological background of silicon effects applied at different concentrations on cold stress mitigation during early growth of a turfgrass, namely Paspalum vaginatum Sw. Results show that silicon applied at different concentrations improved the morphological development of Paspalum subjected to cold stress. It is also effective on the photosynthetic apparatus by maintaining stability the photochemical efficiency. As the primary component of cellular membranes, lipids play a critical function in maintaining the structural integrity of plant cells. Silicon application decreased membrane lipid peroxidation and kept on membrane frontline barrier relatively stable under cold stress.

Keywords: crops, cold stress, silicon, abiotic stress

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Authors: Boris Djartov, Sanaz Mostaghim

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This paper presents a number-based dominance method. The main idea is how to fragment the many attributes of the problem into subsets suitable for the well-established concept of Pareto dominance. Although other similar methods can be found in the literature, they focus on comparing the solutions one objective at a time, while the focus of this method is to compare entire subsets of the objective vector. Given the nature of the method, it is computationally costlier than other methods and thus, it is geared more towards selecting an option from a finite set of alternatives, where each solution is defined by multiple objectives. The need for this method was motivated by dynamic alternate airport selection (DAAS). In DAAS, pilots, while en route to their destination, can find themselves in a situation where they need to select a new landing airport. In such a predicament, they need to consider multiple alternatives with many different characteristics, such as wind conditions, available landing distance, the fuel needed to reach it, etc. Hence, this method is primarily aimed at human decision-makers. Many methods within the field of multi-objective and many-objective decision-making rely on the decision maker to initially provide the algorithm with preference points and weight vectors; however, this method aims to omit this very difficult step, especially when the number of objectives is so large. The proposed method will be compared to Favour (1 − k)-Dom and L-dominance (LD) methods. The test will be conducted using well-established test problems from the literature, such as the DTLZ problems. The proposed method is expected to outperform the currently available methods in the literature and hopefully provide future decision-makers and pilots with support when dealing with many-objective optimization problems.

Keywords: multi-objective decision-making, many-objective decision-making, multi-objective optimization, many-objective optimization

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Authors: Kyriaki Kalaitzidou, Athanasia Tolkou, Christina Raptopoulou, Manassis Mitrakas, Anastasios Zouboulis

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Phosphate rock is the main source of phosphorous (P) in fertilizers and is essential for high crop yield in agriculture; currently, it is considered as a critical element, phasing scarcity. Chemical precipitation, which is a commonly used method of phosphorous removal from wastewaters, finds its significance in that phosphates may be precipitated in appropriate chemical forms that can be reused-recovered. Most often phosphorous is removed from wastewaters in the form of insoluble phosphate salts, by using salts (coagulants) of multivalent metal ions, most frequently iron, aluminum, calcium, or magnesium. The removal degree is affected by various factors, such as pH, chemical agent dose, temperature, etc. In this study, phosphate precipitation from the secondary (biologically treated) effluent of a municipal wastewater treatment plant is examined. Using chlorosulfate (FeClSO4) it was attempted to either remove and/or recover PO43-. Results showed that the use of Fe3+ can achieve residual concentrations lower than the commonly applied legislation limit of PO43- (i.e. 3 mg PO43-/L) by adding 7.5 mg/L Fe3+ in the secondary effluent with an initial concentration of about 10 mg PO43-/L and at pH range between 6 to 9. In addition, the formed sediment has a percentage of almost 24% PO43- content. Therefore, simultaneous removal and recovery of PO43- as ferric phosphate can be achieved, making it possible for the ferric phosphate to be re-used as a possible (secondary) fertilizer source.

Keywords: ferric phosphate, phosphorus recovery, phosphorus removal, wastewater treatment

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Authors: Abdulmagid A. Khattabi, Ahmed A. Hablous, Mofied M. Elnemry

Abstract:

The carbon steel is of one of the most common mineral materials used in engineering and industrial applications in order to have access to the required mechanical properties, especially after the change of carbon ratio, but this may lead to stimulate corrosion. It has been used in models of solids with different carbon ratios such as 0.05% C, 0.2% C, 0.35% C, 0.5% C, and 0.65% C and have been studied using three testing durations which are 4 weeks, 6 weeks, and 8 weeks and among different corrosion environments such as atmosphere, fresh water, and salt water. This research is for the purpose of finding the effect of the carbon content on the corrosion resistance of steels in different corrosion medium by using the weight loss technique as a function of the corrosion resistance. The results that have been obtained through this research shows that a correlation can be made between corrosion rates and steel's carbon content, and the corrosion resistance decreases with the increase in carbon content.

Keywords: proportion of carbon in the steel, corrosion rate, erosion, corrosion resistance in carbon-steel

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Authors: Meriem Hamla, Mohamed Benaicha, Sabrine Derbal

Abstract:

In the present work, several materials such as M/glass (M = Pt, Mo) were investigated to test their suitability for studying the early nucleation stages and growth of copper-tin clusters. It was found that most of these materials stand as good substrates to be used in the study of the nucleation and growth of electrodeposited Cu-Sn alloys from aqueous solution containing CuCl2, SnCl2 as electroactive species and Na3C6H5O7 as complexing agent. Among these substrates, Pt shows instantaneous models followed by 3D diffusion-limited growth. On the other hand, the electrodeposited copper-tin thin films onto Mo substrate followed progressive nucleation. The deposition mechanism of the Cu-Sn films has been studied using stationary electrochemical techniques (cyclic voltammetery (CV) and chronoamperometry (CA). The structural, morphological and compositional of characterization have been studied using X-ray diffraction (XRD), scanning electron microscopy (SEM) and EDAX techniques respectively.

Keywords: electrodeposition, CuSn, nucleation, mechanism

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