Search results for: hybrid choice model

Authors: Azyuni Aziz, Syed A. Malik, Shahrul Kadri Ayop, Fatin Hana Naning

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Currently, organic-inorganic hybrid thin films have attracted researchers to explore them, where these thin films can give a lot of benefits. Hybrid thin films are thin films that consist of inorganic and organic materials. Inorganic and organic materials give high efficiency and low manufacturing cost in some applications such as solar cells application, furthermore, organic materials are environment-friendly. In this study, poly (3-hexylthiophene) was choosing as organic material which combined with inorganic nanoparticles, Cadmium Sulfide (CdS) quantum dots. Samples were prepared using new technique, Angle Lifting Deposition (ALD) at different weight percentage. All prepared samples were then characterized by Field Emission Scanning Electron Microscopy (FESEM) with Energy-dispersive X-ray spectroscopy (EDX) and Atomic Force Microscopy (AFM) to study surface of samples and determine their surface roughness. Results show that these inorganic nanoparticles have affected the surface of samples and surface roughness of samples increased due to increasing of weight percentage of CdS in the thin films samples.

Keywords: AFM, CdS, FESEM-EDX, hybrid thin films, P3HT

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Authors: Amnon Shirizly, Ohad Dolev

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In recent years, the implementation and use of Metal Additive Manufacturing (AM) parts increase. As a result, the demand for bigger parts rises along with the desire to reduce it’s the production cost. Generally, in powder bed Additive Manufacturing technology the part size is limited by the machine build volume. In order to overcome this limitation, the parts can be built in one or more machine operations and mechanically joint or weld them together. An alternative option could be a production of wrought part and built on it the AM structure (mainly to reduce costs). In both cases, the mechanical properties of the interface have to be defined and recognized. In the current study, the authors introduce guidelines on how to examine the interface between wrought alloy and powder-bed AM. The mechanical and metallurgical properties of the Ti6Al4V materials (wrought alloy and powder-bed AM) and their hybrid interface were examined. The mechanical properties gain from tensile test bars in the built direction and fracture toughness samples in various orientations. The hybrid specimens were built onto a wrought Ti6Al4V start-plate. The standard fracture toughness (CT25 samples) and hybrid tensile specimens' were heat treated and milled as a post process to final diminutions. In this Study, the mechanical tensile tests and fracture toughness properties supported by metallurgical observation will be introduced and discussed. It will show that the hybrid approach of utilizing powder bed AM onto wrought material expanding the current limitation of the future manufacturing technology.

Keywords: additive manufacturing, hybrid, fracture-toughness, powder bed

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Authors: Montaceur Zaghdoud, Mohamed Moussaoui, Jalel Akaichi

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Frequent subgraph mining refers usually to graph matching and it is widely used in when analyzing big data with large graphs. A lot of research works dealt with structural exact or inexact graph matching but a little attention is paid to semantic matching when graph vertices and/or edges are attributed and typed. Therefore, it seems very interesting to integrate background knowledge into the analysis and that extracted frequent subgraphs should become more pruned by applying a new semantic filter instead of using only structural similarity in graph matching process. Consequently, this paper focuses on developing a new hybrid approximate structuralsemantic graph matching to discover a set of frequent subgraphs. It uses simultaneously an approximate structural similarity function based on graph edit distance function and a possibilistic vertices similarity function based on affinity function. Both structural and semantic filters contribute together to prune extracted frequent set. Indeed, new hybrid structural-semantic frequent subgraph mining approach searches will be suitable to be applied to several application such as community detection in social networks.

Keywords: approximate graph matching, hybrid frequent subgraph mining, graph mining, possibility theory

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Authors: Kira Gulko Morse

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Choosing one’s primary language may not be as common as choosing an additional foreign language to study or use during travel. In some instances, however, it becomes a matter of internal personal struggle, as language is tied not only to specific circumstances but also to human background and identity. This phenomenological qualitative study focuses on the factors affecting the decision of a person to undergo a language shift. Specifically, it considers how these factors relate to identity negotiation and expression. The data for the study include the analysis of published autobiographical narratives and personal interviews conducted using the Responsive Interviewing model. While research participants come from a variety of geographical locations and have used different reasons for undergoing their individual language shift, the study identifies a number of common features shared by all the participants. Specifically, while all the participants have been able to maintain their first language to varying degrees of proficiency, they have all completed the shift to establish a primary language different from their first. Additionally, the process of self-identification is found to be directly connected to the phenomenon of language choice for each of the participants. The findings of the study further tie the phenomenon of individual language shift to a more comprehensive issue of individual life choices – ethnic revival, immigration, and inter-cultural marriage among others. The study discusses varying language roles and the data indicate that language shift may occur whether it is a symbolic driving force or a secondary means in fulfilling a set life goal. The concept of language addition is suggested as an alternative to the arbitrariness of language shift. Thus, instead of focusing on subtractive bilingualism or language loss, the emphasis becomes the integration of languages within the individual. The study emphasizes the importance of the construct of personal choice in its connection to individual language shift. It places the focus from society onto an individual and the ability of an individual to make decisions in matters of linguistic identification.

Keywords: choice theory, identity negotiation, language shift, psycholinguistics

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Authors: Ivo Zution Goncalves, Christopher M. U. Neale, Hiran Medeiros, Everardo Mantovani, Natalia Souza

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Multispectral and thermal infrared imagery from satellite sensors coupled with climate and soil datasets were used to estimate evapotranspiration and biomass in center pivots planted to maize in Brazil during the 2016 season. The hybrid remote sensing based model named Spatial EvapoTranspiration Modelling Interface (SETMI) was applied using multispectral and thermal infrared imagery from the Landsat Thematic Mapper instrument. Field data collected by the IRRIGER center pivot management company included daily weather information such as maximum and minimum temperature, precipitation, relative humidity for estimating reference evapotranspiration. In addition, soil water content data were obtained every 0.20 m in the soil profile down to 0.60 m depth throughout the season. Early season soil samples were used to obtain water-holding capacity, wilting point, saturated hydraulic conductivity, initial volumetric soil water content, layer thickness, and saturated volumetric water content. Crop canopy development parameters and irrigation application depths were also inputs of the model. The modeling approach is based on the reflectance-based crop coefficient approach contained within the SETMI hybrid ET model using relationships developed in Nebraska. The model was applied to several fields located in Minas Gerais State in Brazil with approximate latitude: -16.630434 and longitude: -47.192876. The model provides estimates of real crop evapotranspiration (ET), crop irrigation requirements and all soil water balance outputs, including biomass estimation using multi-temporal satellite image inputs. An interpolation scheme based on the growing degree-day concept was used to model the periods between satellite inputs, filling the gaps between image dates and obtaining daily data. Actual and accumulated ET, accumulated cold temperature and water stress and crop water requirements estimated by the model were compared with data measured at the experimental fields. Results indicate that the SETMI modeling approach using data assimilation, showed reliable daily ET and crop water requirements for maize, interpolated between remote sensing observations, confirming the applicability of the SETMI model using new relationships developed in Nebraska for estimating mainly ET and water requirements in Brazil under tropical conditions.

Keywords: basal crop coefficient, irrigation, remote sensing, SETMI

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Authors: Jonqlan Lin, C. Y. Tasi, K. H. Lin

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This paper addresses the issue of the autonomous mobile robot (AMR) navigation task based on the hybrid control modes. The novel hybrid control mode, based on multi-sensors information by using the fuzzy approach, has been presented in this research. The system operates in real time, is robust, enables the robot to operate with imprecise knowledge, and takes into account the physical limitations of the environment in which the robot moves, obtaining satisfactory responses for a large number of different situations. An experiment is simulated and carried out with a pioneer mobile robot. From the experimental results, the effectiveness and usefulness of the proposed AMR obstacle avoidance and navigation scheme are confirmed. The experimental results show the feasibility, and the control system has improved the navigation accuracy. The implementation of the controller is robust, has a low execution time, and allows an easy design and tuning of the fuzzy knowledge base.

Keywords: autonomous mobile robot, obstacle avoidance, MEMS, hybrid control mode, navigation control

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Authors: Emmanuel Larbi Offei, Felix Agyei-Sasu, Maura Naa Densua Ashong

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Ghana has 26 universal banks and several banking and non-banking financial institutions operating in the country. The growing number of banks has heightened competition among banks to attract and retain customers more customers to ensure sustainability. Hence the need to identify and understand factors that influences customers’ choice of banks cannot be overemphasised. This study investigates the determinants of bank selection criteria by banking customers in Ghana. Four banks were purposively sampled for this study namely Barclays, Standard Chartered, Sahel Sahara and Unibank. Convenience sampling was then used to select 114 bank customers in Accra and interviewed. Questionnaires were used to collect data that were analysed in tables and charts with the use of STATA software. The findings of the study revealed that quick/prompt services and complaint handling, safety of funds, networked branches, easy access to functional Automated Teller Machines (ATMs) and low/moderate service charges were the major determinants of customers’ choice of banks. The results further show that 89.5 percent of all deposits are held in either current or savings accounts. About 22.1 percent of the respondents indicated that they have plans of changing their banks in the near future because they are not satisfied with their banks. A gender analysis of the choice criteria showed differences between the choice criteria of the male as compared to the female. The study recommends that banks in Ghana should focus on products and policies that will not compromise on the safety of funds of their customers. Again, banks must address customer complaints and dissatisfactions as promptly as possible by taking pragmatic steps to address administrative bureaucracies and infrastructural challenges that prolong the duration of banking transactions.

Keywords: Ghana, banks, determinants, customers’ choice, competition

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Authors: Mueller Jann, Hoffmann Christian Hugo

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Conventional quantitative risk management in banking is a risk factor of its own, because it rests on assumptions such as independence and availability of data which do not hold when rare events of extreme consequences are involved. There is a growing recognition of the need for alternative risk measures that do not make these assumptions. We propose a novel method for modeling the risk associated with investment products, in particular derivatives, by using a formal language for specifying financial contracts. Expressions in this language are interpreted in the category of values annotated with (a formal representation of) uncertainty. The choice of uncertainty formalism thus becomes a parameter of the model, so it can be adapted to the particular application and it is not constrained to classical probabilities. We demonstrate our approach using a simple logic-based uncertainty model and a case study in which we assess the risk of counter party default in a portfolio of collateralized loans.

Keywords: risk model, uncertainty monad, derivatives, contract algebra

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Authors: Abdelli Soulaima, Belhadj Besma

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The paper examines the choice of the central bank toward the movements of the nominal exchange rate and evaluates its effects on the volatility of the output growth and the inflation. The novel hybrid method of the dynamic stochastic general equilibrium called the DSGE-VAR is proposed for analyzing this policy experiment in a small scale open economy in particular Tunisia. The contribution is provided to the empirical literature as we apply the Tunisian data with this model, which is rarely used in this context. Note additionally that the issue of treating the degree of response of the central bank to the exchange rate in Tunisia is special. To ameliorate the estimation, the Bayesian technique is carried out for the sample 1980:q1 to 2011 q4. Our results reveal that the central bank should not react or softly react to the exchange rate. The variance decomposition displayed that the overall inflation volatility is more pronounced with the fixed exchange rate regime for most of the shocks except for the productivity and the interest rate. The output volatility is also higher with this regime with the majority of the shocks exempting the foreign interest rate and the interest rate shocks.

Keywords: DSGE-VAR modeling, exchange rate, monetary policy, Bayesian estimation

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Halil Ibrahim Demir, Caner Erden, Mumtaz Ipek, Ozer Uygun

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Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied.

Keywords: process planning, weighted scheduling, weighted due-date assignment, genetic search, simulated annealing, hybrid meta-heuristics

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Authors: Manoj Gupta, Nirmendra Singh Bhadauria

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Most of the applications in image processing require high spatial and high spectral resolution in a single image. For example satellite image system, the traffic monitoring system, and long range sensor fusion system all use image processing. However, most of the available equipment is not capable of providing this type of data. The sensor in the surveillance system can only cover the view of a small area for a particular focus, yet the demanding application of this system requires a view with a high coverage of the field. Image fusion provides the possibility of combining different sources of information. In this paper, we have decomposed the image using DTCWT and then fused using average and hybrid of (maxima and average) pixel level techniques and then compared quality of both the images using PSNR.

Keywords: image fusion, DWT, DT-CWT, PSNR, average image fusion, hybrid image fusion

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Authors: Alexandra Monteiro, K. Bousson, Fernando J. O. Moreira, Ricardo Reis

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Fixed-wing flying vehicles are usually controlled by means of control surfaces such as elevators, ailerons, and rudders. The failure of these systems may lead to severe or even fatal crashes. These failures resulted in increased popularity for research activities on propulsion control in the last decades. The present work deals with a hybrid control architecture in which the propulsion-controlled vehicle maintains its traditional control surfaces, addressing the issue of robust lateral-directional dynamics control. The challenges stem from the parameter uncertainties in the stability and control derivatives and some unknown terms in the flight dynamics model. Two approaches are implemented and tested: linear quadratic regulation with robustness characteristics and H∞ control. The problem is centered on roll-yaw controller design with full state-feedback, which is able to deal with a standalone propulsion control mode as well as a hybrid mode combining both propulsion control and conventional control surface concepts while maintaining the original flight maneuverability characteristics. The results for both controllers emphasized very good control performances; however, the H∞ controller showed higher stabilization rates and robustness albeit with a slightly higher control magnitude than using the linear quadratic regulator.

Keywords: robust propulsion control, h-infinity control, lateral-directional flight dynamics, parameter uncertainties

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Authors: Roya Alipour

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The present study concentrates on answering the question of whether there are unintentional differences between genders in the translation of emotive and non-emotive texts, resulting in female translators preferring more expressive words when translating emotive texts in comparison to their male counterparts. The works of four translators, two males and two females, who had translated Fredrik Backman’s novel: A Man Called Ove, from English into Persian were used as samples of the study. To answer the research question, qualitative method was used, and the data were collected by analyzing some words, phrases and sentences as the bases for analysis. It was concluded that although there were obvious differences in word choice in translations, no specific pattern was found that showed gender might affect translation of emotive and non-emotive texts.

Keywords: translation, gender, word choice, translator, A Man Called Ove

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Authors: Eugene Stepanov, Arkadi Ponossov

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Many mathematical models used in biological and other applications are ill-posed. The reason for that is the nature of differential equations, where the nonlinearities are assumed to be step functions, which is done to simplify the analysis. Prominent examples are switched systems arising from gene regulatory networks and neural field equations. This simplification leads, however, to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid feedback controls to regularize the problem. Roughly speaking, one attaches a finite state control (‘automaton’), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. This ‘hybridization’ is shown to regularize the original switched system and gives rise to efficient hybrid numerical schemes. Several examples are provided in the presentation, which supports the suggested analysis. The method can be of interest in other applied fields, where differential equations contain step-like nonlinearities.

Keywords: hybrid feedback control, ill-posed problems, singular perturbation analysis, step-like nonlinearities

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Authors: Emdad K. Z. Balanji, M. Neaz Sheikh, Muhammad N. S. Hadi

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This paper presents results of an experimental investigation on the behaviour of Hybrid Steel Fibre Reinforced High Strength Concrete (HSFR-HSC) cylinder specimens (150 mm x 300 mm) under uniaxial compression. Three different combinations of HSFR-HSC specimens and reference specimens without steel fibres were prepared. The first combination of HSFR-HSC included 1.5% Micro Steel (MS) fibre and 1% Deformed Steel (DS) fibre. The second combination included 1.5% MS fibre and 1.5% Hooked-end Steel (HS) fibre. The third combination included 1% DS fibre and 1.5% HS fibre. The experimental results showed that the addition of hybrid steel fibres improved the ductility of high strength concrete. The combination of MS fibre and HS fibre in high strength concrete mixes showed best stress-strain behaviour compared to the other combinations and the reference specimens.

Keywords: high strength concrete, micro steel fibre (MS), deformed steel fibre (DS), hooked-end steel fibre (HS), hybrid steel fibre

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Authors: N. Larbi, F. Debbat

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Wireless communication systems have changed dramatically and shown spectacular evolution over the past two decades. These radio technologies are engaged in a quest endless high-speed transmission coupled to a constant need to improve transmission quality. Various radio communication systems being developed use code division multiple access (CDMA) technique. This work analyses a hybrid honey bees mating optimization algorithm (HBMO) applied to multiuser detection (MuD) in CDMA communication systems. The HBMO is a swarm-based optimization algorithm, which simulates the mating process of real honey bees. We apply a hybridization of HBMO with simulated annealing (SA) in order to improve the solution generated by the HBMO. Simulation results show that the detection based on Hybrid HBMO, in term of bit error rate (BER), is viable option when compared with the classic detectors from literature under Rayleigh flat fading channel.

Keywords: BER, DS-CDMA multiuser detection, genetic algorithm, hybrid HBMO, simulated annealing

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Authors: Royia Soliman, Salma ElAnsary, Akram Amin Abdellatif, Florian Holzapfel

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Model-Based Safety Analysis (MBSA) is an approach in which the system and safety engineers share a common system model created using a model-based development process. The model can also be extended by the failure modes of the system components. There are two famous approaches for the addition of fault behaviors to system models. The first one is to enclose the failure into the system design directly. The second approach is to develop a fault model separately from the system model, thus combining both independent models for safety analysis. This paper introduces a hybrid approach of MBSA. The approach tries to use informal abstracted models to investigate failure behaviors. The approach will combine various concepts such as directed graph traversal, event lists and Constraint Satisfaction Problems (CSP). The approach is implemented using an Object Oriented programming language. The components are abstracted to its failure logic and relationships of connected components. The implemented approach is tested on various flight control systems, including electrical and multi-domain examples. The various tests are analyzed, and a comparison to different approaches is represented.

Keywords: flight control systems, model based safety analysis, safety assessment analysis, system modelling

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Authors: Ahmed Khalaf Reyad Raslan

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Cancer stem cells (CSCs) describe a class of pluripotent cancer cells that behave analogously to normal stem cells in their ability to differentiate into the spectrum of cell types observed in tumors. The de-differentiation processes, such as an epithelial-mesenchymal transition (EMT), are known to enhance cellular plasticity. Here, we demonstrate a new hypothesis to use hybrid superparamagnetic magnetite nanoparticles (Fe₃O₄)- graphene oxide functionalized surface with Collagen to target the cancer stem cell as an early detection tool for cancer. We think that with the use of magnetic resonance imaging (MRI) and the new hybrid system would be possible to track the cancer stem cells.

Keywords: hydrogel, alginate, reduced graphene oxide, collagen

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Authors: Katarzyna Bialik-Wąs, Klaudia Pluta, Dagmara Malina, Małgorzata Miastkowska

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In recent years, biocompatible hydrogels have been used more and more in medical applications, especially as modern dressings and drug delivery systems. The main goal of this research was the characteristics of bio-hybrid hydrogel materials incorporated with the nanocarrier-drug system, which enable the release in a gradual and prolonged manner, up to 7 days. Therefore, the use of such a combination will provide protection against mechanical damage and adequate hydration. The proposed bio-hybrid hydrogels are characterized by: transparency, biocompatibility, good mechanical strength, and the dual release system, which allows for gradual delivery of the active substance, even up to 7 days. Bio-hybrid hydrogels based on sodium alginate (SA), poly(vinyl alcohol) (PVA), glycerine, and Aloe vera solution (AV) were obtained through the chemical crosslinking method using poly(ethylene glycol) diacrylate as a crosslinking agent. Additionally, a nanocarrier-drug system was incorporated into SA/PVA/AV hydrogel matrix. Here, studies were focused on the release profiles of active substances from bio-hybrid hydrogels using the USP4 method (DZF II Flow-Through System, Erweka GmbH, Langen, Germany). The equipment incorporated seven in-line flow-through diffusion cells. The membrane was placed over support with an orifice of 1,5 cm in diameter (diffusional area, 1.766 cm²). All the cells were placed in a cell warmer connected with the Erweka heater DH 2000i and the Erweka piston pump HKP 720. The piston pump transports the receptor fluid via seven channels to the flow-through cells and automatically adapts the setting of the flow rate. All volumes were measured by gravimetric methods by filling the chambers with Milli-Q water and assuming a density of 1 g/ml. All the determinations were made in triplicate for each cell. The release study of the model active substance was carried out using a regenerated cellulose membrane Spectra/Por®Dialysis Membrane MWCO 6-8,000 Carl Roth® Company. These tests were conducted in buffer solutions – PBS at pH 7.4. A flow rate of receptor fluid of about 4 ml /1 min was selected. The experiments were carried out for 7 days at a temperature of 37°C. The released concentration of the model drug in the receptor solution was analyzed using UV-Vis spectroscopy (Perkin Elmer Company). Additionally, the following properties of the modified materials were studied: physicochemical, structural (FT-IR analysis), morphological (SEM analysis). Finally, the cytotoxicity tests using in vitro method were conducted. The obtained results exhibited that the dual release system allows for the gradual and prolonged delivery of the active substances, even up to 7 days.

Keywords: wound dressings, SA/PVA hydrogels, nanocarrier-drug system, USP4 method

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Authors: Ravipa Rojasavachai, Li Yang

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Working from home has become a global phenomenon after the coronavirus outbreak, and most employees have a choice to choose between working from home or the office. In this paper, we examine the demographics and socio-economics factors influencing individuals’ decision to choose working from home rather than the office before and after the coronavirus outbreak based on Australian household data. We find that all factors impact the working from home choice before the coronavirus outbreak, but the number of children turns to an uninfluenced factor on individuals’ choices after the outbreak. We also find that female employees have a higher probability of choosing to work from home after the coronavirus outbreak. This is because they have less concern for their career opportunities and higher wage premium of working from home due to the changing in cultural norms and advanced working from home technologies in companies after the coronavirus outbreak.

Keywords: work from home, telework, remote working, COVID-19, pandemic, wage

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Authors: Saruhan Kartal, Ilker Kalkan

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The present paper reports the cracking moment estimates of a set of steel-reinforced, Fiber Reinforced Polymer (FRP)-reinforced and hybrid steel-FRP reinforced concrete beams, calculated from different analytical formulations in the codes, together with the experimental cracking load values. A total of three steel-reinforced, four FRP-reinforced, 12 hybrid FRP-steel over-reinforced and five hybrid FRP-steel under-reinforced concrete beam tests were analyzed within the scope of the study. Glass FRP (GFRP) and Basalt FRP (BFRP) bars were used in the beams as FRP bars. In under-reinforced hybrid beams, rupture of the FRP bars preceded crushing of concrete, while concrete crushing preceded FRP rupture in over-reinforced beams. In both types, steel yielding took place long before the FRP rupture and concrete crushing. The cracking moment mainly depends on two quantities, namely the moment of inertia of the section at the initiation of cracking and the flexural tensile strength of concrete, i.e. the modulus of rupture. In the present study, two different definitions of uncracked moment of inertia, i.e. the gross and the uncracked transformed moments of inertia, were adopted. Two analytical equations for the modulus of rupture (ACI 318M and Eurocode 2) were utilized in the calculations as well as the experimental tensile strength of concrete from prismatic specimen tests. The ACI 318M modulus of rupture expression produced cracking moment estimates closer to the experimental cracking moments of FRP-reinforced and hybrid FRP-steel reinforced concrete beams when used in combination with the uncracked transformed moment of inertia, yet the Eurocode 2 modulus of rupture expression gave more accurate cracking moment estimates in steel-reinforced concrete beams. All of the analytical definitions produced analytical values considerably different from the experimental cracking load values of the solely FRP-reinforced concrete beam specimens.

Keywords: polymer reinforcement, four-point bending, hybrid use of reinforcement, cracking moment

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Authors: Masoud Mohammadpour, Nima Yazdian, Radovan Kovacevic

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The Oil and Gas industries are vigorously looking for new ways to increase the efficiency of their pipeline constructions. Besides the other approaches, implementing of new welding methods for joining pipes can be the best candidate on this regard. Hybrid Laser Arc Welding (HLAW) with the capabilities of high welding speed, deep penetration, and excellent gap bridging ability can be a possible alternative method in pipeline girth welding. This paper investigates the feasibility of applying the HLAW to join ASTM A106-B as the mostly used piping material for transporting high-temperature and high-pressure fluids and gases. The experiments were carried out on six-inch diameter pipes with the wall thickness of 10mm. AWS ER 70 S6 filler wire with diameter of 1.2mm was employed. Relating to this welding procedure, characterization of welded samples such as hardness, tensile testing and Charpy V-notch testing were performed and the results will be reported in this paper. In order to have better understanding about the thermal history and the microstructural alterations caused by the welding heat cycle, a comprehensive Finite Element (FE) model was also conducted. The obtained results have shown that the Gas Metal Arc Welding (GMAW) procedure with the minimum number of 5 passes to complete the wall thickness, was reduced to only single pass by using the HLAW process with the welding time less than 15s.

Keywords: finite element modeling, high-temperature service, hybrid laser/arc welding, welding pipes

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Authors: W. Hasan, H. Farhat

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A hybrid quasi-steady thermal lattice Boltzmann model was used to study the combined effects of temperature and contact angle on the movement of slugs and droplets of oil in water (O/W) system flowing between two parallel plates. The model static contact angle due to the deposition of the O/W droplet on a flat surface with simulated hydrophilic characteristic at different fluid temperatures, matched very well the proposed theoretical calculation. Furthermore, the model was used to simulate the dynamic behavior of droplets and slugs deposited on the domain’s upper and lower surfaces, while subjected to parabolic flow conditions. The model accurately simulated the contact angle hysteresis for the dynamic droplets cases. It was also shown that at elevated temperatures the required power to transport the mixture diminished remarkably.

Keywords: lattice Boltzmann method, Gunstensen model, thermal, contact angle, high viscosity ratio

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Authors: Warakorn Supwirapakorn

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The purpose of this research was to study the effects of choice theory in group counseling on coping strategies of students. The sample consisted of 16 students at a boarding school, who had the lowest score on the coping strategies. The sample was divided into two groups by random assignment and then were assigned into the experimental group and the control group, with eight members each. The instruments were the Adolescent Coping Scale and choice theory group counseling program. The data collection procedure was divided into three phases: The pre-test, the post-test, and the follow-up. The data were analyzed by repeated measure analysis of variance: One between-subjects and one within-subjects. The results revealed that the interaction between the methods and the duration of the experiment was found statistically significant at 0.05 level. The students in the experimental group demonstrated significantly higher at 0.05 level on coping strategies score in both the post-test and the follow-up than in the pre-test and the control group. No significant difference was found on coping strategies during the post-test phase and the follow-up phase of the experimental group.

Keywords: coping strategies, choice theory, group counseling, boarding school

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Authors: Y. Kourd, D. Lefebvre

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The monitoring of industrial processes is required to ensure operating conditions of industrial systems through automatic detection and isolation of faults. This paper proposes a method of fault diagnosis based on a neuro-fuzzy hybrid structure. This hybrid structure combines the selection of threshold and decision tree. The validation of this method is obtained with the DAMADICS benchmark. In the first phase of the method, a model will be constructed that represents the normal state of the system to fault detection. Signatures of the faults are obtained with residuals analysis and selection of appropriate thresholds. These signatures provide groups of non-separable faults. In the second phase, we build faulty models to see the flaws in the system that cannot be isolated in the first phase. In the latest phase we construct the tree that isolates these faults.

Keywords: decision tree, residuals analysis, ANFIS, fault diagnosis

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Authors: Amir Ahmad Dehghani, Morteza Nabizadeh

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This paper presents the application of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to flood hydrograph modeling of Shahid Rajaee reservoir dam located in Iran. This was carried out using 11 flood hydrographs recorded in Tajan river gauging station. From this dataset, 9 flood hydrographs were chosen to train the model and 2 flood hydrographs to test the model. The different architectures of neuro-fuzzy model according to the membership function and learning algorithm were designed and trained with different epochs. The results were evaluated in comparison with the observed hydrographs and the best structure of model was chosen according the least RMSE in each performance. To evaluate the efficiency of neuro-fuzzy model, various statistical indices such as Nash-Sutcliff and flood peak discharge error criteria were calculated. In this simulation, the coordinates of a flood hydrograph including peak discharge were estimated using the discharge values occurred in the earlier time steps as input values to the neuro-fuzzy model. These results indicate the satisfactory efficiency of neuro-fuzzy model for flood simulating. This performance of the model demonstrates the suitability of the implemented approach to flood management projects.

Keywords: adaptive neuro-fuzzy inference system, flood hydrograph, hybrid learning algorithm, Shahid Rajaee reservoir dam

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Authors: Miguel Arlenzo Duran Sarmiento, Luis Alfonso Del Portillo Valdés, Carlos Borras Pinilla

Abstract:

Brake energy regeneration systems have the capacity to transform part of the vehicle's kinetic energy during deceleration into useful energy. These systems can be implemented in hybrid vehicles, which can be electric or hydraulic in type, and contribute to reducing the energy required to propel the vehicle thanks to the accumulation of energy. This paper presents the modeling and simulation of a braking energy regeneration system applied in hydraulic hybrid vehicles configured in parallel, the modeling and simulation were performed in Simulink of Matlab, where a performance comparison of the regenerated torque as a function of vehicle load, the displacement of the hydraulic regeneration device and the vehicle speed profile. The speed profiles used in the simulation are standard profiles such as the NEDC and WLTP profiles. The vehicle loads range from 1500 kg to 12000 kg. The results show the comparison of the torque required by the vehicle, the torque regenerated by the system subjected to the different speed and load conditions.

Keywords: braking energy, energy regeneration, hybrid vehicles, kinetic energy, torque

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Authors: Yongquan Zhao, Bo Huang

Abstract:

Spatial, Temporal, and Spectral Resolution (STSR) are three key characteristics of Earth observation satellite sensors; however, any single satellite sensor cannot provide Earth observations with high STSR simultaneously because of the hardware technology limitations of satellite sensors. On the other hand, a conflicting circumstance is that the demand for high STSR has been growing with the remote sensing application development. Although image fusion technology provides a feasible means to overcome the limitations of the current Earth observation data, the current fusion technologies cannot enhance all STSR simultaneously and provide high enough resolution improvement level. This study proposes a Hybrid Spatial-Temporal-Spectral image Fusion Model (HSTSFM) to generate synthetic satellite data with high STSR simultaneously, which blends the high spatial resolution from the panchromatic image of Landsat-8 Operational Land Imager (OLI), the high temporal resolution from the multi-spectral image of Moderate Resolution Imaging Spectroradiometer (MODIS), and the high spectral resolution from the hyper-spectral image of Hyperion to produce high STSR images. The proposed HSTSFM contains three fusion modules: (1) spatial-spectral image fusion; (2) spatial-temporal image fusion; (3) temporal-spectral image fusion. A set of test data with both phenological and land cover type changes in Beijing suburb area, China is adopted to demonstrate the performance of the proposed method. The experimental results indicate that HSTSFM can produce fused image that has good spatial and spectral fidelity to the reference image, which means it has the potential to generate synthetic data to support the studies that require high STSR satellite imagery.

Keywords: hybrid spatial-temporal-spectral fusion, high resolution synthetic imagery, least square regression, sparse representation, spectral transformation

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Authors: Mohammad Besharatloo

Abstract:

Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

Procedia PDF Downloads 62