Search results for: hybrid working models

Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

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A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: bistatic radar cross section, passive radar, propagation losses, radar coverage

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Authors: Peter Fornaro, Lothar Schmitt

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The Digital Humanities Lab and the Institute of Art History at the University of Basel are collaborating in the SNSF research project ‘Digital Materiality’. Its goal is to develop and enhance existing methods for the digital reproduction of cultural heritage objects in order to support art historical research. One part of the project focuses on the visualization of a small eye-catching group of early prints that are noteworthy for their subtle reliefs and glossy surfaces. Additionally, this group of objects – known as ‘paste prints’ – is characterized by its fragile state of preservation. Because of the brittle substances that were used for their production, most paste prints are heavily damaged and thus very hard to examine. These specific material properties make a photographic reproduction extremely difficult. To obtain better results we are working with Reflectance Transformation Imaging (RTI), a computational photographic method that is already used in archaeological and cultural heritage research. This technique allows documenting how three-dimensional surfaces respond to changing lighting situations. Our first results show that RTI can capture the material properties of paste prints and their current state of preservation more accurately than conventional photographs, although there are limitations with glossy surfaces because the mathematical models that are included in RTI are kept simple in order to keep the software robust and easy to use. To improve the method, we are currently developing tools for a more detailed analysis and simulation of the reflectance behavior. An enhanced analytical model for the representation and visualization of gloss will increase the significance of digital representations of cultural heritage objects. For collaborative efforts, we are working on a web-based viewer application for RTI images based on WebGL in order to make acquired data accessible to a broader international research community. At the ICDH Conference, we would like to present unpublished results of our work and discuss the implications of our concept for art history, computational photography and heritage science.

Keywords: art history, computational photography, paste prints, reflectance transformation imaging

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Authors: S. Kaymakçı, D. Gündoğdu, H. Özçelik

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The truck park of a warehouse for a chain of supermarket was going to be constructed on a poor ground. Rather than using a piled foundation, the client was convinced that a ground improvement using a reinforced foundation raft also known as “basal reinforcement” shall work. The retaining structures supporting the truck park area were designed using a hybrid structure made up of the Terramesh® Wall System and MacGrid™ high strength geogrids. The total wall surface area is nearly 2740 sq.m , reaching a maximum height of 13.00 meters. The area is located in the first degree seismic zone of Turkey and the design seismic acceleration is high. The design of walls has been carried out using pseudo-static method (limit equilibrium) taking into consideration different loading conditions using Eurocode 7. For each standard approach stability analysis in seismic condition were performed. The paper presents the detailed design of the reinforced soil structure, basal reinforcement and the construction methods; advantages of using such system for the project are discussed.

Keywords: basal reinforcement, geogrid, reinforced soil raft, reinforced soil wall, soil reinforcement

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Authors: Haneffa M. G.

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Retirement preparedness among Malaysian working individuals found to be poor. Prior research proven women consistently have lower retirement confidence as compared to men. Retirement planning still become the vague issues due to saving for the golden years are being stepsided by many people. Most of them think that their contributions in companies and government retirement plan is enough to comfort them in their golden years. The Employee Provident Fund (EPF) claims that most of nearly retired person have inadequate fund to retire. Therefore, this paper aims to discuss the saving behavior of younger cohort of working individuals towards retirement planning in Malaysia. A theoretical framework is developed to understand the relationship between demographic characteristics, financial education, goal clarity, perceived religiosity and retirement savings behavior.

Keywords: retirement planning, savings behavior, perceived religiosity, goal clarity, Malaysia

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Authors: Ali Hesari, Arezoo Esmaeeli

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Regarding to dramatic changes of fertility and higher order births during recent decades in Iran, access to knowledge about affecting factors on different birth orders has crucial importance. In this study, According to hierarchical structure of many of social sciences data and the effect of variables of different levels of social phenomena that determine different birth orders in 365 days ending to 1390 census have been explored by multilevel approach. In this paper, 2% individual row data for 1390 census is analyzed by HLM software. Three different hierarchical linear regression models are estimated for data analysis of the first and second, third, fourth and more birth order. Research results displays different outcomes for three models. Individual level variables entered in equation are; region of residence (rural/urban), age, educational level and labor participation status and province level variable is GDP per capita. Results show that individual level variables have different effects in these three models and in second level we have different random and fixed effects in these models.

Keywords: fertility, birth order, hierarchical approach, fixe effects, random effects

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Authors: Ehsan Eshtehardian, Saeed Khodaverdi

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This paper surveys the studies on construction change and reveals some of the potential future works. A full-scale investigation of change literature, including change definitions, types, causes and effects, and change management systems, is accomplished to explore some of the coming change trends. It is tried to pick up the critical works in each section to deduct a true timeline of construction changes. The findings show that leaping from best practice guides in late 1990s and generic process models in the early 2000s to very advanced modeling environments in the mid-2000s and the early 2010s have made gaps along with opportunities for change researchers in order to develop some more easy and applicable models. Another finding is that there is a compelling similarity between the change and risk prediction models. Therefore, integrating these two concepts, specifically from proactive management point of view, may lead to a synergy and help project teams avoid rework. Also, the findings show that exploitation of cause-effect relationship models, in order to facilitate the dispute resolutions, seems to be an interesting field for future works.

Keywords: construction change, change management systems, dispute resolutions, change literature

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Authors: Suren Chilingaryan

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We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal setup. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited.

Keywords: quantum optics, quantum phase transition, cavity QED, circuit QED

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

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Authors: Hany Mohamed Abdu, Mohamed Hassan Gadallah, El-Giushi Mokhtar, Yehia Mahmoud Ismail

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Laser beam cutting is one nontraditional machining process. This paper optimizes the parameters of Laser beam cutting machining parameters of Stainless steel (316L) by considering the effect of input parameters viz. power, oxygen pressure, frequency and cutting speed. Statistical design of experiments are carried in three different levels and process responses such as 'Average kerf taper (Ta)' and 'Surface Roughness (Ra)' are measured accordingly. A quadratic mathematical model (RSM) for each of the responses is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27 OA) are employed to search for an optimal parametric combination to achieve desired yield of the process. RSM models are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) using MATLAB environment. Optimum solutions are compared with Taguchi Methodology results.

Keywords: optimization, laser cutting, robust design, kerf width, Taguchi method, RSM and DOE

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Authors: Isaac Kayode Ogunlade

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Data acquisition (DAQ) is the process by which physical phenomena from the real world are transformed into an electrical signal(s) that are measured and converted into a digital format for processing, analysis, and storage by a computer. The DAQ is designed using PIC18F4550 microcontroller, communicating with Personal Computer (PC) through USB (Universal Serial Bus). The research deployed initial knowledge of data acquisition system and embedded system to develop a weather data acquisition device using LM35 sensor to measure weather parameters and the use of Artificial Intelligence(Artificial Neural Network - ANN)and statistical approach(Autoregressive Integrated Moving Average – ARIMA) to predict precipitation (rainfall). The device is placed by a standard device in the Department of Meteorology, Federal University of Technology, Akure (FUTA) to know the performance evaluation of the device. Both devices (standard and designed) were subjected to 180 days with the same atmospheric condition for data mining (temperature, relative humidity, and pressure). The acquired data is trained in MATLAB R2012b environment using ANN, and ARIMAto predict precipitation (rainfall). Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Correction Square (R2), and Mean Percentage Error (MPE) was deplored as standardize evaluation to know the performance of the models in the prediction of precipitation. The results from the working of the developed device show that the device has an efficiency of 96% and is also compatible with Personal Computer (PC) and laptops. The simulation result for acquired data shows that ANN models precipitation (rainfall) prediction for two months (May and June 2017) revealed a disparity error of 1.59%; while ARIMA is 2.63%, respectively. The device will be useful in research, practical laboratories, and industrial environments.

Keywords: data acquisition system, design device, weather development, predict precipitation and (FUTA) standard device

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Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.

Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA

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Authors: Yan Zhang, Felix Kin Peng Hui, Colin Duffield, Caroline X. Gao

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In post-pandemic Australia, it is unclear how building occupant have changed their behaviour in their interaction with buildings and other occupants. This research provides information on occupant behaviour change compared to before the pandemic and examines the predictors for those behaviour changes. This paper analyses survey responses from 2298 building occupants in Melbourne to investigate occupant behaviour change and determinants for those changes one year after the pandemic in Australia. The behaviour changes were grouped into three categories based on respiratory infection routes: (1) fomite: hand-shaking and hand hygiene behaviours; (2) airborne: individual interventions to indoor air quality such as face masking, window openings for occupants working in naturally ventilated space; (3) droplets: social distancing, reducing working hours in the workplace. The survey shows that the pandemic has significantly changed occupants' behaviour in all three categories compared to before the pandemic. The changes are significantly associated with occupants' perceived indoor air quality, indoor environmental cleanliness, and occupant density, demonstrating their growing awareness of respiratory infection risk that influences their health behaviours. The two most significant factors identified from multivariate regressions to drive the behaviour change include occupant risk perception of respiratory infections at the workplace and their observed co-worker's behaviour change. Based on the survey results, the paper provides adjusted estimates for related occupant behaviour parameters. The study also discusses alternatives for managing window operations in naturally ventilated buildings to improve occupant satisfaction. This paper could help Building Managers, and Building Designers understand occupant behaviour change to improve building operations and new building design to enhance occupant experience. Also, building energy modellers and risk assessors may use the findings to adjust occupant behaviour-related parameters to improve the models. The findings contribute to the knowledge of Human-Building Interaction.

Keywords: human-building interaction, risk perception, occupant behaviour, IAQ, COVID-19

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Authors: D. S. C. Soares, D. G. Costa, J. T. S., A. K. S. Abud, T. P. Nunes, A. M. Oliveira Júnior

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Mathematical models of drying are used for the purpose of understanding the drying process in order to determine important parameters for design and operation of the dryer. The jackfruit is a fruit with high consumption in the Northeast and perishability. It is necessary to apply techniques to improve their conservation for longer in order to diffuse it by regions with low consumption. This study aimed to analyse several mathematical models (Page, Lewis, and Midilli) to indicate one that best fits the conditions of convective drying process using performance indicators associated with each model: accuracy (Af) and noise factors (Bf), mean square error (RMSE) and standard error of prediction (% SEP). Jackfruit drying was carried out in convective type tray dryer at a temperature of 50°C for 9 hours. It is observed that the model Midili was more accurate with Af: 1.39, Bf: 1.33, RMSE: 0.01%, and SEP: 5.34. However, the use of the Model Midilli is not appropriate for purposes of control process due to need four tuning parameters. With the performance indicators used in this paper, the Page model showed similar results with only two parameters. It is concluded that the best correlation between the experimental and estimated data is given by the Page’s model.

Keywords: drying, models, jackfruit, biotechnology

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Authors: Didem Can

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Scheduling problems are one of the most fundamental issues of production systems. Many different approaches and models have been developed according to the production processes of the parts and the main purpose of the problem. In this study, one of the bottleneck stations of a company serving in the aerospace industry is analyzed and considered as a single machine scheduling problem with sequence-dependent setup times. The objective of the problem is assigning a large number of similar parts to the same shift -to reduce chemical waste- while minimizing the number of tardy jobs. The goal programming method will be used to achieve two different objectives simultaneously. The assignment of parts to the shift will be expressed using the integer programming method. Finally, the constraint programming method will be used as it provides a way to find a result in a short time by avoiding worse resulting feasible solutions with the defined variables set. The model to be established will be tested and evaluated with real data in the application part.

Keywords: constraint programming, goal programming, integer programming, sequence-dependent setup, single machine scheduling

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Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

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Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

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Authors: T. Y. Liu, C. H. Lin, Y. M. Ferng

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Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyse the flow field and pressure distributions of the wing blades. Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm. Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyse the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.

Keywords: horizontal axis wind turbine, turbulence model, noise, fluid dynamics

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Authors: Ozan Ozkan, Hilal Turkoglu Sasmazel

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Natural polymers are widely used in tissue engineering applications, because of their biocompatibility, biodegradability and solubility in the physiological medium. On the other hand, synthetic polymers are also widely utilized in tissue engineering applications, because they carry no risk of infectious diseases and do not cause immune system reaction. However, the disadvantages of both polymer types block their individual usages as tissue scaffolds efficiently. Therefore, the idea of usage of natural and synthetic polymers together as a single 3D hybrid scaffold which has the advantages of both and the disadvantages of none has been entered to the literature. On the other hand, even though these hybrid structures support the cell adhesion and/or proliferation, various surface modification techniques applied to the surfaces of them to create topographical changes on the surfaces and to obtain reactive functional groups required for the immobilization of biomolecules, especially on the surfaces of synthetic polymers in order to improve cell adhesion and proliferation. In a study presented here, to improve the surface functionality and topography of the layer by layer electrospun 3D poly-epsilon-caprolactone/chitosan/poly-epsilon-caprolactone hybrid tissue scaffolds by using atmospheric pressure plasma method, thus to improve cell adhesion and proliferation of these tissue scaffolds were aimed. The formation/creation of the functional hydroxyl and amine groups and topographical changes on the surfaces of scaffolds were realized by using two different atmospheric pressure plasma systems (nozzle type and dielectric barrier discharge (DBD) type) carried out under different gas medium (air, Ar+O2, Ar+N2). The plasma modification time and distance for the nozzle type plasma system as well as the plasma modification time and the gas flow rate for DBD type plasma system were optimized with monitoring the changes in surface hydrophilicity by using contact angle measurements. The topographical and chemical characterizations of these modified biomaterials’ surfaces were carried out with SEM and ESCA, respectively. The results showed that the atmospheric pressure plasma modifications carried out with both nozzle type plasma and DBD plasma caused topographical and functionality changes on the surfaces of the layer by layer electrospun tissue scaffolds. However, the shelf life studies indicated that the hydrophilicity introduced to the surfaces was mainly because of the functionality changes. Therefore, according to the optimized results, samples treated with nozzle type air plasma modification applied for 9 minutes from a distance of 17 cm and Ar+O2 DBD plasma modification applied for 1 minute under 70 cm3/min O2 flow rate were found to have the highest hydrophilicity compared to pristine samples.

Keywords: biomaterial, chitosan, hybrid, plasma

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Authors: Mariyan Tomov

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Bulgarian working class immigrants are increasingly concerned with UK’s recent immigration policies in the context of Brexit. The new ID system would exclude many people currently working in Britain and would break the usual immigrant travel patterns. Post-Brexit Britain would aim to repeal seasonal immigrants. Measures for keeping long-term and life-long immigrants have been implemented and migrants that aim to remain in Britain and establish a household there would be more privileged than temporary or seasonal workers. The results of such regulating mechanisms come at the expense of migrants’ longings for a ‘normal’ existence, especially for those coming from Central and Eastern Europe. Based on in-depth interviews with Bulgarian working class immigrants, the study found out that their major concerns following the decision of the UK to leave the EU are related with the freedom to travel, reside and work in the UK. Furthermore, many of the interviewed women are concerned that they could lose some of the EU's fundamental rights, such as maternity and protection of pregnant women from unlawful dismissal. The soar of commodity prices and university fees and the limited access to public services, healthcare and social benefits in the UK, are also subject to discussion in the paper. The most serious problem, according to the interview, is that the attitude towards Bulgarians and other immigrants in the UK is deteriorating. Both traditional and social media in the UK often portray the migrants negatively by claiming that they take British job positions while simultaneously abuse the welfare system. As a result, the Bulgarian migrants often face social exclusion, which might have negative influence on their health and welfare. In this sense, some of the interviewed stress on the fact that the most important changes after Brexit must take place in British society itself. The aim of the proposed study is to provide a better understanding of the Bulgarian migrants’ economic, health and sociocultural experience in the context of Brexit. Methodologically, the proposed paper leans on: 1. Analysing ethnographic materials dedicated to the pre- and post-migratory experiences of Bulgarian working class migrants, using SPSS. 2. Semi-structured interviews are conducted with more than 50 Bulgarian working class migrants [N > 50] in the UK, between 18 and 65 years. The communication with the interviewees was possible via Viber/Skype or face-to-face interaction. 3. The analysis is guided by theoretical frameworks. The paper has been developed within the framework of the research projects of the National Scientific Fund of Bulgaria: DCOST 01/25-20.02.2017 supporting COST Action CA16111 ‘International Ethnic and Immigrant Minorities Survey Data Network’.

Keywords: Bulgarian migrants in UK, economic experiences, sociocultural experiences, Brexit

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Authors: Anuj Kumar, Kummara M. Rao, Sung S. Han

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Bone tissue engineering has emerged as a potentially alternative method for localized bone defects or diseases, congenital deformation, and surgical reconstruction. The designing and the fabrication of the ideal scaffold is a great challenge, in restoring of the damaged bone tissues via cell attachment, proliferation, and differentiation under three-dimensional (3D) biological micro-/nano-environment. In this case, hydrogel system composed of high hydrophilic 3D polymeric-network that is able to mimic some of the functional physical and chemical properties of the extracellular matrix (ECM) and possibly may provide a suitable 3D micro-/nano-environment (i.e., resemblance of native bone tissues). Thus, this proposed hydrogel system is highly permeable and facilitates the transport of the nutrients and metabolites. However, the use of hydrogels in bone tissue engineering is limited because of their low mechanical properties (toughness and stiffness) that continue to posing challenges in designing and fabrication of tough and stiff hydrogels along with improved bioactive properties. For this purpose, in our lab, polyacrylamide-based hybrid hydrogels were synthesized by involving sodium alginate, cellulose nanocrystals and silica-based glass using one-step free-radical polymerization. The results showed good in vitro apatite-forming ability (biomineralization) and improved mechanical properties (under compression in the form of strength and stiffness in both wet and dry conditions), and in vitro osteoblastic (MC3T3-E1 cells) cytocompatibility. For in vitro cytocompatibility assessment, both qualitative (attachment and spreading of cells using FESEM) and quantitative (cell viability and proliferation using MTT assay) analyses were performed. The obtained hybrid hydrogels may potentially be used in bone tissue engineering applications after establishment of in vivo characterization.

Keywords: bone tissue engineering, cellulose nanocrystals, hydrogels, polyacrylamide, sodium alginate

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Authors: Abdellatif Chebboub

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Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Keywords: climate change, agriculture, weather change, danger of climate change

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Authors: Ferhat Demir

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Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

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Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

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Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

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Authors: Mehmet Yanardag, Ilker Yilmaz

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Children with autism spectrum disorders (ASD) enjoy and success the aquatic-based exercise and play skills in a pool instead of land-based exercise in a gym. Some authors also observed that many children with ASD experience more success in attaining movement skills in aquatic environment. Properties of the water and hydrodynamic principles cause buoyancy of the water and decrease effects of gravity and it leads to allow a child to practice important aquatic skills with limited motor skills. Also, some authors experience that parents liked the effects of the aquatic intervention program on children with ASD such as improving motor performance, movement capacity and learning basic swimming skills. The purpose of this study was to investigate the effects of aquatic exercise training on water orientation and underwater working capacity were measured in the pool. This study included in four male children between 5 and 7 years old with ASD and 6.25±0.5 years old. Aquatic exercise skills were applied by using one of the error less teaching which is called the 'most to least prompt' procedure during 12-week, three times a week and 60 minutes a day. The findings of this study indicated that there were improvements test results both water orientation skill and underwater working capacity of children with ASD after 12-weeks exercise training. It was seen that the aquatic exercise intervention would be affected to improve working capacity and orientation skills with the special education approaches applying children with ASD in multidisciplinary team-works.

Keywords: aquatic, autism, orientation, ASD, children

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Authors: Abdulrazzak Akroot, Lutfu Namli

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Solid oxide fuel cells (SOFCs) are one of the most promising technologies since they can produce electricity directly from fuel and generate a lot of waste heat that is generally used in the gas turbines to promote the general performance of the thermal power plant. In this study, the energy, and exergy analysis of a solid oxide fuel cell/gas turbine hybrid system was proceed in MATLAB to examine the performance characteristics of the hybrid system in two different configurations: anode-supported model and electrolyte-supported model. The obtained results indicate that if the fuel utilization factor reduces from 0.85 to 0.65, the overall efficiency decreases from 64.61 to 59.27% for the anode-supported model whereas it reduces from 58.3 to 56.4% for the electrolyte-supported model. Besides, the overall exergy reduces from 53.86 to 44.06% for the anode-supported model whereas it reduces from 39.96 to 33.94% for the electrolyte-supported model. Furthermore, increasing the air utilization factor has a negative impact on the electrical power output and the efficiencies of the overall system due to the reduction in the O₂ concentration at the cathode-electrolyte interface.

Keywords: solid oxide fuel cell, anode-supported model, electrolyte-supported model, energy analysis, exergy analysis

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Authors: Naveen Kumar Perumalla, Devadas Kuna, Mohammed Akhter Ali

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Satellite Navigation System such as the United States Global Positioning System (GPS) plays a significant role in determining the user position. Similar to that of GPS, Indian Regional Navigation Satellite System (IRNSS) is a Satellite Navigation System indigenously developed by Indian Space Research Organization (ISRO), India, to meet the country’s navigation applications. This system is also known as Navigation with Indian Constellation (NavIC). The NavIC system’s main objective, is to offer Positioning, Navigation and Timing (PNT) services to users in its two service areas i.e., covering the Indian landmass and the Indian Ocean. Six NavIC satellites are already deployed in the space and their receivers are in the performance evaluation stage. Four NavIC dual frequency receivers are installed in the ‘Advanced GNSS Research Laboratory’ (AGRL) in the Department of Electronics and Communication Engineering, University College of Engineering, Osmania University, India. The NavIC receivers can be operated in two positioning modes: Stand-alone IRNSS and Hybrid (IRNSS+GPS) modes. In this paper, analysis of various parameters such as Dilution of Precision (DoP), three Dimension (3D) Root Mean Square (RMS) Position Error and Horizontal Position Error with respect to Visibility of Satellites is being carried out using the real-time IRNSS data, obtained by operating the receiver in both positioning modes. Two typical days (6th July 2017 and 7th July 2017) are considered for Hyderabad (Latitude-17°24'28.07’N, Longitude-78°31'4.26’E) station are analyzed. It is found that with respect to the considered parameters, the Hybrid mode operation of NavIC receiver is giving better results than that of the standalone positioning mode. This work finds application in development of NavIC receivers for civilian navigation applications.

Keywords: DoP, GPS, IRNSS, GNSS, position error, satellite visibility

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Authors: S. Belhour, A. K. Ferouani, C. Azizi

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In recent years, a considerable effort (experience, numerical simulation, and theoretical prediction models) has characterised by high efficiency and low cost. Then an improved physics analytical model for simulating is proposed. The performance of GaAs MESFETs has been developed for use in device design for high frequency. This model is based on mathematical analysis, and a new approach for the standard model is proposed, this approach allowed to conceive applicable model for MESFET’s operating in the turn-one or pinch-off region and valid for the short-channel and the long channel MESFET’s in which the two dimensional potential distribution contributed by the depletion layer under the gate is obtained by conventional approximation. More ever, comparisons between the analytical models with different values of mobility are proposed, and a good agreement is obtained.

Keywords: analytical, gallium arsenide, MESFET, mobility, models

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Authors: A. Julio, R. Caparica, S. Costa Lima, S. Reis, J. G. Costa, P. Fonte, T. Santos De Almeida

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The Mycobacterium leprae causes a chronic and infectious disease called leprosy, which the most common symptoms are peripheral neuropathy and deformation of several parts of the body. The pharmacological treatment of leprosy is a combined therapy with three different drugs, rifampicin, clofazimine, and dapsone. However, clofazimine and dapsone have poor solubility in water and also low bioavailability. Thus, it is crucial to develop strategies to overcome such drawbacks. The use of ionic liquids (ILs) may be a strategy to overcome the low solubility since they have been used as solubility promoters. ILs are salts, liquid below 100 ºC or even at room temperature, that may be placed in water, oils or hydroalcoholic solutions. Another approach may be the encapsulation of drugs into polymeric nanoparticles, which improves their bioavailability. In this study, two different classes of ILs were used, the imidazole- and the choline-based ionic liquids, as solubility enhancers of the poorly soluble antileprotic drugs. Thus, after the solubility studies, it was developed IL-PLGA nanoparticles hybrid systems to deliver such drugs. First of all, the solubility studies of clofazimine and dapsone were performed in water and in water: IL mixtures, at ILs concentrations where cell viability is maintained, at room temperature for 72 hours. For both drugs, it was observed an improvement on the drug solubility and [Cho][Phe] showed to be the best solubility enhancer, especially for clofazimine, where it was observed a 10-fold improvement. Later, it was produced nanoparticles, with a polymeric matrix of poly(lactic-co-glycolic acid) (PLGA) 75:25, by a modified solvent-evaporation W/O/W double emulsion technique in the presence of [Cho][Phe]. Thus, the inner phase was an aqueous solution of 0.2 % (v/v) of the above IL with each drug to its maximum solubility determined on the previous study. After the production, the nanosystem hybrid was physicochemically characterized. The produced nanoparticles had a diameter of around 580 nm and 640 nm, for clofazimine and dapsone, respectively. Regarding the polydispersity index, it was in agreement of the recommended value of this parameter for drug delivery systems (around 0.3). The association efficiency (AE) of the developed hybrid nanosystems demonstrated promising AE values for both drugs, given their low solubility (64.0 ± 4.0 % for clofazimine and 58.6 ± 10.0 % for dapsone), that prospects the capacity of these delivery systems to enhance the bioavailability and loading of clofazimine and dapsone. Overall, the study achievement may signify an upgrading of the patient’s quality of life, since it may mean a change in the therapeutic scheme, not requiring doses of drug so high to obtain a therapeutic effect. The authors would like to thank Fundação para a Ciência e a Tecnologia, Portugal (FCT/MCTES (PIDDAC), UID/DTP/04567/2016-CBIOS/PRUID/BI2/2018).

Keywords: ionic liquids, ionic liquids-PLGA nanoparticles hybrid systems, leprosy treatment, solubility

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Authors: Sudaff Mohammed, Wahda Shuker Al-Hinkawi, Nada Abdulmueen Hasan

Abstract:

The compatibility of the Rhizome and Complex Adaptive system theory as a strategy within the urban context is the essential interest of this paper since there are only a few attempts to establish a hybrid, multi-scalar, and developable strategy based on the concept of the Rhizome and the CAS theory. This paper aims to establish a Rhizomic CAS strategy for different urban contexts by investigating the principles, characteristics, properties, and mechanisms of Rhizome and Complex Adaptive Systems. The research focused mainly on analyzing three properties: aggregation, non-linearity, and flow through the lens of Rhizome, Rhizomatization of CAS properties. The most intriguing result is that the principal and well-investigated characteristics of Complex Adaptive systems can be ‘Rhizomatized’ in two ways; highlighting commonalities between Rhizome and Complex Adaptive systems in addition to using Rhizome-related concepts. This paper attempts to emphasize the potency of the Rhizome as an apparently stochastic and barely anticipatable structure that can be developed to analyze cities of distinctive contexts for formulating better customized urban strategies.

Keywords: rhizome, complex adaptive system (CAS), system Theory, urban system, rhizomatic CAS, assemblage, human occupation impulses (HOI)

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Authors: Mst. Tuhin Akter, Sharun Akter Khushbu, S. M. Shaqib

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A real-time system architecture is highly effective for monitoring and detecting various damaged products or fruits that may deteriorate over time or become infected with diseases. Deep learning models have proven to be effective in building such architectures. However, building a deep learning model from scratch is a time-consuming and costly process. A more efficient solution is to utilize deep neural network (DNN) based transfer learning models in the real-time monitoring architecture. This study focuses on using a novel strawberry dataset to develop effective transfer learning models for the proposed real-time monitoring system architecture, specifically for evaluating and detecting strawberry freshness. Several state-of-the-art transfer learning models were employed, and the best performing model was found to be Xception, demonstrating higher performance across evaluation metrics such as accuracy, recall, precision, and F1-score.

Keywords: strawberry freshness evaluation, deep neural network, transfer learning, image augmentation

Procedia PDF Downloads 90