Search results for: simulated driving

Authors: Katerina Nerantzaki, Panayiota Metallidou, Anastasia Efklides

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The aim of the study was to investigate: (a) changes in the intensity of various epistemic emotions during cognitive processing in a decision-making task and (b) their associations with metacognitive feelings of difficulty and confidence. One hundred and fifty-two undergraduate university students were asked individually to read in the e-prime environment decision-making scenarios about moral dilemmas concerning self-driving cars, which differed in the level of conflict they produced, and then to make a choice between two options. Further, the participants were asked to rate on a four-point scale four epistemic emotions (surprise, curiosity, confusion, and wonder) and two metacognitive feelings (feeling of difficulty and feeling of confidence) after making their choice in each scenario. Changes in cognitive processing due to the level of conflict affected differently the intensity of the specific epistemic emotions. Further, there were interrelations of epistemic emotions with metacognitive feelings.

Keywords: confusion, curiosity, epistemic emotions, metacognitive experiences, surprise

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Authors: Nelson Lujara

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The paper presents a practical three-phase PWM inverter suitable for low voltage, low rating energy efficient systems. The work in the paper is conducted with the view to establishing the significance of the loss contribution from the PWM inverter in the determination of the complete losses of a photovoltaic (PV) array-powered induction motor drive water pumping system. Losses investigated include; conduction and switching loss of the devices and gate drive losses. It is found that the PWM inverter operates at a reasonable variable efficiency that does not fall below 92% depending on the load. The results between the simulated and experimental results for the system with or without a maximum power tracker (MPT) compares very well, within an acceptable range of 2% margin.

Keywords: energy, inverter, losses, photovoltaic

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Authors: Fatemeh Karimi

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The fashion and textile industry is undergoing a profound transformation, with polymers playing an increasingly pivotal role in driving innovation and sustainability. This paper explores the application of polymers in fashion and textile engineering, focusing on their impact on material properties, sustainability, and the future of garment production. Polymers, both synthetic and bio-based, offer unique opportunities to enhance the performance, durability, and environmental footprint of textiles. By examining recent advancements in polymer science and their integration into fashion design and production, we provide insights into how these materials are reshaping the industry. This paper also discusses the challenges and opportunities associated with the use of polymers, particularly in the context of sustainable fashion and circular economy practices. Through case studies and industry examples, we highlight the innovative ways in which polymers are being utilized to meet the evolving demands of consumers and the industry's sustainability goals.

Keywords: polymer textiles, sustainable fashion, bio-based polymers, smart textiles, fashion innovation, circular economy, textile engineering

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Authors: Jeong-Won Lee, Kyeong-Ok Yoon

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The current study aimed to investigate the effects of topic familiarity and language proficiency on linguistic aspects (lexical complexity, syntactic complexity, accuracy, and fluency) in EFL learners’ argumentative essays. For the study 64 college students were asked to write an argumentative essay for the two different topics (Driving and Smoking) chosen by the consideration of topic familiarity. The students were divided into two language proficiency groups (high-level and intermediate) according to their English writing proficiency. The findings of the study are as follows: 1) the participants of this study exhibited lower levels of lexical and syntactic complexity as well as accuracy when performing writing tasks with unfamiliar topics; and 2) they demonstrated the use of a wider range of vocabulary, and longer and more complex structures, and produced accurate and lengthier texts compared to their intermediate peers. Discussion and pedagogical implications for instruction of writing classes in EFL contexts were addressed.

Keywords: topic familiarity, complexity, accuracy, fluency

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Authors: Jens-Phillip Petersen

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The reduction of GHG emissions in buildings is a focus area of national energy policies in Europe, because buildings are responsible for a major share of the final energy consumption. It is at local scale where policies to increase the share of renewable energies and energy efficiency measures get implemented. Municipalities, as local authorities and responsible entity for land-use planning, have a direct influence on urban patterns and energy use, which makes them key actors in the transition towards sustainable cities. Hence, synchronizing urban planning with energy planning offers great potential to increase society’s energy-efficiency; this has a high significance to reach GHG-reduction targets. In this paper, the actual linkage of urban planning and energy planning in Denmark and Germany was assessed; substantive barriers preventing their integration and driving factors that lead to successful transitions towards a holistic urban energy planning procedures were identified.

Keywords: energy planning, urban planning, renewable energies, sustainable cities

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Authors: Ho Yin Wickson Cheung, Liora Malki-Epshtein

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Outdoor air pollution presents a significant challenge for public health globally, especially in urban areas, with road traffic acting as the primary contributor to air pollution. Several studies have documented the antagonistic relation between traffic-related air pollution (TRAP) and the impact on health, especially to the vulnerable group of population, particularly young pupils. Generally, TRAP could cause damage to their brain, restricting the ability of children to learn and, more importantly, causing detrimental respiratory issues in later life. Butlittle is known about the specific exposure of children at school during the school day and the impact this may have on their overall exposure to pollution at a crucial time in their development. This project has set out to examine the air quality across primary schools in South-East London and assesses the variability of data found based on their geographic location and surroundings. Nitrogen dioxide, PM contaminants, and carbon dioxide were collected with diffusion tubes and portable monitoring equipment for eight schools across three local areas, that are Greenwich, Lewisham, and Tower Hamlets. This study first examines the geographical features of the schools surrounding (E.g., coverage of urban road structure and green infrastructure), then utilize three different methods to capture pollutants data. Moreover, comparing the obtained results with existing data from monitoring stations to understand the differences in air quality before and during the pandemic. Furthermore, most studies in this field have unfortunately neglected human exposure to pollutants and calculated based on values from fixed monitoring stations. Therefore, this paper introduces an alternative approach by calculating human exposure to air pollution from real-time data obtained when commuting within related areas (Driving routes and field walking). It is found that schools located highly close to motorways are generally not suffering from the most air pollution contaminants. Instead, one with the worst traffic congested routes nearby might also result in poor air quality. Monitored results also indicate that the annual air pollution values have slightly decreased during the pandemic. However, the majority of the data is currently still exceeding the WHO guidelines. Finally, the total human exposures for NO2 during commuting in the two selected routes were calculated. Results illustrated the total exposure for route 1 were 21,730 μm/m3 and 28,378.32 μm/m3, and for route 2 were 30,672 μm/m3 and 16,473 μm/m3. The variance that occurred might be due to the difference in traffic volume that requires further research. Exposure for NO2 during commuting was plotted with detailed timesteps that have shown their peak usually occurred while commuting. These have consolidated the initial assumption to the extremeness of TRAP. To conclude, this paper has yielded significant benefits to understanding air quality across schools in London with the new approach of capturing human exposure (Driving routes). Confirming the severity of air pollution and promoting the necessity of considering environmental sustainability for policymakers during decision making to protect society's future pillars.

Keywords: air pollution, schools, pupils, congestion

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Authors: Kang-Mo Jung

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Least squares support vector machine (LS-SVM) is a penalized regression which considers both fitting and generalization ability of a model. However, the squared loss function is very sensitive to even single outlier. We proposed a weighted absolute deviation loss function for the robustness of the estimates in least absolute deviation support vector machine. The proposed estimates can be obtained by a quadratic programming algorithm. Numerical experiments on simulated datasets show that the proposed algorithm is competitive in view of robustness to outliers.

Keywords: least absolute deviation, quadratic programming, robustness, support vector machine, weight

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Authors: Parag Nihawan, Ravinder Singh Bhatia, Dinesh Kumar Jain

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Industrial drives are source of serious power quality problems. In this, two typical industrial drives have been dealt with, namely, FOC induction motor drives and DTC induction motor drive. The Z-source inverter is an emerging topology of power electronic converters which is capable of buck boost characteristics. The performances of different control methods based Z-source inverters feeding these industrial drives have been investigated, in this work. The test systems have been modeled and simulated in MATLAB/SIMULINK. The results obtained after carrying out these simulations have been used to draw the conclusions.

Keywords: Z-source inverter, total harmonic distortion, direct torque control, field orientation control

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Authors: Benalia Nadia, Bensiali Nadia, Zerzouri Noura

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This paper presents an analysis of the effects of parameters np and nq for exponential load on the transmission line voltage profile, transferred power and transmission losses for different shunt compensation size. For different values for np and nq in which active and reactive power vary with it is terminal voltages as in exponential form, variations of the load voltage for different sizes of shunt capacitors are simulated with a simple two-bus power system using Matlab SimPowerSystems Toolbox. It is observed that the compensation level is significantly affected by the voltage sensitivities of loads.

Keywords: static load model, shunt compensation, transmission system, exponentiel load model

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Authors: Hassan M. Elkamchouchi, Samy H. Darwish, Yasser H. Elkamchouchi, M. E. Morsy

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Methodology is suggested to design a linear rectangular microstrip array antenna based on Yagi antenna theory. The antenna with different directors' lengths as parasitic elements were designed, simulated, and analyzed using HFSS. The calculus and results illustrate the effectiveness of using specific parasitic elements to improve the directivity and gain for microstrip array antenna. The results have shown that the suggested methodology has the potential to be applied for improving the antenna performance. Maximum radiation intensity (Umax) of the order of 0.47w/st was recorded, directivity of 6.58dB, and gain better than 6.07dB are readily achievable for the antenna that working.

Keywords: directivity, director, microstrip antenna, gain improvment

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Authors: Andreas D. Jansson

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The availability of inexpensive, yet competent hardware allows for increased level of automation and self-optimization in the context of Industry 4.0. However, such agents require high quality information about their surroundings along with a robust strategy for collision avoidance, as they may cause expensive damage to equipment or other agents otherwise. Manually defining a strategy to cover all possibilities is both time-consuming and counter-productive given the capabilities of modern hardware. This paper explores the idea of a model-free self-optimizing obstacle avoidance strategy for multiple autonomous agents in a simulated dynamic environment using the Q-learning algorithm.

Keywords: autonomous vehicles, industry 4.0, multi-agent system, obstacle avoidance, Q-learning, simulation

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Authors: Kiana Taheri

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Rural tourism has garnered significant attention as a catalyst for rural development and sustainability, particularly in regions like Tuscany, Italy, where the convergence of cultural heritage, picturesque landscapes, and agricultural traditions provides a fertile ground for tourism activities. This paper investigates the pivotal role of women entrepreneurs in driving sustainable rural tourism development, with a specific focus on Tuscany. Drawing upon a synthesis of literature on rural tourism, entrepreneurship, and gender studies, this research offers insights into how women entrepreneurs contribute to the economic, social, and environmental dimensions of rural tourism in Tuscany. The conceptual framework of this study is rooted in the evolving landscape of rural development, shaped by shifting paradigms in agricultural policies, such as the Common Agricultural Policy (CAP) of the European Union. This framework underscores the transition from traditional agrarian economies to dynamic rural tourism destinations characterized by a consumer-centric approach and a focus on sustainable development. Against this backdrop, the study delves into the multifaceted contributions of women entrepreneurs within the rural tourism sector. Central to the analysis is the recognition of rural tourism as a nexus of social, cultural, economic, and environmental interactions, wherein women entrepreneurs play a pivotal role in leveraging local resources, preserving cultural heritage, and fostering community engagement. By capitalizing on their unique perspectives, skills, and networks, women entrepreneurs drive innovation, diversification, and inclusivity within the tourism sector, thereby enhancing its resilience and long-term viability. Moreover, the study highlights the symbiotic relationship between rural tourism development and women's empowerment, as evidenced by the increasing prominence of women entrepreneurs in Tuscany's rural economy. Through their leadership roles in small and medium enterprises (SMEs) and agritourism ventures, women entrepreneurs not only contribute to economic growth but also challenge traditional gender norms and empower local communities. A key empirical focus of this research is a comprehensive case study of Tuscany, renowned for its successful rural tourism model and vibrant entrepreneurial ecosystem. Through qualitative interviews, surveys, and archival analysis, the study elucidates the strategies, challenges, and impacts of women entrepreneurs on sustainable rural tourism development in Tuscany. By examining the experiences of women entrepreneurs across diverse sectors of rural tourism, including hospitality, gastronomy, and cultural heritage, the study offers nuanced insights into their contributions to regional development and empowerment. In conclusion, this research contributes to the burgeoning scholarship on rural tourism, entrepreneurship, and gender studies by shedding light on the transformative role of women entrepreneurs in driving sustainable development agendas in rural areas. By elucidating the interplay between gender dynamics, entrepreneurial activities, and tourism development, this study seeks to inform policy interventions and strategic initiatives aimed at fostering inclusive and sustainable rural tourism ecosystems.

Keywords: rural tourism, women empowerment, entrepreneurship, sustainable development, small and medium-sized enterprises (SMEs)

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Authors: Abdulazeez Balogun Shittu

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This study investigates the role of self-overestimation and underestimation of others in fueling religious conflicts in Nigeria. Using a mixed-methods approach, this research examines how exaggerated self-perceptions and diminished views of others contribute to intergroup tensions, stereotypes, and violence. The findings reveal that self-overestimation and underestimation of others are significant predictors of religious conflict, mediated by factors such as intergroup bias, social identity, cultural narratives and lack of interfaith dialogue. The study also identifies the consequences of these biases, including Escalated sectarian violence, social cohesion erosion and polarized communities. To mitigate these effects, the research recommends interfaith education and dialogue initiatives, inclusive governance and policy frameworks and pluralistic media representation. This study contributes to the understanding of psychological and social dynamics driving religious conflict in Nigeria, informing evidence-based policies and interventions to promote peaceful coexistence.

Keywords: conflict resolution, intergroup relations, Nigeria, Religious conflict, self-overestimation, social psychology, underestimation of others

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Authors: Etienne K. Ngoy

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This analysis suggests that the comprehensive degradation caused by any environmental factor on fiber reinforced plastics under mechanical stress can be measured as a change in viscoelastic properties of the material. The change in viscoelastic characteristics is experimentally determined as a time-dependent function expressing the amplification of the stress relaxation. The variation of this experimental function provides a measure of the environmental degradation rate. Where real service environment conditions can be reliably simulated in the laboratory, it is possible to generate master curves that include environmental degradation effect and hence predict the durability of the fiber reinforced plastics under environmental degradation.

Keywords: environmental effects, fiber reinforced plastics durability, prediction, stress effect

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Authors: Slimani Halima

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One of the main problems of degradation of arid steppe rangelands in the southern Mediterranean is the loss of plant diversity and changes in soil properties. During the last decades, these rangelands faced two main driving forces: climate through more or less lasting and recurrent droughts and overgrazing by sheep. In the present work, the preexisting system was an arid steppe with alfa grass (Stipa tenacissima L.) as the dominant plant, which was considered to be the "keystone" species toward the whole ecosystem structure and functioning. Vegetation and soil change was monitored for 45 years along a grazing intensity gradient. Changes in species richness and diversity, in the vegetation and in the soil, enabled to better understand climate fluctuations effects in comparison to overgrazing ones. The aim is to assess the impacts of grazing and climatic variability and change on biodiversity,vegetation and soil over a period of 45 years, based on data from seven reference years.

Keywords: biodiversity, desertification, droughts, el bayadh, overgrazing, soil, steppe

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Authors: Rosidah Rosidah

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The paper aims to identify and examine the effectiveness of social marketing as an approach for conducting anti-corruption campaign. Social marketing has been widely used to promote social change for the benefit of individual and society; such as for promoting healthy foods consumption, encouraging breastfeeding, reducing smoking, solving alcohol problem and drunk driving. Therefore, it is believed that this approach can be promising to be used in anti-corruption campaign. It is because social marketing can be useful of prompting people to act in accordance to the existing norms that denounce corruption, or help to establish new norms that more averse to corruption. It has established into evidence and insight based approaches to social campaign that focus on changing people’s behavior. Qualitative approach will be used in this study, with the using of literature review and secondary data analysis as the research methods. This paper is still on preliminary stage, which its results is expected to provide fundamental basis for designing model of intervention (anti-corruption campaign) using social marketing approaches.

Keywords: anti-corruption campaign, behavioral change, social influence, social marketing

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Authors: Somdech Rungsrisawas

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The objectives of this study are to examine the relationship between the competitive advantage of small and medium enterprises (SMEs) and their overall performance. A mixed method has been applied to identify the effect of determinants toward competitive advantage. The sample is composed of SMEs in product and service businesses. The study has been tested at an organizational level with samples of SME entrepreneurs, business successors, and board of directors or management team. Quantitative analysis has been conducted through multiple regression analysis with 400 samples. The findings illustrate that each aspect of competitive advantage needs a different set of driving factors to explain either the direct or the indirect effect on firm performance. Interestingly, technological capability is a perfect mediator and interorganizational cooperation toward competitive advantage. In addition, differentiation is difficult to be perceived by customers, as well as difficult to manage; however, it is considered important to develop an SMEs product or service for firm sustainably.

Keywords: competitive advantage, firm performance, technological capability, Small and Medium Enterprise (SMEs)

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Authors: Ulemu Maseko

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In Malawi, empowering youth-led cooperatives is a pivotal strategy for fostering sustainable development and nurturing inclusive growth. The study delves into the pressing need to understand the impact and potential of youth-led cooperatives in driving socio-economic progress within the country. Through a mixed-methods approach encompassing qualitative interviews, surveys, and case studies, this research investigates the role of these cooperatives in promoting entrepreneurship, community engagement, and sustainable practices among young individuals. The results underscore the significant contribution of youth-led cooperatives towards economic empowerment and social inclusion in Malawi, highlighting their capacity to address local challenges effectively. The study concludes that supporting and investing in youth-led cooperatives is imperative for advancing sustainable development goals and achieving inclusive growth. Recommendations include tailored support mechanisms, capacity-building programs, and strategic partnerships to enhance the resilience and scalability of youth-led cooperative initiatives in Malawi.

Keywords: youth-led cooperatives, sustainable development, Malawi, empowerment

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Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

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Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

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Authors: Mohammed Abdulridha Hamdan

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To face the water crisis, understanding the role of human activities on nutrient concentrations in aquatic ecosystems needs more investigations to compare to extensively studies which have been carried out to understand these impacts on the water quality of different aquatic ecosystems. We hypothesized human activates on the catchments of Tigris river may change nutrient concentrations in water along the river. The results showed that phosphate concentration differed significantly among the studied sites due to distributed human activities, while nitrate concentration did not. Phosphate and nitrate concentrations were not affected by water temperature. We concluded that human activities on the surrounding landscapes could be more essential sources for nutrients of aquatic ecosystems than role of ongoing climate warming. Despite the role of warming in driving nutrients availability in aquatic ecosystems, our findings suggest to take the different activities on the surrounding catchments into account in the studies caring about the trophic status classification of aquatic ecosystems.

Keywords: nitrate, phosphate, anthropogenic, warming

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Authors: Mustafa Alhamdi

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Industrial application to classify gamma rays and neutron events is investigated in this study using deep machine learning. The identification using a convolutional neural network and recursive neural network showed a significant improvement in predication accuracy in a variety of applications. The ability to identify the isotope type and activity from spectral information depends on feature extraction methods, followed by classification. The features extracted from the spectrum profiles try to find patterns and relationships to present the actual spectrum energy in low dimensional space. Increasing the level of separation between classes in feature space improves the possibility to enhance classification accuracy. The nonlinear nature to extract features by neural network contains a variety of transformation and mathematical optimization, while principal component analysis depends on linear transformations to extract features and subsequently improve the classification accuracy. In this paper, the isotope spectrum information has been preprocessed by finding the frequencies components relative to time and using them as a training dataset. Fourier transform implementation to extract frequencies component has been optimized by a suitable windowing function. Training and validation samples of different isotope profiles interacted with CdTe crystal have been simulated using Geant4. The readout electronic noise has been simulated by optimizing the mean and variance of normal distribution. Ensemble learning by combing voting of many models managed to improve the classification accuracy of neural networks. The ability to discriminate gamma and neutron events in a single predication approach using deep machine learning has shown high accuracy using deep learning. The paper findings show the ability to improve the classification accuracy by applying the spectrogram preprocessing stage to the gamma and neutron spectrums of different isotopes. Tuning deep machine learning models by hyperparameter optimization of neural network models enhanced the separation in the latent space and provided the ability to extend the number of detected isotopes in the training database. Ensemble learning contributed significantly to improve the final prediction.

Keywords: machine learning, nuclear physics, Monte Carlo simulation, noise estimation, feature extraction, classification

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Authors: Madina Hamiane

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Modelling and simulation of an analogy function generator is presented based on a polynomial expansion model. The proposed function generator model is based on a 10th order polynomial approximation of any of the required functions. The polynomial approximations of these functions can then be implemented using basic CMOS circuit blocks. In this paper, a circuit model is proposed that can simultaneously generate many different mathematical functions. The circuit model is designed and simulated with HSPICE and its performance is demonstrated through the simulation of a number of non-linear functions.

Keywords: modelling and simulation, analog function generator, polynomial approximation, CMOS transistors

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Authors: V. Sivasubramanian, M. Jerold

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The advancement of adsorption is the development of nano-biocomposite for the sorption dyes and heavy metal ions. In fact, Nanoscale zerovalent iron (NZVI) is cost-effective reducing agent and a most reliable biosorbent for the dye biosorption. In this study, nano zero valent iron Sargassum swartzii (nZVI-SS) biocomposite, a novel marine algal based biosorbent, was used for the removal of simulated crystal violet (CV) in batch mode of operation. The Box-Behnen design (BBD) experimental results revealed the biosoprtion was maximum at pH 7.5, biosorbent dosage 0.1 g/L and initial CV concentration of 100 mg/L. Therefore, the result implies that nZVI-SS biocomposite is a cheap and most promising biosorbent for the removal of CV from wastewater.

Keywords: algae, biosorption, zero-valent, dye, waste water

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Authors: A. Elmikaty, Z. Thanawarothon, L. Mezeix

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This paper presents a finite element model to simulate the teeth failure of non-circular composite chainring. Model consists of the chainring and a part of the chain. To reduce the size of the model, only the first 11 rollers are simulated. In order to validate the model, it is firstly applied to a circular aluminum chainring and evolution of the stress in the teeth is compared with the literature. Then, effect of the non-circular shape is studied through three different loading positions. Strength of non-circular composite chainring and failure scenario is investigated. Moreover, two composite lay-ups are proposed to observe the influence of the stacking. Results show that composite material can be used but the lay-up has a large influence on the strength. Finally, loading position does not have influence on the first composite failure that always occurs in the first tooth.

Keywords: CFRP, composite failure, FEA, non-circular chainring

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

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

Keywords: causticizing, lime, prediction, process

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Authors: B. Mahfoud, A. Bendjaghlouli

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Natural convection is simulated in a truncated cone filled with nanofluid. Inclined and top walls have constant temperature where the heat source is located on the bottom wall of the conical container which is thermally insulated. A finite volume approach is used to solve the governing equations using the SIMPLE algorithm for different parameters such as Rayleigh number, inclination angle of inclined walls of the enclosure and heat source length. The results showed an enhancement in cooling system by using a nanofluid, when conduction regime is assisted. The inclination angle of inclined sidewall and heat source length affect the heat transfer rate and the maximum temperature.

Keywords: heat source, truncated cone, nanofluid, natural convection

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Authors: Inderpreet Kaur, Ravinder Pal Singh, Kamal Kant Sharma

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This paper addresses the different configurations used of optical amplifiers with 16 channels in Wavelength Division Multiplexed system. The systems with 16 channels have been simulated for evaluation of various parameters; Bit Error Rate, Quality Factor, for threshold values for a range of wavelength from 1471 nm to 1611 nm. Comparison of various combination of configurations have been analyzed with EDFA and FRA but EDFA-FRA configuration performance has been found satisfactory in terms of performance indices and stable region. The paper also compared various parameters quantized with different configurations individually. It has been found that Q factor has high value with less value of BER and high resolution for EDFA-FRA configuration.

Keywords: EDFA, FRA, WDM, Q factor, BER

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Authors: Liyana Zahid, Mohd Fareq Abd Malek, Ee Meng Cheng, Wei Wen Liu, Yeng Seng Lee, Muhammad Nadeem Iqbal, Fwen Hoon Wee

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One of the parameters that affect the performance of microwave absorbers is the shape of the absorbers. This paper shows the performance (reflection loss) of truncated pyramidal and truncated wedge microwave absorbers in the range frequency between 8.2 to 12.4 GHz (X-Band) in simulation. The material used is sugarcane bagasse (SCB) which is one of the new materials that used to fabricate the microwave absorber. The complex permittivity was measured using Agilent dielectric probe technique. The designs were simulated using CST Microwave Studio Software. The reflection losses between these two shapes were compared.

Keywords: microwave absorber, reflection loss, sugarcane bagasse (SCB), X-Band

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Authors: James Moir

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This paper considers the political controversy in Britain, both pre- and post-EU referendum, concerning claims over welfare benefit tourism and immigration in the UK. These claims were seen to be a significant reason for the vote for Brexit despite evidence to the contrary that benefit tourism was not, and is not, implicated in the migration of East Europeans to the UK. Populist rhetoric is analysed alongside studies that contradict such views. These contentious issues are examined with respect to the agenda set by the United Kingdom Independence Party (UKIP) concerning anti-EU and anti-immigrant sentiment and the notion of cultural differences as the basis for supporting Brexit. The paper also examines the paradoxical claim that East European migrants are taking British jobs and driving down wages. Taken together, it is argued that these two kinds of claims effectively contribute to anti-immigration discourse based on the logic of economics, but also at the same time conceal more irrational fears of adapting to change through the inclusion of others. Such fears are considered as being founded upon a challenge to the stability of totems of national life and identity.

Keywords: benefits, Brexit, immigration, tourism, welfare

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Authors: Faten Hatem

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This paper explores the associated understanding of the role and meaning of art and whether it is perceived to be separate from smart city construction. The paper emphasises the significance of fulfilling the inherent need for discovery and interaction, driving people to explore new places and think of works of art. This is done by exploring the ways of thinking and types of art in Milton Keynes by illustrating a general pattern of misunderstanding that relies on the separation between smart, art, and architecture, promoting a better and deeper understanding of the interconnections between neuroscience, art, and architecture. A reflective approach is used to clarify the potential and impact of using art-based research, methodology, and ways of knowing when approaching global phenomena and knowledge production while examining the process of making and developing smart cities, in particular, asserting that factors can severely impact it in the process of conducting the study itself. It follows a case study as a research strategy. The qualitative methods included data collection and analysis that involved interviews and observations that depended on visuals.

Keywords: smart cities, art and smart, smart cities design, smart cities making, sustainability, city brain and smart cities metrics, smart cities standards, smart cities applications, governance, planning and policy

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