Search results for: computer fluid dynamic simulation in urban environment

Authors: I. L. Kim, J. Y. Lee, A. K. Tekile

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In consequence of the very high urbanization rate of Korea, the number of traffic noise damages in areas congested with population and facilities is steadily increasing. The current environmental noise levels data in major cities of the country show that the noise levels exceed the standards set for both day and night times. This research was about comparative analysis in search for optimal soundproof panel shape and design factor that can minimize sound reflection noise. In addition to the normal flat-type panel shape, the reflection noise reduction of swelling-type, combined swelling and curved-type, and screen-type were evaluated. The noise source model Nord 2000, which often provides abundant information compared to models for the similar purpose, was used in the study to determine the overall noise level. Based on vehicle categorization in Korea, the noise levels for varying frequency from different heights of the sound source (directivity heights of Harmonize model) have been calculated for simulation. Each simulation has been made using the ray-tracing method. The noise level has also been calculated using the noise prediction program called SoundPlan 7.2, for comparison. The noise level prediction was made at 15m (R1), 30 m (R2) and at middle of the road, 2m (R3) receiving the point. By designing the noise barriers by shape and running the prediction program by inserting the noise source on the 2nd lane to the noise barrier side, among the 6 lanes considered, the reflection noise slightly decreased or increased in all noise barriers. At R1, especially in the cases of the screen-type noise barriers, there was no reduction effect predicted in all conditions. However, the swelling-type showed a decrease of 0.7~1.2 dB at R1, performing the best reduction effect among the tested noise barriers. Compared to other forms of noise barriers, the swelling-type was thought to be the most suitable for reducing the reflection noise; however, since a slight increase was predicted at R2, further research based on a more sophisticated categorization of related design factors is necessary. Moreover, as swellings are difficult to produce and the size of the modules are smaller than other panels, it is challenging to install swelling-type noise barriers. If these problems are solved, its applicable region will not be limited to other types of noise barriers. Hence, when a swelling-type noise barrier is installed at a downtown region where the amount of traffic is increasing every day, it will both secure visibility through the transparent walls and diminish any noise pollution due to the reflection. Moreover, when decorated with shapes and design, noise barriers will achieve a visual attraction than a flat-type one and thus will alleviate any psychological hardships related to noise, other than the unique physical soundproofing functions of the soundproof panels.

Keywords: reflection noise, shaped noise barriers, sound proof panel, traffic noise

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Authors: Ishan Tank, Ashmita Rupal, Sanjay Kumar Sharma

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Concrete, a widely used building material, has cement as its main constituent. An excessive amount of emissions are released into the atmosphere during the manufacture of cement, which is detrimental to the environment. To minimize this problem, innovative materials like geopolymer mortar (GPM) seem to be a better alternative. By using fly ash-based geopolymer instead of standard cement mortar as a binding ingredient, this concept has been successfully applied to the building sector. The advancement of this technology significantly reduces greenhouse gas emissions and helps in source reduction, thereby minimizing pollution of the environment. In order to produce mortar and use this geopolymer mortar in the development of building materials, the current investigation is properly introducing this geopolymeric material, namely fly ash, as a binder in place of standard cement. In the domain of the building material industry, fly ash based geopolymer is a new and optimistic replacement for traditional binding materials because it is both environmentally sustainable and has good durability. The setting behaviour and strength characteristics of fly ash, when mixed with alkaline activator solution with varied concentration of sodium hydroxide solution, alkaline liquids mix ratio, and curing temperature, must be investigated, though, in order to determine its suitability and application in comparison with the traditional binding material, by activating the raw materials, which include various elements of silica and alumina, finer material known as geopolymer mortar is created. The concentration of the activator solution has an impact on the compressive strength of the geopolymer concrete formed. An experimental examination of compressive strength after 7, 14, and 28 days of fly ash-based geopolymer concrete is presented in this paper. Furthermore, the process of geopolymerization largely relies on the curing temperature. So, the setting time of Geopolymer mortar due to different curing temperatures has been studied and discussed in this paper.

Keywords: geopolymer mortar, setting time, flyash, compressive strength, binder material

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Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov

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Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).

Keywords: cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing

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Authors: Nini Johana Marín Rodríguez, William Fernando Oquendo Patino

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In this work, we model a coupled system where we explore the effects of steady and random behavior on a linear system like an extension of the classic Strogatz model. This is exemplified by modeling a couple love dynamics as a linear system of two coupled differential equations and studying its stability for four types of lovers chosen as CC='Cautious- Cautious', OO='Only other feelings', OP='Opposites' and RR='Romeo the Robot'. We explore the effects of, first, introducing saturation, and second, adding a random variation to one of the CC-type lover, which will shape his character by trying to model how its variability influences the dynamics between love and hate in couple in a long run relationship. This work could also be useful to model other kind of systems where interactions can be modeled as linear systems with external or internal random influence. We found the final results are not easy to predict and a strong dependence on initial conditions appear, which a signature of chaos.

Keywords: differential equations, dynamical systems, linear system, love dynamics

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Authors: Eui-Hak Lee, Jae-Hyun Ro, Hyoung-Kyu Song

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In internet of things (IoT) system, the communication scheme with reliability and low power is required to connect a terminal. Cooperative communication can achieve reliability and lower power than multiple-input multiple-output (MIMO) system. Cooperative communication increases the reliability with low power, but decreases a throughput. It has a weak point that the communication throughput is decreased. In this paper, a novel scheme is proposed to increase the communication throughput. The novel scheme is a transmission structure that increases transmission rate. And a decoding scheme according to the novel transmission structure is proposed. Simulation results show that the proposed scheme increases the throughput without bit error rate (BER) performance degradation.

Keywords: cooperative communication, IoT, STBC, transmission rate

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Authors: Masoumeh Mofarrah, Amir NahanMoghadam

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Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise, and improve EOR methods and their application. Recently, Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic, and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization infeasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

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Authors: Gyu-Dong Kim, Wuk-Jae Yoo, Sang-Youl Lee

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Composite structures offer numerous advantages over conventional structural systems in the form of higher specific stiffness and strength, lower life-cycle costs, and benefits such as easy installation and improved safety. Recently, there has been a considerable increase in the use of composites in engineering applications and as wraps for seismic upgrading and repairs. However, these composites deteriorate with time because of outdated materials, excessive use, repetitive loading, climatic conditions, manufacturing errors, and deficiencies in inspection methods. In particular, damaged fibers in a composite result in significant degradation of structural performance. In order to reduce the failure probability of composites in service, techniques to assess the condition of the composites to prevent continual growth of fiber damage are required. Condition assessment technology and nondestructive evaluation (NDE) techniques have provided various solutions for the safety of structures by means of detecting damage or defects from static or dynamic responses induced by external loading. A variety of techniques based on detecting the changes in static or dynamic behavior of isotropic structures has been developed in the last two decades. These methods, based on analytical approaches, are limited in their capabilities in dealing with complex systems, primarily because of their limitations in handling different loading and boundary conditions. Recently, investigators have introduced direct search methods based on metaheuristics techniques and artificial intelligence, such as genetic algorithms (GA), simulated annealing (SA) methods, and neural networks (NN), and have promisingly applied these methods to the field of structural identification. Among them, GAs attract our attention because they do not require a considerable amount of data in advance in dealing with complex problems and can make a global solution search possible as opposed to classical gradient-based optimization techniques. In this study, we propose an alternative damage-detection technique that can determine the degraded stiffness distribution of vibrating laminated composites made of Glass Fiber-reinforced Polymer (GFRP). The proposed method uses a modified form of the bivariate Gaussian distribution function to detect degraded stiffness characteristics. In addition, this study presents a method to detect the fiber property variation of laminated composite plates from the micromechanical point of view. The finite element model is used to study free vibrations of laminated composite plates for fiber stiffness degradation. In order to solve the inverse problem using the combined method, this study uses only first mode shapes in a structure for the measured frequency data. In particular, this study focuses on the effect of the interaction among various parameters, such as fiber angles, layup sequences, and damage distributions, on fiber-stiffness damage detection.

Keywords: stiffness detection, fiber damage, genetic algorithm, layup sequences

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Authors: Jung Hyun Kim, Gyo Woo Lee

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In this study, the enhancement of the heat release performance of an extruded-type heat sink to prepare the large-capacity solar inverter thru the flow holes in the base plate near the heat sources was investigated. Optimal location and number of the holes in the baseplate were determined by using a commercial computation program. The heat release performance of the shape-modified heat sink was measured experimentally and compared with that of the simulation. The heat sink with 12 flow holes in the 18-mm-thick base plate has a 8.1% wider heat transfer area, a 2.5% more mass flow of air, and a 2.7% higher heat release rate than those of the original heat sink. Also, the surface temperature of the base plate was lowered 1.5°C by the holes.

Keywords: heat sink, forced convection, heat transfer, performance evaluation, flow holes

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Authors: O. Akinola, R. Mustapha

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Obesity is the most serious long-term health problem currently facing adolescents and its prevalence increasing worldwide including developing countries. A cross-sectional study was carried out among age 11-19 years in both public and private school in the urban area of the state. The data was collected using pretest self-administered questionnaire; Anthropometric measurement was also used to examine their nutritional status. Obesity status were determined using BMI cut off point, the overweight was found to be 3.06% among female and 0.6% among male whereas the prevalence of obesity was 0.46% in female and non among male. 62.6% snack daily, fruit consumption pattern was low 0.6%, and 43.7% spend between 4-5 hours watching television daily after school. A positive association exists between the lifestyle and nutritional status of the respondents. Education effort to improve nutrition knowledge can be incorporated into course curriculum and focus on various components within the system when implementing preventive measure on obesity.

Keywords: adolescent, obesity, overweight, prevalence

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Authors: Ibrahim A. Aref, Tarek El-Mihoub, Khadiga Ben Musa

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This paper presents Carrier Sense Multiple Access (CSMA) communication model based on SoC design methodology. Such model can be used to support the modelling of the complex wireless communication systems, therefore use of such communication model is an important technique in the construction of high performance communication. SystemC has been chosen because it provides a homogeneous design flow for complex designs (i.e. SoC and IP based design). We use a swarm system to validate CSMA designed model and to show how advantages of incorporating communication early in the design process. The wireless communication created through the modeling of CSMA protocol that can be used to achieve communication between all the agents and to coordinate access to the shared medium (channel).

Keywords: systemC, modelling, simulation, CSMA

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Authors: Piotr Prewysz-Kwinto

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A dynamic development of financial market is accompanied by the emergence of new products on stock exchanges which give absolutely new possibilities of investing money. Currently, the most innovative financial instruments offered to investors are exchange traded products (ETP). They can be defined as financial instruments whose price depends on the value of the underlying instrument. Thus, they offer investors a possibility of making a profit that results from the change in value of the underlying instrument without having to buy it. Currently, the Warsaw Stock Exchange offers many types of ETPs. They are investment products with full or partial capital protection, products without capital protection as well as leverage products, issued on such underlying instruments as indices, sector indices, commodity indices, prices of energy commodities, precious metals, agricultural produce or prices of shares of domestic and foreign companies. This paper presents the mechanism of functioning of ETP available on the Warsaw Stock Exchange and the results of the analysis of statistical data on these financial instruments.

Keywords: exchange traded products, financial market, investment, stock exchange

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Authors: Drew Commandeur, Ryan Brodie, Sandra Hundza, Marc Klimstra

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The amplitude of raw electromyography (EMG) is affected by recording conditions and often requires normalization to make meaningful comparisons. Bioelectric methods normalize with an EMG signal recorded during a standardized task or from the experimental protocol itself, while biomechanical methods often involve measurements with an additional sensor such as a force transducer. Common bioelectric normalization techniques for treadmill walking include maximum voluntary isometric contraction (MVIC), dynamic EMG peak (EMGPeak) or dynamic EMG mean (EMGMean). There are several concerns with using MVICs to normalize EMG, including poor reliability and potential discomfort. A limitation of bioelectric normalization techniques is that they could result in a misrepresentation of the absolute magnitude of force generated by the muscle and impact the interpretation of EMG between functionally disparate groups. Additionally, methods that normalize to EMG recorded during the task may eliminate some real inter-individual variability due to biological variation. This study compared biomechanical and bioelectric EMG normalization techniques during treadmill walking to assess the impact of the normalization method on the functional interpretation of EMG data. For the biomechanical method, we normalized EMG to a target torque (EMGTS) and the bioelectric methods used were normalization to the mean and peak of the signal during the walking task (EMGMean and EMGPeak). The effect of normalization on muscle activation pattern, EMG amplitude, and inter-individual variability were compared between disparate cohorts of OLD (76.6 yrs N=11) and YOUNG (26.6 yrs N=11) adults. Participants walked on a treadmill at a self-selected pace while EMG was recorded from the right lower limb. EMG data from the soleus (SOL), medial gastrocnemius (MG), tibialis anterior (TA), vastus lateralis (VL), and biceps femoris (BF) were phase averaged into 16 bins (phases) representing the gait cycle with bins 1-10 associated with right stance and bins 11-16 with right swing. Pearson’s correlations showed that activation patterns across the gait cycle were similar between all methods, ranging from r =0.86 to r=1.00 with p<0.05. This indicates that each method can characterize the muscle activation pattern during walking. Repeated measures ANOVA showed a main effect for age in MG for EMGPeak but no other main effects were observed. Interactions between age*phase of EMG amplitude between YOUNG and OLD with each method resulted in different statistical interpretation between methods. EMGTS normalization characterized the fewest differences (four phases across all 5 muscles) while EMGMean (11 phases) and EMGPeak (19 phases) showed considerably more differences between cohorts. The second notable finding was that coefficient of variation, the representation of inter-individual variability, was greatest for EMGTS and lowest for EMGMean while EMGPeak was slightly higher than EMGMean for all muscles. This finding supports our expectation that EMGTS normalization would retain inter-individual variability which may be desirable, however, it also suggests that even when large differences are expected, a larger sample size may be required to observe the differences. Our findings clearly indicate that interpretation of EMG is highly dependent on the normalization method used, and it is essential to consider the strengths and limitations of each method when drawing conclusions.

Keywords: electromyography, EMG normalization, functional EMG, older adults

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Authors: Matthew McArthur, Margaret Friend

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The COVID-19 pandemic disrupted the stability of the home environment for families across the world. Potential disruptions include parent work modality (in-person vs. remote), levels of health anxiety, family routines, and caregiving. These disruptions may have interfered with the processes of early vocabulary acquisition, carrying lasting effects over the life course. Our justification for this research is as follows: First, early, stable, caregiver-child reciprocal interactions, which may have been disrupted during the pandemic, contribute to the development of the brain architecture that supports language, cognitive, and social-emotional development. Second, early vocabulary predicts several cognitive outcomes, such as numeracy, literacy, and executive function. Further, disruption in the home is associated with adverse cognitive, academic, socio-emotional, behavioral, and communication outcomes in young children. We are interested in how disruptions related to the COVID-19 pandemic are associated with vocabulary acquisition in children born during the first two waves of the pandemic. We are conducting a moderated online experiment to assess this question. Participants are 16 children (10F) ranging in age from 19 to 39 months (M=25.27) and their caregivers. All child participants were screened for language background, health history, and history of language disorders, and were typically developing. Parents completed a modified version of the COVID-19 Family Stressor Scale (CoFaSS), a published measure of COVID-19-related family stressors. Thirteen items from the original scale were replaced to better capture change in family organization and stability specifically related to disruptions in income, anxiety, family relations, and childcare. Following completion of the modified CoFaSS, children completed a Web-Based version of the Computerized Comprehension Task and the Receptive One Word Picture Vocabulary if 24 months or older or the MacArthur-Bates Communicative Development Inventory if younger than 24 months. We report our preliminary data as a partial correlation analysis controlling for age. Raw vocabulary scores on the CCT, ROWPVT-4, and MCDI were all negatively associated with pandemic-related disruptions related to anxiety (r12=-.321; r1=-.332; r9=-.509), family relations (r12=-.590*; r1=-.155; r9=-.468), and childcare (r12=-.294; r1=-.468; r9=-.177). Although the small sample size for these preliminary data limits our power to detect significance, this trend is in the predicted direction, suggesting that increased pandemic-related disruption across multiple domains is associated with lower vocabulary scores. We anticipate presenting data on a full sample of 50 monolingual English participants. A sample of 50 participants would provide sufficient statistical power to detect a moderate effect size, adhering to a nominal alpha of 0.05 and ensuring a power level of 0.80.

Keywords: COVID-19, early vocabulary, home environment, language acquisition, multiple measures

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Authors: A. Keshavarz, Z. Roosta

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In this paper, propagation of cos-Gaussian beam in strongly nonlocal nonlinear media has been stimulated by using paraxial group transformation. At first, cos-Gaussian beam, nonlocal nonlinear media, critical power, transfer matrix, and paraxial group transformation are introduced. Then, the propagation of the cos-Gaussian beam in strongly nonlocal nonlinear media is simulated. Results show that beam propagation has periodic structure during self-focusing effect in this case. However, this simple method can be used for investigation of propagation of kinds of beams in ABCD optical media.

Keywords: paraxial group transformation, nonlocal nonlinear media, cos-Gaussian beam, ABCD law

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Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: B. Seetanah, H. Neeliah

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This paper investigates the relationship among energy, emissions and economic growth in Mauritius in the presence of trade activities, with capital and labour as other control variables. Using annual data from 1960 to 2011, it is found that the variables are non-stationary and cointegrated. The relationship among the various variables are thus examined in a dynamic VECM framework. Our empirical results comply with the growth hypothesis. Output elasticities of 0.17, 0.25 and 0.43 show that increases in energy consumption cause increases in economic growth, capital accumulation and trade in the long run. We also found that CO2 negatively affects output, but has no significant effect on trade. Findings for the long-run generally tend to tally with those in the short-run. Interestingly we found that energy consumption has a significant impact on CO2 emissions. Our results tend to suggest that implementing energy conservation strategies to mitigate the negative impact of CO2 emissions can dent economic growth, and that promoting cleaner energy production could be a better alternative for Mauritius.

Keywords: energy, emissions, economic growth, export, VECM

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Authors: Elabed Saud

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This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

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Authors: D. B. Gohil

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Closed die forging is a very complex process, and measurement of actual forces for real material is difficult and time consuming. Hence, the modelling technique has taken the advantage of carrying out the experimentation with the proper model material which needs lesser forces and relatively low temperature. The results of experiments on the model material then may be correlated with the actual material by using the theory of similarity. There are several methods available to resolve the complexity involved in the closed die forging process. Finite Element Method (FEM) and Finite Difference Method (FDM) are relatively difficult as compared to the slab method. The slab method is very popular and very widely used by the people working on shop floor because it is relatively easy to apply and reasonably accurate for most of the common forging load requirement computations.

Keywords: experimentation, forging, process modeling, strain distribution

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Authors: R. Nasrin, M. Ferdows

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Among the renewable energy sources, photovoltaic (PV) is a high potential, effective, and sustainable system. Irradiation intensity from 200 W/m2 to 1000 W/m2 has been considered to observe the performance of PV module. Generally, this module converts only about 15% - 20% of incident irradiation into electrical energy and the rest part is converted into heat energy. Finite element method has been used to solve the problem numerically. Simulation has been performed by considering the ambient temperature 30°C. Higher irradiation increase solar cell temperature and electrical power. The electrical efficiency of PV module decreases with the variation of solar radiation. The efficiency of PV module can be increased if cell temperature is reduced. Thus the effect of irradiation is significant to enhance the efficiency of PV module if the solar cell temperature is kept at a certain level.

Keywords: PV module, solar radiation, efficiency, cell temperature

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Authors: Utkan Mutman, Cihan Dirlik

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Kocaeli/TURKEY district in which wastewater held in a chosen field increased property has made piling in order to improve the ground under the aeration basin. In this study, the degree of improvement the ground after bored piling held in the field were investigated. In this context, improving the ground before and after the investigation was carried out and that the solution values obtained by the finite element method analysis using Plaxis program have been made. The diffuses in the aeration basin whose treatment is to aide is influenced with and without geogrid on the ground. On the ground been improved, for the purpose of control of manufactured bored piles, pile continuity, and pile load tests were made. Taking into consideration both the data in the field as well as dynamic loads in the aeration basic, an analysis was made on Plaxis program and compared the data obtained from the analysis result and data obtained in the field.

Keywords: geogrid, bored pile, soil improvement, plaxis

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Authors: Tung-Kuang Wu, Hsing-Pei Hsieh, Ying-Ru Meng

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Special Education in Taiwan has been facing difficulties including shortage of teachers and lack in resources. Some students need to receive special education are thus not identified or admitted. Fortunately, information technologies can be applied to relieve some of the difficulties. For example, on-line multimedia courseware can be used to assist the learning of special education students and take pretty much workload from special education teachers. However, there may exist cognitive variations between students in special or regular educations, which suggests the design of online courseware requires different considerations. This study aims to investigate the difference in focus of attention (FOA) between special and regular education students of primary school in viewing the computer screen. The study is essential as it helps courseware developers in determining where to put learning elements that matter the most on the right position of screen. It may also assist special education specialists to better understand the subtle differences among various subtypes of learning disabilities. This study involves 76 special education students (among them, 39 are students with mental retardation, MR, and 37 are students with learning disabilities, LDs) and 42 regular education students. The participants were asked to view a computer screen showing a picture partitioned into 3 × 3 areas with each area filled with text or icon. The subjects were then instructed to mark on the prior given paper sheets, which are also partitioned into 3 × 3 grids, the areas corresponding to the pictures on the computer screen that they first set their eyes on. The data are then collected and analyzed. Major findings are listed: 1. In both text and icon scenario, significant differences exist in the first preferred FOA between special and regular education students. The first FOA for the former is mainly on area 1 (upper left area, 53.8% / 51.3% for MR / LDs students in text scenario; and 53.8% / 56.8% for MR / LDs students in icons scenario), while the latter on area 5 (middle area, 50.0% and 57.1% in text and icons scenarios). 2. The second most preferred area in text scenario for students with MR and LDs are area 2 (upper-middle, 20.5%) and 5 (middle area, 24.3%). In icons scenario, the results are similar, but lesser in percentage. 3. Students with LDs that show similar preference (either in text or icons scenarios) in FOA to regular education students tend to be of some specific sub-type of learning disabilities. For instance, students with LDs that chose area 5 (middle area, either in text or icon scenario) as their FOA are mostly ones that have reading or writing disability. Also, three (out of 13) subjects in this category, after going through the rediagnosis process, were excluded from being learning disabilities. In summary, the findings suggest when designing multimedia courseware for students with MR and LDs, the essential learning elements should be placed on area 1, 2 and 5. In addition, FOV preference may also potentially be used as an indicator for diagnosing students with LDs.

Keywords: focus of attention, learning disabilities, mental retardation, on-line multimedia courseware, special education

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Authors: Rakhyun Kim, Sungho Tae

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Global environmental issues such as abnormal weathers due to global warming, resource depletion, and ecosystem distortions have been escalating due to rapid increase of population growth, and expansion of industrial and economic development. Accordingly, initiatives have been implemented by many countries to protect the environment through indirect regulation methods such as Environmental Product Declaration (EPD), in addition to direct regulations such as various emission standards. Following this trend, life cycle assessment (LCA) techniques that provide quantitative environmental information, such as Human Toxicity Potential (HTP), for buildings are being developed in the construction industry. However, at present, the studies on the environmental database of building materials are not sufficient to provide this support adequately. The purpose of this study is to analysis human toxicity potential of major building material production stage using life cycle assessment. For this purpose, the theoretical consideration of the life cycle assessment and environmental impact category was performed and the direction of the study was set up. That is, the major material in the global warming potential view was drawn against the building and life cycle inventory database was selected. The classification was performed about 17 kinds of substance and impact index, such as human toxicity potential, that it specifies in CML2001. The environmental impact of analysis human toxicity potential for the building material production stage was calculated through the characterization. Meanwhile, the environmental impact of building material in the same category was analyze based on the characterization impact which was calculated in this study. In this study, establishment of environmental impact coefficients of major building material by complying with ISO 14040. Through this, it is believed to effectively support the decisions of stakeholders to improve the environmental performance of buildings and provide a basis for voluntary participation of architects in environment consideration activities.

Keywords: human toxicity potential, major building material, life cycle assessment, production stage

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Authors: M. A. Sohaly, M. A. Elfouly

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Parkinson's disease (PD) is a heterogeneous movement disorder that often appears in the elderly. PD is induced by a loss of dopamine secretion. Some drugs increase the secretion of dopamine. In this paper, we will simply study the stability of PD models as a nonlinear delay differential equation. After a period of taking drugs, these act as positive feedback and increase the tremors of patients, and then, the differential equation has positive coefficients and the system is unstable under these conditions. We will present a set of suggested modifications to make the system more compatible with the biodynamic system. When giving a set of numerical examples, this research paper is concerned with the mathematical analysis, and no clinical data have been used.

Keywords: Parkinson's disease, stability, simulation, two delay differential equation

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Authors: Ohud Adnan Saffar

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This study aims to know the effect of using universal design for learning (UDL) to improve the quality of vocational programme with intellectual disabilities (SID) and the challenges facing this method from the teachers' point of view. The significance of the study: There are comparatively few published studies on UDL in emerging nations. Therefore, this study will encourage the researchers to consider a new approaches teaching. Development of this study will contribute significant information on the cognitively disabled community on a universal scope. In order to collect and evaluate the data and for the verification of the results, this study has been used the mixed research method, by using two groups comparison method. To answer the study questions, we were used the questionnaire, lists of observations, open questions, and pre and post-test. Thus, the study explored the advantages and drawbacks, and know about the impact of using the UDL method on integrating SID with students non-special education needs in the same classroom. Those aims were realized by developing a workshop to explain the three principles of the UDL and train (16) teachers in how to apply this method to teach (12) students non-special education needs and the (12) SID in the same classroom, then take their opinion by using the questionnaire and questions. Finally, this research will explore the effects of the UDL on the teaching of professional photography skills for the SID in Saudi Arabia. To achieve this goal, the research method was a comparison of the performance of the SID using the UDL method with that of female students with the same challenges applying other strategies by teachers in control and experiment groups, we used the observation lists, pre and post-test. Initial results: It is clear from the previous response to the participants that most of the answers confirmed that the use of UDL achieves the principle of inclusion between the SID and students non-special education needs by 93.8%. In addition, the results show that the majority of the sampled people see that the most important advantages of using UDL in teaching are creating an interactive environment with using new and various teaching methods, with a percentage of 56.2%. Following this result, the UDL is useful for integrating students with general education, with a percentage of 31.2%. Moreover, the finding indicates to improve understanding through using the new technology and exchanging the primitive ways of teaching with the new ones, with a percentage of 25%. The result shows the percentages of the sampled people's opinions about the financial obstacles, and it concluded that the majority see that the cost is high and there is no computer maintenance available, with 50%. There are no smart devices in schools to help in implementing and applying for the program, with a percentage of 43.8%.

Keywords: universal design for learning, intellectual disabilities, vocational programme, the challenges facing this method

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Authors: Ida Bagus Ilham Malik, Bart Julian Dewancker

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The road construction will affect the development of the region along the new road. With this principle, the government developed Antasari Street in order to become one of the main economic corridors for the city of Bandar Lampung. Since its construction in 1997, Antasari Street developed into one of the main economic corridors that greatly affect the economic condition of the city, in addition to other economic corridors such as Pagar Alam Street and Teuku Umar Street. The data shows that the construction of roads affects economic development in the corridor that with the advent of commercial buildings in large quantities. Among them are shops, office, restaurants, and a car showroom. This study proves that the road construction could accelerate the economic progress of the road corridor, especially in the construction and development of urban roads.

Keywords: road development, commercial area, Antasari street, Bandar Lampung

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Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

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Authors: Victoria Masi Haruna Karatu, Nik Kamariah Nikmat

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In recent times awareness about the environment and green purchase has been on the increase across nations due to global warming. Previous researchers have attempted to determine what actually influences the purchase intention of consumers in this environmentally conscious epoch. The consumers too have become conscious of what to buy and who to buy from in their purchasing decisions as this action will reflect their concern about the environment and their personal well-being. This trend is a widespread phenomenon in most developed countries of the world. On the contrary evidence revealed that only 5% of the populations of Nigeria involve in green purchase activities thus making the country lag behind its counterparts in green practices. This is not a surprise as Nigeria is facing problems of inadequate green knowledge, non-enforcement of environmental regulations, sensitivity to the price of green products when compared with the conventional ones and distrust towards green products which has been deduced from prior studies of other regions. The main objectives of this study is to examine the direct antecedents of green purchase intention (green availability, government regulations, perceived green knowledge, perceived value and green price sensitivity) in Nigeria and secondly to establish the mediating role of perceived behavioral control on the relationship between these antecedents and green purchase intention. The study adopts quantitative method whereby 700 questionnaires were administered to lecturers in three Nigerian universities. 502 datasets were collected which represents 72 percent response rate. After screening the data only 440 were usable and analyzed using structural equation modeling (SEM) and bootstrapping. From the findings, three antecedents have significant direct relationships with green purchase intention (perceived green knowledge, perceived behavioral control, and green availability) while two antecedents have positive and significant direct relationship with perceived behavioral control (perceived value and green price sensitivity). On the other hand, PBC does not mediate any of the paths from the predictors to criterion variable. This result is discussed in the Nigerian context.

Keywords: Green Availability, Green Price Sensitivity, Green Purchase Intention, Perceived Green Knowledge, Perceived Value

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Authors: Angel Adams

Abstract:

In Australia, the contemporary social construction of hatred against the Islamic community was facilitated through the mainstream media. Australian public figures who have depicted Muslims and Islam not only as potential terrorists but also as incompatible with the country’s values and identities have helped to increase the level of fear against the Islamic community, leading sympathetic far-right movements to shift discussions towards anti-Islamic and anti-Muslim rhetoric. Political opportunities combined with a socially constructed narrative of fear of the ‘other’, introduced during the White Australia Policy of 1901, has allowed extreme and radical far-right movements to justify hate against the contemporary Australian Islamic community. This study aims to answer the following question: How does Australia’s founding provide a fertile environment to the spread of hatred against the contemporary Islamic community? The paper demonstrates that a forged social construct of grievances concerning the Islamic community in Australia has led to a surge in supply of far-right activism to combat what has become a perceived ‘national threat’. In essence, Australia’s history of a fear of the ‘other’ brings challenges to a multicultural society, and can potentially lead to a more unstable socio-political environment where abuse and violence are normalized and more likely to develop. Furthermore, the paper aims to bring a more nuanced understanding of what is considered ‘new far-right’ discourses with shared anti-Islam and anti-Muslim agendas in Australia. The political opportunity structures theory was the mechanism used to determine how new forms of far-right groups have become more mainstream in Australia. Previous studies on far-right groups in Australia have relied on qualitative data, but further empirical research in this area is sorely needed. Above all, this paper clarifies how hatred against minorities can have a negative impact on wider communities and allow a global narrative of ‘us’ versus ‘them’ to erupt from the fringes of society in Australia.

Keywords: Australia, Islamophobia, far-right, nationalism, political opportunity structures, political violence, social construction

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Authors: Mathias U. Bonet, Pericles Pilidis, Georgios Doulgeris

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A gas turbine-powered cruise Liner is scheduled to transport pilgrim passengers from Lagos-Nigeria to the Islamic port city of Jeddah in Saudi Arabia. Since the gas turbine is an air breathing machine, changes in the density and/or mass flow at the compressor inlet due to an encounter with variations in weather conditions induce negative effects on the performance of the power plant during the voyage. In practice, all deviations from the reference atmospheric conditions of 15 ^oC and 1.103 bar tend to affect the power output and other thermodynamic parameters of the gas turbine cycle. Therefore, this paper seeks to evaluate how a simple cycle marine gas turbine power plant would react under a variety of scenarios that may be encountered during a voyage as the ship sails across the Atlantic Ocean and the Mediterranean Sea before arriving at its designated port of discharge. It is also an assessment that focuses on the effect of varying aerodynamic and hydrodynamic conditions which deteriorate the efficient operation of the propulsion system due to an increase in resistance that results from some projected levels of the ship hull fouling. The investigated passenger ship is designed to run at a service speed of 22 knots and cover a distance of 5787 nautical miles. The performance evaluation consists of three separate voyages that cover a variety of weather conditions in winter, spring and summer seasons. Real-time daily temperatures and the sea states for the selected transit route were obtained and used to simulate the voyage under the aforementioned operating conditions. Changes in engine firing temperature, power output as well as the total fuel consumed per voyage including other performance variables were separately predicted under both calm and adverse weather conditions. The collated data were obtained online from the UK Meteorological Office as well as the UK Hydrographic Office websites, while adopting the Beaufort scale for determining the magnitude of sea waves resulting from rough weather situations. The simulation of the gas turbine performance and voyage analysis was effected through the use of an integrated Cranfield-University-developed computer code known as ‘Turbomatch’ and ‘Poseidon’. It is a project that is aimed at developing a method for predicting the off design behavior of the marine gas turbine when installed and operated as the main prime mover for both propulsion and powering of all other auxiliary services onboard a passenger cruise liner. Furthermore, it is a techno-economic and environmental assessment that seeks to enable the forecast of the marine gas turbine part and full load performance as it relates to the fuel requirement for a complete voyage.

Keywords: cruise ship, gas turbine, hull fouling, performance, propulsion, weather

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Authors: Jared Beard, Ali Baheri

Abstract:

As autonomous systems become more prominent in society, ensuring their safe application becomes increasingly important. This is clearly demonstrated with autonomous cars traveling through a crowded city or robots traversing a warehouse with heavy equipment. Human environments can be complex, having high dimensional state and action spaces. This gives rise to two problems. One being that analytic solutions may not be possible. The other is that in simulation based approaches, searching the entirety of the problem space could be computationally intractable, ruling out formal methods. To overcome this, approximate solutions may seek to find failures or estimate their likelihood of occurrence. One such approach is adaptive stress testing (AST) which uses reinforcement learning to induce failures in the system. The premise of which is that a learned model can be used to help find new failure scenarios, making better use of simulations. In spite of these failures AST fails to find particularly sparse failures and can be inclined to find similar solutions to those found previously. To help overcome this, multi-fidelity learning can be used to alleviate this overuse of information. That is, information in lower fidelity can simulations can be used to build up samples less expensively, and more effectively cover the solution space to find a broader set of failures. Recent work in multi-fidelity learning has passed information bidirectionally using “knows what it knows” (KWIK) reinforcement learners to minimize the number of samples in high fidelity simulators (thereby reducing computation time and load). The contribution of this work, then, is development of the bidirectional multi-fidelity AST framework. Such an algorithm, uses multi-fidelity KWIK learners in an adversarial context to find failure modes. Thus far, a KWIK learner has been used to train an adversary in a grid world to prevent an agent from reaching its goal; thus demonstrating the utility of KWIK learners in an AST framework. The next step is implementation of the bidirectional multi-fidelity AST framework described. Testing will be conducted in a grid world containing an agent attempting to reach a goal position and adversary tasked with intercepting the agent as demonstrated previously. Fidelities will be modified by adjusting the size of a time-step, with higher-fidelity effectively allowing for more responsive closed loop feedback. Results will compare the single KWIK AST learner with the multi-fidelity algorithm with respect to number of samples, distinct failure modes found, and relative effect of learning after a number of trials.

Keywords: multi-fidelity reinforcement learning, multi-fidelity simulation, safety validation, falsification

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