Search results for: parallel manipulator

Authors: Liliana M. Marinelli, Cristina T. Varanese

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In the last few years, students from higher education have difficulties in grasping mathematical concepts which support physical matters, especially those in the first years of this education. Classical Physics teaching turns to be complex when students are not able to make use of mathematical tools which lead to the conceptual structure of Physics. When derivation and integration rules are not used or developed in parallel with other disciplines, the physical meaning that we attempt to convey turns to be complicated. Due to this fact, it could be of great use to see the Classical Mechanics from an axiomatic approach, where the correspondence rules give physical meaning, if we expect students to understand concepts clearly and accurately. Using the Minkowski point of view adapted to a two-dimensional space and time where vectors, matrices, and straight lines (worked from an affine space) give mathematical and physical rigorosity even when it is more abstract. An interesting option would be to develop the disciplinary contents from an axiomatic version which embraces the Classical Mechanics as a particular case of Relativistic Mechanics. The observation about the increase in the difficulties stated by students in the first years of education allows this idea to grow as a possible option to improve performance and understanding of the concepts of this subject.

Keywords: axioms, classical physics, physical concepts, relativity

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Authors: M. A. At-Tasneem, N. T. Rao, T. M. Y. S. Tuan Ya, M. S. Idris, M. Ammar

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River flow over micro hydro power (MHP) turbines of multiple arrays arrangement is simulated with computational fluid dynamics (CFD) software to obtain the flow characteristics. In this paper, CFD software is used to simulate the water flow over MHP turbines as they are placed in a river. Multiple arrays arrangement of MHP turbines lead to generate large amount of power. In this study, a river model is created and simulated in CFD software to obtain the water flow characteristic. The process then continued by simulating different types of arrays arrangement in the river model. A MHP turbine model consists of a turbine outer body and static propeller blade in it. Five types of arrangements are used which are parallel, series, triangular, square and rhombus with different spacing sizes. The velocity profiles on each MHP turbines are identified at the mouth of each turbine bodies. This study is required to obtain the arrangement with increasing spacing sizes that can produce highest power density through the water flow variation.

Keywords: micro hydro power, CFD, arrays arrangement, spacing sizes, velocity profile, power

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Authors: S. Rashidi, L. C. Abdullah, R. Walvekar, K. Mohammad, F-R. Ahmadun, M. Y. Faizah

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In this research, stability and rheology behavior of Multi-walled carbon nanotube (MWCNT) nanofluids by using Xanthan Gum as a dispersant were measured. This paper addresses the effects of Xanthan Gum (XG) concentration and nanoparticle loading on stability and viscosity of nanofluids. The stability of nanofluids is measured by Zeta Sizer Nano-ZS (Malvern Instruments, ZEN 3600). The zeta potential of the stable samples was analyzed. The rheological behavior of carbon nanotube CNT nanofluids was analyzed using rheometer (Model AR G2, TA Instrument). Both stability and viscosity of the nanofluids increased with increasing CNT and XG concentration. The experimental results indicated that the zeta potential of nanofluid samples is stable. The results demonstrated that the zeta potential was affected by the CNT concentration and is augmented in parallel with increasing CNT concentration. The rheology results showed that the viscosity of CNT/XG nanofluid was increased. The escalated viscosity of CNT/XG nanofluid is owing to the higher van der Waals interaction between the CNT nanoparticles. On the other hand, the viscosity of the CNT/XG nanofluid decreases with increasing temperature. In summary, this research provides useful insight into the behavior of CNT nanofluids.

Keywords: nanofluid, carbon nanotube, stability, rheology

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Authors: Sita Yiemkuntitavorn

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The purposes of this research were to: (1) Develop a distance training package on the teaching principles foundation english language in order to gain the teaching ability for secondary school english teachers in Bangkok and its vicinity (2) study the satisfaction of English teachers towards the quality of a distance training package. The samples for the efficiency testing consisted of 30 english teachers in Bangkok and its vicinity, obtained by purposive sampling. Research tools comprised (1) a distance learning package on the foundation of English writing for teachers. (2) The questionnaires asking the teachers on the quality of the distance training package, and (3) two parallel forms of an achievement test for pre-testing and post-testing. Statistics used were the E1/E2 index, mean and standard deviation. Research findings showed that, (1) the distance training package were efficient at 80.2/80.6 according to the set efficiency criterion of 80/80; (2) and the satisfaction of the teachers on the distance training package of the teaching principles of foundation english for secondary school english teachers in Bangkok and its vicinity was at “Satisfied” level.

Keywords: a distance training package, teaching principles of foundation english, secondary school, Bangkok and its vicinity

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Authors: Naci Büyükkaracığan, Murat Ahmet Ökmen

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Emerging demand for energy in developing countries rapid population growth and industrialization are causing a rapid increase, such as Turkey. Energy is an important and indispensable factor in the industry. At the same time, energy is one of the main indicators that reflect a country's economic and social development potential. There is a linear relationship between the energy consumption and social development, and in parallel this situation, it is seen that energy consumption increase with economic growth and prosperity. In recent year’s, energy sources consumption is increasingly continuing, because of population growth and economy in Turkey. 80% of the energy used in Turkey is supplied from abroad. At the same time, while almost all of the energy obtained from our country is met by hydropower. Alternatively, studies of determining and using potential renewable energy sources such as solar energy have been realized for recent years. In this study, first of all, the situation of energy sources was examined in Turkey. Information of reserve/capacity, production and consumption values of energy sources were emphasized. For this purpose, energy production and consumption, CO2 emission and electricity energy consumption of countries were investigated. Energy consumption and electricity energy consumption per capita were comparatively analyzed.

Keywords: energy potential, alternative energy sources, solar energy, Turkey

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Authors: Agnieszka Misztal

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The popularity of the quality management system models continues to grow despite the transitional crisis in 2008. Their development is associated with the demands of the new requirements for entrepreneurs, such as risk analysis projects and more emphasis on supervision of outsourced processes. In parallel appropriate to focus attention on the selection of companies aspiring to quality management system. This is particularly important in the automotive supplier industry, where requirements transferred to the levels in the supply chain should be clear, transparent and fairly satisfied. The author has carried out series of researches aimed at finding the factors that allow for the effective implementation of the quality management system in automotive companies. The research was focused on four groups of companies: 1) manufacturing (parts and assemblies for the purpose of sale or for vehicle manufacturers), 2) service (repair and maintenance of the car), 3) services for the transport of goods or people, 4) commercial (auto parts and vehicles). Identified determinants were divided in two types of criteria into: internal and external, as well as: hard and soft. The article presents hard - technical factors that automotive company must meet in order to achieve the goal of the quality management system implementation.

Keywords: automotive industry, quality management system, automotive technology, automotive company

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Authors: B. K. Yadav, A. Gandhi, A. K. Verma, T. S. Rao, A. Saraswat, E. R. Kumar, M. Sarkar, K. N. Vyas

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This paper deals with the conceptual design of Experimental Helium Cooling Loop (EHCL) for Indian Test Blanket Module (TBM) and its related thermal hydraulic experiments. Indian TBM team is developing Lead Lithium cooled Ceramic Breeder (IN-LLCB) TBM to be tested in ITER. The TBM box structure is cooled by high pressure (8 MPa) and high temperature (300-500C) helium gas. The first wall of TBM made of complex channel geometry having several parallel channels carrying helium gas for efficient heat extraction. Several mock-ups of these channels need to be tested before finalizing the TBM first wall design and fabrication. Besides the individual testing of such mock-ups of breeding blanket, the testing of Pb-Li to helium heat exchanger, the operational experience of helium loop and understanding of the behaviour of high pressure and high temperature system components are very essential for final development of Helium Cooling System for LLCB TBM in ITER. The main requirements and characteristics of the EHCL and its conceptual design are presented in this paper.

Keywords: DEMO, EHCL, ITER, LLCB TBM

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Authors: Liwen Hou

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The booming mobile business has been penetrating the taxi industry worldwide with P2P (peer to peer) taxi services, as an emerging business model, transforming the industry. Parallel with other mobile businesses, member recommendations and online reviews are believed to be very effective with regard to acquiring new users for P2P taxi services. Based on an empirical dataset of the taxi industry in China, this study aims to reveal which factors influence users’ recommendations and review-writing behaviors. Differing from the existing literature, this paper takes the taxi driver’s perspective into consideration and hence selects a group of variables related to the drivers. We built two models to reflect the factors that influence the number of recommendations and reviews posted on the platform (i.e., the app). Our models show that all factors, except the driver’s score, significantly influence the recommendation behavior. Likewise, only one factor, passengers’ bad reviews, is insignificant in generating more drivers’ reviews. In the conclusion, we summarize the findings and limitations of the research.

Keywords: online recommendation, P2P taxi service, review-writing, word of mouth

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Authors: Lea Lenhardt, Ivana Zeković, Tatjana Dramićanin, Miroslav D. Dramićanin

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Rapid and sensitive analytical technologies for food analysis are needed to respond to the growing public interest in food quality and safety. In this context, fluorescence spectroscopy offers several inherent advantages for the characterization of food products: high sensitivity, low price, objective, relatively fast and non-destructive. The objective of this work was to investigate the potential of fluorescence spectroscopy coupled with multi-way technique for characterization of cereal flours. Fluorescence landscape also known as excitation-emission matrix (EEM) spectroscopy utilizes multiple-color illumination, with the full fluorescence spectrum recorded for each excitation wavelength. EEM was measured on various types of cereal flours (wheat, oat, barley, rye, corn, buckwheat and rice). Obtained spectra were analyzed using PARAllel FACtor analysis (PARAFAC) in order to decompose the spectra and identify underlying fluorescent components. Results of the analysis indicated the presence of four fluorophores in cereal flours. It has been observed that relative concentration of fluorophores varies between different groups of flours. Based on these findings we can conclude that application of PARAFAC analysis on fluorescence data is a good foundation for further qualitative analysis of cereal flours.

Keywords: cereals, fluors, fluorescence, PARAFAC

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Authors: Hyun-Ho Lee, Kee-Won Kim

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The arithmetic operations over GF(2m) have been extensively used in error correcting codes and public-key cryptography schemes. Finite field arithmetic includes addition, multiplication, division and inversion operations. Addition is very simple and can be implemented with an extremely simple circuit. The other operations are much more complex. The multiplication is the most important for cryptosystems, such as the elliptic curve cryptosystem, since computing exponentiation, division, and computing multiplicative inverse can be performed by computing multiplication iteratively. In this paper, we present a parallel computation algorithm that operates Montgomery multiplication over finite field using redundant basis. Also, based on the multiplication algorithm, we present an efficient semi-systolic multiplier over finite field. The multiplier has less space and time complexities compared to related multipliers. As compared to the corresponding existing structures, the multiplier saves at least 5% area, 50% time, and 53% area-time (AT) complexity. Accordingly, it is well suited for VLSI implementation and can be easily applied as a basic component for computing complex operations over finite field, such as inversion and division operation.

Keywords: finite field, Montgomery multiplication, systolic array, cryptography

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Authors: Hooshmand Kalayeh

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The human brain consists of reptilian, mammalian, and thinking brain. And mind consists of conscious, subconscious, and unconscious parallel neural-net programs. The primary objective of this paper is to propose a methodology for quantitative analysis of neural-nets associated with these mental activities in the neocortex. The secondary objective of this paper is to suggest a methodology for quantitative analysis of presence; the proposed methodologies can be used as a first-step to measure, monitor, and understand consciousness and presence. This methodology is based on Neural-Networks (NN), number of neuron in each NN associated with consciousness, subconsciouness, and unconsciousness, and number of neurons in neocortex. It is assumed that the number of neurons in each NN is correlated with the associated area and volume. Therefore, online and offline visualization techniques can be used to identify these neural-networks, and online and offline measurement methods can be used to measure areas and volumes associated with these NNs. So, instead of the number of neurons in each NN, the associated area or volume also can be used in the proposed methodology. This quantitative analysis and associated online and offline measurements and visualizations of different Neural-Networks enable us to rewire the connections in our brain for a more balanced living.

Keywords: brain, mind, consciousness, presence, sub-consciousness, unconsciousness, skills, concentrations, attention

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Authors: Seyyed Feisal Asbaghian Namin, Reza Pilafkan, Mahmood Kaffash Irzarahimi

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TThis paper considers vibration of single-layered graphene sheets using molecular dynamics (MD) and nonlocal elasticity theory. Based on the MD simulations, Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), an open source software, is used to obtain fundamental frequencies. On the other hand, governing equations are derived using nonlocal elasticity and first order shear deformation theory (FSDT) and solved using generalized differential quadrature method (GDQ). The small-scale effect is applied in governing equations of motion by nonlocal parameter. The effect of different side lengths, boundary conditions and nonlocal parameter are inspected for aforementioned methods. Results are obtained from MD simulations is compared with those of the nonlocal elasticity theory to calculate appropriate values for the nonlocal parameter. The nonlocal parameter value is suggested for graphene sheets with various boundary conditions. Furthermore, it is shown that the nonlocal elasticity approach using classical plate theory (CLPT) assumptions overestimates the natural frequencies.

Keywords: graphene sheets, molecular dynamics simulations, fundamental frequencies, nonlocal elasticity theory, nonlocal parameter

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Authors: Mohammed Berka, Khaled Merit

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Recent works on microwave filters show that the constituent materials such filters are very important in the design and realization. Several solutions have been proposed to improve the qualities of filtering. In this paper, we propose a new dual band-pass filter based on the coupling of a composite (CRLH) coplanar waveguide with complementary split ring resonators (CSRRs). The (CRLH) CPW is composed of two resonators, each one has an interdigital capacitor (CID) and two short-circuited stubs parallel to top ground plane. On the lower ground plane, we use defected ground structure technology (DGS) to engrave two (CSRRs) offered with different shapes and dimensions. Between the top ground plane and the substrate, we place a ferrite layer to control the electromagnetic coupling between (CRLH) CPW and (CSRRs). The global filter that has coplanar access will have a dual band-pass behavior around the magnetic resonances of (CSRRs). Since there’s no scientific or experimental result in the literature for this kind of complicated structure, it was necessary to perform simulation using HFSS Ansoft designer.

Keywords: complementary split ring resonators, coplanar waveguide, ferrite, filter, stub.

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Authors: Carolina Silva, João Nuno Oliveira, Rui Sousa, João Paulo Silva

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This study uses genetic algorithms to solve a job scheduling problem in a weaving factory. The underline problem regards an NP-Hard problem concerning unrelated parallel machines, with sequence-dependent setup times. This research uses real data regarding a weaving industry located in the North of Portugal, with a capacity of 96 looms and a production, on average, of 440000 meters of fabric per month. Besides, this study includes a high level of complexity once most of the real production constraints are applied, and several real data instances are tested. Topics such as data analyses and algorithm performance are addressed and tested, to offer a solution that can generate reliable and due date results. All the approaches will be tested in the operational environment, and the KPIs monitored, to understand the solution's impact on the production, with a particular focus on the total number of weeks of late deliveries to clients. Thus, the main goal of this research is to develop a solution that allows for the production of automatically optimized production plans, aiming to the tardiness minimizing.

Keywords: genetic algorithms, textile industry, job scheduling, optimization

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Authors: Tadesse Abera

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This study aimed to investigate the contribution of self-advocacy and engagement in the inclusion of SWDs in HEIs. A convergent parallel mixed methods design was employed. This article reports the quantitative strand. A total of 246 SWDs were selected through stratified proportionate random sampling technique from five public HEIs in Ethiopia. Data were collected through Self-advocacy questionnaire, student engagement scale, and college student experience questionnaire and analyzed through frequency, percentage, mean, standard deviation, correlation, one sample t-test and multiple regression. Both self-advocacy and engagement were found to have a predictive power on inclusion of respondents in the HEIs, where engagement was found to be more predictor. From the components of self-advocacy, knowledge of self and leadership and from engagement dimensions sense of belonging, cognitive, and valuing in their respective orders were found to have a stronger predictive power on the inclusion of respondents in the institutions. Based on the findings it was concluded that, if students with disabilities work hard to be self-determined, strive for realizing social justice, exert quality effort and seek active involvement, their inclusion in the institutions would be ensured.

Keywords: self-advocacy, engagement, inclusion, students with disabilities, higher education institution

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Authors: Si Mon Kueh, Tom J. Kazmierski

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There are about 1% of the world population suffering from the hidden disability known as epilepsy and major developing countries are not fully equipped to counter this problem. In order to reduce the inconvenience and danger of epilepsy, different methods have been researched by using a artificial neural network (ANN) classification to distinguish epileptic waveforms from normal brain waveforms. This paper outlines the aim of achieving massive ANN parallelization through a dedicated hardware using bit-serial processing. The design of this bit-serial Neural Processing Element (NPE) is presented which implements the functionality of a complete neuron using variable accuracy. The proposed design has been tested taking into consideration non-idealities of a hardware ANN. The NPE consists of a bit-serial multiplier which uses only 16 logic elements on an Altera Cyclone IV FPGA and a bit-serial ALU as well as a look-up table. Arrays of NPEs can be driven by a single controller which executes the neural processing algorithm. In conclusion, the proposed compact NPE design allows the construction of complex hardware ANNs that can be implemented in a portable equipment that suits the needs of a single epileptic patient in his or her daily activities to predict the occurrences of impending tonic conic seizures.

Keywords: Artificial Neural Networks (ANN), bit-serial neural processor, FPGA, Neural Processing Element (NPE)

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Authors: Randy Price, Harbir Antil, Rainald Löhner, Fumiya Togashi

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Chemically reacting flows are common in engineering applications such as hypersonic flow, combustion, explosions, manufacturing process, and environmental assessments. The number of reactions in combustion simulations can exceed 100, making a large number of flow and combustion problems beyond the capabilities of current supercomputers. Motivated by this, deep neural networks (DNNs) will be introduced with the goal of eventually replacing the existing chemistry software packages with DNNs. The DNNs used in this paper are motivated by the Residual Neural Network (ResNet) architecture. In the continuum limit, ResNets become an optimization problem constrained by an ODE. Such a feature allows the use of ODE control techniques to enhance the DNNs. In this work, DNNs are constructed, which update the species un at the nᵗʰ timestep to uⁿ⁺¹ at the n+1ᵗʰ timestep. Parallel DNNs are trained for each species, taking in uⁿ as input and outputting one component of uⁿ⁺¹. These DNNs are applied to multiple species and reactions common in chemically reacting flows such as H₂-O₂ reactions. Experimental results show that the DNNs are able to accurately replicate the dynamics in various situations and in the presence of errors.

Keywords: chemical reacting flows, computational fluid dynamics, ODEs, residual neural networks, ResNets

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Authors: Amina Smai, Fairouz Haddadj, Habiba Saadi-Idouhar, Meriem Aissi, Safia Zenia, Salaheddine Doumandji

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Coccidiosis is a very common intestinal parasitic disease caused by a worldwide distributed protozoan of the genus Eimeria. This disease is very common in young birds beyond the second week of life, especially in land-based breeding. The study was carried out in a hunting center of Zeralda located in the north-east of Algiers. The objective of our work is to study the evolution of coccidiosis in quails from 1 to 35 days old by collecting their droppings daily. These are analyzed in the laboratory using the flotation method and the Mac Master one to count coccidia. Weight changes are taken into account as well as mortality in parallel with certain zootechnical parameters such as density. The species of coccidia recovered is Eimeria coturnicis. The results showed that there is an average evolution of mortality of individuals with a rate of 13.33% due to the presence of coccidia with a significant regression (p=0.031). The weight of the quails increases with the age of the animal with a rapid growth rate from the 3rd week onwards. Indeed, the statistical analysis reveals that the evolution of the number did not affect the evolution of the weight (p=0.70) and the GMQ (R=0.52).

Keywords: coccidiosis, Coturnix japonica, daily average gain, weight

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Authors: Sara Zatir, Kouide Brahimi, Amira Zatir

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The planning and the environment have long evolved at the same two parallel tracks. But today, we can design a layout without addressing its environmental impact on the landscape. And the role of The documents of the regulatory planning is to control the urbanization of a common and its effects indirectly on the urban environment, but what about the urban landscape? Algeria is like many countries in the world leans primarily on developing sustainable economy, it was officially declared in the Maghreb countries, with the enactment of Law No. 01-20 of 12 December 2001 on the organization and sustainable development of the territory, one of the purposes of this law is the protection, mapping values and rational use of, natural resources, heritage and the natural preservation for future generations. However, Algeria initiatives have recently been undertaken but it still have some infancy which can be detected by the cavity between the delineation instruments,regulations and. In this context, we should note the important role of public authorities in the situation of the living and its future. The idea is to find a balance from the unbalanced conditions (between present and future generations, between economic needs, and the needs of environmental protection and cultural, between individual and collective interests) and to develop new strategies management laws and the urban landscape.

Keywords: Algeria, sustainable, development urban landscapes, laws

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Authors: Jairo A. Muñoz, Alexander Komissarov, Alexander Gromov

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In this investigation, a hypoeutectic AlSi11Cu alloy was printed. This alloy was obtained in powder form with an average particle size of 40 µm. Bars 20 mm in diameter and 100 mm in length were printed with the building direction parallel to the bars' longitudinal direction. The microstructural characterization demonstrated an Al matrix surrounded by a Si network forming a coral-like pattern. The microstructure of the alloy showed a heterogeneous behavior with a mixture of columnar and equiaxed grains. Likewise, the texture indicated that the columnar grains were preferentially oriented towards the building direction, while the equiaxed followed a texture dominated by the cube component. On the other hand, the as-printed material strength showed higher values than those obtained in the same alloy using conventional processes such as casting. In addition, strength and ductility differences were found in the printed material, depending on the measurement direction. The highest values were obtained in the radial direction (565 MPa maximum strength and 4.8% elongation to failure). The lowest values corresponded to the transverse direction (508 MPa maximum strength and 3.2 elongation to failure), which corroborate the material anisotropy.

Keywords: additive manufacturing, aluminium alloy, melting pools, tensile test

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Authors: Umang Prajapati

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Elected prime minister of India Narendra Modi has very largely focused on improving ties with the neighbors since day one of his regime. This was the most significant initiative to focus on major Asian powers also emphasizing on the two decades old look east policy. The “neighborhood first policy” as termed by the media has been a corner stone in improving ties with the immediate neighbors of the country through several bilateral talks with the nations individually. However, the announcement of demonetisation policy in India, ceasing the usage of 500 and 1000 rupee notes has rattled countries like Nepal, Bangladesh, Bhutan, Sri Lanka and Myanmar who encourage Indian currency parallel to theirs. According to the ministry of commerce and industry (MCI), India’s total trade with neighboring countries stood at US$21.6 in the fiscal year 2015-16, India has good surplus trade surplus with its neighbors and has a strong interest in ensuring smooth trade flows. India might have this benefit, but yet this policy can create issues between India and neighboring countries. The demonetisation policy might benefit in the long run, but in the short run, this might create border issues. While there would be more countries affected by this policy, this paper will emphasize on the problems faced by the countries and the impact of demonetisation on all other neighboring countries.

Keywords: bilateral trades, demonetization, neighborhood policy, value of rupee

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Authors: Pooya Niksiar, Ali Ashrafizadeh, Mehrzad Shams, Amir Hossein Madani

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There are many computationally demanding applications in science and engineering which need efficient algorithms implemented on high performance computers. Recently, Graphics Processing Units (GPUs) have drawn much attention as compared to the traditional CPU-based hardware and have opened up new improvement venues in scientific computing. One particular application area is Computational Fluid Dynamics (CFD), in which mature CPU-based codes need to be converted to GPU-based algorithms to take advantage of this new technology. In this paper, numerical solutions of two classes of discrete fluid flow models via both CPU and GPU are discussed and compared. Test problems include an Eulerian model of a two-dimensional incompressible laminar flow case and a Lagrangian model of a two phase flow field. The CUDA programming standard is used to employ an NVIDIA GPU with 480 cores and a C++ serial code is run on a single core Intel quad-core CPU. Up to two orders of magnitude speed up is observed on GPU for a certain range of grid resolution or particle numbers. As expected, Lagrangian formulation is better suited for parallel computations on GPU although Eulerian formulation represents significant speed up too.

Keywords: CFD, Eulerian formulation, graphics processing units, Lagrangian formulation

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Authors: Astha Sinha, Anjali Kanagali

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The United Kingdom’s withdrawal from the European Union, also termed as “Brexit,” took place on June 23, 2016 and immediately had global repercussions on the stock markets of the world. It is however expected to have a greater impact on the Banking sector in the UK. There is a two-fold effect on the earnings of banks which is being expected. First is of the trading activity and investment banking businesses being hit due to global weakness in financial markets. Second is that the banks having a large presence in the European Union will have to restructure their operations in order to cover other European countries as well increase their operating costs. As per the analysis, banks are expected to face rate cuts, bad loans, and tight liquidity. The directives in the Brexit negotiations on the Markets in Financial Instruments Directive (MiFID) will be a major decision to be taken for the Banking sector. New regulations will be required since most of the regulations governing the financial services industry allowing for the cross-border transactions were at the EU level. This paper aims to analyze the effect of Brexit on the UK Banking sector and changes in regulations that are expected due to the same. It shall also lay down the lessons learnt from the 2008 financial crisis and draw a parallel in terms of potential areas to be focused on for revival of the financial sector of Britain.

Keywords: Brexit, Brexit impact on UK, impact of Brexit on banking, impact of Brexit on financial services

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Authors: Ghania Zerari, Abderrezak Guessoum, Rachid Beguenane

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This paper introduces high-performance architecture for fully parallel stochastic Low-Density Parity-Check (LDPC) field programmable gate array (FPGA) based LDPC decoder. The new approach is designed to decrease the decoding latency and to reduce the FPGA logic utilisation. To accomplish the target logic utilisation reduction, the routing of the proposed sub-variable node (VN) internal memory is designed to utilize one slice distributed RAM. Furthermore, a VN initialization, using the channel input probability, is achieved to enhance the decoder convergence, without extra resources and without integrating the output saturated-counters. The Xilinx FPGA implementation, of IEEE 802.3an standard LDPC code, shows that the proposed decoding approach attain high performance along with reduction of FPGA logic utilisation.

Keywords: low-density parity-check (LDPC) decoder, stochastic decoding, field programmable gate array (FPGA), IEEE 802.3an standard

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Authors: Víctor Martínez del Rey, Kourosh Nasr Esfahani, Amir Masoud Samani Majd

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In this experimental study, the behaviors of Mixed Oxidant solution components (MOS) and sodium hypochlorite (HYPO) as the most commonly applied surface disinfectant were compared through the effectiveness of chlorine disinfection as a function of the contact time and residual chlorine. In this regard, the variation of pH, free available chlorine (FAC) concentration, and electric conductivity (EC) of disinfection solutions in different concentrations were monitored over 48 h contact time. In parallel, the plant stress activated by chlorine-based disinfectants was assessed by comparing MOS and HYPO. The elements of pH and EC in the plant-soil and their environmental impacts, spread by disinfection solutions were analyzed through several concentrations of FAC including 500 mg/L, 1000 mg/L, and 5000 mg/L in irrigated water. All the experiments were carried out at the service station of Sant Cugat, Spain. The outcomes indicated lower pH and higher durability of MOS than HYPO at the same concentration of FAC which resulted in promising stability of FAC within MOS. Furthermore, the pH and EC value of plant-soil irrigated by NaOCl solution were higher than that of MOS solution at the same FAC concentration. On-site generation of MOS as a safe chlorination option might be considered an imaginary future of smart cities.

Keywords: disinfection, free available chlorine, on-site generation, sodium hypochlorite

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Authors: Omer Cahana, Ofer Levi, Maya Herman

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

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Authors: Stefan K. Behfar

Abstract:

The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, Bayesian, echocardiographic image, feature vector

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Authors: Omer Cahana, Maya Herman, Ofer Levi

Abstract:

Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach, such as compress sensing (CS) or parallel imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

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Authors: Benalia Kouini, Aicha Serier

Abstract:

This work aims to investigate the structure–property relationship in ternary nanocomposites consisting of polypropylene as the matrix, polyamide 66 as the minor phase and treated nanoclay DELLITE 67G as the reinforcement. All PP/PA66/Nanoclay systems with polypropylene grafted maleic anhydride PP-g-MAH as a compatibilizer were prepared via melt compounding and characterized in terms of nanoclay content. Morphological structure was investigated by scanning electron microscopy. The rheological behavior of the nanocomposites was determined by various methods, viz melt flow index (MFI) and parallel plate rheological measurements. The PP/PP-g-MAH/PA66 nanocomposites showed a homogeneous morphology supporting the compatibility improvement between PP, PA66 and nanoclay. SEM results revealed the formation of nanocomposites as the nanoclay was intercalated and exfoliated. In the ternary nanocomposites, the rheological behavior showed that, the complex viscosity is increased with increasing the nanoclay content; however, at low frequencies this increase is governed by the content of nanofiller while at high frequencies it is mainly determined by talc content. A similar trend was also observed for the variations of storage modulus (G′) and loss modulus (G″) with frequency. The results showed that the use of nanoclay considerably affects the melt elasticity.

Keywords: nanocomposites, polypropylene, polyamide66, modified nanoclay, rheology

Procedia PDF Downloads 362