Search results for: maximum distance separable (MDS) matrix

Authors: Wu Wei-Ting, Liu Po-Yen, Chang Chin-Tzu, Cheng Wei-Chun

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Three types of low-temperature phase transformations in an Fe-12.5 Mn-6.53 Al-1.28 C (wt %) alloy have been studied. The steel underwent solution heat treatment at 1100℃ and isothermal holding at low temperatures. γ’ phase appears in the austenite matrix in the air-cooled steel. Coherent ultra-fine particles of γ’ phase precipitated uniformly in the austenite matrix after the air-cooling process. These ultra-fine particles were very small and only could be detected by TEM through dark-field images. After short periods of isothermal holding at low temperatures these particles of γ’ phase grew and could be easily detected by TEM. A pro-eutectoid reaction happened after isothermal holding at temperatures below 875 ℃. Proeutectoid κ-carbide and ferrite appear in the austenite matrix as grain boundary precipitates and cellular precipitates. The cellular precipitates are composed of lamellar κ-carbide and austenite. The lamellar κ-carbide grains are always accompanied by layers of austenite twins. The presence of twin layers adhering to the κ-carbide plates might be attributed to the lower activation energy for the precipitation of κ-carbide plates in the austenite. The final form of phase transformation is the eutectoid reaction for the decomposition of supersaturated austenite into stable κ-carbide and ferrite phases at temperatures below 700℃. The ferrite and κ-carbide are in the form of pearlite lamellae.

Keywords: austenite, austenite twin layers, κ-carbide, twins

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Authors: M. Abdelmalek

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In this work, we study the hypersurfaces of constant weighted mean curvature embedded in weighted manifolds. We give a condition about these hypersurfaces to be minimal. This condition is given by the ellipticity of the weighted Newton transformations. We especially prove that two compact hypersurfaces of constant weighted mean curvature embedded in space forms and with the intersection in at least a point of the boundary must be transverse. The method is based on the calculus of the matrix of the second fundamental form in a boundary point and then the matrix associated with the Newton transformations. By equality, we find the weighted elementary symmetric function on the boundary of the hypersurface. We give in the end some examples and applications. Especially in Euclidean space, we use the above result to prove the Alexandrov spherical caps conjecture for the weighted case.

Keywords: weighted mean curvature, weighted manifolds, ellipticity, Newton transformations

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Authors: Irina Khutsishvili

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In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations, since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.

Keywords: In the present research, a decision support methodology for the multi-attribute group decision-making (MAGDM) problem is developed, namely for the selection of investment projects. The objective of the investment project selection problem is to choose the best project among the set of projects, seeking investment, or to rank all projects in descending order. The project selection is made considering a set of weighted attributes. To evaluate the attributes in our approach, expert assessments are used. In the proposed methodology, lingual expressions (linguistic terms) given by all experts are used as initial attribute evaluations since they are the most natural and convenient representation of experts' evaluations. Then lingual evaluations are converted into trapezoidal fuzzy numbers, and the aggregate trapezoidal hesitant fuzzy decision matrix will be built. The case is considered when information on the attribute weights is completely unknown. The attribute weights are identified based on the De Luca and Termini information entropy concept, determined in the context of hesitant fuzzy sets. The decisions are made using the extended Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method under a hesitant fuzzy environment. Hence, a methodology is based on a trapezoidal valued hesitant fuzzy TOPSIS decision-making model with entropy weights. The ranking of alternatives is performed by the proximity of their distances to both the fuzzy positive-ideal solution (FPIS) and the fuzzy negative-ideal solution (FNIS). For this purpose, the weighted hesitant Hamming distance is used. An example of investment decision-making is shown that clearly explains the procedure of the proposed methodology.

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Authors: Jatindranath Gain, Madhumita DasSarkar, Sudakshina Kundu

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Quantum information is stored in states with multiple quasiparticles, which have a topological degeneracy. Topological quantum computation is concerned with two-dimensional many body systems that support excitations. Anyons are elementary building block of quantum computations. When anyons tunneling in a double-layer system can transition to an exotic non-Abelian state and produce Fibonacci anyons, which are powerful enough for universal topological quantum computation (TQC).Here the exotic behavior of Fibonacci Superlattice is studied by using analytical transfer matrix methods and hence Fibonacci anyons. This Fibonacci anyons can build a quantum computer which is very emerging and exciting field today’s in Nanophotonics and quantum computation.

Keywords: quantum computing, quasicrystals, Multiple Quantum wells (MQWs), transfer matrix method, fibonacci anyons, quantum hall effect, nanophotonics

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Authors: Arsalan Hassan Pour, Mansoureh Jeihani, Samira Ahangari

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Distracted driving has been one of the most integral concerns surrounding our daily use of vehicles since the invention of the automobile. While much attention has been recently given to cell phones related distraction, commercial billboards along roads are also candidates for drivers' visual and cognitive distractions, as they may take drivers’ eyes from the road and their minds off the driving task to see, perceive and think about the billboard’s content. Using a driving simulator and a head-mounted eye-tracking system, speed change, acceleration, deceleration, throttle response, collision, lane changing, and offset from the center of the lane data along with gaze fixation duration and frequency data were collected in this study. Some 92 participants from a fairly diverse sociodemographic background drove on a simulated freeway in Baltimore, Maryland area and were exposed to three different billboards to investigate the effects of billboards on drivers’ behavior. Participants glanced at the billboards several times with different frequencies, the maximum of which occurred on the billboard with the highest cognitive load. About 74% of the participants didn’t look at billboards for more than two seconds at each glance except for the billboard with a short visible area. Analysis of variance (ANOVA) was performed to find the variations in driving behavior when they are invisible, readable, and post billboards area. The results show a slight difference in speed, throttle, brake, steering velocity, and lane changing, among different areas. Brake force and deviation from the center of the lane increased in the readable area in comparison with the visible area, and speed increased right after each billboard. The results indicated that billboards have a significant effect on driving performance and visual attention based on their content and visibility status. Generalized linear model (GLM) analysis showed no connection between participants’ age and driving experience with gaze duration. However, the visible distance of the billboard, gender, and billboard content had a significant effect on gaze duration.

Keywords: ANOVA, billboards, distracted driving, drivers' behavior, driving simulator, eye-Tracking system, GLM

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Authors: Bharat Singh Om Prakash Vyas

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Now a day’s applications deal with High Dimensional Data have tremendously used in the popular areas. To tackle with such kind of data various approached has been developed by researchers in the last few decades. To tackle with such kind of data various approached has been developed by researchers in the last few decades. One of the problems with the NMF approaches, its randomized valued could not provide absolute optimization in limited iteration, but having local optimization. Due to this, we have proposed a new approach that considers the initial values of the decomposition to tackle the issues of computationally expensive. We have devised an algorithm for initializing the values of the decomposed matrix based on the PSO (Particle Swarm Optimization). Through the experimental result, we will show the proposed method converse very fast in comparison to other row rank approximation like simple NMF multiplicative, and ACLS techniques.

Keywords: ALS, NMF, high dimensional data, RMSE

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Authors: Duy Cuong Nguyen, Ali Makke, Guillaume Montay

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This work presents an improved single fiber pull-out test for fiber/matrix interface characterization. This test has been used to study the Inter-Facial Shear Strength ‘IFSS’ of hemp fibers reinforced polypropylene (PP). For this aim, the fiber diameter has been carefully measured using a tomography inspired method. The fiber section contour can then be approximated by a circle or a polygon. The results show that the IFSS is overestimated if the circular approximation is used. The Influence of the molding temperature on the IFSS has also been studied. We find a molding temperature of 183°C leads to better interface properties. Above or below this temperature the interface strength is reduced.

Keywords: composite, hemp, interface, pull-out, processing, polypropylene, temperature

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Authors: Aishwarya Ravichandra, Kirtana Kirtivasan, Adithi Mahesh, Ashwini S.Savanth

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A Non-Contact Digital Music System has been conceptualized and implemented to create a new era of digital music. This system replaces the strings of a traditional stringed instrument with laser beams to avoid bruising of the user’s hand. The system consists of seven laser modules, detector modules and distance sensors that form the basic hardware blocks of this instrument. Arduino ATmega2560 microcontroller is used as the primary interface between the hardware and the software. MIDI (Musical Instrument Digital Interface) is used as the protocol to establish communication between the instrument and the virtual synthesizer software.

Keywords: Arduino, detector, laser, MIDI, note on, note off, pitch bend, Sharp IR distance sensor

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Authors: Sadegh Torfi

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Realization of anticipated energy efficiency from recuperative run-around energy recovery (RER) systems requires identification of the system components influential parameters. Because simulation modeling is considered as an integral part of the design and economic evaluation of RER systems, it is essential to calibrate the developed models and validate the performance predictions by means of comparison with data from experimental measurements. Several theoretical and numerical analyses on RER systems by researchers have been done, but generally the effect of distance between hot and cold flow is ignored. The objective of this study is to develop a thermohydroulic model for a typical RER system that accounts for energy loss from the interconnecting piping and effects of interconnecting pipes length performance of run-around energy recovery systems. Numerical simulation shows that energy loss from the interconnecting piping is change linear with pipes length and if pipes are properly isolated, maximum reduction of effectiveness of RER systems is 2% in typical piping systems.

Keywords: combined heat and power, heat recovery, effectiveness, CGS

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Authors: Rabia Khan, Nargis Munir, Suriya Gharib, Syeda Roshana Ali

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In this paper linear equations are discussed in detail along with elimination method. Gaussian elimination and Gauss Jordan schemes are carried out to solve the linear system of equation. This paper comprises of matrix introduction, and the direct methods for linear equations. The goal of this research was to analyze different elimination techniques of linear equations and measure the performance of Gaussian elimination and Gauss Jordan method, in order to find their relative importance and advantage in the field of symbolic and numeric computation. The purpose of this research is to revise an introductory concept of linear equations, matrix theory and forms of Gaussian elimination through which the performance of Gauss Jordan and Gaussian elimination can be measured.

Keywords: direct, indirect, backward stage, forward stage

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Authors: Asteria Nsamba

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Social networking applications and tools have become compelling platforms for generating and sharing knowledge across the world. Social networking applications and tools refer to a variety of social media platforms which include Facebook, Twitter WhatsApp, blogs and Wikis. The most popular of these platforms are Facebook, with 2.41 billion active users on a monthly basis, followed by WhatsApp with 1.6 billion users and Twitter with 330 million users. These communication platforms have not only impacted social lives but have also impacted students’ learning, across different delivery modes in higher education: distance, conventional and blended learning modes. With this amount of interest in these platforms, knowledge sharing has gained importance within the context in which it is required. In open distance learning (ODL) contexts, social networking platforms can offer students and teachers the platform on which to create and share knowledge, and form learning collaborations. Thus, they can serve as support mechanisms to increase interactions and reduce isolation and loneliness inherent in ODL. Despite this potential and opportunity, research indicates that many ODL teachers are not inclined to using social media tools in learning. Although it is unclear why these tools are uncommon in these environments, concerns raised in the literature have indicated that many teachers have not mastered the art of teaching with technology. Using technological, pedagogical content knowledge (TPCK) and product quality theory, and Bloom’s Taxonomy as lenses, this paper is aimed at; firstly, assessing the quality of three social media applications: Facebook, Twitter and WhatsApp, in order to determine the extent to which they are suitable platforms for teaching and learning, in terms of content generation, information sharing and learning collaborations. Secondly, the paper demonstrates the application of teaching, learning and assessment using Bloom’s Taxonomy.

Keywords: distance education, quality, social networking tools, TPACK

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Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

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Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method

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Authors: William Sidharta, Chin-Tu Lu

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Fluorescent ultraviolet lamp generates ultraviolet light which is commonly used in industrial field with certain purposes especially for curing process. Due to the value of inefficiency, there are changes in energy from electrical energy to the heat energy and this would make a defect on the industrial product caused by high temperature of lamp tube during ultraviolet light emission. The condition of industrial scale is further worsening, since commonly using dozens of fluorescent ultraviolet lamps to support huge production process and then it will generates much more heat energy. The maximum temperature of fluorescent ultraviolet lamp will get affected by arranging the lamp tube reflector and this study presents CFX simulation results of the maximum lamp tube temperature with some different reflector arrangements on purely natural convection phenomena. There exists certain spaces value of the reflector and the lamp tube to obtaining lower maximum temperature of the fluorescent ultraviolet lamp.

Keywords: CFX simulation, fluorescent UV lamp, lamp tube reflector, UV light

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Authors: Mohammad Reza Ebrahimi

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In new restructured power systems, swift fault detection is very important. The parallel transmission-lines are vastly used in this kind of power systems because of high amount of energy transferring. In this paper, a method based on the comparison of two schemes, i.e., i) maximum magnitude of travelling-wave (TW) energy ii) the instants of maximum energy occurrence at the circuits of parallel transmission-line is proposed. Using the travelling-wave of fault in order to faulted line identification this method has noticeable operation time. Moreover, the algorithm can cover for identification of faults as external or internal faults. For an internal fault, the exact location of the fault can be estimated confidently. A lot of simulations have been done with PSCAD/EMTDC to verify the performance of the proposed algorithm.

Keywords: travelling-wave, maximum energy, parallel transmission-line, fault location

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Authors: Camille Lacan, Pierre Desmet

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In the crowdfunding model, a campaign succeeds by collecting the funds required over a predefined duration. The success of a CF campaign depends both on the capacity to attract members of the online communities concerned, and on the community members’ involvement in online word-of-mouth recommendations. To maximize the campaign's success probability, project creators (i.e., an organization appealing for financial resources) send messages to contributors to ask them to issue word of mouth. Internet users relay information about projects through Word of Mouth which is defined as “a critical tool for facilitating information diffusion throughout online communities”. The effectiveness of these messages depends on the message framing and the time at which they are sent to contributors (i.e., at the start of the campaign or close to the deadline). This article addresses the following question: What are the effect of message framing and temporal distance on the willingness to share word of mouth? Drawing on Perspectives Theory and Construal Level Theory, this study examines the interplay between message framing (Gains vs. Losses) and temporal distance (message while the deadline is coming vs. far) on intention to share word of mouth. A between-subject experimental design is conducted to test the research model. Results show significant differences between a loss-framed message (lack of benefits if the campaign fails) associated with a short deadline (ending tomorrow) compared to a gain-framed message (benefits if the campaign succeeds) associated with a distant deadline (ending in three months). However, this effect is moderated by the anticipated regret of a campaign failure and the temporal orientation. These moderating effects contribute to specifying the boundary condition of the framing effect. Handling the message framing and the temporal distance are thus the key decisions to influence the willingness to share word of mouth.

Keywords: construal levels, crowdfunding, message framing, word of mouth

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Authors: Patrick M. Stanton, William R. McCumber

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Using a large dataset of more than 2,400 individual microfinance institutions (MFIs) from 120 countries from 1999 to 2016, this study finds that nearly half of the international MFIs operate as for-profit institutions. Formal institutions (business regulatory environment, property rights, social protection, and a developed financial sector) impact the likelihood of MFIs being for-profit across countries. Cultural differences across countries (power distance, individualism, masculinity, and indulgence) seem to be a factor in the legal status of the MFI (non-profit or for-profit). MFIs in countries with stronger formal institutions, a greater degree of power distance, and a higher degree of collectivism experience better financial and social performance.

Keywords: Hofstede cultural dimensions, international finance, microfinance institutions, non-profite

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Authors: Oyegunle Oke, James Daramola, Oluwaseun Iyasere, Babatunde Modinat

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Wood shavings are the most common materials used as litter in commercial broiler production in many areas in Nigeria. A study was conducted to determine the effects of litter materials on organ weights, meat quality, footpad, and breast dermatitis of broiler chickens under hot humid climate. One hundred and eighty broiler chicks of marshal strains were randomly assigned to three treatments of wood shavings, maize cobs and chopped Panicum maximum as litter materials replicated four (4) times with 15 birds each in a completely randomized design. Data were collected on the relative body weights, meat quality, breast and foot pad dermatitis. The result showed that birds reared on chopped Panicum maximum had higher relative weight on the liver than those reared on wood shavings and maize cobs. Spleen and bursa of Fabricius were not significantly affected by litter materials. There was no significant effect of litter materials on meat quality. The relative weight of thigh of birds reared on chopped Panicum maximum, and Maize cobs were similar but higher than those reared on Wood shavings. Fresh breast weight of birds reared on wood shavings was higher than those reared on chopped Panicum maximum and maize cobs. It was concluded that chopped Panicum maximum could serve as a replacement for wood shavings as a litter material for broiler chickens.

Keywords: chickens, dermatitis, organs, litter materials

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Authors: Rashid Ahmed , John N. Avaritsiotis

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Many signal subspace-based approaches have already been proposed for determining the fixed Direction of Arrival (DOA) of plane waves impinging on an array of sensors. Two procedures for DOA estimation based neural networks are presented. First, Principal Component Analysis (PCA) is employed to extract the maximum eigenvalue and eigenvector from signal subspace to estimate DOA. Second, minor component analysis (MCA) is a statistical method of extracting the eigenvector associated with the smallest eigenvalue of the covariance matrix. In this paper, we will modify a Minor Component Analysis (MCA(R)) learning algorithm to enhance the convergence, where a convergence is essential for MCA algorithm towards practical applications. The learning rate parameter is also presented, which ensures fast convergence of the algorithm, because it has direct effect on the convergence of the weight vector and the error level is affected by this value. MCA is performed to determine the estimated DOA. Preliminary results will be furnished to illustrate the convergences results achieved.

Keywords: Direction of Arrival, neural networks, Principle Component Analysis, Minor Component Analysis

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Authors: Marzie Shahini, Rasoul Mirghaderi

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This paper describes collapse assessments of a steel moment-frame high-rise tower with setback irregularity, designed per the 2010 ASCE7 code, under spectral-matched ground motion records. To estimate a safety margin against life-threatening collapse, an analytical model of the tower is subjected to a suite of ground motions with incremental intensities from maximum considered earthquake hazard level to the incipient collapse level. Capability of the structural system to collapse prevention is evaluated based on the similar methodology reported in FEMA P695. Structural performance parameters in terms of maximum/mean inter-story drift ratios, residual drift ratios, and maximum plastic hinge rotations are also compared to the acceptance criteria recommended by the TBI Guidelines. The results demonstrate that the structural system satisfactorily safeguards the building against collapse. Moreover, for this tower, the code-specified requirements in ASCE7-10 are reasonably adequate to satisfy seismic performance criteria developed in the TBI Guidelines for the maximum considered earthquake hazard level.

Keywords: high-rise buildings, set back, residual drift, seismic performance

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Authors: Roham Rafiee, Behzad Mazhari

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Composite structures, having incredible properties, have gained considerable popularity in the last few decades. Among all types, polymer matrix composites are being used extensively due to their unique characteristics including low weight, convenient fabrication process and low cost. Having polymer as matrix, these type of composites show different creep behavior when compared to metals and even other types of composites since most polymers undergo creep even in room temperature. One of the most challenging topics in creep is to introduce new techniques for predicting long term creep behavior of materials. Depending on the material which is being studied the appropriate method would be different. Methods already proposed for predicting long term creep behavior of polymer matrix composites can be divided into five categories: (1) Analytical Modeling, (2) Empirical Modeling, (3) Superposition Based Modeling (Semi-empirical), (4) Rheological Modeling, (5) Finite Element Modeling. Each of these methods has individual characteristics. Studies have shown that none of the mentioned methods can predict long term creep behavior of all PMC composites in all circumstances (loading, temperature, etc.) but each of them has its own priority in different situations. The reason to this issue can be found in theoretical basis of these methods. In this study after a brief review over the background theory of each method, they are compared in terms of their applicability in predicting long-term behavior of composite structures. Finally, the explained materials are observed through some experimental studies executed by other researchers.

Keywords: creep, comparative study, modeling, composite materials

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Authors: Lamia L. G. Al-Mahamad, Benjamin R. Horrocks, Andrew Houlton

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Hydrogels based on metal coordination polymers of nucleosides and a range of metal ions (Au, Ag, Cu) have been prepared and characterized by atomic force microscopy (AFM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy, Fourier transform infrared spectroscopy, ultraviolet-visible absorption spectroscopy, and powder X-ray diffraction. AFM images of the xerogels revealed the formation of extremely long polymer molecules (> 10 micrometers, the maximum scan range). This result is also consistent with TEM images which show a fibrous morphology. Oxidative doping of the Au-nucleoside fibres produces an electrically conductive nanowire. No sharp Bragg peaks were found at the at the X-ray diffraction pattern for metal ions hydrogels indicating that the samples were amorphous, but instead the data showed broad peaks in the range 20 < Q < 40 and correspond to distances d=2μ/Q. The data was analysed using a simplified Rietveld method by fitting a regression model to obtain the distance between atoms.

Keywords: hydrogel, metal ions, nanowire, nucleoside

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Authors: Yoonjung An, Yongtae Park

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Offering a Product-Service System (PSS) is a well-accepted strategy that companies may adopt to provide a set of systemic solutions to customers. PSSs were initially provided in a simple form but now take diversified and complex forms involving multiple services, products and technologies. With the growing interest in the PSS, frameworks for the PSS development have been introduced by many researchers. However, most of the existing frameworks fail to examine various relations existing in a complex PSS. Since designing a complex PSS involves full integration of multiple products and services, it is essential to identify not only product-service relations but also product-product/ service-service relations. It is also equally important to specify how they are related for better understanding of the system. Moreover, as customers tend to view their purchase from a more holistic perspective, a PSS should be developed based on the whole system’s requirements, rather than focusing only on the product requirements or service requirements. Thus, we propose a framework to develop a complex PSS that is coordinated fully with the requirements of both worlds. Specifically, our approach adopts a multi-domain matrix (MDM). A MDM identifies not only inter-domain relations but also intra-domain relations so that it helps to design a PSS that includes highly desired and closely related core functions/ features. Also, various dependency types and rating schemes proposed in our approach would help the integration process.

Keywords: inter-domain relations, intra-domain relations, multi-domain matrix, product-service system design

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Authors: E. Batista, R. Mendes, A. Furtado, M. C. Ferreira, I. Godinho, J. A. Sousa, M. Alvares, R. Martins

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Syringe pumps are commonly used for drug delivery in hospitals and clinical environments. These instruments are critical in neonatology and oncology, where any variation in the flow rate and drug dosing quantity can lead to severe incidents and even death of the patient. Therefore it is very important to determine the accuracy and precision of these devices using the suitable calibration methods. The Volume Laboratory of the Portuguese Institute for Quality (LVC/IPQ) uses two different methods to calibrate syringe pumps from 16 nL/min up to 20 mL/min. The Interferometric method uses an interferometer to monitor the distance travelled by a pusher block of the syringe pump in order to determine the flow rate. Therefore, knowing the internal diameter of the syringe with very high precision, the travelled distance, and the time needed for that travelled distance, it was possible to calculate the flow rate of the fluid inside the syringe and its uncertainty. As an alternative to the gravimetric and the interferometric method, a methodology based on the application of optical technology was also developed to measure flow rates. Mainly this method relies on measuring the increase of volume of a drop over time. The objective of this work is to compare the results of the calibration of two syringe pumps using the different methodologies described above. The obtained results were consistent for the three methods used. The uncertainties values were very similar for all the three methods, being higher for the optical drop method due to setup limitations.

Keywords: calibration, flow, interferometry, syringe pump, uncertainty

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Authors: Carla Palencia-Aguilar

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In order to attain the 2050’s zero emissions goal, it is necessary to know the carbon dioxide changes over time either from pollution to attenuations in the mining industry versus at green zones to establish real goals and redirect efforts to reduce greenhouse effects. Two methods were used to compute the amount of CO2 tons in specific mining zones in Colombia. The former by means of NPP with MODIS MOD17A3HGF from years 2000 to 2021. The latter by using MODIS MYD021KM bands 33 to 36 with maximum values of 644 data points distributed in 7 sites corresponding to surface mineral mining of: coal, nickel, iron and limestone. The green zones selected were located at the proximities of the studied sites, but further than 1 km to avoid information overlapping. Year 2012 was selected for method 2 to compare the results with data provided by the Colombian government to determine range of values. Some data was compared with 2022 MODIS energy values and converted to kton of CO2 by using the Greenhouse Gas Equivalencies Calculator by EPA. The results showed that Nickel mining was the least pollutant with 81 kton of CO2 e.q on average and maximum of 102 kton of CO2 e.q. per year, with green zones attenuating carbon dioxide in 103 kton of CO2 on average and 125 kton maximum per year in the last 22 years. Following Nickel, there was Coal with average kton of CO2 per year of 152 and maximum of 188, values very similar to the subjacent green zones with average and maximum kton of CO2 of 157 and 190 respectively. Iron had similar results with respect to 3 Limestone sites with average values of 287 kton of CO2 for mining and 310 kton for green zones, and maximum values of 310 kton for iron mining and 356 kton for green zones. One of the limestone sites exceeded the other sites with an average value of 441 kton per year and maximum of 490 kton per year, eventhough it had higher attenuation by green zones than a close Limestore site (3.5 Km apart): 371 kton versus 281 kton on average and maximum 416 kton versus 323 kton, such vegetation contribution is not enough, meaning that manufacturing process should be improved for the most pollutant site. By comparing bands 33 to 36 for years 2012 and 2022 from January to August, it can be seen that on average the kton of CO2 were similar for mining sites and green zones; showing an average yearly balance of carbon dioxide emissions and attenuation. However, efforts on improving manufacturing process are needed to overcome the carbon dioxide effects specially during emissions’ peaks because surrounding vegetation cannot fully attenuate it.

Keywords: carbon dioxide, MODIS, surface mining, vegetation

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Authors: Kenichiro Hida, Shin-Ichi Kuribayashi

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NFV-based network implements a variety of network functions with software on general-purpose servers, and this allows the network operator to select any capabilities and locations of network functions without any physical constraints. In this paper, we evaluate the influence of the maximum tolerable network delay on the virtual routing function deployment guidelines which the authors proposed previously. Our evaluation results have revealed the following: (1) the more the maximum tolerable network delay condition becomes severe, the more the number of areas where the route selection function is installed increases and the total network cost increases, (2) the higher the routing function cost relative to the circuit bandwidth cost, the increase ratio of total network cost becomes larger according to the maximum tolerable network delay condition.

Keywords: NFV (Network Functions Virtualization), resource allocation, virtual routing function, minimum total network cost

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Authors: Aastha Paliwal, H. N. Chanakya, S. Dasappa

Abstract:

Lignocellulose, as an alternate feedstock for biogas production, has been an active area of research. However, lignocellulose poses a lot of operational difficulties- widespread variation in the structural organization of lignocellulosic matrix, amenability to degradation, low bulk density, to name a few. Amongst these, the low bulk density of the lignocellulosic feedstock is crucial to the process operation and optimization. Low bulk densities render the feedstock floating in conventional liquid/wet digesters. Low bulk densities also restrict the maximum achievable organic loading rate in the reactor, decreasing the power density of the reactor. However, during digestion, lignocellulose undergoes very high compaction (up to 26 times feeding density). This first reduces the achievable OLR (because of low feeding density) and compaction during digestion, then renders the reactor space underutilized and also imposes significant mass transfer limitations. The objective of this paper was to understand the effects of compacting lignocellulose on mass transfer and the influence of loss of different components on the bulk density and hence structural integrity of the digesting lignocellulosic feedstock. 10 different lignocellulosic feedstocks (monocots and dicots) were digested anaerobically in a fed-batch, leach bed reactor -solid-state stratified bed reactor (SSBR). Percolation rates of the recycled bio-digester liquid (BDL) were also measured during the reactor run period to understand the implication of compaction on mass transfer. After 95 ds, in a destructive sampling, lignocellulosic feedstocks digested at different SRT were investigated to quantitate the weekly changes in bulk density and lignocellulosic composition. Further, percolation rate data was also compared to bulk density data. Results from the study indicate loss of hemicellulose (r²=0.76), hot water extractives (r²=0.68), and oxalate extractives (r²=0.64) had dominant influence on changing the structural integrity of the studied lignocellulose during anaerobic digestion. Further, feeding bulk density of the lignocellulose can be maintained between 300-400kg/m³ to achieve higher OLR, and bulk density of 440-500kg/m³ incurs significant mass transfer limitation for high compacting beds of dicots.

Keywords: anaerobic digestion, bulk density, feed compaction, lignocellulose, lignocellulosic matrix, cellulose, hemicellulose, lignin, extractives, mass transfer

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Authors: Kevin De Castro Cogle, Mirian Kubo, Maria Anastasiadi, Fady Mohareb, Claire Rossi

Abstract:

Background: The bioaccessibility of bioactive compounds is a critical determinant of the nutritional quality of various food products. Despite its importance, there is a limited number of comprehensive studies aimed at assessing how the composition of a food matrix influences the bioaccessibility of a compound of interest. This knowledge gap has prompted a growing need to investigate the intricate relationship between food matrix formulations and the bioaccessibility of bioactive compounds. One such class of bioactive compounds that has attracted considerable attention is curcuminoids. These naturally occurring phytochemicals, extracted from the roots of Curcuma longa, have gained popularity owing to their purported health benefits and also well known for their poor bioaccessibility Project aim: The primary objective of this research project is to systematically assess the influence of matrix composition on the bioaccessibility of curcuminoids. Additionally, this study aimed to develop a series of predictive models for bioaccessibility, providing valuable insights for optimising the formula for functional foods and provide more descriptive nutritional information to potential consumers. Methods: Food formulations enriched with curcuminoids were subjected to in vitro digestion simulation, and their bioaccessibility was characterized with chromatographic and spectrophotometric techniques. The resulting data served as the foundation for the development of predictive models capable of estimating bioaccessibility based on specific physicochemical properties of the food matrices. Results: One striking finding of this study was the strong correlation observed between the concentration of macronutrients within the food formulations and the bioaccessibility of curcuminoids. In fact, macronutrient content emerged as a very informative explanatory variable of bioaccessibility and was used, alongside other variables, as predictors in a Bayesian hierarchical model that predicted curcuminoid bioaccessibility accurately (optimisation performance of 0.97 R2) for the majority of cross-validated test formulations (LOOCV of 0.92 R2). These preliminary results open the door to further exploration, enabling researchers to investigate a broader spectrum of food matrix types and additional properties that may influence bioaccessibility. Conclusions: This research sheds light on the intricate interplay between food matrix composition and the bioaccessibility of curcuminoids. This study lays a foundation for future investigations, offering a promising avenue for advancing our understanding of bioactive compound bioaccessibility and its implications for the food industry and informed consumer choices.

Keywords: bioactive bioaccessibility, food formulation, food matrix, machine learning, probabilistic modelling

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Authors: Sandrine Cardinal, Jean-Marc Pelletier, Guang Xie, Florian Mercier, Florent Delmas

Abstract:

Bulk metallic glasses exhibit several superior properties, compared to their corresponding crystalline counterpart, such as high strength, high elastic limit or good corrosion resistance. Therefore they can be considered as good candidates for structural applications in many sectors. However, they are generally brittle and do not exhibit plastic deformation at room temperature. These materials are mainly obtained by rapid cooling from a liquid state to prevent crystallization, which limits their size. To overcome these two drawbacks: fragility and limited dimensions, composite metallic glass matrix reinforced by a second phase whose role is to slow crack growth are developed. Concerning the limited size of the pieces, the proposed solution is to get the material from amorphous powders by densifying under load. In this study, Cu50Zr45Al5 bulk metallic glassy matrix composites (MGMCs) containing different volume fraction (Vf) of Zr crystalline particles were manufactured by spark plasma sintering (SPS). Microstructure, thermal stability and mechanical properties of the MGMCs were investigated. Matrix of the composites remains a fully amorphous phase after consolidation at 420°C under 600 MPa. A good dispersion of the particles in the glassy matrix is obtained. Results show that the compressive strength decreases with Vf : 1670 MPa (Vf=0%) to 1300MPa (Vf=30%), the elastic modulus decreases but only slighty respectively 97.3GPa and 94.5 GPa and plasticity is improved from 0 to 4%. Fractographic investigation indicates a good bonding between amorphous and crystalline particles. In conclusion, present study has demonstrated that SPS method is useful for the synthesis of the bulk glassy composites. Large controlled microstructure specimens with interesting ductility can be obtained compared with others methods.

Keywords: composite, mechanical properties, metallic glasses, spark plasma sintering

Procedia PDF Downloads 269

Authors: Davood Barari Tari

Abstract:

In order to investigate the correlation of rice traits in different nitrogen management methods by modeling programming, an experiment was laid out in rice paddy field in an experimental field at Caspian Coastal Sea region from 2013 to 2014. Variety used was Shiroudi as a high yielding variety. Nitrogen management was in two methods. Amount of nitrogen at four levels (30, 60, 90, and 120 Kg N ha-1 and control) and nitrogen-splitting at four levels (T1: 50% in base + 50% in maximum tillering stage, T2= 33.33% basal +33.33% in maximum tillering stage +33.33% in panicle initiation stage, T3=25% basal+37.5% in maximum tillering stage +37.5% in panicle initiation stage, T4: 25% in basal + 25% in maximum tillering stage + 50% in panicle initiation stage). Results showed that nitrogen traits, total grain number, filled spikelets, panicle number per m2 had a significant correlation with grain yield. Results related to calibrated and validation of rice model methods indicated that correlation between rice yield and yield components was accurate. The correlation between panicle length and grain yield was minimum. Physiological indices was simulated with low accuracy. According to results, investigation of the correlation between rice traits in physiological, morphological and phenological characters and yield by modeling and simulation methods are very useful.

Keywords: rice, physiology, modelling, simulation, yield traits

Procedia PDF Downloads 337

Authors: Sandy Bao, Yankang Bao

Abstract:

The understanding of information that is being processed in the brain, especially in the lateral geniculate nucleus (LGN), has been proven challenging for modern neuroscience and for researchers with a focus on how neurons process signals and images. In this paper, we are proposing a method to image process different colors within different layers of LGN, that is, green information in layers 4 & 6 and red & blue in layers 3 & 5 based on the surface dimension of layers. We take into consideration the images in LGN and visual cortex, and that the edge detected information from the visual cortex needs to be considered in order to return back to the layers of LGN, along with the image in LGN to form the new image, which will provide an improved image that is clearer, sharper, and making it easier to identify objects in the image. Matrix Laboratory (MATLAB) simulation is performed, and results show that the clarity of the output image has significant improvement.

Keywords: lateral geniculate nucleus, matrix laboratory, neuroscience, visual cortex

Procedia PDF Downloads 258