Search results for: lattice Green's function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7166

Search results for: lattice Green's function

3026 Towards Sustainable Construction in the United Arab Emirates: Challenges and Opportunities

Authors: Yousef Alqaryouti, Mariam Al Suwaidi, Raed Mohmood AlKhuwaildi, Hind Kolthoum, Issa Youssef, Mohammed Al Imam

Abstract:

The UAE has experienced rapid economic growth due to its mature oil production industry, leading to a surge in urbanization and infrastructure development in the construction sector. Sustainable development practices are becoming increasingly important, and the UAE government has taken proactive measures to promote them, including the introduction of sustainable building codes, energy-efficient technologies, and renewable energy sources. Initiatives such as the Masdar City project and the Emirates Green Building Council further demonstrate the government's commitment to a cleaner and healthier environment. By adopting sustainable practices, the UAE can reduce its carbon footprint, lessen its reliance on fossil fuels, and achieve cost savings in the long run. The purpose of this paper is to conduct a thorough review of the current state of sustainability in the construction industry of the UAE. Our research methodology includes a local market survey and qualitative observational analysis of executed housing construction projects by the Mohammed Bin Rashid Housing Establishment. The market survey assesses eleven different challenging factors that affect sustainable construction project delivery. The qualitative observational research is based on data collected from three projects, including construction progress, bill of quantity, and construction program. The study concludes that addressing these challenges requires a collaborative team approach, incentivized contracts, traditional project management practices, an integrated project team, and an increase in sustainability awareness among stakeholders. The recommendations proposed in this study aim to promote and improve the application of sustainability in the UAE's construction industry for the future.

Keywords: sustainability, construction, challenges, opportunities, case study, market survey

Procedia PDF Downloads 49
3025 Influence of a Pulsatile Electroosmotic Flow on the Dispersivity of a Non-Reactive Solute through a Microcapillary

Authors: Jaime Muñoz, José Arcos, Oscar Bautista Federico Méndez

Abstract:

The influence of a pulsatile electroosmotic flow (PEOF) at the rate of spread, or dispersivity, for a non-reactive solute released in a microcapillary with slippage at the boundary wall (modeled by the Navier-slip condition) is theoretically analyzed. Based on the flow velocity field developed under such conditions, the present study implements an analytical scheme of scaling known as the Theory of Homogenization, in order to obtain a mathematical expression for the dispersivity, valid at a large time scale where the initial transients have vanished and the solute spreads under the Taylor dispersion influence. Our results show the dispersivity is a function of a slip coefficient, the amplitude of the imposed electric field, the Debye length and the angular Reynolds number, highlighting the importance of the latter as an enhancement/detrimental factor on the dispersivity, which allows to promote the PEOF as a strong candidate for chemical species separation at lab-on-a-chip devices.

Keywords: dispersivity, microcapillary, Navier-slip condition, pulsatile electroosmotic flow, Taylor dispersion, Theory of Homogenization

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3024 Chinese Sentence Level Lip Recognition

Authors: Peng Wang, Tigang Jiang

Abstract:

The computer based lip reading method of different languages cannot be universal. At present, for the research of Chinese lip reading, whether the work on data sets or recognition algorithms, is far from mature. In this paper, we study the Chinese lipreading method based on machine learning, and propose a Chinese Sentence-level lip-reading network (CNLipNet) model which consists of spatio-temporal convolutional neural network(CNN), recurrent neural network(RNN) and Connectionist Temporal Classification (CTC) loss function. This model can map variable-length sequence of video frames to Chinese Pinyin sequence and is trained end-to-end. More over, We create CNLRS, a Chinese Lipreading Dataset, which contains 5948 samples and can be shared through github. The evaluation of CNLipNet on this dataset yielded a 41% word correct rate and a 70.6% character correct rate. This evaluation result is far superior to the professional human lip readers, indicating that CNLipNet performs well in lipreading.

Keywords: lipreading, machine learning, spatio-temporal, convolutional neural network, recurrent neural network

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3023 Polypharmacy Overdose: Case Report on Mixed Overdose of Ramipril, Quetiapine, Lercanidipine and Duloxetine

Authors: Chui Ling Teng, R. Matsa

Abstract:

We report a case with combined overdose of Lercanidipine (non-dihydropyridine calcium channel blocker), Quetiapine (Atypical antipsychotic), Ramipril and Duloxetine. A 66-year old male presented to the Emergency Department 12-hours after the ingestion of 1.2g Lercanidipine, 3g Quetiapine, 280mg of Ramipril and 420mg of Duloxetine. He describes lethargic, drowsiness and was unable to pass any urine since overdosed. He was found to be bradycardic, hypotensive and anuric. He had refractory hypotension and anuric despite fluid resuscitation, glucagon therapy and intravenous naloxone. His care was escalated to Intensive care, requiring noradrenaline, adrenaline, vasopressin, and hyperinsulinaemic euglycaemia therapy. He achieved haemodynamic stability and kidney function improved gradually with the support received. The total length of therapy lasted for 30 horus in which individual therapy was weaned down based on the requirement. He was then transferred to medical ward for further psychiatric assessment. This is a the first repored case of mixed overdose with lercanidipine, Quetiapine, Rampmipril and Duloxetine.

Keywords: calcium channel blocker, hyperinsulinaemic Euglycaemia therapy, lercanidipine, overdose

Procedia PDF Downloads 317
3022 Study of Mechanical Behavior of Unidirectional Composite Laminates According

Authors: Deliou Adel, Saadalah Younes, Belkaid Khmissi, Dehbi Meriem

Abstract:

Composite materials, in the most common sense of the term, are a set of synthetic materials designed and used mainly for structural applications; the mechanical function is dominant. The mechanical behaviors of the composite, as well as the degradation mechanisms leading to its rupture, depend on the nature of the constituents and on the architecture of the fiber preform. The profile is required because it guides the engineer in designing structures with precise properties in relation to the needs. This work is about studying the mechanical behavior of unidirectional composite laminates according to different failure criteria. Varying strength parameter values make it possible to compare the ultimate mechanical characteristics obtained by the criteria of Tsai-Hill, Fisher and maximum stress. The laminate is subjected to uniaxial tensile membrane forces. Estimates of their ultimate strengths and the plotting of the failure envelope constitute the principal axis of this study. Using the theory of maximum stress, we can determine the various modes of damage of the composite. The different components of the deformation are presented for different orientations of fibers.

Keywords: unidirectional kevlar/epoxy composite, failure criterion, membrane stress, deformations, failure envelope

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3021 Analysis of the Suspension Rocker of Formula SAE Prototype by Finite Element Method

Authors: Jessyca A. Bessa, Darlan A. Barroso, Jonas P. Reges, Auzuir R. Alexandria

Abstract:

This work aims to study the rocker. This is a device of the suspension of Formula SAE vehicle that receives efforts from the motion scrolling of the vehicle and transmits them to the chassis frame minimized by a momentum ratio and smoothed by the set spring - damper. A review of parameters used in vehicle dynamics and a geometric analysis of the forces and stresses caused by such was carried out. The main function of the rocker is to reduce the force transmitted to the frame due to movement of rolling and subsequent application of the suspension. This functions is taken as satisfactory, since the force applied to the wheel and which would be transmitted to the chassis is reduced from 3833.9N to 3496.48N. From these values can be further more detailed simulations using the finite element method aimed at mass reduction or even rocker manufacturing feasibility aluminum. Then, the analysis by the finite element method was applied. This analysis uses the theory of discretization of systems and examines the strength of the component based on the distortion energy, determining the maximum straining experienced by the component and the region of higher demand.

Keywords: rocker, suspension, the finite element method, mechatronics engineering

Procedia PDF Downloads 534
3020 The Role of Ionic Strength and Mineral Size to Zeta Potential for the Adhesion of P. putida to Mineral Surfaces

Authors: Fathiah Mohamed Zuki, Robert George Edyvean

Abstract:

Electrostatic interaction energy (∆EEDL) is a part of the Extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory, which, together with van der Waals (∆EVDW) and acid base (∆EAB) interaction energies, has been extensively used to investigate the initial adhesion of bacteria to surfaces. Electrostatic or electrical double layer interaction energy is considerably affected by surface potential, however it cannot be determined experimentally and is usually replaced by zeta (ζ) potential via electrophoretic mobility. This paper focuses on the effect of ionic concentration as a function of pH and the effect of mineral grain size on ζ potential. It was found that both ionic strength and mineral grain size play a major role in determining the value of ζ potential for the adhesion of P. putida to hematite and quartz surfaces. Higher ζ potential values lead to higher electrostatic interaction energies and eventually to higher total XDLVO interaction energy resulting in bacterial repulsion.

Keywords: XDLVO, electrostatic interaction energy, zeta potential, P. putida, mineral

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3019 Effect of Fibres-Chemical Treatment on the Thermal Properties of Natural Composites

Authors: J. S. S. Neto, R. A. A. Lima, D. K. K. Cavalcanti, J. P. B. Souza, R. A. A. Aguiar, M. D. Banea

Abstract:

In the last decade, investments in sustainable processes and products have gained space in several segments, such as in the civil, automobile, textile and other industries. In addition to increasing concern about the development of environmentally friendly materials that reduce, energy costs and reduces environmental impact in the production of these products, as well as reducing CO2 emissions. Natural fibers offer a great alternative to replace synthetic fibers, totally or partially, because of their low cost and their renewable source. The purpose of this research is to study the effect of surface chemical treatment on the thermal properties of hybrid fiber reinforced natural fibers (NFRC), jute + ramie, jute + sisal, jute + curauá, and jute fiber in polymer matrices. Two types of chemical treatment: alkalinization and silanization were employed, besides the condition without treatment. Differential scanning calorimetry (DSC), thermogravimetry (TG) and dynamic-mechanical analysis (DMA) were performed to explore the thermal stability and weight loss in the natural fiber reinforced composite as a function of chemical treatment.

Keywords: chemical treatment, hybrid composite, jute, thermal

Procedia PDF Downloads 304
3018 Multiclass Support Vector Machines with Simultaneous Multi-Factors Optimization for Corporate Credit Ratings

Authors: Hyunchul Ahn, William X. S. Wong

Abstract:

Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

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3017 Solar-Plasma Reactors for a Zero-Emission Economy

Authors: Dassou Nagassou

Abstract:

Recent increase in frequency and severity of climatic impacts throughout the world has put a particular emphasis on the urgency to address the anthropogenic greenhouse gas emissions. The latter, mainly composed of carbon dioxide are responsible for the global warming of planet earth. Despite efforts to transition towards a zero-emission economy, manufacturing industries, electricity generation power plants, and transportation sectors continue to encounter challenges which hinder their progress towards a full decarbonization. The growing energy demand from both developed and under-developed economies exacerbates the situation and as a result, more carbon dioxide is discharged into the atmosphere. This situation imposes a lot of constraints on industries which are involved i.e., manufacturing industries, transportation, and electricity generation which must navigate the stringent environmental regulations in order to remain profitable. Existing solutions such as energy efficiencies, green materials (life cycle analysis), and many more have fallen short to address the problem due to their inadaptation to existing infrastructures, low efficiencies, and prohibitive costs. The proposed technology exploits the synergistic interaction between solar radiation and plasma to boost a direct decomposition of the molecules of carbon dioxide while producing alternative fuels which can be used to sustain on-site high-temperature processes via 100% solar energy harvesting in the form of photons and electricity. The advantages of this technology and its ability to be easily integrated into existing systems make it appealing for the industry which can now afford to fast track on the path towards full decarbonization, thanks to the solar plasma reactor. Despite the promising experimental results which proved the viability of this concept, solar-plasma reactors require further investigations to understand the synergistic interactions between plasma and solar radiation for a potential technology scale-up.

Keywords: solar, non-equilibrium, plasma, reactor, greenhouse-gases, solar-fuels

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3016 The Stability Study of Large-Scale Grid-Tied Photovoltaic System Containing Different Types of Inverter

Authors: Chen Zheng, Lin Zhou, Bao Xie, Xiao Du, Nianbin Shao

Abstract:

Power generated by large-scale photovoltaic plants (LSPVPs) is usually transmitted to the grid through several transformers and long distance overhead lines. Impedance of transformers and transmission lines results in complex interactions between the plant and the grid and among different inverters. In accordance with the topological structure of LSPV in reality, an equivalent model containing different inverters was built and then interactions between the plant and the grid and among different inverters were studied. Based on the vector composition principle of voltage at the point of common coupling (PCC), the mathematic function of PCC voltage in regard to the total power and grid impedance was deduced, from which the uttermost total power to guarantee the system stable is obtained. Taking the influence of different inverters numbers and the length of transmission lines to the system stability into account, the stability criterion of LSPV containing different inverters was derived. The result of simulation validated the theory analysis in the paper.

Keywords: LSPVPs, stability analysis, grid impedance, different types of inverter, PCC voltage

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3015 Processing and Characterization of Cereal Bar Containing Cassava Flour

Authors: E. L. Queiroz, S. M. A. Souza, R. T. S. Santos

Abstract:

The cereal bars have emerged as a healthy alternative in the food sector, by presenting a remarkable functional appeal, being a product of high nutritional value. Cereals have an important function in feeding because they have features that particularize them as their variety, smooth flavour and aroma and easy digestion and absorption in the body. Brazil is the largest producer of cassava in the world, and the flour produced from this raw material is a source of nutrients for much of the low-income population, however it is little explored industrially. The northeast region of Brazil has great potential for honey production, which is a source of vitamins, proteins, minerals and organic acids but it is much used as a medicine. Aiming to combine the production of healthy food with the sustainable utilization and enhancement of family farming products, was created a cereal bar using regional raw materials of desirable nutritional characteristics: honey, umbu pulp and cassava flour. The cereal bar was characterized by physicochemical analyzes quantifying the content of lipids, proteins, moisture and ashes, microbiological and sensory evaluation showed that the cereal bar is a safe, and nutritious food with good sensory properties.

Keywords: cassava flour, cereal bar, honey, insoluble fibre

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3014 Identification of Analogues to EGCG for the Inhibition of HPV E7: A Fundamental Insights through Structural Dynamics Study

Authors: Murali Aarthy, Sanjeev Kumar Singh

Abstract:

High risk human papillomaviruses are highly associated with the carcinoma of the cervix and the other genital tumors. Cervical cancer develops through the multistep process in which increasingly severe premalignant dysplastic lesions called cervical intraepithelial neoplastic progress to invasive cancer. The oncoprotein E7 of human papillomavirus expressed in the lower epithelial layers drives the cells into S-phase creating an environment conducive for viral genome replication and cell proliferation. The replication of the virus occurs in the terminally differentiating epithelium and requires the activation of cellular DNA replication proteins. To date, no suitable drug molecule is available to treat HPV infection whereas identification of potential drug targets and development of novel anti-HPV chemotherapies with unique mode of actions are expected. Hence, our present study aimed to identify the potential inhibitors analogous to EGCG, a green tea molecule which is considered to be safe to use for mammalian systems. A 3D similarity search on the natural small molecule library from natural product database using EGCG identified 11 potential hits based on their similarity score. The structure based docking strategies were implemented in the potential hits and the key interacting residues of protein with compounds were identified through simulation studies and binding free energy calculations. The conformational changes between the apoprotein and the complex were analyzed with the simulation and the results demonstrated that the dynamical and structural effects observed in the protein were induced by the compounds and indicated the dominance to the oncoprotein. Overall, our study provides the basis for the structural insights of the identified potential hits and EGCG and hence, the analogous compounds identified can be potent inhibitors against the HPV 16 E7 oncoprotein.

Keywords: EGCG, oncoprotein, molecular dynamics simulation, analogues

Procedia PDF Downloads 119
3013 In-House Enzyme Blends from Polyporus ciliatus CBS 366.74 for Enzymatic Saccharification of Pretreated Corn Stover

Authors: Joseph A. Bentil, Anders Thygesen, Lene Langea, Moses Mensah, Anne Meyer

Abstract:

The study investigated the saccharification potential of in-house enzymes produced from a white-rot basidiomycete strain, Polyporus ciliatus CBS 366.74. The in-house enzymes were produced by growing the fungus on mono and composite substrates of cocoa pod husk (CPH) and green seaweed (GS) (Ulva lactuca sp.) with and without the addition of 25mM ammonium nitrate at 4%w/v substrate concentration in submerged condition for 144 hours. The crude enzyme extracts preparations (CEE 1-5 and CEE 1-5+AN) obtained from the fungal cultivation process were sterile-filtered and used as enzyme sources for enzymatic hydrolysis of hydrothermally pretreated corn stover using a commercial cocktail enzyme, Cellic Ctec3, as benchmark. The hydrolysis was conducted at 50ᵒC with 50mM sodium acetate buffer, pH 5 based on enzyme dosages of 5 and 10 CMCase Units/g biomass at 1%w/v dry weight substrate concentration at time points of 6, 24, and 72 hours. The enzyme activity profile of the in-house enzymes varied among the growth substrates with the composite substrates (50-75% GS and AN inclusion), yielding better enzyme activities, especially endoglucanases (0.4-0.5U/mL), β-glucosidases (0.1-0.2 U/mL), and xylanases (3-10 U/mL). However, nitrogen supplementation had no significant effect on enzyme activities of crude extracts from 100% GS substituted substrates. From the enzymatic hydrolysis, it was observed that the in-house enzymes were capable of hydrolysing the pretreated corn stover at varying degrees; however, the saccharification yield was less than 10%. Consequently, theoretical glucose yield was ten times lower than Cellic Ctec3 at both dosage levels. There was no linear correlation between glucose yield and enzyme dosage for the in-house enzymes, unlike the benchmark enzyme. It is therefore recommended that the in-house enzymes are used to complement the dosage of commercial enzymes to reduce the cost of biomass saccharification.

Keywords: enzyme production, hydrolysis yield, feedstock, enzyme blend, Polyporus ciliatus

Procedia PDF Downloads 254
3012 Deep Learning for SAR Images Restoration

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 64
3011 Software Engineering Inspired Cost Estimation for Process Modelling

Authors: Felix Baumann, Aleksandar Milutinovic, Dieter Roller

Abstract:

Up to this point business process management projects in general and business process modelling projects in particular could not rely on a practical and scientifically validated method to estimate cost and effort. Especially the model development phase is not covered by a cost estimation method or model. Further phases of business process modelling starting with implementation are covered by initial solutions which are discussed in the literature. This article proposes a method of filling this gap by deriving a cost estimation method from available methods in similar domains namely software development or software engineering. Software development is regarded as closely similar to process modelling as we show. After the proposition of this method different ideas for further analysis and validation of the method are proposed. We derive this method from COCOMO II and Function Point which are established methods of effort estimation in the domain of software development. For this we lay out similarities of the software development rocess and the process of process modelling which is a phase of the Business Process Management life-cycle.

Keywords: COCOMO II, busines process modeling, cost estimation method, BPM COCOMO

Procedia PDF Downloads 433
3010 Study of Parameters Influencing Dwell Times for Trains

Authors: Guillaume Craveur

Abstract:

The work presented here shows a study on several parameters identified as influencing dwell times for trains. Three kinds of rolling stocks are studied for this project and the parameters presented are the number of passengers, the allocation of passengers, their priorities, the platform station height, the door width and the train design. In order to make this study, a lot of records have been done in several stations in Paris (France). Then, in order to study these parameters, numerical simulations are completed. The goal is to quantify the impact of each parameter on the dwelling times. For example, this study highlights the impact of platform height and the presence of steps between the platform and the train. Three types of station platforms are concerned by this study : ‘optimum’ station platform which is 920 mm high, standard station platform which is 550 mm high, and high station platform which is 1150 mm high and different kinds of steps exist in order to fill these gaps. To conclude, this study shows the impact of these parameters on dwell times and their impact in function of the size of population.

Keywords: dwell times, numerical tools, rolling stock, platforms

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3009 Intraoperative ICG-NIR Fluorescence Angiography Visualization of Intestinal Perfusion in Primary Pull-Through for Hirschsprung Disease

Authors: Mohammad Emran, Colton Wayne, Shannon M Koehler, P. Stephen Almond, Haroon Patel

Abstract:

Purpose: Assessment of anastomotic perfusion in Hirschsprung disease using Indocyanine Green (ICG)-near-infrared (NIR) fluorescence angiography. Introduction: Anastomotic stricture and leak are well-known complications of Hirschsprung pull-through procedures. Complications are due to tension, infection, and/or poor perfusion. While a surgeon can visually determine and control the amount of tension and contamination, assessment of perfusion is subject to surgeon determination. Intraoperative use of ICG-NIR enhances this decision-making process by illustrating perfusion intensity and adequacy in the pulled-through bowel segment. This technique, proven to reduce anastomotic stricture and leak in adults, has not been studied in children to our knowledge. ICG, an FDA approved, nontoxic, non-immunogenic, intravascular (IV) dye, has been used in adults and children for over 60 years, with few side effects. ICG-NIR was used in this report to demonstrate the adequacy of perfusion during transanal pullthrough for Hirschsprung’s disease. Method: 8 patients with Hirschsprung disease were evaluated with ICG-NIR technology. Levels of affected area ranged from sigmoid to total colonic Hirschsprung disease. After leveling, but prior to anastomosis, ICG was administered at 1.25 mg (< 2 mg/kg) and perfusion visualized using an NIR camera, before and during anastomosis. Video and photo imaging was performed and perfusion of the bowel was compared to surrounding tissues. This showed the degree of perfusion and demarcation of perfused and non-perfused bowel. The anastomosis was completed uneventfully and the patients all did well. Results: There were no complications of stricture or leak. 5 of 8 patients (62.5%) had modification of the plan based on ICG-NIR imaging. Conclusion: Technologies that enhance surgeons’ ability to visualize bowel perfusion prior to anastomosis in Hirschsprung’s patients may help reduce post-operative complications. Further studies are needed to assess the potential benefits.

Keywords: colonic anastomosis, fluorescence angiography, Hirschsprung disease, pediatric surgery, SPY

Procedia PDF Downloads 136
3008 Control Strategy for a Solar Vehicle Race

Authors: Francois Defay, Martim Calao, Jean Francois Dassieu, Laurent Salvetat

Abstract:

Electrical vehicles are a solution for reducing the pollution using green energy. The shell Eco-Marathon provides rules in order to minimize the battery use for the race. The use of solar panel combined with efficient motor control and race strategy allow driving a 60kg vehicle with one pilot using only the solar energy in the best case. This paper presents a complete modelization of a solar vehicle used for the shell eco-marathon. This project called Helios is cooperation between non-graduated students, academic institutes, and industrials. The prototype is an ultra-energy-efficient vehicle based on one-meter square solar panel and an own-made brushless controller to optimize the electrical part. The vehicle is equipped with sensors and embedded system to provide all the data in real time in order to evaluate the best strategy for the course. A complete modelization with Matlab/Simulink is used to test the optimal strategy to increase the global endurance. Experimental results are presented to validate the different parts of the model: mechanical, aerodynamics, electrical, solar panel. The major finding of this study is to provide solutions to identify the model parameters (Rolling Resistance Coefficient, drag coefficient, motor torque coefficient, etc.) by means of experimental results combined with identification techniques. One time the coefficients are validated, the strategy to optimize the consumption and the average speed can be tested first in simulation before to be implanted for the race. The paper describes all the simulation and experimental parts and provides results in order to optimize the global efficiency of the vehicle. This works have been started four years ago and evolved many students for the experimental and theoretical parts and allow to increase the knowledge on electrical self-efficient vehicle.

Keywords: electrical vehicle, endurance, optimization, shell eco-marathon

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3007 Effects of Two Cross Focused Intense Laser Beams On THz Generation in Rippled Plasma

Authors: Sandeep Kumar, Naveen Gupta

Abstract:

Terahertz (THz) generation has been investigated by beating two cosh-Gaussian laser beams of the same amplitude but different wavenumbers and frequencies through rippled collisionless plasma. The ponderomotive force is operative which is induced due to the intensity gradient of the laser beam over the cross-section area of the wavefront. The electrons evacuate towards a low-intensity regime, which modifies the dielectric function of the medium and results in cross focusing of cosh-Gaussian laser beams. The evolution of spot size of laser beams has been studied by solving nonlinear Schrodinger wave equation (NLSE) with variational technique. The laser beams impart oscillations to electrons which are enhanced with ripple density. The nonlinear oscillatory motion of electrons gives rise to a nonlinear current density driving THz radiation. It has been observed that the periodicity of the ripple density helps to enhance the THz radiation.

Keywords: rippled collisionless plasma, cosh-gaussian laser beam, ponderomotive force, variational technique, nonlinear current density

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3006 Rotor Dynamic Analysis for a Shaft Train by Using Finite Element Method

Authors: M. Najafi

Abstract:

In the present paper, a large turbo-generator shaft train including a heavy-duty gas turbine engine, a coupling, and a generator is established. The method of analysis is based on finite element simplified model for lateral and torsional vibration calculation. The basic elements of rotor are the shafts and the disks which are represented as circular cross section flexible beams and rigid body elements, respectively. For more accurate results, the gyroscopic effect and bearing dynamics coefficients and function of rotation are taken into account, and for the influence of shear effect, rotor has been modeled in the form of Timoshenko beam. Lateral critical speeds, critical speed map, damped mode shapes, Campbell diagram, zones of instability, amplitudes, phase angles response due to synchronous forces of excitation and amplification factor are calculated. Also, in the present paper, the effect of imbalanced rotor and effects of changing in internal force and temperature are studied.

Keywords: rotor dynamic analysis, finite element method, shaft train, Campbell diagram

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3005 Seismic Assessment of Old Existing RC Buildings with Masonry Infill in Madinah as Per ASCE

Authors: Tarek M. Alguhane, Ayman H. Khalil, Nour M. Fayed, Ayman M. Ismail

Abstract:

An existing RC building in Madinah is seismically evaluated with and without infill wall. Four model systems have been considered i. e. model I (no infill), model IIA (strut infill-update from field test), model IIB (strut infill- ASCE/SEI 41) and model IIC (strut infill-Soft storey-ASCE/SEI 41). Three dimensional pushover analyses have been carried out using SAP 2000 software incorporating inelastic material behavior for concrete, steel and infill walls. Infill wall has been modeled as equivalent strut according to suggested equation matching field test measurements and to the ASCE/SEI 41 equation. The effect of building modeling on the performance point as well as capacity and demand spectra due to EQ design spectrum function in Madinah area has been investigated. The response modification factor (R) for the 5 story RC building is evaluated from capacity and demand spectra (ATC-40) for the studied models. The results are summarized and discussed.

Keywords: infill wall, pushover analysis, response modification factor, seismic assessment

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3004 Interesting Behavior of Non-Thermal Plasma Photonic Crystals

Authors: A. Mousavi, S. Sadegzadeh

Abstract:

In this research, the effect of non-thermal micro plasma with non-Maxwellian distribution function on the one dimensional plasma photonic crystals containing alternate plasma-dielectric layers, has been studied. By using Kronig Penny model, the dispersion relation of electromagnetic modes for such a periodic structure is obtained. In this study we take two plasma photonic crystals with different dielectric layers: the first one with Silicon monoxide named PPCI, and the second one with Tellurium dioxide named PPCII. The effects of the plasma layer thickness and the material of the dielectric layer on the plasma photonic crystal band gaps have been illustrated in the dispersion relation and the group velocity figures. Results revealed that in such a system, the non-thermal plasma exerts stronger limit on the wave’s propagation. In another word, for the non-thermal plasma photonic crystals (NPPC), there are two distinct regions in the dispersion plot. The upper region consists of alternate band gaps in such a way that both width and length of the bands decrease gradually as the band gaps order increases. Whereas in the lower region where v_ph > 20 c (for PPCI), waves will not be allowed to propagate.

Keywords: band gap, dispersion relation, non-thermal plasma, plasma photonic crystal

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3003 A Near-Optimal Domain Independent Approach for Detecting Approximate Duplicates

Authors: Abdelaziz Fellah, Allaoua Maamir

Abstract:

We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.

Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery

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3002 Experimental Modal Analysis of Reinforced Concrete Square Slabs

Authors: M. S. Ahmed, F. A. Mohammad

Abstract:

The aim of this paper is to perform experimental modal analysis (EMA) of reinforced concrete (RC) square slabs. EMA is the process of determining the modal parameters (Natural Frequencies, damping factors, modal vectors) of a structure from a set of frequency response functions FRFs (curve fitting). Although experimental modal analysis (or modal testing) has grown steadily in popularity since the advent of the digital FFT spectrum analyzer in the early 1970’s, studying all members and materials using such method have not yet been well documented. Therefore, in this work, experimental tests were conducted on RC square specimens (0.6m x 0.6m with 40 mm). Experimental analysis is based on freely supported boundary condition. Moreover, impact testing as a fast and economical means of finding the modes of vibration of a structure was used during the experiments. In addition, Pico Scope 6 device and MATLAB software were used to acquire data, analyze and plot Frequency Response Function (FRF). The experimental natural frequencies which were extracted from measurements exhibit good agreement with analytical predictions. It is showed that EMA method can be usefully employed to perform the dynamic behavior of RC slabs.

Keywords: natural frequencies, mode shapes, modal analysis, RC slabs

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3001 Kinetics and Toxicological Effects of Kickxia elatine Extract-Based Silver Nanoparticles on Rat Brain Acetylcholinesterase

Authors: Noor Ul Huda, Mushtaq Ahmed, Nadia Mushtaq, Naila Sher, Rahmat Ali Khan

Abstract:

Purpose: The green synthesis of AgNPs has been favored over chemical synthesis due to their distinctive properties such as high dispersion, surface-to-volume ratio, low toxicity, and easy preparation. In the present work, the biosynthesis of AgNPs (KE-AgNPs) was carried out in one step by using the traditionally used plant Kickxia elatine (KE) extract and then investigated its enzyme inhibiting activity against rat’s brain acetylcholinesterase (AChE) in vitro. Methods: KE-AgNPs were synthesized from 1mM AgNO₃ using KE extract and characterized by UV–spectroscopy, SEM, EDX, XRD, and FTIR analysis. Rat’s brain acetylcholinesterase (AChE) inhibition activity was evaluated by the standard protocol. Results: UV–spectrum at 416 nm confirmed the formation of KE-AgNPs. X-ray diffraction (XRD) pattern presented 2θ values corresponding to the crystalline nature of KE-AgNPs with an average size of 42.47nm. The scanning electron microscope (SEM) analysis confirmed the presence of spherical-shaped and huge density KE-AgNPs with a size of 50nm. Fourier transform infrared spectroscopy (FT-IR) suggested that the functional groups present in KE extract and on the surface of KE-AgNPs are responsible for the stability of biosynthesized NPs. Energy dispersive X-ray (EDX) displayed an intense sharp peak at 3.2 keV, presenting that Ag was the chief element with 61.67%. Both KE extract and KE-AgNPs showed good and potent anti-AChE activity, with higher inhibition potential at a concentration of 175 µg/ml. Statistical analysis showed that both KEE and AgNPs exhibited non-competitive type inhibition against AChE, i.e., Vmax decreased (34.17-68.64% and 22.29- 62.10%) in the concentration-dependent mode for KEE and KE-AgNPs respectively and while Km values remained constant. Conclusions: KEE and KE-AgNPs can be considered an inhibitor of rats’ brain AChE, and the synthesis of KE-AgNPs-based drugs can be used as a cheaper and alternative option against diseases such as Alzheimer’s disease.

Keywords: Kickxia elatine, AgNPs, brain homogenate, acetylcholinesterase, kinetics

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3000 Classification of Echo Signals Based on Deep Learning

Authors: Aisulu Tileukulova, Zhexebay Dauren

Abstract:

Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

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2999 Flexural Response of Glass Fiber Reinforced Polymer Sandwich Panels with 3D Woven Honeycomb Core

Authors: Elif Kalkanli, Constantinos Soutis

Abstract:

The use of textile preform in the advanced fields including aerospace, automotive and marine has exponentially grown in recent years. These preforms offer excellent advantages such as being lightweight and low-cost, and also, their suitability for creating different fiber architectures with different materials whilst improved mechanical properties in certain aspects. In this study, a novel honeycomb core is developed by a 3Dweaving process. The assembly of the layers is achieved thanks to innovative weaving design. Polyester yarn is selected for the 3D woven honeycomb core (3DWHC). The core is used to manufacture a sandwich panel with 2x2 twill glass fiber composite face sheets. These 3DWHC sandwich panels will be tested in three-point bending. The in-plane and out-of-plane (through-the-thickness) mechanical response of the core will be examined as a function of cell size in addition to the flexural response of the sandwich panel. The failure mechanisms of the core and the sandwich skins will be reported in addition to flexural strength and stiffness. Possible engineering applications will be identified.

Keywords: 3D woven, assembly, failure modes, honeycomb sandwich panel

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2998 Proposing an Index for Determining Key Knowledge Management Processes in Decision Making Units Using Fuzzy Quality Function Deployment (QFD), Data Envelopment Analysis (DEA) Method

Authors: Sadegh Abedi, Ali Yaghoubi, Hamidreza Mashatzadegan

Abstract:

This paper proposes an approach to identify key processes required by an organization in the field of knowledge management and aligning them with organizational objectives. For this purpose, first, organization’s most important non-financial objectives which are impacted by knowledge management processes are identified and then, using a quality house, are linked with knowledge management processes which are regarded as technical elements. Using this method, processes that are in need of improvement and more attention are prioritized based on their significance. This means that if a process has more influence on organization’s objectives and is in a dire situation comparing to others, is prioritized for choice and improvement. In this research process dominance is considered to be an influential element in process ranking (in addition to communication matrix). This is the reason for utilizing DEA techniques for prioritizing processes in quality house. Results of implementing the method in Khuzestan steel company represents this method’s capability of identifying key processes that require improvements in organization’s knowledge management system.

Keywords: knowledge management, organizational performance, fuzzy data, envelopment analysis

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2997 Optimal Feature Extraction Dimension in Finger Vein Recognition Using Kernel Principal Component Analysis

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

Abstract:

In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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