Search results for: thermal images
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5715

Search results for: thermal images

5235 Influence of Exfoliated Graphene Nanoplatelets on Thermal Stability of Polypropylene Reinforced Hybrid Graphen-rice Husk Nanocomposites

Authors: Obinna Emmanuel Ezenkwa, Sani Amril Samsudin, Azman Hassan, Ede Anthony

Abstract:

A major challenge of polypropylene (PP) in high-heat application areas is its poor thermal stability. Under high temperature, PP burns readily with high degradation temperature and can self-ignite. In this study, PP is reinforced with hybrid filler of graphene (xGNP) and rice husk (RH) with RH at 15 wt%, and xGNP varied at 0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 parts per hundred (phr) of the composite. Compatibilizer MAPP was also added in each sample at 4phr of the composite. Sample formulations were melt-blended using twin screw extruder and injection moulding machine. At xGNP optimum content of 1.5 phr, hybrid PP/RH/G1.5/MAPP nanocomposite increased in thermal stability by 24 °C and 30 °C compared to pure PP and unhybridized PP/RH composite respectively; char residue increased by 513% compared to pure PP and degree of crystallization (Xc) increased from 35.4% to 36.4%. The observed thermal properties enhancement in the hybrid nanocomposites can be related to the high surface area, gap-filling effect and exfoliation characteristics of the graphene nanofiller which worked in synergy with rice husk fillers in reinforcing PP. This study therefore, shows that graphene nanofiller inclusion in polymer composites fabrication can enhance the thermal stability of polyolefins for high heat applications.

Keywords: polymer nanocomposites, thermal stability, exfoliation, hybrid fillers, polymer reinforcement

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5234 Estimating Cyclone Intensity Using INSAT-3D IR Images Based on Convolution Neural Network Model

Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

Abstract:

Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

Procedia PDF Downloads 108
5233 Simplified 3R2C Building Thermal Network Model: A Case Study

Authors: S. M. Mahbobur Rahman

Abstract:

Whole building energy simulation models are widely used for predicting future energy consumption, performance diagnosis and optimum control.  Black box building energy modeling approach has been heavily studied in the past decade. The thermal response of a building can also be modeled using a network of interconnected resistors (R) and capacitors (C) at each node called R-C network. In this study, a model building, Case 600, as described in the “Standard Method of Test for the Evaluation of Building Energy Analysis Computer Program”, ASHRAE standard 140, is studied along with a 3R2C thermal network model and the ASHRAE clear sky solar radiation model. Although building an energy model involves two important parts of building component i.e., the envelope and internal mass, the effect of building internal mass is not considered in this study. All the characteristic parameters of the building envelope are evaluated as on Case 600. Finally, monthly building energy consumption from the thermal network model is compared with a simple-box energy model within reasonable accuracy. From the results, 0.6-9.4% variation of monthly energy consumption is observed because of the south-facing windows.

Keywords: ASHRAE case study, clear sky solar radiation model, energy modeling, thermal network model

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5232 Influence of Thermal Radiation on MHD Micropolar Fluid Flow, Heat and Mass Transfer over Vertical Flat Plate

Authors: Alouaoui Redha, Ferhat Samira, Bouaziz Mohamed Najib

Abstract:

In this work, we examine the thermal radiation effect on heat and mass transfer in steady laminar boundary layer flow of an incompressible viscous micropolar fluid over a vertical plate, with the presence of a magnetic field. Rosseland approximation is applied to describe the radiative heat flux in the energy equation. The resulting similarity equations are solved numerically. Many results are obtained and representative set is displayed graphically to illustrate the influence of the various parameters on different profiles. The conclusion is drawn that the flow field, temperature, concentration and microrotation as well as the skin friction coefficient and the both local Nusselt and local Sherwood numbers are significantly influenced by Magnetic parameter, material parameter and thermal radiation parameter.

Keywords: MHD, micropolar fluid, thermal radiation, heat and mass transfer, boundary layer

Procedia PDF Downloads 441
5231 Human Intraocular Thermal Field in Action with Different Boundary Conditions Considering Aqueous Humor and Vitreous Humor Fluid Flow

Authors: Dara Singh, Keikhosrow Firouzbakhsh, Mohammad Taghi Ahmadian

Abstract:

In this study, a validated 3D finite volume model of human eye is developed to study the fluid flow and heat transfer in the human eye at steady state conditions. For this purpose, discretized bio-heat transfer equation coupled with Boussinesq equation is analyzed with different anatomical, environmental, and physiological conditions. It is demonstrated that the fluid circulation is formed as a result of thermal gradients in various regions of eye. It is also shown that posterior region of the human eye is less affected by the ambient conditions compared to the anterior segment which is sensitive to the ambient conditions and also to the way the gravitational field is defined compared to the geometry of the eye making the circulations and the thermal field complicated in transient states. The effect of variation in material and boundary conditions guides us to the conclusion that thermal field of a healthy and non-healthy eye can be distinguished via computer simulations.

Keywords: bio-heat, boussinesq, conduction, convection, eye

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5230 Effect of Realistic Lubricant Properties on Thermal Electrohydrodynamic Lubrication Behavior in Circular Contacts

Authors: Puneet Katyal, Punit Kumar

Abstract:

A great deal of efforts has been done in the field of thermal effects in electrohydrodynamic lubrication (TEHL) during the last five decades. The focus was primarily on the development of an efficient numerical scheme to deal with the computational challenges involved in the solution of TEHL model; however, some important aspects related to the accurate description of lubricant properties such as viscosity, rheology and thermal conductivity in EHL point contact analysis remain largely neglected. A few studies available in this regard are based upon highly complex mathematical models difficult to formulate and execute. Using a simplified thermal EHL model for point contacts, this work sheds some light on the importance of accurate characterization of the lubricant properties and demonstrates that the computed TEHL characteristics are highly sensitive to lubricant properties. It also emphasizes the use of appropriate mathematical models with experimentally determined parameters to account for correct lubricant behaviour.

Keywords: TEHL, shear thinning, rheology, conductivity

Procedia PDF Downloads 188
5229 Comprehensive Evaluation of COVID-19 Through Chest Images

Authors: Parisa Mansour

Abstract:

The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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5228 Evaluate the Changes in Stress Level Using Facial Thermal Imaging

Authors: Amin Derakhshan, Mohammad Mikaili, Mohammad Ali Khalilzadeh, Amin Mohammadian

Abstract:

This paper proposes a stress recognition system from multi-modal bio-potential signals. For stress recognition, Support Vector Machines (SVM) and LDA are applied to design the stress classifiers and its characteristics are investigated. Using gathered data under psychological polygraph experiments, the classifiers are trained and tested. The pattern recognition method classifies stressful from non-stressful subjects based on labels which come from polygraph data. The successful classification rate is 96% for 12 subjects. It means that facial thermal imaging due to its non-contact advantage could be a remarkable alternative for psycho-physiological methods.

Keywords: stress, thermal imaging, face, SVM, polygraph

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5227 Chemical Functionalization of Graphene Oxide for Improving Mechanical and Thermal Properties of Polyurethane Composites

Authors: Qifei Jing, Vadim V. Silberschmidt, Lin Li, ZhiLi Dong

Abstract:

Graphene oxide (GO) was chemically functionalized to prepare polyurethane (PU) composites with improved mechanical and thermal properties. In order to achieve a well exfoliated and stable GO suspension in an organic solvent (dimethylformamide, DMF), 4, 4′- methylenebis(phenyl isocyanate) and polycaprolactone diol, which were the two monomers for synthesizing PU, were selectively used to functionalize GO. The obtained functionalized GO (FGO) could form homogeneous dispersions in DMF solvent and the PU matrix, as well as provide a good compatibility with the PU matrix. The most efficient improvement of mechanical properties was achieved when 0.4 wt% FGO was added into the PU matrix, showing increases in the tensile stress, elongation at break and toughness by 34.2%, 27.6% and 64.5%, respectively, compared with those of PU. Regarding the thermal stability, PU filled with 1 wt% FGO showed the largest extent of improvement with T2% and T50% (the temperatures at which 2% and 50% weight-loss happened) 16 °C and 21 °C higher than those of PU, respectively. The significant improvement in both mechanical properties and thermal stability of FGO/PU composites should be attributed to the homogeneous dispersion of FGO in the PU matrix and strong interfacial interaction between them.

Keywords: composite, dispersion, graphene oxide, polyurethane

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5226 Thermal Performance of the Extensive Wetland Green Roofs in Winter in Humid Subtropical Climate

Authors: Yi-Yu Huang, Chien-Kuo Wang, Sreerag Chota Veettil, Hang Zhang, Hu Yike

Abstract:

Regarding the pressing issue of reducing energy consumption and carbon footprint of buildings, past research has focused more on analyzing the thermal performance of the extensive terrestrial green roofs with sedum plants in summer. However, the disadvantages of this type of green roof are relatively limited thermal performance, low extreme weather adaptability, relatively higher demands in maintenance, and lower added value in healing landscape. In view of this, this research aims to develop the extensive wetland green roofs with higher thermal performance, high extreme weather adaptability, low demands in maintenance, and high added value in healing landscape, and to measure its thermal performance for buildings in winter. The following factors are considered including the type and mixing formula of growth medium (light weight soil, akadama, creek gravel, pure water) and the type of aquatic plants. The research adopts a four-stage field experiment conducting on the rooftop of a building in a humid subtropical climate. The results found that emergent (Roundleaf rotala), submerged (Ribbon weed), floating-leaved (Water lily) wetland green roofs had similar thermal performance, and superior over wetland green roof without plant, traditional terrestrial green roof (without plant), and pure water green roof (without plant, nighttime only) in terms of overall passive cooling (8.00C) and thermal insulation (4.50C) effects as well as a reduction in heat amplitude (77-85%) in winter in a humid subtropical climate. The thermal performance of the free-floating (Water hyacinth) wetland green roof is inferior to that of the other three types of wetland green roofs, whether in daytime or nighttime.

Keywords: thermal performance, extensive wetland green roof, Aquatic plant, Winter , Humid subtropical climate

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5225 Segmenting 3D Optical Coherence Tomography Images Using a Kalman Filter

Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

Abstract:

Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

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5224 Classifications of Images for the Recognition of People’s Behaviors by SIFT and SVM

Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

Abstract:

Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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5223 Thermo-Exergy Optimization of Gas Turbine Cycle with Two Different Regenerator Designs

Authors: Saria Abed, Tahar Khir, Ammar Ben Brahim

Abstract:

A thermo-exergy optimization of a gas turbine cycle with two different regenerator designs is established. A comparison was made between the performance of the two regenerators and their roles in improving the cycle efficiencies. The effect of operational parameters (the pressure ratio of the compressor, the ambient temperature, excess of air, geometric parameters of the regenerators, etc.) on thermal efficiencies, the exergy efficiencies, and irreversibilities were studied using thermal balances and quantitative exegetic equilibrium for each component and for the whole system. The results are given graphically by using the EES software, and an appropriate discussion and conclusion was made.

Keywords: exergy efficiency, gas turbine, heat transfer, irreversibility, optimization, regenerator, thermal efficiency

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5222 Review of Ultrasound Image Processing Techniques for Speckle Noise Reduction

Authors: Kwazikwenkosi Sikhakhane, Suvendi Rimer, Mpho Gololo, Khmaies Oahada, Adnan Abu-Mahfouz

Abstract:

Medical ultrasound imaging is a crucial diagnostic technique due to its affordability and non-invasiveness compared to other imaging methods. However, the presence of speckle noise, which is a form of multiplicative noise, poses a significant obstacle to obtaining clear and accurate images in ultrasound imaging. Speckle noise reduces image quality by decreasing contrast, resolution, and signal-to-noise ratio (SNR). This makes it difficult for medical professionals to interpret ultrasound images accurately. To address this issue, various techniques have been developed to reduce speckle noise in ultrasound images, which improves image quality. This paper aims to review some of these techniques, highlighting the advantages and disadvantages of each algorithm and identifying the scenarios in which they work most effectively.

Keywords: image processing, noise, speckle, ultrasound

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5221 Improved Super-Resolution Using Deep Denoising Convolutional Neural Network

Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

Abstract:

Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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5220 Object Recognition Approach Based on Generalized Hough Transform and Color Distribution Serving in Generating Arabic Sentences

Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

Abstract:

The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: recognition of shape, generalized hough transformation, histogram, spatiogram, learning

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5219 Analysis of the Reaction to the Fire of a Composite Material the Base of Scrapes of Tires and Latex for Thermal Isolation in Vehicles

Authors: Elmo Thiao Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale, R. M. Nascimento, J. U. L. Mendes

Abstract:

Now the great majority of the applications of thermal isolation in the strip of drops and averages temperatures (up to 200ºC), it is made being used from aggressive materials to the nature such an as: glass wool, rock wool, polystyrene, EPS among others. Such materials, in spite of the effectiveness in the retention of the flow of heat, possess considerable cost and when discarded they are long years to be to decompose. In that context, trying to adapt the world politics the about of the preservation of the environment, a study began with intention of developing a material composite, with properties of thermal, originating from insulating industrial residues. In this research, the behavior of the composite was analyzed, as submitted the fire. For this, the reaction rehearsals were accomplished to the fire for the composites 2:1; 1:1; 1:2 and for the latex, based in the "con" experiment in agreement with the norm ASTM–E 1334-90. As consequence, in function of the answers of the system, was possible to observe to the acting of each mixture proportion.

Keywords: composite, Latex, reacion to the fire, thermal isolation

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5218 Coupling Heat Transfer by Natural Convection and Thermal Radiation in a Storage Tank of LNG

Authors: R. Hariti, M. Saighi, H. Saidani-Scott

Abstract:

A numerical simulation of natural convection double diffusion, coupled with thermal radiation in unsteady laminar regime in a storage tank is carried out. The storage tank contains a liquefied natural gas (LNG) in its gaseous phase. Fluent, a commercial CFD package, based on the numerical finite volume method, is used to simulate the flow. The radiative transfer equation is solved using the discrete coordinate method. This numerical simulation is used to determine the temperature profiles, stream function, velocity vectors and variation of the heat flux density for unsteady laminar natural convection. Furthermore, the influence of thermal radiation on the heat transfer has been investigated and the results obtained were compared to those found in the literature. Good agreement between the results obtained by the numerical method and those taken on site for the temperature values.

Keywords: tank, storage, liquefied natural gas, natural convection, thermal radiation, numerical simulation

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5217 Investigation on Phase Change Device for Satellite Thermal Control

Authors: Meng-Hao Chen, Jeng-Der Huang, Chia-Ray Chen

Abstract:

With the new space mission need of high power dissipation, low thermal inertia and cyclical operation unit, such as high power amplifier (HPA) for synthetic aperture radar (SAR) satellite, the development of phase change material (PCM) technology seems to be a proper solution. Generally, the expected benefit of PCM solution is to eliminate temperature variation and maintain the stability of electronic units by using the latent heat during phase change process. It can also result in advantages of decreased radiator area and heater power. However, the PCMs have a drawback of low thermal conductivity that leads to large temperature gradient between the heat source and PCM. This paper thus presents both experimental and simplified numerical investigations on configuration design of PCM’s container. A comparison was carried out between the container with and without internal pin-fins structure. The results showed the benefit of pin-fins that act as the heat transfer enhancer to improve the temperature uniformity during phase transition. Furthermore, thermal testing and measurements were presented for four PCM candidates (i.e. n-octadecane, n-eicosane, glycerin and gallium). The solidification and supercooling behaviors on different PCMs were compared with available literature data and discussed in this study

Keywords: phase change material (PCM), thermal control, solidification, supercooling

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5216 Design and Thermal Analysis of a Concrete House in Libya Using BEopt

Authors: Gamal Alamri, Tariq Iqbal

Abstract:

This paper presents an optimum designs and thermal analysis of concrete house in the hot climate of Libya. For this goal we have used BEopt software (building energy optimization) that provides capabilities for estimating residential building design and thermal analysis. The most area of the house that is exposed to the sunlight’s is the roof leading to heat gain. Therefore, house cooling consumes high energy. The cooling energy consumption is three times the heating energy consumption. In order to maintain comfortable indoor conditions in a low-energy house, the entire building envelope needs to be perfectly insulated and prevented from air leakages. Insulated roof is selected to reduce cooling demand, and the paper presents details and BEopt simulation results. Designed house needs 12.02mmbtus/year. Furthermore, the modeling indicates that the designed house is close to achieving the Passive standard.

Keywords: concrete house design, thermal analysis, hot climate, BEopt software

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5215 Influences of Thermal Treatments on Dielectric Behaviors of Carbon Nanotubes-BaTiO₃ Hybrids Reinforced Polyvinylidene Fluoride Composites

Authors: Benhui Fan, Fahmi Bedoui, Jinbo Bai

Abstract:

Incorporated carbon nanotube-BaTiO₃ hybrids (H-CNT-BT) with core-shell structure, a better dispersion of CNTs can be achieved in a semi-crystalline polymeric matrix, polyvinylidene fluoride (PVDF). Carried by BT particles, CNTs are easy to mutually connect which helps to obtain an extremely low percolation threshold (fc). After thermal treatments, the dielectric constants (ε’) of samples further increase which depends on the conditions of thermal treatments such as annealing temperatures, annealing durations and cooling ways. Thus, in order to study more comprehensively about the influence of thermal treatments on composite’s dielectric behaviors, in situ synchrotron X-ray is used to detect re-crystalline behavior of PVDF. Results of wide-angle X-ray diffraction (WAXD) and small-angle X-ray scattering (SAXS) show that after the thermal treatment, the content of β polymorph (the polymorph with the highest ε’ among all the polymorphs of PVDF’s crystalline structure) has increased nearly double times at the interfacial region of CNT-PVDF, and the thickness of amorphous layers (La) in PVDF’s long periods (Lp) has shrunk around 10 Å. The evolution of CNT’s network possibly occurs in the procedure of La shrinkage, where the strong interfacial polarization may be aroused and increases ε’ at low frequency. Moreover, an increase in the thickness of crystalline lamella may also arouse more orientational polarization and improve ε’ at high frequency.

Keywords: dielectric properties, thermal treatments, carbon nanotubes, crystalline structure

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5214 A Palmprint Identification System Based Multi-Layer Perceptron

Authors: David P. Tantua, Abdulkader Helwan

Abstract:

Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

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5213 A Comparative Study of the Effects of Vibratory Stress Relief and Thermal Aging on the Residual Stress of Explosives Materials

Authors: Xuemei Yang, Xin Sun, Cheng Fu, Qiong Lan, Chao Han

Abstract:

Residual stresses, which can be produced during the manufacturing process of plastic bonded explosive (PBX), play an important role in weapon system security and reliability. Residual stresses can and do change in service. This paper mainly studies the influence of vibratory stress relief (VSR) and thermal aging on residual stress of explosives. Firstly, the residual stress relaxation of PBX via different physical condition of VSR, such as vibration time, amplitude and dynamic strain, were studied by drill-hole technique. The result indicated that the vibratory amplitude, time and dynamic strain had a significant influence on the residual stress relief of PBX. The rate of residual stress relief of PBX increases first and then decreases with the increase of dynamic strain, amplitude and time, because the activation energy is too small to make the PBX yield plastic deformation at first. Then the dynamic strain, time and amplitude exceed a certain threshold, the residual stress changes show the same rule and decrease sharply, this sharply drop of residual stress relief rate may have been caused by over vibration. Meanwhile, the comparison between VSR and thermal aging was also studied. The conclusion is that the reduction ratio of residual stress after VSR process with applicable vibratory parameters could be equivalent to 73% of thermal aging with 7 days. In addition, the density attenuation rate, mechanical property, and dimensional stability with 3 months after VSR process was almost the same compared with thermal aging. However, compared with traditional thermal aging, VSR only takes a very short time, which greatly improves the efficiency of aging treatment for explosive materials. Therefore, the VSR could be a potential alternative technique in the industry of residual stress relaxation of PBX explosives.

Keywords: explosives, residual stresses, thermal aging, vibratory stress relief, VSR

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5212 Prediction of Bodyweight of Cattle by Artificial Neural Networks Using Digital Images

Authors: Yalçın Bozkurt

Abstract:

Prediction models were developed for accurate prediction of bodyweight (BW) by using Digital Images of beef cattle body dimensions by Artificial Neural Networks (ANN). For this purpose, the animal data were collected at a private slaughter house and the digital images and the weights of each live animal were taken just before they were slaughtered and the body dimensions such as digital wither height (DJWH), digital body length (DJBL), digital body depth (DJBD), digital hip width (DJHW), digital hip height (DJHH) and digital pin bone length (DJPL) were determined from the images, using the data with 1069 observations for each traits. Then, prediction models were developed by ANN. Digital body measurements were analysed by ANN for body prediction and R2 values of DJBL, DJWH, DJHW, DJBD, DJHH and DJPL were approximately 94.32, 91.31, 80.70, 83.61, 89.45 and 70.56 % respectively. It can be concluded that in management situations where BW cannot be measured it can be predicted accurately by measuring DJBL and DJWH alone or both DJBD and even DJHH and different models may be needed to predict BW in different feeding and environmental conditions and breeds

Keywords: artificial neural networks, bodyweight, cattle, digital body measurements

Procedia PDF Downloads 358
5211 Performance Analysis of Search Medical Imaging Service on Cloud Storage Using Decision Trees

Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel

Abstract:

Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.

Keywords: cloud storage, decision trees, diagnostic image, search, telemedicine

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5210 Intensification of Process Kinetics for Conversion of Organic Volatiles into Syngas Using Non-Thermal Plasma

Authors: Palash Kumar Mollick, Leire Olazar, Laura Santamaria, Pablo Comendador, Manomita Mollick, Gartzen Lopez, Martin Olazar

Abstract:

The entire world is skeptical towards a silver line technology of converting plastic waste into valuable synthetic gas. At this junction, besides an adequately studied conventional catalytic process for steam reforming, a non-thermal plasma is being introduced. Organic volatiles are produced in the first step, pyrolysing the plastic materials. Resultant lightweight olefins and carbon monoxide are the major components that undergo a steam reforming process to achieve syngas. A non-thermal plasma consists of ionized gases and free electrons with an electronic temperature as high as 10³ K. Organic volatiles are, in general, endorganics inactive and thus demand huge bond-breaking energy. Conventional catalyst is incapable of providing the required activation energy, leading to poor thermodynamic equilibrium, whereas a non-thermal plasma can actively collide with reactants to produce a rich mix of reactive species, including vibrationally or electronically excited molecules, radicals, atoms, and ions. In addition, non-thermal plasma provides nonequilibrium conditions leading to electric discharge only in certain degrees of freedom without affecting the intrinsic chemical conditions of the participating reactants and products. In this work, we report thermodynamic and kinetic aspects of the conversion of organic volatiles into syngas using a non-thermal plasma. Detailed characteristics of plasma and its effect on the overall yield of the process will be presented.

Keywords: non thermal plasma, plasma catalysis, steam reforming, syngas, plastic waste, green energy

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5209 Toward Sustainable Building Design in Hot and Arid Climate with Reference to Riyadh City, Saudi Arabia

Authors: M. Alwetaishi

Abstract:

One of the most common and traditional strategies in architecture is to design buildings passively. This is a way to ensure low building energy reliance with respect to specific micro-building locations. There are so many ways where buildings can be designed passively, some of which are applying thermal insulation, thermal mass, courtyard and glazing to wall ratio. This research investigates the impact of each of these aspects with respect to the hot and dry climate of the capital of Riyadh. Thermal Analysis Simulation (TAS) will be utilized which is powered by Environmental Design Simulation Limited company (EDSL). It is considered as one of the most powerful tools to predict energy performance in buildings. There are three primary building designs and methods which are using courtyard, thermal mass and thermal insulation. The same building size and fabrication properties have been applied to all designs. Riyadh city which is the capital of the country was taken as a case study of the research. The research has taken into account various zone directions within the building as it has a large contribution to indoor energy and thermal performance. It is revealed that it is possible to achieve nearly zero carbon building in the hot and dry region in winter with minimum reliance on energy loads for building zones facing south, west and east. Moreover, using courtyard is more beneficial than applying construction materials into building envelope. Glazing to wall ratio is recommended to be 10% and not exceeding 30% in all directions in hot and arid regions.

Keywords: sustainable buildings, hot and arid climates, passive building design, Saudi Arabia

Procedia PDF Downloads 143
5208 Performance Investigation of Thermal Insulation Materials for Walls: A Case Study in Nicosia (Turkish Republic of North Cyprus)

Authors: L. Vafaei, McDominic Eze

Abstract:

The performance of thermal energy in homes and buildings is a significant factor in terms of energy efficiency of a building. In a large sense, the performance of thermal energy is dependent on many factors of which the amount of thermal insulation is at one end a considerable factor, as likewise the essence of mass and the wall thickness and also the thermal resistance of wall material. This study is aimed at illustrating the different wall system in Turkish Republic of North Cyprus (TRNC), acknowledge the problem and suggest a solution through comparing the effect of thermal radiation two model rooms- L1 (Ytong wall) and L2 (heat insulated wall using stone wool) set up for experimentation. The model room has four face walls. The study consists of two stage, the first test is to access the effect of solar radiation for south facing wall and the second stage is to test the thermal performance of Ytong and heat insulated wall, the effects of climatic condition during winter. The heat insulated wall contains material hollow brick, stone wool, and gypsum while the Ytong wall contains cement concrete, for the outer surface and the inner surface and Ytong stone. The total heat of the wall was determined, 7T-Type thermocouple was used with a data logger system to record the data, temperature change recorded at an interval of 10 minutes. The result obtained was that Ytong wall save more energy than the heat insulated wall at night while heat insulated wall saves energy during the day when intensity is at maximum.

Keywords: heat insulation, hollow bricks, south facing, Ytong bricks wall

Procedia PDF Downloads 253
5207 Multimodal Direct Neural Network Positron Emission Tomography Reconstruction

Authors: William Whiteley, Jens Gregor

Abstract:

In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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5206 Thermal Regeneration of CO2 Spent Palm Shell-Polyetheretherketone Activated Carbon Sorbents

Authors: Usman D. Hamza, Noor S. Nasri, Mohammed Jibril, Husna M. Zain

Abstract:

Activated carbons (M4P0, M4P2, and M5P2) used in this research were produced from palm shell and polyetherether ketone (PEEK) via carbonization, impregnation, and microwave activation. The adsorption/desorption process was carried out using static volumetric adsorption. Regeneration is important in the overall economy of the process and waste minimization. This work focuses on the thermal regeneration of the CO2 exhausted microwave activated carbons. The regeneration strategy adopted was thermal with nitrogen purge desorption with N2 feed flow rate of 20 ml/min for 1 h at atmospheric pressure followed by drying at 1500C. Seven successive adsorption/regeneration processes were carried out on the material. It was found that after seven adsorption regeneration cycles; the regeneration efficiency (RE) for CO2 activated carbon from palm shell only (M4P0) was more than 90% while that of hybrid palm shell-PEEK (M4P2, M5P2) was above 95%. The cyclic adsorption and regeneration shows the stability of the adsorbent materials.

Keywords: activated carbon, palm shell-PEEK, regeneration, thermal

Procedia PDF Downloads 477