Search results for: Thermal images.
4888 A Phase Change Materials Thermal Storage for Ground-Source Heat Pumps: Computational Fluid Dynamics Analysis of Innovative Layouts
Authors: Emanuele Bonamente, Andrea Aquino, Franco Cotana
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The exploitation of the low-temperature geothermal resource via ground-source heat pumps is often limited by the high investment cost mainly due to borehole drilling. From the monitoring of a prototypal system currently used by a commercial building, it was found that a simple upgrade of the conventional layout, obtained including a thermal storage between the ground-source heat exchangers and the heat pump, can optimize the ground energy exploitation requiring for shorter/fewer boreholes. For typical applications, a reduction of up to 66% with respect to the conventional layout can be easily achieved. Results from the monitoring campaign of the prototype are presented in this paper, and upgrades of the thermal storage using phase change materials (PCMs) are proposed using computational fluid dynamics simulations. The PCM thermal storage guarantees an improvement of the system coefficient of performance both for summer cooling and winter heating (up to 25%). A drastic reduction of the storage volume (approx. 1/10 of the original size) is also achieved, making it possible to easily place it within the technical room, avoiding extra costs for underground displacement. A preliminary optimization of the PCM geometry is finally proposed.Keywords: computational fluid dynamics (CFD), geothermal energy, ground-source heat pumps, phase change materials (PCM)
Procedia PDF Downloads 2674887 Estimating Leaf Area and Biomass of Wheat Using UAS Multispectral Remote Sensing
Authors: Jackson Parker Galvan, Wenxuan Guo
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Unmanned aerial vehicle (UAV) technology is being increasingly adopted in high-throughput plant phenotyping for applications in plant breeding and precision agriculture. Winter wheat is an important cover crop for reducing soil erosion and protecting the environment in the Southern High Plains. Efficiently quantifying plant leaf area and biomass provides critical information for producers to practice site-specific management of crop inputs, such as water and fertilizers. The objective of this study was to estimate wheat biomass and leaf area index using UAV images. This study was conducted in an irrigated field in Garza County, Texas. High-resolution images were acquired on three dates (February 18, March 25, and May 15th ) using a multispectral sensor onboard a Matrice 600 UAV. On each data of image acquisition, 10 random plant samples were collected and measured for biomass and leaf area. Images were stitched using Pix4D, and ArcGIS was applied to overlay sampling locations and derive data for sampling locations.Keywords: precision agriculture, UAV plant phenotyping, biomass, leaf area index, winter wheat, southern high plains
Procedia PDF Downloads 954886 Investigating the Effects of Thermal and Surface Energy on the Two-Dimensional Flow Characteristics of Oil in Water Mixture between Two Parallel Plates: A Lattice Boltzmann Method Study
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A hybrid quasi-steady thermal lattice Boltzmann model was used to study the combined effects of temperature and contact angle on the movement of slugs and droplets of oil in water (O/W) system flowing between two parallel plates. The model static contact angle due to the deposition of the O/W droplet on a flat surface with simulated hydrophilic characteristic at different fluid temperatures, matched very well the proposed theoretical calculation. Furthermore, the model was used to simulate the dynamic behavior of droplets and slugs deposited on the domain’s upper and lower surfaces, while subjected to parabolic flow conditions. The model accurately simulated the contact angle hysteresis for the dynamic droplets cases. It was also shown that at elevated temperatures the required power to transport the mixture diminished remarkably.Keywords: lattice Boltzmann method, Gunstensen model, thermal, contact angle, high viscosity ratio
Procedia PDF Downloads 3694885 Speed up Vector Median Filtering by Quasi Euclidean Norm
Authors: Vinai K. Singh
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For reducing impulsive noise without degrading image contours, median filtering is a powerful tool. In multiband images as for example colour images or vector fields obtained by optic flow computation, a vector median filter can be used. Vector median filters are defined on the basis of a suitable distance, the best performing distance being the Euclidean. Euclidean distance is evaluated by using the Euclidean norms which is quite demanding from the point of view of computation given that a square root is required. In this paper an optimal piece-wise linear approximation of the Euclidean norm is presented which is applied to vector median filtering.Keywords: euclidean norm, quasi euclidean norm, vector median filtering, applied mathematics
Procedia PDF Downloads 4744884 The Effect of Impinging WC-12Co Particles Temperature on Thickness of HVOF Thermally Sprayed Coatings
Authors: M. Jalali Azizpour
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In this paper, the effect of WC-12Co particle Temperature in HVOF thermal spraying process on the coating thickness has been studied. The statistical results show that the spray distance and oxygen-to-fuel ratio are more effective factors on particle characterization and thickness of HVOF thermal spraying coatings. Spray Watch diagnostic system, scanning electron microscopy (SEM), X-ray diffraction and thickness measuring system were used for this purpose.Keywords: HVOF, temperature thickness, velocity, WC-12Co
Procedia PDF Downloads 2414883 Development of Al-5%Cu/Si₃N₄, B₄C or BN Composites for Piston Applications
Authors: Ahmed Lotfy, Andrey V. Pozdniakov, Vadim C. Zolotorevskiy
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The purpose of this research is to provide a competitive alternative to aluminum silicon alloys used in automotive applications. This alternative was created by developing three types of composites Al-5%Cu- (B₄C, BN or Si₃N₄) particulates with a low coefficient of thermal expansion. Stir casting was used to synthesis composites containing 2, 5 and 7 wt. % of B₄C, Si₃N₄ and 2, 5 of BN followed by squeeze casting. The squeeze casting process decreased the porosity of the final composites. The composites exhibited a fairly uniform particle distribution throughout the matrix alloy. The microstructure and XRD results of the composites suggested a significant reaction occurred at the interface between the particles and alloy. Increasing the aging temperature from 200 to 250°C decreased the hardness values of the matrix and the composites and decreased the time required to reach the peak. Turner model was used to calculate the expected values of thermal expansion coefficient CTE of matrix and its composites. Deviations between calculated and experimental values of CTE were not exceeded 10%. Al-5%Cu-B₄C composites experimentally showed the lowest values of CTE (17-19)·10-6 °С-1 and (19-20) ·10-6 °С-1 in the temperature range 20-100 °С and 20-200 °С respectively.Keywords: aluminum matrix composites, coefficient of thermal expansion, X-ray diffraction, squeeze casting, electron microscopy,
Procedia PDF Downloads 4084882 Characterization of Biodegradable Polycaprolactone Containing Titanium Dioxide Micro and Nanoparticles
Authors: Emi Govorčin Bajsića, Vesna Ocelić Bulatović, Miroslav Slouf, Ana Šitum
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Composites based on a biodegradable polycaprolactone (PCL) containing 0.5, 1.0 and 2.0 wt % of titanium dioxide (TiO2) micro and nanoparticles were prepared by melt mixing and the effect of filler type and contents on the thermal properties, dynamic-mechanical behaviour and morphology were investigated. Measurements of storage modulus and loss modulus by dynamic mechanical analysis (DMA) showed better results for microfilled PCL/TiO2 composites than nanofilled composites, with the same filler content. DSC analysis showed that the Tg and Tc of micro and nanocomposites were slightly lower than those of neat PCL. The crystallinity of the PCL increased with the addition of TiO2 micro and nanoparticles; however, the c for the PCL was unchanged with micro TiO2 content. The thermal stability of PCL/TiO2 composites were characterized using thermogravimetric analysis (TGA). The initial weight loss (5 wt %) occurs at slightly higher temperature with micro and nano TiO2 addition and with increasing TiO2 content.Keywords: polycaprolactone, titanium dioxide, thermal properties, morphology
Procedia PDF Downloads 3624881 Manufacturing New Insulating Materials: A Study on Thermal Properties of Date Palm Wood
Authors: K. Almi, S. Lakel, A. Benchabane, A. Kriker
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The fiber–matrix compatibility can be improved if suitable enforcements are chosen. Whenever the reinforcements have more thermal stability, they can resist to the main processes for wood–thermoplastic composites. Several researches are focused on natural resources for the production of biomaterials intended for technical applications. Date palm wood present one of the world’s most important natural resource. Its use as insulating materials will help to solve the severe environmental and recycling problems which other artificial insulating materials caused. This paper reports the results of an experimental investigation on the thermal proprieties of date palm wood from Algeria. A study of physical, chemical and mechanical properties is also carried out. The goal is to use this natural material in the manufacture of thermal insulation materials for buildings. The local natural resources used in this study are the date palm fibers from Biskra oasis in Algeria. The results have shown that there is no significant difference in the morphological proprieties of the four types of residues. Their chemical composition differed slightly; with the lowest amounts of cellulose and lignin content belong to Petiole. Water absorption study proved that Rachis has a low value of sorption whereas Petiole and Fibrillium have a high value of sorption what influenced their mechanical properties. It is seen that the Rachis and leaflets exhibit a high tensile strength values compared to the other residue. On the other hand the low value of bulk density of Petiole and Fibrillium leads to high value of specific tensile strength and young modulus. It was found that the specific young modulus of Petiole and Fibrillium was higher than that of Rachis and Leaflets and that of other natural fibers or even artificial fibers. Compared to the other materials date palm wood provide a good thermal proprieties thus, date palm wood will be a good candidate for the manufacturing efficient and safe insulating materials.Keywords: composite materials, date palm fiber, natural fibers, tensile tests, thermal proprieties
Procedia PDF Downloads 6424880 Advances in Machine Learning and Deep Learning Techniques for Image Classification and Clustering
Authors: R. Nandhini, Gaurab Mudbhari
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Ranging from the field of health care to self-driving cars, machine learning and deep learning algorithms have revolutionized the field with the proper utilization of images and visual-oriented data. Segmentation, regression, classification, clustering, dimensionality reduction, etc., are some of the Machine Learning tasks that helped Machine Learning and Deep Learning models to become state-of-the-art models for the field where images are key datasets. Among these tasks, classification and clustering are essential but difficult because of the intricate and high-dimensional characteristics of image data. This finding examines and assesses advanced techniques in supervised classification and unsupervised clustering for image datasets, emphasizing the relative efficiency of Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), Deep Embedded Clustering (DEC), and self-supervised learning approaches. Due to the distinctive structural attributes present in images, conventional methods often fail to effectively capture spatial patterns, resulting in the development of models that utilize more advanced architectures and attention mechanisms. In image classification, we investigated both CNNs and ViTs. One of the most promising models, which is very much known for its ability to detect spatial hierarchies, is CNN, and it serves as a core model in our study. On the other hand, ViT is another model that also serves as a core model, reflecting a modern classification method that uses a self-attention mechanism which makes them more robust as this self-attention mechanism allows them to lean global dependencies in images without relying on convolutional layers. This paper evaluates the performance of these two architectures based on accuracy, precision, recall, and F1-score across different image datasets, analyzing their appropriateness for various categories of images. In the domain of clustering, we assess DEC, Variational Autoencoders (VAEs), and conventional clustering techniques like k-means, which are used on embeddings derived from CNN models. DEC, a prominent model in the field of clustering, has gained the attention of many ML engineers because of its ability to combine feature learning and clustering into a single framework and its main goal is to improve clustering quality through better feature representation. VAEs, on the other hand, are pretty well known for using latent embeddings for grouping similar images without requiring for prior label by utilizing the probabilistic clustering method.Keywords: machine learning, deep learning, image classification, image clustering
Procedia PDF Downloads 104879 Development of Real Time System for Human Detection and Localization from Unmanned Aerial Vehicle Using Optical and Thermal Sensor and Visualization on Geographic Information Systems Platform
Authors: Nemi Bhattarai
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In recent years, there has been a rapid increase in the use of Unmanned Aerial Vehicle (UAVs) in search and rescue (SAR) operations, disaster management, and many more areas where information about the location of human beings are important. This research will primarily focus on the use of optical and thermal camera via UAV platform in real-time detection, localization, and visualization of human beings on GIS. This research will be beneficial in disaster management search of lost humans in wilderness or difficult terrain, detecting abnormal human behaviors in border or security tight areas, studying distribution of people at night, counting people density in crowd, manage people flow during evacuation, planning provisions in areas with high human density and many more.Keywords: UAV, human detection, real-time, localization, visualization, haar-like, GIS, thermal sensor
Procedia PDF Downloads 4654878 Real Time Ultrasoft Transverse Photons Self Energy at Next To-Leading Order in Hot Scalar Quantum Electrodynamics
Authors: Karima Bouakaz, Amel Youcefi, Abdessamad Abada
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We determine a compact analytic expression for the complete next-to-leading contribution to the retarded transverse photons self-energy in the context of hard-thermal-loop summed perturbation of massless quantum electrodynamics (QED) at high temperature to calculate the next-to-leading order dispersion relations for slow-moving transverse photons at high temperature scalar quantum electrodynamics (Scalar QED), using the real time formalism (RTF) in physical representation. We derive the analytic expressions of hard thermal loop (HTL) contributions to propagators and vertices to determine the expressions of the effective propagators and vertices in RTF that contribute to the complete next-to leading order contribution of retarded transverse photons self-energy.Keywords: hard thermal loop, hot scalar QED, NLO computations, soft transverse photons
Procedia PDF Downloads 814877 A Case Study of Deep Learning for Disease Detection in Crops
Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell
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In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture
Procedia PDF Downloads 2594876 LES Simulation of a Thermal Plasma Jet with Modeled Anode Arc Attachment Effects
Authors: N. Agon, T. Kavka, J. Vierendeels, M. Hrabovský, G. Van Oost
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A plasma jet model was developed with a rigorous method for calculating the thermophysical properties of the gas mixture without mixing rules. A simplified model approach to account for the anode effects was incorporated in this model to allow the valorization of the simulations with experimental results. The radial heat transfer was under-predicted by the model because of the limitations of the radiation model, but the calculated evolution of centerline temperature, velocity and gas composition downstream of the torch exit corresponded well with the measured values. The CFD modeling of thermal plasmas is either focused on development of the plasma arc or the flow of the plasma jet outside of the plasma torch. In the former case, the Maxwell equations are coupled with the Navier-Stokes equations to account for electromagnetic effects which control the movements of the anode arc attachment. In plasma jet simulations, however, the computational domain starts from the exit nozzle of the plasma torch and the influence of the arc attachment fluctuations on the plasma jet flow field is not included in the calculations. In that case, the thermal plasma flow is described by temperature, velocity and concentration profiles at the torch exit nozzle and no electromagnetic effects are taken into account. This simplified approach is widely used in literature and generally acceptable for plasma torches with a circular anode inside the torch chamber. The unique DC hybrid water/gas-stabilized plasma torch developed at the Institute of Plasma Physics of the Czech Academy of Sciences on the other hand, consists of a rotating anode disk, located outside of the torch chamber. Neglecting the effects of the anode arc attachment downstream of the torch exit nozzle leads to erroneous predictions of the flow field. With the simplified approach introduced in this model, the Joule heating between the exit nozzle and the anode attachment position of the plasma arc is modeled by a volume heat source and the jet deflection caused by the anode processes by a momentum source at the anode surface. Furthermore, radiation effects are included by the net emission coefficient (NEC) method and diffusion is modeled with the combined diffusion coefficient method. The time-averaged simulation results are compared with numerous experimental measurements. The radial temperature profiles were obtained by spectroscopic measurements at different axial positions downstream of the exit nozzle. The velocity profiles were evaluated from the time-dependent evolution of flow structures, recorded by photodiode arrays. The shape of the plasma jet was compared with charge-coupled device (CCD) camera pictures. In the cooler regions, the temperature was measured by enthalpy probe downstream of the exit nozzle and by thermocouples in radial direction around the torch nozzle. The model results correspond well with the experimental measurements. The decrease in centerline temperature and velocity is predicted within an acceptable range and the shape of the jet closely resembles the jet structure in the recorded images. The temperatures at the edge of the jet are underestimated due to the absence of radial radiative heat transfer in the model.Keywords: anode arc attachment, CFD modeling, experimental comparison, thermal plasma jet
Procedia PDF Downloads 3674875 Communication About Health and Fitness in Media and Its Hidden Message About Objectification
Authors: Emiko Suzuki
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Although fitness is defined as the body’s ability to respond to the demand of physical activity without undue fatigue in health science, in media oftentimes physical activity is presented as means to an attractive body rather than a fit and healthy one. Of all types of media, Instagram is becoming an increasingly persuasive source of information and advice on health and fitness, where individuals conceptualize what health and fitness mean for them. However, this user-generated and unregulated platform can be problematic, as it can communicate misleading information about health and fitness and possibly leading individuals to psychological problems such as eating disorders. In fact, previous research has shown that some messages that were posted with a tag that related to inspire others to do fitness, in fact, encouraged distancing the self from the internal needs of the body. For this reason, this present study aims to explore how health and fitness are communicated on Instagram by analyzing images and texts. A content analysis of images that were labeled with particular hashtags was performed, followed by a thematic analysis of texts from the same set of images. The result shows an interesting insight about messages about how health and fitness are communicated from companies through media, then digested and further shared among communities on Instagram. The study explores how the use of visual focused way of communicating health and fitness can lead to the dehumanization of human bodies.Keywords: Instagram, fitness, dehumanization, body image, embodiment
Procedia PDF Downloads 1384874 Image Enhancement of Histological Slides by Using Nonlinear Transfer Function
Authors: D. Suman, B. Nikitha, J. Sarvani, V. Archana
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Histological slides provide clinical diagnostic information about the subjects from the ancient times. Even with the advent of high resolution imaging cameras the image tend to have some background noise which makes the analysis complex. A study of the histological slides is done by using a nonlinear transfer function based image enhancement method. The method processes the raw, color images acquired from the biological microscope, which, in general, is associated with background noise. The images usually appearing blurred does not convey the intended information. In this regard, an enhancement method is proposed and implemented on 50 histological slides of human tissue by using nonlinear transfer function method. The histological image is converted into HSV color image. The luminance value of the image is enhanced (V component) because change in the H and S components could change the color balance between HSV components. The HSV image is divided into smaller blocks for carrying out the dynamic range compression by using a linear transformation function. Each pixel in the block is enhanced based on the contrast of the center pixel and its neighborhood. After the processing the V component, the HSV image is transformed into a colour image. The study has shown improvement of the characteristics of the image so that the significant details of the histological images were improved.Keywords: HSV space, histology, enhancement, image
Procedia PDF Downloads 3294873 Experimental Investigation and Optimization of Nanoparticle Mass Concentration and Heat Input of Loop Heat Pipe
Authors: P. Gunnasegaran, M. Z. Abdullah, M. Z. Yusoff, Nur Irmawati
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This study presents experimental and optimization of nanoparticle mass concentration and heat input based on the total thermal resistance (Rth) of loop heat pipe (LHP), employed for PC-CPU cooling. In this study, silica nanoparticles (SiO2) in water with particle mass concentration ranged from 0% (pure water) to 1% is considered as the working fluid within the LHP. The experimental design and optimization is accomplished by the design of the experimental tool, Response Surface Methodology (RSM). The results show that the nanoparticle mass concentration and the heat input have a significant effect on the Rth of LHP. For a given heat input, the Rth is found to decrease with the increase of the nanoparticle mass concentration up to 0.5% and increased thereafter. It is also found that the Rth is decreased when the heat input is increased from 20W to 60W. The results are optimized with the objective of minimizing the Rt, using Design-Expert software, and the optimized nanoparticle mass concentration and heat input are 0.48% and 59.97W, respectively, the minimum thermal resistance being 2.66(ºC/W).Keywords: loop heat pipe, nanofluid, optimization, thermal resistance
Procedia PDF Downloads 4614872 Theoretical Performance of a Sustainable Clean Energy On-Site Generation Device to Convert Consumers into Producers and Its Possible Impact on Electrical National Grids
Authors: Eudes Vera
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In this paper, a theoretical evaluation is carried out of the performance of a forthcoming fuel-less clean energy generation device, the Air Motor. The underlying physical principles that support this technology are succinctly described. Examples of the machine and theoretical values of input and output powers are also given. In addition, its main features like portability, on-site energy generation and delivery, miniaturization of generation plants, efficiency, and scaling down of the whole electric infrastructure are discussed. The main component of the Air Motor, the Thermal Air Turbine, generates useful power by converting in mechanical energy part of the thermal energy contained in a fan-produced airflow while leaving intact its kinetic energy. Due to this fact an air motor can contain a long succession of identical air turbines and the total power generated out of a single airflow can be very large, as well as its mechanical efficiency. It is found using the corresponding formulae that the mechanical efficiency of this device can be much greater than 100%, while its thermal efficiency is always less than 100%. On account of its multiple advantages, the Air Motor seems to be the perfect device to convert energy consumers into energy producers worldwide. If so, it would appear that current national electrical grids would no longer be necessary, because it does not seem practical or economical to bring the energy from far-away distances while it can be generated and consumed locally at the consumer’s premises using just the thermal energy contained in the ambient air.Keywords: electrical grid, clean energy, renewable energy, in situ generation and delivery, generation efficiency
Procedia PDF Downloads 1754871 A Step-by-Step Analytical Protocol For Detecting and Identifying Minor Differences In Like Materials and Polymers Using Pyrolysis -Gas Chromatography/Mass Spectrometry Technique
Authors: Athena Nguyen, Rojin Belganeh
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Detecting and identifying differences in like polymer materials are key factors in failure and deformulation analysis, and reverse engineering. Pyrolysis-GC/MS is an easy solid sample introduction technique which expands the application areas of gas chromatography and mass spectrometry. The Micro furnace pyrolyzer is directly interfaced with the GC injector preventing any potential of cold spot, carryover, and cross contamination. In this presentation, the analysis of the differences in three polystyrene samples is demonstrated. Although the three samples look very similar by Evolve gas analysis (EGA) and Flash pyrolysis, there are indications of small levels of other materials. By performing Thermal desorption-GC/MS, the additive compounds between samples show the differences. EGA, flash pyrolysis, and thermal desorption analysis are the different modes of operations of the micro-furnace pyrolyzer enabling users to perform multiple analytical techniques.Keywords: Gas chromatography/Mass spectrometry, pyrolysis, pyrolyzer, thermal desorption-GC/MS
Procedia PDF Downloads 1874870 An Extraction of Cancer Region from MR Images Using Fuzzy Clustering Means and Morphological Operations
Authors: Ramandeep Kaur, Gurjit Singh Bhathal
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Cancer diagnosis is very difficult task. Magnetic resonance imaging (MRI) scan is used to produce image of any part of the body and provides an efficient way for diagnosis of cancer or tumor. In existing method, fuzzy clustering mean (FCM) is used for the diagnosis of the tumor. In the proposed method FCM is used to diagnose the cancer of the foot. FCM finds the centroids of the clusters of the foot cancer obtained from MRI images. FCM thresholding result shows the extract region of the cancer. Morphological operations are applied to get extracted region of cancer.Keywords: magnetic resonance imaging (MRI), fuzzy C mean clustering, segmentation, morphological operations
Procedia PDF Downloads 3984869 Mammographic Multi-View Cancer Identification Using Siamese Neural Networks
Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin
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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network
Procedia PDF Downloads 1384868 Termite Brick Temperature and Relative Humidity by Continuous Monitoring Technique
Authors: Khalid Abdullah Alshuhail, Syrif Junidi, Ideisan Abu-Abdoum, Abdulsalam Aldawoud
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For the intention of reducing energy consumption, a proposed construction brick was made of imitation termite mound soil referred here as termite brick (TB). To calculate the thermal performance, a real case model was constructed by using this biomimetic brick for testing purposes. This paper aims at investigating the thermal performance of this brick during different climatic months. Its thermal behaviour was thoroughly studied over the course of four months by using continuous method (CMm). The main parameters were focused on temperature and relative humidity. It was found that the TB does not perform similarly in all four months and/or in all orientations. Each four-month model study was deeply analyzed. By using the CMm method, the model was also examined. The measuring period shows generally that internal temperature and internal humidity are higher in the roof within 2 degrees and lowest at north wall orientation. The relative humidity was also investigated systematically. The paper reveals more interesting findings.Keywords: building material, continious monitoring, orientation, wall, temprature
Procedia PDF Downloads 1234867 Effects of Thermal Radiation on Mixed Convection in a MHD Nanofluid Flow over a Stretching Sheet Using a Spectral Relaxation Method
Authors: Nageeb A. H. Haroun, Sabyasachi Mondal, Precious Sibanda
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The effects of thermal radiation, Soret and Dufour parameters on mixed convection and nanofluid flow over a stretching sheet in the presence of a magnetic field are investigated. The flow is subject to temperature dependent viscosity and a chemical reaction parameter. It is assumed that the nanoparticle volume fraction at the wall may be actively controlled. The physical problem is modelled using systems of nonlinear differential equations which have been solved numerically using a spectral relaxation method. In addition to the discussion on heat and mass transfer processes, the velocity, nanoparticles volume fraction profiles as well as the skin friction coefficient are determined for different important physical parameters. A comparison of current findings with previously published results for some special cases of the problem shows an excellent agreement.Keywords: non-isothermal wedge, thermal radiation, nanofluid, magnetic field, soret and dufour effects
Procedia PDF Downloads 2354866 Characterization and Antimicrobial Properties of Functional Polypropylene Films Incorporated with AgSiO2, AgZn, and AgZ Useful as Returnable Packaging in Seafood Distribution
Authors: Suman Singh, Myungho Lee, Insik Park, Yangjai Shin, Youn Suk Lee
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Active antimicrobial films prepared by incorporating AgSiO2, AgZn, and AgZ at 1%, 3%, 5%, 10% (w/w) into polypropylene (PP) matrix. Complete thermal, structural, mechanical and functional characterization were carried out of all formulations and determined the antimicrobial efficiency and returnable antimicrobial efficiency according to the Japanese Industrial Standard method. The morphology of the films showed agglomerates of particles in the composites. The active formulation had decreased elongation compared to the pure PP sample. Thermal analyses indicated that the active formulation compositions had increased thermal stability. The films showed 50% antimicrobial properties after the fifth wash against the tested microorganisms, presenting better activity against Gram negative organisms than Gram positive ones. These findings suggest that PP films with AgSiO2, AgZn, and AgZ particles could provide a significant contribution to the quality and safety of seafood in the distribution chain.Keywords: antimicrobial film, properties and characterization, returnable packaging, sea food
Procedia PDF Downloads 3644865 Archetypes in the Rorschach Inkblots: Imparting Universal Meaning in the Face of Ambiguity
Authors: Donna L. Roberts
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The theory of archetypes contends that themes based on universal foundational images reside in and are transmitted generationally through the collective unconscious, which is referenced throughout an individual’s experience in order to make sense of that experience. There is then, a profoundly visceral and instinctive agreement on the gestalt of these universal themes and how they apply to the human condition throughout space and time. The inherent nature of projective tests, such as the Rorschach Inkblot, necessitates that the stimulus is ambiguous and thus elicits responses that reflect the unconscious inner psyche of the respondent. As the development of the Rorschach inkblots was relatively random and serendipitous - i.e., the inkblots were not engineered to elicit a specifically defined response - it would stand to reason that without a collective unconscious, every individual would interpret the inkblots in an individualized and unique way. Yet this is not the case. Instead, common themes appear in the images of the inkblots and their interpretation that reflect this deeper iconic understanding. This study analyzed the ten Rorschach inkblots in terms of Jungian archetypes, both with respect to the form of images on each plate and the commonly observed themes in responses. Examples of the archetypes were compared to each of the inkblots, with subsequent descriptions matched to the standard responses. The findings yielded clear and distinct instances of the universal symbolism intrinsic in the inkblot images as well as ubiquitous throughout the responses. This project illustrates the influence of the theories of psychologist Carl Gustav Jung on the interpretation of the ambiguous stimuli. It further serves to demonstrate the merit of Jungian psychology as a valuable tool with which to understand the nature of projective tests in general, Rorschach’s work specifically, and ultimately the broader implications for our collective unconscious and common humanity.Keywords: archetypes, inkblots, projective tests, Rorschach
Procedia PDF Downloads 1064864 An Experiment of Three-Dimensional Point Clouds Using GoPro
Authors: Jong-Hwa Kim, Mu-Wook Pyeon, Yang-dam Eo, Ill-Woong Jang
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Construction of geo-spatial information recently tends to develop as multi-dimensional geo-spatial information. People constructing spatial information is also expanding its area to the general public from some experts. As well as, studies are in progress using a variety of devices, with the aim of near real-time update. In this paper, getting the stereo images using GoPro device used widely also to the general public as well as experts. And correcting the distortion of the images, then by using SIFT, DLT, is acquired the point clouds. It presented a possibility that on the basis of this experiment, using a video device that is readily available in real life, to create a real-time digital map.Keywords: GoPro, SIFT, DLT, point clouds
Procedia PDF Downloads 4694863 Thermal Characterization of Smart and Large-Scale Building Envelope System in a Subtropical Climate
Authors: Andrey A. Chernousov, Ben Y. B. Chan
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The thermal behavior of a large-scale, phase change material (PCM) enhanced building envelope system was studied in regard to the need for pre-fabricated construction in subtropical regions. The proposed large-scale envelope consists of a reinforced aluminum skin, insulation core, phase change material and reinforced gypsum board. The PCM impact on an energy efficiency of an enveloped room was resolved by validation of the Energy Plus numerical scheme and optimization of a smart material location in the core. The PCM location was optimized by a minimization method of a cooling energy demand. It has been shown that there is good agreement between the test and simulation results. The optimal location of the PCM layer in Hong Kong summer conditions has been then recomputed for core thicknesses of 40, 60 and 80 mm. A non-dimensional value of the optimal PCM location was obtained to be same for all the studied cases and the considered external and internal conditions.Keywords: thermal performance, phase change material, energy efficiency, PCM optimization
Procedia PDF Downloads 4024862 Secure Image Encryption via Enhanced Fractional Order Chaotic Map
Authors: Ismail Haddad, Djamel Herbadji, Aissa Belmeguenai, Selma Boumerdassi
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in this paper, we provide a novel approach for image encryption that employs the Fibonacci matrix and an enhanced fractional order chaotic map. The enhanced map overcomes the drawbacks of the classical map, especially the limited chaotic range and non-uniform distribution of chaotic sequences, resulting in a larger encryption key space. As a result, this strategy improves the encryption system's security. Our experimental results demonstrate that our proposed algorithm effectively encrypts grayscale images with exceptional efficiency. Furthermore, our technique is resistant to a wide range of potential attacks, including statistical and entropy attacks.Keywords: image encryption, logistic map, fibonacci matrix, grayscale images
Procedia PDF Downloads 3184861 Designing Agricultural Irrigation Systems Using Drone Technology and Geospatial Analysis
Authors: Yongqin Zhang, John Lett
Abstract:
Geospatial technologies have been increasingly used in agriculture for various applications and purposes in recent years. Unmanned aerial vehicles (drones) fit the needs of farmers in farming operations, from field spraying to grow cycles and crop health. In this research, we conducted a practical research project that used drone technology to design and map optimal locations and layouts of irrigation systems for agriculture farms. We flew a DJI Mavic 2 Pro drone to acquire aerial remote sensing images over two agriculture fields in Forest, Mississippi, in 2022. Flight plans were first designed to capture multiple high-resolution images via a 20-megapixel RGB camera mounted on the drone over the agriculture fields. The Drone Deploy web application was then utilized to develop flight plans and subsequent image processing and measurements. The images were orthorectified and processed to estimate the area of the area and measure the locations of the water line and sprinkle heads. Field measurements were conducted to measure the ground targets and validate the aerial measurements. Geospatial analysis and photogrammetric measurements were performed for the study area to determine optimal layout and quantitative estimates for irrigation systems. We created maps and tabular estimates to demonstrate the locations, spacing, amount, and layout of sprinkler heads and water lines to cover the agricultural fields. This research project provides scientific guidance to Mississippi farmers for a precision agricultural irrigation practice.Keywords: drone images, agriculture, irrigation, geospatial analysis, photogrammetric measurements
Procedia PDF Downloads 754860 Properties of Ettringite According to Hydration, Dehydration and Carbonation Process
Authors: Bao Chen, Frederic Kuznik, Matthieu Horgnies, Kevyn Johannes, Vincent Morin, Edouard Gengembre
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The contradiction between energy consumption, environment protection, and social development is increasingly intensified during recent decade years. At the same time, as avoiding fossil-fuels-thirsty, people turn their view on the renewable green energy, such as solar energy, wind power, hydropower, etc. However, due to the unavoidable mismatch on geography and time for production and consumption, energy storage seems to be one of the most reasonable solutions to enlarge the use of renewable energies. Thermal energy storage (TES), a branch of energy storage solution, mainly concerns the capture, storage and consumption of thermal energy for later use in different scales (individual house, apartment, district, and city). In TES research field, sensible heat and latent heat storage have been widely studied and presented at an advanced stage of development. Compared with them, thermochemical energy storage is still at initial phase but provides a relatively higher theoretical energy density and a long shelf life without heat dissipation during storage. Among thermochemical energy storage materials, inorganic pure or composite compounds like micro-porous silica gel, SrBr₂ hydrate and MgSO₄-Zeolithe have been reported as promising to be integrated into thermal energy storage systems. However, the cost of these materials, one of main obstacles, may hinder the wide use of energy storage systems in real application scales (individual house, apartment, district and even city). New studies on ettringite show promising application for thermal energy storage since its high energy density and large resource from cementitious materials. Ettringite, or calcium trisulfoaluminate hydrate, of which chemical formula is 3CaO∙Al₂O₃∙3CaSO₄∙32H₂O, or C₆AS̅₃H₃₂ as known in cement chemistry notation, is one of the most important members of AFt group. As a common compound in hydrated cements, ettringite has been widely studied for its performances in construction but barely known as a thermochemical material. For this study, we summarize available data about the structure and properties of ettringite and its metastable phase (meta-ettringite), including the processes of hydration, thermal conversion and carbonation durability for thermal energy storage.Keywords: building materials, ettringite, meta-ettringite, thermal energy storage
Procedia PDF Downloads 2144859 A General Framework for Knowledge Discovery Using High Performance Machine Learning Algorithms
Authors: S. Nandagopalan, N. Pradeep
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The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.Keywords: active contour, bayesian, echocardiographic image, feature vector
Procedia PDF Downloads 420