Search results for: fine bubbles
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1058

Search results for: fine bubbles

578 Tidal Current Behaviors and Remarkable Bathymetric Change in the South-Western Part of Khor Abdullah, Kuwait

Authors: Ahmed M. Al-Hasem

Abstract:

A study of the tidal current behavior and bathymetric changes was undertaken in order to establish an information base for future coastal management. The average velocity for tidal current was 0.46 m/s and the maximum velocity was 1.08 m/s during ebb tide. During spring tides, maximum velocities range from 0.90 m/s to 1.08 m/s, whereas maximum velocities vary from 0.40 m/s to 0.60 m/s during neap tides. Despite greater current velocities during flood tide, the bathymetric features enhance the dominance of the ebb tide. This can be related to the abundance of fine sediments from the ebb current approaching the study area, and the relatively coarser sediment from the approaching flood current. Significant bathymetric changes for the period from 1985 to 1998 were found with dominance of erosion process. Approximately 96.5% of depth changes occurred within the depth change classes of -5 m to 5 m. The high erosion processes within the study area will subsequently result in high accretion processes, particularly in the north, the location of the proposed Boubyan Port and its navigation channel.

Keywords: bathymetric change, Boubyan island, GIS, Khor Abdullah, tidal current behavior

Procedia PDF Downloads 269
577 Multimodal Convolutional Neural Network for Musical Instrument Recognition

Authors: Yagya Raj Pandeya, Joonwhoan Lee

Abstract:

The dynamic behavior of music and video makes it difficult to evaluate musical instrument playing in a video by computer system. Any television or film video clip with music information are rich sources for analyzing musical instruments using modern machine learning technologies. In this research, we integrate the audio and video information sources using convolutional neural network (CNN) and pass network learned features through recurrent neural network (RNN) to preserve the dynamic behaviors of audio and video. We use different pre-trained CNN for music and video feature extraction and then fine tune each model. The music network use 2D convolutional network and video network use 3D convolution (C3D). Finally, we concatenate each music and video feature by preserving the time varying features. The long short term memory (LSTM) network is used for long-term dynamic feature characterization and then use late fusion with generalized mean. The proposed network performs better performance to recognize the musical instrument using audio-video multimodal neural network.

Keywords: multimodal, 3D convolution, music-video feature extraction, generalized mean

Procedia PDF Downloads 193
576 Suburban Large Residential Area Development Strategy with an Example of Liangzhu Culture Village in Hangzhou

Authors: Liang Fang

Abstract:

The development of the large suburban residential area is a product of the leap development during the rapid urbanization process in China. On the process of the large-scale development of large settlements in a short time, various problems arose in the suburban residential area, such as spatial layout being disorder, basic facilities construction lagging behind and being unreasonable, residential neighborhood space and street culture missing. Aimed at the contradictions mentioned above, exploring a way is imminent to construct appropriate residential area. We select a typical Liangzhu Culture Village in Hangzhou and put forward functional composite residential area of fine development strategy, along which business promotes and assists community autonomy and then a good community culture is constructed. All in all, the development and construction mode, contributing to an all-people and full-time participation, is beneficial to create a harmonious community of sustainable development, which gives good implication to a single enterprise development city real estate projects.

Keywords: community autonomy, development and construction mode, functional composite, suburban large residential area

Procedia PDF Downloads 335
575 Turbulence Modeling of Source and Sink Flows

Authors: Israt Jahan Eshita

Abstract:

Flows developed between two parallel disks have many engineering applications. Two types of non-swirling flows can be generated in such a domain. One is purely source flow in disc type domain (outward flow). Other is purely sink flow in disc type domain (inward flow). This situation often appears in some turbo machinery components such as air bearings, heat exchanger, radial diffuser, vortex gyroscope, disc valves, and viscosity meters. The main goal of this paper is to show the mesh convergence, because mesh convergence saves time, and economical to run and increase the efficiency of modeling for both sink and source flow. Then flow field is resolved using a very fine mesh near-wall, using enhanced wall treatment. After that we are going to compare this flow using standard k-epsilon, RNG k-epsilon turbulence models. Lastly compare some experimental data with numerical solution for sink flow. The good agreement of numerical solution with the experimental works validates the current modeling.

Keywords: hydraulic diameter, k-epsilon model, meshes convergence, Reynolds number, RNG model, sink flow, source flow, wall y+

Procedia PDF Downloads 513
574 A Fuzzy Approach to Liver Tumor Segmentation with Zernike Moments

Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy C-Means methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc).

Keywords: defuzzification, floating search, fuzzy clustering, Zernike moments

Procedia PDF Downloads 434
573 High Performance Fibre Reinforced Alkali Activated Slag Concrete

Authors: A. Sivakumar, K. Srinivasan

Abstract:

The main objective of the study is focused in producing slag based geopolymer concrete obtained with the addition of alkali activator. Test results indicated that the reaction of silicates in slag is based on the reaction potential of sodium hydroxide and the formation of alumino-silicates. The study also comprises on the evaluation of the efficiency of polymer reaction in terms of the strength gain properties for different geopolymer mixtures. Geopolymer mixture proportions were designed for different binder to total aggregate ratio (0.3 & 0.45) and fine to coarse aggregate ratio (0.4 & 0.8). Geopolymer concrete specimens casted with normal curing conditions reported a maximum 28 days compressive strength of 54.75 MPa. The addition of glued steel fibres at 1.0% Vf in geopolymer concrete showed reasonable improvements on the compressive strength, split tensile strength and flexural properties of different geopolymer mixtures. Further, comparative assessment was made for different geopolymer mixtures and the reinforcing effects of steel fibres were investigated in different concrete matrix.

Keywords: accelerators, alkali activators, geopolymer, hot air oven curing, polypropylene fibres, slag, steam curing, steel fibres

Procedia PDF Downloads 248
572 DOA Estimation Using Golden Section Search

Authors: Niharika Verma, Sandeep Santosh

Abstract:

DOA technique is a localization technique used in the communication field. Various algorithms have been developed for direction of arrival estimation like MUSIC, ROOT MUSIC, etc. These algorithms depend on various parameters like antenna array elements, number of snapshots and various others. Basically the MUSIC spectrum is evaluated and peaks obtained are considered as the angle of arrivals. The angles evaluated using this process depends on the scanning interval chosen. The accuracy of the results obtained depends on the coarseness of the interval chosen. In this paper, golden section search is applied to the MUSIC algorithm and therefore, more accurate results are achieved. Initially the coarse DOA estimations is done using the MUSIC algorithm in the range -90 to 90 degree at the interval of 10 degree. After the peaks obtained then fine DOA estimation is done using golden section search. Also, the partitioning method is applied to estimate the number of signals incident on the antenna array. Dependency of the algorithm on the number of snapshots is also being explained. Hence, the accurate results are being determined using this algorithm.

Keywords: Direction of Arrival (DOA), golden section search, MUSIC, number of snapshots

Procedia PDF Downloads 429
571 Utilization of Waste Marble Dust as a Viscosity Modifying Agent in Self Compacting Concrete

Authors: Shams Ul Khaliq, Mushtaq Zeb, Fawad Bilal, Faizan Akbar, Syed Aamir Abbas

Abstract:

Self Compacting Concrete as the name implies--is the concrete requiring a very little or no vibration to fill the form homogeneously. Self Compacting Concrete (SCC) is defined by two primary properties: Ability to flow or deform under its own weight (with or without obstructions) and the ability to remain homogeneous while doing so. Flow ability is achieved by utilizing high range water reducing admixtures and segregation resistance is ensured by introducing a chemical viscosity modifying admixture (VMA) or increasing the amount of fines in the concrete. The study explores the use waste marble dust (WMD) to increase the amount of fines and hence achieve self-compatibility in an economical way, suitable for Pakistani construction industry. The study focuses on comparison of fresh properties of SCC containing varying amounts of waste marble dust (WMD) with that containing commercially available viscosity modifying admixture. The comparison is done at different dosages of super plasticizer keeping cement, water, coarse aggregate, and fine aggregate contents constant.

Keywords: self compacting concrete, waste marble dust (WMD), flow ability, segregation resistance

Procedia PDF Downloads 298
570 Staphylococcus Aureus Septic Arthritis and Necrotizing Fasciitis in a Patient With Undiagnosed Diabetes Mellitus.

Authors: Pedro Batista, André Vinha, Filipe Castelo, Bárbara Costa, Ricardo Sousa, Raquel Ricardo, André Pinto

Abstract:

Background: Septic arthritis is a diagnosis that must be considered in any patient presenting with acute joint swelling and fever. Among the several risk factors for septic arthritis, such as age, rheumatoid arthritis, recent surgery, or skin infection, diabetes mellitus can sometimes be the main risk factor. Staphylococcus aureus is the most common pathogen isolated in septic arthritis; however, it is uncommon in monomicrobial necrotizing fasciitis. Objectives: A case report of concomitant septic arthritis and necrotizing fasciitis in a patient with undiagnosed diabetes based on clinical history. Study Design & Methods: We report a case of a 58-year-old Portuguese previously healthy man who presented to the emergency department with fever and left knee swelling and pain for two days. The blood work revealed ketonemia of 6.7 mmol/L and glycemia of 496 mg/dL. The vital signs were significant for a temperature of 38.5 ºC and 123 bpm of heart rate. The left knee had edema and inflammatory signs. Computed tomography of the left knee showed diffuse edema of the subcutaneous cellular tissue and soft tissue air bubbles. A diagnosis of septic arthritis and necrotising fasciitis was made. He was taken to the operating room for surgical debridement. The samples collected intraoperatively were sent for microbiological analysis, revealing infection by multi-sensitive Staphylococcus aureus. Given this result, the empiric flucloxacillin (500 mg IV) and clindamycin (1000 mg IV) were maintained for 3 weeks. On the seventh day of hospitalization, there was a significant improvement in subcutaneous and musculoskeletal tissues. After two weeks of hospitalization, there was no purulent content and partial closure of the wounds was possible. After 3 weeks, he was switched to oral antibiotics (flucloxacillin 500 mg). A week later, a urinary infection by Pseudomonas aeruginosa was diagnosed and ciprofloxacin 500 mg was administered for 7 days without complications. After 30 days of hospital admission, the patient was discharged home and recovered. Results: The final diagnosis of concomitant septic arthritis and necrotizing fasciitis was made based on the imaging findings, surgical exploration and microbiological tests results. Conclusions: Early antibiotic administration and surgical debridement are key in the management of septic arthritis and necrotizing fasciitis. Furthermore, risk factors control (euglycemic blood glucose levels) must always be taken into account given the crucial role in the patient's recovery.

Keywords: septic arthritis, Necrotizing fasciitis, diabetes, Staphylococcus Aureus

Procedia PDF Downloads 283
569 Numerical Study of Off-Design Performance of a Highly Loaded Low Pressure Turbine Cascade

Authors: Shidvash Vakilipour, Mehdi Habibnia, Rouzbeh Riazi, Masoud Mohammadi, Mohammad H. Sabour

Abstract:

The flow field passing through a highly loaded low pressure (LP) turbine cascade is numerically investigated at design and off-design conditions. The Field Operation And Manipulation (OpenFOAM) platform is used as the computational Fluid Dynamics (CFD) tool. Firstly, the influences of grid resolution on the results of k-ε, k-ω, and LES turbulence models are investigated and compared with those of experimental measurements. A numerical pressure under-shoot is appeared near the end of blade pressure surface which is sensitive to grid resolution and flow turbulence modeling. The LES model is able to resolve separation on a coarse and fine grid resolutions. Secondly, the off-design flow condition is modeled by negative and positive inflow incidence angles. The numerical experiments show that a separation bubble generated on blade pressure side is predicted by LES. The total pressure drop is also been calculated at incidence angle between -20◦ and +8◦. The minimum total pressure drop is obtained by k-ω and LES at the design point.

Keywords: low pressure turbine, off-design performance, openFOAM, turbulence modeling, flow separation

Procedia PDF Downloads 338
568 SEM Image Classification Using CNN Architectures

Authors: Güzi̇n Ti̇rkeş, Özge Teki̇n, Kerem Kurtuluş, Y. Yekta Yurtseven, Murat Baran

Abstract:

A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: convolutional neural networks, deep learning, image classification, scanning electron microscope

Procedia PDF Downloads 96
567 Waste Bone Based Catalyst: Characterization and Esterification Application

Authors: Amit Keshav

Abstract:

Waste bone, produced in large quantity (8-10 kg./day) from a slaughterhouse, could be a cheap (cost $0.20 per kg) substitute for commercial catalysts. In the present work, catalyst for esterification reaction was prepared from waste bone and characterized by various techniques. Bone was deoiled and then sulfonated. Fourier-transform infrared spectroscopy (FTIR) spectra of prepared catalyst predicted –OH vibration at 3416 and 1630 cm⁻¹, S-O stretching at 1124 cm⁻¹ and intense bands of hydroxypatite in a region between 500 and 700 cm⁻¹. X-ray diffraction (XRD) predicts peaks of hydroxyapatite, CaO, and tricalcium phosphate. Scanning electron microscope (SEM) was employed to reveal the presence of non-uniformity deposited fine particles on the catalyst surface that represents active acidic sites. The prepared catalyst was employed to study its performance on esterification reaction between acrylic acid and ethanol in a molar ratio of 1:1 at a set temperature of 60 °C. Results show an equilibrium conversion of 49% which is matched to the commercial catalysts employed in literature. Thus waste bone could be a good catalyst for acrylic acid removal from waste industrial streams via the process of esterification.Keywords— Heterogeneous catalyst, characterization, esterification, equilibrium conversion

Keywords: heterogeneous catalyst, characterization, esterification, equilibrium conversion

Procedia PDF Downloads 126
566 Texture Characteristics and Depositional Environment of the Lower Mahi River Sediment, Mainland Gujarat, India

Authors: Shazi Farooqui, Anupam Sharma

Abstract:

The Mahi River (~600km long) is an important west flowing the river of Central India. It originates in Madhya Pradesh and starts flowing in NW direction and enters into the state of Rajasthan. It flows across southern Rajasthan and then enters into Gujarat and finally debouches in the Gulf of Cambay. In Gujarat state, it flows through all four geomorphic zones i.e. eastern upland zone, shallow buried piedmont zone, alluvial zone and coastal zone. In lower reaches and particularly when it is flowing under the coastal regime, it provides an opportunity to study – 1. Land–Sea interaction and role of relative sea level changes, 2. Coastal/estuarine geological process, 3. Landscape evolution in marginal areas and so on. The Late Quaternary deposits of Mainland Gujarat is appreciably studied by Chamyal and his group of MS University of Baroda, and they have established that the 30-35m thick sediment package of the Mainland Gujarat is comprised of marine, fluvial and aeolian sediments. It is also established that in the estuarine zone, the upper few meter thick sediments package is of marine nature. However, its thickness, characters and the depositional environment including the role of climate and tectonics is still not clearly defined. To understand few aspects of the above mentioned, in the present study, a 17m subsurface sediment core has been retrieved from the estuarine zone of Mahi river basin. The Multiproxy studies which include the textural analysis (grain size), Loss on ignition (LOI), Bulk and clay mineralogy and geochemical studies have been carried out. In the entire sedimentary sequence, the grain size largely varies from coarse sand to clay; however, a solitary gravel bed is also noticed. The lower part (depth 9-17m), is mainly comprised of sub equal proportion of sand and silt. The sediments mainly have bimodal and leptokurtic distribution and deposited in alternate sand-silt package, probably indicating flood deposits. Relatively low moisture (1.8%) and organic carbon (2.4%) with increased carbonate values (12%) indicate that conditions must have to remain oxidizing. The middle part (depth 9–6m) has a 1m thick gravel bed at the bottom and overlain by coarse sand to very fine sand showing fining upward sequence. The presence of gravel bed suggests some kind of tectonic activity resulting into change in base level or enhanced precipitation in the catchment region. The upper part (depth 6–0m; top part of sequence) mainly comprised of fine sand to silt size grains (with appreciable clay content). The sediment of this part is Unimodal and very leptokurtic in nature suggesting wave and winnowing process and deposited in low energy suspension environment. This part has relatively high moisture (2.1%) and organic carbon (2.7%) with decreased carbonate content (4.2%) indicating change in the depositional environment probably under estuarine conditions. The presence of chlorite along with smectite clay mineral further supports the significant marine contribution in the formation of upper part of the sequence.

Keywords: grain size, statistical analysis, clay minerals, late quaternary, LOI

Procedia PDF Downloads 162
565 Hyperspectral Data Classification Algorithm Based on the Deep Belief and Self-Organizing Neural Network

Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

Abstract:

In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

Procedia PDF Downloads 321
564 Effect of Blast Furnace Iron Slag on the Mechanical Performance of Hot Mix Asphalt (HMA)

Authors: Ayman M. Othman, Hassan Y. Ahmed

Abstract:

This paper discusses the effect of using blast furnace iron slag as a part of fine aggregate on the mechanical performance of hot mix asphalt (HMA). The mechanical performance was evaluated based on various mechanical properties that include; Marshall/stiffness, indirect tensile strength and unconfined compressive strength. The effect of iron slag content on the mechanical properties of the mixtures was also investigated. Four HMA with various iron slag contents, namely; 0%, 5%, 10% and 15% by weight of total mixture were studied. Laboratory testing has revealed an enhancement in the compressive strength of HMA when iron slag was used. Within the tested range of iron slag content, a considerable increase in the compressive strength of the mixtures was observed with the increase of slag content. No significant improvement on Marshall/stiffness and indirect tensile strength of the mixtures was observed when slag was used. Even so, blast furnace iron slag can still be used in asphalt paving for environmental advantages.

Keywords: blast furnace iron slag, compressive strength, HMA, indirect tensile strength, marshall/stiffness, mechanical performance, mechanical properties

Procedia PDF Downloads 414
563 Modelling and Optimisation of Floating Drum Biogas Reactor

Authors: L. Rakesh, T. Y. Heblekar

Abstract:

This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

Procedia PDF Downloads 124
562 Subjective Quality Assessment for Impaired Videos with Varying Spatial and Temporal Information

Authors: Muhammad Rehan Usman, Muhammad Arslan Usman, Soo Young Shin

Abstract:

The new era of digital communication has brought up many challenges that network operators need to overcome. The high demand of mobile data rates require improved networks, which is a challenge for the operators in terms of maintaining the quality of experience (QoE) for their consumers. In live video transmission, there is a sheer need for live surveillance of the videos in order to maintain the quality of the network. For this purpose objective algorithms are employed to monitor the quality of the videos that are transmitted over a network. In order to test these objective algorithms, subjective quality assessment of the streamed videos is required, as the human eye is the best source of perceptual assessment. In this paper we have conducted subjective evaluation of videos with varying spatial and temporal impairments. These videos were impaired with frame freezing distortions so that the impact of frame freezing on the quality of experience could be studied. We present subjective Mean Opinion Score (MOS) for these videos that can be used for fine tuning the objective algorithms for video quality assessment.

Keywords: frame freezing, mean opinion score, objective assessment, subjective evaluation

Procedia PDF Downloads 468
561 Getting to Know the Types of Concrete and its Production Methods

Authors: Mokhtar Nikgoo

Abstract:

Definition of Concrete and Concreting: Concrete (in French: Béton) in a broad sense is any substance or combination that consists of a sticky substance with the property of cementation. In general, concrete refers to concrete made by Portland cement, which is produced by mixing fine and coarse aggregates, Portland cement and water. After enough time, this mixture turns into a stone-like substance. During the hardening or processing of the concrete, cement is chemically combined with water to form strong crystals that bind the aggregates together, a process called hydration. During this process, significant heat is released called hydration heat. Additionally, concrete shrinks slightly, especially as excess water evaporates, a phenomenon known as drying shrinkage. The process of hardening and the gradual increase in concrete strength that occurs with it does not end suddenly unless it is artificially interrupted. Instead, it decreases more over long periods of time, although, in practical applications, concrete is usually set after 28 days and is considered at full design strength. Concrete may be made from different types of cement as well as pozzolans, furnace slag, additives, additives, polymers, fibers, etc. It may also be used in the way it is made, heating, water vapor, autoclave, vacuum, hydraulic pressures and various condensers.

Keywords: concrete, RCC, batching, cement, Pozzolan, mixing plan

Procedia PDF Downloads 73
560 Convergence Analysis of a Gibbs Sampling Based Mix Design Optimization Approach for High Compressive Strength Pervious Concrete

Authors: Jiaqi Huang, Lu Jin

Abstract:

Pervious concrete features with high water permeability rate. However, due to the lack of fine aggregates, the compressive strength is usually lower than other conventional concrete products. Optimization of pervious concrete mix design has long been recognized as an effective mechanism to achieve high compressive strength while maintaining desired permeability rate. In this paper, a Gibbs Sampling based algorithm is proposed to approximate the optimal mix design to achieve a high compressive strength of pervious concrete. We prove that the proposed algorithm efficiently converges to the set of global optimal solutions. The convergence rate and accuracy depend on a control parameter employed in the proposed algorithm. The simulation results show that, by using the proposed approach, the system converges to the optimal solution quickly and the derived optimal mix design achieves the maximum compressive strength while maintaining the desired permeability rate.

Keywords: convergence, Gibbs Sampling, high compressive strength, optimal mix design, pervious concrete

Procedia PDF Downloads 156
559 Malignancy Assessment of Brain Tumors Using Convolutional Neural Network

Authors: Chung-Ming Lo, Kevin Li-Chun Hsieh

Abstract:

The central nervous system in the World Health Organization defines grade 2, 3, 4 gliomas according to the aggressiveness. For brain tumors, using image examination would have a lower risk than biopsy. Besides, it is a challenge to extract relevant tissues from biopsy operation. Observing the whole tumor structure and composition can provide a more objective assessment. This study further proposed a computer-aided diagnosis (CAD) system based on a convolutional neural network to quantitatively evaluate a tumor's malignancy from brain magnetic resonance imaging. A total of 30 grade 2, 43 grade 3, and 57 grade 4 gliomas were collected in the experiment. Transferred parameters from AlexNet were fine-tuned to classify the target brain tumors and achieved an accuracy of 98% and an area under the receiver operating characteristics curve (Az) of 0.99. Without pre-trained features, only 61% of accuracy was obtained. The proposed convolutional neural network can accurately and efficiently classify grade 2, 3, and 4 gliomas. The promising accuracy can provide diagnostic suggestions to radiologists in the clinic.

Keywords: convolutional neural network, computer-aided diagnosis, glioblastoma, magnetic resonance imaging

Procedia PDF Downloads 123
558 Machine Learning Invariants to Detect Anomalies in Secure Water Treatment

Authors: Jonathan Heng, Yoong Cheah Huei

Abstract:

A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

Procedia PDF Downloads 161
557 Ultrafine Non Water Soluble Drug Particles

Authors: Shahnaz Mansouri, David Martin, Xiao Dong Chen, Meng Wai Woo

Abstract:

Ultrafine hydrophobic and non-water-soluble drugs can increase the percentage of absorbed compared to their initial dosage. This paper provides a scalable new method of making ultrafine particles of substantially insoluble water compounds specifically, submicron particles of ethanol soluble and water insoluble pharmaceutical materials by steaming an ethanol droplet to prepare a suspension and then followed by immediate drying. This suspension is formed by adding evaporated water molecules as an anti-solvent to the solute of the samples and in early stage of precipitation continued to dry by evaporating both solvent and anti-solvent. This fine particle formation has produced fast dispersion powder in water. The new method is an extension of the antisolvent vapour precipitation technique which exposes a droplet to an antisolvent vapour with reference to the dissolved materials within the droplet. Ultrafine vitamin D3 and ibuprofen particles in the submicron ranges were produced. This work will form the basis for using spray dryers as high-throughput scalable micro-precipitators.

Keywords: single droplet drying, nano size particles, non-water-soluble drugs, precipitators

Procedia PDF Downloads 465
556 Effect of Equal Channel Angular Pressing Process on Impact Property of Pure Copper

Authors: Fahad Al-Mufadi, F. Djavanroodi

Abstract:

Ultrafine grained (UFG) and nanostructured (NS) materials have experienced a rapid development during the last decade and made profound impact on every field of materials science and engineering. The present work has been undertaken to develop ultra-fine grained pure copper by severe plastic deformation method and to examine the impact property by different characterizing tools. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90°, 17° and 20 mm had been designed and manufactured. Commercial pure copper billets were ECAPed up to four passes by route BC at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 136HV from 52HV after the final pass. Also, about 285% and 125% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by imposing ECAP process and pass numbers. It is needed to say that about 56% reduction in the impact energy have been attained for the samples as contrasted to annealed specimens.

Keywords: SPD, ECAP, pure cu, impact property

Procedia PDF Downloads 245
555 A Systamatic Review on Experimental, FEM Analysis and Simulation of Metal Spinning Process

Authors: Amol M. Jadhav, Sharad S. Chudhari, S. S. Khedkar

Abstract:

This review presents a through survey of research paper work on the experimental analysis, FEM Analysis & simulation of the metal spinning process. In this literature survey all the papers being taken from Elsevier publication and most of the from journal of material processing technology. In a last two decade or so, metal spinning process gradually used as chip less formation for the production of engineering component in a small to medium batch quantities. The review aims to provide include into the experimentation, FEM analysis of various components, simulation of metal spinning process and act as guide for research working on metal spinning processes. The review of existing work has several gaps in current knowledge of metal spinning processes. The evaluation of experiment is thickness strain, the spinning force, the twisting angle, the surface roughness of the conventional & shear metal spinning process; the evaluation of FEM of metal spinning to path definition with sufficient fine mesh to capture behavior of work piece; The evaluation of feed rate of roller, direction of roller,& type of roller stimulated. The metal spinning process has the more flexible to produce a wider range of product shape & to form more challenge material.

Keywords: metal spinning, FEM analysis, simulation of metal spinning, mechanical engineering

Procedia PDF Downloads 368
554 An Experimental Study of the Influence of Flow Rate on Formation Damage at Different pH

Authors: Khabat M. Ahmad

Abstract:

This experiment focuses on the reduction of permeability (formation damage) as a result of fines migration by changing pH and flow rate on core plugs selected from sandstone reservoir of Pannonian basin (Upper Miocene, East Hungary). The main objective of coreflooding experiments was to investigate the influence of both high and low pH fluids and the flow rate on stability of clay minerals. The selected core samples were examined by X-ray powder diffraction (XRD) for bulk mineralogical and clay mineral composition. The shape, position, distribution and type of clay minerals within the core samples were diagnosed by scanning electron microscopy and energy dispersive spectroscopy (SEM- EDS). The basic petrophysical properties such as porosity and initial permeability were determined prior to experiments. The special core analysis (influence of pH and flow rate) on permeability reduction was examined through a series of laboratory coreflooding experiments, testing for acidic (3) and alkaline (11) solutions at different flow rates (50, 100 and 200 ml/h). Permeability in continuously reduced for pH 11 to more than 50 % of initial permeability. However, at pH 3 after a slow decrease, a significant increase is observed, to more than 40 % of initial permeability. The variation is also influenced by flow rate.

Keywords: flow rate, pH, permeability, fine migration, formation damage, XRD, SEM- EDS

Procedia PDF Downloads 36
553 Spatial Variability of Environmental Parameters and Its Relationship with an Environmental Injustice on the Bike Paths of Santiago, Chile

Authors: Alicia Muñoz, Pedro Oyola, Cristian Henriquez

Abstract:

Pollution in Santiago de Chile has a spatial variability due to different factors, including meteorological parameters and emission sources. Socioenvironmental aspects are also significant for pollution in the canopy layer since it influences the type of edification, vegetal mass proportion and other environmental conditions. This study analyzes spatially urban pollution in Santiago, specifically, from the bike path perspective. Bike paths are located in high traffic zones, as consequence, users are constantly exposed to urban pollution. Measurements were made at the higher polluted hour, three days a week, including three transit regimes, on the most polluted month of the year. The environmental parameters are fine particulate matter (Model 8520, DustTrak Aerosol Monitor, TSI), temperature and relative humidity; it was also considerate urban parameters as sky view factor and vegetal mass. Identification of an environmental injustice will be achieved with a spatial modeling, including all urban factors and environmental mediations with an economic index of population.

Keywords: canopy layer, environmental injustice, spatial modeling, urban pollution

Procedia PDF Downloads 205
552 Structural and Electrical Properties of VO₂/ZnO Nanostructures

Authors: Sang-Wook Han, Zhenlan Jin, In-Hui Hwang, Chang-In Park

Abstract:

We examined structural and electrical properties of uniformly-oriented VO₂/ZnO nanostructures. VO₂ was deposited on ZnO templates by using a direct current-sputtering deposition. Scanning electron microscope and transmission electron microscope measurements indicated that b-oriented VO₂ were uniformly crystallized on ZnO templates with different lengths. VO₂/ZnO formed nanorods on ZnO nanorods with length longer than 250 nm. X-ray absorption fine structure at V K edge of VO₂/ZnO showed M1 and R phases of VO₂ at 30 and 100 ℃, respectively, suggesting structural phase transition between temperatures. Temperature-dependent resistance measurements of VO₂/ZnO nanostructures revealed metal-to-insulator transition at 65 ℃ and 55 ℃ during heating and cooling, respectively, regardless of ZnO length. The bond lengths of V-O and V-V pairs in VO₂/ZnO nanorods were somewhat distorted, and a substantial amount of structural disorder existed in the atomic pairs, compared to those of VO₂ films without ZnO. Resistance from VO₂/ZnO nanorods revealed a sharp MIT near 65 ℃ during heating and a hysteresis behavior. The resistance results suggest that microchannel for charge carriers exist nearly room temperature during cooling. VO₂/ZnO nanorods are quite stable and reproducible so that they can be widely used for practical applications to electronic devices, gas sensors, and ultra-fast switches, as examples.

Keywords: metal-to-insulator transition, VO₂, ZnO, XAFS, structural-phase transition

Procedia PDF Downloads 461
551 A Computational Analysis of Gas Jet Flow Effects on Liquid Aspiration in the Collison Nebulizer

Authors: James Q. Feng

Abstract:

Pneumatic nebulizers (as variations based on the Collison nebulizer) have been widely used for producing fine aerosol droplets from a liquid material. As qualitatively described by many authors, the basic working principle of those nebulizers involves utilization of the negative pressure associated with an expanding gas jet to syphon liquid into the jet stream, then to blow and shear into liquid sheets, filaments, and eventually droplets. But detailed quantitative analysis based on fluid mechanics theory has been lacking in the literature. The purpose of present work is to investigate the nature of negative pressure distribution associated with compressible gas jet flow in the Collison nebulizer by a computational fluid dynamics (CFD) analysis, using an OpenFOAM® compressible flow solver. The value of the negative pressure associated with a gas jet flow is examined by varying geometric parameters of the jet expansion channel adjacent to the jet orifice outlet. Such an analysis can provide valuable insights into fundamental mechanisms in liquid aspiration process, helpful for effective design of the pneumatic atomizer in the Aerosol Jet® direct-write system for micro-feature, high-aspect-ratio material deposition in additive manufacturing.

Keywords: collison nebulizer, compressible gas jet flow, liquid aspiration, pneumatic atomization

Procedia PDF Downloads 154
550 The Use of Seashell by-Products in Pervious Concrete Pavers

Authors: Dang Hanh Nguyen, Nassim Sebaibi, Mohamed Boutouil, Lydia Leleyter, Fabienne Baraud

Abstract:

Pervious concrete is a green alternative to conventional pavements with minimal fine aggregate and a high void content. Pervious concrete allows water to infiltrate through the pavement, thereby reducing the runoff and the requirement for stormwater management systems. Seashell By-Products (SBP) are produced in an important quantity in France and are considered as waste. This work investigated to use SBP in pervious concrete and produce an even more environmentally friendly product, Pervious Concrete Pavers. The research methodology involved substituting the coarse aggregate in the previous concrete mix design with 20%, 40% and 60% SBP. The testing showed that pervious concrete containing less than 40% SBP had strengths, permeability and void content which are comparable to the pervious concrete containing with only natural aggregate. The samples that contained 40% SBP or higher had a significant loss in strength and an increase in permeability and a void content from the control mix pervious concrete. On the basis of the results in this research, it was found that the natural aggregate can be substituted by SBP without affecting the delicate balance of a pervious concrete mix. Additional, it is recommended that the optimum replacement percentage for SBP in pervious concrete is 40 % direct replacement of natural coarse aggregate while maintaining the structural performance and drainage capabilities of the pervious concrete.

Keywords: seashell by-products, pervious concrete pavers, permeability, mechanical strength

Procedia PDF Downloads 461
549 Land Cover Classification Using Sentinel-2 Image Data and Random Forest Algorithm

Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

Abstract:

The currently launched Sentinel 2 (S2) satellite (June, 2015) bring a great potential and opportunities for land use/cover map applications, due to its fine spatial resolution multispectral as well as high temporal resolutions. So far, there are handful studies using S2 real data for land cover classification. Especially in northern Vietnam, to our best knowledge, there exist no studies using S2 data for land cover map application. The aim of this study is to provide the preliminary result of land cover classification using Sentinel -2 data with a rising state – of – art classifier, Random Forest. A case study with heterogeneous land use/cover in the eastern of Hanoi Capital – Vietnam was chosen for this study. All 10 spectral bands of 10 and 20 m pixel size of S2 images were used, the 10 m bands were resampled to 20 m. Among several classified algorithms, supervised Random Forest classifier (RF) was applied because it was reported as one of the most accuracy methods of satellite image classification. The results showed that the red-edge and shortwave infrared (SWIR) bands play an important role in land cover classified results. A very high overall accuracy above 90% of classification results was achieved.

Keywords: classify algorithm, classification, land cover, random forest, sentinel 2, Vietnam

Procedia PDF Downloads 354