Search results for: satellite images
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2838

Search results for: satellite images

1338 Development of 111In-DOTMP as a New Bone Imaging Agent

Authors: H. Yousefnia, S. Zolghadri, AR. Jalilian, A. Mirzaei, A. Bahrami-Samani, M. Erfani

Abstract:

The objective of this study is the preparation of 111In-DOTMP as a new bone imaging agent. 111In was produced at the Agricultural, Medical and Industrial Research School (AMIRS) by means of 30 MeV cyclotron via natCd(p,x)111In reaction. Complexion of In‐111 with DOTMP was carried out by adding 0.1 ml of the stock solution (50 mg/ml in 2 N NaoH) to the vial containing 1 mCi of 111In. pH of the mixture was adjusted to 7-8 by means of phosphate buffer. The radiochemical purity of the complex at the optimized condition was higher than 98% (by using whatman No.1 paper in NH4OH:MeOH: H2O (0.2:2:4)). Both the biodistribution studies and SPECT imaging indicated high bone uptake. The ratio of bone to other soft tissue accumulation was significantly high which permit to observe high quality images. The results show that 111In-DOTMP can be used as a suitable tracer for diagnosis of bone metastases by SPECT imaging.

Keywords: biodistribution, DOTMP, 111In, SPECT

Procedia PDF Downloads 514
1337 Investigation on Performance of Optical Shutter Panels for Transparent Displays

Authors: Jaehong Kim, Sunhee Park, HongSeop Shin, Kyongho Lim, Suhyun Kwon, Don-Gyou Lee, Pureum Kim, Moojong Lim, JongSang Baek

Abstract:

Transparent displays with OLEDs are the most commonly produced forms of see-through displays on the market or in development. In order to block the visual interruption caused by the light coming from the background, the special panel is combined with transparent displays with OLEDs. There is, however, few studies performance of optical shutter panel for transparent displays until now. This paper, therefore, describes the performance of optical shutter panels. The novel evaluation method was developed by measuring the amount of light which can form a transmitted background image. The new proposed method could tell how recognizable transmitted background images cannot be seen, and is consistent with viewer’s perception.

Keywords: optical shutter panel, optical performance, transparent display, visual interruption

Procedia PDF Downloads 514
1336 A Neural Approach for Color-Textured Images Segmentation

Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

Abstract:

In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: segmentation, color-texture, neural networks, fractal, watershed

Procedia PDF Downloads 323
1335 Irrigation Potential Assessment for Eastern Ganga Canal, India Using Geographic Information System

Authors: Deepak Khare, Radha Krishan, Bhaskar Nikam

Abstract:

The present study deals with the results of the Ortho-rectified Cartosat-1 PAN (2.5 m resolution) satellite data analysis for the extraction of canal networks under the Eastern Ganga Canal (EGC) command. Based on the information derived through the remote sensing data, in terms of the number of canals, their physical status and hydraulic connectivity from the source, irrigation potential (IP) created in the command was assessed by comparing with planned/design canal-wise irrigation potentials. All the geospatial information generated in the study is organized in a geodatabase. The EGC project irrigates the command through one main canal, five branch canals, 36 distributaries and 186 minors. The study was conducted with the main objectives of inventory and mapping of irrigation infrastructure using geographic information system (GIS), remote sensing and field data. Likewise, the assessment of irrigation potential created using the mapped infrastructure was performed as on March 2017. Results revealed that the canals were not only pending but were also having gap/s, and hydraulically disconnected in each branch canal and also in minors of EGC. A total of 16622.3 ha of commands were left untouched with canal water just due to the presence of gaps in the EGC project. The sum of all the gaps present in minor canals was 11.92 km, while in distributary, it was 2.63 km. This is a very good scenario that balances IP can be achieved by working on the gaps present in minor canals. Filling the gaps in minor canals can bring most of the area under irrigation, especially the tail reaches command.

Keywords: canal command, GIS, hydraulic connectivity, irrigation potential

Procedia PDF Downloads 127
1334 Computational Models for Accurate Estimation of Joint Forces

Authors: Ibrahim Elnour Abdelrahman Eltayeb

Abstract:

Computational modelling is a method used to investigate joint forces during a movement. It can get high accuracy in the joint forces via subject-specific models. However, the construction of subject-specific models remains time-consuming and expensive. The purpose of this paper was to identify what alterations we can make to generic computational models to get a better estimation of the joint forces. It appraised the impact of these alterations on the accuracy of the estimated joint forces. It found different strategies of alterations: joint model, muscle model, and an optimisation problem. All these alterations affected joint contact force accuracy, so showing the potential for improving the model predictions without involving costly and time-consuming medical images.

Keywords: joint force, joint model, optimisation problem, validation

Procedia PDF Downloads 151
1333 Application of an Artificial Neural Network to Determine the Risk of Malignant Tumors from the Images Resulting from the Asymmetry of Internal and External Thermograms of the Mammary Glands

Authors: Amdy Moustapha Drame, Ilya V. Germashev, E. A. Markushevskaya

Abstract:

Among the main problems of medicine is breast cancer, from which a significant number of women around the world are constantly dying. Therefore, the detection of malignant breast tumors is an urgent task. For many years, various technologies for detecting these tumors have been used, in particular, in thermal imaging in order to determine different levels of breast cancer development. These periodic screening methods are a diagnostic tool for women and may have become an alternative to older methods such as mammography. This article proposes a model for the identification of malignant neoplasms of the mammary glands by the asymmetry of internal and external thermal imaging fields.

Keywords: asymmetry, breast cancer, tumors, deep learning, thermogram, convolutional transformation, classification

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1332 Investigating the Viability of Ultra-Low Parameter Count Networks for Real-Time Football Detection

Authors: Tim Farrelly

Abstract:

In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

Procedia PDF Downloads 126
1331 Comparison of Back-Projection with Non-Uniform Fast Fourier Transform for Real-Time Photoacoustic Tomography

Authors: Moung Young Lee, Chul Gyu Song

Abstract:

Photoacoustic imaging is the imaging technology that combines the optical imaging and ultrasound. This provides the high contrast and resolution due to optical imaging and ultrasound imaging, respectively. We developed the real-time photoacoustic tomography (PAT) system using linear-ultrasound transducer and digital acquisition (DAQ) board. There are two types of algorithm for reconstructing the photoacoustic signal. One is back-projection algorithm, the other is FFT algorithm. Especially, we used the non-uniform FFT algorithm. To evaluate the performance of our system and algorithms, we monitored two wires that stands at interval of 2.89 mm and 0.87 mm. Then, we compared the images reconstructed by algorithms. Finally, we monitored the two hairs crossed and compared between these algorithms.

Keywords: back-projection, image comparison, non-uniform FFT, photoacoustic tomography

Procedia PDF Downloads 420
1330 Breast Cancer Metastasis Detection and Localization through Transfer-Learning Convolutional Neural Network Classification Based on Convolutional Denoising Autoencoder Stack

Authors: Varun Agarwal

Abstract:

Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

Procedia PDF Downloads 113
1329 Between Kenzo Tange and Fernando Távora: An ‘Affinitarian’ Architectural Regard

Authors: João Cepeda

Abstract:

In crafting their way between theory and practice, authors and artists seem to be always immersed in a never-ending process of relating epochs, objects, and images. Endless ‘affinities’ emerge from a somewhat unexplainable (and intimate) magnetic relation. It is through this ‘warburgian’ assessment that two of the most prominent twentieth-century modern architects from Japan and Portugal are put into perspective, focusing on their paths and thinking-practice, and on the research of their personal and professional archives. Moreover, this research especially aims its focus at essaying specifically on the possible ‘affinities’ between two of their most renowned architectural projects: the Kenzo Tange’s (demolished) Villa Seijo project in Tokyo (Japan) and Fernando Távora’s Tennis Pavilion design in Matosinhos (Portugal), respectively, side-by-side – through in-depth fieldwork in the sites, bibliographical and archival research, (unprecedented) material analysis, and final critical consideration.

Keywords: Tange, Távora, architecture, affinities

Procedia PDF Downloads 43
1328 A Review on Light Shafts Rendering for Indoor Scenes

Authors: Hatam H. Ali, Mohd Shahrizal Sunar, Hoshang Kolivand, Mohd Azhar Bin M. Arsad

Abstract:

Rendering light shafts is one of the important topics in computer gaming and interactive applications. The methods and models that are used to generate light shafts play crucial role to make a scene more realistic in computer graphics. This article discusses the image-based shadows and geometric-based shadows that contribute in generating volumetric shadows and light shafts, depending on ray tracing, radiosity, and ray marching technique. The main aim of this study is to provide researchers with background on a progress of light scattering methods so as to make it available for them to determine the technique best suited to their goals. It is also hoped that our classification helps researchers find solutions to the shortcomings of each method.

Keywords: shaft of lights, realistic images, image-based, and geometric-based

Procedia PDF Downloads 261
1327 Application of Remote Sensing and GIS in Assessing Land Cover Changes within Granite Quarries around Brits Area, South Africa

Authors: Refilwe Moeletsi

Abstract:

Dimension stone quarrying around Brits and Belfast areas started in the early 1930s and has been growing rapidly since then. Environmental impacts associated with these quarries have not been documented, and hence this study aims at detecting any change in the environment that might have been caused by these activities. Landsat images that were used to assess land use/land cover changes in Brits quarries from 1998 - 2015. A supervised classification using maximum likelihood classifier was applied to classify each image into different land use/land cover types. Classification accuracy was assessed using Google Earth™ as a source of reference data. Post-classification change detection method was used to determine changes. The results revealed significant increase in granite quarries and corresponding decrease in vegetation cover within the study region.

Keywords: remote sensing, GIS, change detection, granite quarries

Procedia PDF Downloads 293
1326 A Comparative Study of Various Control Methods for Rendezvous of a Satellite Couple

Authors: Hasan Basaran, Emre Unal

Abstract:

Formation flying of satellites is a mission that involves a relative position keeping of different satellites in the constellation. In this study, different control algorithms are compared with one another in terms of ΔV, velocity increment, and tracking error. Various control methods, covering continuous and impulsive approaches are implemented and tested for satellites flying in low Earth orbit. Feedback linearization, sliding mode control, and model predictive control are designed and compared with an impulsive feedback law, which is based on mean orbital elements. Feedback linearization and sliding mode control approaches have identical mathematical models that include second order Earth oblateness effects. The model predictive control, on the other hand, does not include any perturbations and assumes circular chief orbit. The comparison is done with 4 different initial errors and achieved with velocity increment, root mean square error, maximum steady state error, and settling time. It was observed that impulsive law consumed the least ΔV, while produced the highest maximum error in the steady state. The continuous control laws, however, consumed higher velocity increments and produced lower amounts of tracking errors. Finally, the inversely proportional relationship between tracking error and velocity increment was established.

Keywords: chief-deputy satellites, feedback linearization, follower-leader satellites, formation flight, fuel consumption, model predictive control, rendezvous, sliding mode

Procedia PDF Downloads 86
1325 Production, Quality Control and Biodistribution Assessment of 166 Ho-BPAMD as a New Bone Seeking Agent

Authors: H. Yousefnia, N. Amraee, M. Hosntalab, S. Zolghadri, A. Bahrami-Samani

Abstract:

The aim of this study was the preparation of a new agent for bone marrow ablation in patients with multiple myeloma. 166Ho was produced at Tehran research reactor via 165Ho(n,γ)166Ho reaction. Complexion of Ho‐166 with BPAMD was carried out by the addition of about 200µg of BPAMD in absolute water to 1 mci of 166HoCl3 and warming up the mixture 90 0C for 1 h. 166Ho-BPAMD was prepared successfully with radio chemical purity of 95% which was measured by ITLC method. The final solution was injected to wild-type mice and bio distribution was determined up to 48 h. SPECT images were acquired after 2 and 48 h post injection. Both the bio distribution studies and SPECT imaging indicated high bone uptake, while accumulation in other organs was approximately negligible. The results show that 166Ho-BPAMD has suitable characteristics and can be used as a new bone marrow ablative agent.

Keywords: bone marrow ablation, BPAMD, 166Ho, SPECT

Procedia PDF Downloads 493
1324 Stepanovia osogoviensis sp. n. (Hymenoptera: Eulophidae) in Galls of Diplolepis rosae from Bulgaria

Authors: Ivaylo A. Todorov, Peter S. Boyadzhiev

Abstract:

A new distinctive species of Stepanovia Kostjukov (Hymenoptera: Eulophidae: Tetrastichinae) was reared in laboratory from mature galls of Diplolepis rosae (Linnaeus) (Cynipidae). The galls were collected from Rosa sp. bushes growing in Osogovo Mt. in Western Bulgaria. The new species is close to Stepanovia rosae Boyadzhiev & Todorov but differs in POL and OOL characteristics, width of antennae, forewings and ovipositor sheaths characteristics, different U-shaped pale stripe above clypeus and the length of the ventral plaque on male antenna. The taxonomically important morphological features are illustrated and compared with the rest species of the genus using Scanning electron microscopy and light reflection by compound microscopy. Images of male genitalia are also prepared.

Keywords: Eulophidae, Diplolepis rosae, galls, Stepanovia osogoviensis, Bulgaria

Procedia PDF Downloads 235
1323 Development of 4D Dynamic Simulation Tool for the Evaluation of Left Ventricular Myocardial Functions

Authors: Deepa, Yashbir Singh, Shi Yi Wu, Michael Friebe, Joao Manuel R. S. Tavares, Hu Wei-Chih

Abstract:

Cardiovascular disease can be detected by measuring the regional and global wall motion of the left ventricle (LV) of the heart; In this study, we designed a dynamic simulation tool using Computed Tomography (CT) images to assess the difference between actual and simulated left ventricular functions. Thirteen healthy subjects were involved in the study with actual and simulated left ventricular functions. In this research, we found the high correlation between actual left ventricular wall motion and simulated left ventricular wall motion. Our results confirm that our simulation tool is feasible for simulating left ventricular motion.

Keywords: cardiac imaging, left-ventricular remodeling, cardiac wall motion, myocardial functions

Procedia PDF Downloads 328
1322 India and Space Insurance Policy: An Analytical Insight

Authors: Shreyas Jayasimha, Suneel Anand Sundharesan, Rohan Tigadi

Abstract:

In the recent past, the United States of America and Russia were the only two dominant players in the field of space exploration and had a virtual monopoly in the field of space and technology. However, this has changed over the past few years. Many other nation states such as India, China, and the UK have made significant progress in this field. Amongst these nations, the growth and development of the Indian space program have been nothing short of a miracle. Starting recently, India has successfully launched a series of satellites including its much acclaimed Mangalyaan mission, which placed a satellite in Mars’ orbit. The fact that India was able to attain this feat in its attempt demonstrates the enormous growth potential and promise that the Indian space program holds for the coming years. However, unlike other space-faring nations, India does not have a comprehensive and consolidated space insurance policy. In this regard, it is pertinent to note that, the costs and risks involved in a administering a space program are enormous. Therefore, in the absence of a comprehensive space insurance policy, any losses from an unsuccessful will have to be borne by the state exchequer. Thus, in order to ensure that Indian space program continues on its upward trajectory, the Indian establishment should seriously consider formulating a comprehensive insurance policy. This paper intends to analyze the international best practices followed by other space-faring nations in relation to space insurance policy. Thereafter, the authors seek to examine the current regime in India relating to space insurance policy. Finally, the authors will conclude by providing a series of recommendations regarding the essential elements that should be part of any Indian space insurance policy regime.

Keywords: India, space insurance policy, space law, Indian space research organization

Procedia PDF Downloads 208
1321 Simulation of Climatic Change Effects on the Potential Fishing Zones of Dorado Fish (Coryphaena hippurus L.) in the Colombian Pacific under Scenarios RCP Using CMIP5 Model

Authors: Adriana Martínez-Arias, John Josephraj Selvaraj, Luis Octavio González-Salcedo

Abstract:

In the Colombian Pacific, Dorado fish (Coryphaena hippurus L.) fisheries is of great commercial interest. However, its habitat and fisheries may be affected by climatic change especially by the actual increase in sea surface temperature. Hence, it is of interest to study the dynamics of these species fishing zones. In this study, we developed Artificial Neural Networks (ANN) models to predict Catch per Unit Effort (CPUE) as an indicator of species abundance. The model was based on four oceanographic variables (Chlorophyll a, Sea Surface Temperature, Sea Level Anomaly and Bathymetry) derived from satellite data. CPUE datasets for model training and cross-validation were obtained from logbooks of commercial fishing vessel. Sea surface Temperature for Colombian Pacific were projected under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 using Coupled Model Intercomparison Project Phase 5 (CMIP5) and CPUE maps were created. Our results indicated that an increase in sea surface temperature reduces the potential fishing zones of this species in the Colombian Pacific. We conclude that ANN is a reliable tool for simulation of climate change effects on the potential fishing zones. This research opens a future agenda for other species that have been affected by climate change.

Keywords: climatic change, artificial neural networks, dorado fish, CPUE

Procedia PDF Downloads 224
1320 Investigation on Optical Performance of Operational Shutter Panels for Transparent Displays

Authors: Jaehong Kim, Sunhee Park, HongSeop Shin, Kyongho Lim, Suhyun Kwon, Don-Gyou Lee, Pureum Kim, Moojong Lim, JongSang Baek

Abstract:

Transparent displays with OLEDs are the most commonly produced forms of see-through displays on the market or in development. In order to block the visual interruption caused by the light coming from the background, the special panel is combined with transparent displays with OLEDs. There is, however, few studies optical performance of operational shutter panel for transparent displays until now. This paper, therefore, describes the optical performance of operational shutter panels. The novel evaluation method was developed by measuring the amount of light which can form a transmitted background image. The new proposed method could tell how recognize transmitted background images cannot be seen, and is consistent with viewer’s perception.

Keywords: transparent display, operational shutter panel, optical performance, OLEDs

Procedia PDF Downloads 423
1319 Texture-Based Image Forensics from Video Frame

Authors: Li Zhou, Yanmei Fang

Abstract:

With current technology, images and videos can be obtained more easily than ever. It is so easy to manipulate these digital multimedia information when obtained, and that the content or source of the image and video could be easily tampered. In this paper, we propose to identify the image and video frame by the texture-based approach, e.g. Markov Transition Probability (MTP), which is in space domain, DCT domain and DWT domain, respectively. In the experiment, image and video frame database is constructed, and is used to train and test the classifier Support Vector Machine (SVM). Experiment results show that the texture-based approach has good performance. In order to verify the experiment result, and testify the universality and robustness of algorithm, we build a random testing dataset, the random testing result is in keeping with above experiment.

Keywords: multimedia forensics, video frame, LBP, MTP, SVM

Procedia PDF Downloads 412
1318 A Conglomerate of Multiple Optical Character Recognition Table Detection and Extraction

Authors: Smita Pallavi, Raj Ratn Pranesh, Sumit Kumar

Abstract:

Information representation as tables is compact and concise method that eases searching, indexing, and storage requirements. Extracting and cloning tables from parsable documents is easier and widely used; however, industry still faces challenges in detecting and extracting tables from OCR (Optical Character Recognition) documents or images. This paper proposes an algorithm that detects and extracts multiple tables from OCR document. The algorithm uses a combination of image processing techniques, text recognition, and procedural coding to identify distinct tables in the same image and map the text to appropriate the corresponding cell in dataframe, which can be stored as comma-separated values, database, excel, and multiple other usable formats.

Keywords: table extraction, optical character recognition, image processing, text extraction, morphological transformation

Procedia PDF Downloads 126
1317 Integrated Free Space Optical Communication and Optical Sensor Network System with Artificial Intelligence Techniques

Authors: Yibeltal Chanie Manie, Zebider Asire Munyelet

Abstract:

5G and 6G technology offers enhanced quality of service with high data transmission rates, which necessitates the implementation of the Internet of Things (IoT) in 5G/6G architecture. In this paper, we proposed the integration of free space optical communication (FSO) with fiber sensor networks for IoT applications. Recently, free-space optical communications (FSO) are gaining popularity as an effective alternative technology to the limited availability of radio frequency (RF) spectrum. FSO is gaining popularity due to flexibility, high achievable optical bandwidth, and low power consumption in several applications of communications, such as disaster recovery, last-mile connectivity, drones, surveillance, backhaul, and satellite communications. Hence, high-speed FSO is an optimal choice for wireless networks to satisfy the full potential of 5G/6G technology, offering 100 Gbit/s or more speed in IoT applications. Moreover, machine learning must be integrated into the design, planning, and optimization of future optical wireless communication networks in order to actualize this vision of intelligent processing and operation. In addition, fiber sensors are important to achieve real-time, accurate, and smart monitoring in IoT applications. Moreover, we proposed deep learning techniques to estimate the strain changes and peak wavelength of multiple Fiber Bragg grating (FBG) sensors using only the spectrum of FBGs obtained from the real experiment.

Keywords: optical sensor, artificial Intelligence, Internet of Things, free-space optics

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1316 Functionalization of Single-Walled Nanotubes by Synthesied Pigments

Authors: Shahab Zomorodbakhsh, Hayron Nesa Motevasel

Abstract:

Water soluble compoundes were attached to single-walled carbon nanotubes (SWNTs) to form water-soluble nano pigments. functionalized SWNTs were then characterized by Fourier Transform Infrared spectroscopy (FT-IR), Raman spectroscopy, UV analysis, Transmission electron microscopy (TEM)and defunctionalization test and Representative results concerning the solubility. The product can be dissolved in water and High-resolution transmission electron microscope images showed that the SWNTs were efficiently functionalized, thus the p-stacking interaction between aromatic rings and COOH of SWNTs was considered responsible for the high solubility and High transmission electron in singlewall nanotubes.

Keywords: functionalized CNTs, singlewalled carbon nanotubes, water soluble compoundes, nano pigments

Procedia PDF Downloads 294
1315 Travel Delay and Modal Split Analysis: A Case Study

Authors: H. S. Sathish, H. S. Jagadeesh, Skanda Kumar

Abstract:

Journey time and delay study is used to evaluate the quality of service, the travel time and study can also be used to evaluate the quality of traffic movement along the route and to determine the location types and extent of traffic delays. Components of delay are boarding and alighting, issue of tickets, other causes and distance between each stops. This study investigates the total journey time required to travel along the stretch and the influence the delays. The route starts from Kempegowda Bus Station to Yelahanka Satellite Station of Bangalore City. The length of the stretch is 16.5 km. Modal split analysis has been done for this stretch. This stretch has elevated highway connecting to Bangalore International Airport and the extension of metro transit stretch. From the regression analysis of total journey time it is affected by delay due to boarding and alighting moderately, Delay due to issue of tickets affects the journey time to a higher extent. Some of the delay factors affecting significantly the journey time are evident from F-test at 10 percent level of confidence. Along this stretch work trips are more prevalent as indicated by O-D study. Modal shift analysis indicates about 70 percent of commuters are ready to shift from current system to Metro Rail System. Metro Rail System carries maximum number of trips compared to private mode. Hence Metro is a highly viable choice of mode for Bangalore Metropolitan City.

Keywords: delay, journey time, modal choice, regression analysis

Procedia PDF Downloads 481
1314 Recognition of Cursive Arabic Handwritten Text Using Embedded Training Based on Hidden Markov Models (HMMs)

Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

Abstract:

In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

Procedia PDF Downloads 334
1313 Image Rotation Using an Augmented 2-Step Shear Transform

Authors: Hee-Choul Kwon, Heeyong Kwon

Abstract:

Image rotation is one of main pre-processing steps for image processing or image pattern recognition. It is implemented with a rotation matrix multiplication. It requires a lot of floating point arithmetic operations and trigonometric calculations, so it takes a long time to execute. Therefore, there has been a need for a high speed image rotation algorithm without two major time-consuming operations. However, the rotated image has a drawback, i.e. distortions. We solved the problem using an augmented two-step shear transform. We compare the presented algorithm with the conventional rotation with images of various sizes. Experimental results show that the presented algorithm is superior to the conventional rotation one.

Keywords: high-speed rotation operation, image rotation, transform matrix, image processing, pattern recognition

Procedia PDF Downloads 261
1312 Air–Water Two-Phase Flow Patterns in PEMFC Microchannels

Authors: Ibrahim Rassoul, A. Serir, E-K. Si Ahmed, J. Legrand

Abstract:

The acronym PEM refers to Proton Exchange Membrane or alternatively Polymer Electrolyte Membrane. Due to its high efficiency, low operating temperature (30–80 °C), and rapid evolution over the past decade, PEMFCs are increasingly emerging as a viable alternative clean power source for automobile and stationary applications. Before PEMFCs can be employed to power automobiles and homes, several key technical challenges must be properly addressed. One technical challenge is elucidating the mechanisms underlying water transport in and removal from PEMFCs. On one hand, sufficient water is needed in the polymer electrolyte membrane or PEM to maintain sufficiently high proton conductivity. On the other hand, too much liquid water present in the cathode can cause “flooding” (that is, pore space is filled with excessive liquid water) and hinder the transport of the oxygen reactant from the gas flow channel (GFC) to the three-phase reaction sites. The experimental transparent fuel cell used in this work was designed to represent actual full scale of fuel cell geometry. According to the operating conditions, a number of flow regimes may appear in the microchannel: droplet flow, blockage water liquid bridge /plug (concave and convex forms), slug/plug flow and film flow. Some of flow patterns are new, while others have been already observed in PEMFC microchannels. An algorithm in MATLAB was developed to automatically determine the flow structure (e.g. slug, droplet, plug, and film) of detected liquid water in the test microchannels and yield information pertaining to the distribution of water among the different flow structures. A video processing algorithm was developed to automatically detect dynamic and static liquid water present in the gas channels and generate relevant quantitative information. The potential benefit of this software allows the user to obtain a more precise and systematic way to obtain measurements from images of small objects. The void fractions are also determined based on images analysis. The aim of this work is to provide a comprehensive characterization of two-phase flow in an operating fuel cell which can be used towards the optimization of water management and informs design guidelines for gas delivery microchannels for fuel cells and its essential in the design and control of diverse applications. The approach will combine numerical modeling with experimental visualization and measurements.

Keywords: polymer electrolyte fuel cell, air-water two phase flow, gas diffusion layer, microchannels, advancing contact angle, receding contact angle, void fraction, surface tension, image processing

Procedia PDF Downloads 290
1311 Toward Cloud E-learning System Based on Smart Tools

Authors: Mohsen Maraoui

Abstract:

In the face of the growth in the quantity of data produced, several methods and techniques appear to remedy the problems of processing and analyzing large amounts of information mainly in the field of teaching. In this paper, we propose an intelligent cloud-based teaching system for E-learning content services. This system makes easy the manipulation of various educational content forms, including text, images, videos, 3 dimensions objects and scenes of virtual reality and augmented reality. We discuss the integration of institutional and external services to provide personalized assistance to university members in their daily activities. The proposed system provides an intelligent solution for media services that can be accessed from smart devices cloud-based intelligent service environment with a fully integrated system.

Keywords: cloud computing, e-learning, indexation, IoT, learning in Arabic language, smart tools

Procedia PDF Downloads 117
1310 Analysis of Various Copy Move Image Forgery Techniques for Better Detection Accuracy

Authors: Grishma D. Solanki, Karshan Kandoriya

Abstract:

In modern era of information age, digitalization has revolutionized like never before. Powerful computers, advanced photo editing software packages and high resolution capturing devices have made manipulation of digital images incredibly easy. As per as image forensics concerns, one of the most actively researched area are detection of copy move forgeries. Higher computational complexity is one of the major component of existing techniques to detect such tampering. Moreover, copy move forgery is usually performed in three steps. First, copying of a region in an image then pasting the same one in the same respective image and finally doing some post-processing like rotation, scaling, shift, noise, etc. Consequently, pseudo Zernike moment is used as a features extraction method for matching image blocks and as a primary factor on which performance of detection algorithms depends.

Keywords: copy-move image forgery, digital forensics, image forensics, image forgery

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1309 Assessing the Utility of Unmanned Aerial Vehicle-Borne Hyperspectral Image and Photogrammetry Derived 3D Data for Wetland Species Distribution Quick Mapping

Authors: Qiaosi Li, Frankie Kwan Kit Wong, Tung Fung

Abstract:

Lightweight unmanned aerial vehicle (UAV) loading with novel sensors offers a low cost approach for data acquisition in complex environment. This study established a framework for applying UAV system in complex environment quick mapping and assessed the performance of UAV-based hyperspectral image and digital surface model (DSM) derived from photogrammetric point clouds for 13 species classification in wetland area Mai Po Inner Deep Bay Ramsar Site, Hong Kong. The study area was part of shallow bay with flat terrain and the major species including reedbed and four mangroves: Kandelia obovata, Aegiceras corniculatum, Acrostichum auerum and Acanthus ilicifolius. Other species involved in various graminaceous plants, tarbor, shrub and invasive species Mikania micrantha. In particular, invasive species climbed up to the mangrove canopy caused damage and morphology change which might increase species distinguishing difficulty. Hyperspectral images were acquired by Headwall Nano sensor with spectral range from 400nm to 1000nm and 0.06m spatial resolution image. A sequence of multi-view RGB images was captured with 0.02m spatial resolution and 75% overlap. Hyperspectral image was corrected for radiative and geometric distortion while high resolution RGB images were matched to generate maximum dense point clouds. Furtherly, a 5 cm grid digital surface model (DSM) was derived from dense point clouds. Multiple feature reduction methods were compared to identify the efficient method and to explore the significant spectral bands in distinguishing different species. Examined methods including stepwise discriminant analysis (DA), support vector machine (SVM) and minimum noise fraction (MNF) transformation. Subsequently, spectral subsets composed of the first 20 most importance bands extracted by SVM, DA and MNF, and multi-source subsets adding extra DSM to 20 spectrum bands were served as input in maximum likelihood classifier (MLC) and SVM classifier to compare the classification result. Classification results showed that feature reduction methods from best to worst are MNF transformation, DA and SVM. MNF transformation accuracy was even higher than all bands input result. Selected bands frequently laid along the green peak, red edge and near infrared. Additionally, DA found that chlorophyll absorption red band and yellow band were also important for species classification. In terms of 3D data, DSM enhanced the discriminant capacity among low plants, arbor and mangrove. Meanwhile, DSM largely reduced misclassification due to the shadow effect and morphological variation of inter-species. In respect to classifier, nonparametric SVM outperformed than MLC for high dimension and multi-source data in this study. SVM classifier tended to produce higher overall accuracy and reduce scattered patches although it costs more time than MLC. The best result was obtained by combining MNF components and DSM in SVM classifier. This study offered a precision species distribution survey solution for inaccessible wetland area with low cost of time and labour. In addition, findings relevant to the positive effect of DSM as well as spectral feature identification indicated that the utility of UAV-borne hyperspectral and photogrammetry deriving 3D data is promising in further research on wetland species such as bio-parameters modelling and biological invasion monitoring.

Keywords: digital surface model (DSM), feature reduction, hyperspectral, photogrammetric point cloud, species mapping, unmanned aerial vehicle (UAV)

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