Search results for: natural and geometric images
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8508

Search results for: natural and geometric images

7398 Rejuvenate: Face and Body Retouching Using Image Inpainting

Authors: Hossam Abdelrahman, Sama Rostom, Reem Yassein, Yara Mohamed, Salma Salah, Nour Awny

Abstract:

In today’s environment, people are becoming increasingly interested in their appearance. However, they are afraid of their unknown appearance after a plastic surgery or treatment. Accidents, burns and genetic problems such as bowing of body parts of people have a negative impact on their mental health with their appearance and this makes them feel uncomfortable and underestimated. The approach presents a revolutionary deep learning-based image inpainting method that analyses the various picture structures and corrects damaged images. In this study, A model is proposed based on the in-painting of medical images with Stable Diffusion Inpainting method. Reconstructing missing and damaged sections of an image is known as image inpainting is a key progress facilitated by deep neural networks. The system uses the input of the user of an image to indicate a problem, the system will then modify the image and output the fixed image, facilitating for the patient to see the final result.

Keywords: generative adversarial network, large mask inpainting, stable diffusion inpainting, plastic surgery

Procedia PDF Downloads 74
7397 Antarctica, Global Change and Deaf Education in Brazil

Authors: Luiz Antonio Da Costa Rodrigues, Mara Aparecida De Castilho Lopes, Alexandre Santos Alencar

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Teaching of science must transcend simple transmission of fundamental concepts and allow scientific literacy, as a process for understanding the human being as an integral part of a complex and interdependent whole. In this context, approaching the theme ‘Antarctica’ in deaf education is an important advance for teaching, considering that that continent has direct interactions with the climatic and environmental system of the planet. Therefore, textbooks can be important tools to enable the Deaf Community to access the discussion about the natural environment. A specific script was used to analyze textbooks adopted by schools in the Rio de Janeiro Metropolitan Region. Results show that none of the 14 analyzed books have a specific chapter on the theme, some presents images of the continent without reference to their environmental importance, and the complementary texts present in the analyzed material do not address the theme either. It is concluded that the study on Antarctica and global changes in elementary education is still incipient and the material used by most Brazilian public schools does not contemplate that subject in an accessible way for the deaf person. This fact represents the distance between deaf students and their environment, denoting the need for actions to promote that and other neglected themes in Science teaching.

Keywords: Antarctica, deaf education, science teaching, textbook

Procedia PDF Downloads 281
7396 Natural Frequency Analysis of Spinning Functionally Graded Cylindrical Shells Subjected to Thermal Loads

Authors: Esmaeil Bahmyari

Abstract:

The natural frequency analysis of the functionally graded (FG) rotating cylindrical shells subjected to thermal loads is studied based on the three-dimensional elasticity theory. The temperature-dependent assumption of the material properties is graded in the thickness direction, which varies based on the simple power law distribution. The governing equations and the appropriate boundary conditions, which include the effects of initial thermal stresses, are derived employing Hamilton’s principle. The initial thermo-mechanical stresses are obtained by the thermo-elastic equilibrium equation’s solution. As an efficient and accurate numerical tool, the differential quadrature method (DQM) is adopted to solve the thermo-elastic equilibrium equations, free vibration equations and natural frequencies are obtained. The high accuracy of the method is demonstrated by comparison studies with those existing solutions in the literature. Ultimately, the parametric studies are performed to demonstrate the effects of boundary conditions, temperature rise, material graded index, the thickness-to-length and the aspect ratios for the rotating cylindrical shells on the natural frequency.

Keywords: free vibration, DQM, elasticity theory, FG shell, rotating cylindrical shell

Procedia PDF Downloads 84
7395 Effect on Surface Temperature Reduction of Asphalt Pavements with Cement–Based Materials Containing Ceramic Waste Powder

Authors: H. Higashiyama, M. Sano, F. Nakanishi, M. Sugiyama, O. Takahashi, S. Tsukuma

Abstract:

The heat island phenomenon becomes one of the environmental problems. As countermeasures in the field of road engineering, cool pavements such as water retaining pavements and solar radiation reflective pavements have been developed to reduce the surface temperature of asphalt pavements in the hot summer climate in Japan. The authors have studied on the water retaining pavements with cement–based grouting materials. The cement–based grouting materials consist of cement, ceramic waste powder, and natural zeolite. The ceramic waste powder is collected through the recycling process of electric porcelain insulators. In this study, mixing ratio between the ceramic waste powder and the natural zeolite and a type of cement for the cement–based grouting materials is investigated to measure the surface temperature of asphalt pavements in the outdoor. All of the developed cement–based grouting materials were confirmed to effectively reduce the surface temperature of the asphalt pavements. Especially, the cement–based grouting material using the ultra–rapid hardening cement with the mixing ratio of 0.7:0.3 between the ceramic waste powder and the natural zeolite reduced mostly the surface temperature by 20 °C and more.

Keywords: ceramic waste powder, natural zeolite, road surface temperature, water retaining pavements

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7394 Comparison of Classical Computer Vision vs. Convolutional Neural Networks Approaches for Weed Mapping in Aerial Images

Authors: Paulo Cesar Pereira Junior, Alexandre Monteiro, Rafael da Luz Ribeiro, Antonio Carlos Sobieranski, Aldo von Wangenheim

Abstract:

In this paper, we present a comparison between convolutional neural networks and classical computer vision approaches, for the specific precision agriculture problem of weed mapping on sugarcane fields aerial images. A systematic literature review was conducted to find which computer vision methods are being used on this specific problem. The most cited methods were implemented, as well as four models of convolutional neural networks. All implemented approaches were tested using the same dataset, and their results were quantitatively and qualitatively analyzed. The obtained results were compared to a human expert made ground truth for validation. The results indicate that the convolutional neural networks present better precision and generalize better than the classical models.

Keywords: convolutional neural networks, deep learning, digital image processing, precision agriculture, semantic segmentation, unmanned aerial vehicles

Procedia PDF Downloads 260
7393 Environmental Geochemistry of Natural Geysers in an Urban Zone of Mexico

Authors: Zayre I. Gonzalez-Acevedo, Marco A. Garcia-Zarate

Abstract:

Environmental pollution by heavy metals is due to several processes, whether natural as weathering, or anthropogenic, related to human activities. Geysers may content dissolved heavy metals, related with their geothermal origin, and they are widely used by local people and tourists for treatment of dermal diseases and other therapeutic applications. In this study, 20 geysers with temperatures between 32 to 94 °C, located in the vicinity of Queretaro and Guanajuato in Central Mexico, were studied. These geysers were sampled in dry and rainy seasons in order to investigate seasonal changes of trace elements. The samples were analyzed in SWAMP Lab, University of Alberta, Canada for 34 elements. Most of the analyzed trace elements sowed concentrations below guidelines for natural waters. The elements showed seasonal variability with higher concentrations during rainy season. Arsenic varied from 49.29 to 2.16 µg L⁻¹. Arsenic was highly correlated with Fe, Sr, Th and Tl. Barium varied from 93.52 to 1.79 µg L⁻¹. Barium was highly correlated with Co, Cr, Mo, Ni, U, V, and Y. Copper and Zinc were correlated as well. According to the comparison of sites and the correlations between trace elements, their source was identified as natural regional, geothermal or anthropogenic origin. Because of application of geyser's water to balneology and health treatments, and also, because they are located in an urban zone in development, advise on their direct uses, according to their environmental quality is appointed in this research.

Keywords: balneology, direct uses, environmental quality and trace elements

Procedia PDF Downloads 160
7392 Geomorphology and Flood Analysis Using Light Detection and Ranging

Authors: George R. Puno, Eric N. Bruno

Abstract:

The natural landscape of the Philippine archipelago plus the current realities of climate change make the country vulnerable to flood hazards. Flooding becomes the recurring natural disaster in the country resulting to lose of lives and properties. Musimusi is among the rivers which exhibited inundation particularly at the inhabited floodplain portion of its watershed. During the event, rescue operations and distribution of relief goods become a problem due to lack of high resolution flood maps to aid local government unit identify the most affected areas. In the attempt of minimizing impact of flooding, hydrologic modelling with high resolution mapping is becoming more challenging and important. This study focused on the analysis of flood extent as a function of different geomorphologic characteristics of Musimusi watershed. The methods include the delineation of morphometric parameters in the Musimusi watershed using Geographic Information System (GIS) and geometric calculations tools. Digital Terrain Model (DTM) as one of the derivatives of Light Detection and Ranging (LiDAR) technology was used to determine the extent of river inundation involving the application of Hydrologic Engineering Center-River Analysis System (HEC-RAS) and Hydrology Modelling System (HEC-HMS) models. The digital elevation model (DEM) from synthetic Aperture Radar (SAR) was used to delineate watershed boundary and river network. Datasets like mean sea level, river cross section, river stage, discharge and rainfall were also used as input parameters. Curve number (CN), vegetation, and soil properties were calibrated based on the existing condition of the site. Results showed that the drainage density value of the watershed is low which indicates that the basin is highly permeable subsoil and thick vegetative cover. The watershed’s elongation ratio value of 0.9 implies that the floodplain portion of the watershed is susceptible to flooding. The bifurcation ratio value of 2.1 indicates higher risk of flooding in localized areas of the watershed. The circularity ratio value (1.20) indicates that the basin is circular in shape, high discharge of runoff and low permeability of the subsoil condition. The heavy rainfall of 167 mm brought by Typhoon Seniang last December 29, 2014 was characterized as high intensity and long duration, with a return period of 100 years produced 316 m3s-1 outflows. Portion of the floodplain zone (1.52%) suffered inundation with 2.76 m depth at the maximum. The information generated in this study is helpful to the local disaster risk reduction management council in monitoring the affected sites for more appropriate decisions so that cost of rescue operations and relief goods distribution is minimized.

Keywords: flooding, geomorphology, mapping, watershed

Procedia PDF Downloads 230
7391 Deep Convolutional Neural Network for Detection of Microaneurysms in Retinal Fundus Images at Early Stage

Authors: Goutam Kumar Ghorai, Sandip Sadhukhan, Arpita Sarkar, Debprasad Sinha, G. Sarkar, Ashis K. Dhara

Abstract:

Diabetes mellitus is one of the most common chronic diseases in all countries and continues to increase in numbers significantly. Diabetic retinopathy (DR) is damage to the retina that occurs with long-term diabetes. DR is a major cause of blindness in the Indian population. Therefore, its early diagnosis is of utmost importance towards preventing progression towards imminent irreversible loss of vision, particularly in the huge population across rural India. The barriers to eye examination of all diabetic patients are socioeconomic factors, lack of referrals, poor access to the healthcare system, lack of knowledge, insufficient number of ophthalmologists, and lack of networking between physicians, diabetologists and ophthalmologists. A few diabetic patients often visit a healthcare facility for their general checkup, but their eye condition remains largely undetected until the patient is symptomatic. This work aims to focus on the design and development of a fully automated intelligent decision system for screening retinal fundus images towards detection of the pathophysiology caused by microaneurysm in the early stage of the diseases. Automated detection of microaneurysm is a challenging problem due to the variation in color and the variation introduced by the field of view, inhomogeneous illumination, and pathological abnormalities. We have developed aconvolutional neural network for efficient detection of microaneurysm. A loss function is also developed to handle severe class imbalance due to very small size of microaneurysms compared to background. The network is able to locate the salient region containing microaneurysms in case of noisy images captured by non-mydriatic cameras. The ground truth of microaneurysms is created by expert ophthalmologists for MESSIDOR database as well as private database, collected from Indian patients. The network is trained from scratch using the fundus images of MESSIDOR database. The proposed method is evaluated on DIARETDB1 and the private database. The method is successful in detection of microaneurysms for dilated and non-dilated types of fundus images acquired from different medical centres. The proposed algorithm could be used for development of AI based affordable and accessible system, to provide service at grass root-level primary healthcare units spread across the country to cater to the need of the rural people unaware of the severe impact of DR.

Keywords: retinal fundus image, deep convolutional neural network, early detection of microaneurysms, screening of diabetic retinopathy

Procedia PDF Downloads 142
7390 Use of Machine Learning Algorithms to Pediatric MR Images for Tumor Classification

Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

Abstract:

Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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7389 3D Remote Sensing Images Parallax Refining Based On HTML5

Authors: Qian Pei, Hengjian Tong, Weitao Chen, Hai Wang, Yanrong Feng

Abstract:

Horizontal parallax is the foundation of stereoscopic viewing. However, the human eye will feel uncomfortable and it will occur diplopia if horizontal parallax is larger than eye separation. Therefore, we need to do parallax refining before conducting stereoscopic observation. Although some scholars have been devoted to online remote sensing refining, the main work of image refining is completed on the server side. There will be a significant delay when multiple users access the server at the same time. The emergence of HTML5 technology in recent years makes it possible to develop rich browser web application. Authors complete the image parallax refining on the browser side based on HTML5, while server side only need to transfer image data and parallax file to browser side according to the browser’s request. In this way, we can greatly reduce the server CPU load and allow a large number of users to access server in parallel and respond the user’s request quickly.

Keywords: 3D remote sensing images, parallax, online refining, rich browser web application, HTML5

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7388 Excessive Recruitment of Neutrophils and Elastase Release in Emphysema and COPD; Effect of Natural Protease Inhibitors

Authors: Rachid Kacem

Abstract:

Excessive recruitment of Neutrophils into the lungs is a hallmark of several chronic inflammatory disorders such as emphysema and COPD. The resulting of this recruitment is the pathogenesis of lungs which is characterized by an imbalance between leukocyte serine proteinases mainly neutrophil elastase and the physiological inhibitors. The development of emphysema and remodeling of airway tissue occurred when neutrophil migrate into the lungs with more release of elastase and other proteolytic enzymes. Many reports have demonstrated that the extracts from medicinal plants such as Nigella sativa (L.) seeds extracts have anti-elastase activity; this is mainly due to the enrichment of the extracts with many bioactive molecules mainly phenolic compounds. Neutrophil serine proteases including human neutrophil elastase are involved in many inflammatory diseases, such as chronic obstructive pulmonary disease and emphysema. Since the current therapies for these diseases are inadequate and have numerous adverse effects, there is an acute need of potential alternative therapies. The natural protease inhibitors have received increasing attention as useful tools for potential utilization in pharmacology. This work is elucidating the most important natural phenolic substances that have been reported recently for their effectiveness as natural anti-elastase molecules, and hence, to the possibility of their use in the field of pharmaceuticals.

Keywords: medicinal plants, phenols, elastase, anti-elastase, chronic obstructive pulmonary disease, COPD, emphysema

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7387 A Journey to the Past: Hoşap Castle in Van

Authors: Muhammet Kurucu

Abstract:

Hoşap Castle, located in Gürpınar, Van, is one of the most important symbols of the city because it hosted sacred memories of its time. Besides the location and construction features of Güzelsu, in resort city of Van, Hoşap Castle is a great place with an architecture consisting of an outer fortress and the inner fortress. It is one of the Ottoman castles and was built in the 17th century by Sarı Süleyman who was known as bey of Mahmudi. Although some parts of Hoşap Castle have been destroyed by natural disasters, it has survived until today without total collapse and most places with excavations are revealed. In this study, present condition of the Hoşap Castle is observed and introduced briefly.

Keywords: Güzelsu, Hoşap Castle, natural disasters, restoration, Van

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7386 Theoretical Investigation on the Dynamic Characteristics of One Degree of Freedom Vibration System Equipped with Inerter of Variable Inertance

Authors: Barenten Suciu, Yoshiki Tsuji

Abstract:

In this paper, a theoretical investigation on the dynamic characteristics of one degree of freedom vibration system equipped with inerter of variable inertance, is presented. Differential equation of movement was solved under proper initial conditions in the case of free undamped/damped vibration, considered in the absence/presence of the inerter in the mechanical system. Influence of inertance on the amplitude of vibration, phase angle, natural frequency, damping ratio, and logarithmic decrement was clarified. It was mainly found that the inerter decreases the natural frequency of the undamped system and also of the damped system if the damping ratio is below 0.707. On the other hand, the inerter increases the natural frequency of the damped system if the damping ratio exceeds 0.707. Results obtained in this work are useful for the adequate design of inerters.

Keywords: damping, frequency control, inerter, one degree of freedom vibration system, parallel connection, variable inertance

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7385 Free Vibration Analysis of Gabled Frame Considering Elastic Supports and Semi-Rigid Connections

Authors: A. Shooshtari, A. R. Masoodi, S. Heyrani Moghaddam

Abstract:

Free vibration analysis of a gabled frame with elastic support and semi-rigid connections is performed by using a program in OpenSees software. Natural frequencies and mode shape details of frame are obtained for two states, which are semi-rigid connections and elastic supports, separately. The members of this structure are analyzed as a prismatic nonlinear beam-column element in software. The mass of structure is considered as two equal lumped masses at the head of two columns in horizontal and vertical directions. Note that the degree of freedom, allocated to all nodes, is equal to three. Furthermore, the mode shapes of frame are achieved. Conclusively, the effects of connections and supports flexibility on the natural frequencies and mode shapes of structure are investigated.

Keywords: natural frequency, mode shape, gabled frame, semi-rigid connection, elastic support, OpenSees software

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7384 The Use of X-Ray Computed Microtomography in Petroleum Geology: A Case Study of Unconventional Reservoir Rocks in Poland

Authors: Tomasz Wejrzanowski, Łukasz Kaczmarek, Michał Maksimczuk

Abstract:

High-resolution X-ray computed microtomography (µCT) is a non-destructive technique commonly used to determine the internal structure of reservoir rock sample. This study concerns µCT analysis of Silurian and Ordovician shales and mudstones from a borehole in the Baltic Basin, north of Poland. The spatial resolution of the µCT images obtained was 27 µm, which enabled the authors to create accurate 3-D visualizations and to calculate the ratio of pores and fractures volume to the total sample volume. A total of 1024 µCT slices were used to create a 3-D volume of sample structure geometry. These µCT slices were processed to obtain a clearly visible image and the volume ratio. A copper X-ray source filter was used to reduce image artifacts. Due to accurate technical settings of µCT it was possible to obtain high-resolution 3-D µCT images of low X-ray transparency samples. The presented results confirm the utility of µCT implementations in geoscience and show that µCT has still promising applications for reservoir exploration and characterization.

Keywords: fractures, material density, pores, structure

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7383 Images Selection and Best Descriptor Combination for Multi-Shot Person Re-Identification

Authors: Yousra Hadj Hassen, Walid Ayedi, Tarek Ouni, Mohamed Jallouli

Abstract:

To re-identify a person is to check if he/she has been already seen over a cameras network. Recently, re-identifying people over large public cameras networks has become a crucial task of great importance to ensure public security. The vision community has deeply investigated this area of research. Most existing researches rely only on the spatial appearance information from either one or multiple person images. Actually, the real person re-id framework is a multi-shot scenario. However, to efficiently model a person’s appearance and to choose the best samples to remain a challenging problem. In this work, an extensive comparison of descriptors of state of the art associated with the proposed frame selection method is studied. Specifically, we evaluate the samples selection approach using multiple proposed descriptors. We show the effectiveness and advantages of the proposed method by extensive comparisons with related state-of-the-art approaches using two standard datasets PRID2011 and iLIDS-VID.

Keywords: camera network, descriptor, model, multi-shot, person re-identification, selection

Procedia PDF Downloads 278
7382 Intelligent Chatbot Generating Dynamic Responses Through Natural Language Processing

Authors: Aarnav Singh, Jatin Moolchandani

Abstract:

The proposed research work aims to build a query-based AI chatbot that can answer any question related to any topic. A chatbot is software that converses with users via text messages. In the proposed system, we aim to build a chatbot that generates a response based on the user’s query. For this, we use natural language processing to analyze the query and some set of texts to form a concise answer. The texts are obtained through web-scrapping and filtering all the credible sources from a web search. The objective of this project is to provide a chatbot that is able to provide simple and accurate answers without the user having to read through a large number of articles and websites. Creating an AI chatbot that can answer a variety of user questions on a variety of topics is the goal of the proposed research project. This chatbot uses natural language processing to comprehend user inquiries and provides succinct responses by examining a collection of writings that were scraped from the internet. The texts are carefully selected from reliable websites that are found via internet searches. This project aims to provide users with a chatbot that provides clear and precise responses, removing the need to go through several articles and web pages in great detail. In addition to exploring the reasons for their broad acceptance and their usefulness across many industries, this article offers an overview of the interest in chatbots throughout the world.

Keywords: Chatbot, Artificial Intelligence, natural language processing, web scrapping

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7381 21st Century Teacher Image to Stakeholders of Teacher Education Institutions in the Philippines

Authors: Marilyn U. Balagtas, Maria Ruth M. Regalado, Carmelina E. Barrera, Ramer V. Oxiño, Rosarito T. Suatengco, Josephine E. Tondo

Abstract:

This study presents the perceptions of the students and teachers from kindergarten to tertiary level of the image of the 21st century teacher to provide basis in designing teacher development programs in Teacher Education Institutions (TEIs) in the Philippines. The highlights of the report are the personal, psychosocial, and professional images of the 21st century teacher in basic education and the teacher educators based on a survey done to 612 internal stakeholders of nine member institutions of the National Network of Normal Schools (3NS). Data were obtained through the use of a validated researcher-made instrument which allowed generation of both quantitative and qualitative descriptions of the teacher image. Through the use of descriptive statistics, the common images of the teacher were drawn, which were validated and enriched by the information drawn from the qualitative data. The study recommends a repertoire of teacher development programs to create the good image of the 21st century teachers for a better Philippines.

Keywords: teacher image, 21st century teacher, teacher education, development program

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7380 The Employment of Unmanned Aircraft Systems for Identification and Classification of Helicopter Landing Zones and Airdrop Zones in Calamity Situations

Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

Abstract:

Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

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7379 Marker-Controlled Level-Set for Segmenting Breast Tumor from Thermal Images

Authors: Swathi Gopakumar, Sruthi Krishna, Shivasubramani Krishnamoorthy

Abstract:

Contactless, painless and radiation-free thermal imaging technology is one of the preferred screening modalities for detection of breast cancer. However, poor signal to noise ratio and the inexorable need to preserve edges defining cancer cells and normal cells, make the segmentation process difficult and hence unsuitable for computer-aided diagnosis of breast cancer. This paper presents key findings from a research conducted on the appraisal of two promising techniques, for the detection of breast cancer: (I) marker-controlled, Level-set segmentation of anisotropic diffusion filtered preprocessed image versus (II) Segmentation using marker-controlled level-set on a Gaussian-filtered image. Gaussian-filtering processes the image uniformly, whereas anisotropic filtering processes only in specific areas of a thermographic image. The pre-processed (Gaussian-filtered and anisotropic-filtered) images of breast samples were then applied for segmentation. The segmentation of breast starts with initial level-set function. In this study, marker refers to the position of the image to which initial level-set function is applied. The markers are generally placed on the left and right side of the breast, which may vary with the breast size. The proposed method was carried out on images from an online database with samples collected from women of varying breast characteristics. It was observed that the breast was able to be segmented out from the background by adjustment of the markers. From the results, it was observed that as a pre-processing technique, anisotropic filtering with level-set segmentation, preserved the edges more effectively than Gaussian filtering. Segmented image, by application of anisotropic filtering was found to be more suitable for feature extraction, enabling automated computer-aided diagnosis of breast cancer.

Keywords: anisotropic diffusion, breast, Gaussian, level-set, thermograms

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7378 Analyzing Natural and Social Resources for the Planning of Complex Development Based on Ecotourism: A Case Study from Hungary and Slovakia

Authors: Barnabás Körmöndi

Abstract:

The recent crises have affected societies worldwide, resulting in the irresponsible exploitation of natural resources and the unattainability of sustainability. Regions that are economically underdeveloped, such as the Bodrogköz in Eastern Hungary and Slovakia, experience these issues more severely. The aim of this study is to analyze the natural and social resources of the Bodrogköz area for the planning of complex development based on ecotourism. The objective is to develop ecotourism opportunities in this least developed area of the borderland of Hungary and Slovakia. The study utilizes desk research, deep interviews, focus group meetings, and remote sensing methods. Desk research is aimed at providing a comprehensive understanding of the area, while deep interviews and focus group meetings were conducted to understand the stakeholders' perspectives on the potential for ecotourism. Remote sensing methods were used to better understand changes in the natural environment. The study identified the potential for ecotourism development in the Bodrogköz area due to its near-natural habitats along its bordering rivers and rich cultural heritage. The analysis revealed that ecotourism could promote the region's sustainable development, which is essential for its economic growth. Additionally, the study identified the possible threats to the natural environment during ecotourism development and suggested strategies to mitigate these threats. This study highlights the significance of ecotourism in promoting sustainable development in underdeveloped areas such as the Bodrogköz. It provides a basis for future research on ecotourism development and sustainable planning in similar regions. The analysis is based on the data collected through desk research, deep interviews, focus group meetings, and remote sensing. The assessment was conducted through content analysis, which allowed for the identification of themes and patterns in the data. The study addressed the question of how to develop ecotourism in the least developed area of the borderland of Hungary and Slovakia and promote sustainable development in the region. In conclusion, the study highlights the potential for ecotourism development in Bodrogköz and identifies the natural and social resources that contribute to its development. The study emphasizes the need for sustainable development to promote economic growth and mitigate any environmental threats. The findings can inform the development of future strategic plans for ecotourism, promoting sustainable development in underdeveloped regions.

Keywords: ecotourism, natural resources, remote sensing, social development

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7377 Dynamics Pattern of Land Use and Land Cover Change and Its Driving Factors Based on a Cellular Automata Markov Model: A Case Study at Ibb Governorate, Yemen

Authors: Abdulkarem Qasem Dammag, Basema Qasim Dammag, Jian Dai

Abstract:

Change in Land use and Land cover (LU/LC) has a profound impact on the area's natural, economic, and ecological development, and the search for drivers of land cover change is one of the fundamental issues of LU/LC change. The study aimed to assess the temporal and Spatio-temporal dynamics of LU/LC in the past and to predict the future using Landsat images by exploring the characteristics of different LU/LC types. Spatio-temporal patterns of LU/LC change in Ibb Governorate, Yemen, were analyzed based on RS and GIS from 1990, 2005, and 2020. A socioeconomic survey and key informant interviews were used to assess potential drivers of LU/LC. The results showed that from 1990 to 2020, the total area of vegetation land decreased by 5.3%, while the area of barren land, grassland, built-up area, and waterbody increased by 2.7%, 1.6%, 1.04%, and 0.06%, respectively. Based on socio-economic surveys and key informant interviews, natural factors had a significant and long-term impact on land change. In contrast, site construction and socio-economic factors were the main driving forces affecting land change in a short time scale. The analysis results have been linked to the CA-Markov Land Use simulation and forecasting model for the years 2035 and 2050. The simulation results revealed from the period 2020 to 2050, the trend of dynamic changes in land use, where the total area of barren land decreased by 7.0% and grassland by 0.2%, while the vegetation land, built-up area, and waterbody increased by 4.6%, 2.6%, and 0.1 %, respectively. Overall, these findings provide LULC's past and future trends and identify drivers, which can play an important role in sustainable land use planning and management by balancing and coordinating urban growth and land use and can also be used at the regional level in different levels to provide as a reference. In addition, the results provide scientific guidance to government departments and local decision-makers in future land-use planning through dynamic monitoring of LU/LC change.

Keywords: LU/LC change, CA-Markov model, driving forces, change detection, LU/LC change simulation

Procedia PDF Downloads 64
7376 Analysis of Building Response from Vertical Ground Motions

Authors: George C. Yao, Chao-Yu Tu, Wei-Chung Chen, Fung-Wen Kuo, Yu-Shan Chang

Abstract:

Building structures are subjected to both horizontal and vertical ground motions during earthquakes, but only the horizontal ground motion has been extensively studied and considered in design. Most of the prevailing seismic codes assume the vertical component to be 1/2 to 2/3 of the horizontal one. In order to understand the building responses from vertical ground motions, many earthquakes records are studied in this paper. System identification methods (ARX Model) are used to analyze the strong motions and to find out the characteristics of the vertical amplification factors and the natural frequencies of buildings. Analysis results show that the vertical amplification factors for high-rise buildings and low-rise building are 1.78 and 2.52 respectively, and the average vertical amplification factor of all buildings is about 2. The relationship between the vertical natural frequency and building height was regressed to a suggested formula in this study. The result points out an important message; the taller the building is, the greater chance of resonance of vertical vibration on the building will be.

Keywords: vertical ground motion, vertical amplification factor, natural frequency, component

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7375 The Role of Semi Open Spaces on Exploitation of Wind-Driven Ventilation

Authors: Paria Saadatjoo

Abstract:

Given that HVAC systems are the main sources of carbon dioxide producers, developing ways to reduce dependence on these systems and making use of natural resources is too important to achieve environmentally friendly buildings. A major part of building potential in terms of using natural energy resources depends on its physical features. So architectural decisions at the first step of the design process can influence the building's energy efficiency significantly. Implementation of semi-open spaces into solid apartment blocks inspired by the concept of courtyard in ancient buildings as a passive cooling strategy is currently enjoying great popularity. However, the analysis of these features and their effect on wind behavior at initial design steps is a difficult task for architects. The main objective of this research was to investigate the influence of semi-open to closed space ratio on airflow patterns in and around midrise buildings and introduce the best ratio in terms of harnessing natural ventilation. The main strategy of this paper was semi-experimental, and the research methodology was descriptive statistics. At the first step, by changing the terrace area, 6 models with various open to closed space ratios were created. These forms were then transferred to CFD software to calculate the primary indicators of natural ventilation potentials such as wind force coefficient, air flow rate, age of air distribution, etc. Investigations indicated that modifying the terrace area and, in other words, the open to closed space ratio influenced the wind force coefficient, airflow rate, and age of air distribution.

Keywords: natural ventilation, wind, midrise, open space, energy

Procedia PDF Downloads 170
7374 Numerical Analysis of Heat Transfer in Water Channels of the Opposed-Piston Diesel Engine

Authors: Michal Bialy, Marcin Szlachetka, Mateusz Paszko

Abstract:

This paper discusses the CFD results of heat transfer in water channels in the engine body. The research engine was a newly designed Diesel combustion engine. The engine has three cylinders with three pairs of opposed pistons inside. The engine will be able to generate 100 kW mechanical power at a crankshaft speed of 3,800-4,000 rpm. The water channels are in the engine body along the axis of the three cylinders. These channels are around the three combustion chambers. The water channels transfer combustion heat that occurs the cylinders to the external radiator. This CFD research was based on the ANSYS Fluent software and aimed to optimize the geometry of the water channels. These channels should have a maximum flow of heat from the combustion chamber or the external radiator. Based on the parallel simulation research, the boundary and initial conditions enabled us to specify average values of key parameters for our numerical analysis. Our simulation used the average momentum equations and turbulence model k-epsilon double equation. There was also used a real k-epsilon model with a function of a standard wall. The turbulence intensity factor was 10%. The working fluid mass flow rate was calculated for a single typical value, specified in line with the research into the flow rate of automotive engine cooling pumps used in engines of similar power. The research uses a series of geometric models which differ, for instance, in the shape of the cross-section of the channel along the axis of the cylinder. The results are presented as colourful distribution maps of temperature, speed fields and heat flow through the cylinder walls. Due to limitations of space, our paper presents the results on the most representative geometric model only. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK ‘PZL-KALISZ’ S.A. and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: Ansys fluent, combustion engine, computational fluid dynamics CFD, cooling system

Procedia PDF Downloads 219
7373 Degraded Document Analysis and Extraction of Original Text Document: An Approach without Optical Character Recognition

Authors: L. Hamsaveni, Navya Prakash, Suresha

Abstract:

Document Image Analysis recognizes text and graphics in documents acquired as images. An approach without Optical Character Recognition (OCR) for degraded document image analysis has been adopted in this paper. The technique involves document imaging methods such as Image Fusing and Speeded Up Robust Features (SURF) Detection to identify and extract the degraded regions from a set of document images to obtain an original document with complete information. In case, degraded document image captured is skewed, it has to be straightened (deskew) to perform further process. A special format of image storing known as YCbCr is used as a tool to convert the Grayscale image to RGB image format. The presented algorithm is tested on various types of degraded documents such as printed documents, handwritten documents, old script documents and handwritten image sketches in documents. The purpose of this research is to obtain an original document for a given set of degraded documents of the same source.

Keywords: grayscale image format, image fusing, RGB image format, SURF detection, YCbCr image format

Procedia PDF Downloads 377
7372 Modelling and Simulation of Natural Gas-Fired Power Plant Integrated to a CO2 Capture Plant

Authors: Ebuwa Osagie, Chet Biliyok, Yeung Hoi

Abstract:

Regeneration energy requirement and ways to reduce it is the main aim of most CO2 capture researches currently being performed and thus, post-combustion carbon capture (PCC) option is identified to be the most suitable for the natural gas-fired power plants. From current research and development (R&D) activities worldwide, two main areas are being examined in order to reduce the regeneration energy requirement of amine-based PCC, namely: (a) development of new solvents with better overall performance than 30wt% monoethanolamine (MEA) aqueous solution, which is considered as the base-line solvent for solvent-based PCC, (b) Integration of the PCC Plant to the power plant. In scaling-up a PCC pilot plant to the size required for a commercial-scale natural gas-fired power plant, process modelling and simulation is very essential. In this work, an integrated process made up of a 482MWe natural gas-fired power plant, an MEA-based PCC plant which is developed and validated has been modelled and simulated. The PCC plant has four absorber columns and a single stripper column, the modelling and simulation was performed with Aspen Plus® V8.4. The gas turbine, the heat recovery steam generator and the steam cycle were modelled based on a 2010 US DOE report, while the MEA-based PCC plant was modelled as a rate-based process. The scaling of the amine plant was performed using a rate based calculation in preference to the equilibrium based approach for 90% CO2 capture. The power plant was integrated to the PCC plant in three ways: (i) flue gas stream from the power plant which is divided equally into four stream and each stream is fed into one of the four absorbers in the PCC plant. (ii) Steam draw-off from the IP/LP cross-over pipe in the steam cycle of the power plant used to regenerate solvent in the reboiler. (iii) Condensate returns from the reboiler to the power plant. The integration of a PCC plant to the NGCC plant resulted in a reduction of the power plant output by 73.56 MWe and the net efficiency of the integrated system is reduced by 7.3 % point efficiency. A secondary aim of this study is the parametric studies which have been performed to assess the impacts of natural gas on the overall performance of the integrated process and this is achieved through investigation of the capture efficiencies.

Keywords: natural gas-fired, power plant, MEA, CO2 capture, modelling, simulation

Procedia PDF Downloads 446
7371 User Guidance for Effective Query Interpretation in Natural Language Interfaces to Ontologies

Authors: Aliyu Isah Agaie, Masrah Azrifah Azmi Murad, Nurfadhlina Mohd Sharef, Aida Mustapha

Abstract:

Natural Language Interfaces typically support a restricted language and also have scopes and limitations that naïve users are unaware of, resulting in errors when the users attempt to retrieve information from ontologies. To overcome this challenge, an auto-suggest feature is introduced into the querying process where users are guided through the querying process using interactive query construction system. Guiding users to formulate their queries, while providing them with an unconstrained (or almost unconstrained) way to query the ontology results in better interpretation of the query and ultimately lead to an effective search. The approach described in this paper is unobtrusive and subtly guides the users, so that they have a choice of either selecting from the suggestion list or typing in full. The user is not coerced into accepting system suggestions and can express himself using fragments or full sentences.

Keywords: auto-suggest, expressiveness, habitability, natural language interface, query interpretation, user guidance

Procedia PDF Downloads 474
7370 Temperature Contour Detection of Salt Ice Using Color Thermal Image Segmentation Method

Authors: Azam Fazelpour, Saeed Reza Dehghani, Vlastimil Masek, Yuri S. Muzychka

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The study uses a novel image analysis based on thermal imaging to detect temperature contours created on salt ice surface during transient phenomena. Thermal cameras detect objects by using their emissivities and IR radiance. The ice surface temperature is not uniform during transient processes. The temperature starts to increase from the boundary of ice towards the center of that. Thermal cameras are able to report temperature changes on the ice surface at every individual moment. Various contours, which show different temperature areas, appear on the ice surface picture captured by a thermal camera. Identifying the exact boundary of these contours is valuable to facilitate ice surface temperature analysis. Image processing techniques are used to extract each contour area precisely. In this study, several pictures are recorded while the temperature is increasing throughout the ice surface. Some pictures are selected to be processed by a specific time interval. An image segmentation method is applied to images to determine the contour areas. Color thermal images are used to exploit the main information. Red, green and blue elements of color images are investigated to find the best contour boundaries. The algorithms of image enhancement and noise removal are applied to images to obtain a high contrast and clear image. A novel edge detection algorithm based on differences in the color of the pixels is established to determine contour boundaries. In this method, the edges of the contours are obtained according to properties of red, blue and green image elements. The color image elements are assessed considering their information. Useful elements proceed to process and useless elements are removed from the process to reduce the consuming time. Neighbor pixels with close intensities are assigned in one contour and differences in intensities determine boundaries. The results are then verified by conducting experimental tests. An experimental setup is performed using ice samples and a thermal camera. To observe the created ice contour by the thermal camera, the samples, which are initially at -20° C, are contacted with a warmer surface. Pictures are captured for 20 seconds. The method is applied to five images ,which are captured at the time intervals of 5 seconds. The study shows the green image element carries no useful information; therefore, the boundary detection method is applied on red and blue image elements. In this case study, the results indicate that proposed algorithm shows the boundaries more effective than other edges detection methods such as Sobel and Canny. Comparison between the contour detection in this method and temperature analysis, which states real boundaries, shows a good agreement. This color image edge detection method is applicable to other similar cases according to their image properties.

Keywords: color image processing, edge detection, ice contour boundary, salt ice, thermal image

Procedia PDF Downloads 314
7369 Development and Characterization of Biodegradable Films Based on Biopolymer Extracted From Natural Sources

Authors: Dalila Hammiche, Lisa Klaai, Sonia Imzi, Amar Boukerrou

Abstract:

The fight against plastic pollution implies the development of polymers as alternatives to synthetic polymers. Starch is a natural polymer that can easily be plasticized by means of additives. The objective of this work is to develop and characterize biodegradable biofilms based on starch, plasticized by glycerol (20 and 30%). The elaboration of the biofilms was carried out by the casting method under simple conditions. The samples were characterized by infrared spectroscopy analysis with Fourier transform (FTIR), thermogravimetric analysis, and biodegradability test. Infrared spectral analysis showed that the 30% and 20% glycerol films have the same chemical structure and no functional group changes occurred. Thermogravimetric analysis showed that a 30% glycerol film has higher thermal stability than a 20% glycerol film. Biodegradability test showed that the lower the percentage of glycerol, the more easily the biofilm degrades.

Keywords: starch, natural sources, FTIR, thermogravimetric analysis, biodegradability test

Procedia PDF Downloads 102