Search results for: city image
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6071

Search results for: city image

4511 Classifier for Liver Ultrasound Images

Authors: Soumya Sajjan

Abstract:

Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.

Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix

Procedia PDF Downloads 413
4510 Damage Micromechanisms of Coconut Fibers and Chopped Strand Mats of Coconut Fibers

Authors: Rios A. S., Hild F., Deus E. P., Aimedieu P., Benallal A.

Abstract:

The damage micromechanisms of chopped strand mats manufactured by compression of Brazilian coconut fiber and coconut fibers in different external conditions (chemical treatment) were used in this study. Mechanical analysis testing uniaxial traction were used with Digital Image Correlation (DIC). The images captured during the tensile test in the coconut fibers and coconut fiber mats showed an uncertainty of measurement in order centipixels. The initial modulus (modulus of elasticity) and tensile strength decreased with increasing diameter for the four conditions of coconut fibers. The DIC showed heterogeneous deformation fields for coconut fibers and mats and the displacement fields showed the rupture process of coconut fiber. The determination of poisson’s ratio of the mat was performed through of transverse and longitudinal deformations found in the elastic region.

Keywords: coconut fiber, mechanical behavior, digital image correlation, micromechanism

Procedia PDF Downloads 459
4509 Retina Registration for Biometrics Based on Characterization of Retinal Feature Points

Authors: Nougrara Zineb

Abstract:

The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.

Keywords: fovea, optic disc, registration, retinal images

Procedia PDF Downloads 267
4508 An Advanced Automated Brain Tumor Diagnostics Approach

Authors: Berkan Ural, Arif Eser, Sinan Apaydin

Abstract:

Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

Procedia PDF Downloads 419
4507 Investigation of New Gait Representations for Improving Gait Recognition

Authors: Chirawat Wattanapanich, Hong Wei

Abstract:

This study presents new gait representations for improving gait recognition accuracy on cross gait appearances, such as normal walking, wearing a coat and carrying a bag. Based on the Gait Energy Image (GEI), two ideas are implemented to generate new gait representations. One is to append lower knee regions to the original GEI, and the other is to apply convolutional operations to the GEI and its variants. A set of new gait representations are created and used for training multi-class Support Vector Machines (SVMs). Tests are conducted on the CASIA dataset B. Various combinations of the gait representations with different convolutional kernel size and different numbers of kernels used in the convolutional processes are examined. Both the entire images as features and reduced dimensional features by Principal Component Analysis (PCA) are tested in gait recognition. Interestingly, both new techniques, appending the lower knee regions to the original GEI and convolutional GEI, can significantly contribute to the performance improvement in the gait recognition. The experimental results have shown that the average recognition rate can be improved from 75.65% to 87.50%.

Keywords: convolutional image, lower knee, gait

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4506 Cross Ventilation Potential in an Array of Building Blocks: The Case Study of Alexandria

Authors: Bakr Gomaa

Abstract:

Wind driven Cross ventilation is achieved when air moves indoors due to the pressure difference on the building envelope. This is especially important in breezy moderate to humid settings in which fast air flow can promote thermal comfort. Studies have shown that the use of simple building forms or ignoring the urban context when studying natural ventilation can lead to inaccurate results. In this paper, the impact of the urban form of a regular array of buildings is investigated to define the impact of this urban setting on cross ventilation potential. The objective of this paper is to provide the necessary tools to achieve natural ventilation for cooling purposes in an array of building blocks context. The array urban form has been studied before for natural ventilation purposes yet to the best of our knowledge no study has considered the relationship between the urban form and the pressure patterns that develop on the buildings envelope for cross ventilation. For this we use detailed weather data for a case study city of Alexandria (Egypt), as well as a validated CFD simulations to investigate the cross ventilation potential in terms of pressure patterns in waterfront as well as in-city wind flows perpendicular to the buildings array. it was found that for both waterfront and in-city wind speeds the windows needed for cross ventilation in rear raws of the array are significantly larger than those needed for front raw.

Keywords: Alexandria, CFD, cross ventilation, pressure coefficient

Procedia PDF Downloads 387
4505 Prevalence and Associated Factors with Burnout Among Secondary School Teachers in the City of Cotonou in Benin in 2022

Authors: Antoine Vikkey Hinson, Ranty Jolianelle Dassi, Menonli Adjobimey, Rose Mikponhoue, Paul Ayelo

Abstract:

Introduction: The psychological hardship of the teaching profession maintains a chronic stress that inevitably evolves into burnout (BO) in the absence of adequate preventive measures. The objective of this study is to study the prevalence and factors associated with burnout among secondary school teachers in the city of Cotonou in 2022. Methods: This was a descriptive cross-sectional study with an analytical aim and prospective data collection that took place over a period of 2 months, from July 19 to August 19 and from October 1 to October 31, 2022. Sampling was done using a three-stage probability sampling technique. Data analysis was performed using R 4.1.1 software. Bivariate logistic regression was used to identify associated factors. The significance level chosen was 5% (p < 0.05). Results: A total of 270 teachers were included in the study, of whom 208 (77.00%) were men. The mean age of the workers was 38.03 ± 8.30 years. According to the Maslach Burnout Inventory, 58.51% of the teachers had burnout, with 41.10% of teachers in emotional exhaustion, 27.40% in depersonalization and 21.90% in loss of personal accomplishment. The severity of the syndrome was low to moderate in almost all teachers. The occurrence of BO was associated with), not practicing sports (ORa= 2,38 [1,32; 4,28]), jobs training (ORa= 1,86 [1,04; 3,34]) and an imbalance of effort/reward (ORa= 5,98 [2,24;15,98]). Conclusion: The prevalence of BO is high among secondary school teachers in the city of Cotonou. A larger scale study, including research on its consequences on the teacher and the learner, is necessary in order to act quickly to implement a prevention program.

Keywords: burnout, teachers, Maslach burnout inventory, associated factors, Benin

Procedia PDF Downloads 77
4504 Systematic Evaluation of Convolutional Neural Network on Land Cover Classification from Remotely Sensed Images

Authors: Eiman Kattan, Hong Wei

Abstract:

In using Convolutional Neural Network (CNN) for classification, there is a set of hyperparameters available for the configuration purpose. This study aims to evaluate the impact of a range of parameters in CNN architecture i.e. AlexNet on land cover classification based on four remotely sensed datasets. The evaluation tests the influence of a set of hyperparameters on the classification performance. The parameters concerned are epoch values, batch size, and convolutional filter size against input image size. Thus, a set of experiments were conducted to specify the effectiveness of the selected parameters using two implementing approaches, named pertained and fine-tuned. We first explore the number of epochs under several selected batch size values (32, 64, 128 and 200). The impact of kernel size of convolutional filters (1, 3, 5, 7, 10, 15, 20, 25 and 30) was evaluated against the image size under testing (64, 96, 128, 180 and 224), which gave us insight of the relationship between the size of convolutional filters and image size. To generalise the validation, four remote sensing datasets, AID, RSD, UCMerced and RSCCN, which have different land covers and are publicly available, were used in the experiments. These datasets have a wide diversity of input data, such as number of classes, amount of labelled data, and texture patterns. A specifically designed interactive deep learning GPU training platform for image classification (Nvidia Digit) was employed in the experiments. It has shown efficiency in both training and testing. The results have shown that increasing the number of epochs leads to a higher accuracy rate, as expected. However, the convergence state is highly related to datasets. For the batch size evaluation, it has shown that a larger batch size slightly decreases the classification accuracy compared to a small batch size. For example, selecting the value 32 as the batch size on the RSCCN dataset achieves the accuracy rate of 90.34 % at the 11th epoch while decreasing the epoch value to one makes the accuracy rate drop to 74%. On the other extreme, setting an increased value of batch size to 200 decreases the accuracy rate at the 11th epoch is 86.5%, and 63% when using one epoch only. On the other hand, selecting the kernel size is loosely related to data set. From a practical point of view, the filter size 20 produces 70.4286%. The last performed image size experiment shows a dependency in the accuracy improvement. However, an expensive performance gain had been noticed. The represented conclusion opens the opportunities toward a better classification performance in various applications such as planetary remote sensing.

Keywords: CNNs, hyperparamters, remote sensing, land cover, land use

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4503 Assessment the Infiltration of the Wastewater Ponds and Its Impact on the Water Quality of Pleistocene Aquifer at El Sadat City Using 2-D Electrical Resistivity Tomography and Water Chemistry

Authors: Abeer A. Kenawy, Usama Massoud, El-Said A. Ragab, Heba M. El-Kosery

Abstract:

2-D Electrical Resistivity Tomography (ERT) and hydrochemical study have been conducted at El Sadat industrial city. The study aims to investigate the area around the wastewater ponds to determine the possibility of water percolation from the wastewater ponds to the Pleistocene aquifer and to inspect the effect of this seepage on the groundwater chemistry. Pleistocene aquifer is the main groundwater reservoir in this area, where El Sadat city and its vicinities depend totally on this aquifer for water supplies needed for drinking, agricultural, and industrial activities. In this concern, seven ERT profiles were measured around the wastewater ponds. Besides, 10 water samples were collected from the ponds and the nearby groundwater wells. The water samples have been chemically analyzed for major cations, anions, nutrients, and heavy elements. Also, the physical parameters (pH, Alkalinity, EC, TDS) of the water samples were measured. Inspection of the ERT sections shows that they exhibit lower resistivity values towards the water ponds and higher values in opposite sides. In addition, the water table was detected at shallower depths at the same sides of lower resistivity. This could indicate a wastewater infiltration to the groundwater aquifer near the oxidation ponds. Correlation of the physical parameters and ionic concentrations of the wastewater samples with those of the groundwater samples indicates that; the ionic levels are randomly varying and no specific trend could be obtained. In addition, the wastewater samples shows some ionic levels lower than those detected in other groundwater samples. Besides, the nitrate level is higher in samples taken from the cultivated land than the wastewater samples due to the over using of nitrogen fertilizers. Then, we can say that the infiltrated water from wastewater ponds are not the main controller of the groundwater chemistry in this area, but rather the variable ionic concentrations could be attributed to local, natural, and anthropogenic processes.

Keywords: El Sadat city, ERT, hydrochemistry, percolation, wastewater ponds

Procedia PDF Downloads 356
4502 Statistical Feature Extraction Method for Wood Species Recognition System

Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

Abstract:

Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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4501 Late Roman-Byzantine Glass Bracelet Finds at Amorium and Comparison with Other Cultures

Authors: Atilla Tekin

Abstract:

Amorium was one of the biggest cities of Byzantine Empire, located under and around the modern village of Hisarköy, Emirdağ, Afyonkarahisar Province, Turkey. It was situated on the routes of trades and Byzantine military road from Constantinople to Cilicia. In addition, it was on the routes of trades and a center of bishopric. After Arab invasion, Amorium gradually lost importance. The research consists of 1372 pieces of glass bracelet finds from mostly at 1998- 2009 excavations. Most of them were found as glass bracelets fragments. The fragments are of various size, forms, colors, and decorations. During the research, they were measured and grouped according to their crossings, at first. After being photographed, they were sketched by Adobe Illustrator and decoupaged by Photoshop. All forms, colors, and decorations were specified and compared to each other. Thus, they have been tried to be dated and uncovered the place of manufacture. The importance of the research is presenting the perception of image and admiration and comparing with other cultures.

Keywords: Amorium, glass bracelets, image, Byzantine empire, jewelry

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4500 A Method Development for Improving the Efficiency of Solid Waste Collection System Using Network Analyst

Authors: Dhvanidevi N. Jadeja, Daya S. Kaul, Anurag A. Kandya

Abstract:

Municipal Solid Waste (MSW) collection in a city is performed in less effective manner which results in the poor management of the environment and natural resources. Municipal corporation does not possess efficient waste management and recycling programs because of the complex task involving many factors. Solid waste collection system depends upon various factors such as manpower, number and size of vehicles, transfer station size, dustbin size and weight, on-road traffic, and many others. These factors affect the collection cost, energy and overall municipal tax for the city. Generally, different types of waste are scattered throughout the city in a heterogeneous way that poses changes for efficient collection of solid waste. Efficient waste collection and transportation strategy must be effectively undertaken which will include optimization of routes, volume of waste, and manpower. Being these optimized, the overall cost can be reduced as the fuel and energy requirements would be less and also the municipal waste taxes levied will be less. To carry out the optimization study of collection system various data needs to be collected from the Ahmedabad municipal corporation such as amount of waste generated per day, number of workers, collection schedule, road maps, number of transfer station, location of transfer station, number of equipment (tractors, machineries), number of zones, route of collection etc. The ArcGis Network Analyst is introduced for the best routing identification applied in municipal waste collection. The simulation consists of scenarios of visiting loading spots in the municipality of Ahmedabad, considering dynamic factors like network traffic changes, closed roads due to natural or technical causes. Different routes were selected in a particular area of Ahmedabad city, and present routes were optimized to reduce the length of the routes, by using ArcGis Network Analyst. The result indicates up to 35% length minimization in the routes.

Keywords: collection routes, efficiency, municipal solid waste, optimization

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4499 Studies on the Existing Status of MSW Management in Agartala City and Recommendation for Improvement

Authors: Subhro Sarkar, Umesh Mishra

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Agartala Municipal Council (AMC) is the municipal body which regulates and governs the Agartala city. MSW management may be proclaimed as a tool which rests on the principles of public health, economy, engineering and other aesthetic or environmental factors by dealing with the controlled generation, collection, transport, processing and disposal of MSW. Around 220-250 MT of solid waste per day is collected by AMC out of which 12-14 MT is plastic and is disposed of in Devendra Chandra Nagar dumping ground (33 acres), nearly 12-15 km from the city. A survey was performed to list down the prevailing operations conducted by the AMC which includes road sweeping, garbage lifting, carcass removal, biomedical waste collection, dumping, and incineration. Different types of vehicles are engaged to carry out these operations. Door to door collection of garbage is done from the houses with the help of 220 tricycles issued by 53 NGOs. The location of the dustbin containers were earmarked which consisted of 4.5 cum, 0.6 cum containers and 0.1 cum containers, placed at various locations within the city. The total household waste was categorized as organic, recyclable and other wastes. It was found that East Pratapgarh ward produced 99.3% organic waste out of the total MSW generated in that ward which is maximum among all the wards. A comparison of the waste generation versus the family size has been made. A questionnaire for the survey of MSW from household and market place was prepared. The average waste generated (in kg) per person per day was found out for each of the wards. It has been noted that East Jogendranagar ward had a maximum per person per day waste generation of 0.493 kg/day.In view of the studies made, it has been found that AMC has failed to implement MSWM in an effective way because of the unavailability of suitable facilities for treatment and disposal of the large amount of MSW. It has also been noted that AMC is not following the standard procedures of handling MSW. Transportation system has also been found less effective leading to waste of time, money and manpower.

Keywords: MSW, waste generation, solid waste disposal, management

Procedia PDF Downloads 318
4498 CT Medical Images Denoising Based on New Wavelet Thresholding Compared with Curvelet and Contourlet

Authors: Amir Moslemi, Amir movafeghi, Shahab Moradi

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One of the most important challenging factors in medical images is nominated as noise.Image denoising refers to the improvement of a digital medical image that has been infected by Additive White Gaussian Noise (AWGN). The digital medical image or video can be affected by different types of noises. They are impulse noise, Poisson noise and AWGN. Computed tomography (CT) images are subjected to low quality due to the noise. The quality of CT images is dependent on the absorbed dose to patients directly in such a way that increase in absorbed radiation, consequently absorbed dose to patients (ADP), enhances the CT images quality. In this manner, noise reduction techniques on the purpose of images quality enhancement exposing no excess radiation to patients is one the challenging problems for CT images processing. In this work, noise reduction in CT images was performed using two different directional 2 dimensional (2D) transformations; i.e., Curvelet and Contourlet and Discrete wavelet transform(DWT) thresholding methods of BayesShrink and AdaptShrink, compared to each other and we proposed a new threshold in wavelet domain for not only noise reduction but also edge retaining, consequently the proposed method retains the modified coefficients significantly that result in good visual quality. Data evaluations were accomplished by using two criterions; namely, peak signal to noise ratio (PSNR) and Structure similarity (Ssim).

Keywords: computed tomography (CT), noise reduction, curve-let, contour-let, signal to noise peak-peak ratio (PSNR), structure similarity (Ssim), absorbed dose to patient (ADP)

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4497 Traffic Sign Recognition System Using Convolutional Neural NetworkDevineni

Authors: Devineni Vijay Bhaskar, Yendluri Raja

Abstract:

We recommend a model for traffic sign detection stranded on Convolutional Neural Networks (CNN). We first renovate the unique image into the gray scale image through with support vector machines, then use convolutional neural networks with fixed and learnable layers for revealing and understanding. The permanent layer can reduction the amount of attention areas to notice and crop the limits very close to the boundaries of traffic signs. The learnable coverings can rise the accuracy of detection significantly. Besides, we use bootstrap procedures to progress the accuracy and avoid overfitting problem. In the German Traffic Sign Detection Benchmark, we obtained modest results, with an area under the precision-recall curve (AUC) of 99.49% in the group “Risk”, and an AUC of 96.62% in the group “Obligatory”.

Keywords: convolutional neural network, support vector machine, detection, traffic signs, bootstrap procedures, precision-recall curve

Procedia PDF Downloads 123
4496 Objects Tracking in Catadioptric Images Using Spherical Snake

Authors: Khald Anisse, Amina Radgui, Mohammed Rziza

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Tracking objects on video sequences is a very challenging task in many works in computer vision applications. However, there is no article that treats this topic in catadioptric vision. This paper is an attempt that tries to describe a new approach of omnidirectional images processing based on inverse stereographic projection in the half-sphere. We used the spherical model proposed by Gayer and al. For object tracking, our work is based on snake method, with optimization using the Greedy algorithm, by adapting its different operators. The algorithm will respect the deformed geometries of omnidirectional images such as spherical neighborhood, spherical gradient and reformulation of optimization algorithm on the spherical domain. This tracking method that we call "spherical snake" permitted to know the change of the shape and the size of object in different replacements in the spherical image.

Keywords: computer vision, spherical snake, omnidirectional image, object tracking, inverse stereographic projection

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4495 Augmented Reality and Storytelling in Cities: An Application to Lisbon Street Art

Authors: Francisco Guimarães, Mauro Figueiredo, José Rodrigues

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Cities are spaces of memory with several zones (parts of cities) with their own history and cultural events. Today, cities are also marked by a form of intangible cultural heritage like street art, which creates a visual culture based on the process of reflection about the city and the world. To link these realities and create a personal user interaction with this cultural heritage it is important to capture the story and aesthetics, and find alternatives to immerse the user in these spaces of memory. To that end, this article presents a project which combines Augmented Reality technologies and concepts of Transmedia Storytelling applied to Lisbon City, using Street Art artifacts as markers in a framework of digital media-art.

Keywords: augmented reality, cultural heritage, street art, transmedia storytelling, digital media-art

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4494 Wildfires Assessed By Remote Sensed Images And Burned Land Monitoring

Authors: Maria da Conceição Proença

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This case study implements the evaluation of burned areas that suffered successive wildfires in Portugal mainland during the summer of 2017, killing more than 60 people. It’s intended to show that this evaluation can be done with remote sensing data free of charges in a simple laptop, with open-source software, describing the not-so-simple methodology step by step, to make it available for county workers in city halls of the areas attained, where the availability of information is essential for the immediate planning of mitigation measures, such as restoring road access, allocate funds for the recovery of human dwellings and assess further restoration of the ecological system. Wildfires also devastate forest ecosystems having a direct impact on vegetation cover and killing or driving away from the animal population. The economic interest is also attained, as the pinewood burned becomes useless for the noblest applications, so its value decreases, and resin extraction ends for several years. The tools described in this paper enable the location of the areas where took place the annihilation of natural habitats and establish a baseline for major changes in forest ecosystems recovery. Moreover, the result allows the follow up of the surface fuel loading, enabling the targeting and evaluation of restoration measures in a time basis planning.

Keywords: image processing, remote sensing, wildfires, burned areas evaluation, sentinel-2

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4493 Clay Develop Plasticity With Water

Authors: Boualla Nabila

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The problems created by the water in Civil Engineering are sometimes neglected or often badly posed when they are not completely ignored, and yet they are fundamental as regards both the conditions of execution of the worksites and the stability. Several damages were caused by the infiltration of water in the soils, in particular in clay regions which can swell under the effect of an increase in their water content as in the case of the Oued Tlelat clay which is made up of yellow-colored marly clays and red-colored El Maleh area. This study was carried out on soil from a site, located near the city of Oran and the city of Ain Tmouchent (northern Algeria) where we encounter many problems of cracking of buildings and bottom uplift of excavations. The study consists first of all in determining the mechanical and physical characteristics of the clay, namely the parameters of sheer, simple compression, and that of the odometer. Then the study focused on a comparison of the influence of water type on the mechanical and physical properties of swelling clay soil.

Keywords: clay, water, liquidity limit, plastic limit

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4492 Generous Edge – Inviting the Spontaneous

Authors: Ofri Earon

Abstract:

This article is about a growing focus in the city of Copenhagen – the edge zone between the private space inside the residential building and the public space out at the residential street. A slow transition between the private living room and the public urban space creates a mutual benefit. The urban space benefits from an insertion of a homey atmosphere by the extended performance of living rooms to the exterior. The dwelling benefits from belonging to a liveable neighborliness, which means an extension of the private home to a collective home (= the neighborhood). Grounded by this reciprocal value of the edge zone, through the article, it is argued that a wide generosity of the edge zones is of interest among both planners and residents. The article introduces the idea of the edge zone and its possible implications in the development of the liveable residential city. Three examples of ongoing projects at Arkitema Architects are bought to illustrate the challenges and potentials of a generous edge zone. Every example represents a specific dwelling typology in a particular urban context: (1) multi-family residential building in a previous industrial area in the city (2) new courtyard building in the city’s outskirt (3) low and dense residential area out in the suburbia. Throughout these examples, the article seeks to discuss the significance of the edge zone in forthcoming residential areas in Denmark. The analysis of the Danish examples raises the question of why a social behavior that happens spontaneously in the south of Europe has to be carefully implemented in the architecture of north of Europe. In this light, the article ends with a discussion on how to create edge zones that are not designed for a particular usage, but rather as an architectural invitation for varied social behaviors that spontaneously occur in different moments of time by different people. Finally, the article ends with a list of recommendations for the development of the generous edge zone as an open invitation for diverse usage over time.

Keywords: dwelling, edge zone, generosity, livability, urban space

Procedia PDF Downloads 358
4491 Assessment of Intra-City Road Infrastructure in Ado-Ekiti, Ekiti State, Nigeria

Authors: Aruna Kemisola Kehinde, Oyinloye Michael Ajide, Aboluje Oluwafemi Bolarinwa

Abstract:

The development of the nation's overall growth is directly impacted by the vital substructure of the transportation system. The majority of developing countries experience issues with road transportation, including limited and low-quality infrastructure. The study assessed intra-city road infrastructure in Ado-Ekiti with a view to identifying its adequacy and functionality for efficient transport in the town. To this end, the study examined the locations of the road infrastructure, characteristics of the road infrastructure, and condition of the road infrastructure. A systematic random sampling method was adopted to select respondents for the study. Data were sourced from both primary and secondary sources. A 2.5% of 20,160 households, amounting to 503 households, was used as the sample size. Data analysis was based on responses from 500 questionnaires retrieved, and the data were analyzed using descriptive statistics. The results of this study showed that based on the locations of road infrastructure, disparity exists in the distribution of infrastructure amongst the major roads. Inferences from the results gathered also demonstrated that the infrastructure that is available is very much less than the non-available infrastructure. About 50% of the respondents are satisfied that the condition of road infrastructure in Ado-Ekiti is fair. The study's recommendations for the Ekiti state government include quantifying the number of existing road infrastructure, establishing a state maintenance board to expedite their renovation, and diversifying its goals for providing road infrastructure through public-private partnership (PPP) agreements with the private sector.

Keywords: road transportation, infrastructure, availability, intra-city

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4490 Exploring Methods and Strategies for Sustainable Urban Development

Authors: Klio Monokrousou, Maria Giannopoulou

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Urban areas, as they have been developed and operate today, are areas of accumulation of a significant amount of people and a large number of activities that generate desires and reasons for traveling. The territorial expansion of the cities as well as the need to preserve the importance of the central city areas lead to the continuous increase of transportation needs which in the limited urban space results in creating serious traffic and operational problems. The modern perception of urban planning is directed towards more holistic approaches and integrated policies that make it economically competitive, socially just and more environmentally friendly. Over the last 25 years, the goal of sustainable transport development has been central to the agenda of any plan or policy for the city. The modern planning of urban space takes into account the economic and social aspects of the city and the importance of the environment to sustainable urban development. In this context, the European Union promotes direct or indirect related interventions according to the cohesion and environmental policies; many countries even had the chance to actually test them. This paper is part of a wider research still in progress and it explores the methods and processes that have been developed towards this direction and presents a review and systematic presentation of this work. The ultimate purpose of this research is to effectively use this review to create a decision making methodological framework which can be the basis of a useful operational tool for sustainable urban planning.

Keywords: methods, sustainable urban development, urban mobility, methodological framework

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4489 Study of the Benefit Analysis Using Vertical Farming Method in Urban Renewal within the Older City of Taichung

Authors: Hsu Kuo-Wei, Tan Roon Fang, Chao Jen-chih

Abstract:

Cities face environmental challenges, including over-urbanization issues, air and water quality issues, lack of green space, excess heat capture, polluted storm water runoff and lack of ecological biodiversity. The vertical farming holds the condition of technology addressing these issues by enabling more food to be produced with finite less resources use and space. Most of the existing research regarding to technology Industry of agriculture between plant factory and vertical greening, which with high costs and high-technology. Relative research developed a sustainable model for construction and operation of the vertical farm in urban housing which aims to revolutionize our daily life of food production and urban development. However, those researches focused on quantitative analysis. This study utilized relative research for key variables of benefits of vertical farming. In the second stage, utilizes Fuzzy Delphi Method to obtain the critical factors of benefits of vertical farming using in Urban Renewal by interviewing the foregoing experts. Then, Analytic Hierarchy Process is applied to find the importance degree of each criterion as the measurable indices of the vertical farming method in urban renewal within the older city of Taichung.

Keywords: urban renewal, vertical farming, urban agriculture, benefit analysis, the older city of Taichung

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4488 Exposure to Particulate Matter Taking Various Transportation Modes in Cebu City, Philippines

Authors: Mona Loraine M. Barabad, Duckshin Park, Michael E. Versoza

Abstract:

This study gives a comparison of the commuters’ exposure to particulate matter while taking different transportation mode (jeepney, motorcycle and taxi) in Cebu City, Philippines. A personal aerosol monitor (Sidepak AM510) was used for data collection; in addition, both temperature and humidity were also documented. Analysis was done and showed that Jeepney, which is the most commonly used mode in the country, has the highest PM collected having an average of 358.0μg/m^3, followed by the motorcycle with an average of 244.6 μg/m^3. The taxi recorded to have an average of 50.0 μg/m^3 and the lowest between the microenvironments sampled. The outcome was greatly significant to the traffic volume together with several factors that could possibly affect the result. However, due to the lack of time and resources, the data collected was limited. Further and thorough investigation should be implemented to provide more essential information regarding the subject.

Keywords: air quality, particulate matter, Philippines, transportation

Procedia PDF Downloads 371
4487 Imagology: The Study of Multicultural Imagery Reflected in the Heart of Elif Shafak’s 'The Bastard of Istanbul'

Authors: Mohammad Reza Haji Babai, Sepideh Ahmadkhan Beigi

Abstract:

Internationalization and modernization of the globe have played their roles in the process of cultural interaction between globalized societies and, consequently, found their way to the world of literature under the name of ‘imagology’. Imagology has made it possible for the reader to understand the author’s thoughts and judgments of others. The present research focuses on the intercultural images portrayed in the novel of a popular Turkish-French writer, Elif Shafak, about the lifestyle, traditions, habits, and social norms of Turkish, Americans, and Armenians. The novel seeks to articulate a more intricate multicultural memory of Turkishness by grieving over the Armenian massacre. This study finds that, as a mixture of multiple lifestyles and discourses, The Bastard of Istanbul reflects not only images of oriental culture but also occidental cultures. This means that the author has attempted to maintain selfhood through historical and cultural recollection, which resulted in constructing the self and another identity.

Keywords: imagology, Elif Shafak, The Bastard of Istanbul, self-image, other-image

Procedia PDF Downloads 142
4486 Locative Media Apps for Re-Building Urban Experience: Discovering Cities Through Technology

Authors: Kerem Rızvanoglu, Serhat Güney, Betül Aydoğan, Emre Kızılkaya, Ayşegül Boyalı, Onurcan Güden

Abstract:

This study investigates the urban experience of international students coming to Istanbul with exchange programs and reveals how locative media applications accompany their urban experiences. The sample of the research consists of international students who lived, perceived, and conceived the city on a daily basis during the academic year of 2022. Focusing on this particular sample would demonstrate the opportunities and authentic experiences offered by the city as well as the prevalent urban problems for the foreigners. In this regard, international students' urban experience in Istanbul, the blockages they encounter as resident tourists, the hotspots that the city offers, and the role of locative media in enriching the urban experience are the main axes to be evaluated. In the first step of the multi-staged research, we conduct an online qualitative survey with a sample; then, we evaluate the data obtained from the survey using cluster analysis to identify the urban experience, consumption habits, and tastes. In the final stage, digital ethnographic fieldwork will be carried out with representative personas identified by the cluster analysis. With this field research on the urban experience accompanied by locative media applications, suggestions will be developed by evaluating the opportunities these applications offer to enrich the urban practice of foreigners.

Keywords: digital ethnography, international students, locative media applications, urban experience

Procedia PDF Downloads 140
4485 Deep Learning Based on Image Decomposition for Restoration of Intrinsic Representation

Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

Abstract:

Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

Procedia PDF Downloads 190
4484 Reviving the Past, Enhancing the Future: Preservation of Urban Heritage Connectivity as a Tool for Developing Liveability in Historical Cities in Jordan, Using Salt City as a Case Study

Authors: Sahar Yousef, Chantelle Niblock, Gul Kacmaz

Abstract:

Salt City, in the context of Jordan’s heritage landscape, is a significant case to explore when it comes to the interaction between tangible and intangible qualities of liveable cities. Most city centers, including Jerash, Salt, Irbid, and Amman, are historical locations. Six of these extraordinary sites were designated UNESCO World Heritage Sites. Jordan is widely acknowledged as a developing country characterized by swift urbanization and unrestrained expansion that exacerbate the challenges associated with the preservation of historic urban areas. The aim of this study is to conduct an examination and analysis of the existing condition of heritage connectivity within heritage city centers. This includes outdoor staircases, pedestrian pathways, footpaths, and other public spaces. Case study-style analysis of the urban core of As-Salt is the focus of this investigation. Salt City is widely acknowledged for its substantial tangible and intangible cultural heritage and has been designated as ‘The Place of Tolerance and Urban Hospitality’ by UNESCO since 2021. Liveability in urban heritage, particularly in historic city centers, incorporates several factors that affect our well-being; its enhancement is a critical issue in contemporary society. The dynamic interaction between humans and historical materials, which serves as a vehicle for the expression of their identity and historical narrative, constitutes preservation that transcends simple conservation. This form of engagement enables people to appreciate the diversity of their heritage recognising their previous and planned futures. Heritage preservation is inextricably linked to a larger physical and emotional context; therefore, it is difficult to examine it in isolation. Urban environments, including roads, structures, and other infrastructure, are undergoing unprecedented physical design and construction requirements. Concurrently, heritage reinforces a sense of affiliation with a particular location or space and unifies individuals with their ancestry, thereby defining their identity. However, a considerable body of research has focused on the conservation of heritage buildings in a fragmented manner without considering their integration within a holistic urban context. Insufficient attention is given to the significance of the physical and social roles played by the heritage staircases and baths that serve as connectors between these valued historical buildings. In doing so, the research uses a methodology that is based on consensus. Given that liveability is considered a complex matter with several dimensions. The discussion starts by making initial observations on the physical context and societal norms inside the urban center while simultaneously establishing the definitions of liveability and connectivity and examining the key criteria associated with these concepts. Then, identify the key elements that contribute to liveable connectivity within the framework of urban heritage in Jordanian city centers. Some of the outcomes that will be discussed in the presentation are: (1) There is not enough connectivity between heritage buildings as can be seen, for example, between buildings in Jada and Qala'. (2) Most of the outdoor spaces suffer from physical issues that hinder their use by the public, like in Salalem. (3) Existing activities in the city center are not well attended because of lack of communication between the organisers and the citizens.

Keywords: connectivity, Jordan, liveability, salt city, tangible and intangible heritage, urban heritage

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4483 Characterization of Anisotropic Deformation in Sandstones Using Micro-Computed Tomography Technique

Authors: Seyed Mehdi Seyed Alizadeh, Christoph Arns, Shane Latham

Abstract:

Geomechanical characterization of rocks in detail and its possible implications on flow properties is an important aspect of reservoir characterization workflow. In order to gain more understanding of the microstructure evolution of reservoir rocks under stress a series of axisymmetric triaxial tests were performed on two different analogue rock samples. In-situ compression tests were coupled with high resolution micro-Computed Tomography to elucidate the changes in the pore/grain network of the rocks under pressurized conditions. Two outcrop sandstones were chosen in the current study representing a various cementation status of well-consolidated and weakly-consolidated granular system respectively. High resolution images were acquired while the rocks deformed in a purpose-built compression cell. A detailed analysis of the 3D images in each series of step-wise compression tests (up to the failure point) was conducted which includes the registration of the deformed specimen images with the reference pristine dry rock image. Digital Image Correlation (DIC) technique based on the intensity of the registered 3D subsets and particle tracking are utilized to map the displacement fields in each sample. The results suggest the complex architecture of the localized shear zone in well-cemented Bentheimer sandstone whereas for the weakly-consolidated Castlegate sandstone no discernible shear band could be observed even after macroscopic failure. Post-mortem imaging a sister plug from the friable rock upon undergoing continuous compression reveals signs of a shear band pattern. This suggests that for friable sandstones at small scales loading mode may affect the pattern of deformation. Prior to mechanical failure, the continuum digital image correlation approach can reasonably capture the kinematics of deformation. As failure occurs, however, discrete image correlation (i.e. particle tracking) reveals superiority in both tracking the grains as well as quantifying their kinematics (in terms of translations/rotations) with respect to any stage of compaction. An attempt was made to quantify the displacement field in compression using continuum Digital Image Correlation which is based on the reference and secondary image intensity correlation. Such approach has only been previously applied to unconsolidated granular systems under pressure. We are applying this technique to sandstones with various degrees of consolidation. Such element of novelty will set the results of this study apart from previous attempts to characterize the deformation pattern in consolidated sands.

Keywords: deformation mechanism, displacement field, shear behavior, triaxial compression, X-ray micro-CT

Procedia PDF Downloads 190
4482 Image Instance Segmentation Using Modified Mask R-CNN

Authors: Avatharam Ganivada, Krishna Shah

Abstract:

The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

Procedia PDF Downloads 75