Search results for: fixed live camera images

Authors: Siddharth Rana

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As we know so far, there are 3 dimensions that we are capable of interpreting and perceiving, and there is a 4th dimension, called time, about which we don’t know much yet. We, as humans, live in the 4th dimension, not the 3rd. We travel 3 dimensionally but cannot yet travel 4 dimensionally; perhaps if we could, then visiting the past and the future would be like climbing a mountain or going down a road. So far, we humans are not even capable of imagining any higher dimensions than the three dimensions in which we can travel. We are the beings of the 4th dimension; we are the beings of time; that is why we can travel 3 dimensionally; however, if, say, there were beings of the 5th dimension, then they would easily be able to travel 4 dimensionally, i.e., they could travel in the 4th dimension as well. Beings of the 5th dimension can easily time travel. However, beings of the 4th dimension, like us, cannot time travel because we live in a 4-D world, traveling 3 dimensionally. That means to ever do time travel, we just need to go to a higher dimension and not only perceive it but also be able to travel in it. However, traveling to the past is not very possible, unlike traveling to the future. Even if traveling to the past were possible, it would be very unlikely that an event in the past would be changed. In this paper, some approaches are provided to define time, our movement in time to the future, some aspects of time travel using dimensions, and how we can perceive a higher dimension.

Keywords: time, dimensions, String theory, relativity

Procedia PDF Downloads 81

Authors: B. L. Gadiga

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This study assesses the major ecological zones in Nigeria with the view to understanding the spatial pattern of vegetation zones and the implications on conservation within the period of sixteen (16) years. Satellite images used for this study were acquired from the SPOT-VEGETATION between 1998 and 2013. The annual NDVI images selected for this study were derived from SPOT-4 sensor and were acquired within the same season (November) in order to reduce differences in spectral reflectance due to seasonal variations. The images were sliced into five classes based on literatures and knowledge of the area (i.e. <0.16 Non-Vegetated areas; 0.16-0.22 Sahel Savannah; 0.22-0.40 Sudan Savannah, 0.40-0.47 Guinea Savannah and >0.47 Forest Zone). Classification of the 1998 and 2013 images into forested and non forested areas showed that forested area decrease from 511,691 km² in 1998 to 478,360 km² in 2013. Differencing change detection method was performed on 1998 and 2013 NDVI images to identify areas of ecological concern. The result shows that areas undergoing vegetation degradation covers an area of 73,062 km² while areas witnessing some form restoration cover an area of 86,315 km². The result also shows that there is a weak correlation between rainfall and the vegetation zones. The non-vegetated areas have a correlation coefficient (r) of 0.0088, Sahel Savannah belt 0.1988, Sudan Savannah belt -0.3343, Guinea Savannah belt 0.0328 and Forest belt 0.2635. The low correlation can be associated with the encroachment of the Sudan Savannah belt into the forest belt of South-eastern part of the country as revealed by the image analysis. The degradation of the forest vegetation is therefore responsible for the serious erosion problems witnessed in the South-east. The study recommends constant monitoring of vegetation and strict enforcement of environmental laws in the country.

Keywords: vegetation, NDVI, SPOT-vegetation, ecology, degradation

Procedia PDF Downloads 196

Authors: Arun Prasad

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Background: Robotic Bariatric Surgery is a good option for the super obese where laparoscopy demands challenging technical skills. Gastric bypass can be difficult due to inability of the robot to work in two quadrants at the same time. Lonroth technique of gastric bypass involves a totally supracolic surgery where all anastomosis are done in one quadrant only. Methods: We have done 78 robotic gastric bypass surgeries using the modified Lonroth technique. The robot is docked above the head of the patient in the midline. Camera port is placed supra umbilically. Two ports are placed on the left side of the patient and one port on the right side of the patient. An assistant port is placed between the camera port and right sided robotic port for use of stapler. Gastric pouch is made first followed by the gastrojejunostomy that is a four layered sutured anastomosis. Jejuno jejunostomy is then performed followed by a leak test and then the jejunum is divided. A 150 cm biliopancreatic limb and a 75 cm alimentary limb are finally obtained. Mesenteric and Petersen’s defects are then closed. Results: All patients had a successful robotic procedure. Mean time taken in the first 5 cases was 130 minutes. This reduced to a mean of 95 minutes in the last five cases. There were no intraoperative or post operative complications. Conclusions: While a hybrid technique of partly laparoscopic and partly robotic gastric bypass has been done at many centres, we feel using the modified Lonroth technique, a totally robotic gastric bypass surgery fully utilizes the potential of robotic bariatric surgery.

Keywords: robot, bariatric, totally robotic, gastric bypass

Procedia PDF Downloads 232

Authors: M. S. Jouini, A. Al-Sumaiti, M. Tembely, K. Rahimov

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Characterizing rock properties of carbonate reservoirs is highly challenging because of rock heterogeneities revealed at several length scales. In the last two decades, the Digital Rock Physics (DRP) approach was implemented successfully in sandstone rocks reservoirs in order to understand rock properties behaviour at the pore scale. This approach uses 3D X-ray Microtomography images to characterize pore network and also simulate rock properties from these images. Even though, DRP is able to predict realistic rock properties results in sandstone reservoirs it is still suffering from a lack of clear workflow in carbonate rocks. The main challenge is the integration of properties simulated at different scales in order to obtain the effective rock property of core plugs. In this paper, we propose several approaches to characterize absolute permeability in some carbonate core plugs samples using multi-scale numerical simulation workflow. In this study, we propose a procedure to simulate porosity and absolute permeability of a carbonate rock sample using textures of Micro-Computed Tomography images. First, we discretize X-Ray Micro-CT image into a regular grid. Then, we use a textural parametric model to classify each cell of the grid using supervised classification. The main parameters are first and second order statistics such as mean, variance, range and autocorrelations computed from sub-bands obtained after wavelet decomposition. Furthermore, we fill permeability property in each cell using two strategies based on numerical simulation values obtained locally on subsets. Finally, we simulate numerically the effective permeability using Darcy’s law simulator. Results obtained for studied carbonate sample shows good agreement with the experimental property.

Keywords: multiscale modeling, permeability, texture, micro-tomography images

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Authors: B. Ramesh Naik, T. Venugopal

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This paper presents a novel approach which improves the high-level semantics of images based on machine learning approach. The contemporary approaches for image retrieval and object recognition includes Fourier transforms, Wavelets, SIFT and HoG. Though these descriptors helpful in a wide range of applications, they exploit zero order statistics, and this lacks high descriptiveness of image features. These descriptors usually take benefit of primitive visual features such as shape, color, texture and spatial locations to describe images. These features do not adequate to describe high-level semantics of the images. This leads to a gap in semantic content caused to unacceptable performance in image retrieval system. A novel method has been proposed referred as discriminative learning which is derived from machine learning approach that efficiently discriminates image features. The analysis and results of proposed approach were validated thoroughly on WANG and Caltech-101 Databases. The results proved that this approach is very competitive in content-based image retrieval.

Keywords: CBIR, discriminative learning, region weight learning, scale invariant feature transforms

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Authors: Tempe S. F. Adams, Michael J. Chase, Tracey L. Rogers, Keith E. A. Leggett

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Transfrontier wildlife corridors can be successful conservation tools, connecting protected areas and reducing the impact of habitat fragmentation on mobile species. Urban wildlife corridors have been proposed as a potential mitigation tool to facilitate the passage of elephants through towns without causing conflict with urban communities. However, because such corridors are typically narrow and close to human development, wildlife (particularly large mammals) may be less likely to use them. We used remote-sensor camera traps and global positioning system collars to identify the movement patterns of African elephants Loxondonta africana through narrow, urban corridors in Botswana. The corridors were in three types of human-dominated land-use designations with varying levels of human activity: agricultural, industrial and open space recreational land. We found that elephants used the corridors within all three land-use designations and we identified, using a model selection approach, that season, time of day and rainfall were important factors in determining the presence of elephants in the corridors. Elephants moved more slowly through the narrow corridors compared with their movement patterns through broader, wide-ranging corridors. Our results indicate that urban wildlife corridors are useful for facilitating elephants to pass through urban areas.

Keywords: camera traps, conservation, human-elephant coexistence, land management, urban wildlife corridors

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Authors: Mohammad Ali Oghabian, Reza Reiazi, Esmaeel Parsai, Mehdi Aghili, Ramin Jaberi

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In this project a new procedure has been introduced for utilizing digitally reconstructed radiograph from MRI images in Brachytherapy treatment planning. This procedure enables us to localize the tumor volume and delineate the extent of critical structures in vicinity of tumor volume. The aim of this project was to improve the accuracy of dose delivered to targets of interest in 2D treatment planning system.

Keywords: brachytherapy, cervix, digitally reconstructed radiographs, lymph node

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Authors: Ahmed F. Elaksher, Islam Omar

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In this project, we used MOLA-based DEMs to orthorectify HiRISE optical images. The MOLA data was interpolated using the kriging interpolation technique. Corresponding tie points were then digitized from both datasets. These points were employed in co-registering both datasets using GIS analysis tools. Different transformation models, including the affine and projective transformation models, were used with different sets and distributions of tie points. Additionally, we evaluated the use of the MOLA elevations in co-registering the MOLA and HiRISE datasets. The planimetric RMSEs achieved for each model are reported. Results suggested the use of 3D-2D transformation models.

Keywords: photogrammetry, Mars, MOLA, HiRISE

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Authors: Ravi Vishwanath, Saumya Kumaar, S. N. Omkar

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Brain-computer interfacing (BCI) is a technology that is almost four decades old, and it was developed solely for the purpose of developing and enhancing the impact of neuroprosthetics. However, in the recent times, with the commercialization of non-invasive electroencephalogram (EEG) headsets, the technology has seen a wide variety of applications like home automation, wheelchair control, vehicle steering, etc. One of the latest developed applications is the mind-controlled quadrotor unmanned aerial vehicle. These applications, however, do not require a very high-speed response and give satisfactory results when standard classification methods like Support Vector Machine (SVM) and Multi-Layer Perceptron (MLPC). Issues are faced when there is a requirement for high-speed control in the case of fixed-wing unmanned aerial vehicles where such methods are rendered unreliable due to the low speed of classification. Such an application requires the system to classify data at high speeds in order to retain the controllability of the vehicle. This paper proposes a novel method of classification which uses a combination of Common Spatial Paradigm and Linear Discriminant Analysis that provides an improved classification accuracy in real time. A non-linear SVM based classification technique has also been discussed. Further, this paper discusses the implementation of the proposed method on a fixed-wing and VTOL unmanned aerial vehicles.

Keywords: brain-computer interface, classification, machine learning, unmanned aerial vehicles

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Authors: Prosper Kudzanai Mushauri

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In issues of anomalous experiences commonly referred to as madness or mental illness, attempts have been made to deal with it so that people manage to live their lives in a more functional way. It is in this stance that psychiatry has sort of portraying itself as seeking to ameliorate perturbations which individuals live with via nosological systems and use of medicine to anomalous experiences. It is from this hegemony that has led to the untold harm which people living with madness have endured from antique to contemporary life. The paper reflects via a literature review on the history of psychiatry and argues that it is akin to contemporary psychiatry to be involved in iatrogenic acts. As antique psychiatry meddled with gory issues of inhumanity, deceit and mass murders which some of those the contemporary psychiatry has not weaned itself from such diabolical acts. The objective of the paper is to suggest to psychiatry that it has not comported to the mores of psychological ethics. In doing this, the paper hopes that psychiatry will reflect and reform its curricular and praxis so that it comports to ethical standards in psychological science in ameliorating anomalous experiences.

Keywords: nosology, psychiatry, madness, diagnosis, eugenics

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Authors: Haitao Yang, Jianming Lv, Fei Xu, Xintong Wang, Yilin Huang, Lanting Xia, Xuewu Zhu

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Given a fixed fund, purchasing fewer hosts of higher capability or inversely more of lower capability is a must-be-made trade-off in practices for building a Hadoop big data platform. An exploratory study is presented for a Housing Big Data Platform project (HBDP), where typical big data computing is with SQL queries of aggregate, join, and space-time condition selections executed upon massive data from more than 10 million housing units. In HBDP, an empirical formula was introduced to predict the performance of host clusters potential for the intended typical big data computing, and it was shaped via a regression approach. With this empirical formula, it is easy to suggest an optimal cluster configuration. The investigation was based on a typical Hadoop computing ecosystem HDFS+Hive+Spark. A proper metric was raised to measure the performance of Hadoop clusters in HBDP, which was tested and compared with its predicted counterpart, on executing three kinds of typical SQL query tasks. Tests were conducted with respect to factors of CPU benchmark, memory size, virtual host division, and the number of element physical host in cluster. The research has been applied to practical cluster procurement for housing big data computing.

Keywords: Hadoop platform planning, optimal cluster scheme at fixed-fund, performance predicting formula, typical SQL query tasks

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Authors: Burçin Saltık, Levent Genç

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In this study, it was aimed to determine a route for identification of rice cultivation areas within Thrace and Marmara regions of Turkey using remote sensing and GIS. Landsat 8 (OLI-TIRS) imageries acquired in production season of 2013 with 181/32 Path/Row number were used. Four different seasonal images were generated utilizing original bands and different transformation techniques. All images were classified individually using supervised classification techniques and Land Use Land Cover Maps (LULC) were generated with 8 classes. Areas (ha, %) of each classes were calculated. In addition, district-based rice distribution maps were developed and results of these maps were compared with Turkish Statistical Institute (TurkSTAT; TSI)’s actual rice cultivation area records. Accuracy assessments were conducted, and most accurate map was selected depending on accuracy assessment and coherency with TSI results. Additionally, rice areas on over 4° slope values were considered as mis-classified pixels and they eliminated using slope map and GIS tools. Finally, randomized rice zones were selected to obtain maximum-minimum value ranges of each date (May, June, July, August, September images separately) NDVI, LSWI, and LST images to test whether they may be used for rice area determination via raster calculator tool of ArcGIS. The most accurate classification for rice determination was obtained from seasonal LSWI LULC map, and considering TSI data and accuracy assessment results and mis-classified pixels were eliminated from this map. According to results, 83151.5 ha of rice areas exist within study area. However, this result is higher than TSI records with an area of 12702.3 ha. Use of maximum-minimum range of rice area NDVI, LSWI, and LST was tested in Meric district. It was seen that using the value ranges obtained from July imagery, gave the closest results to TSI records, and the difference was only 206.4 ha. This difference is normal due to relatively low resolution of images. Thus, employment of images with higher spectral, spatial, temporal and radiometric resolutions may provide more reliable results.

Keywords: landsat 8 (OLI-TIRS), LST, LSWI, LULC, NDVI, rice

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Authors: Moch Agus Choiron

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Crash box design has been developed to obtain optimum energy absorption. In this study, two-segment crash box design with holes is investigated under oblique load. The deformation behavior and crash energy absorption are observed. The analysis was performed using finite element method. The crash test components were impactor, crash box, and fixed rigid base. Impactor and the fixed base material are modelled as a rigid, and crash box material as bilinear isotropic hardening. The models consist of 2 and 4 holes laid within ¼, ½ and ¾ from first segment length. 100 mm aluminum crash box and frontal crash velocity of 16 km/jam were selected. Based on simulation results, it can be concluded that 2 holes located at ¾ has the largest crash energy absorption. This behavior associated with deformation pattern, which produces higher number of folding than other models.

Keywords: crash Box, two-segments, holes configuration, oblique load, deformation pattern

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Authors: Zama Mahmood

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The increasing demand of food management, monitoring of the crop growth and forecasting its yield well before harvest is very important. These days, yield assessment together with monitoring of crop development and its growth are being identified with the help of satellite and remote sensing images. Studies using remote sensing data along with field survey validation reported high correlation between vegetation indices and yield. With the development of remote sensing technique, the detection of crop and its mechanism using remote sensing data on regional or global scales have become popular topics in remote sensing applications. Punjab, specially the southern Punjab region is extremely favourable for wheat production. But measuring the exact amount of wheat production is a tedious job for the farmers and workers using traditional ground based measurements. However, remote sensing can provide the most real time information. In this study, using the Normalized Differentiate Vegetation Index (NDVI) indicator developed from Landsat satellite images, the yield of wheat has been estimated during the season of 2013-2014 for the agricultural area around Bahawalpur. The average yield of the wheat was found 35 kg/acre by analysing field survey data. The field survey data is in fair agreement with the NDVI values extracted from Landsat images. A correlation between wheat production (ton) and number of wheat pixels has also been calculated which is in proportional pattern with each other. Also a strong correlation between the NDVI and wheat area was found (R2=0.71) which represents the effectiveness of the remote sensing tools for crop monitoring and production estimation.

Keywords: landsat, NDVI, remote sensing, satellite images, yield

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Authors: Preetham Shankapal, Jill King, Kori Murray, Corby Martin, Paula Giselman, Jason Hicks, Owen Carmicheal

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Activation of reward and satiety networks in the brain while processing palatable food cues, as well as functional connectivity during rest has been studied using functional Magnetic Resonance Imaging of the brain in various obesity phenotypes. However, functional connectivity within the reward and satiety network during food cue processing is understudied. 14 obese individuals underwent two fMRI scans during viewing of Macronutrient Picture System images. Each scan included two blocks of images of High Sugar/High Fat (HSHF), High Carbohydrate/High Fat (HCHF), Low Sugar/Low Fat (LSLF) and also non-food images. Seed voxels within seven food reward relevant ROIs: Insula, putamen and cingulate, precentral, parahippocampal, medial frontal and superior temporal gyri were isolated based on a prior meta-analysis. Beta series correlation for task-related functional connectivity between these seed voxels and the rest of the brain was computed. Voxel-level differences in functional connectivity were calculated between: first and the second scan; individuals who saw novel (N=7) vs. Repeated (N=7) images in the second scan; and between the HC/HF, HSHF blocks vs LSLF and non-food blocks. Computations and analysis showed that during food image viewing, reward network ROIs showed significant functional connectivity with each other and with other regions responsible for attentional and motor control, including inferior parietal lobe and precentral gyrus. These functional connectivity values were heightened among individuals who viewed novel HS/HF images in the second scan. In the second scan session, functional connectivity was reduced within the reward network but increased within attention, memory and recognition regions, suggesting habituation to reward properties and increased recollection of previously viewed images. In conclusion it can be inferred that Functional Connectivity within reward network and between reward and other brain regions, varies by important experimental conditions during food photography viewing, including habituation to shown foods.

Keywords: fMRI, functional connectivity, task-based, beta series correlation

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Authors: Ali Almadan, Anoop Krishnan, Ajita Rattani

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Facial recognition is a widely adopted technology in surveillance, border control, healthcare, banking services, and lately, in mobile user authentication with Apple introducing “Face ID” moniker with iPhone X. A lot of research has been conducted in the area of face recognition on datasets captured by surveillance cameras, DSLR, and mobile devices. Recently, face recognition technology has also been deployed on body-worn cameras to keep officers safe, enabling situational awareness and providing evidence for trial. However, limited academic research has been conducted on this topic so far, without the availability of any publicly available datasets with a sufficient sample size. This paper aims to advance research in the area of face recognition using body-worn cameras. To this aim, the contribution of this work is two-fold: (1) collection of a dataset consisting of a total of 136,939 facial images of 102 subjects captured using body-worn cameras in in-door and daylight conditions and (2) evaluation of various deep-learning architectures for face identification on the collected dataset. Experimental results suggest a maximum True Positive Rate(TPR) of 99.86% at False Positive Rate(FPR) of 0.000 obtained by SphereFace based deep learning architecture in daylight condition. The collected dataset and the baseline algorithms will promote further research and development. A downloadable link of the dataset and the algorithms is available by contacting the authors.

Keywords: face recognition, body-worn cameras, deep learning, person identification

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Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman

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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.

Keywords: computer vision, deep learning, object detection, semiconductor

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Authors: Rashmi Yadawad, Disha Narayanan, Ravi Gautam

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Through Wall Radar Imaging is gaining increasing importance now a days in the field of Defense and one of the most important criteria that forms the basis for the image quality obtained is the Cross-Range resolution of the image. In this research paper, the Bilateral Back projection algorithm has been implemented for Through Wall Radar Imaging. The sole purpose is to enhance the resolution in the cross range direction of the obtained Back projection image. Synthetic Data is generated for two targets which are placed at various locations in a room of dimensions 8 m by 6m. Two algorithms namely, simple back projection and Bilateral Back projection have been implemented, images are obtained and the obtained images are compared. Numerical simulations have been coded in MATLAB and experimental results of the two algorithms have been shown. Based on the comparison between the two images, it can be clearly seen that the ringing effect and chess board effect have been heavily reduced in the bilaterally back projected image and hence promising results are obtained giving a relatively sharper image with relatively well defined edges.

Keywords: through wall radar imaging, bilateral back projection, cross range resolution, synthetic data

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Authors: Ferit Çakıcı, M. Kemal Leblebicioğlu

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In this study, characteristics and flight test analysis of a fixed-wing unmanned aerial vehicle (UAV) with hover capability is analyzed. The base platform is chosen as a conventional airplane with throttle, ailerons, elevator and rudder control surfaces, that inherently allows level flight. Then this aircraft is mechanically modified by the integration of vertical propellers as in multi rotors in order to provide hover capability. The aircraft is modeled using basic aerodynamical principles and linear models are constructed utilizing small perturbation theory for trim conditions. Flight characteristics are analyzed by benefiting from linear control theory’s state space approach. Distinctive features of the aircraft are discussed based on analysis results with comparison to conventional aircraft platform types. A hybrid control system is proposed in order to reveal unique flight characteristics. The main approach includes design of different controllers for different modes of operation and a hand-over logic that makes flight in an enlarged flight envelope viable. Simulation tests are performed on mathematical models that verify asserted algorithms. Flight tests conducted in real world revealed the applicability of the proposed methods in exploiting fixed-wing and rotary wing characteristics of the aircraft, which provide agility, survivability and functionality.

Keywords: flight test, flight characteristics, hybrid aircraft, unmanned aerial vehicle

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Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

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Authors: Geeta Kasana, Kulbir Singh, Satvinder Singh

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In this paper, a steganographic scheme for digital images using Integer Wavelet Transform (IWT) is proposed. The cover image is decomposed into wavelet sub bands using IWT. Each of the subband is divided into blocks of equal size and secret data is embedded into the largest and smallest pixel values of each block of the subband. Visual quality of stego images is acceptable as PSNR between cover image and stego is above 40 dB, imperceptibility is maintained. Experimental results show better tradeoff between capacity and visual perceptivity compared to the existing algorithms. Maximum possible error analysis is evaluated for each of the wavelet subbands of an image.

Keywords: DWT, IWT, MSE, PSNR

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Authors: Majed Al-Quran

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Language arts, as a domain of learning, principally covers the study of literature and the arts of reading and writing. These three areas deal with the art of conceptualizing and representing in language how people live and might live their lives. And all three are significantly concerned with gaining command of language and expression. Of course, there is no command of language separate from the command of thought. The paper addresses how EFL learners can develop insight and sense into what can be earned from literature and a sense of putting experiences into words. It further shows how critical thinking-based instruction helps students develop command of their own ideas, which consequently requires command over the words in which they express them. Critical thinking stipulates that in words and ideas, there is the power to create systems of beliefs and multiple conceptions of life. Remodeling language lessons aim at overcoming the challenge of stimulating learners to cultivate a new and different conception of language skills, including those of reading and writing.

Keywords: language arts, remodeling, critical thinking, pedagogy

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Authors: C. A. Anser Pasha

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In this paper, a new Vehicular Speed Detection Camera System that is applicable as an alternative to traditional radars with the same accuracy or even better is presented. The real-time measurement and analysis of various traffic parameters such as speed and number of vehicles are increasingly required in traffic control and management. Image processing techniques are now considered as an attractive and flexible method for automatic analysis and data collections in traffic engineering. Various algorithms based on image processing techniques have been applied to detect multiple vehicles and track them. The SDCS processes can be divided into three successive phases; the first phase is Objects detection phase, which uses a hybrid algorithm based on combining an adaptive background subtraction technique with a three-frame differencing algorithm which ratifies the major drawback of using only adaptive background subtraction. The second phase is Objects tracking, which consists of three successive operations - object segmentation, object labeling, and object center extraction. Objects tracking operation takes into consideration the different possible scenarios of the moving object like simple tracking, the object has left the scene, the object has entered the scene, object crossed by another object, and object leaves and another one enters the scene. The third phase is speed calculation phase, which is calculated from the number of frames consumed by the object to pass by the scene.

Keywords: radar, image processing, detection, tracking, segmentation

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Authors: Ali A. Ukasha, Majdi F. Elbireki, Mohammad F. Abdullah

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Data security needed in data transmission, storage, and communication to ensure the security. This paper is divided into two parts. This work interests with the color image which is decomposed into red, green and blue channels. The blue and green channels are compressed using 3-levels discrete wavelet transform. The Arnold transform uses to changes the locations of red image channel pixels as image scrambling process. Then all these channels are encrypted separately using the key image that has same original size and are generating using private keys and modulo operations. Performing the X-OR and modulo operations between the encrypted channels images for image pixel values change purpose. The extracted contours from color images recovery can be obtained with accepted level of distortion using single step parallel contour extraction (SSPCE) method. Experiments have demonstrated that proposed algorithm can fully encrypt 2D Color images and completely reconstructed without any distortion. Also shown that the analyzed algorithm has extremely large security against some attacks like salt and pepper and Jpeg compression. Its proof that the color images can be protected with a higher security level. The presented method has easy hardware implementation and suitable for multimedia protection in real time applications such as wireless networks and mobile phone services.

Keywords: SSPCE method, image compression and salt and peppers attacks, bitplanes decomposition, Arnold transform, color image, wavelet transform, lossless image encryption

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Authors: Abdulkader Helwan

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Iris cancer, so called intraocular melanoma is a cancer that starts in the iris; the colored part of the eye that surrounds the pupil. There is a need for an accurate and cost-effective iris cancer detection system since the available techniques used currently are still not efficient. The combination of the image processing and artificial neural networks has a great efficiency for the diagnosis and detection of the iris cancer. Image processing techniques improve the diagnosis of the cancer by enhancing the quality of the images, so the physicians diagnose properly. However, neural networks can help in making decision; whether the eye is cancerous or not. This paper aims to develop an intelligent system that stimulates a human visual detection of the intraocular melanoma, so called iris cancer. The suggested system combines both image processing techniques and neural networks. The images are first converted to grayscale, filtered, and then segmented using prewitt edge detection algorithm to detect the iris, sclera circles and the cancer. The principal component analysis is used to reduce the image size and for extracting features. Those features are considered then as inputs for a neural network which is capable of deciding if the eye is cancerous or not, throughout its experience adopted by many training iterations of different normal and abnormal eye images during the training phase. Normal images are obtained from a public database available on the internet, “Mile Research”, while the abnormal ones are obtained from another database which is the “eyecancer”. The experimental results for the proposed system show high accuracy 100% for detecting cancer and making the right decision.

Keywords: iris cancer, intraocular melanoma, cancerous, prewitt edge detection algorithm, sclera

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Authors: Khalid. M. O. Elmabrok, M. L. Burby, G. G. Nasr

Abstract:

Flow instability during gas lift operation is caused by three major phenomena – the density wave oscillation, the casing heading pressure and the flow perturbation within the two-phase flow region. This paper focuses on the causes and the effect of flow instability during gas lift operation and suggests ways to control it in order to maximise productivity during gas lift operations. A laboratory-scale two-phase flow system to study the effects of flow perturbation was designed and built. The apparatus is comprised of a 2 m long by 66 mm ID transparent PVC pipe with air injection point situated at 0.1 m above the base of the pipe. This is the point where stabilised bubbles were visibly clear after injection. Air is injected into the water filled transparent pipe at different flow rates and pressures. The behavior of the different sizes of the bubbles generated within the two-phase region was captured using a digital camera and the images were analysed using the advanced image processing package. It was observed that the average maximum bubbles sizes increased with the increase in the length of the vertical pipe column from 29.72 to 47 mm. The increase in air injection pressure from 0.5 to 3 bars increased the bubble sizes from 29.72 mm to 44.17 mm and then decreasing when the pressure reaches 4 bars. It was observed that at higher bubble velocity of 6.7 m/s, larger diameter bubbles coalesce and burst due to high agitation and collision with each other. This collapse of the bubbles causes pressure drop and reverse flow within two phase flow and is the main cause of the flow instability phenomena.

Keywords: gas lift instability, bubbles forming, bubbles collapsing, image processing

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Authors: Junaid Kameran Ahmed

Abstract:

A laminated plate composite of graphite/epoxy has been analyzed dynamically in the present work by using a quadratic element (8-node diso-parametric), and by depending on 1^st order shear deformation theory, every node in this element has 6-degrees of freedom (displacement in x, y, and z axis and twist about x, y, and z axis). The dynamic analysis in the present work covered parametric studies on a composite laminated plate (square plate) to determine its effect on the natural frequency of the plate. The parametric study is represented by set of changes (plate thickness, number of layers, support conditions, layer orientation), and the plates have been simulated by using ANSYS package 12. The boundary conditions considered in this study, at all four edges of the plate, are simply supported and fixed boundary condition. The results obtained from ANSYS program show that the natural frequency for both fixed and simply supported increases with increasing the number of layers, but this increase in the natural frequency for the first five modes will be neglected after 10 layers. And it is observed that the natural frequency of a composite laminated plate will change with the change of ply orientation, the natural frequency increases and it will be at maximum with angle 45 of ply for simply supported laminated plate, and maximum natural frequency will be with cross-ply (0/90) for fixed laminated composite plate. It is also observed that the natural frequency increase is approximately doubled when the thickness is doubled.

Keywords: laminated plate, orthotropic plate, square plate, natural frequency (free vibration), composite (graphite / epoxy)

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Authors: Alison Wilde, Stephen Millett

Abstract:

The cultural value of disabled people has largely been overlooked within forms of media and cultural analysis until the 1980s, when disabled people and disability studies highlighted the cultural misrecognition of disabled people and called for improved forms of cultural recognition and representation. Despite an increase in cultural analysis of representations of disabled people, much has been assumed about how images are read, and little work has been done on the value attributed to disabled people by media audiences and the viewing interests and encounters of film audiences. In particular, there has been little work on film reception, or on the way that young people interpret images of disability. We set out to understand some of the ways that young people read disability imagery, by showing small groups of young people different types of film featuring impairments, chosen from three different eras in film. These were Freaks, Rear Window (remake), and Finding Nemo. The discussions after these films allowed them to explore their own experiences of disability alongside the evolution of cultural representations; in so doing they discussed significant themes of cultural value and reflected on their own identities, e.g. in/dependency, autonomy, and competency and the ways these intersected with self-identity, and attitudes to disabled people.

Keywords: film, audience, identity, disability

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Authors: Abdul Razzaq Azad

Abstract:

It is known that every human society throughout the world and throughout history, the various religions and their theologies, ethics, and traditions influence everything in their life, shaping socio-economic and political ideas, attitudes and institutions. It is observed that religious teachings and traditions shape how people respond to each other in their daily social inter-course and interaction in the community at large. The majorities of us preserves and protect our own religious beliefs and traditions as generally they symbolize our essential identities, theologically, historically, culturally, socially, and even politically. Our religious faiths symbolize our dignity as persons and our very souls as communities and individuals. It thus goes without saying that in our multi racial and multi religious society, the only way for us to live in peace and harmony is for us to live in peaceful co-existence. It is important for us to recognize, understand, accept and respect each other regardless of our respective belief. The history of interfaith is as ancient as the religions since men and women when not at war with their neighbors have always made an effort to understand them (not least because understanding is a strategy for defense, but also because for as long as there is dialogue wars are delayed).

Keywords: interfaith harmony, world piece order, Islam, religions, lightness,

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Authors: Khaled Missaoui, Amina Beldjazia, Rachid Gharzouli, Yamna Djellouli

Abstract:

Optical remote sensing makes use of visible, near infrared and short-wave infrared sensors to form images of the earth's surface by detecting the solar radiation reflected from targets on the ground. Different materials reflect and absorb differently at different wavelengths. Thus, the targets can be differentiated by their spectral reflectance signatures in the remotely sensed images. In this work, we are interested to study the distribution of vegetation in the massif forest of Boutaleb (North East of Algeria) which suffered between 1998 and 1999 very large fires. In this case, we use remote sensing with Landsat images from two dates (1984 and 2000) to see the results of these fires. Vegetation has a unique spectral signature which enables it to be distinguished readily from other types of land cover in an optical/near-infrared image. Normalized Difference Vegetation Index (NDVI) is calculated with ENVI 4.7 from Band 3 and 4. The results showed a very important floristic diversity in this forest. The comparison of NDVI from the two dates confirms that there is a decrease of the density of vegetation in this area due to repeated fires.

Keywords: remote sensing, boutaleb, diversity, forest

Procedia PDF Downloads 542