Search results for: image recognition

Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Anne Hovgaard Jorgensen

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This study investigates how Muslim fathers in Denmark are struggling to overcome notions of mistrust from teachers and educators. Starting from school-home-cooperation (parent conferences, school-home communication, etc.), the study finds that many Muslim fathers do not feel acknowledged as a resource in the upbringing of their children. To explain these experiences further, the study suggest the notion of ‘mistrusted masculinity’ to grasp the controlling image these fathers meet in various schools and child-care-institutions in the Danish Welfare state. The paper is based on 9 months of fieldwork in a Danish school, a social housing area and in various ‘father groups’ in Denmark. Additional, 50 interviews were conducted with fathers, children, mothers, schoolteachers, and educators. By using Connell's concepts 'hegemonic' and 'marginalized' masculinity as steppingstones, the paper argues that these concepts might entail a too static and dualistic picture of gender. By applying the concepts of 'emergent masculinity' and 'emergent fatherhood' the paper brings along a long needed discussion of how Muslim men in Denmark are struggling to overcome and change the controlling images of them as patriarchal and/or ignorant fathers regarding the upbringing of their children. As such, the paper shows how Muslim fathers are taking action to change this controlling image, e.g. through various ‘father groups’. The paper is inspired by the phenomenological notions of ‘experience´ and in the light of this notion, the paper tells the fathers’ stories about their upbringing of their children and aspirations for fatherhood. These stories share light on how these fathers take care of their children in everyday life. The study also shows that the controlling image of these fathers have affected how some Muslim fathers are actually being fathers. The study shows that fear of family-interventions from teachers or social workers e.g. have left some Muslim fathers in a limbo, being afraid of scolding their children, and being confused of ‘what good parenting in Denmark is’. This seems to have led to a more lassie fair upbringing than these fathers actually wanted. This study is important since anthropologists generally have underexposed the notion of fatherhood, and how fathers engage in the upbringing of their children. Over more, the vast majority of qualitative studies of fatherhood have been on white middleclass fathers, living in nuclear families. In addition, this study is crucial at this very moment due to the major refugee crisis in Denmark and in the Western world in general. A crisis, which has resulted in a vast number of scare campaigns against Islam from different nationalistic political parties, which enforces the negative controlling image of Muslim fathers.

Keywords: fatherhood, Muslim fathers, mistrust, education

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Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

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Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

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Authors: X. Wang

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Timely and accurate information on urban building damage caused by earthquake is important basis for disaster assessment and emergency relief. Very high resolution (VHR) remotely sensed imagery containing abundant fine-scale information offers a large quantity of data for detecting and assessing urban building damage in the aftermath of earthquake disasters. However, the accuracy obtained using spectral features alone is comparatively low, since building damage, intact buildings and pavements are spectrally similar. Therefore, it is of great significance to detect urban building damage effectively using multi-source data. Considering that in general height or geometric structure of buildings change dramatically in the devastated areas, a novel multi-stage urban building damage detection method, using bi-temporal spectral, height and corner information, was proposed in this study. The pre-event height information was generated using stereo VHR images acquired from two different satellites, while the post-event height information was produced from airborne LiDAR data. The corner information was extracted from pre- and post-event panchromatic images. The proposed method can be summarized as follows. To reduce the classification errors caused by spectral similarity and errors in extracting height information, ground surface, shadows, and vegetation were first extracted using the post-event VHR image and height data and were masked out. Two different types of building damage were then extracted from the remaining areas: the height difference between pre- and post-event was used for detecting building damage showing significant height change; the difference in the density of corners between pre- and post-event was used for extracting building damage showing drastic change in geometric structure. The initial building damage result was generated by combining above two building damage results. Finally, a post-processing procedure was adopted to refine the obtained initial result. The proposed method was quantitatively evaluated and compared to two existing methods in Port au Prince, Haiti, which was heavily hit by an earthquake in January 2010, using pre-event GeoEye-1 image, pre-event WorldView-2 image, post-event QuickBird image and post-event LiDAR data. The results showed that the method proposed in this study significantly outperformed the two comparative methods in terms of urban building damage extraction accuracy. The proposed method provides a fast and reliable method to detect urban building collapse, which is also applicable to relevant applications.

Keywords: building damage, corner, earthquake, height, very high resolution (VHR)

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Ashwani Kumar Aggarwal

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NIR Light is non-ionizing and can pass easily through living tissues such as breast without any harmful effects. Therefore, use of NIR light for imaging the biological tissue and to quantify its optical properties is a good choice over other invasive methods. Optical tomography involves two steps. One is the forward problem and the other is the reconstruction problem. The forward problem consists of finding the measurements of transmitted light through the tissue from source to detector, given the spatial distribution of absorption and scattering properties. The second step is the reconstruction problem. In X-ray tomography, there is standard method for reconstruction called filtered back projection method or the algebraic reconstruction methods. But this method cannot be applied as such, in optical tomography due to highly scattering nature of biological tissue. A hybrid algorithm for reconstruction has been implemented in this work which takes into account the highly scattered path taken by photons while back projecting the forward data obtained during Monte Carlo simulation. The reconstructed image suffers from blurring due to point spread function. This blurred reconstructed image has been enhanced using a digital filter which is optimal in mean square sense.

Keywords: least-squares optimization, filtering, tomography, laser interaction, light scattering

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Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

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Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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Authors: Mehena Fedoul

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This paper examines the intersection of race, gender, and disability through a Critical disability race theory and black feminist disability perspective in Keah Brown's memoir, "The Pretty One." The background of the study highlights the significance of intersectionality in understanding the multifaceted experiences of individuals who navigate multiple marginalized identities. The study contributes to the underrepresented field of disability studies from Critical race and black feminist perspectives, shedding light on the unique challenges and resilience of black disabled women. The study employs a qualitative analysis of Keah Brown's memoir as a primary text. Drawing on intersectionality theory and black feminist disability scholarship, the analysis focuses on how Brown's memoir illuminates the ways in which her race, gender, and disability intersect and shape her lived experiences. The analysis reveals how Brown's memoir challenges traditional notions of disability, beauty, and empowerment through the unapologetic celebration of her blackness, femaleness, and disability. The major findings of the study indicate that Brown's memoir provides a powerful narrative of the complexity, uniqueness and richness of the lived experiences of black disabled women. It demonstrates how the intersectionality of race, gender, and disability shapes Brown's identity, body image, relationships, and societal interactions. The paper also highlights how Brown's memoir emphasizes the importance of inclusivity and intersectionality in understanding and addressing the challenges faced by black disabled women. In conclusion, this study offers a critical analysis of the intersection of race, gender, and disability in Keah Brown's memoir, "The Pretty One," from a black feminist disability perspective. It contributes to the growing body of literature that recognizes the significance of intersectionality in understanding the experiences of marginalized individuals in the disability community. The study underscores the need for more inclusive and intersectional perspectives in disability studies and advocates for greater recognition of the voices and experiences of black disabled women in academic and societal discourse.

Keywords: disability studies, intersectionality, black feminism, Keah Brown

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Authors: Cosmin-Gabriel Porumb-Ghiurco, Dumitrana Fiț-Iordache, Szőke Árpád

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The literature incorporating geographical or tourist-geographical themes and explicit references to the Carpathian area is extremely abundant. Through this paper, we attempt to “undermine” the traditional, tourist-geographical approaches of the Carpathian Arch by targeting an aspect often regarded as marginal but which, if examined, even only empirically, takes the form of a vast problem with multidisciplinary vocation. Therefore, we propose a more extravagant yet pro-touristic approach to the Romanian Carpathian geo-space. Consequently, the explicit goal of this approach consists precisely in broadening the multidisciplinary, essentially geographic scope of the research, the vision and mental representation of the Carpathian area by advancing a lever that would symbolize a different kind of unification between geography and tourism on a more intimate, subtle, mythological and archetypal level. The spiritual and mercantile dimensions of the tourism field in general and of the local Carpathian tourism can meld harmoniously together in order to create a common territorial reality of referral and favorable perspectives for the consolidation of their symbiotic relationship.

Keywords: tourist image, mythical geography, collective imaginary, spiritual patrimony, Carpathians

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Authors: A. C. Galvis-Castro, R. D. Tovar, R. Salgado, M. Prezzi

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It is generally accepted that the shaft capacity of piles in the sand is lower for tensile loading that for compressive loading. So far, very little attention has been paid to the role of the influence of the installation method on the tensile to compressive shaft capacity ratio. The objective of this paper is to analyze the effect of installation method on the tensile to compressive shaft capacity of piles in dense sand as observed in tests on half-circular model pile tests in a half-circular calibration chamber with digital image correlation (DIC) capability. Model piles are either monotonically jacked, jacked with multiple strokes or pre-installed into the dense sand samples. Digital images of the model pile and sand are taken during both the installation and loading stages of each test and processed using the DIC technique to obtain the soil displacement and strain fields. The study provides key insights into the mobilization of shaft resistance in tensile and compressive loading for both displacement and non-displacement piles.

Keywords: digital image correlation, piles, sand, shaft resistance

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Authors: Thanh Noi Phan, Martin Kappas, Jan Degener

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

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

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Authors: M. C. Paliwal, A. K. Jain, S. K. Katiyar

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Classification of satellite imagery is very important for the assessment of its accuracy. In order to determine the accuracy of the classified image, usually the assumed-true data are derived from ground truth data using Global Positioning System. The data collected from satellite imagery and ground truth data is then compared to find out the accuracy of data and error matrices are prepared. Overall and individual accuracies are calculated using different methods. The study illustrates advanced classification and accuracy assessment of land use/land cover mapping using satellite imagery. IRS-1C-LISS IV data were used for classification of satellite imagery. The satellite image was classified using the software in fourteen classes namely water bodies, agricultural fields, forest land, urban settlement, barren land and unclassified area etc. Classification of satellite imagery and calculation of accuracy was done by using ERDAS-Imagine software to find out the best method. This study is based on the data collected for Bhopal city boundaries of Madhya Pradesh State of India.

Keywords: resolution, accuracy assessment, land use mapping, satellite imagery, ground truth data, error matrices

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Authors: Mingxin Li, Liya Ni

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Autonomous parking is a valuable feature applicable to many robotics applications such as tour guide robots, UV sanitizing robots, food delivery robots, and warehouse robots. With auto-parking, the robot will be able to park at the charging zone and charge itself without human intervention. As compared to self-driving vehicles, auto-parking is more challenging for a small-scale mobile robot only equipped with a front camera due to the camera view limited by the robot’s height and the narrow Field of View (FOV) of the inexpensive camera. In this research, auto-parking of a small-scale mobile robot with a front camera only was achieved in a four-step process: Firstly, transfer learning was performed on the AlexNet, a popular pre-trained convolutional neural network (CNN). It was trained with 150 pictures of empty parking slots and 150 pictures of occupied parking slots from the view angle of a small-scale robot. The dataset of images was divided into a group of 70% images for training and the remaining 30% images for validation. An average success rate of 95% was achieved. Secondly, the image of detected empty parking space was processed with edge detection followed by the computation of parametric representations of the boundary lines using the Hough Transform algorithm. Thirdly, the positions of the entrance point and center of available parking space were predicted based on the robot kinematic model as the robot was driving closer to the parking space because the boundary lines disappeared partially or completely from its camera view due to the height and FOV limitations. The robot used its wheel speeds to compute the positions of the parking space with respect to its changing local frame as it moved along, based on its kinematic model. Lastly, the predicted entrance point of the parking space was used as the reference for the motion control of the robot until it was replaced by the actual center when it became visible again by the robot. The linear and angular velocities of the robot chassis center were computed based on the error between the current chassis center and the reference point. Then the left and right wheel speeds were obtained using inverse kinematics and sent to the motor driver. The above-mentioned four subtasks were all successfully accomplished, with the transformed learning, image processing, and target prediction performed in MATLAB, while the motion control and image capture conducted on a self-built small scale differential drive mobile robot. The small-scale robot employs a Raspberry Pi board, a Pi camera, an L298N dual H-bridge motor driver, a USB power module, a power bank, four wheels, and a chassis. Future research includes three areas: the integration of all four subsystems into one hardware/software platform with the upgrade to an Nvidia Jetson Nano board that provides superior performance for deep learning and image processing; more testing and validation on the identification of available parking space and its boundary lines; improvement of performance after the hardware/software integration is completed.

Keywords: autonomous parking, convolutional neural network, image processing, kinematics-based prediction, transfer learning

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Authors: Elizabeth Malebogo Mosepele

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Road transport has become increasingly common in the world; people rely on road networks for transportation purpose on a daily basis. However, environmental impact of roads on surrounding landscapes extends their potential effects even further. This study investigates the impact of road network on natural vegetation. The study will provide baseline knowledge regarding roadside vegetation and would be helpful in future for conservation of biodiversity along the road verges and improvements of road verges. The general hypothesis of this study is that the amount and condition of road side vegetation could be explained by road network conditions. Remote sensing techniques were used to analyze vegetation conditions. Landsat 8 OLI image was used to assess vegetation cover condition. NDVI image was generated and used as a base from which land cover classes were extracted, comprising four categories viz. healthy vegetation, degraded vegetation, bare surface, and water. The classification of the image was achieved using the supervised classification technique. Road networks were digitized from Google Earth. For observed data, transect based quadrats of 50*50 m were conducted next to road segments for vegetation assessment. Vegetation condition was related to road network, with the multinomial logistic regression confirming a significant relationship between vegetation condition and road network. The null hypothesis formulated was that 'there is no variation in vegetation condition as we move away from the road.' Analysis of vegetation condition revealed degraded vegetation within close proximity of a road segment and healthy vegetation as the distance increase away from the road. The Chi Squared value was compared with critical value of 3.84, at the significance level of 0.05 to determine the significance of relationship. Given that the Chi squared value was 395, 5004, the null hypothesis was therefore rejected; there is significant variation in vegetation the distance increases away from the road. The conclusion is that the road network plays an important role in the condition of vegetation.

Keywords: Chi squared, geographic information system, multinomial logistic regression, remote sensing, road side vegetation

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Authors: Abdul Rahman Chamseddine

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Tawfiq al-Hakim remains one of the most prominent playwrights in his native in Egypt, and in the broader Arab world. His works, at the time of their release, drew international attention and acclaim. His first 1933 masterpiece Ahl al-Kahf (The People of the Cave) especially, garnered fame and recognition in both Europe and the Arab world. Borrowing its title from the Qur’anic Sura, al-Hakim’s play relays the untold story of the life of those 'three saints' after they wake up from their prolonged sleep. The playwright’s selection of topics upon which to base his works displays a deep appreciation of Arabic and Islamic heritage. Al-Hakim was clearly influenced by Islam, to such a degree that he wrote the biography of the Prophet Muhammad in 1936 very early in his career. Knowing that Al-Hakim was preceded by many poets and creative writers in writing the Prophet Muhammad’s biography. Notably like Al-Barudi, Ahmad Shawqi, Haykal, Al-‘Aqqad, and Taha Husayn who have had their own ways in expressing their views of the Prophet Muhammad. The attempt to understand the concern of all those renaissance men and others in the person of the Prophet would be indispensable in this study. This project will examine the reasons behind al-Hakim’s choice to draw upon these particular texts, embedded as they are in the context of Arabic and Islamic heritage, and how the use of traditional texts serves his contemporary goals. The project will also analyze the image of Islam in al-Hakim’s imagination. Elsewhere, he envisions letters or conversations between God and himself, which offers a window into understanding the powerful impact of the Divine on Tawfiq al-Hakim, one that informs his literature and merits further scholarly attention. His works occupying a major rank in Arabic literature, does not reveal Al-Hakim solely but the unquestioned assumptions operative in the life of his community, its mental make-up and its attitudes. Furthermore, studying the reception of works that touch on sensitive issues, like writing a letter to God, in Al-Hakim’s historical context would be of a great significance in the process of comprehending the mentality of the Muslim community at that time.

Keywords: Arabic language, Arabic literature, Arabic theology, modern Arabic literature

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Authors: Shishay T. Kidanu

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The study area is located in Southwestern Missouri and is mainly underlain by Mississippian Age limestone which is highly susceptible to karst processes. The area is known for the presence of various karst features like caves, springs and more importantly Sinkholes. Sinkholes are one of the most common karst features and the primary hazard in karst areas. Investigating the subsurface structure and development mechanism of existing sinkholes enables to understand their long-term impact and chance of reactivation and also helps to provide effective mitigation measures. In this study ERT (Electrical Resistivity Tomography), MASW (Multichannel Analysis of Surface Waves) and borehole control data have been used to image the subsurface structure and investigate the development mechanism of a sinkhole in Southwestern Missouri. The study shows that the main process responsible for the development of the sinkhole is the downward piping of fine grained soils. Furthermore, the study reveals that the sinkhole developed along a north-south oriented vertical joint set characterized by a vertical zone of water seepage and associated fine grained soil piping into preexisting fractures.

Keywords: ERT, Karst, MASW, sinkhole

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Authors: Michael Karnes, Alper Yilmaz

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This paper presents the application of the omni-modeler towards pedestrian redetection. The pedestrian redetection task creates several challenges when applying deep neural networks (DNN) due to the variety of pedestrian appearance with camera position, the variety of environmental conditions, and the specificity required to recognize one pedestrian from another. DNNs require significant training sets and are not easily adapted for changes in class appearances or changes in the set of classes held in its knowledge domain. Pedestrian redetection requires an algorithm that can actively manage its knowledge domain as individuals move in and out of the scene, as well as learn individual appearances from a few frames of a video. The Omni-Modeler is a dynamically learning few-shot visual recognition algorithm developed for tasks with limited training data availability. The Omni-Modeler adapts the knowledge domain of pre-trained deep neural networks to novel concepts with a calculated localized language encoder. The Omni-Modeler knowledge domain is generated by creating a dynamic dictionary of concept definitions, which are directly updatable as new information becomes available. Query images are identified through nearest neighbor comparison to the learned object definitions. The study presented in this paper evaluates its performance in re-identifying individuals as they move through a scene in both single-camera and multi-camera tracking applications. The results demonstrate that the Omni-Modeler shows potential for across-camera view pedestrian redetection and is highly effective for single-camera redetection with a 93% accuracy across 30 individuals using 64 example images for each individual.

Keywords: dynamic learning, few-shot learning, pedestrian redetection, visual recognition

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Authors: Nour Eldin Afyouni, Hassan Assoum, Kamel Abed-Meraim, Anas Sakout

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The acoustic of an impinging jet holds significant importance in the engineering field. In HVAC systems, the jet impingement, in some cases, generates noise that destroys acoustic comfort. This paper presents an experimental study of a rectangular air jet impinging on a slotted plate to investigate the correlation between sound emission and turbulence dynamics. The experiment was conducted with an impact ratio L/H = 4 and a Reynolds number Re = 4700. The survey shows that coherent structures within the impinging jet are responsible for self-sustaining tone production. To achieve this, a specific experimental setup consisting of two simultaneous Stereoscopic Particle Image Velocimetry (S-PIV) measurements was developed to track vortical structures both before and after the plate, in addition to acoustic measurements. The results reveal a significant correlation between acoustic waves and the passage of coherent structures. Variations in the arrangement of vortical structures between the upstream and downstream sides of the plate were observed. This analysis of flow dynamics can enhance our understanding of slot noise.

Keywords: impinging jet, coherent structures, SPIV, aeroacoustics

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Authors: Omer Cahana, Ofer Levi, Maya Herman

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: magnetic resonance imaging, image reconstruction, pyramid network, deep learning

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Authors: Behcet Al, Mehmet Murat Oktay, Suat Zengin, Mustafa Sabak, Cuma Yildirim

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Objective: Th Recognition of arrest patients and application of basic life support (BLS) by bystanders in the field and the activation of emergency serves were evaluated in present study. Methodology: The present study was carried out by Emergency Department of Medicine Faculty of Gaziantep University at 33 of Emergency Health center in Gaziantep between December 2012- April 2014 prospectively. Of 539 arrested patients, 171 patients were included in study. Results: 118 (69%) male, and 53 31(%) female with a totlay of 171 patients were included in this study. Of patients, 32.2% had syncope and 24% had shorth breathing just befor being arrested. The majority of arrest cases had occured at home (61.4%) and rural area (11.7%) respectively. Of asking help, %48.5 were constructed by family members. Of announcement, only 15.2% occured within first minute of arrest. The BLS ratio that was applied by bystanders was 22.2%. Of bystanders, 47.4% had a course experience of BLS. The emergency serve had reached to the field with a mean of 8.43 min. Of cases, 55% (n=94) were evaluated as exitus firstly bu emergency staff. The most noticed rythim was asystol (73.1%). BLS and advanced life support (ALS) were applied to 98.8% and 60% respectively at the field. 10.5% (n=18) of cases were defibrilated, and 45 (26.3%) were intubated endotrecealy. The majority (48.5%) of staff who applied BLS and ALS at the fied were emergency medicine technicians. CPR was performed to 86.5% (n=148) cases in ambulance while they were transported. The mean arrival time to mergency department was 9.13 min. When the patients arrived to ED 15.2% needed defirlitation. 91.2% (n =156) of patients resulted in exitus in ED. 15 (8.8%) patients were discharged (9 with recovery, six patients with damage). Conclusion: The ratio of inntervention for arrest patients by bystanders is still low. To optain a high percentage of survival, BLS training should be widened among the puplic especiallyamong the caregivers.

Keywords: arrest patients, cardiopulmonary resuscitation, bystanders, chest compressions, prehospital

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Authors: Raquel Rossini, Edelvais Caldeira

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The aim of this work is to investigate the motivation for the metaphorical uses of two verb combinations: come out and take over. Drawing from cognitive semantics theories, image schemas and metaphors, it was attempted to demonstrate that: a) the metaphorical senses of both 'come out' and 'take over' extend from both the verbs and the particles central (spatial) senses in such verb combinations; and b) the particles 'out' and 'over' also contribute to the whole meaning of the verb combinations. In order to do so, a random selection of 579 concordance lines for come out and 1,412 for take over was obtained from the Corpus of Contemporary American English – COCA. One of the main procedures adopted in the present work was the establishment of verb and particle central senses. As per the research questions addressed in this study, they are as follows: a) how does the identification of trajector and landmark help reveal patterns that contribute for the identification of the semantic network of these two verb combinations?; b) what is the relationship between the schematic structures attributed to the particles and the metaphorical uses found in empirical data?; and c) what conceptual metaphors underlie the mappings from the source to the target domains? The results demonstrated that not only the lexical verbs come and take, but also the particles out and over play an important whole in the different meanings of come out and take over. Besides, image schemas and conceptual metaphors were found to be helpful in order to establish the motivations for the metaphorical uses of these linguistic structures.

Keywords: cognitive linguistics, English syntax, multi-word verbs, prepositions

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Authors: Kazumoto Tanaka, Takayuki Fujino

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Sports games conducted as a group are a form of therapeutic exercise for aged people with decreased strength and for people suffering from permanent damage of stroke and other conditions. However, it is difficult for patients with different athletic abilities to play a game on an equal footing. This study specifically examines a computer video game designed for therapeutic exercise, and a game system with support given depending on athletic ability. Thereby, anyone playing the game can participate equally. This video-game, to be specific, is a popular variant of balloon volleyball, in which players hit a balloon by hand before it falls to the floor. In this game system, each player plays the game watching a monitor on which the system displays tailor-made video-game images adjusted to the person’s athletic ability, providing players with player-adaptive assist support. We have developed a multiplayer game system with an image generation technique for the tailor-made video-game and conducted tests to evaluate it.

Keywords: therapeutic exercise, computer video game, disability-adaptive assist, tailor-made video-game image

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Authors: Wanderson Goncalves e Goncalves, José Alberto Silva de Sá

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Human actions are a threat to the balance and conservation of the Amazon forest. Therefore the environmental monitoring services play an important role as the preservation and maintenance of this environment. This study classified forest types using data from a forest inventory provided by the 'Florestal e da Biodiversidade do Estado do Pará' (IDEFLOR-BIO), located between the municipalities of Santarém, Juruti and Aveiro, in the state of Pará, Brazil, covering an area approximately of 600,000 hectares, Bands 3, 4 and 5 of the TM-Landsat satellite image, and Self - Organizing Maps. The information from the satellite images was extracted using QGIS software 2.8.1 Wien and was used as a database for training the neural network. The midpoints of each sample of forest inventory have been linked to images. Later the Digital Numbers of the pixels have been extracted, composing the database that fed the training process and testing of the classifier. The neural network was trained to classify two forest types: Rain Forest of Lowland Emerging Canopy (Dbe) and Rain Forest of Lowland Emerging Canopy plus Open with palm trees (Dbe + Abp) in the Mamuru Arapiuns glebes of Pará State, and the number of examples in the training data set was 400, 200 examples for each class (Dbe and Dbe + Abp), and the size of the test data set was 100, with 50 examples for each class (Dbe and Dbe + Abp). Therefore, total mass of data consisted of 500 examples. The classifier was compiled in Orange Data Mining 2.7 Software and was evaluated in terms of the confusion matrix indicators. The results of the classifier were considered satisfactory, and being obtained values of the global accuracy equal to 89% and Kappa coefficient equal to 78% and F1 score equal to 0,88. It evaluated also the efficiency of the classifier by the ROC plot (receiver operating characteristics), obtaining results close to ideal ratings, showing it to be a very good classifier, and demonstrating the potential of this methodology to provide ecosystem services, particularly in anthropogenic areas in the Amazon.

Keywords: artificial neural network, computational intelligence, pattern recognition, unsupervised learning

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Authors: Odete Paiva, Cláudia Seabra, José Luís Abrantes, Fernanda Cravidão

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There is a clear ‘cult of authenticity’, at least in modern Western society. So, there is a need to analyze the tourist perception of authenticity, bearing in mind the destination, its attractions, motivations, cultural distance, and contact with other tourists. Our study seeks to investigate the relationship among cultural values, image, sense of place, perception of authenticity and behavior intentions at World Heritage Historic Centers. From a theoretical perspective, few researches focus on the impact of cultural values, image and sense of place on authenticity and intentions behavior in tourists. The intention of this study is to help close this gap. A survey was applied to collect data from tourists visiting two World Heritage Historic Centers – Guimarães in Portugal and Cordoba in Spain. Data was analyzed in order to establish a structural equation model (SEM). Discussion centers on the implications of model to theory and managerial development of tourism strategies. Recommendations for destinations managers and promoters and tourist organizations administrators are addressed.

Keywords: authenticity perception, behavior intentions, cultural tourism, cultural values, world heritage historic centers

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Authors: M. A. H. Barry

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The concept of Good faith (husn al-niyyah) and fair-dealing (Nadl) are the fundamental guiding elements in all contracts and other agreements under Islamic law. The preaching of Al-Quran and Prophet Muhammad’s (Peace Be upon Him) firmly command people to act in good faith in all dealings. There are several Quran verses and the Prophet’s saying which stressed the significance of dealing honestly and fairly in all transactions. Under the English law, the good faith is not considered a fundamental requirement for the formation of a legal contract. However, the concept of Good Faith in private contracts is recognized by the civil law system and in Article 7(1) of the Convention on International Sale of Goods (CISG-Vienna Convention-1980). It took several centuries for the international trading community to recognize the significance of the concept of good faith for the international sale of goods transactions. Nevertheless, the recognition of good faith in Civil law is only confined for the commercial contracts. Subsequently to the CISG, this concept has made inroads into the private international law. There are submissions in favour of applying the good faith concept to public international law based on tacit recognition by the international conventions and International Tribunals. However, under public international law the concept of good faith is not recognized as a source of rights or obligations. This weakens the spirit of the good faith concept, particularly when determining the international disputes. This also creates a fundamental flaw because the absence of good faith application means the breaches tainted by bad faith are tolerated. The objective of this research is to evaluate, examine and analyze the application of the concept of good faith in the modern laws and identify its limitation, in comparison with Islamic concept of good faith. This paper also identifies the problems and issues connected with the non-application of this concept to public international law. This research consists of three key components (1) the preliminary inquiry (2) subject analysis and discovery of research results, and (3) examining the challenging problems, and concluding with proposals. The preliminary inquiry is based on both the primary and secondary sources. The same sources are used for the subject analysis. This research also has both inductive and deductive features. The Islamic concept of good faith covers all situations and circumstances where the bad faith causes unfairness to the affected parties, especially the weak parties. Under the Islamic law, the concept of good faith is a source of rights and obligations as Islam prohibits any person committing wrongful or delinquent acts in any dealing whether in a private or public life. This rule is applicable not only for individuals but also for institutions, states, and international organizations. This paper explains how the unfairness is caused by non-recognition of the good faith concept as a source of rights or obligations under public international law and provides legal and non-legal reasons to show why the Islamic formulation is important.

Keywords: good faith, the civil law system, the Islamic concept, public international law

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Authors: S. Sarumathi, C. Deepadharani, Garimella Archana, S. Dakshayani, D. Logeshwaran, D. Jayakumar, Vijayarangan Natarajan

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The need of the hour for the customers who use a dial-up or a low broadband connection for their internet services is to access HD video data. This can be achieved by developing a new video format using H. 265. This is the latest video codec standard developed by ISO/IEC Moving Picture Experts Group (MPEG) and ITU-T Video Coding Experts Group (VCEG) on April 2013. This new standard for video compression has the potential to deliver higher performance than the earlier standards such as H. 264/AVC. In comparison with H. 264, HEVC offers a clearer, higher quality image at half the original bitrate. At this lower bitrate, it is possible to transmit high definition videos using low bandwidth. It doubles the data compression ratio supporting 8K Ultra HD and resolutions up to 8192×4320. In the proposed model, we design a new video format which supports this H. 265 standard. The major areas of applications in the coming future would lead to enhancements in the performance level of digital television like Tata Sky and Sun Direct, BluRay Discs, Mobile Video, Video Conferencing and Internet and Live Video streaming.

Keywords: access HD video, H. 265 video standard, high performance, high quality image, low bandwidth, new video format, video streaming applications

Procedia PDF Downloads 350

Authors: Wen Zhang

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The smartphone plays a significant role in media convergence, and smartphone photography is reconstructing the way we communicate and think. This article aims to explore the smartphone photography practices of urban Chinese smartphone users and images produced by smartphones from a techno-cultural perspective. The analysis consists of two types of data: One is a semi-structured interview of 21 participants, and the other consists of the images created by the participants. The findings are organised in two parts. The first part summarises the current tendencies of capturing, editing, sharing and archiving digital images via smartphones. The second part shows that food and selfie/anti-selfie are the preferred subjects of smartphone photographic images from a technical and multi-purpose perspective and demonstrates that screenshots and image texts are new genres of non-photographic images that are frequently made by smartphones, which contributes to improving operational efficiency, disseminating information and sharing knowledge. The analyses illustrate the positive impacts between smartphones and photography enthusiasm and practices based on the diffusion of innovation theory, which also makes us rethink the value of photographs and the practice of ‘photographic seeing’ from the screen itself.

Keywords: digital photography, image-text, media convergence, photographic- seeing, selfie/anti-selfie, smartphone, technological innovation

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Authors: Kaitlyn Deierlein, Janet Lydecker

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Stereotypes surrounding anorexia nervosa are that the illness is commonly perceived as a self-inflicted disorder influenced by controlling parents, vanity, and cultural pressures. According to the authors' best knowledge minimal research has examined interactions with other factors, including gender and racial stereotypes involving this disorder. A common stereotype of this disease is that it mainly only affects Caucasian women and is very rarely seen in any other ethnicity. Previous literature has failed to investigate how visual body image and ethnic stereotypes affect the mental health of different ethnic groups, how various cultures impact the type of anorexia nervosa in the patient, and the different stereotypes associated with their eating disorder. Participants completed a pre-test questionnaire with vignettes, an image exposure portion, and a post-test questionnaire, which will all be evaluated and analyzed by ANOVA t-test and SPSS. Results showed that participants picked Caucasian females as more likely to have anorexia nervosa than those of Asian, Latin American, or African American descent subjects in both picture identification and vignettes. Future research should be conducted to further the results of this study by examining differences between gender stereotypes with anorexia nervosa as well as how sexuality has a role in perception.

Keywords: anorexia nervosa, ethnicity, stereotypes, eating disorders, perception

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Authors: María García-García, Esther Simancas-González, Said Balhadj, Carmen Silva-Robles, Driss Ferhane

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Cooperation between the territories on both sides of the Strait of Gibraltar is an urgent reality. the south of Spain and northern Morocco share a common historical past and belong to a very similar geographical and ecological area. Economic, social and cultural relations make cooperation between the two countries’ (Spain and Morocco) a priority for the EU and both countries governments. Likewise, deepened changes happened in production systems and consumption patterns had seriously damaged and weakened the craftwork sector. The promotion of local crafts, and its economic value, and the cooperation with the north of Morocco has been an important issue for the Andalusian government in recent years. The main aim of this work is to understand the strengths and weaknesses of the Tangier - Tetuan region craftworks sector in order to develop accurate communication and promotion plans. From the knowledge of the real identity, the sector could be repositioned. Promotion and communication could be a spur to traditional sectors, such as crafts. Competitiveness requires "the culture of communication, the cooperation between different companies to build powerful territory brands and maintain the establishment confidence and effectiveness relationships among agencies and organizations". The lack of previous literature addressing how Tangier craftwork promote and communicate its value to their stakeholders, has conducted the study to an exploratory approach with a double dimension: internal, Tangier craftwork sector image, and external, Andalusia image of the sector in Tangier. Different interviews were conducted with Andalusian partners involved in the artisanal sector (9 master craftsmen and 3 institutions) and focus groups with 9 Tangiers craftsmen were developed. The result of these interviews and expert groups are reflected in a SWOT analysis which reveals a handcraft industry with a worrying wide-spread and undifferentiated identity and reluctance to innovation and new technologies.

Keywords: communication management, image, Moroccan crafts, Spain-Morocco cooperation

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Authors: M. Kastek, M. Kowalski, M. Szustakowski, H. Polakowski, T. Sosnowski

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Development of highly efficient security systems is one of the most urgent topics for science and engineering. There are many kinds of threats and many methods of prevention. It is very important to detect a threat as early as possible in order to neutralize it. One of the very challenging problems is detection of dangerous objects hidden under human’s clothing. This problem is particularly important for safety of airport passengers. In order to develop methods and algorithms to detect hidden objects it is necessary to determine the thermal signatures of such objects of interest. The laboratory measurements were conducted to determine the thermal signatures of dangerous tools hidden under various clothes in different ambient conditions. Cameras used for measurements were working in spectral range 0.6-12.5 μm An infrared imaging Fourier transform spectroradiometer was also used, working in spectral range 7.7-11.7 μm. Analysis of registered thermograms and hyperspectral datacubes has yielded the thermal signatures for two types of guns, two types of knives and home-made explosive bombs. The determined thermal signatures will be used in the development of method and algorithms of image analysis implemented in proposed monitoring systems.

Keywords: hyperspectral detection, nultispectral detection, image processing, monitoring systems

Procedia PDF Downloads 341