Search results for: lidar Radar data fusion

Authors: Nicole M. Martino

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Reinforced concrete bridge deck condition assessments primarily use visual inspection methods, where an inspector looks for and records locations of cracks, potholes, efflorescence and other signs of probable deterioration. Sounding is another technique used to diagnose the condition of a bridge deck, however this method listens for damage within the subsurface as the surface is struck with a hammer or chain. Even though extensive procedures are in place for using these inspection techniques, neither one provides the inspector with a comprehensive understanding of the internal condition of a bridge deck – the location where damage originates from.  In order to make accurate estimates of repair locations and quantities, in addition to allocating the necessary funding, a total understanding of the deck’s deteriorated state is key. The research presented in this paper collected infrared thermography and ground penetrating radar data from reinforced concrete bridge decks without an asphalt overlay. These decks were of various ages and their condition varied from brand new, to in need of replacement. The goals of this work were to first verify that these nondestructive evaluation methods could identify similar areas of healthy and damaged concrete, and then to see if combining the results of both methods would provide a higher confidence than if the condition assessment was completed using only one method. The results from each method were presented as plan view color contour plots. The results from one of the decks assessed as a part of this research, including these plan view plots, are presented in this paper. Furthermore, in order to answer the interest of transportation agencies throughout the United States, this research developed a step-by-step guide which demonstrates how to collect and assess a bridge deck using these nondestructive evaluation methods. This guide addresses setup procedures on the deck during the day of data collection, system setups and settings for different bridge decks, data post-processing for each method, and data visualization and quantification.

Keywords: bridge deck deterioration, ground penetrating radar, infrared thermography, NDT of bridge decks

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Authors: Wilayat Ali, Li Sheng, Waleed Ahmed

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The ability of the robot to make simultaneously map of the environment and localize itself with respect to that environment is the most important element of mobile robots. To solve SLAM many algorithms could be utilized to build up the SLAM process and SLAM is a developing area in Robotics research. Robot Operating System (ROS) is one of the frameworks which provide multiple algorithm nodes to work with and provide a transmission layer to robots. Manyof these algorithms extensively in use are Hector SLAM, Gmapping and Cartographer SLAM. This paper describes a ROS-based Simultaneous localization and mapping (SLAM) library Google Cartographer mapping, which is open-source algorithm. The algorithm was applied to create a map using laser and pose data from 2d Lidar that was placed on a mobile robot. The model robot uses the gazebo package and simulated in Rviz. Our research work's primary goal is to obtain mapping through Cartographer SLAM algorithm in a static indoor environment. From our research, it is shown that for indoor environments cartographer is an applicable algorithm to generate 2d maps with LIDAR placed on mobile robot because it uses both odometry and poses estimation. The algorithm has been evaluated and maps are constructed against the SLAM algorithms presented by Turtlebot2 in the static indoor environment.

Keywords: SLAM, ROS, navigation, localization and mapping, gazebo, Rviz, Turtlebot2, slam algorithms, 2d indoor environment, cartographer

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Authors: Chhabi Nigam, S. Ramakrishnan

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This paper brings out the analysis of the airborne Synthetic Aperture Radar (SAR) data to study the impact of Doppler centroid on Image quality and geocoding accuracy from the perspective of Stripmap mode of data acquisition. Although in Stripmap mode of data acquisition radar beam points at 90 degrees broad side (side looking), shift in the Doppler centroid is invariable due to platform motion. In-accurate estimation of Doppler centroid leads to poor image quality and image miss-registration. The effect of Doppler centroid is analyzed in this paper using multiple sets of data collected from airborne platform. Occurrences of ghost (ambiguous) targets and their power levels have been analyzed that impacts appropriate choice of PRF. Effect of aircraft attitudes (roll, pitch and yaw) on the Doppler centroid is also analyzed with the collected data sets. Various stages of the RDA (Range Doppler Algorithm) algorithm used for image formation in Stripmap mode, range compression, Doppler centroid estimation, azimuth compression, range cell migration correction are analyzed to find the performance limits and the dependence of the imaging geometry on the final image. The ability of Doppler centroid estimation to enhance the imaging accuracy for registration are also illustrated in this paper. The paper also tries to bring out the processing of low squint SAR data, the challenges and the performance limits imposed by the imaging geometry and the platform dynamics on the final image quality metrics. Finally, the effect on various terrain types, including land, water and bright scatters is also presented.

Keywords: ambiguous target, Doppler Centroid, image registration, Airborne SAR

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Authors: Tamas Jancso, Andrea Podor, Eva Nagyne Hajnal, Peter Udvardy, Gabor Nagy, Attila Varga, Meng Qingyan

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The paper deals with the conditions and circumstances of integration of remotely sensed data for rural environmental monitoring purposes. The main task is to make decisions during the integration process when we have data sources with different resolution, location, spectral channels, and dimension. In order to have exact knowledge about the integration and data fusion possibilities, it is necessary to know the properties (metadata) that characterize the data. The paper explains the joining of these data sources using their attribute data through a sample project. The resulted product will be used for rural environmental analysis.

Keywords: remote sensing, GIS, metadata, integration, environmental analysis

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Authors: Bang Haeyong

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Purpose: The objectives of this study were to determine the prevalence, incidence, and risk factors for postoperative fever after lumbar fusion. Methods: This study was a retrospective chart review of 291 patients who underwent lumbar fusion between March 2015 and February 2016 at the Asan Medical Center. Information was extracted from electronic medical records. Postoperative fever was measured at Tmax > 37.7 ℃ and Tmax > 38.3 ℃. The presence of postoperative fever, blood culture, urinary excretion, and/or chest x-ray were evaluated. Patients were evaluated for infection after lumbar fusion. Results: We found 222 patients (76.3%) had a postoperative temperature of 37.7 ℃, and 162 patients (55.7%) had a postoperative temperature of 38.3 ℃ or higher. The percentage of febrile patients trended down following the mean 1.8days (from the first postoperative day to seventh postoperative day). Infection rate was 9 patients (3.1%), respiratory virus (1.7%), urinary tract infection (0.3%), phlebitis (0.3%), and surgical site infection (1.4%). There was no correlation between Tmax > 37.7℃ or Tmax > 38.3℃, and timing of fever, positive blood or urine cultures, pneumonia, or surgical site infection. Risk factors for increased postoperative fever following surgery were confirmed to be delay of defecation (OR=1.37, p=.046), and shorten of remove drainage (OR=0.66, p=.037). Conclusions: The incidence of fever was 76.3% after lumbar fusion and the drainage time was faster in the case of fever. It was thought that the bleeding was absorbed at the operation site and fever occurred. The prevalence of febrile septicemia was higher in patients with long bowel movements before surgery than after surgery. Clinical symptoms should be considered because postoperative fever cannot be determined by fever alone because fever and infection are not significant.

Keywords: lumbar surgery, fever, postoperative, risk factor

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Authors: Keyur Raval, Steffen Krohn, Bruno Moerschbacher

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Chitin, the biopolymer of the N-acetylglucosamine, is the most abundant biopolymer on the planet after cellulose. Industrially, chitin is isolated and purified from the shell residues of shrimps. A deacetylated derivative of chitin i.e. chitosan has more market value and applications owing to it solubility and overall cationic charge compared to the parent polymer. This deacetylation on an industrial scale is performed chemically using alkalis like sodium hydroxide. This reaction not only is hazardous to the environment owing to negative impact on the marine ecosystem. A greener option to this process is the enzymatic process. In nature, the naïve chitin is converted to chitosan by chitin deacetylase (CDA). This enzymatic conversion on the industrial scale is however hampered by the crystallinity of chitin. Thus, this enzymatic action requires the substrate i.e. chitin to be soluble which is technically difficult and an energy consuming process. We in this project wanted to address this shortcoming of CDA. In lieu of this, we have modeled a fusion protein with CDA and an auxiliary protein. The main interest being to increase the accessibility of the enzyme towards crystalline chitin. A similar fusion work with chitinases had improved the catalytic ability towards insoluble chitin. In the first step, suitable partners were searched through the protein data bank (PDB) wherein the domain architecture were sought. The next step was to create the models of the fused product using various in silico techniques. The models were created by MODELLER and evaluated for properties such as the energy or the impairment of the binding sites. A fusion PCR has been designed based on the linker sequences generated by MODELLER and would be tested for its activity towards insoluble chitin.

Keywords: chitin deacetylase, modeling, chitin binding domain, chitinases

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Authors: Dorota Miroslaw-Swiatek, Mateusz Grygoruk, Sylwia Szporak

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We applied a two-dimensional surface water flow model with irregular wet boundaries. In this model, flow equations are in the form of a 2-D, non-linear diffusion equations which allows to account spatial variations in flow resistance and topography. Calculation domain to simulate the flow pattern in the floodplain is congruent with a Digital Elevation Model (DEM) grid. The rate and direction of sheet flow in wetlands is affected by vegetation type and density, therefore the developed model take into account spatial distribution vegetation resistance to the water flow. The model was tested in a part of the Biebrza Valley, of an outstanding heterogeneity in the elevation and flow resistance distributions due to various ecohydrological conditions and management measures. In our approach we used the highest-possible quality of the DEM in order to obtain hydraulic slopes and vegetation distribution parameters for the modelling. The DEM was created from the cloud of points measured in the LiDAR technology. The LiDAR reflects both the land surface as well as all objects on top of it such as vegetation. Depending on the density of vegetation cover the ability of laser penetration is variable. Therefore to obtain accurate land surface model the “vegetation effect” was corrected using data collected in the field (mostly the vegetation height) and satellite imagery such as Ikonos (to distinguish different vegetation types of the floodplain and represent them spatially). Model simulation was performed for the spring thaw flood in 2009.

Keywords: floodplain flow, Biebrza valley, model simulation, 2D surface flow model

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Authors: Ahmed Ashit

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Image fusion is a significant and efficient image processing method used for detecting different types of tumors. This method has been used as an effective combination technique for obtaining high quality images that combine anatomy and physiology of an organ. It is the main key in the huge biomedical machines for diagnosing cancer such as PET-CT machine. This thesis aims to develop an image analysis system for the detection of the eye tumor. Different image processing methods are used to extract the tumor and then mark it on the original image. The images are first smoothed using median filtering. The background of the image is subtracted, to be then added to the original, results in a brighter area of interest or tumor area. The images are adjusted in order to increase the intensity of their pixels which lead to clearer and brighter images. once the images are enhanced, the edges of the images are detected using canny operators results in a segmented image comprises only of the pupil and the tumor for the abnormal images, and the pupil only for the normal images that have no tumor. The images of normal and abnormal images are collected from two sources: “Miles Research” and “Eye Cancer”. The computerized experimental results show that the developed image fusion based eye tumor detection system is capable of detecting the eye tumor and segment it to be superimposed on the original image.

Keywords: image fusion, eye tumor, canny operators, superimposed

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Authors: Altilio Rosa, Chirico Francesco, Foglia Goffredo

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In recent years, the number of Unmanned Aerial Vehicles (UAVs) has significantly increased. The rapid development of commercial and recreational drones makes them an important part of our society. Despite the growing list of their applications, these vehicles pose a huge threat to civil and military installations: detection, classification and neutralization of such flying objects become an urgent need. Radar is an effective remote sensing tool for detecting and tracking flying objects, but scenarios characterized by the presence of a high number of tracks related to flying birds make especially challenging the drone detection task: operator PPI is cluttered with a huge number of potential threats and his reaction time can be severely affected. Flying birds compared to UAVs show similar velocity, RADAR cross-section and, in general, similar characteristics. Building from the absence of a single feature that is able to distinguish UAVs and birds, this paper uses a multiple features approach where an original feature selection technique is developed to feed binary classifiers trained to distinguish birds and UAVs. RADAR tracks acquired on the field and related to different UAVs and birds performing various trajectories were used to extract specifically designed target movement-related features based on velocity, trajectory and signal strength. An optimization strategy based on a genetic algorithm is also introduced to select the optimal subset of features and to estimate the performance of several classification algorithms (Neural network, SVM, Logistic regression…) both in terms of the number of selected features and misclassification error. Results show that the proposed methods are able to reduce the dimension of the data space and to remove almost all non-drone false targets with a suitable classification accuracy (higher than 95%).

Keywords: birds, classification, machine learning, UAVs

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Authors: Jigg L. Pelayo, Ricardo G. Villar, Einstine M. Opiso

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The advances of aerial laser scanning in the Philippines has open-up entire fields of research in remote sensing and machine vision aspire to provide accurate timely information for the government and the public. Rapid mapping of polygonal roads and roof boundaries is one of its utilization offering application to disaster risk reduction, mitigation and development. The study uses low density LiDAR data and high resolution aerial imagery through object-oriented approach considering the theoretical concept of data analysis subjected to machine learning algorithm in minimizing the constraints of feature extraction. Since separating one class from another in distinct regions of a multi-dimensional feature-space, non-trivial computing for fitting distribution were implemented to formulate the learned ideal hyperplane. Generating customized hybrid feature which were then used in improving the classifier findings. Supplemental algorithms for filtering and reshaping object features are develop in the rule set for enhancing the final product. Several advantages in terms of simplicity, applicability, and process transferability is noticeable in the methodology. The algorithm was tested in the different random locations of Misamis Oriental province in the Philippines demonstrating robust performance in the overall accuracy with greater than 89% and potential to semi-automation. The extracted results will become a vital requirement for decision makers, urban planners and even the commercial sector in various assessment processes.

Keywords: feature extraction, machine learning, OBIA, remote sensing

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Authors: Asma Omri, Noureddine Benothman, Sofiane Sayahi, Fethi Tlili, Hichem Besbes

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Cycling, a popular mode of transportation, can also be perilous due to cyclists' vulnerability to collisions with vehicles and obstacles. This paper presents an innovative cyclist safety system based on radar technology designed to offer real-time collision risk warnings to cyclists. The system incorporates a low-power radar sensor affixed to the bicycle and connected to a microcontroller. It leverages radar point cloud detections, a clustering algorithm, and a supervised classifier. These algorithms are optimized for efficiency to run on the TI’s AWR 1843 BOOST radar, utilizing a coarse classification approach distinguishing between cars, trucks, two-wheeled vehicles, and other objects. To enhance the performance of clustering techniques, we propose a 2-Level clustering approach. This approach builds on the state-of-the-art Density-based spatial clustering of applications with noise (DBSCAN). The objective is to first cluster objects based on their velocity, then refine the analysis by clustering based on position. The initial level identifies groups of objects with similar velocities and movement patterns. The subsequent level refines the analysis by considering the spatial distribution of these objects. The clusters obtained from the first level serve as input for the second level of clustering. Our proposed technique surpasses the classical DBSCAN algorithm in terms of geometrical metrics, including homogeneity, completeness, and V-score. Relevant cluster features are extracted and utilized to classify objects using an SVM classifier. Potential obstacles are identified based on their velocity and proximity to the cyclist. To optimize the system, we used the View of Delft dataset for hyperparameter selection and SVM classifier training. The system's performance was assessed using our collected dataset of radar point clouds synchronized with a camera on an Nvidia Jetson Nano board. The radar-based cyclist safety system is a practical solution that can be easily installed on any bicycle and connected to smartphones or other devices, offering real-time feedback and navigation assistance to cyclists. We conducted experiments to validate the system's feasibility, achieving an impressive 85% accuracy in the classification task. This system has the potential to significantly reduce the number of accidents involving cyclists and enhance their safety on the road.

Keywords: 2-level clustering, coarse classification, cyclist safety, warning system based on radar technology

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Authors: Metuku Shyamsunder, Kakarla Subbarao, P. Prasanna

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In radars, an electromagnetic waveform is sent, and an echo of the same signal is received by the receiver. From this received signal, by extracting various parameters such as round trip delay, Doppler frequency it is possible to find distance, speed, altitude, etc. However, nowadays as the technology increases, intruders are intercepting transmitted signal as it reaches them, and they will be extracting the characteristics and trying to modify them. So there is a need to develop a system whose signal cannot be identified by no cooperative intercept receivers. That is why LPI radars came into existence. In this paper, a brief discussion on LPI radar and its modulation (polytime code (PT1)), detection (cyclostationary (DFSM & FAM) techniques such as DFSM, FAM are presented and compared with respect to computational complexity.

Keywords: LPI radar, polytime codes, cyclostationary DFSM, FAM

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Authors: A. Torokhti

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A new method of mathematical modeling of the distributed nonlinear system is developed. The system is represented by a combination of the set of spatially distributed sensors and the fusion center. Its mathematical model is obtained from the iterative procedure that converges to the model which is optimal in the sense of minimizing an associated cost function.

Keywords: mathematical modeling, non-linear system, spatially distributed sensors, fusion center

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Authors: Jyh-Cherng Chen, Yi-Jie Lin

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This study tries to reuse the fly ash of municipal solid waste incinerator (MSWI) for the synthesis of zeolites. The fly ashes were treated with NaOH alkali fusion at different temperatures for 40 mins and then synthesized the zeolites with hydrothermal method at 105oC for different operation times. The effects of different operation conditions and the optimum synthesis parameters were explored. The specific surface area, surface morphology, species identification, adsorption capacity, and the reuse potentials of the synthesized zeolites were analyzed and evaluated. Experimental results showed that the optimum operation conditions for the synthesis of zeolite from the mixed fly ash were Si/Al=20, alkali/ash=1.5, alkali fusion reaction with NaOH at 800oC for 40 mins, hydrolysis with L/S=200 at 105oC for 24 hr, and hydrothermal synthesis at 105oC for 48 hr. The largest specific surface area of synthesized zeolite could be increased to 943.05m2/g. The influence of different operation parameters on the synthesis of zeolite from mixed fly ash followed the sequence of Si/Al > hydrolysis L/S> hydrothermal time > alkali fusion temperature > alkali/ash ratio. The XRD patterns of synthesized zeolites were identified to be similar with the ZSM-23 zeolite. The adsorption capacities of synthesized zeolite for pollutants were increased as rising the specific surface area of synthesized zeolite. In summary, MSWI fly ash can be treated and reused to synthesize the zeolite with high specific surface area by the alkali fusion and hydrothermal method. The zeolite can be reuse for the adsorption of various pollutants. They have great potential for development.

Keywords: alkali fusion, hydrothermal, fly ash, zeolite

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Authors: Jonathan A. Noble

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‘Origins’ is an exhibition designed and installed by MMA Design Studio, at the 2023 Venice Biennale. The instillation formed part of the ‘Dangerous Liaisons’ group exhibition at the Arsenale building. An immersive experience was created for those who visited, where video projection and the bodies of visitors interacted with the scene. Designed by South African architect, Mphethi Morojele – founder and owner of MMA – the primary inspiration for ‘Origins’ was the recent discovery by Professor Karim Sadr in 2019, of a substantial Tswana settlement. Situated in present day Suikerbosrand Nature Reserve, some 45km south of Johannesburg, this precolonial city named Kweneng, has been dated back to the fifteenth century. This remarkable discovery was achieved thanks to advanced aerial, LiDAR scanning technology, which was used to capture the traces of Kweneng, spanning a terrain of some 10km long and 2km wide. Discovered by light (LiDAR) and exhibited through light, Origins presents a simulated experience of Kweneng. The presentation of Kweneng was achieved primarily though video, with a circular projection onto the floor of an animated LiDAR data sequence, and onto the walls a filmed dance sequence choreographed to embody the architectural, spatial and symbolic significance of Kweneng. This paper documents the design process that was involved in the conceptualization, development and final realization of this noteworthy exhibition, with an elucidation upon key social and cultural questions pertaining to precolonial heritage, reimagined histories and postcolonial identity. Periods of change and of social awakening sometimes spark an interest in questions of origin, of cultural lineage and belonging – and which certainly is the case for contemporary, post-Apartheid South Africa. Researching this paper has required primary study of MMA Design Studio’s project archive, including various proposals and other design related documents, conceptual design sketches, architectural drawings and photographs. This material is supported by the authors first-hand interviews with Morejele and others who were involved, especially with respect to the choreography of the interpretive dance, LiDAR visualization techniques and video production that informed the simulated, immersive experience at the exhibition. Presenting a ‘dangerous liaison’ between architecture and dance, Origins looks into the distant past to frame contemporary questions pertaining to intangible heritage, animism and embodiment through architecture and dance – considerations which are required “to survive the future”, says Morojele.

Keywords: architecture and dance, Kweneng, MMA design studio, origins, Venice Biennale

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Authors: B. Elshafei, X. Mao

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The demand for renewable energy is significantly increasing, major investments are being supplied to the wind power generation industry as a leading source of clean energy. The wind energy sector is entirely dependable and driven by the prediction of wind speed, which by the nature of wind is very stochastic and widely random. This s0tudy employs deep multi-fidelity Gaussian process regression, used to predict wind speeds for medium term time horizons. Data of the RUNE experiment in the west coast of Denmark were provided by the Technical University of Denmark, which represent the wind speed across the study area from the period between December 2015 and March 2016. The study aims to investigate the effect of pre-processing the data by denoising the signal using empirical wavelet transform (EWT) and engaging the vector components of wind speed to increase the number of input data layers for data fusion using deep multi-fidelity Gaussian process regression (GPR). The outcomes were compared using root mean square error (RMSE) and the results demonstrated a significant increase in the accuracy of predictions which demonstrated that using vector components of the wind speed as additional predictors exhibits more accurate predictions than strategies that ignore them, reflecting the importance of the inclusion of all sub data and pre-processing signals for wind speed forecasting models.

Keywords: data fusion, Gaussian process regression, signal denoise, temporal extrapolation

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Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words (BOVW), classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar (PolSAR)

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Authors: Davide D’Aria, Paolo Falcone, Luigi Maggi, Aldo Cero, Giovanni Amoroso

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The paper presents a methodology for real-time structural health monitoring and geophysical applications. The key elements of the system are a high performance MIMO RADAR sensor, an optical camera and a dedicated set of software algorithms encompassing interferometry, tomography and photogrammetry. The MIMO Radar sensor proposed in this work, provides an extremely high sensitivity to displacements making the system able to react to tiny deformations (up to tens of microns) with a time scale which spans from milliseconds to hours. The MIMO feature of the system makes the system capable of providing a set of two-dimensional images of the observed scene, each mapped on the azimuth-range directions with noticeably resolution in both the dimensions and with an outstanding repetition rate. The back-scattered energy, which is distributed in the 3D space, is projected on a 2D plane, where each pixel has as coordinates the Line-Of-Sight distance and the cross-range azimuthal angle. At the same time, the high performing processing unit allows to sense the observed scene with remarkable refresh periods (up to milliseconds), thus opening the way for combined static and dynamic structural health monitoring. Thanks to the smart TX/RX antenna array layout, the MIMO data can be processed through a tomographic approach to reconstruct the three-dimensional map of the observed scene. This 3D point cloud is then accurately mapped on a 2D digital optical image through photogrammetric techniques, allowing for easy and straightforward interpretations of the measurements. Once the three-dimensional image is reconstructed, a 'repeat-pass' interferometric approach is exploited to provide the user of the system with high frequency three-dimensional motion/vibration estimation of each point of the reconstructed image. At this stage, the methodology leverages consolidated atmospheric correction algorithms to provide reliable displacement and vibration measurements.

Keywords: interferometry, MIMO RADAR, SAR, tomography

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Authors: Y. S. Zhou, C. R. Li, L. L. Tang, C. X. Gao, D. J. Wang, Y. Y. Guo

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Triangular trihedral corner reflector (CR) has been widely used as point target for synthetic aperture radar (SAR) calibration and image quality assessment. The additional “tip” of the triangular plate does not contribute to the reflector’s theoretical RCS and if it interacts with a perfectly reflecting ground plane, it will yield an increase of RCS at the radar bore-sight and decrease the accuracy of SAR calibration and image quality assessment. Regarding this problem, two types of CRs were manufactured. One was the hexagonal trihedral CR. It is a self-illuminating CR with relatively small plate edge length, while large edge length usually introduces unexpected edge diffraction error. The other was the triangular trihedral CR with extended bottom plate which considers the effect of ‘tip’ into the total RCS. In order to assess the performance of the two types of new CRs, flight campaign over the National Calibration and Validation Site for High Resolution Remote Sensors was carried out. Six hexagonal trihedral CRs and two bottom-extended trihedral CRs, as well as several traditional triangular trihedral CRs, were deployed. KOMPSAT-5 X-band SAR image was acquired for the performance analysis of the hexagonal trihedral CRs. C-band airborne SAR images were acquired for the performance analysis of the bottom-extended trihedral CRs. The analysis results showed that the impulse response function of both the hexagonal trihedral CRs and bottom-extended trihedral CRs were much closer to the ideal sinc-function than the traditional triangular trihedral CRs. The flight campaign results validated the advantages of new types of CRs and they might be useful in the future SAR calibration mission.

Keywords: synthetic aperture radar, calibration, corner reflector, KOMPSAT-5

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Authors: Jigg Pelayo, Ricardo Villar

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Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.

Keywords: algorithm, LiDAR, object recognition, OBIA

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Authors: Hasan Basri Jumin

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Protoplasts isolated from embryogenic callus of Citrus sinensis were electrically used with mesophyll protoplasts isolated from seedless Citrus relatives. Hybrid of somatic embryos plantlets was obtained after 7 months of culture. Somatic hybrid plants were regenerated into normal seedlings and successfully transferred to soil after strictly acclimatization in the glass pot. The somatic hybrid plants were obtained by screening on the basis of chromosomes count. The number of chromosome of root tip counting revealed plantlets tetraploids (2n = 4x = 36) and the other were diploids (2n = 2x = 18) morphologically resembling the mesophyll parent. This somatic hybrid will be utilized as a possible pollen parent for improving the Citrus sinensis. A complete protoplast-to-plant system of somatic hybrid was developed for Citrus sinensis and Citrus relatives which could facilitate the transfer of nuclear and cytoplasmic genes from this species into cultivated Citrus through protoplast fusion.

Keywords: chromosome, Murraya paniculata, protoplast fusion, somatic hybrid, tetrapoliod

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Authors: H. Yousefnia, S. Zolghadri

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An early diagnosis of bone metastases is very important for providing a profound decision on a subsequent therapy. A prerequisite for the clinical application of new diagnostic radiopharmaceutical is the measurement of organ radiation exposure dose from biodistribution data in animals. In this study, the dosimetric studies of a novel agent for SPECT-imaging of bone methastases, 111In-(4-{[(bis(phosphonomethyl))carbamoyl]methyl}-7,10-bis(carboxymethyl)-1,4,7,10-tetraazacyclododec-1-yl) acetic acid (111In-BPAMD) complex, have been estimated in human organs based on mice data. The radiolabeled complex was prepared with high radiochemical purity at the optimal conditions. Biodistribution studies of the complex were investigated in male Syrian mice at selected times after injection (2, 4, 24 and 48 h). The human absorbed dose estimation of the complex was performed based on mice data by the radiation absorbed dose assessment resource (RADAR) method. 111In-BPAMD complex was prepared with high radiochemical purity >95% (ITLC) and specific activities of 2.85 TBq/mmol. Total body effective absorbed dose for 111In-BPAMD was 0.205 mSv/MBq. This value is comparable to the other 111In clinically used complexes. The results show that the dose to critical organs the complex is well within the acceptable considered range for diagnostic nuclear medicine procedures. Generally, 111In-BPAMD has interesting characteristics and can be considered as a viable agent for SPECT-imaging of the bone metastases in the near future.

Keywords: In-111, BPAMD, absorbed dose, RADAR

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Authors: Sahar Maâlej Dammak, Anis Jedidi, Rafik Bouaziz

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With the great mass of pages managed through the world, and especially with the advent of the Web, their manual annotation is impossible. We focus, in this paper, on the semiautomatic annotation of the web pages. We propose an approach and a framework for semantic annotation of web pages entitled “Querying Web”. Our solution is an enhancement of the first result of annotation done by the “Semantic Radar” Plug-in on the web resources, by annotations using an enriched domain ontology. The concepts of the result of Semantic Radar may be connected to several terms of the ontology, but connections may be uncertain. We represent annotations as possibility distributions. We use the hierarchy defined in the ontology to compute degrees of possibilities. We want to achieve an automation of the fuzzy semantic annotation of web resources.

Keywords: fuzzy semantic annotation, semantic web, domain ontologies, querying web

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Authors: Hantian Wu, Bo Huang, Yuan Zeng

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Divisions between wealthy and poor, private and public landscapes are propagated by the increasing economic inequality of cities. While these are the spatial reflections of larger social issues and problems, urban design can at least employ spatial techniques that promote more inclusive rather than exclusive, overlapping rather than segregated, interlinked rather than disconnected landscapes. Indeed, the type of edge or border between urban landscapes plays a critical role in the way the environment is perceived. China experiences rapid urbanization, which poses unpredictable environmental challenges. The urban green cover and water body are under changes, which highly relevant to resident wealth and happiness. However, very limited knowledge and data on their rapid changes are available. In this regard, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understating the driving forces of urban landscape changes can be a significant contribution for urban planning and studying. High-resolution remote sensing data has been widely applied to urban management in China. The map of urban land use map for the entire China of 2018 with 10 meters resolution has been published. However, this research focuses on the large-scale and high-resolution remote sensing land use but does not precisely focus on the seasonal change of urban covers. High-resolution remote sensing data has a long-operation cycle (e.g., Landsat 8 required 16 days for the same location), which is unable to satisfy the requirement of monitoring urban-landscape changes. On the other hand, aerial-remote or unmanned aerial vehicle (UAV) sensing are limited by the aviation-regulation and cost was hardly widely applied in the mega-cities. Moreover, those data are limited by the climate and weather conditions (e.g., cloud, fog), and those problems make capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Particularly, during the rainy season, no data are available even for Sentinel Satellite data with 5 days interval. Many natural events and/or human activities drive the changes of urban covers. In this case, enhancing the monitoring of urban landscape with high-frequency method, evaluating and estimating the impacts of the urban landscape changes, and understanding the mechanism of urban landscape changes can be a significant contribution for urban planning and studying. This project aims to use the high spatiotemporal fusion of remote sensing data to create short-cycle, high-resolution remote sensing data sets for exploring the high-frequently urban cover changes. This research will enhance the long-term monitoring applicability of high spatiotemporal fusion of remote sensing data for the urban landscape for optimizing the urban management of landscape border to promoting the inclusive of the urban landscape to all communities.

Keywords: urban land cover changes, remote sensing, high spatiotemporal fusion, urban management

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Authors: Aishwarya Shekhar, Himanshu Sharma

Abstract:

Data deduplication is one of important data compression techniques for eliminating duplicate copies of repeating data, and has been widely used in cloud storage to reduce the amount of storage space and save bandwidth. In this process, duplicate data is expunged, leaving only one copy means single instance of the data to be accumulated. Though, indexing of each and every data is still maintained. Data deduplication is an approach for minimizing the part of storage space an organization required to retain its data. In most of the company, the storage systems carry identical copies of numerous pieces of data. Deduplication terminates these additional copies by saving just one copy of the data and exchanging the other copies with pointers that assist back to the primary copy. To ignore this duplication of the data and to preserve the confidentiality in the cloud here we are applying the concept of hybrid nature of cloud. A hybrid cloud is a fusion of minimally one public and private cloud. As a proof of concept, we implement a java code which provides security as well as removes all types of duplicated data from the cloud.

Keywords: confidentiality, deduplication, data compression, hybridity of cloud

Procedia PDF Downloads 366

Authors: Ki-Cheong Yoo, Yushik Han, Heejeung Sohn, Jinwoo Kim

Abstract:

A ground collapse can be caused by natural and artificial factors. Ground collapses that have occurred frequently in Korea were observed and classified into different types by the main contributing factor. In this study, ground collapse induced by groundwater level disturbance in an excavation site was analyzed. Also, ground loosening region around the excavation site was detected and analyzed using non-destructive testing, such as GPR (Ground Penetrating Radar) survey and Electrical Resistivity. The result of the surveys showed that the ground was loosened widely over the surrounding area of the excavation due to groundwater discharge.

Keywords: electrical resistivity, ground collapse, groundwater level, GPR (ground penetrating radar)

Procedia PDF Downloads 178

Authors: Arturo Daag

Abstract:

The Philippine Institute of Volcanology and Seismology (PHIVOLCS) is enhancing its liquefaction hazard map towards a detailed probabilistic approach using SDS and geophysical data. Target sites for liquefaction assessment are public schools in Metro Manila. Since target sites are in highly urbanized-setting, the objective of the project is to conduct both non-destructive geotechnical studies using Screw Driving Testing (SDFS) combined with geophysical data such as refraction microtremor array (ReMi), 3 component microtremor Horizontal to Vertical Spectral Ratio (HVSR), and ground penetrating RADAR (GPR). Initial test data was conducted in liquefaction impacted areas from the Mw 6.1 earthquake in Central Luzon last April 22, 2019 Province of Pampanga. Numerous accounts of liquefaction events were documented areas underlain by quaternary alluvium and mostly covered by recent lahar deposits. SDS estimated values showed a good correlation to actual SPT values obtained from available borehole data. Thus, confirming that SDS can be an alternative tool for liquefaction assessment and more efficient in terms of cost and time compared to SPT and CPT. Conducting borehole may limit its access in highly urbanized areas. In order to extend or extrapolate the SPT borehole data, non-destructive geophysical equipment was used. A 3-component microtremor obtains a subsurface velocity model in 1-D seismic shear wave velocity of the upper 30 meters of the profile (Vs30). For the ReMi, 12 geophone array with 6 to 8-meter spacing surveys were conducted. Microtremor data were computed through the Factor of Safety, which is the quotient of Cyclic Resistance Ratio (CRR) and Cyclic Stress Ratio (CSR). Complementary GPR was used to study the subsurface structure and used to inferred subsurface structures and groundwater conditions.

Keywords: screw drive testing, microtremor, ground penetrating RADAR, liquefaction

Procedia PDF Downloads 182

Authors: Yo-Sheng Lin, Chien-Chin Wang, Yun-Wen Lin, Chien-Yo Lee

Abstract:

A wide band power amplifier (PA) for 60 GHz and 77 GHz direct-conversion transceiver using standard 90 nm CMOS technology is reported. The PA comprises a cascode input stage with a wide band T-type input-matching network and inductive interconnection and load, followed by a common-source (CS) gain stage and a CS output stage. To increase the saturated output power (PSAT) and power-added efficiency (PAE), the output stage adopts a two-way power dividing and combining architecture. Instead of the area-consumed Wilkinson power divider and combiner, miniature low-loss transmission-line inductors are used at the input and output terminals of each of the output stages for wide band input and output impedance matching to 100 ohm. This in turn results in further PSAT and PAE enhancement. The PA consumes 92.2 mW and achieves maximum power gain (S21) of 23.3 dB at 56 GHz, and S21 of 21.7 dB and 14 dB, respectively, at 60 GHz and 77 GHz. In addition, the PA achieves excellent saturated output power (PSAT) of 10.6 dB and maximum power added efficiency (PAE) of 12.3% at 60 GHz. At 77 GHz, the PA achieves excellent PSAT of 10.4 dB and maximum PAE of 6%. These results demonstrate the proposed wide band PA architecture is very promising for 60 GHz wireless personal local network (WPAN) and 77 GHz automobile radar systems.

Keywords: 60 GHz, 77 GHz, PA, WPAN, automotive radar

Procedia PDF Downloads 563

Authors: A. E. El-Henawey, A. A. El-Kouny, M. M. Abd –El-Halim

Abstract:

Moving target indication (MTI) which is an anti-clutter technique that limits the display of clutter echoes. It uses the radar received information primarily to display moving targets only. The purpose of MTI is to discriminate moving targets from a background of clutter or slowly-moving chaff particles as shown in this paper. Processing system in these radars is so massive and complex; since it is supposed to perform a great amount of processing in very short time, in most radar applications the response of a single canceler is not acceptable since it does not have a wide notch in the stop-band. A double-delay canceler is an MTI delay-line canceler employing the two-delay-line configuration to improve the performance by widening the clutter-rejection notches, as compared with single-delay cancelers. This canceler is also called a double canceler, dual-delay canceler, or three-pulse canceler. In this paper, a double delay line canceler is chosen for study due to its simplicity in both concept and implementation. Discussing the implementation of a simple digital moving target indicator (DMTI) using FPGA which has distinct advantages compared to other application specific integrated circuit (ASIC) for the purposes of this work. The FPGA provides flexibility and stability which are important factors in the radar application.

Keywords: FPGA, MTI, double delay line canceler, Doppler Shift

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Authors: Kohei Inoue, Kenji Hara, Kiichi Urahama

Abstract:

We describe a relationship between integral images and differential images. First, we derive a simple difference filter from conventional integral image. In the derivation, we show that an integral image and the corresponding differential image are related to each other by simultaneous linear equations, where the numbers of unknowns and equations are the same, and therefore, we can execute the integration and differentiation by solving the simultaneous equations. We applied the relationship to an image fusion problem, and experimentally verified the effectiveness of the proposed method.

Keywords: integral images, differential images, differential filters, image fusion

Procedia PDF Downloads 487