Search results for: fixed live camera images

Authors: Ł. Morawiński, C. Jasiński, M. Jurkiewicz, S. Bou Habib, M. Bondyra

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With the development of optics, electronics, and computers, vision systems are increasingly used in various areas of life, science, and industry. Vision systems have a huge number of applications. They can be used in quality control, object detection, data reading, e.g., QR-code, etc. A large part of them is used for measurement purposes. Some of them make it possible to obtain a 3D reconstruction of the tested objects or measurement areas. 3D reconstruction algorithms are mostly based on creating depth maps from data that can be acquired from active or passive methods. Due to the specific appliance in airfield technology, only passive methods are applicable because of other existing systems working on the site, which can be blinded on most spectral levels. Furthermore, reconstruction is required to work long distances ranging from hundreds of meters to tens of kilometers with low loss of accuracy even with harsh conditions such as fog, rain, or snow. In response to those requirements, HRESS (Heliport REmote Safeguard System) was developed; which main part is a rotational head with a two-camera stereovision rig gathering images around the head in 360 degrees along with stereovision 3D reconstruction and point cloud combination. The sub-pixel analysis introduced in the HRESS system makes it possible to obtain an increased distance measurement resolution and accuracy of about 3% for distances over one kilometer. Ultimately, this leads to more accurate and reliable measurement data in the form of a point cloud. Moreover, the program algorithm introduces operations enabling the filtering of erroneously collected data in the point cloud. All activities from the programming, mechanical and optical side are aimed at obtaining the most accurate 3D reconstruction of the environment in the measurement area.

Keywords: airfield monitoring, artificial intelligence, stereovision, 3D reconstruction

Procedia PDF Downloads 104

Authors: Kerri L. Surbaugh, Lakmini Y. Mallikarachchi, Jason R. Rohr

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Emerging diseases are key factors in the disconcerting rate of contemporary amphibian declines. The chytrid fungus, Batrachochytrium dendrobatidis (Bd), ranks among the chief pathogenic challenges to vulnerable amphibian populations. Although live Bd can immunosuppress amphibian hosts, amphibian exposure to dead Bd can induce an adaptive immune response, leading to acquired resistance to the pathogen. In this experiment, dose and duration of flash-frozen Bd were manipulated over a variety of life-stages of the Cuban treefrog (Osteopilus septentrionalis) and the magnitude of acquired resistance to the pathogen was quantified via qPCR analyses of spore abundance post subsequent live Bd challenges. It was found that Cuban treefrogs can develop resistance to Bd and that life stage, dose and duration thresholds exist for acquired resistance. This experiment will aid in facilitating the development of a vaccine against Bd which could be used on location and could help curb worldwide amphibian declines associated with this pathogen.

Keywords: acquired resistance, ecoimmunology, emerging infectious disease, fungal host response, fungal pathogen, immunization

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Authors: Ingrid Argote, John Archila, Marcelo Becker

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In agriculture, intelligent systems applications have generated great advances in automating some of the processes in the production chain. In order to improve the efficiency of those systems is proposed a vision system to estimate the amount of fruits in sweet orange trees. This work presents a system proposal using capture of thermal images and fuzzy logic. A bibliographical review has been done to analyze the state-of-the-art of the different systems used in fruit recognition, and also the different applications of thermography in agricultural systems. The algorithm developed for this project uses the metrics of the fuzzines parameter to the contrast improvement and segmentation of the image, for the counting algorith m was used the Hough transform. In order to validate the proposed algorithm was created a bank of images of sweet orange Citrus (L.) Osbeck acquired in the Maringá Farm. The tests with the algorithm Indicated that the variation of the tree branch temperature and the fruit is not very high, Which makes the process of image segmentation using this differentiates, This Increases the amount of false positives in the fruit counting algorithm. Recognition of fruits isolated with the proposed algorithm present an overall accuracy of 90.5 % and grouped fruits. The accuracy was 81.3 %. The experiments show the need for a more suitable hardware to have a better recognition of small temperature changes in the image.

Keywords: Agricultural systems, Citrus, Fuzzy logic, Thermal images.

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Authors: Kartik Gupta, Umar Khan, Mayur Parab, Dhiraj Chaudhari, Afzal Ansari

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The report focuses on the study related to the Design and Simulation of a stabilator (an all-movable horizontal stabilizer) for a fixed-wing aircraft. The project involves the development of a computerized direct optimization procedure for designing an aircraft all-movable stabilator. This procedure evaluates various design variables to synthesize an optimal stabilator that meets specific requirements, including performance, control, stability, strength, and flutter velocity constraints. The work signifies the CFD (Computational Fluid Dynamics) analysis of the airfoils used in the stabilator along with the CFD analysis of the Stabilizer and Stabilator of an aircraft named Thorp- T18 in software like XFLR5 and ANSYS-Fluent. A comparative analysis between a Stabilizer and Stabilator of equal surface area and under the same environmental conditions was done, and the percentage of drag reduced by the Stabilator for the same amount of lift generated as the Stabilizer was also calculated lastly, Wind tunnel testing was performed on a scale down model of the Stabilizer and Stabilator and the results of the Wind tunnel testing were compared with the results of CFD.

Keywords: wind tunnel testing, CFD, stabilizer, stabilator

Procedia PDF Downloads 37

Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

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Authors: Shih-Yu Wang, Shun-Wen Hsiao

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In the field of cybersecurity, there exists many vendors giving malware samples classified results, namely naming after the label that contains some important information which is also called AV label. Lots of researchers relay on AV labels for research. Unfortunately, AV labels are too cluttered. They do not have a fixed format and fixed naming rules because the naming results were based on each classifiers' viewpoints. A way to fix the problem is taking a majority vote. However, voting can sometimes create problems of bias. Thus, we create a novel ensemble approach which does not rely on the cacophonous naming result but depend on group identification to aggregate everyone's opinion. To achieve this purpose, we develop an scoring system called Pairwise Consensus Score (PCS) to calculate result similarity. The entire method architecture combine Genetic Algorithm and PCS to find maximum consensus in the group. Experimental results revealed that our method outperformed the majority voting by 10% in term of the score.

Keywords: genetic algorithm, ensemble learning, malware family, malware labeling, AV labels

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Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

Procedia PDF Downloads 127

Authors: Baghdad Said

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Differential equations of fractional order have proved to be important tools to describe many physical phenomena and have been used in diverse fields such as engineering, mathematics as well as other applied sciences. On the other hand, the theory of differential equations involving the Stieltjes derivative (SD) with respect to a non-decreasing function is a new class of differential equations and has many applications as a unified framework for dynamic equations on time scales and differential equations with impulses at fixed times. The aim of this paper is to investigate the existence, uniqueness, and generalized Ulam-Hyers-Rassias stability (UHRS) of solutions for a boundary value problem of sequential fractional differential equations (SFDE) containing (SD). This study is based on the technique of noncompactness measures (MNCs) combined with Monch-Krasnoselski fixed point theorems (FPT), and the results are proven in an appropriate Banach space under sufficient hypotheses. We also give an illustrative example. In this work, we introduced a class of (SFDE) and the results are obtained under a few hypotheses. Future directions connected to this work could focus on another problem with different types of fractional integrals and derivatives, and the (SD) will be assumed under a more general hypothesis in more general functional spaces.

Keywords: SFDE, SD, UHRS, MNCs, FPT

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Authors: Yudhajit Datta, Hamsi Iyer, Jonathan Bandi, Ankit Sethia

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Motion Tracking and Stereo Vision are complicated, albeit well-understood problems in computer vision. Existing softwares that combine the two approaches to perform stereo motion tracking typically employ complicated and computationally expensive procedures. The purpose of this study is to create a simple and effective solution capable of combining the two approaches. The study aims to explore a strategy to combine the two techniques of two-dimensional motion tracking using Kalman Filter; and depth detection of object using Stereo Vision. In conventional approaches objects in the scene of interest are observed using a single camera. However for Stereo Motion Tracking; the scene of interest is observed using video feeds from two calibrated cameras. Using two simultaneous measurements from the two cameras a calculation for the depth of the object from the plane containing the cameras is made. The approach attempts to capture the entire three-dimensional spatial information of each object at the scene and represent it through a software estimator object. In discrete intervals, the estimator tracks object motion in the plane parallel to plane containing cameras and updates the perpendicular distance value of the object from the plane containing the cameras as depth. The ability to efficiently track the motion of objects in three-dimensional space using a simplified approach could prove to be an indispensable tool in a variety of surveillance scenarios. The approach may find application from high security surveillance scenes such as premises of bank vaults, prisons or other detention facilities; to low cost applications in supermarkets and car parking lots.

Keywords: kalman filter, stereo vision, motion tracking, matlab, object tracking, camera calibration, computer vision system toolbox

Procedia PDF Downloads 307

Authors: Laid Fekih

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Background: The purpose of this paper is to examine the psychological stressors caused by urbanization, a field study conducted on a sample range of youth who live in urban areas. Some of them reside in areas with green surroundings while others reside in lack of green areas, which saw the terrible expansion of urban. The study included the impact of urbanization on the mental health of youths; select the psychological problems most commonly caused by urbanization, and the impact of green spaces in alleviating stress. Method: The method used in this research is descriptive, as the data collected from a sample of 160 young men were analyzed. The tool used is the psychological distress test. We proceeded with some statistical techniques, which provided percentages, analysis of variance, and t-tests. Results: The findings of this research were: (i) The psychological stressors caused by urban expansion are mainly in the intensity of stress, incompetence, emotional, and psychosomatic problems. (ii) There was a statistically significant difference at the level of significance 0.02 among young people who live in places in green spaces and without green space in terms of psychological stressors, in favor of young people who live in places free of greenery. (iii) The quality of this primary variable effect of housing (rental or ownership) is statistically significant in favor of young people living in rented accommodation. Conclusion: The green spaces provided by Tlemcen city are inadequate and insufficient to fulfill the population's requirements for contact with nature, leading to such effects that may negatively affect mental health, which makes it a prominent process that should not be neglected. Incorporating green spaces into the design of buildings, homes, and communities to create shared spaces, which facilitate interaction and foster well-being, becomes the main purpose. We think this approach can support the reconstruction of the built environment with green spaces by facilitating the link between psychological stress perception studies and technologies.

Keywords: psychological stressors, urbanization, psychological problems, green spaces

Procedia PDF Downloads 64

Authors: N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Rita Magdalena, R. D. Atmaja, Sofia Saidah, Ocky Tiaramukti

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Colon cancer or colorectal cancer is a type of cancer that attacks the last part of the human digestive system. Lymphoma and carcinoma are types of cancer that attack human’s colon. Colon cancer causes deaths about half a million people every year. In Indonesia, colon cancer is the third largest cancer case for women and second in men. Unhealthy lifestyles such as minimum consumption of fiber, rarely exercising and lack of awareness for early detection are factors that cause high cases of colon cancer. The aim of this project is to produce a system that can detect and classify images into type of colon cancer lymphoma, carcinoma, or normal. The designed system used 198 data colon cancer tissue pathology, consist of 66 images for Lymphoma cancer, 66 images for carcinoma cancer and 66 for normal / healthy colon condition. This system will classify colon cancer starting from image preprocessing, feature extraction using Principal Component Analysis (PCA) and classification using K-Nearest Neighbor (K-NN) method. Several stages in preprocessing are resize, convert RGB image to grayscale, edge detection and last, histogram equalization. Tests will be done by trying some K-NN input parameter setting. The result of this project is an image processing system that can detect and classify the type of colon cancer with high accuracy and low computation time.

Keywords: carcinoma, colorectal cancer, k-nearest neighbor, lymphoma, principle component analysis

Procedia PDF Downloads 191

Authors: Sandy Bao, Yankang Bao

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The understanding of information that is being processed in the brain, especially in the lateral geniculate nucleus (LGN), has been proven challenging for modern neuroscience and for researchers with a focus on how neurons process signals and images. In this paper, we are proposing a method to image process different colors within different layers of LGN, that is, green information in layers 4 & 6 and red & blue in layers 3 & 5 based on the surface dimension of layers. We take into consideration the images in LGN and visual cortex, and that the edge detected information from the visual cortex needs to be considered in order to return back to the layers of LGN, along with the image in LGN to form the new image, which will provide an improved image that is clearer, sharper, and making it easier to identify objects in the image. Matrix Laboratory (MATLAB) simulation is performed, and results show that the clarity of the output image has significant improvement.

Keywords: lateral geniculate nucleus, matrix laboratory, neuroscience, visual cortex

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Authors: Tony K. Joseph, Balasubramanian Vathilingam, Stephane Morin

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Currently, the refiners around the world are more focused on improving the yield of light olefins (propylene and ethylene) as both of them are very prominent raw materials to produce wide spectrum of polymeric materials such as polyethylene and polypropylene. Henceforth, it is desirable to increase the yield of light olefins via selective cracking of heavy oil fractions. In this study, zeolite grown on SiC was used as the catalyst to do model cracking reaction of n-heptane. The catalytic cracking of n-heptane was performed in a fixed bed reactor (12 mm i.d.) at three different temperatures (425, 450 and 475 °C) and at atmospheric pressure. A carrier gas (N₂) was mixed with n-heptane with ratio of 90:10 (N₂:n-heptane), and the gaseous mixture was introduced into the fixed bed reactor. Various flow rate of reactants was tested to increase the yield of ethylene and propylene. For the comparison purpose, commercial zeolite was also tested in addition to Zeolite on SiC. The products were analyzed using an Agilent gas chromatograph (GC-9860) equipped with flame ionization detector (FID). The GC is connected online with the reactor and all the cracking tests were successfully reproduced. The entire catalytic evaluation results will be presented during the conference.

Keywords: cracking, catalyst, evaluation, ethylene, heptane, propylene

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Authors: Gannouni Sonia, Hammami Asma, Saidi Salwa, Rebai Noamen

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Water resources in Tunisia have experienced quantitative and qualitative degradation, especially when talking about wetlands and Sbekhas. Indeed, the objective of this work is to study the spatio-temporal evolution of salinity for 29 years (from 1987 to 2016). A study of the connection between surface water and groundwater is necessary to know the degree of influence of the Sebkha brines on the water table. The evolution of surface salinity is determined by remote sensing based on Landsat TM and OLI/TIRS satellite images of the years 1987, 2007, 2010, and 2016. The processing of these images allowed us to determine the NDVI(Normalized Difference Vegetation Index), the salinity index, and the surface temperature around Sebkha. In addition, through a geographic information system(GIS), we could establish a map of the distribution of salinity in the subsurface of the water table of Chott Mariem and Hergla/SidiBouAli/Kondar. The results of image processing and the calculation of the index and surface temperature show an increase in salinity downstream of in addition to the sebkha and the development of vegetation cover upstream and the western part of the sebkha. This richness may be due both to contamination by seawater infiltration from the barrier beach of Hergla as well as the passage of groundwater to the sebkha.

Keywords: spatio-temporal monitoring, salinity, satellite images, NDVI, sebkha

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Authors: T. Prabakaran

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Gas Insulated Substations (GIS) are widely used as important switchgear equipment because of its high reliability, low space requirement, low risk factor and easy maintenance, yet some failures have been reported. Some of the failures are due to presence of metallic particles inside the GIS compartment. The defect can be generated in GIS during production, maintenance, installation and can be due to ageing of the component. The Ultra-High Frequency (UHF) method is used to diagnose the insulation condition of GIS by detecting the PD signals in GIS. This paper identifies PD patterns for free moving particle defect and particle fixed on cone using UHF method. As insulation failure usually starts with PD activity, this paper investigates the differences in PD characteristics in SF6 gas with different types of defects. Experimental results show that correct identification of defects can be achieved based on considered PD characteristics. The method can be applied to prove the quality of assembly work at commissioning, also on a regular basis after many years in service to detect aged and conducting particles as a part of the condition based maintenance.

Keywords: gas insulated substation, partial discharge, free moving particle defect, particle fixed on cone defect, ultra high frequency method

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Authors: Marine Segui, Simon Bezin, Ruxandra Mihaela Botez

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As part of a ‘Morphing-Wing’ idea, this study consists of measuring how a winglet, which is able to change its shape during the flight, is efficient. Conventionally, winglets are fixed-vertical platforms at the wingtips, optimized for a cruise condition that the airplane should use most of the time. However, during a cruise, an airplane flies through a lot of cruise conditions corresponding to altitudes variations from 30,000 to 45,000 ft. The fixed winglets are not optimized for these variations, and consequently, they are supposed to generate some drag, and thus to deteriorate aircraft fuel consumption. This research assumes that it exists a winglet position that reduces the fuel consumption for each cruise condition. In this way, the methodology aims to find these optimal winglet positions, and to further simulate, and thus estimate the fuel consumption of an aircraft wearing this type of adaptive winglet during several cruise conditions. The adaptive winglet is assumed to have degrees of freedom given by the various changes of following surfaces: the tip chord, the sweep and the dihedral angles. Finally, results obtained during cruise simulations are presented in this paper. These results show that an adaptive winglet can reduce, thus improve up to 2.12% the fuel consumption of an aircraft during a cruise.

Keywords: aerodynamic, Cessna, Citation X, optimization, winglet

Procedia PDF Downloads 224

Authors: M. Abuqebitah, H. Tanyildizi, N. Yeyin, I. Cavdar, M. Demir, L. Kabasakal

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Aim: Targeted radionuclide therapy (TRT) is an increasingly used treatment modality for wide range of cancers. Presently dosimetry is highly required either to plan treatment or to ascertain the absorbed dose delivered to critical organs during treatment. Methods and Materials: The study comprised 7 patients suffered from prostate cancer with progressive disease and candidate to undergo Lu-177-DOTA-617 therapy following to PSMA- PET/CT imaging for all patients. (5.2±0.3 mCi) was intravenously injected. To evaluate bone marrow absorbed dose 2 cc blood samples were withdrawn in short variable times (3, 15, 30, 60, 180 minutes) after injection. Furthermore, whole body scans were performed using scintillation gama camera in 4, 24, 48, and 120 hours after injection and in order to quantify the activity taken up in the body, kidneys , liver, right parotid, and left parotid the geometric mean of anterior and posterior counts were determined through ROI analysis, after that background subtraction and attenuation correction were applied using patients PSMA- PET/CT images taking in a consideration: organ thickness, body thickness, and Hounsfield unites from CT scan. OLINDA/EXM dosimetry program was used for curve fitting, residence time calculation, and absorbed dose calculations. Findings: Absorbed doses of bone marrow, left kidney, right kidney, liver, left parotid, right parotid, total body were 1.28±0.52, 32.36±16.36, 32.7±13.68, 10.35±3.45, 38.67±21.29, 37.55±19.77, 2.25±0.95 (mGy/mCi), respectively. Conclusion: Our first results clarify that Lu-177-DOTA-617 is safe and reliable therapy as there were no complications seen. In the other hand, the observable variation in the absorbed dose of the critical organs among the patients necessitate patient-specific dosimetry approach to save body organs and particularly highly exposed kidneys and parotid gland.

Keywords: Lu-177-PSMA, prostate cancer, radionuclide therapy

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Authors: Liwei Liu, Shuguo Pan, Wang Gao

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In order to take full advantages of the BDS-3 penta-frequency signals in the long-baseline RTK positioning, a long-baseline RTK positioning method based on the BDS-3 penta-frequency ionospheric-reduced (IR) combinations is proposed. First, the low noise and weak ionospheric delay characteristics of the multi-frequency combined observations of BDS-3is analyzed. Second, the multi-frequency extra-wide-lane (EWL)/ wide-lane (WL) combinations with long-wavelengths are constructed. Third, the fixed IR EWL combinations are used to constrain the IR WL, then constrain narrow-lane (NL)ambiguityies and start multi-epoch filtering. There is no need to consider the influence of ionospheric parameters in the third step. Compared with the estimated ionospheric model, the proposed method reduces the number of parameters by half, so it is suitable for the use of multi-frequency and multi-system real-time RTK. The results using real data show that the stepwise fixed model of the IR EWL/WL/NL combinations can realize long-baseline instantaneous cimeter-level positioning.

Keywords: penta-frequency, ionospheric-reduced (IR), RTK positioning, long-baseline

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Authors: Stephen Tullis, M. David DiDonato, Hong Sung Park

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Rowing boats (shells) are often steered by a small rudder operated by one of the backward-facing rowers; the attention required of that athlete then slightly decreases the power that that athlete can provide. Reducing the steering distraction would then increase the overall boat speed. Races are straight 2000 m courses with each boat in a 13.5 m wide lane marked by small (~15 cm) widely-spaced (~10 m) buoys, and the boat trajectory is affected by both cross-currents and winds. An optical buoy recognition and tracking system has been developed that provides the boat’s location and orientation with respect to the lane edges. This information is provided to the steering athlete as either: a simple overlay on a video display, or fed to a simplified autopilot system giving steering directions to the athlete or directly controlling the rudder. The system is then effectively a “lane-assist” device but with small, widely-spaced lane markers viewed from a very shallow angle due to constraints on camera height. The image is captured with a lightweight 1080p webcam, and most of the image analysis is done in OpenCV. The colour RGB-image is converted to a grayscale using the difference of the red and blue channels, which provides good contrast between the red/yellow buoys and the water, sky, land background and white reflections and noise. Buoy detection is done with thresholding within a tight mask applied to the image. Robust linear regression using Tukey’s biweight estimator of the previously detected buoy locations is used to develop the mask; this avoids the false detection of noise such as waves (reflections) and, in particular, buoys in other lanes. The robust regression also provides the current lane edges in the camera frame that are used to calculate the displacement of the boat from the lane centre (lane location), and its yaw angle. The interception of the detected lane edges provides a lane vanishing point, and yaw angle can be calculated simply based on the displacement of this vanishing point from the camera axis and the image plane distance. Lane location is simply based on the lateral displacement of the vanishing point from any horizontal cut through the lane edges. The boat lane position and yaw are currently fed what is essentially a stripped down marine auto-pilot system. Currently, only the lane location is used in a PID controller of a rudder actuator with integrator anti-windup to deal with saturation of the rudder angle. Low Kp and Kd values decrease unnecessarily fast return to lane centrelines and response to noise, and limiters can be used to avoid lane departure and disqualification. Yaw is not used as a control input, as cross-winds and currents can cause a straight course with considerable yaw or crab angle. Mapping of the controller with rudder angle “overall effectiveness” has not been finalized - very large rudder angles stall and have decreased turning moments, but at less extreme angles the increased rudder drag slows the boat and upsets boat balance. The full system has many features similar to automotive lane-assist systems, but with the added constraints of the lane markers, camera positioning, control response and noise increasing the challenge.

Keywords: auto-pilot, lane-assist, marine, optical, rowing

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Authors: Gebrehiwot H., Giorgis Bahita

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Firms in Africa experience less financial market in comparison to other emerging and developed countries, thus lagging behind the rest of the world in terms of innovation and growth. Though there are different factors to be considered, underdeveloped financial systems take the lion's share in hindering firm innovation and growth in Africa. Insufficient capacity to innovate is one of the problems facing African businesses. Moreover, a critical challenge faced by firms in Africa is access to finance and the inability of financially constrained firms to grow. Only little is known about how different sources of finance affect firm innovation and growth in Africa, specifically the formal and informal finance effect on firm innovation and growth. This study's aim is to address this gap by using formal and informal finance for working capital and fixed capital and its role in firm innovation and firm growth using firm-level data from the World Bank enterprise survey 2006-2019 with a total of 5661 sample firms from 14 countries based on available data on the selected variables. Additionally, this study examines factors for accessing credit from a formal financial institution. The logit model is used to examine the effect of finance on a firm’s innovation and factors to access formal finance, while the Ordinary List Square (OLS) regression mode is used to investigate the effect of finance on firm growth. 2SLS instrumental variables are used to address the possible endogeneity problem in firm growth and finance-innovation relationships. A result from the logistic regression indicates that both formal and informal finance used for working capital and investment in fixed capital was found to have a significant positive association with product and process innovation. In the case of finance and growth, finding show that positive association of both formal and informal financing to working capital and new investment in fixed capital though the informal has positive relations to firm growth as measured by sale growth but no significant association as measured by employment growth. Formal finance shows more magnitude of effect on innovation and growth when firms use formal finance to finance investment in fixed capital, while informal finance show less compared to formal finance and this confirms previous studies as informal is mainly used for working capital in underdeveloped economies like Africa. The factors that determine credit access: Age, firm size, managerial experience, exporting, gender, and foreign ownership are found to have significant determinant factors in accessing credit from formal and informal sources among the selected sample countries.

Keywords: formal finance, informal finance, innovation, growth

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Authors: R. Vigneswaran, S. Thilakanathan

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Variable time-stepping algorithms for solving dynamical systems performed poorly for long time computations which pass close to a fixed point. To overcome this difficulty, several authors considered phase space error controls for numerical simulation of dynamical systems. In one generalized phase space error control, a step-size selection scheme was proposed, which allows this error control to be incorporated into the standard adaptive algorithm as an extra constraint at negligible extra computational cost. For this generalized error control, it was already analyzed the forward Euler method applied to the linear system whose coefficient matrix has real and negative eigenvalues. In this paper, this result was extended to the linear system whose coefficient matrix has complex eigenvalues with negative real parts. Some theoretical results were obtained and numerical experiments were carried out to support the theoretical results.

Keywords: adaptivity, fixed point, long time simulations, stability, linear system

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Authors: Kamalpreet Kaur, Renu Dhir

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Climate prediction is an essential component of climate research, which helps evaluate possible effects on economies, communities, and ecosystems. Climate prediction involves short-term weather prediction, seasonal prediction, and long-term climate change prediction. Climate prediction can use the information gathered from satellites, ground-based stations, and ocean buoys, among other sources. The paper's four architectures, such as ResNet50, VGG19, Inception-v3, and Xception, have been combined using an ensemble approach for overall performance and robustness. An ensemble of different models makes a prediction, and the majority vote determines the final prediction. The various architectures such as ResNet50, VGG19, Inception-v3, and Xception efficiently classify the dataset RSI-CB256, which contains satellite images into cloudy and non-cloudy. The generated ensembled S-E model (Sar-ensembled model) provides an accuracy of 99.25%.

Keywords: climate, satellite images, prediction, classification

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Authors: Marilei Amadeu Sabino

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The aim of this study is to establish differences between the terms ‘false cognates’, ‘false friends’ and ‘deceptive cognates’, usually considered to be synonyms. It will be shown they are not synonyms, since they do not designate the same linguistic process or phenomenon. Despite their differences in meaning, many pairs of formally similar words in two (or more) different languages are true cognates, although they are usually known as ‘false’ cognates – such as, for instance, the English and Italian lexical items ‘assist x assistere’; ‘attend x attendere’; ‘argument x argomento’; ‘apology x apologia’; ‘camera x camera’; ‘cucumber x cocomero’; ‘fabric x fabbrica’; ‘factory x fattoria’; ‘firm x firma’; ‘journal x giornale’; ‘library x libreria’; ‘magazine x magazzino’; ‘parent x parente’; ‘preservative x preservativo’; ‘pretend x pretendere’; ‘vacancy x vacanza’, to name but a few examples. Thus, one of the theoretical objectives of this paper is firstly to elaborate definitions establishing a distinction between the words that are definitely ‘false cognates’ (derived from different etyma) and those that are just ‘deceptive cognates’ (derived from the same etymon). Secondly, based on Set Theory and on the concepts of equal sets, subsets, intersection of sets and disjoint sets, this study is intended to elaborate some theoretical and practical questions that will be useful in identifying more precisely similarities and differences between cognate words of different languages, and according to graphic interpretation of sets it will be possible to classify them and provide discernment about the processes of semantic changes. Therefore, these issues might be helpful not only to the Learning of Second and Foreign Languages, but they could also give insights into Foreign and Second Language Teaching Methodology. Acknowledgements: FAPESP – São Paulo State Research Support Foundation – the financial support offered (proc. n° 2017/02064-7).

Keywords: deceptive cognates, false cognates, foreign language learning, teaching methodology

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Authors: Marwa Al-Subhi, Eiman Al-Ajmi, Mallak Al-Maamari, Humood Al-Dhuhli, Srinivasa Rao

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The orbit and its contents are affected by various pathologies and craniofacial anomalies. Sound knowledge of the normal orbital dimensions is clinically essential for successful surgical outcomes and also in the field of forensic anthropology. Racial, ethnic, and regional variations in the orbital dimensions have been reported. This study sought to determine the orbital dimensions of Omani subjects who had been referred for computed tomography (CT) images at a tertiary care hospital. A total of 273 patients’ CT images were evaluated retrospectively by using an electronic medical records database. The orbital dimensions were recorded using both axial and sagittal planes of CT images. The mean orbital index (OI) was found to be 83.25±4.83 and the prevalent orbital type was categorized as mesoseme. The mean orbital index was 83.34±5.05 and 83.16±4.57 in males and females, respectively, with their difference being statistically not significant (p=0.76). A statistically significant association was observed between the right and left orbits with regard to horizontal distance (p<0.05) and vertical distance (p<0.01) of orbit and OI (p<0.05). No significant difference between the OI and age groups was observed in both males and females. The mean interorbital distance and interzygomatic distance were found to be 19.45±1.52 mm and 95.59±4.08 mm, respectively. Both of these parameters were significantly higher in males (p<0.05). Results of the present study provide reference values of orbital dimensions in Omani subjects. The prevalent orbital type of Omani subjects is mesoseme, which is a hallmark of the white race.

Keywords: orbit, orbital index, mesoseme, ethnicity, variation

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Authors: Thuvanan Borvornvitchotikarn, Werasak Kurutach

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Mutual information (MI) is widely used in medical image registration. In the different medical images analysis, it is difficult to choose an optimal bins size number for calculating the probability distributions in MI. As the result, this paper presents a new adaptive bins number selection approach that named a hybrid EMPCA-Scott approach. This work combines an expectation maximization principal component analysis (EMPCA) and the modified Scott’s rule. The proposed approach solves the binning problem from the various intensity values in medical images. Experimental results of this work show the lower registration errors compared to other adaptive binning approaches.

Keywords: mutual information, EMPCA, Scott, probability distributions

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Authors: Babajide Olufemi Diyaolu

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The opportunity provided by advances in technology as regards sports betting is so numerous that even at one's comfort, with the use of a phone, Nigerian youth are found engaging in all kinds of betting. Today it is more difficult to differentiate a true fan as there are quite a number of them that became fans as a result of betting on live games. This study investigated the influence of online sports events on betting among Nigerian youth. A descriptive survey research design was used, and the population consists of all Nigerian youth that engages in betting and live within the southwest zone of Nigeria. A simple random sampling technique was used to pick three states from the southwest zone of Nigeria. Two thousand five hundred respondents comprising males and female were sampled from the three states. A structured questionnaire on online sports event contribution to sports betting (OSECSB) was used. The Instrument consists of three sections. Section A seeks information on the demographic data of the respondents. Section B seeks information on online sports events, while section C is used to extract information on sports betting. The modified instrument, which consists of 14 items, has a reliability coefficient of 0.74. The hypothesis was tested at 0.05 significance level. The completed questionnaire was collated, coded, and analyzed using descriptive statistics of frequency counts, percentage and pie chart, and inferential statistics of multiple regressions. The findings of this study revealed that online sports betting is a significant predictor of an increase in sports betting among Nigerian youth. The media and television, as well as globalization and the internet coupled with social media and various online platforms, have all contributed to the immense increase in sports betting. The increase in the advertisement of the betting platform during live matches, especially football, is becoming more alarming. In most organized international events, the media attention, as well as sponsorship right, are now been given to one or two betting platforms. There is a need for all stakeholders to put in place school-based intervention programs to reorientate our youth about the consequences of addiction to betting. Such programs must include meta-analyses and emotional control towards sports betting.

Keywords: betting platform, Nigerian fans, Nigerian youth, sports betting

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Authors: Mahdi Motahari, Mojtaba Farzaneh, Armin Parsian Nejad

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The rapidly growing wind industry is highly expressing the need for education and training worldwide, particularly on the system level. Modelling and simulating wind generator system using Matlab-Simulink provides expert help in understanding wind systems engineering and system design. Working under Matlab-Simulink we present the integration of the developed WECS model with public electrical grid. A test of the calculated power and Cp related to the experimental equivalent data, using statistical analysis is performed. The statistical indicators of accuracy show better results of the presented method with RMSE: 21%, 22%, MBE : 0.77%, 0.12 % and MAE :3%, 4%.On the other hand we study its behavior when integrated in whole power system. Three level of wind speeds have been chosen: low with 5m/s as the mean value, medium with 8m/s as the mean value and high speed with 12m/s as the mean value. These allowed predicting and supervising the active power produced by the system, characterized respectively by the middle powers of -150 kW, -250kW and -480 kW which will be injected directly into the public electrical grid and the reactive power, characterized respectively by the middle powers of 60 kW, 180 kW and 320 kW and will be consumed by the wind generator.

Keywords: modelling, simulation, wind generator, fixed speed wind turbine, Matlab-Simulink

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Dina Safrina

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This paper aims to discuss the suitability of tax administration in Indonesia based on Islamic Shari'a by looking at Abu Yusuf's idea of taxation. This research is a qualitative research and using data collection method by library research, that is by studying, deepening and citing theories or concepts from a number of literature. The purpose of this paper is to find out whether taxation in Indonesia is consistent with the thinking of Islamic economists, namely Abu Yusuf's idea which became known by economists as the canons of taxation. The ability to pay, lax time giving for taxpayers and the centralization of decision-making in the tax administration are some of the principles it emphasizes. In taxation he recommends the use of the Muqassamah (Proportional Tax) system rather than the Mixed (Fixed Tax) system. In this case, the determination of tax rates in Indonesia there are using fixed tax system, proportional tax, progressive tax and regressive tax. Abu Yusuf opposed the existence of Qabalah institution (the guarantor of tax payments to the state) at the time and suggested a tax administration centered and paid directly to the state. This is in accordance with those already applied in Indonesia where tax collection is done centrally. The tax system in Indonesia using self assessment system, which is the authority and responsibility given by the government to the taxpayer to calculate, pay and report the tax itself becomes the gap for taxpayers to commit fraud. Prerequisites that must be met for the success of this system is with the tax consciousness, tax honesty, tax mindedness, and tax discipline.

Keywords: Abu Yusuf, Indonesia, tax, tax administration

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Authors: Carolina Brandão Piva

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In our visual culture, images play a newly significant role in the basis of a complex dialogue between imagination, creativity, and social practice. Insofar as imagination has broken out of the 'special expressive space of art' to become a part of the quotidian mental work of ordinary people, it is pertinent to recognize that visual representation can no longer be assumed as if in a domain detached from everyday life or exclusively 'centered' within the limited frame of 'art history.' The approach of Visual Culture as a field of study is, in this sense, indispensable to comprehend that not only 'the image,' but also 'the imagined' and 'the imaginary' are produced in the plurality of social interactions; crucial enough, this assertion directs us to something new in contemporary cultural processes, namely both imagination and image production constitute a social practice. This paper starts off with this approach and seeks to examine the artistic practice of two women from the State of Goiás, Brazil, who are ordinary citizens with their daily activities and narratives but also dedicated to visuality production. With no formal training from art schools, branded or otherwise, Maria Aparecida de Souza Pires deploys 'waste disposal' of daily life—from car tires to old work clothes—as a trampoline for art; also adept at sourcing raw materials collected from her surroundings, she manipulates raw hewn wood, tree trunks, plant life, and various other pieces she collects from nature giving them new meaning and possibility. Hilda Freire works with sculptures in clay using different scales and styles; her art focuses on representations of women and pays homage to unprivileged groups such as the practitioners of African-Brazilian religions, blue-collar workers, poor live-in housekeepers, and so forth. Although they have never been acknowledged by any mainstream art institution in Brazil, whose 'criterion of value' still favors formally trained artists, Maria Aparecida de Souza Pires, and Hilda Freire have produced visualities that instigate 'new ways of seeing,' meriting cultural significance in many ways. Their artworks neither descend from a 'traditional' medium nor depend on 'canonical viewing settings' of visual representation; rather, they consist in producing relationships with the world which do not result in 'seeing more,' but 'at least differently.' From this perspective, the paper finally demonstrates that grouping this kind of artistic production under the label of 'mere craft' has much more to do with who is privileged within the fields of power in art system, who we see and who we do not see, and whose imagination of what is fed by which visual images in Brazilian contemporary society.

Keywords: visual culture, artistic practice, women's art in the Brazilian State of Goiás, Maria Aparecida de Souza Pires, Hilda Freire

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