Search results for: dynamic object tracking

Authors: Monica Racha, Siva Chandrasekaran, Alex Stojcevski

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The engineering programs focus on promoting students' personal and professional development by ensuring that students acquire technical and professional competencies during four-year studies. The traditional engineering laboratory provides an opportunity for students to "practice by doing," and laboratory facilities aid them in obtaining insight and understanding of their discipline. Due to rapid technological advancements and the current COVID-19 outbreak, the traditional labs were transforming into virtual learning environments. Aim: To better understand the limitations of the physical laboratory, this research study aims to use a Machine Learning (ML) algorithm that interfaces with the Augmented Reality HoloLens and predicts the image behavior to classify and detect the electronic components. The automated electronic components error classification and detection automatically detect and classify the position of all components on a breadboard by using the ML algorithm. This research will assist first-year undergraduate engineering students in conducting laboratory practices without any supervision. With the help of HoloLens, and ML algorithm, students will reduce component placement error on a breadboard and increase the efficiency of simple laboratory practices virtually. Method: The images of breadboards, resistors, capacitors, transistors, and other electrical components will be collected using HoloLens 2 and stored in a database. The collected image dataset will then be used for training a machine learning model. The raw images will be cleaned, processed, and labeled to facilitate further analysis of components error classification and detection. For instance, when students conduct laboratory experiments, the HoloLens captures images of students placing different components on a breadboard. The images are forwarded to the server for detection in the background. A hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm will be used to train the dataset for object recognition and classification. The convolution layer extracts image features, which are then classified using Support Vector Machine (SVM). By adequately labeling the training data and classifying, the model will predict, categorize, and assess students in placing components correctly. As a result, the data acquired through HoloLens includes images of students assembling electronic components. It constantly checks to see if students appropriately position components in the breadboard and connect the components to function. When students misplace any components, the HoloLens predicts the error before the user places the components in the incorrect proportion and fosters students to correct their mistakes. This hybrid Convolutional Neural Networks (CNNs) and Support Vector Machines (SVMs) algorithm automating electronic component error classification and detection approach eliminates component connection problems and minimizes the risk of component damage. Conclusion: These augmented reality smart glasses powered by machine learning provide a wide range of benefits to supervisors, professionals, and students. It helps customize the learning experience, which is particularly beneficial in large classes with limited time. It determines the accuracy with which machine learning algorithms can forecast whether students are making the correct decisions and completing their laboratory tasks.

Keywords: augmented reality, machine learning, object recognition, virtual laboratories

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Authors: Manu Manu, Pardha J. Saradhi, Ramana M. V. Murthy

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Wind Energy is accepted as one of the most developed, cost effective and proven renewable energy technologies to meet increasing electricity demands in a sustainable manner. Preliminary assessment studies along Indian Coastline by Ministry of New and Renewable Energy have indicated prospects for development of offshore wind power along Tamil Nadu Coast, India. The commercial viability of a wind project mainly depends on wind characteristics on site. Hence, it is internationally recommended to perform site-specific wind resource assessment based on two years’ wind profile as a part of the feasibility study. Conventionally, guy wire met mast are used onshore for the collection of wind profile. Installation of similar structure in offshore requires complex marine spread and are very expensive. In the present study, an attempt is made to develop 120 m long lattice tower supported on the jacket, piled to the seabed at Rameshwaram, Tamil Nadu, India. Offshore met-masts are subjected to combined wind and hydrodynamic loads, and these lateral loads should be safely transferred to soil. The wind loads are estimated based on gust factor method, and the hydrodynamic loads are estimated by Morison’s equation along with suitable wave theory. The soil is modeled as three nonlinear orthogonal springs based on API standards. The structure configuration and optimum member sizes are obtained for extreme cyclone events. The dynamic behavior of mast under coupled wind and wave loads is also studied. The static responses of a mast with jacket type offshore platform have been studied using a frame model in SESAM. It is found from the study that the maximum displacement at the top of the mast for the random wave is 0.003 m and that of the tower for wind is 0.08 m during the steady state. The dynamic analysis results indicate that the structure is safe against coupled wind and wave loading.

Keywords: offshore wind, mast, static, aerodynamic load, hydrodynamic load

Procedia PDF Downloads 197

Authors: Pranjal Srivastava, Piyali Sengupta

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The performance of marine drilling risers is crucial in the offshore oil and gas industry to ensure safe drilling operation with minimum downtime. Experimental investigations on marine drilling risers are limited in the literature owing to the expensive and exhaustive test setup required to replicate the realistic riser model and ocean environment in the laboratory. Therefore, this study presents an analytical model of marine drilling riser for determining its fragility under ocean environmental loading. In this study, the marine drilling riser is idealized as a continuous beam having a concentric circular cross-section. Hydrodynamic loading acting on the marine drilling riser is determined by Morison’s equations. By considering the equilibrium of forces on the marine drilling riser for the connected and normal drilling conditions, the governing partial differential equations in terms of independent variables z (depth) and t (time) are derived. Subsequently, the Runge Kutta method and Finite Difference Method are employed for solving the partial differential equations arising from the analytical model. The proposed analytical approach is successfully validated with respect to the experimental results from the literature. From the dynamic analysis results of the proposed analytical approach, the critical design parameters peak displacements, upper and lower flex joint rotations and von Mises stresses of marine drilling risers are determined. An extensive parametric study is conducted to explore the effects of top tension, drilling depth, ocean current speed and platform drift on the critical design parameters of the marine drilling riser. Thereafter, incremental dynamic analysis is performed to derive the fragility functions of shallow water and deep-water marine drilling risers under ocean environmental loading. The proposed methodology can also be adopted for downtime estimation of marine drilling risers incorporating the ranges of uncertainties associated with the ocean environment, especially at deep and ultra-deepwater.

Keywords: drilling riser, marine, analytical model, fragility

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Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

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It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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Authors: R. Ghasemi, M. R. Rahimi Khoygani

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This paper proposes the designing direct adaptive neural controller to apply for a class of a nonlinear pendulum dynamic system. The radial basis function (RBF) neural adaptive controller is robust in presence of external and internal uncertainties. Both the effectiveness of the controller and robustness against disturbances are importance of this paper. The simulation results show the promising performance of the proposed controller.

Keywords: adaptive neural controller, nonlinear dynamical, neural network, RBF, driven pendulum, position control

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Authors: Selma R. Oliveira, E. W. Cazarini

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Recently, studies have referenced innovation as a key factor affecting the performance of firms. Companies make use of its innovative capacities to achieve sustainable competitive advantage. In this perspective, the objective of this paper is to contribute to innovation planning policies in industry 4.0. Thus, this paper examines the disruptive innovation capacity on firm performance in Europe. This procedure was prepared according to the following phases: Phase 1: Determination of the conceptual model; and Phase 2: Verification of the conceptual model. The research was initially conducted based on the specialized literature, which extracted the data regarding the constructs/structure and content in order to build the model. The research involved the intervention of experts knowledgeable on the object studied, selected by technical-scientific criteria. The data were extracted using an assessment matrix. To reduce subjectivity in the results achieved the following methods were used complementarily and in combination: multicriteria analysis, multivariate analysis, psychometric scaling and neurofuzzy technology. The data were extracted using an assessment matrix and the results were satisfactory, validating the modeling approach.

Keywords: disruptive innovation, capacity, performance, Industry 4.0

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Authors: Abdelkader Merah, Kada Hartani

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A reference model based control approach for improving behavior following car is proposed in this paper. The reference model is nonlinear and provides dynamic solutions consistent with safety constraints and comfort specifications. a robust fuzzy logic based control strategy is further proposed in this paper. A set of simulation results showing the suitability of the proposed technique for various demanding cenarios is also included in this paper.

Keywords: reference model, longitudinal control, fuzzy logic, design of car

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Authors: Bensaid A., Mostephaoui T., Nedjai R.

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Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

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Authors: Souhila Belabbas

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This paper focuses on the Kabyles’ multilingual practices in the UK, within the Kabyle/Amazigh Cultural Organisation in London, on online platforms and at home. The Kabyles have roots in northern Algeria and associate their language, Kabyle, with a pre-Arabized history of northern Africa. Drawing on ethnographic research with this community, this study brings together their post-migration language preservation activisms as well as their dynamic multilingual practices and situational language choice into a dialogue. This shows the enduring significance of the heritage language for social, cultural and historical identity. It also demonstrates that the current survival of the “mother tongue” hinges on multilingual and multi-sited language activisms, which bear the hallmarks of both new creativities and diminishing fluencies in multilingual spaces. These multilingual repertoires also included a range of ideological stances, expressed as cultural, moral, and political attitudes to the “mother tongue” and to other, potentially more dominant, languages in their lives, involving both inclusive and exclusive instances. The Kabyles in the UK practice everyday forms of multilingualism in the dynamic terms whilst making strong identity claims to an endangered heritage language. Crucially, their language contact experiences were not a post-migration novelty but part of their pre-migration lifeworlds. The participants involved in this study shared a commitment to Kabyle identity activism. They expressed this differently, varyingly foregrounding cultural, social or political issues. These differences were related to their North-African cultural background, live, gender, religious and/or political affiliation, as well as to their different migratory trajectories. Among these ethno-conscious individuals, the use of Kabyle was often particularly vibrant in informal domains of casual conversations and mixed in with French, English and often Arabic. During community events and festivals, though, many made special efforts to converse in Kabyle as if to make a point about their commitment to a shared identity.

Keywords: ethnography, language ideology, language choice, heritage language, migration trajectories, multilingual repertoires

Procedia PDF Downloads 62

Authors: Souhila Belabbas

Abstract:

This paper focuses on the Kabyles’ multilingual practices in the UK, within the Kabyle/Amazigh Cultural Organisation in London, on online platforms and at home. The Kabyles have roots in northern Algeria and associate their language, Kabyle, with a pre-Arabized history of northern Africa. Drawing on ethnographic research with this community, this study brings together their post-migration language preservation activisms as well as their dynamic multilingual practices and situational language choice into a dialogue. This shows the enduring significance of the heritage language for social, cultural and historical identity. It also demonstrates that the current survival of the “mother tongue” hinges on multilingual and multi-sited language activisms, which bear the hallmarks of both new creativities and diminishing fluencies in multilingual spaces. These multilingual repertoires also included a range of ideological stances, expressed as cultural, moral, and political attitudes to the “mother tongue” and to other, potentially more dominant, languages in their lives, involving both inclusive and exclusive instances. The Kabyles in the UK practice everyday forms of multilingualism in the dynamic terms whilst making strong identity claims to an endangered heritage language. Crucially, their language contact experiences were not a post-migration novelty but part of their pre-migration lifeworlds. The participants involved in this study shared a commitment to Kabyle identity activism. They expressed this differently, varyingly foregrounding cultural, social or political issues. These differences were related to their North-African cultural background, live, gender, religious and/or political affiliation, as well as to their different migratory trajectories. Among these ethno-conscious individuals, the use of Kabyle was often particularly vibrant in informal domains of casual conversations and mixed in with French, English and often Arabic. During community events and festivals, though, many made special efforts to converse in Kabyle as if to make a point about their commitment to a shared identity.

Keywords: ethnography, language ideology, language choice, heritage language, migration trajectories, multilingual repertoires

Procedia PDF Downloads 60

Authors: Analen Malnegro, Gina Malacas

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Dominating sets and related topics have been studied extensively in the past few decades. A dominating set of a graph G is a subset D of V such that every vertex not in D is adjacent to at least one member of D. The domination number γ(G) is the number of vertices in a smallest dominating set for G. Some problems involving detection devices can be modeled with graphs. Finding the minimum number of devices needed according to the type of devices and the necessity of locating the object gives rise to locating-dominating sets. A subset S of vertices of a graph G is called locating-dominating set, LD-set for short, if it is a dominating set and if every vertex v not in S is uniquely determined by the set of neighbors of v belonging to S. The location-domination number λ(G) is the minimum cardinality of an LD-set for G. The complement of a graph G is a graph Ḡ on same vertices such that two distinct vertices of Ḡ are adjacent if and only if they are not adjacent in G. An LD-set of a graph G is global if it is an LD-set of both G and its complement Ḡ. The global location-domination number λg(G) is defined as the minimum cardinality of a global LD-set of G. In this paper, global LD-sets on the join of two graphs are characterized. Global location-domination numbers of these graphs are also determined.

Keywords: dominating set, global locating-dominating set, global location-domination number, locating-dominating set, location-domination number

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Authors: Ambreen Amir Ali

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In todays’ dynamic environment, it has become very crucial to have comprehensive management trainee program to hire future leaders of organization. It is being proved that fresh graduates mostly join organizations because of its institution but later on they leave organization because of their immediate manager or supervisor. The concept of coaching and mentoring in talent management systems are very important, because mentors are those who can advise, facilitate, help and support new entrants to advance in their career. When it comes to going for talent hunt, one point needs to be highlighted that MTs are the raw talent for your organization, now it’s the responsibility of employers to nourish them, polish and developed them so that they can enthusiastically take care of senior leadership roles.

Keywords: management trainee, retention, leadership roles, coaching

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Authors: K. Jagannath, Akhilesh Kotian, S. S. Sharma, Achutha Kini U., P. R. Prabhu

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Boiling process is characterized by the rapid formation of vapour bubbles at the solid–liquid interface (nucleate boiling) with pre-existing vapour or gas pockets. Computational fluid dynamics (CFD) is an important tool to study bubble dynamics. In the present study, CFD simulation has been carried out to determine the bubble detachment diameter and its terminal velocity. Volume of fluid method is used to model the bubble and the surrounding by solving single set of momentum equations and tracking the volume fraction of each of the fluids throughout the domain. In the simulation, bubble is generated by allowing water-vapour to enter a cylinder filled with liquid water through an inlet at the bottom. After the bubble is fully formed, the bubble detaches from the surface and rises up during which the bubble accelerates due to the net balance between buoyancy force and viscous drag. Finally when these forces exactly balance each other, it attains a constant terminal velocity. The bubble detachment diameter and the terminal velocity of the bubble are captured by the monitor function provided in FLUENT. The detachment diameter and the terminal velocity obtained is compared with the established results based on the shape of the bubble. A good agreement is obtained between the results obtained from simulation and the equations in comparison with the established results.

Keywords: bubble growth, computational fluid dynamics, detachment diameter, terminal velocity

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Authors: Thochi Seb Rengma, Mahendra Kumar Gupta, P. M. V. Subbarao

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Hydrokinetic turbines can be used to produce power in inaccessible villages located near rivers. The hydrokinetic turbine uses the kinetic energy of the water and maybe put it directly into the natural flow of water without dams. For off-grid power production, the Savonius-type vertical axis turbine is the easiest to design and manufacture. This proposal uses three-dimensional computational fluid dynamics (CFD) simulations to measure the considerable interaction and complexity of turbine blades. Savonius hydrokinetic turbine (SHKT) performance is affected by a blockage in the river, canals, and waterways. Putting a large object in a water channel causes water obstruction and raises local free stream velocity. The blockage correction factor or velocity increment measures the impact of velocity on the performance. SHKT performance is evaluated by comparing power coefficient (Cp) with tip-speed ratio (TSR) at various blockage ratios. The maximum Cp was obtained at a TSR of 1.1 with a blockage ratio of 45%, whereas TSR of 0.8 yielded the highest Cp without blockage. The greatest Cp of 0.29 was obtained with a 45% blockage ratio compared to a Cp max of 0.18 without a blockage.

Keywords: savonius hydrokinetic turbine, blockage ratio, vertical axis turbine, power coefficient

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Authors: M. Yushalify Misro, Ahmad Ramli, Jamaludin M. Ali

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Bezier curves have useful properties for path generation problem, for instance, it can generate the reference trajectory for vehicles to satisfy the path constraints. Both algorithms join cubic Bezier curve segment smoothly to generate the path. Some of the useful properties of Bezier are curvature. In mathematics, the curvature is the amount by which a geometric object deviates from being flat, or straight in the case of a line. Another extrinsic example of curvature is a circle, where the curvature is equal to the reciprocal of its radius at any point on the circle. The smaller the radius, the higher the curvature thus the vehicle needs to bend sharply. In this study, we use Bezier curve to fit highway-like curve. We use the different approach to finding the best approximation for the curve so that it will resemble highway-like curve. We compute curvature value by analytical differentiation of the Bezier Curve. We will then compute the maximum speed for driving using the curvature information obtained. Our research works on some assumptions; first the Bezier curve estimates the real shape of the curve which can be verified visually. Even, though, the fitting process of Bezier curve does not interpolate exactly on the curve of interest, we believe that the estimation of speed is acceptable. We verified our result with the manual calculation of the curvature from the map.

Keywords: speed estimation, path constraints, reference trajectory, Bezier curve

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Authors: M. Goodarzi, M. Mohammadi, A. Gharib

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Solar energy is a renewable energy which has attracted special attention in many countries. Solar cathodic protectionsystems harness the sun’senergy to protect underground pipelinesand tanks from galvanic corrosion. The object of this study is to design and the economic analysis a cathodic protection system by impressed current supplied with solar energy panels applied to underground pipelines. In the present study, the technical and economic analysis of using solar energy for cathodic protection system in southwestern of Iran (Khuzestan province) is investigated. For this purpose, the ecological conditions such as the weather data, air clearness and sunshine hours are analyzed. The economic analyses were done using computer code to investigate the feasibility analysis from the using of various energy sources in order to cathodic protection system. The overall research methodology is divided into four components: Data collection, design of elements, techno economical evaluation, and output analysis. According to the results, solar renewable energy systems can supply adequate power for cathodic protection system purposes.

Keywords: renewable energy, solar energy, solar cathodic protection station, lifecycle cost method

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Authors: Gustavo Rodrigues, Hans Weber, Larissa Driemeier

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The prevision of post-impact conditions and the behavior of the bodies during the impact have been object of several collision models. The formulation from Hertz’s theory is generally used dated from the 19^th century. These models consider the repulsive force as proportional to the deformation of the bodies under contact and may consider it proportional to the rate of deformation. The objective of the present work is to analyze the behavior of the bodies during impact using the Finite Element Method (FEM) with elastic and plastic material models. The main parameters to evaluate are, the contact force, the time of contact and the deformation of the bodies. An advantage of using the FEM approach is the possibility to apply a plastic deformation to the model according to the material definition: there will be used Johnson–Cook plasticity model whose parameters are obtained through empirical tests of real materials. This model allows analyzing the permanent deformation caused by impact, phenomenon observed in real world depending on the forces applied to the body. These results are compared between them and with the model-based Hertz theory.

Keywords: collision, impact models, finite element method, Hertz Theory

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Authors: Nuseiba M. Altarawneh, Suhuai Luo, Brian Regan, Guijin Tang

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Liver segmentation from medical images poses more challenges than analogous segmentations of other organs. This contribution introduces a liver segmentation method from a series of computer tomography images. Overall, we present a novel method for segmenting liver by coupling density matching with shape priors. Density matching signifies a tracking method which operates via maximizing the Bhattacharyya similarity measure between the photometric distribution from an estimated image region and a model photometric distribution. Density matching controls the direction of the evolution process and slows down the evolving contour in regions with weak edges. The shape prior improves the robustness of density matching and discourages the evolving contour from exceeding liver’s boundaries at regions with weak boundaries. The model is implemented using a modified distance regularized level set (DRLS) model. The experimental results show that the method achieves a satisfactory result. By comparing with the original DRLS model, it is evident that the proposed model herein is more effective in addressing the over segmentation problem. Finally, we gauge our performance of our model against matrices comprising of accuracy, sensitivity and specificity.

Keywords: Bhattacharyya distance, distance regularized level set (DRLS) model, liver segmentation, level set method

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Authors: B. Ramesh Naik, T. Venugopal

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

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

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Authors: Percy Galvez, Anatoly Petukhin, Paul Somerville, Ken Miyakoshi, Kojiro Irikura, Daniel Peter

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Physics-based dynamic rupture modelling is necessary for estimating parameters such as rupture velocity and slip rate function that are important for ground motion simulation, but poorly resolved by observations, e.g. by seismic source inversion. In order to generate a large number of physically self-consistent rupture models, whose rupture process is consistent with the spatio-temporal heterogeneity of past earthquakes, we use multicycle simulations under the heterogeneous rate-and-state (RS) friction law for a 45deg dip-slip fault. We performed a parametrization study by fully dynamic rupture modeling, and then, a set of spontaneous source models was generated in a large magnitude range (Mw > 7.0). In order to validate rupture models, we compare the source scaling relations vs. seismic moment Mo for the modeled rupture area S, as well as average slip Dave and the slip asperity area Sa, with similar scaling relations from the source inversions. Ground motions were also computed from our models. Their peak ground velocities (PGV) agree well with the GMPE values. We obtained good agreement of the permanent surface offset values with empirical relations. From the heterogeneous rupture models, we analyzed parameters, which are critical for ground motion simulations, i.e. distributions of slip, slip rate, rupture initiation points, rupture velocities, and source time functions. We studied cross-correlations between them and with the friction weakening distance Dc value, the only initial heterogeneity parameter in our modeling. The main findings are: (1) high slip-rate areas coincide with or are located on an outer edge of the large slip areas, (2) ruptures have a tendency to initiate in small Dc areas, and (3) high slip-rate areas correlate with areas of small Dc, large rupture velocity and short rise-time.

Keywords: earthquake dynamics, strong ground motion prediction, seismic engineering, source characterization

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Authors: Tianyang Xu

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Small underwater targets generally have a non-centrosymmetric geometry, and the acoustic scattering field of the target has spatial inhomogeneity under active sonar detection conditions. In view of the above problems, this paper takes the hemispherical cylindrical shell as the research object, and considers the angle continuity implied in the echo characteristics, and proposes a cluster-driven research method for the non-uniform characteristics of target echo angle. First, the target echo features are extracted, and feature vectors are constructed. Secondly, the t-SNE algorithm is used to improve the internal connection of the feature vector in the low-dimensional feature space and to construct the visual feature space. Finally, the implicit angular relationship between echo features is extracted under unsupervised condition by cluster analysis. The reconstruction results of the local geometric structure of the target corresponding to different categories show that the method can effectively divide the angle interval of the local structure of the target according to the natural acoustic scattering characteristics of the target.

Keywords: underwater target;, non-uniform characteristics;, cluster-driven method;, acoustic scattering characteristics

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Authors: Mifta Ul Jannat, Raju Ahmed, Al Mamun, Jannatul Ferdaus, Ritu Costa, Milon Biswas

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Blockchain is an internet-based invention that is coveted in the permanent, scumbled record for its capacity to openly accept, record, and distribute transactions. In a traditional supply chain, there are no trustworthy participants for an organic product. Yet blockchain engineering may provide confidence, transparency, and traceability. Blockchain varies in how companies get real, checked, and lasting information from their supply chain and lock in customers. In an arrangement of cryptographic squares, Blockchain digitizes each connection by sparing it. No one person may alter the documents, and any alteration within the agreement is clear to all. The coming to the record is tamper proof and unchanging, offering a complete history of the object’s life cycle and minimizing opening for extorting. The primary aim of this analysis is to identify the underlying problem that the customer faces. In this post, we will minimize the allocation of fraud data through the ’Smart Contract’ and include a certificate of quality assurance.

Keywords: blockchain technology, food supply chain, Ethereum, smart contract, quality assurance, trustability, security, transparency

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Wedad Albalawi

Abstract:

The mathematical inequalities have been the core of mathematical study and used in almost all branches of mathematics as well in various areas of science and engineering. The inequalities by Hardy, Littlewood and Polya were the first significant composition of several science. This work presents fundamental ideas, results and techniques and it has had much influence on research in various branches of analysis. Since 1934, various inequalities have been produced and studied in the literature. Furthermore, some inequalities have been formulated by some operators; in 1989, weighted Hardy inequalities have been obtained for integration operators. Then, they obtained weighted estimates for Steklov operators that were used in the solution of the Cauchy problem for the wave equation. They were improved upon in 2011 to include the boundedness of integral operators from the weighted Sobolev space to the weighted Lebesgue space. Some inequalities have been demonstrated and improved using the Hardy–Steklov operator. Recently, a lot of integral inequalities have been improved by differential operators. Hardy inequality has been one of the tools that is used to consider integrity solutions of differential equations. Then dynamic inequalities of Hardy and Coposon have been extended and improved by various integral operators. These inequalities would be interesting to apply in different fields of mathematics (functional spaces, partial differential equations, mathematical modeling). Some inequalities have been appeared involving Copson and Hardy inequalities on time scales to obtain new special version of them. A time scale is defined as a closed subset contains real numbers. Then the inequalities of time scales version have received a lot of attention and has had a major field in both pure and applied mathematics. There are many applications of dynamic equations on time scales to quantum mechanics, electrical engineering, neural networks, heat transfer, combinatorics, and population dynamics. This study focuses on double integrals to obtain new time-scale inequalities of Copson driven by Steklov operator. They will be applied in the solution of the Cauchy problem for the wave equation. The proof can be done by introducing restriction on the operator in several cases. In addition, the obtained inequalities done by using some concepts in time scale version such as time scales calculus, theorem of Fubini and the inequality of H¨older.

Keywords: time scales, inequality of Hardy, inequality of Coposon, Steklov operator

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Authors: Rujijan Vichivanives, Kittiya Poonsilp, Canasanan Wanavijit

Abstract:

This research aims to create mobile tools to analyze rice disease quickly and easily. The principle of object-oriented software engineering and objective-C language were used for software development methodology and the principle of decision tree technique was used for analysis method. Application users can select the features of rice disease or the color appears on the rice leaves for recognition analysis results on iOS mobile screen. After completing the software development, unit testing and integrating testing method were used to check for program validity. In addition, three plant experts and forty farmers have been assessed for usability and benefit of this system. The overall of users’ satisfaction was found in a good level, 57%. The plant experts give a comment on the addition of various disease symptoms in the database for more precise results of the analysis. For further research, it is suggested that image processing system should be developed as a tool that allows users search and analyze for rice diseases more convenient with great accuracy.

Keywords: rice disease, data analysis system, mobile application, iOS operating system

Procedia PDF Downloads 273

Authors: A. Chellil, I. Gahlouz, S. Lecheb, A. Nour, S. Chellil, H. Mechakra, H. Kebir

Abstract:

In this paper, the experimental study for the instability of a separator rotor is presented, under dynamic loading response in the harmonic analysis condition. The analysis of the stress which operates the rotor is done. Calculations of different energies and the virtual work of the aerodynamic loads from the rotor are developed. Numerical calculations on the model develop of three dimensions prove that the defects effect has a negative effect on the stability of the rotor. Experimentally, the study of the rotor in the transient system allowed to determine the vibratory responses due to the unbalances and various excitations.

Keywords: rotor, frequency, finite element, specter

Procedia PDF Downloads 369

Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

Abstract:

The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: color moments, visual thing recognition system, SIFT, color SIFT

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Authors: Mohsen Tehranizadeh, Mahboobe Forghani

Abstract:

The impact of higher modes on the seismic response of dual structural system consist of concrete moment-resisting frame and with RC shear walls is investigated against near-field earthquakes in this paper. a 20 stories reinforced concrete shear wall-special moment frame structure is designed in accordance with ASCE7 requirements and The nonlinear model of the structure was performed on OpenSees platform. Nonlinear time history dynamic analysis with 3 near-field records are performed on them. In order to further understand the structural collapse behavior in the near field, the response of the structure at the moment of collapse especially the formation of plastic hinges is explored. The results revealed that the amplification of moment at top of the wall due to higher modes, the plastic hinge can form in the upper part of wall, even when designed and detailed for plastic hinging at the base only (according to ACI code).on the other hand, shear forces in excess of capacity design values can develop due to the contribution of the higher modes of vibration to dynamic response due to the near field can cause brittle shear or sliding failure modes. The past investigation on shear walls clearly shows the dual-hinge design concept is effective at reducing the effects of the second mode of response. An advantage of the concept is that, when combined with capacity design, it can result in relaxation of special reinforcing detailing in large portions of the wall. In this study, to investigate the implications of multi-design approach, 4 models with varies arrangement of hinge plastics at the base and height of the shear wall are considered. results base on time history analysis showed that the dual or multi plastic hinges approach can be useful in order to control the high moment and shear demand of higher mode effect.

Keywords: higher mode effect, Near-field earthquake, nonlinear time history analysis, multi plastic hinge design

Procedia PDF Downloads 413

Authors: Harper Staples

Abstract:

A necessary outcome of today’s contemporary globalised reality, current views of multilingualism hold that it no longer represents the exception, but rather the rule. As such, the simultaneous acquisition of multiple languages represents a common experience for many of today's students and therefore represents a key area of inquiry in the domain of foreign language learner identity. Second and multilingual language acquisition processes parallel each other in many ways; however, there are differences to be found in the ways in which a student may learn a third language. A multilingual repertoire will have to negotiate complex change as language competencies dynamically evolve; moreover, this process will vary according to the contextual factors attributed to a unique learner. A developing multilingual identity must, therefore, contend with an array of potential challenges specific to the individual in question. Despite an overarching recognition in the literature that pluri-language acquisition represents a unique field of inquiry within applied linguistic research, there is a paucity of empirical work which examines the ways in which individuals construct a sense of their own identity as multilingual speakers in such contexts of learning. This study explores this phenomenon via a mixed-methods, comparative case study approach at four school sites based in Finland, France, Wales, and England. It takes a strongly individual-in-context view, conceptualising each adolescent participant in dynamic terms in order to undertake a holistic exploration of the myriad factors that might impact upon, and indeed be impacted by, a learner's developing multilingual identity. Emerging themes of note thus far suggest that, beyond the expected divergences in the experience of multilinguality at the individual level, there are contradictions in the way in which adolescent students in each site 'claim' their plurilingualism. This can be argued to be linked to both meso and macro-level factors, including the foreign language curriculum and, more broadly, societal attitudes towards multilingualism. These diverse emergent identifications have implications not only for attainment in the foreign language but also for student well-being more generally.

Keywords: foreign language learning, student identity, multilingualism, educational psychology

Procedia PDF Downloads 161