Search results for: dynamic PET images

Authors: Mejía M. Paula, Ramírez L. Leonardo, Puerta A. Gabriel

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In telemedicine, the image repository service is important to increase the accuracy of diagnostic support of medical personnel. This study makes comparison between two routing algorithms regarding the quality of service (QoS), to be able to analyze the optimal performance at the time of loading and/or downloading of medical images. This study focused on comparing the performance of Tabu Search with other heuristic and metaheuristic algorithms that improve QoS in telemedicine services in Colombia. For this, Tabu Search and Simulated Annealing heuristic algorithms are chosen for their high usability in this type of applications; the QoS is measured taking into account the following metrics: Delay, Throughput, Jitter and Latency. In addition, routing tests were carried out on ten images in digital image and communication in medicine (DICOM) format of 40 MB. These tests were carried out for ten minutes with different traffic conditions, reaching a total of 25 tests, from a server of Universidad Militar Nueva Granada (UMNG) in Bogotá-Colombia to a remote user in Universidad de Santiago de Chile (USACH) - Chile. The results show that Tabu search presents a better QoS performance compared to Simulated Annealing, managing to optimize the routing of medical images, a basic requirement to offer diagnostic images services in telemedicine.

Keywords: medical image, QoS, simulated annealing, Tabu search, telemedicine

Procedia PDF Downloads 206

Authors: Vahid Bayrami Rad

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In recent years, the use of artificial intelligence techniques, tools, and methods in processing medical images and health-related applications has been highlighted and a lot of research has been done in this regard. For example, colonoscopy and diagnosis of colon lesions are some cases in which the process of diagnosis of lesions can be improved by using image processing and artificial intelligence algorithms, which help doctors a lot. Due to the lack of accurate measurements and the variety of injuries in colonoscopy images, the process of diagnosing the type of lesions is a little difficult even for expert doctors. Therefore, by using different software and image processing, doctors can be helped to increase the accuracy of their observations and ultimately improve their diagnosis. Also, by using automatic methods, the process of diagnosing the type of disease can be improved. Therefore, in this paper, a deep learning framework called KCBA is proposed to classify colonoscopy lesions which are composed of several methods such as K-means clustering, a bag of features and deep auto-encoder. Finally, according to the experimental results, the proposed method's performance in classifying colonoscopy images is depicted considering the accuracy criterion.

Keywords: colorectal cancer, colonoscopy, region of interest, narrow band imaging, texture analysis, bag of feature

Procedia PDF Downloads 40

Authors: Divvela Vishnu Sai Kumar, Deepak Arora, Sheenu Rizvi

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Forecasting a cyclone through satellite images consists of the estimation of the intensity of the cyclone and predicting it before a cyclone comes. This research work can help people to take safety measures before the cyclone comes. The prediction of the intensity of a cyclone is very important to save lives and minimize the damage caused by cyclones. These cyclones are very costliest natural disasters that cause a lot of damage globally due to a lot of hazards. Authors have proposed five different CNN (Convolutional Neural Network) models that estimate the intensity of cyclones through INSAT-3D IR images. There are a lot of techniques that are used to estimate the intensity; the best model proposed by authors estimates intensity with a root mean squared error (RMSE) of 10.02 kts.

Keywords: estimating cyclone intensity, deep learning, convolution neural network, prediction models

Procedia PDF Downloads 106

Authors: Bahlouli Ahmed, Bentalab Nourdin, Nigrou Mourad

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This study was aimed at investigating the effect of orientation fiber reinforced on dynamic properties of laminate composite FRP. An experimental investigation is implemented using an impulse technique. The various specimens are excited in free vibration by the use of bi-channel Analyzer. The experimental results are compared by model of finite element analysis using ANSYS. The results studies (natural frequencies measurements, vibration mode, dynamic modulus and damping ratio) show that the effects of significant parameters such as lay-up and stacking sequence, boundary conditions and excitation place of accelerometer. These results are critically examined and discussed. The accuracy of these results is demonstrated by comparing results with those available in the literature.

Keywords: natural frequency, damping ratio, laminate composite, dynamic modulus

Procedia PDF Downloads 338

Authors: Gong Kangming, Zhao Caiqi

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High-rise special-shaped structure, such as main frame structure of the statues, is one of the structure forms in irregular structure widely used. Due to the complex shape of the statue structure, with a large aspect ratio, its wind load value and the overall mechanical properties are very different from the high-rise buildings with the general rules. The paper taking a certain 48 meters high main frame structure of the statue located in Shuangyashan City, Heilongjiang Province, static and dynamic properties are analyzed by the finite element software. Through static and dynamic analysis, it got a number of useful conclusions that have a certain reference value for the analysis and design of the future similar structure.

Keywords: a Buddhism goddess Guanyin body, wind load, dynamic analysis, bolster, node design

Procedia PDF Downloads 455

Authors: Aydin Teymourifar, Gurkan Ozturk

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In this paper, a new hybrid Hopfield neural network is proposed for the dynamic, flexible job shop scheduling problem. A new heuristic based and easy to implement energy function is designed for the Hopfield neural network, which penalizes the constraints violation and decreases makespan. Moreover, for enhancing the performance, several heuristics are integrated to it that achieve active, and non-delay schedules also, prevent early convergence of the neural network. The suggested algorithm that is designed as a generalization of the previous studies for the flexible and dynamic scheduling problems can be used for solving real scheduling problems. Comparison of the presented hybrid method results with the previous studies results proves its efficiency.

Keywords: dynamic flexible job shop scheduling, neural network, heuristics, constrained optimization

Procedia PDF Downloads 405

Authors: Noppadon Sintuboon, Benjamas Sawatdipong, Anchalee Kongsuk

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This study was conducted to investigate the engineering parameters: compressional wave: Vp, shear wave: Vs, and density: ρ related to the dynamically geotechnical properties of soils compaction in the core of earth-filled dam located in northern part of Thailand by using multichannel analysis of surface wave (MASW) techniques. The Vp, Vs, and ρ from MASW were 1,624 - 1,649 m/s, 301-323 m/s, and 1,829 kg/m3, respectively. Those parameters were calculated to Poison’s ratio: ν (0.48), shear modulus: G (1.66 x 108 - 1.92 x 108 kg/m2), Vp/Vs ratio (5.10 – 5.39) and Standard Penetration Test (SPT) showing the dynamic characteristics of soil deformation and stress resulting from dynamic loads. The results of this study will be useful in primary evaluating the current condition and foundation of the dam and can be compared to the data from the laboratory in the future.

Keywords: earth-filled dam, MASW, dynamic elastic constant, shear wave

Procedia PDF Downloads 287

Authors: Parisa Mansour

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The coronavirus disease 2019 (COVID-19) was discovered and rapidly spread to various countries around the world since the end of 2019. Computed tomography (CT) images have been used as an important alternative to the time-consuming RT. PCR test. However, manual segmentation of CT images alone is a major challenge as the number of suspected cases increases. Thus, accurate and automatic segmentation of COVID-19 infections is urgently needed. Because the imaging features of the COVID-19 infection are different and similar to the background, existing medical image segmentation methods cannot achieve satisfactory performance. In this work, we try to build a deep convolutional neural network adapted for the segmentation of chest CT images with COVID-19 infections. First, we maintain a large and novel chest CT image database containing 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of an infected lung can be improved by global intensity adjustment, we introduce a feature variable block into the proposed deep CNN, which adjusts the global features of features to segment the COVID-19 infection. The proposed PV array can effectively and adaptively improve the performance of functions in different cases. We combine features of different scales by proposing a progressive atrocious space pyramid fusion scheme to deal with advanced infection regions with various aspects and shapes. We conducted experiments on data collected in China and Germany and showed that the proposed deep CNN can effectively produce impressive performance.

Keywords: chest, COVID-19, chest Image, coronavirus, CT image, chest CT

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Authors: Deniz Guven, Wil Ward, Jinming Duan, Li Bai

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Over the past two decades or so, Optical Coherence Tomography (OCT) has been used to diagnose retina and optic nerve diseases. The retinal nerve fibre layer, for example, is a powerful diagnostic marker for detecting and staging glaucoma. With the advances in optical imaging hardware, the adoption of OCT is now commonplace in clinics. More and more OCT images are being generated, and for these OCT images to have clinical applicability, accurate automated OCT image segmentation software is needed. Oct image segmentation is still an active research area, as OCT images are inherently noisy, with the multiplicative speckling noise. Simple edge detection algorithms are unsuitable for detecting retinal layer boundaries in OCT images. Intensity fluctuation, motion artefact, and the presence of blood vessels also decrease further OCT image quality. In this paper, we introduce a new method for segmenting three-dimensional (3D) OCT images. This involves the use of a Kalman filter, which is commonly used in computer vision for object tracking. The Kalman filter is applied to the 3D OCT image volume to track the retinal layer boundaries through the slices within the volume and thus segmenting the 3D image. Specifically, after some pre-processing of the OCT images, points on the retinal layer boundaries in the first image are identified, and curve fitting is applied to them such that the layer boundaries can be represented by the coefficients of the curve equations. These coefficients then form the state space for the Kalman Filter. The filter then produces an optimal estimate of the current state of the system by updating its previous state using the measurements available in the form of a feedback control loop. The results show that the algorithm can be used to segment the retinal layers in OCT images. One of the limitations of the current algorithm is that the curve representation of the retinal layer boundary does not work well when the layer boundary is split into two, e.g., at the optic nerve, the layer boundary split into two. This maybe resolved by using a different approach to representing the boundaries, such as b-splines or level sets. The use of a Kalman filter shows promise to developing accurate and effective 3D OCT segmentation methods.

Keywords: optical coherence tomography, image segmentation, Kalman filter, object tracking

Procedia PDF Downloads 471

Authors: M. K. Benhaoua, A. K. Singh, A. E. H. Benyamina

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In this paper, we propose heuristic for dynamic communications mapping that considers the placement of communications in order to optimize the overall performance. The mapping technique uses a newly proposed Algorithm to place communications between the tasks. The placement we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed mapping approach provides significant performance improvements when compared to those using static routing.

Keywords: Multi-Processor Systems-on-Chip (MPSoCs), Network-on-Chip (NoC), heterogeneous architectures, dynamic mapping heuristics

Procedia PDF Downloads 519

Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

Procedia PDF Downloads 368

Authors: Kwazikwenkosi Sikhakhane, Suvendi Rimer, Mpho Gololo, Khmaies Oahada, Adnan Abu-Mahfouz

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Medical ultrasound imaging is a crucial diagnostic technique due to its affordability and non-invasiveness compared to other imaging methods. However, the presence of speckle noise, which is a form of multiplicative noise, poses a significant obstacle to obtaining clear and accurate images in ultrasound imaging. Speckle noise reduces image quality by decreasing contrast, resolution, and signal-to-noise ratio (SNR). This makes it difficult for medical professionals to interpret ultrasound images accurately. To address this issue, various techniques have been developed to reduce speckle noise in ultrasound images, which improves image quality. This paper aims to review some of these techniques, highlighting the advantages and disadvantages of each algorithm and identifying the scenarios in which they work most effectively.

Keywords: image processing, noise, speckle, ultrasound

Procedia PDF Downloads 90

Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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Authors: Nada Farhani, Naim Terbeh, Mounir Zrigui

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The recognition of the objects contained in images has always presented a challenge in the field of research because of several difficulties that the researcher can envisage because of the variability of shape, position, contrast of objects, etc. In this paper, we will be interested in the recognition of objects. The classical Hough Transform (HT) presented a tool for detecting straight line segments in images. The technique of HT has been generalized (GHT) for the detection of arbitrary forms. With GHT, the forms sought are not necessarily defined analytically but rather by a particular silhouette. For more precision, we proposed to combine the results from the GHT with the results from a calculation of similarity between the histograms and the spatiograms of the images. The main purpose of our work is to use the concepts from recognition to generate sentences in Arabic that summarize the content of the image.

Keywords: recognition of shape, generalized hough transformation, histogram, spatiogram, learning

Procedia PDF Downloads 144

Authors: Fairouz Fakhfakh, Hatem Hadj Kacem, Ahmed Hadj Kacem

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Cloud computing offers a new model of service provisioning for workflow applications, thanks to its elasticity and its paying model. However, it presents various challenges that need to be addressed in order to be efficiently utilized. The resources provisioning problem for workflow applications has been widely studied. Nevertheless, the existing works did not consider the change in workflow instances while they are being executed. This functionality has become a major requirement to deal with unusual situations and evolution. This paper presents a first step towards the resources provisioning for a dynamic workflow. In fact, we propose a provisioning algorithm which minimizes the overall workflow execution cost, while meeting a deadline constraint. Then, we extend it to support the dynamic adding of tasks. Experimental results show that our proposed heuristic demonstrates a significant reduction in resources cost by using a consolidation process.

Keywords: cloud computing, resources provisioning, dynamic workflow, workflow applications

Procedia PDF Downloads 273

Authors: David P. Tantua, Abdulkader Helwan

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Biometrics has been recently used for the human identification systems using the biological traits such as the fingerprints and iris scanning. Identification systems based biometrics show great efficiency and accuracy in such human identification applications. However, these types of systems are so far based on some image processing techniques only, which may decrease the efficiency of such applications. Thus, this paper aims to develop a human palmprint identification system using multi-layer perceptron neural network which has the capability to learn using a backpropagation learning algorithms. The developed system uses images obtained from a public database available on the internet (CASIA). The processing system is as follows: image filtering using median filter, image adjustment, image skeletonizing, edge detection using canny operator to extract features, clear unwanted components of the image. The second phase is to feed those processed images into a neural network classifier which will adaptively learn and create a class for each different image. 100 different images are used for training the system. Since this is an identification system, it should be tested with the same images. Therefore, the same 100 images are used for testing it, and any image out of the training set should be unrecognized. The experimental results shows that this developed system has a great accuracy 100% and it can be implemented in real life applications.

Keywords: biometrics, biological traits, multi-layer perceptron neural network, image skeletonizing, edge detection using canny operator

Procedia PDF Downloads 360

Authors: Yalçın Bozkurt

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Prediction models were developed for accurate prediction of bodyweight (BW) by using Digital Images of beef cattle body dimensions by Artificial Neural Networks (ANN). For this purpose, the animal data were collected at a private slaughter house and the digital images and the weights of each live animal were taken just before they were slaughtered and the body dimensions such as digital wither height (DJWH), digital body length (DJBL), digital body depth (DJBD), digital hip width (DJHW), digital hip height (DJHH) and digital pin bone length (DJPL) were determined from the images, using the data with 1069 observations for each traits. Then, prediction models were developed by ANN. Digital body measurements were analysed by ANN for body prediction and R2 values of DJBL, DJWH, DJHW, DJBD, DJHH and DJPL were approximately 94.32, 91.31, 80.70, 83.61, 89.45 and 70.56 % respectively. It can be concluded that in management situations where BW cannot be measured it can be predicted accurately by measuring DJBL and DJWH alone or both DJBD and even DJHH and different models may be needed to predict BW in different feeding and environmental conditions and breeds

Keywords: artificial neural networks, bodyweight, cattle, digital body measurements

Procedia PDF Downloads 355

Authors: González A. Julio, Ramírez L. Leonardo, Puerta A. Gabriel

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Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.

Keywords: cloud storage, decision trees, diagnostic image, search, telemedicine

Procedia PDF Downloads 193

Authors: B. Chetti, W. A. Crosby

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This paper presents a numerical analysis for the dynamic performance of a finite journal bearing lubricated with couple stress fluid taking into account the effect of the deformation of the bearing liner. The modified Reynolds equation has been solved by using finite difference technique. The dynamic characteristics in terms of stiffness coefficients, damping coefficients, critical mass and whirl ratio are evaluated for different values of eccentricity ratio and elastic coefficient for a journal bearing lubricated with a couple stress fluids and a Newtonian fluid. The results show that the dynamic characteristics of journal bearings lubricated with couple stress fluids are improved compared to journal bearings lubricated with Newtonian fluids.

Keywords: journal bearing, elastohydrodynamic, stability, couple stress

Procedia PDF Downloads 355

Authors: Mohammad Derakhshani, Saeed Reza Allahkaram, Michael Isakani-Zakaria, Masoud Samadian, Hojat Sharifi Rasaey

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Dynamic stray currents tend to change their magnitude and polarity with time at their source which will create anodic and cathodic spots on a nearby interfered structure. To date, one of the biggest known dynamic stray current sources are DC traction systems. Laboratory simulation is a suitable method to apply theoretical principles in order to identify effective parameters in dynamic stray current influenced corrosion. Simulation techniques can be utilized for various mitigation methods applied in a small scales for selection of the most efficient method with regards to field applications. In this research, laboratory simulation of potential fluctuations caused by dynamic stray current on a cathodically protected structure was investigated. A lab model capable of generating DC static and dynamic stray currents and simulating its effects on cathodically protected samples were developed based on stray current induced (contact-less) polarization technique. Stray current pick-up and discharge spots on an influenced structure were simulated by inducing fluctuations in the sample’s stationary potential. Two mitigation methods for dynamic stray current interference on buried structures namely application of sacrificial anodes as preferred discharge point for the stray current and potentially controlled cathodic protection was investigated. Results showed that the application of sacrificial anodes can be effective in reducing interference only in discharge spot. But cathodic protection through potential controlling is more suitable for mitigating dynamic stray current effects.

Keywords: simulation, dynamic stray current, fluctuating potentials, sacrificial anode

Procedia PDF Downloads 285

Authors: Ferhat Kadioglu

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A clamped-free vibrating beam technique was used to evaluate dynamic properties of glass fiber reinforced polymer matrix composite. In the experiment, an electromagnetic shaker and a non-contact laser head were used to vibrate and to take the response of the specimens, respectively. Test results showed that damping and elastic modulus of the material, as dynamic properties, could be obtained successfully using this technique. It was found that the balanced and symmetric specimens with 45 degrees are the best for damping performance. It is believed that such results could be used for the modal design of aerospace structures.

Keywords: composite materials, damping values, dynamic properties, non-contact measurements

Procedia PDF Downloads 335

Authors: William Whiteley, Jens Gregor

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In recent developments of direct neural network based positron emission tomography (PET) reconstruction, two prominent architectures have emerged for converting measurement data into images: 1) networks that contain fully-connected layers; and 2) networks that primarily use a convolutional encoder-decoder architecture. In this paper, we present a multi-modal direct PET reconstruction method called MDPET, which is a hybrid approach that combines the advantages of both types of networks. MDPET processes raw data in the form of sinograms and histo-images in concert with attenuation maps to produce high quality multi-slice PET images (e.g., 8x440x440). MDPET is trained on a large whole-body patient data set and evaluated both quantitatively and qualitatively against target images reconstructed with the standard PET reconstruction benchmark of iterative ordered subsets expectation maximization. The results show that MDPET outperforms the best previously published direct neural network methods in measures of bias, signal-to-noise ratio, mean absolute error, and structural similarity.

Keywords: deep learning, image reconstruction, machine learning, neural network, positron emission tomography

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Authors: Bandar Alahmadi

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The fact that people tend to remember pictures better than texts, motivates researchers to develop graphical passwords as an alternative to textual passwords. Graphical passwords as such were introduced as a possible alternative to traditional text passwords, in which users prove their identity by clicking on pictures rather than typing alphanumerical text. In this paper, we present a scheme for graphical passwords that are resistant to shoulder surfing attacks and spyware attacks. The proposed scheme introduces a clicking technique to chosen images. First, the users choose a set of images, the images are then included in a grid where users can click in the cells around each image, the location of the click and the number of clicks are saved. As a result, the proposed scheme can be safe from shoulder surface and spyware attacks.

Keywords: security, password, authentication, attack, applications

Procedia PDF Downloads 153

Authors: Dor Oppenheim, Yael Edan, Guy Shani

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This paper presents an image analysis algorithm to detect and count yellow tomato flowers in a greenhouse with uneven illumination conditions, complex growth conditions and different flower sizes. The algorithm is designed to be employed on a drone that flies in greenhouses to accomplish several tasks such as pollination and yield estimation. Detecting the flowers can provide useful information for the farmer, such as the number of flowers in a row, and the number of flowers that were pollinated since the last visit to the row. The developed algorithm is designed to handle the real world difficulties in a greenhouse which include varying lighting conditions, shadowing, and occlusion, while considering the computational limitations of the simple processor in the drone. The algorithm identifies flowers using an adaptive global threshold, segmentation over the HSV color space, and morphological cues. The adaptive threshold divides the images into darker and lighter images. Then, segmentation on the hue, saturation and volume is performed accordingly, and classification is done according to size and location of the flowers. 1069 images of greenhouse tomato flowers were acquired in a commercial greenhouse in Israel, using two different RGB Cameras – an LG G4 smartphone and a Canon PowerShot A590. The images were acquired from multiple angles and distances and were sampled manually at various periods along the day to obtain varying lighting conditions. Ground truth was created by manually tagging approximately 25,000 individual flowers in the images. Sensitivity analyses on the acquisition angle of the images, periods throughout the day, different cameras and thresholding types were performed. Precision, recall and their derived F1 score were calculated. Results indicate better performance for the view angle facing the flowers than any other angle. Acquiring images in the afternoon resulted with the best precision and recall results. Applying a global adaptive threshold improved the median F1 score by 3%. Results showed no difference between the two cameras used. Using hue values of 0.12-0.18 in the segmentation process provided the best results in precision and recall, and the best F1 score. The precision and recall average for all the images when using these values was 74% and 75% respectively with an F1 score of 0.73. Further analysis showed a 5% increase in precision and recall when analyzing images acquired in the afternoon and from the front viewpoint.

Keywords: agricultural engineering, image processing, computer vision, flower detection

Procedia PDF Downloads 312

Authors: Nor Mazlin Zahari, Lian Gan, Xuerui Mao

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The power production in wind farms and the mechanical loads on the turbines are strongly impacted by the wake of the wind turbine. Thus, there is a need for understanding and modelling the turbine wake dynamic in the wind farm and the layout optimization. Having a good wake model is important in predicting plant performance and understanding fatigue loads. In this paper, the Dynamic Mode Decomposition (DMD) was applied to the simulation data generated by a Direct Numerical Simulation (DNS) of flow around a turbine, perturbed by upstream inflow noise. This technique is useful in analyzing the wake flow, to predict its future states and to reflect flow dynamics associated with the coherent structures behind wind turbine wake flow. DMD was employed to describe the dynamic of the flow around turbine from the DNS data. Since the DNS data comes with the unstructured meshes and non-uniform grid, the interpolation of each occurring within each element in the data to obtain an evenly spaced mesh was performed before the DMD was applied. DMD analyses were able to tell us characteristics of the travelling waves behind the turbine, e.g. the dominant helical flow structures and the corresponding frequencies. As the result, the dominant frequency will be detected, and the associated spatial structure will be identified. The dynamic mode which represented the coherent structure will be presented.

Keywords: coherent structure, Direct Numerical Simulation (DNS), dominant frequency, Dynamic Mode Decomposition (DMD)

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Authors: Beciri Mohamed Walid

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Some architectural conditions required some shapes often lead to an irregular distribution of masses, rigidities and resistances. The main object of the present study consists in estimating the influence of the irregularity both in plan and in elevation which presenting some structures on the dynamic characteristics and his influence on the behavior of this structures. To do this, it is necessary to make apply both dynamic methods proposed by the RPA99 (spectral modal method and method of analysis by accelerogram) on certain similar prototypes and to analyze the parameters measuring the answer of these structures and to proceed to a comparison of the results.

Keywords: structure, irregular, code, seismic, method, force, period

Procedia PDF Downloads 300

Authors: Yousif Mohamed Y. Abdallah, Eltayeb Wagallah

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Image enhancement allows the observer to see details in images that may not be immediately observable in the original image. Image enhancement is the transformation or mapping of one image to another. The enhancement of certain features in images is accompanied by undesirable effects. To achieve maximum image quality after denoising, a new, low order, local adaptive Gaussian scale mixture model and median filter were presented, which accomplishes nonlinearities from scattering a new nonlinear approach for contrast enhancement of bones in bone scan images using both gamma correction and negative transform methods. The usual assumption of a distribution of gamma and Poisson statistics only lead to overestimation of the noise variance in regions of low intensity but to underestimation in regions of high intensity and therefore to non-optional results. The contrast enhancement results were obtained and evaluated using MatLab program in nuclear medicine images of the bones. The optimal number of bins, in particular the number of gray-levels, is chosen automatically using entropy and average distance between the histogram of the original gray-level distribution and the contrast enhancement function’s curve.

Keywords: bone scan, nuclear medicine, Matlab, image processing technique

Procedia PDF Downloads 493

Authors: Jhe-Hao Huang, Kun-Da Wu, Wei-Cheng Shih, Jui-Pin Hung

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This study presented the investigation on the dynamic characteristics of a spindle tool system by experimental and finite element modeling approaches. As well known facts, the machining stability is greatly determined by the dynamic characteristics of the spindle tool system. Therefore, understanding the factors affecting dynamic behavior of a spindle tooling system is a prerequisite in dominating the final machining performance of machine tool system. To this purpose, a physical spindle unit was employed to assess the dynamic characteristics by vibration tests. Then, a three-dimensional finite element model of a high-speed spindle system integrated with tool holder was created to simulate the dynamic behaviors. For modeling the angular contact bearings, a series of spring elements were introduced between the inner and outer rings. The spring constant can be represented by the contact stiffness of the rolling bearing based on Hertz theory. The interface characteristic between spindle nose and tool holder taper can be quantified from the comparison of the measurements and predictions. According to the results obtained from experiments and finite element predictions, the vibration behavior of the spindle is dominated by the bending deformation of the spindle shaft in different modes, which is further determined by the stiffness of the bearings in spindle housing. Also, the spindle unit with tool holder shows a different dynamic behavior from that of spindle without tool holder. This indicates the interface property between tool holder and spindle nose plays an dominance on the dynamic characteristics the spindle tool system. Overall, the dynamic behaviors the spindle with and without tool holder can be successfully investigated through the finite element model proposed in this study. The prediction accuracy is determined by the modeling of the rolling interface of ball bearings in spindles and the interface characteristics between tool holder and spindle nose. Besides, identifications of the interface characteristics of a ball bearing and spindle tool holder are important for the refinement of the spindle tooling system to achieve the optimum machining performance.

Keywords: contact stiffness, dynamic characteristics, spindle, tool holder interface

Procedia PDF Downloads 286

Authors: Masao Nakagawa, Toshiki Hirogaki, Eiichi Aoyama, Mohamed Ali Ben Abbes

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A planetary gear set is widely used in hybrid vehicles as the power distribution system or in electric vehicles as the high reduction system, but due to its complexity with planet gears, its dynamic characteristic is not fully understood. There are many reports on two-axes driving or displacement of the planet gears under these conditions, but only few reports deal with three-axes driving. A three-axes driving condition is tested using three-axes torque measurement and focuses on the dynamic characteristic around the planet gears in this report. From experimental result, it was confirmed that the transition forces around the planet gears were balanced and the torques were also balanced around the instantaneous rotation center. The meshing frequency under these conditions was revealed to be the harmonics of two meshing frequencies; meshing frequency of the ring gear and that of the planet gears. The input power of the ring gear is distributed to the carrier and the sun gear in the dynamic sequential change of three fixed conditions; planet, star and solar modes.

Keywords: dynamic characteristic, gear, planetary gear set, torque measuring

Procedia PDF Downloads 369

Authors: Recep Gundogan, Turgay Dindaroglu, Hikmet Gunal, Mustafa Ulukavak, Ron Bingner

Abstract:

A majority of total soil losses in agricultural areas could be attributed to ephemeral gullies caused by heavy rains in conventionally tilled fields; however, ephemeral gully erosion is often ignored in conventional soil erosion assessments. Ephemeral gullies are often easily filled from normal soil tillage operations, which makes capturing the existing ephemeral gullies in croplands difficult. This study was carried out to determine topographic features, including slope and aspect composite topographic index (CTI) and initiation points of gully channels, using images obtained from unmanned aerial vehicle (UAV) images. The study area was located in Topcu stream watershed in the eastern Mediterranean Region, where intense rainfall events occur over very short time periods. The slope varied between 0.7 and 99.5%, and the average slope was 24.7%. The UAV (multi-propeller hexacopter) was used as the carrier platform, and images were obtained with the RGB camera mounted on the UAV. The digital terrain models (DTM) of Topçu stream micro catchment produced using UAV images and manual field Global Positioning System (GPS) measurements were compared to assess the accuracy of UAV based measurements. Eighty-one gully channels were detected in the study area. The mean slope and CTI values in the micro-catchment obtained from DTMs generated using UAV images were 19.2% and 3.64, respectively, and both slope and CTI values were lower than those obtained using GPS measurements. The total length and volume of the gully channels were 868.2 m and 5.52 m³, respectively. Topographic characteristics and information on ephemeral gully channels (location of initial point, volume, and length) were estimated with high accuracy using the UAV images. The results reveal that UAV-based measuring techniques can be used in lieu of existing GPS and total station techniques by using images obtained with high-resolution UAVs.

Keywords: aspect, compound topographic index, digital terrain model, initial gully point, slope, unmanned aerial vehicle

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