Search results for: Partially perfect object

Authors: Delowar Hossain, Genci Capi

Abstract:

This paper concerns with the problem of deep learning parameters tuning using a genetic algorithm (GA) in order to improve the performance of deep learning (DL) method. We present a GA based DL method for robot object recognition and grasping. GA is used to optimize the DL parameters in learning procedure in term of the fitness function that is good enough. After finishing the evolution process, we receive the optimal number of DL parameters. To evaluate the performance of our method, we consider the object recognition and robot grasping tasks. Experimental results show that our method is efficient for robot object recognition and grasping.

Keywords: Deep learning, genetic algorithm, object recognition, robot grasping.

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Authors: Elmi Abu Bakar, Tetsuo Miyake, Zhong Zhang, Takashi Imamura

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Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.

Keywords: CAD, rendering, feature extraction, feature classification.

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Authors: George Karkavitsas, Maria Rangoussi

Abstract:

We present a genetic algorithm application to the problem of object registration (i.e., object detection, localization and recognition) in a class of medical images containing various types of blood cells. The genetic algorithm approach taken here is seen to be most appropriate for this type of image, due to the characteristics of the objects. Successful cell registration results on real life microscope images of blood cells show the potential of the proposed approach.

Keywords: Genetic algorithms, object registration, pattern recognition, blood cell microscope images.

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Authors: Ismat Beg, Asma Rashid Butt

Abstract:

Let (X,) be a partially ordered set and d be a metric on X such that (X, d) is a complete metric space. Assume that X satisfies; if a non-decreasing sequence xn → x in X, then xn  x, for all n. Let F be a set valued mapping from X into X with nonempty closed bounded values satisfying; (i) there exists κ ∈ (0, 1) with D(F(x), F(y)) ≤ κd(x, y), for all x  y, (ii) if d(x, y) < ε < 1 for some y ∈ F(x) then x  y, (iii) there exists x0 ∈ X, and some x1 ∈ F(x0) with x0  x1 such that d(x0, x1) < 1. It is shown that F has a fixed point. Several consequences are also obtained.

Keywords: Fixed point, partially ordered set, metric space, set valued mapping.

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Authors: Mussarat Abdullah, Fazal Wahab

Abstract:

Data hiding into text documents itself involves pretty complexities due to the nature of text documents. A robust text watermarking scheme targeting an object based environment is presented in this research. The heart of the proposed solution describes the concept of watermarking an object based text document where each and every text string is entertained as a separate object having its own set of properties. Taking advantage of the z-ordering of objects watermark is applied with the z-axis letting zero fidelity disturbances to the text. Watermark sequence of bits generated against user key is hashed with selected properties of given document, to determine the bit sequence to embed. Bits are embedded along z-axis and the document has no fidelity issues when printed, scanned or photocopied.

Keywords: Digital Watermarking, Object Based Environment, Watermark, z-ordering.

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Authors: M A Hannan, A. Hussain, S. A. Samad, K. A. Ishak, A. Mohamed

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This paper presents a general trainable framework for fast and robust upright human face and non-human object detection and verification in static images. To enhance the performance of the detection process, the technique we develop is based on the combination of fast neural network (FNN) and classical neural network (CNN). In FNN, a useful correlation is exploited to sustain high level of detection accuracy between input image and the weight of the hidden neurons. This is to enable the use of Fourier transform that significantly speed up the time detection. The combination of CNN is responsible to verify the face region. A bootstrap algorithm is used to collect non human object, which adds the false detection to the training process of the human and non-human object. Experimental results on test images with both simple and complex background demonstrate that the proposed method has obtained high detection rate and low false positive rate in detecting both human face and non-human object.

Keywords: Algorithm, detection of human and non-human object, FNN, CNN, Image training.

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Authors: Miika Toivanen, Jouko Lampinen

Abstract:

This paper presents an online method that learns the corresponding points of an object from un-annotated grayscale images containing instances of the object. In the first image being processed, an ensemble of node points is automatically selected which is matched in the subsequent images. A Bayesian posterior distribution for the locations of the nodes in the images is formed. The likelihood is formed from Gabor responses and the prior assumes the mean shape of the node ensemble to be similar in a translation and scale free space. An association model is applied for separating the object nodes and background nodes. The posterior distribution is sampled with Sequential Monte Carlo method. The matched object nodes are inferred to be the corresponding points of the object instances. The results show that our system matches the object nodes as accurately as other methods that train the model with annotated training images.

Keywords: Bayesian modeling, Gabor filters, Online learning, Sequential Monte Carlo.

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Authors: J. Fernandez de Canete

Abstract:

Object-oriented modeling is spreading in current simulation of physiological systems through the use of the individual components of the model and its interconnections to define the underlying dynamic equations. In this paper we describe the use of both the SIMSCAPE and MODELICA simulation environments in the object-oriented modeling of the closed loop cardiovascular system. The performance of the controlled system was analyzed by simulation in light of the existing hypothesis and validation tests previously performed with physiological data. The described approach represents a valuable tool in the teaching of physiology for graduate medical students.

Keywords: Object-Oriented Modeling, SIMSCAPE Simulation Language, MODELICA Simulation Language, Cardiovascular System.

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Authors: Amel Grissa-Touzi, Habib Ounally, Aissa Boulila

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The utility of expert system generators has been widely recognized in many applications. Several generators based on concept of the paradigm object, have been recently proposed. The generator of oriented object expert system (GSEOO) offers languages that are often complex and difficult to use. We propose in this paper an extension of the expert system generator, JESS, which permits a friendly use of this expert system. The new tool, called VISUAL JESS, bring two main improvements to JESS. The first improvement concerns the easiness of its utilization while giving back transparency to the syntax and semantic aspects of the JESS programming language. The second improvement permits an easy access and modification of the JESS knowledge basis. The implementation of VISUAL JESS is made so that it is extensible and portable.

Keywords: Generator of Systems Expert, Programming oriented object classifies, object, inheritance, polymorphism.

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Authors: Sachin Kumar, Y. K. Gupta, J. R. Sharma

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In the present article, a new class of solutions of Einstein field equations is investigated for a spherically symmetric space-time when the source of gravitation is a perfect fluid. All the solutions have been derived by making some suitable arrangements in the field equations. The solutions so obtained have been seen to describe Schwarzschild interior solutions. Most of the solutions are subjected to the reality conditions. As far as the authors are aware the solutions are new.

Keywords: Einstein's equations, General Relativity, PerfectFluid, Spherical symmetric.

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Authors: Marina Velikova, Hennie Daniels, Ad Feelders

Abstract:

In many data mining applications, it is a priori known that the target function should satisfy certain constraints imposed by, for example, economic theory or a human-decision maker. In this paper we consider partially monotone prediction problems, where the target variable depends monotonically on some of the input variables but not on all. We propose a novel method to construct prediction models, where monotone dependences with respect to some of the input variables are preserved by virtue of construction. Our method belongs to the class of mixture models. The basic idea is to convolute monotone neural networks with weight (kernel) functions to make predictions. By using simulation and real case studies, we demonstrate the application of our method. To obtain sound assessment for the performance of our approach, we use standard neural networks with weight decay and partially monotone linear models as benchmark methods for comparison. The results show that our approach outperforms partially monotone linear models in terms of accuracy. Furthermore, the incorporation of partial monotonicity constraints not only leads to models that are in accordance with the decision maker's expertise, but also reduces considerably the model variance in comparison to standard neural networks with weight decay.

Keywords: mixture models, monotone neural networks, partially monotone models, partially monotone problems.

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Authors: A. Kumar, G. K. Singh, R. S. Anand

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In this paper, various algorithms for designing quadrature mirror filter are reviewed and a new algorithm is presented for the design of near perfect reconstruction quadrature mirror filter bank. In the proposed algorithm, objective function is formulated using the perfect reconstruction condition or magnitude response condition of prototype filter at frequency (ω = 0.5π) in ideal condition. The cutoff frequency is iteratively changed to adjust the filters coefficients using optimization algorithm. The performances of the proposed algorithm are evaluated in term of computation time, reconstruction error and number of iterations. The design examples illustrate that the proposed algorithm is superior in term of peak reconstruction error, computation time, and number of iterations. The proposed algorithm is simple, easy to implement, and linear in nature.

Keywords: Aliasing cancellations filter bank, Filter banks, quadrature mirror filter (QMF), subband coding.

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Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

Abstract:

With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: Service Robot, Object Recognition, 3D Sensors, Plane Segmentation.

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Authors: Haibo Hu, Hong Xiang

Abstract:

Due to its special data structure and manipulative principle, Object-Oriented Database (OODB) has a particular security protection and authorization methods. This paper first introduces the features of security mechanism about OODB, and then talked about authorization checking process of OODB. Implicit authorization mechanism is based on the subject hierarchies, object hierarchies and access hierarchies of the security authorization modes, and simplifies the authorization mode. In addition, to combine with other authorization mechanisms, implicit authorization can make protection on the authorization of OODB expediently and effectively.

Keywords: Object-oriented database(OODB), security protection, authorization mechanism, implicit authorization, authorization check.

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Authors: J. Fernandez de Canete, S. Fernandez-Calvo, I. García-Moral

Abstract:

This paper presents and discusses the application of the object-oriented modelling software SIMSCAPE to hydraulic systems, with particular reference to multivariable proportional-integral-derivative (PID) control. As a result, a particular modelling approach of a double cylinder-piston coupled system is proposed and motivated, and the SIMULINK based PID tuning tool has also been used to select the proper controller parameters. The paper demonstrates the usefulness of the object-oriented approach when both physical modelling and control are tackled.

Keywords: Object-oriented modeling, multivariable hydraulic system, multivariable PID control, computer simulation.

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Authors: Waralak Vongdoiwang Siricharoen

Abstract:

One of object oriented software developing problem is the difficulty of searching the appropriate and suitable objects for starting the system. In this work, ontologies appear in the part of supporting the object discovering in the initial of object oriented software developing. There are many researches try to demonstrate that there is a great potential between object model and ontologies. Constructing ontology from object model is called ontology engineering can be done; On the other hand, this research is aiming to support the idea of building object model from ontology is also promising and practical. Ontology classes are available online in any specific areas, which can be searched by semantic search engine. There are also many helping tools to do so; one of them which are used in this research is Protégé ontology editor and Visual Paradigm. To put them together give a great outcome. This research will be shown how it works efficiently with the real case study by using ontology classes in travel/tourism domain area. It needs to combine classes, properties, and relationships from more than two ontologies in order to generate the object model. In this paper presents a simple methodology framework which explains the process of discovering objects. The results show that this framework has great value while there is possible for expansion. Reusing of existing ontologies offers a much cheaper alternative than building new ones from scratch. More ontologies are becoming available on the web, and online ontologies libraries for storing and indexing ontologies are increasing in number and demand. Semantic and Ontologies search engines have also started to appear, to facilitate search and retrieval of online ontologies.

Keywords: Software Developing, Ontology, Ontology Library, Artificial Intelligent, Protégé, Object Model.

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Authors: H. T. Barney, G. C. Low

Abstract:

The design of distributed systems involves the partitioning of the system into components or partitions and the allocation of these components to physical nodes. Techniques have been proposed for both the partitioning and allocation process. However these techniques suffer from a number of limitations. For instance object replication has the potential to greatly improve the performance of an object orientated distributed system but can be difficult to use effectively and there are few techniques that support the developer in harnessing object replication. This paper presents a methodological technique that helps developers decide how objects should be allocated in order to improve performance in a distributed system that supports replication. The performance of the proposed technique is demonstrated and tested on an example system.

Keywords: Allocation, Distributed Systems, Replication.

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Authors: Won-Ho Kim, Nuwan Sanjeewa Rajasooriya

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In this paper, a simple moving human detection method is proposed for video surveillance system or access monitoring system. The frame difference and noise threshold are used for initial detection of a moving human-object, and simple labeling method is applied for final human-object segmentation. The simulated results show that the applied algorithm is fast to detect the moving human-objects by performing 95% of correct detection rate. The proposed algorithm has confirmed that can be used as an intelligent video access monitoring system.

Keywords: Moving human-object detection, Video access monitoring, Image processing.

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Authors: Afef Salhi, Ameni Yengui Jammaoussi

Abstract:

This paper presents a implementation of an object tracking system in a video sequence. This object tracking is an important task in many vision applications. The main steps in video analysis are two: detection of interesting moving objects and tracking of such objects from frame to frame. In a similar vein, most tracking algorithms use pre-specified methods for preprocessing. In our work, we have implemented several object tracking algorithms (Meanshift, Camshift, Kalman filter) with different preprocessing methods. Then, we have evaluated the performance of these algorithms for different video sequences. The obtained results have shown good performances according to the degree of applicability and evaluation criteria.

Keywords: Tracking, meanshift, camshift, Kalman filter, evaluation.

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Authors: Nedal Tahat

Abstract:

Recently, many existing partially blind signature scheme based on a single hard problem such as factoring, discrete logarithm, residuosity or elliptic curve discrete logarithm problems. However sooner or later these systems will become broken and vulnerable, if the factoring or discrete logarithms problems are cracked. This paper proposes a secured partially blind signature scheme based on factoring (FAC) problem and elliptic curve discrete logarithms (ECDL) problem. As the proposed scheme is focused on factoring and ECDLP hard problems, it has a solid structure and will totally leave the intruder bemused because it is very unlikely to solve the two hard problems simultaneously. In order to assess the security level of the proposed scheme a performance analysis has been conducted. Results have proved that the proposed scheme effectively deals with the partial blindness, randomization, unlinkability and unforgeability properties. Apart from this we have also investigated the computation cost of the proposed scheme. The new proposed scheme is robust and it is difficult for the malevolent attacks to break our scheme.

Keywords: Cryptography, Partially Blind Signature, Factoring, Elliptic Curve Discrete Logarithms.

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Authors: H. A. Rahim, U. U. Sheikh, R. B. Ahmad, A. S. M. Zain

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This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.

Keywords: camera calibration, object tracking, velocity estimation, video image processing

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Authors: Hongmao Zhu, Jun Chu, Lei Shen, Zhihua Luo

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The principle of frequency and amplitude measurement of a vibrating object in water using ultrasonic speckle technique is presented in this paper. Compared with other traditional techniques, the ultrasonic speckle technique can be applied to vibration measurement of a nonmetal object with rough surface in water in a noncontact way. The relationship between speckle movement and object movement was analyzed. Based on this study, an ultrasonic speckle measurement system was set up. With this system the frequency and amplitude of an underwater vibrating cantilever beam was detected. The result shows that the experimental data is in good agreement with the calibrating data.

Keywords: Frequency, Amplitude, Vibration measurement, Ultrasonic speckle

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Authors: Zenaide Carvalho da Silva, Leandro Rodrigues Ferreira, Andrey Ricardo Pimentel

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Learning styles (LS) refer to the ways and forms that the student prefers to learn in the teaching and learning process. Each student has their own way of receiving and processing information throughout the learning process. Therefore, knowing their LS is important to better understand their individual learning preferences, and also, understand why the use of some teaching methods and techniques give better results with some students, while others it does not. We believe that knowledge of these styles enables the possibility of making propositions for teaching; thus, reorganizing teaching methods and techniques in order to allow learning that is adapted to the individual needs of the student. Adapting learning would be possible through the creation of online educational resources adapted to the style of the student. In this context, this article presents the structure of a learning object interface adaptation based on the LS. The structure created should enable the creation of the adapted learning object according to the student's LS and contributes to the increase of student’s motivation in the use of a learning object as an educational resource.

Keywords: Adaptation, interface, learning object, learning style.

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Authors: H. B. Darbandi, M. R. Ito, J. Little

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This paper describes a probabilistic method for three-dimensional object recognition using a shared pool of surface signatures. This technique uses flatness, orientation, and convexity signatures that encode the surface of a free-form object into three discriminative vectors, and then creates a shared pool of data by clustering the signatures using a distance function. This method applies the Bayes-s rule for recognition process, and it is extensible to a large collection of three-dimensional objects.

Keywords: Object recognition, modeling, classification, computer vision.

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Authors: Nidhi Gadura

Abstract:

Given the increase in the number of students and administrators asking for online courses the author developed two partially online courses. One was a biology majors at genetics course while the other was a non-majors at biology course. The student body at Queensborough Community College is generally underprepared and has work and family obligations. As an educator, one has to be mindful about changing the pedagogical approach, therefore, special care was taken when designing the course material. Despite the initial concerns, both of these partially online courses were received really well by students. Lessons learnt were that student engagement is the key to success in an online course. Good practices to run a successful online course for underprepared students are discussed in this paper. Also discussed are the lessons learnt for making the eLearning environment better for all the students in the class, overachievers and underachievers alike.

Keywords: Partially online course, pedagogy, student engagement, community college.

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Authors: Deniz Karagöz Yüncü

Abstract:

This study tested a structural model which investigates the relationships among tourists’ need for uniqueness, perceived authenticity (object-based authenticity and existential authenticity) and behavioral intentions to consume cultural and heritage destinations. The sample of the study comprised of 281 participants in a cultural heritage site, in Cappadocia, Turkey. The data were provided via face to face interviews in two months (September and October) which considered the high season. Structural equation modeling was employed to test the causal relationships among the hypotheses. Findings revealed tourists’ creative choice had an influence on object-based authenticity and existential authenticity. Tourists’ avoidance had an influence on object-based authenticity. The study concluded that two dimensions, namely, the object based authenticity and existential authenticity had significant impact on behavioral intentions.

Keywords: Needs for uniqueness, object-based authenticity, existential authenticity, behavioral intentions.

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Authors: Hui-Chuan Lu

Abstract:

In a perfect secret-sharing scheme, a dealer distributes a secret among a set of participants in such a way that only qualified subsets of participants can recover the secret and the joint share of the participants in any unqualified subset is statistically independent of the secret. The access structure of the scheme refers to the collection of all qualified subsets. In a graph-based access structures, each vertex of a graph G represents a participant and each edge of G represents a minimal qualified subset. The average information ratio of a perfect secret-sharing scheme realizing a given access structure is the ratio of the average length of the shares given to the participants to the length of the secret. The infimum of the average information ratio of all possible perfect secret-sharing schemes realizing an access structure is called the optimal average information ratio of that access structure. We study the optimal average information ratio of the access structures based on bipartite graphs. Based on some previous results, we give a bound on the optimal average information ratio for all bipartite graphs of girth at least six. This bound is the best possible for some classes of bipartite graphs using our approach.

Keywords: Secret-sharing scheme, average information ratio, star covering, deduction, core cluster.

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Authors: Iman Iraei, Mina Sharifi

Abstract:

A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.

Keywords: Mean shift, object tracking, blur extent, wavelet transform, motion blur.

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Authors: A. M. Maqableh

Abstract:

Modelling techniques for a fluid coupling taken from published literature have been extended to include the effects of the filling and emptying of the coupling with oil and the variation in losses when the coupling is partially full. In the model, the fluid flow inside the coupling is considered to have two principal velocity components; one circumferentially about the coupling axis (centrifugal head) and the other representing the secondary vortex within the coupling itself (vortex head). The calculation of liquid mass flow rate circulating between the two halves of the coupling is based on: the assumption of a linear velocity variation in the circulating vortex flow; the head differential in the fluid due to the speed difference between the two shafts; and the losses in the circulating vortex flow as a result of the impingement of the flow with the blades in the coupling and friction within the passages between the blades.

Keywords: Fluid Coupling, Mathematical Modelling, partially filled.

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Authors: Sallama Athab, Hala Bahjat

Abstract:

Detecting object in video sequence is a challenging mission for identifying, tracking moving objects. Background removal considered as a basic step in detected moving objects tasks. Dual static cameras placed in front and rear moving platform gathered information which is used to detect objects. Background change regarding with speed and direction moving platform, so moving objects distinguished become complicated. In this paper, we propose framework allows detection moving object with variety of speed and direction dynamically. Object detection technique built on two levels the first level apply background removal and edge detection to generate moving areas. The second level apply Moving Areas Filter (MAF) then calculate Correlation Score (CS) for adjusted moving area. Merging moving areas with closer CS and marked as moving object. Experiment result is prepared on real scene acquired by dual static cameras without overlap in sense. Results showing accuracy in detecting objects compared with optical flow and Mixture Module Gaussian (MMG), Accurate ratio produced to measure accurate detection moving object.

Keywords: Background Removal, Correlation, Mixture Module Gaussian, Moving Platform, Object Detection.

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