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  • Muhammad Abuzar Fahiem and Abad Ali Shah. 3D Reconstruction from 2D Camera Perspectives
    3D Reconstruction from 2D Camera Perspectives
    Muhammad Abuzar Fahiem and Abad Ali Shah
    Engineering industry requires line drawings for manufacturing, machining and production of engineering equipments/objects. The generation of these paper-based drawings or computerized drawings is a complex and time consuming task. Conventionally, these drawings contain three two dimensional (2D) orthographic views, namely top, front and side of an object. Modern trends in engineering industry require three dimensional (3D) engineering drawings. Therefore, to fulfill this requirement the conversion of these 2D drawings to 3D drawings is essential. This conversion is referred to as the reconstruction. Various approaches have been proposed for the conversion/reconstruction using existing drawings. In this thesis, we developed 3D reconstruction methodology that uses camera perspectives in the reconstruction process. Note that in the existing approaches this feature (camera perspective) is not used. Another salient feature of our approach is in its underlying mechanism of tangential lines...
  • David Antonio Gomez Jauregui and Patrick Horain. 3D Motion Capture by Computer Vision and Virtual Rendering
    3D Motion Capture by Computer Vision and Virtual Rendering
    David Antonio Gomez Jauregui and Patrick Horain
    Networked 3D virtual environments allow multiple users to interact with each other over the Internet. Users can share some sense of telepresence by remotely animating an avatar that represents them. However, avatar control may be tedious and still render user gestures poorly. This work aims at animating a user’s avatar from real time 3D motion capture by monocular computer vision, thus allowing virtual telepresence to anyone using a personal computer with a webcam. The approach followed consists of registering a 3D articulated upper-body model to a video sequence. The first contribution of this work is a method of allocating computing iterations under real-time constrain that achieves optimal robustness and accuracy. The major issue for robust 3D tracking from monocular images is the 3D/2D ambiguities that result from the lack of depth information. As a second contribution, this work enhances particle filtering for 3D/2D registration under limited computation constrains with a number...
  • Teresa Terroso. 3D Object Reconstruction using Computer Vision
    3D Object Reconstruction using Computer Vision
    Teresa Terroso
    This book belongs to the Computer Vision domain, more specifically, to the area of Three-Dimensional (3D) Vision. The 3D information of the surrounding environment perceived by human eyes is one of the most important kinds of information offered by sight. Thus, a large effort has been developed by the scientific community throughout time in the development of methods that make possible the acquisition of a scene (or object) using techniques of Computer Vision. Computational methods were developed to obtain 3D models of the human body from image sequences. On both the image pixel information is transformed into 3D spatial coordinates. The images are acquired by moving the camera or the object to be reconstructed, without imposing severe restrictions, on either the movement involved or on the illumination conditions. The first method adopts the Stereo Vision approach, in which a depth map of scene objects is recovered. The second method is based on a volumetric approach for...
  • Ammara Nasim and Aisha Gul Hafeez. 3D Echocardiographic Image Fusion to Improve Image Quality
    3D Echocardiographic Image Fusion to Improve Image Quality
    Ammara Nasim and Aisha Gul Hafeez
    Diagnosis made easy by 3D Echocardiography Fusion ,An innovation that leads to Diagnosis of Heart diseases without the cost of a cardiac MRI and side effects of a CT scan.Implementation of state of the art techniques like Wavelet and Principal Component Analysis on 3D Echocardiographic Images has been explained in a very simple and easy to understand manner.Hence a combination of Cardiology and Engineering.
  • Lara Kanbar,Hasnaa Rabbat and Adam Aboudan. A Biometric Based on Online Text-Independent Arabic Handwriting
    A Biometric Based on Online Text-Independent Arabic Handwriting
    Lara Kanbar,Hasnaa Rabbat and Adam Aboudan
    A biometric algorithm for personal recognition by identification or verification of the person from his/her Arabic handwriting is presented. The system is online and text-independent. Dynamic data pertaining to handwriting, such as pressure, altitude and azimuth is collected from the user during the writing process, and is used to train models for each writer, after which a recognition system is developed for implementation. The focus in this work is to achieve a high recognition rate with minimal requirements for data and processing time. Based on our experimental results , a system based on Gaussian mixture models (GMM) yields the best classification performance. A full system is developed with a MATLAB-based Graphical User Interface and the Wacom Intuos4 digitizer tablet. We have achieved a best identification rate of 96% for writer identification; whereas for verification, we have obtained an FAR of 4.26% and an FRR of 4.00 %.
  • Andrey Palma,Luis Otavio Alvares and Vania Bogorny. A Clustering-Based Approach for Discovering Places in Trajectories
    A Clustering-Based Approach for Discovering Places in Trajectories
    Andrey Palma,Luis Otavio Alvares and Vania Bogorny
    This work is a clustering point of view about how deduce interesting places considering the points and its speed in a trajectory context. The author explain a clustering trajectory technique and associates the discovered clusters with the trajectory context. The objective is to find out interesting places related to the person/object that generated the points of the trajectory looking mainly at the physical features of the trajectory, i.e. its speed. The clustering technique is extended to consider the spatio-temporal data instead use only the position (spatial) approach.
  • Bayan Abu Shawar. A Corpus Based Approach to Generalising a Chatbot System
    A Corpus Based Approach to Generalising a Chatbot System
    Bayan Abu Shawar
    Chatbot tools are computer programs which interact with users using natural languages. This thesis shows that chatbot technology could be used in many different ways in addition to being a tool for having fun. A chatbot could be used as a tool to learn or to study a new language; a tool to access an information system, a tool to visualise the contents of a corpus; and a tool to give answers to questions in a specific domain. Instead of being restricted to a specific domain or written language, a chatbot could be trained with any text in any language. Some of the differences between real human conversations and human-chatbot dialogues are presented. A Java program has been developed to read a text from a machine readable text (corpus) and convert it to ALICE chatbot format language (AIML). The program was built to be general, the generality in this respect implies, no restrictions on specific language, domain, or structure. Different languages were tested: English, Arabic, Afrikaans,...
  • Assia Belbachir. A Cooperative Architecture to Localize Targets for Underwater Vehicles
    A Cooperative Architecture to Localize Targets for Underwater Vehicles
    Assia Belbachir
    Underwater target localization using several autonomous underwater vehicles(AUVs) is a challenging issue. A systematic and exhaustive coverage strategy is not efficient in term of exploration time: it can be improved by making the AUVs share their information and cooperate to optimize their motions. Communication points are required to make underwater vehicles exchange information: for that purpose the system involves one autonomous surface vehicle (ASV), which helps the AUVs to re-localize and to exchange data, and two AUVs that adapt their strategy according to gathered information, while satisfying the associated communication constraints. Each AUV is endowed with a sensor that estimates its distance with respect to targets, and cooperates with others to explore an area with the help of an ASV. To provide the required autonomy for these vehicles, we built upon an existing system with additional components, which provides an embedded planning and execution control framework....
  • Hammad Afzal. A Framework for Semantic Descriptions of e-Science Resources
    A Framework for Semantic Descriptions of e-Science Resources
    Hammad Afzal
    A literature-based framework for semantic description of e-Science resources is presented. The main hypothesis is that the scientific literature can be used to mine semantic descriptions to facilitate semi-automatic annotation of e-Science resources. The approach includes text-mining methodologies to automatically learn domain annotation tag-sets; identify descriptive sentences and extract semi-formal functional descriptions of e-Science resources from the literature; link similar resources into semantic networks to enhance the resource discovery process.
  • Paolo Di Benedetto. A Framework For Context Aware Adaptable Software Services
    A Framework For Context Aware Adaptable Software Services
    Paolo Di Benedetto
    The near future envisions a pervasive heterogeneous computing infrastructure that makes it possible for mobile users to run software services on a variety of (resource-constrained) devices. To ensure that users meet their non-functional requirements by experiencing the best quality of service according to their needs and the resource characteristics of the specific contexts of use, services need to be context-aware and adaptable. This book presents an approach to context-aware adaptable services based on a modified service oriented interaction pattern to discover and access adaptable services and on a service level specification model to take care of the non functional dimensions. Services are implemented as adaptable components and are deployed on heterogeneous resource constrained mobile devices using an integrated framework that supplies a complete support for developing, reasoning and adapting Java programs with respect to heterogeneous execution environments. This book proposes...
  • Ibrahim Moawad. A Framework for Multi-agent Diagnosis System
    A Framework for Multi-agent Diagnosis System
    Ibrahim Moawad
    Three decades ago, many diagnosis knowledge-based systems have been developed in different diagnostic domains. The diagnosis systems may provide different solutions for the same problem. These solutions mirror different viewpoints for different experts. This book presents a framework for multi-agent diagnosis system as an effective solution for the problem of acquiring different diagnostic results when consulting different diagnostic systems. The framework defines how the agents can negotiate, and cooperate together to resolve the belief conflict that may arise among them. The framework can be applied in any diagnostic domain. Also, the book presents a system prototype in the plant disorders domain. The prototype has been developed on the basis of this framework as a real case study. This book is very interesting for post-graduate students and researchers who have interested in the research areas of multi-agent systems, conflict resolution, diagnosis systems, and...
  • Hudson Ogubi and Cecilia Okumu. A Framework for Adoption of BPO in Kenya's Mobile Phone Companies
    A Framework for Adoption of BPO in Kenya's Mobile Phone Companies
    Hudson Ogubi and Cecilia Okumu
    This research was concern with investigating the factors that affect adoption of business process outsourcing in mobile phone companies in kenya. the study was motivated by the low level of business process outsourcing adoption in these companies amidst high operations cost and shrinking profitability as reported by communication commission of kenya. it is on this premise that the research was concern with investigating the factors that affect the adoption of business process outsourcing. The study developed a framework that can help ease the diffusion of the innovation.
  • Tiago Massoni. A Model-driven Approach to Refactoring
    A Model-driven Approach to Refactoring
    Tiago Massoni
    Refactoring object-oriented software, as any other evolutionary task, usually affects source code and object models, burdening developers to keep those artifacts correct and up to date. Due to the gap between modeling and programming artifacts, refactoring efforts soon become duplicate and considerably expensive. In this context, currently used tool support, in special Round-Trip Engineering (RTE) tools, fails to fully automate evolution tasks. Consequently, most projects discard object models early in the life cycle, adhering to code-driven approaches. This work proposes a formal approach to consistently refactor object models and object-oriented programs of a system in a model-driven manner. Model refactoring is backed by formal laws of modeling, which are guaranteed to be semantics preserving. Each refactoring, a composition of laws, applicable to an object model, is associated with a semi-automatic sequence of applications of laws of programming, called strategy. Strategies are...
  • Nicolas Loeff. A New Framework for Semisupervised and Multitask Learning
    A New Framework for Semisupervised and Multitask Learning
    Nicolas Loeff
    Labeling image collections is a tedious and time consuming task, especially when multiple labels have to be chosen for each image. On the other hand, the explosion of Internet content has provided cheap access to almost unlimited amounts of data, albeit with a lower quality of annotations. This dissertation deals with the problem of automatically annotating images, by introducing a new framework that extends state-of-the-art models in word prediction to incorporate information from two sources, unlabeled examples and correlated labels. This is the first semisupervised multitask model used in vision problems of these characteristics.
  • Besmir Hasanaj. A Part of Speech Tagging Model for Albanian
    A Part of Speech Tagging Model for Albanian
    Besmir Hasanaj
    With the enormous growth of the digital information, it is necessary to find advanced ways to process it. The goal is to enhance information retrieval, information extraction and natural language processing. One of the most complicated processes is text mining which deals with finding high quality information from text. This book presents a statistical part-of-speech tagging model for Albanian. The training, testing and evaluation processes are done with Apache OpenNLP tool. The tagging process is performed based on a basic and a large tagset. The experiments are performed on a tagger model trained with corpus composed of a standard Albanian text written by Albanian authors. The tagger model is tested using a cross-validation and a sample text. Results showed that the accuracy of the trained tagger model in real testing environments was about 70%, and up to 98% when the environment settings were optimized for the best accuracy. It was also noticed that the overall accuracy for this...
  • Marcos Salgueiro Balsa. A Private Cloud Implementation for MapReduce Applications
    A Private Cloud Implementation for MapReduce Applications
    Marcos Salgueiro Balsa
    The Internet has become the orchestrating background for a new crop of smart services constantly feeding on raw data to improve user experience and results quality. Data defined by two fundamental qualities that make them hard to handle with traditional methods: unstructured and with exponential growth. Cloud Computing, natural evolution of virtualization and modern solution to heterogeneous distribution of service demand, together with a modern MapReduce implementation, constitute the cutting-edge in Big Data technologies. This book will get you acquainted with both paradigms to later introduce 'qosh': A Private Cloud Implementation for MapReduce Applications.
  • Gianpaolo Coro. A Step Forward in Multi-granular Automatic Speech Recognition
    A Step Forward in Multi-granular Automatic Speech Recognition
    Gianpaolo Coro
    This book is a first effort to make a step further in the understanding of speech recognition mechanisms in humans. The starting point of the ideas here presented goes back to the early language scientific theories, which have been followed in time, by a set of psychoacoustic experiments, models, and technical realization attempts. An hypothesis is assumed, which is called 'multi-granular': the human auditory system needs that more parallel cognitive functions operate a chunking on the unfolding of the information over time, to catch all the information coming from the signal. The left-to-right speech stream is captured in a multilevel grid in which several linguistic analyses take place simultaneously. Here, I present an example of realization of a multi-granular automatic speech recognizer. Dynamics coming from the signal, which are segmental or supersegmental in nature, are caught in a single model which tries to take the best of them, in order to improve system performances.
  • Mela Ali and Loay George. A Spatial Invarient Model for Local Attributes of Fingerprint Ridges
    A Spatial Invarient Model for Local Attributes of Fingerprint Ridges
    Mela Ali and Loay George
    Fingerprint recognition and verification are always the key issues in intelligent technology and information security. For a considerable fraction of population, the representation based on complete detection of ridge structures in the fingerprint is difficult to be accomplished. The main challenge is partial loss of the ridge structures. In this work, we developed a geometrically based method for fingerprint recognition and verification tasks; a set of partial local features extracted from fingerprint ridges, minutia, and pores attributes are used. The proposed system passes through two main phases: Training phase and Test phase. In the training phase, the system is trained using a set of low quality fingerprint images to select the best discriminating local features which can lead to best recognition rates. During the test phase, the system performance is examined to know the cognitive power of the system.
  • Mikheil Rukhaia. About Cut-Elimination in Schematic Proofs
    About Cut-Elimination in Schematic Proofs
    Mikheil Rukhaia
    Gentzen's Hauptsatz (cut-elimination theorem) is the cornerstone in proof theory. It leads to analytic proofs. But in the systems, having induction as a rule, cut-elimination is not possible in general. One way to overcome this problem is to define an infinite sequence of proofs in a uniform way and a method, which will obtain a uniform description of corresponding analytic proofs. This book presents such a formalism, alternative to the inductive systems and defines a cut-elimination method for it. First, the basic concepts of proof theory, such as sequent and resolution calculi are defined. Later they are enriched with inductive definitions and schemata of terms, formulas, proofs, etc., are obtained. The cut-elimination method for such proof schemata is illustrated on several examples. The text is self-contained, thus can be read by not only experts, but anyone else interested in mathematical logic and proof theory.
  • Guido Scatena. Abstract Probabilistic Semantics for the Analysis of Bio Sys Models
    Abstract Probabilistic Semantics for the Analysis of Bio Sys Models
    Guido Scatena
    This book concerns the development of probabilistic semantics tailored to model the dynamic behavior of biological systems in order to formally analyze them. More specifically, it attempts to overcome problems, related to uncertainty and to the state space explosion, inherent to models describing biological systems. Recently, many formalisms originated from Computer Science have been successfully applied to describe biological systems. Many of these formalisms include probabilistic aspects, and techniques like stochastic simulation and probabilistic model checking have been proposed to study biological systems properties. However, the practical application of formal analysis tools in this context is still limited. The size of state space associated with models is often prohibitively large. Moreover, the knowledge of biological processes is often incomplete, resulting in models with uncertain parameters. To overcome these problems, in this Thesis, we propose to apply...

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