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  Partner: UNT Libraries
 Degree Discipline: Computer Science and Engineering
 Collection: UNT Theses and Dissertations
Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements

Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements

Date: August 2013
Creator: Kumara, Muthukudage Jayantha
Description: The effectiveness of colonoscopy depends on the quality of the inspection of the colon. There was no automated measurement method to evaluate the quality of the inspection. This thesis addresses this issue by investigating an automated post-procedure quality measurement technique and proposing a novel approach automatically deciding a percentage of stool areas in images of digitized colonoscopy video files. It involves the classification of image pixels based on their color features using a new method of planes on RGB (red, green and blue) color space. The limitation of post-procedure quality measurement is that quality measurements are available long after the procedure was done and the patient was released. A better approach is to inform any sub-optimal inspection immediately so that the endoscopist can improve the quality in real-time during the procedure. This thesis also proposes an extension to post-procedure method to detect stool, bite-block, and blood regions in real-time using color features in HSV color space. These three objects play a major role in quality measurements in colonoscopy. The proposed method partitions very large positive examples of each of these objects into a number of groups. These groups are formed by taking intersection of positive examples with a hyper plane. ...
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Capacity and Throughput Optimization in Multi-cell 3G WCDMA Networks

Capacity and Throughput Optimization in Multi-cell 3G WCDMA Networks

Date: December 2005
Creator: Nguyen, Son
Description: User modeling enables in the computation of the traffic density in a cellular network, which can be used to optimize the placement of base stations and radio network controllers as well as to analyze the performance of resource management algorithms towards meeting the final goal: the calculation and maximization of network capacity and throughput for different data rate services. An analytical model is presented for approximating the user distributions in multi-cell third generation wideband code division multiple access (WCDMA) networks using 2-dimensional Gaussian distributions by determining the means and the standard deviations of the distributions for every cell. This model allows for the calculation of the inter-cell interference and the reverse-link capacity of the network. An analytical model for optimizing capacity in multi-cell WCDMA networks is presented. Capacity is optimized for different spreading factors and for perfect and imperfect power control. Numerical results show that the SIR threshold for the received signals is decreased by 0.5 to 1.5 dB due to the imperfect power control. The results also show that the determined parameters of the 2-dimensional Gaussian model match well with traditional methods for modeling user distribution. A call admission control algorithm is designed that maximizes the throughput in multi-cell ...
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Comparative Study of RSS-Based Collaborative Localization Methods in Wireless Sensor Networks

Comparative Study of RSS-Based Collaborative Localization Methods in Wireless Sensor Networks

Date: December 2006
Creator: Koneru, Avanthi
Description: In this thesis two collaborative localization techniques are studied: multidimensional scaling (MDS) and maximum likelihood estimator (MLE). A synthesis of a new location estimation method through a serial integration of these two techniques, such that an estimate is first obtained using MDS and then MLE is employed to fine-tune the MDS solution, was the subject of this research using various simulation and experimental studies. In the simulations, important issues including the effects of sensor node density, reference node density and different deployment strategies of reference nodes were addressed. In the experimental study, the path loss model of indoor environments is developed by determining the environment-specific parameters from the experimental measurement data. Then, the empirical path loss model is employed in the analysis and simulation study of the performance of collaborative localization techniques.
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Detection of Temporal Events and Abnormal Images for Quality Analysis in Endoscopy Videos

Detection of Temporal Events and Abnormal Images for Quality Analysis in Endoscopy Videos

Date: August 2013
Creator: Nawarathna, Ruwan D.
Description: Recent reports suggest that measuring the objective quality is very essential towards the success of colonoscopy. Several quality indicators (i.e. metrics) proposed in recent studies are implemented in software systems that compute real-time quality scores for routine screening colonoscopy. Most quality metrics are derived based on various temporal events occurred during the colonoscopy procedure. The location of the phase boundary between the insertion and the withdrawal phases and the amount of circumferential inspection are two such important temporal events. These two temporal events can be determined by analyzing various camera motions of the colonoscope. This dissertation put forward a novel method to estimate X, Y and Z directional motions of the colonoscope using motion vector templates. Since abnormalities of a WCE or a colonoscopy video can be found in a small number of frames (around 5% out of total frames), it is very helpful if a computer system can decide whether a frame has any mucosal abnormalities. Also, the number of detected abnormal lesions during a procedure is used as a quality indicator. Majority of the existing abnormal detection methods focus on detecting only one type of abnormality or the overall accuracies are somewhat low if the method tries to ...
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E‐Shape Analysis

E‐Shape Analysis

Date: December 2009
Creator: Sroufe, Paul
Description: The motivation of this work is to understand E-shape analysis and how it can be applied to various classification tasks. It has a powerful feature to not only look at what information is contained, but rather how that information looks. This new technique gives E-shape analysis the ability to be language independent and to some extent size independent. In this thesis, I present a new mechanism to characterize an email without using content or context called E-shape analysis for email. I explore the applications of the email shape by carrying out a case study; botnet detection and two possible applications: spam filtering and social-context based finger printing. The second part of this thesis takes what I apply E-shape analysis to activity recognition of humans. Using the Android platform and a T-Mobile G1 phone I collect data from the triaxial accelerometer and use it to classify the motion behavior of a subject.
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Evaluating Appropriateness of Emg and Flex Sensors for Classifying Hand Gestures

Evaluating Appropriateness of Emg and Flex Sensors for Classifying Hand Gestures

Date: May 2013
Creator: Akumalla, Sarath Chandra
Description: Hand and arm gestures are a great way of communication when you don't want to be heard, quieter and often more reliable than whispering into a radio mike. In recent years hand gesture identification became a major active area of research due its use in various applications. The objective of my work is to develop an integrated sensor system, which will enable tactical squads and SWAT teams to communicate when there is absence of a Line of Sight or in the presence of any obstacles. The gesture set involved in this work is the standardized hand signals for close range engagement operations used by military and SWAT teams. The gesture sets involved in this work are broadly divided into finger movements and arm movements. The core components of the integrated sensor system are: Surface EMG sensors, Flex sensors and accelerometers. Surface EMG is the electrical activity produced by muscle contractions and measured by sensors directly attached to the skin. Bend Sensors use a piezo resistive material to detect the bend. The sensor output is determined by both the angle between the ends of the sensor as well as the flex radius. Accelerometers sense the dynamic acceleration and inclination in 3 ...
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Exploring Privacy in Location-based Services Using Cryptographic Protocols

Exploring Privacy in Location-based Services Using Cryptographic Protocols

Date: May 2011
Creator: Vishwanathan, Roopa
Description: Location-based services (LBS) are available on a variety of mobile platforms like cell phones, PDA's, etc. and an increasing number of users subscribe to and use these services. Two of the popular models of information flow in LBS are the client-server model and the peer-to-peer model, in both of which, existing approaches do not always provide privacy for all parties concerned. In this work, I study the feasibility of applying cryptographic protocols to design privacy-preserving solutions for LBS from an experimental and theoretical standpoint. In the client-server model, I construct a two-phase framework for processing nearest neighbor queries using combinations of cryptographic protocols such as oblivious transfer and private information retrieval. In the peer-to-peer model, I present privacy preserving solutions for processing group nearest neighbor queries in the semi-honest and dishonest adversarial models. I apply concepts from secure multi-party computation to realize our constructions and also leverage the capabilities of trusted computing technology, specifically TPM chips. My solution for the dishonest adversarial model is also of independent cryptographic interest. I prove my constructions secure under standard cryptographic assumptions and design experiments for testing the feasibility or practicability of our constructions and benchmark key operations. My experiments show that the proposed ...
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Extrapolating Subjectivity Research to Other Languages

Extrapolating Subjectivity Research to Other Languages

Date: May 2013
Creator: Banea, Carmen
Description: Socrates articulated it best, "Speak, so I may see you." Indeed, language represents an invisible probe into the mind. It is the medium through which we express our deepest thoughts, our aspirations, our views, our feelings, our inner reality. From the beginning of artificial intelligence, researchers have sought to impart human like understanding to machines. As much of our language represents a form of self expression, capturing thoughts, beliefs, evaluations, opinions, and emotions which are not available for scrutiny by an outside observer, in the field of natural language, research involving these aspects has crystallized under the name of subjectivity and sentiment analysis. While subjectivity classification labels text as either subjective or objective, sentiment classification further divides subjective text into either positive, negative or neutral. In this thesis, I investigate techniques of generating tools and resources for subjectivity analysis that do not rely on an existing natural language processing infrastructure in a given language. This constraint is motivated by the fact that the vast majority of human languages are scarce from an electronic point of view: they lack basic tools such as part-of-speech taggers, parsers, or basic resources such as electronic text, annotated corpora or lexica. This severely limits the ...
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Finding Meaning in Context Using Graph Algorithms in Mono- and Cross-lingual Settings

Finding Meaning in Context Using Graph Algorithms in Mono- and Cross-lingual Settings

Date: May 2013
Creator: Sinha, Ravi Som
Description: Making computers automatically find the appropriate meaning of words in context is an interesting problem that has proven to be one of the most challenging tasks in natural language processing (NLP). Widespread potential applications of a possible solution to the problem could be envisaged in several NLP tasks such as text simplification, language learning, machine translation, query expansion, information retrieval and text summarization. Ambiguity of words has always been a challenge in these applications, and the traditional endeavor to solve the problem of this ambiguity, namely doing word sense disambiguation using resources like WordNet, has been fraught with debate about the feasibility of the granularity that exists in WordNet senses. The recent trend has therefore been to move away from enforcing any given lexical resource upon automated systems from which to pick potential candidate senses,and to instead encourage them to pick and choose their own resources. Given a sentence with a target ambiguous word, an alternative solution consists of picking potential candidate substitutes for the target, filtering the list of the candidates to a much shorter list using various heuristics, and trying to match these system predictions against a human generated gold standard, with a view to ensuring that the ...
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Incremental Learning with Large Datasets

Incremental Learning with Large Datasets

Date: May 2012
Creator: Giritharan, Balathasan
Description: This dissertation focuses on the novel learning strategy based on geometric support vector machines to address the difficulties of processing immense data set. Support vector machines find the hyper-plane that maximizes the margin between two classes, and the decision boundary is represented with a few training samples it becomes a favorable choice for incremental learning. The dissertation presents a novel method Geometric Incremental Support Vector Machines (GISVMs) to address both efficiency and accuracy issues in handling massive data sets. In GISVM, skin of convex hulls is defined and an efficient method is designed to find the best skin approximation given available examples. The set of extreme points are found by recursively searching along the direction defined by a pair of known extreme points. By identifying the skin of the convex hulls, the incremental learning will only employ a much smaller number of samples with comparable or even better accuracy. When additional samples are provided, they will be used together with the skin of the convex hull constructed from previous dataset. This results in a small number of instances used in incremental steps of the training process. Based on the experimental results with synthetic data sets, public benchmark data sets from ...
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