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Articles 361 - 390 of 666
Full-Text Articles in Computer Sciences
Design And Implementation Of An Open Beaconing Architecture For Internet Of Things, Arjun Kumar Bhaskar Shetty
Design And Implementation Of An Open Beaconing Architecture For Internet Of Things, Arjun Kumar Bhaskar Shetty
Computer Science and Engineering Theses - Archive
The power of the Internet is penetrating into the physical world with ever increasing speed and expanding reach under the general concept of Internet of Things. Extensive sets of efforts have been devoted toward establishing an interconnected network of smart devices in a self-organized manner. Nowadays, using low power beacons to announce the presences of physical objects has gained tremendous momentum exemplified by iBeacon from Apple. Unfortunately, schemes like iBeacon use abstract codes to denote a physical entity, limiting it to be only understandable by those with knowledge of it beforehand. In this thesis, we develop an open architecture where …
Faster Sampling Over Theoritical And Online Social Networks, Ramakrishna Aduri
Faster Sampling Over Theoritical And Online Social Networks, Ramakrishna Aduri
Computer Science and Engineering Theses - Archive
Online social networks have become very popular recently and are used bymillions of users. Researchers increasingly want to leverage the rich variety ofinformation available. However, social networks often feature a web interface that onlyallows local-neighborhood queries - i.e., given a user of the online social network asinput, the system returns the immediate neighbors of the user. Additionally, they alsohave rate limits that restrict the number of queries issued over a given time period. Theserestrictions make third party analytics extremely challenging. The traditional approach ofusing random walks is not effective as they require significant burn-in period before theirstationary distribution converges to …
Microblog Analyzer Aggregate Estimation Over A Micro Blog Platform, Satishkumar Masilamani
Microblog Analyzer Aggregate Estimation Over A Micro Blog Platform, Satishkumar Masilamani
Computer Science and Engineering Theses - Archive
Microblogging is a new mode of communication in which users can share their current status in brief and agile way in the form of text, image, video etc over smart phones, email or web. Recently, Microblogs such as Twitter, Tumblr, Google+ have experience phenomenal growth and are regularly used by millions of users. The data from microblogs is very useful for researchers to analyze various facets such as user behaviors, user intentions (like daily chatter, conversations, sharing information and reporting news), microblog social network structure etc. For example, a sociologist might want to use the microblog postings to analyze the …
A Real-Time Embedded Data Acquisition System For Surface Measurements Using Multiple Line Lasers, A P Vikram Simha
A Real-Time Embedded Data Acquisition System For Surface Measurements Using Multiple Line Lasers, A P Vikram Simha
Computer Science and Engineering Theses - Archive
In the last few years there has been a significant increase in the number of hand held devices. These devices boast of delivering features such as high performance, low power consumption, high memory availability, serial and parallel interfacing capability, connectivity through the Ethernet, wireless, etc., at a very low cost. These embedded devices powered by open source software like Linux and Arduino have paved the way for the development of high efficiency, low cost portable products in a very short period of time.The objective of this thesis is to enhance the portability, efficiency, and other features of the existing Roline …
Mechanical Reliability Of Porous Low-K Dielectrics For Advanced Interconnect: Study Of The Instability Mechanisms In Porous Low-K Dielectrics And Their Mediation Through Inert Plasma Induced Re-Polymerization Of The Backbone Structure, Yoonki Sa
Computer Science and Engineering Dissertations - Archive
Continuous scaling down of critical dimensions in interconnect structures requires the use of ultralow dielectric constant (k) films as interlayer dielectrics to reduce resistance-capacitance delays. Porous carbon-doped silicon oxide (p-SiCOH) dielectrics have been the leading approach to produce these ultralow-k materials. However, embedding of porosity into dielectric layer necessarily decreases the mechanical reliability and increases its susceptibility to adsorption of potentially deleterious chemical species during device fabrication process. Among those, exposure of porous-SiCOH low-k (PLK) dielectrics to oxidizing plasma environment causes the increase in dielectric constant and their vulnerability to mechanical instability of PLKs due to the loss of methyl …
Methods For Human Motion Analysis For American Sign Language Recognition And Assistive Environments, Zhong Zhang
Methods For Human Motion Analysis For American Sign Language Recognition And Assistive Environments, Zhong Zhang
Computer Science and Engineering Dissertations - Archive
The broad application domain of the work presented in this thesis is human motion analysis with a focus on hand detection for American Sign Language recognition and fall detection for assistive environments.One of the motivations of the proposed thesis is a semi-automatic vision based American Sign Language recognition system. This system allows a user to submit as query a video of the sign of interest, or simply perform the sign in front of a camera. The system then asks the user to annotate the hands' locations in the sign. Next, the hand trajectory of the query sign is compared with …
A Personalized Profile Based Learning System For Power Management In Android, Ashwin Arikere
A Personalized Profile Based Learning System For Power Management In Android, Ashwin Arikere
Computer Science and Engineering Dissertations - Archive
Mobile computing devices are becoming more ubiquitous everyday due to the phenomenal growth in technology powering them. With the amount of computing power available in these devices, users are capable of achieving a multitude of tasks that were only possible with a PC just a few years ago. However, these devices still face issues regarding power management. Battery technology has not kept pace with the development in other areas. With a limited supply of energy, the mobile device of today requires a fine balance of power management to provide adequate energy to support the heavy duty computing of the user …
Dynamic Symbolic Data Structure Repair And Evaluation Of Program Analysis Tools With The Rugrat Random Program Generator, Ishtiaque Hussain
Dynamic Symbolic Data Structure Repair And Evaluation Of Program Analysis Tools With The Rugrat Random Program Generator, Ishtiaque Hussain
Computer Science and Engineering Dissertations - Archive
Generic automatic repair of complex data structures is a new and exciting area of research. Existing approaches can integrate with good software engineering practices such as program assertions. But in practice there is a wide variety of assertions and not all of them satisfy the style rules imposed by existing repair techniques. That is, a badly written assertion may render generic repair inefficient or ineffective. Moreover, the performance of existing approaches may depend on the location of an error in a corrupted data structure. This dissertation shows that generic automatic data structure repair can be implemented with full dynamic symbolic …
Social Data Analytics Using Tensors And Sparse Techniques, Miao Zhang
Social Data Analytics Using Tensors And Sparse Techniques, Miao Zhang
Computer Science and Engineering Dissertations - Archive
The development of internet and mobile technologies is driving an earthshaking social media revolution. They bring the internet world a huge amount of social media content, such as images, videos, comments, etc. Those massive media content and complicate social structures require the analytic expertise to transform those flood of information into actionable strategies, because mining those data can help organizations take control of those data, therefore organizations can improve customer satisfaction, identify patterns and trends, and make smarter marketing strategies. Mining those data can also help the consumers to grasp the most important and convenient information from the overwhelming data …
Run-Time Compilation And Dynamic Memory Use Analysis For Gpus, Derek White
Run-Time Compilation And Dynamic Memory Use Analysis For Gpus, Derek White
Computer Science and Engineering Dissertations - Archive
Powerful Graphics Processing Units (commonly called GPUs) are proliferatingrapidly and are becoming a viable choice for a wide range of user applications. Forperforming computationally intensive tasks on these processors, it is highly desirable to have software tools that can facilitate writing effective programming codewhile taking advantage of the full potential offered by these processors. Multi-levelmemory hierarchy, extensive data transfer, and the utilization of a large number ofprocessing cores are daunting challenges in writing code for data-parallel computingtasks. The programming experience becomes more cumbersome due to the significantrestrictions imposed by the OpenCL specification including the inability to allocatememory dynamically. The contribution …
Graph Embedding Discriminative Unsupervised Dimensionality Reduction, Yun Liu
Graph Embedding Discriminative Unsupervised Dimensionality Reduction, Yun Liu
Computer Science and Engineering Theses - Archive
In this thesis, a novel graph embedding unsupervised dimensionality reduction method was proposed. Simultaneously, we assigned the adaptive and optimal neighbors on the basis of the projected local distances, thus we developed the dimensionality reduction along with the graph construction. The clustering results could be directly exhibited from the learnt graph which has the explicit block diagonal structure.The analysis of experimental result on different databases also determines that the proposed dimensionality reduction method is superior to other related dimensionality reduction methods, like PCA and LPP. In this study, we use synthetic data and real-world benchmark data sets. Also experimental results …
A Hmm-Based Prediction Model For Spatio-Temporal Trajectories, Sakthi Kumaran Shanmuganathan
A Hmm-Based Prediction Model For Spatio-Temporal Trajectories, Sakthi Kumaran Shanmuganathan
Computer Science and Engineering Theses - Archive
Spatio-temporal trajectories are time series data that represent movement of an object over the time. Hidden Markov Models (HMM), a variant of Markov Models (MM), were first applied at a large scale to speech recognition but have also been used in time series prediction by analyzing trends in historical time series data. In this research, we propose a storm prediction model using a HMM built from overall storm trajectories derived from raw rainfall data. This HMM is built by assuming the states are associated with clusters created by clustering the locations of each storm from the overall storm trajectories. Then …
Improving Tor Performance By Modifying Path Selection, Mehrdad Amirabadi
Improving Tor Performance By Modifying Path Selection, Mehrdad Amirabadi
Computer Science and Engineering Theses - Archive
Tor is a popular volunteer-based overlay network that provides anonymity andprivacy for Internet users. Using the Onion Proxy (OP) client, users connect to anetwork of Onion Routers (ORs) and send their traffic through an encrypted path ofthree ORs. One of the main problems of the Tor network is its slow performance, anda key cause of this is the Tor path selection algorithm. In Tor, ORs are selected basedprimarily on their bandwidth. In this work, we improve on the Tor path selectionalgorithm by proposing a new algorithm that besides bandwidth, uses distance as afactor to help reduce propagation delay. In our …
Linking Entity Profiles, Ramesh Venkataraman
Linking Entity Profiles, Ramesh Venkataraman
Computer Science and Engineering Theses - Archive
Entity linking allows one to have collections of data from multiple sources as a global dataset and then query those data. Entity linking allows us to do knowledge discovery on this global dataset which might result in the discovery of some interesting facts and information. Microsoft Academic Search (MAS) is a free public search engine for academic papers and contains the bibliographic information for papers published in journals, conference proceedings and respective citations. As of February 2014, it has indexed over 40 million publications and 20 million authors. LinkedIn is a social networking service used for professional networking. LinkedIn has …
Discovery Of Anomalous Patterns Within Multidimensional, Asynchronous Time-Series With An Emphasis On The "Internet Of Things", Stephen P. Emmons
Discovery Of Anomalous Patterns Within Multidimensional, Asynchronous Time-Series With An Emphasis On The "Internet Of Things", Stephen P. Emmons
Computer Science and Engineering Dissertations - Archive
In this dissertation we examine ``Internet-scale'' systems that present us with multidimensional time-series data characterized by many sources sending symbols at irregular intervals over a common channel. We explore a unique method for the discovery of hidden populations of similar sources and their previously-unknown behavioral patterns, and using these discoveries, reveal anomalous sources and/or time-frames based on their statistical properties. To do so, we employ several well-studied mechanisms, such as k-means and Principle Component Analysis (PCA), and bring to bear analysis tools from other disciplines, such as the use of n-grams and "motifs," that have not previously been considered in …
Analysis And Modeling Techniques For Geo-Spatial And Spatio-Temporal Datasets, Kulsawasd Jitkajornwanich
Analysis And Modeling Techniques For Geo-Spatial And Spatio-Temporal Datasets, Kulsawasd Jitkajornwanich
Computer Science and Engineering Dissertations - Archive
In recent years, spatio-temporal data has received a lot of attention and increasingly plays an important role in our everyday lives as we can witness from the fast-growing mobile technologies and its location-based application development. By spatio-temporal data, we mean data that is associated with specific spatial locations that change over time. For example, a cellphone or car with GPS will generate the object location at regular time intervals. Another example would be the track of a storm center as it moves. Spatio-temporal data could be thought of as a huge data warehouse, which contains hidden and meaningful information. However, …
Estimation Myopia: Tinkering With Perception In Software Estimation And Placebo Estimation In Edw, Hazem Hasan Yassin
Estimation Myopia: Tinkering With Perception In Software Estimation And Placebo Estimation In Edw, Hazem Hasan Yassin
Computer Science and Engineering Theses - Archive
The goal of this study is to explore an effective way to provide timely and accurate size estimates for software and for an enterprise data warehouse (EDW). Several research papers attempt to adapt function point (FP) analysis to EDW, but there is not much research in comprehensive techniques to estimate large EDW projects. Despite the generality of FP, it is challenging to employ in an EDW environment. This thesis describes such a technique. Additionally, the thesis provides an overview of general estimating approaches, techniques, models, and tools.This work presents a software tool that is a custom built estimation utility that …
Online Efficient And Effective Search In Large And Noisy Sequence Databases, Alexios Kotsifakos
Online Efficient And Effective Search In Large And Noisy Sequence Databases, Alexios Kotsifakos
Computer Science and Engineering Dissertations - Archive
This thesis investigates the problem of similarity search in large and noisy sequence databases. A key application domain of interest in this work is the very challenging Query-By-Humming (QBH) problem, according to which, given a hummed part of a song, we would like to identify the closest matches in a large music repository. The problem of selecting the most appropriate, based on each specific query, distance measure out of a pool of measures for classification in time series data is also investigated. In addition, searching time series databases via examples, which may be either time series or models, is also …
A Method To Evade Keyword Based Censorship, Ritu R. Patil
A Method To Evade Keyword Based Censorship, Ritu R. Patil
Computer Science and Engineering Theses - Archive
Many countries block the content of web pages which are deemed against the morals, religious rules or policies set by government or organization. Countries like China block the post which is against their government interest. Germany blocks contents related to Neo-Nazi group. Most of these web pages are subjected to IP address blocking, DNS poisoning and keyword based filtering. We mainly focus on keyword based filtering as it is fine grained filtering technique where the contents of web pages are filtered using blacklisting. So with increase in surveillance over network, arms race for circumvention techniques has also increased. We propose …
A Cloud Based Automated Anomaly Detection Framework, Prathibha Datta Kumar
A Cloud Based Automated Anomaly Detection Framework, Prathibha Datta Kumar
Computer Science and Engineering Theses - Archive
A machine-to-machine (M2M) communications network hosts millions of heterogeneous devices such as for vehicle tracking, medical services, and home automation and security services. These devices exchange thousands of messages over cellular networks. These messages are Signaling System No. 7 (SS7) messages of various types like authentication, mobility management, and many more, resulting in tera bytes of SS7 signaling traffic data over a period of days. The data generated is diverse, depending on several factors like device activity, hardware manufacturers, and radio / tower interaction. This inherent diversity makes anomaly detection in a M2M network challenging. With millions of messages to …
Integrative Approaches For Biological Network Inferences, Dongchul Kim
Integrative Approaches For Biological Network Inferences, Dongchul Kim
Computer Science and Engineering Dissertations - Archive
Inferring biological networks from high-throughput bioinformatics data is one of the most interesting areas in the systems biology research in order to elucidate cellular and physiological mechanisms. In this thesis, network inference methods are proposed to solve biological problems. We first investigated how the exposure to low dose ionizing radiation (IR) affects the human body by observing the signaling pathway associated with Ataxia Telangiectasia mutated using Reverse Phase Protein Array and isogenic human Ataxia Telangiectasia cells under different amounts and durations of IR exposure. DNA damage-caused pathways are derived from learning Bayesian networks in integration with prior knowledge such as …
Inferring Answer Quality, Answerer Expertise, And Ranking In Question Answer Social Networks, Yuanzhe Cai
Inferring Answer Quality, Answerer Expertise, And Ranking In Question Answer Social Networks, Yuanzhe Cai
Computer Science and Engineering Dissertations - Archive
Search has become ubiquitous mainly because of its usage simplicity. Search has made great strides in making information gathering relatively easy and without a learning curve. Question answering services/communities (termed CQA services or Q/A networks; e.g., Yahoo! Answers, Stack Overflow) have come about in the last decade as yet another way to search. Here the intent is to obtain good/high quality answers (from users with different levels of expertise) for a question when posed, or to retrieve answers from an archived Q/A repository. To make use of these services (and archives) effectively as an alternative to search, it is imperative …
Efficient Frameworks For Lifetime Maximization In Tree Based Sensor Networks, Sk Kajal Arefin Imon
Efficient Frameworks For Lifetime Maximization In Tree Based Sensor Networks, Sk Kajal Arefin Imon
Computer Science and Engineering Dissertations - Archive
In most wireless sensor network (WSN) applications, data are typically gathered by the sensor nodes and reported to a data collection point, called the sink. In order to support such data collection, a tree structure rooted at the sink is usually defined. Based on different aspects, including the actual WSN topology and the available energy budget, the energy consumption of nodes belonging to different paths in the data collection tree may vary significantly. This affects the overall network lifetime, defined in terms of when the first node in the network runs out of energy. In this thesis, we address the …
A Source Code Search Engine For Keyword Based Structural Relationship Search, Asheq Hamid
A Source Code Search Engine For Keyword Based Structural Relationship Search, Asheq Hamid
Computer Science and Engineering Theses - Archive
In an Object Oriented Program, we often see that a package contains several classes, a class contains several methods, a method calls other methods. We may say, there is a contains relationship between a package and a class or a calls relationship between two methods. We refer to these relationships as structural relationships. There may be other structural relationships apart from contains or calls in the source code. A software developer may sometime want to search for structural relationships within source code. She may prefer using Google like free form query to do so. To facilitate free form query based …
Practical End-To-End Performance Evaluation Of Backend Software Applications, Tuli Nivas
Practical End-To-End Performance Evaluation Of Backend Software Applications, Tuli Nivas
Computer Science and Engineering Dissertations - Archive
This dissertation makes contributions to four areas of performance testing - the test process itself, monitoring, automation and end-to-end performance evaluation of backend applications. The first contribution deals with the testing process. Performance testing is a key element of industrial software development, but we still encountered the following two problems. (1) While testing textbooks prescribe writing tests against performance goals, we find that it is impractical to gather from business analysts performance goals that are detailed enough for finding subtle performance bugs. (2) Once performance tests are conducted, we were asked questions such as - how do you make sure …
New Matrix Completion Models For Social Information Retrieval Application, Jin Huang
New Matrix Completion Models For Social Information Retrieval Application, Jin Huang
Computer Science and Engineering Dissertations - Archive
Many popular social web sites have emerged during the past decade and completely changed many users' everyday live. Recently, social information retrieval models, where conventional information retrieval meets the social context of search and recommendation, have become the central topic in machine learning, data mining, information retrieval and many other areas.A particular application of social information retrieval is the recommendation. Such recommendation ranges from classic recommendation movie rating recommendation in user-item matrices, trust and reputation modeling between members in any social network. If we model such recommendation in the form of matrices, then such recommendation can be formulated as recovering …
Quantitative Analysis Of Surface Enhanced Raman Spectra, Shuo Li
Quantitative Analysis Of Surface Enhanced Raman Spectra, Shuo Li
Computer Science and Engineering Dissertations - Archive
Quantitative analysis of Raman spectra using surface-enhanced Raman scattering (SERS) nanoparticles has shown the potential and promising trend of development in vivo molecular imaging. One of the key job is from the intensities of Raman signals to predict the quantities of analytes. Direct classical least squares (DCLS) and multivariate calibration (MC) are commonly used methods. DCLS relies on source Raman signals as the references. But the inherent Instability of Raman signals make the DCLS model not robust enough. MC model relies on a batch of training mixture Raman signals together with the ground truth mixing concentrations to build the multivariate …
Image Annotation And Feature Engineering Via Structural Sparsity And Low Rank Approximation, Deguang Kong
Image Annotation And Feature Engineering Via Structural Sparsity And Low Rank Approximation, Deguang Kong
Computer Science and Engineering Dissertations - Archive
Nowadays, in order to sense environment and understand human behaviors, data analysis plays a more and more important role to handle heterogeneous data ranging from different domains, e.g., image categorization/annotation, customer segmentation, traffic prediction, ad optimization, recommendation systems, privacy analysis, etc. The large amount of multivariate data raises the fundamental problem of data mining: how to discover meaningful compact patterns hidden in the high-dimensional noisy observations? One approach is to do dimension reduction, which finds the low-dimensional subspace and thus encodes data in a low-dimensional structure. The other approach is to do feature selection or feature engineering, which manipulates the …
Sparse And Large-Scale Learning Models And Algorithms For Mining Heterogeneous Big Data, Xiao Cai
Sparse And Large-Scale Learning Models And Algorithms For Mining Heterogeneous Big Data, Xiao Cai
Computer Science and Engineering Dissertations - Archive
With the development of PC, internet as well as mobile devices, we are facing a data exploding era. On one hand, more and more features can be collected to describe the data, making the size of the data descriptor larger and larger. On the other hand, the number of data itself explodes and can be collected from multiple resources. When the data becomes large scale, the traditional data analysis method may fail, suffering the curse of dimensionality and etc. In order to explore and analyze the large-scale data more accurately and more efficiently, based on the characteristic of the data, …
An Interpolation Based Approach For Pattern Recognition And Generation, Vishnukumar Galigekere Nagabhushana
An Interpolation Based Approach For Pattern Recognition And Generation, Vishnukumar Galigekere Nagabhushana
Computer Science and Engineering Dissertations - Archive
A large number of problems in computer vision and computer graphics can essentially be reduced to a pattern recognition problem. In this thesis, we explore a novel interpolation based framework to address some of the various recognition problems in these areas. Our interpolation based framework is a supervised learning algorithm that allows for both generation (synthesis) of new patterns as well as perception (analysis) of existing patterns. The method is simple to implement and yet, expects a very straightforward and intuitive set of parameters to model the complex nature of such recognition problems.Specifically, given a set of training data along …