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Articles 271 - 300 of 666
Full-Text Articles in Computer Sciences
Maximizing Code Coverage In Database Applications, Tulsi Chandwani
Maximizing Code Coverage In Database Applications, Tulsi Chandwani
Computer Science and Engineering Theses - Archive
A database application takes input as user-defined queries and determines the program logic to be executed based on the results returned by the queries. A change in existing application or a new application is expected pass through extensive testing to cover the entire code and check all the cases possible in execution. Testing the code coverage of traditional or CRUD-based applications is a straightforward process backed by various tools and libraries. Unlike traditional applications, checking the code coverage of database applications is a complex procedure due to its inherent structure and the inputs passed to it. Measuring the code coverage …
Visual Logging Framework Using Elk Stack, Ravi Nishant
Visual Logging Framework Using Elk Stack, Ravi Nishant
Computer Science and Engineering Theses - Archive
Logging is the process of storing information for future reference and audit purposes. In software applications, logging plays a very critical role as a development utility and ensures code quality. It acts as an enabler for developers and support professionals by providing them capability to see application’s functionality and understand any issues with it. Data logging has a widespread use in scientific experiments and analytical systems. Major systems which heavily uses data logging are weather reporting services, digital advertisement, search engines, space exploration systems to name a few. Although, data logging increases the productivity and efficiency of a software system, …
Igait: Vision-Based Low-Cost, Reliable Machine Learning Framework For Gait Abnormality Detection, Saif Sayed
Igait: Vision-Based Low-Cost, Reliable Machine Learning Framework For Gait Abnormality Detection, Saif Sayed
Computer Science and Engineering Theses - Archive
Human gait has shown to be a strong indicator of health issues under a wide variety of conditions. For that reason, gait analysis has become a powerful tool for clinicians to assess functional limitations due to neurological or orthopedic conditions that are reflected in gait. Therefore, accurate gait monitoring and analysis methods have found a wide range of applications from diagnosis to treatment and rehabilitation. This thesis focuses on creating a low-cost and non-intrusive vision-based machine learning framework dubbed as iGait to accurately detect CLBP patients using 3-D capturing devices such as MS Kinect. To analyze the performance of the …
Frameworks, Algorithms, And Systems For Efficient Discovery Of Data-Backed Facts, Gensheng Zhang
Frameworks, Algorithms, And Systems For Efficient Discovery Of Data-Backed Facts, Gensheng Zhang
Computer Science and Engineering Dissertations - Archive
This thesis studies the problem of finding facts from semi-structured and structured data. The amount of data in our world is exploding, and the proliferation of data is making them increasingly inaccessible. It is now more challenging than ever how to efficiently identify useful information where a vast amount of data is available. This thesis first studies the problem of finding facts in semi-structured data, specifically, in knowledge graphs. We built Maverick, a general, extensible framework that discovers exceptional facts about entities in knowledge graphs. We model an exceptional fact about an entity of interest as a context-subspace pair, in …
On The Influence Of Spatio-Temporal Analysis On Clustering And Recommendation, Madhuri Debnath
On The Influence Of Spatio-Temporal Analysis On Clustering And Recommendation, Madhuri Debnath
Computer Science and Engineering Dissertations - Archive
In this dissertation, we propose efficient frameworks to analyze spatio-temporal data. In the first part of the dissertation, we use a clustering based method to mine useful information from trajectory data. Existing trajectory clustering algorithms have focused on geometric properties and spatial features of trajectories. In contrast to existing algorithms, we propose a new framework to cluster sub-trajectories based on a combination of spatial and non-spatial features. In the second part of dissertation, we propose a unified framework to build recommendation systems by analyzing human movement data. We propose recommendation frameworks to recommend POI locations and travel routes that use …
Evaluation Of A Factual Claim Classifier With And Without Using Entities As Features, Abu Ayub Ansari Syed
Evaluation Of A Factual Claim Classifier With And Without Using Entities As Features, Abu Ayub Ansari Syed
Computer Science and Engineering Theses - Archive
Fact-checking in real-time for events such as presidential debates is a challenging task. These fact-checking processes have a difficult and rigorous task in having the best accuracy in classifying facts, finding topics, etc. The first and foremost task in fact-checking is to find out whether a sentence is factually check-worthy. The UTA IDIR Lab has deployed an automated fact-checking system named ClaimBuster. ClaimBuster has a core functionality of identifying check-worthy factual sentences. Named entities are essentially an important component of any textual data. To use these named entities, it is required to link them to labels such as a person, …
Deep Learning Based Multi-Label Classification For Surgical Tool Presence Detection In Laparoscopic Videos, Ashwin Raju
Deep Learning Based Multi-Label Classification For Surgical Tool Presence Detection In Laparoscopic Videos, Ashwin Raju
Computer Science and Engineering Theses - Archive
Laparoscopic surgery, Modern surgery, where the surgery is performed far away from the patient by inserting small incisions on the patient's body and the surgery is performed with a help of a video recorder and through which the doctor performs the surgery. The computer assisted intervention are increasing exponentially and the need for accurate and reliable intervention is very important because of the domain which is very critical. Efforts have made to develop a system that is both fast and accurate approach but it is still an active area of research due its importance. Some applications which involve identifying the …
An Intelligent Multimodal Upper-Limb Rehabilitation Robotic System, Alexandros Lioulemes
An Intelligent Multimodal Upper-Limb Rehabilitation Robotic System, Alexandros Lioulemes
Computer Science and Engineering Dissertations - Archive
A traffic accident, a battlefield injury, or a stroke can lead to brain or musculoskeletal injuries that impact motor and cognitive functions and can drastically change a person's life. In such situations, rehabilitation plays a critical role in the ability of the patient to partially or totally regain motor function, but the optimal training approach remains unclear. Robotic technologies are recognized as powerful tools to promote neuroplasticity and stimulate motor re-learning. Moreover, they deliver high-intensity, repetitive, active and task-oriented training; in addition, they provide objective measurements for patient evaluation. The primary focus of this research is to investigate the development …
Performance Analysis Of Scale-Out Workloads On Parallel And Distributed Systems, Minh Quang Nguyen
Performance Analysis Of Scale-Out Workloads On Parallel And Distributed Systems, Minh Quang Nguyen
Computer Science and Engineering Dissertations - Archive
Scale-out applications have emerged to be the predominant datacenter workloads. The request processing workflow for such a workload may consist of one or more stages with massive numbers of compute nodes for parallel data-intensive processing. As a classic model for the most essential building block of a workflow, the Fork-Join queuing network model is found to be notoriously hard to solve due to the involvement of task partitioning and merging with barrier synchronization. The work in this dissertation aims to develop approximation methods for the prediction of tail and mean latency for Fork-Join queuing networks in a high load region, …
Neural Image And Video Understanding, Rasool Fakoor
Neural Image And Video Understanding, Rasool Fakoor
Computer Science and Engineering Dissertations - Archive
Even though recent works on neural architectures have shown promising results at tasks like image recognition, object detection, playing Atari games, etc., learning a mapping from a visual space to a language space or vice versa remains challenging in problems like image/video captioning or question-answering tasks. Furthermore, transferring knowledge between seen and unseen classes in a setting like zero-shot learning is quite challenging given the fact that a model should be able to make a prediction for novel test data belonging to classes for which no examples have been seen during training. To address these issues, this dissertation will first …
Integration Of Multimodal Sensor Data For Targeted Assessment And Intervention, Shawn N. Gieser
Integration Of Multimodal Sensor Data For Targeted Assessment And Intervention, Shawn N. Gieser
Computer Science and Engineering Dissertations - Archive
Physical and Occupational Therapy have been used for many years to help people who have suffered an injury of some kind. This injury could be caused by a physical injury, such as falling or breaking a bone, or a brain injury, such as a stroke. Traditional interventions involve having a therapist watch a patient perform any prescribed interventions to see if they are done correctly and to assess progress, or to have a patient perform exercises at home unsupervised. Patients, once discharged, do not always adhere to the prescribed intervention. They begin to not keep scheduled appointments and not complete …
Stateful Detection Of Stealthy Behaviors In Android Apps, Mohsin Junaid
Stateful Detection Of Stealthy Behaviors In Android Apps, Mohsin Junaid
Computer Science and Engineering Dissertations - Archive
The number of smartphones has increased greatly during the last few years. Among the popular mobile operating systems (such as iOS and Android) installed on these devices, Android captures most of the mobile market share. This also puts Android OS in a spotlight to attract malware attacks. A recent study shows that for the last two years, more than ~99% of the mobile malware targeted Android OS. Examples of such attacks are leakage of privacy-sensitive data available on the devices (such as phone number, contacts, photos, and SMS and call logs), recording audio and video files, silently making phone calls …
A Study Of Using Multiple Cues To Aid People With Learning Disabilities In Learning System-Assigned Passwords, Sonali Tukaram Marne
A Study Of Using Multiple Cues To Aid People With Learning Disabilities In Learning System-Assigned Passwords, Sonali Tukaram Marne
Computer Science and Engineering Theses - Archive
Traditional user-chosen passwords often offer weak password security and are prone to password reuse and password patterns whereas system-assigned passwords are secure but fail to provide sufficient memorability. LDs are problems that affect the brain’s ability to receive, process, analyze and store information, i.e. they are disorders of neurologically-based processing. These problems can make it difficult for an individual to learn as quickly and accurately as someone who isn’t affected with learning disabilities. Learning disability cannot be cured or fixed but may make it hard to learn and use passwords. With right assistance and with unique learning strategies, we may …
Inferring In-Screen Animations And Inter-Screen Transition From User Interface Screenshots, Siva Natarajan Balasubramania
Inferring In-Screen Animations And Inter-Screen Transition From User Interface Screenshots, Siva Natarajan Balasubramania
Computer Science and Engineering Theses - Archive
In practice, many companies have adopted the concept of creating interactive prototypes for explaining workflows and animations. Designing and developing a user interface is a time-consuming process, and the user experience of the application has a major impact on the success of the application itself. User interface designing marks the start of the app development, and it is very expensive regarding cost and time for making any modification after the coding phase kicks in. Currently, companies have adopted UI prototyping as part of the app development process. Third-party tools like Flinto or Invision use the high fidelity screen designs for …
A Deep Learning Based Pipeline For Metastatic Breast Cancer Classification From Whole Slide Images (Wsi), Arjun Punabhai Vekariya
A Deep Learning Based Pipeline For Metastatic Breast Cancer Classification From Whole Slide Images (Wsi), Arjun Punabhai Vekariya
Computer Science and Engineering Theses - Archive
Pathology is a 150-year-old medical specialty that has seen a paradigm shift over the past few years with the advent of Digital Pathology. Digital Pathology is a very promising approach to diagnostic medicine to accomplish better, faster and cheaper diagnosis, prognosis and prediction of cancer and other important diseases. Historical approaches in Digital Pathology have focused primarily on low-level image analysis tasks (e.g., color normalization, nuclear segmentation, and feature extraction) hence they are not generalized, thus not useful for practical use in clinical practices. In this thesis, a general Deep Learning based classification pipeline for identifying cancer metastases from histological …
Activity Detection And Classification On A Smart Floor, Anil Kumar Mullapudi
Activity Detection And Classification On A Smart Floor, Anil Kumar Mullapudi
Computer Science and Engineering Theses - Archive
Detecting and analyzing human activities in the home has the potential to improve monitoring of the inhabitants' health especially for elderly people. There are many approaches to detect and categorize human activities that have been applied to data from several devices such as cameras and tactile sensors. However, use of these sensors is not feasible in many places due to security and privacy concerns or because of users who may not be able to attach sensor to their body. Some of these issues can be addressed using less intrusive sensors such as a smart floor. A smart floor setup allows …
A Parallel Implementation Of Apriori Algorithm For Mining Frequent Itemsets In Hadoop Mapreduce Framework, Gokarna Neupane
A Parallel Implementation Of Apriori Algorithm For Mining Frequent Itemsets In Hadoop Mapreduce Framework, Gokarna Neupane
Computer Science and Engineering Theses - Archive
With explosive growth of data in past few years, discovering previously unknown, frequent patterns within the huge transactional data sets has been one of the most challenging and ventured fields in data mining. Apriori algorithm is widely used and one of the most researched field for frequent pattern mining. The exponential increase in the size of the input data has adverse effect on the efficiency of the traditional or centralized implementation of this algorithm. Thus, various distributed Frequent Itemset Mining(FIM) algorithms have been developed. MapReduce is a programming framework that allows the processing of large datasets with a distributed algorithm …
Person Identification And Anomaly Detection Using Gait Parameters Extracted From Time Series Data, Suhas Mandikal Rama Krishna Reddy
Person Identification And Anomaly Detection Using Gait Parameters Extracted From Time Series Data, Suhas Mandikal Rama Krishna Reddy
Computer Science and Engineering Theses - Archive
Gait generally refers to the style of walk and is influenced by a number of parameters and conditions. In particular, chronic and temporary health conditions often influence gait patterns. As such conditions increase with age, changes in gait pattern and gait disorders become more common. Changes in the walking pattern in the elderly can suggest neurological problems or age related problems that influence the walk. For example, individuals with parkinsonian and vascular dementias generally display gait disorders. Similarly, short term changes in muscle tone, strength, and overall condition can reflect in gait parameters. Analysis of the gait for abnormal walk …
A Probabilistic Approach To Crowdsourcing Pareto-Optimal Object Finding By Pairwise Comparisons, Nigesh Shakya
A Probabilistic Approach To Crowdsourcing Pareto-Optimal Object Finding By Pairwise Comparisons, Nigesh Shakya
Computer Science and Engineering Theses - Archive
This is an extended study on crowdsourcing Pareto-Optimal Object Finding by Pairwise Comparisons. The prior study on the same topic demonstrate the framework and algorithms used to determine all the Pareto-Optimal objects with the goal of asking the fewest possible questions to the crowd. One of the drawbacks in that approach is it fails to incorporate every inputs given by the crowd and is biased towards the majority. We have developed an approach which represent the inputs provided by users as probabilistic values rather than a concrete one. The goal of this study is to find the ranks of the …
Crowdsourcing For Decision Making With Analytic Hierarchy Process, Ishwor Timilsina
Crowdsourcing For Decision Making With Analytic Hierarchy Process, Ishwor Timilsina
Computer Science and Engineering Theses - Archive
Analytic Hierarchy Process (AHP) is a Multiple-Criteria Decision-Making MCDM) technique devised by Thomas L. Saaty. In AHP, all the pairwise comparisons between criteria and alternatives in terms of each criterion are used to calculate global rankings of the alternatives. In the classic AHP, the comparisons are provided collectively by a small group of decision makers. We have formulated a technique to incorporate crowd-sourced inputs into AHP. Instead of taking just one comparison for each pair of criteria or alternatives, multiple users are asked to provide inputs. As in AHP, our approach also supports consistency check of the comparison matrices. The …
Auto-Roi System: Automatic Localization Of Roi In Gigapixel Whole-Slide Images, Shirong Xue
Auto-Roi System: Automatic Localization Of Roi In Gigapixel Whole-Slide Images, Shirong Xue
Computer Science and Engineering Theses - Archive
Digital Pathology is a very promising approach to diagnostic medicine to accomplish better, faster prognosis and prediction of cancer. The high-resolution whole slide imaging (WSI) can be analyzed on any computer, easily stored, and quickly shared. However, a digital WSI is quite large, like over 1M pixels by 1M pixels (3TB), depending on the tissue and the biopsy type. Automatic localization of regions of interest (ROIs) is important because it decreases the computational load and improves the diagnostic accuracy. Some popular applications in the market already support in viewing and marking the ROIs, such as ImageScope, OpenSlide, and ImageJ. However, …
An Mrql Visualizer Using Json Integration, Rohit Bhawal
An Mrql Visualizer Using Json Integration, Rohit Bhawal
Computer Science and Engineering Theses - Archive
In today’s world where there is no limit to the amount of data being collected from IOT devices, social media platforms, and other big data applications, there is a need for systems to process them efficiently and effortlessly. Analyzing the data to identify trends, detect patterns and find other valuable information is critical for any business application. The analyzed data when produced in visual format like graphs, enables one to grasp difficult concepts or identify new patterns easily. MRQL is an SQL-like query language for large scale data analysis built on top of Apache Hadoop, Spark, Flink and Hama which …
Learning From Wizard-Of-Oz Using Dynamic User Modeling, Tasnim Inayat Makada
Learning From Wizard-Of-Oz Using Dynamic User Modeling, Tasnim Inayat Makada
Computer Science and Engineering Theses - Archive
Socially assistive robotics (SAR) is a field of study that combines assistive robotics with socially interactive robotics where the goal of the robot is to provide assistance to human users through social interaction. The effectiveness of a SAR system basically depends on the user’s engagement in the interaction and the level of autonomy obtained by the system such that it requires no human intervention. The focus of this thesis is to build a SAR system that progressively learns to make autonomous decisions in an online manner, based on human input. An expert/therapist provides guidance to the system during the interaction …
Software Defined Load Balancing Over An Openflow-Enabled Network, Deepak Verma
Software Defined Load Balancing Over An Openflow-Enabled Network, Deepak Verma
Computer Science and Engineering Theses - Archive
In this modern age of the Internet, the amount of data flowing through networking channels has exploded exponentially. The network services and routing mechanism affect the scalability and performance of such networks. Software Defined Networks (SDN) is an upcoming network model which overcomes many challenges faced by traditional approaches. The basic principle of SDN is to separate the control plane and the data plane in network devices such as router and switches. This separation of concern allows a central controller to make the logical decisions by having an overall map of the network. SDN makes the network programmable and agile …
Divide And Conquer Approach To Scalable Substructure Discovery: Partitioning Schemes, Algorithms, Optimization And Performance Analysis Using Map/Reduce Paradigm, Soumyava Das
Computer Science and Engineering Dissertations - Archive
With the proliferation of applications rich in relationships, graphs are becoming the preferred choice of data model for representing/storing data with relationships. The notion of "information retrieval'' and "information discovery" in graphs has acquired a completely new connotation and are currently being applied to a wide range of contexts ranging from social networks, chemical compounds, telephone networks to transactional networks. From the point of view of an end user, one of the most important aspects on graphs is to discover recurrent patterns following user-defined parameters. Finding frequent patterns play an important role in mining associations, correlations and many other interesting …
Machine Learning: Several Advances In Linear Discriminant Analysis, Multi-View Regression And Support Vector Machine, Shuai Zheng
Machine Learning: Several Advances In Linear Discriminant Analysis, Multi-View Regression And Support Vector Machine, Shuai Zheng
Computer Science and Engineering Dissertations - Archive
Machine learning technology is now widely used in engineering, science, finance, healthcare, etc. In this dissertation, we make several advances in machine learning technologies for high dimensional data analysis, image data classification, recommender systems and classification algorithms. In this big data era, many data are high dimensional data which is difficult to analyze. We propose two efficient Linear Discriminant Analysis (LDA) based methods to reduce data to low dimensions. Kernel alignment measures the degree of similarity between two kernels. We propose kernel alignment inspired LDA to find a subspace to maximize the alignment between subspace-transformed data kernel and class indicator …
Video-Based Face Recognition Using Deep Learning For Single Sample Per Person (Sspp) Surveillance Applications, Mostafa Parchami
Video-Based Face Recognition Using Deep Learning For Single Sample Per Person (Sspp) Surveillance Applications, Mostafa Parchami
Computer Science and Engineering Dissertations - Archive
Face Recognition (FR) is the task of identifying a person based on images of the face of the identity. Systems for video-based face recognition in video surveillance seek to recognize individuals of interest in real-time over a distributed network of surveillance cameras. These systems are exposed to challenging unconstrained environments, where the appearance of faces captured in videos varies according to pose, expression, illumination, occlusion, blur, scale, etc. In addition, facial models for matching must be designed using a single reference facial image per target individual captured from a high-quality still camera under controlled conditions. Deep learning has shown great …
Automated Systems For Testing Android Applications To Detect Sensitive Information Leakage, Sarker Tanveer Ahmed Rumee
Automated Systems For Testing Android Applications To Detect Sensitive Information Leakage, Sarker Tanveer Ahmed Rumee
Computer Science and Engineering Dissertations - Archive
Smart phones have become an important daily companion and often used by users to store various private data such as contacts, photos, messages, various social network accounts etc. Users can furthermore extend the functionality of their phone by downloading applications (or apps) from various developers and online application stores. However, apps may misuse the data stored on the phone or obtained from the sensors and users do not have any direct means to track that. Hence, the need for improved mechanisms to better manage the privacy of user data is very important. There has been a lot of effort to …
Crowd Data Analytics And Optimization, Habibur Rahman
Crowd Data Analytics And Optimization, Habibur Rahman
Computer Science and Engineering Dissertations - Archive
Crowdsourcing can be defined as outsourcing with crowd, where crowd refers to the online workers who are willing to complete simple tasks for small monetary compensation. The overwhelming reach of internet has enabled us to exploit crowd in an unprecedented way. Crowdsourcing, nowadays, is considered as a tool to solve both simple tasks (such as labeling ground truth, image recognition etc.) and complex tasks (such as collaborative writing, citizen journalism etc.). Furthermore, it is also used to solve computational problems such as Entity Resolution, Top-k, Group-by etc. While crowdsourcing provides us with plenty of opportunities, it also presents us with …
Predicting Human Behavior Based On Survey Response Patterns Using Markov And Hidden Markov Models, Arun Kumar Pokharna
Predicting Human Behavior Based On Survey Response Patterns Using Markov And Hidden Markov Models, Arun Kumar Pokharna
Computer Science and Engineering Theses - Archive
With technological advancements in World Wide Web (www), connecting with people for gathering information has become common. Among several ways, surveys are one of the most commonly used way of collecting information from people. Given a specific objective, multiple surveys are conducted to collect various pieces of information. This collected information, in the form of survey responses, can be categorical values or a descriptive text that represents information regarding the survey question. If additional details regarding the response behavior, scenario in which survey is being responded, or survey outcomes is available, machine learning and prediction modeling can be used to …