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Articles 91 - 120 of 365
Full-Text Articles in Computer Sciences
Claimportal: Building A Social Media Analytics System For Assisting Fact-Checking, Sarthak Majithia
Claimportal: Building A Social Media Analytics System For Assisting Fact-Checking, Sarthak Majithia
Computer Science and Engineering Theses - Archive
We are in a digital era where claims made by people can attract attention and spread like wildfire. Misinformation and disinformation about important social and political issues can be intentional and motive can be malicious. Thus, we built a Twitter monitoring platform, namely, ClaimPortal. It assists its users by searching, checking, and providing analytics of factual claims made by politicians and influential people on Twitter. ClaimPortal empowers users with a search API which enables filtering conditions such as date range, tweets from/mentioning specific users, keyword based search, hashtags, check-worthiness scores, and types of claims. We explain the architecture of ClaimPortal …
Deepsign: A Deep-Learning Architecture For Sign Language, Jai Amrish Shah
Deepsign: A Deep-Learning Architecture For Sign Language, Jai Amrish Shah
Computer Science and Engineering Theses - Archive
Sign languages are used by deaf people for communication. In sign languages, humans use hand gestures, body, facial expressions and movements to convey meaning. Humans can easily learn and understand sign languages, but automatic sign language recognition for machines is a challenging task. Using recent advances in the field of deep-learning, we introduce a fully automated deep-learning architecture for isolated sign language recognition. Our architecture tries to address three problems: 1) Satisfactory accuracy with limited data samples 2) Reducing chances of over-fitting when the data is limited 3) Automating recognition of isolated signs. Our architecture uses deep convolutional encoder-decoder architecture …
Classification Of Clinical Narratives Using Convolutional Neural Network, Nikit Rajiv Lonari
Classification Of Clinical Narratives Using Convolutional Neural Network, Nikit Rajiv Lonari
Computer Science and Engineering Theses - Archive
Patient safety is a key aspect for good consumer care. When an individual is hospitalized or receives medication the family wants the patient safety to be above all factors. For instance, a drug can do both either cure the disease or perhaps, give rise to an adverse event. A drug administered for an indicated condition has substantial power to reduce or cure a disease and further to prevent it from happening again in the future but at the risk of side effects. At present, there are several methods in patient safety and in particular in the area of signal detection …
Towards End-To-End Semi-Supervised Deep Learning For Drug Discovery, Xiaoyu Zhang
Towards End-To-End Semi-Supervised Deep Learning For Drug Discovery, Xiaoyu Zhang
Computer Science and Engineering Theses - Archive
Observing the recent progress in Deep Learning, the employment of AI is surging to accelerate drug discovery and cut R&D costs in the last few years. However, the success of deep learning is attributed to large-scale clean high-quality labeled data, which is generally unavailable in drug discovery practices. In this thesis, we address this issue by proposing an end-to-end deep learning framework in a semi supervised learning fashion. That is said, the proposed deep learning approach can utilize both labeled and unlabeled data. While labeled data is of very limited availability, the amount of available unlabeled data is generally huge. …
Dwrelu : Double Weighted Rectifier Linear Unit An Activation Function With Trainable Scaling Parameter, Bhaskar Chandra Trivedi
Dwrelu : Double Weighted Rectifier Linear Unit An Activation Function With Trainable Scaling Parameter, Bhaskar Chandra Trivedi
Computer Science and Engineering Theses - Archive
Deep Neural Network have become very popular for computer vision application in recent years. At the same time, it remains important to understand the different implementation choices that need to be made when designing a neural network and to thoroughly investigate existing and novel alternatives for those choices. One of those choices is the activation function. The ReLU activation function is a widely used activation function. It discards all the values below zero and keeps the ones greater than zero. Variations such as Leaky ReLU and Parametric ReLU do not discard values, so that gradiants are nonzero for the entire …
Health Monitoring Of Atlas Data Center Clusters And Failure Analysis, Meenakshi Balasubramanian
Health Monitoring Of Atlas Data Center Clusters And Failure Analysis, Meenakshi Balasubramanian
Computer Science and Engineering Theses - Archive
Monitoring the health of data center clusters is an integral part of any industrial facility. ATLAS is one of the High Energy Physics experiments at the Large Hadron Collider (LHC) at CERN. ATLAS DDM (Distributed Data Management) is a system that manages data transfer, staging, deletions and experimental data on the LHC grid. Currently, the DDM system relies on Rucio software, with Cloud based object storage and No-SQL solutions. It is a cumbersome process in the current system, to fetch and analyze the transfer, staging and deletion metrics of a specific site for any regional center. In this thesis, a …
Monitoring Of Swt2 Data Clusters For The Atlas Experiment, Antara Ray
Monitoring Of Swt2 Data Clusters For The Atlas Experiment, Antara Ray
Computer Science and Engineering Theses - Archive
Monitoring of the South West Tier 2 RSEs is done by CERN with the help of Rucio. The challenge faced by the team monitoring the servers at the University of Texas site was that the monitoring data is pictorially represented and provided to them in GIF format. In this work we focus on creating an interactive site that will not only monitor the data at the local RSEs but also create a platform to analyze the data storage systems. It turn it will also create alerts whenever during monitoring an aberration from expected behavior is noticed either in the storage …
Topological And Feature Based Identification Of Hole Boundaries In Point Cloud Data And Differentiation Between Surface And Physical Holes, Aaqif Muhtasim
Topological And Feature Based Identification Of Hole Boundaries In Point Cloud Data And Differentiation Between Surface And Physical Holes, Aaqif Muhtasim
Computer Science and Engineering Theses - Archive
With the advent of autonomous agents becoming prominent in everyday lives, the importance of processing the surroundings into understandable features becomes more and more important. 3D point clouds play a major role in the perception of such agents and thus having the ability to correctly decipher features from point clouds is crucial to the planning of actions that the agent would need to undertake. This thesis analyzes holes found in point clouds. Based on two approaches that center around topological data analysis and local point set features respectively. It studies how each of the methods works and how a combination …
Generating An Adaptive Path Using Rrt Sampling And Potential Functions With Directional Nearest Neighbors, Sandeep Chahal
Generating An Adaptive Path Using Rrt Sampling And Potential Functions With Directional Nearest Neighbors, Sandeep Chahal
Computer Science and Engineering Theses - Archive
Planning algorithms have attained omnipresent successes in several fields including robotics, animation, manufacturing, drug design, computational biology and aerospace applications. Path Planning is an essential component for autonomous robots. The problem involves searching the configuration space and constructing a desired collision-free path that connects two states (the start and the goal) for a robot to gradually navigate from one state to another. In global path planners, the complete path is computed prior to the robot set off. Sampling based planning like Rapidly Expanding Random Trees (RRT) and Probabilistic Road Maps (PRM) used for single or multi-query planning has gained popularity …
Text Mining On Twitter Data To Evaluate Sentiment, Srijanee Niyogi
Text Mining On Twitter Data To Evaluate Sentiment, Srijanee Niyogi
Computer Science and Engineering Theses - Archive
Social media platforms have been a major part of our daily lives. But with the freedom of expression there is no way one can check whether the posts/tweets/expressions are classified on which polarity. Since Twitter is one of the biggest social platforms for microblogging, hence the experiment was done on this platform. There are several topics that are popular over the internet like sports, politics, finance, technology are chosen as the source of the experiment. These tweets were collected over a span of time for more than 2 months via a cron job. Every tweet can be divided into three …
Malware Early-Stage Detection Using Machine Learning On Hardware Performance Counters, Anchal Raheja
Malware Early-Stage Detection Using Machine Learning On Hardware Performance Counters, Anchal Raheja
Computer Science and Engineering Theses - Archive
Systems affected by Malware in the past 10 years has risen from 29 million to 780 million, which tells us it’s a rapidly growing threat. Viruses, ransomware, worms, backdoors, botnets etc. all come under malware. Ransomware alone is predicted to cost $11.5 billion in 2019. As the downtime and financial damages are rising the researchers are finding new ways to tackle this threat. However, the usual approach is prone to high false positive rate or delayed detection rate. This research explores a dynamic approach for early-stage malware detection by modeling it’s behavior using hardware performance counters with low overhead. The …
Finding Representative Entities From Entity Graph By Using Neighborhood Based Entity Similarity, Ankit Anil Shingavi
Finding Representative Entities From Entity Graph By Using Neighborhood Based Entity Similarity, Ankit Anil Shingavi
Computer Science and Engineering Theses - Archive
Several applications deploy the use of large entity graphs. Given the entirety of its application scope, it is challenging to select a single entity graph for a particular need from numerous data sources. For a comprehensible overview of the entity graph, we may project a preview table for compact representation of an entity graph. Each preview table represents a single entity type in the dataset. We need to find the representative entities for a given entity type from the entity graph to show the coverage of a dataset. In this paper, we propose a method to find representative entities for …
Improving Time And Space Efficiency Of Trie Data Structure, Nirmik Milind Kale
Improving Time And Space Efficiency Of Trie Data Structure, Nirmik Milind Kale
Computer Science and Engineering Theses - Archive
Trie or prefix tree is a data structure that has been used widely in some applications such as prefix-matching, auto-complete suggestions, and IP routing tables for a long time. What makes tries even more interesting is that its time complexity is dependent on the length of the keys inserted or searched in the trie, instead of on the total number of keys in the data structure. Tries are also strong contenders to consider against hash tables in various applications due to two reasons - their almost deterministic time complexity based on average key length, especially when using large number of …
Face Detection And Recognition Using Moving Window Accumulator With Various Deep Learning Architecture, Anil Kumar Nayak
Face Detection And Recognition Using Moving Window Accumulator With Various Deep Learning Architecture, Anil Kumar Nayak
Computer Science and Engineering Theses - Archive
Recent advancement in the field of Computer Vision and Deep Learning is making object detection and recognition easier. Hence, growing research activities in the field of deep learning are enabling researchers to find new ideas in the area of face detection and recognition. Implementation of such systems has a number of challenges when it comes to the current approaches. In this paper, we have presented a system of Face Detection and Recognition with newly designed deep learning classification models like CNN, Inception and various state of art models like SVM and we also compared the result with FaceNet. Multiple approaches …
Design Of Haptically Enabled Wheelchair For Assistive Autonomy, Arjun Mani Gupta
Design Of Haptically Enabled Wheelchair For Assistive Autonomy, Arjun Mani Gupta
Computer Science and Engineering Theses - Archive
The first records of wheeled seats being used for transporting disabled people date to 8th century in China, however the wheelchair has evolved tremendously since its inception. An electric-powered wheelchair, commonly called a "powerchair" is a wheelchair which incorporates batteries and electric motors into the frame, and so it can be controlled by either the user or an attendant. This control is most commonly done via a small joystick mounted on the armrest, or on the upper rear of the frame. For users who cannot manage a manual joystick, head-switches, chin-operated joysticks, sip-and-puff controllers or other custom controls may allow …
Mavvstream: Expressing And Processing Situations On Videos Using The Stream Processing Paradigm, Mayur Arora
Mavvstream: Expressing And Processing Situations On Videos Using The Stream Processing Paradigm, Mayur Arora
Computer Science and Engineering Theses - Archive
Image and Video Analysis (IVA) has been ongoing for several decades and has come up with impressive techniques for object identification, re-identification, activity detection etc. A large number of techniques have been developed and used for processing video frames to detect objects and situations from videos. Camera angles, lighting effect, color differences, and attire make it difficult to analyze videos. Several approaches for searching, and querying videos and images have been developed using indexing and other techniques. This thesis takes a novel approach by converting a video (through extraction of its contents) into a representation over which queries can be …
From Text Classification To Image Clustering, Problems Less Optimized, Amirhossein Herandi
From Text Classification To Image Clustering, Problems Less Optimized, Amirhossein Herandi
Computer Science and Engineering Theses - Archive
Machine Learning is thriving. Every industry is using its techniques in some way to improve their efficiency and revenue. However, the focus on research is not divided equally between all of the different areas and problems that this field can tackle and analyze. Currently, Computer Vision is the one area that is being focused very extensively by researchers and companies alike, and as a result has seen an amazing boost in the recent years. This ranges from the well-known problems of classification that use discriminative models all the way to more novel problems that use generative models such as style …
Learning To Generate Individual Data Sequence From Population Statistics Using Dynamic Bayesian Networks, Mohammed Azmat Qureshi
Learning To Generate Individual Data Sequence From Population Statistics Using Dynamic Bayesian Networks, Mohammed Azmat Qureshi
Computer Science and Engineering Theses - Archive
Data collection rose exponentially with the dawn of the 21st Century, However the most important data to humans, individual health data, is difficult to get approved for public research, as medical history is very sensitive to be distributed. The only available public data which can be retrieved from institutions like the Centre for Disease Control (CDC), World Health Organization (WHO), National Health Interview Survey (NHIS), etc. largely only contain population statistics for different attributes of a person.What we propose here is a generative model which would learn to create data sequences for a population, each sequence mimicking an individual person’s …
Jsspe: A Symbolic Partial Evaluator For Javascript, Sumeyye Suslu
Jsspe: A Symbolic Partial Evaluator For Javascript, Sumeyye Suslu
Computer Science and Engineering Theses - Archive
Currently, JavaScript is one of the mostly used programming languages for Web and Mobile platforms. This brings a large demand for optimization and smarter resource allocation of the applications written in JavaScript. Partial evaluation is a program transformation technique which rewrites a program by evaluating it with respect to its known variables. Recently, Facebook proposed Prepack: A partial evaluator for JavaScript which will make original program shorter and faster by performing both concrete and symbolic evaluation (concolic evaluation). Although it is proposed as a planned improvement, symbolic evaluation engine currently does not implement an SMT solver. In this work, a …
Enabling Third Party Services Over Deep Web Databases And Location Based Services, Yeshwanth Durairaj Gunasekaran
Enabling Third Party Services Over Deep Web Databases And Location Based Services, Yeshwanth Durairaj Gunasekaran
Computer Science and Engineering Theses - Archive
Deep web databases are pillars of today’s internet services hidden behind HTML forms and Top-K search interfaces. While Top-K search interfaces provide a good way to retrieve information, it still lacks in addressing the diverse preferences of the users. Due to query rate limit constraint - i.e., maximum number of k-Nearest Neighbors queries a user/IP address can issue over a specific period of time, it is often impossible to access all the tuples in backed database. With the query rate limit constraint in mind, our motivation is twofold (i) Enable users to obtain individual records from these databases and rank …
Crypto Ransomware Analysis And Detection Using Process Monitor, Ashwini Balkrushna Kardile
Crypto Ransomware Analysis And Detection Using Process Monitor, Ashwini Balkrushna Kardile
Computer Science and Engineering Theses - Archive
Ransomware is a faster growing threat that encrypts user’s files and locks the computer and holds the key required to decrypt the files for ransom. Over the past few years, the impact of ransomware has increased exponentially. There have been several reported high profile ransomware attacks, such as CryptoLocker, CryptoWall, WannaCry, Petya and Bad Rabbit which have collectively cost individuals and companies well over a billion dollars according to FBI. As the threat of ransomware has become more prevalent, security companies and researchers have begun proposing new approaches for detection and prevention of ransomware. However, these approaches generally lack dynamicity …
Scalable Conversion Of Textual Unstructured Data To Nosql Graph Representation Using Berkeley Db Key-Value Store For Efficient Querying, Jasmine Manoj Varghese
Scalable Conversion Of Textual Unstructured Data To Nosql Graph Representation Using Berkeley Db Key-Value Store For Efficient Querying, Jasmine Manoj Varghese
Computer Science and Engineering Theses - Archive
Graph database is a popular choice for representing data with relationships. It facilitates easy modifications to the relational information without the need for structural redefinition, as in case of relational databases. Exponentially growing graph sizes demand efficient querying, memory limitations notwithstanding. Use of indexes, to speed up query processing, is integral to databases. Existing works have used in-memory approaches that were limited by the main memory size. This thesis proposes a way to use graph representation, indexing technique and secondary memory to efficiently answer queries. Textual unstructured data is parsed to identify entities and assign unique identification. The entities and …
Portable Wireless Antenna Sensor For Simultaneous Shear And Pressure Monitoring, Farnaz Farahanipad
Portable Wireless Antenna Sensor For Simultaneous Shear And Pressure Monitoring, Farnaz Farahanipad
Computer Science and Engineering Theses - Archive
Microstrip antenna-sensor has received considerable interests in recent years due to its simple configuration, compact size, and multi-modality sensitivity. Having a simple and conformal planar configuration, antenna-sensor can be easily attached on the structure surface for Structure Health Monitoring (SHM). As a promising sensor, the resonant frequency of the antenna-sensor is sensitive to different structure properties: such as planar stress, temperature, moisture, pressure and shear. As a passive antenna, antenna-sensor’s resonant frequency can be wirelessly interrogated at a middle range distance without using an on-board battery. However, a major challenge of antenna-sensor’s wireless interrogation is to isolate the antenna backscattering …
Social Coding Standards On Touchdevelop: An Empirical Study, Shivangi Kulshrestha
Social Coding Standards On Touchdevelop: An Empirical Study, Shivangi Kulshrestha
Computer Science and Engineering Theses - Archive
This study compares and contrasts the application development pattern on Microsoft’s mobile application development platform with leading version control and social coding sites like Github. TouchDevelop is an in-browser editor for developing mobile applications with the main aim to concentrate on ‘touch’ as the only input. Apart from being the first of it’s kind platform, TouchDevelop also allows users to upload their script directly to cloud. This is what makes this study interesting, since the API data of the app has never been studied before to follow social coding standards or version control techniques. Till today, all major IDEs, e.g …
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 …
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 …
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 …