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Articles 451 - 480 of 1053

Full-Text Articles in Computer Sciences

Speech Emotion Detection Using Machine Learning Techniques, Neethu Sundarprasad Apr 2018

Speech Emotion Detection Using Machine Learning Techniques, Neethu Sundarprasad

Master's Projects

Communication is the key to express one’s thoughts and ideas clearly. Amongst all forms of communication, speech is the most preferred and powerful form of communications in human. The era of the Internet of Things (IoT) is rapidly advancing in bringing more intelligent systems available for everyday use. These applications range from simple wearables and widgets to complex self-driving vehicles and automated systems employed in various fields. Intelligent applications are interactive and require minimum user effort to function, and mostly function on voice-based input. This creates the necessity for these computer applications to completely comprehend human speech. A speech percept …

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Deep Learning For Chatbots, Vyas Ajay Bhagwat Apr 2018

Deep Learning For Chatbots, Vyas Ajay Bhagwat

Master's Projects

Natural Language Processing (NLP) requires modelling complex relationships between the semantics of the language. While traditional machine learning techniques are used for NLP, the models built for conversations, called chatbots, are unable to be truly generic. While chatbots have been made with traditional machine learning techniques, deep learning has allowed the complexities within NLP to be easier to model and can be leveraged to build a chatbot which has a real conversation with a human. In this project, we explore the problems and techniques used to build chatbots and where improvements can be made. We analyze different architectures to build …

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Validating Key-Value Based Implementations Of The Raft Consensus Algorithm For Distributed Systems, Deepthi Vishwanath Apr 2018

Validating Key-Value Based Implementations Of The Raft Consensus Algorithm For Distributed Systems, Deepthi Vishwanath

Master's Projects

Distributed systems are a group of systems connected via a network, all working towards achieving a common goal. To achieve fault tolerance and reliability, all the systems should work towards achieving consensus. Paxos is the most widely used consensus algorithm since 2 or 3 decades, but the shift is now happening towards a new algorithm known as Raft. Raft is a consensus algorithm (paper published in the year 2014) which is easier to understand and works like Paxos in terms of fault tolerance and performance. Since Raft is new, there is a need for a tool that verifies systems built …

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Facial Emotion Recognition Using Machine Learning, Nitisha Raut Apr 2018

Facial Emotion Recognition Using Machine Learning, Nitisha Raut

Master's Projects

Face detection has been around for ages. Taking a step forward, human emotion displayed by face and felt by brain, captured in either video, electric signal (EEG) or image form can be approximated. Human emotion detection is the need of the hour so that modern artificial intelligent systems can emulate and gauge reactions from face. This can be helpful to make informed decisions be it regarding identification of intent, promotion of offers or security related threats. Recognizing emotions from images or video is a trivial task for human eye, but proves to be very challenging for machines and requires many …

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Load Balancing And Virtual Machine Allocation In Cloud-Based Data Centers, Saily Satish Ghodke Apr 2018

Load Balancing And Virtual Machine Allocation In Cloud-Based Data Centers, Saily Satish Ghodke

Master's Projects

As cloud services see an exponential increase in consumers, the demand for faster processing of data and a reliable delivery of services becomes a pressing concern. This puts a lot of pressure on the cloud-based data centers, where the consumers’ data is stored, processed and serviced. The rising demand for high quality services and the constrained environment, make load balancing within the cloud data centers a vital concern. This project aims to achieve load balancing within the data centers by means of implementing a Virtual Machine allocation policy, based on consensus algorithm technique. The cloud-based data center system, consisting of …

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Stock Price Prediction Using Deep Learning, Abhinav Tipirisetty Apr 2018

Stock Price Prediction Using Deep Learning, Abhinav Tipirisetty

Master's Projects

Stock price prediction is one among the complex machine learning problems. It depends on a large number of factors which contribute to changes in the supply and demand. This paper presents the technical analysis of the various strategies proposed in the past, for predicting the price of a stock, and evaluation of a novel approach for the same. Stock prices are represented as time series data and neural networks are trained to learn the patterns from trends. Along with the numerical analysis of the stock trend, this research also considers the textual analysis of it by analyzing the public sentiment …

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Intrusion Detection In Containerized Environments, Shyam Sundar Durairaju Apr 2018

Intrusion Detection In Containerized Environments, Shyam Sundar Durairaju

Master's Projects

In this paper, we present the results of using Hidden Markov Models for learning the behavior of Docker containers. This is for use in anomaly-detection based intrusion detection system. Containers provide isolation between the host system and the containerized environment by efficiently packaging applications along with their dependencies. This way, containers become a portable software environment for applications to run and scale. Unlike virtual machines, containers share the same kernel as the host operating system. This is leveraged to monitor the system calls of the container from the host system for anomaly detection. Thus, the monitoring system is not required …

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Subtopics In Yelp Reviews, Riya Suchdev Apr 2018

Subtopics In Yelp Reviews, Riya Suchdev

Master's Projects

Yelp is a review platform that connects people to local businesses. It is a very popular platform that helps customers decide which business to choose. It relies on crowd sourced plain text reviews. From the business’s description some facts can be determined, such as category and location. However, more detailed description can be extracted from the reviews. Discovering latent topics and subtopics in Yelp reviews, can help summarize the reviews to gain knowledge. For example, we can deduce that reviews related to the Restaurant category tend to emphasize on service, food, order etc. Additionally, one can deduce positive or negative …

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Bitcoin Transaction Fee Estimation Using Mempool State And Linear Perceptron Machine Learning Algorithm, Abdullah Al-Shehabi Apr 2018

Bitcoin Transaction Fee Estimation Using Mempool State And Linear Perceptron Machine Learning Algorithm, Abdullah Al-Shehabi

Master's Projects

Bitcoin, the world’s most valued cryptocurrency, uses a network of computers across the globe to create an immutable transaction record on a public ledger known as the blockchain. The blockchain consists of a series of timestamped blocks, where each block contains a series of transactions selected for inclusion in the block, generally based on how high of a fee the transaction allocates to the party responsible for confirming the transaction. Estimating an appropriate fee for Bitcoin transactions is a challenge for many transacting parties using Bitcoin as a digital currency. This work aims to help Bitcoin users save funds in …

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Image Spam Classification Using Deep Learning, Ajay Pal Singh Apr 2018

Image Spam Classification Using Deep Learning, Ajay Pal Singh

Master's Projects

Image classification is a fundamental problem of computer vision and pattern recognition. Spam is unwanted bulk content and image spam is unwanted content embedded inside the images. Image spam creates threat to the email based communication systems. Nowadays, a lot of unsolicited content is circulated over the internet. While a lot of machine learning techniques are successful in detecting textual based spam, this is not the case for image spams, which can easily evade these textual-spam detection systems. In this project, we explore and evaluate four deep learning techniques that detect image spams. First, we study neural networks and the …

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Deep Learning Algorithm Recommender, Rajat Kabra Apr 2018

Deep Learning Algorithm Recommender, Rajat Kabra

Master's Projects

Deep learning contains a set of algorithms that are based on the functioning of human brain i.e. neural networks. These algorithms require a lot of computation power and time along with complex setup to get good results. The project contains several artificial neural network implementation for a variety of tasks like data classification, image classification, natural language processing and more. The project contains an exploratory analysis of hyperparameters of deep learning algorithms in domain of deep learning applications to prove that it is possible to achieve a good accuracy with less resources.

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Sql Injection Detection Using Machine Learning Techniques And Multiple Data Sources, Kevin Ross Apr 2018

Sql Injection Detection Using Machine Learning Techniques And Multiple Data Sources, Kevin Ross

Master's Projects

SQL Injection continues to be one of the most damaging security exploits in terms of personal information exposure as well as monetary loss. Injection attacks are the number one vulnerability in the most recent OWASP Top 10 report, and the number of these attacks continues to increase. Traditional defense strategies often involve static, signature-based IDS (Intrusion Detection System) rules which are mostly effective only against previously observed attacks but not unknown, or zero-day, attacks. Much current research involves the use of machine learning techniques, which are able to detect unknown attacks, but depending on the algorithm can be costly in …

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A Neural Network Classifier For The Coi Barcode Gene, Saurabh Marathe Apr 2018

A Neural Network Classifier For The Coi Barcode Gene, Saurabh Marathe

Master's Projects

Mitochondrial Cytochrome C Oxidase subunit I (CO I – to be read as “see – oh one”) is a 658 base pair region in the gene encoding that is proposed as standard barcode for animals. Meaning, the CO I is a special region found in animal DNA that is studied to identify the species of the animal. Currently, there is an implementation of an algorithm called ARBitrator which identifies and extracts these CO I sequences from enormous genes database called GenBank. The ARBitrator is good at extracting the CO I sequences that have better specificity and accuracy as compared to …

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Joint Computation Offloading And Prioritized Scheduling In Mobile Edge Computing, Lingfang Gao Apr 2018

Joint Computation Offloading And Prioritized Scheduling In Mobile Edge Computing, Lingfang Gao

Master's Projects

With the rapid development of smart phones, enormous amounts of data are generated and usually require intensive and real-time computation. Nevertheless, quality of service (QoS) is hardly to be met due to the tension between resourcelimited (battery, CPU power) devices and computation-intensive applications. Mobileedge computing (MEC) emerging as a promising technique can be used to copy with stringent requirements from mobile applications. By offloading computationally intensive workloads to edge server and applying efficient task scheduling, energy cost of mobiles could be significantly reduced and therefore greatly improve QoS, e.g., latency. This paper proposes a joint computation offloading and prioritized task …

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Machine Learning Playground, Adil Khan Apr 2018

Machine Learning Playground, Adil Khan

Master's Projects

Machine learning is a science that “learns” about the data by finding unique patterns and relations in the data. There are a lot of libraries or tools available for processing machine learning datasets. You can upload your dataset in seconds and quickly start using these tools to get prediction results in a few minutes. However, generating an optimal model is a time consuming and tedious task. The tunable parameters (hyper-parameters) of any machine learning model may greatly affect the accuracy metrics. While most of the tools have models with default parameter setting to provide good results, they can often fail …

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Mandala Generation From Brainwave With Feedforward, Kumari Anamika Sharaf Apr 2018

Mandala Generation From Brainwave With Feedforward, Kumari Anamika Sharaf

Master's Projects

Most experiments conducted in the early 1900s with Electroencephalography (EEG) [10] devices explored mental illness of the participants. Historically, EEG has had specific applications to diagnose sleep disorder, epilepsy, coma and brain death. Today, EEG devices are used extensively for research purposes [10], especially in the field of neuroscience. Traditionally, most experiments included a human participant wherein an EEG device was connected to the subject’s forehead to detect electrical impulses indicating different brainwaves. Each brainwave implied a different emotional state of mind. Past experiments [2] [3] [4] then used the brainwave signals as input to build audio/visual art to aid …

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Image To Latex Via Neural Networks, Avinash More Apr 2018

Image To Latex Via Neural Networks, Avinash More

Master's Projects

Many research papers in mathematics, computer science, and physics are written in LaTeX. Technical papers and articles in these areas often involve mathematical equations. Writing such equations in LaTeX takes longer than handwriting the same equations on paper. In this report, we want to show that the time-consuming process of typesetting LaTeX equations from images of these equations can be automated and optimized. Neural networks are good at solving related problems such as handwritten digit recognition, so we adapted these well-studied approaches to the LaTeX problem. Neural network model training involves large amounts of good quality data. So, for our …

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Genetic Barcode Identification With Profile Hidden Markov Models, Vishrut Sharma Apr 2018

Genetic Barcode Identification With Profile Hidden Markov Models, Vishrut Sharma

Master's Projects

DNA barcoding is a method that uses an organism’s DNA to identify its species. The gene cytochrome c oxidase I (COI) has been used effectively as a DNA barcode to identify organisms and elucidate relationships among species [1]. There also exists a database BOLD (Barcode Of Life Database) that contains COI sequences used for DNA barcoding for more than 1 million different species. Using BOLD to identify samples that have a match in the database is an uncomplicated process. However, this method fails to determine samples that are absent from the database. Given a sample that is not represented in …

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Outfit Recommender System, Nikita Ramesh Apr 2018

Outfit Recommender System, Nikita Ramesh

Master's Projects

The online apparel retail market size in the United States is worth about seventy-two billion US dollars. Recommendation systems on retail websites generate a lot of this revenue. Thus, improving recommendation systems can increase their revenue. Traditional recommendations for clothes consisted of lexical methods. However, visual-based recommendations have gained popularity over the past few years. This involves processing a multitude of images using different image processing techniques. In order to handle such a vast quantity of images, deep neural networks have been used extensively. With the help of fast Graphics Processing Units, these networks provide results which are extremely accurate, …

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Optimal Constrained Wireless Emergency Network Antennae Placement, Swapnil Mohan Gaikwad Apr 2018

Optimal Constrained Wireless Emergency Network Antennae Placement, Swapnil Mohan Gaikwad

Master's Projects

With increasing number of mobile devices, newly introduced smart devices, and the Internet of things (IoT) sensors, the current microwave frequency spectrum is getting rapidly congested. The obvious solution to this frequency spectrum congestion is to use millimeter wave spectrum ranging from 6 GHz to 300 GHz. With the use of millimeter waves, we can enjoy very high communication speeds and very low latency. But, this technology also introduces some challenges that we hardly faced before. The most important one among these challenges is the Line of Sight (LOS) requirement. In the emergent concept of smart cities, the wireless emergency …

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Analysis Of Encrypted Malicious Traffic, Anish Singh Shekhawat Apr 2018

Analysis Of Encrypted Malicious Traffic, Anish Singh Shekhawat

Master's Projects

In recent years there has been a dramatic increase in the number of malware attacks that use encrypted HTTP traffic for self-propagation and communication. Due to the volume of legitimate encrypted data, encrypted malicious traffic resembles benign traffic. As the malicious traffic is similar to benign traffic, it poses a challenge for antivirus software and firewalls. Since antivirus software and firewalls will not typically have access to encryption keys, detection techniques are needed that do not require decrypting the traffic. In this research, we apply a variety of machine learning techniques to the problem of distinguishing malicious encrypted HTTP traffic …

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A Study On Effects Of Data Poisoning On Hmms, Rachel Gonsalves Apr 2018

A Study On Effects Of Data Poisoning On Hmms, Rachel Gonsalves

Master's Projects

With the ever increasing use of burgeoning volumes of data, machine learning systems involving minimal human oversight are crucial for classification and analysis tasks. Machine learning algorithms used for such purposes have revolutionized the way we sort, classify, and analyze data. The accuracy of any machine learning algorithm depends heavily on the data it is trained on. In some circumstances, an attacker can attempt to poison the training data to subvert a machine learning system. In this research, we analyze the effects of training data poisoning attacks on hidden Markov models (HMMs), in the context of malware classification. With the …

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Sentiment Analysis Using An Ensemble Of Feature Selection Algorithms, Manankumar Bhagat Apr 2018

Sentiment Analysis Using An Ensemble Of Feature Selection Algorithms, Manankumar Bhagat

Master's Projects

To determine the opinion of any person experiencing any services or buying any product, the usage of Sentiment Analysis, a continuous research in the field of text mining, is a common practice. It is a process of using computation to identify and categorize opinions expressed in a piece of text. Individuals post their opinion via reviews, tweets, comments or discussions which is our unstructured information. Sentiment analysis gives a general conclusion of audits which benefit clients, individuals or organizations for decision making. The primary point of this paper is to perform an ensemble approach on feature reduction methods identified with …

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Multi-Objective Path Finding Using Reinforcement Learning, Prashant Thombre Apr 2018

Multi-Objective Path Finding Using Reinforcement Learning, Prashant Thombre

Master's Projects

Path Finding is a vastly studied subject in the field of Computer Science. The problem of path-finding is defined as the discovery and plotting of an optimal route between two points on a plane. The existing algorithms that solve this problem are mostly static and rely heavily on the prior knowledge of the environment. They also require the environment to be deterministic. However, in real-world applications of the path-finding problem, often the environment is priorly unknown and stochastic, and with several conflicting objectives. In such cases, the aforementioned algorithms fail to produce effective results. In this project, we study and …

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Ontology Based Technical Skill Similarity, Yeshwanth Bashyam Balachander Apr 2018

Ontology Based Technical Skill Similarity, Yeshwanth Bashyam Balachander

Master's Projects

Online job boards have become a major platform for technical talent procurement and job search. These job portals have given rise to challenging matching and search problems. The core matching or search happens between technical skills of the job requirements and the candidate's profile or keywords. The extensive list of technical skills and its polyonymous nature makes it less effective to perform a direct keyword matching. This results in substandard job matching or search results which misses out a closely matching candidate on account of it not having the exact skills. It is important to use a semantic similarity measure …

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Feature Selection Using Genetic Algorithms, Vandana Kannan Apr 2018

Feature Selection Using Genetic Algorithms, Vandana Kannan

Master's Projects

With the large amount of data of different types that are available today, the number of features that can be extracted from it is huge. The ever-increasing popularity of multimedia applications, has been a major factor for this, especially in the case of image data. Image data is used for several applications such as classification, retrieval, object recognition, and annotation. Often, utilizing the entire feature set for each of these activities can be not only be time consuming but can also negatively impact the performance. Given the large number of features, it is difficult to find the subset of features …

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Boosted Hidden Markov Models For Malware Detection, Aditya Raghavan Apr 2018

Boosted Hidden Markov Models For Malware Detection, Aditya Raghavan

Master's Projects

Digital security is an important issue today, and efficient malware detection is at the forefront of research into building secure digital systems. As with many other fields, malware detection research has seen a dramatic increase in the application of machine learning algorithms. One machine learning technique that has found widespread application in the field of pattern matching and malware detection is hidden Markov models (HMMs). Since HMM training is a hill climb technique, we can often significantly improve a model by training multiple times with different initial values. In this research, we compare boosted HMMs (using AdaBoost) to HMMs trained …

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Using Sentiment Analysis And Pattern Matching To Signal User Review Abnormalities, Stefan S. Gloutnikov Apr 2018

Using Sentiment Analysis And Pattern Matching To Signal User Review Abnormalities, Stefan S. Gloutnikov

Master's Projects

User opinions on websites like Amazon, Yelp, and TripAdvisor are a key input for consumers when figuring out what to purchase, or where and what to eat. This means that in order for such websites to provide a better service to their customers, they must guard against fake and targeted reviews. Detecting such users and reviews automatically is a very complex multi-step process, and there is no direct mechanism for solving the problem reliably. Multiple AI and Machine Learning algorithms are coupled together when examining user reviews in determining if a review is fake or not. In this project we …

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Anomaly Detection For Application Log Data, Aarish Grover Apr 2018

Anomaly Detection For Application Log Data, Aarish Grover

Master's Projects

In software development, there is an absolute requirement to ensure that a system once developed, functions at its best throughout its lifetime. Application log data is critical to maintaining application performance and thus techniques to parse, understand and detect anomalies in application log data are critical to ensuring efficiency in software development. While initially hampered by limited hardware and lack of quality datasets, anomaly detection techniques have recently received a surge of interest with advancements in machine learning technology and especially neural networks. In this paper, we explore anomaly detection, historical techniques to detect anomalies and recent advancements in neural …

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Visual Question Answering, Pankti Kansara Apr 2018

Visual Question Answering, Pankti Kansara

Master's Projects

There has been immense progress in the fields of computer vision, object detection and natural language processing (NLP) in recent years. Artificial Intelligence (AI) systems, such as question answering models, use NLP to provide a "comprehensive" capability to the machine. Such a machine can answer natural language queries about any portion of an unstructured text. An extension of this system is to combine NLP with computer vision to accomplish the task of Visual Question Answering (VQA), which is to build a system that can answer natural language queries about images. A number of systems have been proposed for VQA that …

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