Computer Sciences Commons^™

Batch Arrival Bulk Service Queue With Unreliable Server, Second Optional Service, Two Different Vacations And Restricted Admissibility Policy, G. Ayyappan, R. Supraja

Applications and Applied Mathematics: An International Journal (AAM)

This paper is concerned with batch arrival queue with an additional second optional service to a batch of customers with dissimilar service rate where the idea of restricted admissibility of arriving batch of customers is also introduced. The server may take two different vacations (i) Emergency vacation-during service the server may go for vacation to an emergency call and after completion of the vacation, the server continues the remaining service to a batch of customers. (ii) Bernoulli vacation-after completion of first essential or second optional service, the server may take a vacation or may remain in the system to serve …

An M^X/G(A,B)/1 Queue With Breakdown And Delay Time To Two Phase Repair Under Multiple Vacation, G. Ayyappan, M. Nirmala

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we consider an M^x /G(a,b)/1 queue with active breakdown and delay time to two phase repair under multiple vacation policy. A batch of customers arrive according to a compound Poisson process. The server serves the customers according to the “General Bulk Service Rule” (GBSR) and the service time follows a general (arbitrary) distribution. The server is unreliable and it may breakdown at any instance. As the result of breakdown, the service is suspended, the server waits for the repair to start and this waiting time is called as „delay time‟ and is assumed to follow general …

Revolution In Crime: How Cryptocurrencies Have Changed The Criminal Landscape, Igor Groysman

Student Theses

This thesis will examine the ways in which various cryptocurrencies have impacted certain traditional crimes. While crime is always evolving with technology, cryptocurrencies are a game changer in that they provide anonymous and decentralized payment systems which, while they can be tracked in a reactive sense via the blockchain, are seen by criminals as having better uses for them than traditional fiat currencies, such as the ability to send money relatively fast to another party without going through an intermediary, or the ability to obscure the origin of the money for money laundering purposes. Every week there are new cryptocurrencies …

Parallel Sampling-Pipeline For Indefinite Stream Of Heterogeneous Graphs Using Opencl For Fpgas, Muhammad Usman Tariq, Fahad Saeed

School of Computing and Information Sciences

In the field of data science, a huge amount of data, generally represented as graphs, needs to be processed and analyzed. It is of utmost importance that this data be processed swiftly and efficiently to save time and energy. The volume and velocity of data, along with irregular access patterns in graph data structures, pose challenges in terms of analysis and processing. Further, a big chunk of time and energy is spent on analyzing these graphs on large compute clusters and/or data-centers. Filtering and refining of data using graph sampling techniques are one of the most effective ways to speed …

Learning-Based Analysis On The Exploitability Of Security Vulnerabilities, Adam Bliss

Computer Science and Computer Engineering Undergraduate Honors Theses

The purpose of this thesis is to develop a tool that uses machine learning techniques to make predictions about whether or not a given vulnerability will be exploited. Such a tool could help organizations such as electric utilities to prioritize their security patching operations. Three different models, based on a deep neural network, a random forest, and a support vector machine respectively, are designed and implemented. Training data for these models is compiled from a variety of sources, including the National Vulnerability Database published by NIST and the Exploit Database published by Offensive Security. Extensive experiments are conducted, including testing …

Identifying Criticality In Market Sentiment: A Data Mining Approach, Vaibhav Sahu

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The aim of this thesis is to study and identify time periods of high activity in commodity and stock market sentiment based on a data mining approach. The method is to develop tools to extract relevant information from web searches and Twitter feeds based on the tally of certain keywords and their combinations at regular intervals. Periods of high activity are identified by a measure of complexity developed for analysis of living systems. Experiments were conducted to see if the measure of activity could be applied as a predictor of changes in stock market and commodity prices.

Improving Accuracy Of The Edgebox Approach, Kamna Yadav

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Object region detection plays a vital role in many domains ranging from self-driving cars to lane detection, which heavily involves the task of object detection. Improving the performance of object region detection approaches is of great importance and therefore is an active ongoing research in Computer Vision. Traditional sliding window paradigm has been widely used to identify hundreds of thousands of windows (covering different scales, angles, and aspect ratios for objects) before the classification step. However, it is not only computationally expensive but also produces relatively low accuracy in terms of the classifier output by providing many negative samples. Object …

Collection And Analysis Of Digital Forensic Data From Devices In The Internet Of Things, Raed Alharbi

Theses and Dissertations

Despite the abundance articles that have been written about the Internet of Things (IoT), little attention has been given to how digital forensics approaches can be utilized to direct advanced investigations in IoT-based frameworks. As of yet, IoT has not completely adjusted to digital forensic strategies given the fact that current digital forensic tools and functions are not ready to tackle the complexity of IoT frameworks for the purpose of collecting, analyzing, and testing potential evidence from IoT environments that might be utilized as permissible evidence in a court. Hence, the issue addressed is that; currently, there is no accepted …

Towards Enhanced Security For Automotive Operating Systems, Maksym Hryhorenko

Theses and Dissertations

Modern automotive infotainment systems are represented by highly complex components with broad functionality and network capabilities. As a result, they are becoming more exposed to the outer world, thus turning into potentially lucrative targets for remote cyber attacks. In the worst case scenario, an attacker could gain complete control over critical vehicle’s systems, for instance, steering, braking, engine, etc. This thesis proposes security hardening features based on ARM’s TrustZone technology for infotainment systems that ensures confidentiality and integrity of critical applications. In addition, we present a technique that allows to mitigate the impact of certain attacks on the car’s internal …

Comparison Mining From Text, Maksim Tkachenko

Dissertations and Theses Collection (Open Access)

Online product reviews are important factors of consumers' purchase decisions. They invade more and more spheres of our life, we have reviews on books, electronics, groceries, entertainments, restaurants, travel experiences, etc. More than 90 percent of consumers read online reviews before they purchase products as reported by various consumers surveys. This observation suggests that product review information enhances consumer experience and helps them to make better-informed purchase decisions. There is an enormous amount of online reviews posted on e-commerce platforms, such as Amazon, Apple, Yelp, TripAdvisor. They vary in information and may be written with different experiences and preferences.

If …

The Rise Of Real-Time Retail Payments, Zhiling Guo

MITB Thought Leadership Series

TRANSACTING for just about anything using our mobile phones has become commonplace, and so many consumers will be intrigued to discover that after making a purchase it can still take longer for payment to reach a vendor’s bank account than it does for the purchased goods to be delivered.

Leveraging Artificial Intelligence To Capture The Singapore Rideshare Market, Pradeep Varakantham

MITB Thought Leadership Series

BIKE-SHARING programmes face many of the issues encountered by their counterparts in the carsharing world. But in Singapore, there are a number of factors that have a unique impact on the industry. These include the regulatory structure and the significant fines for those companies who do not abide by these regulations. When this is combined with the competitive nature of the industry in one of the world's most dynamic cities, it becomes clear that first movers who leverage machine learning and prediction will come to dominate the industry

The Analysis Of M/M/1 Queue With Working Vacation In Fuzzy Environment, G. Kannadasan, N. Sathiyamoorth

Applications and Applied Mathematics: An International Journal (AAM)

This study investigates the FM/FM/1 queue with working vacation. For this fuzzy queuing model, the researcher obtains some performance measure of interest such as the regular busy period, working vacation period, stationary queue length and waiting time. Finally, numerical results are presented to show the effects of system parameters.

Induced Hesitant 2-Tuple Linguistic Aggregation Operators With Application In Group Decision Making, Tabasam Rashid, Ismat Beg, Raja N. Jamil

Applications and Applied Mathematics: An International Journal (AAM)

In this article, hesitant 2-tuple linguistic arguments are used to evaluate the group decision making problems which have inter dependent or inter active attributes. Operational laws are developed for hesitant 2-tuple linguistic elements and based on these operational laws hesitant 2- tuple weighted averaging operator and generalized hesitant 2- tuple averaging operator are proposed. Combining Choquet integral with hesitant 2-tuple linguistic information, some new aggregation operators are defined, including the hesitant 2-tuple correlated averaging operator, the hesitant 2-tuple correlated geometric operator and the generalized hesitant 2-tuple correlated averaging operator. These proposed operators successfully manage the correlations among the elements. After …

First Steps In Retrofitting A Versatile Software Testing Infrastructure To Android, Carol Anne Oliver

Theses and Dissertations

Are existing software testing technologies satisfying the needs of mobile software testing practitioners? This dissertation provides evidence that the existing technologies fall short of practitioner’s actual needs and analyzes some reasons why this is so. The first contribution presents a framework for analyzing the software testing needs of practitioners, which is then used to assess the existing software testing tools and body of research, revealing significant gaps. The second contribution proposes a vision for a new software testing technology for mobile apps, which is then applied to a real-world problem causing problems for software testing practitioners (namely, the verification of …

Strong Mutation-Based Test Generation Of Xacml Policies, Roshan Shrestha

Boise State University Theses and Dissertations

There exist various testing methods for XACML policies which vary in their overall fault detection ability and none of them can detect all the (killable) injected faults except for the simple policies. Further, it is unclear that what is essential for the fault detection of XACML policies. To address these issues, we formalized the fault detection conditions in the well-studied fault model of XACML policies so that it becomes clear what is essential for the fault detection. We formalized fault detection conditions in the form of reachability, necessity and propagation constraint. We, then, exploit these constraints to generate a mutation-based …

Using Dna For Data Storage: Encoding And Decoding Algorithm Development, Kelsey Suyehira

Boise State University Theses and Dissertations

The recent explosion of digital data has created an increasing need for improved data storage architectures with the ability to store large amounts of data over extensive periods of time. DNA as a data storage solution shows promise with a thousand times greater increase in information density and information retention times ranging from hundreds to thousands of years. This thesis explores the challenges and potential approaches in developing an encoding and decoding algorithm for use in a DNA data storage architecture. When encoding binary data into sequences representing DNA strands, the algorithms should account for biological constraints representing the idiosyncrasies …

Efficacy Of Deep Learning In Support Of Smart Services, Basheer Mohammed Basheer Qolomany

Dissertations

The massive amount of streaming data generated and captured by smart service appliances, sensors and devices needs to be analyzed by algorithms, transformed into information, and minted to extract knowledge to facilitate timely actions and better decision making. This can lead to new products and services that can dramatically transform our lives. Machine learning and data analytics will undoubtedly play a critical role in enabling the delivery of smart services. Within the machine-learning domain, Deep Learning (DL) is emerging as a superior new approach that is much more effective than any rule or formula used by traditional machine learning. Furthermore, …

Multi-Base Chains For Faster Elliptic Curve Cryptography, Saud Al Musa

Theses and Dissertations

This research addresses a multi-base number system (MBNS) for faster elliptic curve cryptography (ECC). The emphasis is on speeding up the main operation of ECC: scalar multiplication (tP). Mainly, it addresses the two issues of using the MBNS with ECC: deriving optimized formulas and choosing fast methods. To address the first issue, this research studies the optimized formulas (e.g., 3P, 5P) in different elliptic curve coordinate systems over prime and binary fields. For elliptic curves over prime fields, affine Weierstrass, Jacobian Weierstrass, and standard twisted Edwards coordinate systems are reviewed. For binary elliptic curves, affine, Lambda-projective, and twisted mu4-normal coordinate …

Adaptive Parallelism For Coupled, Multithreaded Message-Passing Programs, Samuel K. Gutiérrez

Computer Science ETDs

Hybrid parallel programming models that combine message passing (MP) and shared- memory multithreading (MT) are becoming more popular, especially with applications requiring higher degrees of parallelism and scalability. Consequently, coupled parallel programs, those built via the integration of independently developed and optimized software libraries linked into a single application, increasingly comprise message-passing libraries with differing preferred degrees of threading, resulting in thread-level heterogeneity. Retroactively matching threading levels between independently developed and maintained libraries is difficult, and the challenge is exacerbated because contemporary middleware services provide only static scheduling policies over entire program executions, necessitating suboptimal, over-subscribed or under-subscribed, configurations. In …