Other Computer Engineering Commons^™

Fundamentals Of Neutrosophic Logic And Sets And Their Role In Artificial Intelligence (Fundamentos De La Lógica Y Los Conjuntos Neutrosóficos Y Su Papel En La Inteligencia Artificial ), Florentin Smarandache, Maykel Leyva-Vazquez

Branch Mathematics and Statistics Faculty and Staff Publications

Neutrosophy is a new branch of philosophy which studies the origin, nature and scope of neutralities. This has formed the basis for a series of mathematical theories that generalize the classical and fuzzy theories such as the neutrosophic sets and the neutrosophic logic. In the paper, the fundamental concepts related to neutrosophy and its antecedents are presented. Additionally, fundamental concepts of artificial intelligence will be defined and how neutrosophy has come to strengthen this discipline.

Modelo De Recomendación Basado En Conocimiento Y Números Svn, Maykel Leyva-Vazquez, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

Recommendation models are useful in the decision-making process that allow the user a set of options that are expected to meet their expectations. Recommendation models are useful in the decision-making process that offer the user a set of options that are expected to meet their SVN expectations to express linguistic terms.

Some Aggregation Operators For Bipolar-Valued Hesitant Fuzzy Information, Florentin Smarandache, Tahir Mahmood, Kifayat Ullah, Qaisar Khan

Branch Mathematics and Statistics Faculty and Staff Publications

In this article we define some aggregation operators for bipolar-valued hesitant fuzzy sets. These operations include bipolar-valued hesitant fuzzy ordered weighted averaging (BPVHFOWA) operator, bipolar-valued hesitant fuzzy ordered weighted geometric (BPVHFOWG) operator and their generalized forms. We also define hybrid aggregation operators and their generalized forms and solved a decision-making problem on these operation.

Quantitative Fine-Grained Human Evaluation Of Machine Translation Systems: A Case Study On English To Croatian, Filip Klubicka, Antonio Toral, Victor Manuel Sanchez-Cartagena

Articles

This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performance for MQM error types between different MT systems are statistically significant. We conduct a case study for English-to- Croatian, a language direction that involves translating into a morphologically rich language, for which we compare three MT systems belonging to different paradigms: pure phrase-based, factored phrase-based and neural. First, we design an MQM-compliant error taxonomy tailored to the relevant …

Mobile Cloud Computing: A Comparison Study Of Cuckoo And Aiolos Offloading Frameworks, Inan Kaddour

UNF Graduate Theses and Dissertations

Currently, smart mobile devices are used for more than just calling and texting. They can run complex applications such as GPS, antivirus, and photo editor applications. Smart devices today offer mobility, flexibility, and portability, but they have limited resources and a relatively weak battery. As companies began creating mobile resource intensive and power intensive applications, they have realized that cloud computing was one of the solutions that they could utilize to overcome smart device constraints. Cloud computing helps decrease memory usage and improve battery life. Mobile cloud computing is a current and expanding research area focusing on methods that allow …

Examining A Hate Speech Corpus For Hate Speech Detection And Popularity Prediction, Filip Klubicka, Raquel Fernandez

Other resources

As research on hate speech becomes more and more relevant every day, most of it is still focused on hate speech detection. By attempting to replicate a hate speech detection experiment performed on an existing Twitter corpus annotated for hate speech, we highlight some issues that arise from doing research in the field of hate speech, which is essentially still in its infancy. We take a critical look at the training corpus in order to understand its biases, while also using it to venture beyond hate speech detection and investigate whether it can be used to shed light on other …

Is It Worth It? Budget-Related Evaluation Metrics For Model Selection, Filip Klubicka, Giancarlo Salton, John D. Kelleher

Conference papers

Projects that set out to create a linguistic resource often do so by using a machine learning model that pre-annotates or filters the content that goes through to a human annotator, before going into the final version of the resource. However, available budgets are often limited, and the amount of data that is available exceeds the amount of annotation that can be done. Thus, in order to optimize the benefit from the invested human work, we argue that the decision on which predictive model one should employ depends not only on generalized evaluation metrics, such as accuracy and F-score, but …

Streaming Mysql Database Activity To Aws Kinesis, Chris I. Voncina

Computer Engineering

Connecting Amazon RDS MySQL engine with AWS Kinesis is a feature that RDS customers have often requested. A good example indicating customer demand is demonstrated on AWS’ forum post at https://forums.aws.amazon.com/thread.jspa?messageID=697516.

Upon completion, my project will enable Amazon RDS to pick up the MySQL open source project, integrate the MySQL plugin with Amazon RDS MySQL and deliver this feature to Amazon RDS MySQL customers. Other open source engine projects can follow and build upon my project.

Amazon Aurora delivered similar capability to the project. See details at https://aws.amazon.com/about-aws/whats-new/2016/10/amazon-aurora-new-features-aws-lambda-integration-and-data-load-from-amazon-s3-to-aurora-tables/

Real Time And High Fidelity Quadcopter Tracking System, Tyler Mckay Hall

Computer Engineering

This project was conceived as a desired to have an affordable, flexible and physically compact tracking system for high accuracy spatial and orientation tracking. Specifically, this implementation is focused on providing a low cost motion capture system for future research. It is a tool to enable the further creation of systems that would require the use of accurate placement of landing pads, payload acquires and delivery. This system will provide the quadcopter platform a coordinate system that can be used in addition to GPS.

Field research with quadcopter manufacturers, photographers, agriculture and research organizations were contact and interviewed for information …

A Data Hiding Scheme Based On Chaotic Map And Pixel Pairs, Sengul Dogan Sd

Journal of Digital Forensics, Security and Law

Information security is one of the most common areas of study today. In the literature, there are many algorithms developed in the information security. The Least Significant Bit (LSB) method is the most known of these algorithms. LSB method is easy to apply however it is not effective on providing data privacy and robustness. In spite of all its disadvantages, LSB is the most frequently used algorithm in literature due to providing high visual quality. In this study, an effective data hiding scheme alternative to LSB, 2LSBs, 3LSBs and 4LSBs algorithms (known as xLSBs), is proposed. In this method, random …

Pubwc Bathroom Review App, Clay Jacobs

Computer Science and Software Engineering

For my senior project, I developed an iOS application to allow users to find, rate, and review nearby public restrooms. The app takes advantage of crowdsourced data to collect bathroom and review information. I also created a REST API to interface with the backend database that could be used to port the application to other platforms.

Cloudskulk: Design Of A Nested Virtual Machine Based Rootkit-In-The-Middle Attack, Joseph Anthony Connelly

Boise State University Theses and Dissertations

Virtualized cloud computing services are a crucial facet in the software industry today, with clear evidence of its usage quickly accelerating. Market research forecasts an increase in cloud workloads by more than triple, 3.3-fold, from 2014 to 2019 [33]. Integrating system security is then an intrinsic concern of cloud platform system administrators that with the growth of cloud usage, is becoming increasingly relevant. People working in the cloud demand security more than ever. In this paper, we take an offensive, malicious approach at targeting such cloud environments as we hope both cloud platform system administrators and software developers of these …

Demand Side Management In Smart Grid Using Big Data Analytics, Sidhant Chatterjee

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Smart Grids are the next generation electrical grid system that utilizes smart meter-ing devices and sensors to manage the grid operations. Grid management includes the prediction of load and and classification of the load patterns and consumer usage behav-iors. These predictions can be performed using machine learning methods which are often supervised. Supervised machine learning signifies that the algorithm trains the model to efficiently predict decisions based on the previously available data.

Smart grids are employed with numerous smart meters that send user statistics to a central server. The data can be accumulated and processed using data mining and machine …

Development Of Some Scalable Pattern Recognition Algorithms For Real Life Data Analysis, Partha Garai

Doctoral Theses

A huge amount of data is being generated continuously as a result of recent advancement and wide use of high-throughput technologies. With the rapid increase in size of data distributed worldwide, understanding the data has become critical. In this regard, dimensionality reduction and clustering have become the necessary preprocessing steps of multiple research areas and applications. One of the important problems of real life large data sets is uncertainty. Some of the sources of this uncertainty include imprecision in computation and vagueness in class denitions. The uncertainty may also be present in the denition of class membership function. In this …

Applied Deep Learning: Automated Segmentation Of White Matter Hyperintensities (Wmh) On Brain Mr Images, Matt Berseth

DHI Digital Projects Showcase

Small vessel disease plays a crucial role in stroke, dementia, and ageing. White matter hyperintensities (WMH) of vascular origin are one of the main consequences of small vessel disease and well visible on brain MR images. Quantification of WMH volume, location, and shape is of key importance in clinical research studies and likely to find its way into clinical practice; supporting diagnosis, prognosis, and monitoring of treatment for dementia and other neurodegenerative diseases. It has been noted that visual rating of WMH has important limitations and hence a more detailed segmentation of WMH is preferred. Various automated WMH segmentation techniques …

2fly With Rpi - Evaluating The Raspberry Pi For Glass Cockpit Applications, Donald R. Morris

ASA Multidisciplinary Research Symposium

Evaluating the capabilities of Raspberry Pi computers to be used in embedded glass cockpit applications for experimental aircraft. This includes details of what is required for these applications as well as how well the Raspberry Pi 3B can perform in this role.

Simple Implementation Of An Elgamal Digital Signature And A Brute Force Attack On It, Valeriia Laryoshyna

Student Works

This study is an attempt to show a basic mathematical usage of the concepts behind digital signatures and to provide a simple approach and understanding to cracking basic digital signatures. The approach takes on simple C programming of the ElGamal digital signature to identify some limits that can be encountered and provide considerations for making more complex code. Additionally, there is a literature review of the ElGamal digital signature and the brute force attack.

The research component of this project provides a list of possible ways to crack the basic implementations and classifies the different approaches that could be taken …

Natural Language Processing Based Generator Of Testing Instruments, Qianqian Wang

Electronic Theses, Projects, and Dissertations

Natural Language Processing (NLP) is the field of study that focuses on the interactions between human language and computers. By “natural language” we mean a language that is used for everyday communication by humans. Different from programming languages, natural languages are hard to be defined with accurate rules. NLP is developing rapidly and it has been widely used in different industries. Technologies based on NLP are becoming increasingly widespread, for example, Siri or Alexa are intelligent personal assistants using NLP build in an algorithm to communicate with people. “Natural Language Processing Based Generator of Testing Instruments” is a stand-alone program …

In Search Of Homo Sociologicus, Yunqi Xue

Dissertations, Theses, and Capstone Projects

The subject of this dissertation is to build an epistemic logic system that is able to show the spreading of knowledge and beliefs in a social network that contains multiple subgroups. Epistemic logic is the study of logical systems that express mathematical properties of knowledge and belief. In recent years, there have been increasing number of new epistemic logic systems that are focused on community properties such as knowledge and belief adoption among friends.

We are interested in revisable and actionable social knowledge/belief that leads to a large group action. Instead of centralized coordination, bottom-up approach is our focus. We …

Research On Improving Navigation Safety Based On Big Data And Cloud Computing Technology For Qiongzhou Strait, Rui Wang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.