Digital Commons Network^™

A Legal Perspective On Corporate Social Responsibility (Csr), Tala Zein, Sarah Zein

BAU Journal - Creative Sustainable Development

Recent years have been marked by a remarkable decline in trust and confidence in the economy as well as in the business community, as a growing number of economic scandals are being reported by observers and whistleblowers. The need for better governance and higher ethical standards has become a focal issue for governments, regulators, supervisors and business actors themselves. In this context, corporate social responsibility (CSR) has come to play an increasingly important role in business and corporate regulation, paving the way for ethical business practices, as the concept of corporate social responsibility encompasses key components of economic growth, social …

Identification Of Patterns And Disruptions In Ambient Sensor Data From Private Homes, Yan Wang

USF Tampa Graduate Theses and Dissertations

The world’s population is rapidly aging and the increasing demand for home and health care services from this aging population brings unprecedented challenges to the economy and society. Ambient-assisted smart homes, residences equipped with ambient sensors to monitor the resident’s daily activities in a continuous and unobtrusive way, present great potential to manage the growing care service needs of this older population segment, and enable them to age-in-place.

Despite growing research, using ambient sensor data from private homes to monitor daily activities, health and wellness still faces significant challenges. To study ambient sensor data from private homes where annotated data …

Evolution Of Computational Thinking Contextualized In A Teacher-Student Collaborative Learning Environment., John Arthur Underwood

LSU Doctoral Dissertations

The discussion of Computational Thinking as a pedagogical concept is now essential as it has found itself integrated into the core science disciplines with its inclusion in all of the Next Generation Science Standards (NGSS, 2018). The need for a practical and functional definition for teacher practitioners is a driving point for many recent research endeavors. Across the United States school systems are currently seeking new methods for expanding their students’ ability to analytically think and to employee real-world problem-solving strategies (Hopson, Simms, and Knezek, 2001). The need for STEM trained individuals crosses both the vocational certified and college degreed …

Research On Failure Modes Analysis Based On Weighted Evidence Theory, Lulu Shao, Jihong Han, Niu Kan, Xiaohu Liu, Shao Fang

Journal of System Simulation

Abstract: Aiming at the risk priority numbers of different failure modes being equal and the criticality of the fault modes changing greatly due to the tiny change of the risk parameters, a method of the failure modes analysis based on the weighted evidence theory is proposed from the perspective of the methodology of dealing with the uncertainty problem. The method qualifies the epistemic uncertainty existing in the expert evaluation of the risk parameters into the basic belief assignment and expert attribute weight respectively, and the information propagation and processing of the epistemic uncertainty is solved, and the ordered arrangement …

Predicate Informed Syntax-Guidance For Semantic Role Labeling, Sijia Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we consider neural network approaches to the semantic role labeling task in seman-tic parsing. Recent state-of-the-art results for semantic role labeling are achieved by combiningLSTM neural networks and pre-trained features. This work offers a simple BERT-based modelwhich shows that, contrary to the popular belief that more complexity means better performance,removing LSTM improves the state of the art for span-based semantic role labeling. This modelhas improved F1 scores on both the test set of CoNLL-2012, and the Brown test set of CoNLL-2005 by at least 3 percentage points.In addition to this refinement of existing architectures, we also propose …

Centrality Of Blockchain, Zixuan Li

All Computer Science and Engineering Research

Decentralization is widely recognized as the property and one of most important advantage of blockchain over legacy systems. However, decentralization is often discussed on the consensus layer and recent research shows the trend of centralization on several subsystem of blockchain. In this project, we measured centralization of Bitcoin and Ethereum on source code, development eco-system, and network node levels. We found that the programming language of project is highly centralized, code clone is very common inside Bitcoin and Ethereum community, and developer contribution distribution is highly centralized. We further discuss how could these centralizations lead to security issues in blockchain. …

Improving Wake-Up-Word And General Speech Recognition Systems, Gamal Mohamed Bohouta

Theses and Dissertations

Automatic Speech Recognition (ASR), a technology that allows a machine to recognize the utterances spoken into a microphone by a person and then converts it to text, is commonly used for different types of applications, such as command and control systems, personal assistant systems, medical systems, disabilities systems, dictation systems, telephony systems, and embedded applications. Due to its extensive use, interest in ASR technology has surged among inventors and researchers alike. They have worked diligently to improve the performance of the ASR systems by developing several techniques or approaches in different aspects,such as enhancing features, training an acoustic model, enhancing …

Chaprates, Brinly Xavier, Micole Amanda Marietta, Nidhi Vedantam

Student Scholar Symposium Abstracts and Posters

On the Chapman campus, through taking and choosing various classes, there is a significant need for communication and feedback between students and peers, professors, tutors, and study groups. With this, we wanted to create an application that enables users from various majors to not only easily and effectively communicate with various people in their field, but one that also enables them to give and receive feedback on various classes through a rating system. We believe that the application will aid students in a myriad of specific ways, including being involved in study groups and getting tutoring help, determining which classes …

Comparison Of Mpi And Spark For Data Science Applications, Manvi Saxena, Shweta Jha, Saba Khan, John Rodgers, Peggy Lindner, Edgar Gabriel

Engineering Management and Systems Engineering Faculty Research & Creative Works

Data Science applications represent a growing fraction of the scientific computing workload, many of them written in Python. The goal of this paper is to compare two popular parallel programming models, namely MPI and Apache Spark for Python based Data Science applications. The paper presents communication and file I/O microbenchmarks to evaluate the MPI support for Python applications and uses two applications use-cases from Natural Language Processing to compare the performance of the MPI and the Spark versions. Our results indicate that the MPI version shows better scalability and performance than the PySpark version of the code. On the other …

Using Online Discussions To Connect Theory And Practice In Core Engineering Undergraduate Courses, Lisa B. Bosman, Somesh Roy, Walter M. Mcdonald, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

Providing engineering undergraduate students opportunities to connect real-world applications with theory is key to preparing them for the workforce; however, this task often requires a balancing act between meeting course objectives in content-heavy core engineering undergraduate courses and providing experiences that connect real-world applications with theory. This study seeks to address this problem through the integration of online discussion prompts to promote a connection to real-world practical applications. The study included undergraduate students enrolled in three engineering core courses. The hypothesis was that participation in online discussions (using prompts) would lead to 1) an increase in student empowerment towards self-regulated …

On The Characterization Of Natural Language Structure And Literary Stylometry - A Network Science Approach, Younis Anas Younis Al Rozz

Theses and Dissertations

Natural language processing (NLP) techniques have been through many advancements in recent years, linguistics and scientist utilized these techniques to solve many challenges related to written language and literary. Problems such as finding the genetic relationships among languages, attributing author of a text and categorizing text by genre have been treated throughout the years using conventional statistical methods, for instance, bag of words (BoW), N-gram, the frequency of words and the lexical distance between words. By considering written language as a complex system, network science tools and techniques can be used to address those problems. A unified methodology is proposed …

An Algorithm For Building Language Superfamilies Using Swadesh Lists, Bill Mutabazi

School of Computing: Dissertations, Theses, and Student Research

The main contributions of this thesis are the following: i. Developing an algorithm to generate language families and superfamilies given for each input language a Swadesh list represented using the international phonetic alphabet (IPA) notation. ii. The algorithm is novel in using the Levenshtein distance metric on the IPA representation and in the way it measures overall distance between pairs of Swadesh lists. iii. Building a Swadesh list for the author's native Kinyarwanda language because a Swadesh list could not be found even after an extensive search for it.

Advisor: Peter Z. Revesz

2020 - The Twenty-Fourth Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Twenty-fourth Annual Symposium of Student Scholars, held on April 16, 2020. Includes abstracts from the presentations and posters.

Research On Image Description Method Based On Neural Network, Kong Rui, Xie Wei, Lei Tai

Journal of System Simulation

Abstract: The automatic recognition and automatically describing image content is an important research direction to the artificial intelligence to connect the computer vision and the natural language processing. A method of describing the image content is proposed to generate the natural language by using the deep neural network model. The model consists of a convolutional neural network (CNN) and a recurrent neural network (RNN). The CNN is used to extract features of the input image to generate a fixed-length feature vector, which initializes the RNN to generate the sentences. Experimental results on the MSCOCO image description dataset show the syntactic …

Understanding Individual Color Perceptions Within Print And Digital Media, Morgan Haskins

Honors Theses

Color is a subjective attribute that is seen differently by each individual and this research is intended to build upon the subjective nature of color perceptions. This research aims to determine the effect of subjectivity on print and digital design and of extended gamut printing and effective color management on color perception. The significance of understanding color perception is directly applicable to consumer perception of designs using color. If designers want their brand to be immediately recognized and be positively accepted, they must be able to accurately reproduce their brand colors with little to no color difference and be able …

Multimodal Mental Health Analysis In Social Media, Amir Hossein Yazdavar, Mohammad Saeid Mahdavinejad, Goonmeet Bajaj, William Romine, Amit P. Sheth, Amir Hassan Monadjemi, Krishnaprasad Thirunarayan, John M. Meddar, Annie Myers, Jyotishman Pathak, Pascal Hitzler

Publications

Depression is a major public health concern in the U.S. and globally. While successful early identification and treatment can lead to many positive health and behavioral outcomes, depression, remains undiagnosed, untreated or undertreated due to several reasons, including denial of the illness as well as cultural and social stigma. With the ubiquity of social media platforms, millions of people are now sharing their online persona by expressing their thoughts, moods, emotions, and even their daily struggles with mental health on social media. Unlike traditional observational cohort studies conducted through questionnaires and self-reported surveys, we explore the reliable detection of depressive …

Using Fuzzy Models And Time Series Analysis To Predict Water Quality, Zhao Fu, Mei Yang, Jacimaria R. Batista

Electrical & Computer Engineering Faculty Research

Water quality prediction is very important for both water resource scheduling and management. Simple linear regression analysis and artificial neural network models cannot accurately forecast water quality because of complicated linear and nonlinear relationships in the water quality dataset. An adaptive neuro-fuzzy inference system (ANFIS) that can integrate linear and nonlinear relationships has been proposed to address the problem. However, the ANFIS model can only work in scenarios where input and target parameters have strong correlations. In this paper, a fuzzy model integrated with a time series data analysis method is proposed to address the water quality prediction problem when …

Classification Of Seismic Vulnerability Based On Machine Learning Techniques For Rc Frames, Seyed Hooman Ghasemi, Hossein Bahrami, Mahdi Akbari

Henry M. Rowan College of Engineering Departmental Research

Seismic vulnerability means the inability of historical and monumental buildings to withstand the effects of seismic forces. This article presents a classification model to specify the damage state of the Reinforced Concrete (RC) frames based on a collection of datasets from the damaged buildings in Bingol earthquake of Turkey for use in the learning process of the algorithm. The proposed model uses two classifiers including the redundancy and also the construction quality of the buildings to estimate the class of damage from four categories including none, light, moderate and severe. The available database of the considered earthquake includes the information …

Identifying Easy Indicators Of Dementia, Swati Padhee, Tanvi Banerjee, Valerie L. Shalin, Krishnaprasad Thirunarayan

Celebration of Undergraduate & Graduate Research, Scholarship, and Creative Activities Materials

Alzheimer’s Disease (AD) is a degenerative chronic neurodegenerative disease that affects millions of people and whose care costs billions of dollars. There is growing evidence that variations in speech and language may be early indicators of dementia. One of the most initial symptoms of dementia is speech impairment, including difficulty in finding words and changes to the grammatical structure. These early indicators can be detected by having the patients perform a picture description task, such as the Cookie Theft task from the Boston Diagnostic Aphasia Examination. However, much of the state-of-the-art NLP for dementia has been limited due to the …

Dod Mission Engineering And Integration Explorative-Exploitative Architecture For Technology Innovation, Jose L. Bricio-Neto

Engineering Management & Systems Engineering Theses & Dissertations

The ability of U.S. Department of Defense to achieve timely innovation in support of U.S. National Defense and Military Strategies continues to increase in significance. The growing challenges in U.S. Department of Defense (DoD) technological innovation in a context of global security and rapid pace of global competitiveness continue to reveal many shortcomings in current weapon systems development and acquisition practice. As the pace of technological innovation is accelerating, the DoD faces the challenge that the same disruptive technological advances are also being made available to or developed by its adversaries. Based on literature review, no innovation system theory exists …

Historical Edge Assessment: Spatial Comparative Analysis, Nabil Mohareb

Architecture and Planning Journal (APJ)

This paper develops a quantitative analysis method that is capable of examining the urban edges of historic cities with reference to their spatial configuration. This aim provides the opportunity for assessing the current situation of historic urban edges. Accordingly, this assessment will help in developing appropriate regeneration plans for the site. Second, it enhances the process of comparison with other cases, in order to inherit those successful interventions that might fit according to base similarities, such as the spatial configuration, architectural characteristics, or other features, in addition, searching for any repetitive patterns. Assessing the current situation requires the evaluation of …

Analyzing And Learning The Language For Different Types Of Harassment, Mohammadreza Rezvan, Saeedeh Shekarpour, Faisal Alshargi, Krishnaprasad Thirunarayan, Valerie L. Shalin, Amit P. Sheth

Publications

THIS ARTICLE USES WORDS OR LANGUAGE THAT IS CONSIDERED PROFANE, VULGAR, OR OFFENSIVE BY SOME READERS. The presence of a significant amount of harassment in user-generated content and its negative impact calls for robust automatic detection approaches. This requires the identification of different types of harassment. Earlier work has classified harassing language in terms of hurtfulness, abusiveness, sentiment, and profanity. However, to identify and understand harassment more accurately, it is essential to determine the contextual type that captures the interrelated conditions in which harassing language occurs. In this paper we introduce the notion of contextual type in harassment by distinguishing …

Fuzzy Multi Criteria Decision Optimization For Analyzing The Trade Space Of The Myoelectric Prosthetic Arm Architecture, Kenneth Garner

Theses and Dissertations

Fuzzy logic provides a means to address uncertainty in selecting optimal elements in the systems design process. Complex models have been used in the past that inadequately address a dynamic environment with evolving technological changes. Using novel discoveries in mathematical algorithms coupled with existing system engineering tools will prove to increase stakeholder satisfaction and a reduce life-cycle cost of the system to be created. This can be seen within a toy problem that resides in the advance prosthetic industry. Although the prosthetic industry is only an example of complex design constraints this research will prove to be a valuable asset …

Development System For Intelligent Surgical Box-Trainer Research, Janos Grantner

Faculty Research and Creative Activities Award (FRACAA)

Laparoscopic surgery, also referred to as minimally invasive surgery, describes the performance of surgical procedures with the assistance of a video camera and several thin surgical instruments. During the surgical procedure, small incisions of up to half an inch are made and plastic tubes called ports are placed through these incisions. The camera and the surgical instruments are then introduced through the ports which allow access to the inside of the patient. The video camera becomes a surgeon's eyes. Excellent eye-hand coordination capabilities are crucial to carry out laparoscopic surgery procedures. Gaining basic laparoscopic skills such as …

Dynamic Procedural Music Generation From Npc Attributes, Megan E. Washburn

Master's Theses

Procedural content generation for video games (PCGG) has seen a steep increase in the past decade, aiming to foster emergent gameplay as well as to address the challenge of producing large amounts of engaging content quickly. Most work in PCGG has been focused on generating art and assets such as levels, textures, and models, or on narrative design to generate storylines and progression paths. Given the difficulty of generating harmonically pleasing and interesting music, procedural music generation for games (PMGG) has not seen as much attention during this time.

Music in video games is essential for establishing developers' intended mood …

Using Knowledge Bases For Question Answering, Yunshi Lan

Dissertations and Theses Collection (Open Access)

A knowledge base (KB) is a well-structured database, which contains many of entities and their relations. With the fast development of large-scale knowledge bases such as Freebase, DBpedia and YAGO, knowledge bases have become an important resource, which can serve many applications, such as dialogue system, textual entailment, question answering and so on. These applications play significant roles in real-world industry.

In this dissertation, we try to explore the entailment information and more general entity-relation information from the KBs. Recognizing textual entailment (RTE) is a task to infer the entailment relations between sentences. We need to decide whether a hypothesis …

A Reference Architecture For Cubesat Development, Luke J. Farrell

Theses and Dissertations

Developing a space vehicle is a complex and detailed process, and while CubeSats are smaller and more accessible than traditional satellites the design process is relatively unchanged. Creating a viable space vehicle design requires detailed analysis of a set of mission needs in order to define the mission, with this need set used to then create the specific mission requirements. These requirements are used to formulate a concept of operations, and then move into developing a physical system for executing the mission. The successful production of CubeSats within an organization is contingent upon the accurate execution of the general CubeSat …

Techniques To Solve Decision-Making Problems, Dilnoz Tulkunovna Muhamediyeva, Bekmuratov Fayzievich Tulkun

Chemical Technology, Control and Management

Solving decision-making problems in poorly formalized systems only with the help of deterministic and probabilistic methods is insufficient. To do this, it is necessary to widely apply the methods of hybrid intelligent systems and, especially, the methods of “soft” calculations (SoftCalculation, SoftComputing) and the directions of ComputationalIntelligence — intelligent computing technologies that are emerging on this theoretical and methodological base. An immune - fuzzy algorithm for the synthesis of fuzzy inference systems (FIS) is proposed. A two-stage adaptive FIS synthesis algorithm is described. At the first stage, the initial fuzzy parameters are clustered in order to reduce the number of …

Multiple Fault Analysis Using A Fuzzy Logic Technique For An Inverter Control Drive, V. Kannan, M. Santhi, D. Sureshkumar

Journal of Marine Science and Technology–Taiwan

This study evaluates electrical faults on an inverter control drive using simulations in MATLAB Simulink and recommends a fuzzy logic technique for analyzing electrical faults of such drives. Fault analysis of a drive is based on voltage, speed, current, and torque. This article presents soft computing methods for voltage fluctuations and fault detection in an inverter switch to an inverter control drive with the support of a MATLAB Simulink model. Accordingly, failure analysis techniques based on fuzzy logic are explained. The fuzzy system allows altered voltage and open-switch fault detection. Soft computing techniques offer excellent analysis of a faulty structure, …

The Voltage Regulation Of A Buck Converter Using A Neural Network Predictive Controller, Sepehr Saadatmand, Pourya Shamsi, Mehdi Ferdowsi

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a neural network predictive controller (NNPC) is proposed to control a buck converter. Conventional controllers such as proportional-integral (PI) or proportional-integral-derivative (PID) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller in the start-up, load change, or reference change is not optimal since the system model changes by changing the operating point. The neural network predictive controller optimally controls the buck converter by following the concept of the traditional model predictive controller. The advantage of the NNPC is that the neural network system identification decreases the inaccuracy of …