Digital Commons Network^™

Three- And Four-Year Olds Learn About Gears Through Arts Incorporation, Dessy Stoycheva, Leann M. Perkins

Journal of STEM Arts, Crafts, and Constructions

This research paper explores art integration into a science lesson unit that follows the Next Generation Science Standards (K-PS2-1) and focuses on the effects on memory retention of key concepts along with levels of enjoyment. An experiment was conducted with children ages 3 and 4 teaching scientific concepts about gears while incorporating student-made art products. The children were assigned to alternating experimental (art-integrated) or control (no art) conditions during the four stages of the lesson. The results did not show statistically significant differences at the alpha = 0.05 level between conditions in the amount of information retained based on the …

Recent Semantic Changes For The Term "Digital", Tore Brattli

Proceedings from the Document Academy

The term digital originates from the Latin word for finger/counting and has for many years been used to denote discrete signals and information, as opposed to analog. Discrete representation is an important principle, not only in computers, but also for (printed) text, music scores and even our genes. Recently however, the use of the term has increased and the meaning expanded to include almost everything related to information technology, e.g. digital natives and digital addiction. This study investigates the core principles of digital representation and compares this concept with the recent usage, with a focus on Norwegian media. The purpose …

‘‘Can I Drop It This Time?’’ Gender And Collaborative Group Dynamics In An Engineering Design-Based Afterschool Program, Jessica Schnittka, Christine Schnittka

Journal of Pre-College Engineering Education Research (J-PEER)

The 21st century has brought an increasing demand for expertise in science, technology, engineering, and math (STEM). Although strides have been made towards increasing gender diversity in several of these disciplines, engineering remains primarily male dominated. In response, the U.S. educational system has attempted to make engineering curriculum more engaging, informative, and welcoming to girls. Specifically, project-based and design-based learning pedagogies promise to make engineering interesting and accessible for girls while enculturating them into the world of engineering and scientific inquiry. Outcomes for girls learning in these contexts have been mixed. The purpose of this study was to explore how …

Ole Miss Engineer 2016-2017

Ole Miss Engineer

No abstract provided.

Optimal Attribute Weighting In A Nearest Neighbor Classifier, Jugal Raju Sheth

Electrical Engineering Theses - Archive

Nearest Neighbor algorithms are non-parametric algorithms that use distance measure techniques for classification and regressions. This thesis, first improves the traditional nearest neighbor classifier by optimizing its distance measure using a second order training algorithm. It then presents a second order method to adjust center vectors. It is shown that the distance measure weight optimization and center vector optimization, individually and together reduce the final classification error. The testing error of our algorithm is shown to be less than that of LVQ V.2.1

Design And Deployment Of A Real Time Wireless Controller For An Active Angle Foot Orthosis, Mary Ann George

Manipal Journal of Science and Technology

The complex ankle foot movements of patients suffering from muscular and neurological abnormalities are supported and restored by an active ankle foot orthosis (AFO). Foot drop is a symptom in which the muscles around the ankle become weak due to the paralysis of the neural system. Patients with foot drop show abnormal gait patterns, which can reduce the speed of walking and increase the energy consumption. The gait pattern deviation in patients with foot drop can be corrected by designing a fuzzy controller for gait pattern. This paper focuses on designing a fuzzy controller for an active AFO that can …

Examination And Utilization Of Rare Features In Text Classification Of Injury Narratives, Hsin-Ying Huang

Open Access Dissertations

Thanks to the advances in computing and information technology, analyzing injury surveillance data with statistical machine learning methods has grown in popularity, complexity, and quality over recent years. During that same time, researchers have recognized the limitations of statistical text analysis with limited training data. In response to the two primary challenges for statistical text analysis, dimensionality reduction and sparse data, many studies have focused on improving machine learning algorithms. Less research has been done, though, to examine and improve statistical machine learning methods in text classification from a linguistic perspective.

This study addresses this research gap by examining the …

A Unicorn's Tale: Examining The Experiences Of Black Women In Engineering Industry, Monique S. Ross

Open Access Dissertations

Black women have recently been identified as the most educated demographic in the United States, and yet they are grossly underrepresented in engineering. They comprise 6.4 % of the U.S. population and only 0.72 % of engineering industry. Meanwhile, engineers have been identified as the key to the United States’ ability to maintain its prominence and leadership in a competitive global economy due to their contribution to maintaining and improving our infrastructures and standard of living. This significance to society has spawned national initiatives geared towards broadening participation in engineering. This research study was designed to explore the experiences of …

Evaluation Of User Perceived Qoe In Mobile Systems Using Social Media Analytics, Ahmed Yaseen Mjhool

Theses and Dissertations

In mobile system environments, the quality perceived by users is inconstant and reliant on many factors such as cellular network, data connection, cost, coverage area, etc. Even though Quality of Service (QoS) management is enabled in most modern telecommunication systems, it does not guarantee the actual user’s perceived Quality of Experience (QoE) level. Many cellular networks rely on engineering test research, such as drive testing or smart mobile applications, to collect the required parameters in order to provide better service quality to users. However, this approach does not always yield customer satisfaction. Hence, user opinions should be considered. These opinions …

Development Of A Fundamental Autonomous Ground Vehicle Cruise Control Using Matlab And Simulink, Luis F. Martinez

Theses and Dissertations

This study presents and describes the development of a fully autonomous vehicle cruise control system covering the vehicle dynamics and control design needed to simulate such system. It encompasses obstacle avoidance, intelligent-and-optimal lane change as well as adaptive behavior. This study offers a comprehensive two-dimensional cruise control with three degrees of freedom and it is designed using active obstacle avoidance controllers. It also includes optimized fuzzy logic for optimal vehicle trajectory and an extensive array of control law methodology. The end work shows a complete simulation run using MATLAB and Simulink.

A Cad System For Early Diagnosis Of Autism Using Different Imaging Modalities., Marwa Maher Tawfik Ismail

Electronic Theses and Dissertations

The term “autism spectrum disorder” (ASD) refers to a collection of neuro-developmental disorders that affect linguistic, behavioral, and social skills. Autism has many symptoms, most prominently, social impairment and repetitive behaviors. It is crucial to diagnose autism at an early stage for better assessment and investigation of this complex syndrome. There have been a lot of efforts to diagnose ASD using different techniques, such as imaging modalities, genetic techniques, and behavior reports. Imaging modalities have been extensively exploited for ASD diagnosis, and one of the most successful ones is Magnetic resonance imaging(MRI),where it has shown promise for the early diagnosis …

Hashtag Recommendation With Topical Attention-Based Lstm, Yang Li, Ting Liu, Jing Jiang, Liang Zhang

Research Collection School Of Computing and Information Systems

Microblogging services allow users to create hashtags to categorize their posts. In recent years,the task of recommending hashtags for microblogs has been given increasing attention. However,most of existing methods depend on hand-crafted features. Motivated by the successful use oflong short-term memory (LSTM) for many natural language processing tasks, in this paper, weadopt LSTM to learn the representation of a microblog post. Observing that hashtags indicatethe primary topics of microblog posts, we propose a novel attention-based LSTM model whichincorporates topic modeling into the LSTM architecture through an attention mechanism. Weevaluate our model using a large real-world dataset. Experimental results show that …

An Agent-Based Approach To Human Migration Movement, Larry Lin, Kathleen M. Carley, Shih-Fen Cheng

Research Collection School Of Computing and Information Systems

How are the populations of the world likely to shift? Which countries will be impacted by sea-level rise? This paper uses a country-level agent-based dynamic network model to examine shifts in population given network relations among countries, which influences overall population change. Some of the networks considered include: alliance networks, shared language networks, economic influence networks, and proximity networks. Validation of model is done for migration probabilities between countries, as well as for country populations and distributions. The proposed framework provides a way to explore the interaction between climate change and policy factors at a global scale.

Genetic Algorithm Optimization Of Sos Meta-Architecture Attributes For Fuzzy Rule Based Assessments, Andrew Renault, Cihan H. Dagli

Engineering Management and Systems Engineering Faculty Research & Creative Works

The analysis of an acknowledged systems of systems (SoS) meta-architecture requires a preliminary method for potential trade space exploration to ensure compliance to evolving capability requirements. It is important to assess the SoS meta-architecture concept to ensure that it satisfies all stakeholder needs and requirements in the early stages of development. There are numerous linguistic terms called key performance attributes (KPAs) that could be used to assess the different aspects of the architectures capabilities, however, too many KPAs could complicate the assessment. The initial population of suitable KPAs is reduced through non-derivative based optimization employed by a genetic algorithm (GA) …

Fuzzy Expert Systems: A More Human-Based Approach For Sensorial Evaluation Of Coffee-Bean Attributes To Derive Quality Scoring, Javier A. Livio

Theses and Dissertations

In the coffee industry, "cupping" is the process of sensorial evaluations of coffee beans, also known as Sample Evaluation. This process is done for three major reasons: to determine the actual sensory differences between coffee samples, to describe the flavors of the samples, and to determine preference of product. In totality, cupping targets the measurement of the coffee's quality related to fragrance, taste, and appearance which are expressed with a final numerical score. When cupping, the expert judge writes down the individual components' scores (fragrance, aftertaste, acidity, body, etc.) and ranks their intensities for reference. Despite the fact the cuppers …

Clinical Narrative Classification Using Discriminant Word Embeddings With Elm, Paula Lauren, Guangzhi Qu, Feng Zhang, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Clinical Texts Are Inherently Complex Due to the Medical Domain Expertise Required for Content Comprehension. in Addition, the Unstructured Nature of These Narratives Poses a Challenge for Automatically Extracting Information. in Natural Language Processing, the Use of Word Embeddings Are an Effective Approach to Generate Word Representations (Vectors) in a Low Dimensional Space. in This Paper We Use a Log-Linear Model (A Type of Neural Language Model) and Linear Discriminant Analysis with a Kernel-Based Extreme Learning Machine (Elm) to Map the Clinical Texts to the Medical Code. Experimental Results on Clinical Texts Indicate Improvement with Elm in Comparison to Svm …

Fuzzy Logic Controlofgantry Crane System, Betim Shabani

UBT International Conference

The use of gantry crane systems for transporting payload is very common in industrial application. However, moving the payload using the crane is not an easy task especially when strict specifications on the swing angle and on the transfer time need to be satisfied. To overcome this problem, an intelligent gantry crane system had been introduced. Fuzzy logic controllers were adopted, designed and implemented for controlling payload position as well as the swing angle of the gantry crane. Fuzzy logic defines rules that determine the behavior of the system using word descriptions instead of mathematical equations also fuzzy logic control …

Shadow Puppet Plays In Elementary Science Methods Class Help Preservice Teachers Learn About Minority Scientists, Phyllis Gray, Audrey C. Rule, Anneliese Gentzsch, Denise Tallakson

Journal of STEM Arts, Crafts, and Constructions

This practical article describes an arts-integrated project with engineering design and science concepts from the Next Generation Science Standards, art principles from the National Arts Standards, as well as ideas under the theme of “Culture” from the National Council for the Social Studies Standards. Preservice teachers in an undergraduate science methods class researched the background, life, and accomplishments of a minority scientist by reading books and articles about the person. They created a script to present the experiences and contributions of the scientist to other preservice teachers and, eventually, elementary students. Shadow puppets were constructed out of cardboard to portray …

Parallel Reference Speaker Weighting For Kinematic-Independent Acoustic-To-Articulatory Inversion, An Ji, Michael T. Johnson, Jeffrey J. Berry

Speech Pathology and Audiology Faculty Research and Publications

Acoustic-to-articulatory inversion, the estimation of articulatory kinematics from an acoustic waveform, is a challenging but important problem. Accurate estimation of articulatory movements has the potential for significant impact on our understanding of speech production, on our capacity to assess and treat pathologies in a clinical setting, and on speech technologies such as computer aided pronunciation assessment and audio-video synthesis. However, because of the complex and speaker-specific relationship between articulation and acoustics, existing approaches for inversion do not generalize well across speakers. As acquiring speaker-specific kinematic data for training is not feasible in many practical applications, this remains an important and …

Special Issue On Cyberharassment Investigation: Advances And Trends, Joanne Bryce, Virginia N. L. Franqueira, Andrew Marrington

Journal of Digital Forensics, Security and Law

Empirical and anecdotal evidence indicates that cyberharassment is more prevalent as the use of social media becomes increasingly widespread, making geography and physical proximity irrelevant. Cyberharassment can take different forms (e.g., cyberbullying, cyberstalking, cybertrolling), and be motivated by the objectives of inflicting distress, exercising control, impersonation, and defamation. Little is currently known about the modus operandi of offenders and their psychological characteristics. Investigation of these behaviours is particularly challenging because it involves digital evidence distributed across the devices of both alleged offenders and victims, as well as online service providers, sometimes over an extended period of time. This special issue …

Table Of Contents

Journal of Digital Forensics, Security and Law

No abstract provided.

Toward Online Linguistic Surveillance Of Threatening Messages, Brian H. Spitzberg, Jean Mark Gawron

Journal of Digital Forensics, Security and Law

Threats are communicative acts, but it is not always obvious what they communicate or when they communicate imminent credible and serious risk. This paper proposes a research- and theory-based set of over 20 potential linguistic risk indicators that may discriminate credible from non-credible threats within online threat message corpora. Two prongs are proposed: (1) Using expert and layperson ratings to validate subjective scales in relation to annotated known risk messages, and (2) Using the resulting annotated corpora for automated machine learning with computational linguistic analyses to classify non-threats, false threats, and credible threats. Rating scales are proposed, existing threat corpora …

Activist: A New Framework For Dataset Labelling, Jack O'Neill, Sarah Jane Delany, Brian Mac Namee

Conference papers

Acquiring labels for large datasets can be a costly and time-consuming process. This has motivated the development of the semi-supervised learning problem domain, which makes use of unlabelled data — in conjunction with a small amount of labelled data — to infer the correct labels of a partially labelled dataset. Active Learning is one of the most successful approaches to semi-supervised learning, and has been shown to reduce the cost and time taken to produce a fully labelled dataset. In this paper we present Activist; a free, online, state-of-the-art platform which leverages active learning techniques to improve the efficiency of …

Model-Free And Model-Based Active Learning For Regression, Jack O'Neill, Sarah Jane Delany, Brian Macnamee

Conference papers

Training machine learning models often requires large labelled datasets, which can be both expensive and time-consuming to obtain. Active learning aims to selectively choose which data is labelled in order to minimize the total number of labels required to train an effective model. This paper compares model-free and model-based approaches to active learning for regression, finding that model-free approaches, in addition to being less computationally intensive to implement, are more effective in improving the performance of linear regressions than model-based alternatives.

Public Transport Crowding Valuation: Evidence From College Students In Guangzhou, Jianrong Liu, Huiying Wen

Journal of Public Transportation

Overcrowding has grown to be an increasingly important issue for public transit in Guangzhou, China. To capture traveler benefits of reduced crowding from improved public transport, it is necessary to identify the relevant importance of crowding to travelers. This paper analyzes the disutility of crowding in metro car and bus transit with discrete choice models. Based on the stated preference survey data from college students in Guangzhou, the results show that there is non-negligible impact of crowding on passenger travel. The relationship between the disutility of crowding and standee density is not linear; that is, the disutility increases at a …

Capacity Building For Sustainable Workforce In The Construction Industry, Edelmiro F. Escamilla, Mohammadreza Ostadalimakhmalbaf

The Professional Constructor

Research has shown that the construction industry will face workforce shortages that will increase delivery cost and completion time. The purpose of this paper is to first identify and synthesize the fundamental factors impacting recruitment and retention of the potential construction workforce. A qualitative approach was employed in order to collect and synthesize known factors related to workforce development and capacity building for the construction industry. The paper then presents a conceptual framework for conducting research on capacity generation of a sustainable construction workforce—by considering the impact of family unit and cultural values, career path perceptions, higher educational attainment, and …

Activist: A New Framework For Dataset Labelling, Jack O'Neill, Sarah Jane Delany, Brian Macnamee

Conference papers

Acquiring labels for large datasets can be a costly and time-consuming process. This has motivated the development of the semi-supervised learning problem domain, which makes use of unlabelled data — in conjunction with a small amount of labelled data — to infer the correct labels of a partially labelled dataset. Active Learning is one of the most successful approaches to semi-supervised learning, and has been shown to reduce the cost and time taken to produce a fully labelled dataset. In this paper we present Activist; a free, online, state-of-the-art platform which leverages active learning techniques to improve the efficiency …

Research On Navigation Guarantee Measures Of Modified Dan’Gan Waterway Routeing System, Peng Chang

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Risk Assessment On Oil Spill In Dalian Port Sea Area, Yang Wu

Maritime Safety & Environment Management Dissertations (Dalian)

No abstract provided.

Anti-Forensics: Furthering Digital Forensic Science Through A New Extended, Granular Taxonomy, Kevin Conlan, Ibrahim Baggili, Frank Breitinger

Electrical & Computer Engineering and Computer Science Faculty Publications

Anti-forensic tools, techniques and methods are becoming a formidable obstacle for the digital forensic community. Thus, new research initiatives and strategies must be formulated to address this growing problem. In this work we first collect and categorize 308 antidigital forensic tools to survey the field. We then devise an extended anti-forensic taxonomy to the one proposed by Rogers (2006) in order to create a more comprehensive taxonomy and facilitate linguistic standardization. Our work also takes into consideration anti-forensic activity which utilizes tools that were not originally designed for antiforensic purposes, but can still be used with malicious intent. This category …