Digital Commons Network^™

How To Enhance Interdisciplinary Competence—Interdisciplinary Problem-Based Learning Versus Interdisciplinary Project-Based Learning, Mirjam Brassler, Jan Dettmers

Interdisciplinary Journal of Problem-Based Learning

Interdisciplinary competence is important in academia for both employability and sustainable development. However, to date, there are no specific interdisciplinary education models and, naturally, no empirical studies to assess them. Since problem-based learning (PBL) and project-based learning (PjBL) are learning approaches that emphasize students’ collaboration, both pedagogies seem suitable to enhance students’ interdisciplinary competence. Based on the principle of constructive alignment and four instructional principles on interdisciplinary learning, this paper proposes that students profit more from interdisciplinary PBL (iPBL) than interdisciplinary PjBL (iPjBL). A pre-post study was conducted with a sample of 95 students participating in iPBL and 183 students …

Explaining Trained Neural Networks With Semantic Web Technologies: First Steps, Md Kamruzzaman Sarker, Ning Xie, Derek Doran, Michael L. Raymer, Pascal Hitzler

Computer Science and Engineering Faculty Publications

The ever increasing prevalence of publicly available struc-tured data on the World Wide Web enables new applications in a varietyof domains. In this paper, we provide a conceptual approach that lever-ages such data in order to explain the input-output behavior of trainedartificial neural networks. We apply existing Semantic Web technologiesin order to provide an experimental proof of concept.

A Critical Path Problem Using Triangular Neutrosophic Number, Florentin Smarandache, Mai Mohamed, Yongquan Zhou, Mohamed Abdel-Baset

Branch Mathematics and Statistics Faculty and Staff Publications

The Critical Path Method (CPM) is one of several related techniques for planning and managing of complicated projects in real world applications. In many situations, the data obtained for decision makers are only approximate, which gives rise of neutrosophic critical path problem. In this paper, the proposed method has been made to find the critical path in network diagram, whose activity time uncertain. The vague parameters in the network are represented by triangular neutrosophic numbers, instead of crisp numbers. At the end of paper, two illustrative examples are provided to validate the proposed approach.

A Hilbert Space Geometric Representation Of Shared Awareness And Joint Decision Making, Mustafa Canan

Engineering Management & Systems Engineering Theses & Dissertations

Two people in the same situation may ascribe very different meanings to their experiences. They will form different awareness, reacting differently to shared information. Various factors can give rise to this behavior. These factors include, but are not limited to, prior knowledge, training, biases, cultural factors, social factors, team vs. individual context, time, resources, and technology. At the individual level, the differences in attaining separate actions by accessing shared information may not be considered as an anomaly from the perspective of rational decision-making. But for group behavior, reacting differently to the shared information can give rise to conflicts and deviations …

A Low-Dimensional Vector Representation For Words Using An Extreme Learning Machine, Paula Lauren, Guangzhi Qu, Guang Bin Huang, Paul Watta, Amaury Lendasse

Engineering Management and Systems Engineering Faculty Research & Creative Works

Word Embeddings Are a Low-Dimensional Vector Representation of Words that Incorporates Context. Two Popular Methods Are Word2vec and Global Vectors (Glove). Word2vec is a Single-Hidden Layer Feedforward Neural Network (Slfn) that Has an Auto-Encoder Influence for Computing a Word Context Matrix using Backpropagation for Training. Glove Computes the Word Context Matrix First Then Performs Matrix Factorization on the Matrix to Arrive at Word Embeddings. Backpropagation is a Typical Training Method for SLFN's, which is Time Consuming and Requires Iterative Tuning. Extreme Learning Machines (Elm) Have the Universal Approximation Capability of SLFN's, based on a Randomly Generated Hidden Layer Weight Matrix …

Hybrid Fuzzy Logic And Extremum Seeking Attitude Control Of Solar Sail Spacecraft, Nikolai Kalnin

Mechanical Engineering Master's Theses

This thesis explores four controllers applied to the attitude control of a solar sail craft with control masses with the goal of showing benefits over more standard control schemes. The controllers examined in this paper are: 1) a PID controller that incorporates a discrete extremum seeking algorithm, 2) a type-1 fuzzy logic controller that incorporates a discrete extremum seeking algorithm, 3) a type-1 fuzzy logic controller, and 4) a type-2 fuzzy logic controller. The first two controllers are examined for their ability to quickly converge to a set of optimal gains over time. The latter two controllers are evaluated for …

Dual Input Microinverter For Tandem Cells, Forrest M. Lipske, Daniel A. Dich-Dang

Electrical Engineering

For every solar panel, there is an inverter which transforms the harvested DC electricity into AC electricity so that it can connect to the grid and power household appliances. In this project, we examined a tandem solar cell being designed by Iris Photovoltaics which has two layers with two distinct outputs, and we explored several solutions to create a microinverter which can handle dual inputs from the tandem PV and combine them into a single AC output. To examine the viability of such a microinverter, we designed and simulated the DC-DC combination portion of the specialized dual input microinverter, resulting …

A Fuzzy Logic-Based Text Classification Method For Social Media, Keyuan Wu

Theses

Social media offer abundant information for studying people’s behaviors, emotions and opinions during the evolution of various rare events such as natural disasters. It is useful to analyze the correlation between social media and human-affected events. This study uses Hurricane Sandy 2012 related Twitter text data to conduct information extraction and text classification. Considering that the original data contains different topics, we need to find the data related to Hurricane Sandy. A fuzzy logic-based approach is introduced to solve the problem of text classification. Inputs used in the proposed fuzzy logic-based model are multiple useful features extracted from each Twitter’s …

Voice Activated Command And Control With Speech Recognition Over Wireless Networks, Tony Ayres, Brian Nolan

The ITB Journal

This paper presents work conducted to date on the development of a voice activated command and control framework specifically for the control of remote devices in a ubiquitous computing environment. The prototype device is a Java controlled Lego Mindstorm robot. The research considers three different scenario configurations. A recognition grammar for command and control of the robot has been created and implemented in Java, in part in the recognition engine and in part on the robot. The physical topology involves Java at each node endpoint, that is, at the handheld PC (iPaq), the PC workstation, the Linux server and onboard …

Statistical Language Models For Graphical Object Recognition, Laura Keyes, Andrew O'Sullivan, Adam Winstanley

The ITB Journal

This paper explores automatic recognition and semantic capture in vector graphics for graphical information systems. The low-level graphical content of graphical documents, such as a map or architectural drawing, are often captured manually and the encoding of the semantic content seen as an extension of this. The large quantity of new and archived graphical data available on paper makes automatic structuring of such graphical data desirable. A successful method for recognising text data uses statistical language models. This work will investigate and evaluate similar and adapted statistical models (Statistical Graphical Langauge Models, SGLM) to graphical languages based on the associations …

Mobile Phone Game Localisation, Leonie Troy, Matt Smith, Richard Gallery

The ITB Journal

Often, mobile phone games are developed over a short time span. Because of the additional work and complexity that localisation requires, such games are frequently produced without localisation in mind. In recent years automation and standardisation of localisation has been developed and promoted by the Localisation Industry Standard Association (LISA) and Oasis. Mobile phone game localisation involves various types of language transfer on a small scale, which challenges the localisation process carried out on a game. Our work investigated the workflow for the localisation of a mobile phone game into Spanish and German using a LISA Standard TMX (Term Base …

Towards Arabic To English Machine Translation, Yasser Salem, Arnold Hensman, Brian Nolan

The ITB Journal

This paper explores how the characteristics of the Arabic language will effect the development of a Machine Translation (MT) tool from Arabic to English. Several distinguishing features of Arabic pertinent to MT will be explored in detail with reference to some potential difficulties that they might present. The paper will conclude with a proposed model incorporating the Role and Reference Grammar (RRG) technique to achieve this end.

Real Time Learning Level Assessment Using Eye Tracking, Saurin S. Parikh, Hari Kalva

MODVIS Workshop

E-Learning is emerging as a convenient and effective learning tool. However, the challenge with eLearning is the lack of effective tools to assess levels of learning. Ability to predict difficult content in real time enables eLearning systems to dynamically provide supplementary content to meet learners’ needs. Recent developments have made possible low-cost eye trackers, which enables a new class of applications based on eye response. In comparison to past attempts using bio-metrics in learning assessments, with eye tracking, we can have access to the exact stimulus that is causing the response. A key aspect of the proposed approach is the …

2016 "Meeting Of The Minds" Research Symposium Abstracts

OSRI Journal of Student Research and Innovation

No abstract provided.

Toward Measuring Network Aesthetics Based On Symmetry, Zengqiang Chen, Matthias Dehmer, Frank Emmert-Streib, Abbe Mowshowitz, Yongtang Shi

Publications and Research

In this exploratory paper, we discuss quantitative graph-theoretical measures of network aesthetics. Related work in this area has typically focused on geometrical features (e.g., line crossings or edge bendiness) of drawings or visual representations of graphs which purportedly affect an observer’s perception. Here we take a very different approach, abandoning reliance on geometrical properties, and apply information-theoretic measures to abstract graphs and networks directly (rather than to their visual representaions) as a means of capturing classical appreciation of structural symmetry. Examples are used solely to motivate the approach to measurement, and to elucidate our symmetry-based mathematical theory of network aesthetics.

Dynamic Risk Analysis Of Construction Delays Using Fuzzy-Failure Mode Effects Analysis, Mohammadsoroush Tafazzoli

UNLV Theses, Dissertations, Professional Papers, and Capstones

Considering the tremendous losses in the worldwide economy caused by construction delays, it is essential to invest in minimizing the risks of delays. In order to make this happen, two measures should be taken:

1) The roots and fundamental causes of delay should be identified and strategies to mitigate their risks be developed (General remedy).

2) The most significant potential causes of delay in each project should be identified and these causes should be given priority to control (Project-Specific Remedy).

The current research invests in both of the measures. To provide the general remedy, causes of delay in the construction …

Investigation Into The Application Of Personality Insights And Language Tone Analysis In Spam Classification, Colm Mcgetrick

Dissertations

Due to its persistence spam remains as one of the biggest problems facing users and suppliers of email communication services. Machine learning techniques have been very successful at preventing many spam mails from arriving in user mailboxes, however they still account for over 50% of all emails sent. Despite this relative success the economic cost of spam has been estimated as high as $50 billion in 2005 and more recently at $20 billion so spam can still be considered a considerable problem. In essence a spam email is a commercial communication trying to entice the receiver to take some positive …

Arabic Speech Recognition Systems, Hamda M. M. Eljagmani

Theses and Dissertations

Arabic automatic speech recognition is one of the difficult topics of current speech recognition research field. Its difficulty lies on rarity of researches related to Arabic speech recognition and the data available to do the experiments. Moreover, to build Arabic speech recognition system with an optimal word error rate (WER), the system has to be completely trained to the individual user. Even though speaker dependent system can effectively achieve this by training it explicitly for this one speaker, it requires a large amount of training data. In addition speaker dependent system requires to be trained to each speaker individually. For …

A Comparison Of Airline Passengers' Perception And Attention Toward Onboard Safety Briefing Video Presentations, Yousef Aba Alkhail

Theses and Dissertations

The purpose of this study is to determine the effect of the type of safety demonstration on a passenger's perception and attention. Furthermore, the study examined if there are gender differences based on participant gender. The design utilizes a two-study approach. Study 1 used Florida Tech College of Aeronautics students. For Study 1, the design for Florida Tech Aeronautics students was a mixed design using one within subjects variable and one between subjects variable. This study was a nonrandomized, posttest-only design. Experimental conditions were counterbalanced. The ANOVA analysis of Study 1 demonstrated that there was no significant interaction between gender …

Students Explore Fossil Creatures Of The Cambrian Period Burgess Shale Through Model-Making, Andrea Anderson, Ksenia Zhbanova, Phyllis Gray, Jolene K. Teske, Audrey C. Rule

Journal of STEM Arts, Crafts, and Constructions

This practical article features an arts-integrated science unit on fossils of the Burgess Shale for fourteen elementary/ middle school students at a weeklong summer day camp. The day camp had a theme of recycling, reduction and reuse; all of the fossil models had substantial recycled components to support this theme. Next Generation Science Standards were supported by the course activities in which students examined fossil specimens, images, and comparative modern relatives to determine the anatomy and lifestyles of Burgess Shale Cambrian Period fossil animals (e.g., Olenoides trilobites, Anomalocaris, Canadaspis, Opabinia, Wiwaxia, Hallucigenia) through making scientific …

Expression And Reception: An Analytic Method For Assessing Message Production And Consumption In Cmc, Kang Namkoong, Dhavan V. Shah, Bryan Mclaughlin, Ming-Yuan Chih, Tae Joon Moon, Shawnika Hull, David H. Gustafson

Community & Leadership Development Faculty Publications

This article presents an innovative methodology to study computer-mediated communication (CMC), which allows analysis of the multi-layered effects of online expression and reception. The methodology is demonstrated by combining the following three data sets collected from a widely tested eHealth system, the Comprehensive Health Enhancement Support System (CHESS): (1) a flexible and precise computer-aided content analysis; (2) a record of individual message posting and reading; and (3) longitudinal survey data. Further, this article discusses how the resulting data can be applied to online social network analysis and demonstrates how to construct two distinct types of online social networks—open and targeted …

Wall Panel Optimization For Refugee Shelters In Germany: An Ahp Study, Zhu Jiadong

Masters Theses & Specialist Projects

The German government is experiencing difficulties housing and assimilating Syrian refugees in its borders. Erecting temporary shelters on location is one way to deal with the current crises. This thesis attempts to use Analytic Hierarchy Process (AHP) to determine the optimum combination of materials and construction methods to be used in the shelter’s walls in order to improve the living conditions of the refugees and to ensure that the cost is acceptable to the German government. This thesis compares six existing wall panel products from China, which have the lowest cost on the worldwide market. The R-value, strength, price, weight, …

An Immersive Learning Model, Shamsa Abdulla Salem Al Mazrouei

Theses

Our overarching goal is to provide children with immersive game-based learning environments to support Arabic linguistic skills acquisition. We postulate that immersion in- creases learning. To investigate this hypothesis, we developed a model and built an implementation of an educational virtual environment (EVE) that supports immersion and thus, induces effective learning. Experimental results confirm our hypothesis.

Our model integrates learning content, learning activities, immersion and gameplay. Based on our analysis of various curricula, specifically the United Arab Emirates grade one curriculum, we identified the nature of the learning content in order to satisfy the curriculum requirements. This content is conceptually …

Aspect Extraction From Product Reviews Using Category Hierarchy Information, Yifeng Yang, Chen Cen, Minghui Qiu, Forrest Sheng Bao

Research Collection School Of Computing and Information Systems

Aspect extraction is a task to abstract the common properties of objects from corpora discussing them, such as reviews of products. Recent work on aspect extraction is leveraging the hierarchical relationship between products and their categories. However, such effort focuses on the aspects of child categories but ignores those from parent categories. Hence, we propose an LDA-based generative topic model inducing the two-layer categorical information (CAT-LDA), to balance the aspects of both a parent category and its child categories. Our hypothesis is that child categories inherit aspects from parent categories, controlled by the hierarchy between them. Experimental results on 5 …

Study Of A High-Efficient Wide-Bandgap Dc-Dc Power Converter For Solar Power Integration, Yashwanth Bezawada

Electrical & Computer Engineering Theses & Dissertations

This research focuses on the design and analysis of a Boost cascaded Buck-Boost (BoCBB) power converter with super high efficiency in electric power conversion. The BoCBB power converter is based on emerging wide-bandgap silicon-carbide (SiC) MOSFETs and Schottky diodes, which have only 1/6 times of power loss in traditional silicon power semiconductor devices. The BoCBB power converter can be widely applied in solar harvesting for the National Aeronautics and Space Administration (NASA), military bases and electric utilities, as well as high-power DC motor drives for the electric vehicles, robotics, and manufacturing and product lines.

This research analyzed the topology and …

An Analytical System For Determining Disciplinary Vocabulary For Data-Driven Learning: An Example From Civil Engineering, Philippa Jean Otto

Dissertations and Theses

Data-driven learning (DDL), an inductive teaching approach in which students learn through corpus interaction, has gained recent traction as way to teach specialized vocabulary in English for Specific Purposes (ESP) classes. There is little research, however, that addresses how to choose specialized vocabulary for teaching with DDL.

This study addressed this gap in research by exploring the potential of a three-part analytical, corpus-based system for determining vocabulary to teach with DDL for a specific context of language use. This system included (1) identifying words that were significantly more frequent in a specialized expert corpus than in a corpus of general …

A Hierarchical Learning Model For Extracting Public Health Data From Social Media, Elham Rastegari

UNO Student Research and Creative Activity Fair

In decision making processes, particularly when it comes to health-related decisions, each relevant piece of information is important. This is particularly important when it comes to health conditions for which there remains a high degree of non-determinism as far as diagnosis and treatment. Online social media, are places in which people feel free to share their opinions about numerous topics, including public health issues and how individuals have responded to different types of treatments associated with diseases. social media could represent a secondary source that can be used as a supplement to other data sources. This would allow individuals as …

Using Fuzzy Cognitive Maps To Model Policy Issues In The Face Of Uncertainty And Limited Data, Brian Gregor

PSU Transportation Seminars

Planners and policymakers are often faced with the need to make decisions about issues for which there is uncertainty and limited data. For example, transportation planners are now faced with the prospect that new transportation technologies such as autonomous vehicles could greatly alter future transportation system needs. Decisions about these types of issues are difficult to reason about and consequently are likely to be ignored or made on the basis of simplistic logic. Although modeling could be helpful, especially for issues involving complex systems, it is rarely used because models usually require large amounts of data and and handle uncertainty …

Academic Problem-Solving And Students’ Identities As Engineers, Mirka Koro-Ljungberg, Elliot P. Douglas, Nathan J. Mcneill, David J. Therriault, Christine S. Lee, Zaria Malcolm

The Qualitative Report

Socially constructed identities and language practices influence the ways students perceive themselves as learners, problem solvers, and future professionals. While research has been conducted on individuals’ identity as engineers, less has been written about how the language used during engineering problem solving influences students’ perceptions and their construction of identities as learners and future engineers. This study investigated engineering students’ identities as reflected in their use of language and discourses while engaged in an engineering problem solving activity. We conducted interviews with eight engineering students at a large southeastern university about their approaches to open and closed-ended materials engineering problems. …

Tsu Faculty Research Database-Jan 2017, David Owerbach

Office of Research Institutional Research and Scholarship

Research interests and selected publications from 230 Texas Southern University faculty have been updated in Jan 2017. Faculty from Public Affairs, the College of Science, Engineering and Technology, the College of Pharmacy and Health Sciences, the College of Education, the College of Business, the College of Liberal Arts and Behavioral Sciences, the Law School and the School of Communications are included.