Digital Commons Network^™

Data Mining Ancient Script Image Data Using Convolutional Neural Networks, Shruti Daggumati, Peter Revesz

School of Computing: Conference and Workshop Papers

The recent surge in ancient scripts has resulted in huge image libraries of ancient texts. Data mining of the collected images enables the study of the evolution of these ancient scripts. In particular, the origin of the Indus Valley script is highly debated. We use convolutional neural networks to test which Phoenician alphabet letters and Brahmi symbols are closest to the Indus Valley script symbols. Surprisingly, our analysis shows that overall the Phoenician alphabet is much closer than the Brahmi script to the Indus Valley script symbols.

Multi-Task Learning Framework For Mining Crowd Intelligence Towards Clinical Treatment, Shweta Yadav, Asif Ekbal, Sriparna Saha, Pushpak Bhattacharyya, Amit Sheth

Publications

In recent past, social media has emerged as an active platform in the context of healthcare and medicine. In this paper, we present a study where medical user’s opinions on health-related issues are analyzed to capture the medical sentiment at a blog level. The medical sentiments can be studied in various facets such as medical condition, treatment, and medication that characterize the overall health status of the user. Considering these facets, we treat analysis of this information as a multi-task classification problem. In this paper, we adopt a novel adversarial learning approach for our multi-task learning framework to learn the …

Design And Implementation Of Fuzzy Controller For Non-Linear Thermally Insulated Mimo Greenhouse Building Utilizing Weather Conditions And Ground Temperature, Raghed Abdul Menam Al Housari

Electrical Engineering Theses

The increased demand of electricity and water consumption for cooling and heating processes together with the continuous increase in earth temperature due to greenhouse gases emission urged the utilization of sustainable, affordable and clean energy resources. Globally, the biggest amount of water is consumed for agricultural purposes. Domestically, in Abu Dhabi Emirate, the agriculture sector consumes over 50% of the supplied water. Part of this consumption is due to the evaporative cooling approach that is typically used in cooling greenhouses. This approach utilizes a large amount of water and energy to maintain the greenhouse temperature within the desired range. Ground …

Radical Social Ecology As Deep Pragmatism: A Call To The Abolition Of Systemic Dissonance And The Minimization Of Entropic Chaos, Arielle Brender

Student Theses 2015-Present

This paper aims to shed light on the dissonance caused by the superimposition of Dominant Human Systems on Natural Systems. I highlight the synthetic nature of Dominant Human Systems as egoic and linguistic phenomenon manufactured by a mere portion of the human population, which renders them inherently oppressive unto peoples and landscapes whose wisdom were barred from the design process. In pursuing a radical pragmatic approach to mending the simultaneous oppression and destruction of the human being and the earth, I highlight the necessity of minimizing entropic chaos caused by excess energy expenditure, an essential feature of systems that aim …

Automated Development Of Semantic Data Models Using Scientific Publications, Martha O. Perez-Arriaga

Computer Science ETDs

The traditional methods for analyzing information in digital documents have evolved with the ever-increasing volume of data. Some challenges in analyzing scientific publications include the lack of a unified vocabulary and a defined context, different standards and formats in presenting information, various types of data, and diverse areas of knowledge. These challenges hinder detecting, understanding, comparing, sharing, and querying information rapidly.

I design a dynamic conceptual data model with common elements in publications from any domain, such as context, metadata, and tables. To enhance the models, I use related definitions contained in ontologies and the Internet. Therefore, this dissertation generates …

The Role Of Criticality Of Gene Regulatory Networks On Emergent Properties Of Biological Systems, Hyobin Kim

Graduate Dissertations and Theses

The relationship between criticality of gene regulatory networks (GRNs) and dynamics of GRNs at a single cell level has been vigorously studied. However, the relationship between the criticality of GRNs and properties of multicellular organisms at a higher level has not been fully explored. Here we aim at revealing potential roles of the criticality of GRNs at a multicellular and hierarchical level, using a random Boolean network as a GRN. We perform three studies. Firstly, we propose a GRN-based morphogenetic model, and delve into the role of the criticality of GRNs in morphogenesis at a multicellular level. Secondly, we include …

End-To-End Learning Framework For Circular Rna Classification From Other Long Non-Coding Rnas Using Multi-Modal Deep Learning., Mohamed Chaabane

Electronic Theses and Dissertations

Over the past two decades, a circular form of RNA (circular RNA) produced from splicing mechanism has become the focus of scientific studies due to its major role as a microRNA (miR) ac tivity modulator and its association with various diseases including cancer. Therefore, the detection of circular RNAs is a vital operation for continued comprehension of their biogenesis and purpose. Prediction of circular RNA can be achieved by first distinguishing non-coding RNAs from protein coding gene transcripts, separating short and long non-coding RNAs (lncRNAs), and finally pre dicting circular RNAs from other lncRNAs. However, available tools to distinguish circular …

A Recommendation To Implement A Quality Assurance/Quality Control Topics Course, Jacob W. Stapp

Construction Management

The purpose of this report is to recommend and gauge student interest/need for the addition of a Quality Assurance/Quality Control topics course to the Construction Management curriculum. Both Quality Assurance and Quality Control are vital for all construction projects, and without proper implementation there is no way to ensure high quality results. In an industry that demands high quality projects, it is important that our department prepares our students to be well-rounded in all aspects of construction. This will enable our graduates to enter the workforce in full stride, contributing efficiently from the start. Our University’s motto is “Learn by …

Digital Automatic Speech Recognition Using Kaldi, Sarah Habeeb Alyousefi

Theses and Dissertations

The Automatic speech recognition (ASR) system is one of most important technologies that used for human-machine interaction. The main goal of the ASR system is to recognize different natural languages that are spoken by humans. The difficulties of these recognition systems depend on many factors, such as noises, variability of the speakers, and problems of continuous speech. For that reason, many researchers and foundations have designed different kinds of licensed toolkits and software that are specialized in building speech recognition systems, including , Julius, Sphinx-4, RWTH ASR, and HTK toolkits. In this thesis, Kaldi toolkit, which is one of the …

Entity Summarization Of Reviews And Micro-Reviews, Thanh Son Nguyen

Dissertations and Theses Collection (Open Access)

Along with the regular review content, there is a new type of user-generated content arising from the prevalence of mobile devices and social media, that is micro-review. Micro-reviews are bite-size reviews (usually under 200 char- acters), commonly posted on social media or check-in services, using a mobile device. They capture the immediate reaction of users, and they are rich in information, concise, and to the point. Both reviews and micro-reviews are useful for users to get to know the entity of interest, thus facilitating users in making their decision of purchasing or dining. However, the abundant number of both reviews …

Spanish Language Topics Course Curriculum Proposal, George W. Healy

Construction Management

The objective of this report is to initiate the development of an introductory Spanish topics course within the construction management curriculum at Cal Poly. With each construction management student at Cal Poly that graduates, the industry is gifted another future industry expert. However, in order to be truly successful in construction,one must be excellent at communicating with, and coordinating team’s activities. There is no question that workers in the construction industry are subject to life threatening hazards on a regular basis. In order to mitigate the potential harm of these hazards, allsteps must be taken in managing these risks. Faults …

Improving Spatial Visualization Abilities Using 3d Printed Blocks, Vanessa Lebow, Michelle Bernhardt-Barry, Jyotishka Datta

Civil Engineering Undergraduate Honors Theses

Spatial visualization abilities have been shown to be a key predictor of success in science, technology, engineering, and math fields. Past research has revealed that women and underrepresented minorities tend to lag behind in spatial visual abilities, however, research has also shown that these skills can be improved with guided practice. This study seeks to examine whether 3D printed aids help spatial visual retention in 6th graders. A modified Purdue spatial visualization test was used as the assessment standard. Students’ mental rotation abilities were assessed before and after the 3D printed aids were administered. Data was collected from five different …

Speech Emotion Recognition Using Connectionist Models In A Tandem System, Mary Najafi

Theses and Dissertations

This article presents a tandem Speech Emotion Recognition (SER) system by which 8 archetypal emotions can be differentiated based upon two different types of acoustic features as inputs to Artificial Neural Network (ANN) models. The two types of features that are fed into the classifiers reveal the degree of excitement and pleasentness of speech. The author has implied the time-based characteristics of speech in the feature extraction method by monitoring the trend of local features through time. Thus, two global features are proposed that are derived from Teager Energy Operator (TEO)-based (T EOg) and spectral features, Mel-Frequency Cepstral Coeffcients (MF …

Automatic Speech Recognition Adaptation For Various Noise Levels, Azhar Sabah Abdulaziz

Theses and Dissertations

The automatic speech recognition (ASR) is a set of complicated algorithms that convert the intended spoken utterance into a textual form. Acoustic features, which are extracted from the speech signal, are matched against a trained network of linguistic and acoustic models. The ASR performance is degraded significantly when the ambient noise is different than that of the training data. Many approaches have been introduced to address this problem with various degrees of complexity and improvement rates. The general pattern of solving this issue lies in three categories: empowering features, train a general acoustic model and transform models to match noisy …

Impact Of Computer Tablets On General Aviation Flight Training, Anthony Saitabau Lolchoki

Theses and Dissertations

Over the past two decades, Electronic Flight Bags (EFBs) and Personal Electronic Devices (PEDs) have developed from flight publication storage devices hosted on modified laptop computers into fully interactive near-avionics-quality navigation equipment based on consumer-grade tablet computers. Broadly speaking, the Code of Federal Regulation (CFR) 14 regulates the use of this type of equipment for commercial airlines, commuter operations, and fractional ownership operators, but have neglected the General Aviation (GA) sector. Due, in part, to this lack of governance, little has been known about EFB use in GA. After using an internet-based survey, this study was conducted to examine whether …

Process Modeling Of Optimum Mixing Of Cyanic Solutions With Use Of Intellectual Systems Of Measurement On A Basis To A Fuzzy Logic, O.A Jumayev, A.A Akhmatov, G.B Makhmudov

Chemical Technology, Control and Management

Analyzes the principles of the development of microprocessor-based intelligent measurement and control systems that operate based on fuzzy logic rules. Using the possibilities of microprocessor intelligent systems, methods of automatic adjustment of the selected regulator are based on the dynamic model of the object, using the example of the process of optimal displacement of cyanide solutions.

2018 - The Twenty-Third Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Twenty-third Annual Symposium of Student Scholars, held on April 19, 2018. Includes abstracts from the presentations and posters.

Early Alert Of At-Risk Students: An Ontology-Driven Framework, Elias S. Lopez

Electrical and Computer Engineering ETDs

As higher education continues to adapt to the constantly shifting conditions that society places on institutions, the enigma of student attrition continues to trouble universities. Early alerts for students who are at-risk academically have been introduced as a method for solving student attrition at these institutions. Early alert systems are designed to provide students who are academically at-risk a prompt indication so that they may correct their performance and make progress towards successful semester completion. Many early alert systems have been introduced and implemented at various institutions with varying levels of success. Currently, early alert systems employ different techniques for …

Design Of An Intelligent Damping Controller Of Statcom With Hvdc For Large Offshore Wind Farm, Kai-Hung Lu, Hsin-Chuan Chen, Yu Su, Qiangqiang Xu

Journal of Marine Science and Technology–Taiwan

This paper proposes the design of an Intelligent Damping Controller (IDC) for a Static Synchronous Compensator (STATCOM), linking to a high voltage direct current (HVDC) transmission line, where a permanent magnet synchronous generator (PMSG)- based offshore wind farm (OWF) is connected. This IDC consists of a critic network with the proposed Functional Link based Recurrent Fuzzy Neural Network (FLRFNN) and Genetic Algorithm Hybrid Time Varying Particle Swarm Optimization (GAHTVPSO) algorithm. A single-machine infinite-bus and a multi-machine hybrid power system were used for test the system stability. GAHTVPSO approach is developed to adjust the learning rates to improve the learning capability. …

Wright State University's Symposium Of Student Research, Scholarship & Creative Activities From Friday April 13, 2018, Wright State University

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

The student abstract booklet is a compilation of abstracts from students' oral and poster presentations at Wright State University's Symposium of Student Research, Scholarship & Creative Activities on April 13, 2018.

Fusion Of Audio And Visual Information For Implementing Improved Speech Recognition System, Vikrant Satish Acharya

Masters Theses

Speech recognition is a very useful technology because of its potential to develop applications, which are suitable for various needs of users. This research is an attempt to enhance the performance of a speech recognition system by combining the visual features (lip movement) with audio features. The results were calculated using utterances of numerals collected from participants inclusive of both male and female genders. Discrete Cosine Transform (DCT) coefficients were used for computing visual features and Mel Frequency Cepstral Coefficients (MFCC) were used for computing audio features. The classification was then carried out using Support Vector Machine (SVM). The results …

Design And Implementation Of An Artificial Neural Network Controller For Quadrotor Flight In Confined Environment, Ahmed Mekky

Mechanical & Aerospace Engineering Theses & Dissertations

Quadrotors offer practical solutions for many applications, such as emergency rescue, surveillance, military operations, videography and many more. For this reason, they have recently attracted the attention of research and industry. Even though they have been intensively studied, quadrotors still suffer from some challenges that limit their use, such as trajectory measurement, attitude estimation, obstacle avoidance, safety precautions, and land cybersecurity. One major problem is flying in a confined environment, such as closed buildings and tunnels, where the aerodynamics around the quadrotor are affected by close proximity objects, which result in tracking performance deterioration, and sometimes instability. To address this …

Immersive Visualization In Biomedical Computational Fluid Dynamics And Didactic Teaching And Learning, John Thomas Venn

Master's Theses (2009 -)

Virtual reality (VR) can stimulate active learning, critical thinking, decision making and improved performance. It requires a medium to show virtual content, which is called a virtual environment (VE). The MARquette Visualization Lab (MARVL) is an example of a VE. Robust processes and workflows that allow for the creation of content for use within MARVL further increases the userbase for this valuable resource. A workflow was created to display biomedical computational fluid dynamics (CFD) and complementary data in a wide range of VE’s. This allows a researcher to study the simulation in its natural three-dimensional (3D) morphology. In addition, it …

The Journal Of Undergraduate Research: 2017

The Journal of Undergraduate Research

This is the complete issue of the South Dakota State University Journal of Undergraduate Research, Volume 15.

Sentiment Analysis Of Twitter Data, Evan L. Munson

Theses and Dissertations

The rapid expansion and acceptance of social media has opened doors into users’ opinions and perceptions that were never as accessible as they are with today's prevalence of mobile technology. Harvested data, analyzed for opinions and sentiment can provide powerful insight into a population. This research utilizes Twitter data due to its widespread global use, in order to examine the sentiment associated with tweets. An approach utilizing Twitter #hashtags and Latent Dirichlet Allocation topic modeling were utilized to differentiate between tweet topics. A lexicographical dictionary was then utilized to classify sentiment. This method provides a framework for an analyst to …

Front Matter, Adfsl

Annual ADFSL Conference on Digital Forensics, Security and Law

No abstract provided.

Comparisons Of Position Control Of Valve-Controlled And Pump-Controlled Folding Machines, Ray-Hwa Wong, Wei-Heng Wong

Journal of Marine Science and Technology–Taiwan

Control units of electro-hydraulic double-axial folding machine can be classified as throttling type (valve-controlled) and volumetric type (pump-controlled). This paper focuses to compare their control performances. Valve-controlled folding machine (VCFM) has higher supply pressure, different circuit resistance between subsystems. Pump-controlled folding machine (PCFM) has variable working pressure and circuit resistance is slightly different. The folding machine is a coupled system and has significant structural interaction. This paper proposes coupled adaptive self-organizing sliding-mode fuzzy controllers to improve folding machine’s level control performance. It found higher supply pressure of VCFM cause faster transient response, larger maximum overshoot via a variety of coupled …

Patent Keyword Extraction Algorithm Based On Distributed Representation For Patent Classification, Jie Hu, Shaobo Li, Yong Yao, Liya Yu, Guanci Yang, Jianjun Hu

Faculty Publications

Many text mining tasks such as text retrieval, text summarization, and text comparisons depend on the extraction of representative keywords from the main text. Most existing keyword extraction algorithms are based on discrete bag-of-words type of word representation of the text. In this paper, we propose a patent keyword extraction algorithm (PKEA) based on the distributed Skip-gram model for patent classification. We also develop a set of quantitative performance measures for keyword extraction evaluation based on information gain and cross-validation, based on Support Vector Machine (SVM) classification, which are valuable when human-annotated keywords are not available. We used a standard …

A Hierarchical Feature Extraction Model For Multi-Label Mechanical Patent Classification, Jie Hu, Shaobo Li, Jianjun Hu, Guanci Yang

Faculty Publications

Various studies have focused on feature extraction methods for automatic patent classification in recent years. However, most of these approaches are based on the knowledge from experts in related domains. Here we propose a hierarchical feature extraction model (HFEM) for multi-label mechanical patent classification, which is able to capture both local features of phrases as well as global and temporal semantics. First, a n-gram feature extractor based on convolutional neural networks (CNNs) is designed to extract salient local lexical-level features. Next, a long dependency feature extraction model based on the bidirectional long–short-term memory (BiLSTM) neural network model is proposed to …

Multi-Scale And Multi-Modal Streaming Data Aggregation And Processing For Decision Support During Natural Disasters, Shruti Kar

Browse all Theses and Dissertations

With the surge in digital information systems, there is a data deluge from various sources that can be analyzed and integrated to produce relevant, reliable and actionable information, for better decision making. We employ multi-modal data (i.e., unstructured text, gazetteers, and imagery) for an aggregate level analysis and location-centric demand/request matching in the context of disaster relief. After classifying the Need expressed in a tweet (the WHAT), we leverage OpenStreetMap to geolocate that Need on a computationally accessible map of the local terrain (the WHERE) populated with location features such as hospitals and housing. Further, our novel use of flood …