Computer Sciences Commons^™

Analysing The Effects Of Data Augmentation And Free Parameters For Text Classification With Recurrent Convolutional Neural Networks, Jonathan Quijas

Open Access Theses & Dissertations

Convolutional neural networks have seen much success in computer vision and natural language processing tasks. When training convolutional neural networks for text classification tasks, a common technique is to transform an input sequence of words into a dense matrix of word embeddings, or words represented as dense vectors, using table lookup operations. This enables the inputs to be represented in a way that the well-known convolution/pooling operations can be applied to them in a manner similar to images. These word embeddings may be further incorporated into the neural network itself as a trainable layer to allow fine-tuning, usually leading to …

Describing Data And Workflow Provenance Using Design Patterns And Controlled Vocabularies, Smriti Rajkarnikar Tamrakar

Open Access Theses & Dissertations

In any scientific experiment, researchers are required to access, compute, and analyze data to produce useful information to the scientific community. In order to instill trust on such scientific research products, the product users need to understand the procedure applied and the assumptions incorporated. The reuse and replication of reliable scientific data need methods that help the users to understand data origin and the derivation process, i.e. provenance. Although several standards for representing provenance such as PROV model (a W3C recommendation) have been recommended, they have not been widely utilized by scientific communities due to difficulty in aligning such recommended …

Optimization Of Neural Network Architecture For Classification Of Radar Jamming Fm Signals, Alberto Soto

Open Access Theses & Dissertations

Radar jamming signal classification is valuable when situational awareness of radar systems is sought out for timely deployment of electronic support measures. Our Thesis shows that artificial neural networks can be utilized for effective and efficient signal classification. The goal is to optimize an artificial Neural Network (NN) approach capable of distinguishing between two common radar waveforms, namely bandlimited white Gaussian jamming noise (BWGN) and the ubiquitous linearly frequency modulated (LFM) signal. This is made possible by creating a theoretical framework for NN architecture testing that leads to a high probability of detection (PD) and a low probability of false …

Success Stories In Knowledge Management Systems, Leila Halawi, Richard Mccarthy, Janine Aronson

Publications

Historically, information systems have focused on capturing, storing, managing, and reporting explicit knowledge. Organizations today recognize the need to integrate both explicit and tacit knowledge in formal information systems. Knowledge management continues to be a critical strategy for an organization to achieve a sustainable competitive advantage, and consequently succeed in today's knowledge-based economy. Knowledge management systems (KMS) are a class of information systems that manage, store and distribute knowledge. Knowledge management systems have proliferated in practice. In turn, theoretical research on knowledge management and knowledge management systems has proliferated. Knowledge management systems have emerged as powerful sources of competitive advantage. …

Power Budgets For Cubesat Radios To Support Ground Communications And Inter-Satellite Links, Otilia Popescu

Engineering Technology Faculty Publications

CubeSats are a class of pico-satellites that have emerged over the past decade as a cost-effective alternative to the traditional large satellites to provide space experimentation capabilities to universities and other types of small enterprises, which otherwise would be unable to carry them out due to cost constraints. An important consideration when planning CubeSat missions is the power budget required by the radio communication subsystem, which enables a CubeSat to exchange information with ground stations and/or other CubeSats in orbit. The power that a CubeSat can dedicate to the communication subsystem is limited by the hard constraints on the total …

Differences In Perceived Constraints Of Telework Utilization Among Teleworkers And Office Workers, Yolanda West

Walden Dissertations and Doctoral Studies

Approximately 37% of the U.S. labor force currently works from a remote location. Costs and competition are driving organizations to increase the use of telework among remote workplaces. Increasing organizational knowledge of the perceptions of current teleworkers could increase its adoption by employees and improve its implementation by managers. The purpose of this research was to test hypotheses regarding the perceived levels of telework efficiency, social interaction, and technical support to determine in those perceptions differed between teleworkers and office workers. Goldratt's Theory of Constraints framed the quantitative research design. A purposive sample of 54 teleworkers and office workers in …

Overcoming The Adverse Impact Of Internal Subculture Communications Within Organizations, Terrence Lee Farrier

Walden Dissertations and Doctoral Studies

The need for clear and organizationally effective communications is necessary to maintain sustainability as competition increases. Current research has not addressed problems associated with senior managers' clarity and intent and the misinterpretation by midlevel managers of that intent, causing division managers to misinterpret the company plans. Unresolved miscommunications may lead to destructive subculture development. This mixed methods design focused on how to minimize the confusion that manifests between senior and midlevel management within diverse and decentralized decision support structures. The secondary purpose was to advocate for the identification of divisional misalignment and provide information for a tool to help senior …

Strategies For U.S. City Government Enterprise Resource Planning System Implementation Success, Jennifer Miller

Walden Dissertations and Doctoral Studies

Strategies for enterprise resource planning (ERP) system implementation success have been a focus of scholars since the 1990s. Researchers have demonstrated that ERP system implementation could cause both system failures and organization failures, affecting both operations and stakeholders. The theory of constraints was the conceptual framework for this single qualitative case study that explored ERP system critical success factors (CSFs) and strategies U.S. city governments use to successfully implement ERP systems. One city government in New Mexico with a successful ERP system served as the case study's population. Data were collected from semistructured interviews and relevant documents and then open …

Strategies For Integrating Technological Innovations In Small Businesses, Petra Samuel

Walden Dissertations and Doctoral Studies

The effective integration of technological innovation is vital to the success of small businesses and can catapult growth and profitability. Some business managers and supervisors, however, may not have a firm understanding of strategies for integrating technological innovations in businesses; this lack of knowledge may result in employee frustration and costly roadblocks to achieving business objectives. This case study was conducted to identify the strategies used by business managers and supervisors to integrate technological innovations in small businesses. Christensen's theory of disruptive innovation and Rogers' theory of diffusion of innovation served as the conceptual framework. Ten business managers and supervisors …

"I Can Physically Feel The Difference": Exploring Physicalizations Of Running Data, Zann Benjamin Anderson

Theses and Dissertations

We explore user interactions with concrete physical visualizations—physicalizations—of personal experiential data. We conducted three user studies involving physicalizations of data gathered while trail running—a sport in which participants are largely more focused on the experience than the exercise itself. In two qualitative studies, we asked trail runners to give us a GPS path from a "significant run" and then prepared a 3D physicalization featuring the path overlaid as a raised line on the corresponding real-world terrain. In the first, physicalizations had a significant impact in helping participants recall memories of their experiences, and participants shared many stories. In a follow-up …

Automated Refactoring Of Legacy Java Software To Default Methods, Raffi Khatchadourian, Hidehiko Masuhara

Publications and Research

Java 8 default methods, which allow interfaces to contain (instance) method implementations, are useful for the skeletal implementation software design pattern. However, it is not easy to transform existing software to exploit default methods as it requires analyzing complex type hierarchies, resolving multiple implementation inheritance issues, reconciling differences between class and interface methods, and analyzing tie-breakers (dispatch precedence) with overriding class methods to preserve type-correctness and confirm semantics preservation. In this paper, we present an efficient, fully-automated, type constraint-based refactoring approach that assists developers in taking advantage of enhanced interfaces for their legacy Java software. The approach features an extensive …

Long-Term Simulations Of Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, R. Majeti, C. Cotnoir, M. Stefani, D. Ranjan, A. Godunov, V. Morozov, H. Zhang, F. Lin, Y. Roblin, E. Nissen, T. Satogata

Physics Faculty Publications

Future machines such as the electron-ion colliders (JLEIC), linac-ring machines (eRHIC) or LHeC are particularly sensitive to beam-beam effects. This is the limiting factor for long-term stability and high luminosity reach. The complexity of the non-linear dynamics makes it challenging to perform such simulations which require millions of turns. Until recently, most of the methods used linear approximations and/or tracking for a limited number of turns. We have developed a framework which exploits a massively parallel Graphical Processing Units (GPU) architecture to allow for tracking millions of turns in a sympletic way up to an arbitrary order and colliding them …

Simulations Of Coherent Synchrotron Radiation On Parallel Hybrid Gpu/Cpu Platform, B. Terzić, K. Arumugam, D. Duffin, A. Godunov, T. Islam, D. Ranjan, S. Sangam, Mohammad Zubair

Physics Faculty Publications

Coherent synchrotron radiation (CSR) is an effect of self-interaction of an electron bunch as it traverses a curved path. It can cause a significant emittance degradation, as well as fragmentation and microbunching. Numerical simulations of the 2D/3D CSR effects have been extremely challenging due to computational bottlenecks associated with calculating retarded potentials via integrating over the history of the bunch. We present a new high-performance 2D, particle-in-cell code which uses massively parallel multicore GPU/GPU platforms to alleviate computational bottlenecks. The code formulates the CSR problem from first principles by using the retarded scalar and vector potentials to compute the self-interaction …

Clustering-Based Online Player Modeling, Jason M. Bindewald, Gilbert L. Peterson, Michael E. Miller

Faculty Publications

Being able to imitate individual players in a game can benefit game development by providing a means to create a variety of autonomous agents and aid understanding of which aspects of game states influence game-play. This paper presents a clustering and locally weighted regression method for modeling and imitating individual players. The algorithm first learns a generic player cluster model that is updated online to capture an individual’s game-play tendencies. The models can then be used to play the game or for analysis to identify how different players react to separate aspects of game states. The method is demonstrated on …

Decision Process In Mcdm With Large Number Of Criteria And Heterogeneous Risk Preferences, Jian Liu, Hong Kuan Zhao, Zhao Bin Li, Si Feng Liu

Electrical and Computer Engineering Faculty Research & Creative Works

A new decision process is proposed to address the challenge that a large number of criteria in the multi-criteria decision making (MCDM) problem and the decision makers with heterogeneous risk preferences. First, from the perspective of objective data, the effective criteria are extracted based on the similarity relations between criterion values and the criteria are weighted, respectively. Second, the corresponding types of theoretic model of risk preferences expectations will be built, based on the possibility and similarity between criterion values to solve the problem for different interval numbers with the same expectation. Then, the risk preferences (Risk-seeking, risk-neutral and risk-aversion) …

Creating A Game With Procedural Generation, Kirsten Baker

Williams Honors College, Honors Research Projects

In today’s world, gaming is ever growing in popularity. The amount of games is forever increasing and there are many genres of games to suit any player’s desires. I have created a game that generates explorable mazes. Originally written in Java as a 2D game, I translated it into C# and utilized the Unity game engine to make it 3D. The randomly generated mazes would allow players to have endless fun navigating through the different levels and customizing it to fit their preferences.

Semantics-Based Summarization Of Entities In Knowledge Graphs, Kalpa Gunaratna

Browse all Theses and Dissertations

The processing of structured and semi-structured content on the Web has been gaining attention with the rapid progress in the Linking Open Data project and the development of commercial knowledge graphs. Knowledge graphs capture domain-specific or encyclopedic knowledge in the form of a data layer and add rich and explicit semantics on top of the data layer to infer additional knowledge. The data layer of a knowledge graph represents entities and their descriptions. The semantic layer on top of the data layer is called the schema (ontology), where relationships of the entity descriptions, their classes, and the hierarchy of the …

A Power Iteration Based Co-Training Approach To Achieve Convergence For Multi-View Clustering, Pavankalyan Yallamelli

Browse all Theses and Dissertations

Collecting diversified opinions is the key to achieve "the Wisdom of Crowd". In this work, we propose to use a novel multi-view clustering method to group the crowd so that diversified opinions can be effectively sampled from different groups of people.Clustering is the process of dividing input data into possible subsets, where every element (entity) in each subset is considered to be related by some similarity measure. For example, a set of social media users can be clustered using their locations or common interests. However, real-world data is often best represented by multiple views/dimensions. For example, a set of social …

Implementation And Evaluation Of Goal Selection In A Cognitive Architecture, Sravya Kondrakunta

Browse all Theses and Dissertations

A cognitive system attempts to achieve its goals by utilizing the appropriate resources present to yield the best possible outcome within a short duration. To achieve the goals in such an efficient manner, it is important for the agent to manage its goals well. Goal management not only makes the agent efficient but also flexible, more durable to the sudden changes in the environment, and self-reliant. Goal Management consists of various goal operations including goal formulation, selection, change, delegation, achievement, and monitoring. Each operation is unique and has its own significance in aiding the performance of the agent. The thesis …

Development Of A Performance Assessment System For Language Learning, Imen Kasrani

Browse all Theses and Dissertations

Recent advances in computer-assisted, language-speaking, learning/training technology have demonstrated its promising potential to improve the outcome of language learning in early education, special education, English as a Second Language (ESL), and foreign language. The growing number of readily available mobile app-based solutions help encourage interest in learning to speak a foreign language, but their effectiveness is limited due to their lack of objective assessment and performance feedback resembling expert judgment. For example, it has been recognized that, in early education, students learn best with one-on-one instructions. Unfortunately, teachers do not have the time, and it is challenging to extend the …

Development Of An Android Based Performance Assessment System For Motivational Interviewing Training, Sowmya Pappu

Browse all Theses and Dissertations

Motivational Interviewing (MI) has been proved to be an effective Screening, Brief Intervention, and Referral to Treatment (SBIRT) technique. It is an evidence-based practice used to identify, reduce, and prevent problematic use, abuse, and dependence on alcohol and illicit drugs. It emphasizes on patient-centered counseling approach that can help resolve their ambivalence through a non-confrontational, goal-oriented style for eliciting behavior change from the patient, almost like patients talk themselves into change. This approach provokes less resistance and stimulates the progress of patients at their own pace towards deciding about planning, making and sustaining positive behavioral change. Thus, training medical professionals …

Genetic Algorithm For University Course Timetabling Problem, Achini Kumari Herath

Electronic Theses and Dissertations

Creating timetables for institutes which deal with transport, sport, workforce, courses, examination schedules, and healthcare scheduling is a complex problem. It is difficult and time consuming to solve due to many constraints. Depending on whether the constraints are essential or desirable they are categorized as ‘hard’ and ‘soft’, respectively. Two types of timetables, namely, course and examination are designed for academic institutes. A feasible course timetable could be described as a plan for the movement of students and staff from one classroom to another, without conflicts. Being an NP-complete problem, many attempts have been made using varying computational methods to …

Iphone Swift 3 Development For “What’S Good?”, Cameron Reilly

Williams Honors College, Honors Research Projects

Cameron Reilly

Major: Computer Science Management Track

Project Sponsor: Michael Collard

What’s Good?

“What’s Good?” is an iOS application that uses augmented reality to present information about nearby restaurants to the user in real time. Users can hold up their device and look through their camera to see information presented above the restaurant including it’s name, average cost, and average review rating. The user’s location is gathered and used in tandem with the Zomato API to select what data display as those dining locations are currently near the user. Using the gyroscope, compass, and accelerometer to tell the exact orientation …

Efficient Implementation Of Reductions On Gpu Architectures, Stephen W. Timcheck

Williams Honors College, Honors Research Projects

With serial, or sequential, computational operations' growth rate slowing over the past few years, parallel computing has become paramount to achieve speedup. In particular, GPUs (Graphics Processing Units) can be used to program parallel applications using a SIMD (Single Instruction Multiple Data) architecture. We studied SIMD applications constructed using the NVIDIA CUDA language and MERCATOR (Mapping EnumeRATOR for CUDA), a framework developed for streaming dataflow applications on the GPU. A type of operation commonly performed by streaming applications is reduction, a function that performs some associative operation on multiple data points such as summing a list of numbers (additive operator, …

Implementation Of Cuda Accelerated Bayesian Network Learning, Joseph Haddad

Williams Honors College, Honors Research Projects

Bayesian networks can be used to analyze and find relationships among genetic profiles. Unfortunately, Bayesian network learning is an NP­-hard algorithm and thus takes a significant amount of time to generate an output. There has been research in this area in attempts to make this algorithm quicker, such as utilizing consensus networks. Consensus networks are aggregations of many “cheaper” Bayesian networks that are used to formulate a bigger picture. These “cheaper” networks have their search­ spaces restricted, and thus more are required to extract the relationships among the data points.

To accomplish this, I implemented Bayesian network learning in C++, …

Game Collection Development And Marketing, Todd R. Locker Jr

Williams Honors College, Honors Research Projects

The reasons for completing this project include expanding my knowledge of programming features and methodology, and to learn about game platform development and design. This was done by using the Java programming language to create a game platform which can host a variable number of games. One of the most notable features that was utilized is the JavaFX platform. Much programming experience was gained from this platform and all the features and methods it provides for customization. The application that was produced is graphical user interface based and created with event-driven programming. The result of this project was a custom …

Probabilistic Personalized Recommendation Models For Heterogeneous Social Data, Vineeth Rakesh Mohan

Wayne State University Dissertations

Content recommendation has risen to a new dimension with the advent of platforms like Twitter, Facebook, FriendFeed, Dailybooth, and Instagram. Although this uproar of data has provided us with a goldmine of real-world information, the problem of information overload has become a major barrier in developing predictive models. Therefore, the objective of this The- sis is to propose various recommendation, prediction and information retrieval models that are capable of leveraging such vast heterogeneous content. More specifically, this Thesis focuses on proposing models based on probabilistic generative frameworks for the following tasks: (a) recommending backers and projects in Kickstarter crowdfunding domain …

Source Credibility And Cybersecurity Behaviors Of Computer Users, Bracken Sallin

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Health And Safety Monitoring System, Cailin Simpson

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Artificial Intelligence And Its Potential Adverse Impacts On The Philippine Economy, Krista Danielle Yu, Caesar Cororaton, Joel P. Ilao, Charibeth K. Cheng, Kathleen Aviso, Christina D. Cayamanda, Michael Angelo B. Promentilla, Ringgold P. Atienza, Roman Julio B. Infante, Raymond R. Tan

Angelo King Institute for Economic and Business Studies (AKI)

Recent developments in artificial intelligence (AI) and deep learning techniques are expected to reshape the nature of the working environment in many economic sectors through the automation of many white collar jobs. This technological breakthrough poses threats of job obsolescence in several industries, particularly for a labor abundant country such as the Philippines. With human capital as one of its largest resources, the services sector is a major contributor to the country’s economy, contributing around 60% of the total gross domestic product and employing about 22.8 million workers (Philippine Statistics Authority, 2017).