Computer Sciences Commons^™

Structured Summarization Of Multi-Party Conversations, Ching-Sheng Lin

Legacy Theses & Dissertations (2009 - 2024)

Automatic summarization is the task of creating a set of short and concise sentences that capture the content of the original source material. Summaries should retain only the most relevant content of the source, while suppressing secondary and redundant information. Most existing approaches to automatic summarization have been applied to narrative documents such as news, reports, and technical documents. Relatively few techniques were proposed for summarizing meetings and other forms of interactive content.

Network Pruning For Scaling Dynamic Community Detection, Gaurav Ghosh

Legacy Theses & Dissertations (2009 - 2024)

Local community detection is an important tool for the analysis of networks of different genres. The goal is to identify only the best communities in a network instance as opposed to computing a partitioning of the whole network. The majority of the work on local community detection has focused on static networks with less attention on networks that evolve over time. Given a trace of temporal interaction among nodes in a network, how can we detect a period of high interaction for a specific group of nodes? To help temporal community detection with the need to search in the time …

Efficient Execution Of Top-K Closeness Centrality Queries, Paul W. Olsen

Legacy Theses & Dissertations (2009 - 2024)

Many of today's applications can benefit from the discovery of the most central entities in real-world networks.

Persuasion In Online Communication : Automation And Counteraction, Samira Shaikh Shaikh

Legacy Theses & Dissertations (2009 - 2024)

In this thesis, we studied persuasion in online communication and how to automate

Efficient Large-Scale Photometric Reconstruction Using Divide-Conquer And Fusion, Yueming Yang

Legacy Theses & Dissertations (2009 - 2024)

The Structure-from-Motion(SfM) method of constructing a 3D model from 2D images reached maturity in the last decade. However, the computational time of pairwise image feature matching dominates the whole pipeline of SfM, and grows quadratically with the number of images. So the scaling issue is still a challenging problem. This dissertation introduces an efficient framework for large-scale 3D reconstruction from a large set of photos following the SfM paradigm with divide-conquer and fusion. The main novelty is to ensure commonality from overlaps between image sets corresponding to their reconstructed models, which facilitates effective stitching and fusion. Specifically, such commonality is …

Synchronous Subgraphs In Networks, Navita Jain

Legacy Theses & Dissertations (2009 - 2024)

Community detection is a central problem in network analysis. The majority of existing work defines communities as subsets of nodes that are structurally well-connected and isolated from the rest of the network. Apart from their underlying connectivity, nodes in real-world networks exhibit temporal activity: user posts in social networks, browsing activity on web pages and neuron activations in brain networks to name a few. While edges encode potential for community interactions, participation in the community can be quantified by synchronized member activity. Given both the network structure and individual node activity, how can we detect communities that are both well-connected …

Tabulating Pseudoprimes And Tabulating Liars, Andrew Shallue

Scholarship

This paper explores the asymptotic complexity of two problems related to the Miller-Rabin-Selfridge primality test. The first problem is to tabulate strong pseudoprimes to a single fixed base $a$. It is now proven that tabulating up to $x$ requires $O(x)$ arithmetic operations and $O(x\log{x})$ bits of space. The second problem is to find all strong liars and witnesses, given a fixed odd composite $n$. This appears to be unstudied, and a randomized algorithm is presented that requires an expected $O((\log{n})^2 + |S(n)|)$ operations (here $S(n)$ is the set of strong liars). Although interesting in their own right, a notable application …

Energy Management System For Renewable Energy, Ashish R. Derhgawen

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The demand for energy in our society has been increasing exponentially with our growing standard of living. The continued use of fossil fuels to meet these energy needs could lead to potentially catastrophic changes in the Earth's climate. Therefore, finding carbon-neutral energy sources and ensuring energy security are two of the biggest challenges that need to be addressed in the coming years. Recent technological innovations have finally brought us to the cusp of achieving these goals by providing cheap and reliable devices in micro-solar, smart homes , Internet of Things, etc. However, one of the biggest hurdles in the large-scale …

Impacts Of Soil Type And Moisture On The Capacity Of Multi-Carrier Modulation In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran

School of Computing: Conference and Workshop Papers

Unique interactions between soil and communication components in wireless underground communications necessitate revisiting fundamental communication concepts from a different perspective. In this paper, capacity profile of wireless underground (UG) channel for multi-carrier transmission techniques is analyzed based on empirical antenna return loss and channel frequency response models in different soil types and moisture values. It is shown that data rates in excess of 124 Mbps are possible for distances up to 12 m. For shorter distances and lower soil moisture conditions, data rates of 362 Mbps can be achieved. It is also shown that due to soil moisture variations, UG …

Table Headers: An Entrance To The Data Mine, George Nagy, Sharad C. Seth

School of Computing: Conference and Workshop Papers

Algorithmic methods are demonstrated for information extraction from table header elements, including data categories and data hierarchies. The table headers are found with the Minimum Index Point Search algorithm. The header-path alignment and header completion algorithms yield database-ready table content and configuration statistics on a random sample of 400 diverse tables with ground truth and 1120 tables without ground truth from international statistical data sites.

Locality-Aware Dynamic Task Graph Scheduling, Jordyn Maglalang, Sriram Krishnamoorthy, Kunal Agrawal

All Computer Science and Engineering Research

Dynamic task graph schedulers automatically balance work across processor cores by scheduling tasks among available threads while preserving dependences. In this paper, we design NabbitC, a provably efficient dynamic task graph scheduler that accounts for data locality on NUMA systems. NabbitC allows users to assign a color to each task representing the location (e.g., a processor core) that has the most efficient access to data needed during that node’s execution. NabbitC then automatically adjusts the scheduling so as to preferentially execute each node at the location that matches its color—leading to better locality because the node is likely to make …

Obstacle-Aware Wireless Video Sensor Network Deployment For 3d Indoor Space Monitoring, Zhonghui Wang

Electronic Theses and Dissertations

In recent years wireless video sensors networks (WVSNs) have emerged as a leading technology for monitoring 3D indoor space in campus, industrial and medical areas as well as other types of environments. In contrast to traditional sensors such as heat or light sensors often considered with omnidirectional sensing range, the sensing range of a video sensor is directional and can be deemed as a pyramid-shape in 3D. Moreover, in an indoor environment, there are often obstacles such as lamp stands or furniture, which introduce additional challenges and further render the deployment solutions for traditional sensors and 2D sensing field inapplicable …

The Effect Of Hyperparameters In The Activation Layers Of Deep Neural Networks, Clay Lafayette Mcleod

Electronic Theses and Dissertations

Deep neural networks (DNNs), and artificial neural networks (ANNs) in general, have recently received a great amount of attention from both the media and the machine learning community at large. DNNs have been used to produce world-class results in a variety of domains, including image recognition, speech recognition, sequence modeling, and natural language processing. Many of most exciting recent deep neural network studies have made improvements by hardcoding less about the network and giving the neural network more control over its own parameters, allowing flexibility and control within the network. Although much research has been done to introduce trainable hyperparameters …

Cofibrations In The Category Of Noncommutative Cw Complexes, Vida Milani, Ali Asghar Rezaei, Seyed M.H. Mansourbeigi

Computer Science Student Research

Cofibration in the category of noncommutative CW complexes is defined. The C*-algebraic counterparts of topological mapping Cylinder and mapping cone are presented as examples of noncommutative CW complex cofibres. As a generalization, the concepts of noncommutative mapping cylindrical and conical telescope are introduced to provide more examples of NCCW complex cofibres. Their properties and K-theoretic behavior are also studied in detail. We will see that they carry the properties similar to the topological properties of their CW complex counterparts.

Consensus Regularized Selection Based Prediction, Ping Wang

Wayne State University Theses

Integrating regularization methods within a regression framework has become a popular choice for researchers to build predictive models with lower variance and better generalization. Regularizers also aid in building interpretable models with high-dimensional data which makes them very appealing. Regularizers in general are unique in nature as they cater to data specific features such as correlation, structured sparsity, and temporal smoothness. The problem of obtaining a consensus among such diverse regularizers is extremely important in order to determine the optimal regularizer for the model. This is called the consensus regularization problem which has not received much attention in the literature, …

Interactive Refinement Of Hierarchical Object Graphs, Ebrahim Khalaj

Wayne State University Theses

Developers need to understand the runtime structure of object-oriented code, and abstract object graphs can help. To extract abstract object graphs that convey design intent in the form of object hierarchy, additional information is needed to express this hierarchy in the code using ownership types, but adding ownership type qualifiers after the fact involves manual overhead, and requires developers to switch between adding qualifiers in the code and looking at abstract object graphs to understand the object structures that the qualifiers describe. We describe an approach where developers express their design intent by refining an object graph directly, while an …

Single Machine Scheduling With Job-Dependent Machine Deterioration, Wenchang Luo, Xu Yao, Weitian Tong, Guohui Lin

Computer Science: Faculty Publications

We consider the single machine scheduling problem with job-dependent machine deterioration. In the problem, we are given a single machine with an initial non-negative maintenance level, and a set of jobs each with a non-preemptive processing time and a machine deterioration. Such a machine deterioration quantifies the decrement in the machine maintenance level after processing the job. To avoid machine breakdown, one should guarantee a non-negative maintenance level at any time point; and whenever necessary, a maintenance activity must be allocated for restoring the machine maintenance level. The goal of the problem is to schedule the jobs and the maintenance …

Geometric Algorithms For Modeling Protein Structures, Dan Zeng

Undergraduate Research Symposium Posters

Understanding the structures of macromolecular assemblies is necessary to describe the mechanics of a wide variety of cellular processes. Such assemblies often consist of hundreds of proteins and nucleic acid, each with a unique shape. Modern imaging techniques, including electron cryo-microscopy, create 3D density maps to portray the shapes of these assemblies. However, computational methods for deriving structural models from these images are not fully developed because structural geometry varies depending on the image resolution. To address this issue, we developed geometric algorithms in Gorgon, a molecular visualization software. First, we created an interface for Pathwalking. This algorithm determines protein …

Stereographic Visualization Of Bose-Einstein Condensate Clouds To Measure The Gravitational Constant, Ed Wesley Wells

College of Graduate Studies: Theses & Dissertations

This thesis describes a set of tools that can be used for the rapid design of atom interferometer schemes suitable for measuring Newton's Universal Gravitation constant also known as "Big G". This tool set is especially applicable to Bose--Einstein--condensed systems present in NASA's Cold Atom Laboratory experiment to be deployed to the International Space Station in 2017. These tools include a method of approximating the solutions of the nonlinear Schrödinger or Gross--Pitaevskii equation (GPE) using the Lagrangian Variational Method. They also include a set of software tools for translating the approximate solutions of the GPE into images of the optical …

A Study Of Social Web Data On Buprenorphine Abuse Using Semantic Web Technology, Raminta Daniulaityte, Amit P. Sheth

Kno.e.sis Publications

The Specific Aims of this application are to use a paradigmatic approach that combines Semantic Web technology, Natural Language Processing and Machine Learning techniques to:

1) Describe drug users’ knowledge, attitudes, and behaviors related to the non-medical use of Suboxone and Subutex as discussed on Web-based forums.
2) Identify and describe temporal patterns of non-medical use of Suboxone and Subutex as discussed on Web-based forums.

The research was carried out by an interdisciplinary team of members of the Center for Interventions, Treatment and Addictions Research (CITAR) and the Ohio Center of Excellence in Knowledge- enabled Computing (Kno.e.sis) at Wright State …

Building The Web Of Knowledge With Smart Iot Applications, Amelie Gyrard, Pankesh Patel, Amit P. Sheth, Martin Serrano

Kno.e.sis Publications

The Internet of Things (IoT) is experiencing fast adoption because of its positive impact to change all aspects of our lives, from agriculture in rural areas, to health and wellness, to smart home and smart-x applications in cities. The development of IoT applications and deployment of smart IoT-based solutions is just starting; smart IoT applications will modify our physical world and our interaction with cyber spaces, from how we remotely control appliances at home to how we care for patients or elderly persons. The massive deployment of IoT devices represents a tremendous economic impact and at the same time offers …

Co-Evolution Of Rdf Datasets, Sidra Faisal, Kemele M. Endris, Saeedeh Shekarpour, Sören Auer, Maria-Esther Vidal

Kno.e.sis Publications

Linking Data initiatives have fostered the publication of large number of RDF datasets in the Linked Open Data (LOD) cloud, as well as the development of query processing infrastructures to access these data in a federated fashion. However, different experimental studies have shown that availability of LOD datasets cannot be always ensured, being RDF data replication required for envisioning reliable federated query frameworks. Albeit enhancing data availability, RDF data replication requires synchronization and conflict resolution when replicas and source datasets are allowed to change data over time, i.e., co-evolution management needs to be provided to ensure consistency. In this paper, …

Experimental Comparison Of Simulation Tools For Efficient Cloud And Mobile Cloud Computing Applications, K. Bahwaireth, Lo'ai A. Tawalbeh, E. Benkhelifa, Y. Jararweh, M. A. Tawalbeh

Computer Science Faculty Publications (Archived)

Cloud computing provides a convenient and on-demand access to virtually unlimited computing resources. Mobile cloud computing (MCC) is an emerging technology that integrates cloud computing technology with mobile devices. MCC provides access to cloud services for mobile devices. With the growing popularity of cloud computing, researchers in this area need to conduct real experiments in their studies. Setting up and running these experiments in real cloud environments are costly. However, modeling and simulation tools are suitable solutions that often provide good alternatives for emulating cloud computing environments. Several simulation tools have been developed especially for cloud computing. In this paper, …

Mobile Cloud Computing Model And Big Data Analysis For Healthcare Applications, Lo'ai A. Tawalbeh, R. Mehmood, E. Benkhlifa, H. Song

Computer Science Faculty Publications (Archived)

Mobile devices are increasingly becoming an indispensable part of people's daily life, facilitating to perform a variety of useful tasks. Mobile cloud computing integrates mobile and cloud computing to expand their capabilities and benefits and overcomes their limitations, such as limited memory, CPU power, and battery life. Big data analytics technologies enable extracting value from data having four Vs: volume, variety, velocity, and veracity. This paper discusses networked healthcare and the role of mobile cloud computing and big data analytics in its enablement. The motivation and development of networked healthcare applications and systems is presented along with the adoption of …

Web Scraping The Easy Way, Yolande Neil

Honors College Theses

Web scraping refers to a software program that mimics human web surfing behavior by pointing to a website and collecting large amounts of data that would otherwise be difficult for a human to extract. A typical program will extract both unstructured and semi-structured data, as well as images, and convert the data into a structured format. Web scraping is commonly used to facilitate online price comparisons, aggregate contact information, extract online product catalog data, extract economic/demographic/statistical data, and create web mashups, among other uses. Additionally, in the era of big data, semantic analysis, and business intelligence, web scraping is the …

Creating Multi-Functional G-Code For Multi-Process Additive Manufacturing, Efrain Aguilera Jr

Open Access Theses & Dissertations

Additive manufacturing (AM) started over thirty years ago and with it a manufacturing revolution that moves industrial production into the personal home. With recent interest shifting into multi-functional parts fabricated through AM technologies, unified systems are being developed. Merging different manufacturing technologies into one single machine is a challenge but undergoing research has shown promise in the development of multi-functional systems. Concurrent work is being done in the software, automation, and hardware aspect of multi-functional systems. An effort to use industry compatible Computer Aided Design (CAD) software to design multi-functional parts including circuits, micro-machining, and foil embedding then exporting and …

Using Word Embeddings For Text Classification In Positive And Unlabeled Learning, Emmanuel Carlo Tafoya

Open Access Theses & Dissertations

Machine Learning is a sub-field of Artificial intelligence that aims to automatically improve algorithms by experience. It has been used successfully to solve various problems, such as playing checkers, or even as simple as word prediction when typing a sentence. These algorithms perform best with large amounts of training data. The more labeled data, the better a machine learning algorithm will be able to recognize patterns. However, the ideal scenario, where there is a large amount of labeled data available to train the algorithm, does not occur all the time. There are cases where labeling data is both time-consuming and …

The Woz Recognizer: A Tool For Understanding User Perceptions Of Sketch-Based Interfaces, Jared Bott

Electronic Theses and Dissertations

Sketch recognition has the potential to be an important input method for computers in the coming years; however, designing and building an accurate and sophisticated sketch recognition system is a time consuming and daunting task. Since sketch recognition is still at a level where mistakes are common, it is important to understand how users perceive and tolerate recognition errors and other user interface elements with these imperfect systems. A problem in performing this type of research is that we cannot easily control aspects of recognition in order to rigorously study the systems. We performed a study examining user perceptions of …

Gesture Assessment Of Teachers In An Immersive Rehearsal Environment, Roghayeh Barmaki

Electronic Theses and Dissertations

Interactive training environments typically include feedback mechanisms designed to help trainees improve their performance through either guided- or self-reflection. When the training system deals with human-to-human communications, as one would find in a teacher, counselor, enterprise culture or cross-cultural trainer, such feedback needs to focus on all aspects of human communication. This means that, in addition to verbal communication, nonverbal messages must be captured and analyzed for semantic meaning. The goal of this dissertation is to employ machine-learning algorithms that semi-automate and, where supported, automate event tagging in training systems developed to improve human-to-human interaction. The specific context in which …

High-Performance Composable Transactional Data Structures, Deli Zhang

Electronic Theses and Dissertations

Exploiting the parallelism in multiprocessor systems is a major challenge in the post ``power wall'' era. Programming for multicore demands a change in the way we design and use fundamental data structures. Concurrent data structures allow scalable and thread-safe accesses to shared data. They provide operations that appear to take effect atomically when invoked individually. A main obstacle to the practical use of concurrent data structures is their inability to support composable operations, i.e., to execute multiple operations atomically in a transactional manner. The problem stems from the inability of concurrent data structure to ensure atomicity of transactions composed from …