Computer Sciences Commons^™

Semantic Web Based Relational Database Access With Conflict Resolution, Fayez Khazalah

Wayne State University Dissertations

This thesis focuses on (1) accessing relational databases through Semantic Web technologies and (2) resolving conflicts that usually arises when integrating data from heterogeneous source schemas and/or instances.

In the first part of the thesis, we present an approach to access relational databases using Semantic Web technologies. Our approach is built on top of Ontop framework for Ontology Based Data Access. It extracts both Ontop mappings and an equivalent OWL ontology from an existing database schema. The end users can then access the underlying data source through SPARQL queries. The proposed approach takes into consideration the different relationships between the …

Applications Of Machine Learning In Biology And Medicine, Saied Haidarian Shahri

Wayne State University Dissertations

Machine learning as a field is defined to be the set of computational algorithms that improve their performance by assimilating data.

As such, the field as a whole has found applications in many diverse disciplines from robotics and communication in engineering to economics and finance, and also biology and medicine.

It should not come as a surprise that many popular methods in use today have completely different origins.

Despite this heterogeneity, different methods can be divided into standard tasks, such as supervised, unsupervised, semi-supervised and reinforcement learning.

Although machine learning as a field can be formalized as methods trying to …

A Control-Theoretic Design And Analysis Framework For Resilient Hard Real-Time Systems, Pradeep Mahendra Hettiarachchi

Wayne State University Dissertations

We introduce a new design metric called system-resiliency which characterizes the maximum unpredictable

external stresses that any hard-real-time performance mode can withstand. Our proposed systemresiliency

framework addresses resiliency determination for real-time systems with physical and hardware

limitations. Furthermore, our framework advises the system designer about the feasible trade-offs between

external system resources for the system operating modes on a real-time system that operates in a

multi-parametric resiliency environment.

Modern multi-modal real-time systems degrade the system’s operational modes as a response to unpredictable

external stimuli. During these mode transitions, real-time systems should demonstrate a reliable

and graceful degradation of service. Many …

Resource Management In Cloud And Big Data Systems, Lena Mashayekhy

Wayne State University Dissertations

Cloud computing is a paradigm shift in computing, where services are offered and acquired on demand in a cost-effective way. These services are often virtualized, and they can handle the computing needs of big data analytics. The ever-growing demand for cloud services arises in many areas including healthcare, transportation, energy systems, and manufacturing. However, cloud resources such as computing power, storage, energy, dollars for infrastructure, and dollars for operations, are limited. Effective use of the existing resources raises several fundamental challenges that place the cloud resource management at the heart of the cloud providers' decision-making process. One of these challenges …

Efficient Synergistic De Novo Co-Assembly Of Bacterial Genomes From Single Cells Using Colored De Bruijn Graph, Narjes Sadat Movahedi Tabrizi

Wayne State University Dissertations

Recent progress in DNA amplification techniques, particularly multiple displacement

amplification (MDA), has made it possible to sequence and assemble bacterial

genomes from a single cell. However, the quality of single cell genome assembly has

not yet reached the quality of normal multi-cell genome assembly due to the coverage

bias (including uneven depth of coverage and region blackout) and errors caused by

MDA. Computational methods try to mitigates the amplification bias. In this document

we introduce a de novo co-assembly method using colored de Bruijn graph,

which can overcome the problem of blackout regions due to amplification bias. The

algorithm is …

Building Computing-As-A-Service Mobile Cloud System, Kun Wang

Wayne State University Dissertations

The last five years have witnessed the proliferation of smart mobile devices, the explosion of various mobile applications and the rapid adoption of cloud computing in business, governmental and educational IT deployment. There is also a growing trends of combining mobile computing and cloud computing as a new popular computing paradigm nowadays. This thesis envisions the future of mobile computing which is primarily affected by following three trends: First, servers in cloud equipped with high speed multi-core technology have been the main stream today. Meanwhile, ARM processor powered servers is growingly became popular recently and the virtualization on ARM systems …

Efficient Algorithms And Optimizations For Scientific Computing On Many-Core Processors, Kamel Rushaidat

Wayne State University Dissertations

Designing efficient algorithms for many-core and multicore architectures requires using different strategies to allow for the best exploitation of the hardware resources on those architectures. Researchers have ported many scientific applications to modern many-core and multicore parallel architectures, and by doing so they have achieved significant speedups over running on single CPU cores. While many applications have achieved significant speedups, some applications still require more effort to accelerate due to their inherently serial behavior.

One class of applications that has this serial behavior is the Monte Carlo simulations. Monte Carlo simulations have been used to simulate many problems in statistical …

Design And Implementation Of Fast Motion Estimation In Modern Video Compression On Gpu, Zhaohua Yi

Electronic Theses and Dissertations

Motion estimation is the most compute expensive part of high definition video compression. It accounts for more than 50\% of overall execution. Therefore, improving the performance of motion estimation can make significant impact on the overall performance of video compression. The performance of motion estimation can be improved in two aspects: algorithm and implementation. This thesis touches both aspects. We first propose an innovative motion estimation algorithm by replacing the traditional block matching method which comparing blocks pixel by pixel with a brand new method which based on lbp (local binary pattern) code. Our new method first encodes the original …

Impact Of Eu Medical Device Directive On Medical Device Software, Guy Foe Owono

Walden Dissertations and Doctoral Studies

Directive 2007/47/EC of the European Parliament amending Medical Device Directive (MDD) provides medical device manufacturers with a compliance framework. However, the effects of the amendments to the MDD on competition in the U.S. medical device software industry are unknown. This study examined the impact of this directive on the competitiveness of U.S. medical device software companies, the safety and efficacy of medical device software, employee training, and recruitment. The conceptual framework for this study included 3 dimensions of medical device regulations: safety, performance, and reliability. The overall research design was a concurrent mixed method study using both quantitative and qualitative …

Effects Of Investor Sentiment Using Social Media On Corporate Financial Distress, Tarek Hoteit

Walden Dissertations and Doctoral Studies

The mainstream quantitative models in the finance literature have been ineffective in detecting possible bankruptcies during the 2007 to 2009 financial crisis. Coinciding with the same period, various researchers suggested that sentiments in social media can predict future events. The purpose of the study was to examine the relationship between investor sentiment within the social media and the financial distress of firms Grounded on the social amplification of risk framework that shows the media as an amplified channel for risk events, the central hypothesis of the study was that investor sentiments in the social media could predict t he level …

Rice Blast Disease Forecasting For Northern Philippines, Proceso L. Fernandez Jr, Alvin R. Malicdem

Department of Information Systems & Computer Science Faculty Publications

Rice blast disease has become an enigmatic problem in several rice growing ecosystems of both tropical and temperate regions of the world. In this study, we develop models for predicting the occurrence and severity of rice blast disease, with the aim of helping to prevent or at least mitigate the spread of such disease. Data from 2 government agencies in selected provinces from northern Philippines were gathered, cleaned and synchronized for the purpose of building the predictive models. After the data synchronization, dimensionality reduction of the feature space was done, using Principal Component Analysis (PCA), to determine the most important …

Choice Of Human–Computer Interaction Mode In Stroke Rehabilitation, Hossein Mousavi Hondori, Maryam Khademi, Lucy Dodakian, Alison Mackenzie, Cristina V. Lopes, Steven C. Cramer

Physical Therapy Faculty Articles and Research

Background and Objective. Advances in technology are providing new forms of human–computer interaction. The current study examined one form of human–computer interaction, augmented reality (AR), whereby subjects train in the real-world workspace with virtual objects projected by the computer. Motor performances were compared with those obtained while subjects used a traditional human–computer interaction, that is, a personal computer (PC) with a mouse. Methods. Patients used goal-directed arm movements to play AR and PC versions of the Fruit Ninja video game. The 2 versions required the same arm movements to control the game but had different cognitive demands. With …

Physical Engagement As A Way To Increase Emotional Rapport In Interactions With Embodied Conversational Agents, Ivan Gris Sepulveda

Open Access Theses & Dissertations

One of the major goals in research on embodied conversational agents (ECAs) is to increase the believability and perceived trustworthiness of agents. To improve the efficacy of the interaction between humans and ECAs, I focus on the development of rapport, which is a complex and extensive behavioral state of affinity, synchronicity, coordination and mutual understanding that is difficult to model, measure and interpret. I present our AGENT Framework and our ECA, Adriana, which is capable of speech recognition and gesture recognition over long periods of time. Our current system provides up to 60 minutes of human-ECA interaction in a jungle-survival …

Multi-Expert Multi-Criteria Decision Making, Joel Henderson

Open Access Theses & Dissertations

Expert analysis and decisions are highly valued assets in a wide variety of fields, from social services to grant funding committees. However, the use of experts can be prohibitive due to either lack of availability or cost. As such, it is desirable to be able to replicate such decisions. However, there are many obstacles that impede an accurate simulation of expert decisions. For example, despite looking at the same information, two experts may disagree on the decisions. In addition, a single expert may make inconsistent decisions across similar scenarios.

In this work, we focus on multi-criteria decision making and in …

Iso-Power-Efficiency: An Approach To Scaling Application Codes With A Power Budget, Rogelio Long

Open Access Theses & Dissertations

For many applications, speedup saturates and parallel efficiency decreases if the problem size is held fixed while increasing the number of processors. For some problems, it is possible to maintain a fixed parallel efficiency by increasing both the problem size and the number of processing elements. The rate at which the problem size must increase to maintain constant efficiency for a given rate of increase of the number of processors is given by the iso-efficiency function. We have developed a new scalability function called iso-power-efficiency that determines the rate at which the problem size must increase to maintain constant efficiency …

Bounded Rationality In Decision Making Under Uncertainty: Towards Optimal Granularity, Joseph Anthony Lorkowski

Open Access Theses & Dissertations

Starting from well-known studies by Kahmenan and Tversky, researchers have found many examples when our decision making seems to be irrational. We show that this seemingly irrational decision making can be explained if we take into account that human abilities to process information are limited. As a result, instead of the exact values of different quantities, we operate with granules that contain these values. On several examples, we show that optimization under such granularity restriction indeed leads to observed human decision making. Thus, granularity helps explain seemingly irrational human decision making.

Similar arguments can be used to explain the success …

Computation Offloading Decisions For Reducing Completion Time, Salvador Melendez

Open Access Theses & Dissertations

Mobile devices are being widely used in many applications such as image processing, computer vision (e.g. face detection and recognition), wearable computing, language translation, and battlefield operations. However, mobile devices are constrained in terms of their battery life, processor performance, storage capacity, and network bandwidth. To overcome these issues, there is an approach called Computation Offloading, also known as cyber-foraging and surrogate computing. Computation offloading consists of migrating computational jobs from a mobile device to more powerful remote computing resources. Upon completion of the job, the results are sent back to the mobile device. However, a decision must be made; …

Enhancing Workplace Productivity And Competitiveness In Trinidad And Tobago Through Ict Adoption, Kennedy Jerome Swaratsingh

Walden Dissertations and Doctoral Studies

The productivity of Trinidad and Tobago's public sector workplaces is related to their absorptive capacity for technological adoption. Guided by the technology acceptance model, which suggests that individuals' and institutions' use of technology increases in relation to perceived ease of use and apparent value, this case study explored how Trinidad and Tobago used information and communications technology from 2001 - 2010 to improve public sector workplace productivity. Study data were collected from 22 individual interviews with senior executives from the government of Trinidad and Tobago, members of the e-business roundtable, and local industry experts, and from reviewing the archives of …

Project Maelstrom: Forensic Analysis Of The Bittorrent-Powered Browser, Jason Farina, M-Tahar Kechadi, Mark Scanlon

Journal of Digital Forensics, Security and Law

In April 2015, BitTorrent Inc. released their distributed peer-to-peer powered browser, Project Maelstrom, into public beta. The browser facilitates a new alternative website distribution paradigm to the traditional HTTP-based, client-server model. This decentralised web is powered by each of the visitors accessing each Maelstrom hosted website. Each user shares their copy of the website;s source code and multimedia content with new visitors. As a result, a Maelstrom hosted website cannot be taken offline by law enforcement or any other parties. Due to this open distribution model, a number of interesting censorship, security and privacy considerations are raised. This paper explores …

The Subject Librarian Newsletter, Engineering And Computer Science, Fall 2015, Ven Basco

Libraries' Newsletters

No abstract provided.

Features For Ranking Tweets Based On Credibility And Newsworthiness, Jacob W. Ross

Browse all Theses and Dissertations

We create a robust and general feature set for learning to rank algorithms that rank tweets based on credibility and newsworthiness. In previous works, it has been demonstrated that when the training and testing data are from two distinct time periods, the ranker performs poorly. We improve upon previous work by creating a feature set that does not over fit a particular year or set of topics. This is critical given how people utilize social media changes as time progresses, and the topics discussed vary. In addition, we are constantly gaining new tweet data. Thus, it is important to be …

Domain-Specific Document Retrieval Framework For Near Real-Time Social Health Data, Swapnil Soni

Browse all Theses and Dissertations

With the advent of web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these services to share and seek health information in real-time has increased exponentially. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking of the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, the identification of useful information from the deluge of tweets is one of the major challenges. Twitter search is limited to keyword-based techniques to retrieve information for a given query and sometimes the results do not …

Automatic Emotion Identification From Text, Wenbo Wang

Browse all Theses and Dissertations

People's emotions can be gleaned from their text using machine learning techniques to build models that exploit large self-labeled emotion data from social media. Further, the self-labeled emotion data can be effectively adapted to train emotion classifiers in different target domains where training data are sparse.

Emotions are both prevalent in and essential to most aspects of our lives. They influence our decision-making, affect our social relationships and shape our daily behavior. With the rapid growth of emotion-rich textual content, such as microblog posts, blog posts, and forum discussions, there is a growing need to develop algorithms and techniques for …

Knowledge Enabled Location Prediction Of Twitter Users, Revathy Krishnamurthy

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As the popularity of online social networking sites such as Twitter and Facebook continues to rise, the volume of textual content generated on the web is increasing rapidly. The mining of user generated content in social media has proven effective in domains ranging from personalization and recommendation systems to crisis management. These applications stand to be further enhanced by incorporating information about the geo-position of social media users in their analysis. Due to privacy concerns, users are largely reluctant to share their location information. As a consequence of this, researchers have focused on automatic inferencing of location information from the …

A Language For Inconsistency-Tolerant Ontology Mapping, Kunal Sengupta

Browse all Theses and Dissertations

Ontology alignment plays a key role in enabling interoperability among various data sources present in the web. The nature of the world is such, that the same concepts differ in meaning, often so slightly, which makes it difficult to relate these concepts. It is the omni-present heterogeneity that is at the core of the web. The research work presented in this dissertation, is driven by the goal of providing a robust ontology alignment language for the semantic web, as we show that description logics based alignment languages are not suitable for aligning ontologies.

The adoption of the semantic web technologies …

Orthogonal Moment-Based Human Shape Query And Action Recognition From 3d Point Cloud Patches, Huaining Cheng

Browse all Theses and Dissertations

With the recent proliferation of 3D sensors such as Light Detection and Ranging (LIDAR), it is essential to develop feature representation methods that can best characterize the point clouds produced by these devices. When these devices are employed in targeting and surveillance of human actions from both ground and aerial platforms, the corresponding point clouds of body shape often comprise low-resolution, disjoint, and irregular patches of points resulted from self-occlusions and viewing angle variations. The prevailing method of depth image analysis has the limitation of relying on 2D features that are not native representation of 3D spatial relationships. On the …

Ontology Pattern-Based Data Integration, Adila Alfa Krisnadhi

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Data integration is concerned with providing a unified access to data residing at multiple sources. Such a unified access is realized by having a global schema and a set of mappings between the global schema and the local schemas of each data source, which specify how user queries at the global schema can be translated into queries at the local schemas. Data sources are typically developed and maintained independently, and thus, highly heterogeneous. This causes difficulties in integration because of the lack of interoperability in the aspect of architecture, data format, as well as syntax and semantics of the data. …

Learning To Rank Algorithms And Their Application In Machine Translation, Tian Xia

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In this thesis, we discuss two issues in the learning to rank area, choosing effective objective loss function, constructing effective regresstion trees in the gradient boosting framework, as well as a third issus, applying learning to rank models into statistcal machine translation. First, list-wise based learning to rank methods either directly optimize performance measures or optimize surrogate functions of performance measures that have smaller gaps between optimized losses and performance measures, thus it is generally believed that they should be able to lead to better performance than point-and pair-wise based learning to rank methods. However, in real-world applications, state-of-the-art practical …

Adaptive Duty Cycling In Sensor Networks With Energy Harvesting Using Continuous-Time Markov Chain And Fluid Models, Wai Hong Ronald Chan, Pengfei Zhang, Ido Nevat, Sai Ganesh Nagarajan, Alvin C. Valera, Hwee Xian Tan, Natarajan Gautam

Research Collection School Of Computing and Information Systems

Abstract:The dynamic and unpredictable nature of energy harvesting sources available for wireless sensor networks, and the time variation in network statistics like packet transmission rates and link qualities, necessitate the use of adaptive duty cycling techniques. Such adaptive control allows sensor nodes to achieve long-run energy neutrality, where energy supply and demand are balanced in a dynamic environment such that the nodes function continuously. In this paper, we develop a new framework enabling an adaptive duty cycling scheme for sensor networks that takes into account the node battery level, ambient energy that can be harvested, and application-level QoS requirements. We …

Low Effort Crowdsourcing: Leveraging Peripheral Attention For Crowd Work, Vaish Rajan, Peter Organisciak, Kotaro Hara, Jeffrey P. Bigham, Haoqi Zhang

Research Collection School Of Computing and Information Systems

Crowdsourcing systems leverage short bursts of focusedattention from many contributors to achieve a goal. Byrequiring people’s full attention, existing crowdsourcingsystems fail to leverage people’s cognitive surplus in themany settings for which they may be distracted, performingor waiting to perform another task, or barely payingattention. In this paper, we study opportunities for loweffortcrowdsourcing that enable people to contribute toproblem solving in such settings. We discuss the designspace for low-effort crowdsourcing, and through a seriesof prototypes, demonstrate interaction techniques, mechanisms,and emerging principles for enabling low-effortcrowdsourcing.