Digital Commons Network^™

Location Privacy In Emerging Network-Based Applications, Yong Xi

Wayne State University Dissertations

With the wide spread of computer systems and networks, privacy has become an issue that increasingly attracts attention. In wireless sensor networks, the location of an event source may be subject to unintentional disclosure through traffic analysis by the attacker. In vehicular networks, authentication leaves a trail to tie a driver to a sequence of time and space coordinates. In a cloud-based navigation system, the location information of a sensitive itinerary is disclosed. Those scenarios have shown that privacy protection is a far-reaching problem that could span many different aspects of a computer/network system, especially on a diversified landscape of …

Effective Semantic-Based Keyword Search Over Relational Databases For Knowledge Discovery, Sina Fakhraee

Wayne State University Dissertations

Keyword-based search has been popularized by Internet web search engines such as Google which is the most commonly used search engine to locate the information on the web. On the other hand while traditional database management systems offer powerful query languages such as SQL, they do not provide keyword-based search similar to the one provided by web search engines. The current amount of text data in relational databases is massive and is growing fast. This increases the importance and need for non-technical users to be able to search for such information using simple keyword search just as how they would …

A New Semantic Similarity Join Method Using Diffusion Maps And Long String Table Attributes, Bilal Hani Hawashin

Wayne State University Dissertations

With the rapid increase of the distributed data sources, and in order to make information integration, there is a need to combine the information that refers to the same entity from different sources. However, there are no global conventions that control the format of the data, and it is impractical to impose such global conventions. Also, there could be some spelling errors in the data as it is entered manually in most of the cases. For such reasons, the need to find and join similar records instead of exact records is important in order to integrate the data. Most of …

Competencies Of Expert Web-Based Instruction Designers, Yonghui Chen

Wayne State University Dissertations

Web-based instruction has been increasingly accepted in education, business and industry, military and government, healthcare and other sectors as a dominant means to deliver instruction beyond time and geographical constraints. However, the overall quality of WBI courses or programs remains a concern. The reasons for the ineffectiveness can be many, of which is the lack of sufficient competencies and skills in existing professionals. This study attempts to identify the domains, competencies, performance statement for instructional designers in WBI at the expert level. IBSTPI competency model has been used as the conceptual framework, utilizing mixed methods.

As a result, 91 performance …

Hierarchical Multi-Label Classification For Protein Function Prediction Going Beyond Traditional Approaches, Noor Al Aydie

Wayne State University Dissertations

Hierarchical multi-label classification is a variant of traditional classification in which the

instances can belong to several labels, that are in turn organized in a hierarchy. Functional classification of genes is a challenging problem in functional genomics due to several reasons. First, each gene participates in multiple biological activities. Hence, prediction models should support multi-label classification. Second, the genes are organized and classified according to a hierarchical classification scheme that represents the relationships between the functions of the genes. These relationships should be maintained by the prediction models. In addition, various bimolecular data sources, such as gene expression data and …

System Support For Robust Data Collection In Wireless Sensing Systems, Guoxing Zhan

Wayne State University Dissertations

This dissertation studied how to provide system support for robust data collection in wireless sensing systems through addressing a few urgent design issues in the existing systems. A wireless sensing system may suffer issues arising at the sensors, during the data transmission, and during the data access by applications. Due to the unique characteristics of wireless sensing systems, certain conventional solutions for networked systems may not work well with these issues. We developed approaches to resolve these urgent problems in the design of wireless sensing systems. Specially, we have achieved the following: (1) we developed a resilient trust model to …

Systems Support For Genomics Computing In Cloud Environments, Tung Thanh Nguyen

Wayne State University Dissertations

Genomics research has enormous applications in many areas such as health care, forensic, agriculture, etc. Most recent achievements in this field come from the availability of the unprecedented genomic data. However, new sequencing technologies in genomics keep producing data at a faster pace resulting a very huge amount of data. This poses great challenges on how to store, manage, process and analyze the data efficiently. To deal with these, genomics research groups often equip themselves with a small scale server room composed of high storage capacity and computing ability machines. This solution is not only costly, unscalable but also inefficient. …

Rethinking The Design And Implementation Of The I/O Software Stack For High-Performance Computing, Xuechen Zhang

Wayne State University Dissertations

Current I/O stack for high-performance computing is composed of multiple software layers in order to hide users from complexity of I/O performance optimization. However, the design and implementation of a specific layer is usually carried out separately with limited consideration of its impact on other layers, which could result in suboptimal I/O performance because data access locality is weakened, if not lost, on hard disk, a widely used storage medium in high-end storage systems.

In this dissertation, we experimentally demonstrated such issues in four different layers, including operating system process management layer and MPI-IO middleware layer on compute server side, …

Bringing To Life An Ancient Urban Center At Monte Albán, Mexico: Exploiting The Synergy Between The Micro, Meso, And Macro Levels In A Complex System, Thaer W. Jayyousi

Wayne State University Dissertations

In this dissertation, agent-based models of emergent ancient urban centers were constructed through the use of techniques from computational intelligence, agent-based modeling, complex systems, and data-mining of existing archaeological data from the prehistoric urban center, Monte Albán. This real world application was selected because of its importance in understanding the emergence of modern economic and political systems. Specifically, Cultural Algorithms was used to evolve models of early Monte Alban, models that can then be compared with existing models of ancient and modern urban centers.

Features of a complex system were used to help interpret the archaeological data. The analysis went …

Querying And Managing Opm-Compliant Scientific Workflow Provenance, Chunhyeok Lim

Wayne State University Dissertations

Provenance, the metadata that records the derivation history of scientific results, is important in scientific workflows to interpret, validate, and analyze the result of scientific computing. Recently,

to promote and facilitate interoperability among heterogeneous provenance systems, the Open Provenance Model (OPM) has been proposed and has played an important role in the community.

In this dissertation, to efficiently query and manage OPM-compliant provenance, we first propose a provenance collection framework that collects both prospective provenance, which captures

an abstract workflow specification as a recipe for future data derivation and retrospective provenance, which captures past workflow execution and data derivation information. …

A Framework For Personalized Dynamic Cross-Selling In E-Commerce Retailing, Arun K. Timalsina

Wayne State University Dissertations

Cross-selling and product bundling are prevalent strategies in the retail sector. Instead of static bundling offers, i.e. giving the same offer to everyone, personalized dynamic cross-selling generates targeted bundle offers and can help maximize revenues and profits. In resolving the two basic problems of dynamic cross-selling, which involves selecting the right complementary products and optimizing the discount, the issue of computational complexity becomes central as the customer base and length of the product list grows. Traditional recommender systems are built upon simple collaborative filtering techniques, which exploit the informational cues gained from users in the form of product ratings and …

Differential Modeling For Cancer Microarray Data, Omar Odibat

Wayne State University Dissertations

Capturing the changes between two biological phenotypes is a crucial task in understanding the mechanisms of various diseases. Most of the existing computational approaches depend on testing the changes in the expression levels of each single gene individually. In this work, we proposed novel computational approaches to identify the differential genes between two phenotypes. These approaches aim to quantitatively characterize the differences between two phenotypes and can provide better insights and understanding of various diseases. The purpose of this thesis is three-fold. Firstly, we review the state-of-the-art approaches for differential analysis of gene expression data.

Secondly, we propose a novel …

Complex Data Analytics Via Sparse, Low-Rank Matrix Approximation, Lijun Wang

Wayne State University Dissertations

Today, digital data is accumulated at a faster than ever speed in science, engineering, biomedicine, and real-world sensing. Data mining provides us an effective way for the exploration and analysis of hidden patterns from these data for a broad spectrum of applications. Usually, these datasets share one prominent characteristic: tremendous in size with tens of thousands of objects and features. In addition, data is not only collected over a period of time, but the relationship between data points can change over that period too. Besides, knowledge is very sparsely encoded because the patterns are usually active only in a local …