Engineering Commons^™

Rapid Deployment Indoor Localization Without Prior Human Participation, Han Xu, Zimu Zhou, Longfei Shangguan

Research Collection School Of Computing and Information Systems

In this work, we propose RAD, a RApid Deployment localization framework without human sampling. The basic idea of RAD is to automatically generate a fingerprint database through space partition, of which each cell is fingerprinted by its maximum influence APs. Based on this robust location indicator, fine-grained localization can be achieved by a discretized particle filter utilizing sensor data fusion. We devise techniques for CIVD-based field division, graph-based particle filter, EM-based individual character learning, and build a prototype that runs on commodity devices. Extensive experiments show that RAD provides a comparable performance to the state-of-the-art RSSbased methods while relieving it …

Open Source Database And Website To Provide Free And Open Access To Inactive U.S. Patents In The Public Domain, Yuenyong Nilsiam, Joshua M. Pearce

Department of Materials Science and Engineering Publications

Although theoretically the patent system is meant to bolster innovation, the current United States Patent and Trademark Office (USPTO) is cumbersome and involves a significant time investment to locate inactive patents less than 20 years old. This article reports on the development of an open source database to find these public domain ideas. First, a search strategy is explained. Then the operation and use of free and open source software are detailed to meet the needs of open hardware innovators. Finally, a case study is presented to demonstrate the utility of the approach with 3-D printing. The results showed how …

An M-Learning Maturity Model For Universities And Higher Educational Institutes, Luiz Fernando Capretz, Muasaad Alrasheedi, Arif Raza

Electrical and Computer Engineering Publications

An m-learning maturity model is put forward in this research to assess the mobile technology adoption rates in universities and higher educational institutes. The model is derived from Capability Maturity Model (CMM), which has been widely used in organizations to gauge the adoption of various new processes. Five levels of m-learning maturity are specified including preliminary, established, defined, structured, and continuous improvement. Each of these maturity levels is gauged through nine critical success factors (CSFs) in assessment questionnaires. The CSFs used in measuring instrument of the model are adopted from three of our previous empirical studies. Using an assessment questionnaire …

Open Source, Modular Platforms, And The Challenge Of Fragmentation, Christopher S. Yoo

All Faculty Scholarship

Open source and modular platforms represent two powerful conceptual paradigms that have fundamentally transformed the software industry. While generally regarded complementary, the freedom inherent in open source rests in uneasy tension with the strict structural requirements required by modularity theory. In particular, third party providers can produce noncompliant components, and excessive experimentation can fragment the platform in ways that reduce its economic benefits for end users and app providers and force app providers to spend resources customizing their code for each variant. The classic solutions to these problems are to rely on some form of testing to ensure that the …

Access All Around: A Niso Update On Open Access Discovery & Access Related Projects, Pascal Vincent Calarco, John G. Dove, Christine Stohn

Leddy Library Presentations

In this session, members of the NISO Discovery to Delivery Topic Committee will discuss NISO projects, recommendations and standards dealing with hot topics around discovery and access of electronic content. Presentations will include updates on open access discovery, specifically the recommended practice Access and License Indicators (ALI) and discussion of a new project proposal regarding discoverability of open access material. In addition, we will discuss two new projects. The first involves automatic transfer of packages and institutional entitlements from information providers to knowledge bases for the identification of institutional access rights using the KBART recommended practice. The second work item …

Saliency Ratio And Power Factor Of Ipm Motors Optimally Designed For High Efficiency And Low Cost Objectives, Peng Zhang, Dan M. Ionel, Nabeel Demerdash

Electrical and Computer Engineering Faculty Research and Publications

This paper uses formal mathematical optimization techniques based on parametric finite-element-based computationally efficient models and differential evolution algorithms. For constant-power applications, in the novel approach described, three concurrent objective functions are minimized: material cost, losses, in order to ensure high efficiency, and the difference between the rated and the characteristic current, aiming to achieve very high constant-power flux-weakening range. Only the first two objectives are considered for constant-torque applications. Two types of interior permanent magnet rotors in a single- and double-layer V-shaped configuration are considered, respectively. The stator has the typical two slots per pole and phase distributed winding configuration. …

Amulet: An Energy-Efficient, Multi-Application Wearable Platform, Josiah Hester, Travis Peters, Tianlong Yun, Ronald Peterson, Joseph Skinner, Bhargav Golla, Kevin Storer, Steven Hearndon, Kevin Freeman, Sarah Lord, Ryan Halter, David Kotz, Jacob Sorber

Dartmouth Scholarship

Wearable technology enables a range of exciting new applications in health, commerce, and beyond. For many important applications, wearables must have battery life measured in weeks or months, not hours and days as in most current devices. Our vision of wearable platforms aims for long battery life but with the flexibility and security to support multiple applications. To achieve long battery life with a workload comprising apps from multiple developers, these platforms must have robust mechanisms for app isolation and developer tools for optimizing resource usage.\r\n\r\nWe introduce the Amulet Platform for constrained wearable devices, which includes an ultra-low-power hardware architecture …

Formal Performance Guarantees For Behavior-Based Localization Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang

Faculty Publications

Abstract— Localization and mapping algorithms can allow a robot to navigate well in an unknown environment. However, whether such algorithms enhance any specific robot mission is currently a matter for empirical validation. In this paper we apply our MissionLab/VIPARS mission design and verification approach to an autonomous robot mission that uses probabilistic localization software.

Two approaches to modeling probabilistic localization for verification are presented: a high-level approach, and a sample-based approach which allows run-time code to be embedded in verification. Verification and experimental validation results are presented for two different missions, each using each method, demonstrating the accuracy …

Designing Minimal Effective Normative Systems With The Help Of Lightweight Formal Methods, Jianye Hao, Eunsuk Kang, Jun Sun, Daniel Jackson

Research Collection School Of Computing and Information Systems

Normative systems are an important approach to achieving effective coordination among (often an arbitrary number of) agents in multiagent systems. A normative system should be effective in ensuring the satisfaction of a desirable system property, and minimal (i.e., not containing norms that unnecessarily over-constrain the behaviors of agents). Designing or even automatically synthesizing minimal effective normative systems is highly non-trivial. Previous attempts on synthesizing such systems through simulations often fail to generate normative systems which are both minimal and effective. In this work, we propose a framework that facilitates designing of minimal effective normative systems using lightweight formal methods. Given …

Summarization Of Egocentric Videos: A Comprehensive Survey, Ana Garcia Del Molino, Cheston Tan, Joo-Hwee Lim, Ah-Hwee Tan

Research Collection School Of Computing and Information Systems

The introduction of wearable video cameras (e.g., GoPro) in the consumer market has promoted video life-logging, motivating users to generate large amounts of video data. This increasing flow of first-person video has led to a growing need for automatic video summarization adapted to the characteristics and applications of egocentric video. With this paper, we provide the first comprehensive survey of the techniques used specifically to summarize egocentric videos. We present a framework for first-person view summarization and compare the segmentation methods and selection algorithms used by the related work in the literature. Next, we describe the existing egocentric video datasets …

Smart Power Grid Synchronization With Fault Tolerant Nonlinear Estimation, Xin Wang, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

Effective real-time state estimation is essential for smart grid synchronization, as electricity demand continues to grow, and renewable energy resources increase their penetration into the grid. In order to provide a more reliable state estimation technique to address the problem of bad data in the PMU-based power synchronization, this paper presents a novel nonlinear estimation framework to dynamically track frequency, voltage magnitudes and phase angles. Instead of directly analyzing in abc coordinate frame, symmetrical component transformation is employed to separate the positive, negative, and zero sequence networks. Then, Clarke's transformation is used to transform the sequence networks into the αβ …

A Security Analysis Of Cyber-Physical Systems Architecture For Healthcare, Darren Seifert, Hassan Reza

Computer Science Faculty Publications

This paper surveys the available system architectures for cyber-physical systems. Several candidate architectures are examined using a series of essential qualities for cyber-physical systems for healthcare. Next, diagrams detailing the expected functionality of infusion pumps in two of the architectures are analyzed. The STRIDE Threat Model is then used to decompose each to determine possible security issues and how they can be addressed. Finally, a comparison of the major security issues in each architecture is presented to help determine which is most adaptable to meet the security needs of cyber-physical systems in healthcare.

Recognizing And Combating Cybercrime, Marcia L. Dority Baker

Information Technology Services: Publications

Can You Spot the Scam?

Scams make great stories. Tales of Internet crime or other fraud make up some of Hollywood's most exciting thrillers. While cybercrime blockbusters are fun to watch on the big screen, cybercrime is a serious problem on campuses globally.

How many people do you know who are the victim of a scam (Internet or phone)? According to the FBI, cybercrime is a growing threat that affects individuals and businesses around the world. A recent Washington Post article reported that cybercrime cost the global economy $445 billion in 2014.

Development Of A Wireless Environmental Data Acquisition Prototype Adopting Agile Practices: An Experience Report, Paul Celicourt, Richard Sam, Michael Piasecki

Publications and Research

The traditional software development model commonly named “waterfall” is unable to cope with the increasing functionality and complexity of modern embedded systems. In addition, it is unable to support the ability for businesses to quickly respond to new market opportunities due to changing requirements. As a response, the software development community developed the Agile Methodologies (e.g., extreme Programming, Scrum) which were also adopted by the Embedded System community. However, failures and bad experiences in applying Agile Methodologies to the development of embedded systems have not been reported in the literature. Therefore, this paper contributes a detailed account of our first-time …

Studying The Effects Of Serpentine Soil On Adapted And Non-Adapted Species Using Arduino Technology, Kiana Saniee, Edward Himelblau, Brian Paavo

STAR Program Research Presentations

Abstract: Serpentine soils are formed from ultramafic rocks and are represent an extreme environment for plants. Serpentine soils are unique in that they carry high concentrations of heavy metals, are nutrient deficient, particularly in calcium, and have poor water retention capabilities. Although these soils constitute harsh conditions for plant growth, there are a number of species that are adapted and even endemic to serpentine soil. Water retention by commercial potting mix was compared with serpentine soil. Also, serpentine adapted and non-adapted species were grown in both soil treatments and physiological data were collected. We used the Arduino electronic platform to …

A Comparison Of X86 Computer Architecture Simulators, Ayaz Akram, Lina Sawalha

Computer Architecture and Systems Research Laboratory (CASRL)

The significance of computer architecture simulators in advancing computer architecture research is widely acknowledged. Computer architects have developed numerous simulators in the past few decades and their number continues to rise. This paper explores different simulation techniques and surveys many simulators. Comparing simulators with each other and validating their correctness has been a challenging task. In this paper, we compare and contrast x86 simulators in terms of flexibility, level of details, user friendliness and simulation models. In addition, we measure the experimental error and compare the speed of four contemporary x86 simulators: gem5, Sniper, Multi2sim and PTLsim. We also discuss …

Support Vector Machines And Artificial Neural Networks: Assessing The Validity Of Using Technical Features For Security Forecasting, James Dipadua

Dissertations

Stock forecasting is an enticing and well-studied problem in both finance and machine learning literature with linear-based models such as ARIMA and ARCH to non-linear Artificial Neural Networks (ANN) and Support Vector Machines (SVM). However, these forecasting techniques also use very different input features, some of which are seen by economists as irrational and theoretically unjustified. In this comparative study using ANNs and SVMs for 12 publicly traded companies, derivative price “technicals” are evaluated against macro- and microeconomic fundamentals to evaluate the efficacy of model performance. Despite the efficient market hypothesis positing the ill-suitability of technicals as model inputs, this …

Repmatch: Robust Feature Matching And Pose For Reconstructing Modern Cities, Wen-Yan Lin, Siying Liu, Minh N. Do, Ping Tan, Jiangbo Lu

Research Collection School Of Computing and Information Systems

A perennial problem in recovering 3-D models from images is repeated structures common in modern cities. The problem can be traced to the feature matcher which needs to match less distinctive features (permitting wide-baselines and avoiding broken sequences), while simultaneously avoiding incorrect matching of ambiguous repeated features. To meet this need, we develop RepMatch, an epipolar guided (assumes predominately camera motion) feature matcher that accommodates both wide-baselines and repeated structures. RepMatch is based on using RANSAC to guide the training of match consistency curves for differentiating true and false matches. By considering the set of all nearest-neighbor matches, RepMatch can …

2016 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2016.

Violating Of Individual Privacy: Moroccan Perceptions Of The Ban Of Voip Services, Tyler Delhees

Independent Study Project (ISP) Collection

On January 6, 2016, the Moroccan telecommunications regulatory agency, the ANRT, announced a ban onVoice Over Internet Protocol(VoIP) calling services such as Skype, WhatsApp, and Viber. The ban triggered sweeping opposition among the Moroccan public, opening discussion of digital rights, censorship, and Internet governance. Considering liberal democratic rights in the 2011 Moroccan Constitution and a history of censorship, this study analyzes the official justification of the ANRT alongside additional explanations involving business interests and the security services. The purpose of this study is to gauge the perceptions of Moroccans on the decision of the ANRT and provide a holistic explanation. …

Toward Distributed At-Scale Hybrid Network Test With Emulation And Simulation Symbiosis, Rong Rong

FIU Electronic Theses and Dissertations

In the past decade or so, significant advances were made in the field of Future Internet Architecture (FIA) design. Undoubtedly, the size of Future Internet will increase tremendously, and so will the complexity of its users’ behaviors. This advancement means most of future Internet applications and services can only achieve and demonstrate full potential on a large-scale basis. The development of network testbeds that can validate key design decisions and expose operational issues at scale is essential to FIA research. In conjunction with the development and advancement of FIA, cyber-infrastructure testbeds have also achieved remarkable progress. For meaningful network studies, …

Activist: A New Framework For Dataset Labelling, Jack O'Neill, Sarah Jane Delany, Brian Mac Namee

Conference papers

Acquiring labels for large datasets can be a costly and time-consuming process. This has motivated the development of the semi-supervised learning problem domain, which makes use of unlabelled data — in conjunction with a small amount of labelled data — to infer the correct labels of a partially labelled dataset. Active Learning is one of the most successful approaches to semi-supervised learning, and has been shown to reduce the cost and time taken to produce a fully labelled dataset. In this paper we present Activist; a free, online, state-of-the-art platform which leverages active learning techniques to improve the efficiency of …

Empirical Comparative Analysis Of 1-Of-K Coding And K-Prototypes In Categorical Clustering, Fei Wang, Hector Franco, John Pugh, Robert J. Ross

Conference papers

Clustering is a fundamental machine learning application, which partitions data into homogeneous groups. K-means and its variants are the most widely used class of clustering algorithms today. However, the original k-means algorithm can only be applied to numeric data. For categorical data, the data has to be converted into numeric data through 1-of-K coding which itself causes many problems. K-prototypes, another clustering algorithm that originates from the k-means algorithm, can handle categorical data by adopting a different notion of distance. In this paper, we systematically compare these two methods through an experimental analysis. Our analysis shows that K-prototypes is more …

Landmark Detection With Surprise Saliency Using Convolutional Neural Networks, Feng Tang, Damian Lyons, Daniel Leeds

Faculty Publications

Abstract—Landmarks can be used as reference to enable people or robots to localize themselves or to navigate in their environment. Automatic definition and extraction of appropriate landmarks from the environment has proven to be a challenging task when pre-defined landmarks are not present. We propose a novel computational model of automatic landmark detection from a single image without any pre-defined landmark database. The hypothesis is that if an object looks abnormal due to its atypical scene context (what we call surprise saliency), it then may be considered as a good landmark because it is unique and easy to spot by …

Support Vector Machines And Artificial Neural Networks: Assessing The Validity Of Using Technical Features For Security Forecasting, James Di Padua

Dissertations

Stock forecasting is an enticing and well studied problem in both finance and machine learning literature with linear based models such as ARIMA and ARCH to nonlinear Artificial Neural Networks (ANN) and Support Vector Machines (SVM). However, these forecasting techniques also use very different input features, some of which are seen by economists as irrational and theoretically unjustified. In this comparative study using ANNs and SVMs for 12 publicly traded companies, derivative price “technicals” are evaluated against macro and microeconomic fundamentals to evaluate the efficacy of model performance. Despite the efficient market hypothesis positing the ill suitability of technicals as …

Using Spatialisation To Support Exploratory Search Behaviour, Clement Roux

Dissertations

Information-seekers traditionally interact with digital content through keyword-based search interfaces displaying results in list views. Well-defined lookup search tasks are performed brilliantly with these interfaces, enabling users to find relevant information and develop a relative understanding of the underlying information space. However, it is feasible to suggest that ill-defined and abstract search tasks could be better supported with a different interface that could allow the user to explore a library’s content and develop an appropriate mental model of the information space. One such approach is based on the use of visualisation, an approach to data analysis that aims to reduce …

A Regression Study Of Salary Determinants In Indian Job Markets For Entry Level Engineering Graduates, Rajveer Singh

Dissertations

The economic liberalisation of Indian markets in early 90s boosted the economic growth of the nation in various sectors over the next two decades. One such sector that has seen a massive growth in this time is Information Technology (IT). The IT industry has played a very crucial role in transforming India from a slow moving economy to one of the largest exporters of IT services. This growth created a huge demand in the labour markets for skilled labour, which in turn made engineering one of the top choices of study after high school over the years. In addition, the …

Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh

Dissertations

This thesis reviews the current state of photometric classification in Astronomy and identifies two main gaps: a dependence on handcrafted rules, and a lack of interpretability in the more successful classifiers. To address this, Deep Learning and Computer Vision were used to create a more interpretable model, using unsupervised training to reduce human bias.

The main contribution is the investigation into the impact of using unsupervised feature-extraction from multi-wavelength image data for the classification task. The feature-extraction is achieved by implementing an unsupervised Deep Belief Network to extract lower-dimensionality features from the multi-wavelength image data captured by the Sloan Digital …

Routing Algorithm With Uneven Clustering For Energy Heterogeneous Wireless Sensor Networks, Ying Zhang, Wei Xiong, Dezhi Han, Wei Chen, Jun Wang

Computer Science Faculty Research

Aiming at the “hotspots” problem in energy heterogeneous wireless sensor networks, a routing algorithm of heterogeneous sensor network with multilevel energies based on uneven clustering is proposed. In this algorithm, the energy heterogeneity of the nodes is fully reflected in the mechanism of cluster-heads’ election. It optimizes the competition radius of the cluster-heads according to the residual energy of the nodes. This kind of uneven clustering prolongs the lifetime of the cluster-heads with lower residual energies or near the sink nodes. In data transmission stage, the hybrid multihop transmission mode is adopted, and the next-hop routing election fully takes account …

A Fault-Tolerant T-Type Multilevel Inverter Topology With Soft-Switching Capability Based On Si And Sic Hybrid Phase Legs, Jiangbiao He, Nathan Weise, Ramin Katebi, Lixiang Wei, Nabeel Demerdash

Electrical and Computer Engineering Faculty Research and Publications

The performance of a novel three-phase four-leg fault-tolerant T-Type inverter topology is presented in this paper, which significantly improves the inverter's fault-tolerant capability regarding device switch faults. In this new modular inverter topology, only the redundant leg is composed of Silicon Carbide (SiC) power devices and all other phase legs are constituted by Silicon (Si) devices. The addition of the redundant leg, not only provides fault-tolerant solution to switch faults that could occur in the T-Type inverter, but also can share load current with other phase legs. Moreover, quasi zero-voltage switching (ZVS) and zero-current switching (ZCS) in the Si Insulated-Gate …