Engineering Commons^™

Fiber-Optic Temperature And Flow Sensory System And Methods, Ming Han, Guigen Liu, Weilin Hou, Qiwen Shen

Department of Electrical and Computer Engineering: Faculty Publications

A fiber optic sensor, a process for utilizing a fiber optic sensor, and a process for fabricating a fiber optic sensor are described, where a double-side-polished silicon pillar is attacked to an optical fiber tip and forms, a Fabry-Perot cavity. In an implementation, a fiber optic sensor in accordance with an examplary embodiment includes an optical fiber configured to be coupled to a light source and a spectrometer; and a single silicon layer or multiple silicon layers disposed on an end face of the optical fiber, where each of the silicon layer(s) defines a Fabry-Perot interferometer, and where the sensor …

Amodal Instance Segmentation And Multi-Object Tracking With Deep Pixel Embedding, Yanfeng Liu

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

This thesis extends upon the representational output of semantic instance segmentation by explicitly including both visible and occluded parts. A fully convolutional network is trained to produce consistent pixel-level embedding across two layers such that, when clustered, the results convey the full spatial extent and depth ordering of each instance. Results demonstrate that the network can accurately estimate complete masks in the presence of occlusion and outperform leading top-down bounding-box approaches.

The model is further extended to produce consistent pixel-level embeddings across two consecutive image frames from a video to simultaneously perform amodal instance segmentation and multi-object tracking. No post-processing …

Aluminum/Carbon Composites Materials Fabricated By The Powder Metallurgy Process, Amélie Veillère, Hiroki Kurita, Akira Kawasaki, Yongfeng Lu, Jean-Marc Heintz, Jean-François Silvain

Department of Electrical and Computer Engineering: Faculty Publications

Aluminum matrix composites reinforced with carbon fibers or diamond particles have been fabricated by a powder metallurgy process and characterized for thermal management applications. Al/C composite is a nonreactive system (absence of chemical reaction between the metallic matrix and the ceramic reinforcement) due to the presence of an alumina layer on the surface of the aluminum powder particles. In order to achieve fully dense materials and to enhance the thermo-mechanical properties of the Al/C composite materials, a semi-liquid method has been carried out with the addition of a small amount of Al-Si alloys in the Al matrix. Thermal conductivity and …

Advanced Security Analysis For Emergent Software Platforms, Mohannad Alhanahnah

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Emergent software ecosystems, boomed by the advent of smartphones and the Internet of Things (IoT) platforms, are perpetually sophisticated, deployed into highly dynamic environments, and facilitating interactions across heterogeneous domains. Accordingly, assessing the security thereof is a pressing need, yet requires high levels of scalability and reliability to handle the dynamism involved in such volatile ecosystems.

This dissertation seeks to enhance conventional security detection methods to cope with the emergent features of contemporary software ecosystems. In particular, it analyzes the security of Android and IoT ecosystems by developing rigorous vulnerability detection methods. A critical aspect of this work is the …

Formal Modeling And Analysis Of A Family Of Surgical Robots, Niloofar Mansoor

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Safety-critical applications often use dependability cases to validate that specified properties are invariant, or to demonstrate a counterexample showing how that property might be violated. However, most dependability cases are written with a single product in mind. At the same time, software product lines (families of related software products) have been studied with the goal of modeling variability and commonality and building family-based techniques for both modeling and analysis. This thesis presents a novel approach for building an end to end dependability case for a software product line, where a property is formally modeled, a counterexample is found and then …

Domain Adaptation In Unmanned Aerial Vehicles Landing Using Reinforcement Learning, Pedro Lucas Franca Albuquerque

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Landing an unmanned aerial vehicle (UAV) on a moving platform is a challenging task that often requires exact models of the UAV dynamics, platform characteristics, and environmental conditions. In this thesis, we present and investigate three different machine learning approaches with varying levels of domain knowledge: dynamics randomization, universal policy with system identification, and reinforcement learning with no parameter variation. We first train the policies in simulation, then perform experiments both in simulation, making variations of the system dynamics with wind and friction coefficient, then perform experiments in a real robot system with wind variation. We initially expected that providing …

Image Classification Using Fuzzy Fca, Niruktha Roy Gotoor

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Formal concept analysis (FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. It has been used in various domains such as data mining, machine learning, semantic web, Sciences, for the purpose of data analysis and Ontology over the last few decades. Various extensions of FCA are being researched to expand it's scope over more departments. In this thesis,we review the theory of Formal Concept Analysis (FCA) and its extension Fuzzy FCA. Many studies to use FCA in data mining and text learning have been pursued. We extend these studies to include …

Pixel-Level Deep Multi-Dimensional Embeddings For Homogeneous Multiple Object Tracking, Mateusz Mittek

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The goal of Multiple Object Tracking (MOT) is to locate multiple objects and keep track of their individual identities and trajectories given a sequence of (video) frames. A popular approach to MOT is tracking by detection consisting of two processing components: detection (identification of objects of interest in individual frames) and data association (connecting data from multiple frames). This work addresses the detection component by introducing a method based on semantic instance segmentation, i.e., assigning labels to all visible pixels such that they are unique among different instances. Modern tracking methods often built around Convolutional Neural Networks (CNNs) and additional, …

Water Pipeline Leakage Detection Based On Machine Learning And Wireless Sensor Networks, Yang Liu, Xuehui Ma, Yong Tie, Yinghui Zhang, Jing Gao

Department of Electrical and Computer Engineering: Faculty Publications

The detection of water pipeline leakage is important to ensure that water supply networks can operate safely and conserve water resources. To address the lack of intelligent and the low efficiency of conventional leakage detection methods, this paper designs a leakage detection method based on machine learning and wireless sensor networks (WSNs). The system employs wireless sensors installed on pipelines to collect data and utilizes the 4G network to perform remote data transmission. A leakage triggered networking method is proposed to reduce the wireless sensor network’s energy consumption and prolong the system life cycle effectively. To enhance the precision and …

Machine Current Sensor Fdi Strategy In Pmsms, Haibo Li, Yi Qian, Sohrab Asgarpoor, Hamid Sharif

Department of Electrical and Computer Engineering: Faculty Publications

This work proposes a machine current sensor fault detection and isolation (FDI) strategy in permanent magnet synchronous machines (PMSMs) resilient to multiple faults. The fault detection is performed by comparing the measured and estimated DC link currents. The fault isolation is achieved according to machine phase signal estimation and the corresponding residual examination. Single sensor fault, multiple sensor faults and non-sensor fault are covered by the proposed FDI method. The proposed sensor FDI method is not influenced by machine imbalance, feasible for FDI of both single and multiple machine current sensor faults, and capable of distinguishing between machine current sensor …

Bibliometric Survey Of Privacy Of Social Media Network Data Publishing, Rupali Gangarde Ass. Prof., Amit Sharma Dr., Ambika Pawar Dr.

Library Philosophy and Practice (e-journal)

We are witness to see exponential growth of the social media network since the year 2002. Leading social media networking sites used by people are Twitter, Snapchats, Facebook, Google, and Instagram, etc. The latest global digital report (Chaffey and Ellis-Chadwick 2019) states that there exist more than 800 million current online social media users, and the number is still exploding day by day. Users share their day to day activities such as their photos and locations etc. on social media platforms. This information gets consumed by third party users, like marketing companies, researchers, and government firms. Depending upon the purpose, …

The Art Of Selecting Phd Students: Combination Of Bibliometric And Ahp Approach, Preeti Mulay Dr., Rahul Raghvendra Joshi Prof., Sophia Gaikwad Dr.

Library Philosophy and Practice (e-journal)

For the PhD guide or the advisor selecting the accurate PhD scholar is the most elephantine task. It actually requires an art for the perfect selection; as the length, breadth, depth and volume of PhD work is spread across the years and this relationship between the scholar and the guide should start and flourish positively for the immense experience throughout the PhD process. Hence it was essential to understand bibliometric details including how many researchers have already published their contributions in the form of papers and patents, in the Scopus database. In addition to the bibliometric details, in this study, …

Personality Prediction Through Curriculam Vitae Analysis Involving Password Encryption And Prediction Analysis, Gagandeep Kaur, Shruti Maheshwari

Library Philosophy and Practice (e-journal)

A recruitment process requires an eligibility check, an aptitude evaluation and a psychometric analysis of prospective candidates. The work puts forward an application where the system allows employers to post new job offerings and registered candidates can apply. The application estimates applicant’s emotional aptitude through a psychometric analysis based on a test whereas the professional standard is verified via a technical aptitude test. OCEAN Model is used to assess emotional quotient and predict the personality traits. Machine learning techniques such as Logistic Regression are used for modelling the personality predictor. The details of the candidates are kept secure by using …

A Co-Optimal Coverage Path Planning Method For Aerial Scanning Of Complex Structures, Zhexiong Shang, Justin Bradley, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

The utilization of unmanned aerial vehicles (UAVs) in survey and inspection of civil infrastructure has been growing rapidly. However, computationally efficient solvers that find optimal flight paths while ensuring high-quality data acquisition of the complete 3D structure remains a difficult problem. Existing solvers typically prioritize efficient flight paths, or coverage, or reducing computational complexity of the algorithm – but these objectives are not co-optimized holistically. In this work we introduce a co-optimal coverage path planning (CCPP) method that simultaneously co-optimizes the UAV path, the quality of the captured images, and reducing computational complexity of the solver all while adhering to …

Global Research Trend On Cyber Security: A Scientometric Analysis, Somesh Rai, Kunwar Singh Dr, Akhilesh Kumar Varma

Library Philosophy and Practice (e-journal)

Scientometrics is a quantitative analysis of scholarly literature related to a particular subject or area (well defined by some limits, scope and coverage), which helps to understand different aspects about the scholarly literature’s growth in various dimensions of knowledge. Similarly, this study is a quantitative analysis of the Global research trends in cyber security. Some works related to scientometrics of ‘deception, counter-deception in cyberspace’ had been published in 2011, but we have focused on ‘cyber security’ as the topic of research. For analysis we have utilised the published data available in Scopus database, which is directly related to ‘cyber security’. …

The Stability Analysis For Wind Turbines With Doubly Fed Induction Generators, Baohua Dong

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The quickly increasing, widespread use of wind generation around the world reduces carbon emissions, decreases the effects of global warming, and lowers dependence on fossil fuels. However, the growing penetration of wind power requires more effort to maintain power systems stability.

This dissertation focuses on developing a novel algorithm which dynamically optimizes the proportional-integral (PI) controllers of a doubly fed induction generator (DFIG) driven by a wind turbine to increase the transient performance based on small signal stability analysis.

Firstly, the impact of wind generation is introduced. The stability of power systems with wind generation is described, including the different …

Hybrid Superhydrophilic–Superhydrophobic Micro/ Nanostructures Fabricated By Femtosecond Laserinduced Forward Transfer For Sub-Femtomolar Raman Detection, Xiaodan Ma, Lan Jiang, Xiaowei Li, Bohong Li, Ji Huang, Jiaxing Sun, Zhi Wang, Zhijie Xu, Liangti Qu, Yongfeng Lu, Tianhong Cui

Department of Electrical and Computer Engineering: Faculty Publications

Raman spectroscopy plays a crucial role in biochemical analysis. Recently, superhydrophobic surface-enhanced Raman scattering (SERS) substrates have enhanced detection limits by concentrating target molecules into small areas. However, due to the wet transition phenomenon, further reduction of the droplet contact area is prevented, and the detection limit is restricted. This paper proposes a simple method involving femtosecond laser-induced forward transfer for preparing a hybrid superhydrophilic–superhydrophobic SERS (HS-SERS) substrate by introducing a superhydrophilic pattern to promote the target molecules to concentrate on it for ultratrace detection. Furthermore, the HS-SERS substrate is heated to promote a smaller concentrated area. The water vapor …

Advanced Mathematical And Numerical Methods In Control And Optimization For Smart Grids, Zhan Shu, Michael Z.Q. Chen, Qing Hui

Department of Electrical and Computer Engineering: Faculty Publications

While renewable energy, as a part of smart-grid technologies, brings clean energy, it also brings a series of power quality problems. An increasing number of power electronic devices and new smart-grid technologies are used to ensure a safe, reliable, and high-quality operation of the power grid. However, the effectiveness of these control devices and technologies largely depends on the accuracy of the model, the advancement of control methods, and the numerical optimization of the parameters.

This special issue focuses on recent advances in modeling, numerical analysis, control, and optimization of smart grids with some special emphasis on the mathematical problems …

Bibliometric Survey On Incremental Clustering Algorithms, Archana Chaudhari, Rahul Raghvendra Joshi, Preeti Mulay, Ketan Kotecha, Parag Kulkarni

Library Philosophy and Practice (e-journal)

For clustering accuracy, on influx of data, the parameter-free incremental clustering research is essential. The sole purpose of this bibliometric analysis is to understand the reach and utility of incremental clustering algorithms. This paper shows incremental clustering for time series dataset was first explored in 2000 and continued thereafter till date. This Bibliometric analysis is done using Scopus, Google Scholar, Research Gate, and the tools like Gephi, Table2Net, and GPS Visualizer etc. The survey revealed that maximum publications of incremental clustering algorithms are from conference and journals, affiliated to Computer Science, Chinese lead publications followed by India then United States. …

Online Eeg Seizure Detection And Localization, Amirsalar Mansouri, Sanjay P. Singh, Khalid Sayood

Department of Electrical and Computer Engineering: Faculty Publications

Epilepsy is one of the three most prevalent neurological disorders. A significant proportion of patients suffering from epilepsy can be effectively treated if their seizures are detected in a timely manner. However, detection of most seizures requires the attention of trained neurologists-- a scarce resource. Therefore, there is a need for an automatic seizure detection capability. A tunable non-patient-specific, non-seizure-specific method is proposed to detect the presence and locality of a seizure using electroencephalography (EEG) signals. This multifaceted computational approach is based on a network model of the brain and a distance metric based on the spectral profiles of EEG …

Learnfca: A Fuzzy Fca And Probability Based Approach For Learning And Classification, Suraj Ketan Samal

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Formal concept analysis(FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. Over the past several years, many of its extensions have been proposed and applied in several domains including data mining, machine learning, knowledge management, semantic web, software development, chemistry ,biology, medicine, data analytics, biology and ontology engineering.

This thesis reviews the state-of-the-art of theory of Formal Concept Analysis(FCA) and its various extensions that have been developed and well-studied in the past several years. We discuss their historical roots, reproduce the original definitions and derivations with illustrative examples. Further, we provide …

Recent Trends, Current Research In Cyberpsychology: A Literature Review, Amarjit Kumar Singh, Pawan Kumar Singh

Library Philosophy and Practice (e-journal)

Cyberpsychology refers to the study of the mind and behavior in the context of interactions with technology. It is an emerging branch, which has focused on the psychological aspects connected to the increasing presence and usages of technology in modern lives. This paper traces recent advancement and trends of Cyberpsychology is an emerging domain of knowledge and goes on the give a literature review of the same. An analysis of the recent research and literature covering 300 most relevant research papers from the period of 2012 to 15, August 2019 was conducted to determine and shape the research pattern based …

Fqstat: A Parallel Architecture For Very High-Speed Assessment Of Sequencing Quality Metrics, Sree K. Chanumolu, Mustafa Albahrani, Hasan H. Otu

Department of Electrical and Computer Engineering: Faculty Publications

Background: High throughput DNA/RNA sequencing has revolutionized biological and clinical research. Sequencing is widely used, and generates very large amounts of data, mainly due to reduced cost and advanced technologies. Quickly assessing the quality of giga-to-tera base levels of sequencing data has become a routine but important task. Identification and elimination of low-quality sequence data is crucial for reliability of downstream analysis results. There is a need for a high-speed tool that uses optimized parallel programming for batch processing and simply gauges the quality of sequencing data from multiple datasets independent of any other processing steps.

Results: FQStat is a …

Exploring Eye Tracking Data On Source Code Via Dual Space Analysis, Li Zhang

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Eye tracking is a frequently used technique to collect data capturing users' strategies and behaviors in processing information. Understanding how programmers navigate through a large number of classes and methods to find bugs is important to educators and practitioners in software engineering. However, the eye tracking data collected on realistic codebases is massive compared to traditional eye tracking data on one static page. The same content may appear in different areas on the screen with users scrolling in an Integrated Development Environment (IDE). Hierarchically structured content and fluid method position compose the two major challenges for visualization. We present a …

Cooperative Learning For The Consensus Of Multi-Agent Systems, Qishuai Liu

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Due to a lot of attention for the multi-agent system in recent years, the consensus algorithm gained immense popularity for building fault-tolerant systems in system and control theory. Generally, the consensus algorithm drives the swarm of agents to work as a coherent group that can reach an agreement regarding a certain quantity of interest, which depends on the state of all agents themselves. The most common consensus algorithm is the average consensus, the final consensus value of which is equal to the average of the initial values. If we want the agents to find the best area of the particular …

Distributed Edge Bundling For Large Graphs, Yves Tuyishime

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Graphs or networks are widely used to depict the relationships between data entities in diverse scientific and engineering applications. A direct visualization (such as node-link diagram) of a graph with a large number of nodes and edges often incurs visual clutter. To address this issue, researchers have developed edge bundling algorithms that visually merge similar edges into curved bundles and can effectively reveal high-level edge patterns with reduced visual clutter. Although the existing edge bundling algorithms achieve appealing results, they are mostly designed for a single machine, and thereby the size of a graph they can handle is limited by …

Embedded System Design Of Robot Control Architectures For Unmanned Agricultural Ground Vehicles, Ryan Humphrey

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Engineering technology has matured to the extent where accompanying methods for unmanned field management is now becoming a technologically achievable and economically viable solution to agricultural tasks that have been traditionally performed by humans or human operated machines. Additionally, the rapidly increasing world population and the daunting burden it places on farmers in regards to the food production and crop yield demands, only makes such advancements in the agriculture industry all the more imperative. Consequently, the sector is beginning to observe a noticeable shift, where there exist a number of scalable infrastructural changes that are in the process of slowly …

Asymptotic Orthogonal Space Shift Keying In Massive Mimo Systems, Won Mee Jang

Department of Electrical and Computer Engineering: Faculty Publications

We investigate space shift keying, which is a simple form of spatial modulation. The bit error rate performance of line-of-sight (LOS) multiple-input and multiple-output (MIMO) was obtained in the literature with orthogonal subchannels for indoor millimeter-wave (mmWave) communications. It is essential to impose a rigid restriction on the distance between the transmitter and the receiver and antenna spacing to maintain orthogonal subchannels. However, in wireless communications, it is not viable to meet the strict distance requirements since user equipment is portable. We propose asymptotic orthogonal space shift keying with mobile stations. The asymptotic orthogonal space shift keying approaches orthogonal subchannels …

Absorptive/Transmissive Frequency Selective Surface With Wide Absorption Band, Qingxin Guo, Jianxun Su, Zengrui Li, Lamar Y. Yang, Jiming Song

Department of Electrical and Computer Engineering: Faculty Publications

An absorptive/transmissive frequency selective surface (ATFSS) with absorption bands at both sides of a passband is presented. Equivalent circuits of the ATFSS that consists of a lossy frequency selective surface (FSS) and a lossless FSS were modeled. To improve the rejection at an undesired band, a transmission zero was introduced and controlled by loading the lossless FSS with four-legged loaded slots. The parasitic passband was suppressed when the cross structure in the lossless FSS was loaded with resistance. In order to expand the absorption band, loaded dipoles were utilized for the lossy FSS design. An ATFSS with wide absorption bands …

Dimensional Analysis Of Robot Software Without Developer Annotations, John-Paul W. Ore

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Robot software risks the hazard of dimensional inconsistencies. These inconsistencies occur when a program incorrectly manipulates values representing real-world quantities. Incorrect manipulation has real-world consequences that range in severity from benign to catastrophic. Previous approaches detect dimensional inconsistencies in programs but require extra developer effort and technical complications. The extra effort involves developers creating type annotations for every variable representing a real-world quantity that has physical units, and the technical complications include toolchain burdens like specialized compilers or type libraries.

To overcome the limitations of previous approaches, this thesis presents novel methods to detect dimensional inconsistencies without developer annotations. We …