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2019

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Full-Text Articles in Engineering

Comparison And Design Optimization Of A Five-Phase Flux-Switching Pm Machine For In-Wheel Traction Applications, Hao Chen, Xiangdong Liu, Nabeel Demerdash, Ayman M. El-Refaie, Jing Zhao, Jiangbiao He Dec 2019

Comparison And Design Optimization Of A Five-Phase Flux-Switching Pm Machine For In-Wheel Traction Applications, Hao Chen, Xiangdong Liu, Nabeel Demerdash, Ayman M. El-Refaie, Jing Zhao, Jiangbiao He

Electrical and Computer Engineering Faculty Research and Publications

A comparative study of five-phase outer-rotor flux-switching permanent magnet (FSPM) machines with different topologies for in-wheel traction applications is presented in this paper. Those topologies include double-layer winding, single-layer winding, C-core, and E-core configurations. The electromagnetic performance in the low-speed region, the flux-weakening capability in the high-speed region, and the fault-tolerance capability are all investigated in detail. The results indicate that the E-core FSPM machine has performance advantages. Furthermore, two kinds of E-core FSPM machines with different stator and rotor pole combinations are optimized, respectively. In order to reduce the computational burden during the large-scale optimization process, a mathematical technique ...


Where We Are With Enterprise Architecture, Leila Halawi, Richard Mccarthy, James Farah Dec 2019

Where We Are With Enterprise Architecture, Leila Halawi, Richard Mccarthy, James Farah

Publications

Enterprise architecture has been continuously developing since the mid-1980s. Although there is now 35 years of research and use, there is still a lack consistent definitions and standards. This is apparent in the proliferation of so many different enterprise architecture frameworks. Despite the significant body of research, there is a need for standardization of terminology based upon a meta-analysis of the literature. Enterprise architecture programs require commitment throughout an organization to be effective and must be perceived to add value. This research offers an initial basis for researchers who need to expand and continue this research topic with an actual ...


Of Promoting Networking And Protecting Privacy: Effects Of Defaults And Regulatory Focus On Social Media Users’ Preference Settings, Hichang Cho, Sungjong Roh, Byungho Park Dec 2019

Of Promoting Networking And Protecting Privacy: Effects Of Defaults And Regulatory Focus On Social Media Users’ Preference Settings, Hichang Cho, Sungjong Roh, Byungho Park

Research Collection Lee Kong Chian School Of Business

Privacyresearch has debated whether privacy decision-making is determined by users'stable preferences (i.e., individual traits), privacy calculus (i.e.,cost-benefit analysis), or “responses on the spot” that vary across contexts.This study focuses on two factors—default setting as a contextual factor andregulatory focus as an individual difference factor—and examines the degree towhich these factors affect social media users' decisionmaking when usingprivacy preference settings in a fictitious social networking site. Theresults, based on two experimental studies (study 1, n = 414; study 2, n =213), show that default settings significantly affect users' privacypreferences, such that users choose the defaults ...


A Collaborative Visual Localization Scheme For A Low-Cost Heterogeneous Robotic Team With Non-Overlapping Perspectives, Benjamin Abruzzo, David Cappelleri, Philippos Mordohai Nov 2019

A Collaborative Visual Localization Scheme For A Low-Cost Heterogeneous Robotic Team With Non-Overlapping Perspectives, Benjamin Abruzzo, David Cappelleri, Philippos Mordohai

West Point Research Papers

This paper presents and evaluates a relative localization scheme for a heterogeneous team of low-cost mobile robots. An error-state, complementary Kalman Filter was developed to fuse analytically-derived uncertainty of stereoscopic pose measurements of an aerial robot, made by a ground robot, with the inertial/visual proprioceptive measurements of both robots. Results show that the sources of error, image quantization, asynchronous sensors, and a non-stationary bias, were sufficiently modeled to estimate the pose of the aerial robot. In both simulation and experiments, we demonstrate the proposed methodology with a heterogeneous robot team, consisting of a UAV and a UGV tasked with ...


Robot Simulation Analysis, Jacob Miller, Jeremy Evert Nov 2019

Robot Simulation Analysis, Jacob Miller, Jeremy Evert

Student Research

• Simulate virtual robot for test and analysis

• Analyze SLAM solutions using ROS

• Assemble a functional Turtlebot

• Emphasize projects related to current research trajectories for NASA, and general robotics applications


Trajectory Privacy Preservation And Lightweight Blockchain Techniques For Mobility-Centric Iot, Abdur Bin Shahid Nov 2019

Trajectory Privacy Preservation And Lightweight Blockchain Techniques For Mobility-Centric Iot, Abdur Bin Shahid

FIU Electronic Theses and Dissertations

Various research efforts have been undertaken to solve the problem of trajectory privacy preservation in the Internet of Things (IoT) of resource-constrained mobile devices. Most attempts at resolving the problem have focused on the centralized model of IoT, which either impose high delay or fail against a privacy-invading attack with long-term trajectory observation. These proposed solutions also fail to guarantee location privacy for trajectories with both geo-tagged and non-geo-tagged data, since they are designed for geo-tagged trajectories only. While a few blockchain-based techniques have been suggested for preserving trajectory privacy in decentralized model of IoT, they require large storage capacity ...


Malware Analysis For Evaluating The Integrity Of Mission Critical Devices, Robert Heras Nov 2019

Malware Analysis For Evaluating The Integrity Of Mission Critical Devices, Robert Heras

FIU Electronic Theses and Dissertations

The rapid evolution of technology in our society has brought great advantages, but at the same time it has increased cybersecurity threats. At the forefront of these threats is the proliferation of malware from traditional computing platforms to the rapidly expanding Internet-of-things. Our research focuses on the development of a malware detection system that strives for early detection as a means of mitigating the effects of the malware's execution.

The proposed scheme consists of a dual-stage detector providing malware detection for compromised devices in order to mitigate the devices malicious behavior. Furthermore, the framework analyzes task structure features as ...


Security Of The Internet Of Things: Vulnerabilities, Attacks And Countermeasures, Ismail Butun, Houbing Song, Patrik Osterberg Nov 2019

Security Of The Internet Of Things: Vulnerabilities, Attacks And Countermeasures, Ismail Butun, Houbing Song, Patrik Osterberg

Publications

Wireless Sensor Networks (WSNs) constitute one of the most promising third-millennium technologies and have wide range of applications in our surrounding environment. The reason behind the vast adoption of WSNs in various applications is that they have tremendously appealing features, e.g., low production cost, low installation cost, unattended network operation, autonomous and longtime operation. WSNs have started to merge with the Internet of Things (IoT) through the introduction of Internet access capability in sensor nodes and sensing ability in Internet-connected devices. Thereby, the IoT is providing access to huge amount of data, collected by the WSNs, over the Internet ...


Water Pipeline Leakage Detection Based On Machine Learning And Wireless Sensor Networks, Yang Liu, Xuehui Ma, Yong Tie, Yinghui Zhang, Jing Gao Nov 2019

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

Faculty Publications from the Department of Electrical and Computer Engineering

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 ...


Algorithms And Circuits For Analog-Digital Hybrid Multibeam Arrays, Paboda Viduneth A. Beruwawela Pathiranage Nov 2019

Algorithms And Circuits For Analog-Digital Hybrid Multibeam Arrays, Paboda Viduneth A. Beruwawela Pathiranage

FIU Electronic Theses and Dissertations

Fifth generation (5G) and beyond wireless communication systems will rely heavily on larger antenna arrays combined with beamforming to mitigate the high free-space path-loss that prevails in millimeter-wave (mmW) and above frequencies. Sharp beams that can support wide bandwidths are desired both at the transmitter and the receiver to leverage the glut of bandwidth available at these frequency bands. Further, multiple simultaneous sharp beams are imperative for such systems to exploit mmW/sub-THz wireless channels using multiple reflected paths simultaneously. Therefore, multibeam antenna arrays that can support wider bandwidths are a key enabler for 5G and beyond systems.

In general ...


Bibliometric Survey Of Privacy Of Social Media Network Data Publishing, Rupali Gangarde Ass. Prof., Amit Sharma Dr., Ambika Pawar Dr. Nov 2019

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. Nov 2019

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 ...


Aspect And Opinion Aware Abstractive Review Summarization With Reinforced Hard Typed Decoder, Yufei Tian, Jianfei Yu, Jing Jiang Nov 2019

Aspect And Opinion Aware Abstractive Review Summarization With Reinforced Hard Typed Decoder, Yufei Tian, Jianfei Yu, Jing Jiang

Research Collection School Of Computing and Information Systems

In this paper, we study abstractive review summarization. Observing that review summaries often consist of aspect words, opinion words and context words, we propose a two-stage reinforcement learning approach, which first predicts the output word type from the three types, and then leverages the predicted word type to generate the final word distribution. Experimental results on two Amazon product review datasets demonstrate that our method can consistently outperform several strong baseline approaches based on ROUGE scores.


Personality Prediction Through Curriculam Vitae Analysis Involving Password Encryption And Prediction Analysis, Gagandeep Kaur, Shruti Maheshwari Nov 2019

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 ...


Automated Dynamic Detection Of Self-Hiding Behaviors, Luke Baird Nov 2019

Automated Dynamic Detection Of Self-Hiding Behaviors, Luke Baird

Student Works

Certain Android applications, such as but not limited to malware, conceal their presence from the user, exhibiting a self-hiding behavior. Consequently, these apps put the user’s security and privacy at risk by performing tasks without the user’s awareness. Static analysis has been used to analyze apps for self-hiding behavior, but this approach is prone to false positives and suffers from code obfuscation. This research proposes a set of three tools utilizing a dynamic analysis method of detecting self-hiding behavior of an app in the home, installed, and running application lists on an Android emulator. Our approach proves both ...


Cascaded Neural Networks For Identification And Posture-Based Threat Assessment Of Armed People, Benjamin Abruzzo, Kevin Carey, Christopher Lowrance, Eric Sturzinger, Ross Arnold, Christopher Korpela Nov 2019

Cascaded Neural Networks For Identification And Posture-Based Threat Assessment Of Armed People, Benjamin Abruzzo, Kevin Carey, Christopher Lowrance, Eric Sturzinger, Ross Arnold, Christopher Korpela

West Point Research Papers

This paper presents a near real-time, multi-stage classifier which identifies people and handguns in images, and then further assesses the threat-level that a person poses based on their body posture. The first stage consists of a convolutional neural network (CNN) that determines whether a person and a handgun are present in an image. If so, a second stage CNN is then used to estimate the pose of the person detected to have a handgun. Lastly, a feed-forward neural network (NN) makes the final threat assessment based on the joint positions of the person’s skeletal pose estimate from the previous ...


Computing Without Computing: Dna Version, Vladik Kreinovich, Julio C. Urenda Nov 2019

Computing Without Computing: Dna Version, Vladik Kreinovich, Julio C. Urenda

Departmental Technical Reports (CS)

The traditional DNA computing schemes are based on using or simulating DNA-related activity. This is similar to how quantum computers use quantum activities to perform computations. Interestingly, in quantum computing, there is another phenomenon known as computing without computing, when, somewhat surprisingly, the result of the computation appears without invoking the actual quantum processes. In this chapter, we show that similar phenomenon is possible for DNA computing: in addition to the more traditional way of using or simulating DNA activity, we can also use DNA inactivity to solve complex problems. We also show that while DNA computing without computing is ...


Why Deep Learning Is More Efficient Than Support Vector Machines, And How It Is Related To Sparsity Techniques In Signal Processing, Laxman Bokati, Olga Kosheleva, Vladik Kreinovich Nov 2019

Why Deep Learning Is More Efficient Than Support Vector Machines, And How It Is Related To Sparsity Techniques In Signal Processing, Laxman Bokati, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Several decades ago, traditional neural networks were the most efficient machine learning technique. Then it turned out that, in general, a different technique called support vector machines is more efficient. Reasonably recently, a new technique called deep learning has been shown to be the most efficient one. These are empirical observations, but how we explain them -- thus making the corresponding conclusions more reliable? In this paper, we provide a possible theoretical explanation for the above-described empirical comparisons. This explanation enables us to explain yet another empirical fact -- that sparsity techniques turned out to be very efficient in signal processing.


The Stability Analysis For Wind Turbines With Doubly Fed Induction Generators, Baohua Dong Nov 2019

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

Theses, Dissertations, and Student Research from Electrical & Computer Engineering

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 ...


Deep Learning (Partly) Demystified, Vladik Kreinovich, Olga Kosheleva Nov 2019

Deep Learning (Partly) Demystified, Vladik Kreinovich, Olga Kosheleva

Departmental Technical Reports (CS)

Successes of deep learning are partly due to appropriate selection of activation function, pooling functions, etc. Most of these choices have been made based on empirical comparison and heuristic ideas. In this paper, we show that many of these choices -- and the surprising success of deep learning in the first place -- can be explained by reasonably simple and natural mathematics.


Stressmon: Scalable Detection Of Perceived Stress And Depression Using Passive Sensing Of Changes In Work Routines And Group Interactions, Nur Camellia Binte Zakaria, Rajesh Balan, Youngki Lee Nov 2019

Stressmon: Scalable Detection Of Perceived Stress And Depression Using Passive Sensing Of Changes In Work Routines And Group Interactions, Nur Camellia Binte Zakaria, Rajesh Balan, Youngki Lee

Research Collection School Of Computing and Information Systems

Stress and depression are a common affliction in all walks of life. When left unmanaged, stress can inhibit productivity or cause depression. Depression can occur independently of stress. There has been a sharp rise in mobile health initiatives to monitor stress and depression. However, these initiatives usually require users to install dedicated apps or multiple sensors, making such solutions hard to scale. Moreover, they emphasise sensing individual factors and overlook social interactions, which plays a significant role in influencing stress and depression while being a part of a social system. We present StressMon, a stress and depression detection system that ...


Ridesourcing Systems: A Framework And Review, Hai Wang, Hai Yang Nov 2019

Ridesourcing Systems: A Framework And Review, Hai Wang, Hai Yang

Research Collection School Of Computing and Information Systems

With the rapid development and popularization of mobile and wireless communication technologies, ridesourcing companies have been able to leverage internet-based platforms to operate e-hailing services in many cities around the world. These companies connect passengers and drivers in real time and are disruptively changing the transportation indus- try. As pioneers in a general sharing economy context, ridesourcing shared transportation platforms consist of a typical two-sided market. On the demand side, passengers are sensi- tive to the price and quality of the service. On the supply side, drivers, as freelancers, make working decisions flexibly based on their income from the platform ...


Secure Virtual Machine Placement In Cloud Data Centers, Amit Agarwal, Nguyen Binh Duong Ta Nov 2019

Secure Virtual Machine Placement In Cloud Data Centers, Amit Agarwal, Nguyen Binh Duong Ta

Research Collection School Of Computing and Information Systems

Due to an increasing number of avenues for conducting cross-VM side-channel attacks, the security of multi-tenant public IaaS cloud environments is a growing concern. These attacks allow an adversary to steal private information from a target user whose VM instance is co-located with that of the adversary. In this paper, we focus on secure VM placement algorithms which a cloud provider can use for the automatic enforcement of security against such co-location based attacks. To do so, we first establish a metric for evaluating and quantifying co-location security of multi-tenant public IaaS clouds, and then propose a novel VM placement ...


Global Research Trend On Cyber Security: A Scientometric Analysis, Somesh Rai, Kunwar Singh Dr, Akhilesh Kumar Varma Nov 2019

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 ...


Automated Dynamic Detection Of Self-Hiding Behavior In Android Apps, Luke Baird, Seth Rodgers Oct 2019

Automated Dynamic Detection Of Self-Hiding Behavior In Android Apps, Luke Baird, Seth Rodgers

Student Works

Android applications that conceal themselves from a user, defined as exhibiting a “self-hiding behavior,” pose a threat to the user’s privacy, as these applications can live on a device undetected by the user. Malicious applications can do this to execute without being found by the user. Three lists are analyzed in particular—the home, running, and installed lists—as they are directly related to the typical Android app life cycle. Additionally, self-hiding behavior in the device admin list is analyzed due to the potential for catastrophic actions to be taken by device admin malware. This research proposes four dynamic ...


A Privacy Framework For Decentralized Applications Using Blockchains And Zero Knowledge Proofs, David Gabay Oct 2019

A Privacy Framework For Decentralized Applications Using Blockchains And Zero Knowledge Proofs, David Gabay

FIU Electronic Theses and Dissertations

With the increasing interest in connected vehicles along with electrification opportunities, there is an ongoing effort to automate the charging process of electric vehicles (EVs) through their capabilities to communicate with the infrastructure and each other. However, charging EVs takes time and thus in-advance scheduling is needed. As this process is done frequently due to limited mileage of EVs, it may expose the locations and charging pattern of the EV to the service providers, raising privacy concerns for their users. Nevertheless, the EV still needs to be authenticated to charging providers, which means some information will need to be provided ...


Work-In-Progress: Iot Device Signature Validation, Jeffrey Hemmes Oct 2019

Work-In-Progress: Iot Device Signature Validation, Jeffrey Hemmes

Regis University Faculty Publications

Device fingerprinting is an area of security that has received renewed attention in recent years, with a number of classification methods proposed that rely on characteristics unique to a particular vendor or device type. Current works are limited to determining device type for purposes of access control and MAC address spoof prevention. This work synthesizes multiple sources of information to verify device capabilities in a device profile, which can be used in a number of applications not limited to authentication and authorization. The approach proposed in this paper relies on existing protocols and methods proposed in the literature, using a ...


High-Sensitivity Magnetic Sensors Based On Gmi Microwire-Saw Idt Design, Akila Khatun, Florian Bender, Fabien Josse Phd, Arnold Kweku Mensah-Brown, R. Dyche Anderson Oct 2019

High-Sensitivity Magnetic Sensors Based On Gmi Microwire-Saw Idt Design, Akila Khatun, Florian Bender, Fabien Josse Phd, Arnold Kweku Mensah-Brown, R. Dyche Anderson

Electrical and Computer Engineering Faculty Research and Publications

This work presents a design approach for a highly sensitive, miniaturized magnetic sensor. The design makes use of GMI microwires and a multi-electrode SAW IDT. The use of SAW IDTs allows for the magnetic effect of the GMI microwire to be measured through the transduction process. This approach permits simultaneous measurement at different frequencies of operation, enabling highly sensitive measurement over a wide range of magnetic fields. This technique may find application in magnetic sensing for non-invasive battery SOC measurement.


Vibration Alert Bracelet For Notification Of The Visually And Hearing Impaired, Kelsey Conley, Alex Foyer, Patrick Hara, Tom Janik, Jason Reichard, Jon D'Souza, Chandana Tamma, Cristinel Ababei Oct 2019

Vibration Alert Bracelet For Notification Of The Visually And Hearing Impaired, Kelsey Conley, Alex Foyer, Patrick Hara, Tom Janik, Jason Reichard, Jon D'Souza, Chandana Tamma, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

This paper presents the prototype of an electronic vibration bracelet designed to help the visually and hearing impaired to receive and send emergency alerts. The bracelet has two basic functions. The first function is to receive a wireless signal and respond with a vibration to alert the user. The second function is implemented by pushing one button of the bracelet to send an emergency signal. We report testing on a prototype system formed by a mobile application and two bracelets. The bracelets and the application form a complete system intended to be used in retirement apartment communities. However, the system ...


Enginews, Fall 2019, School Of Computer Science & Engineering Oct 2019

Enginews, Fall 2019, School Of Computer Science & Engineering

Department News, Magazines and Reports

The IDEA Lab at SHU offers a variety of state of the art equipment available for students to use.