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Articles 7351 - 7380 of 25611

Full-Text Articles in Computer Engineering

Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt Nov 2020

Extending The Functional Subnetwork Approach To A Generalized Linear Integrate-And-Fire Neuron Model, Nicholas Szczecinski, Roger Quinn, Alexander J. Hunt

Mechanical and Materials Engineering Faculty Publications and Presentations

Engineering neural networks to perform specific tasks often represents a monumental challenge in determining network architecture and parameter values. In this work, we extend our previously-developed method for tuning networks of non-spiking neurons, the “Functional subnetwork approach” (FSA), to the tuning of networks composed of spiking neurons. This extension enables the direct assembly and tuning of networks of spiking neurons and synapses based on the network’s intended function, without the use of global optimization ormachine learning. To extend the FSA, we show that the dynamics of a generalized linear integrate and fire (GLIF) neuronmodel have fundamental similarities to those of …

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Wetting-Driven Formation Of Present-Day Loess Structure, Yanrong Li, Weiwei Zhang, Shengdi He, Adnan Aydin Nov 2020

Wetting-Driven Formation Of Present-Day Loess Structure, Yanrong Li, Weiwei Zhang, Shengdi He, Adnan Aydin

Faculty and Student Publications

© 2020 The Authors Present-day loess, especially Malan loess formed in Later Quaternary, has a characteristic structure composed of vertically aligned strong units and weak segments. Hypotheses describing how this structure forms inside original loess deposits commonly relate it to wetting-drying process. We tested this causal relationship by conducting unique experiments on synthetic samples of initial loess deposits fabricated by free-fall of loess particles. These samples were subjected to a wetting-drying cycle, and their structural evolutions were documented by close-up photography and CT scanning. Analysis of these records revealed three key stages of structural evolution: initiation (evenly distributed cracks appear …

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2020 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department Nov 2020

2020 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the fall of 2020.

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Covid-19 In Spain And India: Comparing Policy Implications By Analyzing Epidemiological And Social Media Data, Parth Asawa, Manas Gaur, Kaushik Roy, Amit P. Sheth Nov 2020

Covid-19 In Spain And India: Comparing Policy Implications By Analyzing Epidemiological And Social Media Data, Parth Asawa, Manas Gaur, Kaushik Roy, Amit P. Sheth

Publications

The COVID-19 pandemic has forced public health experts to develop contingent policies to stem the spread of infection, including measures such as partial/complete lockdowns. The effectiveness of these policies has varied with geography, population distribution, and effectiveness in implementation. Consequently, some nations (e.g., Taiwan, Haiti) have been more successful than others (e.g., United States) in curbing the outbreak. A data-driven investigation into effective public health policies of a country would allow public health experts in other nations to decide future courses of action to control the outbreaks of disease and epidemics. We chose Spain and India to present our analysis …

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An Accurate Vegetation And Non-Vegetation Differentiation Approach Based On Land Cover Classification, Chiman Kwan, David Gribben, Bulent Ayhan, Jiang Li, Sergio Bernabe, Antonio Plaza Nov 2020

An Accurate Vegetation And Non-Vegetation Differentiation Approach Based On Land Cover Classification, Chiman Kwan, David Gribben, Bulent Ayhan, Jiang Li, Sergio Bernabe, Antonio Plaza

Electrical & Computer Engineering Faculty Publications

Accurate vegetation detection is important for many applications, such as crop yield estimation, landcover land use monitoring, urban growth monitoring, drought monitoring, etc. Popular conventional approaches to vegetation detection incorporate the normalized difference vegetation index (NDVI), which uses the red and near infrared (NIR) bands, and enhanced vegetation index (EVI), which uses red, NIR, and the blue bands. Although NDVI and EVI are efficient, their accuracies still have room for further improvement. In this paper, we propose a new approach to vegetation detection based on land cover classification. That is, we first perform an accurate classification of 15 or more …

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Multi-User Verifiable Searchable Symmetric Encryption For Cloud Storage, Xueqiao Liu, Guomin Yang, Guomin Yang Nov 2020

Multi-User Verifiable Searchable Symmetric Encryption For Cloud Storage, Xueqiao Liu, Guomin Yang, Guomin Yang

Research Collection School Of Computing and Information Systems

In a cloud data storage system, symmetric key encryption is usually used to encrypt files due to its high efficiency. In order allow the untrusted/semi-trusted cloud storage server to perform searching over encrypted data while maintaining data confidentiality, searchable symmetric encryption (SSE) has been proposed. In a typical SSE scheme, a users stores encrypted files on a cloud storage server and later can retrieve the encrypted files containing specific keywords. The basic security requirement of SSE is that the cloud server learns no information about the files or the keywords during the searching process. Some SSE schemes also offer additional …

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Enterprise Architecture Transformation Process From A Federal Government Perspective, Tonia Canada, Leila Halawi Nov 2020

Enterprise Architecture Transformation Process From A Federal Government Perspective, Tonia Canada, Leila Halawi

Publications

The need for information technology organizations to transform enterprise architecture is driven by federal government mandates and information technology budget constraints. This qualitative case study aimed to identify factors that hinder federal government agencies from driving enterprise architecture transformation processes from a compliancy to a flexible process. Common themes in interviewee responses were identified, coded, and summarized. Critical recommendations for future best practices, including further research, were also presented.

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Edge Computing For Deep Learning-Based Distributed Real-Time Object Detection On Iot Constrained Platforms At Low Frame Rate, Lakshmikavya Kalyanam Oct 2020

Edge Computing For Deep Learning-Based Distributed Real-Time Object Detection On Iot Constrained Platforms At Low Frame Rate, Lakshmikavya Kalyanam

USF Tampa Graduate Theses and Dissertations

In the era of IoT (Internet of Things) and edge computing, there is a rising need for real-time applications in the domain of computer vision. The increase in hardware computing capabilities gave rise to applications of neural networks in various fields. Implementing IoT with neural networks in domains such as image and video recognition has shown promising performance when deployed in complex environments. There is an emerging demand for applications that require data computation in real-time with low latency. In an effort to address these issues, while keeping in mind the computing capabilities of IoT devices, we seek to develop …

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Roboat - Rescue Operations Bot Operating In All Terrains, Akshay Gulhane Oct 2020

Roboat - Rescue Operations Bot Operating In All Terrains, Akshay Gulhane

USF Tampa Graduate Theses and Dissertations

Natural calamities are on a rise with each passing year. Disasters like floods and fire take many lives all around the world, especially in remote areas or less developed countries. One such incident was the Kerala Floods in India where rescue services had difficulty reaching to all the people on time since a huge landmass (more than 9 districts) was flooded and hence villagers or other people risked their lives to save others in danger without proper safety equipment. Amazon Rainforest Fires was another example for a major destruction of an ecosystem. The main reason for lack of facilities in …

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Control Of A Human Arm Robotic Unit Using Augmented Reality And Optimized Kinematics, Carlo Canezo Oct 2020

Control Of A Human Arm Robotic Unit Using Augmented Reality And Optimized Kinematics, Carlo Canezo

USF Tampa Graduate Theses and Dissertations

There are more than 350000 amputees in the US who suffer loss of functionality in their daily living activities, and roughly 100000 of them are upper arm amputees. Many of these amputees use prostheses to compensate part of their lost arm function, including power prostheses. Research on 6-7 degree of freedom powered prostheses is still relatively new, and most commercially available powered prostheses are typically limited to 1 to 3 degrees of freedom. Due to the myriad of possible options for various powered protheses from different manufacturers, each configuration is governed by a distinct control scheme typically specific to the …

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Epics Urban Farming: Bringing Sustainable Fresh Food To Gary, Indiana, Elijah Klein Oct 2020

Epics Urban Farming: Bringing Sustainable Fresh Food To Gary, Indiana, Elijah Klein

Purdue Journal of Service-Learning and International Engagement

EPICS Urban Farming is a team of seventeen undergraduate students designing and implementing an aquaponics and food distribution system in Gary, Indiana. With the area being a food desert, most people turn to corner stores for food that is easily accessible and cheap but unhealthy. From this diet, there are quite a few widespread health concerns that the population of Gary, Indiana, faces daily. For example, obesity, diabetes, and heart conditions are some of the most common diseases that plague the community. Urban Farming is working to aid in combating these issues with the partnership of Pastor Marty Henderson, who …

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Resource Discovery In A Changing Content World, Allen Jones, Cynthia R. Schwarz, Hannah Mckelvey, Rachelle Mclain, Christine Stohn Oct 2020

Resource Discovery In A Changing Content World, Allen Jones, Cynthia R. Schwarz, Hannah Mckelvey, Rachelle Mclain, Christine Stohn

Charleston Library Conference

Discovery services have evolved to include not just books and articles, but databases, website content, research guides, digital and audiovisual collections, and unique local collections that are all important for their users to be able to find. Search and ranking remain at the core of discovery, but advanced tools such as recommendation, virtual browse, ‘look inside‘, and the use of artificial intelligence are also becoming more prevalent. This group of panelists discussed how content in their discovery systems can change based on the context of the user, using as examples Primo and Blacklight, and how content is populated, discovered and …

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Hateproofing Your Message: Response And Prevention Strategies For "Hatejacks", Bond Benton, Daniela Peterka-Benton Oct 2020

Hateproofing Your Message: Response And Prevention Strategies For "Hatejacks", Bond Benton, Daniela Peterka-Benton

Department of Justice Studies Faculty Scholarship and Creative Works

No abstract provided.

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Research Experience For Undergraduates During Covid-19, Mustafa Akbas Oct 2020

Research Experience For Undergraduates During Covid-19, Mustafa Akbas

Florida Statewide Symposium: Best Practices in Undergraduate Research

This presentation provides the student team interaction and mentorship experience at Embry-Riddle Aeronautical University’s “National Science Foundation (NSF) Research Experiences for Undergraduates (REU) Site: Cybersecurity Research of Unmanned Aerial Vehicles” from the summer semester of 2020. The Site had been planned for a face-of-face research experience under several mentors for an eight-week period. However, due to Covid-19, the teams had to meet, discuss, present and work online, which was both a challenge and an opportunity. Both students and mentors had lessons from this online experience that they will remember and use in the upcoming years. In this presentation, we present …

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Optimizing The Performance Of Multi-Threaded Linear Algebra Libraries Based On Task Granularity, Shahrzad Shirzad Oct 2020

Optimizing The Performance Of Multi-Threaded Linear Algebra Libraries Based On Task Granularity, Shahrzad Shirzad

LSU Doctoral Dissertations

Linear algebra libraries play a very important role in many HPC applications. As larger datasets are created everyday, it also becomes crucial for the multi-threaded linear algebra libraries to utilize the compute resources properly. Moving toward exascale computing, the current programming models would not be able to fully take advantage of the advances in memory hierarchies, computer architectures, and networks. Asynchronous Many-Task(AMT) Runtime systems would be the solution to help the developers to manage the available parallelism. In this Dissertation we propose an adaptive solution to improve the performance of a linear algebra library based on a set of compile-time …

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On Correctness, Precision, And Performance In Quantitative Verification: Qcomp 2020 Competition Report, Carlos E. Budde, Arnd Hartmanns, Michaela Klauck, Jan Křetínský, David Parker, Tim Quatmann, Andrea Turrini, Zhen Zhang Oct 2020

On Correctness, Precision, And Performance In Quantitative Verification: Qcomp 2020 Competition Report, Carlos E. Budde, Arnd Hartmanns, Michaela Klauck, Jan Křetínský, David Parker, Tim Quatmann, Andrea Turrini, Zhen Zhang

Electrical and Computer Engineering Faculty Publications

Quantitative verification tools compute probabilities, expected rewards, or steady-state values for formal models of stochastic and timed systems. Exact results often cannot be obtained efficiently, so most tools use floating-point arithmetic in iterative algorithms that approximate the quantity of interest. Correctness is thus defined by the desired precision and determines performance. In this paper, we report on the experimental evaluation of these trade-offs performed in QComp 2020: the second friendly competition of tools for the analysis of quantitative formal models. We survey the precision guarantees - ranging from exact rational results to statistical confidence statements - offered by the nine …

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Investigating Factors Predicting Effective Learning In A Cs Professional Development Program For K–12 Teachers, Patrick Morrow Oct 2020

Investigating Factors Predicting Effective Learning In A Cs Professional Development Program For K–12 Teachers, Patrick Morrow

School of Computing: Dissertations, Theses, and Student Research

The demand for K-12 Computer Science (CS) education is growing and there is not an adequate number of educators to match the demand. Comprehensive research was carried out to investigate and understand the influence of a summer two-week professional development (PD) program on teachers’ CS content and pedagogical knowledge, their confidence in such knowledge, their interest in and perceived value of CS, and the factors influencing such impacts. Two courses designed to train K-12 teachers to teach CS, focusing on both concepts and pedagogy skills were taught over two separate summers to two separate cohorts of teachers. Statistical and SWOT …

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Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu Oct 2020

Finite-Time State Estimation For An Inverted Pendulum Under Input-Multiplicative Uncertainty, Sergey V. Drakunov, William Mackunis, Anu Kossery Jayaprakash, Krishna Bhavithavya Kidambi, Mahmut Reyhanoglu

Publications

A sliding mode observer is presented, which is rigorously proven to achieve finite-time state estimation of a dual-parallel underactuated (i.e., single-input multi-output) cart inverted pendulum system in the presence of parametric uncertainty. A salient feature of the proposed sliding mode observer design is that a rigorous analysis is provided, which proves finite-time estimation of the complete system state in the presence of input-multiplicative parametric uncertainty. The performance of the proposed observer design is demonstrated through numerical case studies using both sliding mode control (SMC)- and linear quadratic regulator (LQR)-based closed-loop control systems. The main contribution presented here is the rigorous …

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Challenges To Adopting Hybrid Methodology: Addressing Organizational Culture And Change Control Problems In Enterprise It Infrastructure Projects, Harishankar Krishnakumar Oct 2020

Challenges To Adopting Hybrid Methodology: Addressing Organizational Culture And Change Control Problems In Enterprise It Infrastructure Projects, Harishankar Krishnakumar

Dissertations and Theses

IT infrastructure projects have long been an overlooked field superseded by the more popular software development silos and cross-functional project teams when it comes to enterprise Agile transformations. This paper presents a systematic literature review by leveraging a qualitative research methodology based on empirical evidence provided in contemporary scholarly research articles to explore how certain variables such as organizational culture- including team structure, leadership hierarchy, geolocation, etc. along with an organization’s change management processes affect the adoption of a Hybrid/Agile project management methodology, focusing on reported challenges and critical success factors that define such large-scale enterprise transformations. The salient features …

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Content Modelling For Unbiased Information Analysis, Milind Gayakwad, Suhas Patil Dr Oct 2020

Content Modelling For Unbiased Information Analysis, Milind Gayakwad, Suhas Patil Dr

Library Philosophy and Practice (e-journal)

Content is the form through which the information is conveyed as per the requirement of user. A volume of content is huge and expected to grow exponentially hence classification of useful data and not useful data is a very tedious task. Interface between content and user is Search engine. Therefore, the contents are designed considering search engine's perspective. Content designed by the organization, utilizes user’s data for promoting their products and services. This is done mostly using inorganic ways utilized to influence the quality measures of a content, this may mislead the information. There is no correct mechanism available to …

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3d Reconstruction Of Spine Image From 2d Mri Slices Along One Axis, Somoballi Ghoshal, Sourav Banu, Amlan Chakrabarti, Susmita Sur-Kolay, Alok Pandit Oct 2020

3d Reconstruction Of Spine Image From 2d Mri Slices Along One Axis, Somoballi Ghoshal, Sourav Banu, Amlan Chakrabarti, Susmita Sur-Kolay, Alok Pandit

Journal Articles

Magnetic resonance imaging (MRI) is a very effective method for identifying any abnormality in the structure and physiology of the spine. However, MRI is time consuming as well as costly. In this work, the authors propose an algorithm which can reduce the time of MRI and thus the cost, with minimal compromise on accuracy. They reconstruct a three-dimensional (3D) image of the spine from a sequence of 2D MRI slices along any one axis with reasonable slice gap. In order to preserve the image at the edges properly, they regenerate the 3D image by using a combination of bicubic and …

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Bibliometric Survey On Biometric Iris Liveness Detection, Smita Khade, Dr.Swati Ahirrao, Dr. Sudeep Thepade Oct 2020

Bibliometric Survey On Biometric Iris Liveness Detection, Smita Khade, Dr.Swati Ahirrao, Dr. Sudeep Thepade

Library Philosophy and Practice (e-journal)

Authentication is an essential step for giving access to resources to authorized individuals and prevent leakage of confidential information. The traditional authentication systems like a pin, card, a password could not differentiate among the authorized users and fakers who have an illegal access to the system. Traditional authentication technique never alerts about the unwanted access to the system. The device that allows the automatic identification of an individual is known as a biometric system. It is not required to remember a password, card, and pin code in the Bio-metric system. Numerous biometric characteristics like the fingerprint, iris, palm print, face …

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Flight Simulator Modeling Using Recurrent Neural Networks, Nickolas Sabatini, Andreas Natsis Oct 2020

Flight Simulator Modeling Using Recurrent Neural Networks, Nickolas Sabatini, Andreas Natsis

Maseeh Summer Undergraduate Research Experience

Recurrent neural networks (RNNs) are a form of machine learning used to predict future values. This project uses RNNs tor predict future values for a flight simulator. Coded in Python using the Keras library, the model demonstrates training loss and validation loss, referring to the error when training the model.

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Reinforcement Learning Based Maximum Power Point Tracking Control Of Partially Shaded Photovoltaic System, Kuan-Yu Chou, Chia-Shiou Yang, Yon-Ping Chen Oct 2020

Reinforcement Learning Based Maximum Power Point Tracking Control Of Partially Shaded Photovoltaic System, Kuan-Yu Chou, Chia-Shiou Yang, Yon-Ping Chen

Journal of Marine Science and Technology–Taiwan

Under the sun insolation in the daytime, the Maximum Power Point Tracking (MPPT) technique is usually used to achieve the maximum power in the photovoltaic (PV) system and often implemented by the Perturbation and Observation (P&O) method. However, due to the use of fixed step size, the P&O method will generate undesired oscillation around the maximum power point (MPP) and thus reduce the tracking efficiency. Besides, the output power of PV modules highly depends on the environment factors such as irradiance and temperature, especially for a PV array, which is formed by PV modules connected in series and parallel. The …

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A Survey Of Advanced Control Methods For Permanent Magnet Stepper Motors, Yong Woo Jeong, Youngwoo Lee, Chung Choo Chung Oct 2020

A Survey Of Advanced Control Methods For Permanent Magnet Stepper Motors, Yong Woo Jeong, Youngwoo Lee, Chung Choo Chung

Journal of Marine Science and Technology–Taiwan

Permanent Magnet (PM) stepper motors have been widely used in industry due to their low material costs and robustness against the environment. Furthermore, it is relatively easy to implement a control system compared to other type motors. It has been recently reported that advanced control methods show improved tracking performance over the conventional microstepping control. In this paper, we make a survey of advanced control methods for PM stepper motors. First, we introduce basic principles of open-loop control of PM stepper motors, including microstepping. Then we explain various advanced feedback control techniques based on Lyapunov stability. Second, we briefly summarize …

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Agile Rov For Underwater Surveillance, Ikuo Yamamoto, Akihiro Morinaga, Murray Lawn Oct 2020

Agile Rov For Underwater Surveillance, Ikuo Yamamoto, Akihiro Morinaga, Murray Lawn

Journal of Marine Science and Technology–Taiwan

Surveillance of submerged plant is becoming increasingly critical as ocean based resources become more and more important. A wide varieties of new roles have recently emerged ranging from aquaculture to offshore power generation systems, in addition to the monitoring of the aging submerged sections of bridges, piers and dams etc. Consecutive generations of ROVs have been developed at Nagasaki University to meet the changing needs for surveillance of submerged plant. This paper outlines briefly the ROVs developed to date and the move to increase ROV autonomy using AI (artificial intelligence).

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Gain-Scheduled Control Of Discretized Ship Autopilot System Subject To Poleassignment And Passivity Constraints, Wen-Jer Chang, Cheung-Chieh Ku, Chih-Yu Yen, Guan-Wei Chen Oct 2020

Gain-Scheduled Control Of Discretized Ship Autopilot System Subject To Poleassignment And Passivity Constraints, Wen-Jer Chang, Cheung-Chieh Ku, Chih-Yu Yen, Guan-Wei Chen

Journal of Marine Science and Technology–Taiwan

This paper addresses a control performance problem for discretized ship autopilot system with uncertainty. To completely express the uncertainty, Linear Parameter Varying (LPV) modelling technology is employed such that the ship autopilot system is described via several linear systems and weighting function. Furthermore, gain-scheduled scheme is applied to design a controller to achieve the passivity and pole-assignment constraints. Moreover, a Parameter-Dependent Lyapunov Function (PDLF) is used to derive some sufficient conditions. Through the proposed design method, the attenuation performance and stability of the system can be guaranteed. Besides, the transient responses are furtherly improved such that the ship autopilot system …

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Adaptive Pid-Like Control Using Broad Learning System For Nonlinear Dynamic Systems, Ching-Chih Tsai, Chun-Chieh Chan, Chien-Cheng Yu, Hung-Sheng Chen, Guo-Shun Hung Oct 2020

Adaptive Pid-Like Control Using Broad Learning System For Nonlinear Dynamic Systems, Ching-Chih Tsai, Chun-Chieh Chan, Chien-Cheng Yu, Hung-Sheng Chen, Guo-Shun Hung

Journal of Marine Science and Technology–Taiwan

This paper presents a new learning control structure using broad learning system (BLS) for adaptive PID-like control of unknown digital nonlinear dynamic systems with time delays. The proposed control method, abbreviated as BLS-APIDLC, is novel in combining BLS and model predictive control to develop a new PID-like control law for high-performance setpoint tracking control and disturbance rejection. Comparative simulations on two renowned nonlinear digital time-delay systems are well used to show the effectiveness and superiority of the proposed method by comparing to four existing methods. I

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Control Barrier Function Design Using Revived Transformation, Maki Takai, Motoi Igarashi, Hisakazu Nakamura Oct 2020

Control Barrier Function Design Using Revived Transformation, Maki Takai, Motoi Igarashi, Hisakazu Nakamura

Journal of Marine Science and Technology–Taiwan

The state constraint problem is an essential topic in control theory, wherein control methods using a control barrier function (CBF) and a revived transformation have been recently proposed. However, a way of designing the CBF is yet to be developed in a constrained space. In this study, we propose a CBF design method by using a revived transformation. Our method can design a CBF in a constrained space by utilizing a diffeomorphism from an unconstrained space. We demonstrate the effectiveness of the proposed method by human assist control design and computer simulation.

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Constraints To Guarantee Gain And Phase Margins For Data-Driven Controller Tuning Methods, Taiga Sakatoku, Kazuhiro Yubai, Daisuke Yashiro, Satoshi Komada Oct 2020

Constraints To Guarantee Gain And Phase Margins For Data-Driven Controller Tuning Methods, Taiga Sakatoku, Kazuhiro Yubai, Daisuke Yashiro, Satoshi Komada

Journal of Marine Science and Technology–Taiwan

The Noniterative Correlation-based Tuning (NCbT) is one of the data-driven controller tuning methods which directly tune controller parameters from input/output data set of a plant . The NCbT is based on the correlation approach to robustly tune controller parameters using a noisy input/output data set. Since the NCbT guarantees closed-loop stability only for the situation where the data is acquired, a plant fluctuation is not taken into consideration, which may lead to degradation of control performance and/or destabilization of the closed-loop system . In this paper, we virtually produce input/output data sets of the plant with various gain and/or phase …

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