A Privacy-Preserving Strategy For The Trust Layer Of The Energy Grid Of Things Distributed Energy Resource Management System,
2022
Portland State University
A Privacy-Preserving Strategy For The Trust Layer Of The Energy Grid Of Things Distributed Energy Resource Management System, Mohammed Abdullah Alsaid
Dissertations and Theses
Emergent from the shadows of the traditional grid flaws, the Smart Grid (SG) idea was born and led by government mandates toward cleaner energy production. The SG represents the next generation of electricity distribution systems that subsume recent technological innovations. It uses digital communication between its components and entities to attain more automation, self-sufficiency, and reliability. Unfortunately, this relatively new concept is not flawless; the intrinsic reliance on increased digital communication spreads open attack paths for adversaries. Therefore, finding solutions that address information exchange vulnerabilities has become imperative.
The Energy Grid of Things (EGoT) is Portland State University's implementation of …
Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms,
2022
Chapman University
Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms, Rahul Soangra, Yuxin Wen, Hualin Yang, Marybeth Grant-Beuttler
Physical Therapy Faculty Articles and Research
Idiopathic toe walking (ITW) is a gait abnormality in which children’s toes touch at initial contact and demonstrate limited or no heel contact throughout the gait cycle. Toe walking results in poor balance, increased risk of falling, and developmental delays among children. Identifying toe walking steps during walking can facilitate targeted intervention among children diagnosed with ITW. With recent advances in wearable sensing, communication technologies, and machine learning, new avenues of managing toe walking behavior among children are feasible. In this study, we investigate the capabilities of Machine Learning (ML) algorithms in identifying initial foot contact (heel strike versus toe …
Finding Approximate Pythagorean Triples (And Applications To Lego Robot Building),
2022
Loyola University Chicago
Finding Approximate Pythagorean Triples (And Applications To Lego Robot Building), Ronald I. Greenberg, Matthew Fahrenbacher, George K. Thiruvathukal
Computer Science: Faculty Publications and Other Works
This assignment combines programming and data analysis to determine good combinations of side lengths that approximately satisfy the Pythagorean Theorem for right triangles. This can be a standalone exercise using a wide variety of programming languages, but the results are useful for determining good ways to assemble LEGO pieces in robot construction, so the exercise can serve to integrate three different units of the Exploring Computer Science high school curriculum: "Programming", "Computing and Data Analysis", and "Robotics". Sample assignment handouts are provided for both Scratch and Java programmers. Ideas for several variants of the assignment are also provided.
A Distributed Trust Model Simulator For Energy Grid Of Things Distributed Energy Resource Management System,
2022
Portland State University
A Distributed Trust Model Simulator For Energy Grid Of Things Distributed Energy Resource Management System, Abdullah Barghouti
Dissertations and Theses
The evolution of networks into more distributed, self-reliant nodes has mitigated single-point failures that plagued traditional centralized networks. Applied to power grids, distributed systems can increase the integrity and availability of grid services while also offering a power management solution. However, while distributed networks provide scalability, security, and sustainability compared to centralized networks, their distributed nature makes them harder for anomaly detection and prevention. Incorporating a Distributed Trust Model (DTM) System into an Energy Grid of Things Distributed Energy Resource Management System (EGOT DERMS) allows grid participants to be characterized and their communication to be analyzed for possible attacks. A …
Experimenting An Edge-Cloud Computing Model On The Gpulab Fed4fire Testbed,
2022
Graphic Era Deemed to be University
Experimenting An Edge-Cloud Computing Model On The Gpulab Fed4fire Testbed, Vikas Tomer, Sachin Sharma
Conference papers
There are various open testbeds available for testing algorithms and prototypes, including the Fed4Fire testbeds. This demo paper illustrates how the GPULAB Fed4Fire testbed can be used to test an edge-cloud model that employs an ensemble machine learning algorithm for detecting attacks on the Internet of Things (IoT). We compare experimentation times and other performance metrics of our model based on different characteristics of the testbed, such as GPU model, CPU speed, and memory. Our goal is to demonstrate how an edge-computing model can be run on the GPULab testbed. Results indicate that this use case can be deployed seamlessly …
Demonstrating Configuration Of Software Defined Networking In Real Wireless Testbeds,
2022
Technological University Dublin
Demonstrating Configuration Of Software Defined Networking In Real Wireless Testbeds, Saish Urumkar, Gianluca Fontanesi, Avishek Nag, Sachin Sharma
Conference papers
Currently, several wireless testbeds are available to test networking solutions including Fed4Fire testbeds such as w-ilab. t and CityLab in the EU, and POWDER and COSMOS in the US. In this demonstration, we use the w-ilab.t testbed to set up a wireless ad-hoc Software-Defined Network (SDN). OpenFlow is used as an SDN protocol and is deployed using a grid wireless ad-hoc topology in w-ilab.t. In this paper, we demonstrate: (1) the configuration of a wireless ad-hoc network based on w-ilab.t and (2) the automatic deployment of OpenFlow in an ad-hoc wireless network where some wireless nodes are not directly connected …
Influence Of Aluminum Addition On The Laser Powder Bed Fusion Of Copper-Aluminum Mixtures,
2022
University of Nebraska-Lincoln, University of Bordeaux
Influence Of Aluminum Addition On The Laser Powder Bed Fusion Of Copper-Aluminum Mixtures, Nada Kraiem, Loic Constantin, A. Mao, Fei Wang, Bai Cui, Jean-François Silvain, Yongfeng Lu
Department of Electrical and Computer Engineering: Faculty Publications
The high optical reflectivity of copper (Cu) in the near infrared (NIR) domain and its elevated heat dissipation make Cu a challenging metal for laser powder bed fusion (LPBF), even with high energy densities (EDs). In this study, we demonstrated that adding aluminum (Al) powder by as little as 0.75, 1.5, and 3 wt.% substantially enhances Cu processability, leading to denser (up to 98%) and smoother (Ra = 3.3 𝜇m) Cu-Al parts as compared to 95% and 18 𝜇m, respectively, for the parts printed using pure Cu. In addition, this method reduces the ED required by a factor of two …
The Message Design Of Raiders Of The Lost Ark On The Atari 2600 & A Fan’S Map, Quick Start, And Strategy Guide,
2022
Old Dominion University
The Message Design Of Raiders Of The Lost Ark On The Atari 2600 & A Fan’S Map, Quick Start, And Strategy Guide, Miguel Ramlatchan, William I. Ramlatchan
Distance Learning Faculty & Staff Books
The message design and human performance technology in video games, especially early video games have always been fascinating to me. From an instructional design perspective, the capabilities of the technology of the classic game consoles required a careful balance of achievable objectives, cognitive task analysis, guided problem solving, and message design. Raiders on the Atari is an excellent example of this balance. It is an epic adventure game, spanning 13+ distinct areas, with an inventory of items, where those hard to find items had to be used by the player to solve problems during their quest (and who would have …
Addressing The "Leaky Pipeline": A Review And Categorisation Of Actions To Recruit And Retain Women In Computing Education,
2022
Technological University Dublin
Addressing The "Leaky Pipeline": A Review And Categorisation Of Actions To Recruit And Retain Women In Computing Education, Alina Berry, Susan Mckeever, Brenda Murphy, Sarah Jane Delany
Conference papers
Gender imbalance in computing education is a well-known issue around the world. For example, in the UK and Ireland, less than 20% of the student population in computer science, ICT and related disciplines are women. Similar figures are seen in the labour force in the field across the EU. The term "leaky pipeline"; is often used to describe the lack of retention of women before they progress to senior roles. Numerous initiatives have targeted the problem of the leaky pipeline in recent decades. This paper provides a comprehensive review of initiatives related to techniques used to boost recruitment and improve …
Consemblex: A Consensus-Based Transcriptome Assembly Approach That Extends Consemble And Improves Transcriptome Assembly,
2022
University of Nebraska-Lincoln
Consemblex: A Consensus-Based Transcriptome Assembly Approach That Extends Consemble And Improves Transcriptome Assembly, Richard Mwaba
School of Computing: Dissertations, Theses, and Student Research
An accurate transcriptome is essential to understanding biological systems enabling omics analyses such as gene expression, gene discovery, and gene-regulatory network construction. However, assembling an accurate transcriptome is challenging, especially for organisms without adequate reference genomes or transcriptomes. While several methods for transcriptome assembly with different approaches exist, it is still difficult to establish the most accurate methods. This thesis explores the different transcriptome assembly methods and compares their performances using simulated benchmark transcriptomes with varying complexity. We also introduce ConSemblEX to improve a consensus-based ensemble transcriptome assembler, ConSemble, in three main areas: we provide the ability to use any …
Credit Card Fraud Detection Using Machine Learning Techniques,
2022
BIS Helwan University
Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami
Future Computing and Informatics Journal
This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …
Cobol Cripples The Mind!: Academia And The Alienation Of Data Processing,
2022
Northwestern University
Cobol Cripples The Mind!: Academia And The Alienation Of Data Processing, Neel Shah
Swarthmore Undergraduate History Journal
This paper writes a social history of the programming language COBOL that focuses on its reception in academia. Through this focus, the paper seeks to understand the contentious relationship between data processing and the academy. In historicizing COBOL, the paper also illuminates the changing nature of the academy-industry-military triangle that was a mainstay of early computing.
A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity,
2022
Fordham University
A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian M. Lyons, James Finocchiaro, Misha Novitzky, Chris Korpela
Faculty Publications
Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …
A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity,
2022
USMA West Point
A Monte Carlo Framework For Incremental Improvement Of Simulation Fidelity, Damian Lyons, James Finocchiaro, Misha Novitsky, Chris Korpela
Faculty Publications
Robot software developed in simulation often does not be- have as expected when deployed because the simulation does not sufficiently represent reality - this is sometimes called the `reality gap' problem. We propose a novel algorithm to address the reality gap by injecting real-world experience into the simulation. It is assumed that the robot program (control policy) is developed using simulation, but subsequently deployed on a real system, and that the program includes a performance objective monitor procedure with scalar output. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are used to generate …
A Half- Yearly E-Newsletter Of The Department Of Computer Science And Engineering, Manipal Institute Of Technology - Jul 2022,
2022
Department of Computer Science and Engineering Manipal Institute of Technology
A Half- Yearly E-Newsletter Of The Department Of Computer Science And Engineering, Manipal Institute Of Technology - Jul 2022, Ashalatha Nayak Dr.
Faculty work
No abstract provided.
Spiking Neural Networks And Their Applications: A Review,
2022
University of Arkansas, Fayetteville
Spiking Neural Networks And Their Applications: A Review, Kashu Yamazaki, Viet-Khao Vo-Ho, Darshan Bulsara, Ngan Le
Computer Science and Computer Engineering Faculty Publications and Presentations
The past decade has witnessed the great success of deep neural networks in various domains. However, deep neural networks are very resource-intensive in terms of energy consumption, data requirements, and high computational costs. With the recent increasing need for the autonomy of machines in the real world, e.g., self-driving vehicles, drones, and collaborative robots, exploitation of deep neural networks in those applications has been actively investigated. In those applications, energy and computational efficiencies are especially important because of the need for real-time responses and the limited energy supply. A promising solution to these previously infeasible applications has recently been given …
Asymmetric Control Of Light At The Nanoscale,
2022
University of Nebraska - Lincoln
Asymmetric Control Of Light At The Nanoscale, Christos Argyropoulos
Department of Electrical and Computer Engineering: Faculty Publications
Breaking reciprocity at the nanoscale can produce directional formation of images due to the asymmetric nonlinear optical response of subwavelength anisotropic resonators. The self-induced passive non-reciprocity has advantages compared to magnet or time modulation approaches and may impact both classical and quantum photonics.
Breast Cancer-Caps: A Breast Cancer Screening System Based On Capsule Network Utilizing The Multiview Breast Thermal Infrared Images, Devanshu Tiwari, Manish Dixit, Kamlesh Gupta
Turkish Journal of Electrical Engineering and Computer Sciences
This paper proposed an accurate and fully automated breast cancer early screening system called the "Breast Cancer-Caps". The capsule network is used in this approach for the cancer detection in breast utilizing the thermal infrared images for the first time. This capsule network is trained with the help of Dynamic as well as Static breast thermal images dataset consisting of left, right, frontal views along with a new multiview thermal images. These multiview breast thermal images are fabricated by concatenating the conventional left, frontal and right view breast thermal images. The other current and popular deep transfer learning models such …
Comparative Study Of A Bidirectional Multi-Phase Multiinput Converter For Electric Vehicles,
2022
TÜBİTAK
Comparative Study Of A Bidirectional Multi-Phase Multiinput Converter For Electric Vehicles, Furkan Akar, Murat Kale, Sebahatti̇n Yalçin, Gözde Taş
Turkish Journal of Electrical Engineering and Computer Sciences
Multiinput converters allow to create hybrid energy systems in electric vehicles with a reduced part count. In addition, interleaved structures help to build efficient converters with several possible benefits, such as low current ripple and high power density. This paper proposes utilizing a multiphase multiinput converter (MPMIC), which concentrates the aforementioned advantages and presents a comprehensive comparison with its single-phase version, called single phase multiinput converter (SPMIC). After analysing their steady-state characteristics, SPMIC and MPMIC are designed considering same conditions. Then, two laboratory prototypes rated at 2.5kW output power are implemented to validate the analysis. Finally, these prototypes are compared …
On The Performance Analysis Of Flexible Pairing Between Uav And Gu In Noma,
2022
TÜBİTAK
On The Performance Analysis Of Flexible Pairing Between Uav And Gu In Noma, Man Hee Lee, Soo Young Shin
Turkish Journal of Electrical Engineering and Computer Sciences
The wireless communications regarding unmanned aerial vehicles (UAVs) have been investigated for the usage of base stations (BS) to provide Internet access. This paper presents the usage of a UAV as a pairing user to enhance the sum capacity by flexible pairing in nonorthogonal multiple access (NOMA). In the proposed scheme, the UAVs and the ground users (GUs) get paired to promote the line-of-sight (LoS) characteristics. The performance of flexible pairing is presented in terms of sum capacity, outage probability, and throughput with the LoS path loss. Channel modeling is necessary to apply flexible pairing by utilizing the LoS characteristic …
