Computer Engineering Commons^™

Nanomechanical Resonators: Toward Atomic Scale, Bo Xu, Pengcheng Zhang, Jiankai Zhu, Zuheng Liu, Alexander Eichler, Xu-Qian Zheng, Jaesung Lee, Aneesh Dash, Swapnil More, Song Wu, Yanan Yanan, Hao Jia, Akshay Naik, Adrian Bachtold, Rui Yang, Philip X.-L. Feng, Zenghui Wang

Department of Electrical and Computer Engineering: Faculty Publications

The quest for realizing and manipulating ever smaller man-made movable structures and dynamical machines has spurred tremendous endeavors, led to important discoveries, and inspired researchers to venture to new grounds. Scientific feats and technological milestones of miniaturization of mechanical structures have been widely accomplished by advances in machining and sculpturing ever shrinking features out of bulk materials such as silicon. With the flourishing multidisciplinary field of low-dimensional nanomaterials, including one-dimensional (1D) nanowires/nanotubes, and two-dimensional (2D) atomic layers such as graphene/phosphorene, growing interests and sustained efforts have been devoted to creating mechanical devices toward the ultimate limit of miniaturization— genuinely down …

Dielectrophoretic Trapping Of Carbon Nanotubes For Temperature Sensing, Kaylee Burdette

Theses, Dissertations and Capstones

Conventional sensors are rapidly approaching efficiency limitations at their current size. In designing more efficient sensors, low dimensional materials such as carbon nanotubes (CNTs), quantum dots, and DNA origami can be used to enable higher degrees of sensitivity. Because of the high atomic surface to core ratio, these materials can be used to detect slight changes in chemical composition, strain, and temperature. CNTs offer unique advantages in different types of sensors due to their electromechanical properties. In temperature sensing, the high responsiveness to temperature and durability can be used to produce an accurate, reliable sensor in even extreme temperatures. This …

Improving Collaborative Recommendation Based On Item Weight Link Prediction, Sahraoui Kharroubi, Youcef Dahmani, Omar Nouali

Turkish Journal of Electrical Engineering and Computer Sciences

There is a continuous information overload on the Web. The problem treated is how to have relevant items (documents, products, services, etc.) at time and without difficulty. Filtering system also called recommender systems are widely used to recommend items to users by similarity process such as Amazon, MovieLens, Cdnow, etc. In the literature, to predict a link in a bipartite network, most methods are based either on a binary history (like, dislike) or on the common neighbourhood of the active user. In this paper, we modelled the recommender system by a weighted bipartite network. The bipartite topology offers a bidirectional …

A Progressive Learning Strategy For Large-Scale Glacier Mapping, Zhiyuan Xie, Umesh K. Haritashya, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, the worldwide temperature increase has resulted in rapid deglaciation and a higher risk of glacier-related natural hazards such as flooding and debris flow. Due to the severity of these hazards, continuous observation and detailed analysis of glacier fluctuations are crucial. Many such analyses require an accurately delineated glacier boundary. However, the complexity and heterogeneity of glaciers, particularly debris-covered glaciers (DCGs), poses a challenge for glacier mapping when using conventional remote sensing or machine-learning techniques. Some examples exist about small-scale automated glacier mapping, but large or regional-scale mapping is challenging. Previously, a deep-learning-based approach named GlacierNet2 had been …

Study On Performance Of Pruned Cnn-Based Classification Models, Mengling Deng

Electronic Theses and Dissertations

Convolutional Neural Network (CNN) is a neural network developed for processing image data. CNNs have been studied extensively and have been used in numerous computer vision tasks such as image classification and segmentation, object detection and recognition, etc. [1] Although, the CNNs-based approaches showed humanlevel performances in these tasks [2], they require heavy computation in both training and inference stages, and the models consist of millions of parameters. This hinders the development and deployment of CNN-based models for real world applications. Neural Network Pruning and Compression techniques have been proposed [3, 4] to reduce the computation complexity of trained CNNs …

Removing Physical Presence Requirements For A Remote And Automated World - Api Controlled Patch Panel For Conformance Testing, Hunter George Wells

Honors Theses and Capstones

Quality assurance test engineers at the UNH-InterOperability Lab must run tests that require driving and monitoring a selection of DC signals. While the number of signals is numerous, there are limited ports on the test equipment, and only a few signals need patching for any given test. The selection of signals may vary between the 209 different tests and must be re-routed frequently. Currently, testers must leave their desk to manually modify the test setup in another room. This posed a considerable issue at the onset of the COVID-19 Pandemic when physical access was not possible. In order to enable …

Motion-Aware Vehicle Detection In Driving Videos, Mehmet Kiliçarslan, Tansu Temel

Turkish Journal of Electrical Engineering and Computer Sciences

This paper focuses on vehicle detection based on motion features in driving videos. Long-term motion information can assist in driving scenarios since driving is a complicated and dynamic process. The proposed method is a deep learning based model which processes motion frame image. This image merges both spatial (frame) and temporal (motion) information. Hence, the model jointly detects vehicles and their motion from a single image. The trained model on Toyota Motor Europe Motorway Dataset reaches 83% mean average precision (mAP). Our experiments demonstrate that the proposed method has a higher mAP than a tracking-based model. The proposed method runs …

A Futuristic Approach To Generate Random Bit Sequence Using Dynamic Perturbedchaotic System, Sathya Krishnamoorthi, Premalatha Jayapaul, Vani Rajasekar, Rajesh Kumar Dhanaraj, Celestine Iwendi

Turkish Journal of Electrical Engineering and Computer Sciences

Most of the web applications require security which in turn requires random numbers. Pseudo-random numbers are required with good statistical properties and efficiency. Use of chaotic map to dynamically perturb another chaotic map that generates the random bit output is introduced in this work. Perturbance is introduced to improvise the chaotic behaviour of a base map and increase the periodicity. PRNG with this architecture is devised to generate random bit sequence from initial keyspace. The statistical properties of newly constructed PRNG are tested with NIST SP 800-22 statistical test suite and were shown to have good randomness. To ensure its …

A Simple Dual-Band Quasi-Yagi Antenna With Defected Ground Structures, Göksel Turan, Hayretti̇n Odabaşi

Turkish Journal of Electrical Engineering and Computer Sciences

In this article, a dual-band compact quasi-Yagi antenna with defected ground structure (DGS) is proposed. The proposed antenna has a simple feeding mechanism consists of a microstrip and transmission line. Half of the driver and director elements are printed on the opposite side of the substrate to ensure good coupling between the antenna elements and achieve a stable radiation pattern. The ground plane is modified with one rectangular slot below the microstrip line to form dual-band operation. Also rectangular slots placed on the sides of the ground plane to improve the matching. The proposed antenna works at $f_{1}=3.35$ and $f_{2}=6.15$ …

Biomimetic Design, Modeling, And Adaptive Control Of Robotic Gripper For Optimal Grasping, Mushtaq Al-Mohammed

Electronic Theses and Dissertations, 2020-2023

Grasping is an essential skill for almost every assistive robot. Variations in shape and/or weight of different objects involved in Activities of Daily Living (ADL) lead to complications, especially, when the robot is trying to grip novel objects for which it has no prior information –too much force will deform or crush the object while too little force will lead to slipping and possibly dropped objects. Thus, successful grasping requires the gripper to immobilize an object with the minimal force. In Chapter 2, we present the design, analysis, and experimental implementation of an adaptive control to facilitate 1-click grasping of …

Using Long Short-Term Memory Networks To Make And Train Neural Network Based Pseudo Random Number Generator, Aditya Harshvardhan

Electronic Theses and Dissertations

Neural Networks have been used in many decision-making models and been employed in computer vision, and natural language processing. Several works have also used Neural Networks for developing Pseudo-Random Number Generators [2, 4, 5, 7, 8]. However, despite great performance in the National Institute of Standards and Technology (NIST) statistical test suite for randomness, they fail to discuss how the complexity of a neural network affects such statistical results. This work introduces: 1) a series of new Long Short- Term Memory Network (LSTM) based and Fully Connected Neural Network (FCNN – baseline [2] + variations) Pseudo Random Number Generators (PRNG) …

Formation Control With Bounded Controls And Collision Avoidance: Theory And Application To Quadrotor Unmanned Air Vehicles, Zachary S. Lippay

Theses and Dissertations--Mechanical and Aerospace Engineering

This dissertation presents new results on multi-agent formation control and applies the new control algorithms to quadrotor unmanned air vehicles. First, this dissertation presents a formation control algorithm for double-integrator agents, where the formation is time varying and the agents’ controls satisfy a priori bounds (e.g., the controls accommodate actuator saturation). The main analytic results provide sufficient conditions such that all agents converge to the desired time-varying relative positions with one another and the leader, and have a priori bounded controls (if applicable). We also present results from rotorcraft experiments that demonstrate the algorithm with time-varying formations and bounded controls. …

Detecting User Emotions From Audio Conversations With The Smart Assistants, Sunanda Guha

Graduate Theses/Dissertations

With the proliferation of smart home devices like Google Home or Amazon Alexa, significant research endeavors are being carried out to improve the user experience while interacting with these smart assistants. One such dimension in this endeavor is ongoing research on successful emotion detection from short voice commands used in smart home environment. Besides facial expression and body language, etc., speech plays a pivotal role in the classification of emotions when it comes to smart home application. Upon successful implementation of accurate emotion recognition, the smart devices will be able to intelligently and empathetically suggest appropriate actions based on the …

Deepfakes, Shallowfakes, And The Need For A Private Right Of Action, Eric Kocsis

Dickinson Law Review (2017-Present)

For nearly as long as there have been photographs and videos, people have been editing and manipulating them to make them appear to be something they are not. Usually edited or manipulated photographs are relatively easy to detect, but those days are numbered. Technology has no morality; as it advances, so do the ways it can be misused. The lack of morality is no clearer than with deepfake technology.

People create deepfakes by inputting data sets, most often pictures or videos into a computer. A series of neural networks attempt to mimic the original data set until they are nearly …

Book Review: This Is How They Tell Me The World Ends: The Cyberweapons Arms Race (2020) By Nicole Perlroth, Amy C. Gaudion

Dickinson Law Review (2017-Present)

No abstract provided.

Improving Network Policy Enforcement Using Natural Language Processing And Programmable Networks, Pinyi Shi

Theses and Dissertations--Computer Science

Computer networks are becoming more complex and challenging to operate, manage, and protect. As a result, Network policies that define how network operators should manage the network are becoming more complex and nuanced. Unfortunately, network policies are often an undervalued part of network design, leaving network operators to guess at the intent of policies that are written and fill in the gaps where policies don’t exist. Organizations typically designate Policy Committees to write down the network policies in the policy documents using high-level natural languages. The policy documents describe both the acceptable and unacceptable uses of the network. Network operators …

Protocols And Architecture For Privacy-Preserving Authentication And Secure Message Dissemination In Vehicular Ad Hoc Networks, Shafika Showkat Moni

Theses and Dissertations--Computer Science

The rapid development in the automotive industry and wireless communication technologies have enhanced the popularity of Vehicular ad hoc networks (VANETs). Today, the automobile industry is developing sophisticated sensors that can provide a wide range of assistive features, including accident avoidance, automatic lane tracking, semi-autonomous driving, suggested lane changes, and more. VANETs can provide drivers a safer and more comfortable driving experience, as well as many other useful services by leveraging such technological advancements. Even though this networking technology enables smart and autonomous driving, it also introduces a plethora of attack vectors. However, the main issues to be sorted out …

The Lognometer: A New Normalized And Computerized Device For Assessing The Neurodevelopment Of Fine Motor Control In Children, Christian O'Reilly, Rejean Plamondon, Nadir Faci

Publications

Motor skills are fundamental for the development of children. Neurodevelopmental tests currently used by professionals for measuring motor control maturity exhibit several limitations. To address some of these, we have designed the Lognometer, a tablet-based device that can run computerized neuromotor tests. To normalize this tool against a representative population, we collected handwritten triangles from 780 children. We used the Sigma-Lognormal model and a prototype-based parameter estimation algorithm to analyze these movements. To ensure clinical acceptance, we developed an explainable solution relying on statistical regression. We evaluated how well the proposed lognormal decomposition captures the motor control maturation between 6 …

Ksat: Knowledge-Infused Self Attention Transformer - Integrating Multiple Domain-Specific Contexts, Kaushik Roy, Yuxin Zi, Vignesh Narayanan, Manas Gaur, Amit P. Sheth

Publications

Domain-specific language understanding requires integrating multiple pieces of relevant contextual information. For example, we see both suicide and depression related behavior (multiple contexts) in the text “I have a gun and feel pretty bad about my life, and it wouldn’t be the worst thing if I didn’t wake up tomorrow”. Domain specificity in self-attention architectures is handled by fine-tuning on excerpts from relevant domain specific resources (datasets and external knowledge - medical textbook chapters on mental health diagnosis related to suicide and depression). We propose a modified self-attention architecture Knowledge infused Self Attention Transformer (KSAT) that achieves the integration of …

Meltpondnet: A Swin Transformer U-Net For Detection Of Melt Ponds On Arctic Sea Ice, Ivan Sudakow, Vijayan K. Asari, Ruixu Liu, Denis Demchev

Electrical and Computer Engineering Faculty Publications

High-resolution aerial photographs of Arctic region are a great source for different sea ice feature recognition, which are crucial to validate, tune, and improve climate models. Melt ponds on the surface of melting Arctic sea ice are of particular interest as they are sensitive and valuable indicators and are proxy to the processes in the Arctic climate system. Manual analysis of this remote sensing data is extremely difficult and time-consuming due to the complex shapes and unpredictable boundaries of the melt ponds, and that leads to the necessity for automatizing the processes. In this study, we propose a robust and …

Circuit Optimization Techniques For Efficient Ex-Situ Training Of Robust Memristor Based Liquid State Machine, Alex Henderson, Christopher Yakopcic, Cory Merkel, Steven Harbour, Tarek M. Taha, Hananel Hazan

Electrical and Computer Engineering Faculty Publications

Spiking neural network hardware offers a high performance, power-efficient and robust platform for the processing of complex data. Many of these systems require supervised learning, which poses a challenge when using gradient-based algorithms due to the discontinuous properties of SNNs. Memristor based hardware can offer gains in portability, power reduction, and throughput efficiency when compared to pure CMOS. This paper proposes a memristor-based spiking liquid state machine (LSM). The inherent dynamics of the LSM permit the use of supervised learning without backpropagation for weight updates. To carry out the design space evaluation of the LSM for optimal hardware performance, several …

An Experimental Study Towards Underwater Propulsion System Using Structure Borne Traveling Waves, Shreyas Suhas Gadekar

Dissertations, Master's Theses and Master's Reports

The method of generating steady-state structure-borne traveling waves underwater in an infinite media creates abundant opportunities in the field of propulsive applications, and they are gaining attention from several researchers. This experimental study provides a framework for harnessing traveling waves in a 1D beam immersed under quiescent water using two force input methods and providing a motion to an object floating on the surface of the water.

In this study, underwater traveling waves are tailored using structural vibrations at five different frequencies in the range of 10Hz to 300Hz. The resulting fluid motion provides a propulsive thrust that moves a …

Garden Bot: Autonomous Home Garden Weed Removal Robot, Brendon Lovejoy, Robert Connolly, Isaac Lucas, Stevan Veselinov

Williams Honors College, Honors Research Projects

With frequent weeding being a tedious chore and an essential task for a successful garden, there is need for an automated method of handling this routine. Existing technologies utilize computer vision, GPS, multiple units and other tools to remove weeds from garden plots. However, these solutions are often complex and expensive, suited for large agricultural plots in contrast to small-scale home gardens. In addition, many of these technologies, along with manual tillers and cultivators suited for home use, are unable to perform weeding within rows of crops in a process known as intra-row weeding. The Garden Bot is an autonomous, …

Smart Uv-C Disinfectant Module, Nicole Baldy, Luke Rogers, Haitham Saleh

Williams Honors College, Honors Research Projects

The Smart UV Disinfectant device shall sanitize objects which are 18”x14”x8” or smaller and less than 20 lbs. using UV-C light. This device should contain many safety measures to prevent human and animal exposure to the UV-C light and have no public touchpoints to operate the interface. In order to achieve the first objective, this device shall contain a "sanitizing chamber" which completely encloses the object to be sanitized to prevent outside exposure with detection of any lifeforms inside of the chamber; for the second objective, it will contain a wireless interface to an Android application which can be used …

Design Project: 3d Printer/Injection Molder Hybrid, Lee Paolucci, Luke Everhart, Brandon Leap, Karson Lorey

Williams Honors College, Honors Research Projects

In the realm of rapid, small-scale prototyping, there are a few main factors that drive decisions to invest resources in technology to make that prototyping possible. Cost and ease of use are two of the most influential when looking at most SMEs (Small to Medium-sized Enterprises). The U.S. Small Business Administration defines an SME as smaller than 1,250 employees. According to An Assessment of Implementation of Entry-Level 3D Printers from the Perspective of Small Businesses, 59% of small manufacturers had implemented 3D printers as of 2014. However, no matter what technology is used in rapid prototyping, there are common …

Nject-3d, Kody Rinkevich, Logan Henderson, Nathaniel Anderson, James Patton, Cameron Wilson

Williams Honors College, Honors Research Projects

NJECT-3D is a student initiated design project where the utilities of a 3D printer and an injection molding machine are integrated into one cohesive unit. The goal of our project was to test the limits of rapid prototyping by utilizing printed molds. We developed an automated system where a mold can be printed on a 3D printer, translated from said 3D printer to an injection molder, then compressed and injected at said injection molder to output a finalized injection molded part.

Smart Bike Aftermarket System (Sbams), Noah Lamadanie, Jack Bullock, Dawson Beachy, John Albrecht

Williams Honors College, Honors Research Projects

The Smart Bike Aftermarket System will be a set of connected modules, which, when installed on a standard bicycle, will allow it to mimic some of the safety and quality-of-life functionalities of an E-bike. The most notable of these safety features is an ability to detect vehicles approaching from behind and alert the user of potential collisions. The system will also implement lighting (Headlights, taillights, and turn signals), and a coupled application so a user can view more advanced information about their cycling. The primary advantage of this system over a standard E-bike is that it will have a lower …

Magic: The Gathering Card Virtualizer, Vincent Garbonick, Jacen C. Conlan, Jaret A. Varn

Williams Honors College, Honors Research Projects

Any well-versed Magic: The Gathering (MTG) player or collector knows how difficult it can be to keep track of all cards in their collection. Some spend hours searching for that one specific card, and others are constantly scouring the internet for how much their collection costs. However, this issue does not only affect casual fans. Resale companies spend hours a day determining the costs of cards, and tournament judges painstakingly check players’ decks to ensure they are not cheating. To assist with these struggles, the design team proposed to create the MTG Card Virtualizer. This device scans MTG playing cards …

Lapnitor: A Web Service That Protects Your Laptop From Theft., Michael Ameteku

Williams Honors College, Honors Research Projects

Laptop theft is an issue worldwide. According to an article from 2018, Security Boulevard stated that a laptop is stolen every 53 seconds. Using a laptop's camera, we can monitor the surroundings of the laptop and reduce a laptop's probability of being stolen. According to the University of Pittsburgh, a laptop has a 1-in- 10 chance of being stolen and nearly half of these thefts occur in offices or classrooms. These thefts mostly occur when a laptop owner leaves their device unattended for a certain period of time to maybe go visit the restroom or attend to a call when …

Identifying Code Reading Strategies In Debugging Using Sta With A Tolerance Algorithm, Christine Lourrine S. Tablatin, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

The purpose of this study was to identify the common code reading strategies of the high and low performing students engaged in a debugging task. Using Scanpath Trend Analysis (STA) with a tolerance on eye tracking data, common scanpaths of high and low performing students were generated. The common scanpaths revealed differences in the code reading patterns and code reading strategies of high and low performing students. High performing students follow a bottom-up code reading strategy when debugging complex programs with logical and semantic errors. A top-down code reading strategy is employed when debugging programs with simple control structures, few …