Other Computer Engineering Commons^™

Design And Fabrication Of A Trapped Ion Quantum Computing Testbed, Christopher A. Caron

Masters Theses

Here we present the design, assembly and successful ion trapping of a room-temperature ion trap system with a custom designed and fabricated surface electrode ion trap, which allows for rapid prototyping of novel trap designs such that new chips can be installed and reach UHV in under 2 days. The system has demonstrated success at trapping and maintaining both single ions and cold crystals of ions. We achieve this by fabricating our own custom surface Paul traps in the UMass Amherst cleanroom facilities, which are then argon ion milled, diced, mounted and wire bonded to an interposer which is placed …

Learning To Rig Characters, Zhan Xu

Doctoral Dissertations

With the emergence of 3D virtual worlds, 3D social media, and massive online games, the need for diverse, high-quality, animation-ready characters and avatars is greater than ever. To animate characters, artists hand-craft articulation structures, such as animation skeletons and part deformers, which require significant amount of manual and laborious interaction with 2D/3D modeling interfaces. This thesis presents deep learning methods that are able to significantly automate the process of character rigging.

First, the thesis introduces RigNet, a method capable of predicting an animation skeleton for an input static 3D shape in the form of a polygon mesh. The predicted skeletons …

Forecasting Stock Market Indices Using Gated Recurrent Unit (Gru) Based Ensemble Models: Lstm-Gru, Nrusingha Tripathy, Surabi Parida, Subrat Kumar Nayak

International Journal of Computer and Communication Technology

A "time sequence analysis" is a particular method for looking at a group of data points gathered over a long period of time. Instead of merely randomly or infrequently, time series analyzers gather information from data points over a predetermined length of time at scheduled times. But this kind of research requires more than just accumulating data over time. Data in time series may be analyzed to illustrate how variables change over time, which makes them different from other types of data. To put it another way, time is a crucial element since it demonstrates how the data changes over …

Finserv Android Application, Harsh Piyushkumar Shah

Electronic Theses, Projects, and Dissertations

The FINSERV Android application is a mobile tool designed for individuals to manage and track their finances. In financially complex world, many people struggle to maintain a clear overview of their income, expenses, and financial goals. This application aims to bridge that gap by providing users with a powerful and user-friendly platform to efficiently monitor and optimize their personal finances.

With the Personal Finance Tracking Android Application, users can effortlessly track their income and expenses, categorize transactions, and gain valuable insights into their spending patterns. The application offers features such as expense categorization and real-time expense tracking.

To enhance usability …

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

Human-Machine Communication: Complete Volume. Volume 6

Human-Machine Communication

his is the complete volume of HMC Volume 6.

Chatgpt, Lamda, And The Hype Around Communicative Ai: The Automation Of Communication As A Field Of Research In Media And Communication Studies, Andreas Hepp, Wiebke Loosen, Stephan Dreyer, Juliane Jarke, Sigrid Kannengießer, Christian Katzenbach, Rainer Malaka, Michaela Pfadenhauer, Cornelius Puschmann, Wolfgang Schulz

Human-Machine Communication

The aim of this article is to more precisely define the field of research on the automation of communication, which is still only vaguely discernible. The central thesis argues that to be able to fully grasp the transformation of the media environment associated with the automation of communication, our view must be broadened from a preoccupation with direct interactions between humans and machines to societal communication. This more widely targeted question asks how the dynamics of societal communication change when communicative artificial intelligence—in short: communicative AI—is integrated into aspects of societal communication. To this end, we recommend an approach that …

Disentangling Two Fundamental Paradigms In Human-Machine Communication Research: Media Equation And Media Evocation, Margot J. Van Der Goot, Katrin Etzrodt

Human-Machine Communication

In this theoretical paper, we delineate two fundamental paradigms in how scholars conceptualize the nature of machines in human-machine communication (HMC). In addition to the well-known Media Equation paradigm, we distinguish the Media Evocation paradigm. The Media Equation paradigm entails that people respond to machines as if they are humans, whereas the Media Evocation paradigm conceptualizes machines as objects that can evoke reflections about ontological categories. For each paradigm, we present the main propositions, research methodologies, and current challenges. We conclude with theoretical implications on how to integrate the two paradigms, and with a call for mixed-method research that includes …

Automatic Classification And Segmentation Of Patterned Martian Ground Using Deep Learning Techniques, Ruthy Brito

Electronic Thesis and Dissertation Repository

Science autonomy onboard spacecraft can optimize image return by prioritizing downlink of meaningful data. Martian polygonally cracked ground is actively studied by planetary geologists and may be indicative of subsurface water. Filtering images containing these polygonal features can be used as a case study for science autonomy and to reduce the overhead associated with parsing through Martian surface images. This thesis demonstrates the use of deep learning techniques in the classification of Martian polygonally patterned ground from HiRISE images. Three tasks are considered, a binary classification to identify images containing polygons, multiclass classification distinguishing different polygon types and semantic segmentation …

Investigation Of Information Security Incidents In The Enterprise, Fayzullajon Botirov

Chemical Technology, Control and Management

This article analyzes the concept of investigating information security incidents and the processes of responsibility for their commission, checking the place where the incident occurred, collecting and storing their data, as well as organizing the investigation of information security incidents at the enterprise.

Synthesis Of Control Systems With Multilayer Neural Networks Based On Velocity Gradient Methods, Oxunjon Boborayimov, Okyay Kaynak

Chemical Technology, Control and Management

In this manuscripts, the synthesis of control systems with multilayer neural networks based on the speed gradient methods is given. For adjusting the weight coefficients of the base processor element, the gradient method of minimizing the learning criterion is used. A procedure for the synthesis of neural network control systems based on the velocity gradient methods has been developed. This guarantees the stabilization of the system under external limited disturbances that are inaccessible to direct measurement. Taking into account the state vector of the control object in the network learning function ensures the consistency of the processes of setting the …

The Potential Of The Implementation Of Offline Robotic Programming Into Automation-Related Pedagogy, Max Rios Carballo, Xavier Brown

Publications and Research

In this study, the offline programming tool RoboDK is used to program industrial robots for the automation sector. The study explores the feasibility of using this non-disruptive robot programming software for classroom use; assesses how well RoboDK can be used to program various robots used in the industry; creates and tests various applications; and pinpoints technical obstacles that prevent a smooth link between offline programming and actual robots. Initial results indicate that RoboDK is an effective tool for deploying its offline programming code to a Universal Robot, UR3e. There are many potential for advanced applications. The goal of the project …

User Profiling Through Zero-Permission Sensors And Machine Learning, Ahmed Elhussiny

Theses and Dissertations

With the rise of mobile and pervasive computing, users are often ingesting content on the go. Services are constantly competing for attention in a very crowded field. It is only logical that users would allot their attention to the services that are most likely to adapt to their needs and interests. This matter becomes trivial when users create accounts and explicitly inform the services of their demographics and interests. Unfortunately, due to privacy and security concerns, and due to the fast nature of computing today, users see the registration process as an unnecessary hurdle to bypass, effectively refusing to provide …

The First Annual Teaching And Research Showcase Poster Tu Dublin – The Proof Is In The Pudding – Using Perceived Stress To Measure Short-Term Impact In Initiatives To Enhance Gender Balance In Computing Education, Alina Berry, Sarah Jane Delany

Other resources

The problem of gender imbalance in computing higher education has forced academics and professionals to implement a wide range of initiatives. Many initiatives use recruitment or retention numbers as their most obvious evidence of impact. This type of evidence of impact is, however, more resource heavy to obtain, as well as often requires a longitudinal approach. There are many shorter term initiatives that use other ways to measure their success.

First, this poster presents with a review of existing evaluation measures in interventions to recruit and retain women in computing education across the board. Three main groups of evaluation come …

Deep Learning-Based Gated Recurrent Unit Approach To Stock Market Forecasting: An Analysis Of Intel's Stock Data, Nrusingha Tripathy, Ibanga Kpereobong Friday, Dharashree Rath, Debasish Swapnesh Kumar Nayak, Subrat Kumar Nayak

International Journal of Smart Sensor and Adhoc Network

The stock price index prediction is a very challenging task that's because the market has a very complicated nonlinear movement system. This fluctuation is influenced by many different factors. Multiple examples demonstrate the suitability of Machine Learning (ML) models like Neural Network algorithms (NN) and Long Short-Term Memory (LSTM) for such time series predictions, as well as how frequently they produce satisfactory outcomes. However, relatively few studies have employed robust feature engineering sequence models to forecast future prices. In this paper, we propose a cutting-edge stock price prediction model based on a Deep Learning (DL) technique. We chose the stock …

A High-Speed Portable Ground Heat Exchanger Model For Use In Various Energy Simulation Software, Ryan Davies, Matt Mitchell, Edwin Lee

Macalester Journal of Physics and Astronomy

A portable component model (PCM) of a ground source heat pump system was developed and used as a test case in the creating of a PCM development framework. By developing this framework, new building energy simulation models will be able to be easily integrated into existing simulation software such as EnergyPlus and the Modelica Buildings Library. Our model uses a time responsive g-function and numerical methods to simulate ground source heat pumps for single time steps as well as long time scales. We validated our model against GHESim and GLHEPro and found that our model agrees with these two standards …

Vr Force Feedback Gloves, Mark Wu, Claire Chen

Electrical Engineering

The goal of this project is to produce a manufacturing plan for a consumer VR glove. The total addressable market of VR is over 170 million global users as of 2022 (Kolmar , 2022) with a serviceable available market of 300,000 users on Meta’s own social platform (Heath, 2022). The targeted Quest 2 platform utilizes handheld controllers, which causes a lack of immersivity in social settings and gaming scenarios. One common use of the platform involves social platforms such as “Horizons” where users meet in a virtual world to interact; handheld controllers don’t allow users to shake hands, make finger …

Sentiment Analysis Of Text And Emoji Data For Twitter Network, Paramita Dey, Soumya Dey

Al-Bahir Journal for Engineering and Pure Sciences

Twitter is a social media platform where users can post, read, and interact with 'tweets'. Third party like corporate organization can take advantage of this huge information by collecting data about their customers' opinions. The use of emoticons on social media and the emotions expressed through them are the subjects of this research paper. The purpose of this paper is to present a model for analyzing emotional responses to real-life Twitter data. The proposed model is based on supervised machine learning algorithms and data on has been collected through crawler “TWEEPY” for empirical analysis. Collected data is pre-processed, pruned and …

Credit Card Fraud Detection Using Logistic Regression And Synthetic Minority Oversampling Technique (Smote) Approach, Nrusingha Tripathy, Subrat Kumar Nayak, Julius Femi Godslove, Ibanga Kpereobong Friday, Sasanka Sekhar Dalai

International Journal of Computer and Communication Technology

Financial fraud is a serious threat that is expanding effects on the financial sector. The use of credit cards is growing as digitization and internet transactions advance daily. The most common issues in today's culture are credit card scams. This kind of fraud typically happens when someone uses someone else's credit card details. Credit card fraud detection uses transaction data attributes to identify credit card fraud, which can save significant financial losses and affluence the burden on the police. The detection of credit card fraud has three difficulties: uneven data, an abundance of unseen variables, and the selection of an …