Computer Engineering Commons^™

Deep Cnn-Based Automated Optical Inspection For Aerospace Components, Shashi Bhushan Jha

Doctoral Dissertations and Master's Theses

ABSTRACT

The defect detection problem is of outmost importance in high-tech industries such as aerospace manufacturing and is widely employed using automated industrial quality control systems. In the aerospace manufacturing industry, composite materials are extensively applied as structural components in civilian and military aircraft. To ensure the quality of the product and high reliability, manual inspection and traditional automatic optical inspection have been employed to identify the defects throughout production and maintenance. These inspection techniques have several limitations such as tedious, time- consuming, inconsistent, subjective, labor intensive, expensive, etc. To make the operation effective and efficient, modern automated optical inspection …

Round-Robin Algorithm In Load Balancing For National Data Centers, I Kadek Wahyu Sudiatmika, Gede Indrawan, Sariyasa Sariyasa

Knowledge Engineering and Data Science

The Provincial Government of Bali assumes a crucial role in administering various public service applications to meet the requirements of its community, traditional villages, and regional apparatus. Nevertheless, the escalating magnitude of traffic and uneven distribution of requests have resulted in substantial server burdens, which may jeopardize the operation of applications and heighten the likelihood of downtime. Ensuring efficient load distribution is of utmost importance in tackling these difficulties, and the Round Robin algorithm is often utilized for this purpose. However, the current body of research has not extensively examined the distinct circumstances surrounding on-premise servers in the Bali Provincial …

Balanced Blended Space: Foundational Human–Ai Dialogues In A Symmetry-Based Mediation Framework, David Smith

Publications and Research

This working paper documents the early development of the Balanced Blended Space (BBS) framework through a series of iterative interactions between a cognitive agent (human researcher) and a computational agent (AI system) conducted in 2023. The work is motivated by the need for a universal theoretical model capable of describing the integration of physical, virtual, and conceptual spaces, particularly in response to increasing fragmentation across contemporary communication systems.

BBS is proposed as a symmetry-based mediation framework in which relationships between domains—such as physical and virtual space, cognition and computation, and multiple sensory modalities—are treated as structurally equivalent and mappable. Central …

Ant Colony Optimization For Resistor Color Code Detection, Slamet Wibawanto, Kartika Candra Kirana, Hani Ramadhan

Knowledge Engineering and Data Science

In the early stages of learning resistors, introducing color-based values is needed. Moreover, some combinations require a resistor trip analysis to identify. Unfortunately, a resistor body color is considered a local solution, which often confuses resistor coloration. Ant Colony Optimization (ACO) is a heuristic algorithm that can recognize problems with traveling a group of ants. ACO is proposed to select commercial matrix values to be computed without preventing local solutions. In this study, each explores the matrix based on pheromones and heuristic information to generate local solutions. Global solutions are selected based on their high degree of similarity with other …

Exploring The Impact Of Students Demographic Attributes On Performance Prediction Through Binary Classification In The Kdp Model, Issah Iddrisu, Peter Appiahene, Obed Appiah, Inusah Fuseini

Knowledge Engineering and Data Science

During the course of this research, binary classification and the Knowledge Discovery Process (KDP) were used. The experimental and analytical capabilities of Rapid Miner's 9.10.010 instructional environment are supported by five different classifiers. Included in the analysis were 2334 entries, 17 characteristics, and one class variable containing the students' average score for the semester. There were twenty experiments carried out. During the studies, 10-fold cross-validation and ratio split validation, together with bootstrap sampling, were used. It was determined whether or not to use the Random Forest (RF), Rule Induction (RI), Naive Bayes (NB), Logistic Regression (LR), or Deep Learning (DL) …

Optimizing Random Forest Algorithm To Classify Player's Memorisation Via In-Game Data, Akmal Vrisna Alzuhdi, Harits Ar Rosyid, Mohammad Yasser Chuttur, Shah Nazir

Knowledge Engineering and Data Science

Assessment of a player's knowledge in game education has been around for some time. Traditional evaluation in and around a gaming session may disrupt the players' immersion. This research uses an optimized Random Forest to construct a non-invasive prediction of a game education player's Memorization via in-game data. Firstly, we obtained the dataset from a 3-month survey to record in-game data of 50 players who play 4-15 game stages of the Chem Fight (a test case game). Next, we generated three variants of datasets via the preprocessing stages: resampling method (SMOTE), normalization (min-max), and a combination of resampling and normalization. …

Inter-Frame Video Compression Based On Adaptive Fuzzy Inference System Compression Of Multiple Frame Characteristics, Arief Bramanto Wicaksono Putra, Rheo Malani, Bedi Suprapty, Achmad Fanany Onnilita Gaffar, Roman Voliansky

Knowledge Engineering and Data Science

Video compression is used for storage or bandwidth efficiency in clip video information. Video compression involves encoders and decoders. Video compression uses intra-frame, inter-frame, and block-based methods. Video compression compresses nearby frame pairs into one compressed frame using inter-frame compression. This study defines odd and even neighboring frame pairings. Motion estimation, compensation, and frame difference underpin video compression methods. In this study, adaptive FIS (Fuzzy Inference System) compresses and decompresses each odd-even frame pair. First, adaptive FIS trained on all feature pairings of each odd-even frame pair. Video compression-decompression uses the taught adaptive FIS as a codec. The features utilized …

Maximum Marginal Relevance And Vector Space Model For Summarizing Students' Final Project Abstracts, Gunawan Gunawan, Fitria Fitria, Esther Irawati Setiawan, Kimiya Fujisawa

Knowledge Engineering and Data Science

Automatic summarization is reducing a text document with a computer program to create a summary that retains the essential parts of the original document. Automatic summarization is necessary to deal with information overload, and the amount of data is increasing. A summary is needed to get the contents of the article briefly. A summary is an effective way to present extended information in a concise form of the main contents of an article, and the aim is to tell the reader the essence of a central idea. The simple concept of a summary is to take an essential part of …

Long-Term Traffic Prediction Based On Stacked Gcn Model, Atkia Akila Karim, Naushin Nower

Knowledge Engineering and Data Science

With the recent surge in road traffic within major cities, the need for both short and long-term traffic flow forecasting has become paramount for city authorities. Previous research efforts have predominantly focused on short-term traffic flow estimations for specific road segments and paths. However, applications of paramount importance, such as traffic management and schedule routing planning, demand a deep understanding of long-term traffic flow predictions. However, due to the intricate interplay of underlying factors, there exists a scarcity of studies dedicated to long-term traffic prediction. Previous research has also highlighted the challenge of lower accuracy in long-term predictions owing to …

K-Means Clustering And Multilayer Perceptron For Categorizing Student Business Groups, Miftahul Walid, Norfiah Lailatin Nispi Sahbaniya, Hozairi Hozairi, Fajar Baskoro, Arya Yudhi Wijaya

Knowledge Engineering and Data Science

The research conducted in this study was driven by the East Java provincial government's requirement to assess the transaction levels of the Student Business Group (KUS) in the SMA Double Track program. These transaction levels are a basis for allocating supplementary financial aid to each business group. The system's primary objective is to assist the provincial government of East Java in making well-informed choices pertaining to the distribution of supplementary capital to the KUS. The classification technique employed in this study is the multilayer perceptron. However, the K-Means Clustering method is utilised to generate target data due to the limited …

Optimization Techniques For Machine Learning Inference And Near Memory Image Processing In Hardware For Highly Constrained Iot Edge Nodes, Rajeev Joshi

USF Tampa Graduate Theses and Dissertations

The growing demand for fast and energy-efficient hardware for resource-constrained Internet of Things (IoT) edge devices has highlighted the limitations of conventional computing architectures. This research focuses on addressing the demand for fast, optimized, and energy-efficient machine learning inference engines as well as image processing in IoT edge applications. In this work, we address three challenging research problems and devise efficient solutions. Our investigation involved comprehensive exploration and analysis, leading to the proposal of effective approaches for overcoming these demanding issues. Through our work, we contribute novel solutions that offer improved efficiency and effectiveness in handling these research problems.

First, …

Secure Lightweight Cryptographic Hardware Constructions For Deeply Embedded Systems, Jasmin Kaur

USF Tampa Graduate Theses and Dissertations

Lightweight cryptography plays a vital role in securing resource-constrained deeply-embedded systems such as implantable and wearable medical devices, smart fabrics, smart homes, radio frequency identification tags, sensor networks, and privacy-constrained usage models. The National Institute of Standards and Technology (NIST) initiated a standardization process for lightweight cryptography, a relatively-long multi-year effort, which eventually concluded in February 2023. Side-channel attacks (SCAs) exploit the vulnerabilities of a system by observing and analyzing side-channel information leakages. Fault analysis attacks are a type of active SCAs, where an intelligent adversary injects bit/byte faults into the implementation of a cryptographic cipher to recover the secret …

Enhancing The Safety And Reliability Of Closed-Loop Medical Control Systems, Shakil Mahmud

USF Tampa Graduate Theses and Dissertations

The Internet of Medical Things (IoMT) is a rapidly advancing field that relies heavily on semi- or closed-loop Wearable and Implantable Medical Devices (WIMDs). In recent years, there has been renewed interest in clinical automation, with researchers looking for innovative solutions for Physiological Closed-Loop Control Systems (PCLCS). However, these devices can have various security issues, including vulnerabilities in software and firmware, physical attacks, weak encryption/authentication, and compromised system components. Government agencies, including the US Food and Drug Administration (FDA) and European Medicines Agency (EMA), emphasize the importance of ensuring the safety and reliability of PCLCS since malfunctioning medical devices can …

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 …

Development Of A Raspberry Pi-Controlled Vex Robot For A Robotics Technology Course, Lili Ma, Justin Bartholomew, Yu Wang, Xiaohai Li

Publications and Research

This paper describes the development of a Raspberry PI-controlled VEX robot for an undergraduate robotic course. The Raspberry PI controls the mobile base built using the VEX robotics kit without using the Cortex micro-controller that comes with the kit. The aim is to create a physical robot that is manageable, easily replicable, and capable of performing advanced robotic control tasks such as vision-based control.

The constructed robot adopts the great features of the PI and the VEX hardware. Firstly, the VEX hardware consists of various sensors and actuators for students to practice the construction and assembly of an autonomous robot. …

Introducing Ros-Projects To Undergraduate Robotic Curriculum, Lili Ma, Yu Wang, Chen Xu, Xiaohai Li

Publications and Research

This paper describes three MATLAB-ROS-based simulation projects developed for an undergraduate robotics course. The Robot Operating System (ROS) is an open-source framework that helps researchers and developers build and reuse code between robotics applications. Adoption of ROS in the undergraduate curricula is still rare due to its demanding requirements of C++/Python/Java programming skills and familiarity with Linux. Recently, MathWorks released its ROS Toolbox, making it easier to interact with simulators like the Gazebo and ROS-supported physical robots. The MATLAB-ROS-Gazebo simulation platform allows students to utilize other MATLAB Toolboxes, such as Image Processing, Computer Vision, Visualization, and Navigation Toolboxes, for fast …

On Sparse Coding As An Alternate Transform In Video Coding, Michael G. Schimpf

Engineering Ph.D. Theses

In video compression, specifically in the prediction process, a residual signal is calculated by subtracting the predicted from the original signal, which represents the error of this process. This residual signal is usually transformed by a discrete cosine transform (DCT) from the pixel, into the frequency domain. It is then quantized, which filters more or less high frequencies (depending on a quality parameter). The quantized signal is then entropy encoded usually by a context-adaptive binary arithmetic coding engine (CABAC), and written into a bitstream. In the decoding phase the process is reversed. DCT and quantization in combination are efficient tools, …

Assessment Of E-Senses Performance Through Machine Learning Models For Colombian Herbal Teas Classification, Jeniffer Katerine Carrillo, Cristhian Manuel Durán, Juan Martin Cáceres, Carlos Alberto Cuastumal, Jordana Ferreira, José Ramos, Brian Bahder, Martin Oates, Antonio Ruiz

CCE Faculty Articles

This paper describes different E-Senses systems, such as Electronic Nose, Electronic Tongue, and Electronic Eyes, which were used to build several machine learning models and assess their performance in classifying a variety of Colombian herbal tea brands such as Albahaca, Frutos Verdes, Jaibel, Toronjil, and Toute. To do this, a set of Colombian herbal tea samples were previously acquired from the instruments and processed through multivariate data analysis techniques (principal component analysis and linear discriminant analysis) to feed the support vector machine, K-nearest neighbors, decision trees, naive Bayes, and random forests algorithms. The results of the E-Senses were validated using …

An Empirical Investigation Of Network Topology On Majority Illusion, Behavior Adoption, And Polarization, Sreeja Sreekantan Nair

USF Tampa Graduate Theses and Dissertations

Social influence plays a significant role in shaping opinions and behaviors both online and inthe physical world. The ways in which we interact with others and the information we receive can significantly influence our beliefs and attitudes towards different issues. While online social media provide platforms for such interactions, the underlying network structure can impact various social influence phenomena, including majority illusion, behavior adoption, and polarization.

This dissertation examines the role of network topology in three social influence processes:majority illusion, behavior adoption, and polarization. The majority illusion refers to a perception bias that occurs when individuals believe that an opinion …

Only Pick Once-Multi-Object Picking Algorithms For Picking Exact Number Of Objects Efficiently, Zihe Ye

USF Tampa Graduate Theses and Dissertations

Picking up multiple objects at once is a grasping skill that makes a human worker efficient in many domains. However, the State of Arts Robot Grasping skill has not developed such ability to compete with human.This paper presents a system to pick a requested number of objects by only picking once (OPO). The proposed Only-Pick-Once System (OPOS) contains several graph-based algorithms that convert the layout of objects into a graph, cluster nodes in the graph, rank and select candidate clusters based on their topology. OPOS also has a multi-object picking predictor based on a convolutional neural network for estimating how …

A Flexible Ot Testbed For Evaluating On-Device Implementations Of Iec-61850 Goose, Matthew Boeding, Michael Hempel, Hamid Sharif, Juan Lopez Jr., Kalyan Perumalla

Department of Electrical and Computer Engineering: Faculty Publications

The growing convergence of Information Technology and Operational Technology has enhanced communication and visibility across power grids. This, coupled with the growing use of Distributed Energy Resources in power grids, has enhanced the grid capabilities while also creating a larger attack surface for malicious actors. A common protocol vulnerable to these attacks is the IEC-61850 GOOSE protocol due to its low-latency requirements, multicast packet delivery method, and lack of encryption. In this paper, we evaluate the security implications of different hardware implementations of this protocol by contrasting device response and recovery of two commercial off-the-shelf Intelligent Electronic Devices from separate …

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 …

Pii-Codex: A Python Library For Pii Detection, Categorization, And Severity Assessment, Eidan J. Rosado

CCE Faculty Articles

[Summary] There have been a number of advancements in the detection of personal identifiable information (PII) and scrubbing libraries to aid developers and researchers in their detection and anonymization efforts. With the recent shift in data handling procedures and global policy implementations regarding identifying information, it is becoming more important for data consumers to be aware of what data needs to be scrubbed, why it’s being scrubbed, and to have the means to perform said scrubbing. PII-Codex is a collection of extended theoretical, conceptual, and policy works in PII categorization and severity assessment (Milne et al., 2016; Schwartz & Solove, …

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 …

Point Cloud Surface Matching Method Based On Precise Matching Of Critical Point, Xiaojuan Ning, Chunxu Li, Jiahao Wang, Jing Tang, Yinghui Wang, Haiyan Jin

Journal of System Simulation

To solve the low matching efficiency and insufficient accuracy of feature-based point cloud surface matching method during critical point matching, a point cloud surface matching method based on the pairing exaction of critical points is proposed.An improved 3D scale-invariant feature transform(3D-SIFT) algorithm based on curvature information is presented to extract the critical points. Fast point feature histograms(FPFH) feature, the angle between the vector from the center to critical points and the principal direction of the model are taken as the constraints to obtain the exact critical point matching point pair set. The initial matching of the model surface is …

Summary Of Simulation Technology And Its Application In Training Field, Zhiming Qiu, Heng Li, Yufang Zhou, Duzheng Qing

Journal of System Simulation

High-tech weapons operations and battlefield environment become more and more increasingly sophisticated. It is an effective way to resolve the conflicts between huge equipment training cost and limited resources and improve training quality by building networked systematic and intelligent simulation training equipment and system and conducting systematic countermeasure simulation training based on present simulation technologies and training resources. The current situation and trend of the development of system architecture of simulation simulation modeling enemy simulation information system simulation etc are evaluated and summarized. It initially analyses the application and efficacy on the US Navy's normalized training environment typical systems such …

Application Of Digital Twin In Digital Transformation Of Thermal Power Units, Ze Dong, Wei Jiang, Xiaoyan Wang, Lei Liu

Journal of System Simulation

A new state estimation algorithm is proposed to improve the accuracy to obtain the optimal state estimation of distribution network against FDI attack. In the case of phasor measurement units being attacked and the measurement results being alteredthe optimal Kalman estimate can be decomposed into a weighted sum of local state estimates. Focusing on the insecurity of the weighted sum methoda convex optimization based on local estimation is proposed to replace the method and combine the local estimation into a secure state estimation. The simulation results show that the proposed estimator is consistent with the Kalman …

Secure State Estimation Of Distribution Network Based On Kalman Filter Decomposition, Xinghua Liu, Siwen Dong, Jiaqiang Tian

Journal of System Simulation

A new state estimation algorithm is proposed to improve the accuracy to obtain the optimal state estimation of distribution network against FDI attack. In the case of phasor measurement units being attacked and the measurement results being altered,the optimal Kalman estimate can be decomposed into a weighted sum of local state estimates. Focusing on the insecurity of the weighted sum method,a convex optimization based on local estimation is proposed to replace the method and combine the local estimation into a secure state estimation. The simulation results show that the proposed estimator is consistent with the Kalman …