Computer Sciences Commons^™

Multi-Stage Multi-Agv Path Planning With Walk Under Shelves For Robotic Mobile Fulfillment Systems, Teng Li, Peipei Ding, Jinfang Liu

Journal of System Simulation

Abstract: Aiming at the problem of increasing travel time due to turning and obstacle avoidance in robotic mobile fulfillment systems(RMFS) with large-scale multi-AGV path planning, a path planning model with the shortest task completion time is established. A path planning model considering no-load AGV that can pass through the shelf is proposed, and the model is solved by an improving A* algorithm. The AGV operation stage is divided, an turning penalty value is introduced into the A* algorithm to reduce the turning times, and the obstacle avoidance priority with the obstacle avoidance waiting time is set. The simulation results show …

Design And Simulation Of Ts Fuzzy Based Cooperative Control Of Missile Formation, Yexin Zhang, Yu Cheng, Hongyan Yan, Xuwei Fan, Xu Zhang, Yi Tian

Journal of System Simulation

Abstract: Aiming at the requirement of cooperative operation of multi-missile formation, a cooperative control algorithm of multi-missile formation based on Takagi-Sugeno(TS) fuzzy control theory is proposed.The flight speed, trajectory angle and trajectory deflection angle of the missile are taken as parameters in the leader-follower mode missile formation flying system.The local asymptotically stable controller is designed by using the systemlocal linearization of multiple groups of equilibrium pointsduring the whole flight process.Through the expert experience method,the membership function and fuzzy rules for the system are designedwith TS fuzzy theory, and the whole multi-missile cooperative control system is completed and the stability …

Green, Quantized Federated Learning Over Wireless Networks: An Energy-Efficient Design, Minsu Kim, Walid Saad, Mohammad Mozaffari, Mérouane Debbah

Machine Learning Faculty Publications

The practical deployment of federated learning (FL) over wireless networks requires balancing energy efficiency and convergence time due to the limited available resources of devices. Prior art on FL often trains deep neural networks (DNNs) to achieve high accuracy and fast convergence using 32 bits of precision level. However, such scenarios will be impractical for resource-constrained devices since DNNs typically have high computational complexity and memory requirements. Thus, there is a need to reduce the precision level in DNNs to reduce the energy expenditure. In this paper, a green-quantized FL framework, which represents data with a finite precision level in …

Criminal Policy To Combat The Spread Of Electronic Rumours (Under Decree-Law No. 34 Of 2021 On Combating Rumours And Cyber Crimes), Ashraf Kandil

Journal of Police and Legal Sciences

The UAE's role in combating electronic rumors and reducing its dissemination has been demonstrated by the legislative development of IT crime laws in the UAE. The most recent is the issuance of the Federal Decree-Law No. (34) of 2021 concerning the fight against rumors and cybercrime. Otherwise, the problem of the current study revolves around the flexibility of drafting the procedural texts in order to deal with the constant development of the forms and circumstances of spreading rumors, as well as to indicate their effectiveness in reducing their effects. Therefore, the current study aims to identify the criminal policy to …

An Adaptive Multi-Level Quantization-Based Reinforcement Learning Model For Enhancing Uav Landing On Moving Targets, Najmaddin Abo Mosali, Syariful Syafiq Shamsudin, Salama A. Mostafa, Omar Alfandi, Rosli Omar, Najib Al-Fadhali, Mazin Abed Mohammed, R. Q. Malik, Mustafa Musa Jaber, Abdu Saif

All Works

The autonomous landing of an unmanned aerial vehicle (UAV) on a moving platform is an essential functionality in various UAV-based applications. It can be added to a teleoperation UAV system or part of an autonomous UAV control system. Various robust and predictive control systems based on the traditional control theory are used for operating a UAV. Recently, some attempts were made to land a UAV on a moving target using reinforcement learning (RL). Vision is used as a typical way of sensing and detecting the moving target. Mainly, the related works have deployed a deep-neural network (DNN) for RL, which …

Adversarial Pixel Restoration As A Pretext Task For Transferable Perturbations, Hashmat Shadab Malik, Shahina K. Kunhimon, Muzammal Nasser, Salman Khan, Fahad Shahbaz Khan

Computer Vision Faculty Publications

Transferable adversarial attacks optimize adversaries from a pretrained surrogate model and known label space to fool the unknown black-box models. Therefore, these attacks are restricted by the availability of an effective surrogate model. In this work, we relax this assumption and propose Adversarial Pixel Restoration as a self-supervised alternative to train an effective surrogate model from scratch under the condition of no labels and few data samples. Our training approach is based on a min-max objective which reduces overfitting via an adversarial objective and thus optimizes for a more generalizable surrogate model. Our proposed attack is complimentary to our adversarial …

Robustar: Interactive Toolbox Supporting Precise Data Annotation For Robust Vision Learning, Chonghan Chen, Haohan Wang, Leyang Hu, Yuhao Zhang, Shuguang Lyu, Jingcheng Wu, Xinnuo Li, Linjing Sun, Eric Xing

Machine Learning Faculty Publications

We introduce the initial release of our software Robustar, which aims to improve the robustness of vision classification machine learning models through a data-driven perspective. Building upon the recent understanding that the lack of machine learning model’s robustness is the tendency of the model’s learning of spurious features, we aim to solve this problem from its root at the data perspective by removing the spurious features from the data before training. In particular, we introduce a software that helps the users to better prepare the data for training image classification models by allowing the users to annotate the spurious features …

Internal Model Control (Imc)-Based Active And Reactive Power Control Of Brushless Double-Fed Induction Generator With Notch Filter, Ahsanullah Memon, Mohd Wazir Bin Mustafa, Zohaib Hussain Laghari, Touqeer Ahmed Jumani, Waqas Anjum, Shafi Ullah, Muhammad Naveed Aman

School of Computing: Faculty Publications

The increase in demand for electricity and, in particular, green energy has put renewable energy systems at the focal point of energy policy worldwide. The higher reliability of brushless doubly fed induction generators (BDFIGs) makes them suitable for offshore and remote wind energy generation (WEG) applications. Besides, controlling the active and reactive powers in an electrical power system is critical for optimal voltage regulation, reduced power losses, and enhanced utilization of installed equipment. However, the existing literature on BDFIG’s active and reactive power control highlights the poor dynamic response and high transients with harmonic generation during inductive load insertion. It …

Combining Solution Reuse And Bound Tightening For Efficient Analysis Of Evolving Systems, Clay Stevens, Hamid Bagheri

School of Computing: Conference and Workshop Papers

Software engineers have long employed formal verification to ensure the safety and validity of their system designs. As the system changes—often via predictable, domain-specific operations—their models must also change, requiring system designers to repeatedly execute the same formal verification on similar system models. State-of-the-art formal verification techniques can be expensive at scale, the cost of which is multiplied by repeated analysis. This paper presents a novel analysis technique—implemented in a tool called SoRBoT—which can automatically determine domain-specific optimizations that can dramatically reduce the cost of repeatedly analyzing evolving systems. Different from all prior approaches, which focus on either tightening the …

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 …

On The Total Set Chromatic Number Of Graphs, Mark Anthony C. Tolentino, Gerone Russel J. Eugenio, Mari-Jo P. Ruiz

Theory & Applications of Graphs

Given a vertex coloring c of a graph, the neighborhood color set of a vertex is defined to be the set of all of its neighbors’ colors. The coloring c is called a set coloring if any two adjacent vertices have different neighborhood color sets. The set chromatic number χ_s(G) of a graph G is the minimum number of colors required in a set coloring of G. In this work, we investigate a total analog of set colorings; that is, we study set colorings of the total graph of graphs. Given a graph G = (V, E) …

Co-Design To Support Engagement In Activities Of Daily Living And Meaningful Activities For People Living With Dementia, Michael Wilson, Julie Doyle, Ann Marron, Jonathan Turner, Ciaran Nugent, Dympna O'Sullivan

Articles

Dementia is a chronic and progressive neurodegenerative illness, which can lead to significant difficulties in a person’s capacity to perform activities of daily living and engage in meaningful activities. The Smart Dementia Care project aims to establish an understanding of how best to design digital tools that persons with dementia and their carers will find useful and usable for care planning and goal setting. This paper discusses the first phase of this project and describes how co-design is being used to support engagement in activities of daily living and meaningful activities for people living with the early stages of dementia, …

Quertci: A Tool Integrating Github Issue Querying With Comment Classification, Ye Paing, Tatiana Castro Vélez, Raffi Khatchadourian

Publications and Research

Empirical Software Engineering (ESE) researchers study (open-source) project issues and the comments and threads within to discover—among others—challenges developers face when incorporating new technologies, platforms, and programming language constructs. However, such threads accumulate, becoming unwieldy and hindering any insight researchers may gain. While existing approaches alleviate this burden by classifying issue thread comments, there is a gap between searching popular open-source software repositories (e.g., those on GitHub) for issues containing particular keywords and feeding the results into a classification model. This paper demonstrates a research infrastructure tool called QuerTCI that bridges this gap by integrating the GitHub issue comment search …

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.

Reducing Leakage Current And Enhancing Polarization In Multiferroic 3d Supernanocomposites By Microstructure Engineering, Erik Enriquez, Ping Lu, Leigang Li, Bruce Zhang, Haiyan Wang, Quanxi Jia, Aiping Chen

Computer Science Faculty Publications

Multiferroic materials have generated great interest due to their potential as functional device materials. Nanocomposites have been increasingly used to design and generate new functionalities by pairing dissimilar ferroic materials, though the combination often introduces new complexity and challenges unforeseeable in single-phase counterparts. The recently developed approaches to fabricate 3D super-nanocomposites (3D‐sNC) open new avenues to control and enhance functional properties. In this work, we develop a new 3D‐sNC with CoFe2O4 (CFO) short nanopillar arrays embedded in BaTiO3 (BTO) film matrix via microstructure engineering by alternatively depositing BTO:CFO vertically-aligned nanocomposite layers and single-phase BTO layers. This microstructure engineering method allows …

Formal Verification Applications For The Treekem Continuous Group Key Agreement Protocol, Alexander J. Washburn

Theses and Dissertations

The features of Secure Group Messaging, the security guarantees of Message Layer Security, and the TreeKEM protocol designed to satisfy these guarantees and features are explored. A motivation and methodology for verification via explicit model checking is presented. Subsequently, a translation of the TreeKEM protocol into a Promela reference model is described, examining the nuances explicit model checking brings. Finally the results of the formal verification methods are discussed.

Fiesta And Shock-Driven Flows, Brian E. Romero

Mechanical Engineering ETDs

In this study, the interaction of a shock with various gas and particle interfaces is analyzed through simulations using a new, GPU capable, multi-species flow solver, FIESTA (Fast, Interface Evolution, Shocks, and Transport in the Atmosphere), de- veloped for this research. The cases studied include the interaction between a shock and i) a two-dimensional (2D), circular cloud of a dense gas; ii) a 2D curtain of a dense gas; iii) a three-dimensional (3D) cylinder of a dense gas, and iv) a 3D curtain of solid particles.

In simulations of a 2D gas curtain and a 3D gas column, the curtain …

Machine Learning Approach For Classifying Power Outage In Secondary Electric Distribution Network, Stephan Mgaya, Hellen Maziku

Tanzania Journal of Engineering and Technology (TJET)

Power outage is the problem that hinders social and economic development especially for developing countries like Tanzania. Frequent power outages damage electric equipment, and negatively affect the industrial production process. Power outages cannot be completely eradicated due to uncontrolled cause like natural calamities but technical challenges can be managed and hence reducing power outages. The existing manual methods used to locate power outage like customer calls is inefficient and time consuming. On the other hand, modern method like the Advanced Metering Infrastructure (AMI) still faces a challenge in effectively classifying power line outage due to the nature of imbalanced datasets. …

Big Data Analytics Framework For Effective Higher Education Institutions, George Matto

Tanzania Journal of Engineering and Technology (TJET)

There has been an increased dependency on Information and Communication Technologies (ICTs) in undertaking various activities in Higher Education Institutions (HEIs) ecosystems. Because of that, huge volumes of data have increasingly been generated. There have been, for instance, considerable amounts of data generated through electronic platforms involved in students’ admission and registration process, students’ academic records management, teaching and learning data, curriculum related data, and several other administrative data. Analysis of data generated from these platforms stands to give students, lecturers, HEIs Management, policy makers and implementers, and other stakeholders useful insights that would help in improving HEIs’ effectiveness. Unfortunately, …

An Iot Based Worker Safety Helmet Using Cloud Computing Technology, Yuthriya Iddi Khamis, Mahmoud Alawi, Waheed Muhammad Sanya

Tanzania Journal of Engineering and Technology (TJET)

Miner safety and security is a major challenge around the world due to the exposure to toxic gases that are frequently released in underground mines. Miners' health is adversely affected primarily by toxic gases, which endanger the workers' lives. Furthermore, human sensory abilities do not detect these dangerous gases. As a result, this paper proposes a safety monitoring system that includes a temperature sensor, humidity sensor, and gas sensors to detect harmful gases and alert miners to those harmful gases using the smart helmet they wear. These gases are transmitted to the control station via the cloud using Internet of …

Covertness And Timeliness Of Data Collection In Uav-Aided Wireless-Powered Iot, Xingbo Lu, Weiwei Yang, Shihao Yan, Zan Li, Derrick Wing Kwan Ng

Research outputs 2014 to 2021

In this work, we aim to maximize the timeliness of data collection subject to a covertness constraint in unmanned aerial vehicle (UAV)-aided Internet-of-Things (IoT) networks, where a UAV periodically conducts wireless power transfer (WPT) to charge an energy-constrained IoT device and then the IoT device opportunistically sends its collected data to the UAV. To this end, we first derive a lower bound on the covertness constraint and an analytical expression for age of information (AoI) to characterize timeliness. Then, we jointly optimize the UAV’s transmit power for WPT, the WPT duration, and the data transmission duration by considering two practical …

Toward A Standard Formal Semantic Representation Of The Model Card Report, Muhammad Tuan Amith, Licong Cui, Degui Zhi, Kirk Roberts, Xiaoqian Jiang, Fang Li, Evan Yu, Cui Tao

Faculty, Staff and Student Publications

BACKGROUND: Model card reports aim to provide informative and transparent description of machine learning models to stakeholders. This report document is of interest to the National Institutes of Health's Bridge2AI initiative to address the FAIR challenges with artificial intelligence-based machine learning models for biomedical research. We present our early undertaking in developing an ontology for capturing the conceptual-level information embedded in model card reports.

RESULTS: Sourcing from existing ontologies and developing the core framework, we generated the Model Card Report Ontology. Our development efforts yielded an OWL2-based artifact that represents and formalizes model card report information. The current release of …

Cybersecurity Educational Resources For K-12, Debra Bowen, James Jaurez, Nancy Jones, William Reid, Christopher Simpson

Journal of Cybersecurity Education, Research and Practice

There are many resources to guide successful K-12 cybersecurity education. The objective of these resources is to prepare skilled and ethical cybersecurity students at the earliest level to meet the demands of higher-level programs. The goal of this article is to provide, as a starting point, a list of as many currently popular K-12 educational resources as possible. The resources provided are broken into five categories: 1) Career Information, 2) Curriculum, 3) Competitions, 4) CyberCamps, and 5) Labs and Gaming. Each resource listed has a link, the K-12 levels that are supported, whether the resource is free or has a …

Digital Contact Tracing And Privacy, Mahdi Nasereddin, Edward J. Glantz, Galen A. Grimes, Joanne Peca, Michelle Gordon, Mike Bartolacci

Journal of Cybersecurity Education, Research and Practice

Digital contact tracing tools were developed to decrease the spread of COVID-19 by supplementing traditional manual methods. Although these tools have great potential, they were developed rather quickly resulting in tools with varying levels of success. The main issues with these tools are over privacy and who might have access to the information gathered. In general, their effectiveness varied globally, where users expressed privacy concerns associated with sharing identity, illness, and location information. This paper reviews these issues in deployments across Asia, Europe, and the United States. The goal is to begin a discussion that improves the design and development …

Security Simulations In Undergraduate Education: A Review, Joseph Simpson, Aaron Brantly

Journal of Cybersecurity Education, Research and Practice

Several decades of research in simulation and gamification in higher education shows that simulations are highly effective in improving a range of outcomes for students including declarative knowledge and interest in the topic being taught. While there appears to be a broad array of options to provide education in an undergraduate setting related to security, no previous reviews have explored computer-based simulations covering all facets of security. Given the increasing importance and adoption of interdisciplinary educational programs, it is important to take stock of simulations as a tool to broaden the range of problems, perspectives, and solutions presented to students. …

Assessing The Practical Cybersecurity Skills Gained Through Criminal Justice Academic Programs To Benefit Security Operations Centers (Socs), Lucy Tsado, Jung Seob "Scott" Kim

Journal of Cybersecurity Education, Research and Practice

Private-sector and public-sector organizations have increasingly built specific business units for securing company assets, reputation, and lives, known as security operations centers (SOCs). Depending on the organization, these centers may also be referred to as global security operations centers, cybersecurity operations centers, fusion centers, and corporate command centers, among many other names. The concept of centralized function within an organization to improve an organization’s security posture has attracted both the government and the private sectors to either build their own SOCs or hire third-party SOC companies.

In this article, the need for a multidisciplinary approach to cybersecurity education at colleges …

Dynamic Robot Chain Networks For Swarm Foraging, Dohee Lee, Qi Lu, Tsz-Chiu Au

Computer Science Faculty Publications

The objective of foraging robot swarms is to search for and collect resources in an unknown arena as quickly as possible. To avoid the congestion near the central collection zone, we previously proposed an extension to the multiple-place foraging in which robot chains are deployed dynamically so that foraging robots can deliver to the robot chains instead of the central collection zone. However, a robot chain can only reach one location at a time, and congestion can occur at the end of the robot chain. This paper presents an extension to dynamic robot chains called dynamic robot chain networks, which …

Control And Planning For Mobile Manipulators Used In Large Scale Manufacturing Processes, Joshua T. Nguyen

LSU Master's Theses

Sanding operations in industry is one of the few manufacturing tasks that has yet to achieve automation. Sanding tasks require skilled operators that have developed a sense of when a work piece is sufficiently sanded. In order to achieve automation in sanding with robotic systems, this developed sense, or intelligence, that human operators have needs to be understood and implemented in order to achieve, at the minimum, the same quality of work. The system will also need to have the equivalent reach of a human operator and not be constrained to a single, small workspace. This thesis developed solutions for …

Assessment Of 3d Mesh Watermarking Techniques, Neha Sharma, Jeebananda Panda

Journal of Digital Forensics, Security and Law

With the increasing usage of three-dimensional meshes in Computer-Aided Design (CAD), medical imaging, and entertainment fields like virtual reality, etc., the authentication problems and awareness of intellectual property protection have risen since the last decade. Numerous watermarking schemes have been suggested to protect ownership and prevent the threat of data piracy. This paper begins with the potential difficulties that arose when dealing with three-dimension entities in comparison to two-dimensional entities and also lists possible algorithms suggested hitherto and their comprehensive analysis. Attacks, also play a crucial role in deciding a watermarking algorithm so an attack based analysis is also presented …

Learning From Machines: Insights In Forest Transpiration Using Machine Learning Methods, Morgan Thornwell

Dissertations and Theses

Machine learning has been used as a tool to model transpiration for individual sites, but few models are capable of generalizing to new locations without calibration to site data. Using the global SAPFLUXNET database, 95 tree sap flow data sites were grouped using three clustering strategies: by biome, by tree functional type, and through use of a k-means unsupervised clustering algorithm. Two supervised machine learning algorithms, a random forest algorithm and a neural network algorithm, were used to build machine learning models that predicted transpiration for each cluster. The performance and feature importance in each model were analyzed and compared …