Systems and Communications Commons^™

Database Of Academic Institutions: United States K-12

Online Journal of Space Communication

Institutions, research centers and professional associations in the United States that do research and teach content and skills relating to satellite and space communication at the K-12 level.

Zero-Bias Deep Learning Enabled Quick And Reliable Abnormality Detection In Iot, Yongxin Liu, Jian Wang, Jianqiang Li, Shuteng Niu, Houbing Song

Publications

Abnormality detection is essential to the performance of safety-critical and latency-constrained systems. However, as systems are becoming increasingly complicated with a large quantity of heterogeneous data, conventional statistical change point detection methods are becoming less effective and efficient. Although Deep Learning (DL) and Deep Neural Networks (DNNs) are increasingly employed to handle heterogeneous data, they still lack theoretic assurable performance and explainability. This paper integrates zero-bias DNN and Quickest Event Detection algorithms to provide a holistic framework for quick and reliable detection of both abnormalities and time-dependent abnormal events in Internet of Things (IoT).We first use the zero bias dense …

A Bibliometric Survey On Antipodal Vivaldi Antenna, Sumit Kumar, Amruta S. Dixit

Library Philosophy and Practice (e-journal)

In this paper bibliometric survey is presented on Antipodal Vivaldi Antenna. The Antipodal Vivaldi Antenna is a broad band and has symmetric E plane and H plane. It has been used extensively in radars, wireless communication and dual polarization applications. The antipodal Vivaldi antenna has significant researches in biomedical imaging, optical lens, Ground-Penetrating Radar (GPR) System, detecting cancer, 5G communications etc. The bibliometric analysis is done for the reason to understand the reach of antipodal Vivaldi antenna and performance enhancement analysis worldwide. The Scopus and web of science are used for accomplishing this survey. The study focuses on 449 documents …

Metamaterials In 5g Antenna Designs: A Bibliometric Survey, Hema D. Raut, Laxmikant K. Shevada, Rajeshwari R. Malekar, Amruta S. Dixit, Sumit Kumar

Library Philosophy and Practice (e-journal)

The demand of high gain and wideband compact antenna designs are gaining importance to fulfil the need of 5G communication systems. This has opened the doors for the researchers to explore 5G antennas incorporating metamaterials as they can meet the requirement of high gain and wideband compact antennas. Overview of various metamaterial-based antenna designs including Electromagnetic Band Gap (EBG), artificial Magnetic Conductor (AMC), Frequency Selective Surface (FSS) and Partially Reflective Surface (PRS) are discussed in the paper. The paper primarily focuses on bibliometric survey of various types of 5G metamaterial antennas in terms of number of documents published, leading universities …

Guest Editorial: Edge Intelligence For Beyond 5g Networks, Yan Zhang, Zhiyong Feng, Hassnaa Moustafa, Feng Ye, Usman Javaid, Chunfen Cui

Electrical and Computer Engineering Faculty Publications

Beyond fifth-generation (B5G) networks, or so-called "6G", is the next-generation wireless communications systems that will radically change how Society evolves. Edge intelligence is emerging as a new concept and has extremely high potential in addressing the new challenges in B5G networks by providing mobile edge computing and edge caching capabilities together with Artificial Intelligence (AI) to the proximity of end users. In edge intelligence empowered B5G networks, edge resources are managed by AI systems for offering powerful computational processing and massive data acquisition locally at edge networks. AI helps to obtain efficient resource scheduling strategies in a complex environment with …

Distance-Based Formation Control Using Decentralized Sensing With Infrared Photodiodes, Steven Williams

LSU Master's Theses

This study presents an onboard sensor system for determining the relative positions of mobile robots, which is used in decentralized distance-based formation controllers for multi-agent systems. This sensor system uses infrared photodiodes and LEDs; its effective use requires coordination between the emitting and detecting robots. A technique is introduced for calculating the relative positions based on photodiode readings, and an automated calibration system is designed for future maintenance. By measuring the relative positions of their neighbors, each robot is capable of running an onboard formation controller, which is independent of both a centralized controller and a global positioning-like system (e.g., …

Adventuring Into Complexity By Exploring Data: From Complicity To Sustainability, Tim Lutz

Northeast Journal of Complex Systems (NEJCS)

Problems of sustainability are typically represented by major present-day challenges such as climate change, biodiversity loss, and environmental and social injustice. Framed this way, sustainable lives and societies depend on finding solutions to each problem. From another perspective, there is only one problem behind them all, stated by Gregory Bateson as: “…the difference between how nature works and the way people think,” and complexity provides a way to define and approach this problem. I extend Edgar Morin’s conceptions of restricted and general complexity into pedagogy to address problems of simplicity and reductionist teaching. The proposed pedagogy is based on long …

Calculate The Reliability Of The Bts-Bsc Network With The Reserved Line Connection, Dilmurod Davronbekov, Utkir Karimovich Matyokubov

Chemical Technology, Control and Management

The issue of reserving communication lines between the base station and the mobile network base station controller which are considered as one system is considered. Analytical expressions have been developed for calculating the reliability of the system for various options for backing up communication lines between the base station and the base station controller. The results of research and calculations of reliability for ten different types of backup communication lines of the base station and the base station controller are presented.

Flocc: From Agent-Based Models To Interactive Simulations On The Web, Scott Donaldson

Northeast Journal of Complex Systems (NEJCS)

Agent-based modeling (ABM) is a computational technique wherein systems are represented through the actions and interactions of many individual entities (‘agents’) over time. ABM often attempts to elucidate the unpredictable, high-level behavior of systems through the predictable, low-level behavior of actors within the system. There are currently few software or frameworks for ABM that allow modelers to design and build interactive models on the web, for a wide audience as well as a scientifically literate audience well-versed in complexity, models, and simulations. Flocc is a novel framework for agent-based modeling written in JavaScript, the lingua franca programming language of the …

Integrated Cyberattack Detection And Handling For Nonlinear Systems With Evolving Process Dynamics Under Lyapunov-Based Economic Model Predictive Control, Keshav Kasturi Rangan, Henrique Oyama, Helen Durand

Chemical Engineering and Materials Science Faculty Research Publications

Safety-critical processes are becoming increasingly automated and connected. While automation can increase effciency, it brings new challenges associated with guaranteeing safety in the presence of uncertainty especially in the presence of control system cyberattacks. One of the challenges for developing control strategies with guaranteed safety and cybersecurity properties under suffcient conditions is the development of appropriate detection strategies that work with control laws to prevent undetected attacks that have immediate closed-loop stability consequences. Achieving this, in the presence of uncertainty brought about by plant/model mismatch and process dynamics that can change with time, requires a fundamental understanding of the characteristics …

Network-Based Analysis Of Early Pandemic Mitigation Strategies: Solutions, And Future Directions, Pegah Hozhabrierdi, Raymond Zhu, Maduakolam Onyewu, Sucheta Soundarajan

Northeast Journal of Complex Systems (NEJCS)

Despite the large amount of literature on mitigation strategies for pandemic spread, in practice, we are still limited by naive strategies, such as lockdowns, that are not effective in controlling the spread of the disease in long term. One major reason behind adopting basic strategies in real-world settings is that, in the early stages of a pandemic, we lack knowledge of the behavior of a disease, and so cannot tailor a more sophisticated response. In this study, we design different mitigation strategies for early stages of a pandemic and perform a comprehensive analysis among them. We then propose a novel …

The Use Of Supercapacitors To Stabilize The Power Supply System Of The Base Station Of Mobile Communication, Dilmurod Abdujalilovich Davronbekov, Utkir Karimovich Matyokubov

Scientific-technical journal

In this study, an analysis of the current status and available outages of the mobile communication base station power supply system was performed. The effects of these outages on the power supply system have been studied and it has been shown that batteries may not be an ideal solution as a backup source. Also, the issue of the introduction of renewable energy sources in the base station power supply system of the mobile communication system and its shortcomings are mentioned. In order to overcome these problems and stabilize the power changes in the battery auxiliary element and the power supply …

The Use Of Supercapacitors To Stabilize The Power Supply System Of The Base Station Of Mobile Communication, Dilmurod Abdujalilovich Davronbekov, Utkir Karimovich Matyokubov

Scientific-technical journal

In this study, an analysis of the current status and available outages of the mobile communication base station power supply system was performed. The effects of these outages on the power supply system have been studied and it has been shown that batteries may not be an ideal solution as a backup source. Also, the issue of the introduction of renewable energy sources in the base station power supply system of the mobile communication system and its shortcomings are mentioned. In order to overcome these problems and stabilize the power changes in the battery auxiliary element and the power supply …

Virtual Network Function Embedding Under Nodal Outage Using Deep Q-Learning, Swarna Bindu Chetty, Hamed Ahmadi, Sachin Sharma, Avishek Nag

Articles

With the emergence of various types of applications such as delay-sensitive applications, future communication networks are expected to be increasingly complex and dynamic. Network Function Virtualization (NFV) provides the necessary support towards efficient management of such complex networks, by virtualizing network functions and placing them on shared commodity servers. However, one of the critical issues in NFV is the resource allocation for the highly complex services; moreover, this problem is classified as an NP-Hard problem. To solve this problem, our work investigates the potential of Deep Reinforcement Learning (DRL) as a swift yet accurate approach (as compared to integer linear …

Are Terrorist Networks Just Glorified Criminal Cells?, Elie Alhajjar, Ryan Fameli, Shane Warren

Northeast Journal of Complex Systems (NEJCS)

The notions of organized crime and terrorism have an old and rich history around the globe. Researchers and practitioners have been studying events and phenomena related to these notions for a long time. There are pointers in the literature in which it is misleading to see the unfair comparison between terrorist and criminal networks with the argument that all actors involved in these networks are simply evil individuals. In this paper, we conduct a systematic study of the operational structure of such networks from a network science perspective. We highlight some of the major differences between them and support our …

Channel Estimation In Multi-User Massive Mimo Systems By Expectation Propagation Based Algorithms, Mohammed Rashid

LSU Doctoral Dissertations

Massive multiple input multiple output (MIMO) technology uses large antenna arrays with tens or hundreds of antennas at the base station (BS) to achieve high spectral efficiency, high diversity, and high capacity. These benefits, however, rely on obtaining accurate channel state information (CSI) at the receiver for both uplink and downlink channels. Traditionally, pilot sequences are transmitted and used at the receiver to estimate the CSI. Since the length of the pilot sequences scale with the number of transmit antennas, for massive MIMO systems downlink channel estimation requires long pilot sequences resulting in reduced spectral efficiency and the so-called pilot …

Color-Compressive Bilateral Filter And Nonlocal Means For High-Dimensional Images, Christina Karam, Kenjiro Sugimoto, Keigo Hirakawa

Electrical and Computer Engineering Faculty Publications

We propose accelerated implementations of bilateral filter (BF) and nonlocal means (NLM) called color-compressive bilateral filter (CCBF) and color-compressive nonlocal means (CCNLM). CCBF and CCNLM are random filters, whose Monte-Carlo averaged output images are identical to the output images of conventional BF and NLM, respectively. However, CCBF and CCNLM are considerably faster because the spatial processing of multiple color channels are combined into a single random filtering process. This implies that the complexity of CCBF and CCNLM is less sensitive to color dimension (e.g., hyperspectral images) relatively to other BF and NLM methods. We experimentally verified that the execution time …

Deep Learning For Anisoplanatic Optical Turbulence Mitigation In Long-Range Imaging, Matthew A. Hoffmire, Russell C. Hardie, Michael A. Rucci, Richard Van Hook, Barry K. Karch

Electrical and Computer Engineering Faculty Publications

We present a deep learning approach for restoring images degraded by atmospheric optical turbulence. We consider the case of terrestrial imaging over long ranges with a wide field-of-view. This produces an anisoplanatic imaging scenario where turbulence warping and blurring vary spatially across the image. The proposed turbulence mitigation (TM) method assumes that a sequence of short-exposure images is acquired. A block matching (BM) registration algorithm is applied to the observed frames for dewarping, and the resulting images are averaged. A convolutional neural network (CNN) is then employed to perform spatially adaptive restoration. We refer to the proposed TM algorithm as …

Latency Optimization In Smart Meter Networks, Amr Kassab

Theses and Dissertations

In this thesis, we consider the problem of smart meter networks with data collection to a central point within acceptable delay and least consumed energy. In smart metering applications, transferring and collecting data within delay constraints is crucial. IoT devices are usually resource-constrained and need reliable and energy-efficient routing protocol. Furthermore, meters deployed in lossy networks often lead to packet loss and congestion. In smart grid communication, low latency and low energy consumption are usually the main system targets. Considering these constraints, we propose an enhancement in RPL to ensure link reliability and low latency. The proposed new additive composite …

Differential Privacy For Industrial Internet Of Things: Opportunities, Applications And Challenges, Bin Jiang, Houbing Song, Jianqiang Li, Guanghui Yue

Publications

The development of Internet of Things (IoT) brings new changes to various fields. Particularly, industrial Internet of Things (IIoT) is promoting a new round of industrial revolution. With more applications of IIoT, privacy protection issues are emerging. Specially, some common algorithms in IIoT technology such as deep models strongly rely on data collection, which leads to the risk of privacy disclosure. Recently, differential privacy has been used to protect user-terminal privacy in IIoT, so it is necessary to make in-depth research on this topic. In this paper, we conduct a comprehensive survey on the opportunities, applications and challenges of differential …

Enhanced Interest Aware Peoplerank For Opportunistic Mobile Social Networks, Yosra Saad Shahin

Theses and Dissertations

Network infrastructures are being continuously challenged by increased demand, resource-hungry applications, and at times of crisis when people need to work from homes such as the current Covid-19 epidemic situation, where most of the countries applied partial or complete lockdown and most of the people worked from home. Opportunistic Mobile Social Networks (OMSN) prove to be a great candidate to support existing network infrastructures. However, OMSNs have copious challenges comprising frequent disconnections and long delays. we aim to enhance the performance of OMSNs including delivery ratio and delay. We build upon an interest-aware social forwarding algorithm, namely Interest Aware PeopleRank …

Reinforcement Learning-Based Access Schemes In Cognitive Radio Networks, Ehab Maged Elguindy

Theses and Dissertations

In this thesis, we propose different MAC protocols based on three Reinforcement Learning (RL) approaches, namely Q-Learning, Deep Q-Network (DQN), and Deep Deterministic Policy Gradient (DDPG). We exploit the primary user (PU) feedback, in the form of ARQ and CQI bits, to enhance the performance of the secondary user (SU) MAC protocols. Exploiting the PU feedback information can be applied on the top of any SU sensing-based MAC protocol. Our proposed model relies on two main pillars, namely, an infinite-state Partially Observable Markov Decision Process (POMDP) to model the system dynamics besides a queuing-theoretic model for the PU queue; the …

An Optimized Lte-Based Technique For Drone Base Station 3d Placement And Resource Allocation In Delay-Sensitive M2m Networks, Ahmed Fahim

Theses and Dissertations

The deployment of drone-mounted communication systems has received increasing interest and attention recently as it allows significant improvement to the network access capacity and coverage. Many applications can benefit from such deployments in particular machine-to-machine (M2M) communications. Drones are expected to facilitate extending wireless network access for both human users and the smart machine-type-communication devices (MTCDs) that have strict and diverse quality of service (QoS) requirements. In this thesis, we propose an optimal solution for the dynamic placement of an LTE drone-mounted base station to maximize the coverage of MTCDs deployed over a large geographical area in disaster situations or …

Time Series Data Analysis Using Machine Learning-(Ml) Approach, Mvv Prasad Kantipudi Dr., Pradeep Kumar N.S Dr., S.Sreenath Kashyap Dr., Ss Anusha Vemuri Ms

Library Philosophy and Practice (e-journal)

Healthcare benefits related to continuous monitoring of human movement and physical activity can potentially reduce the risk of accidents associated with elderly living alone at home. Based on the literature review, it is found that many studies focus on human activity recognition and are still active towards achieving practical solutions to support the elderly care system. The proposed system has introduced a joint approach of machine learning and signal processing technology for the recognition of human's physical movements using signal data generated by accelerometer sensors. The framework adopts the concept of DSP to select very descriptive feature sets and uses …

Iotiwc: Iot Industrial Wireless Controller, Mohammad Abdellatif, Tassnim , Awad, Walaa Mohamed

Electrical Engineering

Industrial controller systems are crucially essential to the cutting edge power systems industries. Industrial controllers link the integrated technologies of a computer, communication devices, and electric devices. The communication systems act as a physical intermediary layer for transferring, controlling, and acquirement of data within the system from distant locations. This chapter discusses the Supervisory Control And Data Acquisition (SCADA) systems and proposes a similar system that is an IoT based industrial wireless controller. The proposed system can control multiple devices through the network without the need to be physically near the devices. Because it uses simple and cheap devices, the …

Dales Objects: A Large Scale Benchmark Dataset For Instance Segmentation In Aerial Lidar, Nina M. Singer, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

We present DALES Objects, a large-scale instance segmentation benchmark dataset for aerial lidar. DALES Objects contains close to half a billion hand-labeled points, including semantic and instance segmentation labels. DALES Objects is an extension of the DALES (Varney et al., 2020) dataset, adding additional intensity and instance segmentation annotation. This paper provides an overview of the data collection, preprocessing, hand-labeling strategy, and final data format. We propose relevant evaluation metrics and provide insights into potential challenges when evaluating this benchmark dataset. Finally, we provide information about how researchers can access the dataset for their use at go.udayton.edu/dales3d.

6g Enabled Smart Infrastructure For Sustainable Society: Opportunities, Challenges, And Research Roadmap, Abotinam Lucky Imoize, Oluwadara Adedeji, Nistha Tandiya, Sachin Shetty

VMASC Publications

The 5G wireless communication network is currently faced with the challenge of limited data speed exacerbated by the proliferation of billions of data-intensive applications. To address this problem, researchers are developing cutting-edge technologies for the envisioned 6G wireless communication standards to satisfy the escalating wireless services demands. Though some of the candidate technologies in the 5G standards will apply to 6G wireless networks, key disruptive technologies that will guarantee the desired quality of physical experience to achieve ubiquitous wireless connectivity are expected in 6G. This article first provides a foundational background on the evolution of different wireless communication standards to …

Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta

Electrical and Computer Engineering Faculty Publications

Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning, and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent, and overall effective.

A Two-Level Information Modelling Translation Methodology And Framework To Achieve Semantic Interoperability In Constrained Geoobservational Sensor Systems, Paul Stacey

Doctoral

As geographical observational data capture, storage and sharing technologies such as in situ remote monitoring systems and spatial data infrastructures evolve, the vision of a Digital Earth, first articulated by Al Gore in 1998 is getting ever closer. However, there are still many challenges and open research questions. For example, data quality, provenance and heterogeneity remain an issue due to the complexity of geo-spatial data and information representation.

Observational data are often inadequately semantically enriched by geo-observational information systems or spatial data infrastructures and so they often do not fully capture the true meaning of the associated datasets. Furthermore, data …

Hard Hat Ambient Liability Observer (Halo), Hunter Hykes, Nathan Kish, Brian Thomson

Williams Honors College, Honors Research Projects

Capturing workplace incident information is a growing area of concern for most companies. To assist with this, the design team proposed the H.A.L.O. This design uses time-of-flight sensors connected to LEDs to create a proximity-based hazard warning system. It also records incident data using an accelerometer and micro-SD card. This helps workers avoid some of the most common workplace injuries, slips, trips, and falls and accidental collisions.

Students have created a design with engineering, and marketing requirements that accomplish this task. The proposed design allows for this monitoring and mitigation systems to be attached to hard hats. Team members developed …