Systems and Communications Commons^™

Levitate, Stephen Hargreaves, Isaac Hammonds, Russel Pease, Joseph Morris

Williams Honors College, Honors Research Projects

Levitate is designed to create a healthier work environment by providing a way of entertaining a worker while not distracting them. To fulfill this task, the device needs to be interesting and self-sufficient while not being overly flashy. To complete this task, Levitate is designed so that it is able to lift a platform from rest using magnetism and that will be able to stabilize itself using electromagnets. It initiates this process by lifting the permanent magnet using servo motors. Then, the device is able to achieve stability through the use of hall sensors feeding their results to the board …

Urban Underground Infrastructure Monitoring Iot: The Path Loss Analysis, Abdul Salam, Syed Shah

Faculty Publications

The extra quantities of wastewater entering the pipes can cause backups that result in sanitary sewer overflows. Urban underground infrastructure monitoring is important for controlling the flow of extraneous water into the pipelines. By combining the wireless underground communications and sensor solutions, the urban underground IoT applications such as real time wastewater and storm water overflow monitoring can be developed. In this paper, the path loss analysis of wireless underground communications in urban underground IoT for wastewater monitoring has been presented. It has been shown that the communication range of up to 4 kilometers can be achieved from an underground …

An Underground Radio Wave Propagation Prediction Model For Digital Agriculture, Abdul Salam

Faculty Publications

Underground sensing and propagation of Signals in the Soil (SitS) medium is an electromagnetic issue. The path loss prediction with higher accuracy is an open research subject in digital agriculture monitoring applications for sensing and communications. The statistical data are predominantly derived from site-specific empirical measurements, which is considered an impediment to universal application. Nevertheless, in the existing literature, statistical approaches have been applied to the SitS channel modeling, where impulse response analysis and the Friis open space transmission formula are employed as the channel modeling tool in different soil types under varying soil moisture conditions at diverse communication distances …

A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language …

A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak

Faculty Publications

The realization of Internet of Underground Things (IOUT) relies on the establishment of reliable communication links, where the antenna becomes a major design component due to the significant impacts of soil. In this paper, a theoretical model is developed to capture the impacts of change of soil moisture on the return loss, resonant frequency, and bandwidth of a buried dipole antenna. Experiments are conducted in silty clay loam, sandy, and silt loam soil, to characterize the effects of soil, in an indoor testbed and field testbeds. It is shown that at subsurface burial depths (0.1-0.4m), change in soil moisture impacts …

Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Given that there are numerous amounts of unlabeled data available for usage in training neural networks, it is desirable to implement a neural network architecture and training paradigm to maximize the ability of the latent space representation. Through multiple perspectives of the latent space using adversarial learning and autoencoding, data requirements can be reduced, which improves learning ability across domains. The entire goal of the proposed work is not to train exhaustively, but to train with multiperspectivity. We propose a new neural network architecture called Active Recall Network (ARN) for learning with less labels by optimizing the latent space. This …

Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai

Electrical and Computer Engineering Faculty Publications

To reduce the increasingly congestion in cities, it is essential for intelligent transportation system (ITS) to accurately forecast the short-term traffic flow to identify the potential congestion sites. In recent years, the emerging deep learning method has been introduced to design traffic flow predictors, such as recurrent neural network (RNN) and long short-term memory (LSTM), which has demonstrated its promising results. In this paper, different from existing work, we study the temporal convolutional network (TCN) and propose a deep learning framework based on TCN model for short-term city-wide traffic forecast to accurately capture the temporal and spatial evolution of traffic …

Dual Graphene Patch Antenna For Ka Band Satellite Applications, Mohammed Amin Rabah, Mohammed Bekhti

International Journal of Aviation, Aeronautics, and Aerospace

Currently; grapheme offers a new opportunity to use in space technology and this is due to its amazing properties like conductivity, strength, flexibility and transparency which allows us to exploit new generation of ultra-fast nanoscale components; Since future wireless communication techniques are geared towards the use of the high frequency spectrum and many recent research prove this trend. This letter presents a proposal for design of a dual graphene-based antenna to use in new communication techniques in Ka band, where the proposed antenna can work for uplink and dowlink frequencies at same time since it has return loss less then …

Recurrent Residual U-Net For Medical Image Segmentation, Md Zahangir Alom, Christopher Yakopcic, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

Deep learning (DL)-based semantic segmentation methods have been providing state-of-the-art performance in the past few years. More specifically, these techniques have been successfully applied in medical image classification, segmentation, and detection tasks. One DL technique, U-Net, has become one of the most popular for these applications. We propose a recurrent U-Net model and a recurrent residual U-Net model, which are named RU-Net and R2U-Net, respectively. The proposed models utilize the power of U-Net, residual networks, and recurrent convolutional neural networks. There are several advantages to using these proposed architectures for segmentation tasks. First, a residual unit helps when training deep …

A Survey Of Techniques For Mobile Service Encrypted Traffic Classification Using Deep Learning, Pan Wang, Xuejiao Chen, Feng Ye, Zhixin Sun

Electrical and Computer Engineering Faculty Publications

The rapid adoption of mobile devices has dramatically changed the access to various net- working services and led to the explosion of mobile service traffic. Mobile service traffic classification has been a crucial task that attracts strong interest in mobile network management and security as well as machine learning communities for past decades. However, with more and more adoptions of encryption over mobile services, it brings a lot of challenges about mobile traffic classification. Although classical machine learning approaches can solve many issues that port and payload-based methods cannot solve, it still has some limitations, such as time-consuming, costly handcrafted …

Study Of Physical Layer Security And Teaching Methods In Wireless Communications, Zhijian Xie, Christopher Horne

KSU Proceedings on Cybersecurity Education, Research and Practice

In most wireless channels, the signals propagate in all directions. For the communication between Alice and Bob, an Eavesdropper can receive the signals from both Alice and Bob as far as the Eavesdropper is in the range determined by the transmitting power. Through phased array antenna with beam tracking circuits or cooperative iteration, the signals are confined near the straight line connecting the positions of Alice and Bob, so it will largely reduce the valid placement of an Eavesdropper. Sometimes, this reduction can be prohibitive for Eavesdropper to wiretap the channel since the reduced space can be readily protected. Two …

The Design, Building, And Testing Of A Constant On Discreet Jammer For The Ieee 802.15.4/Zigbee Wireless Communication Protocol, Alexandre J. Marette

Master's Theses

As wireless protocols become easier to implement, more products come with wireless connectivity. This latest push for wireless connectivity has left a gap in the development of the security and the reliability of some protocols. These wireless protocols can be used in the growing field of IoT where wireless sensors are used to share information throughout a network. IoT is being implemented in homes, agriculture, manufactory, and in the medical field. Disrupting a wireless device from proper communication could potentially result in production loss, security issues, and bodily harm. The 802.15.4/ZigBee protocol is used in low power, low data rate, …

Adaptation Of Vt-Dbr Lasers For Lidar, Luke Horowitz

Master's Theses

Vernier Tuned Distributed Bragg Reflector (VT-DBR) lasers have had great success in the field of Swept-Source Optical Coherence Tomography (SS-OCT) due to their continuous and nearly 40 nm wavelength tuning range in a single longitudinal mode. Fast sweeps allow for real time imaging with micrometer resolution at a distance of a few centimeters. While this laser has proven quite useful as a medical imaging tool via OCT, it has yet to similarly prove itself for general light detection and ranging (LIDAR) applications due to range limitations that arise from a finite laser coherence length. The goal of this thesis is …

Dual Source Excitation Rectangular Waveguide Design And Evaluation For The Measurement Of Electromagnetic Material Properties, Daniel K. Koch

Theses and Dissertations

Broadband material parameter measurements are essential in understanding how materials interact with electromagnetic waves. Traditional rectangular waveguide material measurement systems are bandwidth limited. This results in multiple rectangular waveguides of different sizes used to conduct broadband material parameter extraction. Efforts to produce a broadband rectangular waveguide have focused on the inclusion of different guiding structures in the waveguide body. These designs have the drawback of requiring precise machining and time-consuming sample preparation. This research proposes a new broadband rectangular waveguide design which uses a dual source excitation design. This is enabled by the fact that rectangular waveguides are linear time …

Passive Self-Interference Suppression For Single Channel Full-Duplex Operation, Adam Narbudowicz, Giuseppe Ruvio, Max Ammann

Articles

Full duplex radios have become a topic of increased interest in the wireless communications community. As part of this development, many efforts were directed to passively decrease the self-interference level at the antenna outputs. However, in many proposed solutions transmission and reception occur through different propagation channels. This paper demonstrates and quantifies the negative impact of channel differentiation on pivotal applications of full-duplex radio, such as cognitive radio. Antenna designs used for self-interference suppression in full-duplex radio architectures are analyzed. In order to ensure that transmission and reception occur within the same propagation channel, the use of the envelope correlation …

Datanet: Deep Learning Based Encrypted Network Traffic Classification In Sdn Home Gateway, Pan Wang, Feng Ye, Xuejiao Chen, And Yi Qian

Electrical and Computer Engineering Faculty Publications

A smart home network will support various smart devices and applications, e.g., home automation devices, E-health devices, regular computing devices, and so on. Most devices in a smart home access the Internet through a home gateway (HGW). In this paper, we propose a software-defined- network (SDN)-HGW framework to better manage distributed smart home networks and support the SDN controller of the core network. The SDN controller enables efficient network quality-of-service management based on real-time traffic monitoring and resource allocation of the core network. However, it cannot provide network management in distributed smart homes. Our proposed SDN-HGW extends the control to …

Handwritten Bangla Character Recognition Using The State-Of-The-Art Deep Convolutional Neural Networks, Md Zahangir Alom, Paheding Sidike, Mahmudul Hasan, Tarek M. Taha, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In spite of advances in object recognition technology, handwritten Bangla character recognition (HBCR) remains largely unsolved due to the presence of many ambiguous handwritten characters and excessively cursive Bangla handwritings. Even many advanced existing methods do not lead to satisfactory performance in practice that related to HBCR. In this paper, a set of the state-of-the-art deep convolutional neural networks (DCNNs) is discussed and their performance on the application of HBCR is systematically evaluated. The main advantage of DCNN approaches is that they can extract discriminative features from raw data and represent them with a high degree of invariance to object …

The Silver Lining: A Novel, Inkjet-Printed Mesh Coplanar-Slot Antenna For The Uhf Band, Anastasios C. Karles

Undergraduate Research Posters

The Federal Communications Commission (FCC) is opening up frequencies within the television range (400MHz to 700MHz) of the Ultra High Frequency (UHF) band for use in emerging technologies, such as cognitive radio networks and machine-to-machine communication. In order for manufacturers to produce affordable antennas that can be used in these emerging technologies, inexpensive antennas are required that meet these new spectrum needs. This paper presents a mesh coplanar-slot bowtie patch antenna fabricated using commercially available inkjet-printing technology. Two antennas were fabricated: a 27x21cm copper FR4 antenna with .25mm lines and a 27x21cm silver antenna with 2mm lines fabricated using inkjet-printing. …

Coupling Radio Frequency Energy Via The Embedded Rebar Cage In A Reinforced Concrete Structure For The Purpose Of Concrete Degradation Sensing, Ryan Campiz

UNF Graduate Theses and Dissertations

This study focuses on utilizing an energy harvesting system in which a dedicated Radio Frequency (RF) power source transmits RF power via rebar in a reinforced concrete column. The RF power is received and decoupled by a receiver, and is then rectified, boosted, and stored as electrical energy in a supercapacitor, later to be used to make measurements, process data, and communicate to the source via rebar. Two design attempts are presented in this study: (a) one uses single line conduction at 2.4 GHz for RF power transfer; (b) the other uses a more conventional two-line conduction at 8.0 kHz …

Coexistence And Secure Communication In Wireless Networks, Saygin Bakşi

Electrical & Computer Engineering Theses & Dissertations

In a wireless system, transmitted electromagnetic waves can propagate in all directions and can be received by other users in the system. The signals received by unintended receivers pose two problems; increased interference causing lower system throughput or successful decoding of the information which removes secrecy of the communication. Radio frequency spectrum is a scarce resource and it is allocated by technologies already in use. As a result, many communication systems use the spectrum opportunistically whenever it is available in cognitive radio setting or use unlicensed bands. Hence, efficient use of spectrum by sharing users is crucial to increase maximize …

Gui For Mri-Compatible Neural Stimulator And Recorder, Soo Han Soon, Nishant Babaria, Ranajay Mandal, Zhongming Liu

The Summer Undergraduate Research Fellowship (SURF) Symposium

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are useful tools to analyze brain activities given active stimulation. However, the electromagnetic noise from the MRI distorts the brain signal recording and damages the subject with excessive heat generated on the electrodes attached to the skin. MRI-compatible recording and stimulation systems previously developed at LIBI lab were capable of removing the electromagnetic noise during the imaging process. Previously, the hardware systems had required the integrative software that could control both circuits simultaneously and enable users to easily change recording and stimulation parameters. Graphical user interface (GUI) programmed with computer language informed …

On-Chip Training Of Memristor Crossbar Based Multi-Layer Neural Networks, Raqibul Hasan, Tarek M. Taha, Christopher Yakopcic

Electrical and Computer Engineering Faculty Publications

Memristor crossbar arrays carry out multiply-add operations in parallel in the analog domain, and so can enable neuromorphic systems with high throughput at low energy and area consumption. On-chip training of these systems have the significant advantage of being able to get around device variability and faults. This paper presents on-chip training circuits for multi-layer neural networks implemented using a single crossbar per layer and two memristors per synapse. Using two memristors per synapse provides double the synaptic weight precision when compared to a design that uses only one memristor per synapse. Proposed on-chip training system utilizes the back propagation …

Two Senior Projects: 2.4 Ghz, 40% Efficiency Radio Frequency Amplifier, Ieee Design Contest, & Design And Implementation Of A Software Costas Loop For Audio Frequencies, Robert J. Tong

Electrical Engineering

How to Read this Document:

This document combines two senior project reports. The first senior project documents designing a class AB RF amplifier. The second, discusses the design and implementation of a software Costas loop for audio frequencies. The first report begins on the next page, while the Costas loop report starts on page 24. The two reports are orthogonal from one another. It is not a prerequisite to read the RF amplifier report before reading the Costas loop report. This document is merely two reports combined into one document. The second report, about the Costas loop, was written as …

Data Logging System For A Synthetic Aperture Radar Unit, Nicholas J. Testin, Philip Davis, Ian Dorell, Alexander Gillespie

KSU Journey Honors College Capstones and Theses

A small, existing radar unit lacked the ability to automatically store the data it was receiving, which made its use clunky and cumbersome. A system was constructed to allow an on-board microprocessor to track distance traveled, and automatically store the data output from the radar unit to a portable memory unit for later data processing. Distance traveled is determined using a specially designed mobile cart, which electronically converts the rotation of a wheel into an electrical signal while also providing stability for taking accurate radar measurements. The output data from the radar unit is stored as a properly-formatted sound file …

Identity‐Based Schemes For A Secured Big Data And Cloud Ict Framework In Smart Grid System, Feng Ye, Yi Qian, Rose Qingyang Hu

Electrical and Computer Engineering Faculty Publications

Smart grid is an intelligent cyber physical system (CPS). The CPS generates a massive amount of data for efficient grid operation. In this paper, a big data‐driven, cloud‐based information and communication technology (ICT) framework for smart grid CPS is proposed. The proposed ICT framework deploys hybrid cloud servers to enhance scalability and reliability of smart grid communication infrastructure. Because the data in the ICT framework contains much privacy of customers and important data for automated controlling, the security of data transmission must be ensured. In order to secure the communications over the Internet in the system, identity‐based schemes are proposed …

Identity-Based Schemes For A Secured Big Data And Cloud Ict Framework In Smart Grid System, Feng Ye, Yi Qian, Rose Qingyang Hu

Electrical and Computer Engineering Faculty Publications

Smart grid is an intelligent cyber physical system (CPS). The CPS generates a massive amount of data for efficient grid operation. In this paper, a big data-driven, cloud-based information and communication technology (ICT) framework for smart grid CPS is proposed. The proposed ICT framework deploys hybrid cloud servers to enhance scalability and reliability of smart grid communication infrastructure. Because the data in the ICT framework contains much privacy of customers and important data for automated controlling, the security of data transmission must be ensured. In order to secure the communications over the Internet in the system, identity-based schemes are proposed …

Analysis Of Various Classification Techniques For Computer Aided Detection System Of Pulmonary Nodules In Ct, Barath Narayanan Narayanan, Russell C. Hardie, Temesguen Messay

Electrical and Computer Engineering Faculty Publications

Lung cancer is the leading cause of cancer death in the United States. It usually exhibits its presence with the formation of pulmonary nodules. Nodules are round or oval-shaped growth present in the lung. Computed Tomography (CT) scans are used by radiologists to detect such nodules. Computer Aided Detection (CAD) of such nodules would aid in providing a second opinion to the radiologists and would be of valuable help in lung cancer screening. In this research, we study various feature selection methods for the CAD system framework proposed in FlyerScan. Algorithmic steps of FlyerScan include (i) local contrast enhancement (ii) …

Histogram Of Oriented Phase (Hop): A New Descriptor Based On Phase Congruency, Hussin Ragb, Vijayan K. Asari

Electrical and Computer Engineering Faculty Publications

In this paper we present a low level image descriptor called Histogram of Oriented Phase based on phase congruency concept and the Principal Component Analysis (PCA). Since the phase of the signal conveys more information regarding signal structure than the magnitude, the proposed descriptor can precisely identify and localize image features over the gradient based techniques, especially in the regions affected by illumination changes. The proposed features can be formed by extracting the phase congruency information for each pixel in the image with respect to its neighborhood. Histograms of the phase congruency values of the local regions in the image …

Diffractive Propagation And Recovery Of Modulated (Including Chaotic) Electromagnetic Waves Through Uniform Atmosphere And Modified Von Karman Phase Turbulence, Monish Ranjan Chatterjee, Fathi H.A. Mohamed

Electrical and Computer Engineering Faculty Publications

In a parallel approach to recently-used transfer function formalism, a study involving diffraction of modulated electromagnetic (EM) waves through uniform and phase-turbulent atmospheres is reported in this paper. Specifically, the input wave is treated as a modulated optical carrier, represented by use of a sinusoidal phasor with a slowly timevarying envelope. Using phasors and (spatial) Fourier transforms, the complex phasor wave is transmitted across a uniform or turbulent medium using the Kirchhoff-Fresnel integral and the random phase screen.

Some preliminary results are presented comparing non-chaotic and chaotic information transmission through turbulence, outlining possible improvement in performance utilizing the robust features …

Differential Tilt Variance Effects Of Turbulence In Imagery: Comparing Simulation With Theory, Daniel A. Lemaster, Russell C. Hardie, Szymon Gladysz, Matthew D. Howard, Michael Armand Rucci, Matthew E. Trippel, Jonathan D. Power, Barry K. Karch

Electrical and Computer Engineering Faculty Publications

Differential tilt variance is a useful metric for interpreting the distorting effects of turbulence in incoherent imaging systems. In this paper, we compare the theoretical model of differential tilt variance to simulations. Simulation is based on a Monte Carlo wave optics approach with split step propagation. Results show that the simulation closely matches theory. The results also show that care must be taken when selecting a method to estimate tilts.