Digital Communications and Networking Commons^™

How Live Streaming And Twitch Have Changed The Gaming Industry, Krystal Ruiz

ART 108: Introduction to Games Studies

Live streaming in itself has become a booming industry in which its content consists of “streamers” who live broadcast numerous events and real-time interactions while simultaneously chatting with viewers drawing huge and increasing numbers (Adamovich). Twitch has especially excelled at garnering attention as one of the most popular live streaming platforms that focuses on broadcasting and viewing video game content (Adamovich). Twitch has grown rapidly within the last few years asserting its dominance as one of the major forces in the games industry and becoming a multi-billion-dollar industry (Adamovich). For example, according to Descrier, in 2016 there were approximately 292 …

A Novel Energy-Efficient Sensor Cloud Model Using Data Prediction And Forecasting Techniques, Kalyan Das, Satyabrata Das, Aurobindo Mohapatra

Karbala International Journal of Modern Science

An energy-efficient sensor cloud model is proposed based on the combination of prediction and forecasting methods. The prediction using Artificial Neural Network (ANN) with single activation function and forecasting using Autoregressive Integrated Moving Average (ARIMA) models use to reduce the communication of data. The requests of the users generate in every second. These requests must be transferred to the wireless sensor network (WSN) through the cloud system in the traditional model, which consumes extra energy. In our approach, instead of one second, the sensors generally communicate with the cloud every 24 hours, and most of the requests reply using the …

A Novel Framework Using Neutrosophy For Integrated Speech And Text Sentiment Analysis, Florentin Smarandache, Kritika Mishra, Ilanthenral Kandasamy, Vasantha Kandasamy W.B.

Branch Mathematics and Statistics Faculty and Staff Publications

With increasing data on the Internet, it is becoming difficult to analyze every bit and make sure it can be used efficiently for all the businesses. One useful technique using Natural Language Processing (NLP) is sentiment analysis. Various algorithms can be used to classify textual data based on various scales ranging from just positive-negative, positive-neutral-negative to a wide spectrum of emotions. While a lot of work has been done on text, only a lesser amount of research has been done on audio datasets. An audio file contains more features that can be extracted from its amplitude and frequency than a …

Analysis Of Cloud Bursting On Openstack Infrastructure To Aws, Bao Pham, Ronald C. Jones, Majid Shaalan

Other Student Works

Cloud computing is the development of distributed and parallel computing that seeks to provide a new model of business computing by automating services and efficiently storing proprietary data. Cloud bursting is one of the cloud computing techniques that adopts the hybrid cloud model which seeks to expand the resources of a private cloud through the integration with a public cloud infrastructure. In this paper, the viability of cloud bursting is experimented and an attempt to integrate AWS EC2 onto an Openstack cloud environment using the Openstack OMNI driver is conducted.

Peer-Inspired Student Performance Prediction In Interactive Online Question Pools With Graph Neural Network, Haotian Li, Huan Wei, Yong Wang, Yangqiu Song, Huamin. Qu

Research Collection School Of Computing and Information Systems

Student performance prediction is critical to online education. It can benefit many downstream tasks on online learning platforms, such as estimating dropout rates, facilitating strategic intervention, and enabling adaptive online learning. Interactive online question pools provide students with interesting interactive questions to practice their knowledge in online education. However, little research has been done on student performance prediction in interactive online question pools. Existing work on student performance prediction targets at online learning platforms with predefined course curriculum and accurate knowledge labels like MOOC platforms, but they are not able to fully model knowledge evolution of students in interactive online …

A Statistical Impulse Response Model Based On Empirical Characterization Of Wireless Underground Channel, Abdul Salam, Mehmet C. Vuran, Suat Irmak

Faculty Publications

Wireless underground sensor networks (WUSNs) are becoming ubiquitous in many areas. The design of robust systems requires extensive understanding of the underground (UG) channel characteristics. In this paper, an UG channel impulse response is modeled and validated via extensive experiments in indoor and field testbed settings. The three distinct types of soils are selected with sand and clay contents ranging from $13\%$ to $86\%$ and $3\%$ to $32\%$, respectively. The impacts of changes in soil texture and soil moisture are investigated with more than $1,200$ measurements in a novel UG testbed that allows flexibility in soil moisture control. Moreover, the …

Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads, Pranav R. Patel

Theses and Dissertations

In legacy Global Positioning System (GPS) Satellite Navigation (SatNav) payloads, the architecture does not provide the flexibility to adapt to changing circumstances and environments. GPS SatNav payloads have largely remained unchanged since the system became fully operational in April 1995. Since then, the use of GPS has become ubiquitous in our day-to-day lives. GPS availability is now a basic assumption for distributed infrastructure; it has become inextricably tied to our national power grids, cellular networks, and global financial systems. Emerging advancements of easy to use radio technologies, such as software-defined radios (SDRs), have greatly lowered the difficulty of discovery and …

Joint 1d And 2d Neural Networks For Automatic Modulation Recognition, Luis M. Rosario Morel

Theses and Dissertations

The digital communication and radar community has recently manifested more interest in using data-driven approaches for tasks such as modulation recognition, channel estimation and distortion correction. In this research we seek to apply an object detector for parameter estimation to perform waveform separation in the time and frequency domain prior to classification. This enables the full automation of detecting and classifying simultaneously occurring waveforms. We leverage a lD ResNet implemented by O'Shea et al. in [1] and the YOLO v3 object detector designed by Redmon et al. in [2]. We conducted an in depth study of the performance of these …

A Fortran-Keras Deep Learning Bridge For Scientific Computing, Jordan Ott, Mike Pritchard, Natalie Best, Erik Linstead, Milan Curcic, Pierre Baldi

Engineering Faculty Articles and Research

Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way …

Decision Agriculture, Abdul Salam, Usman Raza

Faculty Publications

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and …

Underground Phased Arrays And Beamforming Applications, Abdul Salam, Usman Raza

Faculty Publications

This chapter presents a framework for adaptive beamforming in underground communication. The wireless propagation is thoroughly analyzed to develop a model using the soil moisture as an input parameter to provide feedback mechanism while enhancing the system performance. The working of array element in the soil is analyzed. Moreover, the effect of soil texture and soil moisture on the resonant frequency and return loss is studied in detail. The wave refraction from the soil–air interface highly degrades the performance of the system. Furthermore, to beam steering is done to achieve high gain for lateral component improving the UG communication. The …

Signals In The Soil: An Introduction To Wireless Underground Communications, Abdul Salam, Usman Raza

Faculty Publications

In this chapter, wireless underground (UG) communications are introduced. A detailed overview of WUC is given. A comprehensive review of research challenges in WUC is presented. The evolution of underground wireless is also discussed. Moreover, different component of UG communications is wireless. The WUC system architecture is explained with a detailed discussion of the anatomy of an underground mote. The examples of UG wireless communication systems are explored. Furthermore, the differences of UG wireless and over-the-air wireless are debated. Different types of wireless underground channel (e.g., In-Soil, Soil-to-Air, and Air-to-Soil) are reported as well.

Underground Wireless Channel Bandwidth And Capacity, Abdul Salam, Usman Raza

Faculty Publications

The UG channel bandwidth and capacity are vital parameters in wireless underground communication system design. In this chapter, a comprehensive analysis of the wireless underground channel capacity is presented. The impact of soil on return loss, bandwidth, and path loss is discussed. The results of underground multi-carrier modulation capacity are also outlined. Moreover, the single user capacity and multi-carrier capacity are also introduced with an in-depth treatment of soil texture, soil moisture, and distance effects on channel capacity. Finally, the chapter is concluded with a discussion of challenges and open research issues.

Signals In The Soil: Underground Antennas, Abdul Salam, Usman Raza

Faculty Publications

Antenna is a major design component of Internet of Underground Things (IOUT) communication system. The use of antenna, in IOUT, differs from traditional communication in that it is buried in the soil. Therefore, one of the main challenges, in IOUT applications, is to establish a reliable communication. To that end, there is a need of designing an underground-specific antenna. Three major factors that can impact the performance of a buried antenna are: (1) effect of high soil permittivity changes the wavelength of EM waves, (2) variations in soil moisture with time affecting the permittivity of the soil, and (3) difference …

Soil Moisture And Permittivity Estimation, Abdul Salam, Usman Raza

Faculty Publications

The soil moisture and permittivity estimation is vital for the success of the variable rate approaches in the field of the decision agriculture. In this chapter, the development of a novel permittivity estimation and soil moisture sensing approach is presented. The empirical setup and experimental methodology for the power delay measurements used in model are introduced. Moreover, the performance analysis is explained that includes the model validation and error analysis. The transfer functions are reported as well for soil moisture and permittivity estimation. Furthermore, the potential applications of the developed approach in different disciplines are also examined.

Current Advances In Internet Of Underground Things, Abdul Salam, Usman Raza

Faculty Publications

The latest developments in Internet of Underground Things are covered in this chapter. First, the IOUT Architecture is discussed followed by the explanation of the challenges being faced in this paradigm. Moreover, a comprehensive coverage of the different IOUT components is presented that includes communications, sensing, and system integration with the cloud. An in-depth coverage of the applications of the IOUT in various disciplines is also surveyed. These applications include areas such as decision agriculture, pipeline monitoring, border control, and oil wells.

Signals In The Soil: Subsurface Sensing, Abdul Salam, Usman Raza

Faculty Publications

In this chapter, novel subsurface soil sensing approaches are presented for monitoring and real-time decision support system applications. The methods, materials, and operational feasibility aspects of soil sensors are explored. The soil sensing techniques covered in this chapter include aerial sensing, in-situ, proximal sensing, and remote sensing. The underlying mechanism used for sensing is also examined as well. The sensor selection and calibration techniques are described in detail. The chapter concludes with discussion of soil sensing challenges.

Autonomous Irrigation Management In Decision Agriculture, Abdul Salam, Usman Raza

Faculty Publications

In this chapter, the important application of autonomous irrigation management in the field decision agriculture is discussed. The different types of sensor-guided irrigation systems are presented that includes center pivot systems and drip irrigation systems. Their sensing and actuator components are with detailed focus on real-time decision-making and integration to the cloud. This chapter also presents irrigation control systems which takes, as an input, soil moisture and temperature from IOUT and weather data from Internet and communicate with center pivot based irrigation systems. Moreover, the system architecture is explored where development of the nodes including sensing and actuators is presented. …

Variable Rate Applications In Decision Agriculture, Abdul Salam, Usman Raza

Faculty Publications

In this chapter, the variable rate applications (VRA) are presented for the field of decision agriculture. The characteristics of VRA control systems are described along with control hardware. Different types of VRA systems are discussed (e.g., liquid VRA systems and dry VRA systems). A case study is also explored in this regard. Moreover, recent advances and future trends are also outlined. Accordingly, a sustainable variable-rate irrigation scheduling is studied where different hardware and software component of the cyber-physical system are considered. Finally, chapter is concluded with a novel sensor deployment methodology.

Leveraging Conventional Internet Routing Protocol Behavior To Defeat Ddos And Adverse Networking Conditions, Jared M. Smith

Doctoral Dissertations

The Internet is a cornerstone of modern society. Yet increasingly devastating attacks against the Internet threaten to undermine the Internet's success at connecting the unconnected. Of all the adversarial campaigns waged against the Internet and the organizations that rely on it, distributed denial of service, or DDoS, tops the list of the most volatile attacks. In recent years, DDoS attacks have been responsible for large swaths of the Internet blacking out, while other attacks have completely overwhelmed key Internet services and websites. Core to the Internet's functionality is the way in which traffic on the Internet gets from one destination …

Snitch Application: Addressing Cyber Trust In Future Living Spaces, Russell Moore

Cybersecurity Undergraduate Research Showcase

The future of smart homes is filled with excitement and ample opportunity to live in an environment that features extraordinary convenience and energy efficiency. Devices such as Amazon Alexa and Roku Smart TV’s feature voice interaction options that provide the user with enhanced functionality. While voice-activated devices are accommodating, it is imperative to acknowledge how they work on the backend. The problem is that these devices collect and share a large amount of data from users who are oftentimes unaware that it’s even happening. The Snitch App is being developed in order to inform the user of what exactly is …

Intelligent Algorithm For Trapezoidal Interval Valued Neutrosophic Network Analysis, Florentin Smarandache, Said Broumi, Deivanayagampillai Nagarajan, Malayalan Lathamaheswari, Mohamed Talea, Assia Bakali

Branch Mathematics and Statistics Faculty and Staff Publications

The shortest path problem has been one of the most fundamental practical problems in network analysis. One of the good algorithms is Bellman-Ford, which has been applied in network, for the last some years. Due to complexity in the decision-making process, the decision makers face complications to express their view and judgment with an exact number for single valued membership degrees under neutrosophic environment. Though the interval number is a special situation of the neutrosophic, it did not solve the shortest path problems in an absolute manner. Hence, in this work, the authors have introduced the score function and accuracy …

A Novel Path Loss Forecast Model To Support Digital Twins For High Frequency Communications Networks, James Marvin Taylor Jr

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

The need for long-distance High Frequency (HF) communications in the 3-30 MHz frequency range seemed to diminish at the end of the 20th century with the advent of space-based communications and the spread of fiber optic-connected digital networks. Renewed interest in HF has emerged as an enabler for operations in austere locations and for its ability to serve as a redundant link when space-based and terrestrial communication channels fail. Communications system designers can create a “digital twin” system to explore the operational advantages and constraints of the new capability. Existing wireless channel models can adequately simulate communication channel conditions with …

Human Behavior Is A Significant Flaw In Maintaining Cyber Security, Elizabeth Jackson

Cybersecurity Undergraduate Research Showcase

Human behavior and data security utilization must be intertwined; in order to mitigate the negative effects of cyber attacks. No consumer wants their data hacked, breached, stolen, shared or wiped out. It is imperative to survey the type of education is needed to keep users safe and interested in securing their data. This can be done by simply seeking out the consumer's view of data security. The information obtained would allow the cybersecurity community to offer a simple way for consumers to protect their mobile data. There is a constant interaction between human behavior and the need for increased data …

Skin-Mimo: Vibration-Based Mimo Communication Over Human Skin, Dong Ma, Yuezhong Wu, Ming Ding, Mahbub Hassan, Wen Hu

Research Collection School Of Computing and Information Systems

We explore the feasibility of Multiple-Input-Multiple-Output (MIMO) communication through vibrations over human skin. Using off-the-shelf motors and piezo transducers as vibration transmitters and receivers, respectively, we build a 2x2 MIMO testbed to collect and analyze vibration signals from real subjects. Our analysis reveals that there exist multiple independent vibration channels between a pair of transmitter and receiver, confirming the feasibility of MIMO. Unfortunately, the slow ramping of mechanical motors and rapidly changing skin channels make it impractical for conventional channel sounding based channel state information (CSI) acquisition, which is critical for achieving MIMO capacity gains. To solve this problem, we …

Mitigating Stealthy Link Flooding Ddos Attacks Using Sdn-Based Moving Target Defense, Abdullah Aydeger

FIU Electronic Theses and Dissertations

With the increasing diversity and complication of Distributed Denial-of-Service (DDoS) attacks, it has become extremely challenging to design a fully protected network. For instance, recently, a new type of attack called Stealthy Link Flooding Attack (SLFA) has been shown to cause critical network disconnection problems, where the attacker targets the communication links in the surrounding area of a server. The existing defense mechanisms for this type of attack are based on the detection of some unusual traffic patterns; however, this might be too late as some severe damage might already be done. These mechanisms also do not consider countermeasures during …

Autoassociative-Heteroassociative Neural Network, Claudia V. Kropas-Hughes, Steven K. Rogers, Mark E. Oxley, Matthew Kabrisky

AFIT Patents

An efficient neural network computing technique capable of synthesizing two sets of output signal data from a single input signal data set. The method and device of the invention involves a unique integration of autoassociative and heteroassociative neural network mappings, the autoassociative neural network mapping enabling a quality metric for assessing the generalization or prediction accuracy of the heteroassociative neural network mapping.

Sensing, Computing, And Communications For Energy Harvesting Iots: A Survey, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, Sajal K. Das

Research Collection School Of Computing and Information Systems

With the growing number of deployments of Internet of Things (IoT) infrastructure for a wide variety of applications, the battery maintenance has become a major limitation for the sustainability of such infrastructure. To overcome this problem, energy harvesting offers a viable alternative to autonomously power IoT devices, resulting in a number of battery-less energy harvesting IoTs (or EH-IoTs) appearing in the market in recent years. Standards activities are also underway, which involve wireless protocol design suitable for EH-IoTs as well as testing procedures for various energy harvesting methods. Despite the early commercial and standards activities, IoT sensing, computing and communications …

Evaluating Driving Performance Of A Novel Behavior Planning Model On Connected Autonomous Vehicles, Keyur Shah

Honors Scholar Theses

Many current algorithms and approaches in autonomous driving attempt to solve the "trajectory generation" or "trajectory following” problems: given a target behavior (e.g. stay in the current lane at the speed limit or change lane), what trajectory should the vehicle follow, and what inputs should the driving agent apply to the throttle and brake to achieve this trajectory? In this work, we instead focus on the “behavior planning” problem—specifically, should an autonomous vehicle change lane or keep lane given the current state of the system?

In addition, current theory mainly focuses on single-vehicle systems, where vehicles do not communicate with …

Edge-Cloud Iot Data Analytics: Intelligence At The Edge With Deep Learning, Ananda Mohon M. Ghosh

Electronic Thesis and Dissertation Repository

Rapid growth in numbers of connected devices, including sensors, mobile, wearable, and other Internet of Things (IoT) devices, is creating an explosion of data that are moving across the network. To carry out machine learning (ML), IoT data are typically transferred to the cloud or another centralized system for storage and processing; however, this causes latencies and increases network traffic. Edge computing has the potential to remedy those issues by moving computation closer to the network edge and data sources. On the other hand, edge computing is limited in terms of computational power and thus is not well suited for …