Incentivization In Mobile Edge Computing Using A Full Bayesian Approach,
2020
University of New Mexico - Main Campus
Incentivization In Mobile Edge Computing Using A Full Bayesian Approach, Sean Lebien
Electrical and Computer Engineering ETDs
The advances of multi-access edge computing (MEC) have paved the way for the integration of the MEC servers, as intelligent entities into the Internet of Things (IoT) environment as well as into the 5G radio access networks. In this thesis, a novel artificial intelligence-based MEC servers’ activation mechanism is proposed, by adopting the principles of Reinforcement Learning (RL) and Bayesian Reasoning. The considered problem enables the MEC servers’ activation decision-making, aiming at enhancing the reputation of the overall MEC system, as well as considering the total computing costs to serve efficiently the users’ computing demands, guaranteeing at the same time …
A Novel Energy-Efficient Sensor Cloud Model Using Data Prediction And Forecasting Techniques,
2020
Department of Computer Science & Engineering, Veer Surendra Sai University of Technology (VSSUT), Burla, India
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 …
Analysis Of Cloud Bursting On Openstack Infrastructure To Aws,
2020
Harrisburg University of Science and Technology
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.
Poland’S Challenge To Eu Directive 2019/790: Standing Up To The Destruction Of European Freedom Of Expression,
2020
Penn State Dickinson Law
Poland’S Challenge To Eu Directive 2019/790: Standing Up To The Destruction Of European Freedom Of Expression, Michaela Cloutier
Dickinson Law Review (2017-Present)
In 2019, the European Parliament and Council passed Directive 2019/790. The Directive’s passage marked the end of a fouryear- long legislative attempt to impose more liability for copyright violations on Online Service Providers, an effort which was controversial from the start. Online Service Providers fear that the 2019 Directive, especially its Article 17, will completely change the structure of liability on the Internet, forcing providers to adopt expensive content filtering systems. Free speech advocates fear that ineffective filtering technology will infringe upon Internet users’ rights to express themselves, and legal scholars have pointed out the Directive’s inconsistency with prior European …
A Novel Framework Using Neutrosophy For Integrated Speech And Text Sentiment Analysis,
2020
University of New Mexico
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 …
Peer-Inspired Student Performance Prediction In Interactive Online Question Pools With Graph Neural Network,
2020
Singapore Management University
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 …
The Role Of Network Components In Improving The Reliability And Survivability Of Mobile Communication Networks,
2020
Tashkent University of Information Technologies Named after Muhammad Al-Khwarizmi, Uzbekistan
The Role Of Network Components In Improving The Reliability And Survivability Of Mobile Communication Networks, Dilmurod Davronbekov, Utkir Karimovich Matyokubov
Acta of Turin Polytechnic University in Tashkent
This article compares the different architectures of mobile communication networks (MCN) and examines the survivability of the network. Typical survival strategies for improving MCN survivability, failure mitigation strategies for network elements, wireless network survival rates, failure scenarios at MCN levels, and survival indicators are presented. The importance of fiber-optic communication in the construction of communication lines between MCN components has been studied. The issue of designing MCNs in a cost-effective and highly viable way is considered, and the necessary expressions of the design process are given.
A Statistical Impulse Response Model Based On Empirical Characterization Of Wireless Underground Channel,
2020
Purdue University
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 …
Security Analysis Of The Anonabox Pro,
2020
Louisiana State University
Security Analysis Of The Anonabox Pro, Devi Sowjanya Vempati
LSU Master's Theses
The security posture of critical network appliances, such as routers, switches, and firewalls, is crucial as these devices provide the first line of defense against malicious actors. As there is typically no endpoint security software, such as anti-virus available for these devices, it is crucial that vendors release timely updates for vulnerabilities and that customers apply them quickly. The research effort documented in this thesis describes a developed methodology for triaging known vulnerabilities in network devices, assessing the security posture of device vendors, and locating likely weak points in released firmware images. To highlight this methodology, the Anonabox security appliance …
Joint 1d And 2d Neural Networks For Automatic Modulation Recognition,
2020
Air Force Institute of Technology
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 …
Direct Digital Synthesis: A Flexible Architecture For Advanced Signals Research For Future Satellite Navigation Payloads,
2020
Air Force Institute of Technology
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 …
A Study Of Static And Dynamic Characteristics Of Multifunctional Signal Converters,
2020
Tashkent University of Information Technologies named after Muhammad al-Khwarizmi Address: 108, Amir Temur st., 100200, Tashkent city, Republic of Uzbekistan E-mail: [email protected], Phone:+998-94-343-54-91
A Study Of Static And Dynamic Characteristics Of Multifunctional Signal Converters, Akmal Abdumalikov
Chemical Technology, Control and Management
The issues of continuity, accuracy, speed and reliability of signal conversion, which are the main problems of quality control and management of production processes, remain relevant. Research shows that in practice there are different signal variables, the study of which is highly formalized in a number of modeling tasks and basic classification studies, in particular transients in converters, its sources and elements requires a unified mathematical approach, that is, visual, highly formalized modeling and research based on it. The paper presents a graph model of multifunctional signal converters that provide microprocessor and electronic devices with signals in the form of …
A Fortran-Keras Deep Learning Bridge For Scientific Computing,
2020
University of California, Irvine
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 …
Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices,
2020
Embry-Riddle Aeronautical University
Zero-Bias Deep Learning For Accurate Identification Of Internet Of Things (Iot) Devices, Yongxin Liu, Houbing Song, Thomas Yang, Jian Wang, Jianqiang Li, Shuteng Niu, Zhong Ming
Publications
The Internet of Things (IoT) provides applications and services that would otherwise not be possible. However, the open nature of IoT makes it vulnerable to cybersecurity threats. Especially, identity spoofing attacks, where an adversary passively listens to the existing radio communications and then mimic the identity of legitimate devices to conduct malicious activities. Existing solutions employ cryptographic signatures to verify the trustworthiness of received information. In prevalent IoT, secret keys for cryptography can potentially be disclosed and disable the verification mechanism. Noncryptographic device verification is needed to ensure trustworthy IoT. In this article, we propose an enhanced deep learning framework …
Signals In The Soil: An Introduction To Wireless Underground Communications,
2020
Purdue University
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.
Signals In The Soil: Underground Antennas,
2020
Purdue University
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 …
Underground Phased Arrays And Beamforming Applications,
2020
Purdue University
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 …
Current Advances In Internet Of Underground Things,
2020
Purdue University
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.
Soil Moisture And Permittivity Estimation,
2020
Purdue University
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.
Signals In The Soil: Subsurface Sensing,
2020
Purdue University
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.
