Systems and Communications Commons^™

Stress Classification Using Deep Learning With 1d Convolutional Neural Networks, Abdulrazak Yahya Saleh, Lau Khai Xian

Knowledge Engineering and Data Science

Stress has been a major problem impacting people in various ways, and it gets serious every day. Identifying whether someone is suffering from stress is crucial before it becomes a severe illness. Artificial Intelligence (AI) interprets external data, learns from such data, and uses the learning to achieve specific goals and tasks. Deep Learning (DL) has created an impact in the field of Artificial Intelligence as it can perform tasks with high accuracy. Therefore, the primary purpose of this paper is to evaluate the performance of 1D Convolutional Neural Networks (1D CNNs) for stress classification. A Psychophysiological stress (PS) dataset …

Machine Learning Based Critical Resource Allocation In Mixed-Traffic Cellular Networks, Mohamed Nomeir

Theses and Dissertations

The proliferation of cellular networks over the past two decades has encouraged the expansion of their use in many modern applications. These applications involve the use of data traffic of different quality of service (QoS) requirements. Some of these requirements are quite stringent such as in the case of critical Internet of Things (IoT) health care, military and homeland security applications. This situation resulted in imposing a variety of resource allocation requirements on the cellular network operation in a simultaneous manner.

In this thesis, we consider the challenging problem of mixed-traffic resource allocation, or scheduling, in cellular networks. We focus …

Evaluating Deep-Learning Models For Debris-Covered Glacier Mapping, Zhiyuan Xie, Vijayan K. Asari, Umesh K. Haritashya

Electrical and Computer Engineering Faculty Publications

In recent decades, mountain glaciers have experienced the impact of climate change in the form of accelerated glacier retreat and other glacier-related hazards such as mass wasting and glacier lake outburst floods. Since there are wide-ranging societal consequences of glacier retreat and hazards, monitoring these glaciers as accurately and repeatedly as possible is important. However, the accurate glacier boundary, especially the debriscovered glacier (DCG) boundary, which is one of the primary inputs in many glacier analyses, remains a challenge even after many years of research using conventional remote sensing methods or machine-learning methods. The GlacierNet, a deep-learning-based approach, utilized the …

A Comprehensive Analysis Of Reward Function For Adaptive Traffic Signal Control, Abu Rafe Md Jamil, Naushin Nower

Knowledge Engineering and Data Science

Adaptive traffic control systems (ATCS) can play an essential role in reducing traffic congestion in urban areas. The main challenge for ATSC is to determine the proper signal timing. Recently, Deep Reinforcement Learning (DRL) has been used to determine proper signal timing. However, the success of the DRL algorithm depends on the appropriate reward function design. There exist various reward functions for ATSC in the existing research. This research presents a comprehensive analysis of the widely used reward function. The pros and cons of various reward algorithms were discussed, and experimental analysis shows that the multi-objective reward function enhances the …

Similarity Identification Of Large-Scale Biomedical Documents Using Cosine Similarity And Parallel Computing, Merlinda Wibowo, Christoph Quix, Nur Syahela Hussien, Herman Yuliansyah, Faisal Dharma Adhinata

Knowledge Engineering and Data Science

Document similarity computation is an important research topic in information retrieval, and it is a crucial issue for automatic document categorization. The similarity value is between 0 and 1, then the closest value to 1 is represented both documents is considered more relevant, vice versa. However, the large scale of textual information has created the problem of finding the relevance level between documents. Therefore, the relevance between mesh heading text in the PubMed documents is higher than the relevance of the abstract text in the PubMed documents. Furthermore, parallel computing is implemented to speed up the large-scale documents similarity identification …

Recognition Of Handwritten Javanese Script Using Backpropagation With Zoning Feature Extraction, Anik Nur Handayani, Heru Wahyu Herwanto, Katya Lindi Chandrika, Kohei Arai

Knowledge Engineering and Data Science

Backpropagation is part of supervised learning, in which the training process requires a target. The resulting error is transmitted back to the units below in its training process. Backpropagation can solve complicated problems because it consumes less memory than other algorithms. In addition, it also can produce solutions with a low error rate while executing less time. In image pattern recognition, backpropagation can be utilized for cultural preservation in many places worldwide, including Indonesia. It is used to recognize picture patterns in Javanese script writings. This study concluded that feature extraction approaches, zoning, and backpropagation could be utilized to distinguish …

Parallel Approach Of Adaptive Image Thresholding Algorithm On Gpu, Adhi Prahara, Andri Pranolo, Nuril Anwar, Yingchi Mao

Knowledge Engineering and Data Science

Image thresholding is used to segment an image into background and foreground using a given threshold. The threshold can be generated using a specific algorithm instead of a pre-defined value obtained from observation or experiment. However, the algorithm involves per pixel operation, histogram calculation, and iterative procedure to search the optimum threshold that is costly for high-resolution images. In this research, parallel implementations on GPU for three adaptive image thresholding methods, namely Otsu, ISODATA, and minimum cross-entropy, were proposed to optimize their computational times to deal with high-resolution images. The approach involves parallel reduction and parallel prefix sum (scan) techniques …

A Comparative Study Of Machine Learning-Based Approach For Network Traffic Classification, Kien Trang, An Hoang Nguyen

Knowledge Engineering and Data Science

Internet usage has increased rapidly and become an essential part of human life, corresponding to the rapid development of network infrastructure in recent years. Thus, protecting users’ confidential information when joining the global network becomes one of the most significant considerations. Even though multiple encryption algorithms and techniques have been applied in different parties, including internet providers, and web hosting, this situation also allows the hacker to attack the network system anonymously. Therefore, the significance of classifying network data streams to improve network system quality and security is attracting increasing study interests. This work introduces a machine learning-based approach to …

Cnn Based Face Recognition System For Patients With Down And William Syndrome, Endang Setyati, Suharyono Az, Subroto Prasetya Hudiono, Fachrul Kurniawan

Knowledge Engineering and Data Science

Down syndrome, also known as trisomy genetic condition, is a genetic disorder that affects many people. Williams syndrome is a hereditary disorder that can affect anyone at birth. It marks medical and cognitive issues, such as cardiovascular illness, developmental delays, and learning impairments. This is accompanied by exceptional verbal abilities, a gregarious attitude, and a passion for music. Down syndrome and William Syndrome are both genetic illnesses. However, it can be distinguished from the arrangement of chromosome 21. Down syndrome and William syndrome can also be identified by recognizing faces, or facial characteristics, such as observing particular facial features. Therefore, …

Melanoma Classification Based On Simulated Annealing Optimization Neural Network, Edi Jaya Kusuma, Ika Pantiawati, Sri Handayani

Knowledge Engineering and Data Science

Technology development in image processing and artificial intelligence leads to the high demand for smart systems, especially in the health sector. Cancer is one of the diseases with the highest mortality cases worldwide. Melanoma is one of the cancers commonly caused by high exposure to UV light. The earliest the melanoma is identified, the higher the patient's chance of recovering. Therefore, this study proposes melanoma detection based on BPNN optimized by a simulated annealing algorithm. This research utilizes PH2 dermoscopic image data containing 200 color digital images in BMP format. The data is processed using color feature extraction techniques to …

Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil

Theses and Dissertations

Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, …

Analysis Of Deep Learning Methods For Wired Ethernet Physical Layer Security Of Operational Technology, Lucas Torlay

All Theses

The cybersecurity of power systems is jeopardized by the threat of spoofing and man-in-the-middle style attacks due to a lack of physical layer device authentication techniques for operational technology (OT) communication networks. OT networks cannot support the active probing cybersecurity methods that are popular in information technology (IT) networks. Furthermore, both active and passive scanning techniques are susceptible to medium access control (MAC) address spoofing when operating at Layer 2 of the Open Systems Interconnection (OSI) model. This thesis aims to analyze the role of deep learning in passively authenticating Ethernet devices by their communication signals. This method operates at …

Automated Flight Controller Adaptive Compensation For Actuator Failures In Transport Type Aircraft, Daniel James Fresella

Graduate Theses and Dissertations

Aircraft operate over a wide range of conditions including atmospheric, weight, and center ofgravity changes. This presents a substantial challenge to automatic control system designers. When these operating conditions are merged with a partial or full control surface failure, automatic flight control is near impossible with conventional controllers. Additionally, when pilots experience control failure emergencies during flight, workload and fatigue increase drastically. The continued research of automatic flight control systems that can seamlessly adapt to unmodelled failures will enable a new generation of robust aircraft control. In this paper a 9th order 6 degree of freedom aircraft model is used …

Machine Learning For Unmanned Aerial System (Uas) Networking, Jian Wang

Doctoral Dissertations and Master's Theses

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex …

Indoor Positioning Using Synchronized Ultrasonic Ofdma Signals, Julian Bartolone

Master's Theses

This paper proposes a method of short-range indoor localization using differential phase measurements of synchronized two-tone ultrasonic signals in an Orthogonal Frequency Multiple Access (OFDMA) scheme. This indoor positioning system (IPS) operates at an ultrasonic frequency of approximately 40kHz and synchronizes using an infrared signal. The OFDMA scheme allows for a receiver to process the signals from multiple transmitters continuously without the signals interfering with each other. The phases of the signals are measured using Goertzel Filters, allowing for low-complexity frequency content analysis. A MATLAB simulation using the proposed localization method is performed using four transmitter nodes in the corners …

Plasmonic Field-Effect Transistors (Terafets) For 6g Communications, Michael Shur, Gregory Aizin, Taiichi Otsuji, Victor Ryzhii

Publications and Research

Ever increasing demands of data traffic makes the transition to 6G communications in the 300 GHz band inevitable. Short-channel field-effect transistors (FETs) have demonstrated excellent potential for detection and generation of terahertz (THz) and sub-THz radiation. Such transistors (often referred to as TeraFETs) include short-channel silicon complementary metal oxide (CMOS). The ballistic and quasi-ballistic electron transport in the TeraFET channels determine the TeraFET response at the sub-THz and THz frequencies. TeraFET arrays could form plasmonic crystals with nanoscale unit cells smaller or comparable to the electron mean free path but with the overall dimensions comparable with the radiation wavelength. Such …

The Factors Influencing The Acceptance Of Web-Based E-Learning System Among Academic Staffs Of Saudi Arabia, Ikhlas Zamzami

Future Computing and Informatics Journal

It is possible to learn more quickly and effectively with e-learning software development because it provides learners with convenient and flexible learning environments. This allows them to progress further in their careers. Reports on web-based e-learning systems for in-service education have frequently neglected to include the viewpoint of the instructor. In order to conduct quantitative research, a sample of 50 academic staff members was selected. The purpose of this study was to investigate various factors that influence the intention to use web-based e-learning, with the theoretical foundation being provided by university lecturers. According to the findings of the study, the …

Enhancing Academic Advising In Credit Hours System Using Dss, Alaa Salah Eldin Ghoneim

Future Computing and Informatics Journal

Academic advising plays a vital role in achieving higher educational institution’s purposes. Academic advising is a process where an academic advisor decides to select a certain number of courses for a student to register in each semester to fulfil the graduation requirements. This paper presents an Academic Advising Decision Support System (AADSS) to enhance advisors make better decisions regarding their students’ cases. AADSS framework divided into four layers, data preparation layer, data layer, processing layer and decision layer. The testing results from those participating academic advisors and students considered are that AADSS beneficial in enhancing their decision for selecting courses.

Massive Mimo Beamforming Analysis For 5g Systems, Mohammad M. Abdellatif, Aya Abdel Moniem

Electrical Engineering

Multiple input multiple outputs, MIMO Technology is based on the usage of multiple receivers and transmitters or antennas at the sending and receiving end of a signal, to increase the throughput and capacity of the network. The number of antennas in a MIMO station can reach up to eight. The Massive MIMO is like the simple MIMO, with the only difference is the number of antennas can reach hundreds. Massive MIMO operates in time division duplex mode, which means the channel has reciprocal properties of radio propagation. The base station calculates an estimate the channel capacity from the uplink pilots …

Spectrum Sensing Limitations In Cognitive Radio Networks, Mohammad M. Abdellatif, Hazim E. Mustafa

Electrical Engineering

As the number of wireless devices is increasing daily, the radio frequency spectrum is becoming more crowded. Moreover, due to the stochastic nature of wireless communications technologies, some frequency bands which are allocated to services or users can be underutilized. On the other hand, some users may not be able to access the medium as all the frequency bands have been already allocated to different users. Cognitive radio has gained a lot of interest in the past few years as it tackles the problem of spectrum scarcity by taking advantage of spectrum holes that are available in the frequency spectrum. …

Intelligent Internet Of Things Frameworks For Smart City Safety, Dimitrios Sikeridis

Electrical and Computer Engineering ETDs

The emerging Smart City ecosystem consists of a vast edge network of Internet of Things (IoT) devices that continuously interact with mobile devices carried by its citizens. In this setting, the IoT infrastructure, apart from the main communications facilitator, acts as a crowdsourcing mechanism that collects massive amounts of user data, and can support public safety applications for the Smart City. In this thesis, we design and analyze learning mechanisms that extract intelligence from crowd interactions with the wireless IoT infrastructure, and optimize its energy efficiency while operating as a public safety network. First, we deploy a multi-story facility testbed …

Improvement On Pdp Evaluation Performance Based On Neural Networks And Sgdk-Means Algorithm, Fan Deng, Houbing Song, Zhenhua Yu, Liyong Zhang, Xi Song, Min Zhang, Zhenyu Zhang, Yu Mei

Publications

With the purpose of improving the PDP (policy decision point) evaluation performance, a novel and efficient evaluation engine, namely XDNNEngine, based on neural networks and an SGDK-means (stochastic gradient descent K-means) algorithm is proposed. We divide a policy set into different clusters, distinguish different rules based on their own features and label them for the training of neural networks by using the K-means algorithm and an asynchronous SGDK-means algorithm. Then, we utilize neural networks to search for the applicable rule. A quantitative neural network is introduced to reduce a server’s computational cost. By simulating the arrival of requests, XDNNEngine is …

Issue 18: Contributors, Don Flournoy

Online Journal of Space Communication

List of Issue 18 Contributors

Sunsat Design Competition 2015-2016 First Place Winner – Team Space Transport: Power Satellites Beamed Energy Bootstrapping, Keith Henson, Anna Nesterova

Online Journal of Space Communication

This International SunSat Design Competition first-place winner for 2016 describes a beamed energy transport system that will operate in Space above low earth orbit (LEO) as a way to move power satellite parts into high orbits.

This design, entitled “Beamed Energy Bootstrapping,” makes use of small propulsion power satellites to provide the energy for space-based vehicles using electric arcjets. The proposal lays out a scheme to get the first propulsion power satellite in place without damage as it passes through the orbiting space junk below 2000 km.

Click here to see the video: Space Transport for Power Satellites Beamed Energy …

Sunsat Design Competition 2015-2016 Second Place Winner – Team Pathway To Power : Wireless Power Transfer, Javier Tandazo, Ethan Wong, Curtis Waggoner, John Guggenheim, Alexander Carter

Online Journal of Space Communication

Solar Power Satellites (SPS) using Wireless Power Transfer (WPT) to beam renewable energy to consumers on earth face three grand challenges: moving parts, heat dissipation, and radio interference. Solutions to each of these “show stoppers” are presented here. Further, a progressively more-complex pathway is described which starts where we are now and leads step-wise to implementation of large-scale Space Solar Power (SSP).

The first two grand challenges are addressed by a novel SPS design based on a thin-walled cylinder configuration of solar panels. The remaining challenge is tackled through a newly-discovered antenna configuration which allows dramatic reduction in radio/telecom interference …

Sunsat Design Competition 2014-2015 Third Place Winner – Team Martian: Space Solar Power Test Bed, Jeremy Straub, Tristan Plante, Benjamin Kading, Alex Holland, Landon Klein, Jordan Forbord

Online Journal of Space Communication

We propose a four-stage plan to demonstrate the effectiveness and safety of Space Solar Power (SSP) for use on Earth. Our project goal is to achieve Technology Readiness Level (TRL) by means of: 1) a test mission in low Earth orbit using a small spacecraft; 2) that will support a manned mission to Mars; 3) that includes a bent pipe experiment (power supplied from Earth, to a spacecraft and back to Earth), and 4) to complete system deployment.

The primary impediment to SSP implementation is thought to be the acceptance of the system by those on Earth who may be …

Sunsat Design Competition 2014-2015 First Place Winner – Team Cast: Multi-Rotary Joints Sps, Xinbin Hou, Meng Li, Lili Niu, Lu Zhou, Ying Chen, Zhengai Cheng, Haipeng Ji

Online Journal of Space Communication

Space Power Satellite (SPS) is a huge spacecraft designed to collect solar energy in space for supplying electric power to the electric grid on the ground. The SPS concept was first proposed by Dr. Peter Glaser in 1968.

Various studies on SPS in various countries have been produced over the past forty years. Today, there are multiple variations on this early concept, both in innovation and in optimization. Because of the huge size, immense mass and high power of these SPS installations, there are many technological difficulties.

Here, a new Multi-Rotary Joints SPS (MR-SPS) concept is proposed. The large solar …

Sunsat Design Competition 2014-2015 Second Place Winner – Team Sunflower: Thermal Power Satellite, Keith Henson, Steve Nixon, Kris Holland, Anna Nesterova

Online Journal of Space Communication

Space-based Solar Power has failed to be competitive on cost in spite of decades of study. A new approach appears to resolve the cost issue, undercutting coal and opening huge markets for low cost solar power from space. There are two parts to the problem. First is the cost of lifting parts to Geosynchronous Earth Orbit (GEO; second is the mass of parts that make up a power satellite.

Our team is proposing a combination that makes use of Skylon to Low Earth Orbit (LEO), and a 15,000 ton payload ground powered electric propulsion from LEO to GEO. This strategy …

Sunsat Design Competition 2013-2014 Third Place Winner – Team University Of North Dakota: Nano Ssp Satellite, Corey Bergsrud, Robert Bernaciak, Ben Kading, John Mcclure, Jeremy Straub, Subin Shahukhal, Karl Williams

Online Journal of Space Communication

This work presents the conceptualization of a Space-to-Space Microwave Wireless Power Transmission (S2S-MWPT) experimental demonstration mission using small spacecraft. Literature reviews [1, 2] suggest a stepwise procedure for technology demonstrations in support of advancing space solar power satellite (SSPS) systems. These technologies should be verified first on Earth and then in-space using small satellites. This project built its S2S-MWPT demonstration concept within the University NanoSat program restrictions (dimensions of 50cm x 50cm x 60cm and mass of 50kg). The idea is to use these upper limit restrictions to develop the MWPT spacecraft (MicroSat). Contained inside the MicroSat …

Sunsat Design Competition 2013-2014 Second Place Winner – Team Solar Maximum Llc: Sun-Synchronous Orbits, Danny R. Jones, Anna Nesterova

Online Journal of Space Communication

The orbital location of PowerSats plays a critical role in determining the mass of the solar power satellite (PowerSat) transmitter and the size of the rectenna on the Earth’s surface. These in turn play an important role in the cost of deploying the PowerSat, especially the cost of launching the PowerSat into orbit as the transmitter makes up a large part of the PowerSats mass. We will consider a new approach to PowerSat orbital positioning by considering a circular sun-synchronous orbit at 5,185.3 kilometers with an inclination of 142.1 degrees. Locating the PowerSat at this location offers several benefits and …