Performance Analysis Of Vlc-Based Infrastructure-To-Vehicle Communication,
2023
The British University in Egypt
Performance Analysis Of Vlc-Based Infrastructure-To-Vehicle Communication, Noura Elshabasy, Samy S. Soliman, Mohammad Abdellatif
Electrical Engineering
Infrastructure such as traffic signals are expected to communicate various safety messages as a part of the evolution of smart transportation networks. It is anticipated that hybrid Vehicle to Vehicle (V2V) and Infrastructure to Vehicle (I2V) communication links would be taken into account to further enhance the system performance and expand the reach and capacity of the network. This paper proposes a visible light communication (VLC) link by installing multiple Photo-Detectors (PDs) in I2V links in order to improve the Bit Error Rate (BER) performance of the system. The paper investigates the effect of the distances and received powers on …
Exploring Bistatic Scattering Modeling For Land Surface Applications Using Radio Spectrum Recycling In The Signal Of Opportunity Coherent Bistatic Simulator,
2023
Mississippi State University
Exploring Bistatic Scattering Modeling For Land Surface Applications Using Radio Spectrum Recycling In The Signal Of Opportunity Coherent Bistatic Simulator, Dylan R. Boyd
Theses and Dissertations
The potential for high spatio-temporal resolution microwave measurements has urged the adoption of the signals of opportunity (SoOp) passive radar technique for use in remote sensing. Recent trends in particular target highly complex remote sensing problems such as root-zone soil moisture and snow water equivalent. This dissertation explores the continued open-sourcing of the SoOp coherent bistatic scattering model (SCoBi) and its use in soil moisture sensing applications. Starting from ground-based applications, the feasibility of root-zone soil moisture remote sensing is assessed using available SoOp resources below L-band. A modularized, spaceborne model is then developed to simulate land-surface scattering and delay-Doppler …
Physical Layer Security With Unmanned Aerial Vehicles For Advanced Wireless Networks,
2023
Mississippi State University
Physical Layer Security With Unmanned Aerial Vehicles For Advanced Wireless Networks, Aly Sabri Abdalla
Theses and Dissertations
Unmanned aerial vehicles (UAVs) are emerging as enablers for supporting many applications and services, such as precision agriculture, search and rescue, temporary network deployment, coverage extension, and security. UAVs are being considered for integration into emerging wireless networks as aerial users, aerial relays (ARs), or aerial base stations (ABSs). This dissertation proposes employing UAVs to contribute to physical layer techniques that enhance the security performance of advanced wireless networks and services in terms of availability, resilience, and confidentiality. The focus is on securing terrestrial cellular communications against eavesdropping with a cellular-connected UAV that is dispatched as an AR or ABS. …
Modeling Of Signals And Spectra: 5g And Beyond,
2023
Portland State University
Modeling Of Signals And Spectra: 5g And Beyond, Xianzhen Yang
Dissertations and Theses
The collection of papers addresses various aspects of spectra and signals in RF wireless systems for 5G and beyond. The first paper focuses on the nonlinear effects of amplified dual-band OFDM signals, providing a spectrum model for intermodulation and cross-modulation. The second paper extends this analysis beyond bandwidth restrictions, enabling accurate prediction of amplified dual-band spectrum. The third paper emphasizes the significance of out-of-band intermodulation products and derives an analytical expression using third-order intercept points. The fourth paper presents a unified spectrum expression for OFDM, FBMC, and F-OFDM, facilitating comparative insights into these signals. The fifth paper explores second-order intermodulation …
A Study Of 5g Cellular Connectivity To Unmanned Aerial Vehicles,
2023
Clemson University
A Study Of 5g Cellular Connectivity To Unmanned Aerial Vehicles, Jackson Murrin
All Theses
The market of unmanned aerial vehicles (UAVs) has seen significant growth in the past ten years on both the commercial and military sides. The applications for UAVs are endless and options by manufacturers allow users to modify their drones for their specific goals. This industry has opened up the excitement of piloting vehicles in the air, photography, videography, exploration of nature from a different point of view and many other hobbies assisted by the emergence of UAVs. The growth of this industry coincides with the roll out of new 5G cellular network technology. This upgrade in cellular network infrastructure allows …
Generalizable Deep-Learning-Based Wireless Indoor Localization,
2023
Clemson University
Generalizable Deep-Learning-Based Wireless Indoor Localization, Ali Owfi
All Theses
The growing interest in indoor localization has been driven by its wide range of applications in areas such as smart homes, industrial automation, and healthcare. With the increasing reliance on wireless devices for location-based services, accurate estimation of device positions within indoor environments has become crucial. Deep learning approaches have shown promise in leveraging wireless parameters like Channel State Information (CSI) and Received Signal Strength Indicator (RSSI) to achieve precise localization. However, despite their success in achieving high accuracy, these deep learning models suffer from limited generalizability, making them unsuitable for deployment in new or dynamic environments without retraining. To …
Deep Learning For Multi-Structured Javanese Gamelan Note Generator,
2023
Institut Teknologi Sepuluh Nopember, Indonesia
Deep Learning For Multi-Structured Javanese Gamelan Note Generator, Arik Kurniawati, Eko Mulyanto Yuniarno, Yoyon Kusnendar Suprapto
Knowledge Engineering and Data Science
Javanese gamelan, a traditional Indonesian musical style, has several song structures called gendhing. Gendhing (songs) are written in conventional notation and require gamelan musicians to recognize patterns in the structure of each song. Usually, previous research on gendhing focuses on artistic and ethnomusicological perspectives, but this study is to explore the correlation between gendhing as traditional music in Indonesia and deep learning technology that replaces the task of gamelan composers. This research proposes CNN-LSTM to generate notation of ricikan struktural instruments as an accompaniment to Javanese gamelan music compositions based on balungan notation, rhythm, song structure, and gatra …
An Enhanced Adaptive Learning System Based On Microservice Architecture,
2023
Helwan University
An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif
Future Computing and Informatics Journal
This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …
Visual Question Answering: A Survey,
2023
Future University in Egypt
Visual Question Answering: A Survey, Gehad Assem El-Naggar
Future Computing and Informatics Journal
Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …
Politicians, Pundits, And Platform Migration: A Comparison Of Political Polarization On Parler And Twitter,
2023
University of Wisconsin-Madison
Politicians, Pundits, And Platform Migration: A Comparison Of Political Polarization On Parler And Twitter, Abigial Matthews, Jacqueline M. Otala, Esma Wali, Gillian Kurtic, Lynden Millington, Michael Simpson, Jeanna Matthews, Golshan Madraki
Northeast Journal of Complex Systems (NEJCS)
Parler, a self-proclaimed free speech social media platform founded in 2018, attracted a large influx of new members in 2020 as the result of a highly visible platform migration campaign. Parler usage was linked to the planning of the Jan. 6, 2021 attack on the United States Capitol building, leading to a shutdown of the Parler platform. Parler, which is now back online, offers an important lens through which to examine the broader attempts at platform migration in response to changing content moderation and platform governance policies and their impact on political polarization. We begin by examining the network connections …
Exploring The Impact Of Students Demographic Attributes On Performance Prediction Through Binary Classification In The Kdp Model,
2023
University of Energy and Natural Resources,Ghana
Exploring The Impact Of Students Demographic Attributes On Performance Prediction Through Binary Classification In The Kdp Model, Issah Iddrisu, Peter Appiahene, Obed Appiah, Inusah Fuseini
Knowledge Engineering and Data Science
During the course of this research, binary classification and the Knowledge Discovery Process (KDP) were used. The experimental and analytical capabilities of Rapid Miner's 9.10.010 instructional environment are supported by five different classifiers. Included in the analysis were 2334 entries, 17 characteristics, and one class variable containing the students' average score for the semester. There were twenty experiments carried out. During the studies, 10-fold cross-validation and ratio split validation, together with bootstrap sampling, were used. It was determined whether or not to use the Random Forest (RF), Rule Induction (RI), Naive Bayes (NB), Logistic Regression (LR), or Deep Learning (DL) …
Maximum Marginal Relevance And Vector Space Model For Summarizing Students' Final Project Abstracts,
2023
Institut Sains dan Teknologi Terpadu Surabaya, Indonesia
Maximum Marginal Relevance And Vector Space Model For Summarizing Students' Final Project Abstracts, Gunawan Gunawan, Fitria Fitria, Esther Irawati Setiawan, Kimiya Fujisawa
Knowledge Engineering and Data Science
Automatic summarization is reducing a text document with a computer program to create a summary that retains the essential parts of the original document. Automatic summarization is necessary to deal with information overload, and the amount of data is increasing. A summary is needed to get the contents of the article briefly. A summary is an effective way to present extended information in a concise form of the main contents of an article, and the aim is to tell the reader the essence of a central idea. The simple concept of a summary is to take an essential part of …
Inter-Frame Video Compression Based On Adaptive Fuzzy Inference System Compression Of Multiple Frame Characteristics,
2023
Politeknik Negeri Samarinda, Indonesia
Inter-Frame Video Compression Based On Adaptive Fuzzy Inference System Compression Of Multiple Frame Characteristics, Arief Bramanto Wicaksono Putra, Rheo Malani, Bedi Suprapty, Achmad Fanany Onnilita Gaffar, Roman Voliansky
Knowledge Engineering and Data Science
Video compression is used for storage or bandwidth efficiency in clip video information. Video compression involves encoders and decoders. Video compression uses intra-frame, inter-frame, and block-based methods. Video compression compresses nearby frame pairs into one compressed frame using inter-frame compression. This study defines odd and even neighboring frame pairings. Motion estimation, compensation, and frame difference underpin video compression methods. In this study, adaptive FIS (Fuzzy Inference System) compresses and decompresses each odd-even frame pair. First, adaptive FIS trained on all feature pairings of each odd-even frame pair. Video compression-decompression uses the taught adaptive FIS as a codec. The features utilized …
Ant Colony Optimization For Resistor Color Code Detection,
2023
Universitas Negeri Malang, Indonesia
Ant Colony Optimization For Resistor Color Code Detection, Slamet Wibawanto, Kartika Candra Kirana, Hani Ramadhan
Knowledge Engineering and Data Science
In the early stages of learning resistors, introducing color-based values is needed. Moreover, some combinations require a resistor trip analysis to identify. Unfortunately, a resistor body color is considered a local solution, which often confuses resistor coloration. Ant Colony Optimization (ACO) is a heuristic algorithm that can recognize problems with traveling a group of ants. ACO is proposed to select commercial matrix values to be computed without preventing local solutions. In this study, each explores the matrix based on pheromones and heuristic information to generate local solutions. Global solutions are selected based on their high degree of similarity with other …
K-Means Clustering And Multilayer Perceptron For Categorizing Student Business Groups,
2023
Madura Islamic University, Indonesia
K-Means Clustering And Multilayer Perceptron For Categorizing Student Business Groups, Miftahul Walid, Norfiah Lailatin Nispi Sahbaniya, Hozairi Hozairi, Fajar Baskoro, Arya Yudhi Wijaya
Knowledge Engineering and Data Science
The research conducted in this study was driven by the East Java provincial government's requirement to assess the transaction levels of the Student Business Group (KUS) in the SMA Double Track program. These transaction levels are a basis for allocating supplementary financial aid to each business group. The system's primary objective is to assist the provincial government of East Java in making well-informed choices pertaining to the distribution of supplementary capital to the KUS. The classification technique employed in this study is the multilayer perceptron. However, the K-Means Clustering method is utilised to generate target data due to the limited …
Round-Robin Algorithm In Load Balancing For National Data Centers,
2023
Universitas Pendidikan Ganesha, Indonesia
Round-Robin Algorithm In Load Balancing For National Data Centers, I Kadek Wahyu Sudiatmika, Gede Indrawan, Sariyasa Sariyasa
Knowledge Engineering and Data Science
The Provincial Government of Bali assumes a crucial role in administering various public service applications to meet the requirements of its community, traditional villages, and regional apparatus. Nevertheless, the escalating magnitude of traffic and uneven distribution of requests have resulted in substantial server burdens, which may jeopardize the operation of applications and heighten the likelihood of downtime. Ensuring efficient load distribution is of utmost importance in tackling these difficulties, and the Round Robin algorithm is often utilized for this purpose. However, the current body of research has not extensively examined the distinct circumstances surrounding on-premise servers in the Bali Provincial …
Long-Term Traffic Prediction Based On Stacked Gcn Model,
2023
University of Dhaka, Bangladesh
Long-Term Traffic Prediction Based On Stacked Gcn Model, Atkia Akila Karim, Naushin Nower
Knowledge Engineering and Data Science
With the recent surge in road traffic within major cities, the need for both short and long-term traffic flow forecasting has become paramount for city authorities. Previous research efforts have predominantly focused on short-term traffic flow estimations for specific road segments and paths. However, applications of paramount importance, such as traffic management and schedule routing planning, demand a deep understanding of long-term traffic flow predictions. However, due to the intricate interplay of underlying factors, there exists a scarcity of studies dedicated to long-term traffic prediction. Previous research has also highlighted the challenge of lower accuracy in long-term predictions owing to …
Optimizing Random Forest Algorithm To Classify Player's Memorisation Via In-Game Data,
2023
Universitas Negeri Malang, Indonesia
Optimizing Random Forest Algorithm To Classify Player's Memorisation Via In-Game Data, Akmal Vrisna Alzuhdi, Harits Ar Rosyid, Mohammad Yasser Chuttur, Shah Nazir
Knowledge Engineering and Data Science
Assessment of a player's knowledge in game education has been around for some time. Traditional evaluation in and around a gaming session may disrupt the players' immersion. This research uses an optimized Random Forest to construct a non-invasive prediction of a game education player's Memorization via in-game data. Firstly, we obtained the dataset from a 3-month survey to record in-game data of 50 players who play 4-15 game stages of the Chem Fight (a test case game). Next, we generated three variants of datasets via the preprocessing stages: resampling method (SMOTE), normalization (min-max), and a combination of resampling and normalization. …
Resilience Model For Teams Of Autonomous Unmanned Aerial Vehicles (Uav) Executing Surveillance Missions,
2023
Embry-Riddle Aeronautical University
Resilience Model For Teams Of Autonomous Unmanned Aerial Vehicles (Uav) Executing Surveillance Missions, Robert Koeneke
Doctoral Dissertations and Master's Theses
Teams of low-cost Unmanned Aerial Vehicles (UAVs) have gained acceptance as an alternative for cooperatively searching and surveilling terrains. These UAVs are assembled with low-reliability components, so unit failures are possible. Losing UAVs to failures decreases the team's coverage efficiency and impacts communication, given that UAVs are also communication nodes. Such is the case of a Flying Ad Hoc Network (FANET), where the failure of a communication node may isolate segments of the network covering several nodes. The main goal of this study is to develop a resilience model that would allow us to analyze the effects of individual UAV …
On The Use Of Wireless Technologies For Wildlife Monitoring: Wireless Sensor Network Routing Protocols,
2023
Department of Mathematics and Information Communication Technology, The Open University of Tanzania, Dar es Salaam
On The Use Of Wireless Technologies For Wildlife Monitoring: Wireless Sensor Network Routing Protocols, Lilian Mutalemwa
Tanzania Journal of Engineering and Technology (TJET)
Traditional methods for wildlife monitoring are labor-intensive and time-consuming. Therefore, advanced technologies and remote monitoring methods are becoming increasingly popular. This paper presents a study on wireless technologies for wildlife monitoring. In the study, a review of the literature was done to identify the most commonly used wireless technologies. Various technologies were explored including unmanned aerial vehicles (UAVs), Internet of Things (IoT), wireless sensor networks (WSNs), artificial intelligence (AI), global positioning system (GPS), and very high frequency (VHF) radio. Then, a more detailed study was done on WSN technology. Investigations were done to observe the performance of routing protocols in …
