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Articles 1651 - 1680 of 17029
Full-Text Articles in Entire DC Network
Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber
Functional Monitoring For Run-Time Assurance Of A Real-Time Cyber Physical System, Matthew W. Gelber
Theses and Dissertations
As cyber-physical systems (CPS) become more integrated into everyday life, the security of these systems must also be considered during their development due to their ever-increasing importance. With the growth of physical components in the system, more autonomous control requirements, and increased dependence on proper functionality, verifying system safety and correct operation becomes increasingly difficult. CPS have become more complex through the combination of additional hardware and the resulting interconnected software in many layers, each requiring unique security solutions. One example of such a safety-critical CPS embedded system is the Flight Control System (FCS) of an Unmanned Aerial System (UAS). …
Spin Wave Devices For Embedded Applications And Information Processing, Raisa Fabiha
Spin Wave Devices For Embedded Applications And Information Processing, Raisa Fabiha
Theses and Dissertations
Device miniaturization is a prerequisite for modern day electronics. Spintronics offers immense potential in energy efficient data storage, solid states devices, ultrafast computing and other electronic applications because of their low power consumption, non-volatile nature and unique activation mechanism. The conventional nano-antennas used for wireless communication, biomedical and wearable devices and IoT applications are limited by the traditional Harrington limit. As we attempt to miniaturize the antenna size beyond its emitted wavelength (also called “subwavelength” antenna), its gain and efficiency plummet. To overcome this challenge, the researchers have proposed magnetoelectric antennas. The ultra-thin film based magnetoelastic antennas suffer from eddy …
Machine Learning Assisted Optimization For Calculation And Automated Tuning Of Antennas, Lauren Linkous
Machine Learning Assisted Optimization For Calculation And Automated Tuning Of Antennas, Lauren Linkous
Theses and Dissertations
The Antenna Calculation and Autotuning Tool (AntennaCAT) software suite represents a significant advancement in the field of antenna design by automating the entire design, CAD, simulation, and optimization process compatible with several EM simulation software suites. It is the first comprehensive implementation of machine learning in this context. In particular, this work includes the capability to create and export structured datasets from the aforementioned EM software for iterative improvement and includes an expandable selection of optimizers.
Experimental Investigation Of Self-Mixing Interferometric Technique For Displacement Assessment, Dulanjana Anuhas Egodagamage
Experimental Investigation Of Self-Mixing Interferometric Technique For Displacement Assessment, Dulanjana Anuhas Egodagamage
Chulalongkorn University Theses and Dissertations (Chula ETD)
The self-mixing interferometric (SMI) technique has proven effective for achieving precise, contactless measurements of submicron displacements. This study aims to further investigate and experimentally assess the capabilities of the SMI technique in displacement sensing. While extensive research has been conducted on the SMI technique for displacement sensing, its performance can still be further explored in scenarios where the target exhibits varying displacement amplitudes and oscillation frequencies. Understanding the limitations and ranges of the SMI technique is crucial for advancing laboratory-based setups into practical applications. An experimental optoelectronic setup was used in this work, employing a semiconductor laser diode module integrated …
การพัฒนาแพลตฟอร์มเมตาเวิร์สแบบเว็บที่มีระบบสนับสนุนปัญญาประดิษฐ์, สืบพงศ์ น้อยศรี
การพัฒนาแพลตฟอร์มเมตาเวิร์สแบบเว็บที่มีระบบสนับสนุนปัญญาประดิษฐ์, สืบพงศ์ น้อยศรี
Chulalongkorn University Theses and Dissertations (Chula ETD)
วิทยานิพนธ์ฉบับนี้นำเสนอการพัฒนาต้นแบบแพลตฟอร์มเมตาเวิร์สที่มีขีดความสามารถขั้นพื้นฐานครอบคลุมระบบอวาทาร์ ระบบผู้ใช้หลายราย ระบบสื่อสารตามเวลา ระบบการเชื่อมต่อแชตบอต และฉากโลกเสมือนจริงสามมิติที่เหมือนจริง แพลตฟอร์มที่พัฒนาขึ้นนี้ถูกนำไปใช้ประโยชน์กับหน่วยงานภาคการศึกษาและภาคธุรกิจ ทั้งหน่วยงานภายในจุฬาลงกรณ์มหาวิทยาลัยและสถาบันการศึกษาทั้งในประเทศและระดับนานาชาติ ผลการทดสอบพบว่าระบบทำงานได้ให้ผลสัมฤทธิ์ที่ดีและมีคุณภาพตามความต้องการใช้งานในทางปฏิบัติ สามารถประยุกต์ใช้กับการสร้างห้องเรียนเสมือนออนไลน์ในโลกเสมือนจริง รองรับระบบการสื่อสารระหว่างผู้ใช้ทั้งภาพ เสียง และข้อความ อีกทั้งยังสามารถใช้งานร่วมกับระบบแชตบอตจากภายนอกได้ผ่านระบบเอพีไอที่พัฒนาขึ้น ผลการทดสอบบนระบบคลาวด์ของบริษัท โทรคมนาคมแห่งชาติ จำกัด แสดงให้เห็นว่าระบบสามารถรองรับปริมาณผู้ใช้งานได้ไม่น้อยกว่า 30 รายพร้อมกัน ผลการทดสอบในเชิงประสบการณ์การใช้งานมีระดับความพึงพอใจในเชิงบวก งานวิจัยและพัฒนาจึงให้ประโยชน์และเป็นจุดเริ่มต้นของการประยุกต์ใช้เทคโนโลยีเมตาเวิร์สในวงกว้าง
Blockchain Based Framework For Secure And Decentralized Energy Trading - Transforming Local Energy Markets For Sustainable Communities, Saurabh Sachdeva
Blockchain Based Framework For Secure And Decentralized Energy Trading - Transforming Local Energy Markets For Sustainable Communities, Saurabh Sachdeva
Dissertations and Theses
The emergence of prosumers provides an opportunity for the setup of a local energy market (LEM) where individual households with distributed energy resources (DERs) can produce, store, and trade energy. Peer-to-peer(P2P) and decentralized energy trading (ET) can be implemented between the participants within or across microgrids. Several solutions based on the existing technologies have been proposed worldwide for the integration of prosumers in the existing energy setup and to enable and support ET, but these solutions present the issues of centralization, data integrity, and confidentiality, user and anonymity, and transparency. The applications of blockchain technology have recently become fascinating for …
Ring Resonators Intergrating With Dichoric Materials And In Spin-Valley Controlled Photonic Topological System, Yuma Kawaguchi
Ring Resonators Intergrating With Dichoric Materials And In Spin-Valley Controlled Photonic Topological System, Yuma Kawaguchi
Dissertations and Theses
Photonic technology plays an important role in the development of diverse applications, ranging from optical telecommunications to sensing and imaging. The utilization of photonic circuits emerges as a promising platform for the establishment of advanced communication systems characterized by high speed and large capacity. This advancement is crucial to facilitate fast and efficient data transfer while concurrently managing multiple devices. It is imperative that essential components such as lasers, modulators, and isolators exhibit compactness without incurring significant losses.
Non-reciprocal devices represent a valuable addition to photonic circuits, enabling the creation of unidirectional waveguides that function as optical isolators, preventing signals …
Re-Envisioning Electric Railway Power Systems In Dense Urban Regions, Rohama Ahmad
Re-Envisioning Electric Railway Power Systems In Dense Urban Regions, Rohama Ahmad
Dissertations and Theses
Grid decarbonization and modernization are key requisites to combat global warming. Decarbonization entails the deployment of renewable energy sources, improving the energy efficiency of major consumers, and the electrification of the transportation and building sectors. Various US states and cities have pledged to reduce greenhouse gas (GHG) emissions (e.g., the Climate Leadership and Community Protection Act (CLCPA) in New York aims to reduce emissions to 40% below 1990 levels by 2030 and then to 85% below 1990 levels by 2050) via a set of targets in terms of renewable energy, energy storage system (ESS) capacity, and the number of electric …
An Unsupervised Learning Framework For Determining The Excitation Coefficients Using Near-Field Antenna Measurements, Yanming Zhang, Peifeng Ma, Steven Gao, Lijun Jiang
An Unsupervised Learning Framework For Determining The Excitation Coefficients Using Near-Field Antenna Measurements, Yanming Zhang, Peifeng Ma, Steven Gao, Lijun Jiang
Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works
This article presents a novel unsupervised learning framework based on multiscale dynamic mode decomposition for determining the excitation coefficients of antennas using time-domain near-field measurements. The proposed framework integrates temporal multiscale analysis to extract a joint distribution of frequency, damping factors, and spatial modes, enabling precise extraction of excitation frequencies, rising/falling edges, and phases without labeled data. We validate the effectiveness of the proposed approach through two examples involving on-off keying modulation and a phase-shift dipole antenna. It is found that the proposed method performs well in handling nonstationary excitation signals and proves particularly advantageous for calibrating tunable antenna systems. …
Explore Security And Machine Learning Applications In Next Generation Wireless Networks, Haolin Tang
Explore Security And Machine Learning Applications In Next Generation Wireless Networks, Haolin Tang
Theses and Dissertations
Next-generation (NextG) or Beyond-Fifth-Generation (B5G) wireless networks have become a prominent focus in academic and industry circles. This is driven by the increasing demand for cutting-edge applications such as mobile health, self-driving cars, the metaverse, digital twins, virtual reality, and more. These diverse applications typically require high communication network performance, including spectrum utilization, data speed, and latency. New technologies are emerging to meet the communication requirements of various applications. Intelligent Reflecting Surface (IRS) and Artificial Intelligence (AI) are two representatives that have been demonstrated as promising and powerful technologies in NextG communications. While new technologies significantly enhance communication performance, they …
Energy Efficient Spintronic Devices For Non-Volatile Memory And Hardware Ai, Walid Al Misba
Energy Efficient Spintronic Devices For Non-Volatile Memory And Hardware Ai, Walid Al Misba
Theses and Dissertations
Nanomagnetic devices have emerged as a promising alternative to conventional complementary metal-oxide-semiconductor (CMOS) devices due to their low energy dissipation and inherent non-volatility. However, the widespread adoption of these devices requires high-density, high-speed, reliable, scalable, and energy-efficient technologies. This thesis investigates the use of nanomagnetic memory devices as both conventional Boolean memory and multistate memory for hardware AI applications.
Magnetic tunnel junctions (MTJs) are nanomagnetic memory devices that can be switched reliably and energy-efficiently using stress-mediated switching. However, realistic material inhomogeneity and scalability pose challenges for stress-mediated switching of MTJs scaled to lateral dimensions below 50 nm. We demonstrate that …
Hybrid Design Approaches For Reconfigurable Em Structures, Jonathan D. Lundquist
Hybrid Design Approaches For Reconfigurable Em Structures, Jonathan D. Lundquist
Theses and Dissertations
The modern world is replete with reasons for employing reconfigurable electromagnetic (EM) structures, but some of the most pressing needs require advancements in power consumption, speed, and footprint [1]. Next generation air defense (NGAD) fighters could benefit from new electronic warfare (EW) countermeasures [2], as well as adaptive stealth technology [3], while doctors could benefit from reconfigurable microwave ablation antennas that can modify radiation pattern and input impedance to match changes in tissue during ablation and account for variations in tumor shapes [4]. The future of antennas, filters, and lenses is reconfigurable as real-world matters of life and death may …
Bridging The Gap In Epsilon-Near-Zero Nonlinear Materials, Adam R. Ball
Bridging The Gap In Epsilon-Near-Zero Nonlinear Materials, Adam R. Ball
Theses and Dissertations
Studying how light and matter interact has been of interest to humans for thousands of years. From the invention of the first mirror, burning ants with a magnifying glass, to optical fiber communication, light has been central to mankind. Researchers have sought to take this to the extreme with nonlinear optics where intense laser light interacts with materials. The study of this thesis is to understand a new generation of materials that has come to light. Epsilon-near-zero (ENZ) materials have shown promise for ultrafast light manipulation in tandem with modern day CMOS compatible electronics. Here, I seek to bridge the …
Structural Construction And Surface Modification Of Copper Current Collectors For Lithium Metal Batteries, Yaohua Liang
Structural Construction And Surface Modification Of Copper Current Collectors For Lithium Metal Batteries, Yaohua Liang
Electronic Theses and Dissertations
Graphene, a prevalent anode material in commercial lithium-ion batteries, has reached its theoretical capacity limit. The imperative is to develop high-capacity anode materials to meet the growing demand for energy density. Lithium metal, renowned for its exceptionally high theoretical specific capacity density (3680 mAh g-1) and low reduction potential (-3.04 V, relative to the standard hydrogen electrode), is commonly dubbed the "Holy Grail" for negative electrode materials in high-energy-density batteries. However, practical advancements in lithium metal anodes face obstacles like low Coulombic efficiency, limited cycle life, and heightened reactivity to the electrolyte and internal short circuits resulting from lithium dendrite …
Comparative Analysis Of Deep Learning-Based Anomaly Detection Models For Gps Spoofing Detection, Hasan Mirzakhaninafchi
Comparative Analysis Of Deep Learning-Based Anomaly Detection Models For Gps Spoofing Detection, Hasan Mirzakhaninafchi
Electronic Theses and Dissertations
As autonomous vehicles (AVs) become integral to modern transportation, their susceptibility to cyber-attacks, particularly GPS spoofing, presents a serious security threat. This study addresses these challenges by applying a suite of deep learning models to enhance the detection of anomalous GPS signals. Focusing on autoencoder-based architectures, the proposed models such as long short-term memory-based variational autoencoder (LSTM-VAE), LSTM-based autoencoder (LSTM-AE), multilayer perceptron-based variational autoencoder (MLP-VAE), MLP-based Autoencoder (MLPAE), Stacked LSTM-based variational autoencoder (Stacked-LSTM-VAE), stacked LSTM-based autoencoder (Stacked-LSTM-AE), memory-augmented-LSTM-VAE (Mem-LSTM-VAE), and time-series-anomaly-detection-generative-adversarial-networks (TadGAN) were trained exclusively on authentic GPS data. This unsupervised learning approach which used for the above-mentioned models enables …
An Integrated Hybrid P2p-Dr Networks For A Transactive Energy Market Platform Considering Electricity Network Constraints, Sheroze Liaquat
An Integrated Hybrid P2p-Dr Networks For A Transactive Energy Market Platform Considering Electricity Network Constraints, Sheroze Liaquat
Electronic Theses and Dissertations
No abstract provided.
Economical And Environmental Evaluation Of Non-Residential Demand Response In The European Transition To Zero-Carbon Energy, Markus Fleshutz
Economical And Environmental Evaluation Of Non-Residential Demand Response In The European Transition To Zero-Carbon Energy, Markus Fleshutz
Theses
To meet climate objectives, major energy consumers with local multi-energy systems (L- MESs) must transition to renewable energy sources soon. The variability of renewable energies requires increased operational flexibility for integration. In this context, demand response (DR), a strategy in which electricity consumers adjust their load profiles in response to incentives, has become crucial, offering cost-effective flexibility. It supports L-MESs in integrating renewable energy, reducing decarbonization costs, and enhancing resilience. However, quantifying the economic DR potentials for L-MESs under carbon emission constraints is complex, especially when considering investment options in distributed energy resources. This complexity hinders the rapid adoption of …
Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy
Ontolog Summit 2024 Talk Report: Healthcare Assistance Challenges-Driven Neurosymbolic Ai, Kaushik Roy
Publications
Although Artificial Intelligence technology has proven effective in providing healthcare assistance by analyzing health data, it still falls short in supporting decision-making. This deficiency largely stems from the predominance of opaque neural networks, particularly in mental health care AI applications, which raise concerns about their unpredictable and unverifiable nature. This skepticism hinders the transition from information support to decision support. This presentation will explore neurosymbolic approaches that combine neural networks with symbolic control and verification mechanisms. These approaches aim to unlock AI’s full potential by enhancing information analysis and decision-making support for healthcare assistance1.
External Runtime Execution Monitoring Of A Cyber Physical System Via Trace Interfaces, Peter Vaughan Truslow
External Runtime Execution Monitoring Of A Cyber Physical System Via Trace Interfaces, Peter Vaughan Truslow
Theses and Dissertations
In the past two decades, Unmanned Aerial Systems have progressed from expensive military hardware or one-off custom builds, to include off-the-shelf drones that can be purchased for a rather affordable price and flown by nearly anyone. As the technology and performance have improved, the door is opened to applications that require operation in environments where the consequences for failure are high, such as operating in the navigable airspace or in urban environments, or with human passengers. This requires a great deal of trust in the reliability and integrity of the control systems of the aircraft. A method of monitoring the …
Information Access For Infrastructurally-Challenged Environments And Beyond Through Mutually Aware Spectrum Sharing Technologies, Karyn Doke
Electronic Theses & Dissertations (2024 - present)
The Radio Frequency (RF) spectrum is scarce and to make it available for new mobile wireless services, regulators are forced to re-allocate spectrum from existing services or develop mechanisms to share spectrum with new entries. Television White Space (TVWS) and Citizen Broadband Radio Service (CBRS) are two examples of recently commercialized spectrum sharing technologies. TVWS enables sharing among fixed wireless broadband technologies (secondary users) and terrestrial TV broadcast services (primary users). CBRS enables spectrum sharing among 5G/LTE (secondary users) and naval radar (primary users). With both technologies, a central database determines when it is safe for secondary users to operate …
Sparse Representation Learning For Temporal Networks, Maxwell Mcneil
Sparse Representation Learning For Temporal Networks, Maxwell Mcneil
Electronic Theses & Dissertations (2024 - present)
Temporal networks arise in many domains including activity of social network users, sensor network readings over time, and time course gene expression within the interaction network of a model organism. Data of this type contains a wealth of prior information such as the connectivity among nodes (e.g., a friendship graph), and prior knowledge of expected temporal patterns (e.g., periodicity). Modeling these temporal and network patterns jointly is essential for state-of-the-art performance in temporal network data analysis and mining. Sparse dictionary encoding is one modeling approach for such underlying patterns. However, most classical approaches consider only one dimension of the data …
Design Of An Adaptive Robust Pi Controller For Dc/Dc Boost Converter Using Reinforcement-Learning Technique And Snake Optimization Algorithm, Seyyedmorteza Ghamari, Mojtaba Hajihosseini, Daryoush Habibi, Asma Aziz
Design Of An Adaptive Robust Pi Controller For Dc/Dc Boost Converter Using Reinforcement-Learning Technique And Snake Optimization Algorithm, Seyyedmorteza Ghamari, Mojtaba Hajihosseini, Daryoush Habibi, Asma Aziz
Research outputs 2022 to 2026
The DC/DC Boost converter exhibits a non-minimum phase system with a right half-plane zero structure, posing significant challenges for the design of effective control approaches. This article presents the design of a robust Proportional-Integral (PI) controller for this converter with an online adaptive mechanism based on the Reinforcement-Learning (RL) strategy. Classical PI controllers are simple and easy to build, but they need to be more robust against a wide range of disturbances and more adaptable to operational parameters. To address these issues, the RL adaptive strategy is used to optimize the performance of the PI controller. Some of the main …
Optimizing Energy-Efficient Grid Performance: Integrating Electric Vehicles, Dstatcom, And Renewable Sources Using The Hippopotamus Optimization Algorithm, Mohamed Abdelaziz, A.A. Ali, R.A. Swief, Rasha Elazab
Optimizing Energy-Efficient Grid Performance: Integrating Electric Vehicles, Dstatcom, And Renewable Sources Using The Hippopotamus Optimization Algorithm, Mohamed Abdelaziz, A.A. Ali, R.A. Swief, Rasha Elazab
Renewable Electrical Energy Engineering
The rapid increase in renewable energy integration and electric vehicle (EV) adoption creates significant challenges for the stability and efficiency of power distribution networks. This study addresses the need for optimized placement and sizing of Electric Vehicle Charging Stations (EVCSs), photovoltaic (PV) systems, and Distribution Static Compensators (DSTATCOMs) to enhance grid performance. The motivation for this work arises from the fluctuating nature of renewable energy generation and the unpredictable demands of EV charging, which strain existing infrastructure. To address these challenges, we propose a novel optimization framework that introduces the Renewable Distributed Generation Hosting Factor (RDG-HF) and Electric Vehicle Hosting …
Development Of A Low-Cost Resistivity Meter For Local Groundwater Survey, Jose Claro N. Monje, Ma. Leonora Guico, Carlos M. Oppus, Mark Glenn F. Retirado, Alfonso Rafael Cuezon, Justin Bryce M. Torres
Development Of A Low-Cost Resistivity Meter For Local Groundwater Survey, Jose Claro N. Monje, Ma. Leonora Guico, Carlos M. Oppus, Mark Glenn F. Retirado, Alfonso Rafael Cuezon, Justin Bryce M. Torres
Electronics, Computer, and Communications Engineering Faculty Publications
The researchers developed a low-cost resistivity meter with a built-in data file storage system using locally available parts. This effort was done in partnership with the National Water Resources Board and the Department of Science and Technology under the Water for Tourism project for water quality monitoring in tourist areas in the Philippines such as Boracay and Caticlan. The resistivity meter system consists of a power supply module, a sensor module, and an equipment module, built using locally available materials and equipment, emulating the commercially available PASI model 16 GL-N. Due to pandemic restrictions, the developed prototype could only be …
Simulation Of A Pick And Place System For Electronic Cards Using A Yumi Cobot, Derrick Sze, Rosula Sj Reyes, Patricia Angela R. Abu
Simulation Of A Pick And Place System For Electronic Cards Using A Yumi Cobot, Derrick Sze, Rosula Sj Reyes, Patricia Angela R. Abu
Electronics, Computer, and Communications Engineering Faculty Publications
Collaborative Robots are one of the main drivers of Industry 4.0, which started as a vision focusing on industrial production. It addresses several challenges in the current manufacturing industry such as performing repetitive work and requiring highly skilled workers. The goal of the research is to be able to simulate a pick and place environment with electronic cards using a YuMi cobot and mobile platforms in Coppeliasim. The mobile robot is responsible for transporting the electronic cards to the target location through path planning implemented using the OMPL plug-in. After arriving at the target location, YuMi will then perform the …
H-Nobs: Achieving Certified Fairness And Robustness In Distributed Learning On Heterogeneous Datasets, Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian
H-Nobs: Achieving Certified Fairness And Robustness In Distributed Learning On Heterogeneous Datasets, Guanqiang Zhou, Ping Xu, Yue Wang, Zhi Tian
Electrical and Computer Engineering Faculty Publications
Fairness and robustness are two important goals in the design of modern distributed learning systems. Despite a few prior works attempting to achieve both fairness and robustness, some key aspects of this direction remain underexplored. In this paper, we try to answer three largely unnoticed and unaddressed questions that are of paramount significance to this topic: (i) What makes jointly satisfying fairness and robustness difficult? (ii) Is it possible to establish theoretical guarantee for the dual property of fairness and robustness? (iii) How much does fairness have to sacrifice at the expense of robustness being incorporated into the system? To …
Cross-Layer Performance Evaluation Of C-V2x, Dhruba Sunuwar
Cross-Layer Performance Evaluation Of C-V2x, Dhruba Sunuwar
College of Graduate Studies: Theses & Dissertations
The evolution of connected vehicles from a distant futuristic concept to an integral part of daily life is indisputable. Vehicle-to-everything communication (V2X) serves as the cornerstone of this transformation, facilitating seamless interaction among vehicles, infrastructure, pedestrians, and networks. However, evaluating V2X system performance proves intricate due to the dynamic nature of vehicles influenced by mobility factors. To address this complexity, we have developed a specialized system-level simulator expressly for evaluating V2X communication performance. Notably, the simulator encompasses (i) intelligent transportation system (ITS) scenarios integrated into a geographical framework and (ii) the capability to assess cross-layer performance spanning physical (PHY) and …
An Fpga-Based Eit System For Deep Space Medical Imaging, Kendall R. Farnham
An Fpga-Based Eit System For Deep Space Medical Imaging, Kendall R. Farnham
Dartmouth College Ph.D Dissertations
Dangers associated with high radiation and microgravity exposure in space are critical challenges inhibiting us from exploring deep space and pursuing long-duration missions, as current medical systems are unable to monitor, diagnose, or treat tissue injury within physical spacecraft constraints and communication limits. Ultrasound (US) is the current imaging system used on the International Space Station, but this technology relies on telemedical support (or onboard artificial intelligence/autonomous capabilities) for both operation and diagnosis, posing challenges for crews isolated in deep space. Electrical impedance tomography (EIT) is a non-invasive, non-ionizing technology that produces images of the electrical properties of tissues and …
Smart Dog Door, Andrew Shetler, William Boissoneault, Jacob Stump, Benjamin Charlson
Smart Dog Door, Andrew Shetler, William Boissoneault, Jacob Stump, Benjamin Charlson
Williams Honors College, Honors Research Projects
With modern life getting busier and more complex, many have turned to autonomous assistance for taking care of pets. The objective of this project is to design and prototype a device and application that will allow only certain dogs to enter and exit through a dog door while making the owners aware of their dog's activity. The dog door will utilize wireless communication from the dog to the door to control the status of the door’s lock and update the database that will send updates to the application. The application will keep track of when the dog enters and exits …
A Wavegan Approach For Mmwave-Based Fanet Topology Optimization, Enas Odat, Hakim Ghazzai, Ahmad Alsharoa
A Wavegan Approach For Mmwave-Based Fanet Topology Optimization, Enas Odat, Hakim Ghazzai, Ahmad Alsharoa
Electrical and Computer Engineering Faculty Research & Creative Works
The integration of dynamic Flying Ad hoc Networks (FANETs) and millimeter Wave (mmWave) technology can offer a promising solution for numerous data-intensive applications, as it enables the establishment of a robust flying infrastructure with significant data transmission capabilities. However, to enable effective mmWave communication within this dynamic network, it is essential to precisely align the steerable antennas mounted on Unmanned Aerial Vehicles (UAVs) with their corresponding peer units. Therefore, it is important to design a novel approach that can quickly determine an optimized alignment and network topology. In this paper, we propose a Generative Adversarial Network (GAN)-based approach, called WaveGAN, …