Electrical and Electronics Commons^™

A Linear Matrix Inequality Approach To Design State Feedback Control For Non-Polynomial Nonlinear Systems, Phing Lim

Chulalongkorn University Theses and Dissertations (Chula ETD)

This thesis aims to design a state feedback controller for non-polynomial systems with bounded control inputs. The problem formulation begins by transforming the non-polynomial systems into polynomial systems. This can be done by defining non-polynomial terms as new state variables with algebraic constraints satisfying the non-polynomial properties. This method avoids the approximation of the recast polynomial systems. Then we design the state feedback control based on the extended Lyapunov stability theorem and the quadratic performance criterion. Two state feedback control laws are proposed: Theorem 1 for static Lyapunov matrix variables and Theorem 2 for polynomial ones. For Theorem 1, the …

Effect Of Drop-Out Layers Inside Recurrent Neural Networks In Household Load Forecast Application, Sanaullah Soomro

Chulalongkorn University Theses and Dissertations (Chula ETD)

Ensuring precise power load forecasting is highly important in planning the secure, steady, and cost-effective functioning of the power system. Grid planning and decision-making can be based on accurate long- and short-term power load forecasting. Recently, machine learning techniques have gained widespread adoption for both long- and short-term power load forecasting. Specifically, the Long Short-Term Memory (LSTM) is customized for time series data analysis. This research proposes an LSTM model for forecasting the power load of a single house containing electrical appliances over the next 20 days. We conducted a comparative analysis of the impact of dropout layers in load …

Performance Analysis Of Jpeg Xr With Deep Learning-Based Image Super-Resolution, Taingliv Min

Chulalongkorn University Theses and Dissertations (Chula ETD)

The demand for efficient high-level image and video codec compression has widely increased. Conventional image compression methods such as JPEG XR use a high quantization parameter (QP) to produce a highly compressed file for any given image. However, higher QP has unpleasing artifacts that lead to perceptual quality degradation. A feasible solution to tackle this limitation is to reduce the high-resolution image size by downsampling it before encoding it with JPEG XR. Then, the super-resolution algorithm is applied to the resultant low-resolution image to reconstruct the high-resolution result. In this research, we downsample the input image before JPEG XR. Then, …

Deep Consecutive Attention Network For Video Super-Resolution, Talha Saleem

Chulalongkorn University Theses and Dissertations (Chula ETD)

In the video application, slow motion is visually attractive and gets more attention in video super resolution. To generate the high-resolution (HR) slow motion video frames from the low-resolution (LR) frames, two sub-tasks are required, including video super-resolution (VSR) and video frame interpolation (VFI). However, the interpolation approach is not successful to extract low level feature attention to get the maximum advantage from the property of space-time relation. To this extent, we propose a deep consecutive attention network-based method. The multi-head attention and an attentive temporal feature module are designed to achieve better prediction of interpolation feature frame. Bi-directional deformable …

Applications Of Deep Learning Framework And Localization To Intelligent Radio Spectrum Monitoring, Truong Thanh Le

Chulalongkorn University Theses and Dissertations (Chula ETD)

In this thesis, the author proposed an intelligent radio spectrum monitoring system with implemented deep learning framework. Deep learning is a powerful method to handle hard tasks automatically. The system uses the RTL-SDR USB dongle as the sensor to collect the spectrum data. This dongle is a low-cost device that can measure the signal from 500kHz to 1700MHz. The maximum bandwidth of measurement is 2MHz. The main functions of this system are to collect the spectrum data and then detect the representation signals and extract their characteristics, such as bandwidth, center frequency, modulation type, and capacity. The modulation classification task …

Functional Split In 5g Cloud Radio Access Network Using Particle Swarm Optimization, Wai Phyo

Chulalongkorn University Theses and Dissertations (Chula ETD)

The Cloud Radio Access Network (C-RAN) is an innovative approach that has the potential to significantly reduce the expenses of setting up and operating wireless networks. C-RAN's placement of RAN functions, which strives to reduce bandwidth utilization and computation costs, is a critical component. In this study, our main goal is to reduce the costs associated with functionally placing the RAN while accounting for the computational expense and the front-haul bandwidth usage among various users. To achieve this, we propose to apply Particle Swarm Optimization (PSO) to achieve effective allocation of computational resources and the front-haul bandwidth, ensuring an efficient …

Online Self-Learning System For Prediabetes Patients, Ye Moe Myint

Chulalongkorn University Theses and Dissertations (Chula ETD)

This thesis implements a web-based application that combines a 3D learning center and educational game to facilitate the monitoring, management, and treatment of patients with prediabetes mellitus, by providing exercise plans and controlled diets. The application utilizes advanced web technologies, 3D modeling, and gamification principles to create an engaging learning experience. User-centered design ensures usability, and testing demonstrates positive outcomes, including increased knowledge, motivation, and engagement. This research contributes to digital health interventions by empowering prediabetes patients with informed decision-making and healthy habits. Future directions include expanding the application, refining the user interface, and evaluating long-term impact on prediabetes management.

Deep Iterative Convolutional Neural Network For Face Image Super-Resolution, Hein Htet Aung

Chulalongkorn University Theses and Dissertations (Chula ETD)

Face images are often used today for many purposes, including facial identification and recognition. Face identification is used in security to trace crimes. The face application performs poorly due to the camera's low quality and environmental degradation issues. In this thesis, we explore face image super-resolution, which raises low-resolution to high resolution images. We proposed a deep iterative convolutional neural network using attention mechanisms and spatial feature transformation for face super-resolution. The input low-resolution image is enlarged into a super-resolution face image. Then, the image has repeatedly estimated the alignment to enhance the super-resolution image. The experiment was conducted on …

Diabetic Retinopathy Severity Classification Using Convolutional Neural Network Withtransfer Learning, Pranajit Kumar Das

Chulalongkorn University Theses and Dissertations (Chula ETD)

Diabetic Retinopathy is a common retina disease caused by diabetes that is very difficult to diagnose initially because of its asymptomatic nature, which leads to permanent vision loss. Early and accurate detection of diabetic retinopathy is an effective way to prevent blindness. While screening programs are the most effective means of detecting diabetic retinopathy, it has various limitations like time consuming, laborious tasks, require a lot of expert ophthalmologists and technicians with standardized medical equipment. Automatic diabetic retinopathy classification using artificial intelligence and computer vision techniques mostly overcome the above-mentioned limitations despite it still being a challenging task. In this …

Hosting A Community-Based Local Electricity Market In A Residential Network, Aziz Saif, Shafi K. Khadem, Michael Conlon, Brian Norton

Articles

This paper presents the potential of building a local electricity market (LEM) to boost the deployment of the local energy communities, centred around active customers with distributed energy resources (DERs). To conduct a comprehensive and detailed study on different cases with reduced computational burdens, this paper adopts a simplified modelling approach where the market and network model simulations are performed in a cascaded, decoupled fashion. This allows achieving the optimal LEM output for the energy community with different DER assets that are not bounded by the network constraints. The investigation involves quantifying the benefits brought by LEM to energy communities …

Enhanced Chaotic Manta Ray Foraging Algorithm For Function Optimization And Optimal Wind Farm Layout Problem, Fatima Dadqaq, Rachid Ellaia, Mohammed Ouassaid, Hossam Zawbaa, Salah Kamel

Articles

Manta ray foraging optimization (MRFO) algorithm is relatively a novel bio-inspired optimization technique directed to given real-world engineering problems. In this present work, wind turbines layout (WTs) inside a wind farm is considered a real nonlinear optimization problem. In spite of the better convergence of MRFO, it gets stuck into local optima for large problems. The chaotic sequences are among the performed techniques used to tackle this shortcoming and improve the global search ability. Therefore, ten chaotic maps have been embedded into MRFO. To affirm the performance of the suggested chaotic approach CMRFO, it was First assessed using the IEEE …

The Environmental Aspects Of Renewable Energy Consumption And Structural Change In Sweden: A New Perspective From Wavelet-Based Granger Causality Approach, Tomiwa Sunday Adebayo, Ridwan Lanre Ibrahim, Ephraim Bonah Agyekum, Hossam Zawbaa, Salah Kamel

Articles

The current paper assessed the time-frequency analysis interrelationship between CO2 emissions and financial development, economic growth, renewable energy use, structural change, and non-renewable energy use in Sweden. We utilized a quarterly dataset stretching from 1980-2019. In order to unlock these interrelationships, we leverage wavelet tools (wavelet-based Granger causality and wavelet coherence). The wavelet-based Granger causality (WGC) test accounts for the issue of multiple time scales in a time series analysis. Another uniqueness of the WGC lies in its resistance to distribution assumption and misspecification in a time series model. Additionally, the wavelet coherence estimator instantaneously evaluates correlation and causality among …

An Analysis On Adversarial Machine Learning: Methods And Applications, Ali Dabouei

Graduate Theses, Dissertations, and Problem Reports (ETD)

Deep learning has witnessed astonishing advancement in the last decade and revolutionized many fields ranging from computer vision to natural language processing. A prominent field of research that enabled such achievements is adversarial learning, investigating the behavior and functionality of a learning model in presence of an adversary. Adversarial learning consists of two major trends. The first trend analyzes the susceptibility of machine learning models to manipulation in the decision-making process and aims to improve the robustness to such manipulations. The second trend exploits adversarial games between components of the model to enhance the learning process. This dissertation aims to …

Modeling Of Inverter-Based Microgrid For Small-Signal And Large-Signal Stability Analysis, Vishal Verma

Graduate Theses, Dissertations, and Problem Reports (ETD)

Integration of inverter-based resources (IBRs) such as solar photovoltaic, wind, and battery storage, is both a boon and a bane for electric power systems. On one hand, IBRs have helped in making electrical energy a clean (carbon-free) source of energy. On other hand, the dynamics of IBRs have changed the way power system studies have been carried out. With the advantages IBRs offer over conventional resources, it is assumed that a small distribution power system (microgrid) will have a 100% IBRs penetration in the future. Such a microgrid can operate in grid-connected mode or in an islanded mode. Both modes …

Iii-Nitride Nanostructures: Photonics And Memory Device Applications, Barsha Jain

Dissertations

III-nitride materials are extensively studied for various applications. Particularly, III-nitride-based light-emitting diodes (LEDs) have become the major component of the current solid-state lighting (SSL) technology. Current III-nitride-based phosphor-free white color LEDs (White LEDs) require an electron blocking layer (EBL) between the device active region and p-GaN to control the electron overflow from the active region, which has been identified as one of the primary reasons to adversely affect the hole injection process. In this dissertation, the effect of electronically coupled quantum well (QW) is investigated to reduce electron overflow in the InGaN/GaN dot-in-a-wire phosphor-free white LEDs and to improve the …

Scalable Scientific Data Management On High-Performance Computing Systems, Zhenbo Qiao

Dissertations

As high-performance computing (HPC) is being scaled up to exascale to accommodate new modeling and simulation needs, I/O has continued to be a major bottleneck in the end-to-end scientific processes. To bridge the widening gap between compute and I/O, and enable data to be more efficiently stored and analyzed, simulation outputs need to be refactored, reduced, and appropriately mapped to storage tiers. Also, a major question that the community is striving to answer is how to co-design data storage and complex physics-rich analytics in a way that the time to knowledge can be minimized in post-processing. As HPC storage systems …

Design And Learning-Based Decoding Of Low-Density-Parity-Check Codes For Multiterminal Communication, Salman Habib

Dissertations

The field of information theory was initiated by Claude Shannon in 1948. According to his most notable work, data can be transmitted reliably over a noisy communication channel with high probability, as long as a suitable coding scheme is employed to protect the data from channel noise. Since then, coding theorists have made numerous attempts to design low-complexity error correcting schemes which achieve the Shannon limit.

In the 1960s, Robert Gallager introduced sparse graph-based low-density-parity-check (LDPC) codes which are practically suitable for various coding applications, mainly due to their low encoding and decoding complexity compared to classical codes (e.g., Reed-Muller …

A New Two Switched-Impedance Network For High Ratio Quasi-Z-Source Inverter, Irham Fadlika, Mega Agustina, Rahmatullah Aji Prabowo, Misbahul Munir, Arif Nur Afandi

Elinvo (Electronics, Informatics, and Vocational Education)

The increasing demand and widespread of renewable energy inherently compel the development of power electronics converter as an interface between consumers and the energy source/s. This paper presents a new two switched-impedance networks qZSI converter called High Ratio Two Switched-impedance quasi-Z-Source Inverter (HR2SZ-qZSI). Compared with the previous topology, this proposed HR2SZ-qZSI topology can achieve higher voltage gain with lower shoot-through duty ratio, and a higher boost factor. This paper also discusses comparative analysis between the previous topology and the proposed HR2SZ-qZSI topology. Furthermore, the simulation and experimental data are presented to prove the theoretical analysis of the proposed HR2SZ-qZSI topology. …

Flood Analysis And Hydraulic Competence Of Drainage Structures Along Addis Ababa Light Rail Transit, Moses Kiwanuka, Seleshi Yilma, Joel Webster Mbujje, John Bosco Niyomukiza

Journal of Environmental Science and Sustainable Development

The occurrence of flooding events and the associated risks are increasing in the urban areas of most developing countries. Flooding in any circumstance causes major stresses on affected area’s economic, social and environmental regimes. Therefore, the current study presents a flood analysis and hydraulic competence of existing drainage structures on some selected roads of Addis Ababa City, after integration with Addis Ababa Light Rail Transit (AALRT) Drainage Systems. The existing side drains and cross drainage structures located within the study area were inspected and assessed to ascertain different aspects relating to their performance. Different watersheds were delineated. Hydrological analysis was …

Method And Methods For Determining Shapes And Sizes Of Solar Dryer Elements, Sh M. Mirzaev, J R. Kodirov, S S. Ibragimov

Scientific-technical journal

This article presents the calculation of the drying plant, the shape of which is a parallelepiped with non-isosceles triangular bases. Concepts were selected, on the basis of which a computational computational method was developed and the geometric dimensions of the elements of a direct type dryer were determined. The formula for the ratio of the dimensions of the height to the length and, accordingly, to the width of the dryer has been established, and a method has been developed for determining the dimensions of the dampers intended for the flow of air from the environment into the chamber and for …