Digital Commons Network^™

Enhanced Cross-Modality Mri Segmentation Using Dilated Convolutions And Multi-Scale Gradient Map, Ghulam Murtaza

Chulalongkorn University Theses and Dissertations (Chula ETD)

Magnetic resonance imaging (MRI) segmentation is critical for accurate medical diagnosis, but cross-modal segmentation presents significant challenges due to domain shifts between imaging modalities and limited labeled data. This study proposes an enhanced U-Net framework designed to improve segmentation accuracy and generalization across different MRI modalities. The method incorporates dilated convolutions in the encoder to expand the receptive field, allowing for better contextual information capture without increasing the number of parameters. Additionally, squeeze and excite (SE) blocks are introduced to recalibrate channel-wise feature importance, addressing variations in tissue contrast across modalities. A multi-scale gradient map fusion strategy, based on holistic …

การประมาณค่าเส้นผ่านศูนย์กลางเพียงอกของลำต้นยูคาลิปตัสจากข้อมูลไลดาร์ที่ได้จากอากาศยานไร้คนขับด้วยเทคนิคการประมวลผลพอยต์คลาวด์, พีรพงศ์ แดงรุ่งโรจน์

Chulalongkorn University Theses and Dissertations (Chula ETD)

การจัดการป่าไม้สำคัญสำหรับการแก้ปัญหาภาวะโลกร้อน เนื่องจากความสามารถในการดูดซับก๊าซคาร์บอนไดออกไซด์ของป่าไม้ การวัดเส้นผ่านศูนย์กลางเพียงอกของต้นไม้จำเป็นในการประเมินความสามารถในการกักเก็บคาร์บอนของป่าไม้ ซึ่งสำคัญในการพัฒนาการจัดการป่าไม้ให้มีประสิทธิภาพ วิธีการดั้งเดิมใช้แคลิเปอร์หรือเทปในการวัดเส้นผ่านศูนย์กลางเพียงอก ซึ่งใช้แรงและเวลามาก เพราะฉะนั้นวิทยานิพนธ์นี้นำเสนอวิธีการในการประมาณค่าเส้นผ่านศูนย์กลางเพียงอกของลำต้นยูคาลิปตัสจากข้อมูลไลดาร์ที่ได้จากอากาศยานไร้คนขับซึ่งเป็นวิธีที่รวดเร็วและมีประสิทธิภาพสำหรับป่าไม้ขนาดใหญ่ แต่ปัญหาคือความหนาแน่นของจุดข้อมูลไลดาร์ต่ำเนื่องจากระยะห่างระหว่างอากาศยานไร้คนขับติดกล้องไลดาร์และต้นไม้ วัตถุประสงค์ของงานวิจัยนี้คือพัฒนาวิธีการประมาณเส้นผ่านศูนย์กลางเพียงอกภายใต้ปัญหาดังกล่าว ขั้นตอนประกอบด้วย การเก็บข้อมูล การทำให้ข้อมูลเป็นมาตรฐาน การแบ่งแยกต้นไม้แต่ละต้น การแบ่งแยกลำต้น การแปลง 2 มิติ และการประมาณค่าเส้นผ่านศูนย์เพียงอกด้วยเทคนิคต่างๆ ได้แก่ การประมาณค่าเส้นผ่านศูนย์กลางเพียงอกด้วยการปรับค่าด้วยค่าคงที่ การประมาณค่าเส้นผ่านศูนย์กลางเพียงอกด้วยคุณลักษณะของเปลือกหุ้มคอนเวกซ์ และการประมาณค่าเส้นผ่านศูนย์กลางเพียงอกด้วยคุณลักษณะของต้นไม้ ประสิทธิภาพของแต่ละวิธีถูกประเมินโดยการเปรียบเทียบกับวิธีเส้นฐานที่อ้างอิงในงานวิจัย ในแง่ของความคลาดเคลื่อน และระยะเวลาดำเนินงาน ผลการวิจัยแสดงให้เห็นว่าวิธีที่นำเสนอช่วยเพิ่มความแม่นยำในการประมาณเส้นผ่านศูนย์กลางเพียงอกในสภาวะที่มีความหนาแน่นของจุดข้อมูลต่ำ โดยค่าความคลาดเคลื่อนเท่ากับ 1.24 เซนติเมตรหรือเท่ากับร้อยละ 9.5

Programmable Metasurface For Radiation Beam Control, Pubet Sangmahamad

Chulalongkorn University Theses and Dissertations (Chula ETD)

This dissertation focuses on the design, development, and experiment of a programmable metasurface-based reconfigurable reflectarray (R-RA) system, featuring dual polarizations and 1-bit phase shift resolution. The proposed R-RA unit cell incorporates PIN diodes to dynamically control the reflection phase of incident waves, enabling real-time beam control. The dissertation addresses the complexity of the biasing network by introducing a digital control system based on a microcontroller and shift registers, allowing independent biasing control of each unit cell. A 16 by 16 R-RA array using a microstrip Jerusalem cross-shaped element is designed, fabricated, and experimentally tested. Simulations and measurements are conducted to …

Application Of Unscented Kalman Filter To State Of Charge Estimation Of Lithium-Ion Battery, Joshua Chun-Ken Dardchuntuk

Chulalongkorn University Theses and Dissertations (Chula ETD)

Accurately estimating the State of Charge (SoC) in lithium-ion batteries is crucial for optimizing performance, lifespan, and safety in applications such as electric vehicles and renewable energy systems. Traditional methods like Coulomb counting and voltage-based techniques are often inaccurate due to measurement noise, incorrect initialization, and battery aging. This thesis explores the use of the Unscented Kalman Filter (UKF) for real-time SoC estimation, addressing nonlinear battery behavior. Computer simulations in MATLAB/Simulink demonstrate the UKF's high accuracy by comparing estimated SoC with ideal reference SoC, showing improved convergence and reduced Root Mean Square Error (RMSE). The simulations use an ideal load …

การประมาณมวลชีวภาพของต้นไม้ด้วยเทคโนโลยีไลดาร์ร่วมกับภาพถ่ายดาวเทียมเพื่อหาค่าคาร์บอนเครดิต, พสธร ธีระกานตภิรัตน์

Chulalongkorn University Theses and Dissertations (Chula ETD)

งานวิจัยนี้นำเสนอวิธีการประมาณมวลชีวภาพของต้นไม้และการคำนวณคาร์บอนเครดิตในพื้นที่จุฬาลงกรณ์มหาวิทยาลัย โดยใช้เทคโนโลยีไลดาร์จากโทรศัพท์มือถือ เก็บข้อมูลในรูปแบบแผนที่ความลึก เพื่อมาวิเคราะห์องค์ประกอบและคัดแยกชุดข้อมูลในส่วนของลำต้นในการสร้างชุดข้อมูลพอยต์คลาวด์ในรูปแบบสามมิติ และภาพถ่ายดาวเทียมเพื่อหาพื้นที่สีเขียวร่วมด้วย เพื่อวิเคราะห์เส้นผ่านศูนย์กลางระดับอก (DBH) ของต้นไม้ และสร้างความสัมพันธ์ระหว่าง DBH กับความสูงต้นไม้ ผลลัพธ์จะถูกนำไปคำนวณมวลชีวภาพต่อพื้นที่สีเขียว เพื่อคำนวณ การกักเก็บคาร์บอน และคาร์บอนเครดิตทั้งหมดในพื้นที่ศึกษา พร้อมทั้งเปรียบเทียบความแม่นยำระหว่างข้อมูลจากไลดาร์และการวัดจริง งานนี้มีเป้าหมายเพื่อสร้างวิธีการที่สะดวกและมีแบบแผนสำหรับการติดตามพื้นที่สีเขียวและคาร์บอนเครดิตในพื้นที่อื่นๆ ในอนาคต.

Multiple Face Detection And Recognition For System-On-Chip Fpgas, Siraphop Santiwiwat

Chulalongkorn University Theses and Dissertations (Chula ETD)

Recognizing multiple faces within a single frame or image presents a significant challenge in facial recognition tasks. This challenge demands robust algorithms capable of handling variations in facial position, unstable brightness, and the presence of accessories such as glasses or hats. However, in current surveillance applications, multiple face recognition is vital for maintaining various security measures. In such applications, there is a need for processors that are compact and deployable in diverse environments. FPGA is popular due to its compact size, cost-effectiveness, and high performance. In this thesis, we proposed the implementation of multiple face detection and recognition on an …

Cross-Temporal Hierarchical Forecast Reconciliation Of Natural Gas Demand, Colin O. Quinn, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Local natural gas distribution companies (LDCs) require accurate demand forecasts across various time periods, geographic regions, and customer class hierarchies. Achieving coherent forecasts across these hierarchies is challenging but crucial for optimal decision making, resource allocation, and operational efficiency. This work introduces a method that structures the gas distribution system into cross-temporal hierarchies to produce accurate and coherent forecasts. We apply our method to a case study involving three operational regions, forecasting at different geographical levels and analyzing both hourly and daily frequencies. Trained on five years of data and tested on one year, our model achieves a 10% reduction …

Contextual Matching And Aggregation Network For Mri Image Super-Resolution, Abdulhamid Muhammad

Chulalongkorn University Theses and Dissertations (Chula ETD)

High-resolution (HR) Magnetic Resonance Imaging (MRI) provides detailed visualization of healthy and pathological tissues, making it a vital tool for accurate diagnosis, and enhancing physicians’ ability to detect lesions with better precision. However, obtaining HR MRI images in practice is often challenging due to hardware limitations, extended scan durations, and patient discomfort. Super-resolution (SR) techniques have been developed to recover HR image from LR image. However, capturing and integrating local and global features remains a significant challenge, as many approaches inadequately model the complex contextual correlations across multiple scales thereby degrading reconstruction quality. To address these limitations, we propose an …

An Attention-Guided Image Super-Resolution For Scene Text, Tithnorakneath Em

Chulalongkorn University Theses and Dissertations (Chula ETD)

Scene Text Image Super-Resolution (STISR) is crucial in enhancing text recognition for low-resolution images, often degraded due to environmental and device limitations. While many existing STISR approaches leverage super-resolution techniques to refine image quality, they frequently need specialized mechanisms to extract text-specific features. Most existing methods were based on feature extraction methods that missed critical details, such as edges and text-background contrasts, that are usually important for recognition. In this work, we propose a new feature extraction method that uses Channel Attention and Spatial Attention mechanisms to emphasize features related to text, namely edges, contours, and spatial alignment. We add …

A Robust Demand Regulation Strategy For Ders In A Single-Controllable Active Distribution Network, Shah Fahad, Arman Goudarzi, Rui Bo, Muhammad Waseem, Rashid Al-Ammari, Atif Iqbal

Electrical and Computer Engineering Faculty Research & Creative Works

Over the past decade, pq regulation schemes for a single-controllable active distribution network (adn) using coordination among a network of virtual synchronous generators (vsgs) have been proposed. However, considering the variable nature of intermittent renewable energy sources (iress), coupling a cluster of iress with the point of common coupling (pcc) of adn could inflict transient issues for the power management of the whole adn. To counter these challenges, the proposed study has three main objectives: 1) to propose a modified mathematical model that represents the apparent resistance-reactance at the pcc of adn in relation to the pq coordination among the …

Modeling Of Power Distrubition Network (Pdn) Noise Coupling Induced Clock Phase Noise, Zhekun Peng, Junyong Park, Chaofeng Li, Joey Stecher, Srinivas Venkataraman, Xu Wang, Granthana Rangaswamy, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

Phase noise analysis is important to clock design. Noise sources of spurs shown on the phase noise result are challenging to find out due to the unknown source locations and coupling mechanisms. Noise from power distribution network (PDN) is one of the most troublesome sources. A behavioral modeling methodology is proposed to simulate the clock phase noise induced by PDN noise coupling for two different mechanisms: PDN-to-clock additive coupling and PDN-to-PDN up-conversion modulation. The thermal noise and 1/f flicker noise are simplified to provide a straightforward view of spur level. The model can be applied to both single-ended clock and …

Online Continual Safe Reinforcement Learning-Based Optimal Control Of Mobile Robot Formations, Irfan Ganie, S. Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

In this work, a leader-follower tracking and formation control strategy for mobile robots (MRs) with uncertain dynamics is proposed. This strategy utilizes a continual lifelong safe reinforcement learning (CLSRL) framework based on multilayer neural networks (MNNs). The proposed design employs actor-critic MNNs, incorporating a barrier function. This function is derived from the Bellman optimality principle. It addresses the state constraints throughout the control design process. A novel online continual lifelong learning (CLL) method is introduced for MR formation. This method leverages the Bellman residual error for weight significance in MNNs. It addresses catastrophic forgetting and interlayer dependence through layer-specific regularizers. …

Real-Time Occupancy-Based Control Of Hvac Systems In Office Buildings Considering Energy Saving And Thermal Comfort, Emmanuel Agabi

Chulalongkorn University Theses and Dissertations (Chula ETD)

Traditional heating, ventilation, and air conditioning (HVAC) control systems often waste energy and fail to maintain thermal comfort due to their reliance on static setpoints, manual on/off control, and limited responsiveness to occupancy and weather conditions. With advancements in the Internet of Things (IoT), integrating occupancy data into building energy management systems, including HVAC systems, has progressed beyond conventional sensor-based approaches. This thesis addresses the inefficiency of traditional control of HVAC systems by proposing two strategies for a single-zone office building. The first one is occupancy-based control (OBC), and the second is data-driven supervisory model predictive control (SMPC). By leveraging …

Federated Learning: Overview, Strategies, Applications, Tools And Future Directions, Betul Yurdem, Murat Kuzlu, Mehmet Kemal Gullu, Maliha Tabassum

Engineering Technology Faculty Publications

Federated learning (FL) is a distributed machine learning process, which allows multiple nodes to work together to train a shared model without exchanging raw data. It offers several key advantages, such as data privacy, security, efficiency, and scalability, by keeping data local and only exchanging model updates through the communication network. This review paper provides a comprehensive overview of federated learning, including its principles, strategies, applications, and tools along with opportunities, challenges, and future research directions. The findings of this paper emphasize that federated learning strategies can significantly help overcome privacy and confidentiality concerns, particularly for high-risk applications.

Integrating Generative Artificial Intelligence With Systems Architecting Diagram Creation: Advancement, Challenges, Opportunities And Future Perspectives, Cansu Yalim, Holly H. Handley

Engineering Management & Systems Engineering Faculty Publications

Generative AI (GenAI) serves as a powerful tool that can create a wide range of content, including but not limited to text, speech, images, code, videos, and 3D models. ChatGPT stands out as a particularly appealing Generative Pretrained Transformer (GPT) model that offers supplementary capabilities through GPTs and plugins. These extensions enable users to engage with the chatbot and improve its functionality, surpassing mere content generation. Our study delves into the potential of ChatGPT, specifically GPT-4, to expedite the creation of diagrams to support the system architecting process. To this end, we explored the use of ChatGPT's Diagrams Show Me …

Generation Expansion Planning In Isolated Power Systems: A Robust Approach With Dunkelflaute Assessment, Taraneh Ghanbarzadeh, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

Generation expansion planning is vital for decarbonizing power systems and ensuring a reliable and sustainable energy future. Strategically adding new generation and grid capacity is essential for supporting a seamless transition to renewable energy while reducing greenhouse gas emissions. However, achieving the optimal capacity mix of energy resources to ensure network reliability and economic efficiency presents significant challenges, particularly for isolated electricity grids. These challenges are exacerbated during periods of low renewable generation and due to the inherent intermittency of weather-dependent energy resources. This paper presents a comprehensive approach to optimizing long-term expansion planning for an isolated electricity grid, focusing …

Blind Source Separation And Denoising Of Underwater Acoustic Signals, Ruba Zaheer, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi

Research outputs 2022 to 2026

Due to the addition of new underwater vessels and other natural noise contributors, the underwater environment is becoming congested and noisy. Undersea monitoring sonobuoys receive multiple mixed acoustic signals from different vessels that need to be separated and identified in the presence of underwater noise (UWN). It is extremely challenging to separate highly correlated acoustic signals from a noisy mixture without prior knowledge of mixing process and propagation channel. Also, in many cases, the separated signals from the noisy mixture doesn’t accurately describe the correct signal. This study proposes a novel multi-stage method to separate underwater acoustic source signals from …

Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia

Research outputs 2022 to 2026

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …

A Charging Strategy For Large Commercial Electric Vehicle Fleets, Bassam Al-Hanahi, Iftekhar Ahmad, Daryoush Habibi, Pravakar Pradhan, Mohammad A. S. Masoum

Research outputs 2022 to 2026

The popularity of Commercial Electric Vehicles (CEVs) has experienced a surge in recent years, particularly in urban vocational contexts, as a means of advancing towards the goal of attaining net-zero emissions by 2050. The return-to-base charging strategy, which involves charging CEVs at depots, has become a prevalent practice for smaller CEV fleets. Nevertheless, for larger CEV fleets, the limited charging capacity at depots presents a significant challenge, leading to a reliance on both limited depot charging infrastructure and public charging infrastructure. This reliance can have a substantial impact on both the operational costs and the sustainability of logistics services. To …

Enhancing Energy Efficiency With A Dynamic Trust Measurement Scheme In Power Distribution Network, Yilei Wang, Xin Sun, Guiping Zheng, Ahmar Rashid, Sami Ullah, Hisham Alasmary, Muhammad Waqas

Research outputs 2022 to 2026

The application of Intelligent Internet of Things (IIoT) in constructing distribution station areas strongly supports platform transformation, upgrade, and intelligent integration. The sensing layer of IIoT comprises the edge convergence layer and the end sensing layer, with the former using intelligent fusion terminals for real-time data collection and processing. However, the influx of multiple low-voltage in the smart grid raises higher demands for the performance, energy efficiency, and response speed of the substation fusion terminals. Simultaneously, it brings significant security risks to the entire distribution substation, posing a major challenge to the smart grid. In response to these challenges, a …

Application Of The Mixed Integer Nonlinear Programming Technique For The Economic Planning Of Transmission Networks In New Manner, Nader Shawky Abdelhakeem, Maged Gamal Lotfy, Mohamed Shibl Albags, Ahmed Saied Elzawawy

Mansoura Engineering Journal

In the recent years, the mathematical planning model of transmission networks based on full AC load flow has been developed. But, due to the model non-convexity and the existing of large number of local solutions, this model can only be used for small size networks as it consumes large unreasonable computation time in addition to its incapability to yield global solution in most cases. To overcome these problems, two new iterative solution procedures have been presented in this paper. In the first one, the objective function is changed to the minimization of the number of new lines required to satisfy …

Distribution System Losses Allocation Based On Circuit Theory With Distributed Generation, Ahmed S. Abdelkader, Ibrahim I. Mansy, Abdelfattah A. Eladl

Mansoura Engineering Journal

Electricity energy is the most convenient and efficient form of energy transmission and conversion. Nonetheless, losses take place while electrical power is traveling from power stations through transmission and distribution networks to the loads. Despite the high efficiency of electrical transmission and distribution networks, the huge amounts of power moving through these networks make the financial loss due to the lost energy very high and its management becomes a critical consideration for both utility providers and regulatory bodies. The efficient management of losses encompasses two major functions: the first is running the system in a way that minimizes the losses; …

Towards Digital Twins For Optimizing Metrics In Distributed Storage Systems - A Review, May Itani, Layal Abu Daher, Ahmad Hammoud

BAU Journal - Science and Technology

With the exponential data growth, there is a crucial need for highly available, scalable, reliable, and cost-effective Distributed Storage Systems (DSSs). To ensure such efficient and fault tolerant systems, replication and erasure coding techniques are typically used in traditional DSSs. However, these systems are prone to failure and require different failure prevention and recovery algorithms. Failure recovery of DSS and data reconstruction techniques take into consideration different performance metrics optimization in the recovery process. In this paper, DSS performance metrics are introduced. Several recent papers related to adopting erasure coding in DSSs are surveyed together with highlighting related performance metrics …

The Interaction Of The Cotton Piece With The Piles Of The Scrabble Cotton Drum, Fazliddin Egamberdiev, Ilkhom Abbazov, Oybek Kholmuratov, Rashid Kaldybaev

Technical science and innovation

This article presents the results of an analytical study of the process of loosening and cleaning raw cotton from small debris by pileging working bodies of purifiers, on the basis of which directions for further research were chosen to optimize the parameters of the developed pile drum with spherical piles and rubber strips. Cotton entering production contains impurities. The processes of loosening and cleaning the fiber shreds are key in the initial stages of ginning, as they prepare the raw cotton for ginning and directly affect the reliability, productivity of these processes and the quality of the resulting fiber. Weed …

Adaptation Algorithm For Self-Tuning Of Parameters Of Models Of Multi-Stage Flotation Processes, Nilufar Sharifzhanova, Maksadhan Yakubov, Francesco Gregoretti

Technical science and innovation

Modern methods for solving problems of planning the execution of batches of tasks in multi-stage systems are characterized by the presence of restrictions on their dimensionality, the impossibility of guaranteed obtaining better results in comparison with fixed packages for different values of the input parameters of the problem. In the article, the author solved the problem of optimizing the composition of job packages running in multi-stage systems using the branch and bound method. Research has been carried out on various ways to form package execution orders tasks in multi-stage systems (heuristic rules for ordering packages tasks in the sequence of …

Multi-Mode Regulation Of The Drying Process Of Industrial Gas, Isamidin Xakimovich Sidikov Pr, Nashvandova Gulruxsor Murot Qizi Phd

Technical science and innovation

Currently, much attention is paid to the issue of energy efficiency of gas processing enterprises. The continuous growth of world prices for energy resources requires constant improvement of the management system, providing the most optimal conditions for the flow of technological processes. A conceptual model of the heat-mass transfer process occurring in the absorber as an object of research has been developed, which characterizes the relationship of the variables involved in the drying process of natural gas, control, measurable and immeasurable, as well as controlled parameters have been selected, which are used to develop and study a mathematical model of …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Mathematical Models And Calculation Of Parameters Of Optoelectronic Angular Displacement Converters, Yuriy Gennadyevich Shipulin, Azimjon Khusanov

Chemical Technology, Control and Management

The article discusses promising optoelectronic converters (OP) for wide application of angular movements. A methodology and diagram for calculating OP with the transverse movement of a moving element is presented; in order to simplify the calculation, the weight range of angular movements is conventionally divided into three sub ranges. A graph is given of the dependence of the area of the photosensitive surface of a photo resistor made from a single crystal of high-resistivity p-type silicon.

System For Advanced Control Of Thermal Parameters Of Glass Furnaces, O'Tkir Xolmanov

Chemical Technology, Control and Management

The results of an analysis of the functioning of glass furnaces for melting semi-white or discolored glass as an object of automatic control and management are presented. Through experimental research, a parametric control scheme for a glass melting furnace was formed and a system for improved control of thermal glass melting processes was synthesized. The proposed system regulates the parameters of a furnace with a horseshoe-shaped flame development. Based on commercially produced instruments and automation equipment that ensure stabilization of thermal conditions of glass melting. The burner block control algorithm provides control over the performance of the gas burner, safety …

Improvement Of Calorimetric Quality Analyzers For Substances, Makhfuza Azimovna Radjabova

Chemical Technology, Control and Management

It is noted that the development of intelligent means of measuring qualitative indices is of topical importance. Since the quality of many substances is determined by optical methods, an algorithm for spectrophotometric data processing has been developed, which consists of primary data processing (stage I) and determination of qualitative indices of liquid products (stage II). Since the task of numerical determination of colour characteristics of transmittance coefficients of liquid samples is incorrectly set, it is recommended to use regularization methods of A.N.Tikhonov to improve metrological characteristics of the device. On the basis of regularization methods for solving incorrect problems, algorithms …