UV and Visible Spectrometers
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The document outlines the topics that will be covered in 5 units on analytical instruments. Unit I discusses spectrophotometry including Beer-Lambert law and various types of spectroscopy. Unit II covers chromatography techniques like gas chromatography and HPLC. Unit III is about industrial gas analyzers and pollution monitoring instruments. Unit IV is on pH meters and analyzers for dissolved components. Unit V is on nuclear magnetic resonance and mass spectrometry.
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Gas chromatography is most widely used analytical technique in the world
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This document describes inductively coupled plasma atomic emission spectroscopy (ICP-AES) and its applications. ICP-AES involves using inductively coupled plasma to excite sample atoms and ions, causing them to emit electromagnetic radiation at wavelengths characteristic of the elements present. This allows simultaneous multi-element analysis. The document discusses various applications of ICP-AES in environmental analysis, petrochemical analysis, metallurgy, geology, food analysis and more. It also provides details on instrumentation parameters, detection limits, sample preparation and references.
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This document outlines the syllabus statements from the Cambridge IGCSE Combined Science syllabus 0653 for exams from 2016 to 2018 regarding acids, bases and salts. It describes the key properties of acids and bases, including pH and characteristic reactions. It also covers the preparation, separation and purification of salts, methods for identifying common cations and anions using specific tests, and the identification of several common gases.
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22CYT12-Unit-V-E Waste and its Management.ppt
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
AI for Legal Research with applications, tools
AI applications in legal research include rapid document analysis, case law review, and statute interpretation. AI-powered tools can sift through vast legal databases to find relevant precedents and citations, enhancing research accuracy and speed. They assist in legal writing by drafting and proofreading documents. Predictive analytics help foresee case outcomes based on historical data, aiding in strategic decision-making. AI also automates routine tasks like contract review and due diligence, freeing up lawyers to focus on complex legal issues. These applications make legal research more efficient, cost-effective, and accessible.
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Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Generative AI Use cases applications solutions and implementation.pdf
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https://www.leewayhertz.com/generative-ai-use-cases-and-applications/
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Rainfall intensity duration frequency curve statistical analysis and modeling...
Using data from 41 years in Patna’ India’ the study’s goal is to analyze the trends of how often it rains on a weekly, seasonal, and annual basis (1981−2020). First, utilizing the intensity-duration-frequency (IDF) curve and the relationship by statistically analyzing rainfall’ the historical rainfall data set for Patna’ India’ during a 41 year period (1981−2020), was evaluated for its quality. Changes in the hydrologic cycle as a result of increased greenhouse gas emissions are expected to induce variations in the intensity, length, and frequency of precipitation events. One strategy to lessen vulnerability is to quantify probable changes and adapt to them. Techniques such as log-normal, normal, and Gumbel are used (EV-I). Distributions were created with durations of 1, 2, 3, 6, and 24 h and return times of 2, 5, 10, 25, and 100 years. There were also mathematical correlations discovered between rainfall and recurrence interval.
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Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODEL
As digital technology becomes more deeply embedded in power systems, protecting the communication
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Gas agency management system project report.pdf
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Embedded machine learning-based road conditions and driving behavior monitoring
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
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UV and Visible Spectrometers
- 1. EI8551 ANALYTICAL INSTRUMENTS UNIT I SPECTROPHOTOMETRY 9 Spectral methods of analysis – Beer-Lambert law – UV-Visible spectroscopy – IR Spectrophotometry - FTIR spectrophotometry – Atomic absorption spectrophotometry -Flame emission and atomic emission photometry – Construction, working principle, sources detectors and applications. UNIT II CHROMATOGRAPHY 9 General principles – classification – chromatographic behavior of solutes – quantitative determination – Gas chromatography – Liquid chromatography – High-pressure liquid chromatography – Applications. UNIT III INDUSTRIAL GAS ANALYZERS AND POLLUTION MONITORING INSTRUMENTS 9 Gas analyzers – Oxygen, NO2 and H2S types, IR analyzers, thermal conductivity detectors,analysis based on ionization of gases.Air pollution due to carbon monoxide, hydrocarbons, nitrogen oxides, sulphur dioxide estimation - Dust and smoke measurements. UNIT IV pH METERS AND DISSOLVED COMPONENT ANALYZERS 9 Selective ion electrodes - Principle of pH and conductivity measurements – dissolved oxygen analyzer – Sodium analyzer – Silicon analyzer – Water quality Analyzer. UNIT V NUCLEAR MAGNETIC RESONANCE AND MASS SPECTROMETRY 9 NMR – Basic principles – Continuous and Pulsed Fourier Transform NMR spectrometer –Mass Spectrometry – Sample system – Ionization methods – Mass analyzers – Types of mass spectrometry.
- 2. Analytical Instruments •Spectrophotometer •Conductivity Meter •Calorimeter •Flame Photometer •Infrared Analyzer •Oxygen Analyzers •HPLC, •Dissolved Oxygen Meter •Mercury Analysers •Thermometer •Viscometer •TOC Analyzer •Titrators •Polarimeter •Air Sampling •pH Meter •Moisture Titration •T.D.S. Meter •Oscilloscopes •
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- 36. • https://youtu.be/51DSl8BHUjg hplc 1 • https://youtu.be/YaabRXcm4M4 hplc 2 • https://youtu.be/qdmKGskCyh8 thin layer chromatography