If it is hard for you to quit smoking, then usvapeonline.com has launched an online platform for Branded E-cigarette products which will change your identity into Vapers.
Sartorius is a leading provider of laboratory products and services. They offer a wide range of instruments and consumables for weighing, liquid handling, filtration, and lab water purification. Their product lines include balances, pipettes, filters, pipette tips, and lab water systems. Sartorius also provides services like instrument installation, calibration, repair, and preventative maintenance to support customers. Their customers include research and quality control labs in industries like pharmaceuticals, chemicals, food and beverages, and academia.
This document appears to be an assignment submission cover page from a student named Amtiaz Khan from the National Textile University's Department of Fabric Manufacturing. The assignment is for the 3rd semester and is titled "Synthesis of enzymes and their application in textile wet processing", which was submitted to Sir Amjad Javed.
Md. Mahbubul Alam has over 5 years of experience in the pharmaceutical industry, working in quality assurance roles at Incepta Pharmaceuticals Ltd. He is currently a Senior Executive Officer responsible for quality surveillance, internal and external auditing, site master file preparation, and ensuring compliance with cGMP regulations. He has a Master's degree in Pharmaceutical Technology and a Bachelor's degree in Pharmacy. He is proficient in quality management systems, auditing, and computer programs like Excel, Access, and SAP QM. He has contributed to Incepta receiving GMP certificates from several regulatory authorities and has led or participated in over 40 supplier audits in Asia.
El documento clasifica y describe los diferentes tipos de hardware de una computadora. Incluye el hardware interno como la CPU y la memoria, el hardware externo o periféricos como el teclado, mouse y monitores, y los dispositivos de entrada, procesamiento, salida y almacenamiento. Explica que el hardware de entrada recibe información, el hardware de procesamiento procesa la información, el hardware de salida entrega la información procesada y el hardware de almacenamiento almacena programas e información de manera permanente.
Solid Edge is a hybrid 2D/3D CAD system from Siemens that uses synchronous technology to accelerate design processes. It offers applications for 2D drafting, 3D modeling, assemblies, automated drawings, simulation and more. Solid Edge provides tools for digital prototyping, sheet metal design, large assembly management, and integrated design analysis to help companies design better and get products to market faster.
This document discusses key concepts from the Sales of Goods Act 1930 regarding the subject matter of contracts for the sale of goods. It defines what constitutes "goods" and discusses the classification of goods into existing goods, future goods, specific goods, and unascertained goods. It explains the effects of the destruction or damage of goods in different situations, such as before or after a contract is made. The document also discusses the doctrine of caveat emptor (let the buyer beware) and exceptions to it, as well as other concepts like price, ascertainment of price, and agreement to sell at valuation.
Sartorius is a leading provider of laboratory products and services. They offer a wide range of instruments and consumables for weighing, liquid handling, filtration, and lab water purification. Their product lines include balances, pipettes, filters, pipette tips, and lab water systems. Sartorius also provides services like instrument installation, calibration, repair, and preventative maintenance to support customers. Their customers include research and quality control labs in industries like pharmaceuticals, chemicals, food and beverages, and academia.
This document appears to be an assignment submission cover page from a student named Amtiaz Khan from the National Textile University's Department of Fabric Manufacturing. The assignment is for the 3rd semester and is titled "Synthesis of enzymes and their application in textile wet processing", which was submitted to Sir Amjad Javed.
Md. Mahbubul Alam has over 5 years of experience in the pharmaceutical industry, working in quality assurance roles at Incepta Pharmaceuticals Ltd. He is currently a Senior Executive Officer responsible for quality surveillance, internal and external auditing, site master file preparation, and ensuring compliance with cGMP regulations. He has a Master's degree in Pharmaceutical Technology and a Bachelor's degree in Pharmacy. He is proficient in quality management systems, auditing, and computer programs like Excel, Access, and SAP QM. He has contributed to Incepta receiving GMP certificates from several regulatory authorities and has led or participated in over 40 supplier audits in Asia.
El documento clasifica y describe los diferentes tipos de hardware de una computadora. Incluye el hardware interno como la CPU y la memoria, el hardware externo o periféricos como el teclado, mouse y monitores, y los dispositivos de entrada, procesamiento, salida y almacenamiento. Explica que el hardware de entrada recibe información, el hardware de procesamiento procesa la información, el hardware de salida entrega la información procesada y el hardware de almacenamiento almacena programas e información de manera permanente.
Solid Edge is a hybrid 2D/3D CAD system from Siemens that uses synchronous technology to accelerate design processes. It offers applications for 2D drafting, 3D modeling, assemblies, automated drawings, simulation and more. Solid Edge provides tools for digital prototyping, sheet metal design, large assembly management, and integrated design analysis to help companies design better and get products to market faster.
This document discusses key concepts from the Sales of Goods Act 1930 regarding the subject matter of contracts for the sale of goods. It defines what constitutes "goods" and discusses the classification of goods into existing goods, future goods, specific goods, and unascertained goods. It explains the effects of the destruction or damage of goods in different situations, such as before or after a contract is made. The document also discusses the doctrine of caveat emptor (let the buyer beware) and exceptions to it, as well as other concepts like price, ascertainment of price, and agreement to sell at valuation.
E4 e extension_tx_assembly_robotics_commissioning_final-2AIMFirst
The document discusses Siemens' Tecnomatix robotics and commissioning software solutions. It describes how the software allows users to design, simulate, optimize, and validate automated manufacturing processes involving robots offline before production. Key capabilities include 3D modeling, process simulation and validation, offline programming, and virtual commissioning. The software helps maximize resource utilization and reduce production costs. Case studies show customers reducing engineering changes by simulating early and improving automation implementation.
O documento descreve os sistemas de medição e rede inteligente da Landis+Gyr e apresenta alguns casos de sucesso. A Landis+Gyr é líder global em medição inteligente e pioneira em redes inteligentes, com soluções para eletricidade, água, gás e iluminação pública. O documento também resume projetos implementados pela Landis+Gyr para a TEPCO no Japão e para a Light no Brasil.
Alternativas de Financiamento para as Escosslides-mci
MGM Sustainable Energy Fund (MSEF) finances energy efficiency and renewable energy projects in Latin America and the Caribbean and is expanding to Brazil. It focuses on efficiency projects in buildings, municipalities, and industries as well as solar, hydro, and landfill gas generation. MSEF typically invests up to 100% of project costs and uses special purpose vehicles to structure deals. It analyzes projects through several stages and uses operating leases, power purchase agreements, or shared savings contracts. The portfolio has 73% in energy efficiency and 27% in renewables. The pipeline shows most investments planned for Colombia, Mexico, and Brazil.
This document discusses steam generators (boilers) in three parts. It is presented by Mohammad Shoeb Siddiqui, a senior shift supervisor at Saba Power Plant. Part 1 covers introduction and types of steam generators. Part 2 discusses parts, accessories, and auxiliaries of steam generators. Part 3 covers design, efficiency, performance, and protection of steam generators. The document provides detailed information on classification, fundamentals of design, combustion processes, and other technical aspects of steam generators.
Cooling water is used to remove heat from machines and can be recycled or used once. Recirculating systems use cooling towers or ponds to remove heat. Industrial cooling towers use water sources like rivers as makeup water to replace evaporated water. They continuously circulate water through heat exchangers where heat is absorbed and rejected to the atmosphere through partial water evaporation. Different types of cooling towers exist like natural draft, induced draft, and forced draft towers which vary based on design and how air is moved through the tower. Key components, performance parameters, and maintenance factors of cooling towers are discussed.
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.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...amsjournal
The Fourth Industrial Revolution is transforming industries, including healthcare, by integrating digital,
physical, and biological technologies. This study examines the integration of 4.0 technologies into
healthcare, identifying success factors and challenges through interviews with 70 stakeholders from 33
countries. Healthcare is evolving significantly, with varied objectives across nations aiming to improve
population health. The study explores stakeholders' perceptions on critical success factors, identifying
challenges such as insufficiently trained personnel, organizational silos, and structural barriers to data
exchange. Facilitators for integration include cost reduction initiatives and interoperability policies.
Technologies like IoT, Big Data, AI, Machine Learning, and robotics enhance diagnostics, treatment
precision, and real-time monitoring, reducing errors and optimizing resource utilization. Automation
improves employee satisfaction and patient care, while Blockchain and telemedicine drive cost reductions.
Successful integration requires skilled professionals and supportive policies, promising efficient resource
use, lower error rates, and accelerated processes, leading to optimized global healthcare outcomes.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
E4 e extension_tx_assembly_robotics_commissioning_final-2AIMFirst
The document discusses Siemens' Tecnomatix robotics and commissioning software solutions. It describes how the software allows users to design, simulate, optimize, and validate automated manufacturing processes involving robots offline before production. Key capabilities include 3D modeling, process simulation and validation, offline programming, and virtual commissioning. The software helps maximize resource utilization and reduce production costs. Case studies show customers reducing engineering changes by simulating early and improving automation implementation.
O documento descreve os sistemas de medição e rede inteligente da Landis+Gyr e apresenta alguns casos de sucesso. A Landis+Gyr é líder global em medição inteligente e pioneira em redes inteligentes, com soluções para eletricidade, água, gás e iluminação pública. O documento também resume projetos implementados pela Landis+Gyr para a TEPCO no Japão e para a Light no Brasil.
Alternativas de Financiamento para as Escosslides-mci
MGM Sustainable Energy Fund (MSEF) finances energy efficiency and renewable energy projects in Latin America and the Caribbean and is expanding to Brazil. It focuses on efficiency projects in buildings, municipalities, and industries as well as solar, hydro, and landfill gas generation. MSEF typically invests up to 100% of project costs and uses special purpose vehicles to structure deals. It analyzes projects through several stages and uses operating leases, power purchase agreements, or shared savings contracts. The portfolio has 73% in energy efficiency and 27% in renewables. The pipeline shows most investments planned for Colombia, Mexico, and Brazil.
This document discusses steam generators (boilers) in three parts. It is presented by Mohammad Shoeb Siddiqui, a senior shift supervisor at Saba Power Plant. Part 1 covers introduction and types of steam generators. Part 2 discusses parts, accessories, and auxiliaries of steam generators. Part 3 covers design, efficiency, performance, and protection of steam generators. The document provides detailed information on classification, fundamentals of design, combustion processes, and other technical aspects of steam generators.
Cooling water is used to remove heat from machines and can be recycled or used once. Recirculating systems use cooling towers or ponds to remove heat. Industrial cooling towers use water sources like rivers as makeup water to replace evaporated water. They continuously circulate water through heat exchangers where heat is absorbed and rejected to the atmosphere through partial water evaporation. Different types of cooling towers exist like natural draft, induced draft, and forced draft towers which vary based on design and how air is moved through the tower. Key components, performance parameters, and maintenance factors of cooling towers are discussed.
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.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
UNLOCKING HEALTHCARE 4.0: NAVIGATING CRITICAL SUCCESS FACTORS FOR EFFECTIVE I...amsjournal
The Fourth Industrial Revolution is transforming industries, including healthcare, by integrating digital,
physical, and biological technologies. This study examines the integration of 4.0 technologies into
healthcare, identifying success factors and challenges through interviews with 70 stakeholders from 33
countries. Healthcare is evolving significantly, with varied objectives across nations aiming to improve
population health. The study explores stakeholders' perceptions on critical success factors, identifying
challenges such as insufficiently trained personnel, organizational silos, and structural barriers to data
exchange. Facilitators for integration include cost reduction initiatives and interoperability policies.
Technologies like IoT, Big Data, AI, Machine Learning, and robotics enhance diagnostics, treatment
precision, and real-time monitoring, reducing errors and optimizing resource utilization. Automation
improves employee satisfaction and patient care, while Blockchain and telemedicine drive cost reductions.
Successful integration requires skilled professionals and supportive policies, promising efficient resource
use, lower error rates, and accelerated processes, leading to optimized global healthcare outcomes.
DEEP LEARNING FOR SMART GRID INTRUSION DETECTION: A HYBRID CNN-LSTM-BASED MODELgerogepatton
As digital technology becomes more deeply embedded in power systems, protecting the communication
networks of Smart Grids (SG) has emerged as a critical concern. Distributed Network Protocol 3 (DNP3)
represents a multi-tiered application layer protocol extensively utilized in Supervisory Control and Data
Acquisition (SCADA)-based smart grids to facilitate real-time data gathering and control functionalities.
Robust Intrusion Detection Systems (IDS) are necessary for early threat detection and mitigation because
of the interconnection of these networks, which makes them vulnerable to a variety of cyberattacks. To
solve this issue, this paper develops a hybrid Deep Learning (DL) model specifically designed for intrusion
detection in smart grids. The proposed approach is a combination of the Convolutional Neural Network
(CNN) and the Long-Short-Term Memory algorithms (LSTM). We employed a recent intrusion detection
dataset (DNP3), which focuses on unauthorized commands and Denial of Service (DoS) cyberattacks, to
train and test our model. The results of our experiments show that our CNN-LSTM method is much better
at finding smart grid intrusions than other deep learning algorithms used for classification. In addition,
our proposed approach improves accuracy, precision, recall, and F1 score, achieving a high detection
accuracy rate of 99.50%.
Optimizing Gradle Builds - Gradle DPE Tour Berlin 2024Sinan KOZAK
Sinan from the Delivery Hero mobile infrastructure engineering team shares a deep dive into performance acceleration with Gradle build cache optimizations. Sinan shares their journey into solving complex build-cache problems that affect Gradle builds. By understanding the challenges and solutions found in our journey, we aim to demonstrate the possibilities for faster builds. The case study reveals how overlapping outputs and cache misconfigurations led to significant increases in build times, especially as the project scaled up with numerous modules using Paparazzi tests. The journey from diagnosing to defeating cache issues offers invaluable lessons on maintaining cache integrity without sacrificing functionality.
The CBC machine is a common diagnostic tool used by doctors to measure a patient's red blood cell count, white blood cell count and platelet count. The machine uses a small sample of the patient's blood, which is then placed into special tubes and analyzed. The results of the analysis are then displayed on a screen for the doctor to review. The CBC machine is an important tool for diagnosing various conditions, such as anemia, infection and leukemia. It can also help to monitor a patient's response to treatment.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
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.