Latest designed more durable,bottom cover legs with efficiency.We are pioneer in Pakistan in the manufacturing and innovation of Transfer Press for Garment industry.
This document provides information about diabetes mellitus including its causes, risk factors, dietary management principles, and guidelines. It is a chronic metabolic disorder associated with high blood sugar and sugar in the urine. Risk factors include hereditary factors, high blood pressure, obesity, and physical inactivity. The document outlines dietary principles like low calorie, low fat intake and recommends foods to consume and avoid for managing diabetes.
The document provides contact and product information for Hottek, a manufacturer of heat transfer presses and sublimation equipment. It lists the contact details for the factory and key personnel in Pakistan. It then describes the specifications of their automatic sublimation transfer machine models, including plate sizes ranging from 24x36 inches to 48x66 inches, digital temperature control up to 300 degrees Celsius, and automatic plate movement. Finally, it mentions they also offer a roller-type sublimation transfer machine and semi-automatic socks press.
This document provides contact and product information for Hottek, a manufacturer of heat transfer machines. It includes details on several automatic label transfer machines (models HT-1D+, HT-1DD+) and heat transfer presses (HT-6A+, HT-8A+) of varying plate sizes. Specifications are provided for these machines such as power, voltage, temperature control and safety features. Additionally, machines for rhinestone transfer and sublimation transfer up to 48x66 inches are described. Contact information is listed for the CEO and GM of Marketing.
This document provides information on Hot Tek Jeans Finishing Range equipment, including contact details, product lines, and specifications. It describes various machines for wrinkling, whiskering, heat transferring, grinding, scraping, spraying, and baking jeans. The key products summarized are the 3D Natural Whisker Machine, which creates natural whiskers using infrared heating, and the Jeans Baking Conveyor Type Oven, which bakes jeans on a conveyor belt at adjustable temperatures and speeds.
This document provides a summary of the academic and professional experience of Dr. Muhammad Mustansar. It lists his medical degrees and qualifications which include an M.B.B.S., M.Sc. in Nutrition, M. Phil in Biochemistry, and certifications in lactation management and community pediatrics. It also outlines his work history in various roles within academic medical institutions in Pakistan from 1987 to the present day. Finally, it provides a lengthy list of his publications in medical journals.
The document describes several heat transfer machines made by Hot Tek for various applications. The HT-1R is designed for roll-to-roll label transfer onto garments. The HT-1D+ and HT-1DD+ are double action machines for heat seal labels and logos. The HT-6A+ is for heat transfers onto t-shirts. Several other machines are described for specific uses such as gloves, jeans, or sublimation transfers. The SP-6A and SP-8A+ are semi-automatic and advanced socks presses.
This document provides information about diabetes mellitus including its causes, risk factors, dietary management principles, and guidelines. It is a chronic metabolic disorder associated with high blood sugar and sugar in the urine. Risk factors include hereditary factors, high blood pressure, obesity, and physical inactivity. The document outlines dietary principles like low calorie, low fat intake and recommends foods to consume and avoid for managing diabetes.
The document provides contact and product information for Hottek, a manufacturer of heat transfer presses and sublimation equipment. It lists the contact details for the factory and key personnel in Pakistan. It then describes the specifications of their automatic sublimation transfer machine models, including plate sizes ranging from 24x36 inches to 48x66 inches, digital temperature control up to 300 degrees Celsius, and automatic plate movement. Finally, it mentions they also offer a roller-type sublimation transfer machine and semi-automatic socks press.
This document provides contact and product information for Hottek, a manufacturer of heat transfer machines. It includes details on several automatic label transfer machines (models HT-1D+, HT-1DD+) and heat transfer presses (HT-6A+, HT-8A+) of varying plate sizes. Specifications are provided for these machines such as power, voltage, temperature control and safety features. Additionally, machines for rhinestone transfer and sublimation transfer up to 48x66 inches are described. Contact information is listed for the CEO and GM of Marketing.
This document provides information on Hot Tek Jeans Finishing Range equipment, including contact details, product lines, and specifications. It describes various machines for wrinkling, whiskering, heat transferring, grinding, scraping, spraying, and baking jeans. The key products summarized are the 3D Natural Whisker Machine, which creates natural whiskers using infrared heating, and the Jeans Baking Conveyor Type Oven, which bakes jeans on a conveyor belt at adjustable temperatures and speeds.
This document provides a summary of the academic and professional experience of Dr. Muhammad Mustansar. It lists his medical degrees and qualifications which include an M.B.B.S., M.Sc. in Nutrition, M. Phil in Biochemistry, and certifications in lactation management and community pediatrics. It also outlines his work history in various roles within academic medical institutions in Pakistan from 1987 to the present day. Finally, it provides a lengthy list of his publications in medical journals.
The document describes several heat transfer machines made by Hot Tek for various applications. The HT-1R is designed for roll-to-roll label transfer onto garments. The HT-1D+ and HT-1DD+ are double action machines for heat seal labels and logos. The HT-6A+ is for heat transfers onto t-shirts. Several other machines are described for specific uses such as gloves, jeans, or sublimation transfers. The SP-6A and SP-8A+ are semi-automatic and advanced socks presses.
The document provides a table of contents and specifications for various heat transfer machines, screen making equipment, dryers and ovens, denim jeans finishing machines, and other machinery. It includes details on roll to roll label transfer machines, heat presses, sublimation presses, screen stretchers, dryers, embossing presses, wrinkle machines, and more. The specifications cover features like plate size, power, voltage, temperature control, and production rates.
Hot Tek®brand of Pakistani Company Allied Automation Engineers.Dealing in the manufacturing of Heat Transfer Machines,Screen making equipments,Dryers,Denim Fashion Effects Machines.www.hottek.com
Allied Automation Engineers manufactures industrial washing machines in Faisalabad, Pakistan. Their machines have horizontal structures with stainless steel drums and high quality plate frames. They offer semi-automatic washing machines with steam or electric heating in capacities from 15kg to 400kg that are efficient, safe, and widely used in hotels, restaurants, laundries, and for garment washing.
Allied Automation Engineers provides specifications for their Hydro Extractor H Hot Tek washing machine. The machine features a stainless steel basket and housing, heavy duty bearings, automatic operation, low maintenance needs, and low power consumption. It is available in sampling and regular models.
This document provides information about Hot Tek Jeans Finishing Range equipment, including contact details, product lines, and specifications for various machines. Key products described are wrinkle/whisker machines, heat transfer presses, grinding/scraping equipment, spray booths, and jeans baking ovens in box and conveyor styles. Production capacities, electrical requirements, and additional features are specified for representative models.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
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.
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.
The document provides a table of contents and specifications for various heat transfer machines, screen making equipment, dryers and ovens, denim jeans finishing machines, and other machinery. It includes details on roll to roll label transfer machines, heat presses, sublimation presses, screen stretchers, dryers, embossing presses, wrinkle machines, and more. The specifications cover features like plate size, power, voltage, temperature control, and production rates.
Hot Tek®brand of Pakistani Company Allied Automation Engineers.Dealing in the manufacturing of Heat Transfer Machines,Screen making equipments,Dryers,Denim Fashion Effects Machines.www.hottek.com
Allied Automation Engineers manufactures industrial washing machines in Faisalabad, Pakistan. Their machines have horizontal structures with stainless steel drums and high quality plate frames. They offer semi-automatic washing machines with steam or electric heating in capacities from 15kg to 400kg that are efficient, safe, and widely used in hotels, restaurants, laundries, and for garment washing.
Allied Automation Engineers provides specifications for their Hydro Extractor H Hot Tek washing machine. The machine features a stainless steel basket and housing, heavy duty bearings, automatic operation, low maintenance needs, and low power consumption. It is available in sampling and regular models.
This document provides information about Hot Tek Jeans Finishing Range equipment, including contact details, product lines, and specifications for various machines. Key products described are wrinkle/whisker machines, heat transfer presses, grinding/scraping equipment, spray booths, and jeans baking ovens in box and conveyor styles. Production capacities, electrical requirements, and additional features are specified for representative models.
Null Bangalore | Pentesters Approach to AWS IAMDivyanshu
#Abstract:
- Learn more about the real-world methods for auditing AWS IAM (Identity and Access Management) as a pentester. So let us proceed with a brief discussion of IAM as well as some typical misconfigurations and their potential exploits in order to reinforce the understanding of IAM security best practices.
- Gain actionable insights into AWS IAM policies and roles, using hands on approach.
#Prerequisites:
- Basic understanding of AWS services and architecture
- Familiarity with cloud security concepts
- Experience using the AWS Management Console or AWS CLI.
- For hands on lab create account on [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
# Scenario Covered:
- Basics of IAM in AWS
- Implementing IAM Policies with Least Privilege to Manage S3 Bucket
- Objective: Create an S3 bucket with least privilege IAM policy and validate access.
- Steps:
- Create S3 bucket.
- Attach least privilege policy to IAM user.
- Validate access.
- Exploiting IAM PassRole Misconfiguration
-Allows a user to pass a specific IAM role to an AWS service (ec2), typically used for service access delegation. Then exploit PassRole Misconfiguration granting unauthorized access to sensitive resources.
- Objective: Demonstrate how a PassRole misconfiguration can grant unauthorized access.
- Steps:
- Allow user to pass IAM role to EC2.
- Exploit misconfiguration for unauthorized access.
- Access sensitive resources.
- Exploiting IAM AssumeRole Misconfiguration with Overly Permissive Role
- An overly permissive IAM role configuration can lead to privilege escalation by creating a role with administrative privileges and allow a user to assume this role.
- Objective: Show how overly permissive IAM roles can lead to privilege escalation.
- Steps:
- Create role with administrative privileges.
- Allow user to assume the role.
- Perform administrative actions.
- Differentiation between PassRole vs AssumeRole
Try at [killercoda.com](https://killercoda.com/cloudsecurity-scenario/)
Discover the latest insights on Data Driven Maintenance with our comprehensive webinar presentation. Learn about traditional maintenance challenges, the right approach to utilizing data, and the benefits of adopting a Data Driven Maintenance strategy. Explore real-world examples, industry best practices, and innovative solutions like FMECA and the D3M model. This presentation, led by expert Jules Oudmans, is essential for asset owners looking to optimize their maintenance processes and leverage digital technologies for improved efficiency and performance. Download now to stay ahead in the evolving maintenance landscape.
Software Engineering and Project Management - Introduction, Modeling Concepts...Prakhyath Rai
Introduction, Modeling Concepts and Class Modeling: What is Object orientation? What is OO development? OO Themes; Evidence for usefulness of OO development; OO modeling history. Modeling
as Design technique: Modeling, abstraction, The Three models. Class Modeling: Object and Class Concept, Link and associations concepts, Generalization and Inheritance, A sample class model, Navigation of class models, and UML diagrams
Building the Analysis Models: Requirement Analysis, Analysis Model Approaches, Data modeling Concepts, Object Oriented Analysis, Scenario-Based Modeling, Flow-Oriented Modeling, class Based Modeling, Creating a Behavioral Model.
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.
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.
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.