CS8461 - Operating System Laboratory Manual prepared for the Engineering graduates admitted under 2017 Regulations, Anna University affiliated institutions of TamilNadu,India
Leveraging mobile devices to enhance the performance and ease of programming ...IJITE
Programming simple robots allows teachers to reinforce unified science, technology, engineering, and
math (STEM) concepts. However, for many educators, the cost and computer requirements for robotics kits
are prohibitive. As mobile devices have become increasingly ubiquitous, low cost, and powerful, they may
prove to be an attractive means of coding for, controlling, and enhancing the capabilities of low-cost
mobile robots. This study looks into the viability of using LEGO Mindstorms NXT and Google Android
devices by using Bluetooth to establish a link between the two. This allows for the exchange of live data
remotely for use in various applications with the hope of creating a low-cost mobile programming
environment. The mobile applications developed were able to successfully exchange data with NXT
hardware via Bluetooth and show evidence that mobile devices can be used as a tool to assist in robotic
programming in education.
EARLY STAGE SOFTWARE DEVELOPMENT EFFORT ESTIMATIONS – MAMDANI FIS VS NEURAL N...cscpconf
Accurately estimating the software size, cost, effort and schedule is probably the biggest
challenge facing software developers today. It has major implications for the management of
software development because both the overestimates and underestimates have direct impact for
causing damage to software companies. Lot of models have been proposed over the years by
various researchers for carrying out effort estimations. Also some of the studies for early stage
effort estimations suggest the importance of early estimations. New paradigms offer alternatives
to estimate the software development effort, in particular the Computational Intelligence (CI)
that exploits mechanisms of interaction between humans and processes domain
knowledge with the intention of building intelligent systems (IS). Among IS,
Artificial Neural Network and Fuzzy Logic are the two most popular soft computing techniques
for software development effort estimation. In this paper neural network models and Mamdani
FIS model have been used to predict the early stage effort estimations using the student dataset.
It has been found that Mamdani FIS was able to predict the early stage efforts more efficiently in
comparison to the neural network models based models.
DESIGN AND IMPLEMENTATION OF INTEL-SPONSORED REAL-TIME MULTIVIEW FACE DETECTI...csandit
The paper introduces a case study of design and implementation of Intel-sponsored real-time
face detection system conducted in University of Michigan—Shanghai Jiao Tong University
Joint Institute (JI). This work is teamed up totally by 15 JI students and developed in three
phases during 2013 and 2014. The system design of face detection is based on Intel High
Definition (HD) 4000 graphics and OpenCL. With numerous techniques including the
accelerated pipeline over CPU and GPU, image decomposition, two-dimensional (2D) task
allocation, and the combination of Viola-Jones algorithm and continuously adaptive mean-shift
(Camshift) algorithm, the speed reaches 32 fps for real-time multi-view face detection. Plus, the
frontal view detection accuracy obtains 81% in Phase I and reaches 95% for multi-view
detection, in Phase III. Furthermore, an innovative application called face-detection game
controller (FDGC) is developed. At the time of this writing, the technology has been
implemented in wearable devices and mobile with Intel cores.
CS8461 - Operating System Laboratory Manual prepared for the Engineering graduates admitted under 2017 Regulations, Anna University affiliated institutions of TamilNadu,India
Leveraging mobile devices to enhance the performance and ease of programming ...IJITE
Programming simple robots allows teachers to reinforce unified science, technology, engineering, and
math (STEM) concepts. However, for many educators, the cost and computer requirements for robotics kits
are prohibitive. As mobile devices have become increasingly ubiquitous, low cost, and powerful, they may
prove to be an attractive means of coding for, controlling, and enhancing the capabilities of low-cost
mobile robots. This study looks into the viability of using LEGO Mindstorms NXT and Google Android
devices by using Bluetooth to establish a link between the two. This allows for the exchange of live data
remotely for use in various applications with the hope of creating a low-cost mobile programming
environment. The mobile applications developed were able to successfully exchange data with NXT
hardware via Bluetooth and show evidence that mobile devices can be used as a tool to assist in robotic
programming in education.
EARLY STAGE SOFTWARE DEVELOPMENT EFFORT ESTIMATIONS – MAMDANI FIS VS NEURAL N...cscpconf
Accurately estimating the software size, cost, effort and schedule is probably the biggest
challenge facing software developers today. It has major implications for the management of
software development because both the overestimates and underestimates have direct impact for
causing damage to software companies. Lot of models have been proposed over the years by
various researchers for carrying out effort estimations. Also some of the studies for early stage
effort estimations suggest the importance of early estimations. New paradigms offer alternatives
to estimate the software development effort, in particular the Computational Intelligence (CI)
that exploits mechanisms of interaction between humans and processes domain
knowledge with the intention of building intelligent systems (IS). Among IS,
Artificial Neural Network and Fuzzy Logic are the two most popular soft computing techniques
for software development effort estimation. In this paper neural network models and Mamdani
FIS model have been used to predict the early stage effort estimations using the student dataset.
It has been found that Mamdani FIS was able to predict the early stage efforts more efficiently in
comparison to the neural network models based models.
DESIGN AND IMPLEMENTATION OF INTEL-SPONSORED REAL-TIME MULTIVIEW FACE DETECTI...csandit
The paper introduces a case study of design and implementation of Intel-sponsored real-time
face detection system conducted in University of Michigan—Shanghai Jiao Tong University
Joint Institute (JI). This work is teamed up totally by 15 JI students and developed in three
phases during 2013 and 2014. The system design of face detection is based on Intel High
Definition (HD) 4000 graphics and OpenCL. With numerous techniques including the
accelerated pipeline over CPU and GPU, image decomposition, two-dimensional (2D) task
allocation, and the combination of Viola-Jones algorithm and continuously adaptive mean-shift
(Camshift) algorithm, the speed reaches 32 fps for real-time multi-view face detection. Plus, the
frontal view detection accuracy obtains 81% in Phase I and reaches 95% for multi-view
detection, in Phase III. Furthermore, an innovative application called face-detection game
controller (FDGC) is developed. At the time of this writing, the technology has been
implemented in wearable devices and mobile with Intel cores.
ANALYSIS OF SYSTEM ON CHIP DESIGN USING ARTIFICIAL INTELLIGENCEijesajournal
Automation is a powerful word that lies everywhere. It shows that without automation, application will not get developed. In a semiconductor industry, artificial intelligence played a vital role for implementing the chip based design through automation .The main advantage of applying the machine learning & deep learning technique is to improve the implementation rate based upon the capability of the society. The main objective of the proposed system is to apply the deep learning using data driven approach for controlling the system. Thus leads to a improvement in design, delay ,speed of operation & costs. Through this system, huge volume of data’s that are generated by the system will also get control.
Real Time Implementation Of Face Recognition SystemIJERA Editor
This paper proposes face recognition method using PCA for real time implementation. Nowadays security is
gaining importance as it is becoming necessary for people to keep passwords in their mind and carry cards. Such
implementations however, are becoming less secure and practical, also is becoming more problematic thus
leading to an increasing interest in techniques related to biometrics systems. Face recognition system is amongst
important subjects in biometrics systems. This system is very useful for security in particular and has been
widely used and developed in many countries. This study aims to achieve face recognition successfully by
detecting human face in real time, based on Principal Component Analysis (PCA) algorithm.
Things like growing volumes and varieties of available data, cheaper and more powerful computational processing, data storage and large-value predictions that can guide better decisions and smart actions inreal time without human intervention are playing critical role in this age. All of these require models thatcan automatically analyse large complex data and deliver quick accurate results – even on a very largescale. Machine learning plays a significant role in developing these models. The applications of machinelearning range from speech and object recognition to analysis and prediction of finance markets. Artificial Neural Network is one of the important algorithms of machine learning that is inspired by the structure and functional aspects of the biological neural networks. In this paper, we discuss the purpose, representationand classification methods for developing hardware for machine learning with the main focus on neuralnetworks. This paper also presents the requirements, design issues and optimization techniques for buildinghardware architecture of neural networks.
Things like growing volumes and varieties of available data, cheaper and more powerful computational processing, data storage and large-value predictions that can guide better decisions and smart actions in real time without human intervention are playing critical role in this age. All of these require models that can automatically analyse large complex data and deliver quick accurate results – even on a very large scale. Machine learning plays a significant role in developing these models. The applications of machine learning range from speech and object recognition to analysis and prediction of finance markets. Artificial Neural Network is one of the important algorithms of machine learning that is inspired by the structure and functional aspects of the biological neural networks. In this paper, we discuss the purpose, representation and classification methods for developing hardware for machine learning with the main focus on neural networks. This paper also presents the requirements, design issues and optimization techniques for building hardware architecture of neural networks.
ANALYSIS OF SYSTEM ON CHIP DESIGN USING ARTIFICIAL INTELLIGENCEijesajournal
Automation is a powerful word that lies everywhere. It shows that without automation, application will not get developed. In a semiconductor industry, artificial intelligence played a vital role for implementing the chip based design through automation .The main advantage of applying the machine learning & deep learning technique is to improve the implementation rate based upon the capability of the society. The main objective of the proposed system is to apply the deep learning using data driven approach for controlling the system. Thus leads to a improvement in design, delay ,speed of operation & costs. Through this system, huge volume of data’s that are generated by the system will also get control.
Real Time Implementation Of Face Recognition SystemIJERA Editor
This paper proposes face recognition method using PCA for real time implementation. Nowadays security is
gaining importance as it is becoming necessary for people to keep passwords in their mind and carry cards. Such
implementations however, are becoming less secure and practical, also is becoming more problematic thus
leading to an increasing interest in techniques related to biometrics systems. Face recognition system is amongst
important subjects in biometrics systems. This system is very useful for security in particular and has been
widely used and developed in many countries. This study aims to achieve face recognition successfully by
detecting human face in real time, based on Principal Component Analysis (PCA) algorithm.
Things like growing volumes and varieties of available data, cheaper and more powerful computational processing, data storage and large-value predictions that can guide better decisions and smart actions inreal time without human intervention are playing critical role in this age. All of these require models thatcan automatically analyse large complex data and deliver quick accurate results – even on a very largescale. Machine learning plays a significant role in developing these models. The applications of machinelearning range from speech and object recognition to analysis and prediction of finance markets. Artificial Neural Network is one of the important algorithms of machine learning that is inspired by the structure and functional aspects of the biological neural networks. In this paper, we discuss the purpose, representationand classification methods for developing hardware for machine learning with the main focus on neuralnetworks. This paper also presents the requirements, design issues and optimization techniques for buildinghardware architecture of neural networks.
Things like growing volumes and varieties of available data, cheaper and more powerful computational processing, data storage and large-value predictions that can guide better decisions and smart actions in real time without human intervention are playing critical role in this age. All of these require models that can automatically analyse large complex data and deliver quick accurate results – even on a very large scale. Machine learning plays a significant role in developing these models. The applications of machine learning range from speech and object recognition to analysis and prediction of finance markets. Artificial Neural Network is one of the important algorithms of machine learning that is inspired by the structure and functional aspects of the biological neural networks. In this paper, we discuss the purpose, representation and classification methods for developing hardware for machine learning with the main focus on neural networks. This paper also presents the requirements, design issues and optimization techniques for building hardware architecture of neural networks.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Courier management system project report.pdfKamal Acharya
It is now-a-days very important for the people to send or receive articles like imported furniture, electronic items, gifts, business goods and the like. People depend vastly on different transport systems which mostly use the manual way of receiving and delivering the articles. There is no way to track the articles till they are received and there is no way to let the customer know what happened in transit, once he booked some articles. In such a situation, we need a system which completely computerizes the cargo activities including time to time tracking of the articles sent. This need is fulfilled by Courier Management System software which is online software for the cargo management people that enables them to receive the goods from a source and send them to a required destination and track their status from time to time.
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.