Min max a counter-based algorithm for regular expression matching
•
0 likes•108 views
Final Year IEEE Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE Projects, Academic Final Year IEEE Projects 2013, Academic Final Year IEEE Projects 2014, IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects, 2013 IEEE JAVA, .NET Projects in Chennai, 2013 IEEE JAVA, .NET Projects in Trichy, 2013 IEEE JAVA, .NET Projects in Karur, 2013 IEEE JAVA, .NET Projects in Erode, 2013 IEEE JAVA, .NET Projects in Madurai, 2013 IEEE JAVA, .NET Projects in Salem, 2013 IEEE JAVA, .NET Projects in Coimbatore, 2013 IEEE JAVA, .NET Projects in Tirupur, 2013 IEEE JAVA, .NET Projects in Bangalore, 2013 IEEE JAVA, .NET Projects in Hydrabad, 2013 IEEE JAVA, .NET Projects in Kerala, 2013 IEEE JAVA, .NET Projects in Namakkal, IEEE JAVA, .NET Image Processing, IEEE JAVA, .NET Face Recognition, IEEE JAVA, .NET Face Detection, IEEE JAVA, .NET Brain Tumour, IEEE JAVA, .NET Iris Recognition, IEEE JAVA, .NET Image Segmentation, Final Year JAVA, .NET Projects in Pondichery, Final Year JAVA, .NET Projects in Tamilnadu, Final Year JAVA, .NET Projects in Chennai, Final Year JAVA, .NET Projects in Trichy, Final Year JAVA, .NET Projects in Erode, Final Year JAVA, .NET Projects in Karur, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Tirunelveli, Final Year JAVA, .NET Projects in Madurai, Final Year JAVA, .NET Projects in Salem, Final Year JAVA, .NET Projects in Tirupur, Final Year JAVA, .NET Projects in Namakkal, Final Year JAVA, .NET Projects in Tanjore, Final Year JAVA, .NET Projects in Coimbatore, Final Year JAVA, .NET Projects in Bangalore, Final Year JAVA, .NET Projects in Hydrabad, Final Year JAVA, .NET Projects in Kerala, Final Year JAVA, .NET IEEE Projects in Pondichery, Final Year JAVA, .NET IEEE Projects in Tamilnadu, Final Year JAVA, .NET IEEE Projects in Chennai, Final Year JAVA, .NET IEEE Projects in Trichy, Final Year JAVA, .NET IEEE Projects in Erode, Final Year JAVA, .NET IEEE Projects in Karur, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Tirunelveli, Final Year JAVA, .NET IEEE Projects in Madurai, Final Year JAVA, .NET IEEE Projects in Salem, Final Year JAVA, .NET IEEE Projects in Tirupur, Final Year JAVA, .NET IEEE Projects in Namakkal, Final Year JAVA, .NET IEEE Projects in Tanjore, Final Year JAVA, .NET IEEE Projects in Coimbatore, Final Year JAVA, .NET IEEE Projects in Bangalore, Final Year JAVA, .NET IEEE Projects in Hydrabad, Final Year JAVA, .NET IEEE Projects in Kerala, Final Year IEEE MATLAB Projects, Final Year Projects, Academic Final Year Projects, Academic Final Year IEEE MATLAB Projects, Academic Final Year IEEE MATLAB Projects 2013, Academic Final Year IEEE MATLAB Projects 2014, IEEE MATLAB Projects, 2013 IEEE MATLAB Projects, 2013 IEEE MATLAB Projects in Chennai, 2013 IEEE MATLAB Projects in Trichy, 2013 IEEE MATLAB Projects in Karur, 2013 IEEE MATLAB Projects in Erode, 2013 IEEE MATLAB Projects in Madurai, 2013 IEEE MATLAB
Report
Share
Report
Share
Download to read offline
Recommended
Predicting phase durations of traffic lights using live open traffic lights data
Predicting phase durations of traffic lights using live open traffic lights dataBrecht Van de Vyvere
Paper: https://brechtvdv.github.io/Article-Predicting-traffic-light-phases/
Dynamic traffic lights change their current phase duration according to the situation on the intersection, such as crowdedness. In Flanders, only the minimum and maximum duration of the current phase is published. When route planners want to reuse this data they have to predict how long the current phase will take in order to route over these traffic lights. We tested for a live Open Traffic Lights dataset of Antwerp how frequency distributions of phase durations (i) can be used to predict the duration of the current phase and (ii) can be generated client-side on-the-fly with a demonstrator. An overall mean average error (MAE) of 5.1 seconds is reached by using the median for predictions. A distribution is created for every day with time slots of 20 minutes. This result is better than expected, because phase durations can range between a few seconds and over two minutes. When taking the remaining time until phase change into account, we see a MAE around 10 seconds when the remaining time is less than a minute which we still deem valuable for route planning. Unfortunately, the MAE grows linear for phases longer than a minute making our prediction method useless when this occurs. Based on these results, we wish to present two discussion points during the workshop.Ieeee 2014 vlsi completed projects
Final Year Students Project
Opposite to Sripuram Bus Stop
Back of Rajadeepan Jewellers
Tirunelveli.
Phone:+91 - 8903410319
Mail: finalyearstudentsprojecttvl@gmail.com
web:www.finalyearstudentsproject.in
Eliminating synchronization latency using sequenced latching
PhoenixIndia Technologies,
Karur,
7373885830
7373885630
12
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
Network Simulators Comparison Research Help
Notable Simulator Tools
Top 5 Research Projects
Hot Topics in Network Simulators
Recommended
Predicting phase durations of traffic lights using live open traffic lights data
Predicting phase durations of traffic lights using live open traffic lights dataBrecht Van de Vyvere
Paper: https://brechtvdv.github.io/Article-Predicting-traffic-light-phases/
Dynamic traffic lights change their current phase duration according to the situation on the intersection, such as crowdedness. In Flanders, only the minimum and maximum duration of the current phase is published. When route planners want to reuse this data they have to predict how long the current phase will take in order to route over these traffic lights. We tested for a live Open Traffic Lights dataset of Antwerp how frequency distributions of phase durations (i) can be used to predict the duration of the current phase and (ii) can be generated client-side on-the-fly with a demonstrator. An overall mean average error (MAE) of 5.1 seconds is reached by using the median for predictions. A distribution is created for every day with time slots of 20 minutes. This result is better than expected, because phase durations can range between a few seconds and over two minutes. When taking the remaining time until phase change into account, we see a MAE around 10 seconds when the remaining time is less than a minute which we still deem valuable for route planning. Unfortunately, the MAE grows linear for phases longer than a minute making our prediction method useless when this occurs. Based on these results, we wish to present two discussion points during the workshop.Ieeee 2014 vlsi completed projects
Final Year Students Project
Opposite to Sripuram Bus Stop
Back of Rajadeepan Jewellers
Tirunelveli.
Phone:+91 - 8903410319
Mail: finalyearstudentsprojecttvl@gmail.com
web:www.finalyearstudentsproject.in
Eliminating synchronization latency using sequenced latching
PhoenixIndia Technologies,
Karur,
7373885830
7373885630
12
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
www.impulse.net.in
Email: ieeeprojects@yahoo.com/ imbpulse@gmail.com
Network Simulators Comparison Research Help
Notable Simulator Tools
Top 5 Research Projects
Hot Topics in Network Simulators
IEEE 2014 NS2 NETWORKING PROJECTS Fast regular expression matching using sma...
IEEE 2014 NS2 NETWORKING PROJECTS Fast regular expression matching using sma...IEEEBEBTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.orgHOMOGENEOUS MULTISTAGE ARCHITECTURE FOR REAL-TIME IMAGE PROCESSING
In this article, we present a new multistage architecture oriented to real-time complex processing applications. Given a set of rules, this proposed architecture allows the using of different communication links (point to point link, hardware router…) to connect unlimited number of parallel computing elements (software processors) to follow the increasing complexity of algorithms. In particular, this work brings out a parallel implementation of multihypothesis approach for road recognition application on the proposed Multiprocessor Systemon-Chip (MP-SoC) architecture. This algorithm is usually the main part of the lane keeping applications. Experimental results using images of a real road scene are presented. Using a low cost FPGA-based System-on-Chip, our hardware architecture is able to detect and recognize the roadsides in a time limit of 60 mSec. Moreover, we demonstrate that our multistage architecture may be used to achieve good speed-up in solving automotive applications.
Concurrent Matrix Multiplication on Multi-core Processors
With the advent of multi-cores every processor has built-in parallel computational power and that can only be fully utilized only if the program in execution is written accordingly. This study is a part of an on-going research for designing of a new parallel programming model for multi-core architectures. In this paper we have presented a simple, highly efficient and scalable implementation of a common matrix multiplication algorithm using a newly developed parallel programming model SPC3 PM for general purpose multi-core processors. From our study it is found that matrix multiplication done concurrently on multi-cores using SPC3 PM requires much less execution time than that required using the present standard parallel programming environments like OpenMP. Our approach also shows scalability, better and uniform speedup and better utilization of available cores than that the algorithm written using standard OpenMP or similar parallel programming tools. We have tested our approach for up to 24 cores with different matrices size varying from 100 x 100 to 10000 x 10000 elements. And for all these tests our proposed approach has shown much improved performance and scalability
A dynamically reconfigurable multi asip architecture for multistandard and mu...
A Dynamically Reconfigurable Multi-ASIP Architecture for Multistandard and Multimode Turbo Decoding
The multiplication of wireless communication standards is introducing the need of flexible and reconfigurable multistandard baseband receivers. In this context, multiprocessor turbo decoders have been recently developed in order to support the increasing flexibility and throughput requirements of emerging applications. However, these solutions do not sufficiently address reconfiguration performance issues, which can be a limiting factor in the future. This brief presents the design of a reconfigurable multiprocessor architecture for turbo decoding achieving very fast reconfiguration without compromising the decoding performances.
Web : http://www.lemenizinfotech.com
web : http://www.lemenizinfotech.com/vlsi-ieee-projects-2016-2017/
Web : http://ieeemaster.com
Web : http://ieeemaster.com/vlsi-ieee-projects-2016-2017/
Address: 36, 100 Feet Road Near Indira Gandhi Statue, Natesan Nagar, Pondicherry-605 005
Contact numbers: +91 95663 55386, 99625 88976 0413 420 5444
Mail : projects@lemenizinfotech.com
Mobile : 9566355386 / 9962588976
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
High Performance Deep Learning on Edge Devices With Apache MXNet:
Deep network based models are marked by an asymmetry between the large amount of compute power needed to train a model, and the relatively small amount of compute power needed to deploy a trained model for inference. This is particularly true in computer vision tasks such as object detection or image classification, where millions of labeled images and large numbers of GPUs are needed to produce an accurate model that can be deployed for inference on low powered devices with a single CPU. The challenge when deploying vision models on these low powered devices though, is getting inference to run efficiently enough to allow for near real time processing of a video stream. Fortunately Apache MXNet provides the tools to solve this issues, allowing users to create highly performant models with tools like separable convolutions, quantized weights and sparsity exploitation as well as providing custom hardware kernels to ensure inference calculations are accelerated to the maximum amount allowed by the hardware the model is being deployed on. This is demonstrated though a state of the art MXNet based vision network running in near real time on a low powered Raspberry Pi device. We finally discuss how running inference at the edge as well as leveraging MXNet’s efficient modeling tools can be used to massively drive down compute costs for deploying deep networks in a production system at scale.
International Journal of Engineering Research and Development
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
A dynamically reconfigurable multi asip architecture for multistandard and mu...
Chennai Office: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Nagar, Chennai-83. Landmark: Next to Kotak Mahendra Bank/Bharath Scans
Landline: (044) - 43012642 / Mobile: (0)9952649690
Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry - 9
Landmark: Opp. to Thattanchavady Industrial Estate & Next to VVP Nagar Arch.
Landline: (0413) - 4300535 / Mobile: (0)8608600246 / (0)9952649690.
TiReX: Tiled Regular eXpression matching architecture
Regular Expressions (RE) are widely used to find patterns among data, like in genomic markers research for DNA analysis, deep packet inspection or signature-based detection for network intrusion detection system. This paper proposes a novel and efficient RE matching architecture for FPGAs, based on the concept of matching core. RE can be software-compiled into sequences of basic matching instructions that a matching core runs on input data, and can be replaced to change the RE to be matched. This architecture can easily scale up with the available resources and is customizable to multiple usage scenarios. We ran several experiments and compared the obtained results with a software solution, reaching speedups over 100x, while running at 130MHz, over a Flex-based matching application running on an Intel i7 CPU at 2.8GHz.
Automatic Compilation Of MATLAB Programs For Synergistic Execution On Heterog...
Paper Writing Service
http://StudyHub.vip/Automatic-Compilation-Of-MATLAB-Program 👈
Parallelization of Coupled Cluster Code with OpenMP
I present this project thesis to All india NetApp Technical Paper comptition
Synopsys Fusion Compiler-Comprehensive RTL-to-GDSII Implementation System
Fusion Compiler is the next-generation RTL-to-GDSII implementation system architected to address the complexities of advanced node designs and deliver up to 20% improved PPA while reducing Time To Results (TTR) by 2X.
special B.ed 2nd year old paper_20240531.pdf
Instagram:-
https://instagram.com/special_education_needs_01?igshid=YmMyMTA2M2Y=
WhatsApp:-
https://chat.whatsapp.com/JVakNIYlSV94x7bwunO3Dc
YouTube:-
https://youtube.com/@special_education_needs
Teligram :- https://t.me/special_education_needs
Slide Shere :-
https://www.slideshare.net/shabnambano20?utm_campaign=profiletracking&utm_medium=sssite&utm_source=ssslideview
"Protectable subject matters, Protection in biotechnology, Protection of othe...
Protectable subject matters, Protection in biotechnology, Protection of other biological materials, Ownership and period of protection
More Related Content
Similar to Min max a counter-based algorithm for regular expression matching
IEEE 2014 NS2 NETWORKING PROJECTS Fast regular expression matching using sma...
IEEE 2014 NS2 NETWORKING PROJECTS Fast regular expression matching using sma...IEEEBEBTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.orgHOMOGENEOUS MULTISTAGE ARCHITECTURE FOR REAL-TIME IMAGE PROCESSING
In this article, we present a new multistage architecture oriented to real-time complex processing applications. Given a set of rules, this proposed architecture allows the using of different communication links (point to point link, hardware router…) to connect unlimited number of parallel computing elements (software processors) to follow the increasing complexity of algorithms. In particular, this work brings out a parallel implementation of multihypothesis approach for road recognition application on the proposed Multiprocessor Systemon-Chip (MP-SoC) architecture. This algorithm is usually the main part of the lane keeping applications. Experimental results using images of a real road scene are presented. Using a low cost FPGA-based System-on-Chip, our hardware architecture is able to detect and recognize the roadsides in a time limit of 60 mSec. Moreover, we demonstrate that our multistage architecture may be used to achieve good speed-up in solving automotive applications.
Concurrent Matrix Multiplication on Multi-core Processors
With the advent of multi-cores every processor has built-in parallel computational power and that can only be fully utilized only if the program in execution is written accordingly. This study is a part of an on-going research for designing of a new parallel programming model for multi-core architectures. In this paper we have presented a simple, highly efficient and scalable implementation of a common matrix multiplication algorithm using a newly developed parallel programming model SPC3 PM for general purpose multi-core processors. From our study it is found that matrix multiplication done concurrently on multi-cores using SPC3 PM requires much less execution time than that required using the present standard parallel programming environments like OpenMP. Our approach also shows scalability, better and uniform speedup and better utilization of available cores than that the algorithm written using standard OpenMP or similar parallel programming tools. We have tested our approach for up to 24 cores with different matrices size varying from 100 x 100 to 10000 x 10000 elements. And for all these tests our proposed approach has shown much improved performance and scalability
A dynamically reconfigurable multi asip architecture for multistandard and mu...
A Dynamically Reconfigurable Multi-ASIP Architecture for Multistandard and Multimode Turbo Decoding
The multiplication of wireless communication standards is introducing the need of flexible and reconfigurable multistandard baseband receivers. In this context, multiprocessor turbo decoders have been recently developed in order to support the increasing flexibility and throughput requirements of emerging applications. However, these solutions do not sufficiently address reconfiguration performance issues, which can be a limiting factor in the future. This brief presents the design of a reconfigurable multiprocessor architecture for turbo decoding achieving very fast reconfiguration without compromising the decoding performances.
Web : http://www.lemenizinfotech.com
web : http://www.lemenizinfotech.com/vlsi-ieee-projects-2016-2017/
Web : http://ieeemaster.com
Web : http://ieeemaster.com/vlsi-ieee-projects-2016-2017/
Address: 36, 100 Feet Road Near Indira Gandhi Statue, Natesan Nagar, Pondicherry-605 005
Contact numbers: +91 95663 55386, 99625 88976 0413 420 5444
Mail : projects@lemenizinfotech.com
Mobile : 9566355386 / 9962588976
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
High Performance Deep Learning on Edge Devices With Apache MXNet:
Deep network based models are marked by an asymmetry between the large amount of compute power needed to train a model, and the relatively small amount of compute power needed to deploy a trained model for inference. This is particularly true in computer vision tasks such as object detection or image classification, where millions of labeled images and large numbers of GPUs are needed to produce an accurate model that can be deployed for inference on low powered devices with a single CPU. The challenge when deploying vision models on these low powered devices though, is getting inference to run efficiently enough to allow for near real time processing of a video stream. Fortunately Apache MXNet provides the tools to solve this issues, allowing users to create highly performant models with tools like separable convolutions, quantized weights and sparsity exploitation as well as providing custom hardware kernels to ensure inference calculations are accelerated to the maximum amount allowed by the hardware the model is being deployed on. This is demonstrated though a state of the art MXNet based vision network running in near real time on a low powered Raspberry Pi device. We finally discuss how running inference at the edge as well as leveraging MXNet’s efficient modeling tools can be used to massively drive down compute costs for deploying deep networks in a production system at scale.
International Journal of Engineering Research and Development
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
A dynamically reconfigurable multi asip architecture for multistandard and mu...
Chennai Office: JP INFOTECH, Old No.31, New No.86, 1st Floor, 1st Avenue, Ashok Nagar, Chennai-83. Landmark: Next to Kotak Mahendra Bank/Bharath Scans
Landline: (044) - 43012642 / Mobile: (0)9952649690
Pondicherry Office: JP INFOTECH, #45, Kamaraj Salai, Thattanchavady, Puducherry - 9
Landmark: Opp. to Thattanchavady Industrial Estate & Next to VVP Nagar Arch.
Landline: (0413) - 4300535 / Mobile: (0)8608600246 / (0)9952649690.
TiReX: Tiled Regular eXpression matching architecture
Regular Expressions (RE) are widely used to find patterns among data, like in genomic markers research for DNA analysis, deep packet inspection or signature-based detection for network intrusion detection system. This paper proposes a novel and efficient RE matching architecture for FPGAs, based on the concept of matching core. RE can be software-compiled into sequences of basic matching instructions that a matching core runs on input data, and can be replaced to change the RE to be matched. This architecture can easily scale up with the available resources and is customizable to multiple usage scenarios. We ran several experiments and compared the obtained results with a software solution, reaching speedups over 100x, while running at 130MHz, over a Flex-based matching application running on an Intel i7 CPU at 2.8GHz.
Automatic Compilation Of MATLAB Programs For Synergistic Execution On Heterog...
Paper Writing Service
http://StudyHub.vip/Automatic-Compilation-Of-MATLAB-Program 👈
Parallelization of Coupled Cluster Code with OpenMP
I present this project thesis to All india NetApp Technical Paper comptition
Synopsys Fusion Compiler-Comprehensive RTL-to-GDSII Implementation System
Fusion Compiler is the next-generation RTL-to-GDSII implementation system architected to address the complexities of advanced node designs and deliver up to 20% improved PPA while reducing Time To Results (TTR) by 2X.
Similar to Min max a counter-based algorithm for regular expression matching (20)
Min max a counter-based algorithm for regular expression matching
Min max a counter-based algorithm for regular expression matching
Dotnet min-max a counter-based algorithm for regular expression matching
Dotnet min-max a counter-based algorithm for regular expression matching
IEEE 2014 NS2 NETWORKING PROJECTS Fast regular expression matching using sma...
IEEE 2014 NS2 NETWORKING PROJECTS Fast regular expression matching using sma...
HOMOGENEOUS MULTISTAGE ARCHITECTURE FOR REAL-TIME IMAGE PROCESSING
HOMOGENEOUS MULTISTAGE ARCHITECTURE FOR REAL-TIME IMAGE PROCESSING
Concurrent Matrix Multiplication on Multi-core Processors
Concurrent Matrix Multiplication on Multi-core Processors
A dynamically reconfigurable multi asip architecture for multistandard and mu...
A dynamically reconfigurable multi asip architecture for multistandard and mu...
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
Aran Khanna, Software Engineer, Amazon Web Services at MLconf ATL 2017
International Journal of Engineering Research and Development
International Journal of Engineering Research and Development
A dynamically reconfigurable multi asip architecture for multistandard and mu...
A dynamically reconfigurable multi asip architecture for multistandard and mu...
TiReX: Tiled Regular eXpression matching architecture
TiReX: Tiled Regular eXpression matching architecture
Automatic Compilation Of MATLAB Programs For Synergistic Execution On Heterog...
Automatic Compilation Of MATLAB Programs For Synergistic Execution On Heterog...
Vlsi 2015 2016 ieee project list-(v)_with abstract
Vlsi 2015 2016 ieee project list-(v)_with abstract
Parallelization of Coupled Cluster Code with OpenMP
Parallelization of Coupled Cluster Code with OpenMP
Synopsys Fusion Compiler-Comprehensive RTL-to-GDSII Implementation System
Synopsys Fusion Compiler-Comprehensive RTL-to-GDSII Implementation System
Recently uploaded
special B.ed 2nd year old paper_20240531.pdf
Instagram:-
https://instagram.com/special_education_needs_01?igshid=YmMyMTA2M2Y=
WhatsApp:-
https://chat.whatsapp.com/JVakNIYlSV94x7bwunO3Dc
YouTube:-
https://youtube.com/@special_education_needs
Teligram :- https://t.me/special_education_needs
Slide Shere :-
https://www.slideshare.net/shabnambano20?utm_campaign=profiletracking&utm_medium=sssite&utm_source=ssslideview
"Protectable subject matters, Protection in biotechnology, Protection of othe...
Protectable subject matters, Protection in biotechnology, Protection of other biological materials, Ownership and period of protection
Embracing GenAI - A Strategic Imperative
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Event Link:-
https://meetups.mulesoft.com/events/details/mulesoft-mysore-presents-exploring-gemini-ai-and-integration-with-mulesoft/
Agenda
● Java 17 Upgrade Overview
● Why and by when do customers need to upgrade to Java 17?
● Is there any immediate impact to upgrading to Mule Runtime 4.6 and beyond?
● Which MuleSoft products are in scope?
For Upcoming Meetups Join Mysore Meetup Group - https://meetups.mulesoft.com/mysore/
YouTube:- youtube.com/@mulesoftmysore
Mysore WhatsApp group:- https://chat.whatsapp.com/EhqtHtCC75vCAX7gaO842N
Speaker:-
Shubham Chaurasia - https://www.linkedin.com/in/shubhamchaurasia1/
Priya Shaw - https://www.linkedin.com/in/priya-shaw
Organizers:-
Shubham Chaurasia - https://www.linkedin.com/in/shubhamchaurasia1/
Giridhar Meka - https://www.linkedin.com/in/giridharmeka
Priya Shaw - https://www.linkedin.com/in/priya-shaw
Shyam Raj Prasad-
https://www.linkedin.com/in/shyam-raj-prasad/
1.4 modern child centered education - mahatma gandhi-2.pptx
Child centred education is an educational approach that priorities the interest, needs and abilities of the child in the learning process.
The geography of Taylor Swift - some ideas
Geographical themes connected with Taylor Swift's ERAS tour - coming to the UK in June 2024
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
Class 11 CBSE Business Studies Project ( AIDS TO TRADE - INSURANCE)
678020731-Sumas-y-Restas-Para-Colorear.pdf
KKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKKK
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH ANSWERS.
Palestine last event orientationfvgnh .pptx
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Unit 2- Research Aptitude (UGC NET Paper I).pdf
This slide describes the research aptitude of unit 2 in the UGC NET paper I.
Acetabularia Information For Class 9 .docx
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Operation Blue Star - Saka Neela Tara
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
How to Make a Field invisible in Odoo 17
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Recently uploaded (20)
"Protectable subject matters, Protection in biotechnology, Protection of othe...
"Protectable subject matters, Protection in biotechnology, Protection of othe...
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
Mule 4.6 & Java 17 Upgrade | MuleSoft Mysore Meetup #46
1.4 modern child centered education - mahatma gandhi-2.pptx
1.4 modern child centered education - mahatma gandhi-2.pptx
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
TESDA TM1 REVIEWER FOR NATIONAL ASSESSMENT WRITTEN AND ORAL QUESTIONS WITH A...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
Min max a counter-based algorithm for regular expression matching
- 1. MIN-MAX A COUNTER-BASED ALGORITHM FOR REGULAR EXPRESSION MATCHING ABSTRACT: We propose an NFA-based algorithm called MIN-MAX to support matching of regular expressions (regexp) composed of Character Classes with Constraint Repetitions (CCR). MIN- MAX is well suited for massive parallel processing architectures, such as FPGAs, yet it is effective on any other computing platform. In MIN-MAX, each active CCR engine (to implement one CCR term) evaluates input characters, updates (MIN, MAX) counters, and asserts control signals, and all the CCR engines implemented in the FPGA run simultaneously. Unlike traditional designs, (MIN, MAX) counters contain dynamically updated lower and upper bounds of possible matching counts, instead of actual matching counts, so that feasible matching lengths are compactly enclosed in the counter value. The counter-based design can support constraint repetitions of n using O({rm log} n) memory bits rather than that of O(n) in existing solutions. MIN-MAX can resolve character class ambiguity between adjacent CCR terms and support overlapped matching when matching collisions are absent. We developed a set of heuristic rules to assess the absence of collision for CCR-based regexps, and tested them on Snort and SpamAssassin rule sets. The results show that the vast majority of rules are immune from collisions, so that MIN-MAX can cost effectively support overlapped matching. As a bonus, the new architecture also supports fast reconfiguration via ordinary memory writes rather than resynthesis of the entire design, which is critical for time- sensitive regexp deployment scenarios. ECWAY TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS OUR OFFICES @ CHENNAI / TRICHY / KARUR / ERODE / MADURAI / SALEM / COIMBATORE CELL: +91 98949 17187, +91 875487 2111 / 3111 / 4111 / 5111 / 6111 VISIT: www.ecwayprojects.com MAIL TO: ecwaytechnologies@gmail.com