The document discusses DeepCoder, a machine learning system developed by Microsoft that is able to generate its own code by learning from existing code examples. DeepCoder is trained on a large corpus of programs and input/output examples to learn which code snippets are likely to work together to solve new problems. It can then search through code more efficiently than humans to assemble working programs from existing code blocks. While currently limited to simple 5 line programs, DeepCoder represents a significant improvement over previous program synthesis techniques and could eventually make programming accessible to non-coders. However, some media reports exaggerated DeepCoder's capabilities and inaccurately claimed it works by copying code directly from other software.
COMPARATIVE STUDY OF SOFTWARE ESTIMATION TECHNIQUES ijseajournal
Many information technology firms among other organizations have been working on how to perform estimation of the sources such as fund and other resources during software development processes. Software development life cycles require lot of activities and skills to avoid risks and the best software estimation technique is supposed to be employed. Therefore, in this research, a comparative study was conducted, that consider the accuracy, usage, and suitability of existing methods. It will be suitable for the project managers and project consultants during the whole software project development process. In this project technique such as linear regression; both algorithmic and non-algorithmic are applied. Model, composite and regression techniques are used to derive COCOMO, COCOMO II, SLIM and linear multiple respectively. Moreover, expertise-based and linear-based rules are applied in non-algorithm methods. However, the technique needs some advancement to reduce the errors that are experienced during the software development process. Therefore, this paper in relation to software estimation techniques has proposed a model that can be helpful to the information technology firms, researchers and other firms that use information technology in the processes such as budgeting and decision-making processes.
A framework for adoption of machine learning in industry for software defect ...RAKESH RANA
A framework for adoption of machine learning in industry for software defect prediction
Presented at:
9th International Joint Conference on Software Technologies (ICSOFT-EA), Vienna, Austria
Get full text of publication at:
http://rakeshrana.website/index.php/work/publications/
A Defect Prediction Model for Software Product based on ANFISIJSRD
Artificial intelligence techniques are day by day getting involvement in all the classification and prediction based process like environmental monitoring, stock exchange conditions, biomedical diagnosis, software engineering etc. However still there are yet to be simplify the challenges of selecting training criteria for design of artificial intelligence models used for prediction of results. This work focus on the defect prediction mechanism development using software metric data of KC1.We have taken subtractive clustering approach for generation of fuzzy inference system (FIS).The FIS rules are generated at different radius of influence of input attribute vectors and the developed rules are further modified by ANFIS technique to obtain the prediction of number of defects in software project using fuzzy logic system.
A Novel Optimization towards Higher Reliability in Predictive Modelling towar...IJECEIAES
Although, the area of software engineering has made a remarkable progress in last decade but there is less attention towards the concept of code reusability in this regards.Code reusability is a subset of Software Reusability which is one of the signature topics in software engineering. We review the existing system to find that there is no progress or availability of standard research approach toward code reusability being introduced in last decade. Hence, this paper introduced a predictive framework that is used for optimizing the performance of code reusability. For this purpose, we introduce a case study of near real-time challenge and involved it in our modelling. We apply neural network and Damped-Least square algorithm to perform optimization with a sole target to compute and ensure highest possible reliability. The study outcome of our model exhibits higher reliability and better computational response time
Application of Genetic Algorithm in Software Engineering: A ReviewIRJESJOURNAL
Abstract. The software engineering is comparatively new and regularly changing field. The big challenge of meeting strict project schedules with high quality software requires that the field of software engineering be automated to large extent and human resource intervention be minimized to optimum level. To achieve this goal the researcher have explored the potential of machine learning approaches as they are adaptable, have learning ability. In this paper, we take a look at how genetic algorithm (GA) can be used to build tool for software development and maintenance tasks.
COMPARATIVE STUDY OF SOFTWARE ESTIMATION TECHNIQUES ijseajournal
Many information technology firms among other organizations have been working on how to perform estimation of the sources such as fund and other resources during software development processes. Software development life cycles require lot of activities and skills to avoid risks and the best software estimation technique is supposed to be employed. Therefore, in this research, a comparative study was conducted, that consider the accuracy, usage, and suitability of existing methods. It will be suitable for the project managers and project consultants during the whole software project development process. In this project technique such as linear regression; both algorithmic and non-algorithmic are applied. Model, composite and regression techniques are used to derive COCOMO, COCOMO II, SLIM and linear multiple respectively. Moreover, expertise-based and linear-based rules are applied in non-algorithm methods. However, the technique needs some advancement to reduce the errors that are experienced during the software development process. Therefore, this paper in relation to software estimation techniques has proposed a model that can be helpful to the information technology firms, researchers and other firms that use information technology in the processes such as budgeting and decision-making processes.
A framework for adoption of machine learning in industry for software defect ...RAKESH RANA
A framework for adoption of machine learning in industry for software defect prediction
Presented at:
9th International Joint Conference on Software Technologies (ICSOFT-EA), Vienna, Austria
Get full text of publication at:
http://rakeshrana.website/index.php/work/publications/
A Defect Prediction Model for Software Product based on ANFISIJSRD
Artificial intelligence techniques are day by day getting involvement in all the classification and prediction based process like environmental monitoring, stock exchange conditions, biomedical diagnosis, software engineering etc. However still there are yet to be simplify the challenges of selecting training criteria for design of artificial intelligence models used for prediction of results. This work focus on the defect prediction mechanism development using software metric data of KC1.We have taken subtractive clustering approach for generation of fuzzy inference system (FIS).The FIS rules are generated at different radius of influence of input attribute vectors and the developed rules are further modified by ANFIS technique to obtain the prediction of number of defects in software project using fuzzy logic system.
A Novel Optimization towards Higher Reliability in Predictive Modelling towar...IJECEIAES
Although, the area of software engineering has made a remarkable progress in last decade but there is less attention towards the concept of code reusability in this regards.Code reusability is a subset of Software Reusability which is one of the signature topics in software engineering. We review the existing system to find that there is no progress or availability of standard research approach toward code reusability being introduced in last decade. Hence, this paper introduced a predictive framework that is used for optimizing the performance of code reusability. For this purpose, we introduce a case study of near real-time challenge and involved it in our modelling. We apply neural network and Damped-Least square algorithm to perform optimization with a sole target to compute and ensure highest possible reliability. The study outcome of our model exhibits higher reliability and better computational response time
Application of Genetic Algorithm in Software Engineering: A ReviewIRJESJOURNAL
Abstract. The software engineering is comparatively new and regularly changing field. The big challenge of meeting strict project schedules with high quality software requires that the field of software engineering be automated to large extent and human resource intervention be minimized to optimum level. To achieve this goal the researcher have explored the potential of machine learning approaches as they are adaptable, have learning ability. In this paper, we take a look at how genetic algorithm (GA) can be used to build tool for software development and maintenance tasks.
The adoption of machine learning techniques for software defect prediction: A...RAKESH RANA
The adoption of machine learning techniques for software defect prediction: An initial industrial validation
Presented at:
11th Joint Conference On Knowledge-Based Software Engineering, JCKBSE, Volgograd, Russia, 2014
Get full text of publication at:
http://rakeshrana.website/index.php/work/publications/
Review on Algorithmic and Non Algorithmic Software Cost Estimation Techniquesijtsrd
Effective software cost estimation is the most challenging and important activities in software development. Developers want a simple and accurate method of efforts estimation. Estimation of the cost before starting of work is a prediction and prediction always not accurate. Software effort estimation is a very critical task in the software engineering and to control quality and efficiency a suitable estimation technique is crucial. This paper gives a review of various available software effort estimation methods, mainly focus on the algorithmic model and non algorithmic model. These existing methods for software cost estimation are illustrated and their aspect will be discussed. No single technique is best for all situations, and thus a careful comparison of the results of several approaches is most likely to produce realistic estimation. This paper provides a detailed overview of existing software cost estimation models and techniques. This paper presents the strength and weakness of various cost estimation methods. This paper focuses on some of the relevant reasons that cause inaccurate estimation. Pa Pa Win | War War Myint | Hlaing Phyu Phyu Mon | Seint Wint Thu "Review on Algorithmic and Non-Algorithmic Software Cost Estimation Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26511.pdfPaper URL: https://www.ijtsrd.com/engineering/-/26511/review-on-algorithmic-and-non-algorithmic-software-cost-estimation-techniques/pa-pa-win
A DECISION SUPPORT SYSTEM FOR ESTIMATING COST OF SOFTWARE PROJECTS USING A HY...ijfcstjournal
One of the major challenges for software, nowadays, is software cost estimation. It refers to estimating the
cost of all activities including software development, design, supervision, maintenance and so on. Accurate
cost-estimation of software projects optimizes the internal and external processes, staff works, efforts and
the overheads to be coordinated with one another. In the management software projects, estimation must
be taken into account so that reduces costs, timing and possible risks to avoid project failure. In this paper,
a decision- support system using a combination of multi-layer artificial neural network and decision tree is
proposed to estimate the cost of software projects. In the model included into the proposed system,
normalizing factors, which is vital in evaluating efforts and costs estimation, is carried out using C4.5
decision tree. Moreover, testing and training factors are done by multi-layer artificial neural network and
the most optimal values are allocated to them. The experimental results and evaluations on Dataset
NASA60 show that the proposed system has less amount of the total average relative error compared with
COCOMO model.
Software Defect Prediction Using Local and Global AnalysisEditor IJMTER
The software defect factors are used to measure the quality of the software. The software
effort estimation is used to measure the effort required for the software development process. The defect
factor makes an impact on the software development effort. Software development and cost factors are
also decided with reference to the defect and effort factors. The software defects are predicted with
reference to the module information. Module link information are used in the effort estimation process.
Data mining techniques are used in the software analysis process. Clustering techniques are used
in the property grouping process. Rule mining methods are used to learn rules from clustered data
values. The “WHERE” clustering scheme and “WHICH” rule mining scheme are used in the defect
prediction and effort estimation process. The system uses the module information for the defect
prediction and effort estimation process.
The proposed system is designed to improve the defect prediction and effort estimation process.
The Single Objective Genetic Algorithm (SOGA) is used in the clustering process. The rule learning
operations are carried out sing the Apriori algorithm. The system improves the cluster accuracy levels.
The defect prediction and effort estimation accuracy is also improved by the system. The system is
developed using the Java language and Oracle relation database environment.
Forecasting number of vulnerabilities using long short-term neural memory net...IJECEIAES
Cyber-attacks are launched through the exploitation of some existing vulnerabilities in the software, hardware, system and/or network. Machine learning algorithms can be used to forecast the number of post release vulnerabilities. Traditional neural networks work like a black box approach; hence it is unclear how reasoning is used in utilizing past data points in inferring the subsequent data points. However, the long short-term memory network (LSTM), a variant of the recurrent neural network, is able to address this limitation by introducing a lot of loops in its network to retain and utilize past data points for future calculations. Moving on from the previous finding, we further enhance the results to predict the number of vulnerabilities by developing a time series-based sequential model using a long short-term memory neural network. Specifically, this study developed a supervised machine learning based on the non-linear sequential time series forecasting model with a long short-term memory neural network to predict the number of vulnerabilities for three vendors having the highest number of vulnerabilities published in the national vulnerability database (NVD), namely microsoft, IBM and oracle. Our proposed model outperforms the existing models with a prediction result root mean squared error (RMSE) of as low as 0.072.
Digital Security by Design: Formal Verification with Broad-Spectrum ANSI-C Re...KTN
KTN ran a collaborators' workshop on 26 September 2019 in London to explain more about the Digital Security by Design Challenge announced by the government.
The Digital Security by Design challenge has been recently announced by the Department for Business, Energy & Industrial Strategy (BEIS). This challenge, amounting to £70 million of government funding over 5 years, was delivered by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF).
This Collaborators' Workshop provides an opportunity to hear more details of the challenge and forthcoming competitions.
A Scoping Workshop for this challenge was held on 30th May: http://ow.ly/oz6230pHlGl
Find out more about the Defence and Security Interest Group at https://ktn-uk.co.uk/interests/defence-security
Join the Defence and Security Interest Group at https://www.linkedin.com/groups/8584397 or Follow KTN_UK Defence group on Twitter https://twitter.com/KTNUK_Defence
Programmer Productivity Enhancement Through Controlled Natural Language Inputijseajournal
We have created CABERNET, a Controlled Nature Language (CNL) based approach to program creation. CABERNET allows programmers to use a simple outline-based syntax. This allows increased programmer efficiency and syntax flexibility. CNLs have successfully been used for writing requirements documents. We propose taking this approach well beyond this to fully functional programs. Through the use of heuristics and inference to analyze and determine the programmer’s intent we are able to create fully functional mobile applications. The goal is for programs to be aligned with the way that the humans think rather than the way computers process information. Through the use of templates a CABERNET application can be processed to run on multiple run time environments. Because processing of a CABERNET program file results in native application program performance is maintained.
Improved Strategy for Distributed Processing and Network Application Developm...Editor IJCATR
The complexity of software development abstraction and the new development in multi-core computers have shifted the burden of distributed software performance from network and chip designers to software architectures and developers. We need to look at software development strategies that will integrate parallelization of code, concurrency factors, multithreading, distributed resources allocation and distributed processing. In this paper, a new software development strategy that integrates these factors is further experimented on parallelism. The strategy is multidimensional aligns distributed conceptualization along a path. This development strategy mandates application developers to reason along usability, simplicity, resource distribution, parallelization of code where necessary, processing time and cost factors realignment as well as security and concurrency issues in a balanced path from the originating point of the network application to its retirement.
Improved Strategy for Distributed Processing and Network Application DevelopmentEditor IJCATR
The complexity of software development abstraction and the new development in multi-core computers have shifted the
burden of distributed software performance from network and chip designers to software architectures and developers. We need to
look at software development strategies that will integrate parallelization of code, concurrency factors, multithreading, distributed
resources allocation and distributed processing. In this paper, a new software development strategy that integrates these factors is
further experimented on parallelism. The strategy is multidimensional aligns distributed conceptualization along a path. This
development strategy mandates application developers to reason along usability, simplicity, resource distribution, parallelization of
code where necessary, processing time and cost factors realignment as well as security and concurrency issues in a balanced path from
the originating point of the network application to its retirement.
The adoption of machine learning techniques for software defect prediction: A...RAKESH RANA
The adoption of machine learning techniques for software defect prediction: An initial industrial validation
Presented at:
11th Joint Conference On Knowledge-Based Software Engineering, JCKBSE, Volgograd, Russia, 2014
Get full text of publication at:
http://rakeshrana.website/index.php/work/publications/
Review on Algorithmic and Non Algorithmic Software Cost Estimation Techniquesijtsrd
Effective software cost estimation is the most challenging and important activities in software development. Developers want a simple and accurate method of efforts estimation. Estimation of the cost before starting of work is a prediction and prediction always not accurate. Software effort estimation is a very critical task in the software engineering and to control quality and efficiency a suitable estimation technique is crucial. This paper gives a review of various available software effort estimation methods, mainly focus on the algorithmic model and non algorithmic model. These existing methods for software cost estimation are illustrated and their aspect will be discussed. No single technique is best for all situations, and thus a careful comparison of the results of several approaches is most likely to produce realistic estimation. This paper provides a detailed overview of existing software cost estimation models and techniques. This paper presents the strength and weakness of various cost estimation methods. This paper focuses on some of the relevant reasons that cause inaccurate estimation. Pa Pa Win | War War Myint | Hlaing Phyu Phyu Mon | Seint Wint Thu "Review on Algorithmic and Non-Algorithmic Software Cost Estimation Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26511.pdfPaper URL: https://www.ijtsrd.com/engineering/-/26511/review-on-algorithmic-and-non-algorithmic-software-cost-estimation-techniques/pa-pa-win
A DECISION SUPPORT SYSTEM FOR ESTIMATING COST OF SOFTWARE PROJECTS USING A HY...ijfcstjournal
One of the major challenges for software, nowadays, is software cost estimation. It refers to estimating the
cost of all activities including software development, design, supervision, maintenance and so on. Accurate
cost-estimation of software projects optimizes the internal and external processes, staff works, efforts and
the overheads to be coordinated with one another. In the management software projects, estimation must
be taken into account so that reduces costs, timing and possible risks to avoid project failure. In this paper,
a decision- support system using a combination of multi-layer artificial neural network and decision tree is
proposed to estimate the cost of software projects. In the model included into the proposed system,
normalizing factors, which is vital in evaluating efforts and costs estimation, is carried out using C4.5
decision tree. Moreover, testing and training factors are done by multi-layer artificial neural network and
the most optimal values are allocated to them. The experimental results and evaluations on Dataset
NASA60 show that the proposed system has less amount of the total average relative error compared with
COCOMO model.
Software Defect Prediction Using Local and Global AnalysisEditor IJMTER
The software defect factors are used to measure the quality of the software. The software
effort estimation is used to measure the effort required for the software development process. The defect
factor makes an impact on the software development effort. Software development and cost factors are
also decided with reference to the defect and effort factors. The software defects are predicted with
reference to the module information. Module link information are used in the effort estimation process.
Data mining techniques are used in the software analysis process. Clustering techniques are used
in the property grouping process. Rule mining methods are used to learn rules from clustered data
values. The “WHERE” clustering scheme and “WHICH” rule mining scheme are used in the defect
prediction and effort estimation process. The system uses the module information for the defect
prediction and effort estimation process.
The proposed system is designed to improve the defect prediction and effort estimation process.
The Single Objective Genetic Algorithm (SOGA) is used in the clustering process. The rule learning
operations are carried out sing the Apriori algorithm. The system improves the cluster accuracy levels.
The defect prediction and effort estimation accuracy is also improved by the system. The system is
developed using the Java language and Oracle relation database environment.
Forecasting number of vulnerabilities using long short-term neural memory net...IJECEIAES
Cyber-attacks are launched through the exploitation of some existing vulnerabilities in the software, hardware, system and/or network. Machine learning algorithms can be used to forecast the number of post release vulnerabilities. Traditional neural networks work like a black box approach; hence it is unclear how reasoning is used in utilizing past data points in inferring the subsequent data points. However, the long short-term memory network (LSTM), a variant of the recurrent neural network, is able to address this limitation by introducing a lot of loops in its network to retain and utilize past data points for future calculations. Moving on from the previous finding, we further enhance the results to predict the number of vulnerabilities by developing a time series-based sequential model using a long short-term memory neural network. Specifically, this study developed a supervised machine learning based on the non-linear sequential time series forecasting model with a long short-term memory neural network to predict the number of vulnerabilities for three vendors having the highest number of vulnerabilities published in the national vulnerability database (NVD), namely microsoft, IBM and oracle. Our proposed model outperforms the existing models with a prediction result root mean squared error (RMSE) of as low as 0.072.
Digital Security by Design: Formal Verification with Broad-Spectrum ANSI-C Re...KTN
KTN ran a collaborators' workshop on 26 September 2019 in London to explain more about the Digital Security by Design Challenge announced by the government.
The Digital Security by Design challenge has been recently announced by the Department for Business, Energy & Industrial Strategy (BEIS). This challenge, amounting to £70 million of government funding over 5 years, was delivered by UK Research and Innovation (UKRI) through the Industrial Strategy Challenge Fund (ISCF).
This Collaborators' Workshop provides an opportunity to hear more details of the challenge and forthcoming competitions.
A Scoping Workshop for this challenge was held on 30th May: http://ow.ly/oz6230pHlGl
Find out more about the Defence and Security Interest Group at https://ktn-uk.co.uk/interests/defence-security
Join the Defence and Security Interest Group at https://www.linkedin.com/groups/8584397 or Follow KTN_UK Defence group on Twitter https://twitter.com/KTNUK_Defence
Programmer Productivity Enhancement Through Controlled Natural Language Inputijseajournal
We have created CABERNET, a Controlled Nature Language (CNL) based approach to program creation. CABERNET allows programmers to use a simple outline-based syntax. This allows increased programmer efficiency and syntax flexibility. CNLs have successfully been used for writing requirements documents. We propose taking this approach well beyond this to fully functional programs. Through the use of heuristics and inference to analyze and determine the programmer’s intent we are able to create fully functional mobile applications. The goal is for programs to be aligned with the way that the humans think rather than the way computers process information. Through the use of templates a CABERNET application can be processed to run on multiple run time environments. Because processing of a CABERNET program file results in native application program performance is maintained.
Improved Strategy for Distributed Processing and Network Application Developm...Editor IJCATR
The complexity of software development abstraction and the new development in multi-core computers have shifted the burden of distributed software performance from network and chip designers to software architectures and developers. We need to look at software development strategies that will integrate parallelization of code, concurrency factors, multithreading, distributed resources allocation and distributed processing. In this paper, a new software development strategy that integrates these factors is further experimented on parallelism. The strategy is multidimensional aligns distributed conceptualization along a path. This development strategy mandates application developers to reason along usability, simplicity, resource distribution, parallelization of code where necessary, processing time and cost factors realignment as well as security and concurrency issues in a balanced path from the originating point of the network application to its retirement.
Improved Strategy for Distributed Processing and Network Application DevelopmentEditor IJCATR
The complexity of software development abstraction and the new development in multi-core computers have shifted the
burden of distributed software performance from network and chip designers to software architectures and developers. We need to
look at software development strategies that will integrate parallelization of code, concurrency factors, multithreading, distributed
resources allocation and distributed processing. In this paper, a new software development strategy that integrates these factors is
further experimented on parallelism. The strategy is multidimensional aligns distributed conceptualization along a path. This
development strategy mandates application developers to reason along usability, simplicity, resource distribution, parallelization of
code where necessary, processing time and cost factors realignment as well as security and concurrency issues in a balanced path from
the originating point of the network application to its retirement.
Multi step automated refactoring for code smelleSAT Journals
Abstract
Brain MR Image can detect many abnormalities like tumor, cysts, bleeding, infection etc. Analysis of brain MRI using image
processing techniques has been an active research in the field of medical imaging. In this work, it is shown that MR image of brain
represent a multi fractal system which is described a continuous spectrum of exponents rather than a single exponent (fractal
dimension). Multi fractal analysis has been performed on number of images from OASIS database are analyzed. The properties of
multi fractal spectrum of a system have been exploited to prove the results. Multi fractal spectra are determined using the modified
box-counting method of fractal dimension estimation.
Keywords: Brain MR Image, Multi fractal, Box-counting
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
A Defect Prediction Model for Software Product based on ANFISIJSRD
Artificial intelligence techniques are day by day getting involvement in all the classification and prediction based process like environmental monitoring, stock exchange conditions, biomedical diagnosis, software engineering etc. However still there are yet to be simplify the challenges of selecting training criteria for design of artificial intelligence models used for prediction of results. This work focus on the defect prediction mechanism development using software metric data of KC1.We have taken subtractive clustering approach for generation of fuzzy inference system (FIS).The FIS rules are generated at different radius of influence of input attribute vectors and the developed rules are further modified by ANFIS technique to obtain the prediction of number of defects in software project using fuzzy logic system.
Insights on Research Techniques towards Cost Estimation in Software Design IJECEIAES
Software cost estimation is of the most challenging task in project management in order to ensuring smoother development operation and target achievement. There has been evolution of various standards tools and techniques for cost estimation practiced in the industry at present times. However, it was never investigated about the overall picturization of effectiveness of such techniques till date. This paper initiates its contribution by presenting taxonomies of conventional cost-estimation techniques and then investigates the research trends towards frequently addressed problems in it. The paper also reviews the existing techniques in well-structured manner in order to highlight the problems addressed, techniques used, advantages associated and limitation explored from literatures. Finally, we also brief the explored open research issues as an added contribution to this manuscript.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
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.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Automobile Management System Project Report.pdfKamal Acharya
The proposed project is developed to manage the automobile in the automobile dealer company. The main module in this project is login, automobile management, customer management, sales, complaints and reports. The first module is the login. The automobile showroom owner should login to the project for usage. The username and password are verified and if it is correct, next form opens. If the username and password are not correct, it shows the error message.
When a customer search for a automobile, if the automobile is available, they will be taken to a page that shows the details of the automobile including automobile name, automobile ID, quantity, price etc. “Automobile Management System” is useful for maintaining automobiles, customers effectively and hence helps for establishing good relation between customer and automobile organization. It contains various customized modules for effectively maintaining automobiles and stock information accurately and safely.
When the automobile is sold to the customer, stock will be reduced automatically. When a new purchase is made, stock will be increased automatically. While selecting automobiles for sale, the proposed software will automatically check for total number of available stock of that particular item, if the total stock of that particular item is less than 5, software will notify the user to purchase the particular item.
Also when the user tries to sale items which are not in stock, the system will prompt the user that the stock is not enough. Customers of this system can search for a automobile; can purchase a automobile easily by selecting fast. On the other hand the stock of automobiles can be maintained perfectly by the automobile shop manager overcoming the drawbacks of existing system.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.