Software Performance Estimate using Fuzzy Based Backpropagation Learning

2016 ◽  
pp. 376-398
Author(s):  
Khaleel Ahmad ◽  
Gaurav Kumar ◽  
Abdul Wahid ◽  
Mudasir M. Kirmani
Keyword(s):  
Software Industry ◽  
Performance Measure ◽  
Performance Estimation ◽  
Accurate Estimation ◽  
Software Performance ◽  
Daily Lives ◽  
Software Application ◽  
Performance Estimate ◽  
Efficient Performance ◽  
Software Product

Accurate estimation of the software performance and its reliability is an important task in designing, developing and implementing software as per the desired requirements. With the increase in individuals relying on software application in their daily lives has resulted in increase in demand for good quality software with efficient performance. The professionals in the software industry are facing an uphill task of developing software with efficient performance measure and at the same time capable of evaluating software performance. In order to evaluate software performance it is necessary to have a method to estimate the software performance. The estimation of software performance plays an important role in predicting acceptability and longevity of a software product. Software performance estimation is essential in existing software-dominated environment where part of daily life is directly or indirectly dependent on software for fulfilling requirements. In this chapter discusses the reasons underlying the proposals and shows the pitfalls associated to these software attributes.

Software Performance Estimate using Fuzzy Based Backpropagation Learning

2016 ◽  
pp. 320-344
Author(s):  
Khaleel Ahmad ◽  
Gaurav Kumar ◽  
Abdul Wahid ◽  
Mudasir M. Kirmani
Keyword(s):  
Software Industry ◽  
Performance Measure ◽  
Performance Estimation ◽  
Accurate Estimation ◽  
Software Performance ◽  
Daily Lives ◽  
Software Application ◽  
Performance Estimate ◽  
Efficient Performance ◽  
Software Product

Accurate estimation of the software performance and its reliability is an important task in designing, developing and implementing software as per the desired requirements. With the increase in individuals relying on software application in their daily lives has resulted in increase in demand for good quality software with efficient performance. The professionals in the software industry are facing an uphill task of developing software with efficient performance measure and at the same time capable of evaluating software performance. In order to evaluate software performance it is necessary to have a method to estimate the software performance. The estimation of software performance plays an important role in predicting acceptability and longevity of a software product. Software performance estimation is essential in existing software-dominated environment where part of daily life is directly or indirectly dependent on software for fulfilling requirements. In this chapter discusses the reasons underlying the proposals and shows the pitfalls associated to these software attributes.

scholarly journals APPLICATION OF NEURAL NETWORK TECHNOLOGIES IN THE DENTAL CARIES FORECAST

2020 ◽  
Vol 73 (7) ◽  
pp. 1499-1504
Author(s):  
Oleksandr A. Udod ◽  
Hanna S. Voronina ◽  
Olena Yu. Ivchenkova
Keyword(s):  
Neural Network ◽  
Dental Caries ◽  
Old Patients ◽  
Software Application ◽  
The Neural Network ◽  
Software Product ◽  
High Level ◽  
Network Technologies ◽  
Python Programming ◽  
And Training

The aim: of the work was to develop and apply in the clinical trial a software product for the dental caries prediction based on neural network programming. Materials and methods: Dental examination of 73 persons aged 6-7, 12-15 and 35-44 years was carried out. The data obtained during the survey were used as input for the construction and training of the neural network. The output index was determined by the increase in the intensity of caries, taking into account the number of cavities. To build a neural network, a high-level Python programming language with the NumPay extension was used. Results: The intensity of carious dental lesions was the highest in 35-44 years old patients – 6.69 ± 0.38, in 6-7 years old children and 12-15 years old children it was 3.85 ± 0.27 and 2.15 ± 0.24, respectively (p <0.05). After constructing and training the neural network, 61 true and 12 false predictions were obtained based on these indices, the accuracy of predicting the occurrence of caries was 83.56%. Based on these results, a graphical user interface for the “CariesPro” software application was created. Conclusions: The resulting neural network and the software product based on it permit to predict the development of dental caries in persons of all ages with a probability of 83.56%.

The Performance Mining Method

Big Data ◽  
2016 ◽  
pp. 181-199
Author(s):  
Stella Pachidi ◽  
Marco Spruit
Keyword(s):  
Data Mining ◽  
Financial Management ◽  
Performance Monitoring ◽  
Software As A Service ◽  
Software Performance ◽  
Mining Method ◽  
Data Mining Techniques ◽  
Software Products ◽  
Software Product ◽  
Operation Knowledge

Software Performance is a critical aspect for all software products. In terms of Software Operation Knowledge, it concerns knowledge about the software product's performance when it is used by the end-users. In this paper the authors suggest data mining techniques that can be used to analyze software operation data in order to extract knowledge about the performance of a software product when it operates in the field. Focusing on Software-as-a-Service applications, the authors present the Performance Mining Method to guide the process of performance monitoring (in terms of device demands and responsiveness) and analysis (finding the causes of the identified performance anomalies). The method has been evaluated through a prototype which was implemented for an online financial management application in the Netherlands.

Analytical Model for High–Level Area Estimation of FPGA Design

2016 ◽  
Vol 7 (2) ◽  
pp. 35-44
Author(s):  
Rachna Singh ◽  
Arvind Rajawat
Keyword(s):  
Early Stage ◽  
Estimation Error ◽  
Research Work ◽  
Performance Estimation ◽  
Estimation Accuracy ◽  
Accurate Estimation ◽  
Fpga Design ◽  
Estimation Model ◽  
Area Estimation ◽  
High Level

FPGAs have been used as a target platform because they have increasingly interesting in system design and due to the rapid technological progress ever larger devices are commercially affordable. These trends make FPGAs an alternative in application areas where extensive data processing plays an important role. Consequently, the desire emerges for early performance estimation in order to quantify the FPGA approach. A mathematical model has been presented that estimates the maximum number of LUTs consumed by the hardware synthesized for different FPGAs using LLVM.. The motivation behind this research work is to design an area modeling approach for FPGA based implementation at an early stage of design. The equation based area estimation model permits immediate and accurate estimation of resources. Two important criteria used to judge the quality of the results were estimation accuracy and runtime. Experimental results show that estimation error is in the range of 1.33% to 7.26% for Spartan 3E, 1.6% to 5.63% for Virtex-2pro and 2.3% to 6.02% for Virtex-5.

scholarly journals An Uneasy Truce: Navigating Interdisciplinary Collaboration in the Software Industry

2018 ◽  
Vol 7 (2) ◽  
pp. 184-209
Author(s):  
Natalie D. Hanson
Keyword(s):  
Software Industry ◽  
Interdisciplinary Collaboration ◽  
Project Teams ◽  
Work Context ◽  
Social Scientists ◽  
Team Members ◽  
The Past ◽  
New Concepts ◽  
Software Product

Over the past few decades, much has been written about the ways in which project teams bring technologies to market.  In this context, social scientists typically partner with specialized designers to bring their research and new concepts to life in a way that is consumable by a variety of team members, including engineers and data scientists.  This paper explores one such collaboration, and describes the challenging conditions that team members face — both in their work context and with their peers — in imagining and building a commercially viable software product.  

Legal Mechanisms for Mitigating the Effect of Restrictive Licensing Provisions

2017 ◽  
Author(s):  
Noam Shemtov
Keyword(s):  
Software Industry ◽  
Competition Law ◽  
Contract Law ◽  
Third Parties ◽  
Functional Elements ◽  
Eu Competition Law ◽  
Software Product ◽  
The Us ◽  
Functional Features ◽  
The Eu

This chapter examines the legal mechanisms for mitigating the effect of restrictive licensing provisions used by right holders to regulate the use of functional elements of software, focusing on both negotiable and non-negotiable licences. In particular, it considers the extent to which existing judicial and statutory tools are effective in regulating restrictive licensing provisions in the software industry. The chapter first discusses contract law-based mechanisms, giving emphasis to the implications of whether a transaction is classified as a sale or a licence for the publishers’ ability to restrict third parties from reproducing or appropriating functional features in their software product. It then analyses pre-emption-based mechanisms, as well as competition law-based mechanisms, citing the EU competition law and the US antitrust law.

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