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In this paper, we discussed redundant tasks in consumer electronics software in terms of Petri nets. We first defined redundant tasks formally. Next we proposed sufficient conditions and necessary conditions to find redundant tasks in consumer electronics software. Then we showed the efficiency of the proposed reduction by using an application example to smart refrigerator.
Software Development Effort Estimation (SDEE) plays a primary role in software project management. Among several techniques suggested for estimating software development effort, analogy-based software effort estimation approaches stand out as promising techniques.In this paper, the performance of Fuzzy Analogy is compared with that of six other SDEE techniques (Linear Regression, Support Vector Regression,...
In the electricity sector, new sides have emerged with the development of technology and the increasing the electric energy need. Today, electricity has become a product that is bought and sold in the market environment. Forecasting which is the first step of plans and planning have become much more important and have been made mandatory for the market participants by energy market regulators. In...
With the increase in the availability of information regarding energy use, there is an increase of forecasting software on the energy market, that can forecast on the short, medium and long term. In the paper, there is presented a software solution for load forecasting using Artificial Neural Networks (ANN) method. In the case study, we have written an application for a consumer which is engaged in...
The current developments of software defined networking (SDN) paradigm provide a flexible architecture for network control and management, in the cost of deploying new hardwares by replacing the existing routing infrastructure. Further, the centralized controller architecture of SDN makes the network prone to single point failure and creates performance bottleneck. To avoid these issues and to support...
In this study, text mining based methods are proposed for requirement traceability analysis which is one of the most essential steps in the software life cycle. It is aimed to automate the requirements traceability process of the software architecture, which is conducted by a data analyst manually, with the proposed methods. For this purpose, besides the tf-idf and Latent Semantic Analysis (LSI/LSA)...
Today, much more than in the past are discussed of plagiarism in the research. Conditions of the Web and Possibility of complex and smart searches in a short time, is rated to this, and as a result has arrived significant damages to the research. Tools designed to deal with plagiarism act on the text and ignore images. On the other, an inseparable part of information transfer are images that transfer...
Spiking Neural Networks (SNNs) are widely regarded as the third generation of artificial neural networks, and are expected to drive new classes of recognition, data analytics and computer vision applications. However, large-scale SNNs (e.g., of the scale of the human visual cortex) are highly compute and data intensive, requiring new approaches to improve their efficiency. Complementary to prior efforts...
The effort required for the development of a software system is predicted through the cost of software estimation. Completion of project within time and budget limits is required for accurate cost estimation. Effort and cost estimation can be done through various modes. A new hybrid algorithm which is a combination of concepts of Artificial Bee Colony (ABC) and Local search procedures is used here...
Service providers and vendors are moving toward a network virtualized core, whereby multiple applications would be treated on their own merit in programmable hardware. Such a network would have the advantage of being customized for user requirements and allow provisioning of next generation services that are built specifically to meet user needs. In this article, we articulate the impact of network...
The evaluation method of factors affecting software reliability is based on the effect factors related to software reliability in each stage of software life cycle, by this method, an early prediction about the software reliability can be made. The selection of factors and its weights allocation are the keys to make the result reasonable. There are a lot of weighting methods, such as expert investigation...
In software project management, software development effort estimation (SDEE) is one of the critical activities. Analogy-Based Estimation (ABE) is most popular estimation technique suggested in SDEE literature [1, 7, 22]. Researchers have proposed various methods to improve the accuracy of ABE by adjusting the retrieved solution. The research suggests all published calibration methods depend on linear...
The cost of deleting a software bug increases ten times as it is floated onto the next phase of software development lifecycle (SDLC). This makes the task of the project managers difficult and also degrades the quality of the output software product. Software defect prediction (SDP) was proposed as a solution to the problem which could anticipate the defective modules and hence, deal with them in...
The paper presents application of STATISTICA v6.0 and STATISTICA NEURAL NETWORKS software for electrical load forecasting. Relevance of forecasting is influenced by the fact that extraction of minerals in oil and gas industry is increasing. As oil extraction and transportation is very power intensive, the problem of load growth has arisen. Then, a task for forecasting of load growth occurs. The results...
Development of complex program software of automated control systems is connected with essential expenses. Failure of the software can lead to control system fail as a whole and to connected with these economic or other losses. Ways of rational decrease in expenses and losses are given in this article. In article three questions are considered: Problem definition of optimization of reliability of...
The evaluation model of the software reliability is implemented on the basis of artificial intelligence methods, using artificial neural networks. On entry of the model the debugging time is served, on return the outlook the value of the failure rate is formed. For the model implementation a special type of neural network — a vertically-layered neural network is worked out. The model accuracy is increasing...
To facilitate the development of low-cost, low-power, and high-density hardware neural networks, we have successfully developed a Ta/TaOx/TiO2/Ti RRAM-based synaptic device. The device exhibits numerous synaptic functions resembling those in biological synapses, including synaptic plasticity of potentiation and depression, spike-timing dependent plasticity, paired-pulse facilitation and a transition...
Software defect prediction (SDP) is a most dynamic research area in software engineering. SDP is a process used to predict the deformities in the software. To identifying the defects before the arrival of item or aimed the software improvement, to make software dependable, defect prediction model is utilized. It is always desirable to predict the defects at early stages of life cycle. Hence to predict...
Online Social Networks (OSNs) are becoming increasingly important in our day to day lives. Statistics show that 74% of the Internet users are involved in social networking. Unfortunately many of us are unaware of the threats and vulnerabilities that come with OSNs. These issues can be resolved by using Data Sanitization; the process of disguising sensitive information by overwriting it with realistic...
This paper presents an approach for the medical diagnostics of pulmonary diseases condensate of moisture in exhaled air. A new approach is proposed which solves the problem of automated intelligent diagnostic using machine learning techniques. Our method runs in real-time and reaches the accuracy about 95%.
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