Cross project defect prediction: a comprehensive survey with its SWOT analysis

Innovations in Systems and Software Engineering - Software fault prediction (SFP) refers to the process of identifying (or predicting) faulty modules based on its characteristics/software metrics....     

A constrained non-linear optimization model for fuzzy pairwise comparison matrices using teaching learning based optimization

Non-linear optimization models have been recently proposed to derive crisp weights from fuzzy pairwise comparison matrices. In this paper, a TLBO (Teaching Learning Based Optimization) based solution is presented for solving an optimization model as a system of non-linear equations to derive crisp weights from fuzzy pairwise comparison matrices in AHP (Analytic Hierarchy Process). This fuzzy-AHP method is named as TLBO-1. It has been found that TLBO-1 can lead to inconsistent or less consistent weights. To solve the problem of inconsistent weights, a new constrained non-linear optimization model is proposed in this paper. This model is based on the min-max approach for fuzzy pairwise comparison ratios of weights. TLBO is again used to solve this optimization model, and crisp weights are derived. This fuzzy AHP method is named as TLBO-2. The effectiveness of the proposed model is illustrated by three examples. For each example, the consistency of the derived crisp weights is compared with other optimization models. The results show that the TLBO-2 method can derive more consistent weights for the fuzzy AHP based Multi-Criteria Decision Making (MCDM) systems as compared to the other optimization models.     

Artificial intelligence applications in Permanent Magnet Brushless DC motor drives

Permanent Magnet Brushless DC (PMBLDC) machines are more popular due its simple structure and low cost. Improvements in permanent magnetic materials and power electronic devices have resulted in reliable, cost effective PMBLDC drives, for many applications. Advances in artificial intelligent applications like neural network, fuzzy logic, Genetic algorithm etc. have made tremendous impact on electric motor drives. The brushless DC motor is a multivariable and non-linear system. In conventional PMBLDC drives speed and position sensing of brushless DC motors require high degree of accuracy. Unfortunately, traditional methods of control require detailed modelling of all the motor parameters to achieve this. The Intelligent control techniques like, fuzzy logic control/Neural network control etc. uses heuristic input–output relations to deal with vague and complex situations. This paper presents a literature survey on the intelligent control techniques for PMBLDC motor drives. Various AI techniques for PMBLDC motor drives are described. Attempt is made to provide a guideline and quick reference for the researchers and practicing engineers those are working in the area of PMBLDC motor drives.     

A novel protocol for efficient authentication in cloud-based IoT devices

The Internet of Things (IoT) has emerged as one of the most revolutionary technological innovations with the proliferation of applications within almost all fields of the human race. A cloud environment is the main component of IoT infrastructure to make IoT devices efficient, safe, reliable, usable, and autonomous. Reduction in infrastructure cost and demand accessibility of shared resources are essential parts of cloud-based IoT (CIoT) infrastructure. Information leakage in cloud-assisted IoT devices may invite dangerous activities and phenomena. Various cloud-based systems store IoT sensor data and later on access it accordingly. Some of them are public, and some of them are private. Private cloud services must be secured from external as well as internal adversaries. Hence, there must be a robust mechanism to prevent unauthorized access to devices. This paper proposes a novel and efficient protocol based on the Elliptic Curve property known as Elliptic Curve Discrete Logarithm Problem (ECDLP) with hash and XOR functions for the authentication in cloud-based IoT devices. In comparison to the existing protocols, the proposed protocol is resistant to attacks and other security vulnerabilities. The one-way hash function and XOR function effectively ensure a reduction in computation cost. AVISPA and BAN logic have been used for formal analysis of the proposed protocol. As per the performance analysis results, it is clear that the proposed protocol is efficiently suitable for cloud-assisted IoT devices.

     

Significant full reference image segmentation evaluation: a survey in remote sensing field

Multimedia Tools and Applications - Image segmentation is a crucial step in remote sensing application, as it breaks down a larger image into smaller chunks, which contains useful information....     

Deep transfer modeling for classification of Maize Plant Leaf Disease

Multimedia Tools and Applications - Currently, Deep Learning is playing an influential role for Image analysis and object classification. Maize’s diseases reduce production that subsequently...     

An efficient verifiable (t,n)-threshold secret image sharing scheme with ultralight shares

Multimedia Tools and Applications - A secret sharing scheme partitions a secret into a set of shares and distributes them among the eligible participants, with each participant receiving one share...