DFD-SS: Document Forgery Detection using Spectral – Spatial Features for Hyperspectral Images

In the present era of machines and edge-cutting technologies, still document frauds persist. They are done intuitively by using almost identical inks, that it becomes challenging to detect them—this demands an approach that efficiently investigates the document and leaves it intact. Hyperspectral imaging is one such a type of approach that captures the images from hundreds to thousands of spectral bands and analyzes the images through their spectral and spatial features, which is not possible by conventional imaging. Deep learning is an edge-cutting technology known for solving critical problems in various domains. Utilizing supervised learning imposes constraints on its usage in real scenarios, as the inks used in forgery are not known prior. Therefore, it is beneficial to use unsupervised learning. An unsupervised feature extraction through a Convolutional Autoencoder (CAE) followed by Logistic Regression (LR) for classification is proposed (CAE-LR). Feature extraction is evolved around spectral bands, spatial patches, and spectral-spatial patches. We inspected the impact of spectral, spatial, and spectral-spatial features by mixing inks in equal and unequal proportion using CAE-LR on the UWA writing ink hyperspectral images dataset for blue and black inks. Hyperspectral images are captured at multiple correlated spectral bands, resulting in information redundancy handled by restoring certain principal components. The proposed approach is compared with eight state-of-art approaches used by the researchers. The results depicted that by using the combination of spectral and spatial patches, the classification accuracy enhanced by 4.85% for black inks and 0.13% for blue inks compared to state-of-art results. In the present scenario, the primary area concern is to identify and detect the almost similar inks used in document forgery, are efficiently managed by the proposed approach.     

A Channel Borrowing Approach for Cluster-based Hierarchical Wireless Sensor Networks

Mobile Networks and Applications - In Wireless Sensor Networks (WSNs), energy-efficient routing is required to conserve the scarce resources of these networks. Various energy-efficient routing...     

An innovative technology of directional propagation of hydraulic fracture guided by radial holes in fossil hydrogen energy development

Conventional hydraulic fracturing fails to develop low permeability reservoirs of fossil hydrogen energy that are not located in the direction of maximum principal in-situ stress. A new technology of fracture propagation guided by radial holes is proposed, which can realize directional propagation of hydraulic fracture along radial holes in fossil hydrogen energy development. In order to verify this new technology, a model of radial holes combined with hydraulic fracturing is established by the ABAQUS extended finite element method. Simulation results show that radial holes play a guiding role in fractures propagation. The influence extent of seven factors on the directional propagation of hydraulic fracture is listed as follows (from strong to weak): azimuth of radial holes > horizontal in-situ stress difference of fossil hydrogen reservoir > injection rate of fracturing fluid > Young's modulus of rock > permeability of fossil hydrogen reservoir > Poisson ratio of rock > viscosity of fracturing fluid. True tri-axial experiment is carried out to verify the accuracy of numerical simulation, and the result is consistent with numerical model, which indicates that numerical simulation is reliable.     

Application of a software agility assessment model – AgilityMod in the field

Adoption of agile values and principles and transformation of organizations towards agility are not easy and straightforward. Misinterpretation of agile principles and values, and adoption of partial solutions with few agile practices instead of holistic approaches prevent organizations to obtain full benefits of agile methods. We developed the Software Agility Assessment Reference Model (AgilityMod) for the appraisal of software projects from agility perspective and to provide guidance on specifying gaps on the road towards agility (agile maturity). The meta-model of AgilityMod was defined in relation with the ISO/IEC 15504-Process Assessment Model. AgilityMod was developed in an iterative and incremental manner by running successive case studies and getting opinions of experts for the evaluation and improvement of the Model. The multiple case study that we present here in detail included the implementation of the Model in eight software development companies. The results of this case study were evaluated by the case study participants. According to the significant majority of the case study participants, AgilityMod achieves its purpose.     

Scalable parallel implementation of migrating birds optimization for the multi-objective task allocation problem

The Journal of Supercomputing - As the distributed computing systems have been widely used in many research and industrial areas, the problem of allocating tasks to available processors in the...