Hybrid Algorithm for the detection of Pixel-based digital image forgery using Markov and SIFT descriptors

Today, image forgery is common due to the massification of low-cost/high-resolution digital cameras, along with the accessibility of computer programs for image processing. All media is affected by this issue, which makes the public doubt the news. Though image modification is a typical process in entertainment, when images are taken as evidence in a legal process, modification cannot be considered trivial. Digital forensics has the challenge of ensuring the accuracy and integrity of digital images to overcome this issue. This investigation introduces an algorithm to detect the main types of pixel-based alterations such as copy-move forgery, resampling, and splicing in digital images. For the evaluation of the algorithm, CVLAB, CASIA V1, Columbia, and Columbia Uncompressed datasets were used. Of 7100 images evaluated, 3666 were unaltered, 791 had resampling, 2213 had splicing, and 430 had copy-move forgeries. The algorithm detected all proposed forgery pixel methods with an accuracy of 91%. The main novelties of the proposal are the reduced number of features needed for identification and its robustness for the file format and image size.

Deposition of YSZ Layer by PS-PVD on Different Materials

Plasma Spray Physical Vapour Deposition (PS-PVD) method was designed for production of ceramic layer on nickel superalloys. In typical process before deposition the base material is heated by plasma up to 900 °C. In present article the yttria stabilized zirconia (YSZ) was deposited on low melting point materials: 2017A-type aluminium alloy and Cu-ETP copper. The influence of power current, process time and powder feed rate on structure and thickness of obtained coatings was analysed. During first deposition process the overheating of Al-sample was observed and as result the power current was decreased to 1600 A. In the next experimental the approx. 5 mm thick dense coating was formed. During experimental processes of YSZ deposition on copper the thickness of coating increased from approx. 5 to 22 mm. The copper-oxide layer was formed under ceramic layer. The microscopic assessment showed the difficulties in formation of columnar ceramic layer on use base materials. The obtained coating was characterized by dense structure as a result of lower plasma energy during process. The increasing of power current is not possible in the case of overheating of base material.

Les polls électoraux

The polling system of «Polls» in Belgium is a typical process of the political life. Its purpose is to elaborate into the political parties the voting lists, either with internal polling processes, or by mecanisms of cooptation, or simply by choices corresponding to the establishment of the Belgian society.The pre-voting process seems to be relevant and adapted to the technique of the proportional repartition of votes between the lists of the parties.In fact, only several organizations of the Belgian Socialist Party utilize regularly this process for the structure of their lists of candidates before the legislature votes.It is a postulat of the political Democracy in Belgium of which the specific result is to reinforce the oligarchies.

Survey on Prediction of Loan Approval Using Machine Learning Techniques

The enhancement in the banking sector lots of people are applying for bank loans but the bank has its limited assets which it has to grant to limited people only, so finding out to whom the loan can be granted which will be a safer option for the bank is a typical process. So in this paper we try to reduce this risk factor behind selecting the safe person so as to save lots of bank efforts and assets. This is done by mining the Big Data of the previous records of the people to whom the loan was granted before and on the basis of these records/experiences the machine was trained using the machine learning model which give the most accurate result. The main objective of this paper is to predict whether assigning the loan to particular person will be safe or not. This paper is divided into four sections (i)Data Collection (ii) Comparison of machine learning models on collected data (iii) Training of system on most promising model (iv) Testing.

FRAMEWORK FOR SYSTEMATIZATION OF DATA SCIENCE METHODS

The rapid development of data science has led to the accumulation of many models, methods, and techniques that had been successfully applied. As the analysis of publications has shown, the systematization of data science methods and techniques is an urgent task. However, in most cases, the results are relevant to applications in a particular problem domain. The paper develops the framework for the systematization of data science methods, neither domain-oriented nor task-oriented. The metamodel-method-technique hierarchy organizes the relationships between existing methods and techniques and reduces the complexity of their understanding. The first level of the hierarchy consists of metamodels of data preprocessing, data modeling, and data visualization. The second level comprises methods corresponded to metamodels. The third level collects the main techniques grouped according to methods. The authors describe the guiding principles of the framework use. It provides a possibility to define the typical process of problem-solving with data science methods. A case study is used to verify the framework’s appropriateness. Four cases of applying data science methods to solve practical problems described in publications are examined. It is shown that the described solutions are entirely agreed with the proposed framework. The recommended directions for applying the framework are defined. The constraint of the framework applying is structured or semi-structured data that should be analyzed. Finally, the ways of further research are given.

Antisolvent treatment of copper(I) thiocyanate (CuSCN) hole transport layer for efficiency improvements in organic solar cells and light-emitting diodes

Copper(I) thiocyanate (CuSCN) has been widely used as a hole-transport layer in organic optoelectronic devices. However, being a coordination polymer, its solution-processing is not straightforward; the typical process requires sulfide-based...

Hierarchically multifunctional integrated catalyst with intimate and synergistic active sites for one-pot tandem catalysis

As a typical process intensified strategy, tandem reaction driven by multifunctional catalyst is a paragon of the green catalytic process. Two or more active sites are usually required and their...

Linear models for diallel crosses: a review with R functions

Key message A new R-software procedure for fixed/random Diallel models was developed. We eased the diallel schemes approach by considering them as specific cases with different parameterisations of a general linear model. Abstract Diallel experiments are based on a set of possible crosses between some homozygous (inbred) lines. For these experiments, six main diallel models are available in literature, to quantify genetic effects, such as general combining ability (GCA), specific combining ability (SCA), reciprocal (maternal) effects and heterosis. Those models tend to be presented as separate entities, to be fitted by using specialised software. In this manuscript, we reinforce the idea that diallel models should be better regarded as specific cases (different parameterisations) of a general linear model and might be fitted with general purpose software facilities, as used for all other types of linear models. We start from the estimation of fixed genetical effects within the R environment and try to bridge the gap between diallel models, linear models and ordinary least squares estimation (OLS). First, we review the main diallel models in literature. Second, we build a set of tools to enable geneticists, plant/animal breeders and students to fit diallel models by using the most widely known R functions for OLS fitting, i.e. the ‘lm()’ function and related methods. Here, we give three examples to show how diallel models can be built by using the typical process of GLMs and fitted, inspected and processed as all other types of linear models in R. Finally, we give a fourth example to show how our tools can be also used to fit random/mixed effect diallel models in the Bayesian framework.