Cybercrime and risks to children between the problems and solutions( An analytical study in the light of international, Arab and national statistics).
Lies the problem of the study to identify a new type of crime is different from the same traditional character of the crimes or what was customary since human creation up to the information revolution and we enter the era of globalization, which is also called (cyber crime) and their negative impact on all segments of society, especially children, as they the day of the most important social security threats, for all local and international communities alike , and those risks require collective action to various sectors and segments of society ,especially the educated classes in order to raise community awareness of the dangers of these crimes and their dimensions and manifestations that are still under study and research and digital exploration and statistical especially states that characterized Banglagaha prolonged contact of the world , making it more vulnerable to such crimes characterized by a high degree of organization , precision and uncertainty for large segments of individuals , specifically in the Iraqi society , The importance of this study lies in its search optimization for this phenomenon, and the legacy of a great vacuum in punitive legal aspect to criminalize this type of crime, which requires us a quick review of all laws that seek to curb cyber crime, whether at the international, regional or Arab or national through a modification and change, so in line with the new reality
The consisting of four topics to study in answer focused on some questions including: What are the cyber crimes, and what are the kinds of characteristics, and what are the difficulties that could face means control at the international level and Aarabiy and local, and what are the risks to various private groups in society, the kids category 1. The study has concluded that these crimes notifier great on all members of the community, especially children.
2. It threatens Social Security is not only the local and national community, but that the risks and penetrate beyond the territorial and national and international borders.
3. Azert results that traditional laws and new laws still do not rise to the level of combating this type of crime, and need more studies with to find the kind of coordination and cooperation with various countries to track crimes that carry the trait and the nature of the laws that could criminalize the perpetrators real quest.
4.Azart study that this type of crime suffered material losses and moral expensive process threatens the advancement of society and its development in the long run, particularly with regard to terrorism and the exploitation of children in this type of crime offenses.
A comprehensive review focuses on 3D network-on-chip (NoC) simulators and plugins while paying attention to the 2D simulators as the baseline is presented. Discussions include the programming languages, installation configuration, platforms and operating systems for the respective simulators. In addition, the simulator’s properties and plugins for design metrics evaluations are addressed. This review is intended for the early career researchers starting in 3D NoC, offering selection guidelines on the right tools for the targeted NoC architecture, design, and requirements.
The main reason for the emergence of a deepfake (deep learning and fake) term is the evolution in artificial intelligence techniques, especially deep learning. Deep learning algorithms, which auto-solve problems when giving large sets of data, are used to swap faces in digital media to create fake media with a realistic appearance. To increase the accuracy of distinguishing a real video from fake one, a new model has been developed based on deep learning and noise residuals. By using Steganalysis Rich Model (SRM) filters, we can gather a low-level noise map that is used as input to a light Convolution neural network (CNN) to classify a real face from fake one. The results of our work show that the training accuracy of the CNN model
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Image pattern classification is considered a significant step for image and video processing. Although various image pattern algorithms have been proposed so far that achieved adequate classification, achieving higher accuracy while reducing the computation time remains challenging to date. A robust image pattern classification method is essential to obtain the desired accuracy. This method can be accurately classify image blocks into plain, edge, and texture (PET) using an efficient feature extraction mechanism. Moreover, to date, most of the existing studies are focused on evaluating their methods based on specific orthogonal moments, which limits the understanding of their potential application to various Discrete Orthogonal Moments (DOM
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The topic of supra.topological.spaces considered one of the important topics because it is a generalization to topological.spaces. Many researchers have presented generalizations to supra open sets such as supra semi.open and supra pre.open sets and others. In this paper, the concept of δ∼open sets was employed and introduced in to the concept of supra topology and a new type of open set was extracted, which was named S∼δ∼open. Our research entails the utilization of this category of sets to form a new concepts in these spaces, namely S∼δ∼limit points and S∼δ∼derive points, and examining its relationship with S∼open and S∼reg∼open. Based on this class of sets, we have introduced other new concepts such as S∼isolate
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