Malware represents one of the dangerous threats to computer security. Dynamic analysis has difficulties in detecting unknown malware. This paper developed an integrated multi – layer detection approach to provide more accuracy in detecting malware. User interface integrated with Virus Total was designed as a first layer which represented a warning system for malware infection, Malware data base within malware samples as a second layer, Cuckoo as a third layer, Bull guard as a fourth layer and IDA pro as a fifth layer. The results showed that the use of fifth layers was better than the use of a single detector without merging. For example, the efficiency of the proposed approach is 100% compared with 18% and 63% of Virus Total and Bellegarde respectively. Â
In this paper, one of the Machine Scheduling Problems is studied, which is the problem of scheduling a number of products (n-jobs) on one (single) machine with the multi-criteria objective function. These functions are (completion time, the tardiness, the earliness, and the late work) which formulated as . The branch and bound (BAB) method are used as the main method for solving the problem, where four upper bounds and one lower bound are proposed and a number of dominance rules are considered to reduce the number of branches in the search tree. The genetic algorithm (GA) and the particle swarm optimization (PSO) are used to obtain two of the upper bounds. The computational results are calculated by coding (progr
... Show MoreCurrently no one can deny the importance of data protection, especially with the proliferation of hackers and theft of personal information in all parts of the world .for these reasons the encryption has become one of the important fields in the protection of digital information.
This paper adopts a new image encryption method to overcome the obstacles to previous image encryption methods, where our method will be used Duffing map to shuffled all image pixels ,after that the resulting image will be divided into a group of blocks for perform the shuffling process via Cross Chaotic Map.
Finally, an image called key image was created by using Quadratic number spirals which will be used to generate nu
This research asks what are negative social behaviours in the Kurdistan Region of Iraq (KRI) raised by the talk shows on the (NRT) channel? Furthermore, it aims to identify the most significant themes addressed by talk shows on the (NRT) channel regarding negative social behaviours in the KRI by using the content analysis approach through non-random purposive sampling to understand the dialogue contents that dealt with this subject. This study has reached a set of results: through its talk shows, the (NRT) channel attempts to create a media vision about the spread of negative social behaviours in the KRI and stand up to the dangers associated with these behaviours. At the same time, those programs tried to marginalize the behaviours that
... Show MoreIntelligent systems can be used to build systems that simulate human behavior. One such system is lip reading. Hence, lip reading is considered one of the hardest problems in image analysis, and thus machine learning is used to solve this problem, which achieves remarkable results, especially when using a deep neural network, in which it dives deeply into the texture of any input. Microlearning is the new trend in E-learning. It is based on small pieces of information to make the learning process easier and more productive. In this paper, a proposed system for multi-layer lip reading is presented. The proposed system is based on micro content (letters) to achieve the lip reading process using deep learning and auto-correction mo
... Show MoreThe proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
... Show MoreCompression is the reduction in size of data in order to save space or transmission time. For data transmission, compression can be performed on just the data content or on the entire transmission unit (including header data) depending on a number of factors. In this study, we considered the application of an audio compression method by using text coding where audio compression represented via convert audio file to text file for reducing the time to data transfer by communication channel. Approach: we proposed two coding methods are applied to optimizing the solution by using CFG. Results: we test our application by using 4-bit coding algorithm the results of this method show not satisfy then we proposed a new approach to compress audio fil
... Show MoreWith a descriptive and analytical approach, it discusses the concept of phenomenology as an approach to seeing the aesthetics of ugliness as one of the concepts associated with the aesthetic experience in contemporary art designs, as it is the result of communication between artistic production and the recipient, which leads to creating a state of aesthetic pleasure. A phenomenological method is used to uncover the aesthetics of ugly and to connect ugliness and beauty since ugliness in aesthetics incorporates beauty as a modern aesthetic vision from the phenomenological perspective. The study investigated aesthetics as a phenomenon of perception, sensory knowledge, and the aesthetic response to the production of designs in contemporary a
... Show MoreAbstract—In this study, we present the experimental results of ultra-wideband (UWB) imaging oriented for detecting small malignant breast tumors at an early stage. The technique is based on radar sensing, whereby tissues are differentiated based on the dielectric contrast between the disease and its surrounding healthy tissues. The image reconstruction algorithm referred to herein as the enhanced version of delay and sum (EDAS) algorithm is used to identify the malignant tissue in a cluttered environment and noisy data. The methods and procedures are tested using MRI-derived breast phantoms, and the results are compared with images obtained from classical DAS variant. Incorporating a new filtering technique and multiplication procedure, t
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