The lower respiratory tract of sheep was studied to determine the torsion and branching of the bronchial tree. The respiratory system of ruminants and all living organisms is one of the most important organs in the body that controls the amount of gas exchange between the heart and lungs through the airways, it is clear that in sheep it consists of a narrow bronchial tube that reaches the extent of lung tissue repercussions. He used silicon, water, acid, and at room temperature, and the substance was injected with an injection gun through the trachea and was pushed gently to spread and distribute in all parts of the lungs with moderate manual pressure. The results showed that the mold shape in the lung and the bronchial branches of

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 Bel

The urban Gentrification  is an inclusive global phenomenon to restructure the cities on the overall levels, the research to propose a specific study about the concept of urban Gentrification in the cities and showcasing its, specifications, and results, and how to deal with the variables that occur on cities through improvements as part of urban renewal projects, then the general axis of the research is shrinked, choosing the urban centers as the most important areas that deal with the urban Gentrification process due to its direct connection with indivisuals and social changes, and to process the specific axis of the research theses and studies will be showcased that discuss the topic in different research directions, and emerged

The study dealt with measuring the impact of the availability of each of the content elements of the interaction, electronic services, and information on the evaluation of the users of the government website for its effectiveness in terms of the site’s functions and for measuring the site’s ability to present the organization’s tasks to customer groups.

Authority is concerned with measuring the confidence of customers in the content of the site, and in the organization as a whole. Validity is related to measuring the effectiveness of employing the site’s content to achieve the goal of its creation and in communicating with customers. Availability It is for measuring the ease of use of the site. The relevance, which means

The Internet of Things (IoT) is an information network that connects gadgets and sensors to allow new autonomous tasks. The Industrial Internet of Things (IIoT) refers to the integration of IoT with industrial applications. Some vital infrastructures, such as water delivery networks, use IIoT. The scattered topology of IIoT and resource limits of edge computing provide new difficulties to traditional data storage, transport, and security protection with the rapid expansion of the IIoT. In this paper, a recovery mechanism to recover the edge network failure is proposed by considering repair cost and computational demands. The NP-hard problem was divided into interdependent major and minor problems that could be solved in polynomial t

The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog