The issue of increasing the range covered by a wireless sensor network with restricted sensors is addressed utilizing improved CS employing the PSO algorithm and opposition-based learning (ICS-PSO-OBL). At first, the iteration is carried out by updating the old solution dimension by dimension to achieve independent updating across the dimensions in the high-dimensional optimization problem. The PSO operator is then incorporated to lessen the preference random walk stage's imbalance between exploration and exploitation ability. Exceptional individuals are selected from the population using OBL to boost the chance of finding the optimal solution based on the fitness value. The ICS-PSO-OBL is used to maximize coverage in WSN by converting r

DeepFake is a concern for celebrities and everyone because it is simple to create. DeepFake images, especially high-quality ones, are difficult to detect using people, local descriptors, and current approaches. On the other hand, video manipulation detection is more accessible than an image, which many state-of-the-art systems offer. Moreover, the detection of video manipulation depends entirely on its detection through images. Many worked on DeepFake detection in images, but they had complex mathematical calculations in preprocessing steps, and many limitations, including that the face must be in front, the eyes have to be open, and the mouth should be open with the appearance of teeth, etc. Also, the accuracy of their counterfeit detectio

Theoretical calculation of the electronic current at N 3 contact with TiO 2 solar cell devices ARTICLES YOU MAY BE INTERESTED IN Theoretical studies of electronic transition characteristics of senstizer molecule dye N3-SnO 2 semiconductor interface AIP Conference. Available from: https://www.researchgate.net/publication/362813854_Theoretical_calculation_of_the_electronic_current_at_N_3_contact_with_TiO_2_solar_cell_devices_ARTICLES_YOU_MAY_BE_INTERESTED_IN_Theoretical_studies_of_electronic_transition_characteristics_of_senstiz [accessed May 01 2023].

Purpose: The purpose of this study was to clarify the basic dimensions, which seeks to indestructible scenarios practices within the organization, as a final result from the use of this philosophy.

Methodology: The methodology that focuses adoption researchers to study survey of major literature that dealt with this subject in order to provide a conceptual theoretical conception of scenarios theory  .

The most prominent findings: The only successful formulation of scenarios, when you reach the decision-maker's mind wa takes aim to form a correct mental models, which appear in the expansion of Perception managers, and adopted as the basis of the decisions taken. The strength l

 Abstract

It considers training programs is an important process contributing to provide employees with the skills required to do their jobs efficiently and effectively, so it should be concerned with and the focus of all government our organizations, and perhaps the most important reasons that I was invited to select the subject (evaluation of training programs directed toward the diagnosis of the phenomenon of financial and administrative corruption) It is the importance of those programs working in the regulatory institutions General and the Office of Inspector General of Finance and the Ministry particularly for employees because of their role in the development of their skills and their experience and their beha

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

Статья посвящена возможности использования в обучении русскому языку как иностранному лингвоориентированной методики для арабских студентов. Обосновывается термин «лингвоориентированная методика», предложенный В. Н. Вагнер, и на основе положений заявленной методики проводится сопоставление изучаемого (русского) языка с родным (арабским) языком обучающихся.

Dust is a frequent contributor to health risks and changes in the climate, one of the most dangerous issues facing people today. Desertification, drought, agricultural practices, and sand and dust storms from neighboring regions bring on this issue. Deep learning (DL) long short-term memory (LSTM) based regression was a proposed solution to increase the forecasting accuracy of dust and monitoring. The proposed system has two parts to detect and monitor the dust; at the first step, the LSTM and dense layers are used to build a system using to detect the dust, while at the second step, the proposed Wireless Sensor Networks (WSN) and Internet of Things (IoT) model is used as a forecasting and monitoring model. The experiment DL system

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when