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].

 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

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

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

Drilling deviated wells is a frequently used approach in the oil and gas industry to increase the productivity of wells in reservoirs with a small thickness. Drilling these wells has been a challenge due to the low rate of penetration (ROP) and severe wellbore instability issues. The objective of this research is to reach a better drilling performance by reducing drilling time and increasing wellbore stability.

In this work, the first step was to develop a model that predicts the ROP for deviated wells by applying Artificial Neural Networks (ANNs). In the modeling, azimuth (AZI) and inclination (INC) of the wellbore trajectory, controllable drilling parameters, unconfined compressive strength (UCS), formation