درخت حوزه‌های تخصصی

The objective of this research is to identify the technology of cloud computing in terms of its concept, its development, its objectives, its components, models, classifications, and the advantages of its use in the teaching process at the University of Samarra, as well as to identify the most important challenges and obstacles that teachers face in using University of Samarra. The researcher used the descriptive approach in his research. This research was carried out on an objective sample of 40 teaching staff members in the Department of Life Sciences and English at the Faculty of Education / Samarra University. A questionnaire consisting of 22 questions were used as a data collection tool, which included two axes: The first axis: the advantages of using cloud computing technology in the process of teaching at the University of Samarra. The second axis: the challenges of using cloud computing technology in the process of teaching at the University of Samarra. The researcher used the statistical program (SPSS 20) in order to examine the differences between the responses of the members of the research sample. The results revealed that the estimates of the teaching of the advantages of the use of cloud computing technology in the teaching process at the University of Samarra, which included the search tool, came very much, and the results revealed the most important challenges which stand in the way of the use of cloud computing technology in university education. The study recommended institutions of higher learning and universities with a set of important recommendations regarding the use of cloud computing technology in educational institutions. 

The condition of the hotel's competitiveness is a strong brand. The introduction of digital marketing in the strategy of hotel branding creates new opportunities for hotels when interacting with guests through digital channels. The purpose of this study is to develop theoretical and practical measures to improve the effectiveness of marketing strategies in hotel branding using digital tools. To achieve the goal of the study was conducted research on targeted branding some of the largest hotel chains. The results of the analysis showed that in the process of branding at each stage the corresponding goals have achieved by means of advertising, marketing, public relations management, personnel selection, corporate culture.This study substantiates the main tools of the strategy of the Digital Marketing and Sales. The brands need to constantly monitor changes in market positions and audience sentiment using all the features and channels. The priorities should be implemented by performing key tasks, in particular such astimely measurements as far as brand experience has a positive effect on customer satisfaction and loyalty.

Now a day's software is the baseline for the success of any organization. There is a huge demand of quality software in the customer-oriented market. Regression testing makes it possible but it’s a costly affair. Regression test suite minimization is way to reduce this cost but it is NP hard problem. This paper proposes an effective approach for regression test suite minimization using Artificial Ecosystem Optimization algorithm. To improve its performance a modified Artificial Ecosystem Optimization algorithm is proposed for Test case minimization. To evaluate the performance of proposed approach experiment is conducted in controlled parameter setting on open-source subject program from SIR repository. The results are collected and analyzed in comparison to existing approaches using statistical test. The test results reflect the superiority of proposed approach.

The main goal of the given research is to conduct cross-cultural analysis of financial support mechanisms in Europe in order to develop practical recommendations, focused on SME recovery, for emerging markets, in particular Ukraine. The article examines the main effects of pandemic on economy, focusing on business disruption, in particular SME. The financial flows as a response on anti-pandemic prevention measures were analyzed all over the world through digital tools, namely BI, as well as differentiation of support measures. The general fall in the main macroeconomic indicators was indicated for European countries and the deep analysis of financial support mechanisms provided by states was conducted. Taking into account research results, it was revealed that complex policy mechanisms were developed mainly by advanced economies while emerging markets, in particular Ukraine, do not have the effective mechanisms aimed at eliminating negative effects of pandemic. So, on the basis of conducted analysis the practical recommendations for emerging markets, in particular Ukraine, were developed using relevant European experience

Chatbots is a computer software powered by artificial intelligence designed to replicate human interaction. It is also possible to refer to them as digital assistants that comprehend the capacities of humans. The bot interprets the user's intent, then processes their queries and provides prompt responses. Chatbots perform their most crucial role: to analyse and detect the intent of the user's request to extract relevant entities. AI-powered chatbots were introduced to improve operational efficiency, eventually saving organisational costs. This study investigates the role of system and service quality in customer satisfaction in banking services. One hundred forty-five usable data were used for analysis. Data were analysed using the Smart PLS. The results revealed that response time, usability, adaptability, empathy and responsiveness were insignificant for customer satisfaction. The result is important as it gave the insight point of customers with regards to the new services. Business organisations may need to introduce chatbots and perhaps make some improvements from time to time to provide better services.

The main idea of IoT is to connect several objects to each other through Internet. In the field of Computer Network the main problem identified by researchers is network congestion. Now a day’s network congestion is increasing very rapidly because IoT connect a huge number of devices to internet. A transport layer protocol TCP (Transmission Control Protocol) is accountable for network congestion control. The behavior of TCP is not stable as it takes long time to fill the available capacity of the network. It also continuously keeps assessing the capacity of data transmission through increasing the limits.TCP drops its data transmission rate aggressively when packets are dropped, which significantly reduces the throughput. This paper suggests a new approach, stable transmission control protocol for IoT applications. The experimental results show that stable transmission control protocol achieves better performance in terms of goodput.

Recommender systems are important tools for users to identify their preferred items and for businesses to improve their products and services. In recent years, the use of online services for selection and reservation of hotels have witnessed a booming growth. Customer’ reviews have replaced the word of mouth marketing, but searching hotels based on user priorities is more time-consuming. This study is aimed at designing a recommender system based on the explicit and implicit preferences of the customers in order to increase prediction’s accuracy. In this study, we have combined sentiment analysis with the Collaborative Filtering (CF) based on deep learning for user groups in order to increase system accuracy. The proposed system uses Natural Language Processing (NLP) and supervised classification approach to analyze sentiments and extract implicit features. In order to design the recommender system, the Singular Value Decomposition (SVD) was used to improve scalability. The results show that our proposed method improves CF performance.