This work provides a reliable and classified stocks dataset merged with Saudi stock news. This dataset allows researchers to analyze and better understand the realities, impacts, and relationships between stock news and stock fluctuations. The data were collected from the Saudi stock market via the Corporate News (CN) and Historical Data Stocks (HDS) datasets. As their names suggest, CN contains news, and HDS provides information concerning how stock values change over time. Both datasets cover the period from 2011 to 2019, have 30,098 rows, and have 16 variables-four of which they share and 12 of which differ. Therefore, the combined dataset presented here includes 30,098 published news pieces and information about stock fluctuations across nine years. Stock news polarity has been interpreted in various ways by native Arabic speakers associated with the stock domain. Therefore, this polarity was categorized manually based on Arabic semantics. As the Saudi stock market massively contributes to the international economy, this dataset is essential for stock investors and analyzers. The dataset has been prepared for educational and scientific purposes, motivated by the scarcity of data describing the impact of Saudi stock news on stock activities. It will, therefore, be useful across many sectors, including stock market analytics, data mining, statistics, machine learning, and deep learning. The data evaluation is applied by testing the data distribution of the categories and the sentiment prediction-the data distribution over classes and sentiment prediction accuracy. The results show that the data distribution of the polarity over sectors is considered a balanced distribution. The NB model is developed to evaluate the data quality based on sentiment classification, proving the data reliability by achieving 68% accuracy. So, the data evaluation results ensure dataset reliability, readiness, and high quality for any usage.

The main purpose of the study is to determine the main features of the socio-economic development of the countries of the world under the influence of the digital economy and COVID-19. The modern world has already taken the first step towards a fundamentally new technological, economic and social reality. However, the challenges facing the modern industrial society cannot be overestimated. We are talking about changing the global socio-technological order, the consequence of which is a complete reformatting of the systems familiar to us, the formation of new social and economic strategies. the technological paradigm is immediately changing, management models and social norms are changing, large-scale demographic shifts are taking place. As a result of the study, key aspects of socio-economic development in the digital economy were identified.

Modern technology drives the world, increasing performance while reducing labor and time expenses. Tanzania Atomic Energy Commission (TAEC) tracks employee's levels of exposure to radiation sources using dosimeters. According to legal compliance, workers wear dosimeters for three months and one month at the workplace. However, TAEC has problems in tracking, issuing and returning dosimeters because the existing tracking is done manually. The study intended to develop a Personal Dose Management System (PDMS) that processes and manages the data collected by dosimeters for easy and accurate records. During the requirements elicitation process, the study looked at the existing system. PDMS' requirement gathering included document reviews, user interviews, and focused group discussions. Development and testing of the system were implemented by applying the evolutionary prototyping technique. The system provides a login interface for system administrators, radiation officers, and Occupational Exposed Workers. The PDMS grants TAEC Staff access to monitor individual exposed workers, prints individual and institutional reports and manages workers' information. The system reminds the users when to return dosimeters to TAEC, generate reports, and facilitates dispatching and receiving dosimeters effectively. PDMS increases efficiency and effectiveness while minimizing workload, paperwork, and inaccurate records. Therefore, based on the results obtained from the system, it is recommended to use the system to improve dosimeter data management at the institution.

The present study has been conducted to evaluate the experience in using peer-to-peer platforms and immersive technologies in the training of future masters of pharmacy from the Pharmaceutical Faculty of Bogomolets National Medical University, Ukraine. The selected participants were given the pre- and post-test containing multiple choice questions to assess the effectiveness of immersive technologies. Further, a self-designed structured questionnaire contained 10 questions with 5 options was delivered to consented participants through email and WhatsApp. The results of test presented that students attained an average of 26% in their pre-test while the average attained score post-test was 74% that showed a significant improvement with peer-to-peer platforms and virtual reality technology. The results of survey questions also showed an overall 86.73% satisfaction for the use of peer-to-peer platforms and virtual reality technology in the training of future masters of pharmacy. These results demonstrated that 90.81% showed agreement that they gained a high level of confidence through peer-to-peer platforms and virtual reality to handle patients in clinical practice. It can be concluded that participants of this study showed a strong agreement with positive experience in using peer-to-peer platforms and virtual reality technology in the training of future masters of pharmacy in medical lyceum.

The growth of digitalization processes around the world, covering almost all areas of human life, including the Fintech sector. In the field of financial technology, radical changes are taking place with increasing levels of automation, openness and consumer focus. In addition, in the context of the spread of coronavirus infection, quarantine and forced isolation, the role of digital technology is coming to the fore worldwide, including in Ukraine. The purpose of the article is to assess the development of Fintech ecosystem of European countries and outline the strategic parameters of domestic Fintech development. The study concluded that the investment raised for the Fintech industry increases annually and the quality and size of transactions gradually increases. Today, Fintech maintains its position as one of the most attractive markets for venture capitalists and the image of an industry with high potential, especially in the era of open banking. The most attractive markets for investors are mature markets, such as the United States, Germany and the United Kingdom, and the preferred niches for investment - the vertical of payments and lending. Trends in investment activity in terms of investing in financial technologies are studied. Moreover, investors prefer businesses that already have a significant scale or considerable potential to achieve it and become sustainable businesses.

The article is devoted to clarifying current trends in the digitalization of financial services. To this end, the evolution of this process in the financial sector was studied and six stages of its development were identified. The components of successful implementation of digitalization in the field of financial services and its tasks are outlined. It was found that fintech companies, which work to achieve effective interaction between the financial sector and innovative technologies in the use of mobile applications in order to most fully and quickly meet the needs of customers with financial services, are of great importance for the formation and development of digitalization in financial services. Current trends in the digitalization of financial services in Ukraine based on the use of fintech in general and banking institutions in particular are presented.

The article defines the principles of formation of digital marketing strategy of enterprises in the conditions of intensification of competition on the international market. The stages of development of digital marketing strategy of enterprises in the conditions of intensification of competition in the international market are substantiated, which includes: setting goals, which envisages observance of the principles of SMART-scheme; product or service analysis; monitoring of competitors; analytics of definition and segmentation of the target audience of the enterprise; selection of digital marketing tools and channels for promotion on the international market of products or services; formation of a unique, unique trade offer, selection of indicators for evaluating the effectiveness of digital marketing strategy and its tools. It is proved that according to the principle of SMART method of goal setting it is necessary that the goals have: specificity, measurability, achievability, relevance, achievement of the goal should be limited in time, have specific deadlines. To increase the effectiveness of digital marketing strategy, it is necessary to analyze the internal and external environment using the method of SWOT-analysis, the advantage of which is a comprehensive assessment of the company, competitors and the industry as a whole in the face of competition in the international market. The main indicators of evaluation of the effectiveness of digital marketing strategy in the conditions of intensification of competition on the international market are substantiated.

The attractiveness of e-sports games¹ and the way it is spread has changed in recent years. Instead of conventional approaches, such as advertising campaigns or televised events, spectators are increasingly drawn to online platforms, which offer more opportunities for communication. Besides live streaming services like Twitch. tv, where spectators can watch matches in real-time or via recorded videos, social media platforms like Facebook and Twitter are now adding e-sports related content to their networks [1]. Especially the combination of live streams on Twitch, Twitter, and Facebook opens many possibilities regarding how information is shared. This might be an efficient way of spreading attractiveness among female audiences. This paper focuses on the attractiveness of e-sports events in general for females. It has been hypothesized that there are certain factors that influence this attractiveness. Studying past research papers and online resources, three factors were identified: The players' behavior and charisma, the impact of social media as well as videogames themselves. It is found that females are attracted to e-sport games because they allow them to engage more in the game compared to other videogames. This is because there are no time constraints that require players to accomplish certain tasks within a specific time frame. As such, female gamers can choose how much effort they want to put into the game depending on their personal preferences.

Repressive measures in the Crimea against the Ukrainian media and the ban on the entry of international and Ukrainian monitoring missions created the conditions for the function of providing information to be performed by representatives of civil society. Such a phenomenon was called Crimean citizen journalism and became a post-occupation phenomenon characteristic of the Crimean information sphere. The journalists' activities are aimed at reporting on human rights violations and repression against Ukrainian citizens who find themselves in conditions of information bans and restrictions. Crimean citizen journalism, which connects the peninsula with the mainland of Ukraine, is monothematic in nature, and its emergence has become a form of nonviolent resistance to the occupation of Crimea. The purpose of the study is to cover the characteristic features, the development of common Crimean citizen journalistic movement features as a social phenomenon, a phenomenon that arose after the occupation through the identification of a modern journalist portrait. The study uses the general scientific method of empirical research as the main one, the sociological method of a questionnaire survey, as well as the methods of classification, generalisation, observation, statistical calculation. An analysis of a survey of Crimean citizen journalists demonstrates the existence of an active, mobile community in Crimea that seeks to provide information and human rights nonviolent resistance to the occupation.

With the rapid growth of Internet of Things (IoT) applications and devices, there are still defects in safety and privacy. Current researches indicate that there are weak security mechanisms to protect these devices. Humans use the Internet of Things to control and connect their devices with the Internet. Using the Internet of things has been increased over time. Therefore, capture of sensitive user data has increased intentionally or not [1]. The IP Camera is a type of (IOT) devices. Therefore, in this paper we aim to create a "Security Eyes" application that protects IP Cameras from security attacks according to certain security mechanisms (increasing the strength of encryption and filling the usual security holes in IP cameras … etc) and alerts the user when the live broadcast is interrupted or an error occurs.

There are several ways to improve software performance by using existing software. So, the developments of some programs are the most promising ways. However, traditional part programming studies usually assume that the components are recycled "as is". Existing models of component objects only provide limited support for partial adjustments, namely white box technologies ( copy-paste & inheritance) and the black-box methods (such as mixing and encapsulation). These technologies have problems related to recovery, efficiency, implementation of indirect costs, or their own problems. This paper suggests as JALTREE, The Black Box adaptation technology, which allows us for the implementation of previous components, but we need configurable the interface types, for measuring the adaptability. In this article we discussed the types of adjustments including component interfaces and component composition. An example of customizing JALTREE and component can be illustrated in several examples

To support early intervention, it is necessary to develop programming system tools that enable accurate, valid, and reliable assessments and can help achieve reasonable, generalizable, and measurable goals. This study examined the Assessment, Evaluation, and Programming System (AEPS) used by associations of children with disabilities in Saudi Arabia to assess its suitability for children with intellectual disabilities. A group of 16 specialists with different professional backgrounds (including special education, physiotherapy, occupational therapy, speech therapy and psychology) from 11 associations of children with disabilities took part in semi-structured personal interviews. The study concluded that AEPS is generally suited for use with children with intellectual disabilities. However, its suitability depends on the type and severity of the child's disability. The more severe the disability, the less effective the AEPS is likely to be. On the basis of this finding the researchers formed interdisciplinary teams to organise and integrate the children's learning and assess the benefits of AEPS, including its accuracy and ability to achieve adaptive, cognitive, and social targets, enhance family engagement and learning and develop basic development skills. This study also identified obstacles associated with the use of AEPS. These include the lack of comprehensiveness and accuracy of the goal, lack of precision and non-applicability to large movements and the fact that it cannot be used with all children with intellectual disabilities. In addition, the research showed that non-cooperation within the family is a major obstacle to the implementation of the AEPS. The results of this study have several implications.

The main purpose of the study is to determine the key aspects of Agile management as the basis of a management system in the context of globalization. The research methodology includes several scientific and theoretical methods that have achieved this goal. Adaptation of enterprises engaged in the development, production, and sale of innovative products to constant and rapid changes in the external environment requires managers to apply appropriate management methods. The use of Agile management in the management of innovation processes can speed up their implementation, minimize and optimize the use of resources, time, and effort of staff, can increase customer and customer satisfaction with the end result and, consequently, improve the company's competitive position in the market. The results of the study identified key aspects of the application of Agile management in the management system in the context of globalization.

The main purpose of this study is to substantiate the theoretical and methodological foundations of the organizational and economic mechanism of development of the agro-industrial complex in modern conditions. Organizational and economic mechanism is presented as a complex organizational structure of the system type, which is aimed at performing specific functions, the characteristic feature of which is the constant support of process changes without which the organizational and economic mechanism can not exist. There are four components of the agro-industrial complex, represented by agriculture and the national economy, which ensure its operation, including industry, processing of agricultural products, its storage and transportation, sale and repair and maintenance of agricultural machinery and more. It is proved that the organizational and economic mechanism of development of agro-industrial complex in modern conditions it is expedient to consider: from the point of view of system and process approaches; as a set of economic levers and organizational measures to influence the agro-industrial complex; constituent components of organizational influence on the development of the complex; a set of components, elements that are integrated into the system of economic relations of the subjects of the agro-industrial complex; a set of purposeful stimulators of agro-industrial complex development. The functions of the organizational component of the mechanism of agro-industrial complex include: redistributive, planning, interaction, control, integration and regulatory functions, the functions of the economic component include consumer, investment and innovation, social, incentive, monitoring functions of the mechanism. The symbiosis of the functions of organizational and economic components ensure the effectiveness of the organizational and economic mechanism of the organizational and economic mechanism through its functionalities as a whole.

Component adaptation is widely recognized as one of the main problems of the components, used in component based software engineering (CBSE). We developed methods to adjust the components classified by the keywords. Three main methods are discussed in this article those methods are combined with several domain component interfaces, high level simple notation for the adapter design patterns. The automated process for classifying high-level components are using adaptation is novel to software engineering domain. All Specifications and many technologies for re-using software, CBD and further developments have been emerged in recent years. The effects of these technologies on program quality or software costs must be analyzed. The risk concerns a single technology and must identify its combinations. In this paper, we are going to discuss the methods to adapt components of different technologies

During the past decades, detection of gear defects remains as a major problem, especially when the gears are subject to non-stationary phenomena. The idea of this paper is to mixture a multilevel wavelet transform with a fast EMD decomposition in order to early detect gear defects. The sensitivity of a kurtosis is used as an indicator of gears defect burn. When the gear is damaged, the appearance of a crack on the gear tooth disrupts the signal. This is due to the presence of periodic pulses. Nevertheless, the existence of background noise induced by the random excitation can have an impact on the values of these temporal indicators. The denoising of these signals by multilevel wavelet transform improves the sensitivity of these indicators and increases the reliability of the investigation. Finally, a defect diagnosis result can be obtained after the fast transformation of the EMD. The proposed approach consists in applying a multi-resolution wavelet analysis with variable decomposition levels related to the severity of gear faults, then a fast EMD is used to early detect faults. The proposed mixed methods are evaluated on vibratory signals from the test bench, CETIM. The obtained results have shown the occurrence of a teeth defect on gear on the 5th and 8th day. This result agrees with the report of the appraisal made on this gear system.

Soft sensors are used to anticipate complicated model parameters using data from classifiers that are comparatively easy to gather. The goal of this study is to use artificial intelligence techniques to design and build soft sensors. The combination of a Long Short-Term Memory (LSTM) network and Grey Wolf Optimization (GWO) is used to create a unique soft sensor. LSTM is developed to tackle linear model with strong nonlinearity and unpredictability of manufacturing applications in the learning approach. GWO is used to accomplish input optimization technique for LSTM in order to reduce the model's inappropriate complication. The newly designed soft sensor originally brought LSTM's superior dynamic modeling with GWO's exact variable selection. The performance of our proposal is demonstrated using simulations on real-world datasets.

The smart cities are evolving constantly and are responsible for the current transformation of cities and countries into a completely connected network of information and technology This interconnected network of a huge number of smart devices is capable of exchanging complex information and provides tremendous support including enhanced quality of life within urban locations. Unfortunately this set-up is vulnerable to security attacks and requires the widespread ubiquitous network to authorize access through privacy and thus offer security in order to ensure civilian participation in a country. The smart network should benefit the individuals of the country by developing potential strategies to protect the smart cities and their participating entities from the unauthorized attacks. Trustworthy data sharing strategies based on the utilization of advanced technology features via smart communication network could solve some issues of privacy and security. This paper presents the challenges and issues related to protection and highlights the important aspects of securing the smart cities and its components. It also presents the role of cloud security for building a secure smart city.

One of the impacts of Covid-19 on education systems has been the shift to online education. This shift has changed the way education is consumed and perceived by students. However, the exact nature of student perception about online education is not known. The aim of this study was to understand the perceptions of Saudi higher education students (e.g., post-school students) about online education during the Covid-19 pandemic. Various aspects of online education including benefits, features and cybersecurity were explored. The data collected were analysed using statistical techniques, especially artificial neural networks, to address the research aims. The key findings were that benefits of online education was perceived by students with positive experience or when ensured of safe use of online platforms without the fear cyber security breaches for which recruitment of a cyber security officer was an important predictor. The issue of whether perception of online education as a necessity only for Covid situation or a lasting option beyond the pandemic is a topic for future research.

The Internet of Things (IoT) has gotten a lot of research attention in recent years. IoT is seen as the internet's future. IoT will play a critical role in the future, transforming our lifestyles, standards, and business methods. In the following years, the use of IoT in various applications is likely to rise. In the world of information technology, cyber security is critical. In today's world, protecting data has become one of the most difficult tasks. Different type of emerging cyber threats such as malicious, network based and abuse of network have been identified in the IoT. These can be done by virus, Phishing, Spam and insider abuse. This paper focuses on emerging threats, various challenges and vulnerabilities which are faced by the cyber security in the field of IoT and its applications. It focuses on the methods, ethics, and trends that are reshaping the cyber security landscape. This paper also focuses on an attempt to classify various types of threats, by analyzing and characterizing the intruders and attacks facing towards the IoT devices and its services.

Artificial Intelligence has stimulated every aspect of today's life. Human thinking quality is trying to be involved through digital tools in all research areas of the modern era. The education industry is also leveraging artificial intelligence magical power. Uses of digital technologies in pedagogical paradigms are being observed from the last century. The widespread involvement of artificial intelligence starts reshaping the educational landscape. Adaptive learning is an emerging pedagogical technique that uses computer-based algorithms, tools, and technologies for the learning process. These intelligent practices help at each learning curve stage, from content development to student's exam evaluation. The quality of information technology students and professionals training has also improved drastically with the involvement of artificial intelligence systems. In this paper, we will investigate adopted digital methods in the education sector so far. We will focus on intelligent techniques adopted for information technology students and professionals. Our literature review works on our proposed framework that entails four categories. These categories are communication between teacher and student, improved content design for computing course, evaluation of student's performance and intelligent agent. Our research will present the role of artificial intelligence in reshaping the educational process.

Vehicular Ad hoc Networks are considered as special kind of Mobile Ad Hoc Networks. VANETs are a new emerging recently developed, advanced technology that allows a wide set of applications related to providing more safety on roads, more convenience for passengers, self-driven vehicles, and intelligent transportation systems (ITS). Delay Tolerant Networks (DTN) are networks that allow communication in the event of connection problems, such as delays, intermittent connections, high error rates, and so on. Moreover, these are used in areas that may not have end-to-end connectivity. The expansion from DTN to VANET resulted in Vehicle Delay Tolerant Networks (VDTN). In this approach, a vehicle stores and carries a message in its buffer, and when the opportunity arises, it forwards the message to another node. Carry-store-forward mechanisms, packets in VDTNs can be delivered to the destination without clear connection between the transmitter and the receiver. The primary goals of routing protocols in VDTNs is to maximize the probability of delivery ratio to the destination node, while minimizing the total end-to-end delay. DTNs are used in a variety of operating environments, including those that are subject to failures and interruptions, and those with high delay, such as vehicle ad hoc networks (VANETs). This paper discusses DTN routing protocols belonging to unicast delay tolerant position based. The comparison was implemented using the NS2 simulator. Simulation of the three DTN routing protocols GeOpps, GeoSpray, and MaxProp is recorded, and the results are presented.

Voice over Internet Protocol (VoIP) has grown in popularity as a low-cost, flexible alternative to the classic public switched telephone network (PSTN) that offers advanced digital features. However, additional security vulnerabilities are introduced by the VoIP system's flexibility and the convergence of voice and data networks. These additional challenges add to the normal security challenges that a VoIP system's underlying IP data network infrastructure confront. As a result, the VoIP network adds to the complexity of the security assurance task faced by businesses that use this technology. It's time to start documenting the many security risks that a VoIP infrastructure can face, as well as analyzing the difficulties and solutions that could help guide future efforts in research & development. We discuss and investigate the challenges and requirements of VoIP security in this research. Following a thorough examination of security challenges, we concentrate on VoIP system threats, which are critical for present and future VoIP deployments. Then, towards the end of this paper, some future study directions are suggested. This article intends to guide future scholars and provide them with useful guidance.

Forecasting and time series modelling plays a vital role in the data analysis process. Time Series is widely used in analytics & data science. Forecasting stock prices is a popular and important topic in financial and academic studies. A stock market is an unregulated place for forecasting due to the absence of essential rules for estimating or predicting a stock price in the stock market. Therefore, predicting stock prices is a time-series problem and challenging. Machine learning has many methods and applications instrumental in implementing stock price forecasting, such as technical analysis, fundamental analysis, time series analysis, statistical analysis. This paper will discuss implementing the stock price, forecasting, and research using prophet and LSTM models. This process and task are very complex and involve uncertainty. Although the stock price never is predicted due to its ambiguous field, this paper aims to apply the concept of forecasting and data analysis to predict stocks.

Face Detection is one of the most important aspects of image processing, it considers a time-consuming problem in real-time applications such as surveillance systems, face recognition systems, attendance system and many. At present, commodity hardware is getting more and more heterogeneity in terms of architectures such as GPU and MIC co-processors. Utilizing those co-processors along with the existing traditional CPUs gives the algorithm a better chance to make use of both architectures to achieve faster implementations. This paper presents a hybrid implementation of the face detection based on the local binary pattern (LBP) algorithm that is deployed on both traditional CPU and MIC co-processor to enhance the speed of the LBP algorithm. The experimental results show that the proposed implementation achieved improvement in speed by 3X when compared to a single architecture individually.

The world health organization classified the emerging coronavirus (known as Covid-19) as a pandemic after confirming the extent of spread and scale. As a matter of fact, outbreaks of similar scale or even worse have been witnessed throughout history. Thus, the development of prevention strategies exists to protect against such calamaties. One of the widely proven measures that controls the spread of any contagious diseases is social distancing. As a result, this paper will demonstrate the concept of an application "Be Aware" on enabling the implementation of this preventive measure. In particular "Be aware" evaluates the extent of congestion in public places using current time data. The proposed project will use Global Positioning System (GPS), and Application Programming Interface (API), to ensure information accuracy, and the API use Crowdsourcing to collect Real-Time Data (RTD) from the selected places. One line

Key exchange protocol (KEP) is an essential setup to secure authenticates transmission among two or more users in cyberspace. Digital files protected and transmitted by the encryption of the files over public channels, a single key communal concerning the channel parties and utilized for both to encrypt the files as well as decrypt the files. If entirely done, this impedes unauthorized third parties from imposing a key optimal on the authorized parties. In this article, we have suggested a new KEP term as isokey interchange protocol based on generalization of modern mathematics term as isomathematics by utilizing isonumbers for corresponding isounits over the Block Upper Triangular Isomatrices (BUTI) which is secure, feasible and extensible. We also were utilizing arithmetic operations like Isoaddition, isosubtraction, isomultiplication and isodivision from isomathematics to build iso-key interchange protocol for network communication. The execution of our protocol is for two isointegers corresponding two elements of the group of isomatrices and cryptographic performance of products eachother. We demonstrate the protection of suggested isokey interchange protocol against Brute force attacks, Menezes et al. algorithm and Climent et al. algorithm.

Convolutional Neural networks (CNNs) are a category of deep learning networks that have proven very effective in computer vision tasks such as image classification. Notwithstanding, not much has been seen in its use for remote sensing image classification in developing countries. This is majorly due to the scarcity of training data. Recently, transfer learning technique has successfully been used to develop state-of-the art models for remote sensing (RS) image classification tasks using training and testing data from well-known RS data repositories. However, the ability of such model to classify RS test data from a different dataset has not been sufficiently investigated. In this paper, we propose a deep CNN model that can classify RS test data from a dataset different from the training dataset. To achieve our objective, we first, re-trained a ResNet-50 model using EuroSAT, a large-scale RS dataset to develop a base model then we integrated Augmentation and Ensemble learning to improve its generalization ability. We further experimented on the ability of this model to classify a novel dataset (Nig_Images). The final classification results shows that our model achieves a 96% and 80% accuracy on EuroSAT and Nig_Images test data respectively. Adequate knowledge and usage of this framework is expected to encourage research and the usage of deep CNNs for land cover mapping in cases of lack of training data as obtainable in developing countries.

The application of computer software into the linguistic analysis of texts proves useful to arrive at concise and authentic results from large data texts. Based on this assumption, this paper employs a Computer-Aided Text Analysis (CATA) and a Critical Discourse Analysis (CDA) to explore the manipulative strategies of positive/negative presentation in Orwell's Animal Farm. More specifically, the paper attempts to explore the extent to which CATA software represented by the three variables of Frequency Distribution Analysis (FDA), Content Analysis (CA), and Key Word in Context (KWIC) incorporate with CDA decipher the manipulative purposes beyond positive presentation of selfness and negative presentation of otherness in the selected corpus. The analysis covers some CDA strategies, including justification, false statistics, and competency, for positive self-presentation; and accusation, criticism, and the use of ambiguous words for negative other-presentation. With the application of CATA, some words will be analyzed by showing their frequency distribution analysis as well as their contextual environment in the selected text to expose the extent to which they are employed as strategies of positive/negative presentation in the text under investigation. Findings show that CATA software contributes significantly to the linguistic analysis of large data texts. The paper recommends the use and application of the different CATA software in the stylistic and corpus linguistics studies.

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

The current research attempts to measure the level of the acceptance of the Blackboard System (BBS) during the Corona crisis, and whether this is one of the reasons for the low use of the BBS at Al-Jouf University. To achieve this, the technology accepting model in the time of crisis (TAMTC) has been proposed to measure the degree of acceptance by students, which was then applied to a random sample of 339 of such. The results show a high level of student acceptance, despite their lower use of the system. The research also highlights the importance of upgrading e-courses and that the discontinuation of exam disqualification of students is secondary to their poor course attendance.

Mobile Banking Applications (MBAPs) is one of the recent fads in mobile trading applications (Apps). MBAPs permit users to execute exchanges of money and many more whenever it might suit them; however, the primary issue for mobile banking Apps is usability. Hardly any investigation analyzes usability issues dependent on user's age, gender, exchanging accomplices, or experience. The purpose of this study is to determine the degree of usability issues, and experience of mobile banking users. The survey employs a quantitative method and performs user experiment on 240 participants with six different tasks on the application's interface. The post experiment survey is done with concerning participants. On the other hand, banking experts and Information Technology (IT) expert's group is also involved after the experiment. Expert's opinions about existing mobile banking Apps and suggestions for improving usability of MBAPs are collected through physical means (like questionnaire and interview) and online means like Google form. After that comparison of the opinions of users and experts about MBAPs is performed. The experimentation measures the tasks usability of various mobile banking apps with respect to its effectiveness, efficiency, trustfulness, learnability, memorability and satisfaction. The usability testing was led at different Universities and the outcomes acquired show that there are privacy and trust issues with their mobile banking apps. There is also a gap between users and experts which should be minimized by applying customized usability models, modes concept like other application software and also by adding complete features of banking in MBAPs. It will benefit mobile banking apps users, developers and usability engineers by providing user-friendly which are up to the mark of user's requirements.

The study aimed to identify the impact of the application of technical equipment for infrastructure to achieve the quality of e-learning for students in the faculties at Northern Border University, in Arar city. The study applied the analytical survey study method. To achieve the study purpose, the researcher prepared a study tool which is a questionnaire to measure the impact o of applying technical instrument for the infrastructure to achieve the quality of e-learning for students. The study sample size reached (218) students from both groups from the university faculties in Arar city. The results of the study revealed a tendency in the study sample's responses to the availability of the majority of the questionnaire criteria significantly. This indicates the positive impact of the application of technical equipment on the infrastructure to achieve the application quality of e-learning at Northern Border University, the study recommended the following: The need to pay attention to measuring the quality of electronic courses every two years in addition to the need to adjust the quality standards of e-content provided through e-learning platforms. Also, there is the gradual application of e-learning at the university in addition to spreading the culture of e-learning quality among all groups of the university community. Also, it is necessary to direct them towards benefiting from the advantages of e-learning that observes quality standards.

Between 2014 and 2019, the US lost more than 2.1 billion USD to phishing attacks, according to the FBI's Internet Crime Complaint Center, and COVID-19 scam complaints totaled more than 1,200. Phishing attacks reflect these awful effects. Phishing websites (PWs) detection appear in the literature. Previous methods included maintaining a centralized blacklist that is manually updated, but newly created pseudonyms cannot be detected. Several recent studies utilized supervised machine learning (SML) algorithms and schemes to manipulate the PWs detection problem. URL extraction-based algorithms and schemes. These studies demonstrate that some classification algorithms are more effective on different data sets. However, for the phishing site detection problem, no widely known classifier has been developed. This study is aimed at identifying the features and schemes of SML that work best in the face of PWs across all publicly available phishing data sets. The Scikit Learn library has eight widely used classification algorithms configured for assessment on the public phishing datasets. Eight was tested. Later, classification algorithms were used to measure accuracy on three different datasets for statistically significant differences, along with the Welch t-test. Assemblies and neural networks outclass classical algorithms in this study. On three publicly accessible phishing datasets, eight traditional SML algorithms were evaluated, and the results were calculated in terms of classification accuracy and classifier ranking as shown in tables 4 and 8. Eventually, on severely unbalanced datasets, classifiers that obtained higher than 99.0 percent classification accuracy. Finally, the results show that this could also be adapted and outperforms conventional techniques with good precision.

The main purpose of the study is to determine the main aspects of the introduction of modern technologies in the personnel management system in the context of the development of the digital economy. The human factor is one of the most important resources of any organization, which has a significant impact on the success of its activities. It is people who are the source of advantages that provide the company with victory in the competition. Therefore, the primary task of the organization's management should be the formation of effective personnel management systems. As a result, the main features of the introduction of modern technologies into the personnel management system in the context of the development of the digital economy were identified.

Big Data is a data analysis technology empowered by late advances in innovations and engineering. In any case, big data involves a colossal responsibility of equipment and handling assets, making reception expenses of big data innovation restrictive to little and medium estimated organizations. Cloud computing offers the guarantee of big data execution to little and medium measured organizations. Big Data preparing is performed through a programming worldview known as MapReduce. Normally, execution of the MapReduce worldview requires organized joined stockpiling and equal preparing. The computing needs of MapReduce writing computer programs are frequently past what little and medium measured business can submit. Cloud computing is on-request network admittance to computing assets, given by an external element. Normal arrangement models for cloud computing incorporate platform as a service (PaaS), software as a service (SaaS), framework as a service (IaaS), and equipment as a service (HaaS).

The main purpose of the study is to determine the main aspects of the problem of socio-economic development in the conditions of the digital economy. The post-industrial era is characterized by the development of the electronic environment and the transition to an information civilization. In this regard, the developed countries of the world pay considerable attention to the development of the digital economy. However, there are a significant number of problems associated with this process. The country cannot be successful in the development of the digital economy in the absence of the necessary legal framework, an economic development strategy based on digital technologies. The research methodology involves the use of several theoretical methods for analyzing and synthesizing information. As a result of the study, the key problems of socio-economic development in the digital economy were characterized.

This research examines the views of teachers and parents of special schools in Saudi Arabia, exploring the schools' strengths and disadvantages, as well as their impact on teachers, parents, and students with disabilities. The respondents' key views of the schools are identified, including the areas of consensus and conflict, and recommendations are made for the future, based on the findings. This research concerns a specific special education school in Saudi Arabia, and focuses on the understanding of special education in the country. The approach to the study is targeted and qualitative, with the six participants, three teachers and three parents, intentionally selected. The data collection is conducted via semi-structured interviews that explore the participants' views of special education in Saudi Arabia. A number of issues emerge from the results, and one raised by all three teachers is the need to improve school facilities. Although all three parents report that their children clearly benefited from attending a special school, two felt that the offering was insufficient, in terms of the teaching methods, and of supporting cognitive skills.

The research is devoted to the substantiation of the system approach to the involvement of digital marketing tools as a guarantee of international business development. It is proved that digital marketing, as a type of marketing based on the use of digital technologies allows to make a profit, to promote the brand, as well as goods and services in the market. The digital marketing toolkit system is a set of elements with existing relationships that ensure the effectiveness of the entire digital marketing, which in total is greater than its individual components. The implementation of a systems approach involves the implementation of the philosophy of digital marketing in general, its functions in the form of systems analysis, formation of strategic development goals and entry and promotion in the international market, preparation and implementation of tactical and strategic development plans.The use of such digital marketing tools as: content marketing, social media marketing, Email-marketing, targeted advertising, contextual advertising, media advertising, Search Engine Optimization, affiliate programs and the company's website is analyzed in detail.

Marketing stress testing is a new method of identifying the company's strengths and weaknesses in a turbulent environment. Technically, this is a complex procedure, so it involves artificial intelligence and machine learning. The main problem is currently the development of methodological approaches to the development of the company's digital model, which will provide a framework for machine learning. The aim of the study was to identify and develop an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. This aim provided the company's activities to be considered as a set of elements (business processes, products) and factors that affect them (marketing environment). The article proposes an author's approach to the parameterization of the company's business processes for machine learning-based marketing stress testing. The proposed approach includes four main elements that are subject to parameterization: elements of the company's internal environment, factors of the marketing environment, the company' core competency and factors impacting the company. Matrices for evaluating the results of the work of expert groups to determine the degree of influence of the marketing environment factors were developed. It is proposed to distinguish between mega-level, macro-level, meso-level and micro-level factors depending on the degree of impact on the company. The methodological limitation of the study is that it involves the modelling method as the only one possible at this stage of the study. The implementation limitation is that the proposed approach can only be used if the company plans to use machine learning for marketing stress testing.

Internet Protocol Television (IPTV) has emerged as a personal entertainment source for home users. Streaming IPTV content over a wireless medium with good Quality of Service (QoS) can be a challenging task as IPTV content requires more bandwidth and Wireless Local Area Networks (WLANs) are susceptible to packet loss, delay and jitter. This research presents the capacity of IPTV using User Datagram Protocol (UDP) and TCP Friendly Rate Control (TFRC) over IEEE 802.11ac WLANs in good and bad network conditions. Experimental results show that in good network conditions, UDP and TFRC could accommodate a maximum of 78 and 75 Standard Definition Television (SDTV) users, respectively. In contrast, 15 and 11 High-Definition Television (HDTV) users were supported by UDP and TFRC, respectively. Performance of UDP and TFRC was identical in bad network conditions and same number of SDTV and HDTV users were supported by TFRC and UDP. With background Transmission Control Protocol (TCP) traffic, both UDP and TFRC can support nearly the same number of SDTV users. It was found that TFRC can co-exist fairly with TCP by giving more throughput to TCP unlike UDP.

The main purpose of the study is to determine the main aspects of the introduction of modern technologies in the public administration system in the context of globalization. Public administration is inherent in all known models of representation of social systems, characteristic management and other sciences of social management. This allows using the methods and technologies of management, marketing, social partnership and others in public administration and administration at a modern level. One of the main directions of public management and administration is social engineering, aimed at the development and development of the country's social system, and the tool is appropriate technologies. Based on the results of the analysis, the key modern technologies of the public administration system were identified in the context of the impact of globalization.

This research is designed to help and offer hold up to complete the requirements of aged and disable in a home. The control approach and the tone approach are used to manage the house appliances. The major organize system implementation in technology of wireless to offer distant contact from a phone Internet Protocol connectivity for access and calculating strategy and appliance remotely. The planned system no need a committed server PC with value of parallel systems and offers a new communication-protocol to observe and control a house environment with more than just the switch functionality. To express the possibility and efficiency of this system, devices like as lights switches, power plugs, and motion-sensors have been included with the planned home control system and supply more security manage on the control with low electrical energy activate method. The rank of switches is corresponding in all this control system whereby all user interfaces indicate the real time existing status. This system planned to manage electrical-appliances and devices in house with reasonably low cost of design, user friendly interface, easily install and provide high security. Research community generally specified that the network "Reconnaissance Attacks" in IPv6 are usually impossible due to they will take huge challenge to carry out address scanning of 264 hosts in an IPv6 subnet."It being deployed of IPv6 shows that it definitely enhances security and undermines the probability". This research of the IPv6 addressing-strategies at present utilizes and planned a new strategy and move toward to "mitigate reconnaissance attacks".

The article is devoted to substantiation of theoretical and methodical bases of formation of the organizational-economic mechanism of maintenance of stability of development of region on the bases of influence of potential-forming space in the conditions of formation of creative economy. It was found that the organizational-economic mechanism due to its multifaceted nature does not have a single generally accepted definition, and its acceptable scale and complexity is reflected in the structure, which is very dependent on the scope and conditions of its application, can be very different and contain different elements. In view of this, in order to highlight the characteristics that are inherent in the organizational-economic mechanism of sustainable development of the region on the basis of potential-forming space in the formation of creative economy, the article examines the properties and characteristics of direct organizational and economic mechanism. The necessity of basing the process of formation of any organizational-economic mechanism, including the organizational-economic mechanism of ensuring the sustainability of the region on the basis of the potential-forming space in the conditions of creative economy on the system of principles. In this context, the author's vision is proposed and a set of principles for the formation of organizational-economic mechanism for sustainable development of the region on the basis of the potential of the potential-forming space in the creative economy, as well as revealed the essence of each. According to the structural aspect, the organizational-economic mechanism of ensuring the sustainability of the region's development on the basis of the potential-forming space is proposed to be presented as a set of seven stages, which are implemented in a certain sequence. Within the limits of this research the sequence of realization of the stages making process of formation of the organizational-economic mechanism of maintenance of stability of development of region on the basis of influence of potential-forming space in the conditions of formation of creative economy is defined and their maintenance and essence is presented.

Employing the available technologies and utilizing the advanced means to improve the level of health care provided to citizens in their various locations. Citizens have the right to get a proper health care services despite the location of their residency or the distance from the health care delivery centers, a goal that can be achieved by utilizing air ambulance systems. In such systems, aircrafts and their life spans are the essential component, the flight duration of the aircraft during its life span is determined by the maintenance schedule. This research, enhances the air ambulance systems by presenting a proposal that maximizes the aircraft flight duration during its life span. The enhancement will be reached by developing a set of algorithms that handles the aircraft maintenance problem. The objective of these algorithms is to minimize the maximum completion time of all maintenance tasks, thus increasing the aircraft operation time. Practical experiments performed to these algorithms showed the ability of these algorithms to achieve the desired goal. The developed algorithms will manage the maintenance scheduling problem to maximize the uptime of the air ambulance which can be achieved by maximizing the minimum life of spare parts. The developed algorithms showed good performance measures during experimental tests. The 3LSL algorithm showed a higher performance compared to other algorithms during all performed experiments.

The main purpose of the article is to study the key aspects of the use of modern technologies to ensure economic security in the context of achieving high efficiency of public administration.The economic security of the country is a multi-level system, the structure of which is determined by the peculiarities of the structure and key development priorities both in the regional aspect and nationally. The fundamental role of economic security is realized through a set of goals and objectives that are achieved in the process of ensuring it, among the main ones is the effective, dynamic and progressive development of the economy, which is impossible without the development of innovations. The essence of ensuring economic security from the standpoint of innovative development lies in the development of innovations that can increase the level of competitiveness of the state-level economic system, which necessitated an analysis of the conditions and dynamics of innovation development. As a result of the study, the basic aspects of the implementation of modern technologies were analyzed in the context of achieving high efficiency in public administration.

The article is timed to coincide with the thirtieth anniversary of Ukraine's independence. Based on the generalization of fundamental and applied studies of scientists, the author's vision of such category as the gender parity is conceptualized. Based on the analysis of historical events related to the development of the state, the formation of cultural and social values in determining the gender identity of modern society is substantiated. Based on the analysis of literary and regulatory sources, the structure of the state administration of Ukraine is visualized, which has become the basis for the diagnosis of gender aspects. Based on the analysis, the problems of gender parity in the public administration system of Ukraine are identified.

The article considers the features of the organizational-economic mechanism of attracting investment resources in the innovative development of regions in terms of sustainable development. Factors influencing the investment activity of regions in terms of sustainable development, including: institutional structure, intellectual capital, level of innovation infrastructure, business development, financial and credit component, level of human resources development, information environment, production development, environmental component. Factors influencing the attraction of investment resources in the regions are identified. The dynamics of changes in the volume of capital investments and foreign direct investment in Ukraine is analyzed. The regional features of the distribution of capital investments in the conditions of sustainable development are revealed. The essence of the main principles on the basis of which the organizational - economic mechanism of attraction of investment resources in innovative development of regions in the conditions of sustainable development should be formed is analyzed. A set of measures to regulate the investment processes of the regions has been identified. The mechanism of attraction of investment resources in innovative development of regions in the conditions of sustainable development is outlined. The results of activity of separate Agencies of regional development for 2020 in the direction of investment and innovation activity and increase of level of investment attractiveness of regions are analyzed. Important prerequisites for the effective implementation of the organizational-economic mechanism for attracting investment resources in the innovative development of regions in terms of sustainable development are identified. The main directions of directing the efforts of the organizational-economic mechanism to ensure the attraction of investment resources in the innovative development of regions in the context of increasing the level of investment activity in the regional aspect are substantiated.

In the study of the mechanism of labor motivation as a determinant of economic security of the enterprise in competitive conditions, it was found that motivation is determinant in creating the conditions for production and ensuring the active functioning of the enterprise. It is substantiated that the motivational mechanism is the presence of a system of levers, incentives, measures and other elements for economic and administrative incentives for employees, which are used for incentives to work, increase productivity and safety, and more. The motivational mechanism plays an important role in ensuring the economic security of the enterprise and at the same time is a lever to increase competitiveness in the market. The functions of the mechanism of labor motivation are singled out, among which: explanatory-substantiating, regulative, communicative, socialization, regulating. The stages of occurrence of the motive for the employee are classified. The interrelation of motives and incentives in the mechanism of labor motivation as determinants of economic security of the enterprise in competitive conditions is proved. It is proved that the mechanism of labor motivation as a determinant of economic security of the enterprise in competitive conditions should be aimed at: assistance in forming and achieving goals and objectives of the enterprise and achieving balance and equilibrium of economic goals and social responsibility of the enterprise; ensuring close cooperation between management and employees of the enterprise; focus on building a flexible mechanism; transition to a democratic style of governance and involvement of employees in decision-making.

The article determines that the study of the development of scientific and didactic knowledge about the educational process in higher education should be built mainly on the basis of qualitative research methods that ensure the identification and understanding of the changes taking place in didactic knowledge, in the unity of their internal and external manifestations. On the basis of the epistemological model of the study of science, a generalized model of didactic knowledge about the educational process in higher education, including didactic relations as a theoretical core, subject of research, research methods and positions of researchers, ways of interaction between science and educational practice, and thematic structures of didactic knowledge; scientific and methodological problems of didactic knowledge about the educational process in higher education at the present stage of its developments due to the post-nonclassical transformation and orientation of research towards the humanitarian ideal of scientific character.

This article is devoted to the consideration of the image strategies of higher education on the example of a comparison of Ukrainian and foreign experience. The relevance of the chosen topic is as follows. Today, educational institutions need to position, shape and elevate their image. PR helps to solve all these tasks, performing a function that is so necessary for establishing mutual understanding as communication management. The following tasks are solved in the article: originality of definitions was investigated; revealed PR and related concepts; analyzed the role of PR in the information promotion of universities; determined the specifics of information promotion, due to temporary conditions and regional development; considered image materials of Ukrainian and foreign universities; disclosed the specifics of the information promotion of the objects under study; analyzed.

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

The NHIS provides free or highly subsidized healthcare to all people by providing financial fortification. However, the financial sustainability of the scheme is threatened by numerous factors. Therefore, this work sought to provide a solution to process claims intelligently. The provided Petri net model demonstrated successful data flow among the various participant. For efficiency, scalability, and performance two main subsystems were modelled and integrated - data input and claims processing subsystems. We provided smart claims processing algorithm that has a simple and efficient error detection method. The complexity of the main algorithm is good but that of the error detection is excellent when compared to literature. Performance indicates that the model output is reachable from input and the token delivery rate is promising.

When the owners of the intellectual property rights of digital content have lost control over it in the digital environment, there emerged fears that the intellectual property laws, especially copyright law, would not be effective as in the material (Offline ) world. The reason is that the digital environment helps to reproduce copies in high quality and at almost no cost, while copyright law protection has been limited to programs embedded in CDs. According to copyright laws, the owner of the program did not have the right to prevent buyers of the initial physical copy of the program from copying and reselling it to more than one individual without the permission of the original owner. As a result, business owners have invented the idea of licensing digital content and programs instead of selling them. They set out terms that serve their commercial interests regardless of their abuse to intellectual property laws or even the rules of the traditional contract to sell a material property. The abuse has resulted from the way those terms are concluded and the heavy rules that are unfair to consumer rights. Therefore, business owners insisted on dealing with the website and its programs and digital content as material property. Here raises the question of whether the website and its digital content are subject to the protection of copyright law or the rules of the traditional contract or licensing contracts. As the answer to this question affects the protection of consumer rights, is it possible to find a balance between it and the protection of the owners of digital programs' rights.That is what we will discuss in this paper.