The growth in global population and industrialization has led to an increasing demand for electricity. Accordingly, the electricity providers need to increase the electricity generation. Due to the economical and environmental concerns associated with the generation of electricity from fossil fuels. Alternative power recourses that can potentially mitigate the economical and environmental are of interest. Renewable energy resources are promising recourses that can participate in producing power. Among renewable power resources, solar energy is an abundant resource and is currently a field of research interest. Photovoltaic solar power is a promising renewable energy resource. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. this paper investigates the utilization of machine learning unsupervised neural network techniques that potentially improves the reliability of PV solar power systems during integration into the electrical grid.

Photovoltaic systems provide a reliable green energy solution. The sustainability and low-maintenance of Photovoltaic systems motivate the integration of Photovoltaic systems into the electrical grid and further contribute to a greener environment, as the system does not cause any pollution or emissions. Developing methodologies based on machine learning techniques to assist in reducing the burden of studies related to integrating Photovoltaic systems into the electric grid are of interest. This research aims to develop a methodology based on a unsupervised machine learning algorithm that can reduce the burden of extensive studies and simulations related to the integration of Photovoltaic systems into the electrical grid.

The main purpose of the study is to determine the main elements of the state management of the development of national cybersecurity. Cybersecurity ensures the protection of the properties of information resources and the operability of technical and software users and is directed against relevant cyber incidents. Therefore, today it is impossible to ignore the importance of public administration of the processes taking place in it. The methodological support of our study is determined by its goals and objectives and is based on the use of a combination of general scientific and special methods of scientific knowledge, which ensured the completeness and reliability of the results obtained. The article has limitations and concerns the lack of practical implementation of the research results. The study is purely theoretical to reflect the main aspects of the modern system of state management of the development of national cybersecurity. Further research requires an analysis of the world experience of state management of the development of national cybersecurity.

Hierarchical clustering methods have been proposed for more than sixty years and yet are used in various disciplines for relation observation and clustering purposes. In 1965, divisive hierarchical methods were proposed in biological sciences and have been used in various disciplines such as, and anthropology, ecology. Furthermore, recently hierarchical methods are being deployed in economy and energy studies. Unlike most clustering algorithms that require the number of clusters to be specified by the user, hierarchical clustering is well suited for situations where the number of clusters is unknown. This paper presents an overview of the hierarchical clustering algorithm. The dissimilarity measurements that can be utilized in hierarchical clustering algorithms are discussed. Further, the paper highlights the various and recent disciplines where the hierarchical clustering algorithms are employed.

The main purpose of the study is to analyze the main aspects of the impact of military actions on the EU labor market. The research methodology includes modern theoretical methods and methods for analyzing the state of the EU labor market. The war in Ukraine changed not only the economy of one country, but the whole continent. The European Union has very sensitively felt the changes brought about by the military actions on the territory of Ukraine. Military actions on the territory of Ukraine are a destructive factor in the labor market. Today, the main task of economic recovery is to minimize the consequences of humanitarian problems and preserve human potential, which is an important source of business activity. Based on the results of the study, we have identified key aspects of the impact of military actions on the EU labor market.

The article highlights the educational potential of information and communication technologies in the study of philological disciplines in higher education institutions. The study aims to analyze the didactic potential of ICT in the study of philological disciplines, as well as to check the scientific hypothesis that the use of ICT in HEIs in the study of philological disciplines will intensify and enhance the effectiveness of the learning process. To confirm the validity of the hypothesis, experimental testing was carried out and the results are illustrated in the article. The above-mentioned goal of the study determined the use of theoretical and empirical methods: analysis, synthesis, generalization, and systematization of pedagogical and scientific-methodological literature to clarify the state of research problem development and to identify pedagogical foundations on which the process of ICT use is based, comparison and prediction; questioning and testing of educational process participants to understand the effectiveness of ICT use in their training in HEIs. The research results showed positive changes in all analyzed criteria in the experimental group, which is due to the introduction of additional ICT tools into the educational process of the mentioned group. The scientific novelty of the study consists in highlighting the main characteristics and didactic functions of ICT in the learning process of philological students; in covering the classification of ICT, ICT tools, and typology of training sessions using ICT in the study of philological disciplines. In the conclusion it is summarized that the introduction of modern ICT in the educational process allows intensifying the learning process, implementation of a variety of ideas, increases the pace of classes and material assimilation, influencing the motivation for learning, increases the amount of independent work of students.

The main purpose of the work is to analyze modern innovative educational practices in the field of culture and art and their effectiveness in the context of the spread of digitalization trends. The study used general scientific theoretical methods of analysis, synthesis, analogy, comparative, induction, deduction, reductionism, and a number of others, allowing you to fully understand the pattern of modern modernization processes in a long historical development and demonstrate how the rejection of the negativity of progress allows talented artists to realize their own potential. The study established the advantages and disadvantages of involving innovative technologies in the educational process on the example of European experience and outlined possible ways of implementing digitalization processes in Ukrainian institutions of higher education, formulated the main difficulties encountered by teachers and students in the use of technological innovation in the pandemic. The rapid development of digital technologies has had a great impact on the sphere of culture and art, both visual, scenic, and musical in all processes: creation, reproduction, perception, learning, etc. In the field of art education, there is a synthesis of creative practices with digital technologies. In terms of music education, these processes at the present stage are provided with digital tools of specially developed software (music programs for composition and typing of musical text, recording, and correction of sound, for quality listening to the whole work or its fragments) for training programs used in institutional education and non-institutional learning as a means of independent mastering of the theory and practice of music-making, as well as other programs and technical tools without which contemporary art cannot be imagined. In modern stage education, the involvement of video technologies, means of remote communication, allowing realtime adjustment of the educational process, is actualized. In the sphere of fine arts, there is a transformation of communicative forms of interaction between the teacher and students, which in the conditions of the pandemic are of two-way communication with the help of information and communication technologies. At this stage, there is an intensification of transformation processes in the educational industry in the areas of culture and art.

The objective of this study was to examine the function of the items on the Arabic version of the Social Networking Time Use Scale (SONTUS) using Differential Item Functioning (DIF) across groups of university students in SA (i.e., males and females at UQU). The findings of this study indicated that some of the items in the Arabic version of the SONTUS functioned differently across male and female students in SA. University faculty and administrators in Saudi Arabia as well as in the Arabic world can benefit from understanding students use of SNS.

Acceleration of the pace of life, increasing the amount of information, the emergence of "clip way of thinking" as a phenomenon has led to the problem of choosing forms of presentation of educational materials to students. One of the ways to solve this problem is to use the means of visualization of information flow, forasmuch as the thinking of modern youth is more effective in perceiving visual images than verbal means. The purpose of the research is to prove the effectiveness of the use of visualization in the process of teaching Ukrainian as a foreign language to students with clip way of thinking. The following methods have been used, namely: analysis, synthesis, comparison, systematization and generalization of scientific literature; testing and surveys; pedagogical experiment; quantitative and qualitative analysis of data, interpretation and generalization of the research results. The essence of visualization means has been revealed; the expediency of their use in the methodology of teaching foreign students the Ukrainian language has been substantiated. It has been proven that the role of Ukrainian teachers lies in taking into account all new trends in teaching, integrating computer perception of information by foreign students into teaching technology and using cognitive visualization in order to intensify the learning process.

The main purpose of the article is to analyze the key aspects of didactic games and exercises in the sensory development of preschoolers. The relevance of the chosen subject determines the fact that there are a number of problems in the specifics of the development of preschoolers and their characteristics, which manifest themselves individually. The importance of using didactic games and exercises in the development of preschoolers has been proved. The methodology includes a number of theoretical and practical methods, which together form the research methodology. Based on the results of the study, key aspects of the importance of the influence of dadactic games and exercises in the sensory development of preschoolers were identified. Further research requires the question of analyzing modern technologies for the formation of modern methods of sensory development for preschoolers.

There has been a significant growth in global population and industrialization, as a consequence demand for electricity is increasing rapidly and the power systems need to increase the electricity generation. Currently, most of generated electricity is generated from fossil fuels. However, there are many financial and environmental concerns associated with the generation of electricity from such resource. Photovoltaic )PV) solar as a renewable resource is promising. The power output of PV systems is mainly affected by the solar irradiation and ambient temperature. This paper attempts at reducing the burden and improving the accuracy of the extensive simulations related to integrating PV systems into the electrical grid.

The aim of this paper is to investigate the prevalence of Deep Learning in the literature on Fire & Rescue Service. It is found that deep learning techniques are only beginning to benefit the firefighters. The popular areas where deep learning techniques are making an impact are situational awareness, decision making, mental stress, injuries, well-being of the firefighter such as his sudden fall, inability to move and breathlessness, path planning by the firefighters while getting to an fire scene, wayfinding, tracking firefighters, firefighter physical fitness, employment, prediction of firefighter intervention, firefighter operations such as object recognition in smoky areas, firefighter efficacy, smart firefighting using edge computing, firefighting in teams, and firefighter clothing and safety. The techniques that were found applied in firefighting were Deep learning, Traditional K-Means clustering with engineered time and frequency domain features, Convolutional autoencoders, Long Short-Term Memory (LSTM), Deep Neural Networks, Simulation, VR, ANN, Deep Q Learning, Deep learning based on conditional generative adversarial networks, Decision Trees, Kalman Filters, Computational models, Partial Least Squares, Logistic Regression, Random Forest, Edge computing, C5 Decision Tree, Restricted Boltzmann Machine, Reinforcement Learning, and Recurrent LSTM. The literature review is centered on Firefighters/firemen not involved in wildland fires. The focus was also not on the fire itself. It must also be noted that several deep learning techniques such as CNN were mostly used in fire behavior, fire imaging and identification as well. Those papers that deal with fire behavior were also not part of this literature review.

Modern production requires production staff who have design competence, experience and skills to work in various types of work integrated into professional activities. Possession of digital design methods significantly expands the opportunities for professional activities of qualified workers. The purpose of our study was to study the impact of pedagogical conditions on the formation of design competence of future qualified workers in a group work. We have identified a set of pedagogical conditions that promote the development of professionally oriented artistic and technical creativity of workers in the conditions of curricular and extracurricular activities, which include motivational-target, procedural-semantic, organizational-technological, and subject-oriented. It is shown that the formation of design competence is determined by motivational, informational-active and reflection criteria, which are aimed at motivational-value, cognitive, operational-active, creative, social and emotional components of this competence. The methodology of the research is highlighted, which includes the use of the following methods: determination of the personality's motivational sphere in order to identify strong and weak motives of students activity; multiple intelligence to identify students talents in the direction of practical intelligence, which is important for design competence; determining the level of creative activity to identify manifestations of students creative abilities; identifying the type of students innovative thinking in order to develop motivation for success; factor-criterion model, developed on the basis of a qualimetric approach, which is used to identify the level of design competence formation in accordance with its components. The results of the study showed that the creation of separate pedagogical conditions in the institution of vocational education and training (VET) had a positive impact on the development of design competence, which shows the potential of artistic and technical design in the development of professional creativity of future qualified workers taking into account the environmental approach.

Security is still a great concern to this day, albeit we have come a long way to mitigate its numerous threats. No-SQL databases are rapidly becoming the new database de-facto, as more and more apps are being developed every day. However, No-SQL databases security could be improved. In this paper, we discuss a way to improve the security of XML-based databases with the use of trust labels to be used as an access control model.

Network intrusion detection is becoming an increasing necessity for both organizations and individuals alike. Detecting intrusions is one of the major components that aims to prevent information compromise. Automated systems have been put to use due to the voluminous nature of the domain. The major challenge for automated models is the noise and data imbalance components contained in the network transactions. This work proposes an ensemble model, Attribute Subset Selector Bagging (ASUB) that can be used to effectively handle noise and data imbalance. The proposed model performs attribute subset based bag creation, leading to reduction of the influence of the noise factor. The constructed bagging model is heterogeneous in nature, hence leading to effective imbalance handling. Experiments were conducted on the standard intrusion detection datasets KDD CUP 99, Koyoto 2006 and NSL KDD. Results show effective performances, showing the high performance of the model.

The Internet of Things (IoT) is one of the fastest technologies that are used in various applications and fields. The concept of IoT will not only be limited to the fields of scientific and technical life but will also gradually spread to become an essential part of our daily life and routine. Before, IoT was a complex term unknown to many, but soon it will become something common. IoT is a natural and indispensable routine in which smart devices and sensors are connected wirelessly or wired over the Internet to exchange and process data. With all the benefits and advantages offered by the IoT, it does not face many security and privacy challenges because the current traditional security protocols are not suitable for IoT technologies. In this paper, we presented a comprehensive survey of the latest studies from 2018 to 2021 related to the security of the IoT and the use of machine learning (ML) and deep learning and their applications in addressing security and privacy in the IoT. A description was initially presented, followed by a comprehensive overview of the IoT and its applications and the basic important safety requirements of confidentiality, integrity, and availability and its application in the IoT. Then we reviewed the attacks and challenges facing the IoT. We also focused on ML and its applications in addressing the security problem on the IoT.

New realities of social relations are changing the understanding of certain phenomena, including the emergence of new concepts among the objects of property rights, such as: virtual assets, and the circulation of virtual assets. The rapid development of the virtual assets market involves the legislative consolidation of the status of such assets, changes in taxation, their circulation, and so on. These circumstances increase the interest in the study of virtual assets as the latest object of property rights and necessitate the study of this topic. The work aims to explore the theoretical developments and regulations on virtual assets in the modern world, as well as to summarize the conclusions about virtual assets as the latest object of property rights. The object of research is the content of the concept of "virtual asset" and its legal status. The methodology of work is represented by a set of methods and techniques that were used to achieve this goal, namely: hermeneutic, historical, extrapolation, comparative law, generalization, analysis, synthesis, and deduction. The study analyzed different approaches to understanding virtual assets, analyzed the characteristics of virtual assets, and concluded that in today's conditions there is no single unified legal regulation of virtual assets, although many countries are moving towards consolidating the status of virtual assets.

Hadoop and Apache Spark are Apache Software Foundation open source projects, and both of them are premier large data analytic tools. Hadoop has led the big data industry for five years. The processing velocity of the Spark can be significantly different, up to 100 times quicker. However, the amount of data handled varies: Hadoop Map Reduce can process data sets that are far bigger than Spark. This article compares the performance of both spark and map and discusses the advantages and disadvantages of both above-noted technologies.

Generally developed for medical testing, electrocardiogram (ECG) recordings seizure the cardiac electrical signals from the surface of the body. ECG study can consequently be a vital first step to support analyze, comprehend, and expect cardiac ailments accountable for 31% of deaths globally. Different tools are used to analyze ECG signals based on computational methods, and explicitly machine learning method. In all abovementioned computational simulations are prevailing tools for cataloging and clustering. This review demonstrates the different effective methods for heart disease based on computational methods for ECG analysis. The accuracy in machine learning and three-dimensional computer simulations, among medical inferences and contributions to medical developments. In the first part the classification and the methods developed to get data and cataloging between standard and abnormal cardiac activity. The second part emphases on patient analysis from entire ECG recordings due to different kind of diseases present. The last part represents the application of wearable devices and interpretation of computer simulated results. Conclusively, the discussion part plans the challenges of ECG investigation and offers a serious valuation of the approaches offered. Different approaches described in this review are a sturdy asset for medicinal encounters and their transformation to the medical world can lead to auspicious developments.

Despite global medical advancements, many patients are misdiagnosed, and more people are dying as a result. We must now develop techniques that provide the most accurate diagnosis of heart disease based on recorded data. To help immediate and accurate diagnose of heart disease, several data mining methods are accustomed to anticipating the disease. A large amount of clinical information offered data mining strategies to uncover the hidden pattern. This paper presents, comparison between different classification techniques, we applied on the same dataset to see what is the best. In the end, we found that the Random Forest algorithm had the best results.

Brain tumor classification is an important process that allows doctors to plan treatment for patients based on the stages of the tumor. To improve classification performance, various CNN-based architectures are used for brain tumor classification. Existing methods for brain tumor segmentation suffer from overfitting and poor efficiency when dealing with large datasets. The enhanced CNN architecture proposed in this study is based on U-Net for brain tumor segmentation, RefineNet for pattern analysis, and SegNet architecture for brain tumor classification. The brain tumor benchmark dataset was used to evaluate the enhanced CNN model's efficiency. Based on the local and context information of the MRI image, the U-Net provides good segmentation. SegNet selects the most important features for classification while also reducing the trainable parameters. In the classification of brain tumors, the enhanced CNN method outperforms the existing methods. The enhanced CNN model has an accuracy of 96.85 percent, while the existing CNN with transfer learning has an accuracy of 94.82 percent.

This study examines the effect of using interactive electronic models to teach mathematical concepts on students' achievement in the linear algebra course at university. The field sample consisted of 200 students divided into two equal groups, an experimental group of 100 students and a control group of 100 students. The researcher used an achievement test in some mathematical concepts related to linear algebra. The results of the study showed that there were statistically significant differences (0.05) between the average achievement scores of the experimental and control groups in the post application of the achievement test, in favor of the experimental group. The size of the influence of the independent factor on the results of the study, which is "interactive electronic forms", on the dependent factor, which is the students' academic achievement in the prepared test, had a very large effect. Also, the results of the study showed that there were statistically significant differences (0.05) between the mean scores of the experimental group in the pre and post applications of the achievement test, in favor of the post application. The researcher recommended the use of interactive electronic models in teaching mathematical concepts at the university level and diversifying the strategies of teaching mathematics, using technology to attract learners and raise their academic achievement.

Digital marketing tools are actively used in managing the development of park and recreation complexes to familiarize the population with the objects of natural heritage. This article aims to empirically evaluate digital marketing tools for popularizing the park and recreational complexes. The methodology was based on the concept of ecosystem value of park and recreation complexes as a natural heritage site. These methods included: identifying and selecting websites with information about park and recreation complexes in Slovakia and Ukraine. structural analysis of the main channels of online details about natural parks. Assessing the current state of online identity of the studied sites from the perspective of Internet users. The results indicate that to manage the development of park and recreational complexes developed their driven official websites in the Internet space, on which sections structure the information with the allocation of data on tourism and recreational potential. The article identifies additional digital marketing tools for managing the development of park and recreation complexes, particularly social networks and tourist websites. There is a sufficient amount of information about tourist recreation sites within these natural parks and tourist routes. Among the main problems of the websites: the information on the websites is entirely textual, there is a lack of sufficient data on social networks, despite the created official pages, there is no video content, which was more attracted tourists and visitors, allowing a visual assessment of the tourist potential; there is a problem of many communication channels to present the natural heritage of the countries. The research proves that the website is the primary and most common digital marketing tool for natural heritage, structuring information about tourism potential and recreation.

The article explores linguo-stylistic influence markers in essayistic texts. The novelty of this investigation is provided by its perspective. Essayism is looked at as a style of thinking and writing and studied as a holistic philosophical and cultural phenomenon, as a revalent form of comprehension of reality that features non-lasting author's judgements and enhancement of the author's voice in the text. Based on the texts by V. Rosanov, G.K. Chesterton, and D. Dontsov, the remarkable English, Russian, and Ukrainian essay-writers of the first party of the 20th century, the article tracks the typical ontological-and-existentialist correlation at the content, stylistic, and semantic levels. It is observed in terms of the ideas presented in the texts of these publicists and the lexicostylistic markers of the influence on the reader that enable these ideas to implement. The explored poetic syntax, key lexemes, dialogueness, intonational melodics, specific language, free associations, aphoristic nature, verbalization of emotions and feeling in the psycholinguistic form of their expression, stress, heroic elevation, metaphors and evaluative linguistic units in the ontological-and-existentialist aspects contribute to extremely delicate and demanding nature of the essayistic style. They create a "lacework" of unpredictable properties, intellectual illumination, unexpected similarity, metaphorical freshness, sudden discoveries, unmotivated unities.

The article defines the organizational conditions for effective management, the actions of the team to implement the concept of marketing management using the tools of pedagogical and strategic management. Due to this, results are achieved - indicators, since in our study they will be indicators of managerial efficiency: improving the "organization" function through the construction of new organizational structures; improving the functions of "analytical activity and planning" through enriching managerial work with economic and gnostic methods, analytical activities with the mandatory inclusion of financial activities, introspection of all participants, widespread use of licensed automated systems; synthesis of educational, economic, social results.

COVID-19 is an acute respiratory syndrome that affects the host's breathing and respiratory system. The novel disease's first case was reported in 2019 and has created a state of emergency in the whole world and declared a global pandemic within months after the first case. The disease created elements of socioeconomic crisis globally. The emergency has made it imperative for professionals to take the necessary measures to make early diagnoses of the disease. The conventional diagnosis for COVID-19 is through Polymerase Chain Reaction (PCR) testing. However, in a lot of rural societies, these tests are not available or take a lot of time to provide results. Hence, we propose a COVID-19 classification system by means of machine learning and transfer learning models. The proposed approach identifies individuals with COVID-19 and distinguishes them from those who are healthy with the help of Deep Visual Embeddings (DVE). Five state-of-the-art models: VGG-19, ResNet50, Inceptionv3, MobileNetv3, and EfficientNetB7, were used in this study along with five different pooling schemes to perform deep feature extraction. In addition, the features are normalized using standard scaling, and 4-fold cross-validation is used to validate the performance over multiple versions of the validation data. The best results of 88.86% UAR, 88.27% Specificity, 89.44% Sensitivity, 88.62% Accuracy, 89.06% Precision, and 87.52% F1-score were obtained using ResNet-50 with Average Pooling and Logistic regression with class weight as the classifier.

All the aspects of human life have been affected by the novel coronavirus (Covid-19). It has rapidly spread in most countries including the Kingdom of Saudi Arabia. As a result, early precautionary actions aiming to minimise the virus effect are taken by the Saudi government. One of these actions is the sudden shift to online classes and suspending the attendees to all educational institutes. Such immediate change can have a significant effect on the educational process, especially for students. One can argue that students' information-seeking behaviour within the current situation can affect their learning quality and outcomes. Therefore, this paper examines the Saudi students' information-seeking behaviour by taking a sample of students from Umm Al-Qura University. A descriptive analysis is conducted with 193 students and two approaches are used to collect data, questionnaire and semi-structured interview. The results showed that the majority of students face difficulties when searching and retrieving e-resources from the university library website. The problems range from mainly poor User Experience (UX), network connection, multiple errors and lack of subscription with academic publishers.

After the everyday use of systems and applications of artificial intelligence in our world. Consequently, machine learning technologies have become characterized by exceptional capabilities and unique and distinguished performance in many areas. However, these applications and systems are vulnerable to adversaries who can be a reason to confer the wrong classification by introducing distorted samples. Precisely, it has been perceived that adversarial examples designed throughout the training and test phases can include industrious Ruin the performance of the machine learning. This paper provides a comprehensive review of the recent research on adversarial machine learning. It's also worth noting that the paper only examines recent techniques that were released between 2018 and 2021. The diverse systems models have been investigated and discussed regarding the type of attacks, and some possible security suggestions for these attacks to highlight the risks of adversarial machine learning.

Speedy development has been witnessed in communication technologies and the adoption of the Internet across the world. Information dissemination is the primary goal of these technologies. One of the rapidly developing nations in the Middle East is Saudi Arabia, where the use of communication technologies, including mobile and Internet, has drastically risen in recent times. These advancements are relatively new to the region when contrasted to developed nations. Thus, offenses arising from the adoption of these technologies may be new to Saudi Arabians. This study examines cyber security awareness among Saudi Arabian citizens in distinct settings. A comparison is made between the cybersecurity policy guidelines adopted in Saudi Arabia and three other nations. This review will explore distinct essential elements and approaches to mitigating cybercrimes in the United States, Singapore, and India. Following an analysis of the current cybersecurity framework in Saudi Arabia, suggestions for improvement are determined from the overall findings. A key objective is enhancing the nationwide focus on efficient safety and security systems. While the participants display a clear knowledge of IT, the surveyed literature shows limited awareness of the risks related to cyber security practices and the role of government in promoting data safety across the Internet. As the findings indicate, proper frameworks regarding cyber security need to be considered to ensure that associated threats are mitigated as Saudi Arabia aspires to become an efficient smart nation.

Bankruptcy is one of the major areas that have attracted the interest of many researchers in the American system, particularly in terms of the laws that oversee it. It provides a plan of reorganization that enables the debtor or the proprietor to discharge liabilities to the creditors through dividing the assets to settle debts. This activity is carried out under supervision to fairly protect the interests of the creditors. Bankruptcy protection systems are dynamic and complex in nature, in line with the economic sector, ensuring the protection of affected individuals from falling into huge losses. Some bankruptcy procedures give the debtor the opportunity to stay in operation or business activity and benefit from revenues until the debt is settled. This law allows some debtors to be relived from any financial burden after the distribution of assets, even if the debt is not paid in full. In light of the above information, this research paper seeks to explore the nature of the complexity of bankruptcy protection laws, their characteristics, and the justice system that regulate them. It also sheds more light on the decision-making powers on bankruptcy cases. There are specialized courts that cover bankruptcy cases located in district courts in every state.

The teacher is considered the cornerstone of the educational process; the quality of education is linked mainly to teachers who perform such a necessary process. The shift in pedagogical thinking has led to progress in looking at the teacher's roles; he is no longer transferring knowledge to learners, but instead, he has become a mentor, a mediator, a planner, an intellect, and a leader. If we analyze these missions from the perspective of mental habits, we will see that they require the teacher to develop the skills of perseverance, listening comprehension, thinking flexibly, controlling emotions, self-confidence, communication skills, and other essential skills. The current research verifies the effectiveness of an instructional program based on web quests in developing habits of the mind of English language students. The study employed a quasi-experimental design. The sample consisted of 46 male students representing two classes. They were assigned randomly into an experimental group (n=24) and a control group (n=22). They were undergraduate students majoring in the English language. The findings showed a statistically significant difference in the mean scores of the experimental and control groups favoring the experimental group. The study concludes with some recommendations to differentiate teaching techniques in EFL classrooms.

Due to the large number of documents that are important to people and many of their requests from time to time to perform an essential official procedure, this requires a practical arrangement and organization for them. When necessary, many people struggle with effectively arranging official documents that enable display, which takes a lot of time and effort. Also, no mobile apps specialize in professionally preserving essential electronic records and displaying them when needed. Dataset consisting of 10,841 rows and 13 columns was analyzed using Anaconda, Python, and Mito Data Science new tool obtained from Google Play. The research was conducted using the quantitative descriptive approach. The presented solution is a model specialized in saving essential documents, categorizing according to the user's desire, and displaying them when needed. It is possible to send in an image or a pdf file. Aside from identifying file kinds like PDFs and pictures, the model also looks for and verifies specific file extensions. The file extension and its properties are checked before sharing or saving it by applying the similarity algorithm (Levenshtein). Our method effectively and efficiently facilitated the search process, saving the user time and effort. In conclusion, such an application is not available, which facilitates the process of classifying documents effectively and displaying them quickly and easily for people for printing or sending to some official procedures, and it is considered one of the applications that greatly help in preserving time, effort, and money for people.

Tourism products involve the transfer of money that is flowing to countries with partners or borders, which do not possess any relations surrounding their business environment. Suitable platforms must be generated by the tourism industry, which are beneficial to users when their demands are satisfied based on financial, technology, knowledge, and industry matters. Intermediaries are applied to alleviate different problems that are related to the non-fulfilment of contracts of existing users and service providers who are offering their services and represent a reliable third party. However, it is significant that intermediaries must be reliable when charges are incurred for any possible commission. Cryptocurrencies rely on blockchain technology to provide smoothness in money interchange without the need for reliable third parties. This interchange allows an increasing number of different new forms, which are related to different customer-to-customer transactions. The study attempts to provide an appropriate answer to the main research question, which is: 'Will the widespread adoption of cryptocurrencies bring new types of customer-to-customer markets from a technological, organizational, and environmental perspective?'.

This paper explored gifted students' perspectives on using educational technologies in their schools in the Saudi context. Adopting a descriptive research approach, a questionnaire was used to collect information from a sample of 196 gifted secondary school students in Jeddah. Findings showed that educational technology was used to a high degree, with an overall mean of 3.74 and 4.06 for the degree of importance of technological usage. Based on the findings, the researcher forwards some recommendations for effectively using such technologies to promote gifted students' abilities and talents.

This study touched on the limitations of educational technologies in gifted students' schools depending on the learners' viewpoints. The descriptive approach was used, and the tool was represented in a questionnaire distributed to a sample of 196 gifted secondary school students in Jeddah. Results showed moderate obstacles to educational technologies in gifted students' schools. The general mean of the responses of the study sample was 2.76. based on the findings, the author suggested some recommendations to reduce the difficulties that gifted students face in using educational technologies, as well as provide gifted students with electronic applications in order to their development, and especially the development of school buildings for gifted students with modern devices to help them facilitate the use of technology.

Educational programs for students with intellectual disabilities have undergone drastic changes in pursuit of the general curriculum. Accordingly, teachers in various fields, including mathematics, strive to find effective methods that enhance learning. The objective of this systematic review is to examine the field of teaching mathematics to students with intellectual disabilities to investigate relevant effective teaching strategies and required teaching skills. To achieve this goal, studies published during the period 2018-2021 were reviewed. Findings indicate the inclusion of nine studies that met the inclusion criteria out of 55 studies. The included studies found that the system of least prompts (SLP) in conjunction with feedback and error correction, and schema-based instruction are generally the most effective strategies in teaching mathematical skills to students with intellectual disabilities. Addition is the most targeted skill, followed by subtraction and algebra problem solving. The least targeted skills are multiplication, recognition of geometric shapes, calculating price after discount, rapid recognition of numbers, and rapid problem solving. The paper provides recommendations and suggests venues of future research.

The study aimed to pinpoint the effects of an educational environment based on gamification on developing achievement motivation among first-grade intermediate students. Using an achievement motivation scale, the study adopted a quasi-experimental design with experimental and control groups. The sample consisted of 52 students selected randomly from the first-grade intermediate students. They were studying in public intermediate schools in Jeddah at the time of this study. They were divided into two groups. The control group (n=24 respondent), and the experimental group (n=28 respondent). The results showed statistically significant differences at the level α ≥ 0.05 between the mean scores of the experimental group and the control group in the posttest of the achievement motivation measurement in favor of the experimental group. The study recommended using gamification in designing computer curricula and courses across educational stages in Saudi Arabia. It also recommends training the computer and information technology teachers on using gamification in their teaching.

Email phishing has become very prevalent especially now that most of our dealings have become technical. The victim receives a message that looks as if it was sent from a known party and the attack is carried out through a fake cookie that includes a phishing program or through links connected to fake websites, in both cases the goal is to install malicious software on the user's device or direct him to a fake website. Today it is difficult to deploy robust cybersecurity solutions without relying heavily on machine learning algorithms. This research seeks to detect phishing emails using high-accuracy machine learning techniques. using the WEKA tool with data preprocessing we create a proposed methodology to detect emails phishing. outperformed random forest algorithm on Naïve Bayes algorithms by accuracy of 99.03 %.

The article analyzes the regulations of current criminal law, which ensures the protection and protection of information relations, offers the optimal model of the system of norms of the Criminal Code of Ukraine, which establishes liability for violation of information. The subject of the article is protected information, which should include information or data, the procedure for access to and distribution of which, regardless of the method of submission, storage or organization, are subject to legal regulation in accordance with laws and regulations. For the purposes of criminal law, information as an object of criminal law protection should be classified on the following grounds: depending on the content: personal or family secrets; information constituting a state secret; data included in the official secret; information that constitutes a professional secret; information that constitutes a commercial, tax, banking secret, and, depending on the medium - documented and undocumented.

"Tolerance" is considered as an important professional quality of a modern specialist, which is manifested in an active moral position and readiness for constructive interaction with other participants in the pedagogical process; characterized by the manifestation of humanity, tolerance, friendliness, focus on resolving conflict situations in the professional sphere on a non-violent basis. The article considers scientific approaches to understanding the phenomenon of "tolerance". There are a number of factors that significantly affect the formation of tolerance in students. The way to the formation of tolerance is the rejection of social prejudices, negative social stereotypes, the development of an objective attitude to man regardless of his individual characteristics, the formation of skills of tolerant interpersonal interaction, the use of lectures, discussions, games and training in educational work. The purpose of this article is to highlight communicative tolerance as a necessary component of pedagogical practice of future professionals. It was emphasized that tolerance is the basis of religious tolerance and peace, prevention of all kinds of extremism, which are of particular importance for a multinational and multi-religious Ukraine.

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

Through our study, bill of exchange is defined as a written document that contains an order from the drawer directed to the drawee during which the predetermined amount must be paid within a certain time period or on sight. The research begins with an examination of how it was founded, the parties involved, and the organizer's formal conditions. Then, it discusses how to negotiate a bill of exchange through endorsement along with the different types of endorsement and its ramifications. The research concludes by elucidating the bill of exchange impact on the business community, since it decreases commercial conflicts and enables merchants to benefit from, circulate, and recycle their debts without being damaged by debts collection delays.

The article provides a theoretical substantiation of the pedagogical interaction of the subjects of the educational process in the context of distance learning; taking into account the identified features of the implementation of pedagogical interaction defined teaching methods in distance learning; a course has been developed that reveals the features of the pedagogical interaction of participants in the educational process in conditions of distance learning. To solve the tasks and check starting points, a set of methods was used: theoretical: analysis of philosophical, psychological and pedagogical literature, dissertation research, curricula, analysis of the conceptual and terminological system; empirical: questioning, conversation, self-diagnosis.

Rich morphology language such as Arabic needs more investigation and method to improve the sentiment analysis task. Using all document parts in the process of the sentiment analysis may add some unnecessary information to the classifier. Therefore, this paper shows the ongoing work to use sentence location as a feature with Arabic sentiment analysis. Our proposed method employs a supervised sentiment classification method by enriching the feature space model with some information from the document. The experiments and evaluations that were conducted in this work show that our proposed feature in the sentiment analysis for Arabic improves the performance of the classifier compared to the baseline model.

The use of the Internet has become commonplace for billions of people on the planet. The rapid development of technology, in particular, mobile gadgets, has provided access to communication anywhere, anytime. At the same time, there are growing concerns about the behavior of people on the Internet, in particular, towards each other and social groups in general. This raises the issue of human rights in today's information society. In this study, we focused on human rights such as the right to privacy, confidentiality, freedom of expression, the right to be forgotten, etc. We point to some differences in this regard, in particular between the EU, etc. In addition, we describe the latest legal regulation in this aspect in European countries. Such methods as systemic, factual, formal and legal, to show the factors of formation and development of human rights in the context of digitalization were used. The authors indicate which of them deserve the most attention due to their prevalence and relevance. Thus, we concluded that the technological development of social communications has laid the groundwork for a legal settlement of privacy and opinion issues on the Internet. Simultaneously, jurisdictions address issues on every aspect of human rights on the Internet, based on previous norms, case law, and principles of law. It is concluded that human rights legislation on the Internet will continue to be actively developed to ensure a balance of private and public interests, safe online access and unimpeded access to it.

Education is affected by technical and scientific developments. Progress in one of these areas leads give way to new educational methods and strategies. One of these advanced learning modes is what has been conventionally termed as Micro-learning (ML). It has emerged in educational technology as a result of advances in information technology as well as advances in research in memory, brain, and social-cognitive processes.In this paper, the researcher discusses micro-learning in terms of its concepts, tools, and associated concepts, advantages and disadvantages.

In light of the decreasing crop production and shortage of food across the world, one of the crucial criteria of agriculture nowadays is selecting the right crop for the right piece of land at the right time. First problem is that How Farmers can predict the right crop for cultivation because famers have no knowledge about prediction of crop. Second problem is that which algorithm is best that provide the maximum accuracy for crop prediction. Therefore, in this research Author proposed a method that would help to select the most suitable crop(s) for a specific land based on the analysis of the affecting parameters (Temperature, Humidity, Soil Moisture) using machine learning. In this work, the author implemented Random Forest Classifier, Support Vector Machine, k-Nearest Neighbor, and Decision Tree for crop selection. The author trained these algorithms with the training dataset and later these algorithms were tested with the test dataset. The author compared the performances of all the tested methods to arrive at the best outcome. In this way best algorithm from the mention above is selected for crop prediction.

This article is devoted to the study of the process of formation of the digital generation in a distance learning environment. With the introduction of quarantine due to the spread of COVID-19, opponents of digital technologies were forced to turn to relevant resources, while supporters identified new opportunities for the development of didactics and education in general. The irreversibility of the former educational reality became apparent and only the scale of the vision of potential change by interested and disinterested groups differed. Using a comprehensive approach, the authors consider the issues related to the direct and indirect impact of distance learning on children and young people born after the beginning of the XXI century. The article reveals the prerequisites and implications of distance education for the interaction of participants in the educational process. IC technologies during the educational process in the primary grades, in addition to identifying the student's learning deficit, should provide the transmission of non-verbal signals, which are important for children of this age. At the same time in the secondary school IR-technologies are designed to replace frontal learning during the assimilation of knowledge and at the same time not to worsen the quality of the educational process. Formation of students in the HEI takes place in the political science format, constant discussion of problem situations, so the task of introducing IC technology in this process is the accurate transfer of the content of the discussions. Individualization and autonomization of the educational process, its dependence on the results of the choice of educational content, and the use of pedagogical management tools change the philosophy of education for children and youth. The authors conclude that the formation of a digital generation, characterized by an increased level of digital literacy of children and youth, the possession of a certain level of digital capacity requires the use of strategies aimed at optimizing the learning process in a digital educational environment.

On Cloud, the important data of the user that is protected on remote servers can be accessed via internet. Due to rapid shift in technology nowadays, there is a swift increase in the confidential and pivotal data. This comes up with the requirement of data security of the user's data. Data is of different type and each need discrete degree of conservation. The idea of data security data science permits building the computing procedure more applicable and bright as compared to conventional ones in the estate of data security. Our focus with this paper is to enhance the safety of data on the cloud and also to obliterate the problems associated with the data security. In our suggested plan, some basic solutions of security like cryptographic techniques and authentication are allotted in cloud computing world. This paper put your heads together about how machine learning techniques is used in data security in both offensive and defensive ventures, including analysis on cyber-attacks focused at machine learning techniques. The machine learning technique is based on the Supervised, UnSupervised, Semi-Supervised and Reinforcement Learning. Although numerous research has been done on this topic but in reference with the future scope a lot more investigation is required to be carried out in this field to determine how the data can be secured more firmly on cloud in respect with the Machine Learning Techniques and cryptographic methods.

Software fault prediction is a method to compute fault in the software sections using software properties which helps to evaluate the quality of software in terms of cost and effort. Recently, several software fault detection techniques have been proposed to classifying faulty or non-faulty. However, for such a person, and most studies have shown the power of predictive errors in their own databases, the performance of the software is not consistent. In this paper, we propose a hybrid soft computing technique for SFP based on optimal feature extraction and classification (HST-SFP). First, we introduce the bat induced butterfly optimization (BBO) algorithm for optimal feature selection among multiple features which compute the most optimal features and remove unnecessary features. Second, we develop a layered recurrent neural network (L-RNN) based classifier for predict the software faults based on their features which enhance the detection accuracy. Finally, the proposed HST-SFP technique has the more effectiveness in some sophisticated technical terms that outperform databases of probability of detection, accuracy, probability of false alarms, precision, ROC, F measure and AUC.

Arabic skills are the tools by which children are prepared for the educational procedures on which their life depends. Deaf and hard of hearing students (DHH), must be able to grasp the same Arabic terms as hearing students and their different meanings in a context of different sentences less than what they are supposed to be due to their inability. However, problems arise in the same Arabic word and their different meanings in a context for (DHH) students since the way of comprehending such words does not meet the needs and circumstances of (DHH) students. Therefore, researchers introduce web-based method for Arabic words and their meanings in a context prototype that can overcome those problems. Methodology: The study sample consists of 30 (DHH) students at Al Amal City of Palestine, Gaza Region (GR). Those participants that agreed to take part in this study were recruited using a purposeful sampling method. Additionally, to examine the survey information descriptively, the Statistical Packages for social Sciences (SPSS) version 24.0 was used. A sign language teaching movie is utilized in the prototype to standardize the process and verify that Arabic vocabulary and their implications are comprehended. The Evolutionary Process Model of Prototype technique was utilized to create this system. Finding: The findings of this study show that the prototype built is workable and has the ability to help DHHS differentiate between phrases that have the same letters but distinct meanings. The findings of this study are expected to contribute to a better understanding and application of Development of Web-based Arabic Assessments for (DHH) Students in developing countries, which will help to increase the use of Development of Web-based Arabic for (HDD) students in those countries. The empirical models of Web-based Arabic for (DHH) students are established as a proof of concept for the proposed model. The results of this study are predicted to have a significant impact to the information system practitioners and to the body of knowledge.

Children are by nature curious and enthusiastic about learning and love to explore and search for everything they see around them, but as a result of this exploration they may sometimes be exposed to dangerous situations ranging from falls to poisoning and suffocation. That is why when supporting a child's natural desire to explore the world and supporting his awareness of dangerous situations and good handling of them, helps him build a conscious scientific mind and enhance his curiosity in the natural world. It is not easy to imagine a difficult situation in which we or one of our family is in danger, unable to help ourselves or to help them in time, due to our complete ignorance of the rules of first aid. Hence the importance of learning first aid not only for the child but for the community and the world at large. "Hakeem" is an Arabic E-health educational application that aims to teach children from the age of six to eleven years first aid, in our belief that the seed of renaissance lies in the care and education of children, and the lack of Arabic content that aims to teach children first aid skills. The idea is to create a scenario in which the child is responsible for saving the person who will be in a dangerous situation using Augmented Reality (AR) technology, to increase engagement and interaction and provides a rich user experience, and according to the child's performance, he will get reward points. The game will have several levels: Beginner, Intermediate, and Hakeem, and based on the player's points he will get a title and move to the next level, and when he reaches the end, he will get the certificate.

Virtual and augmented reality technologies provide access to learning materials and improve the organization of a modern library's media space. This article aims to identify the significance and role of virtual and augmented reality technologies in the modern library's media space organization. Methodology. The research uses a university library case study methodology to empirically investigate virtual and augmented reality technologies. Results. Virtual and augmented reality technologies provide research and improve learning outcomes by engaging students and learners with significant interest in such technologies. Libraries offer users the opportunity to create their VR content through available software. Students can test their VR content in the libraries' labs. Libraries support access to a variety of virtual and augmented reality content. The content is accessed using "virtual reality headsets" for viewing and workstations with "authoring software and loanable 360 cameras" for creating. The library lab is a space to support students' digital creativity and research through virtual and augmented reality. There are 3D Design Labs within the libraries as a medium to large group design learning spaces with virtual reality technology. Libraries form a media space where users can create videos, podcasts, portfolios, edit media, and book tours, and students and researchers can explore different scientific knowledge. In this way, technology ensures that risks in learning are minimized as opposed to hands-on seminars and classes.