The subject of navigation has drawn a large interest in the last few years. Navigation problem (or path planning) finds the path between two points, source location and destination location. In smart cities, solving navigation problem is essential to all residents and visitors of such cities to guide them to move easily between locations. Also, the navigation problem is very important in case of moving robots that move around the city or part of it to get some certain tasks done such as delivering packages, delivering food, etc. In either case, solution to the navigation is essential. The core to navigation systems is the navigation algorithms they employ. Navigation algorithms can be classified into navigation algorithms that depend on maps and navigation without the use of maps. The map contains all available routes and its directions. In this proposal, we consider the first class. In this paper, we are interested in getting path planning solutions very fast. In doing so, we employ a parallel platform, Reconfigurable mesh (R-Mesh), to compute the path from source location to destination location. R-Mesh is a parallel platform that has very fast solutions to many problems and can be deployed in moving vehicles and moving robots. This paper presents two algorithms for path planning. The first assumes maps with linear streets. The second considers maps with branching streets. In both algorithms, the quality of the path is evaluated in terms of the length of the path and the number of turns in the path.

Blockchain and its infrastructure technology have expanded rapidly in the last decade and are in high demand, but there is a lack of comprehensive studies on those platforms. Blockchain is a new technology based on the distributed digital ledger system. Decentralized trust is one of the key factors behind the blockchain-based system. Transparency of such a system is better than a conventional centralized ledger system. By using a blockchain-based transaction system, any business organization can harness key benefits like data integrity, confidentiality, and anonymity without involving any third party in control of the transactions. Since the blockchain is used in numerous applications and the horizon is expanding at an unprecedented pace. So, there is a need for an introducing and reviewing of blockchain platforms. In this paper, we have reported a review on existing contemporary blockchain platforms. In particular, From the existing studies, we have identified eighty blockchain platforms and the majority of them have a lack of technical details. To provide the researchers a comprehensive introducing on blockchain platforms to perform a broad guideline for future research and investment in the blockchain domain.

Tasks scheduling have been gaining attention in both industry and research. The scheduling that ensures independent task execution is critical in real-time systems. While task scheduling has gained a lot of attention in recent years, there have been few works that have been implemented into real-time architecture. The efficiency of the classical scheduling strategy in real-time systems, in particular, is still understudied. To reduce total waiting time, we apply three scheduling approaches in this paper: First In/First Out (FIFO), Shortest Execution Time (SET), and Shortest-Longest Execution Time (SLET). Experimental results have demonstrated the efficacy of the SLET in comparison with the others in most cases in a wide range of configurations.

The article discusses the theoretical and methodological part that characterizes and assessment of the current state of the theory of GR-activity, disclosed the essence and content of the concept of GR-technologies, as well as their classification. The analysis of the system of additional education for children in the social structure, as well as the analysis of the current state of the education system is carried out. The formulation of tasks for the construction of an effective model for the use of GR-technologies in the process of developing the education system using GR-technologies

The traveling salesman problem (TSP) is one of the well-known and extensively studied NPC problems in combinatorial optimization. To solve it effectively and efficiently, various optimization algorithms have been developed by scientists and researchers. However, most optimization algorithms are designed based on the concept of improving route in the iterative improvement process so that the optimal solution can be finally found. In contrast, there have been relatively few algorithms to find the optimal solution using route construction mechanism. In this paper, we propose a route construction optimization algorithm to solve the symmetric TSP with the help of ratio value. The proposed algorithm starts with a set of sub-routes consisting of three cities, and then each good sub-route is enhanced step by step on both ends until feasible routes are formed. Before each subsequent expansion, a ratio value is adopted such that the good routes are retained. The experiments are conducted on a collection of benchmark symmetric TSP datasets to evaluate the algorithm. The experimental results demonstrate that the proposed algorithm produces the best-known optimal results in some cases, and performs better than some other route construction optimization algorithms in many symmetric TSP datasets.

The article studies the implementation of automation in the education process as a convenient interface of a document management system, on the one hand, which makes it easy to navigate the program, requiring from the user only a small amount of any special skills in working with electronic computers, on the other hand, it provides to the user operational information about all the data of interest to him, taking into account the access rights given to this or that information, stored in the enterprise database.

The article analyzes and studies that pedagogical design of the educational process using information and communication technologies in educational institutions of higher education based on the development of a model and methodology personalization of training will improve the quality of the educational process at the university and solve the identified contradiction. A qualitative analysis of foreign countries in the possibility of using information and communication technologies in educational institutions of higher education is carried out.

Questionnaires and surveys are increasingly being used to collect information from participants of empirical software engineering studies. Usually, such data is analyzed using statistical methods to show an overall picture of participants' agreement or disagreement. In general, the whole survey population is considered as one group with some methods to extract varieties. Sometimes, there are different opinions in the same group, but they are not well discovered. In some cases of the analysis, the population may be divided into subgroups according to some data. The opinions of different segments of the population may be the same. Even though the existing approach can capture the general trends, there is a risk that the opinions of different sub-groups are lost. The problem becomes more complex in longitudinal studies where minority opinions might fade over time. Longitudinal survey data may include several interesting patterns that can be extracted using a clustering process. It can discover new information and give attention to different opinions. We suggest using a data mining approach to finding the diversity among the different groups in longitudinal studies. Our study shows that diversity can be revealed and tracked over time using the clustering approach, and the minorities have an opportunity to be heard.

The article proposes the process of formation of the teacher's innovative competence in the space of lifelong education the foundations of the formation of the teacher's innovative competence in the space of continuous education. The concept of the formation of the teacher's innovative competence in the space of lifelong education is proposed; it includes initial ideas, goals, objectives, patterns, principles, stages, content and technologies implementation of this process.

The rapid change in gold price is an issue of concern in the global economy and financial markets. Gold has been used as a means for trading and transaction around the world for long period of time and it plays an integral role in monetary, business, commercial and financial activities. More importantly, it is used as economic measure for the global economy and will continue to play an important economic vital role - both locally and globally. There has been an explosive growth in demand for efficient and effective scheme to predict gold price due its volatility and fluctuation. Hence, there is need for the development of gold price prediction scheme to assist and support investors, marketers, and financial institutions in making effective economic and monetary decisions. This paper primarily proposed an intelligent based system for predicting and characterizing the gold market trend. The simulation result shows that the proposed intelligent gold price scheme has been able to predict the gold price with high accuracy and precision, and ultimately it has significantly reduced the prediction error when compared to baseline neural network (NN).

The article covered theoretical aspects use of information and communication technologies in teaching. Information and communication technologies are technologies that allow you to search, process and assimilate information from various sources, including the Internet. This is the presentation of information in electronic form, its processing and storage, the use of the computer, a variety of programs. The use of information and communication technologies in the work of a student gives an increase in motivation for learning; increased cognitive interest; evaluate their learning activities, identify the problems of their own educational activities; the formation of cognitive independence of students.

The article analyzes and shows the rapid development information and telecommunication technologies, and their capabilities are becoming unprecedented for human development, effective solutions to many professional problems. The analysis of information and communication technologies of education used in higher educational institutions of Ukraine confirmed that for the effective use of special teaching methods, as well as software and technical teaching aids, it is necessary to have a trained teaching staff and students.

Care services are a significant asset in human life. Care in its overall nature focuses on human needs and covers several aspects such as health care, homes, personal care, and education. In fact, care deals with many dimensions: physical, psychological, and social interconnections. Very little information is available on estimating the cost of care services that provided to orphans and abandoned children. Prediction of the cost of the care system delivered by governmental or non-governmental organizations to support orphans and abandoned children is increasingly needed. The purpose of this study is to analyze the care cost for orphanage organizations in Saudi Arabia to forecast the cost as well as explore the most influence factor on the cost. By using business analytic process that applied statistical and machine learning techniques, we proposed a model includes simple linear regression, Naive Bayes classifier, and Random Forest algorithms. The finding of our predictive model shows that Naive Bayes has addressed the highest accuracy equals to 87% in predicting the total care cost. Our model offers predictive approach in the perspective of business analytics.

The world is facing an unprecedented economic, social and political crisis with the spread of COVID-19. The Corona Virus (COVID-19) and its global spread have resulted in declaring a pandemic by the World Health Organization. The deadly pandemic of 21st century has spread its wings across the globe with an exponential increase in the number of cases in many countries. The developing and underdeveloped countries are struggling hard to counter the rapidly growing and widespread challenge of COVID-19 because it has greatly influenced the global economies whereby the underdeveloped countries are more affected by its devastating impacts, especially the life of the low-income population. Information and Communication Technology (ICT) were particularly useful in spreading key emergency information and helping to maintain extensive social distancing. Updated information and testing results were published on national and local government websites. Mobile devices were used to support early testing and contact tracing. The government provided free smartphone apps that flagged infection hotspots with text alerts on testing and local cases. The purpose of this research work is to provide an in depth overview of emerging technologies and recent ICT developments to combat COVID-19 Pandemic. Finally, the author highlights open challenges in order to give future research directions.

A conceptual model can be used to manage complexity in both the design and implementation phases of the system development life cycle. Such a model requires a firm grasp of the abstract principles on which a system is based, as well as an understanding of the high-level nature of the representation of entities and processes. In this context, models can have distinct architectural characteristics. This paper discusses model multiplicity (e.g., unified modeling language [UML]), model singularity (e.g., object-process methodology [OPM], thinging machine [TM]), and a heterogeneous model that involves multiplicity and singularity. The basic idea of model multiplicity is that it is not possible to present all views in a single representation, so a number of models are used, with each model representing a different view. The model singularity approach uses only a single unified model that assimilates its subsystems into one system. This paper is concerned with current approaches, especially in software engineering texts, where multimodal UML is introduced as the general-purpose modeling language (i.e., UML is modeling). In such a situation, we suggest raising the issue of multiplicity versus singularity in modeling. This would foster a basic appreciation of the UML advantages and difficulties that may be faced during modeling, especially in the educational setting. Furthermore, we advocate the claim that a multiplicity of views does not necessitate a multiplicity of models. The model singularity approach can represent multiple views (static, behavior) without resorting to a collection of multiple models with various notations. We present an example of such a model where the static representation is developed first. Then, the dynamic view and behavioral representations are built by incorporating a decomposition strategy interleaved with the notion of time.

In the recent past enormous enterprise applications have migrated into the cloud computing (CC). The researchers have contributed to this ever growing technology and as a result several innovations strengthened to offer the quality of service (QoS) as per the demand of the customer. It was treated that management of resources as the major challenge to offer the QoS while focusing on the trade-offs among the performance, availability, reliability and the cost. Apart from these regular key focuses to meet the QoS other key issues in CC are data integrity, privacy, transparency, security and legal aspects (DIPTSL). This paper aims to carry out the literature survey by reflecting on the prior art of the work with regard to QoS in CC and possible implementation of block chain to implement decentralised CC solutions governing DIPTSL as an integral part of QoS.

A novel approach for the detection of cheating during e-Exams is presented here using convolutional neural networks (CNN) based systems. This system will help the proctors to identify any kind of uncertain event at the time of online exams, for which most of the government's across the globe are recommending due to the Covid-19 pandemic. Most of the institutions and students across the globe are badly affected by their academic programs and it is a challenging task for universities to conduct examinations using the traditional methods. Therefore, the students are attending most of their classes using different types of third party applications that are available online. However, to conduct online exams the universities cannot rely on these service providers for a long time. Therefore, in this work, a complete setup of the software tools is provided for the students, which can be used by students at their respective laptops/personal computers with strict guidelines from the university. The proposed approach helps most of the universities in Saudi Arabia to maintain their database of different events/activities of students at the time of E-Exams. This method proved to be more accurate and CNN based detection proved to be more sensitive with an accuracy of 97% to detect any kind of uncertain activity of the students at the time of e-Exam.

In current time, anomaly detection is the primary concern of the administrative authorities. Suspicious activity identification is shifting from a human operator to a machine-assisted monitoring in order to assist the human operator and react to an unexpected incident quickly. These automatic surveillance systems face many challenges due to the intrinsic complex characteristics of video sequences and foreground human motion patterns. In this paper, we propose a novel approach to detect anomalous human activity using a hybrid approach of statistical model and Genetic Programming. The feature-set of local motion patterns is generated by a statistical model from the video data in an unsupervised way. This features set is inserted to an enhanced Genetic Programming based classifier to classify normal and abnormal patterns. The experiments are performed using publicly available benchmark datasets under different real-life scenarios. Results show that the proposed methodology is capable to detect and locate the anomalous activity in the real time. The accuracy of the proposed scheme exceeds those of the existing state of the art in term of anomalous activity detection.

The article considers aspects of improving the quality of training of specialists based on the use of modern information and communication technologies in the educational process; the use of teaching methods and, as a result, an increase in the creative and intellectual components of educational activities; integration of various types of educational activities (educational, research, etc.); adaptation of information technology training to individual the characteristics of the student; ensuring continuity and consistency in learning; development of information technologies for distance learning; improving the software and methodological support of educational process.

M-learning is one of the most important modern learning environments in developed countries, especially in the context of the COVID-19 pandemic. According to the Ministry of Education policies in Saudi Arabia, gender segregation in education reflects the country's religious values, which are a part of the national policy. Thus, it will help many in the target audience to accept online learning more easily in Saudi society. The literature review indicates the importance to use the UTAUT conceptual framework to study the level of acceptance through adding a new construct to the model which is Mobile Application Quality. The study focuses on the end user's requirements to use M-learning applications. It is conducted with a qualitative method to find out the students' and companies' opinions who working in the M-learning field to determine the requirements for the development of M-learning applications that are compatible with the aspirations of conservative societies.

The scientific paper studies the impact of tourism and traveling on the economic level of development of countries at the macro level and its relationship with other sectors of the economy. Tourism is one of the budget-forming factors of every economy. This work describes the main trends in the development of tourism. It is determined that about one third of tourism revenues are generated by the food sector, i.e., the culinary niche of tourism. Culinary tourism is a new direction of tourism, but it is developing quite dynamically in the EU. Culinary is an important part of rural tourism in the EU and culinary tourism is actively promoted at fairs and festivals. In recent years rural tourism has been developing both at the international level and in Ukraine, primarily due to its features, which include the implementation of the principles of sustainable community development, preservation of local traditions and cultural values, gastronomic events to promote them. The aim of the article is to study the theoretical aspects of the development of gastronomic tourism in the world, to analyze the actual condition of gastronomic tourism in the EU and Ukraine, identifying prospects and ways to develop regional gastronomic tourism. The methodological and informational basis of the work is analytical reports and researches related to the development of event tourism and statistics. Systematic and logistical approaches to the studied problems were used to achieve this goal. Various general scientific and special research methods were also used. Based on PESTLE analysis, key aspects of the external environment of gastronomic tourism in Ukraine are identified. We took into account the principles of sustainable development: political, economic, social, technological, legal and environmental. The main trends in the development of gastronomic tourism in the world are studied and it is found that the greatest development in the coming years will be the trend of combining gastronomic and event tourism on the basis of sustainable development. The main preconditions and possibilities of introduction of this holistic approach to the strategy of development of the tourist branch of Ukraine are determined. A model of sustainable value chain of gastronomic tourism in the region is formed and the main advantages of its implementation are identified: formation of a regional brand, preservation of culinary traditions, development of green farming, minimization of negative impact on the environment, sustainable development of communities.

The emergence of social networks has led to the flourishing of a new golden era of branding, which is a challenge for companies due to the need for creative positioning of companies with an emphasis on building trust and loyalty to the brand. Consumers are becoming more demanding and due to a wide range of products in different markets, make demands that are more stringent on companies. The goal of this article was to study the main trends of branding and advertising on social networks to develop a new approach to brand promotion. Methodology. The quantitative and qualitative research design was used to determine the main trends in branding and advertising on social networks. The methodology included the following methods: 1) analysis of the relationship between brand value and brand content strategy, 2) content analysis of the content of companies in social networks on the example of 10 world-famous brands with the highest value. The results allowed forming the criteria of effective content and communication: simplicity of content and simplicity of communication, lack of direct advertising of products, emphasis on global socio-economic problems and social orientation, unobtrusive communication, content creativity, indirect information about the product or work, the history of the company's development through various tools. The main content strategies of brands are defined: storytelling strategy; strategy of informing about the history of the company's development; entertainment and information strategy; strategy of joint interaction with the audience through the involvement of wellknown influencers or users of products. The theoretical and practical value of the results is confirmed by the conceptualization of the main content strategies of world-famous brands, which are pioneers in new ways to build relationships with users through social networks. The research proposes to use a customer-oriented approach to brand promotion. This means studying consumer behavior and predicting possible changes in behavior, which determines the level of interaction with the brand, the content strategy of the brand, and its effectiveness.

The introduction of digital technologies affects most socio-economic processes and activities in the economy, from agriculture to public services. Even though the world is currently only in the early stages of digital transformation, the digital economy is growing rapidly, especially in developing countries. Shortly, digital platforms will be able to replace the "invisible hand" of the market and turn it into digital. Some digital platforms have already reached global reach in some sectors of the economy. The growing value of data and artificial intelligence is reflected in the high capitalization of these enterprises. Their growing role has far-reaching consequences for the organization of economic activity and integration into the field of e-business. However, their importance and level of development in different countries differ significantly. The main purpose of this article is an assessment of the level and trends of the digital economy in the world and the identification of homogeneous groups of states following the main trends in the development of its components from among the EU countries. The methodology of the conducted research is based on the use of general scientific research methods in the analysis of secondary sources and the application of statistical methods of correlation-regression and cluster analysis. Macroeconomic indicators and components of DESI (Digital Economy and Society Index) were used for the analysis. Results. Based on the analysis established that most developed countries have a medium level of digitalization of the business environment and a high level of digitalization of socially oriented public services, while countries with lower GDP focus their policies on building digital infrastructure and training qualified personnel. The study summarizes and analyzes current trends in digital technology, analyzes the level and dynamics of integration of digital technologies of the studied EU countries, the level of development of e-business and e-commerce. The conceptualization of mechanisms of creation of added value in the digital economy is offered and the possible consequences of digitalization of the economy of developing countries are generalized.

This is an era of technology and with the rapid growth of the Internet, networks are continuously growing. Companies are shifting from simple to more complex networks. Since networks are responsible to transmit huge data which is often sensitive and a point of concern for hackers. Despite the sizes of the networks, all networks are subject to several threats. Companies deploy several security measures to protect their networks from unauthorized access. These security measures are implemented from the device level to the network level. Every security layer adds more to the security of the company's network. Firewalls are the piece of software that provides internal and external security of the network. Firewalls aim to enhance the device level as well as network-level security. This paper aims to investigate the different types of firewalls, their architecture, and vulnerabilities of the firewall. This paper improves the understanding of firewall and its various types of architecture.

Data mining is the application of specific algorithms for extracting patterns from data and KDD is the automated or convenient extraction of patterns representing knowledge implicitly stored or captured in large databases, data warehouses, the Web, other massive information repositories or data streams. Data mining can be used for decision making in educational system. But educational institution does not use any knowledge discovery process approach on these data; this knowledge can be used to increase the quality of education. The problem was happening in the educational management system, but to make education system more flexible and discover knowledge from it huge data, we will use data mining techniques to solve problem.

Recently, the growth of e-commerce in Saudi Arabia has been exponential, bringing new remarkable challenges. A naive approach for product matching and categorization is needed to help consumers choose the right store to purchase a product. This paper presents a machine learning approach for product matching that combines deep learning techniques with standard artificial neural networks (ANNs). Existing methods focused on product matching, whereas our model compares products based on unstructured descriptions. We evaluated our electronics dataset model from three business-to-consumer (B2C) online stores by putting the match products collectively in one dataset. The performance evaluation based on k-mean classifier prediction from three real-world online stores demonstrates that the proposed algorithm outperforms the benchmarked approach by 80% on average F1-measure.

As a consequence of sudden outbreak of COVID-19 pandemic worldwide, educational institutes around the globe are forced to switch from traditional learning systems to e-learning systems. This has led to a variety of technology-driven pedagogies in e-teaching as well as e-learning. In order to take the best advantage, an appropriate understanding of the cognitive capability is of prime importance. This paper presents an intelligent cognitive maturity recognition system for confidence-based e-learning. We gather the data from actual test environment by involving a number of students and academicians to act as experts. Then a Genetic Programming based simulation and modeling is applied to generate a generalized classifier in the form of a mathematical expression. The simulation is derived towards an optimal space by carefully designed fitness function and assigning a range to each of the class labels. Experimental results validate that the proposed method yields comparative and superior results which makes it feasible to be used in real world scenarios.

The article seeks to explore Ukrainian media art and its features in a global context. In particular, it performs an in-depth analysis of the stages of its development from video art of the 1990s, media installations of the 2000s, and to various digital and VR technologies today. Due to historical circumstances, the development of media art was quite rapid, as young artists sought to gain new experience in media art. Most often, their experience was broadened through international cooperation and studying abroad. The paper analyzes the presentation of Ukrainian media art outside the country during 1993-2020 and distinguishes the main thematic areas of the artists' work. It examines how artists present and reveal the peculiarities of the Ukrainian worldview, aesthetics, and culture through the problematization of certain aspects and themes in their work. Specifically, among the principal topics which are problematized in the work of media artists are a sensory experience, limited sensory capabilities, gender issues, the Chernobyl tragedy, the development of utopian models of the city, and global communication. The leading themes of Ukrainian artists also include revolution and war. Notably, political and social sentiments determine the unique energy and vitality of contemporary Ukrainian art, create a revolutionary creative environment, and unite media artists in group art projects. It is concluded that by showing, exhibiting, and presenting them outside the country, artists shape the image of Ukrainian art in a global context.

The article reviews the social media as an Internet phenomenon, determines their place and level of popularity in the society, as a result of which the social networks are a resource with perspective pedagogical potential. The analysis of social media from the point of view of studying a foreign language and the possibility of their usage as a learning medium has been carried out. The most widespread and popular platforms have been considered and, based on their capabilities in teaching all types of speech activities, the "Instagram", "Twitter", and "Facebook" Internet resources have been selected as the subject of the research. The system of tasks of teaching all types of speech activities and showing the advantages of the "Instagram", "Twitter", and "Facebook" platforms has been proposed and briefly reviewed.

Our society is depending on mobile devices that play a major role in our lives. Utilizing these devices is possible due to their speed power and efficiency in performing basic as well as sophisticated operations that can be found in traditional computers like desktop workstations. The challenge with using mobile devices is that organizations are concerned with the interference between personal and corporate use due to Bring Your Own Device (BYOD) trend. This paper highlights the importance of mobile devices in our daily tasks and the associated risks involved with using these devices. Several technologies and countermeasures are reviewed in this paper to secure the mobile devices from different attempts of attacks. It is important to mention that this paper focuses on technical measures rather than considering different aspects of security measures as recommended by the cybersecurity community.

Smart grid is a fully-automated, bi-directional, power transmission network based on the physical grid system, which combines sensor measurement, computer, information communication, and automatic control technology. Blockchain technology, with its security features, can be integrated with Smart Grids to provide secure and efficient power management and transmission. This paper dicusses the deployment of Blockchain technology in Smart Grid. It presents application areas and protocols in which blockchain can be applied to in securing smart grid. One application of each area is explored in detail, such as efficient peer-to-peer transaction, lower platform costs, faster processes, greater flexibility in power generation to transmission, distribution and power consumption in different energy storage systems, current barriers obstructing the implementation of blockchain applications with some level of maturity in financial services but concepts only in energy and other sectors. Wide range of energy applications suggesting a suitable blockchain architecture in smart grid operations, a sample block structure and the potential blockchain technicalities employed in it. Also, added with efficient data aggregation schemes based on the blockchain technology to overcome the challenges related to privacy and security in the smart grid. Later on, consensus algorithms and protocols are discussed. Monitoring of the usage and statistics of energy distribution systems that can also be used to remotely control energy flow to a particular area. Further, the discussion on the blockchain-based frameworks that helps in the diagnosis and maintenance of smart grid equipment. We have also discussed several commercial implementations of blockchain in the smart grid. Finally, various challenges have been discussed for integrating these technologies. Overall, it can be said at the present point in time that blockchain technology certainly shows a lot of potentials from a customer perspective too and should be further developed by market participants. The approaches seen thus far may have a disruptive effect in the future and might require additional regulatory intervention in an already tightly regulated energy market. If blockchains are to deliver benefits for consumers (whether as consumers or prosumers of energy), a strong focus on consumer issues will be needed.

From an information security perspective, protecting sensitive data requires utilizing algorithms which resist theoretical attacks. However, treating an algorithm in a purely mathematical fashion or in other words abstracting away from its physical (hardware or software) implementation opens the door to various real-world security threats. In the modern age of electronics, cryptanalysis attempts to reveal secret information based on cryptosystem physical properties, rather than exploiting the theoretical weaknesses in the implemented cryptographic algorithm. The correlation power attack (CPA) is a Side-Channel Analysis attack used to reveal sensitive information based on the power leakages of a device. In this paper, we present a power Hacking technique to demonstrate how a power analysis can be exploited to reveal the secret information in AES crypto-core. In the proposed case study, we explain the main techniques that can break the security of the considered crypto-core by using CPA attack. Using two cryptographic devices, FPGA and 8051 microcontrollers, the experimental attack procedure shows that the AES hardware implementation has better resistance against power attack compared to the software one. On the other hand, we remark that the efficiency of CPA attack depends statistically on the implementation and the power model used for the power prediction.

Presently, Online / Offline Users are facing cyber attacks every day. These cyber attacks affect user's performance, resources and various daily activities. Due to this critical situation, attention must be given to prevent such users through cyber attacks. The objective of this research paper is to improve the IDS systems by using machine learning approach to develop a hybrid model which controls the cyber attacks. This Hybrid model uses the available KDD 1999 intrusion detection dataset. In first step, Hybrid Model performs feature optimization by reducing the unimportant features of the dataset through decision tree, support vector machine, genetic algorithm, particle swarm optimization and principal component analysis techniques. In second step, Hybrid Model will find out the minimum number of features to point out accurate detection of cyber attacks. This hybrid model was developed by using machine learning algorithms like PSO, GA and ELM, which trained the system with available data to perform the predictions. The Hybrid Model had an accuracy of 99.94%, which states that it may be highly useful to prevent the users from cyber attacks.

The objective of this project is to conduct an underwater survey. The primary goal is to develop a device that can achieve the desired output under test conditions. For this reason, certain practical considerations must be taken into account, and the implementation is then developed to be carried out to obtain stable performance with the available hardware based on that experiment. The experiment was performed via BlueROV2 (Remotely Operated Vehicle) using RaspberryPi and softwares such as QGC (QGroundControl) and ArduPilot. This paper explains the work, the results with the collected data and how we implemented the work is presented in the end. The intention of this experiment is to connect two PCs using RaspberryPi with MAVLink communication using a Commercial-Off-The-Shelf device.

Human-computer interaction is a discipline concerned with the design, evaluation, and implementation of interactive systems for human use. In this paper we suggest designing a smart deaf emergency application based on Human-Computer Interaction (HCI) principles whereas nowadays everything around us is becoming smart, People already have smartphones, smartwatches, smart cars, smart houses, and many other technologies that offer a wide range of useful options. So, a smart mobile application using Text Telephone or TeleTYpe technology (TTY) has been proposed to help people with deafness or impaired hearing to communicate and seek help in emergencies. Deaf people find it difficult to communicate with people, especially in emergency status. It is stipulated that deaf people In all societies must have equal rights to use emergency services as other people. With the proposed application the deafness or impaired hearing can request help with one touch, and the location will be determined, also the user status will be sent to the emergency services through the application, making it easier to reach them and provide them with assistance. The application contains several classifications and emergency status (traffic, police, road safety, ambulance, fire fighting). The expected results from this design are interactive, experiential, efficient, and comprehensive features of human-computer interactive technology which may achieve user satisfaction.

Non-abelian group based Cryptography is a field which has become a latest trend in research due to increasing vulnerabilities associated with the abelian group based cryptosystems which are in use at present and the interesting algebraic properties associated that can be thought to provide higher security. When developing cryptographic primitives based on non-abelian groups, the researchers have tried to extend the similar layouts associated with the traditional underlying mathematical problems and assumptions by almost mimicking their operations which is fascinating even to observe. This survey contributes in highlighting the different analogous extensions of traditional assumptions presented by various authors and a set of open problems. Further, suggestions to apply the Hamiltonian Cycle/Path Problem in a similar direction is presented.

Scientific space, one can observe the differentiation of the definition of the terms "value", "value orientations" because it does not yet have a clear standard definition. Many researchers have dealt with this topic, researched, analyzed, observed, and made conclusions. However, there is still a rich scope for research of such phenomena of personal structure as value orientations. Psychologists-researchers who, in their scientific, practical, and theoretical works, dealt with the topic of values and value orientations and came to the general conclusion that values are a structural component of a personality, with the help of which a person achieves a goal, sets this goal, and characterizes position in life. Saw the relationship between values and the basic structures of the personality, including value orientations-considered in values a system of orientation and personality attitudes.

The main goal of higher education institutions is to present a high level of quality education to its students. This study uses data mining techniques to extract educational data from cumulative databases and used them to make the right decisions. This paper also aims to find the factors affecting students' academic performance in Majmaah University, KSA, during 2010 - 2017 period. The study utilized a sample of 6,158 students enrolled from two colleges, males and females. The results showed a high percentage of stumbling and dismissed between graduate and regular students where more than 62.5% failed to follow the plan. Only 2% of students scored distinction during their study of all graduated since their grade point average, secondary level, was statistically significant, where p<0.05. Dismissed percentage was higher among males. These results promoted some recommendations in which decision-makers could take them in considerations for better improvement of academic achievements: including of specialized programs to follow-up in regards to stumbling and failure. Utilization of different communication tools are needed to activate academic advisory for dismiss and dropout evaluation.

This study empirically investigates the factors influencing the intention to accept mobile technology in Saudi healthcare service delivery using the extended unified theory of acceptance and use of technology model (UTAUT) with perceived reliability and price value. Accordingly, a conceptual model combining behavioral constructs with those linked to the technology acceptance model is developed. This model aims to identify factors that predict patients' acceptance of mobile technology healthcare service delivery. The developed model is examined using responses obtained from a survey on 545 participants receiving healthcare services in Saudi Arabia. Thus, we have conceptualized the developed model and validated seven hypotheses involving key constructs. Results suggest that performance expectancy, effort expectancy, social influence, facilitating conditions, price value, and perceived reliability are direct predictors of user behavior to accept mobile technology in healthcare service delivery. The results provide empirical evidence to the literature on the effect of facilitating conditions and effort expectancy on mobile health (mHealth) adoption. The results show that the COVID-19 pandemic has significantly increased the adoption of mHealth services in Saudi Arabia.