An amazing growth in the field of Internet of Things (IoT) and Blockchain based smart cities from both industry and academia has been witnessed in the recent years. There are many smart applications such as intelligent transportation, smart banking, improving the life style of citizen, energy consumption and managing the waste in the city, handling home needs are supporting the Smart city concept. These applications are profoundly supported by the advanced technologies like Blockchain as well as IoT in the recent past. Smart cities can be supported by the Blockchain core concepts such as secure, transparent, decentralized and immutable nature. Still, Blockchain and IoT technologies implementation in smart cities are in their early stages and significant research efforts are desirable to integrate them. This review article explores the roles and responsibilities of Blockchain and IoT in building smart cities.

The tourism industry is influenced by a large number of factors that affect the development scenarios of the tourism in different ways. At the same time, tourism is an important component of the national economy of any state, forms its image, investment attractiveness, is a source of income and a stimulus for business development. The aim of the article is to conduct an empirical study to identify the importance of cognitive determinants in the development of tourism. The study used general and special methods: systems analysis, synthesis, grouping, systematization, cognitive modeling, cognitive map, pulse method, predictive extrapolation. Target factors, indicators, and control factors influencing the development of tourism in Ukraine are determined and a cognitive model is built, which graphically reflects the nature of the influence of these factors. Four main scenarios of the Ukrainian tourism industry are established on the basis of creating a matrix of adjacency of an oriented graph and forecast modeling based on a scenario approach. The practical significance of the obtained results lies in the possibility of their use to forecast the prospects of tourism development in Ukraine, the definition of state policy to support the industry that will promote international and domestic tourism.

This study aimed to examine the Factor Structure of the teacher satisfaction scale (TSS) with distance education during the Covid-19 pandemic, as well as affirming the (Factorial Invariance) according to gender variable. It also aimed at identifying the degree of satisfaction according to some demographic variables of the sample. The study population consisted of all teachers in public education and faculty members in higher education in the Kingdom of Saudi Arabia. The (TSS) was applied to a random sample representing the study population consisting of (2399) respondents. The results of the study showed that the scale consists of five main factors, with a reliability value of (0.94). The scale also showed a high degree of construct validity through fit indices of the confirmatory factor analysis. The results have shown a gradual consistency of the measure's invariance that reaches the third level (Scalar-invariance) of the Measurement Invariance across the gender variable. The results also showed that the average response of the study sample on the scale reached (3.74) with a degree of satisfaction, as there are no statistically significant differences between the averages of the study sample responses with respect to the gender variable. While there were statistically significant differences in the averages with respect to the variable of the educational level in favor of the middle school and statistically significant differences in the averages attributed to the years of experience variable in favor of those whose experience is less than (5) years.

In the article, the authors investigate the economic security system in the conditions of the powers transformation. It is substantiated that economic security acts as a certain system that includes components and at the same time acts as a subsystem of the highest order. It is determined that the economic security system of regions acting as a system has its subsystems, which include: production, financial, environmental, innovation, investment and social subsystems. The parameters of the economic security system include relative economic independence, economic stability and self-development of economic systems, and it is proved that an important feature of economic security in addition to its systemic nature is multi-vector. It is substantiated that the monitoring of ensuring the economic security system of the development of economic systems of different levels in the conditions of the powers transformation should contain the analysis of social, economic and ecological development of regions; spheres of possible dangers of the development of regional economic systems; the nature of the threats; the degree of the possibility of threats; time perspective of economic development threats; possible consequences of losses for economic entities; the impact of threats to the object of the economic entities' activity; possible asymmetry of economic development of regional economic entities. Possible threats as a consequence of the powers transformation have been identified. A PEST analysis of the impact of factors of different nature on economic security and the development of regional economic systems in the powers transformation is carried out. A recurrent ratio is proposed for the economic security system in the conditions of the powers transformation.

The amount of Big Data generated from multiple sources is continuously increasing. Traditional storage methods lack the capacity for such massive amounts of data. Consequently, most organizations have shifted to the use of cloud storage as an alternative option to store Big Data. Despite the significant developments in cloud storage, it still faces many challenges, such as privacy and security concerns. This paper discusses Big Data, its challenges, and different classifications of security and privacy challenges. Furthermore, it proposes a new classification of Big Data security and privacy challenges and offers some perspectives to provide solutions to these challenges.

The surge in generic attacks execution against cipher text on the computer network has led to the continuous advancement of the mechanisms to protect information integrity and confidentiality. The implementation of explicit decision tree machine learning algorithm is reported to accurately classifier generic attacks better than some multi-classification algorithms as the multi-classification method suffers from detection oversight. However, there is a need to improve the accuracy and reduce the false alarm rate. Therefore, this study aims to improve generic attack classification by implementing two hybridized decision tree algorithms namely Naïve Bayes Decision tree (NBTree) and Logistic Model tree (LMT). The proposed hybridized methods were developed using the 10-fold cross-validation technique to avoid overfitting. The generic attack detector produced a 99.8% accuracy, an FPR score of 0.002 and an MCC score of 0.995. The performances of the proposed methods were better than the existing decision tree method. Similarly, the proposed method outperformed multi-classification methods for detecting generic attacks. Hence, it is recommended to implement hybridized decision tree method for detecting generic attacks on a computer network.

Flipped learning is necessary for modern education but quite difficult to implement. In pedagogical science, the question remains to what extent the practical work of the teacher in combination with the technologies of flipped learning will improve the quality of higher education. The aim of this article is to study the effectiveness and feasibility of using flipped learning technologies, assessing their perception by students (advantages and problems), identified an algorithm for introducing flipped learning technology in higher education institutions. Research methods. The main method is an experiment. An evaluation of the effectiveness of the study was conducted using a questionnaire and observation method. Statistical methods were used to evaluate the results of the experiment. The research hypothesis is that flipped learning allows the teacher to spend more time on an individual approach, to understand the real needs of students, and provide effective feedback, thereby improving the quality of learning and motivation of students, especially while studying complex material. The results of the study are to prove the effectiveness of the technology of flipped education in the study of complex disciplines, courses, topics. The use of flipped learning strategies improves the self-regulation of the educational process, group work skills, improves students' ability to learn, overcome difficulties. The technology of flipped learning in the presence of modern technical means and constant work on improving the level of digital literacy is an effective means for students to master complex topics and problematic issues that require additional consideration and discussion. The perspective of further research is the consideration of integrated approaches to the application of flipped learning technologies to the principles of STEAM-education, multilingual and multicultural programs, etc. It is also worth continuing to develop a set of methods aimed at enhancing the student's learning activities, the formation of group work skills, direct participation in creating the foundations of higher education.

The relevance of intelligence involves the definition of such communication systems of PR-management and branding of media channels with the use of social networks, which are already implemented in practice by modern representatives of professional PR product. The purpose of the investigation is to determine the system of implementation of technologies of PR-management and branding of media channels with the use of social networks based on a survey of PR and brand of different media channels on the basis of a survey of brand managers and PR. 980 respondents from Ukraine took part in the survey. The survey was conducted on the Google-forms platform. The results outline a list of the most popular social networks and messengers for the implementation of PR management and branding technologies, including Facebook, Twitter, Google, LinkedIn, Tumblr; Telegram, WhatsApp, Viber, Skype. It is determined that the criteria of branding analysis are informativeness, centralization/distribution, content, feedback intensity. Identified 2 prospects for the development of branding in an interactive media environment (creation of a presentation system; integration of websites of social media and companies in universal centers). The criteria of general importance of the factors influencing the behavioral intention of consumers to use social media channels are presented (satisfaction, accessibility, perceived usefulness, trust, ease of use, attitude, social influence, self-efficacy). The meaning of the content of social media channels (public, informational and communication) is indicated. The practical significance of the study was to present the links between the criteria, development prospects and the values of branding factors.

The article is devoted to the consideration of the methodological and general theoretical foundations of a rational methodology for teaching foreign language communicative competence of students of a non-linguistic university. The analysis of the vectors of research of problems of increasing the efficiency of the process of mastering foreign language communicative competence of non-linguistic students is presented. As a methodological basis for a rational methodology for teaching a foreign language communicative competence, the key aspects of the philosophy of rationality are considered, the basic principles of a rational methodology are formulated, linguo-didactic means of its implementation are determined, indicators of rationality are identified.

The article analyzes the psychological and pedagogical scientific literature on the problem of motivation of students' educational activity, compiled and implemented a diagnostic research program, studied the system of conditions for the development of motivation for educational activity of students, compiled and implemented a program for the development of motivation for educational activity of students, highlighted the features of motivation for educational activity of students and conducted a comparative study analysis.

Analysis of current state of construction industry functioning in Ukraine allows us to identify a number of problems having negative impact on sustainable development of construction industry, especially in terms of its organization. Therefore, it is absolutely essential to study existing methods of organization system supplying construction sites with necessary material resources. Companies can develop their own logistics departments, which independently solve logistics issues related to transportation organization and management, accounting and inventory management, acquisition and warehousing, intercommunication (ability to obtain both final and intermediate information during transporting materials). Using a complex of methods is substantiated: the hierarchy analysis method (Saati's method), the network method, the defect elimination algorithm DEA, the transportation problem that finds optimal problem solutions for construction sector with the purpose of rational supplying uninterrupted construction with building resources in the designed model "provider-transportation-costs".

This study aimed to test method on the accuracy of estimating the items parameters and ability, using the Three Parameter Logistic. To achieve the objectives of the study, an achievement test in chemistry was constructed for third-year secondary school students in the course of "natural sciences". A descriptive approach was employed to conduct the study. The test was applied to a sample of (507) students of the third year of secondary school in the "Natural Sciences Course". The study's results revealed that the (EAP) method showed a higher degree of accuracy in the estimation of the difficulty parameter and the abilities of persons higher than the MML method. There were no statistically significant differences in the accuracy of the parameter estimation of discrimination and guessing regarding the difference of the two methods: (MML) and (EAP).

The article analyzes the theoretical aspects of the relationship between the right to medical secrecy and the employer's right to receive information on the employee's state of health, resulting in a more complete description of the implementation of the right to medical secrecy and the employer's right to information on the employee's health state and the possibilities of protecting violated rights. The limits of permissible restrictions on the right to secrecy of health in terms of ensuring the person's performance of their job function have been clarified.

This paper aims to presents the overview of research in the sustainable smart cities development domain. It investigates the key challenges of the sustainable smart cities development that faced by the developers from different countries. The qualitative research method via the interview is conducted to collect the data. 10 experts on the sustainable smart cities development project were interviewed in this study. The results indicate that there are 12 sustainable smart cities development challenges named: (1) budgetary constraint; (2) lack of resources; (3) lack of institutional capacity to deliver technology; (4) lack of systems integration; (5) social acceptability; (6) lack of awareness level in the smart city development among residents; (7) the need to drive towards content development; (8) lack of strategically approach in the smart city transformation; (9) disagreement on standardizing the smart city model; (10) lack of overarching institution to create the governance structure; (11) lack of sustainable focused strategies; and (12) lack of the smart city operational framework. Furthermore, the solutions framework for these challenges was proposed as the guidelines to overcome or minimize them.

Today, both sides of modern culture are decisively invaded by digitalization. Authentication is considered to be one of the main components in keeping this process secure. Cyber criminals are working hard in penetrating through the existing network channels to encounter malicious attacks. When it comes to enterprises, the company's information is a major asset. Question here arises is how to protect the vital information. This takes into account various aspects of a society often termed as hyper connected society including online communication, purchases, regulation of access rights and many more. In this research paper, we will discuss about the concepts of MFA and KBA, i.e., Multi-Factor Authentication and Knowledge Based Authentication. The purpose of MFA and KBA its utilization for human.to.everything..interactions, offering easy to be used and secured validation mechanism while having access to the service. In the research, we will also explore the existing yet evolving factor providers (sensors) used for authenticating a user. This is an important tool to protect data from malicious insiders and outsiders. Access Management main goal is to provide authorized users the right to use a service also preventing access to illegal users. Multiple techniques can be implemented to ensure access management. In this paper, we will discuss various techniques to ensure access management suitable for enterprises, primarily focusing/restricting our discussion to multifactor authentication. We will also highlight the role of knowledge-based authentication in multi factor authentication and how it can make enterprises data more secure from Cyber Attack. Lastly, we will also discuss about the future of MFA and KBA.

Rapid growth of the higher education role in ensuring the socio-economic and innovative development of the national economy in the context of the development of the information society and the knowledge economy is observed. Achieving positive synergistic effects of the higher education development requires proper funding for university education and research. The existing funding models for national higher education systems in a number of developing countries need modernization in accordance with the modern challenges of economic and innovative development. The purpose of the article is to formulate theoretical - methodological and applied foundations for the development and implementation of the integrated model of the higher education financing under the Quadruple Helix concept. At the center of the developed model are the areas of interaction identified by the authors, namely: Personnel, Science, Management, Innovation, Social area. This made it possible to specify the interests of all stakeholders and orient the activities of higher education institutions to the satisfaction of these interests. Effective implementation of the integrated Model of the higher education financing requires increasing the level of investment attractiveness and practical value of university research; activation of innovative development of enterprises; state stimulation of business participation in university research and education; harmonization of current legislation with EU standards. Implementation of the Model will diversify sources of funding for universities, increase their level of economic security and achieve integrated synergies from the interaction of universities, business, government and the public (as the main stakeholders within the Quadruple Helix concept).

The purpose of this study is to explore the role of information systems in the implementation of knowledge management, at King Abdul-Aziz University (KAU) in Jeddah, by highlighting the importance of information systems and their implementation of the knowledge processes. The researcher used the case-study method to explore the importance of information systems in supporting the implementation of knowledge management at the university. Moreover, the study has used the questionnaire as a tool for collecting information and obtaining feedbacks from the administrators at the university, and a random sample was chosen to identify the study community. The study resulted that there is a statistical indication of the importance and degree of the use of electronic systems in the university by the administrators. The study sample members believe that the university is keen to provide information systems, where systems analyze data and convert them into knowledge information that benefits the senior management at the university. Members of the study sample emphasize the importance of electronic information systems at the university, which in turn saves time and effort in extracting information, reports, statistics and providing them easily to senior management. The study also concluded with some recommendations, such as emphasizing the importance of knowledge management as one of its top priorities, spreading the knowledge culture, instilling a vision of knowledge among individuals, and emphasizing the importance of information systems.

The study identifies the importance of informational and legislative support in ensuring gender equality. It determines the relevance of gender inequality, the main problem, which is confirmed by research and statistical information. The study aims to determine the methods of collecting information and legal regulation of gender issues and the possibility of solving them by public authorities. The main methods of gathering information are census surveys, questionnaires, surveys on public service websites, work with local communities, surveys in nursing homes and orphanages, special survey programs, and election polls. The paper considers the legal regulation of gender inequalities at the international, state, local and organizational levels. According to the analysis of the problem of gender inequality, it is established that the problem is practically eliminated in many developed countries, while countries with low incomes face gender inequality constantly.

Detecting cyber-attacks using machine learning or deep learning is being studied and applied widely in network intrusion detection systems. We noticed that the application of deep learning algorithms yielded many good results. However, because each deep learning model has different architecture and characteristics with certain advantages and disadvantages, so those deep learning models are only suitable for specific datasets or features. In this paper, in order to optimize the process of detecting cyber-attacks, we propose the idea of building a new deep learning network model based on the association and combination of individual deep learning models. In particular, based on the architecture of 2 deep learning models: Convolutional Neural Network (CNN) and Long Short Term Memory (LSTM), we combine them into a combined deep learning network for detecting cyber-attacks based on network traffic. The experimental results in Section IV.D have demonstrated that our proposal using the CNN-LSTM deep learning model for detecting cyber-attacks based on network traffic is completely correct because the results of this model are much better than some individual deep learning models on all measures.

Based on the scientific and pedagogical analysis of the theory and experience of teaching computer science disciplines, the didactic mechanism for ensuring the continuity of the average (full) general and higher professional education of economists for practical implementation innovative technology of personal experience foundation. The pedagogical conditions for the formation of information competence, including laboratory, design, research work, the use of active teaching methods for acquiring management skills in production and activities of the enterprise. An indispensable requirement for the conditions for the implementation of basic of educational programs is the assessment of competencies. With this the goal was to develop criteria and levels of formation information competence of future economists and carried out complex diagnostics.

The Ministry of Education in Saudi Arabia encourages Saudi students to continue their education at Saudi universities or abroad. Currently, an estimated 1,282,140 Saudi students are studying at Saudi universities. The extent of the research so far has not focused on Saudi student experiences, but it has shown that even a single negative event can dramatically reduce the chances of a student completing a degree. Thus, more research is necessary to identify and describe the context and obstacles (environmental and psychological) that Saudi students face. The evaluation was multifaceted to capture not only performance outcomes, but also other factors that have been suggested by research as influential to students' ability, such as the environmental, cultural, and psychological risks for graduation that Saudi students self-report. A single group pretest (survey) design was used in this study. Findings suggest depression stress and college stress predict stress levels, while subjective happiness predicts levels of scientific participations of the sample. Moreover, depression stress shows more consistency with hours spent on the internet for study purposes. These results should be considered in study support programs both institutionally and geopolitically by universities and governments.

Deep learning is an advanced technology for large-scale data analysis, with numerous promising cases like image processing, object detection and significantly more. It becomes customarily to use transfer learning and fine-tune a pre-trained CNN model for most image recognition tasks. Having people taking photos and tag themselves provides a valuable resource of in-data. However, these tags and labels might be noisy as people who annotate these images might not be experts. This paper aims to explore the impact of noisy labels on fine-tuning pre-trained CNN models. Such effect is measured on a food recognition task using Food101 as a benchmark. Four pre-trained CNN models are included in this study: InceptionV3, VGG19, MobileNetV2 and DenseNet121. Symmetric label noise will be added with different ratios. In all cases, models based on DenseNet121 outperformed the other models. When noisy labels were introduced to the data, the performance of all models degraded almost linearly with the amount of added noise.

The software development life cycle (SDLC) is a procedure used to develop a software system that meets both the customer's needs and real-world requirements. The first phase of the SDLC involves creating a conceptual model that represents the involved domain in reality. In requirements engineering, building such a model is considered a bridge to the design and construction phases. However, this type of model can also serve as a basic model for identifying business processes and how these processes are interconnected to achieve the final result. This paper focuses on process modeling in organizations, per se, beyond its application in the SDLC when an organization needs further documentation to meet its growth needs and address regular changes over time. The resultant process documentation is created alongside the daily operations of the business process. The model provides visualization and documentation of processes to assist in defining work patterns, avoiding redundancy, or even designing new processes. In this paper, a proposed diagrammatic representation models each process using one diagram comprising five actions and two types of relations to build three levels of depiction. These levels consist of a static description, events, and the behavior of the modeled process. The viability of a thinging machine is demonstrated by re-modeling some examples from the literature.

In this paper, the possibility of using a contactless smart card as a cache for geocaching is analyzed. Geocaching is an outdoor game in which players search for hidden boxes, or caches based on geographical coordinates. The problems with this game are the possibility of players cheating and the need to maintain the caches. And then there is the problem of the ignorant public accidentally discovering a cache and considering it an explosive device. This paper proposes a concept for a possible solution to the above problems by replacing the boxes with conventional contactless smart cards. Also, this concept makes geocaching more attractive by using various games. This paper proposes a system architecture as well as the cryptographic protocol required for secure communication between the player's smartphone and the card.

The aim of the study is to implement a factor analysis of the determinants of pricing in a state-regulated competitive market using economic and mathematical modelling methods and to develop ways to improve the pricing environment of the market under study. The purpose of the work defines the main objectives: (i) to investigate the features of the competitive model of the Ukrainian flour market; (ii) to analyse the current price conjuncture of the flour market and the dynamics of the main determinants of pricing; (iii)to develop ways of improving the price situation on the flour market on the basis of the factor analysis on the results of economic and mathematical modelling. In order to ensure the reliability and validity of the research results, the following methods were applied: the logical-dialectical method of scientific knowledge in the study of the main theoretical aspects of flour market functioning, the method of logical generalisation and synthesis, comparison, factor analysis, correlation and regression analysis, the graphical method, etc. It has been shown that pricing in a state-regulated competitive market has its own characteristics. For example, in the flour market the price of goods cannot be influenced by producers (sellers) by any methods, therefore determinants of pricing by indirect influence have been taken into account. The five-factor power model of wheat flour price has been constructed. It was substantiated that the price of wheat flour in Ukraine is mostly influenced by consumer price index (0.92 %). The received complex model of wheat flour price may be used also for medium-term forecasting and working out the ways of price formation optimization in the flour market.

In recent years, with the existence of huge amounts of data stored in huge databases, the need for developing accurate tools for analyzing data and extracting information and knowledge from the huge and multi-source databases have been increased. Hence, new and modern techniques have emerged that will contribute to the development of all other sciences. Knowledge discovery techniques are among these technologies, one popular technique of knowledge discovery techniques is data mining which aims to knowledge discovery from huge amounts of data. Such modern technologies of knowledge discovery will contribute to the development of all other fields. Data mining is important, interesting technique, and has many different and varied algorithms; Therefore, this paper aims to present overview of data mining, and clarify the most important of those algorithms and their uses.

The majority of the Web's success can be related to its productivity and flexibility. Web Services (WSs) have the means to create new patterns for the delivery of software capabilities. The WS easily provides the use of existing components available via the Internet. WSs are a new trend that shares ubiquitous systems with others, so the popularity of the Web is increased day by day with their associated systems. This paper will explore and adopt the possibility of developing a technique that will automate instructors' scheduling of timetables within a Web services environment. This technique has an advantage that facilitates users to reduce the time cost and effort by reducing errors and costs for institutes. Providing dependable tables to avoid mistakes related to instituting schedules is ensured by an automated repetitive manual procedure. Automated systems are increasingly developed based on organizations and their customers. Still, the setting's difficulty of automation systems increases to rise as the system architecture and applications must accomplish various requirements and specifications of ever-demanding project scenarios. The automation system is composed of an operating system, platforms, devices, machines, control system, and information technology. This architecture provides more productivity and optimized services. The main purpose of this paper is to apply an automation system to enhance both quality and productivity. This paper also covers an agile method of proving an automation system by Finite State Machine (FSM) and Attributed Graph Grammar (AGG) tool.

Open-source software developments are basically Internet-based communities that voluntarily collaborate in developing software on the Internet and such Internet communities have become an important cultural and economic phenomenon. As a result, the emergence of open-source software has presented a challenge to the traditional offerings by providing free alternatives. The objective of this article is to review the possibility of the adoption of open source software in the creation of digital libraries, highlights advantages and disadvantage preservations. Among our objective also explaining the request of such software at the present time and the criteria evaluated in the digital preservation through surveying the best open source software from the reality of intellectual production, and standards that are being built to evaluate and choose what software to create a digital library without other software available. To achieve the above objectives, we shed the light on the top 11 open-source software to manage Libraries in addition to standards that may represent the basic building block for the selection of the appropriate systems to the needs of the digital library. This article relied on the descriptive approach by reviewing a series of studies and scientific research works related to the subject of the current study. Accordingly, the most prominent of the findings of this work is its illustration of the close association between open source software and the library community, both of which represent free culture. Also it is shown that the selection process of open source software has some obstacles most notably as there are no clear and reliable criteria for selecting these systems. Current study has concluded a set of recommendations, notably awareness of the role and importance of open source software and the facilities it provides in managing digital content.

An issue of security and threat is urgent as well as it concerns everyone: a person, community, state, etc. Today, the question of cybersecurity has become especially relevant due to general digitalization and the spread of the cyberculture. In terms of it, the growing popularity of videogames can be observed. Their impact on society differs significantly, therefore, it needs thorough consideration. The purpose of the article is to disclose the role of videogames in cybersecurity. To achieve the stated purpose, such methods as analysis, synthesis, systematization and practical involvement of videogames have been used. As a result, three levels of possible threat of videogames has been distinguished: videogames as a possibly dangerous software, as a tool of propaganda and spread of stereotypes, as a space for the creation of virtual communities. In conclusion, it is stated that videogames can be not only a threat, but also a tool for strengthening the cybersecurity.

This article examines the features of improving the public management of the market of medical and social services using information technology to improve the efficiency of public activity in modern conditions. The interpretation of the essence of the categories "information technologies" and "information support" is analyzed. The importance of the organization of information support of public authorities in the insurance of the state apparatus of information management for the adoption and solution of state issues of the market of medical and social services has been studied. Issues and system of information support of public management of the market of medical and social services are considered. The stages of the ICT implementation process in the market of medical and social services are described. The tools of state regulation in the market of medical and social services and the introduction of targeted programs for the development of the social sphere and health care are highlighted. Recommendations for improvement are formulated public management of the market of medical services and social way introduction of ICT tools, which provide for the implementation of a set of measures aimed at intellectualizing the entire system public data management spheres. The necessity of development of innovative tools of public management of the market of medical and social services of Ukraine for the purpose of working out of strategies of increase of quality of medical and social services in the XXI century is substantiated. A number of benefits from the implementation of an effective process of application of information support of public management of the market of medical and social services to ensure the efficiency of public authorities of Ukraine. It is proposed to create a "Department of information support of self-government" and electronic health care system (e-Health) to improve the management decision-making process, which will provide an opportunity to accumulate, process, analyze, and as a result, get the expected effect in the form of balanced management decisions by public authorities of Ukraine.

The current study aimed at measuring the rate of loss in search results of the actual number of publications in journals indexed by Web of Science when not using the accurate official authority name as indicated by the Ministry of Education. Conducting a search using the authority name does not always yield complete results of all existing publications. Researchers in Saudi universities tend to use up to 10 different random names of universities when searching. This interesting fact has prompted the authors of this paper to conduct a study on the search results of 30 Saudi universities using the authority name as indicated by the Ministry of Education. The statistical analyses revealed that there is a high tendency for the wrong use of authority names. Results show that 8 universities were not found in the search results. Furthermore, other universities are losing between 10 and 30% of search results that reflect the actual number of publications. Consequently, the rank of each university, as well as the general rank of Saudi universities in the Web of Science, will be affected.

The aim of this paper is to review the current knowledge management (KM) practices and their importance in the public sector of Saudi Arabia. Using the term "knowledge management in public sector", a search for available works was done in Google Scholar. In the first stage, the search for literature published under anytime choice was done in the first 10 pages of the search engine. Then another nine pages of Goggle Scholar were searched for more recent works published setting the time as 2014 to 2018. The search yielded 37 usable works for this review. The results of this literature search and review indicated that out of the 37 works reviewed, only three works were related to Saudi Arabia. Number of papers on factors of KM were maximum, many of them giving diagrammatic presentation of their results. KM modelling itself is not easy as only very few papers on KM modelling were available. Problems of too much reliance on qualitative data and hypotheses not matching with the literature backgrounds for them were also found. Considering the works related to KM, the number of papers in various categories may indicate the dimensions of KM to be considered when KM is implemented or evaluated in any public sector of any country. This applies to Saudi Arabian public sector organizations also. There is a fertile ground of research waiting to be investigated by researchers in Saudi Arabia.

Quality Models are important element of the software industry to develop and implement the best quality product in the market. This type of model provides aid in describing quality measures, which directly enhance the user satisfaction and software quality. In software development, the inheritance technique is an important mechanism used in object-oriented programming that allows the developers to define new classes having all the properties of super class. This technique supports the hierarchy design for classes and makes an "is-a" association among the super and subclasses. This paper describes a standard procedure for validating the inheritance metric in Quality Model for Object-Oriented Design (QMOOD) by using a set of nine properties established by Weyuker. These properties commonly using for investigating the effectiveness of the metric. The integration of two measuring methods (i.e. QMOOD and Weyuker) will provide new way for evaluating the software quality based on the inheritance context. The output of this research shows the extent of satisfaction of the inheritance metric in QMOOD against Weyuker nine properties. Further results proved that Weyker's property number nine could not fulfilled by any inheritance metrics. This research introduces a way for measuring software that developed using object-oriented approach. The theoretical validation of the inheritance metric presented in this paper is a small step taken towards producing quality software and in providing assistance to the software industry.

In a duopoly situation, one firm can gain competitive advantage by attracting the price-sensitive customers from its competitor leading to higher profits through higher sale revenue for the competing company. A simulation study in which there are two electric car manufacturers with agent based modelling was conducted in order to verify this contention. The first step consisted of defining the baseline. Simulations of 1000 times and agent-based modelling were conducted with the assumption that company 1 reduced its price to the maximum of 20% thereby contributing to the switch-over of a maximum of 40% of the price sensitive customers of company 2. The results of 1000 simulations and agent-based modelling highlighted that price reduction by company 1 resulted in a significant increase in the number of customers, presumably due to switch-over from company 2 and there was a corresponding increase in revenues from both of the sales avenues. Thus, Company 1 achieved competitive advantage by marketing its cars to the customers of Company 2 using price reduction strategy to attract them. This study has ramifications for companies that aim to sway the price sensitive customers from a competitor.

The objective is to recognize the better opportunities from targeted reveal advertising, to show a banner ad to the consumer of online who is most expected to obtain a preferred action like signing up for a newsletter or buying a product. Discovering the most excellent commercial impression, it means the chance to exhibit an advertisement to a consumer needs the capability to calculate the probability that the consumer who perceives the advertisement on the users browser will acquire an accomplishment, that is the consumer will convert. On the other hand, conversion possibility assessment is a demanding process since there is tremendous data growth across different information dimensions and the adaptation event occurs infrequently. Retailers and manufacturers extensively employ the retail services from internet as part of a multichannel distribution and promotion strategy. The rate at which web site visitors transfer to consumers is low for online retail, out coming in high customer acquisition expenses. Approximately 96 percent of web site users concluded exclusive of no shopper purchase[1].This category of conversion rate is collected from the advertising of social media sites and pages that dataset must be estimating and assessing with the concept of big data clustering, which is used to group the particular age group of people along with their behavior. This makes to identify the proper consumer of the production which leads to improve the profitability of the concern.

Social media is increasingly becoming a part of our daily life for communicating each other. There are various tools and applications for communication and therefore, identity theft is a common issue among users of such application. A new style of identity theft occurs when cybercriminals break into WhatsApp account, pretend as real friends and demand money or blackmail emotionally. In order to prevent from such issues, data mining can be used for text classification (TC) in analysis authorship attribution (AA) to recognize original sender of the message. Arabic is one of the most spoken languages around the world with different variants. In this research, we built a machine learning model for mining and analyzing the Arabic messages to identify the author of the messages in Saudi dialect. Many points would be addressed regarding authorship attribution mining and analysis: collect Arabic messages in the Saudi dialect, filtration of the messages' tokens. The classification would use a cross-validation technique and different machine-learning algorithms (Naïve Baye, Support Vector Machine). Results of average accuracy for Naïve Baye and Support Vector Machine have been presented and suggestions for future work have been presented.

Agriculture is one of the essential needs of human life on planet Earth. It is the source of food and earnings for many individuals around the world. The economy of many countries is associated with the agriculture sector. Lots of diseases exist that attack various fruits and crops. Apple Tree Leaves also suffer different types of pathological conditions that affect their production. These pathological conditions include apple scab, cedar apple rust, or multiple diseases, etc. In this paper, an automatic detection framework based on deep learning is investigated for apple leaves disease classification. Different pre-trained models, VGG16, ResNetV2, InceptionV3, and MobileNetV2, are considered for transfer learning. A combination of parameters like learning rate, batch size, and optimizer is analyzed, and the best combination of ResNetV2 with Adam optimizer provided the best classification accuracy of 94%.

The Internet of Things (IoT) is a rapidly growing physical network that depends on objects, vehicles, sensors, and smart devices. IoT has recently become an important research topic as it autonomously acquires, integrates, communicates, and shares data directly across each other. The centralized architecture of IoT makes it complex to concurrently access control them and presents a new set of technological limitations when trying to manage them globally. This paper proposes a new decentralized access control architecture to manage IoT devices using blockchain, that proposes a solution to concurrency management problems and enhances resource locking to reduce the transaction conflict and avoids deadlock problems. In addition, the proposed algorithm improves performance using a fully distributed access control system for IoT based on blockchain technology. Finally, a performance comparison is provided between the proposed solution and the existing access management solutions in IoT. Deadlock detection is evaluated with the latency of requesting in order to examine various configurations of our solution for increasing scalability. The main goal of the proposed solution is concurrency problem avoidance in decentralized access control management for IoT devices.

Many emerging mobile ad-hoc network application communications are group-oriented. Multicast supports group-oriented applications efficiently, particularly in a mobile environment that has a limited bandwidth and limited power. Energy effectiveness along with safety are 2 key problem in MANET design. Within this paper, MANET is presented with a stable, energy-efficient clustering technique. In this proposed work advanced clustering in the networks with ticket ID cluster manager (TID-CMGR) has formed in MANET. The proposed routing scheme makes secure networking the shortest route possible. In this article, we propose a Cluster manager approach based on TICKET-ID to address energy consumption issues and reduce CH workload. TID-CMGR includes two mechanism including ticket ID controller, ticketing pool, route planning and other components. The CA (cluster agent) shall control and supervise the functions of nodes and inform to TID-CMGR. The CH conducts and transfers packets to the network nodes. As the CH energy level is depleted, CA elects the corresponding node with elevated energy values, and all new and old operations are simultaneously stored by CA at this time. A simulation trial for 20 to 100 nodes was performed to show the proposed scheme performance. The suggested approach is used to do experimental work using the NS- simulator. TIDCMGR is compared with TID BRM and PSO to calculate the utility of the work proposed. The assessment shows that the proposed TICKET-ID scheme achieves 90 percent more than other current systems.

In modern years, the performance of the students is analysed with lot of difficulties, which is a very important problem in all the academic institutions. The main idea of this paper is to analyze and evaluate the academic performance of the college students with bipolar disorder by applying data mining classification algorithms using Jupiter Notebook, python tool. This tool has been generally used as a decision-making tool in terms of academic performance of the students. The various classifiers could be logistic regression, random forest classifier gini, random forest classifier entropy, decision tree classifier, K-Neighbours classifier, Ada Boost classifier, Extra Tree Classifier, GaussianNB, BernoulliNB are used. The results of such classification model deals with 13 measures like Accuracy, Precision, Recall, F1 Measure, Sensitivity, Specificity, R Squared, Mean Absolute Error, Mean Squared Error, Root Mean Squared Error, TPR, TNR, FPR and FNR. Therefore, conclusion could be reached that the Decision Tree Classifier is better than that of different algorithms.

In recent years Hadoop usage has been increasing day by day. The need of development of the technology and its specified outcomes are eagerly waiting across globe to adopt speedy access of data. Need of computers and its dependency is increasing day by day. Big data is exponentially growing as the entire world is working in online mode. Large amount of data has been produced which is very difficult to handle and process within a short time. In present situation industries are widely using the Hadoop framework to store, process and produce at the specified time with huge amount of data that has been put on the server. Processing of this huge amount of data having small files & its storage optimization is a big problem. HDFS, Sequence files, HAR, NHAR various techniques have been already proposed. In this paper we have discussed about various existing techniques which are developed for accessing and storing small files efficiently. Out of the various techniques we have specifically tried to implement the HDFS- HAR, NHAR techniques.

Covid-19 posed a serious threat to public health worldwide, especially in the absence of vaccines or medicines. The only viable strategies to combat a virus with a high infection rate were to apply lock-down strategies, transport ban, social and physical distancing. In this work, we provide a domain-specific component model for crisis management. The model allows for building a plan for managing Covid-19 crisis and use the plan as a template to generate a system specific for managing that crisis. The crisis component model is derived from X-MAN II, a generic component model that we have developed for the aircraft industry