Academic literature on the topic 'Expanding Knowledge in the Information and Computing Sciences'

In Fog Computing, fog colonies are formed by nodes cooperating to provide services to end-users. To enable efficient operation and seamless scalability of fog colonies, decentralized control over participating nodes should be promoted. In such cases, autonomous Fog Nodes operate independently, sharing the context in which all colony members provide their services. In the paper, we explore different techniques of context diffusion and knowledge sharing between autonomous Fog Nodes within a fog colony, using ECTORAS, a publish/subscribe protocol. With ECTORAS, nodes become actively aware of their operating context, share contextual information and exchange operational policies to achieve self-configuration, self-adaptation and context awareness in an intelligent manner. Two different ECTORAS implementations are studied, one offering centralized control with the existence of a message broker, to manage colony participants and available topics, and one fully decentralized, catering to the erratic topology that Fog Computing may produce. The two schemes are tested as the Fog Colony size is expanding in terms of performance and energy consumption, in a prototype implementation based on Raspberry Pi nodes for smart building management.

Purpose The purpose of the study was to investigate factors promoting innovation and application of internet of things in academic and research information organizations. Design/methodology/approach Quantitative research design involved survey of selected academic and research information organizations in public and private chartered institutions. Information professionals, digital content managers, information systems and technologists that normally consume big data and technological resources were involved in the process of data collection using structured questionnaire and content analysis. Information organizations and information practitioners were selected from public and private academic and research institutions. Findings Innovation of internet of things has increasingly transformed and changed academic and research information organizations as the source of knowledge in addition to expanding access to education, data, information and communication anywhere anytime through hyperconnectivity and networking. Internet of things technologies such as mobile of things, web of things, digital information systems and personal devices are widely applied by digital natives in academic and research information organizations. Mobilization platform and devices is the single biggest provider of data, information and knowledge in academic and research organizations. Modern trends in education and knowledge practices in academic institutions and information organizations depends upon internet of things, digital repositories, electronic books and journals, social media interfaces, multimedia applications, information portal hubs and interactive websites, although challenges regarding inadequate information communication technology infrastructure and social computing facilities still persist. Research limitations/implications Information organizations in public and private chartered academic and research institutions were adopted in the study. Respondents handling and supporting information management, planning and decision-making provided the necessary data. Information professionals, digital content managers, information systems and technologists are proactively involved in data and information analytics. Practical implications Academic and research information organizations are powerhouses that provide knowledge to support research, teaching and learning for sustainable development and the betterment of humanity and society. Innovation of internet of things and associated technologies provides practical aspects of attaining sustainable information development practices in the contemporary knowledge society. Internet of things technologies, principles of economies of scale and investment and customer needs entail that information organizations and practitioners should provide appropriate and smart systems and solutions. Social implications Modern academic and research information organizations have the social corporate responsibility to offer technological innovations to heighten access to knowledge and learning in academic and research institutions. Economically, innovation and application of internet of things provide unlimited access to big data and information in organizations all the time anywhere anytime. Originality/value Data management is a growing phenomenon that information practitioners need to fully understand in the digital economies. Information professionals need to embrace and appreciate innovation and application of internet of things technologies whose role in sustainable development practices is critical in academic and research organizations.

Digital sociology is a computational social science that uses modern information systems and technologies, has already formed. But the conflict with traditional sociology and its research methods has not yet been resolved. This conflict can be overcome if we remember that there is a common goal – the knowledge of the phenomena and processes of social life, which is primary in relation to the methods to be agreed upon. Digital transformation of sociology is essential, since 1) traditional sociological methods do not solve the problem of providing voluminous, reliable empirical data qualitatively and in a short time; 2) the transition from contact research methods to unobtrusive ones is in demand. The adaptation of four modern information technologies-cloud computing, big data, the Internet of things and artificial intelligence – for the purposes of sociology provides a qualitative transition in the methodology of knowledge of the digital society. Cloud computing provide researchers with tools, big data – research materials, Internet of things technology aimed at collecting indicators (receiving signals) in large volume, in real time, as direct, not indirect evidence of human behavior. The development of “artificial intelligence” technology expands the possibility of receiving processed signals of the quality of the social system without building a preliminary hypothesis, in a short time and on a large volume of processed data. Digital transformation of sociology does not mean abandoning the use of traditional methods of sociological analysis, but it involves expanding the competence of a sociologist, which requires a revision of University curricula. At the same time, combining the functions of an expert on the subject (sociologist) and data analyst in one specialist is assessed as unpromising, it is proposed to combine their professional competencies in working on unified research projects.

Purpose Cloud computing technology is advancing and expanding at an explosive rate. These advancements have further extended the capabilities of the virtual learning environment (VLE) to provide accessibility anywhere, anytime where educational resources can be saved, modified, retrieved and shared on the cloud. The purpose of this paper is to examine the predictors of instructional effectiveness of cloud computing VLE by extending the Self Determination and Channel Expansion Theory with external constructs of VLE interactivity, content design, school support, trust in website, knowledge sharing attitude and demographic variables. Design/methodology/approach Random sampling data were collected in two waves of nation-wide survey and analyzed with artificial neural network approach. Findings SDT, CET, content design, interactivity, trust in website, school support and demographics significantly predict instructional effectiveness. Research limitations/implications The study has provided a new paradigm shift from investigating the behavioral intention and continuance intention to the effectiveness of an information system. It advocates that quality of research may be improved by adhering to the basic research methodology starting from rigorous instrument development and validation to future research direction. Practical implications The research provides implications to Ministry of Education, the VLE content and service providers, scholars and practitioners. Social implications The findings of the study may further improve the quality of living of the society when the instructional effectiveness of the cloud-based VLE is further enhanced. Originality/value Existing grid computing VLE studies have focussed on the acceptance of students and teachers and not its instructional effectiveness. Unlike existing studies that examined extrinsic motivational factors (e.g. TAM, UTAUT), this study uses intrinsic motivational factors (e.g. relatedness, competence and autonomy) as well as perceived media richness. Malaysia is the first nation to implement the VLE at a national scale and the findings from this study will provide a new insight on the determinants of instructional effectiveness of the VLE system.

Aim/Purpose: This study aims to propose and empirically validate a model and investigates the factors influencing acceptance and use of Software as a Services cloud computing services (SaaS) from individuals’ perspectives utilizing an integrative model of Theory of Planned Behavior (TPB) and Technology Acceptance Model (TAM) with modifications to suit the objective of the study. Background: Even though SaaS cloud computing services has gained the acceptance in its educational and technical aspects, it is still expanding constantly with emerging cloud technologies. Moreover, the individual as an end-user of this technology has not been given the ample attention pertaining to SaaS acceptance and adoption (AUSaaS). Additionally, the higher education sector needs to be probed regarding AUSaaS perception, not only from a managerial stance, but also the individual. Hence, further investigation in all aspects, including the human factor, deserves deeper inspection. Methodology: A quantitative approach with probability multi-stage sampling procedure conducted utilizing survey instrument distributed among students from three public Malaysian universities. The valid collected responses were 289 Bachelor’s degree students. The survey included the demographic part as well as the items to measure the constructs relationships hypothesized. Contribution: The empirical results disclosed the appropriateness of the integrated model in explaining the individual’s attitude (R2 = 57%), the behavior intention (R2 = 64%), and AUSaaS at the university settings (R2 = 50%). Also, the study offers valuable findings and examines new relationships that considered a theoretical contribution with proven empirical results. That is, the subjective norms effect on attitude and AUSaaS is adding empirical evidence of the model hypothesized. Knowing the significance of social effect is important in utilizing it to promote university products and SaaS applications – developed inside the university – through social media networks. Also, the direct effect of perceived usefulness on AUSaaS is another important theoretical contribution the SaaS service providers/higher education institutes should consider in promoting the usefulness of their products/services developed or offered to students/end-users. Additionally, the research contributes to the knowledge of the literature and is considered one of the leading studies on accepting SaaS services and applications as proliferation of studies focus on the general and broad concept of cloud computing. Furthermore, by integrating two theories (i.e., TPB and TAM), the study employed different factors in studying the perceptions towards the acceptance of SaaS services and applications: social factors (i.e., subjective norms), personal capabilities and capacities (i.e., perceived behavioral control), technological factors (i.e., perceived usefulness and perceived ease of use), and attitudinal factors. These factors are the strength of both theories and utilizing them is articulated to unveil the salient factors affecting the acceptance of SaaS services and applications. Findings: A statistically positive significant influence of the main TPB constructs with AUSaaS was revealed. Furthermore, subjective norms (SN) and perceived usefulness (PU) demonstrated prediction ability on AUSaaS. Also, SN proved a statically significant effect on attitude (ATT). Specifically, the main contributors of intention are PU, perceived ease of use, ATT, and perceived behavioral control. Also, the proposed framework is validated empirically and statistically. Recommendation for Researchers: The proposed model is highly recommended to be tested in different settings and cultures. Also, recruiting different respondents with different roles, occupations, and cultures would likely draw more insights of the results obtained in the current research and its generalizability Future Research: Participants from private universities or other educational institutes suggested in future work as the sample here focused only on public sector universities. The model included limited number of variables suggesting that it can be extended in future works with other constructs such as trialability, compatibility, security, risk, privacy, and self-efficacy. Comparison of different ethnic groups, ages, genders, or fields of study in future research would be invaluable to enhance the findings or reveal new insights. Replication of the study in different settings is encouraged.

The end-user computing satisfaction model (EUCS) has been widely used in previous studies, and Enterprise Resource Planning. Therefore, Enterprise Resource Planning (ERP) System, need to be developed in accordance with cloud computing that dominate current information technology devices. This study was carried out to test the expansion of the EUCS model in a cloud-based ERP system. Therefore, the purpose of this research is to re-examine the validity and reliability of the computer application satisfaction model and its relationship with user performance in cloud-based ERP system. The overall satisfaction variable is added as a mediation between the satisfaction model and user performance. Data was collected through snowball sampling with a questionnaire distributed to the cloud-based ERP users. Additionally, data processing was conducted using the Second-order concept in structural equation modeling with the Partial Least Square approach. Since data processing using WarpPLS confirmed the validity and reliability of the model and all relationships between variables, this research contributes theoretically to the study of end-user satisfaction from information technology applications. Its final section describes the limitations and opportunities for future research.

This article examines recent e-science initiatives through the lens of the concept of `research technologies'. It has been argued that e-science research, which makes use of advanced computing tools to share distributed resources via networks, changes the disciplinary nature of research towards greater interdisciplinarity and paves the way for the increasing globalization of research. However, these claims need to be instantiated in concrete research practices. The essay therefore presents three examples of research projects where these two features can be demonstrated. More generally these three projects — in social science hyperlink analysis, high-energy physics, and astronomy — are examples of `research technologies', which, it has been argued, are often a radical source of innovation. The article describes how the three projects illustrate these arguments about research technologies, but also how this concept is limited as e-science research is still ongoing. The conclusion assesses how the notion of research technologies is useful for understanding how networked computing technologies are changing the current landscape of knowledge production.

Purpose – The main aim of this paper is to investigate the potential of Cloud Computing as a multilayer integrative collaboration space for knowledge acquisition, nurturing and sharing. The paper will pinpoint benefits and challenges of Cloud Computing in satisfying the new techno-sociological requirements of the knowledge society through the provision of information technology (IT) green services. Furthermore, the article calls for the engagement of researchers to generate additional discussion and dialog in this emerging and challenging area. Design/methodology/approach – The paper applies a conceptual analysis to explore the utilization of the Cloud ecosystem as a new platform for knowledge management (KM) technologies characterized by environmental and economic benefits. Findings – This paper reveals the emergence of a new layer in the Cloud stack known as Knowledge Management-as-a-Service. The article discusses how KM has the opportunity to evolve in synergy with Cloud Computing technologies using the modified Metcalfe’s law, while simultaneously pursuing other benefits. This research reveals that if Cloud Computing is successfully deployed, it will contribute to the efficient use of the under-utilized computing resources and enable a low carbon economy. However, challenges such as security, information overload and legal issues must be addressed by researchers before Cloud Computing becomes the de facto KM platform. Originality/value – While the technical, legal and environmental complications of Cloud Computing have received the attention warranted, the KM concepts and implementation facets within the realm of the knowledge society have not yet received adequate consideration. This paper provides enterprise KM architects, planners, chief information officers (CIOs) and chief knowledge officers (CKOs) with a comprehensive review of the critical issues, many of which are often overlooked or treated in a fragmented manner within the Cloud environment.

Knowledge-based expert systems are used to enhance and automate manual processes through the use of a knowledge base and modern computing power. The traditional methodology for creating knowledge-based expert systems has many commonly encountered issues that can prevent successful implementations. Complications during the knowledge acquisition phase can prevent a knowledge-based expert system from functioning properly. Furthermore, the time and resources required to maintain a knowledge-based expert system once implemented can become problematic. There are several concepts that can be integrated into a proposed methodology to improve the knowledge-based expert system lifecycle to create a more efficient process. These methods are commonly used in other disciplines but have not traditionally been incorporated into the knowledge-based expert system lifecycle. A container-loading knowledge-based expert system was created to test the concepts in the proposed methodology. The results from the container-loading knowledge-based expert system test were compared against the historical records of thirteen container ships loaded between 2008 and 2011.

Purpose – The aim of this study is to determine if adopting cloud-based knowledge management is a viable way forward for small enterprises and to investigate what are the main factors that might facilitate or inhibit these companies to adopt such solutions.Design/Methodology/Approach - In order to understand the main factors that could influence the adoption of a cloud-based knowledge management solution in small enterprises, I used a qualitative research approach, based on four semi-structured interviews with four small companies from Romania.Findings – The results of the study suggest that implementing knowledge management in the cloud is particularly beneficial for small enterprises, as a lower investment in IT infra-structure can create a competitive advantage and help them implement knowledge man-agement activities as a strategic resource. Moreover, the study suggests that relative ad-vantage, compatibility and technology readiness will influence companies in moving their knowledge to the cloud. Also, the study reveals that companies which did not adopt such a solution had already established systems for managing knowledge and failed to realize its benefits, it was not perceived as needed, they had a low level of awareness or cited security and uncertainty reasons.

The purpose of this research is to assess the function, form and content of knowledge sharing in communities of practice, social networks and the use of collaborative technologies in Third Sector community networks in the North East of England. This is a significant area worthy of detailed examination due to the acknowledged relationship between communities of practice, social networks and the use of collaborative technologies. These three domains have been examined separately by others and suggestions have been made as to relationships between them but few, if any, studies appear to have used case-based evidence to explore how these relationships add value to knowledge sharing. The research addresses the following research question: To what extent does the use of collaborative technologies in communities of practice and social networks, in the Third Sector of the North East region, add value to face- to-face knowledge sharing and how may this be measured? In order to answer the research question a qualitative holistic case study approach based upon three case studies in Newcastle upon Tyne, South Tyneside and Sunderland has been utilised and grounded theory is used to formulate theory from the observed and analysed practice of the case studies under investigation. The conclusion is drawn that when value is added to knowledge sharing it is relative to the strength of several key variables, including, reciprocity, trust, the strength of network ties and the ability to integrate the use of collaborative technologies into ongoing activities. To aid analysis of the presence and strength of these variables a working paradigm has been designed and developed. Case studies are analysed through this paradigm leading to the development of a theory of knowledge sharing in the Third Sector.

Recent development in modern computing has led to a more diverse use of devices within the field of mobility. Many mobile devices of today can, for instance, surf the web and connect to wireless networks, thus gradually merging the wired Internet with the mobile Internet. As mobile devices by design usually have built-in means for creating rich media content, along with the ability to upload these to the Internet, these devices are potential contributors to the already overwhelming content collection residing on the World Wide Web. While interesting initiatives for structuring and filtering content on the World Wide Web exist – often based on various forms of metadata – a unified understanding of individual content is more or less restricted to technical metadata values, such as file size and file format. These kinds of metadata make it impossible to incorporate the purpose of the content when designing applications. Answers to questions such as "why was this content created?" or "in which context was the content created?" would allow for a more specified content filtering tailored to fit the end-users cause. In the opinion of the authors, this kind of understanding would be ideal for content created with mobile devices which purposely are brought into various environments. This is why we in this thesis have investigated in which way descriptions of contexts could be caught, structured and expressed as machine-readable semantics.

In order to limit the scope of our work we developed a system which mirrored the context of ubiquitous learning activities to a database. Whenever rich media content was created within these activities, the system associated that particular content to its context. The system was tested during live trials in order to gather reliable and “real” contextual data leading to the transition to semantics by generating Rich Document Format documents from the contents of the database. The outcome of our efforts was a fully-functional system able to capture contexts of pre-defined ubiquitous learning activities and transforming these into machine-readable semantics. We would like to believe that our contribution has some innovative aspects – one being that the system can output contexts of activities as semantics in real-time, allowing monitoring of activities as they are performed.

It has been suggested 'expert systems' might have a significant role in the future through enabling many more people to access human experts. It is, therefore, important to understand how potential users interact with these computer systems. This study investigates the effect of extension agents' attitudes towards the features and use of an example expert system for rice disease diagnosis and management(POSOP). It also considers the effect of extension agents' personality traits and intelligence on their attitudes towards its use, and the agents' perception of control over using it. Answers to these questions lead to developing better systems and to increasing their adoption. Using structural equation modelling, two models - the extension agents' perceived usefulness of POSOP, and their attitude towards the use of POSOP, were developed (Models ATU and ATP). Two of POSOP's features (its value as a decision support tool, and its user interface), two personality traits (Openness (0) and Extraversion (E)), and the agents' intelligence, proved to be significant, and were evaluated. The agents' attitude towards POSOP's value had a substantial impact on their perceived usefulness and their attitude towards using it, and thus their intention to use POSOP. Their attitude towards POSOP's user interface also had an impact on their attitude towards its perceived usefulness, but had no impact on their attitude towards using it. However, the user interface did contribute to its value. In Model ATU, neither Openness (0) nor Extraversion (E) had an impact on the agents' perceived usefulness indicating POSOP was considered useful regardless of the agents' personality background. However, Extraversion (E) had a negative impact on their intention to use POSOP in Model ATP indicating that 'introverted' agents had a clear intention to use POSOP relative to the 'extroverted' agents. Extension agents' intelligence, in terms of their GPA, had neither an impact on their attitude, nor their subjective norm (expectation of 'others' beliefs), to the use of POSOP. It also had no association with any of the variables in both models. Both models explain and predict that it is likely that the agents will use POSOP. However, the availability of computers, particularly their capacity, are likely to impede its use. Although the agents believed using POSOP would not be difficult, they still believed training would be beneficial. To be a useful decision support tool, the expert system's value and user interface as well as its usefulness and ease of use, are all crucially important to the preliminary acceptance of a system. Most importantly, the users' problems and needs should be assessed and taken into account as a first priority in developing an expert system. Furthermore, the users should be involved in the system development. The results emphasise that the use of an expert system is not only determined by the system's value and its user interface, but also the agents' perceived usefulness, and their attitude towards using it. In addition, the agents' perception of control over using it is also a significant factor. The results suggested improvements to the system's value and its user interface would increase its potential use, and also providing suitable computers, coupled with training, would encourage its use.

Preventing cyberterrorism is becoming a necessity for individuals, organizations, and governments. However, current policies focus on technical and managerial aspects without asking for experts and non-experts values and preferences for preventing cyberterrorism. This study employs value focused thinking and public value forum to bare strategic measures and alternatives for complex policy decisions for preventing cyberterrorism. The strategic measures and alternatives are per socio-technical process.

This project revolves around Small Histories, an online web-based software system for the uploading and sharing of life stories: http://www.smallhistories.com. I created Small Histories to explore the ways in which the internet can facilitate the urge to tell, share and compare one’s personal history and, by doing so, generate an online network of interlinked personal narratives connected to historical times, events and places. The project originated with a personal event: the tracing of my biological Israeli father in 1997 and my subsequent explorations of my Israeli and German family histories. The stories I encountered in these explorations differed, depending on who was telling them. The Small Histories system was a response to the potential of the burgeoning internet to represent such differing viewpoints, and to generate new forms of encounters with the past. Since then the system has developed in tandem with the internet, especially the explosive growth over recent years of what has been called social software. Conceptually, this project explores the fast-evolving social internet as a setting for auto/biographical narrative practice and how this overlaps with and changes accepted notions of performance, community formation, identity construction and acts of memory. As a framework for these investigations, I propose that the internet is a catalyst without precedent for the production of performances of reconstruction, where fragments of the past are dug up, collected, assembled and presented as an imaginative reconstruction of ‘what used to be’, in an attempt to re-establish a lost sense of roots, identity and belonging; a coherent narrative of identity in an era of fragmentation.

Personal document management is the activity of managing a collection of digital documents performed by the owner of the documents, and consists of creation/acquisition, organisation, finding and maintenance. Document management is a pervasive aspect of digital work, but has received relatively little attention from researchers. The hierarchical file system used by most people to manage their documents has not conceptually changed in decades. Although revolutionary prototypes have been developed, these have not been grounded in a thorough understanding of document management behaviour and therefore have not resulted in significant changes to document management interfaces. Improvements in understanding document management can result in productivity gains for knowledge workers, and since document management is such a common activity, small improvements can deliver large gains. The aim of this research was to understand how people manage their personal document collections and to develop guidelines for the development of tools to support personal document management. A field study was conducted that included interviews, a survey and file system snapshot. The interviews were conducted with ten participants to investigate their document management strategies, structures and struggles. In addition to qualitative analysis of semi-structured interviews, a novel investigation technique was developed in the form of a file system snapshot which collects information about document structures and derives a number of metrics which describe the document structure. A survey was also conducted, consisting of a questionnaire and a file system snapshot, which enabled the findings of the field study to be validated, and to collect information from a greater number of participants. The results of this research culminated in (1) development of a conceptual framework highlighting the key personal document management attitudes, behaviours and concerns; (2) model of basic operations that any document management system needs to provide; (3) identification of piling, filing and structuring as three key document management strategies; (4) guidelines for the development of user interfaces to support document management, including specific guidelines for each document management strategy. These contributions both improve knowledge of personal document management on which future research can build, and provide practical advice to document management system designers which should result in the development of more usable system.

Throughout life, we continuously accumulate data, information and knowledge. The ability to recall much of this accumulated knowledge commonly deteriorates with time, though some forms part of what is referred to as tacit knowledge. In the context of education, students access and interact with a teacher’s knowledge in order to create their own, and may have their own data, information and knowledge that could be added to teacher’s knowledge for everyone’s benefit. The realization that students can contribute to enhancing personal knowledge is an important cornerstone in developing a mentor (teacher, tutor and facilitator) focused knowledge system. The research presented in this thesis discusses an integrated framework that manages an individual’s personal data, information and knowledge and enables it to be enhanced by others, in the context of a blended teaching and learning environment. Existing related models, structures, systems and current practices are discussed. The core outcomes of this thesis include: • the virtualMe framework that can be utilized when developing Web based teaching and learning systems; • the sniplet content model that can be used as the basis for sharing information and knowledge; • an annotation framework used to manage knowledge acquisition; and • a multimedia object (MMO) model that: o allows for related media artefacts to be intuitively grouped in a logical collection; o includes a meta-data schema that encompasses other metadata structures, and manages context and referencing; and o includes a model allowing component parts to be reaggregated if they are separated. The virtualMe framework provides the ability to retain context while transferring the content from one person to another and from one place to another. The framework retains the content’s original context and then allows the receiver to customise the content and metadata so that the content becomes that person’s knowledge. A mechanism has been created for such contextual transfer of content (context retained by the metadata).

The monograph reflects the problems of Russian psycholinguistics from the moment of its inception in Russia to the present day and presents its main directions that are currently developing. In addition, theoretical developments and practical results obtained in the framework of different directions and research centers are described in a concise form. The task of the book is to reflect, as far as it is possible in one edition, firstly, the history of the formation of Russian psycholinguistics; secondly, its methodology and developed methods; thirdly, the results obtained in different research centers and directions in different regions of Russia; fourthly, to outline the main directions of the further development of Russian psycholinguistics. There is no doubt that in the theoretical, methodological and applied aspects, the main problems and the results of their development by Russian psycholinguistics have no analogues in world linguistics and psycholinguistics, or are represented by completely original concepts and methods. We have tried to show this uniqueness of the problematics and the methodological equipment of Russian psycholinguistics in this book. The main role in the formation of Russian psycholinguistics was played by the Moscow psycholinguistic school of A.A. Leontyev. It still defines the main directions of Russian psycholinguistics. Russian psycholinguistics (the theory of speech activity - TSA) is based on the achievements of Russian psychology: a cultural-historical approach to the analysis of mental phenomena L.S. Vygotsky and the system-activity approach of A.N. Leontyev. Moscow is the most "psycholinguistic region" of Russia - INL RAS, Moscow State University, Moscow State Linguistic University, RUDN, Moscow State Pedagogical University, Moscow State Pedagogical University, Sechenov University, Moscow State University and other Moscow universities. Saint Petersburg psycholinguists have significant achievements, especially in the study of neurolinguistic problems, ontolinguistics. The most important feature of Russian psycholinguistics is the widespread development of psycholinguistics in the regions, the emergence of recognized psycholinguistic research centers - St. Petersburg, Tver, Saratov, Perm, Ufa, Omsk, Novosibirsk, Voronezh, Yekaterinburg, Kursk, Chelyabinsk; psycholinguistics is represented in Cherepovets, Ivanovo, Volgograd, Vyatka, Kaluga, Krasnoyarsk, Irkutsk, Vladivostok, Abakan, Maikop, Barnaul, Ulan-Ude, Yakutsk, Syktyvkar, Armavir and other cities; in Belarus - Minsk, in Ukraine - Lvov, Chernivtsi, Kharkov, in the DPR - Donetsk, in Kazakhstan - Alma-Ata, Chimkent. Our researchers work in Bulgaria, Hungary, Vietnam, China, France, Switzerland. There are Russian psycholinguists in Canada, USA, Israel, Austria and a number of other countries. All scientists from these regions and countries have contributed to the development of Russian psycholinguistics, to the development of psycholinguistic theory and methods of psycholinguistic research. Their participation has not been forgotten. We tried to present the main Russian psycholinguists in the Appendix - in the sections "Scientometrics", "Monographs and Manuals" and "Dissertations", even if there is no information about them in the Electronic Library and RSCI. The principles of including scientists in the scientometric list are presented in the Appendix. Our analysis of the content of the resulting monograph on psycholinguistic research in Russia allows us to draw preliminary conclusions about some of the distinctive features of Russian psycholinguistics: 1. cultural-historical approach to the analysis of mental phenomena of L.S.Vygotsky and the system-activity approach of A.N. Leontiev as methodological basis of Russian psycholinguistics; 2. theoretical nature of psycholinguistic research as a characteristic feature of Russian psycholinguistics. Our psycholinguistics has always built a general theory of the generation and perception of speech, mental vocabulary, linked specific research with the problems of ontogenesis, the relationship between language and thinking; 3. psycholinguistic studies of speech communication as an important subject of psycholinguistics; 4. attention to the psycholinguistic analysis of the text and the development of methods for such analysis; 5. active research into the ontogenesis of linguistic ability; 6. investigation of linguistic consciousness as one of the important subjects of psycholinguistics; 7. understanding the need to create associative dictionaries of different types as the most important practical task of psycholinguistics; 8. widespread use of psycholinguistic methods for applied purposes, active development of applied psycholinguistics. The review of the main directions of development of Russian psycholinguistics, carried out in this monograph, clearly shows that the direction associated with the study of linguistic consciousness is currently being most intensively developed in modern Russian psycholinguistics. As the practice of many years of psycholinguistic research in our country shows, the subject of study of psycholinguists is precisely linguistic consciousness - this is a part of human consciousness that is responsible for generating, understanding speech and keeping language in consciousness. Associative experiments are the core of most psycholinguistic techniques and are important both theoretically and practically. The following main areas of practical application of the results of associative experiments can be outlined. 1. Education. Associative experiments are the basis for constructing Mind Maps, one of the most promising tools for systematizing knowledge, assessing the quality, volume and nature of declarative knowledge (and using special techniques and skills). Methods based on smart maps are already widely used in teaching foreign languages, fast and deep immersion in various subject areas. 2. Information search, search optimization. The results of associative experiments can significantly improve the quality of information retrieval, its efficiency, as well as adaptability for a specific person (social group). When promoting sites (promoting them in search results), an associative experiment allows you to increase and improve the quality of the audience reached. 3. Translation studies, translation automation. An associative experiment can significantly improve the quality of translation, take into account intercultural and other social characteristics of native speakers. 4. Computational linguistics and automatic word processing. The results of associative experiments make it possible to reveal the features of a person's linguistic consciousness and contribute to the development of automatic text processing systems in a wide range of applications of natural language interfaces of computer programs and robotic solutions. 5. Advertising. The use of data on associations for specific words, slogans and texts allows you to predict and improve advertising texts. 6. Social relationships. The analysis of texts using the data of associative experiments makes it possible to assess the tonality of messages (negative / positive moods, aggression and other characteristics) based on user comments on the Internet and social networks, in the press in various projections (by individuals, events, organizations, etc.) from various social angles, to diagnose the formation of extremist ideas. 7. Content control and protection of personal data. Associative experiments improve the quality of content detection and filtering by identifying associative fields in areas subject to age restrictions, personal information, tobacco and alcohol advertising, incitement to ethnic hatred, etc. 8. Gender and individual differences. The data of associative experiments can be used to compare the reactions (and, in general, other features of thinking) between men and women, different social and age groups, representatives of different regions. The directions for the further development of Russian psycholinguistics from the standpoint of the current state of psycholinguistic science in the country are seen by us, first of all:  in the development of research in various areas of linguistic consciousness, which will contribute to the development of an important concept of speech as a verbal model of non-linguistic consciousness, in which knowledge revealed by social practice and assigned by each member of society during its inculturation is consolidated for society and on its behalf;  in the expansion of the problematics, which is formed under the influence of the growing intercultural communication in the world community, which inevitably involves the speech behavior of natural and artificial bilinguals in the new object area of psycholinguistics;  in using the capabilities of national linguistic corpora in the interests of researchers studying the functioning of non-linguistic and linguistic consciousness in speech processes;  in expanding research on the semantic perception of multimodal texts, the scope of which has greatly expanded in connection with the spread of the Internet as a means of communication in the life of modern society;  in the inclusion of the problems of professional communication and professional activity in the object area of psycholinguistics in connection with the introduction of information technologies into public practice, entailing the emergence of new professions and new features of the professional ethos;  in the further development of the theory of the mental lexicon (identifying the role of different types of knowledge in its formation and functioning, the role of the word as a unit of the mental lexicon in the formation of the image of the world, as well as the role of the natural / internal metalanguage and its specificity in speech activity);  in the broad development of associative lexicography, which will meet the most diverse needs of society and cognitive sciences. The development of associative lexicography may lead to the emergence of such disciplines as associative typology, associative variantology, associative axiology;  in expanding the spheres of applied use of psycholinguistics in social sciences, sociology, semasiology, lexicography, in the study of the brain, linguodidactics, medicine, etc. This book is a kind of summarizing result of the development of Russian psycholinguistics today. Each section provides a bibliography of studies on the relevant issue. The Appendix contains the scientometrics of leading Russian psycholinguists, basic monographs, psycholinguistic textbooks and dissertations defended in psycholinguistics. The content of the publications presented here is convincing evidence of the relevance of psycholinguistic topics and the effectiveness of the development of psycholinguistic problems in Russia.

In this chapter, Big Data provide large-volume, complex structure, heterogeneous and irregular growing data sets include multiple and autonomous different resources. In this chapter, With the growing improvement of networking sites, image information storing capacity become big issue too, Big Data concept are most growing expanding in all technical area and knowledge engineering domains, including physical, medical and paramedical sciences. Here a data-driven method consist demand-driven aggregation of information and knowledge mining and analysis, user interest prototyping, security and privacy aspects has been presented.

Before the internet, libraries were the best source of information available. The library was not only a repository of knowledge; it was also a place to hang out and study. However, the internet and the ever-expanding digital gateway have resulted in the rise and prevalence of information on our phones, tablets, or our laptops. Some people have argued the place of LIS in the digital era and have concluded that there is no need of heading down to the library anymore for information. It is important to clear up such misconceptions. People do still use libraries to find out information. The researchers organized the chapter in the following way: introduction and background, history and development of LIS, overview of library and information science (LIS), librarianship past and present, trends and issues in library and information science curriculum, significance of LIS in the digital era, challenges of LIS profession in the digital era, recommendations, conclusion, and references.

While most organizations have deployed knowledge management systems (KMS), only a handful have been able to leverage these investments. Existing knowledge management (KM) research offered valuable insights on how to introduce KMS in a sense of innovation-diffusion, yet little guidance has been offered to KMS developers who need to decide on functionalities of a tool they are to introduce in a particular organizational setting. The goal of this paper is to propose theoretical background for design of IS that successfully support and enable decision making, which is seen as the ultimate form of knowledge creation and utilization. By using principles of the design science, design profiles proposed build upon works from organization and IS sciences, primarily the evolutionary information-processing theory of knowledge creation (Li & Kettinger, 2006) and the task technology fit theory (Zigurs & Buckland, 1998), the latter being amended for particularities of the KM environment. Proposed fit profiles suggest that one-size-fits-all approaches do not work and that organizations must take, in contrast with suggestions of extant literature, a segmented approach to KM activities and fitting IT support.

The constant demand for complex applications, the ever increasing complexity and size of software systems, and the inherently complicated nature of the information drive the needs for developing radically new approaches for information representation. This drive is leading to creation of new and exciting interdisciplinary fields that investigate convergence of software science and intelligence science, as well as computational sciences and their applications. This survey article discusses the new paradigm of the algorithmic models of intelligence, based on the adaptive hierarchical model of computation, and presents the algorithms and applications utilizing this paradigm in data-intensive, collaborative environment. Examples from the various areas include references to adaptive paradigm in biometric technologies, evolutionary computing, swarm intelligence, robotics, networks, e-learning, knowledge representation and information system design. Special topics related to adaptive models design and geometric computing are also included in the survey.

Data Mining (DM) is a rapidly expanding field in many disciplines, and it is greatly inspiring to analyze massive data types, which includes geospatial, image and other forms of data sets. Such the fast growths of data characterized as high volume, velocity, variety, variability, value and others that collected and generated from various sources that are too complex and big to capturing, storing, and analyzing and challenging to traditional tools. The SDM is, therefore, the process of searching and discovering valuable information and knowledge in large volumes of spatial data, which draws basic principles from concepts in databases, machine learning, statistics, pattern recognition and 'soft' computing. Using DM techniques enables a more efficient use of the data warehouse. It is thus becoming an emerging research field in Geosciences because of the increasing amount of data, which lead to new promising applications. The integral SDM in which we focused in this chapter is the inference to geospatial and GIS data.

With the fast growth of big data, IoT, industrial internet, and intelligent control technology, digital twins are extensively employed as a novel form of technology in many aspects of life. Digital twins have emerged as the ideal connection between the real world of manufacturing and the digital virtual world, as well as an effective technological way of realizing the interaction and cooperation of the real and information worlds. Digital twins rely on knowledge mechanisms, digitization, and other technologies to build digital models. They use IoT and other technologies to convert data and information in the physical world into general data. Its necessity is mainly reflected in the massive data processing and system self-optimization in the digital twin ecosystem, so that the digital twin ecosystem is orderly and intelligent cloud travel, and it is the central brain of the digital twin ecosystem. The rapidly expanding digital twin market indicates that this technology is already in use across many industries and is demanded to rise at an estimated USD 48.2 billion in 2026.

Nowadays the Web comprises a significant advance in technology, and the rapidity of its acceptance has been remarkable. It is a powerful tool that has changed the way of conducting business, providing companies and customers with limitless options and opportunities. Online catalogs, 24/7 service availability, a cut down in transaction costs, reduction of customer service time, personalized features, and absence of paper and personalization features are only a few of the advantages. Companies, in an effort to stay competitive in the new global economy, are increasingly expanding their activities to this new communication channel, which features as a factor of major profit potential. As a direct consequence of e-commerce spreading, we are witnessing the emergence of a new consumer type, the online consumer or e-customer that uses the Internet for purchasing products/services (Solomon, 2001). The online consumer is empowered with new, exciting capabilities: he can search globally for products/services, compare available options, find additional information, read the opinion of other people who have bought the product/service, or proceed with the transaction. All these options are available from his office or home and can be used conveniently and fast, while all alternative e-shops are only a few clicks away. As in the case of trivial customers, ensuring e-customer satisfaction is not a simple task. To a certain degree, e-customers (expect to) behave online similarly to how they behave off-line (in traditional real-life shops); but in order to fully understand their behavior, one should explore issues like the reasons why people use the Internet for their purchases, the benefits/drawbacks of online buying, and the identification of clusters of customers who share common attitudes, behavior, and preferences online (Blackwell, Miniard, & Engel, 2000). According to Seybold and Marshak (1998), consumers prefer the Internet because it offers easier and faster shopping. Convenience, timesaving, moneysaving, greater options, and fun are among the top reasons, and this kind of knowledge is of great value for dictating efficient e-marketing strategies and motivating e-commerce use with twofold objective: turn non-shoppers into shoppers and increase shopping of current shoppers. This article presents the overall consumer purchase decision cycle and investigates the issues that affect Web users, from selecting a specific e-shop to the delivery of the product and the overall assessment of the shopping experience. This process has been divided into 13 states referring to customer behavior: outside the e-shop, inside the e-shop, and after sales. Special focus is set on identifying the potential abandonment factors thus leading to practical guidelines for all those whose decisions and objectives affect the online shopping experience (e-shop owners, marketing specialists, Web site designers, and developers).

The constant demand for complex applications, the ever increasing complexity and size of software systems, and the inherently complicated nature of the information drive the needs for developing radically new approaches for information representation. This drive is leading to creation of new and exciting interdisciplinary fields that investigate convergence of software science and intelligence science, as well as computational sciences and their applications. This survey article discusses the new paradigm of the algorithmic models of intelligence, based on the adaptive hierarchical model of computation, and presents the algorithms and applications utilizing this paradigm in data-intensive, collaborative environment. Examples from the various areas include references to adaptive paradigm in biometric technologies, evolutionary computing, swarm intelligence, robotics, networks, e-learning, knowledge representation and information system design. Special topics related to adaptive models design and geometric computing are also included in the survey.

Development and progress mainly depends on education and its solid dissemination. Technologies as well as engineering solutions are important for the business and corporate houses. In this context, educational initiatives and programs play a vital role. Developing countries are suffering from many problems and therefore fostering new academic innovation and researches on economic development in today's context. Information Technologies and management science are important for solid business solutions. Therefore, education and knowledge dissemination play an important and valuable role. In many developing countries, gaps between industrial needs and the availability of skilled labor are limited. Information Sciences and Computing are the most valuable areas of study in today's knowledge world. The components, subsets, and subfields of Information Sciences and Technology are rapidly emerging worldwide. Among the emerging and popular areas, a few include Cloud Computing, Green Computing, Green Systems, Big-Data Science, Internet, Business Analytics, and Business Intelligence. Developing countries (like China, Colombia, Malaysia, Mauritius, India, Brazil, South Africa) depend in many ways on knowledge dissemination and solid manpower for their development. Thus, there is an urgent need to introduce such programs and the majority of these programs have been proposed here. Information Science and Technology (IST) with programs such as Bachelors, Masters, and Doctoral Degrees have been listed here with academic and industrial contexts. This article highlights these programs with proper SWOT analysis.

Academic computing programs often want to keep pace with technological changes by frequently updating their program contents. These program changes are often reactionary and lack uniform standards. Thus some of the changes are often rolled back and, as a result, face additional changes shortly after their implementation. A helpful strategy in computer program updates is to utilize a standard curriculum to gauge and benchmark the program. This paper compares the content of two technology programs with a standard curriculum developed by the Association of Computing Machinery (ACM) and other organizations including, AIS, AITP, IEEE and ABET-CAC. The paper examines the content of two technology programs: The T echnology Support and Training program (TST) at Eberly College of Business - Indiana University of Pennsylvania (IUP), and the Computer Information Systems (CIS) and Information Sciences (IS) programs in the School of Communications and Information Technology at Robert Morris University (RMU). It then compares the content of both programs with the Computing Curricula Information - Information T echnology Volume (IT2005) Body of Knowledge.

It is known that human influential factors (HIFs, e.g., sense of presence/immersion; attention, stress, and engagement levels; fun factors) play a crucial role in the gamer’s perceived immersive media experience [1]. To this end, recent research has explored the use of affective brain-/body-computer interfaces to monitor such factors [2, 3]. Typically, studies have been conducted in laboratory settings and have relied on research-grade neurophysiological sensors. Transferring the obtained knowledge to everyday settings, however, is not straightforward, especially since it requires cumbersome and long preparation times (e.g., placing electroencephalography caps, gel, test impedances) which could be overwhelming for gamers. To overcome this limitation, we have recently developed an instrumented “plug-and-play” virtual reality head-mounted display (termed iHMD) [4] which directly embeds a number of dry ExG sensors (electroencephalography, EEG; electrocardiography, ECG; electromyography, EMG; and electrooculography, EoG) into the HMD. A portable bioamplifier is used to collect, stream, and/or store the biosignals in real-time. Moreover, a software suite has been developed to automatically measure signal quality [5], enhance the biosignals [6, 7, 8], infer breathing rate from the ECG [9], and extract relevant HIFs from the post-processed signals [3, 10, 11]. More recently, we have also developed companion software to allow for use and monitoring of the device at the gamer’s home with minimal experimental supervision, hence exploring its potential use truly “in the wild”. The iHMD, VR controllers, and a laptop, along with a copy of the Half-Life: Alyx videogame, were dropped off at the homes of 10 gamers who consented to participate in the study. All public health COVID-19 protocols were followed, including sanitizing the iHMD in a UV-C light chamber and with sanitizing wipes 48h prior to dropping the equipment off. Instructions on how to set up the equipment and the game, as well as a google form with a multi-part questionnaire [12] to be answered after the game were provided via videoconference. The researcher remained available remotely in case any participant questions arose, but otherwise, interventions were minimal. Participants were asked to play the game for around one hour and none of the participants reported cybersickness. This paper details the obtained results from this study and shows the potential of measuring HIFs from ExG signals collected “in the wild,” as well as their use in remote gaming experience monitoring. In particular, we will show the potential of measuring gamer engagement and sense of presence from the collected signals and their influence on overall experience. The next steps will be to use these signals and inferred HIFs to adjust the game in real-time, thus maximizing the experience for each individual gamer.References[1] Perkis, A., et al, 2020. QUALINET white paper on definitions of immersive media experience (IMEx). arXiv preprint arXiv:2007.07032.[2] Gupta, R., et al, 2016. Using affective BCIs to characterize human influential factors for speech QoE perception modelling. Human-centric Computing and Information Sciences, 6(1):1-19.[3] Clerico, A., et al, 2016, Biometrics and classifier fusion to predict the fun-factor in video gaming. In IEEE Conf Comp Intell and Games (pp. 1-8).[4] Cassani, R., et al 2020. Neural interface instrumented virtual reality headsets: Toward next-generation immersive applications. IEEE SMC Mag, 6(3):20-28.[5] Tobon, D. et al, 2014. MS-QI: A modulation spectrum-based ECG quality index for telehealth applications. IEEE TBE, 63(8):1613-1622.[6] Tobón, D. and Falk, T.H., 2016. Adaptive spectro-temporal filtering for electrocardiogram signal enhancement. IEEE JBHI, 22(2):421-428.[7] dos Santos, E., et al, 2020. Improved motor imagery BCI performance via adaptive modulation filtering and two-stage classification. Biomed Signal Proc Control, Vol. 57.[8] Rosanne, O., et al, 2021. Adaptive filtering for improved EEG-based mental workload assessment of ambulant users. Front. Neurosci, Vol.15.[9] Cassani, R., et al, 2018. Respiration rate estimation from noisy electrocardiograms based on modulation spectral analysis. CMBES Proc., Vol. 41.[10] Tiwari, A. and Falk, T.H., 2021. New Measures of Heart Rate Variability based on Subband Tachogram Complexity and Spectral Characteristics for Improved Stress and Anxiety Monitoring in Highly Ecological Settings. Front Signal Proc, Vol.7.[11] Moinnereau, M.A., 2020, Saccadic Eye Movement Classification Using ExG Sensors Embedded into a Virtual Reality Headset. In IEEE Conf SMC, pp. 3494-3498.[12] Tcha-Tokey, K., et al, 2016. Proposition and Validation of a Questionnaire to Measure the User Experience in Immersive Virtual Environments. Intl J Virtual Reality, 16:33-48.

Qubit by Qubit’s Quantum Computing Summer School is a four-week summer course for high school and university students in their first or second year of studies. The aim of the summer school is to introduce the field of Quantum Information Sciences and Engineering (QISE), specifically quantum computing. Through the course, students learn about quantum mechanics, quantum computation and information (quantum gates, circuits, and algorithms and protocols, including Grover’s Algorithm and Quantum Key Distribution), applications of quantum computing, and quantum hardware. Students also learn how to program in Qiskit and basic mathematics for quantum, including matrices and vectors. The Quantum Computing Summer School program enrolled a diverse population of high school and undergraduate students with 48% of participants identifying at female or non-binary, 20% of students identifying as Hispanic, 17% identifying as Black, and 38% identifying as Asian. The program substantially increased participants’ knowledge about quantum computing, as exhibited by large gains on a technical assessment that was administered at the beginning and end of the program. On a survey of student motivation, students in the program showed a statistically significant increase in their expectancy of being successful in quantum computing and valuing quantum computing. From the beginning of the program to the end of the program, there was a statistically significant increase in students’ reported sense of belonging in quantum. Participation in the program increased students’ interest in pursuing additional coursework and careers in STEM generally and in quantum specifically.