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This paper reports on the perceptions of Spanish academic libraries regarding Open Science (OS). OS is irrupting into academia and academic librarians need to support researchers. On the other side, researchers need to be ready to change their scientific behaviour in relation to publications and research data. We conducted a focus group with 8 academic librarians. We also sent a survey to (N = 67) academic libraries, obtaining a response rate of 71.6%. In the survey, we asked for drivers and constraints for OS services as well as for any training taking place. Our results show that facilitators are the system relationships (SD = 4.74) and internal promotion of systems relationships (SD = 4.54). In relation to the level of knowledge of OS, both researchers (SD = 3.27) and librarians have a high level in terms of the OA area (SD = 4.15) but little development of the rest of the components of OS. On the other hand, in relation to training librarians, results indicated that OA (SD = 4.79), Open Data (SD = 4.79) and new evaluation models (SD = 4.79) should be part of the training for researchers. The results of the focus group reinforce some of the indicators mentioned. We conclude that academic libraries may train researchers in OS through the acquisition of new skills and trainers-training and with the strategic support of the university. We argue that academic incentives and a change in research accreditation are also needed to shift researchers' perceptions in relation to OS. [ABSTRACT FROM AUTHOR]

This paper discusses the organization of students' internship in new circumstances caused by COVID-19 pandemic. The focus of the research is on the IT companies in eastern part of Croatia and their perspective on how they managed students' internship during and after the lockdown. Some of these IT companies successfully cooperate with the Department of Information Sciences, Faculty of Humanities and Social Sciences at the University of Osijek. Since 2015 the Department enrolls students in graduate study of Information Technology track. From that time students used to do their internship and later find employment in IT companies in the region. The well based cooperation with local IT companies was interrupted in 2020 by the COVID-19 lockdown and semi-lockdown. In such a situation, teachers and IT companies' managers have been trying to find out the proper ways in which students could fulfill their tasks via online or hybrid mode. To learn more about the experience from the perspective of IT companies, we interviewed 18 of them. The paper points out the observed advantages and disadvantages as well as suggestions for setting a framework for future internship programs. Employers are thinking about continuing to perform online or hybrid internships, and it is clear to them that one of the answers is well defined and regulated model of internships in the online environment. [ABSTRACT FROM AUTHOR]

With the rapid development of information science and social networks, the Internet has accumulated various data containing valuable information and topics. The topic model has become one of the primary semantic modeling and classification methods. It has been widely studied in academia and industry. However, most topic models only focus on long texts and often suffer from semantic sparsity problems. The sparse, short text content and irregular data have brought major challenges to the application of topic models in semantic modeling and topic discovery. To overcome these challenges, researchers have explored topic models and achieved excellent results. However, most of the current topic models are applicable to a specific model task. The majority of current reviews ignore the whole-cycle perspective and framework. It brings great challenges for novices to learn topic models. To deal with the above challenges, we investigate more than a hundred papers on topic models and summarize the research progress on the entire topic model process, including theory, method, datasets, and evaluation indicator. In addition, we also analyzed the statistical data results of the topic model through experiments and introduced its applications in different fields. The paper provides a whole-cycle learning path for novices. It encourages researchers to give more attention to the topic model algorithm and the theory itself without paying extra attention to understanding the relevant datasets, evaluation methods and latest progress. [ABSTRACT FROM AUTHOR]

Big data is changing our lives and the way we understand the world, as well as the operational patterns of business and social organizations. Fully understanding the value of data and knowing how to use big data to provide a basis for business decision-making has gradually become the most basic thinking that business organizations should possess in the era of big data. Under the thinking mode of data-driven decision-making, many information science researchers have discussed the model, architecture, operation mechanism and other aspects of big data competitive intelligence system. At the same time, more and more enterprises, such as IBM, Amazon, Google, Microsoft, Wal Mart, etc., have begun to attach importance to the development and construction of big data competitive intelligence software systems, and have achieved certain results. The enterprise competitive intelligence system evaluation in the context of big data is regarded as multi-attribute decision-making (MADM). In this paper, the Hamy mean (HM) and the power average (PA) are connected with 2-tuple linguistic neutrosophic sets (2TLNSs) to propose the 2-tuple linguistic neutrosophic numbers power HM (2TLNPHM) operator. Then, use the 2TLNPHM operator to handle MADM with 2TLNS. Finally, taking the enterprise competitive intelligence system evaluation in the context of big data as an example, the proposed method is explained. The main contributions of this study are summarized: the establishment of the 2TLNPHM operator; (2) The 2TLNPHM operator was developed to handle MADM with 2TLNS; (3) Through the empirical application of the enterprise competitive intelligence system evaluation, the proposed method is validated; (4) Some comparative studies have shown the rationality of the 2TLNPHM operator. [ABSTRACT FROM AUTHOR]

Education curricula need constant updates in response to job market requirements, which may be influenced by the changing technological environment. In the library and information science (LIS) job market there are dynamics brought about by the Fourth Industrial Revolution (4IR). These dynamics call for LIS schools to reconsider their curricula in line with the job market. The job markets expect the education system to reflect their demands, as they are the primary clients. This study explored the education and training of LIS professionals on digital scholarship in line with the LIS curriculum in higher education institutions of South Africa. This was to enable the development of a framework for incorporating digital scholarship into the LIS curriculum. Wolf's (2007) curriculum development model and an aspect of the customer satisfaction model (Zeithaml et al., 1993) informed the study. The models assisted in producing a framework that can be used to incorporate digital scholarship content into the LIS curriculum in South Africa. The framework suggests that when developing digital scholarship, consultation with relevant stakeholders both internal and external should be considered. Relevant infrastructure and resources should also be in place when developing a digital scholarship curriculum. The relevant infrastructure should include the 4IR-driven infrastructure such as smart sensors, three-dimension (3D) modeling, and cybersecurity tools, among others. Relevant documentation such as resources in the form of policies, course outlines, and other curriculum-related documents should also be consulted. This model, if adopted, could assist LIS schools in developing a curriculum that is driven by digital scholarship, leading to the production of LIS graduates that meet the requirements of the current LIS job market. [ABSTRACT FROM AUTHOR]

This paper summarizes what is known about everyday health information seeking and use, as supported by empirical research largely conducted during the 1980s and 1990's. It draws implications for research and system design applicable to the U.S. National Library of Medicine's (NLM) MedlinePlus web portal and data base of consumer health information. Its focus is on the two academic disciplines that bear most directly on information seeking and use, each with different perspectives. Communication (COMM) whose orientation is the study of messaging and the effective transmission of information, and Library and Information Science (LIS) whose focus is on meeting user information needs. Although there is very little overlapping literature, Dr. Dervin's career was spent working across these two research genres. She is known most prominently for her Sense-Making Methodology. Dr. Dervin supports the view that there are more commonalities than differences between the two disciplines, and that research focusing on the commonalities provides a better opportunity for accounting for more variance in human information seeking than the highly compartmentalized approaches that dominate the study of information seeking. Dr. Dervin's first-person review of these literatures was commissioned by NLM in 2001. It remains relevant today both for its critical insights, and as an historical resource. It is published posthumously in 2023 in tribute to Dr. Dervin on her recent passing. [ABSTRACT FROM AUTHOR]

In this mixed methods and multi-phased study, through a multi-round feedback and confirmation process, we established a meaningful approach to developing, revising, and finalizing a competency framework for InterProfessional Informationists (IPI). As an emerging profession, IPI has not yet been established as a formal educational program with a guiding framework. It is important both to the field of practice and to educational programming to develop a competency framework, specifically targeted to IPI, and has been informed/verified through current practice. Our process started with using the initial competency framework developed by Tang and Martin (2019) as the basis, and involved gathering comments from numerous stakeholders, including IPI students and working professionals from relevant communities ranging from health science librarians to library directors, informationists, and LIS scholars and educators. The finalized IPI framework features four levels, six competency areas, and 67 elements, with separate beginner and advanced levels for subject expertise and work practice/culture. By including a variety of voices, this comprehensive framework not only outlines relevant foundational knowledge, skills, and attitudes (KSAs), but also accentuates timely cutting-edge skills and forward-looking elements required of InterProfessional Informationists. [ABSTRACT FROM AUTHOR]

This special issue on race relations and racial inequity in Library and Information Science (LIS) is a response a recent wave of advocacy, activism, and protests. Its explicit purpose is to address the lack of research on race and inequity within our field. The purpose of this contribution to the issue is to substantiate that statement by performing a bibliometric analysis of the last 40 years of LIS scholarship to quantify the amount of attention given to race and racial inequality over that period. We find that despite an important increase in BIPOC-related research in LIS, the numbers remain quite low with approximately 2% of LIS publications containing terms related to racial inequality and BIPOC communities, and this research also tends to be less cited than the average LIS papers in the same area. We also find that this research is present in several areas of the field, although unevenly distributed across them. The trends presented in this paper may help when discussing sensitive issues regarding systematic discrimination, help create and sustain momentum towards change, and address the persistent lack of diverse perspectives and approaches across LIS scholarship and practice. [ABSTRACT FROM AUTHOR]

Using the Conway model of data science education as a guide, this paper introduces a model for undergraduate data science education for information schools. The core idea of the suggested model is that data science programs in information schools are unique due to their particular substantive expertise, which includes data management, information behavior, and ethics. This paper also suggests that, to create a data science program within an information school, it may be useful to expand curriculums by adding programming, statistics, and machine learning requirements. [ABSTRACT FROM AUTHOR]

The study presented in this paper investigates LIS doctoral students' perceptions and experiences about the supervision during their doctoral experience, with special emphasis on the qualities of good supervisors and doctoral students. Data were collected through an online survey and follow-up semi-structured interviews with doctoral students from Croatia's three state universities offering a doctorate in LIS. A total of 60 respondents participated in a quantitative study, and 13 respondents were interviewed. The survey results show that doctoral students tend to prefer formally regulated supervisory relationships whereas supervisors and students have unambiguous and clear understanding of their roles and responsibilities. The findings also reveal that doctoral students seek support in the following areas: research, methodology, emotional support and administrative procedures. Interview participants suggest that a successful supervisory relationship could be facilitated by adequate training, both for supervisors and students. Large majority of survey respondents think that four main characteristics of good supervisors are the following: having time for the student, providing students with timely and constructive feedback, setting research goals and timeline together and helping students become independent in scientific work. Respondents agree that doctoral students, in order to be successful in their study, must be internally motivated and well informed about the chosen study program, they must attend to their responsibilities in a timely manner, meet physically with the supervisor and work toward achieving scholarly independence. The findings of this study can contribute toward better understanding of supervisory relationship at doctoral level, in particular in Croatian LIS academic community, and development of guidelines for successful supervision based on the first hand experience of doctoral students. [ABSTRACT FROM AUTHOR]

With the rapid development of database and Internet technologies, data collection and storage is possible. It is often impossible to correctly analyze the valuable information contained in the data, and it becomes more difficult to obtain valuable information. Therefore, it faces the status of "rich data and scarce knowledge". Traditional information processing technology can no longer meet the needs of reality. There is an urgent need for more capable and effective information processing skills to help us analyze the information we need from big data and guide us to make the right decisions. Data mining technology is born in the background. Data mining technology is one of the effective methods to solve rich data and improve lack of knowledge. It is also one of the main research topics in the field of information science. Related research and applications have greatly improved people's decision-making ability. It has been recognized as one of the extremes of data research and has a very broad application prospect. Large databases often contain redundant and unnecessary attributes for many search rules, so the ability to remove duplicate attributes can greatly improve the clarity of potential system knowledge and reduce the time complexity of finding rules. At the same time, it enables efficient operation and improved adaptability. Because the structure of the neural network is variable, it has strong self-organization, self-learning, nonlinearity and high fault tolerance, but the ability to express and interpret knowledge is very poor. The network parameters lack physical meaning and learning. Therefore, it has become an inevitable trend to form a fuzzy neural network combining the characteristics of the two. Therefore, exploring the organic combination between rough sets and fuzzy neural networks is undoubtedly of great significance for data mining technology research. This paper proposes a data mining method based on the combination of rough set and fuzzy neural network technology. Using the approximate set to discover the rules of the database rules, the initial structure of the fuzzy neural network is determined, and the training data is used to train the network. Since the fuzzy neural network thus constructed has a good topology of data distribution features from the beginning, the network scale can be greatly reduced and the network training speed can be improved. [ABSTRACT FROM AUTHOR]

Libraries have adapted and are continuing to adapt to the rapidly changing information and data needs of the communities they support. The following paper presents the evolution of Virginia Tech University Libraries, with special attention given to program and service developments in data and information science. The author describes leadership strategies for advancing services, shares stories about developing sustainable, human-centered, and technology-enhanced service infrastructures, and paints a picture of aspirations to enable individuals' success through active campus engagement. The paper will end with an overview of challenges and opportunities for future collaboration within higher education and beyond. [ABSTRACT FROM AUTHOR]

The article provides information on the Libraries and Information Institutions in the Digital Age (LIDA) 2020 to be held in Dubrovnik, Croatia.

In contrast to the considerable coverage of research methods and report writing, relatively little attention has been given in the professional literature to the steps that should be taken and issues which may be borne in mind by a researcher seeking to have his or her work published. By addressing ten broad questions reflecting common concerns, this paper is designed to give a beginner guidance in his or her efforts to publish research in Library and Information Science journals. It deals with such matters as the benefits to be gained from having one's work disseminated in this way, factors that the researcher may wish to consider in determining a journal to target, matters of ethics and etiquette associated with publishing, the structure that may be employed within a paper and the criteria typically used by editors and reviewers when assessing submissions. A sequenced list of significant stages within the publication process and principles for good practice are also presented. The paper concludes with consideration of the qualities and skills that the published author may be expected to demonstrate and isolates instances in which they are applied. [ABSTRACT FROM AUTHOR]

The article offers information on Conceptions of Library and Information Science (CoLIS) 10th conference to be held in University of Ljubljana, Slovenia from June 16-19, 2019. It is mentioned that the conference aims at providing new knowledge on knowledge organization, knowledge management, and library studies. The article also discusses a Doctoral Forum and submission of research papers.

This paper discusses the planning and implementation of Open Badges in library and information science education at Tallinn University in order to foster and personalise student learning. The first part of the paper gives an overview of the concept and nature of Open Badges through a review of literature, the second describes the use of Open Badges in the Study Area of Information Sciences of the School of Digital Technologies at Tallinn University. The course used four types of open badges in the assessment process: basic knowledge badges, advanced knowledge badges, skill based badges and level based badges. Open Badges were directly linked to the learning outcomes and formal grading system of the course. Based on recent experience, it can be said that Open Badges are valuable tools in the assessment process which will give a more holistic picture of educational achievement of the learner. Multiple learning pathways within the course provided learners opportunities to choose their personal learning path according to their personal learning goals, learning style, interests and other preferences. Open Badges also allowed to recognize 'soft skills' or literacies. Open Badges could be also a useful tool to assess students' information literacies in different contexts. [ABSTRACT FROM AUTHOR]

Background: Gait recognition is an emerging biometric technology applied to the mobile environment. With built-in accelerometers, wearable devices are used to recognize user identity according to gait periodic pattern, which shows strong stability and uniqueness property.Objective: The purpose of this study is to build analyzing models to find the change of gait normal and pathological function based on gait features.Methods: This work relies on gait recognition methods. In this paper, the performance of different hybrid filter methods is compared by combining four classical filtering methods. The influence of the abnormal pattern of gait cycle is estimated by standard deviation. The effectiveness of feature matching methods is evaluated by six classical distance discrimination function.Results: The results highlight the stability and invariance of gait periodic pattern. For analyzing models, the best recognition rate is 96.67% with the combination of MF hybrid filter and Correlation distance function in the small sample, and minimal time consumption is 0.038 s. The effectiveness of analyzing models is further analyzed for different practical applications.Conclusions: This study provides evidence for future scientific teams to make decisions on selecting filter methods and discrimination functions which can more efficiently extract gait features and suggest ways to analyze clinical gait pattern. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on topics including algorithms, future and digital rights; discussions on the dystopia and post-reality in social media; and the information on the challenges of Information and Communication Technologies for science.

The article focuses on the interchange between information behavior research and neighboring fields. Topics include the challenges of explaining information behavior to colleagues from the similarities and differences between information behavior research and closely related fields such as user experience, human-computer interaction, and information retrieval; and the need for information behavior researchers to recognize added value they bring to interdisciplinary collaborations.

A complex fuzzy set is a set whose membership values are vectors in the unit circle in the complex plane. To enhance and extend the applicability of complex fuzzy sets, this paper investigates and develops different types of distance measures for complex fuzzy sets. Several distance measures of complex fuzzy sets are introduced. After that, the application of these distances to continuity problems of complex fuzzy operations is given. [ABSTRACT FROM AUTHOR]

Current Research Information Systems (CRISs) offer great opportunities for assessments of institutional research outputs and extraction of useful and actionable knowledge based on various data-analysis techniques. However, many of these opportunities have not been explored in depth, especially in culture-sensitive areas such as gender-based analysis of research productivity and collaboration. In this paper we present GERBER, a network-based methodology and accompanying tool for gender-based analysis of publication data stored in institutional CRISs. GERBER relies on statistically robust techniques applied on weighted co-authorship networks whose nodes are enriched with different types of researcher evaluation metrics. The functionality of GERBER is demonstrated on publication data stored in the institutional CRIS of the Faculty of Sciences, University of Novi Sad, Serbia. The obtained results show that GERBER enables institutional research managers and policy makers to detect gender inequalities and homophily in research productivity and collaboration. Finally, we discuss different possibilities to integrate GERBER with CRISs in order to facilitate continuous gender-based evaluation of researchers. [ABSTRACT FROM AUTHOR]

Background: Disease leaf segmentation in color image is used to explore the disease shape and lesion regions. It is of great significance for pathological diagnosis and pathological research.Objective: This paper proposes a superpixel algorithm using Non-symmetry and Anti-packing Model with Squares (NAMS) for color image segmentation of leaf disease.Methods: First of all, the NAMS model is presented for color leaf disease image representation. The model can segment images asymmetrically and preserve the characteristics of image context. Second, NAMS based superpixel (NAMS superpixel) algorithm is proposed for clustering pixels, which can represent large homogeneous areas by super squares. By this way, the impact of complex background and the data redundancy in image segmentation can be reduced.Results: Experimental results indicate that compared with segmenting the original image directly and manipulating by Simple Linear Iterative Clustering (SLIC) superpixel, the proposed NAMS superpixel performs more excellently in not only saving storage but also adhering to the lesion region edge.Conclusions: The outcome of NAMS superpixel can be regarded as a preprocess procedure for leaf disease region detection since the method can segment the image into superpixel blocks and preserve the lesion area. [ABSTRACT FROM AUTHOR]

Virtual reality (VR) offers potential for teaching and learning, though there seems to be no prior use of VR for teaching library and information science. This paper reports on a project that used VR for teaching library design, specifically for designing a library for customers with physical impairments. A survey and interviews were used to collect data. The results suggest that students prefer using VR to more traditional forms of learning because it makes physical problems seem more real than they would if presented in a book or video. [ABSTRACT FROM AUTHOR]

The aim of this paper is to correct the assertions (3) and (4) of Proposition 5.2 proposed by Alkhazaleh [Journal of Intelligent and Fuzzy Systems 30 (2016) 1087-1098]. Every notions involved are extend to the arbitrary set case in a clear, rigorous, and non-burdensome manner. A counterexample illustrates the flaw of the assertions. We introduce some new notions describing 'subset' of time-neutrosophic soft sets (T-NSSs for short) and 'equal' of T-NSSs, and give some examples and related propositions. Then we use these results to remedy the flaw of the assertions, and to improve the work of Alkhazaleh. [ABSTRACT FROM AUTHOR]

Data-intensive flows deploy a variety of complex data transformations to build information pipelines from data sources to different end users. As data are processed, these workflows generate large intermediate results, typically pipelined from one operator to the following ones. Materializing intermediate results, shared among multiple flows, brings benefits not only in terms of performance but also in resource usage and consistency. Similar ideas have been proposed in the context of data warehouses, which are studied under the materialized view selection problem. With the rise of Big Data systems, new challenges emerge due to new quality metrics captured by service level agreements which must be taken into account. Moreover, the way such results are stored must be reconsidered, as different data layouts can be used to reduce the I/O cost. In this paper, we propose a novel approach for automatic selection of multi-objective materialization of intermediate results in data-intensive flows, which can tackle multiple and conflicting quality objectives. In addition, our approach chooses the optimal storage data format for selected materialized intermediate results based on subsequent access patterns. The experimental results show that our approach provides 40% better average speedup with respect to the current state-of-the-art, as well as an improvement on disk access time of 18% as compared to fixed format solutions. [ABSTRACT FROM AUTHOR]

This paper provides an overview of the continuing evolution of scholarly publishing, leveraged in the last decades by the tremendous potential of Internet technology. It introduces “self-archiving”, the broad term often applied to the electronic publishing of author-supplied documents on the World Wide Web without commercial publisher mediation, and examines its impact on scholarly communication along with the Open Access Movement. The intensity of self-archiving and its pivotal role in scholarly communication is put into perspective through reference to some self-archiving initiatives set in motion in several countries. Finally, the paper concludes by outlining the challenges for information managers in developing the full potential of Open Access. [ABSTRACT FROM AUTHOR]

The Darwin Core vocabulary is widely used to transmit biodiversity data in the form of simple text files. In order to support expression of biodiversity data in the Resource Description Framework (RDF), a guide was created as a non-normative addition to the Darwin Core standard. This paper describes the major issues that were addressed in the creation of the guide, particularly problems related to adapting terms designed to have literal values for use with IRI references. By making it possible to express millions of existing records as RDF, the guide is an important step towards enabling the biodiversity informatics community to participate in broader Linked Data and Semantic Web efforts. [ABSTRACT FROM AUTHOR]

The aim of this paper is to introduce and study the concepts of fuzzifying semipre-θ-neighborhood system of a point, fuzzifying semipre-θ-closure of a set, fuzzifying semipre-θ-interior of a set, fuzzifying semipre-θ-open sets and fuzzifying semipre-θ-closed sets in fuzzifying topological spaces, and investigate some of their basic properties. Also, we present two types of functions in a fuzzifying topological spaces called fuzzifying strong β -irresolute and fuzzifying weak β -irresolute functions. The interrelations of these functions with the parallel existing allied concepts are established. Further, several characterizations of these functions along with different conditions for their existence are obtained. [ABSTRACT FROM AUTHOR]

Investment project assessment is one of the most critical activities in the investment process, which requires a trade-off between multiple attributes exhibiting vagueness and imprecision with the involvement of a group of experts. The multiple attribute group decision-making (MAGDM) method based on trapezoidal interval type-2 fuzzy sets (IT2FSs) is suitable for the decision makers to deal with this problem. However, some shortcomings in the arithmetic operations of trapezoidal IT2FSs, and some of ranking methods in some cases are invalid. In this paper, the arithmetic operations of trapezoidal IT2FSs are redefined, which can overcome some shortcomings of the ones developed in existing literature. And then, a new ranking method of trapezoidal IT2FSs based on the incentre point of fuzzy sets is developed. In order to verify the proposed method, thirteen fuzzy sets are used in comparison with some of the existing methods, and the comparison results demonstrate the superiority of the proposed method. Finally, the proposed method is integrated into the technique for order preference by similarity to the ideal solution (TOPSIS) method and an illustrative example in investment project assessment is presented to evaluate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Background: Video-based face recognition has attracted much attention owning to its wide range of applications such as video surveillance. There are various approaches for facial feature extraction. Feature vectors extracted by these approaches tend to have large dimension and may include redundant information for face representation, which limits the application of methods with high accuracy such as machine learning.Objective: Facial landmarks represent the intrinsic characteristics of human face, which can be utilized to decrease redundant information and reduce the computation complexity. But feature points extracted in each frame of a video are irregular which needed to be aligned.Methods: This paper presents a novel method which is based on facial landmarks and machine learning. We proposed a method to align the feature data into a common co-ordinate frame, and use a robust AdaBoost algorithm for classification.Results: Experiments on the public Honda/UCSD database demonstrate the superior performance of our method to several state-of-the-art approaches. Experiments on Yale database show the sensitivity and specificity of the proposed method.Conclusion: The proposed methods can improve the image-set based recognition performance. [ABSTRACT FROM AUTHOR]

Deep Neural Networks (DNNs) have powerful recognition abilities to classify different objects. Although the models of DNNs can reach very high accuracy even beyond human level, they are regarded as black boxes that are absent of interpretability. In the training process of DNNs, abstract features can be automatically extracted from high-dimensional data, such as images. However, the extracted features are usually mapped into a representation space that is not aligned with human knowledge. In some cases, the interpretability is necessary, e.g. medical diagnoses. For the purpose of aligning the representation space with human knowledge, this paper proposes a kind of DNNs, termed as Conceptual Alignment Deep Neural Networks (CADNNs), which can produce interpretable representations in the hidden layers. In CADNNs, some hidden neurons are selected as conceptual neurons to extract the human-formed concepts, while other hidden neurons, called free neurons, can be trained freely. All hidden neurons will contribute to the final classification results. Experiments demonstrate that the CADNNs can keep up with the accuracy of DNNs, even though CADNNs have extra constraints of conceptual neurons. Experiments also reveal that the free neurons could learn some concepts aligned with human knowledge in some cases. [ABSTRACT FROM AUTHOR]

A pervasive computing environment is characterized by computing capabilities and effective use of smart spaces. Many critical elements of pervasive computing, such as wireless networks are now viably commercial products. Ambient services are known as one of the main types of pervasive information services in which suitable information is presented to the users based on their surrounding geographical environments. Increase in the use of such services may cause service domain overlapping in which many of the users are located in several domains simultaneously. The aim of this paper is to present the best information service composition to such users by considering spatio-temporal contexts and analyses. User's location, direction and speed were regarded as the most effective spatial contexts. Spatio-temporal topological relationships as well as influence ability relation were used to model the topological context. The proposed methodology was implemented in three nested service domains. Based on the results, composition of the proposed services and the period for service update were described as "good" by 75 and 80 percent of the users, respectively. [ABSTRACT FROM AUTHOR]

Presents an update on conferences, seminars and research and development in library and information studies as of June 2003. Aims of the Library and Information Science Education in Asia Seminar in Kuala Lumpur, Malaysia in December 2003; Workshop, program and panel proposals for the scheduled Association of Library and Information Science Educators annual conference in January 2004; Features of the Deep Net search engine technology of the search engine Turbo10.

Concerning the problems that abnormal detection of network security situation is not easy to be operated with high time and spatial complexity, a quantitative method about hypothesis test has been proposed by acquiring a set of observation samples. Firstly, it can generate network security situation by inference rule from Bayesian network. Then, it can detect whether network security situation is abnormal or not by hypothesis test method, which can forecast the trend of network security situation in future. Thus, it can provide a reliable basis for administrators to make decisions and defensive measures. Finally, taking full use of the simulation data, network abnormal detection algorithm of security situation is verified and the results show that the method is correct and feasible. [ABSTRACT FROM AUTHOR]

Management issue incorporates a huge amount of fuzzy information processing, that is exactly representing the essentials of human intelligence in reasoning for managing problems. This paper distinguishes the qualitative (empirical) management versus the quantitative (digital) management and focuses the studies of the latter one and verifies the possibility and necessity of adopting quantitative project management in many real world problems. The theoretical arguments of "Fuzzy-AI model" are presented for dealing with the quantization of uncertain management events, which simulates the intelligence of human being by AI (Artificial Intelligence) technology and quantizes the management solution by fuzzy approach. Several practical examples are presented in this paper as the evidence of the applicability of this model in the project management issues, which provides digital support to decision maker in the management. Finally, the theoretical framework of applying this model in different stages of project management is presented for the purpose of calibrating its application scope. [ABSTRACT FROM AUTHOR]

By reading the titles, abstracts, and keywords of LIS doctoral dissertations in China from 2011–2020 and conducting cluster analysis and network analysis of keywords, this study aims to understand the intelligence structure of LIS doctoral dissertations in China, as well as the disciplines and topics intersecting with LIS. The results indicated that Wuhan University had the highest number of doctoral dissertations among all the selected universities offering LIS doctoral education. Research fields mainly focus on online information behavior and information services. The findings could be because of the development of computer science and information technology in the past decade, which indicates that the research direction of LIS in China follows the trend of time development. [ABSTRACT FROM AUTHOR]

The purpose of this work is to assess the societal value of a Service-Learning (SL) project carried out during the Covid-19 pandemic by the Faculty of Information Science of the Complutense University of Madrid (UCM) in collaboration with two Senior Centers of the City of Madrid. The aim of the project was to support elderly's integration in the online activities carried out during the Covid-19 pandemic and to train them in the use of Information and Communication Technologies (ICT). The analysis of societal value is based on a case study and a varied range of data whose purpose is to provide multiple insights into the experience, emphasizing communicative processes. The results corroborate the educational value of experiential learning for students, although the impact on the community appears limited by the role of consumers of a service that participating elderly ended up playing. The evaluation of the project by the faculty leading the activities was corroborated by the institutional partner and provides evidence of the capacity for societal transformation of higher education institutions. [ABSTRACT FROM AUTHOR]

This paper examines the implications of the continued growth of e-government information, communication, and services for Library and Information Science programs in the United States in light of the development of e-government educational programs and library/government partnerships. The implementation of e-government raises several important challenges and opportunities for information organizations, and the programs and partnerships explored in this paper detail innovative approaches and pressing challenges in pedagogy and practice. Following an overview of e-government and the roles of government information in numerous information organizations, this paper discusses the programs, partnerships, and key lessons they raise for information educators and information professionals. [ABSTRACT FROM AUTHOR]

The paper examines the idea of copyright and how it functions for both digital and non-digital publications. Various different interpretations of copyright and its application are discussed. Ideas such as databases, fair use and exceptions are explored in their relationship to technological measures used to control the use of copyright material. Examples from the CITED, COPYSMART, IMPRIMATUR, and COPICAT projects of the European Union are described briefly. The impact of the latest EU directive on copyright and the information society is explained and the need for co-operative planning and implementation of technical measures throughout the information industry is emphasised. [ABSTRACT FROM AUTHOR]

This paper reviews the history and current situation of postgraduate studies in Librarianship and Information Science (LIS) at the university level in Spain before and after the development of the Bologna Process's European Higher Education Area (EHEA). It contextualizes the historical development of these studies, describing how official postgraduate studies in Librarianship developed in those Spanish universities which had traditionally offered the first-cycle or Bachelor's degree LIS studies and which have instructors in this area. A distinction is made between the official postgraduate offer (which is regulated by Spain's Ministry of Education) and the unofficial offer (which is governed by the separate regulations of each university). It is concluded that the Bologna Process has led to the consolidation of a range of official Master's and Doctorate studies accredited by the ANECA, a government agency that certifies the minimum quality of the courses. However, there has been little renovation of the LIS content that was being taught before the appearance of the EHEA. [ABSTRACT FROM AUTHOR]

In this paper the tolerance soft set relation on a soft set is defined and some examples are given with their matrix representations. Also, pre-class and tolerance class concepts for a given tolerance soft set relation are introduced and some examples related to these definitions are illustrated. Some theoretical results are proved such as every pre-class contained by a tolerance class and intersection of two pre-classes is a pre-class as well. Moreover, a method to find out the tolerance classes and pre-classes by using matrix representation of a tolerance soft set relation is explained with examples. [ABSTRACT FROM AUTHOR]

This paper provides an historical overview of the theoretical antecedents leading to information theory, specifically those useful for understanding and teaching information science and systems. Information may be discussed in a philosophical manner and at the same time be measureable. This notion of information can thus be the subject of philosophical discussion and the ideas about information may be applied rigorously to a wide range of practical applications where processes are studied. Theoretical Information Science and specific Information Science applications may provide tools by which questions such as "when and what information can be produced"? can be answered, as well as how to implement a system to serve a particular commercial or other specific function. These topics are discussed, and philosophical literature that might serve as a prerequisite to learning Information Science is suggested. [ABSTRACT FROM AUTHOR]

Background: Mild cognitive impairment (MCI) is a transitional stage from normal aging to Alzheimer's disease (AD) dementia. It is extremely important to develop criteria that can be used to separate the MCI subjects at imminent risk of conversion to Alzheimer-type dementia from those who would remain stable. We have developed an automatic algorithm for computing a novel measure of hippocampal volumetric integrity (HVI) from structural MRI scans that may be useful for this purpose.Objective: To determine the utility of HVI in classification between stable and progressive MCI patients using the Random Forest classification algorithm.Methods: We used a 16-dimensional feature space including bilateral HVI obtained from baseline and one-year follow-up structural MRI, cognitive tests, and genetic and demographic information to train a Random Forest classifier in a sample of 164 MCI subjects categorized into two groups [progressive (n = 86) or stable (n = 78)] based on future conversion (or lack thereof) of their diagnosis to probable AD.Results: The overall accuracy of classification was estimated to be 82.3% (86.0% sensitivity, 78.2% specificity). The accuracy in women (89.1%) was considerably higher than that in men (78.9%). The prediction accuracy achieved in women is the highest reported in any previous application of machine learning to AD diagnosis in MCI.Conclusion: The method presented in this paper can be used to separate stable MCI patients from those who are at early stages of AD dementia with high accuracy. There may be stronger indicators of imminent AD dementia in women with MCI as compared to men. [ABSTRACT FROM AUTHOR]

The need to map the evolution of trends in any field of activity arises when a large amount of data is available on that activity, thus making impossible a manual exploration of the data in order to understand how the field or the activity is evolving. Topic and trend mapping is a mature field with hundreds of publications on approaches, methods and tools for data collection, analysis, feature extraction and reduction, clustering and visualisation tools and algorithms. Our study aims to map the evolution of topics published by the journal Education for Information. Interdisciplinary Journal on Information Studies (EFI henceforth) which has been in existence since 1983, in order to understand how this journal has evolved and how it is positioned with regard to the field of Library and Information Science to which it belongs. Our study is part of the body of work on topic detection and text mining. Our results showed that the journal displayed a remarkable stability in its editorial policy over more than three decades. With the arrival of its third Editor in Chief in 2018, a shift towards more technologically oriented topics and to specialties from other fields are perceptible such as health information, data science and digital humanities. [ABSTRACT FROM AUTHOR]

Learning the essential concepts and skills of information architecture (IA) has the potential to not only significantly extend the abilities of practicing library and information science (LIS) professionals, but also to evolve their professional identities and envisioned career opportunities. An online course on IA was designed around: the principles of threshold concepts, practical knowledge for the workplace, and professional 'soft' skills, such as collaboration and basic project management. The primary objective for the course was creating experiences for students in which they could discover and engage with critical concepts in IA and to collaborate with their peers to design content-rich and user-centred websites. The learning experiences of two sections of the course (n = 32) were studied, through questionnaires and reflective writings, and analysed thematically. The outcome was that, in learning information architecture concepts, and acquiring and applying the concepts and tools to do information architecture work, the students did more than acquire new professional skillsets; they also evolved in their professional identities. [ABSTRACT FROM AUTHOR]

Presents information on several conferences about information science. Sixth International Society for Knowledge Organization Conference on July 10-13, 2000 in Toronto, Ontario; 2000 Annual Meeting and Conference of the American Association of Law Libraries; Fourth International Conference on Grey Literature on October 4-5, 1999.

A parallel version of the problem of cooperative path-finding (pCPF) is introduced in this paper. The task in CPF is to determine a spatio-temporal plan for each member of a group of agents. Each agent is given its initial location in the environment and its task is to reach the given goal location. Agents must avoid obstacles and must not collide with one another. The environment where agents are moving is modeled as an undirected graph. Agents are placed in vertices and they move along edges. At most one agent is placed in each vertex and at least one vertex remains unoccupied. An agent can only move into a currently unoccupied vertex in the standard version of CPF. In the parallel version, an agent can also move into a vertex being currently vacated by another agent supposing the character of this movement is not cyclic. The optimal pCPF where the task is to find the smallest possible solution of the makespan is particularly studied. The main contribution of this paper is the proof of NP-completeness of the decision version of the optimal pCPF. A reduction of propositional satisfiability (SAT) to the problem is used in the proof. [ABSTRACT FROM AUTHOR]

Fuzzy set theory, soft set theory and rough set theory are powerful mathematical tools for dealing with various types of uncertainty. This paper is devoted to define a broad family of soft fuzzy rough sets, each one of which, called an (I, J)-soft fuzzy rough set, is determined by a pair of border implicators (I, J). Alternatively, it shows that a fuzzy soft set can induce a T-equivalence fuzzy relation which is used to granulate the universe. In particular, we prove that (I, J)-fuzzy soft rough sets in our work are equivalent to (I, J)-fuzzy rough sets of Yao et al. by using a T-equivalence fuzzy relation determined by a fuzzy soft set. Furthermore, basic properties of (I, J)-fuzzy soft rough sets are investigated. Meanwhile, an operator-oriented characterization of (I, J)-fuzzy soft rough sets is proposed. Finally, an example is given to illustrate the approach of present paper. [ABSTRACT FROM AUTHOR]