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Are computer science papers extended after they are published? We have surveyed 200 computer science publications, 100 journal articles, and 100 conference papers, using self-citations to identify potential and actual continuations. We are interested in determining the proportion of papers that do indeed continue, how and when the continuation takes place, and whether any distinctions are found between the journal and conference populations. Despite the implicit assumption of a research line behind each paper, manifest in the ubiquitous 'future research' notes that close many of them, we find that more than 70% of the papers are never continued. [ABSTRACT FROM AUTHOR]

The emergence of new technologies such as AI, machine learning, and so on drives the discussion over human consciousness among researchers from various disciplines, particularly those from philosophy of mind and computer science. This is true since certain academic theories argue that new technologies like those are much more efficient at simulating human tasks. This allows the discussion concerning human consciousness to acquire attention among researchers interested in learning more about human consciousness. As a result, this study provides a bibliometric analysis of human consciousness research from 2000 to 2022 to provide researchers and academics worldwide with an overview of the outcomes and trends in human consciousness research. A textual query on two databases; Scopus (1413 articles), and PubMed (258 papers) using the term "human consciousness" was conducted on 16 August 2022 by collecting 1671 academic works from 2000 to 2022 relating to human consciousness research for in-depth study. Bibliometric analyses were performed using Rstudio software version 4.2.0 and biblioshiniy for bibliometrix to show the current of human consciousness research. This bibliometric study examined the yearly scientific publishing growth, the most productive authors, most often term that has been utilised, most renowned journal name, and which nation has the maximum cooperation with other country. According to the findings of the study, there is a significant inconsistency in worldwide patterns in yearly scientific output, with the number of publications growing and declining. Among all nations, United States of America (USA) published the most papers around human consciousness study. According to the research, it has shown that the most relevant contributors is Jun'ichi Takeno (Scopus), and Brian L Edlow (PubMed). Moreover, the most famous journal in human consciousness research includes Journal of Consciousness Studies (Scopus), and Frontiers in Psychology (PubMed). The significance of this study may aid new researchers in this area by offering information on important publications and authors to refer while undertaking research on this issue. Furthermore, this research helps other researchers understand current trends in this field of study. As an outcome, the objective for conducting this study is to give bibliometric analysis and to fulfill research gaps in bibliometric studies of human consciousness by giving information in the form of an overview, and suggestions. [ABSTRACT FROM AUTHOR]

Graduate employability has become an issue since there are broad mismatches between the acquired graduate skills from university and the required skills by employers. While previous researches have outlined the salient skills that need to be embedded in graduate education, to date no studies have attempted to methodically identify and synthesize the literature on graduate attributes. In this paper a total of 39 relevant studies on graduate skills and attributes in the subject areas of business and management, accounting, and computer science were extracted from Scopus® (database). This revealed a total of 53 graduate attributes, with some being highly used, such as communication, teamwork, problem solving, technological skills, creativity, interpersonal skills, leadership skills, self-management and flexibility/adaptability. The majority of studies used a quantitative survey method to collect and rank graduate attributes, and Australia emerged as the most active country in researching the domain.

This article attempts to measure the scientific productivity in terms of number of papers published in journals by authors in the field of information science, compared to the publication pattern for science in general. Information science has been defined by the American Society for Information Science as the science that investigates the properties and behavior of information, the forces governing the flow of information, and the means of processing information, for optimum accessibility and usability. According to this definition, information science emerges as an umbrella-like discipline. If the basic professional society in this discipline is considered to be the American Society for Information Science, then its prime indexing journal may be considered to be "Information Science Abstracts," and its prime review vehicle may be the "Annual Review of Information Science and Technology."

Focuses on what author perceives to be trends of the 1980s in library education; i.e., dominance of electronic technology and its applications in information science; the stabilization of enrollments; continuing shift in programs from private to public universities; and lack of acceptance of 2-year master's programs. Forty-six references are listed. (EJS)

Presents overview of library uses of automation, noting the earliest example of a "black box" in 1588, the "indicator" invented in England in 1863, various forms of card catalogs, and computer solutions posed by Vannevar Bush, J. C. R. Licklider, Project Intrex, and John G. Kemeny. Ten references are cited. (EJS)

In the 21st century, as part of the fourth industrial revolution, artificial intelligence (AI), is one of the most important and well-known technology. AI also has made it possible to execute human tasks without the need for humans. However, there is one important concern with consciousness. This is because consciousness is one of the most defining qualities between AI and humans. So, this study presents a literature review and bibliometric analysis of artificial and mind consciousness research around the world from 2000 to 2022 in order to provide researchers and scholars around the world with an overview of the results and trends in artificial and mind consciousness research. A textual query on two databases; Scopus (289 papers), and Web of Science (303 papers) using the term "artificial consciousness" OR "mind consciousness" was performed on 10 June 2022 retrieving 509 scholarly papers from 2000 to 2022 related to artificial and mind consciousness studies for in-depth analysis. Bibliometric analysis were performed using Rstudio software version 4.2.0 and biblioshiniy for bibliometrix to visualize and analyze trends of artificial and mind consciousness research. This bibliometric analysis was analyzed the annual scientific publication growth, the most productive authors, most frequent word has been using, most famous journal name, and which countries has highest collaboration with other country. According to the findings of the analysis, there is significant inconsistency in global trends in annual scientific production, with the number of publications increasing and decreasing. Among all countries, United States (USA) contributed the most publications in the field of artificial and mind consciousness research. According to the findings has show the most relevant authors is Kelley TM (Scopus), and Patel AD (WoS). Moreover, the most relevant journals articles in artificial and mind consciousness studies is Procedia Computer Science (Scopus), and Journal Of Consciousness Studies (WoS). The implication of this study is can help new researchers in this field by providing information on relevant publications and authors to consult when conducting research on this topic. Furthermore, this research helps other researchers understand current trends in this area of study. As a result, the justification for doing this study is to provide the first bibliometric analysis and to fill research gaps in bibliometric studies of artificial consciousness and the mind by providing information in the form of a literature review, overview, and guidelines. [ABSTRACT FROM AUTHOR]

Using the InCites tool of Thomson Reuters, this study compares normalized citation impact values calculated for China, Japan, France, Germany, United States, and the UK throughout the time period from 1981 to 2010. InCites offers a unique opportunity to study the normalized citation impacts of countries using (i) a long publication window (1981 to 2010), (ii) a differentiation in (broad or more narrow) subject areas, and (iii) allowing for the use of statistical procedures in order to obtain an insightful investigation of national citation trends across the years. Using four broad categories, our results show significantly increasing trends in citation impact values for France, the UK, and especially Germany across the last thirty years in all areas. The citation impact of papers from China is still at a relatively low level (mostly below the world average), but the country follows an increasing trend line. The USA exhibits a stable pattern of high citation impact values across the years. With small impact differences between the publication years, the US trend is increasing in engineering and technology but decreasing in medical and health sciences as well as in agricultural sciences. Similar to the USA, Japan follows increasing as well as decreasing trends in different subject areas, but the variability across the years is small. In most of the years, papers from Japan perform below or approximately at the world average in each subject area. [ABSTRACT FROM AUTHOR]

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Overlaying Computer Science (CS) courses on top of inequitable schooling systems will not move us toward "CS for All." This paper prioritizes the perspectives of minoritized students enrolled in high school CS classrooms across a large, urban school district in the Western United States, to help inform how CS can truly be for all. This paper explores what student agency looks like while answering the research question "From the perspective of minoritized students historically underrepresented in computing, what makes a critical difference in their sense of agency in introductory CS high school classes?" Our research-practice partnership used qualitative data (including classroom observations, interviews, student artifacts, and video/photos) and surveys to surface the perspectives and visions of minoritized youth. The research describes what student agency looks like as youth – who have had no prior CS learning experiences – use CS as a tool to resist marginalization and dehumanizing school contexts, while declaring their own "rightful presence" in CS classrooms. Findings demonstrate the importance for CS curricula and pedagogy to center the lives of students in ways that are consequential for minoritized youth. This would support deeper engagement with content learning and student agency with computing. [ABSTRACT FROM AUTHOR]

Purpose: To analyze the AI research in the field of nursing, to explore the current situation, hot topics, and prospects of AI research in the field of nursing, and to provide a reference for researchers to carry out related studies. Methods: We used the VOSviewer 1.6.17, SciMAT, and CiteSpace 5.8.R3 to generate visual cooperation network maps for the country, organizations, authors, citations, and keywords and perform burst detection, theme evolution, and so forth. Findings A total of 9318 articles were obtained from the Web of Science Core Collection database. Four hundred and thirty‐one AI research related to the field of nursing was published by 855 institutions from 54 countries. CIN‐Computers Informatics Nursing was the top productive journal. The United States was the dominant country. The transnational cooperation between authors from developed countries was closer than that between authors from developing countries. The main hot topics included nurse rostering, nursing diagnosis, nursing decision support, disease risk factor prediction, nursing big data management, expert system, support vector machine, decision tree, deep learning, natural language processing, and nursing education. Machine learning represented one of the cutting‐edge and most applicable branches of artificial intelligence in the field of nursing, and deep learning was the hottest technology among many machine learning methods in recent years. One of the most cited papers was published by Burke in 2004 and cited 500 times, which critically evaluated AI methods to deal with nurse scheduling problems. Conclusions: Although AI has been paid more and more attention to the field of nursing, there is still a lack of high‐yielding authors who have been engaged in this field for a long time. Most of the high contribution authors and institutions came from developed countries; therefore, more transnational and multi‐disciplinary cooperation is needed to promote the development of AI in the nursing field. This bibliometric analysis not only provided a comprehensive overview to help researchers to understand the important articles, journals, potential collaborators, and institutions in this field but also analyzed the history, hot spots, and future trends of the research topic to provide inspiration for researchers to choose research directions. [ABSTRACT FROM AUTHOR]

The subject of computer science (CS) and computer science education (CSE) has relatively recently arisen as a subject for inclusion within the compulsory school curriculum. Up to this present time, a major focus of technologies in the school curriculum has in many countries been on applications of existing technologies into subject practice (both software such as office applications, and hardware such as robots and sensors). Through uses of these applications, information and communications technologies (ICT) have focused on activities to support subject and topic learning (across wide age and subject ranges). Very recently, discussions for including computers in the curriculum have shifted to a much greater focus on computing and CS, more concerned with uses of and development of programming, together with fundamental principles of problem-solving and creativity. This paper takes a policy analysis approach; it considers evidence of current implementation of CSE in school curricula, the six main arguments for wider-scale introduction of the subject, the implications for researchers, schools, teachers and learners, the state of current discussions in a range of countries, and evidence of outcomes of CSE in compulsory curricula. The paper concludes by raising key questions for the future from a policy analysis perspective. [ABSTRACT FROM AUTHOR]

The study discussed in this article attempts to trace the research trends in information and communication technology (ICT) in top 10 countries during 1999-2018, as reflected by scholarly publications index in the Scopus database. During the mentioned time period, total 18,382 research papers were published. Of these, maximum 1622 (8.82%) records were published in 2017. The annual growth (- 11.07 to 51.30) and the compound annual growth (- 0.01 to 0.23) have shown a fluctuating trend. However, a considerable number of records (7345) were published in the field of computer science while 52.35% of the records (9623) were journal article-type publications. 'Information and communication technology' was the most significant keyword used in 4997 records while the average (145.3) publications were contributed by top 10 organizations in which Japan National Institute of Information and Communications Technology was the most productive organization with 256 records. The maximum contributing country was the United States, standing for 22% of the total publications produced. Toyoshima, M. is the most prolific author with 53 publications on a particular topic, that is, ICT. The overall relative growth has shown a decreasing trend (0.92 to 0.09) while during the period of study, the doubling time has shown an increasing trend (0.75 to 7.54). Out of the total 18,382 records, total 209,919 citations were recorded in which the maximum citations (20,548) were found in 2010. Out of the total 55,913 research papers, maximum (5058) records were contributed by two authors while the least number of publications (2186) came from four authors. The mean value of the degree of collaborations was 0.92 and the overall degree of collaboration has exhibited an increasing trend during the period of study. The average author's collaboration coefficient and modified collaboration coefficient was recorded to be 0.69 while collaborative index was recorded at 4.21. However, Lotka's law of authors' productivity shows, the authors observed are somehow unlike from the numbers of authors expected during the period of study. [ABSTRACT FROM AUTHOR]

The Third International Conference on Data Engineering was held in Los Angeles, California on February 2 to 6, 1987. The conference was designed as an international forum for bringing together researchers, developers, managers, strategic planners and other users with an interest in the research, design and development of data engineering methodologies, strategies and systems. Its scope includes computer science, artificial intelligence, electrical engineering, and computer engineering. It featured papers from all major areas of data engineering, including database design and modeling, performance evaluation, algorithms, integrity, security, fault tolerance, query language, artificial intelligence approaches, knowledge bases, database machines, distributed databases and data engineering applications.

Constraints arise naturally in many scientific experiments/studies such as in, epidemiology, biology, toxicology, etc. and often researchers ignore such information when analyzing their data and use standard methods such as the analysis of variance (ANOVA). Such methods may not only result in a loss of power and efficiency in costs of experimentation but also may result poor interpretation of the data. In this paper we discuss constrained statistical inference in the context of linear mixed effects models that arise naturally in many applications, such as in repeated measurements designs, familial studies and others. We introduce a novel methodology that is broadly applicable for a variety of constraints on the parameters. Since in many applications sample sizes are small and/or the data are not necessarily normally distributed and furthermore error variances need not be homoscedastic (i.e. heterogeneity in the data) we use an empirical best linear unbiased predictor (EBLUP) type residual based bootstrap methodology for deriving critical values of the proposed test. Our simulation studies suggest that the proposed procedure maintains the desired nominal Type I error while competing well with other tests in terms of power. We illustrate the proposed methodology by re-analyzing a clinical trial data on blood mercury level. The methodology introduced in this paper can be easily extended to other settings such as nonlinear and generalized regression models. [ABSTRACT FROM AUTHOR]

The Capsule Reviews are intended to provide a short succinct review of each paper in the issue in order to bring it to a wider readership. The Capsule Reviews were compiled by Fairouz Kamareddine. Professor Kamareddine is an Associate Editor of The Computer Journal and is based in the Department of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh, UK. [ABSTRACT FROM AUTHOR]

In this paper we present a method for the recognition of hand-written digits and a practical implementation of this method for real-time recognition. A theoretical framework for the neural networks used to classify the handwritten digits is also presented. The classification task is performed using a Convolutional Neural Network (CNN). CNN is a special type of multi-layer neural network, being trained with an optimized version of the back-propagation learning algorithm. CNN is designed to recognize visual patterns directly from pixel images with minimal preprocessing, being capable to recognize patterns with extreme variability (such as handwritten characters), and with robustness to distortions and simple geometric transformations. The main contributions of this paper are related to the original methods for increasing the efficiency of the learning algorithm by preprocessing the images before the learning process and a method for increasing the precision and performance for real-time applications, by removing the non useful information from the background. By combining these strategies we have obtained an accuracy of 96.76%, using as training set the NIST (National Institute of Standards and Technology) database. [ABSTRACT FROM AUTHOR]

Computer science (CS) education is plagued by a gender divide, with few girls and women participating in this high-status discipline. A proven strategy to broaden participation for girls and other underrepresented students interested in CS is the availability of teacher preparation that requires classroom teachers to grow their knowledge of CS content as well as the pedagogical practices that enhance inclusive learning opportunities for historically underrepresented students. This case study describes the design and impact of an Online Professional Development (PD) for CS teachers, a year-long PD program aimed at broadening participation in the United States. Using survey and observation data from more than 200 participants over three years in PD settings, this paper examines how the design of an online learning community model of PD provides an inclusive venue for teachers to examine their belief systems, develop inclusive pedagogical practices, and collectively transform the culture of CS classrooms to places that support all learners. Findings suggest that purposeful facilitation creates a transformative culture of "shared experience" whereby facilitators and groups of teachers engage in collaborative lesson planning and debriefing discussions, in both synchronous and asynchronous sessions. This case study can inform other online PD efforts aimed at broadening participation in computing. [ABSTRACT FROM AUTHOR]

This paper intends to explore the impact of Information technology (IT) development on the legal concept of `signatures'. To what extent and in which way does it impact on the legal concept of `signatures'? This paper attempts to examine this issue from an international and comparative perspective. It was found that IT development has different levels of impact on the legal concept of `signatures' in different jurisdictions. In the Common Law system such as the UK and the US, it does not change the legal concept of `signatures'. However, it does put the legal concept on such an important position. On the contrary, IT development changes the legal concept of `signatures' in the Civil Law system such as Germany and China. [ABSTRACT FROM AUTHOR]

The author has surveyed a quarter of the accredited undergraduate computer science programs in the United States. More than half of these programs offer a "social and ethical implications of computing" course taught by a computer science faculty member, and there appears to be a trend toward teaching ethics classes within computer science departments. Although the decision to create an "in house" computer ethics course may sometimes be a pragmatic response to pressure from the accreditation agency, this paper argues that teaching ethics within a computer science department can provide students and faculty members with numerous benefits. The paper lists topics that can be covered in a computer ethics course and offers some practical suggestions for making the course successful. [ABSTRACT FROM AUTHOR]

In educational research, investigators in one field are often ignorant of similar research in other fields. Physics education in particular has undergone dramatic reforms in recent years, all based on insights gained from conducting educational research. Often, pedagogical methods resulting from research in one field can be revised and transferred to another. This paper demonstrates that many methods used in physics and other science programmes Throughout this paper, programme will refer to the curricular concept and program will refer to computer programs. can be adapted to teaching computer science. The author has pursued action research in computer science and implemented ideas from science education, especially from physics education, in teaching computer science classes at a small religious secondary school in the southwestern United States. This paper presents ideas and teaching strategies with the hope of building bridges between computer science education research and other science education research. [ABSTRACT FROM AUTHOR]

Background: Increasing emphasis in performance-based payment, public reporting, and quality improvement (QI) has led to widespread interest in measuring and improving the quality of care. By 2014, hospice programs will be required to report quality data to the federal government or incur financial penalties. With this increased interest in quality reporting comes an opportunity to develop informatics tools to capture data that reflect the complex practices involved in palliative care (PC). Therefore, there is a need to disseminate information on developing tools that facilitate capturing data and fostering improved performance. The Veterans Health Care Administration, a national leader in health information technology (HIT) and PC, established the Quality Improvement Resource Center (QuIRC) to develop innovative HIT tools to standardize and improve PC practices throughout the 153 Department of Veterans Affairs (VA) medical centers nationwide. Objective: The aim of the paper is to describe the development of the Palliative Care-National Clinical Template (PC-NCT) for documenting initial PC consults. Results: Domains of quality of life provided the foundation for this template. Principles of user-centered informatics design guided development activities. A national consensus panel of PC experts prioritized quality indicators as targets for QI. An interdisciplinary team of PC providers identified desired aspects of template functionality. QuIRC balanced PC providers' desired aspects of functionality against the feasibility within the VA HIT system. Formal pilot and usability testing contributed to numerous iterations of the PC-NCT currently piloted in five geographically distributed sites. Conclusion: This paper presents a robust approach to developing an informatics tool for PC practice. Data collected via the PC-NCT will bring variations in current practice into view and assist in directing resources at 'important targets' for QI. Although the development of HIT tools to quantify PC practice is complex, there is enormous potential to improve the quality of care for patients and families facing serious illnesses. [ABSTRACT FROM AUTHOR]

The high-tech sector is concentrated in a small number of cities. The ten largest clusters in computer science, semiconductors, and biology account for 69 percent, 77 percent, and 59 percent of all US inventors, respectively. Using longitudinal data on 109,846 inventors, I find that geographical agglomeration results in significant productivity gains. When an inventor moves to a city with a large cluster of inventors in the same field, she experiences a sizable increase in the number and quality of patents produced. The presence of significant productivity externalities implies that the agglomeration of inventors generates large gains in the aggregate amount of innovation produced in the United States. (JEL D62, J24, L60, O31, 034, R32) [ABSTRACT FROM AUTHOR]

This paper examines students' pre-college experience with computers. It finds significant gender differences in how students develop interest in computers; exposure to computers at home; availability of computers in high schools; and high-school preparations for college study in a computing field. The paper has a number of implications to improve the digital divide for women. It is based on 150 in-depth interviews of female and male undergraduate students, members of five major ethnic/racial groups (White, Afro-American, Hispanic, Asian American, and Native American) from seven institutions in the USA. [ABSTRACT FROM AUTHOR]

Presents a series of literary papers from the U.S.-based Workshop on Advances in Parallel and Distributed Computational Models, published in the February 2003 issue of 'International Journal of Foundations of Computer Science.' Features of the workshop; Method for selecting literary papers for the issue.

The generalization error bounds found by current error models using the number of effective parameters of a classifier and the number of training samples are usually very loose. These bounds are intended for the entire input space. However, support vector machine (SVM), radial basis function neural network (RBFNN), and multilayer perceptron neural network (MLPNN) are local learning machines for solving problems and treat unseen samples near the training samples to be more important. In this paper, we propose a localized generalization error model which bounds from above the generalization error within a neighborhood of the training samples using stochastic sensitivity measure. It is then used to develop an architecture selection technique for a classifier with maximal coverage of unseen samples by specifying a generalization error threshold. Experiments using 17 University of California at Irvine (UCI) data sets show that, in comparison with cross validation (CV), sequential learning, and two other ad hoc methods, our technique consistently yields the best testing classification accuracy with fewer hidden neurons and less training time. [ABSTRACT FROM AUTHOR]

Student retention is one of the greatest challenges facing computer science programs. Difficulties in an introductory programming class often snowball, resulting in poor student performance or dropping the major completely. In this paper, we present an analysis of 197 students over 6 semesters from 11 sections of an introductory programming class at a private four-year liberal arts university in the southeastern United States. The goal of this research was to find the earliest point in the assessment sequence which could predict final grade outcomes. Accordingly, we measured the degree of correlation between student performance on quizzes, labs, programs, and tests compared to final course grade. Overall, the results show a strong positive correlation for all four assessment modalities. These results hold significance for educators and researchers insofar as the body of computing education research is extended by evaluating the relative effectiveness of early semester subsets of each of the four categories of student data to model class outcomes. [ABSTRACT FROM AUTHOR]

Being a journal editor is one of the most exciting positions in any scientific field. You get a frontrow seat for all of the best research and scholarly work being done in the field. The Independent Sector (IS) Spring Research Forum for 2001, which was devoted to technology was held some months back. But as a longtime technology buff, the author had like to offer several impressions of the way nonprofits are now using information technology (IT), as reflected in the conference and elsewhere. First, it was interesting to see how far they have come in the six years since the first conference on nonprofit technology, organized by Tim Akers at Michigan State in 1995. One of the major subtexts of the 1995 conference was a not-so-subtle message to the nonprofit community: there is much to learn from what higher education has done with IT and this new thing called the Internet. Another strong impression was that after years of hesitation and uncertainty a sectorwide embrace of IT, though still somewhat halting and uncertain at times, is now real and widespread. Technology use is no longer restricted to the early adopters. The technology revolution is finally well under way in the mainstream of the nonprofit world.