Search

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]

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]

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 purpose of this articles is to identify errors related to management information systems through a Scientometric analysis to divulge the dynamics of the research topic to the academic community. The study was carried out, between 1971 and January 30, 2021, using the Scopus database and VOSviewer software. As a result of the search string "management information system" and "error*" or "mistakes" were obtained 826 published scientific articles. The highest percentage of documents published are conference paper (53.3%), and Article (39.7%). The most productive countries are the United States and Austria (60% articles) and citations are focused on United States (65%). The chronological analysis revealed that the scientific production in the area showed a particular increase from 2006 to 2009. The Lecture Notes in Computer Science. Lecture notes in Artificial Intelligence and Lecture Notes in Bioinformatics was the most productive journal. The 32.7% of the literature was published in the Computer Science field. 6 clusters were identified, and 19 keywords related with errors or mistakes were recognized. The Scientometric analysis accomplished allowed a descriptive analysis and identification of the countries, journals, keywords, sponsors, most cited articles, clustering the results facilitating the visual representation of the study. [ABSTRACT FROM AUTHOR]

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]

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]

This paper presents the results of an analysis of indicators that can be used to predict whether a student will succeed in a Computer Science Ph.D. program. The analysis was conducted by studying the records of 75 students who have been in the Computer Science Ph.D. program of the University of Alabama in Huntsville. Seventy-seven variables were extracted from each student's record, and the variables were correlated with whether the student did or did not successfully graduate from the program. A multivariate model was developed that predicts success with a high degree of accuracy. Importantly, the model relies on variables that can be determined reasonably early in a student's Ph.D. class work, enabling its use as a selection metric. Hypotheses about the composition of the model are also presented and discussed. [ABSTRACT FROM AUTHOR]

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]

The last twenty years has seen the development of demand for a new type of computing professional, which has resulted in the emergence of the academic discipline of Information Technology (IT). Numerous colleges and universities across the country and abroad have responded by developing programs without the advantage of an existing model for guidance. Efforts to define a model curriculum for IT began at the first Conference on Information Technology curriculum (CITC-1) in December 2001, which included representatives from 15 IT programs at four-year universities across the United States. Membership in SIGITE (Special Interest Group Information Technology Education) has grown to over 400 representing many of the four-year IT programs in the United States and abroad and some of the two-year IT programs in the United States. Continued development of the curriculum and subsequent funding by the Education Board of ACM enabled the completion of a first draft of the model curriculum for IT establishing program outcomes and a body of knowledge defining the discipline. This paper presents an overview of the process followed and the results achieved. [ABSTRACT FROM AUTHOR]

Providing adequate computing lab support for Management Information Systems (MIS) and Computer Science (CS) programs is a perennial challenge for most academic institutions in the US and abroad. Factors, such as lack of physical space, budgetary constraints, conflicting needs of different courses, and rapid obsolescence of computing technology, precipitate this challenge. While introductory computing courses can be adequately supported through general labs, advanced computing courses typically require dedicated labs. Normally, however, even a dedicated lab must simultaneously support multiple courses with diverse support requirements. Consequently, in designing dedicated computing labs, versatility and flexibility of the lab must be the prime consideration. Drawing on the insights gained from developing a dedicated lab, the authors present a model for developing a versatile, flexible lab to support computer network courses. The proposed model entails a modular design approach which offers ease of management, configuration and upgrading of the lab by decoupling the lab functions into layers. The layered design divides the lab into four management layers: (1) wiring layer, (2) networking layer, (3) server systems layer, and (4) support procedures layer. Each layer offers a versatile and configurable design and serves as a foundation for the next higher layer. Wiring layer minimizes the wire configuration efforts and enhances wiring flexibility by utilizing patch panels at the computer desks and the racks housing networking devices, and sufficient underground wiring between desks and racks. The underground wiring allows for network, telephone and serial cable connections as needed. Network layer builds LANs, subnets and internets with minimal configuration effort through a careful arrangement of network hubs, switches, routers, and firewalls. The network layer distinguishes between permanent networks needed in the lab, called pre-configured networks, and the networks that are assembled and disassembled by the students, called configurable networks. The network address allocation schemes for different types of network experiments are also discussed. Server systems layer covers two categories of servers: pre-configured servers and configurable servers. Pre-configured servers, such as DNS and file servers, are production servers that support network experiments. Configurable servers are hardware platforms that can be configured as needed according to experimental needs. The last layer, procedural layer, provides policies, guidelines and operational procedures that are needed for proper utilization of the lab space and the equipment. The paper also illustrates the application of the proposed model through the design and configuration of the computing lab for network courses underlying this case study. [ABSTRACT FROM PUBLISHER]

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA. [ABSTRACT FROM AUTHOR]

A comparison between the development of cognitive science in France and the USA enables us to analyze some national differences linked to specific connections between the scientific, military, economic and political worlds. The influence of new practices and tools developed during World War II and the Cold War appears to be of crucial importance in understanding the development of this new field, as well as that of cybernetics, computer science, artificial intelligence and molecular biology. This paper can be considered as a study in how the differing contexts in France and the USA shaped the history of the construction of cognitive science in each of these two countries. In spite of various differences, some common aspects may be pointed out: in both cases, computer experts and psychologists using a computational modelling approach were those first engaged in the construction of cognitive science. If in France neuroscience-oriented cognitive science research was stronger than in the USA, it seems that the artificial intelligence orientation is also of growing importance in France. [ABSTRACT FROM AUTHOR]

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA. [ABSTRACT FROM AUTHOR]

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA. [ABSTRACT FROM AUTHOR]

Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA. [ABSTRACT FROM AUTHOR]

This section is maintained by Vladik Kreinovich. Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to: Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA. [ABSTRACT FROM AUTHOR]

This section is maintained by Vladik Kreinovich. Please send your abstracts (or copies of papers that you want to see reviewed here) to vladik@utep.edu, or by regular mail to: V. Kreinovich, Department of Computer Science, University of Texas, El Paso, TX 79968, USA. [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.

Previous analytical work [16], [17] on the resilience of P2P networks has been restricted to disconnection arising from simultaneous failure of all neighbors in routing tables of participating users. In this paper, we focus on a different technique for maintaining consistent graphs—Chord's successor sets and periodic stabilizations—under both static and dynamic node failure. We derive closed-form models for the probability that Chord remains connected under both types of node failure and show the effect of using different stabilization interval lengths (i.e., exponential, uniform, and constant) on the probability of partitioning in Chord. [ABSTRACT FROM AUTHOR]