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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]

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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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]

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]

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]

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]

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 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]

The origin and history of Landauer's principle is traced through the development of the thermodynamics of computation at IBM from 1959 to 1982. This development was characterized by multiple conceptual shifts: memory came to be seen not as information storage, but as delayed information transmission; information itself was seen not as a disembodied logical entity, but as participating in the physical world; and logical irreversibility was connected with physical, thermodynamic, irreversibility. These conceptual shifts were characterized by an ambivalence opposing strong metaphysical claims to practical considerations. Three sorts of practical considerations are discussed. First, these conceptual shifts engaged materials central to IBM's business practice. Second, arguments for metaphysical certainties were made with reference to the practical functioning of typical computers. Third, arguments for metaphysical certainties were made in the context of establishing the thermodynamics of information as a sub-discipline of physics. [ABSTRACT FROM AUTHOR]

The Advanced Encryption Standard (AES) is a 128-bit block cipher with a user key of 128, 192 or 256 bits, released by NIST in 2001 as the next-generation data encryption standard for use in the USA. It was adopted as an ISO international standard in 2005. Impossible differential cryptanalysis and the boomerang attack are powerful variants of differential cryptanalysis for analysing the security of a block cipher. In this paper, building on the notions of impossible differential cryptanalysis and the boomerang attack, we propose a new cryptanalytic technique, which we call the impossible boomerang attack, and then describe an extension of this attack which applies in a related-key attack scenario. Finally, we apply the impossible boomerang attack to break 6-round AES with 128 key bits and 7-round AES with 192/256 key bits, and using two related keys we apply the related-key impossible boomerang attack to break 8-round AES with 192 key bits and 9-round AES with 256 key bits. In the two-key related-key attack scenario, our results, which were the first to achieve this amount of attacked rounds, match the best currently known results for AES with 192/256 key bits in terms of the numbers of attacked rounds. The (related-key) impossible boomerang attack is a general cryptanalytic technique, and can potentially be used to cryptanalyse other block ciphers. [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 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]

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]

There is little argument that early investment in computing and communications (C&C) research and development (R&D) has paid off, given the growth and vitality of the computing industry in the United States. Less clear are how and why federal C&C research support has been effective overall; guidance for future research policy can come from an examination of history. Whereas a vigorous industry has been visible for decades, many outside observers who question the need for federal C&C research support are often ignorant of the continuing exploitation by industry of science and technologies developed decades ago via past support and how such support has complemented industrial activities. This paper outlines how the organization of federal funding for C&C R&D has helped to make such funding so fertile, noting dimensions that may be of enduring value even as circumstances change. It focuses on the High Performance Computing and Communications Initiative of the 1980's and early 1990's, which evolved from earlier funding programs and influences current programs and prospects.[l] By design (and reflecting space limitations), the paper emphasizes positive aspects that may be relevant for the future. [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]

Background: Numerous efforts worldwide have been made to increase diversity in engineering and computer science (ECS), fields that pay well and promote upward mobility. However, in the United States (U.S.), females and students from underrepresented racial/ethnic minority groups (URM) still pursue ECS training far less than do their peers. The current study explored sex and racial/ethnic differences in ECS college enrollment as a function of math and verbal SAT score patterns (balanced or imbalanced) using an intersectional approach within a U.S. context. Data represented a census of students who took the SAT, graduated from all Virginia public high schools between 2006 and 2015, and enrolled in a 4-year college (N = 344,803). Results: Our findings show, within each sex, URM students were at least as likely as their non-URM peers to enroll in ECS programs when they scored within similar SAT score ranges. Students were more likely to enroll in ECS programs if their SAT profile favored math, compared to students with similar math and verbal SAT scores (balanced profile). This overall pattern is notably less pronounced for URM female students; their propensity to major in ECS appeared to be largely independent of verbal scores. Conclusions: Our findings inform strategies to diversify ECS enrollment. If programs continue to emphasize SAT scores during admission decisions or if more systemic issues of resource allocation in secondary schools are not addressed, other efforts to broaden participation in ECS programs may fall short of goals. Our findings also highlight the importance of considering the intersection of sex and race/ethnicity for recruitment or other educational promotions. [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]

Using responses from a large respondent-initiated online survey, we find that the career interests of many current and aspiring computer scientists in the United States diverge from a popular and official depiction of computer scientists' interests used for career and workforce development worldwide. Distinct profiles of career interests emerged from the data. These profiles suggest that many women in the field value social and artistic expression in a way not currently recognized by established depictions of computer scientists' interests. Better capturing the diversity of interests in computer science might help to boost women's, and men's, engagement in this STEM field. [ABSTRACT FROM AUTHOR]

We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. We do so by combining (1) a massive, geo-tagged data set comprising over 80 million words generated in 2011 on the social network service Twitter and (2) annually-surveyed characteristics of all 50 states and close to 400 urban populations. Among many results, we generate taxonomies of states and cities based on their similarities in word use; estimate the happiness levels of states and cities; correlate highly-resolved demographic characteristics with happiness levels; and connect word choice and message length with urban characteristics such as education levels and obesity rates. Our results show how social media may potentially be used to estimate real-time levels and changes in population-scale measures such as obesity rates. [ABSTRACT FROM AUTHOR]

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]

This paper discussed the concept of computer competency and investigated the relationship between students' computer competency and their perception of enjoyment and difficulty level of web-based distance-learning courses. Participants were 237 entering graduate students in library and information science from a mid-southwestern state university in the United States from year 2001 to 2003. Computer competency was estimated by students' self-report of their prior knowledge of information technology skills in a survey called Computer Skill and Use Assessment. Statistical significance was found between the correlation of computer competency and students' perception of enjoyment level (p=.011) and difficulty level (p=.001). [ABSTRACT FROM AUTHOR]

This is a study of a well-known controversy in computer science, between artificial intelligence and neural networks researchers. It examines claims made by participants in the field that the controversy was triggered, shaped and finally resolved in connection to activities of state research agencies, particularly the US Department of Defense Advanced Research Projects Agency (ARPA). In contrast to these claims, this account concludes that, although ARPA's relations to the controversy among researchers were important, they were indirect. This study thus brings the analytical resources of studies of scientific controversy to bear on a domain which has so far gone largely unexamined in studies of 20th-century controversies— namely, state research policy and management. The account is based on contemporary documents, historical literature, and interviews with researchers and ARPA officials. [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]

Much has been made of the dark web's dangers, but democracy has more to fear from Citizens United and the global surveillance industry than Silk Road or Tor. [ABSTRACT FROM AUTHOR]

Background: Evaluating environmental health risks in communities requires models characterizing geographic and demographic patterns of exposure to multiple stressors. These exposure models can be constructed from multivariable regression analyses using individual-level predictors (microdata), but these microdata are not typically available with sufficient geographic resolution for community risk analyses given privacy concerns. Methods: We developed synthetic geographically-resolved microdata for a low-income community (New Bedford, Massachusetts) facing multiple environmental stressors. We first applied probabilistic reweighting using simulated annealing to data from the 2006–2010 American Community Survey, combining 9,135 microdata samples from the New Bedford area with census tract-level constraints for individual and household characteristics. We then evaluated the synthetic microdata using goodness-of-fit tests and by examining spatial patterns of microdata fields not used as constraints. As a demonstration, we developed a multivariable regression model predicting smoking behavior as a function of individual-level microdata fields using New Bedford-specific data from the 2006–2010 Behavioral Risk Factor Surveillance System, linking this model with the synthetic microdata to predict demographic and geographic smoking patterns in New Bedford. Results: Our simulation produced microdata representing all 94,944 individuals living in New Bedford in 2006–2010. Variables in the synthetic population matched the constraints well at the census tract level (e.g., ancestry, gender, age, education, household income) and reproduced the census-derived spatial patterns of non-constraint microdata. Smoking in New Bedford was significantly associated with numerous demographic variables found in the microdata, with estimated tract-level smoking rates varying from 20% (95% CI: 17%, 22%) to 37% (95% CI: 30%, 45%). Conclusions: We used simulation methods to create geographically-resolved individual-level microdata that can be used in community-wide exposure and risk assessment studies. This approach provides insights regarding community-scale exposure and vulnerability patterns, valuable in settings where policy can be informed by characterization of multi-stressor exposures and health risks at high resolution. [ABSTRACT FROM AUTHOR]

We developed linguistics-driven prediction models to estimate the risk of suicide. These models were generated from unstructured clinical notes taken from a national sample of U.S. Veterans Administration (VA) medical records. We created three matched cohorts: veterans who committed suicide, veterans who used mental health services and did not commit suicide, and veterans who did not use mental health services and did not commit suicide during the observation period (n = 70 in each group). From the clinical notes, we generated datasets of single keywords and multi-word phrases, and constructed prediction models using a machine-learning algorithm based on a genetic programming framework. The resulting inference accuracy was consistently 65% or more. Our data therefore suggests that computerized text analytics can be applied to unstructured medical records to estimate the risk of suicide. The resulting system could allow clinicians to potentially screen seemingly healthy patients at the primary care level, and to continuously evaluate the suicide risk among psychiatric patients. [ABSTRACT FROM AUTHOR]

Background: Ovarian cancer is the most lethal gynecologic disease in the United States, with more women dying from this cancer than all gynecological cancers combined. Ovarian cancer has been termed the “silent killer” because some patients do not show clear symptoms at an early stage. Currently, there is a lack of approved and effective early diagnostic tools for ovarian cancer. There is also an apparent severe knowledge gap of ovarian cancer in general and of its indicative symptoms among both public and many health professionals. These factors have significantly contributed to the late stage diagnosis of most ovarian cancer patients (63% are diagnosed at Stage III or above), where the 5-year survival rate is less than 30%. The paucity of knowledge concerning ovarian cancer in the United States is unknown. Methods: The present investigation examined current public awareness and knowledge about ovarian cancer. The study implemented design strategies to develop an unbiased survey with quality control measures, including the modern application of multiple statistical analyses. The survey assessed a reasonable proxy of the US population by crowdsourcing participants through the online task marketplace Amazon Mechanical Turk, at a highly condensed rate of cost and time compared to traditional recruitment methods. Conclusion: Knowledge of ovarian cancer was compared to that of breast cancer using repeated measures, bias control and other quality control measures in the survey design. Analyses included multinomial logistic regression and categorical data analysis procedures such as correspondence analysis, among other statistics. We confirmed the relatively poor public knowledge of ovarian cancer among the US population. The simple, yet novel design should set an example for designing surveys to obtain quality data via Amazon Mechanical Turk with the associated analyses. [ABSTRACT FROM AUTHOR]

The article focuses on the current and potential library based support efforts for clinical and translational research provided by the Clinical and Translational Science Awards (CTSA). It discusses the national-level organizational scheme of the CTSA Key Function Committees to support the goals of translational science. Further it presents an assessment of library-based translational support services for the translational science institute (TSI).

The northeastern United States is a predominately-forested region that, like most of the eastern U.S., has undergone a 400-year history of intense logging, land clearance for agriculture, and natural reforestation. This setting affords the opportunity to address a major ecological question: How similar are today's forests to those existing prior to European colonization? Working throughout a nine-state region spanning Maine to Pennsylvania, we assembled a comprehensive database of archival land-survey records describing the forests at the time of European colonization. We compared these records to modern forest inventory data and described: (1) the magnitude and attributes of forest compositional change, (2) the geography of change, and (3) the relationships between change and environmental factors and historical land use. We found that with few exceptions, notably the American chestnut, the same taxa that made up the pre-colonial forest still comprise the forest today, despite ample opportunities for species invasion and loss. Nonetheless, there have been dramatic shifts in the relative abundance of forest taxa. The magnitude of change is spatially clustered at local scales (<125 km) but exhibits little evidence of regional-scale gradients. Compositional change is most strongly associated with the historical extent of agricultural clearing. Throughout the region, there has been a broad ecological shift away from late successional taxa, such as beech and hemlock, in favor of early- and mid-successional taxa, such as red maple and poplar. Additionally, the modern forest composition is more homogeneous and less coupled to local climatic controls. [ABSTRACT FROM AUTHOR]

The Indo-pacific panther grouper (Chromileptes altiveli) is a predatory fish species and popular imported aquarium fish in the United States which has been recently documented residing in western Atlantic waters. To date, the most successful marine invasive species in the Atlantic is the lionfish (Pterois volitans/miles), which, as for the panther grouper, is assumed to have been introduced to the wild through aquarium releases. However, unlike lionfish, the panther grouper is not yet thought to have an established breeding population in the Atlantic. Using a proven modeling technique developed to track the lionfish invasion, presented is the first known estimation of the potential spread of panther grouper in the Atlantic. The employed cellular automaton-based computer model examines the life history of the subject species including fecundity, mortality, and reproductive potential and combines this with habitat preferences and physical oceanic parameters to forecast the distribution and periodicity of spread of this potential new invasive species. Simulations were examined for origination points within one degree of capture locations of panther grouper from the United States Geological Survey Nonindigenous Aquatic Species Database to eliminate introduction location bias, and two detailed case studies were scrutinized. The model indicates three primary locations where settlement is likely given the inputs and limits of the model; Jupiter Florida/Vero Beach, the Cape Hatteras Tropical Limit/Myrtle Beach South Carolina, and Florida Keys/Ten Thousand Islands locations. Of these locations, Jupiter Florida/Vero Beach has the highest settlement rate in the model and is indicated as the area in which the panther grouper is most likely to become established. This insight is valuable if attempts are to be made to halt this potential marine invasive species. [ABSTRACT FROM AUTHOR]

Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980–2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products. [ABSTRACT FROM AUTHOR]

Objectives: We examined temporal trends, spatial variation, and gender differences in rates of hospitalization due to acute myocardial infarction. Methods: We used data from the Centers for Disease Control National Environmental Public Health Tracking Network to evaluate temporal trends, geographic variation, and gender differences in 20 Environmental Public Health Tracking Network states from 2000 to 2008. A longitudinal linear mixed effects model was fitted to the acute myocardial infarction hospitalization rates for the states and counties within each state to examine the overall temporal trend. Results: There was a significant overall decrease in age-adjusted acute myocardial infarction hospitalization rates between 2000 and 2008, with most states showing over a 20% decline during the period. The ratio of male/female rates for acute myocardial infarction hospitalization rates remained relatively consistent over time, approximately two-fold higher in men compared to women. A large geographic variability was found for age-adjusted acute myocardial infarction hospitalization rates, with the highest rates found in the Northeastern states. Results of two ecological analyses revealed that the NE region remained significantly associated with increased AMI hospitalization rates after adjustment for socio-demographic factors. Conclusions: This investigation is one of the first to explore geographic differences in AMI age adjusted hospital rates in individuals 35+ years of age for 2000–2008. We showed a decreasing trend in AMI hospitalization rates in men and women. A large geographic variability in rates was found with particularly higher rates in the New England/Mid-Atlantic region of the US and lower rates in the mountain and Pacific states of the tracking network. It appeared that over time this disparity in rates became less notable. [ABSTRACT FROM AUTHOR]

Social movements rely in large measure on networked communication technologies to organize and disseminate information relating to the movements’ objectives. In this work we seek to understand how the goals and needs of a protest movement are reflected in the geographic patterns of its communication network, and how these patterns differ from those of stable political communication. To this end, we examine an online communication network reconstructed from over 600,000 tweets from a thirty-six week period covering the birth and maturation of the American anticapitalist movement, Occupy Wall Street. We find that, compared to a network of stable domestic political communication, the Occupy Wall Street network exhibits higher levels of locality and a hub and spoke structure, in which the majority of non-local attention is allocated to high-profile locations such as New York, California, and Washington D.C. Moreover, we observe that information flows across state boundaries are more likely to contain framing language and references to the media, while communication among individuals in the same state is more likely to reference protest action and specific places and times. Tying these results to social movement theory, we propose that these features reflect the movement’s efforts to mobilize resources at the local level and to develop narrative frames that reinforce collective purpose at the national level. [ABSTRACT FROM AUTHOR]

The article discusses the relationship of gender perception towards computing with computer anxiety and computer self-efficacy among female and male students in the U.S. It examines the impact of the two psychological factors on gender assessment concerning computing-related education and careers between American male and female students. It further investigates the same relationship among Indian students wherein female participation in the field is rapidly intensifying due to the growing demand for information technology (IT) outsourcing worldwide.

The under representation of women and minorities in undergraduate computer science and information systems programs is a pervasive and persistent problem in the United States. Needed is a better understanding of the background and psychosocial factors that attract, or repel, minority students from computing disciplines. An examination of these factors is the focus of this multimethodological study that has been conducted over three phases with three separate populations. During phase 1, a survey was administered to students, who were non computer science or information systems majors, enrolled in computer applications courses at both a public and a private Historically Black Universities located in Maryland. The purpose was to examine whether a correlation existed between institutional type and access, education, counseling, and exposure to computing and/or information systems. Analysis of the data found that the participating students came to college with little information about computer science (CS) and information systems (IS) as fields of study. However, a significant disparity was found when institutional type was considered. According to the findings the students attending the private minority-serving institution reported greater access to technology, skill levels, and computing studies prior to entering college. In the second phase of the study, a satisfaction survey was administered, to students majoring in computer science at the public Historically Black University. The purpose was to examine the pre-college preparedness of minority students and whether differences would exist between the responses of the male and female participants. The respondents reported that they did not come to college with the adequate programming skills and/or prior training to succeed as a CS major, with females found to be less prepared than males. In the third phase of the study, a focus group was held with CS students in order to consider changes that would increase the enrollment and retention of underrepresented students. The participants suggested that the addition of bridge programs, increased scholarship opportunities, and greater academic support would increase the enrollment, success, and retention of underrepresented students in CS and IS majors. [ABSTRACT FROM PUBLISHER]

The article discusses the "INSPIRED" program at Lamar University, which seeks to increase encourage women and underrepresented minorities to enter the field of computer science. In the U.S. women typically receive less than 20% of university computing degrees awarded annually, and the situation is worse for African Americans, Native Americans, and Hispanics. INSPIRED seeks to address this state of affairs through a number of initiatives including faculty mentoring, efforts at educating students about opportunities in computer science, and outreach programs targeted at children in kindergarten through grade 12.

The article extends prior work on object inlining by improving the analysis and developing new code transformation techniques to further improve the compilation of Java scientific applications in the U.S. Moreover, the article implements object and array alias strategies to address the aliasing problem while utilizing an idea from Telescoping Languages to address the binary method invocation problem. Meanwhile, these improvements will increase the scientific community's acceptance of the Java programming language in the development of high-performance, high-productivity and scientific applications.

The unprecedented growth, development and implementation of information technology (IT) driven by e-commerce and other technological advances have resulted in an increased demand of technology skilled workers (Reichgelt, Zhang, & Price, 2002; United States Department of Labor Bureau of Labor Statistics, 2005). In response to degree-dependent employment requirements, academic institutions have fallen prey to the laws of supply and demand. The increased interest in obtaining IT-related positions has prompted students to enroll in IT-related degree programs. The government has supported universities interested in developing such programs by providing grants to build schools and colleges of information sciences and technology (IST). Furthermore, as IST programs grow by leaps and bounds, universities and accreditation organizations have been working to develop guidelines by which to monitor and maintain academic standards. This study identifies national standards for IST baccalaureate programs in the United States. A survey containing 138 IST standard criteria grouped in 15 categories was sent to 50 individuals affiliated with five IST-related accrediting bodies in the United States: the Accreditation Board for Engineering and Technology (ABET) (2006); the American Library Association (ALA) (2003); American Society for Information Science and Technology (ASIS&T) (2002); the Business Accreditation Committee (BAC) (2002); and the Computer Sciences Accreditation Board (CSAB) (2001), who served as a panel of experts in the area of IST to identify a theoretical framework for IST degree programs. The results of the survey revealed that all respondents agreed with the IST program standards outlined in this study. The IST standards categories outlined in this study may be utilized by any academic organization interested in developing, implementing, evaluating, or improving their IST degree program. Future studies could be conducted to identify degree requirements for virtual or online IST degree programs, graduate degree programs, and/or continuing education IST programs. [ABSTRACT FROM PUBLISHER]

The link between information technology and productivity is clear. Yet how computers affect productivity is not well understood Ours is the first study using data for approximately 30,000 U S. manufacturing plants to examine the effect of computer networks on productivity. We find a positive and significant relationship between computer networks and plant labor productivity. Plants with lower productivity in earlier periods are also more likely to have a computer network, supporting the hypothesis that plants use networks to catch up. The positive network effect remains significant when we account for endogenous computer networks. [ABSTRACT FROM AUTHOR]

Discusses degree trends and policy implications among women of color in information technology in the U.S. Definition of terms concerning minorities; Science and engineering bachelor's degrees.

Objective: To predict the true cost of developing and maintaining an electronic immunization registry, and to set the framework for developing future cost-effective and cost-benefit analysis.Data Sources/study Setting: Primary data collected at three immunization registries located in California, accounting for 90 percent of all immunization records in registries in the state during the study period.Study Design: A parametric cost analysis compared registry development and maintenance expenditures to registry performance requirements.Data Collection/extraction Methods: Data were collected at each registry through interviews, reviews of expenditure records, technical accomplishments development schedules, and immunization coverage rates.Principal Findings: The cost of building immunization registries is predictable and independent of the hardware/software combination employed. The effort requires four man-years of technical effort or approximately $250,000 in 1998 dollars. Costs for maintaining a registry were approximately $5,100 per end user per three-year period.Conclusions: There is a predictable cost structure for both developing and maintaining immunization registries. The cost structure can be used as a framework for examining the cost-effectiveness and cost-benefits of registries. The greatest factor effecting improvement in coverage rates was ongoing, user-based administrative investment. [ABSTRACT FROM AUTHOR]

Reports the integration of Accreditation Board for Engineering and Technology and the Computing Sciences Accreditation Board into a single agency in New York. Accreditation responsibility of the single organization on educational programs; Introduction of computer science on programming; Evaluation of baccalaureate degree programs on computer science.

Presents updates on issues related to computer science in the U.S. published in the February 2001 issue of the 'Expert Systems' journal. Plan of the O'Hare International Airport in Chicago to upgrade its building access control system; Automation of the frozen abd perishable distribution centers of the Perishable Distributors of Iowa using speech recognition systems; Awarding of U.S. patent to a system and methods for searching for genetic sequence database for Nanogen Inc.