Catherine A. Larson

Trends for nanotechnology development in China, Russia, and India.

China, Russia, and India are playing an increasingly important role in global nanotechnology research and development (R&D). This paper comparatively inspects the paper and patent publications by these three countries in the Thomson Science Citation Index Expanded (SCI) database and United States Patent and Trademark Office (USPTO) database (1976–2007). Bibliographic, content map, and citation network analyses are used to evaluate country productivity, dominant research topics, and knowledge diffusion patterns. Significant and consistent growth in nanotechnology papers are noted in the three countries. Between 2000 and 2007, the average annual growth rate was 31.43% in China, 11.88% in Russia, and 33.51% in India. During the same time, the growth patterns were less consistent in patent publications: the corresponding average rates are 31.13, 10.41, and 5.96%. The three countries’ paper impact measured by the average number of citations has been lower than the world average. However, from 2000 to 2007, it experienced rapid increases of about 12.8 times in China, 8 times in India, and 1.6 times in Russia. The Chinese Academy of Sciences (CAS), the Russian Academy of Sciences (RAS), and the Indian Institutes of Technology (IIT) were the most productive institutions in paper publication, with 12,334, 6,773, and 1,831 papers, respectively. The three countries emphasized some common research topics such as “Quantum dots,” “Carbon nanotubes,” “Atomic force microscopy,” and “Scanning electron microscopy,” while Russia and India reported more research on nano-devices as compared with China. CAS, RAS, and IIT played key roles in the respective domestic knowledge diffusion.

Global nanotechnology development from 1991 to 2012: patents, scientific publications, and effect of NSF funding

In a relatively short interval for an emerging technology, nanotechnology has made a significant economic impact in numerous sectors including semiconductor manufacturing, catalysts, medicine, agriculture, and energy production. A part of the United States (US) government investment in basic research has been realized in the last two decades through the National Science Foundation (NSF), beginning with the nanoparticle research initiative in 1991 and continuing with support from the National Nanotechnology Initiative after fiscal year 2001. This paper has two main goals: (a) present a longitudinal analysis of the global nanotechnology development as reflected in the United States Patent and Trade Office (USPTO) patents and Web of Science (WoS) publications in nanoscale science and engineering (NSE) for the interval 1991–2012; and (b) identify the effect of basic research funded by NSF on both indicators. The interval has been separated into three parts for comparison purposes: 1991–2000, 2001–2010, and 2011–2012. The global trends of patents and scientific publications are presented. Bibliometric analysis, topic analysis, and citation network analysis methods are used to rank countries, institutions, technology subfields, and inventors contributing to nanotechnology development. We then, examined how these entities were affected by NSF funding and how they evolved over the past two decades. Results show that dedicated NSF funding used to support nanotechnology R&D was followed by an increased number of relevant patents and scientific publications, a greater diversity of technology topics, and a significant increase of citations. The NSF played important roles in the inventor community and served as a major contributor to numerous nanotechnology subfields.

West Nile Virus and Botulism Portal: A Case Study in Infectious Disease Informatics

Information technologies and infectious disease informatics are playing an increasingly important role in preventing, detecting, and managing infectious disease outbreaks. This paper presents a collaborative infectious disease informatics project called the WNV-BOT Portal system. This Portal system provides integrated, Web-enabled access to a variety of distributed data sources related to West Nile Virus and Botulism. It also makes available a preliminary set of data analysis and visualization tools tailored for these two diseases. This system has helped to demonstrate the technological feasibility of developing a cross jurisdiction and cross species infectious disease information infrastructure and identify related technical and policy-related challenges with its national implementation.

POS-RS

The rise of social media has fueled interest in sentiment classification.POS-RS is proposed for sentiment analysis based on part-of-speech analysis.Ten public datasets were investigated to verify the effectiveness of POS-RS.Experimental results reveal POS-RS can be used as a viable method. With the rise of Web 2.0 platforms, personal opinions, such as reviews, ratings, recommendations, and other forms of user-generated content, have fueled interest in sentiment classification in both academia and industry. In order to enhance the performance of sentiment classification, ensemble methods have been investigated by previous research and proven to be effective theoretically and empirically. We advance this line of research by proposing an enhanced Random Subspace method, POS-RS, for sentiment classification based on part-of-speech analysis. Unlike existing Random Subspace methods using a single subspace rate to control the diversity of base learners, POS-RS employs two important parameters, i.e. content lexicon subspace rate and function lexicon subspace rate, to control the balance between the accuracy and diversity of base learners. Ten publicly available sentiment datasets were investigated to verify the effectiveness of proposed method. Empirical results reveal that POS-RS achieves the best performance through reducing bias and variance simultaneously compared to the base learner, i.e., Support Vector Machine. These results illustrate that POS-RS can be used as a viable method for sentiment classification and has the potential of being successfully applied to other text classification problems.

Developing a Dark Web collection and infrastructure for computational and social sciences

In recent years, there have been numerous studies from a variety of perspectives analyzing the Internet presence of hate and extremist groups. Yet the websites and forums of extremist and terrorist groups have long remained an underutilized resource for terrorism researchers due to their ephemeral nature and access and analysis problems. The purpose of the Dark Web archive is to provide a research infrastructure for use by social scientists, computer and information scientists, policy and security analysts, and others studying a wide range of social and organizational phenomena and computational problems. The Dark Web Forum Portal provides web enabled access to critical international jihadist and other extremist web forums. The focus of this paper is on the significant extensions to previous work including: increasing the scope of data collection, adding an incremental spidering component for regular data updates; enhancing the searching and browsing functions; enhancing multilingual machine-translation for Arabic, French, German and Russian; and advanced Social Network Analysis. A case study on identifying active participants is shown at the end.

Dark web forums portal: Searching and analyzing jihadist forums

With the advent of Web 2.0, the Web is acting as a platform which enables end-user content generation. As a major type of social media in Web 2.0, Web forums facilitate intensive interactions among participants. International Jihadist groups often use Web forums to promote violence and distribute propaganda materials. These Dark Web forums are heterogeneous and widely distributed. Therefore, how to access and analyze the forum messages and interactions among participants is becoming an issue. This paper presents a general framework for Web forum data integration. Specifically, a Web-based knowledge portal, the Dark Web Forums Portal, is built based on the framework. The portal incorporates the data collected from different international Jihadist forums and provides several important analysis functions, including forum browsing and searching (in single forum and across multiple forums), forum statistics analysis, multilingual translation, and social network visualization. Preliminary results of our user study show that the Dark Web Forums Portal helps users locate information quickly and effectively. Users found the forum statistics analysis, multilingual translation, and social network visualization functions of the portal to be particularly valuable.

Information sharing and collaboration policies within government agencies

This paper describes the necessity for government agencies to share data as well as obstacles to overcome in order to achieve information sharing. We study two domains: law enforcement and disease informatics. Some of the ways in which we were able to overcome the obstacles, such as data security and privacy issues, are explained. We conclude by highlighting the lessons learned while working towards our goals.

Developing syndrome definitions based on consensus and current use.

OBJECTIVE Standardized surveillance syndromes do not exist but would facilitate sharing data among surveillance systems and comparing the accuracy of existing systems. The objective of this study was to create reference syndrome definitions from a consensus of investigators who currently have or are building syndromic surveillance systems. DESIGN Clinical condition-syndrome pairs were catalogued for 10 surveillance systems across the United States and the representatives of these systems were brought together for a workshop to discuss consensus syndrome definitions. RESULTS Consensus syndrome definitions were generated for the four syndromes monitored by the majority of the 10 participating surveillance systems: Respiratory, gastrointestinal, constitutional, and influenza-like illness (ILI). An important element in coming to consensus quickly was the development of a sensitive and specific definition for respiratory and gastrointestinal syndromes. After the workshop, the definitions were refined and supplemented with keywords and regular expressions, the keywords were mapped to standard vocabularies, and a web ontology language (OWL) ontology was created. LIMITATIONS The consensus definitions have not yet been validated through implementation. CONCLUSION The consensus definitions provide an explicit description of the current state-of-the-art syndromes used in automated surveillance, which can subsequently be systematically evaluated against real data to improve the definitions. The method for creating consensus definitions could be applied to other domains that have diverse existing definitions.

Introduction to special issue on terrorism informatics

Since September 11th, the multidisciplinary field of terrorism informatics has experienced tremendous growth, and research communities as well as local, state, and national governments are facing increasingly more complex and challenging issues. The challenges facing the intelligence and national security communities worldwide include accurately and efficiently monitoring, analyzing, predicting and preventing terrorist activities. The development and use of advanced information technologies, including methodologies, models and algorithms, infrastructure, systems, and tools for national/international and homeland security related applications have provided promising new directions for study. Terrorism informatics has been defined as the application of advanced methodologies, information fusion and analysis techniques to acquire, integrate process, analyze, and manage the diversity of terrorism-related information for international and homeland security-related applications (Chen et al. 2008). It is a highly interdisciplinary and comprehensive field. The wide variety of methods used in terrorism informatics are derived from Computer Science, Informatics, Statistics, Mathematics, Linguistics, Social Sciences, and Public Policy, and these methods are involved in the collection of huge amounts of many types of multi-lingual information from varied and multiple sources. Information fusion and information technology analysis techniques, which include data mining, data integration, language translation technologies, and image and video processing, play central roles in the prevention, detection, and remediation of terrorism. The purpose of this special issue is to bring together international researchers, engineers, policy makers, and practitioners working on terrorism informatics as well as related fields such as the organizational and social sciences. We have accepted nine papers that report research in terrorism informatics. They study a variety of topics from terrorist social networks to terrorist Website sophistication, from online forum to Twitter, and from English content to Chinese content. They represent a good mix of multiple disciplines and look at terrorism informatics from different perspectives. The first two papers provide comprehensive reviews of the field, demand, techniques and trends. These papers provide guidelines as what are the interests and challenges in this community. “Tracking and Disrupting Dark Networks: Challenges of Data Collection and Analysis” by Roberts (Roberts 2011) provide challenges of data collection and analysis from within the intelligence community. Various relevant government agencies, their research interests and their ongoing projects on terrorism information collection and analysis are introduced. “Computational Approaches to Suspicion in Adversarial Settings” by Skillicorn 2011 provides a computational framework for adversarial data analysis in the context of crime and terrorism investigations. The author reviewed and discussed three major components including adversary-based data collection and characteristics, the detection techniques that identify suspicious individuals, and the network-based association techniques that find individuals related to a known suspicious individual. The next four papers focus on web content analysis with the last one also addresses web structure analysis to reveal sophistication level of terrorist websites. Two of them look at a new and promising data source: Twitter. “Information Control H. Chen Management Information Systems, University of Arizona, Tucson, AZ, USA

Customers First: Using Process Improvement to Improve Service Quality and Efficiency

In this article, Larson introduces the basic components of process improvement, through the framework of a specific library‐related project. Process improvement is a defined and systematic methodology for understanding and improving work taks and systems (processes). When properly implemented, it will streamline work processes, improve productivity, reduce costs, and increase customer satisfaction. In 1995, because of customer complaints, the University of Arizona Library undertook a process improvement project to improve its manual reserve book services. Success would be measured based on the library’s ability to meet customer requirements at the same or lower cost. Staff initially identified two general goals: place materials on reserve in a time frame that met the needs of faculty and students, and improve the quality of service overall. Process improvement methodologies supported a more specific and valid measurement of success than is normally possible, and helped establish a means of continuous data collection and monitoring of the improvements.