Relevant bibliographies by topics / User activity

Academic literature on the topic 'User activity'

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Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "User activity"

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Zhang, Tongda, Xiao Sun, Yueting Chai, and Hamid Aghajan. "Human Computer Interaction Activity Based User Identification." International Journal of Machine Learning and Computing 4, no. 4 (2014): 354–58. http://dx.doi.org/10.7763/ijmlc.2014.v4.436.

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Santosa, Paulus Insap, Kwok Kee Wei, and Hock Chuan Chan. "User involvement and user satisfaction with information-seeking activity." European Journal of Information Systems 14, no. 4 (December 2005): 361–70. http://dx.doi.org/10.1057/palgrave.ejis.3000545.

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Sanklecha, Ms Sakshi, Mr Darshit Deotale, Ms Jyoti Yadav, Ms Dipti Mishra, and Prof V. P. Yadav. "User Activity Monitoring System / SPYWARE." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 1382–89. http://dx.doi.org/10.22214/ijraset.2022.40854.

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Abstract: User activity monitoring (UAM) do the task of monitoring and recording of user actions, in the field of information security or cyber security. Including the use of applications, windows opened, system commands executed, checkboxes clicked, text entered/edited, URLs visited and nearly every everything on-screen event to protect data by ensuring that employees and contractors are performing their assigned tasks and not posing any risk to the organization are all captured and recorded in the system by the UAMS. Video-like playback of user activity and process the videos into user activity logs that keep step-by-step records of user actions that can be searched and analysed is delivered by the User Activity Monitoring System to investigate any out-of-scope activities. Creating a visual record of potentially hazardous user activity are all involved in Visual Forensics. Each user action is logged, and recorded. Once a user session is completed, UAM creates a written record as well as visual record. It can be screen- captures/screenshots or video of exactly what kind of activity a user has done. This written record of our UAMS differs from that of a SIEM or logging tool, because it captures data at a user-level not at a system level –providing plain English logs rather than System Logs (which is originally created for debugging purposes). These textual logs can be used to pair with the corresponding screen- captures/screenshots or video summaries. Using these corresponding logs and images, the visual forensics component of UAM allows for organizations to search for exact user activity in case of a security incident. In the case of a security threat, i.e. a data breach or data leak, visual Forensics are used to show exactly what kind of activity a user has done, and everything leading to the incident. Visual Forensics can also be used to provide evidence to any law enforcement that investigate the intrusion or leak.
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Herzberg, Rafael. "BRAZIL: Energy End–user Activity." Strategic Planning for Energy and the Environment 21, no. 4 (April 2002): 74–79. http://dx.doi.org/10.1080/10485230209509598.

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Herzberg, Rafael. "BRAZIL Energy End-user Activity." Strategic Planning for Energy and the Environment 21, no. 4 (April 1, 2002): 74–79. http://dx.doi.org/10.1092/8k2g-8k25-rb8u-pge9.

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Abitbol, Jacob Levy, and Alfredo J. Morales. "Socioeconomic Patterns of Twitter User Activity." Entropy 23, no. 6 (June 19, 2021): 780. http://dx.doi.org/10.3390/e23060780.

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Stratifying behaviors based on demographics and socioeconomic status is crucial for political and economic planning. Traditional methods to gather income and demographic information, like national censuses, require costly large-scale surveys both in terms of the financial and the organizational resources needed for their successful collection. In this study, we use data from social media to expose how behavioral patterns in different socioeconomic groups can be used to infer an individual’s income. In particular, we look at the way people explore cities and use topics of conversation online as a means of inferring individual socioeconomic status. Privacy is preserved by using anonymized data, and abstracting human mobility and online conversation topics as aggregated high-dimensional vectors. We show that mobility and hashtag activity are good predictors of income and that the highest and lowest socioeconomic quantiles have the most differentiated behavior across groups.
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Yin, Jie, Qiang Yang, Dou Shen, and Ze-Nian Li. "Activity recognition via user-trace segmentation." ACM Transactions on Sensor Networks 4, no. 4 (August 2008): 1–34. http://dx.doi.org/10.1145/1387663.1387665.

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Mortazavi, Bobak J., Mohammad Pourhomayoun, Sunghoon Ivan Lee, Suneil Nyamathi, Brandon Wu, and Majid Sarrafzadeh. "User-optimized activity recognition for exergaming." Pervasive and Mobile Computing 26 (February 2016): 3–16. http://dx.doi.org/10.1016/j.pmcj.2015.11.001.

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Shah, Syed W., and Salil S. Kanhere. "Smart user identification using cardiopulmonary activity." Pervasive and Mobile Computing 58 (August 2019): 101024. http://dx.doi.org/10.1016/j.pmcj.2019.05.005.

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Di Lascio, Luigi, Antonio Gisolfi, and Vincenzo Loia. "Uncertainty processing in user-modeling activity." Information Sciences 106, no. 1-2 (April 1998): 25–47. http://dx.doi.org/10.1016/s0020-0255(97)10009-3.

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Dissertations / Theses on the topic "User activity"

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Song, Chenxi. "USER ACTIVITY TRACKER USING ANDROID SENSOR." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1418938538.

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Stäger, Mathias. "Low-power sound-based user activity recognition /." Zürich : ETH, 2006. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=16719.

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Trevisiol, Michele. "Exploiting implicit user activity for media recommendation." Doctoral thesis, Universitat Pompeu Fabra, 2014. http://hdl.handle.net/10803/283657.

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This thesis explores in depth how to use the user browsing behavior, and in particular the referrer URL, in order to understand the interest of the users. The aim is, first, to understand the preferences of the users from their navigation patterns, i.e., from the implicit actions of the users. Then, to exploit this information to personalize the content offered by the service provider. The key findings from our studies allowed us to propose different solutions in terms of recommender systems and ranking approaches for media items. We show how the browsing behavior of the users captured by the browsing logs is extremely meaningful to understand new users and to estimate their preferences.
Esta tesis analiza de modo exhaustivo el comportamiento del usuario en la web y, en particular, su interacción con las URLs recomendadas, para así conocer sus intereses. El objetivo fundamental es, en primer lugar, entender las preferencias de usuario a partir de sus patrones de navegación por la web, estudiando sus acciones implícitas. En segundo lugar, se trata de aprovechar esta información para personalizar el contenido ofrecido por el proveedor de servicios. El resultado de estos estudios nos ha permitido proponer diferentes soluciones en términos de sistemas recomendadores y ranking de productos multimedia. De este modo, hemos podido demostrar cómo el comportamiento del usuario en la web, obtenido a partir de registros de navegación, es extremadamente útil para comprender a nuevos usuarios y poder así estimar sus preferencias.
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Costa, Alceu Ferraz. "Mining User Activity Data in Social Media Services." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-11092017-151000/.

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Social media services have a growing impact in our society. Individuals often rely on social media to get their news, decide which products to buy or to communicate with their friends. As consequence of the widespread adoption of social media, a large volume of data on how users behave is created every day and stored into large databases. Learning how to analyze and extract useful knowledge from this data has a number of potential applications. For instance, a deeper understanding on how legitimate users interact with social media services could be explored to design more accurate spam and fraud detection methods. This PhD research is based on the following hypothesis: data generated by social media users present patterns that can be exploited to improve the effectiveness of tasks such as prediction, forecasting and modeling in the domain of social media. To validate our hypothesis, we focus on designing data mining methods tailored to social media data. The main contributions of this PhD can be divided into three parts. First, we propose Act-M, a mathematical model that describes the timing of users actions. We also show that Act-M can be used to automatically detect bots among social media users based only on the timing (i.e. time-stamp) data. Our second contribution is VnC (Vote-and-Comment), a model that explains how the volume of different types of user interactions evolve over time when a piece of content is submitted to a social media service. In addition to accurately matching real data, VnC is useful, as it can be employed to forecast the number of interactions received by social media content. Finally, our third contribution is the MFS-Map method. MFS-Map automatically provides textual annotations to social media images by efficiently combining visual and metadata features. Our contributions were validated using real data from several social media services. Our experiments show that the Act-M and VnC models provided a more accurate fit to the data than existing models for communication dynamics and information diffusion, respectively. MFS-Map obtained both superior precision and faster speed when compared to other widely employed image annotation methods.
O impacto dos serviços de mídia social em nossa sociedade é crescente. Indivíduos frequentemente utilizam mídias sociais para obter notícias, decidir quais os produtos comprar ou para se comunicar com amigos. Como consequência da adoção generalizada de mídias sociais, um grande volume de dados sobre como os usuários se comportam é gerado diariamente e armazenado em grandes bancos de dados. Aprender a analisar e extrair conhecimentos úteis a partir destes dados tem uma série de potenciais aplicações. Por exemplo, um entendimento mais detalhado sobre como usuários legítimos interagem com serviços de mídia social poderia ser explorado para projetar métodos mais precisos de detecção de spam e fraude. Esta pesquisa de doutorado baseia-se na seguinte hipótese: dados gerados por usuários de mídia social apresentam padrões que podem ser explorados para melhorar a eficácia de tarefas como previsão e modelagem no domínio das mídias sociais. Para validar esta hipótese, foram projetados métodos de mineração de dados adaptados aos dados de mídia social. As principais contribuições desta pesquisa de doutorado podem ser divididas em três partes. Primeiro, foi desenvolvido o Act-M, um modelo matemático que descreve o tempo das ações dos usuários. O autor demonstrou que o Act-M pode ser usado para detectar automaticamente bots entre usuários de mídia social com base apenas nos dados de tempo. A segunda contribuição desta tese é o VnC (Vote-and- Comment), um modelo que explica como o volume de diferentes tipos de interações de usuário evolui ao longo do tempo quando um conteúdo é submetido a um serviço de mídia social. Além de descrever precisamente os dados reais, o VnC é útil, pois pode ser empregado para prever o número de interações recebidas por determinado conteúdo de mídia social. Por fim, nossa terceira contribuição é o método MFS-Map. O MFS-Map fornece automaticamente anotações textuais para imagens de mídias sociais, combinando eficientemente características visuais e de metadados das imagens. As contribuições deste doutorado foram validadas utilizando dados reais de diversos serviços de mídia social. Os experimentos mostraram que os modelos Act-M e VnC forneceram um ajuste mais preciso aos dados quando comparados, respectivamente, a modelos existentes para dinâmica de comunicação e difusão de informação. O MFS-Map obteve precisão superior e tempo de execução reduzido quando comparado com outros métodos amplamente utilizados para anotação de imagens.
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Chang, Tae-Young. "User-activity aware strategies for mobile information access." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22595.

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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008.
Committee Chair: Raghupathy Sivakumar; Committee Member: Chuanyi Ji; Committee Member: George Riley; Committee Member: Magnus Egerstedt; Committee Member: Umakishore Ramachandran.
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Shun, Yeuk Kiu. "Web mining from client side user activity log /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?COMP%202002%20SHUN.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002.
Includes bibliographical references (leaves 85-90). Also available in electronic version. Access restricted to campus users.
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Sun, Jun. "User readiness to interact with information systems - a human activity perspective." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4316.

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This study focuses on how and why people become ready to interact with certain information systems (IS) based on their previous experiences with the same and/or similar systems. User-system interaction can be regarded as a mediated and collaborative human activity between a user and a system with the motive of transforming raw information into useful outcome. Using Activity Theory as a paradigm, this study conceptualizes a user-system interaction model that specifies the mediating relationships involved. Based on the user-system interaction model, this study proposes a psychological construct, Information System Interaction Readiness (ISIR), that indicates how an individual is prepared and willing to interact with a system within a user context. This construct advances a developmental view of how previous IS experiences may affect user future behavior. Compared with other constructs as predictors of user behavior, such as computer self-efficacy and intention to use, ISIR takes how IS user behavior is mediated into account. To operationalize and measure the ISIR construct, this study develops a measurement instrument for ISIR using the technique of facet analysis and the semantic differential scale type. To explore how user experiences with a system lead to the formation of ISIR, this study identifies the psychological antecedents of ISIR. This enables the discussion of how general IS capabilities, including interactivity, personalization and context-awareness, may affect ISIR through these antecedents. Because ISIR is a user-, system- and context-specific construct, this study also identifies and discusses the personal and situational factors that may affect ISIR. Putting all these relationships together results in a research framework of ISIR. To validate the ISIR measurement instrument and test the ISIR research framework, several laboratory studies were conducted. The results indicated that the ISIR instrument was valid and the ISIR framework was sound. Finally, the contributions and limitations of this study are discussed.
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Burns, Edward E. (Edward Eugene). "End-user modification and correction of home activity recognition." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61941.

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Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 48-50).
Sensor-enabled computer systems capable of recognizing specific activities taking place in the home may enable a host of "context-aware" applications such as health monitoring, home automation, remote presence, and on-demand information and learning, among others. Current state-of-the-art systems can achieve close to 90% accuracy in certain situations, but the decision processes involved in this recognition are too complex for the end-users of the home to understand. Even at 90% accuracy, errors are inevitable and frequent, and when they do occur the end-users have no tools to understand the cause of errors or to correct them. Instead of such complex approaches, this work proposes and evaluates a simplified, user-centric activity recognition system that can be understood, modified, and improved by the occupants of a context-aware home. The system, named Distinguish, relies on high-level, common sense information to construct activity models used in recognition. These models are transferable between homes and can be modified on a mobile phone-sized screen. Observations are reported from a pilot evaluation of Distinguish on naturalistic data gathered continuously from an instrumented home over a period of a month. Without any knowledge of the target home or its occupant's behaviors and no training data other than common sense information contributed by web users, the system achieved a baseline activity recognition accuracy of 20% with 51 target activities. A user test with 10 participants demonstrated that end-users were able to not only understand the cause of the errors, but with a few minutes of effort were also able to improve the system's accuracy in recognizing a particular activity from 12.5% to 52.3%. Based on the user study, 5 design recommendations are presented.
by Edward E. Burns.
S.M.
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Goutham, Mithun. "Machine learning based user activity prediction for smart homes." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595493258565743.

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Voida, Stephen. "Exploring user interface challenges in supporting activity-based knowledge work practices." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/24721.

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Thesis (Ph.D.)--Computing, Georgia Institute of Technology, 2008.
Committee Chair: Mynatt, Elizabeth D.; Committee Member: Abowd, Gregory D.; Committee Member: Edwards, W. Keith; Committee Member: MacIntyre, Blair; Committee Member: Moran, Thomas P.
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Books on the topic "User activity"

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D, Andre Anthony, and Ames Research Center, eds. Activity catalog tool (A.C.T.) v2.0 user manual. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1994.

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D, Andre Anthony, and Ames Research Center, eds. Activity catalog tool (A.C.T.) v2.0 user manual. Moffett Field, Calif: National Aeronautics and Space Administration, Ames Research Center, 1994.

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Taylor, Scott L., Kim Taylor, and Anita Elworthy. Wings of discovery, user guide. Don Mills, Ont: GTK Press, 2004.

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Bødker, Susanne. Through the interface: A human activity approach to user interface design. Hillsdale, N.J: Lawrence Erlbaum, 1991.

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Bødker, Susanne. Through the interface: A human activity approach to user interface design. Aarhus, Denmark: Aarhus Universitet, Matematisk Institut, Datalogisk Afdeling, 1987.

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Bodker, Susanne. Through the interface: A human activity approach to user interface design. Hillsdale, N.J: Lawrence Erlbaum, 1991.

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Through the interface: A human activity approach to user interface design. Hillsdale, N.J: L. Erlbaum, 1990.

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Rydeman, Bitte. The growth of phrases: User-centred design for activity-based voice output communication aids. [Gothenburg]: Department of Philosophy, Linguistics and Theory of Science, University of Gothenburg, 2010.

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Parker, Richard Allen. The effects of DLA IPG I surcharges on DDRW end user activity inventory policies. Monterey, Calif: Naval Postgraduate School, 1992.

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A, Nardi Bonnie, ed. Acting with technology: Activity theory and interaction design. Cambridge, Mass: MIT Press, 2006.

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Book chapters on the topic "User activity"

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McBryan, Tony, and Philip Gray. "User Configuration of Activity Awareness." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, 748–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_113.

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Van Kleek, Max, and Howard E. Shrobe. "A Practical Activity Capture Framework for Personal, Lifetime User Modeling." In User Modeling 2007, 298–302. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73078-1_33.

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Bardram, Jakob, Afsaneh Doryab, and Sofiane Gueddana. "Activity-Based Computing – Metaphors and Technologies for Distributed User Interfaces." In Distributed User Interfaces, 67–74. London: Springer London, 2011. http://dx.doi.org/10.1007/978-1-4471-2271-5_8.

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Partridge, Kurt, and Bob Price. "Enhancing Mobile Recommender Systems with Activity Inference." In User Modeling, Adaptation, and Personalization, 307–18. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02247-0_29.

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Keane, Anthony, and Stephen O’Shaughnessy. "Tracking User Activity on Personal Computers." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 188–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35515-8_16.

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Sang, Jitao. "User Modeling on Social Multimedia Activity." In Springer Theses, 33–56. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-44671-3_3.

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Ortiz Laguna, Javier, Angel García Olaya, and Daniel Borrajo. "A Dynamic Sliding Window Approach for Activity Recognition." In User Modeling, Adaption and Personalization, 219–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22362-4_19.

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Laamanen, Tarja-Kaarina, Pirita Seitamaa-Hakkarainen, and Kai Hakkarainen. "Tracing Design Work through Contextual Activity Sampling." In Design, User Experience, and Usability. Theories, Methods, and Tools for Designing the User Experience, 142–52. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07668-3_15.

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Wang, Liang, Tao Gu, Xianping Tao, Hanhua Chen, and Jian Lu. "Multi-User Activity Recognition in a Smart Home." In Activity Recognition in Pervasive Intelligent Environments, 59–81. Paris: Atlantis Press, 2011. http://dx.doi.org/10.2991/978-94-91216-05-3_3.

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Kuru, Armağan, and Jodi Forlizzi. "Engaging Experience with Physical Activity Tracking Products." In Design, User Experience, and Usability: Design Discourse, 490–501. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20886-2_46.

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Conference papers on the topic "User activity"

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"A User-Oriented Model-Driven Requirements Elicitation Process based on User Modeling." In 1st International Workshop on Computer Supported Activity Coordination. SciTePress - Science and and Technology Publications, 2004. http://dx.doi.org/10.5220/0002647301740184.

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Pelaprat, Etienne, and R. Benjamin Shapiro. "User activity histories." In CHI '02 extended abstracts. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/506443.506643.

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Wilde, Adriana G., Pascal Bruegger, Benjamin Hadorn, and Beat Hirsbrunner. "ROBIN: Activity based robot management system." In 2010 International Conference on User Science and Engineering (i-USEr 2010). IEEE, 2010. http://dx.doi.org/10.1109/iuser.2010.5716736.

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Hocutt, Daniel L. "User Activity in Context." In SIGDOC '16: The 34th ACM International Conference on the Design of Communication. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2987592.2987611.

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Jing, Wu. "A Decentralized User Authentication Model Based on Activity Proof : Use the new user identity credential: activity map." In 2020 International Conference on Communications, Information System and Computer Engineering (CISCE). IEEE, 2020. http://dx.doi.org/10.1109/cisce50729.2020.00047.

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Yamamoto, Shuhei, Noriko Kando, and Tetsuji Satoh. "User-User Relationship Migration Observed in Communication Activity." In UMAP '16: User Modeling, Adaptation and Personalization Conference. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2930238.2930268.

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Wang, Weigang, and Jörg Haake. "Supporting user-defined activity spaces." In the eighth ACM conference. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/267437.267450.

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Pedersen, Elin Rønby, and David W. McDonald. "Relating documents via user activity." In the 13th international conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1378773.1378837.

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Santos, Olga C., and Martha H. Eddy. "Modeling Psychomotor Activity." In UMAP '17: 25th Conference on User Modeling, Adaptation and Personalization. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3099023.3099083.

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Arian, Ali, Alireza Ermagun, and Yi-Chang Chiu. "Characterizing activity patterns using co-clustering and user-activity network." In 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2017. http://dx.doi.org/10.1109/itsc.2017.8317871.

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Reports on the topic "User activity"

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Gates, T. A., and M. B. Burdick. Activity Management System user reference manual. Revision 1. Office of Scientific and Technical Information (OSTI), September 1994. http://dx.doi.org/10.2172/10187657.

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Day, Christopher M., Hiromal Premachandra, and Darcy M. Bullock. Characterizing the Impacts of Phasing, Environment, and Temporal Factors on Pedestrian Demand at Traffic Signals. Purdue University, 2011. http://dx.doi.org/10.5703/1288284317352.

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There is a need for more and higher quality data on pedestrian demand patterns for a number of applications in planning, transportation engineering, public health, and other areas. It is particularly desirable to better characterize the influence of daily, weekly, and annual variations; the impact of weather and special events; and the effects of changes in pedestrian phasing. This paper proposes and demonstrates a methodology for quantifying the relative demand for pedestrian service at a signalized intersection by using the percent of signal cycles per hour in which the pedestrian phase was actuated. Although this performance measure does not by itself provide a pedestrian count, it can be used as a surrogate to characterize how pedestrian volumes vary due to operating conditions. More importantly, since this technique does not require new sensors, the data can be collected at thousands of intersections across the nation where pedestrian push buttons are in use. This paper documents findings from over a year of data collection at a signalized intersection on a college campus. The effects of daily/weekly/annual variations, special events, weather (temperature and precipitation), seasonal changes in activity patterns, and changes in pedestrian signal phasing are documented. A Tobit model is used to account for the influences of these variables and understand how they co-influence pedestrian activity. The implementation of an exclusive pedestrian phase is associated with a 9% increase in pedestrian phase utilization at the intersection. This change is associated with a decrease in user cost relative to performing midblock crossings. The modeled impact of snowfall events adds further insight by showing that as the user cost of making midblock crossings increases, pedestrian activity at the intersection increases.
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Harkema, Marcel, Dick Quartel, Rob van der Mei, and Bart Gijsen. JPMT: A Java Performance Monitoring Tool. Centre for Telematics and Information Technology (CTIT), 2003. http://dx.doi.org/10.3990/1.5152400.

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This paper describes our Java Performance Monitoring Toolkit (JPMT), which is developed for detailed analysis of the behavior and performance of Java applications. JPMT represents internal execution behavior of Java applications by event traces, where each event represents the occurrence of some activity, such as thread creation, method invocation, and locking contention. JPMT supports event filtering during and after application execution. Each event is annotated by high-resolution performance attributes, e.g., duration of locking contention and CPU time usage by method invocations. JPMT is an open toolkit, its event trace API can be used to develop custom performance analysis applications. JPMT comes with an event trace visualizer and a command-line event trace query tool for scripting purposes. The instrumentation required for monitoring the application is added transparently to the user during run-time. Overhead is minimized by only instrumenting for events the user is interested in and by careful implementation of the instrumentation itself.
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Bécu, V., A.-A. Sappin, and S. Larmagnat. User-friendly toolkits for geoscientists: how to bring geology experts to the public. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/331220.

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A growing number of countries are committed toreduce their carbon emissions and are transitioning towards renewable and clean energy sources, leading to an in crease in demand formetals and minerals. This is especially the case for a short list of what are called "critical minerals" which are considered essential to economic development, including the transition to a low-carbon economy and national security. There liability of their supply chain raises concerns considering geological scarcity, difficulty to extract and/or political factors influencing their availability. At the same time, public awareness and perception of geoscience are eroding and there is more and more reluctance towards mining projects, even from traditionally favourable communities. To face this challenge, promote public interest and outline the contribution of geological science to society, geoscientists of the Geological Survey of Canada (GSC-Québec) have designed and put together a portable display that includes a suite of mineral and metal samples considered critical for the sustainable success of Canada's transition towards a clean and digital economy. The display is a user-friendly toolkit that can be used by any GSC geoscientists during outreach activities, in classrooms as well as during public open houses. It comes with straightforward pedagogic material and content, along with presentation scenarios. To broaden and adapt the workshops to specific expectations, additional toolkits were developed and all are contained within easy to carry travel cases. These cover a variety of topics and can be presented as stand-alone displays or be used complementary to one another. For example, the "Mines and minerals" collection may serve as a supplement to the "Critical minerals" display to present every day objects in which minerals are used as well as ores amples from active mines to illustrate the intertwining between mining activities and our everyday lives. Another display covers the ever-popular fossils thematic with the "Sedimentary rocks and fossils" collection and gives an opportunity to address key geoscience themes such as life evolution and biological crisis along with groundwater reservoirs and resources. The "Magmatic rocks" display touches on the formation of rocks from magmas, the different types and active processes of volcanoes, and discusses the risks and benefits related to volcanic activity. Hopefully, these four ready-to-use portable displays will encourage more GSC geoscientists to engage in public oriented activities to make geosciences more accessible, change perceptions and offer an overall tangible scientific experience for people.
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Ledin, Chase, Olujoke Fakoya, and Jaime Garcia-Iglesias. Stories of HIV activists during COVID-19 in the UK. University of Edinburgh, October 2022. http://dx.doi.org/10.2218/ed.9781912669462.

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Stories of HIV Activists during COVID-19 in the UK examines and interprets the experiences of HIV activists during the COVID-19 pandemic. It relies on qualitative data obtained through a UK-ICN BBSRC funded grant. We draw from these stories to start a conversation about how activism translates from one health crisis (HIV/AIDS) to another (COVID-19). These activist stories tell us about how activist individuals and organisations responded to COVID-19, but they also provide insight for future pandemic contexts. The UK and many other countries across the world face a variety of new pandemic threats, including monkeypox and Ebola, which demand new forms of health intervention and strategies to mobilise individuals and communities. We use these stories to illuminate the resilience of some activists in the face of crisis and to articulate ways in which health activism can be adapted and remobilised to respond to new health crises.
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Iatsyshyn, Anna V., Iryna H. Hubeladze, Valeriia O. Kovach, Valentyna V. Kovalenko, Volodymyr O. Artemchuk, Maryna S. Dvornyk, Oleksandr O. Popov, Andrii V. Iatsyshyn, and Arnold E. Kiv. Applying digital technologies for work management of young scientists' councils. [б. в.], June 2021. http://dx.doi.org/10.31812/123456789/4434.

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The publication explores the features of the digital technologies’ usage to organize the work of the Young Scientists’ Councils and describes the best practices. The digital transformation of society and the quarantine restrictions caused by the COVID-19 pandemic have forced the use of various digital technologies for scientific communication, the organization of work for youth associations, and the training of students and Ph.D. students. An important role in increasing the prestige of scientific activity and encouraging talented young people to participate in scientific projects belongs to the Young Scientists’ Councils, which are created at scientific institutions and higher education institutions. It is determined that the peculiarities of the work of Young Scientists’ Councils are in providing conditions for further staff development of the institution in which they operate; contribution to the social, psychological and material support of young scientists and Ph.D. students; creating an environment for teamwork and collaborative partnership; development of leadership and organizational qualities; contribution to the development of digital competence. The advantages of using electronic social networks in higher education and research institutions are analyzed, namely: general popularity and free of charge; prompt exchange of messages and multimedia data; user-friendly interface; availability of event planning functions, sending invitations, setting reminders; support of synchronous and asynchronous communication between network participants; possibility of access from various devices; a powerful tool for organizing the learning process; possibility of organization and work of closed and open groups; advertising of various events, etc. Peculiarities of managing the activity of the Young Scientists’ Council with the use of digital technologies are determined. The Young Scientists’ Council is a social system, and therefore the management of this system refers to social management. The effectiveness of the digital technologies’ usage to manage the activities of the Young Scientists’ Council depends on the intensity and need for their use to implement organizational, presentation functions and to ensure constant communication. The areas to apply digital technologies for the work managing of Young Scientists’ Councils are sorted as the presentation of activity; distribution of various information for young scientists; conducting questionnaires, surveys; organization and holding of scientific mass events; managing of thematic workgroups, holding of work meetings. It is generalized and described the experience of electronic social networks usage for organizing and conducting of scientific mass events.
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Levine, Phillip. The Sexual Activity and Birth Control Use of American Teenagers. Cambridge, MA: National Bureau of Economic Research, March 2000. http://dx.doi.org/10.3386/w7601.

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Shynenko, Mykola, and Olga Pinchuk. Activity of users of the web resource "Electronic Library of the National Academy of Sciences of Ukraine" during crisis events. Institute for Digitalization of Education, 2022. http://dx.doi.org/10.33407/lib.naes.733438.

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The monitoring of the use of the web resource "Electronic Library of the National Academy of Sciences of Ukraine" is aimed at providing informational and methodological support by means of the Google Analytics service in order to track the processes of visiting and using electronic resources, as well as to increase the efficiency of the development, improvement and maintenance of the electronic library site. A comparative analysis of the use of library resources for the period from March 1-May 31, 2022 to September 1-November 30, 2022 during the full-scale Russian invasion of Ukraine was performed. Also, to identify trends in changes in the activity of users of the web resource, a comparative analysis of the use of library resources was performed for the period: 2021. - 2022. The monitoring of the use of the website of the electronic library of the National Academy of Sciences of Ukraine is carried out according to the following indicators: overview of visitors, demographics of visitors, behavior of visitors on the website of the electronic library, technologies for visiting the site, mobile devices used, traffic, information of the statistical module. For scientists, post-graduate students, heads of scientific institutions of the National Academy of Sciences of Ukraine and specialists in the field of librarianship.
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Fu, Gongkang, and Gabriel Bryk. BrM Quantity-Based Bridge Element Deterioration/Improvement Modeling and Software Tools. Illinois Center for Transportation, February 2024. http://dx.doi.org/10.36501/0197-9191/24-005.

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This study reviewed the state of the art and practice in bridge element deterioration / improvement modeling. It also developed a new and practical method for such modeling using element quantities in BrM inspection records along with bridge age. For reliable forecasting, this method uses these quantities directly to determine transition probability matrices (TPMs). The example TPMs were found age-dependent for the do-nothing case. Results show that this approach is effective in forecasting the bridge element life. Condition improvement TPMs were also similarly derived from the quantity evolution for consistency. Examples of renewal construction work are deck overlay of micro-silica concrete, steel beam repainting, bridge cleaning, etc. Two computer software programs in Microsoft Excel were developed to obtain TPMs for do-nothing deterioration and condition improvement. Bridge owners may use the tools to generate TPMs for any element whose inspection records are provided. As a result, TPMs can be continuously updated whenever more inspections are performed and their records are included as input to the software programs. In addition, the software tools are transparent for the user to perform expert elicitation, especially when the inspection records are questionable or unavailable. Such activity can be informatively guided by the results from the software, as illustrated by two application examples in the delivered programs. This new concept and associated tools may be applied by other bridge owners using the BrM system. Two application examples for elements 12 and 107 in the programs can be readily transplanted to other states as a starting point for application of the research products herein. They show that the age-dependent TPM is able to realistically replicate deterioration for the do-nothing case, particularly the behavior of faster deterioration while aging. They also demonstrate that TPMs for different renewal construction work are able to contrast their effectiveness, such as micro-silica overlays vs. sealing for a concrete deck.
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DISSELKAMP RS. WATER ACTIVITY DATA ASSESSMENT TO BE USED IN HANFORD WASTE SOLUBILITY CALCULATIONS. Office of Scientific and Technical Information (OSTI), January 2011. http://dx.doi.org/10.2172/1004089.

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