The Encyclopedia of Neutrosophic Researchers - vol. 3

This is the third volume of the Encyclopedia of Neutrosophic Researchers, edited from materials offered by the authors who responded to the editor’s invitation. The authors are listed alphabetically. The introduction contains a short history of neutrosophics, together with links to the main papers and books. Neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics, neutrosophic measure, neutrosophic precalculus, neutrosophic calculus and so on are gaining significant attention in solving many real life problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistent, and indeterminacy. In the past years the fields of neutrosophics have been extended and applied in various fields, such as: artificial intelligence, data mining, soft computing, decision making in incomplete / indeterminate / inconsistent information systems, image processing, computational modelling, robotics, medical diagnosis, biomedical engineering, investment problems, economic forecasting, social science, humanistic and practical achievements

Digitization of World Heritage Sites of Iran as a Tool for Facilitating Online Access During Worldwide Pandemic: Case Study of Pasargadae World Heritage Site

Purpose Cultural heritage digitization facilitates the preservation of culturally valuable objects, entities, or items into a digital form allowing more comprehensive and concurrent access to such objects. It becomes more significant for overcoming the constraints associated with physical access, especially during turmoil, disasters, and pandemics like COVID-19, where physical interactions are almost restricted. Covid-19 restrictions and resultant social distancing protocols impacted nearly every facet of human life. Galleries, Libraries, Archives, Museums, and heritage sites across the globe were also affected as they were closed for the general public. Therefore, the study explores the importance of making diverse cultural heritage information available online and accessible to the broader user community and provisions for data security through proper backups, setting user privileges, and maintaining necessary updates. Design/Methodology/Approach The study selected Pasargadae world heritage site in Iran as the study area by analyzing the database maintained and available for consultation. Further, the study attempts to highlight the advantages associated with the digitization of cultural items, including manuscripts, images, monuments, sites, etc. It also highlights prerequisites for managing such information online effectively using digitization. Findings Given the state of cultural heritage in Iran, digitization is still in the infancy stage. It is necessary to develop well-equipped policies, technological infrastructures, including high-speed internet, scanning machines, high-resolution digital cameras, and servers with high capacity processing for digitization. Besides, adequate funding and significant management concerns are needed to address various ethical and privacy issues, including copyright concerns associated with Iran’s cultural heritage digitization process. Originality/value The work is a thorough attempt towards surveying Pasargadae world heritage site to understand the basic requirements for creating an online information delivery portal through the digitization of rich cultural heritage sites for enabling access even in virtual mode

China Maritime Report No. 6: Djibouti: China\u27s First Overseas Strategic Strongpoint

This China Maritime Report on Djibouti is the first in a series of case studies on China’s “overseas strategic strongpoints” (海外战略支点). The strategic strongpoint concept has no formal definition, but is used by People’s Republic of China (PRC) officials and analysts to describe foreign ports with special strategic and economic value that host terminals and commercial zones operated by Chinese firms.https://digital-commons.usnwc.edu/cmsi-maritime-reports/1005/thumbnail.jp

Disentangling and Operationalizing AI Fairness at LinkedIn

Operationalizing AI fairness at LinkedIn's scale is challenging not only because there are multiple mutually incompatible definitions of fairness but also because determining what is fair depends on the specifics and context of the product where AI is deployed. Moreover, AI practitioners need clarity on what fairness expectations need to be addressed at the AI level. In this paper, we present the evolving AI fairness framework used at LinkedIn to address these three challenges. The framework disentangles AI fairness by separating out equal treatment and equitable product expectations. Rather than imposing a trade-off between these two commonly opposing interpretations of fairness, the framework provides clear guidelines for operationalizing equal AI treatment complemented with a product equity strategy. This paper focuses on the equal AI treatment component of LinkedIn's AI fairness framework, shares the principles that support it, and illustrates their application through a case study. We hope this paper will encourage other big tech companies to join us in sharing their approach to operationalizing AI fairness at scale, so that together we can keep advancing this constantly evolving field

Reaching beyond ourselves: Celebrating 40 years of CALA (1973 - 2013)

The CALA 40th Anniversary Issue, Reaching Beyond Ourselves: Celebrating 40 Years of CALA (1973-2013), is without doubt a unique collection of the Chinese American Librarians Association’s (CALA) history. It contains pictures, biographies, citations and messages from the presidents of the CALA since its very beginning in 1973, obtained from historical CALA newsletters and the presidents themselves. It records the major events in a timeline format including the establishment of the association, the merge of CALA and CLA, the California based Chinese Librarians Association, the annual conference programs and the new initiatives. It collects personal contemplations, messages and greetings from a variety of people, including CALA members and its leaders, ALA leaders, government officials, and Chinese libraries and librarian associations. It documents the effort in finding and archiving some of the CALA historical materials. It reports the endeavors of some major initiatives such as the CALA 21st Century Librarian Seminar Series and the “Think Globally, Act Globally” US-China Librarian Collaboration project. It contains a special article on Dr. Hwa-Wei Lee and the special Chinese collections in the Library of Congress; and a first-hand report on the CALA 40th Anniversary Celebration and Awards Banquet. It also includes information on the seven CALA chapters, a glimpse into CALA’s 1980 and 2013 membership and the Chinese Librarians Summer Program at the University of Illinois at Urbana-Champaign. It concludes with a collection of pictures taken at the 40th Anniversary annual program and banquet. This publication documents the history of a professional organization and celebrates creativity, diversity and global outreach. Its presentation is pleasant to the eyes of the general public and will be a valuable source for the librarians and researchers

Accelerated Federated Learning with Decoupled Adaptive Optimization

The federated learning (FL) framework enables edge clients to collaboratively learn a shared inference model while keeping privacy of training data on clients. Recently, many heuristics efforts have been made to generalize centralized adaptive optimization methods, such as SGDM, Adam, AdaGrad, etc., to federated settings for improving convergence and accuracy. However, there is still a paucity of theoretical principles on where to and how to design and utilize adaptive optimization methods in federated settings. This work aims to develop novel adaptive optimization methods for FL from the perspective of dynamics of ordinary differential equations (ODEs). First, an analytic framework is established to build a connection between federated optimization methods and decompositions of ODEs of corresponding centralized optimizers. Second, based on this analytic framework, a momentum decoupling adaptive optimization method, FedDA, is developed to fully utilize the global momentum on each local iteration and accelerate the training convergence. Last but not least, full batch gradients are utilized to mimic centralized optimization in the end of the training process to ensure the convergence and overcome the possible inconsistency caused by adaptive optimization methods