New and improved monthly statistics reports are now available containing enriched visual analytics dashboards that can be used for monthly trending. These comprehensive dashboards improve efficiency by allowing OUs to quickly access data that is relevant to them by OU, Region, Section, Grade, Division, etc.
As a reminder for continuing chapter chairs and for incoming chapter chairs for 2019, we would like to highlight a valuable resource available to you. Launched last year was IEEE OU Analytics, a web-based business intelligence tool to deliver essential metrics on memberships or subscriptions to OUs, including Societies, Councils, Technical Communities, etc.
The title of "Memberships, Subscriptions, and More..." dashboard on the OU Analytics landing page has been renamed to add a parenthetical reference within the title to include (Societies, TCs, Affinities). There has been some confusion as to the content provided within the "Members and Affiliates" versus the "Memberships, Subscriptions, and More..." dashboard.
Please be advised that IEEE gauges the vitality of a chapter by tracking how many meetings are reported during the year through vTools. If a chapter reports "0" meetings for three consecutive years, the chapter is placed on a dissolution list that is reviewed at the November Board Meeting.
Many of us marveled in awe in March 2018 at the sight of the Ghana teacher who, using colored chalk, drew on his blackboard a snapshot of how an open window of the Microsoft Word software would look like on the screen of a computer...
This is an age of mobility. Phones, tablets, notebook computers, smart watches, and various other devices now supply people around the world with instant communication capabilities that were only dreamed of a generation ago. Mobility technologies are also transforming medicine, helping to improve the quality of care for people at all stages of life, giving both patients and healthcare providers deeper...
The success of artificial neural networks (ANNs) in carrying out various specialized cognitive tasks has brought renewed efforts to apply machine learning (ML) tools for economic, commercial, and societal aims, while also raising expectations regarding the advent of an artificial “general intelligence” [1]–[2][3]. Recent highly publicized examples of ML breakthroughs include the ANN-based algorithm AlphaGo...
The success of artificial neural networks (ANNs) in carrying out various specialized cognitive tasks has brought renewed efforts to apply machine learning (ML) tools for economic, commercial, and societal aims, while also raising expectations regarding the advent of an artificial “general intelligence” [1]–[2][3]. Recent highly publicized examples of ML breakthroughs include the ANN-based algorithm AlphaGo...
In my September editorial [1], I outlined the important components of good feature articles in response to feedback from our recent IEEE Periodicals Review and Advisory Committee (PRAC) meeting. In this issue's editorial, I discuss the process of organizing a special issue (SI) for IEEE Signal Processing Magazine (SPM).
In this paper, we consider the problem of bandwidth-constrained distributed estimation of a Gaussian vector with linear observation model. Each sensor makes a scalar noisy observation of the unknown vector, employs a multi-bit scalar quantizer to quantize its observation, and maps it to a digitally modulated symbol.
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