Your employer brand is not just a logo; it is the reason talent chooses you over a competitor. This guide breaks down the strategy, visuals, and metrics necessary to reduce recruitment costs and ...

The Committee on National Statistics (CNSTAT) contributes to a better understanding of important national issues by working to improve the statistical methods and information on which public policy ...

We might earn a commission if you make a purchase through one of the links. The McClatchy Commerce Content team, which is independent from our newsroom, oversees this content. This article has ...

Meta has refused to sign the European Union’s code of practice for its AI Act, weeks before the bloc’s rules for providers of general-purpose AI models take effect. “Europe is heading down the wrong ...

This issue proposes adding cluster sampling capabilities to the scikit-sampling library. Cluster sampling is a probability sampling technique where the population is divided into naturally occurring ...

Within-individual sampling revealed differential effects of weekends on heart rate, which were obscured by aggregated sampling methods. Conclusions: This work highlights the leverage provided by ...

Apache Kafka has become an essential component in modern data architectures, enabling real-time data streaming and processing at scale. At the heart of Kafka's publish-subscribe model lies the Kafka ...

In chromatographic analysis, the number of repeated measurements is often limited due to time, cost, and sample availability constraints. It is therefore not uncommon for chromatographers to do a ...

Tissue testing as a diagnostic tool can be a difference-maker for farms in search of understanding for in-field problems or in pursuit of higher yield. For farmers in the Midsouth, taking samples or ...

The following is a summary of “Experiences of quality cluster meetings in general practice – Findings from a national survey two years after initiation of quality clusters in Denmark,” published in ...

Abstract: Federated learning (FL) is an innovative privacy-preserving machine learning paradigm that enables clients to train a global model without sharing their local data. However, the coexistence ...