Currently, most approaches to retrieving textual materials from scienti c databases depend on a lexical match b e t ween words in users' requests and those in or assigned to documents in a database. Because of the tremendous diversity i n t h e w ords people use to describe the same document, lexical methods are necessarily incomplete and imprecise. Using the singular value decomposition (SVD), one can take a d v antage of the implicit higher-order structure in the association of terms with documents by determining the SVD of large sparse term by document matrices. Terms and documents represented by 200-300 of the largest singular vectors are then matched against user queries. We call this retrieval method Latent Semantic Indexing (LSI) because the subspace represents important associative relationships between terms and documents that are not evident in individual documents. LSI is a completely automatic yet intelligent indexing method, widely applicable, and a promising way to improve users' access to many kinds of textual materials, or to documents and services for which textual descriptions are available. A survey of the computational requirements for managing LSI-encoded databases as well as current and future applications of LSI is presented.

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▪ Patient information in electronic health records (EHRs) needs to be protected so it is not exploited to endanger patient health or compromise identity and privacy. ▪ If not protected, patient information collected, stored, processed, and transmitted on mobile devices is especially vulnerable to attack. ▪ The National Cybersecurity Center of Excellence (NCCoE) developed an example solution to this problem by using commercially available products. ▪ The example solution is described in the "How-To" guide, which provides organizations with detailed instructions to recreate it. The NCCoE's approach secures patient information when practitioners access it with mobile devices. ▪ Organizations can use some or all of the guide to help them implement relevant standards and best practices contained in the National Institute of Standards and Technology (NIST) Cybersecurity Framework and in the Health Insurance Portability and Accountability Act (HIPAA) Security Rule. In areas where there are no standards, such as malware prevention and detection or antivirus, our solution uses best practices. CHALLENGE Healthcare providers increasingly use mobile devices to store, process, and transmit patient information. When health information is stolen, inappropriately made public, or altered, healthcare organizations can face penalties and lose consumer trust, and patient care and safety may be compromised. The NCCoE helps organizations implement safeguards to ensure the security of patient information when doctors, nurses, and other caregivers use mobile devices in conjunction with an EHR system.