top of page

Agnuslims in Asia

Public·8 members

Search Results For SONIC

Your account allows you to see most of your blood and urine lab tests in the enhanced views on the Trends, Get Smart, and My Labs pages. You can view the results for all of your lab tests in their original lab reports by going to the My Labs tab at the top of the page. Once you are in My Labs, you can click on the Result Options Menu at the upper right-hand side of the page. From the drop down, click on View Lab Reports. Here, you will see your lab reports arranged by date, with your most recent lab report appearing at the top. You can click on the calendar icon at the left of each lab report listing to open a PDF view of your original lab report.

Search results for sONIC

No, you will only see historical results that were performed by Clinical Pathology Laboratories. To view results from other Sonic Healthcare Clinical Laboratories located throughout the United States you will need to log into your account from the SonicMyAccess page specific to the location. Sonic Healthcare Clinical Laboratory locations include: American Esoteric Laboratories (AEL), Clinical Pathology Laboratories (CPL), East side Clinical Laboratory, Pathology Laboratories, Sunrise Medical Laboratories, and WestPac Labs

Appropriate medical expertise is required for the correct interpretation of clinical laboratory results and is not available from laboratory personnel. Action should not be taken based on test results without first discussing them with your healthcare provider.

The American Meteor Society, Ltd. is a non-profit scientific organization founded in 1911 and established to inform, encourage, and support the research activities of both amateur and professional astronomers who are interested in the fascinating field of Meteor Astronomy. Our affiliates observe, monitor, collect data on, study, and report on meteors, meteor showers, fireballs, and related meteoric phenomena. Please note that the AMS does not deal in meteorites.

When one builds a product, a good measure of success would not be how much time users spend on the product, but how much time users save by using it. Let search be at the core of any product for that purpose.

Certain of those Crisp users have received millions of customer support messages in their Crisp Inbox over the year. They also usually host large CRMs with tens of millions of contacts in it. Needless to say: those users want to be able to make sense out of all this data, through search. They want their search to be fast, they want reliable results.

As of 2019, Crisp hosts north to half a billion objects (cumulated: conversations, messages, contacts, helpdesk articles, etc.). Indexing all those objects using traditional search solutions would be costly both in RAM and disk space (we've tried an SQL database in FULLTEXT mode to keep things light compared to Elasticsearch, and it was a no-go: huge disk overhead and slow search). As Crisp has a freemium business model, it means that we need to index a lot of data for a majority of users that does not pay for the service.

Now that you know how to push and query objects in the search index, I invite you to learn more on what you can do on: node-sonic-channel. You may an alternate library for your programming language on the Sonic integrations registry.

The following implementation concepts are quick notes that can help anyone understand how Sonic works, if he or she intends to modify Sonic's source code, or build their own search index backend from scratch. I did not get into the "gory" details there purposefully.

Once someone comes with a search query, the query is split into words. Then, each word gets looked up in the index separately. Object references are returned for each word. Finally, all references are aggregated together so that the final result is the algebraic intersection of all world's objects.

As humans all make mistakes, correcting typos is a nice thing to have. To correct typos, we need to search all words for likely alternate words for a given word (eg. user enters 'animol' while he meant 'animal'). A perfect data structure to do this is an ordered graph. We use what's called an FST (a Finite-State Transducer). Using that, we are capable of correcting typos using the Levenshtein distance (ie. find the alternate word with the lowest distance) and prefix matching (ie. find words that have a suffix for a common prefix; eg. 'ani' would map to 'animal').

In building Sonic, we hope that our Crisp users will save time and find the data they are looking for. Sonic has been deployed on all Crisp products and is now used as the sole backend for all our search features. This ranges from Crisp Inbox to Crisp Helpdesk. Yet, there are still so many existing features we could improve with search!

In releasing it to the wider public as open-source software, we want to provide the community with a missing piece in the "build your own SaaS business" ecosystem: the Redis of search. It addresses an age-old itch; I can't wait to see what people will build with Sonic!

As of March 2019, Sonic is used in production at Crisp to index half a billion objects across all Crisp's products. After facing weird & pesky production bugs and initial design issues, which we quickly fixed, Sonic is now stable and able to handle all of Crisp's search + ingestion load on a single $5/mth cloud server, without a glitch. Our sysadmins love it.

SourceAudio is proud to announce the release of Sonic Search, a technology which will radically reshape the way music is searched and discovered. Developed entirely in-house, Sonic Search allows users to upload any audio file and return results that are musically similar to the song the user has uploaded.

Sonic Automotive, Inc., a Fortune 500 company based in Charlotte, North Carolina, is on a quest to become the most valuable automotive retailer and service brand in America. Our Company culture thrives on creating, innovating, and providing industry-leading guest experiences, driven by strategic investments in technology, teammates, and ideas that ultimately fulfill ownership dreams, enrich lives, and deliver happiness to our guests and teammates. As one of the largest automotive retailers in America, we are committed to delivering on this goal while pursuing expansive growth and taking progressive measures to be the leader in this category. Our new platforms, programs, and people are set to drive the next generation of automotive experiences. More information about Sonic Automotive can be found at and

Sonic can be used as a simple alternative to super-heavy and full-featured search backends such as Elasticsearch in some use-cases. It is capable of normalizing natural language search queries, auto-completing a search query and providing the most relevant results for a query. Sonic is an identifier index, rather than a document index; when queried, it returns IDs that can then be used to refer to the matched documents in an external database.

A strong attention to performance and code cleanliness has been given when designing Sonic. It aims at being crash-free, super-fast and puts minimum strain on server resources (our measurements have shown that Sonic - when under load - responds to search queries in the μs range, eats 30MB RAM and has a low CPU footprint; see our benchmarks).

Sonic is integrated in all Crisp search products on the Crisp platform. It is used to index half a billion objects on a $5/mth 1-vCPU SSD cloud server (as of 2019). Crisp users use it to search in their messages, conversations, contacts, helpdesk articles and more.

You can test Sonic live on: Crisp Helpdesk, and get an idea of the speed and relevance of Sonic search results. You can also test search suggestions from there: start typing at least 2 characters for a word, and get suggested a full word (press the tab key to expand suggestion). Both search and suggestions are powered by Sonic.

Both searches and object management (i.e. data ingestion) is handled via the Sonic Channel protocol only. As we want to keep things simple with Sonic (similarly to how Redis does it), Sonic does not offer a HTTP endpoint or similar; connecting via Sonic Channel is the way to go when you need to interact with the Sonic search database.

Sonic supports a wide range of languages in its lexing system. If a language is not in this list, you will still be able to push this language to the search index, but stop-words will not be eluded, which could lead to lower-quality search results.

Sonic was built for Crisp from the start. As Crisp was growing and indexing more and more search data into a full-text search SQL database, we decided it was time to switch to a proper search backend system. When reviewing Elasticsearch (ELS) and others, we found those were full-featured heavyweight systems that did not scale well with Crisp's freemium-based cost structure.

We want to import all those messages into a clean Sonic instance, and then perform searches on the index we built. We will measure the time that Sonic spent executing each operation (ie. each PUSH and QUERY commands over Sonic Channel), and group results per 1,000 operations (this outputs a mean time per 1,000 operations).

Information from the National Library of Medicine Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the contacts provided below. For general information, Learn About Clinical Studies. Layout table for eligibility information Ages Eligible for Study: 19 Years to 75 Years (Adult, Older Adult) Sexes Eligible for Study: All Accepts Healthy Volunteers: Yes Criteria Inclusion Criteria: 041b061a72

  • About

    Welcome to the group! You can connect with other members, ge...

    Group Page: Groups_SingleGroup
    bottom of page