This evening I attempted to help my wife upload data from her $9000 insulin pump to the crappy Java driven web app on Carelink.medtronic.com that she has to use to extract her data from the pump. I was greeted with the error screen above.
Medtronic is blocking the current version of MacOS from even accessing the website, let alone using the crappy Java web app they wrote over 10 years ago to extract data from the pump.
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We called the 24-hour helpline, and after navigating past the tier one help desk person that didn't understand 'Mac OSX' = Macintosh computer, we got to somebody that was computer literate. She informed us that the website was not compatible with OSX 10.13.2, and she didn't know when it would be. The best she could do was put us on the email list for notification for when all the reporting functions for my wife's $9000 insulin pump wouldn't be crippled.
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After fuming for a few minutes I thought of a workaround, and it worked. If you need to get into the crappy Java web app on Carelink and you are using a Mac updated to High Sierra and Safari, this works. https://torrentfabric.mystrikingly.com/blog/ewd-mac-os.
Go into the Preferences Menu in Safari and select the Advanced Tab. At the bottom, you should see the Show Develop Bar in Menu option. Check the box to turn that option on, and close out preferences.
You should now have a new option in the top menu of Safari, called Develop. Marcos speaks mac os. Click it, and you should see this.
Scroll to the second option, user agent, and select the bottom option of Other on the submenu. Right now, Medtronic is blocking any web browser coming from OSX 10.13.2. So we are going to configure Safari to lie and tell the web server that we are using the older version of OSX.
When you select other you'll get an editable text box that looks like this.
You should see the text string 10_13_2 in there. All you have to do is change that to 10_12_6 to fool Minimed's web server into thinking you are still on the older version of OSX. After you do that and close out you should be able to use the Carelink web site like normal.
One you are done with Carelink don't forget to go back into Developer / User Agent and select default so that the browser reports accurately again.
Also, don't forget to keep complaining to Medtronic, your Endocrinologist, your Diabetes Educator, and anybody else that will listen about how crappy Carelink is. It's 2017, there is no excuse for insulin pump users to be stuck using such shitty software.
Also, if anybody from Medtronic is reading this, Carelink works fine with OSX 10.13.2, I'm not sure what you people have been doing for the last 12 weeks with the website.
Recent bugfixes
Version 2.1 (6 Aug 2004)
- includes new MontyNLGenerator component generates sentences and summaries
Version 2.0.1
- fixes API bug in version 2.0 which prevents java api from being callable
What is MontyLingua?[top]
MontyLingua is a free*, commonsense-enriched, end-to-end natural language understander for English. Feed raw English text into MontyLingua, and the output will be a semantic interpretation of that text. Perfect for information retrieval and extraction, request processing, and question answering. From English sentences, it extracts subject/verb/object tuples, extracts adjectives, noun phrases and verb phrases, and extracts people's names, places, events, dates and times, and other semantic information. MontyLingua makes traditionally difficult language processing tasks trivial!
Version 2.0 is substantially FASTER, MORE ACCURATE, and MORE RELIABLE than version 1.3.1. It has now been tested across Windows, many flavors of UNIX, and Mac OS X, and several flavors of Java, and is in use by several university research projects and under several commercial settings.
MontyLingua differs from other natural language processing tools because:
- it is complete end-to-end. input raw_text; output semantic interpretation
- not many dated tools and implementations sewn together; it is one well-integrated implementation
- it does not require 'training' and other fidgetting, and will work right out-of-the-box
- it is enriched with 'common sense' knowledge about the everyday world, allowing it to escape many stupid interpretive mistakes. e.g.:
- '(NX the/DT mosquito/NN bit/NN NX) (NX the/DT boy/NN NX)' corrected>
- '(NX the/DT mosquito/NN NX) (VX bit/VBD VX) (NX the/DT boy/NN NX)'
- it is lightweight and portable across platforms, written in portable Python and also available as a compiled Java library
- it is easy to customize by allowing for a user lexicon
MontyLingua performs the following tasks over text:
- MontyTokenizer - Tokenizes raw English text (sensitive to abbreviations), and resolve contractions, e.g. 'you're' > 'you are'
- MontyTagger - Part-of-speech tagging based on Brill94, enriched with common sense.
- MontyChunker - Lightning fast regular expression chunker
- MontyExtractor - Extracts phrases and subject/verb/object triplets from sentences
- MontyLemmatiser - Strips inflectional morphology, i.e. changes verbs to infinitive form and nouns to singular form
- MontyNLGenerator - Uses MontyLingua's concise predicate-arg representation to generate naturalistic English sentences and text summaries
* free for non-commercial use. please see MontyLingua Version 2.0 License
Terms of Use [top]
Author: Hugo Liu
Project Page:
Terms of Use Copyright (c) 2002-2004 by Hugo Liu, MIT Media Lab Wake me up (interactive music clip) mac os. Please cite montylingua in academic publications as: Liu, Hugo (2004). MontyLingua: An end-to-end natural |
Documentation [top]
python documentation and api (html) [.html] |
java documentation and api [.html] |
MontyLingua license [.txt] |
Download free slot machine. Version 2.1 (6 Aug 2004)
- includes new MontyNLGenerator component generates sentences and summaries
Version 2.0.1
- fixes API bug in version 2.0 which prevents java api from being callable
New in version 2.0 (29 Jul 2004)
- 2.5X speed enhancement for whole system, 2X speed enhancement for tagger component
- rule-based chunker replaced with much faster and more accurate regular expression chunker
- common sense added to MontyTagger component improves word-level tagger accuracy to 97%
- updated and expanded lexicon for English
- added a user-customizable lexicon CUSTOMLEXICON.MDF
- improvements to MontyLemmatiser incorporating exception cases
- html documentation added
- speed optimizations to all code
- improvements made to semantic extraction
- expanded Java API
Download MontyLingua[top]
Please read the following information to proceed to the download of Version 2.1 for Java and Python.
MontyLingua version 2.1 Terms of UseCopyright (c) 2002-2004 by Hugo Liu, MIT Media LabAll rights reserved.Non-commercial use is free, as provided in the MontyLingua version 2.0 License. By downloading and using MontyLingua, you agree to abide by the additional copyright and licensing information in 'license.txt', included in this distribution.If you use this software in your research, please acknowledge MontyLingua and its author, and link to back to the project page http://web.media.mit.edu/~hugo/montylingua.Please cite montylingua in academic publications as: Liu, Hugo (2004). MontyLingua: An end-to-end naturallanguage processor with common sense. Available at: web.media.mit.edu/~hugo/montylingua. If you have read and agree to the terms of use, click below to continue to the download (Download is a 12 MB zip file) |
READ THIS if you are running ML on Mac OS X, or Unix Free sloto coins.
- The distribution ZIP includes datafiles designed for windows. If you are running MontyLingua on Unix or Mac OS X, and the phrase 'I love you' is tagged incorrectly, then the datafiles need to be rebuilt. This is simple:
- delete all files of the form, FASTLEXICON_n.MDF, where n is a number.
- re-run the MontyLingua program, either from Python, or Java, and the correct datafiles will be rebuilt. If running Java and you run out of memory during the rebuild process, use the -MX or -Xmx option in Java to increase the memory size. You will only need to rebuild these datafiles once.
Research and Industry Applications which use MontyLingua [top]
These are some of the research and industry projects which use MontyLingua and MontyTagger. To submit your project, email a web url and short description to the author.
William W. Cohen (2004) Minorthird: Methods for Identifying Names and Ontological Relations in Text using Heuristics for Inducing Regularities from Data, http://minorthird.sourceforge.net (website)
Jacob Eisenstein and Randall Davis. Visual and Linguistic Information in Gesture Classification. Accepted to International Conference on Multimodal Interfaces (ICMI'04)(paper)
L. Xie, L. Kennedy, S.-F. Chang, A. Divakaran, H. Sun, C.-Y. Lin (2004). 'Discovering Meaningful Multimedia Patterns with Audio-visual Concepts and Associated Text.' IEEE International Conference on Image Processing (ICIP 2004), Singapore, October 2004. (paper)
Ashwani Kumar, Sharad C. Sundararajan, Henry Lieberman (2004). Common Sense Investing: Bridging the Gap Between Expert and Novice. Conference on Human Factors in Computing Systems (CHI 04), Vienna, Austria.
Hugo Liu and Push Singh (2004) ConceptNet: A Practical Commonsense Reasoning Toolkit. BT Technology Journal, upcoming. Kluwer Academic Publishers. (website)
Google for MontyLingua and MontyTagger to see who else has been using this software.