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Thursday, November 9th, 2023

 

Kalikow Senior Presidential Fellows Ari Fleischer, Former White House Press Secretary, George W. Bush Administration, and Phil Schiliro, Political Strategist and Former Director of Legislative Affairs, Barack Obama Administration, will discuss the 2024 election.

 

PANELISTS:

 

Ari Fleischer

 

Media Consultant; White House Press Secretary, George W. Bush Administration

 

Phil Schiliro

 

Political Strategist; Director of Legislative Affairs, Barack Obama Administration

 

MODERATOR:

 

Meena Bose

 

Executive Dean, Kalikow School; Director, Kalikow Center; Peter S. Kalikow Chair in Presidential Studies; Professor of Political Science

 

This event is FREE and open to the public. Advanced registration is required.

 

Join the conversation on social media via #HofstraVotes and #KalikowPanel.

 

For more information, call the Hofstra Cultural Center at 516-463-5669 or visit hofstra.edu/kalikow.

 

Photo: Matteo Bracco

 

Team Predictor Lotto preparing for the Tour de France Prologue

Predicted snow accumulations are continuing to grow for the upper Midwest. Check out the totals below!

PREDICTIVE ART BOT V.3

Photo : Gabriel Asper, CC NC-SA 4.0

 

Predictive Art Bot is an algorithm that uses current discourse as a basis to create concepts for artistic projects and, at times, prophesize absurd future trajectories for art.

Algorithms are now widely used in different fields to make predictions using data analysis, statistical analysis, and pattern recognition for applications including the purchasing behavior of particular groups, global market developments and even potential crimes. In contrast, the Predictive Art Bot is a specialist in making art forecasts, published daily on Twitter, which are meant to expand the limited human imagination with new, non-human perspectives.

As a parody of transhumanist prophecies, the Predictive Art Bot liberates artists from the constraints of creativity and develops ideas not yet implemented or conceived by humans. — Inke Arns

 

Conception : DISNOVATION.ORG

Programming : Jérôme Jerome Saint-Clair

Stopping on the side to take in the amazing views right by the Leavitt Peak\Night Cap Peak around the Sonora Pass. Simply stunning here indeed! This was along California 108 westbound. This was during my (very) spontaneous road trip up to the Sierras. I was on the long road back home at the time, taking in last minute scenic views...

 

*My trip in summary: I drove on the crazy, winding California 108. I even passed by Pinecrest and Dardanelle, places where our family camping trips took place before. It was sad to see wildfire damage around the Dardanelle campgrounds… Some rain was witnessed along the way, nothing exciting. The funny thing was that this was supposed to be a ‘storm chase’ outing since I was bummed that the monsoonal surge that they predicted didn’t come to fruition around the Bay Area. Out of frustration, I left after 9:30 a.m. and headed up to the Sierras to hopefully see some t-storms. I went all the way to the Mono Lake Vista point near Lee Vining, CA (arrived by around 3:15 p.m.) There, I finally saw t-storms with a few distant lightning bolts. Those few bolts made the 4+ hour drive worth it sort of. I then started heading back by 5 p.m., taking in the views along the way. At this point, it was more about the scenic views, trying to make the drive more worth it. I stopped a few times to take in the stunning views on the side, including around the Sonora Pass (sign) and Donnell Vista. I hurried to get down the mountains before dark since I didn’t wanna get caught driving in the dark there. Thankfully, I made it down safely and was able to see the sunset as I entered the vast Central Valley, near Jamestown, CA (western Tuolumne County). I finally got home around 10:30 p.m. I was quite exhausted afterwards and I even had work the very next day. Anyway, what an adventure I had this day! ‘Til next time, safe travels everyone!

 

(Outing taken place Monday, July 19, 2021)

PdM-2007 The Predictive Maintenance Technology Conference Las Vegas NV

How Doctors Can Predict Who Dies From COVID

 

There are a number of studies that have come out about COVID 19 prognosis. We now have a powerful way to predict which patients with COVID 19 pneumonia are more likely to die, and more likely to require longer stays in the hospital.

 

We already know that less than 15% of people who get COVID 19 have severe disease to the point of requiring hospitalization. Less than 5% of people who get coronavirus require ICU. For those with COVID 19 pneumonia who require ICU, and for some of the other patients in the hospital who might not necessarily need ICU, these are the patients who have the cytokine storm that we keep hearing about, meaning the immune system is going haywire, and there is a ton of inflammation taking place in the body….especially the lungs. But now, we have a more specific way of predicting who is more likely to develop cytokine storm, and therefore more likely to die, and who is more likely to require a longer stay in the hospital….and it's based on the bloodwork we get when patients are hospitalized.

PdM-2007 The Predictive Maintenance Technology Conference Las Vegas NV

NiMet predicts thundery, rainy activities for Monday By Gabriel Agbeja Weather Abuja, Sept. 1, 2019 The Nigerian Meteorological Agency (NiMet) has predicted increased cloudiness with prospect of localised thunderstorms and rains for Monday. NiMet’s weather outlook on Sunday in Abuja forecast thunderstorms and rains over the Northern and Central cities with cloudy conditions to isolated […]

  

nnn.com.ng/2019/09/01/nimet-predicts-thundery-rainy-activ...

Tide Prediction Machines (TPMs) were analogue computers (LEGO Machine) which provided an accurate and efficient means of predicting the ocean tide. The TPM was invented in the late 19th century, but most of them were made in the first half of the 20th century, up until the time that the advent of digital computers consigned them to museums.

 

“Time and tide will wait for no man, saith the adage. But all men have to wait for time and tide.”

Charles Dickens

 

One could undertake such a tedious arithmetic computation oneself, by calculating the height of the tide every hour during the year and by plotting the resulting time series. However, it was Lord Kelvin's realisation that TPMs could provide a means for undertaking such a task more efficiently, their accuracy being limited only by the number of constituents included in their design.

 

If one knows the amplitudes and phases of each constituent at a point on the cost (“the harmonic constants), then it is possible to compute the tide at that position for any time, either by considerable arithmetic or with the use of a TPM.

 

Each TPM had its own architecture. However, there were several features common to almost all of them. First a TPM had to have a driving mechanism to provide a circular motion with an angular frequency corresponding to that of a tidal constituent. Second, a TPM required a mechanism for converting that circular motion into sinusoidal motion and third it had to sum the individual sinusoidal motions to derive an overall sum.

 

The video (youtu.be/sAyVcM3g4q4?si=7OJdIBY-CsYugGXb) indicates the circular motion of a crank, with a pin fixed in the crank, which is free to move along the axles. The pulley wheel itself is allowed to move up and down in a vertical direction only. Therefore, its elevation will vary by the distance of the pin from the centre or the amplitude of the constituent.

 

The pully wheels have the following properties (from left to right):

• K1 (lunar) - amplitude: 0.61 studs; frequency: 24h: phase lag: 54 degree

• O1 (lunar) - amplitude: 0.39 studs; frequency: 24h; phase lag: 144 degree

• M2 (lunar) - amplitude: 1.25 studs; frequency: 12;. phase lag: 126 degree

• S2 (solar) - amplitude: 0.75 studs; frequency: 12h; phase lag: 0 degree

 

Then, as the crank rotates, the pulley wheel will rise and fall, thereby simulating the variation in water level due to that constituent. Four of such units can be geared to the main shaft so that the individual speeds are proportional to those of the four constituents. All motions are summed by using a continuous band. The band is fixed at one end and wraps around the four pulley wheels. At its other end it has a pointer which plots the height of the tide on the rotating cylinder.

Terrence O'Hanlon delivered the Keynote for FLIR's Inframation Infrared Conference in Nashville TN May 2015

Thursday, November 9th, 2023

 

Kalikow Senior Presidential Fellows Ari Fleischer, Former White House Press Secretary, George W. Bush Administration, and Phil Schiliro, Political Strategist and Former Director of Legislative Affairs, Barack Obama Administration, will discuss the 2024 election.

 

PANELISTS:

 

Ari Fleischer

 

Media Consultant; White House Press Secretary, George W. Bush Administration

 

Phil Schiliro

 

Political Strategist; Director of Legislative Affairs, Barack Obama Administration

 

MODERATOR:

 

Meena Bose

 

Executive Dean, Kalikow School; Director, Kalikow Center; Peter S. Kalikow Chair in Presidential Studies; Professor of Political Science

 

This event is FREE and open to the public. Advanced registration is required.

 

Join the conversation on social media via #HofstraVotes and #KalikowPanel.

 

For more information, call the Hofstra Cultural Center at 516-463-5669 or visit hofstra.edu/kalikow.

 

Photo: Matteo Bracco

 

The Global Healthcare Predictive Analytics Market size is expected to reach $7.8 billion by 2025, rising at a market growth of 21.17% CAGR during the forecast period.

 

Predictive analytics is a type of data analytics which makes predictions about the future outcomes on the basis of historical data and analytics techniques like machine learning and statistical modeling. Predictive analytics helps in generating future insights with a significant precision degree. Predictive analytics provides healthcare decision-makers the chance for ideal future results. Based on decision optimization technology, these capacities allow users not only to recommend the best course of action for patients or suppliers but also to compare multiple "what if" scenarios to evaluate the effect of selecting one action over another.

 

Full Report: www.kbvresearch.com/healthcare-predictive-analytics-market/

illustration for The NYT Opinion Letters section about new strides to predict Alzheimers

the groundhog predicts an early spring.

But there is a slight rain now. I'm on the Tree of Life theatre

staying dry. Getting here is sure a long hike though.

PdM-2007 The Predictive Maintenance Technology Conference Las Vegas NV

PdM-2007 The Predictive Maintenance Technology Conference Las Vegas NV

Tide Prediction Machines (TPMs) were analogue computers (LEGO Machine) which provided an accurate and efficient means of predicting the ocean tide. The TPM was invented in the late 19th century, but most of them were made in the first half of the 20th century, up until the time that the advent of digital computers consigned them to museums.

 

“Time and tide will wait for no man, saith the adage. But all men have to wait for time and tide.”

Charles Dickens

 

One could undertake such a tedious arithmetic computation oneself, by calculating the height of the tide every hour during the year and by plotting the resulting time series. However, it was Lord Kelvin's realisation that TPMs could provide a means for undertaking such a task more efficiently, their accuracy being limited only by the number of constituents included in their design.

 

If one knows the amplitudes and phases of each constituent at a point on the cost (“the harmonic constants), then it is possible to compute the tide at that position for any time, either by considerable arithmetic or with the use of a TPM.

 

Each TPM had its own architecture. However, there were several features common to almost all of them. First a TPM had to have a driving mechanism to provide a circular motion with an angular frequency corresponding to that of a tidal constituent. Second, a TPM required a mechanism for converting that circular motion into sinusoidal motion and third it had to sum the individual sinusoidal motions to derive an overall sum.

 

The video (youtu.be/sAyVcM3g4q4?si=7OJdIBY-CsYugGXb) indicates the circular motion of a crank, with a pin fixed in the crank, which is free to move along the axles. The pulley wheel itself is allowed to move up and down in a vertical direction only. Therefore, its elevation will vary by the distance of the pin from the centre or the amplitude of the constituent.

 

The pully wheels have the following properties (from left to right):

• K1 (lunar) - amplitude: 0.61 studs; frequency: 24h: phase lag: 54 degree

• O1 (lunar) - amplitude: 0.39 studs; frequency: 24h; phase lag: 144 degree

• M2 (lunar) - amplitude: 1.25 studs; frequency: 12;. phase lag: 126 degree

• S2 (solar) - amplitude: 0.75 studs; frequency: 12h; phase lag: 0 degree

 

Then, as the crank rotates, the pulley wheel will rise and fall, thereby simulating the variation in water level due to that constituent. Four of such units can be geared to the main shaft so that the individual speeds are proportional to those of the four constituents. All motions are summed by using a continuous band. The band is fixed at one end and wraps around the four pulley wheels. At its other end it has a pointer which plots the height of the tide on the rotating cylinder.

Predicting hail and TOR-nados, woo!

PdM-2007 The Predictive Maintenance Technology Conference Las Vegas NV

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