[Video] The High Failure Rate of Research and Development

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A detailed discussion of the high failure rate of research and development with some comments on Operation Warp Speed, the Manhattan Project, the War on Cancer, and the invention of powered flight.

Reference(s):

https://www.statista.com/statistics/184566/deaths-by-cancer-in-the-us-since-1950/

An article showing the increase in cancer death rates from 1950 to the mid 1990’s, overlapping the War on Cancer, followed by more recent decline. Cancer remains a leading cause of death in the US.

The Manhattan Project Considered as a Fluke: https://mathblog.com/the-manhattan-project-considered-as-a-fluke/

The Mathematics of the Manhattan Project:
https://mathblog.com/the-mathematics-of-the-manhattan-project/

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(C) 2021 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video] The CDC’s Grossly Contradictory Flu Death Numbers

Graph Showing Contradictory CDC Pneumonia and Influenza Death Numbers
The CDC’s Grossly Contradictory Flu Death Numbers

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The United States Centers for Disease Control (CDC) has at least three different, grossly contradictory historical pneumonia and influenza death numbers. Pneumonia and influenza are often conflated in the CDC’s documentation and influenza death model. These death numbers are frequently used as the baseline for comparison of COVID-19 death numbers and assessing the severity of the pandemic relative to previous years and influenza pandemics.

Leading Causes of Death Pneumonia and Influenza (P&I) Deaths (About 55,000 per year)

FluView Pneumonia and Influenza (P&I) Deaths (About 188,000 pre-COVID, Over THREE TIMES Leading Causes of Death, About 5-15,000 Influenza Deaths Per Year)

CDC Model Influenza Only Deaths (About 55,000 per year, at least THREE TIMES FluView Influenza Deaths)

This video discusses these different contradictory numbers and their implications for the COVID-19 pandemic.

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About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video] Scientists are People Too

Scientists are People Too

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Scientists are People Too

Think of scientists as lawyers and not ministers or other trusted professions. High intelligence is not correlated with moral character.

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(C) 2021 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Article] How to Unplug

This is a short article on how to unplug from anxiety-inducing, conflict-promoting, mind-clouding social media, the Internet, computer and smartphone apps, and other devices and software. It first discusses why you should “unplug” from these sources. If you are already convinced that you should “unplug” you can skip ahead to the second section on how to unplug.

Why unplug?

We now have communication and persuasion technologies far beyond anything in history, far beyond even a few years ago. We have inexpensive gigantic display screens with very high resolution high contrast imagery, high quality stereo and even 3D surround sound delivering life-size realistic images and video to most homes, offices, and many public places including airports, cafeterias, gyms, restaurants and bars.

Video and images are frequently manipulated with powerful still image and video editors and may be merged with computer generated images which can be completely indistinguishable from real images and video. Movies such as the recent Star Wars movies feature entirely realistic computer generated video of deceased actors such as Carrie Fisher and Peter Cushing.

These displays are combined with powerful algorithms, city-sized computers — “data centers” — and teams of engineers at social media giants such as Google, Facebook, and Netflix working 24/7 to attract and hold viewers usually to watch advertising and sell products and services.

Our understanding of cognitive biases is greater than ever. Social psychologists have learned that knowledge of these cognitive biases does not immunize people from the adverse effects and bad decisions caused by cognitive biases. Even cognitive bias expert Daniel Kahneman fell prey to cognitive biases in his book on cognitive biases! In fact this knowledge of cognitive biases can give people a false sense of security and an arsenal of excuses to rationalize away contradictory evidence or logical arguments: those people who disagree with me are driven by this or that cognitive bias and I clearly know better. Google, Facebook and others have hired experts and students from the Stanford Persuasive Technology Lab and similar research groups to apply this knowledge of cognitive biases to capturing eyeballs and selling the products and services of their advertisers.

Media scholars have referred to modern media methods and technology as hyperreal — more real than real. They not only seem real but can be more engaging and addictive than reality.

The campaign for eyeballs and advertising dollars with this new technology relies heavily on hyperbolic headlines and content that produces outrage, fear, anger, and other strong emotions — frequently to drive viewers into the primal fight-or-flight response which generally degrades high cognitive function, the ability to analyze and process complex longer term issues and problems. This has accelerated dramatically with the COVID-19 pandemic.

Numerous media organizations have shifted from bland, ostensibly objective factual reporting to hyper-partisan, often venomous, shallow emotional “reporting.” Fox News, MSNBC, and CNN are extreme examples of this widespread trend. Reporter Matt Taibbi has labeled this new media landscape as Hate Inc.

This modern technology is far beyond the yellow journalism of the 1910’s that contributed to the outbreak of the First World War that killed about 8.5 million soldiers and about 13 million civilians. Companies such as Google and Facebook know far more about their customers and their hot buttons than the media empires of the past, even just a few decades ago.

If you want to think clearly, carefully, and accurately about public policy issues such as the COVID-19 pandemic, what products and services to use or buy, and even to recognize that the media is selling a product or service to you, you need to unplug from this onslaught of modern persuasive technology and high tech propaganda.

How to Unplug

Banish computers, smartphones and other devices from your bedroom.

Turn off screens at least an hour before going to sleep.

Wait at least one half hour before turning on screens when wake up.

Avoid smartphone use. Put your phone in airplane mode and keep it in an RF-shielded secure case most of the time. Only use when absolutely necessary.

Avoid/minimize other mobile device use such as laptops.

Take social media apps and other non-essential apps off smartphone. Turn off all notifications except messages from live friends, family, and colleagues.

Don’t watch fear/outrage cable news, television, and other video sources such as Fox News, CNN, and MSNBC. If something makes you fear, hate, scorn or ridicule some other group, stop watching.

Completely unplug from computers and Internet one day (or more) per week. Exercise, clean and organize your home, cook some food for the week ahead, read a physical book, spend time with friends or family. (If possible)

Set aside limited time periods for ‘bad news’ or other difficult topics. Don’t allow them to be 24/7.

Diversify away from centralized advertising funded sources such as Google and Facebook that use opaque algorithms and teams to manipulate search results or social media feeds.

The Center for Humane Technology has some additional suggestions that may be helpful on their Take Control web page.

Conclusion

Unplugging from anxiety-inducing, mind-clouding social media, apps, the Internet and devices is doable and essential to think clearly and carefully, to make wise decisions on what products and services to use and buy and how to live in the modern world.

(C) 2021 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video] Frederick Douglass No Progress Without Struggle

Frederick Douglass: No Progress Without Struggle

Short video reciting the two most famous paragraphs from Frederick Douglass’s most famous speech. Gives some context about the speech before the passage. Frederick Douglass was the leading Black American abolitionist of the 1800’s and also the most photographed American of his time with 160 surviving photographs.

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(C) 2021 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video] The Not-So-Secret Romantic Comedy Formula

With Valentine’s Day fast approaching, a lighthearted look at romantic comedy movies with many examples you and your significant other might enjoy.

Alternate Video Links: NewTube Brighteon Archive LBRY

(C) 2021 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

Many Seeming Routes for Efficient Spread of COVID-19 in Santa Clara County, California

In spite of and even because of the stay-at-home, lockdown and other restrictions by health authorities in Santa Clara County, California (USA), there are many plausible routes for rapid efficient spread of the SARS-COV-2 virus presumed to cause COVID-19 in the county. Despite this, total deaths attributed to COVID-19 in the year 2020 remained remarkably low, comparable to expected deaths from pneumonia and influenza in prior years. This may of course change in the coming year.

Many probable routes of transmission are discussed and illustrated with pictures below.

Many Seeming Routes for Rapid Spread of the Disease

Santa Clara County, California (United States) continues to authorize many luxury apartment and other construction projects with teams of workers in close proximity five full days per week, after a brief 3-4 week shutdown in May. The lockdown herds large numbers of citizens into a few gigantic stores such as Safeway, Walmart, and Target, enabling what would seem like an efficient route for rapid spread of the disease. The lockdown also confines a large proportion of residents to large apartment complexes with many seemingly easy routes of transmission. “Essential” workers and others continue to use the county bus service which confines workers and others to an enclosed shared space for many minutes each day.

Ongoing Construction Projects

Santa Clara County continues to authorize many luxury apartment and other construction projects with teams of workers in close proximity five full days per week, after a brief 3-4 week shutdown in May — several weeks after the original lockdown order. On a personal note, a four-story luxury apartment building construction project with at least a dozen workers every weekday from about 7:30 am to 4:30 pm has continued across the street from my apartment building since the original lockdown order except for the brief shutdown in May.

Santa Clara County Allows Construction Projects Despite COVID-19
Over a Dozen Construction Workers Arriving for Work on Luxury Apartment Project in Santa Clara County, CA (August 6, 2020)
Construction Workers in Close Proximity (Santa Clara County, Dec. 7, 2020)

Herding Residents into Big Box Retail Stores

The lockdown continues to herd large numbers of citizens in Santa Clara County into a few gigantic stores such as Safeway, Walmart, and Target, enabling what would seem like an efficient route for rapid spread of the disease.

Safeway with Over Thirty Cars in Parking Lot (about 9:30 AM, December 7, 2020, Santa Clara County)

These giant “Big Box” retail stores have heavily used shared spaces and surfaces where one would expect the virus will rapidly spread. These include the entry/exit door areas, checkout counters, and refrigerators with popular products such as milk purchased by a large fraction of the customers and with door handles that all purchasers must use. These large stores often have hundreds of patrons in the store at the same time — all day, seven days per week.

Milk and other dairy products in a refrigerator with door handle that customers must use

In Santa Clara County, the lockdowns have closed or heavily curtailed restaurants, popular with the large population of single people and leading to a large increase in demand for microwave dinners often found in store refrigerators with door handles that must be used by the customers.

Microwave dinners in store refrigerator with door handle that customers must use

Several other specific scenarios exist for rapid efficient spread of the virus through these giant retail stores.

Bus Service for “Essential” Workers and Others

Santa Clara County also has a bus service, the VTA or Valley Transportation Authority, in widespread use with patrons, often “essential workers,” sharing an enclosed space and seats.

VTA Bus in Operation on December 7, 2020, Santa Clara County, California

Giant Apartment Complexes are Common in Santa Clara County

The lockdown shelter in place and stay at home orders confine “non-essential workers” to numerous generally large apartment complexes, often with hundreds of tenants, possibly thousands in some cases. In Mountain View, California — site of Google’s headquarters — about fifty-eight percent of residents (Town Charts, see Figure 5) are renters, most in large complexes. These complexes feature shared trash chutes/rooms, laundry rooms, hallways and lobbies with exterior doors and fire doors that must be opened by hand in most cases, providing many shared surfaces and spaces for spread of the virus.

Typical Trash Chute Room with Fire Door in Santa Clara County — Note Door Handle (December 7, 2020)
Typical Trash Room Interior with Trash Chute (Note Handle) in Santa Clara County (December 7, 2020)
Typical Laundry Room Door with Handle in Santa Clara County (December 7, 2020)

Note that fire regulations require closely spaced closed fire doors in the interior hallways — with handles or knobs that all residents must use to open the fire doors.

The large apartment complexes common in Santa Clara County provide numerous shared spaces where aerosol virus particles can collect and linger in the air as well as shared surfaces such as door handles that all residents must touch.

Gloves are not required. Gloves would have to be handled carefully and sterilized before and after each or nearly each use to avoid spreading the virus, something probably impractical and certainly currently NOT done by most residents.

In general, the apartment complex support staff cannot clean each door handle after each use. The shared support staff themselves are a high risk of both becoming infected and spreading the infection to other residents. Almost none have training or experience in bio-safety measures.

Conclusion

Despite hyperbolic headlines and reasonable expectations, deaths attributed to COVID-19 have remained remarkably low in 2020, although that may — of course — change. We will see if the usual winter surge in cases and deaths from respiratory illnesses subsides for COVID-19 or not. Prediction is notoriously difficult — especially about the future. As demonstrated above, this appears to have been in spite of rather than because of the stay-at-home and lockdown measures.

The reasons for this remarkably low death rate in Santa Clara County in 2020 remain unknown. Possible explanations include the bright sunny climate — among the most pleasant in the world, close long term past contact with China contributing to a high pre-existing immunity or resistance to SARS type coronaviruses in general, some genetic or cultural difference in Santa Clara County’s heavily Asian population (death rates in Japan and other Asian nations have been quite low compared to the United States or Europe if official figures are to be believed), better treatment of patients such as avoiding intubation, higher consumption of vitamin D by the health conscious residents, or some other cause.

(C) 2021 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

Continuing Improbably Low COVID Deaths in Santa Clara County, California (USA)

COVID-19 Deaths Reported by Santa Clara County, CA on January 6, 2021

COVID-19 deaths in Santa Clara County, California remain remarkably low as the New Year (2021) begins.

Despite frightening headlines and increased lockdown orders, total COVID-19 deaths in Santa Clara County, California remain remarkably low with total officially reported deaths of only 799 in a county with 1.9 million and close contact with China, the presumed source of the pandemic. This is a number comparable to the number of expected deaths in the county from ordinary pneumonia and influenza based on previous years.

The county continues to authorize many luxury apartment and other construction projects with teams of workers in close proximity five full days per week, after a brief 3-4 week shutdown in May. The lockdown continues to herd large numbers of citizens into a few gigantic stores such as Safeway, Walmart, and Target, enabling what would seem like an efficient route for rapid spread of the disease.

Santa Clara County has a population of about 1.9 million people in 2019 according to the US Census with 10,889 total deaths in 2015, the last year for which I could find an exact death count, according to the Office of the Medical Examiner-Coroner for the County of Santa Clara. The most recent estimated death rate for the United States in 2018 was 867.8 deaths per 100,000 people according the US Centers for Disease Control. One point nine million (1.9 million) is nineteen (19) times 100,000. This means an estimated number of deaths in Santa Clara County of nineteen (19) times 867.8 or 16,488 expected deaths in 2020 from all causes.

What percentage of these 16,488 expected deaths would be attributed to pneumonia and influenza in pre-COVID-19 years (2019 and earlier)? The CDC FluView web site shows that six to ten percent of deaths, varying seasonally, are due to pneumonia and influenza (P&I) according to the vertical axis label on the FluView Pneumonia & Influenza Mortality plot, meaning at least six percent of the deaths or 989 deaths would be due to pneumonia and influenza.

US Centers for Disease Control (CDC) FluView Pneumonia & Influenza Mortality Plot (Dec. 4, 2020)

NOTE: https://www.cdc.gov/flu/weekly/fluviewinteractive.htm and click on P&I Mortality Tab

Note also that deaths attributed to “pneumonia and influenza” on the FluView web site are highly seasonal. A substantial increase over the summer is expected during the winter (or rainy season in Northern California), peaking in December and January each year.

Also note that the seasonal variation is sinusoidal — like the oscillation of a pendulum or a mechanical spring. Contrary to popular culture, there is no clear step up when schools open in the fall or step down when schools close for the summer. It looks very much like something driven by the Sun, directly or indirectly by some mechanism or mechanisms. Possible mechanisms include Vitamin D production from sunlight, destruction of viruses and bacteria in the air or on surfaces by ultraviolet light in sunlight, general health benefits of a warm environment, or some other Sun-driven phenomenon.

In contrast, the CDC’s leading causes of death report Table C, Deaths and percentage of total deaths for the 10 leading causes of death: United States, 2016 and 2017 on Page Nine (see screenshot below) attributes only two percent of annual deaths (about 55,000 in 2017) to “influenza and pneumonia.” If this smaller number is used, we would expect about 329 deaths from pneumonia and influenza in Santa Clara County, California (USA) in 2020.

The difference between the CDC FluView and leading causes of death report numbers is probably due to the requirement that pneumonia or influenza be listed as “the underlying cause of death” in the leading causes of death report and only “a cause of death” in the FluView data. This is not clear. Many deaths have multiple “causes of death.” The assignment of an “underlying cause of death” may be quite arbitrary in some cases. Despite this, none of these official numbers either in the leading causes of death report or the FluView web site are reported with error bars or error estimates as required by common scientific and engineering practice when numbers are uncertain.

A longer, more detailed discussion of the FluView, leading causes of death, and the CDC’s influenza virus death model death numbers (yet another number) may be found below. It appears likely the FluView death numbers are defined similarly to current COVID-19 death counts; the reasons for this are explained in some detail.

Screenshots of the official CDC, Santa Clara County, and US Census web sites used for these estimates of typical pneumonia and influenza death numbers in Santa Clara County (screenshots taken on Friday, December 4, 2020):

Santa Clara County Total Reported Deaths from 2000 to 2015
Santa Clara County Population from US Census Bureau
US Centers for Disease Control (CDC) FluView Pneumonia and Influenza Mortality Plots (Dec. 4, 2020)
United States National Death Rate According to US CDC (Dec. 4, 2020)
US CDC Leading Causes of Death Report Attributes Only About Two Percent of All Deaths to Pneumonia and Influenza (Line Item 8: Influenza and Pneumonia) — not the Six to Ten Percent in the FluView Graphs

Remarkably the total number of deaths (799) attributed to COVID-19 in Santa Clara County is clearly within the range of deaths expected from pneumonia and influenza (329 to 989) based on historical data prior to 2020.

Which Pneumonia and Influenza Death Numbers Should Be Compared to the COVID-19 Death Numbers?

The FluView and Leading Causes of Death numbers for “pneumonia and influenza” differ by a factor of OVER THREE. Note that both the FluView and Leading Causes of Death numbers have no error bars or error estimates given, implying exact numbers in common scientific and engineering practice.

The US CDC Attributes 12,000 to 61,000 Pneumonia Deaths to Influenza on Their Web Site: https://www.cdc.gov/flu/about/burden/

The CDC also uses a mysterious mathematical model that attributes roughly 55,000 deaths from pneumonia and influenza to the influenza virus as the underlying cause, a number roughly comparable to the total pneumonia and influenza deaths in the leading causes of death. The influenza virus is confirmed by laboratory tests in only a small fraction of pneumonia and influenza deaths, about 6,000 per year.

Although the language is often unclear in the CDC documents and web site, the CDC appears to claim that an initial influenza infection which disappears or becomes undetectable in laboratory tests leads to the subsequent pneumonia, presumably a bacterial pneumonia although other viruses would be consistent with some lab tests. Based on this argument, the CDC appears to attribute most pneumonia deaths where historically pneumonia was listed as the “underlying cause of death” to the influenza virus for which there is a flu vaccine that the CDC promotes heavily — even though laboratory tests frequently fail to confirm influenza or even detect other viruses or bacteria instead. The “underlying cause of death” is discussed in more detail below.

As shown in the graphic above, the CDC web site Disease Burden of Influenza (Figure 1) appears to give a range from 12,000 to 61,000 influenza deaths from this model. The graphic does not indicate if this range is a 95 percent confidence interval — a common scientific and engineering practice — or some other error estimate. The range in the graphic does not appear to match any of the 95 percent confidence levels for estimated deaths attributed to influenza in Table 1.

There is a long history of serious criticism of the CDC’s “flu” death numbers by medical scientists and others. The most prominent critic is Peter Doshi, currently a professor at the University of Maryland and an associate editor at the British Medical Journal.

Citing the results of actual laboratory tests of deceased patients, critics of the CDC’s flu death numbers such as University of Maryland Professor Peter Doshi have argued that pneumonia deaths are due to a range of different viruses, bacteria, other pathogens, and even toxins, rather than predominantly influenza as implied by the CDC’s influenza deaths model. The output of this model appears to be the basis of the baseline “flu” deaths numbers used in most popular and public policy discussions of COVID-19 deaths — although the leading causes of death report number may also be used.

Why the Large Difference Between the FluView and Leading Causes of Death Numbers

The US CDC documents and web site are frequently unclear and even contradictory as in the case of these grossly contradictory totals of deaths from pneumonia and influenza. This makes it difficult to be certain of the cause for the difference. Nonetheless, the technical notes for each document — FluView and the leading causes of death — give a highly probable reason.

The leading causes of death report uses the language “the underlying cause of death” (sometimes abbreviated UCOD) whereas the FluView web site uses the language “a cause of death”. The leading causes of death report, the smaller number of deaths, appears to count the number of deaths where pneumonia or influenza is listed as the underlying cause of death (Page 74, National Vital Statistics Reports, Vol. 68, No. 6, June 24, 2019).

Leading Causes of Death Report for 2017 with “the underlying cause of death” language circled in red. (Dec. 18, 2020)

Death certificates frequently have multiple causes of death. One of these is assigned as the underlying cause of death. This may be quite arbitrary in some cases. Indeed the concept of “underlying cause of death” may not be well defined for some deaths because the aged may develop multiple health problems in parallel that are fatal in combination.

In contrast, the FluView site, the much larger number of deaths, appears to count deaths where pneumonia or influenza is listed as “a cause of death,” even if it is not the “underlying cause of death.”

FluView Mortality Surveillance notes with “A Cause of Death” Language Circled in Red (Dec. 18, 2020)

Prior to 2020 and COVID-19, most pneumonia deaths did not list pneumonia or the pneumonia-causing pathogen if known as the underlying cause of death. This will be discussed in detail below. The only common partial exception was HIV/AIDS where pneumocystis carinii pneumonia (a common fungus) was often the immediate cause of death and the Human Immunodeficiency Virus (HIV) is almost always listed as the underlying cause of death. However, HIV is not the pneumonia-causing pathogen which is the pneumocystis fungus. Instead, most pneumonia deaths, those included in the FluView numbers but not included in the leading causes of death numbers, were attributed to a cause such as a chronic lower respiratory disease, heart disease, cancer, even accidents, and other usually pre-existing conditions as the underlying cause of death.

The CDC follows the World Health Organization (WHO)’s definition of the underlying cause of death. WHO defines the underlying cause of death as “the disease or injury which initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury” in accordance with the rules of the International Classification of Diseases (ICD).

In the United States, the underlying cause of death is listed last in the list of causes of death in part I of the death certificate. The immediate cause of death is listed first. Part 2 lists other conditions that are considered contributing factors but somehow not causes. Pneumonia is often the immediate cause of death in part 1 of the death certificate.

In principle, death certificates and the assignment of causes of death including the underlying cause of death is governed or at least guided by the CDC’s Medical Examiners’ and Coroners’ Handbook on Death Registration and Fetal Death Reporting (2003 Revision). This one-hundred and thirty-eight (138) page manual actually provides very limited guidance on how to assign the underlying cause of death in cases where pneumonia is present. Page twenty-five (25) has the only detailed discussion of deaths involving pneumonia:

US CDC Medical Examiners’ Handbook 2003 suggests attributing a pneumonia death to either chronic ischemic heart disease or diabetes mellitus as the underlying cause but not the pneumonia or pneumonia-causing pathogen. No clear direction to the physician.

Although the CDC’s Medical Examiners’ Handbook 2003 gives little specific direction on deaths involving pneumonia, it references several books and articles edited or authored by Randy Hanzlick, M.D., now retired Chief of the Fulton County Medical Examiner’s Office and former pathologist with the CDC, including Cause of Death and the Death Certificate: Important Information for Physicians, Coroners, Medical Examiners, And the Public, Randy Hanzlick Editor (2006), College of American Pathologists (the reference seems to have been updated to the year 2006 since the original release of the handbook in 2003) which discusses the cause of death for pneumonia cases in more detail notably on pages 89 and 90:

Pneumonia

Pneumonia is often a nonspecific process that occurs as the terminal event in someone who dies of a more specific underlying cause of death, such as congestive heart failure resulting from ischemic heart disease. In such cases, the specific underlying cause of death should be included in the cause-of-death statement.

Pneumonia is often designated as either community acquired or hospital or institution acquired (nosocomial). If the community- or institution-acquired nature of the pneumonia is known, the cause-of-death statement should include an indication of which one applies.

The specific bacterial, viral, or other infectious agent, if known, should be cited in the cause-of-death statement.

Relevant risk factors should also be cited in the cause-of-death statement, as might occur in an alcoholic who develops tuberculous pneumonia. Only in those instances where pneumonia has caused death and there is no known underlying cause or risk factor should the underlying cause of death be stated as “Pneumonia,” being sure to specify the infectious agent, if known, or specifying that a specific etiology is unknown, if such is the case.

Emphasis Added

And on page 113 of Cause of Death and the Death Certificate by Randy Hanzlick, dementia, cerebrovascular disease, cardiac disease, and lung disease are all listed as common underlying causes of death in cases of deaths due to pneumonia:

Thus, traditionally, pre-2020 and COVID-19, pneumonia deaths were frequently assigned a non-pneumonia underlying cause of death, usually a pre-existing condition and not the pneumonia-causing pathogen such as the influenza virus, in common medical practice. Based on the technical notes these pneumonia and influenza deaths would be included in the FluView death numbers but not in the leading causes of death report.

Comparing COVID-19 Death Numbers to the Pneumonia and Influenza Death Numbers and Estimates from Previous Years

As shown above, the CDC has at least three (3) different pneumonia and influenza death numbers and estimates: the Leading Causes of Death Report (about 55,000 deaths per year, about two percent of annual deaths from all causes), the FluView graph and underlying data from the NCHS (about 188,000 deaths per year, six to ten percent of annual deaths from all causes, before 2020), and the influenza death model estimates that range from 12,000 to 61,000 deaths per year with the best estimate close to the number of pneumonia and influenza deaths in the leading causes of death report. Are any of these the proper baseline for comparing COVID-19 deaths to prior years or should some other number or estimate be used?

In the absence of the RT-PCR and antibody tests for the SARS-COV-2 virus, most COVID-19 deaths would be unexplained pneumonia deaths lacking a laboratory test confirming influenza or other known pathogen. Possibly, some COVID-19 deaths would be listed as heart attacks or strokes, those COVID-19 deaths attributed to the blood clots and other blood-related anomalies currently blamed on COVID-19, or even some other causes. The rest of this article will focus on the pneumonia deaths which would comprise most of the COVID-19 deaths in the absence of laboratory tests.

The US CDC’s April 2020 guidelines for reporting COVID-19 deaths clearly direct physicians and others not to list chronic obstructive pulmonary disease (COPD) as the underlying cause of death in COVID-19 cases, moving it to Part 2 of the death certificate reserved for “non-cause” contributing factors, which differs dramatically from medical practice prior to 2020 as described in Randy Hanzlick’s book and implicit in the FluView pneumonia and influenza deaths data.

In some cases, survival from COVID–19 can be complicated by pre-existing chronic conditions, especially those that result in diminished lung capacity, such as chronic obstructive pulmonary disease (COPD) or asthma. These medical conditions do not cause COVID–19, but can increase the risk of contracting a respiratory infection and death, so these conditions should be reported in Part II and not in Part I.

NVSS: Vital Statistics Reporting Guidance, Report 3, April 2020, Page 2, Paragraph 3

This guidance also gives a specific example of a COVID-19 death with COPD relegated to Part 2:

COVID-19 Death Guidance Example with COPD as Contributing Factor Only

Although other causes of death that are often given as the underlying cause of death in pneumonia cases on pre-2020 death certificates are not explicitly identified in the April 2020 guidance document, it seems probable most physicians would move these pre-existing conditions to Part 2 and not list them as the underlying cause of death for COVID-19 based on the April 2020 CDC guidance document. Note that COPD would fall under the category “lung disease” in the list below from Randy Hanzlick’s Causes of Death and the Death Certificate:

Pre-2020 Guidance to List Dementia, Cerebrovascular disease, Cardiac disease, lung disease etc. as the Underlying Cause of Death in a Pneumonia Case Cause of Death and the Death Certificate: Important Information for Physicians, Coroners, Medical Examiners, And the Public, Randy Hanzlick Editor (2006), College of American Pathologists

Thus, COVID-19 deaths since the April 2020 guidance are probably roughly comparable to the FluView deaths, the larger number, the 188,000 pneumonia and influenza deaths per year. The language “roughly” is used because the April 2020 guidance appears to strongly encourage physicians and others to assign COVID-19 as the underlying cause of death in any death where COVID-19 is detected by tests or perhaps even just suspected, raising the possibility that heart attack and stroke deaths might be wrongly classified as COVID-19 deaths as well as the traditional pneumonia and influenza deaths that would be listed in the FluView data. These would presumably be misclassified as the COVID-19 deaths exhibiting the mysterious blood clots and other blood-related problems reported in some COVID-19 cases and deaths. Thus, the FluView death numbers may represent a lower bound on COVID-19 deaths rather than an exact baseline — unfortunately.

Ealy et al have raised the question whether the CDC complied with the Paperwork Reduction Act (PRA) and Information Quality Act (IQA) requirements in issuing the April and earlier March COVID-19 death certification guidelines, apparently without submitting these for public comment through the Federal Register as Ealy and co-authors claim is required by these federal laws.

Thus, due to the guidance on the death certificates from the CDC in April 2020, COVID-19 deaths on death certificates appear comparable to the larger FluView death numbers — or even larger numbers if heart attacks, strokes or other blood coagulation related deaths with a positive test or clinical diagnosis are being classified as COVID-19 deaths.

COVID-19 Testing Has Increased By About a Factor of Three Since July 2020 in Santa Clara County

COVID-19 Testing Has Increased by a Factor of About Three Since July 2020

Testing for COVID-19 has increased by about a factor of three, from about 7,000 tests per day in July 2020 to about 21,000 tests per day in December. This could likely increase the number of reported deaths by a factor of three even without the usual seasonal variation in deaths attributed to pneumonia and influenza.

There are many issues regarding testing including the false positive and false negative rates of the tests — both the antibody tests and the RT-PCR tests — that make estimating the effects of increased testing quite difficult — and clearly beyond what can be done here in this short article.

Santa Clara County Has Close Ties to China

Santa Clara County, home to Apple, Google, and many other companies with extensive manufacturing operations in China, the presumed source of the Sars-COV-2 virus, and large numbers of direct and contract employees again from China (mainland China), has extensive ties to China, meaning mainland China, not just Taiwan, Singapore, Hong Kong, and other ethnically Chinese nations and communities outside of China proper. Indeed, it probably has the closest ties, travel and trade to and from China of any region in the United States — likely much more than the New York and New Jersey region where the most deaths and highest death rates have been reported. One would expect Santa Clara County, California to have the earliest and largest cumulative number of deaths from COVID-19 in the United States.

According to the New York Times (April 4, 2020), at least 430,000 people returned to the United States from China after the Sars-COV-2 virus appeared, many after President Trump’s travel ban. A large fraction of these probably returned to Santa Clara County given the close ties between China and Santa Clara County. According to the San Francisco Chronicle, the first US COVID case was a 57-year old woman who passed away at home on February 6, 2020, well before the Kirkland Life Care Center cases in late February.

Many Seeming Routes for Rapid Spread of the Disease

Santa Clara County continues to authorize many luxury apartment and other construction projects with teams of workers in close proximity five full days per week, after a brief 3-4 week shutdown in May — several weeks after the original lockdown order. On a personal note, a four-story luxury apartment building construction project with at least a dozen workers every weekday from about 7:30 am to 4:30 pm has continued across the street from my apartment building since the original lockdown order except for the brief shutdown in May.

Santa Clara County Allows Construction Projects Despite COVID-19
Over a Dozen Construction Workers Arriving for Work on Luxury Apartment Project in Santa Clara County, CA (August 6, 2020)
Construction Workers in Close Proximity (Santa Clara County, Dec. 7, 2020)

The lockdown continues to herd large numbers of citizens in Santa Clara County into a few gigantic stores such as Safeway, Walmart, and Target, enabling what would seem like an efficient route for rapid spread of the disease.

Safeway with Over Thirty Cars in Parking Lot (about 9:30 AM, December 7, 2020, Santa Clara County)

These giant “Big Box” retail stores have heavily used shared spaces and surfaces where one would expect the virus will rapidly spread. These include the entry/exit door areas, checkout counters, and refrigerators with popular products such as milk purchased by a large fraction of the customers and with door handles that all purchasers must use. These large stores often have hundreds of patrons in the store at the same time — all day, seven days per week.

Milk and other dairy products in a refrigerator with door handle that customers must use

In Santa Clara County, the lockdowns have closed or heavily curtailed restaurants, popular with the large population of single people and leading to a large increase in demand for microwave dinners often found in store refrigerators with door handles that must be used by the customers.

Microwave dinners in store refrigerator with door handle that customers must use

Several other specific scenarios exist for rapid efficient spread of the virus through these giant retail stores.

Santa Clara County also has a bus service, the VTA or Valley Transportation Authority, in widespread use with patrons, often “essential workers,” sharing an enclosed space and seats.

VTA Bus in Operation on December 7, 2020, Santa Clara County, California

The lockdown shelter in place and stay at home orders confine “non-essential workers” to numerous generally large apartment complexes, often with hundreds of tenants, possibly thousands in some cases. In Mountain View, California — site of Google’s headquarters — about fifty-eight percent of residents (Town Charts, see Figure 5) are renters, most in large complexes. These complexes feature shared trash chutes/rooms, laundry rooms, hallways and lobbies with exterior doors and fire doors that must be opened by hand in most cases, providing many shared surfaces and spaces for spread of the virus.

Typical Trash Chute Room with Fire Door in Santa Clara County — Note Door Handle (December 7, 2020)
Typical Trash Room Interior with Trash Chute (Note Handle) in Santa Clara County (December 7, 2020)
Typical Laundry Room Door with Handle in Santa Clara County (December 7, 2020)

Note that fire regulations require closely spaced closed fire doors in the interior hallways — with handles or knobs that all residents must use to open the fire doors.

The large apartment complexes common in Santa Clara County provide numerous shared spaces where aerosol virus particles can collect and linger in the air as well as shared surfaces such as door handles that all residents must touch.

Gloves are not required. Gloves would have to be handled carefully and sterilized before and after each or nearly each use to avoid spreading the virus, something probably impractical and certainly currently NOT done by most residents.

In general, the apartment complex support staff cannot clean each door handle after each use. The shared support staff themselves are a high risk of both becoming infected and spreading the infection to other residents. Almost none have training or experience in bio-safety measures.

These shared spaces and surfaces are enclosed, protected from exterior wind that can disperse the virus particles and from the ultraviolet component of sunlight which can destroy the virus particles outside. By design, the required fire doors limit air flow in the buildings to prevent a disastrous fire. Citizens are being mandated/encouraged to spend most of their time inside in these complexes.

Conclusion

As of January 6, 2021, the total and daily death numbers for COVID-19 continue to deviate sharply from both hyperbolic headlines and reasonable expectations — as was the case in March and April of 2020. Indeed, the total number of official reported COVID-19 deaths to date (799 on January 6, 2020) remains small enough to be consistent with no new or unusual disease causing more deaths than normal in Santa Clara County in 2020. This may, of course, change in future months.

As noted above, the US Centers for Disease Control and Prevention (CDC)’s historical death numbers for pneumonia and influenza are grossly inconsistent, differing by a factor of over three without clear explanation, lack error bars or error estimates as required by common scientific and engineering practice, and are accompanied by frequently confusing and unclear explanatory text. This should of course be rectified as soon as possible in an open transparent way subject to democratic public comment.

The CDC’s influenza virus death model should be made publicly available as free open-source software such as a Python or R statistical programming language program that can be easily downloaded and run along with the data analyzed or modeled. The CDC should clearly explain and justify the attribution of tens of thousands of pneumonia deaths without laboratory confirmed influenza virus to the influenza virus each year by this model.

(C) 2020 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video] New Year Advice: Unplug and Calm Down

New Year Advice: Unplug and Calm Down

New Year’s advice to unplug from the 24/7 social media/news virtual reality and calm down. I argue that social media, social psychology tricks, recommendation engines, and state of the art AI are driving a massive, costly and dangerous overreaction to the COVID-19 pandemic and offer some advice to retake your mind from technology run amok.

Alternative Video: BitChute NewTube LBRY

References/Credits:

Tristan Harris and the AI Apocalypse

Tristan Harris Image: https://commons.wikimedia.org/wiki/File:Tristan_Harris_at_Collision_Conf_2018_(cropped).jpg

“How a handful of tech companies control billions of minds every day” Tristan Harris TED Talk: https://www.youtube.com/watch?v=C74amJRp730

Tristan Harris Web Site: https://www.tristanharris.com/

Laurie Santos on Knowing About Cognitive Bias is Not Enough:

Lauria Santos and Tamar Gendler on “Knowing is Half the Battle”: https://www.edge.org/response-detail/25436

Nobel Prize Winning Cognitive Bias Expert Falls Prey to Cognitive Bias

Cognitive Bias Expert Daniel Kahneman Placed Too Much Confidence in Underpowered Studies: https://retractionwatch.com/2017/02/20/placed-much-faith-underpowered-studies-nobel-prize-winner-admits-mistakes/

High IQ People are Vulnerable to Cognitive Bias

Does High Intelligence Mean Low Cognitive Bias? https://www.globalcognition.org/intelligence-and-cognitive-bias/

Myside Bias, Rational Thinking, and Intelligence
By Keith E. Stanovich, Richard F. West, and Maggie E. Toplak
http://keithstanovich.com/Site/Research_on_Reasoning_files/Stanovich_CDPS_2013.pdf

High intelligence: A risk factor for psychological and physiological overexcitabilities
By Ruth I.Karpinski,
Audrey M.Kinase Kolb, Nicole A.Tetreault, and Thomas B.Borowski
https://www.sciencedirect.com/science/article/pii/S0160289616303324

Bad News for the Highly Intelligent
Superior IQs are associated with mental and physical disorders, research suggests
By David Z. Hambrick, Madeline Marquardt on December 5, 2017, Scientific American
https://www.scientificamerican.com/article/bad-news-for-the-highly-intelligent/

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(C) 2020 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).

[Video] Twas the Night Before Christmas

Twas the Night Before Christmas

A reading of “Twas the Night Before Christmas” by Clement C. Moore, originally titled “A Visit from St Nicholas,” with vintage illustrations from the nineteenth century.

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(C) 2020 by John F. McGowan, Ph.D.

About Me

John F. McGowan, Ph.D. solves problems using mathematics and mathematical software, including developing gesture recognition for touch devices, video compression and speech recognition technologies. He has extensive experience developing software in C, C++, MATLAB, Python, Visual Basic and many other programming languages. He has been a Visiting Scholar at HP Labs developing computer vision algorithms and software for mobile devices. He has worked as a contractor at NASA Ames Research Center involved in the research and development of image and video processing algorithms and technology. He has published articles on the origin and evolution of life, the exploration of Mars (anticipating the discovery of methane on Mars), and cheap access to space. He has a Ph.D. in physics from the University of Illinois at Urbana-Champaign and a B.S. in physics from the California Institute of Technology (Caltech).