Computer Applications Quotes

Pilots used to fly planes manually, but now they operate a dashboard with the help of computers. This has made flying safer and improved the industry. Healthcare can benefit from the same type of approach, with physicians practicing medicine with the help of data, dashboards, and AI. This will improve the quality of care they provide and make their jobs easier and more efficient

Friedrich Nietzsche, who famously gave us the ‘God is dead’ phrase was interested in the sources of morality. He warned that the emergence of something (whether an organ, a legal institution, or a religious ritual) is never to be confused with its acquired purpose: ‘Anything in existence, having somehow come about, is continually interpreted anew, requisitioned anew, transformed and redirected to a new purpose.’ This is a liberating thought, which teaches us to never hold the history of something against its possible applications. Even if computers started out as calculators, that doesn’t prevent us from playing games on them. (47) (quoting Nietzsche, the Genealogy of Morals)

The contribution of mathematics, and of people, is not computation but intelligence.

Quantum Machine Learning is defined as the branch of science and technology that is concerned with the application of quantum mechanical phenomena such as superposition, entanglement and tunneling for designing software and hardware to provide machines the ability to learn insights and patterns from data and the environment, and the ability to adapt automatically to changing situations with high precision, accuracy and speed. 

Look-Then-Leap Rule: You set a predetermined amount of time for “looking”—that is, exploring your options, gathering data—in which you categorically don’t choose anyone, no matter how impressive. After that point, you enter the “leap” phase, prepared to instantly commit to anyone who outshines the best applicant you saw in the look phase. We

Theory is relevant to you because it shows you a new, simpler, and more elegant side of computers, which we normally consider to be complicated machines. The best computer designs and applications are conceived with elegance in mind. A theoretical course can heighten your aesthetic sense and help you build more beautiful systems.

Broad-Based Education: Reed College at that time offered perhaps the best calligraphy instruction in the country.… I decided to take a calligraphy class to learn how to do this.… It was beautiful, historical, artistically subtle in a way that science can’t capture, and I found it fascinating. None of this had even a hope of any practical application in my life. But ten years later, when we were designing the first Macintosh computer, it all came back to me. —Commencement address, Stanford University, June 12, 2005

This cuts the myth at an awkward angle: it is because the [artificial intelligence] systems are idiots, but still find their way into business, consumer, and government application, that human-value questions are now infecting what were once purely scientific values.

Programmers are always surrounded by complexity; we cannot avoid it. Our applications are complex because we are ambitious to use our computers in ever more sophisticated ways. Programming is complex because of the large number of conflicting objectives for each of our programming projects. If our basic tool, the language in which we design and code our programs, is also complicated, the language itself becomes part of the problem rather than part of its solution.

This sort of information gathering is precisely what we call play. And the important function of play is thus revealed: it permits us to gain, without any particular future application in mind, a holistic understanding of the world, which is both a complement of and a preparation for later analytical activities.

The math-powered applications powering the data economy were based on choices made by fallible human beings. Some of these choices were no doubt made with the best intentions. Nevertheless, many of these models encoded human prejudice, misunderstanding, and bias into the software systems that increasingly managed our lives. Like gods, these mathematical models were opaque, their workings invisible to all but the highest priests in their domain: mathematicians and computer scientists. Their verdicts, even when wrong or harmful, were beyond dispute or appeal. And they tended to punish the poor and the oppressed in our society, while making the rich richer.

treating messages as discrete had application not just for traditional communication but for a new and rather esoteric subfield, the theory of computing machines.

Most of Csongor's time in T'Rain had been spent blundering about in a state of hapless newbie confusion. Only his long experience as a system administrator, struggling with Byzantine software installations, had prevented hum from plummeting into despair and simply giving up. Not that any of the sysadmin's knowledge and skills were applicable here. The psychological stance was the thing: the implicit faith, a little naive and a little cocky, that by banging his head against the problem for long enough he'd be able to break through in the end.

In the history of ideas, it's repeatedly happened that an idea, developed in one area for one purpose, finds an unexpected application elsewhere. Concepts developed purely for philosophy of mathematics turned out to be just what you needed to build a computer. Statistical formulae for understanding genetic change in biology are now applied in both economics and in programming.

As she [Grace Hopper] told a historian is 1968, to make the link between "the computer people" and the outside world of clients, problems, and possible applications, "you needed people with more vocabularies

Computer literacy, however, is really a euphemism for forcing human beings to stretch their thinking to understand the inner workings of application logic, rather than having software-enabled products stretch to meet people’s usual ways of thinking.

As the applicant pool grows, the exact place to draw the line between looking and leaping settles to 37% of the pool, yielding the 37% Rule: look at the first 37% of the applicants,* choosing none, then be ready to leap for anyone better than all those you’ve seen so far.

Two decades later, when I got my PhD in computer science from Carnegie Mellon, I thought that made me infinitely qualified to do anything, so I dashed off my letters of application to Walt Disney Imagineering. And they sent me the nicest go-to-hell letter I'd ever received.

Every computing device today has five basic components: (1) the integrated circuits that do the computing; (2) the memory units that store and retrieve information; (3) the networking systems that enable communications within and across computers; (4) the software applications that enable different computers to perform myriad tasks individually and collectively; and (5) the sensors—cameras and other miniature devices that can detect movement, language, light, heat, moisture, and sound and transform any of them into digitized data that can be mined for insights.

But Unix had a serious shortcoming: No common version existed. Over the years different versions of Unix had proliferated like weeds, so that an application written for one would not run unmodified on another. While DOS presented a single target to consumers, applications writers and computer makers, Unix did not.

You spent enough time working with computers, and the Internet became a second home. A refuge. A place to share ideas, trade snippets of code, and meet people who shared your interest in the extralegal applications of programming. Could such a person live without the Internet? He supposed it was possible. Yes, a voice countered, but was it probable?

If you read about quantum machine-learning applications that solve some conventional machine-learning problem with a fantastic speedup, always be sure to check whether they return a quantum output. Quantum outputs, such as amplitude-encoded vectors, limit the usage of applications, and require additional specification of how to extract practical, useful results.

All through our education we are being taught a kind of reverse mindfulness. A kind of Future Studies where- via the guise of mathematics, or literature, or history, or computer programming, or French- we are being taught to think of a time different to the time we are in. Exam time. Job time. When-we-are-grown-up time. To see the act of learning as something not for its own sake but because of what it will get you reduces the wonder of humanity. We are thinking, feeling, art-making, knowledge-hungry, marvelous animals, who understand ourselves and our world through the act of learning. It is an end in itself. It has far more to offer than the things it lets us write on application forms. It is a way to love living right now.

He had learned over time to keep his thoughts to himself, which was most easily accomplished if his brain activity was split into categories. His mind was like a computer with multiple applications open, some of them buzzing with contemplation in the background. Most of the time Aldo did not give others the impression he was listening, a suspicion that was generally correct.

Finding a zero day is a little like entering God mode in a video game. Once hackers have figured out the commands or written the code to exploit it, they can scamper through the world's computer networks undetected until the day the underlying flaw is discovered. Zero day exploitation is the most direct application of the cliche 'knowledge is power if you know how to use it.

I think actually if you take the analogy with other areas of engineering, and increasingly of science and even mathematics, you can see people do not have to learn the vast number of formulae they used to learn. Instead, they have to learn to use the computer effectively. This frees them, I feel, to understand concepts and the foundations while they’re learning the mechanics of the application of the theory.

New York City manages expertly, and with marvelous predictability, whatever it considers humanly important. Fax machines, computers, automated telephones and even messengers on bikes convey a million bits of data through Manhattan every day to guarantee that Wall Street brokers get their orders placed, confirmed, delivered, at the moment they demand. But leaking roofs cannot be fixed and books cannot be gotten into Morris High in time to meet the fall enrollment. Efficiency in educational provision for low-income children, as in health care and most other elementals of existence, is secreted and doled out by our municipalities as if it were a scarce resource. Like kindness, cleanliness and promptness of provision, it is not secured by gravity of need but by the cash, skin color and class status of the applicant.

Pham Nuwen spent years learning to program/explore. Programming went back to the beginning of time. It was a little like the midden out back of his father’s castle. Where the creek had worn that away, ten meters down, there were the crumpled hulks of machines—flying machines, the peasants said—from the great days of Canberra’s original colonial era. But the castle midden was clean and fresh compared to what lay within the Reprise’s local net. There were programs here that had been written five thousand years ago, before Humankind ever left Earth. The wonder of it—the horror of it, Sura said—was that unlike the useless wrecks of Canberra’s past, these programs still worked! And via a million million circuitous threads of inheritance, many of the oldest programs still ran in the bowels of the Qeng Ho system. Take the Traders’ method of timekeeping. The frame corrections were incredibly complex—and down at the very bottom of it was a little program that ran a counter. Second by second, the Qeng Ho counted from the instant that a human had first set foot on Old Earth’s moon. But if you looked at it still more closely. . .the starting instant was actually some hundred million seconds later, the 0-second of one of Humankind’s first computer operating systems. So behind all the top-level interfaces was layer under layer of support. Some of that software had been designed for wildly different situations. Every so often, the inconsistencies caused fatal accidents. Despite the romance of spaceflight, the most common accidents were simply caused by ancient, misused programs finally getting their revenge. “We should rewrite it all,” said Pham. “It’s been done,” said Sura, not looking up. She was preparing to go off-Watch, and had spent the last four days trying to root a problem out of the coldsleep automation. “It’s been tried,” corrected Bret, just back from the freezers. “But even the top levels of fleet system code are enormous. You and a thousand of your friends would have to work for a century or so to reproduce it.” Trinli grinned evilly. “And guess what—even if you did, by the time you finished, you’d have your own set of inconsistencies. And you still wouldn’t be consistent with all the applications that might be needed now and then.” Sura gave up on her debugging for the moment. “The word for all this is ‘mature programming environment.’ Basically, when hardware performance has been pushed to its final limit, and programmers have had several centuries to code, you reach a point where there is far more signicant code than can be rationalized. The best you can do is understand the overall layering, and know how to search for the oddball tool that may come in handy—take the situation I have here.” She waved at the dependency chart she had been working on. “We are low on working fluid for the coffins. Like a million other things, there was none for sale on dear old Canberra. Well, the obvious thing is to move the coffins near the aft hull, and cool by direct radiation. We don’t have the proper equipment to support this—so lately, I’ve been doing my share of archeology. It seems that five hundred years ago, a similar thing happened after an in-system war at Torma. They hacked together a temperature maintenance package that is precisely what we need.” “Almost precisely.

When the couple asked if there was a way to apply without identifying a race, they were told that their only option was to select “Other.” “I didn’t want to pick ‘Other,’ ” Ramkishun would recall. “I’ve been having to pick ‘Other’ all my life. None of it defines who I am.”2 Because she and her fiancé refused to click on a race category, the computer system couldn’t process their license application. They could not get married without specifying their race.

In a classic study of how names impact people’s experience on the job market, researchers show that, all other things being equal, job seekers with White-sounding first names received 50 percent more callbacks from employers than job seekers with Black-sounding names.5 They calculated that the racial gap was equivalent to eight years of relevant work experience, which White applicants did not actually have; and the gap persisted across occupations, industry, employer size – even when employers included the “equal opportunity” clause in their ads.6 With emerging technologies we might assume that racial bias will be more scientifically rooted out. Yet, rather than challenging or overcoming the cycles of inequity, technical fixes too often reinforce and even deepen the status quo. For example, a study by a team of computer scientists at Princeton examined whether a popular algorithm, trained on human writing online, would exhibit the same biased tendencies that psychologists have documented among humans. They found that the algorithm associated White-sounding names with “pleasant” words and Black-sounding names with “unpleasant” ones.7 Such findings demonstrate what I call “the New Jim Code”: the employment of new technologies that reflect and reproduce existing inequities but that are promoted and perceived as more objective or progressive than the discriminatory systems of a previous era.

the hub, it would allow the portable devices to become simpler. A lot of the functions that the devices tried to do, such as editing the video or pictures, they did poorly because they had small screens and could not easily accommodate menus filled with lots of functions. Computers could handle that more easily. And one more thing . . . What Jobs also saw was that this worked best when everything—the device, computer, software, applications, FireWire—was all tightly integrated. “I became even more of a believer in providing end-to-end

The history of epidemics in human populations has always been closely connected to cities. From the Great Plague of Athens (430 BC) to the COVID-19 pandemic, cities have played a unique role in the lives of epidemics that affect human populations. The increased population density provides the pathogen with a vastly increased likelihood that during a given infectious period, an infected individual will make contact with a susceptible individual. Overcrowding and urban poverty also directly affect other epidemic processes, e.g. attracting vectors who thrive on the byproducts of urban human existence.

We’ve seen several of these oscillations just in the last decade or so since the web became prominent. At first we thought all the computer power would be in server farms, and the browsers would be stupid. Then we started putting applets in the browsers. But we didn’t like that, so we moved dynamic content back to the servers. But then we didn’t like that, so we invented Web 2.0 and moved lots of processing back into the browser with Ajax and JavaScript. We went so far as to create whole huge applications written to execute in the browsers. And now we’re all excited about pulling that JavaScript back into the server with Node.

Take for example job applications. In the 21st century the decision wherever to hire somebody for a job while increasingly be made by algorithms. We cannot rely on the machines to set the relevant ethical standards, humans will still need to do that, but once we decide on an ethical standard in the job market, that it is wrong to discriminate against blacks or against women for example, we can rely on machines to implement and maintain these standards better than humans. A human manager may know and even agree that is unethical to discriminate against blacks and women but then when a black woman applies for a job the manager subconsciously discriminate against her and decides not to hire her. If we allow a computer to evaluate job applications and program computers to completely ignore race and gender we can be certain that the computer will indeed ignore these factors because computers do not have a subconscious. Of course it won't be easy to write code for evaluating job applications and there is always the danger that the engineers will somehow program their own subconscious biases into the software, yet once we discover such mistakes it would probably be far easier to debug the software than to get rid humans of their racist and misogynist biases.

Security is a big and serious deal, but it’s also largely a solved problem. That’s why the average person is quite willing to do their banking online and why nobody is afraid of entering their credit card number on Amazon. At 37signals, we’ve devised a simple security checklist all employees must follow: 1. All computers must use hard drive encryption, like the built-in FileVault feature in Apple’s OS X operating system. This ensures that a lost laptop is merely an inconvenience and an insurance claim, not a company-wide emergency and a scramble to change passwords and worry about what documents might be leaked. 2. Disable automatic login, require a password when waking from sleep, and set the computer to automatically lock after ten inactive minutes. 3. Turn on encryption for all sites you visit, especially critical services like Gmail. These days all sites use something called HTTPS or SSL. Look for the little lock icon in front of the Internet address. (We forced all 37signals products onto SSL a few years back to help with this.) 4. Make sure all smartphones and tablets use lock codes and can be wiped remotely. On the iPhone, you can do this through the “Find iPhone” application. This rule is easily forgotten as we tend to think of these tools as something for the home, but inevitably you’ll check your work email or log into Basecamp using your tablet. A smartphone or tablet needs to be treated with as much respect as your laptop. 5. Use a unique, generated, long-form password for each site you visit, kept by password-managing software, such as 1Password.§ We’re sorry to say, “secretmonkey” is not going to fool anyone. And even if you manage to remember UM6vDjwidQE9C28Z, it’s no good if it’s used on every site and one of them is hacked. (It happens all the time!) 6. Turn on two-factor authentication when using Gmail, so you can’t log in without having access to your cell phone for a login code (this means that someone who gets hold of your login and password also needs to get hold of your phone to login). And keep in mind: if your email security fails, all other online services will fail too, since an intruder can use the “password reset” from any other site to have a new password sent to the email account they now have access to. Creating security protocols and algorithms is the computer equivalent of rocket science, but taking advantage of them isn’t. Take the time to learn the basics and they’ll cease being scary voodoo that you can’t trust. These days, security for your devices is just simple good sense, like putting on your seat belt.

A fungal computer may sound fantastical, but biocomputing is a fast-growing field. Adamatzky has spent years developing ways to use slime molds as sensors and computers. These prototype biocomputers use slime molds to solve a range of geometrical problems. The slime mold networks can be modified—for instance, by cutting a connection—to alter the set of “logical functions” implemented by the network. Adamatzky’s idea of a “fungal computer” is just an application of slime-mold computing to another type of network-based organism. As Adamatzky observes, the mycelial networks of some species of fungus are more convenient for computing than slime molds.

A friend of ours encountered this problem with his home-built computer long ago. He wrote a BIOS that used a magic value in a particular memory location to determine whether a reset was a cold reboot or a warm reboot. After a while the machine refused to boot after power-up because the memory had learned the magic value, and the boot process therefore treated every reset as a warm reboot. As this did not initialize the proper variables, the boot process failed. The solution in his case was to swap some memory chips around, scrambling the magic value that the SRAM had learned. For us, it was a lesson to remember: memory retains more data than you think.

Astounding, really, that Michel could consider psychology any kind of science at all. So much of it consisted of throwing together. Of thinking of the mind as a steam engine, the mechanical analogy most ready to hand during the birth of modern psychology. People had always done that when they thought about the mind: clockwork for Descartes, geological changes for the early Victorians, computers or holography for the twentieth century, AIs for the twenty-first…and for the Freudian traditionalists, steam engines. Application of heat, pressure buildup, pressure displacement, venting, all shifted into repression, sublimation, the return of the repressed. Sax thought it unlikely steam engines were an adequate model for the human mind. The mind was more like—what?—an ecology—a fellfield—or else a jungle, populated by all manner of strange beasts. Or a universe, filled with stars and quasars and black holes. Well—a bit grandiose, that—really it was more like a complex collection of synapses and axons, chemical energies surging hither and yon, like weather in an atmosphere. That was better—weather—storm fronts of thought, high-pressure zones, low-pressure cells, hurricanes—the jet streams of biological desires, always making their swift powerful rounds…life in the wind. Well. Throwing together. In fact the mind was poorly understood.

All through our education we are being taught a kind of reverse mindfulness. A kind of Future Studies where—via the guise of mathematics, or literature, or history, or computer programming, or French—we are being taught to think of a time different to the time we are in. Exam time. Job time. When-we-are-grown-up time. To see the act of learning as something not for its own sake but because of what it will get you reduces the wonder of humanity. We are thinking, feeling, art-making, knowledge-hungry, marvelous animals, who understand ourselves and our world through the act of learning. It is an end in itself. It has far more to offer than the things it lets us write on application forms. It is a way to love living right now.

By tracing the early history of USCYBERCOM it is possible to understand some of the reasons why the military has focused almost completely on network defense and cyber attack while being unaware of the need to address the vulnerabilities in systems that could be exploited in future conflicts against technologically capable adversaries. It is a problem mirrored in most organizations. The network security staff are separate from the endpoint security staff who manage desktops through patch and vulnerability management tools and ensure that software and anti-virus signatures are up to date. Meanwhile, the development teams that create new applications, web services, and digital business ventures, work completely on their own with little concern for security. The analogous behavior observed in the military is the creation of new weapons systems, ISR platforms, precision targeting, and C2 capabilities without ensuring that they are resistant to the types of attacks that USCYBERCOM and the NSA have been researching and deploying. USCYBERCOM had its genesis in NCW thinking. First the military worked to participate in the information revolution by joining their networks together. Then it recognized the need for protecting those networks, now deemed cyberspace. The concept that a strong defense requires a strong offense, carried over from missile defense and Cold War strategies, led to a focus on network attack and less emphasis on improving resiliency of computing platforms and weapons systems.

Bodean James Gazzer had spent thirty-one years perfecting the art of assigning blame. His personal credo - everything bad that happens is someone else's fault - could, with imagination, be stretched to fit any circumstance. Bode stretched it. The intestinal unrest that occasionally afflicted him surely was the result of drinking milk taken from secretly radiated cows. The roaches in his apartment were planted by his filthy immigrant next-door neighbors. His dire financial plight was caused by runaway bank computers and conniving Wall Street Zionists; his bad luck in the South Florida job market, prejudice against English-speaking applicants. Even the lousy weather had a culprit: air pollution from Canada, diluting the ozone and derailing the jet stream

THE RIVE BROTHERS used to be like a technology gang. In the late 1990s, they would jump on skateboards and zip around the streets of Santa Cruz, knocking on the doors of businesses and asking if they needed any help managing their computing systems. The young men, who had all grown up in South Africa with their cousin Elon Musk, soon decided there must be an easier way to hawk their technology smarts than going door-to-door. They wrote some software that allowed them to take control of their clients’ systems from afar and to automate many of the standard tasks that companies required, such as installing updates for applications. The software became the basis of a new company called Everdream, and the brothers promoted their technology in some compelling ways.

RENEWABLE ENERGY REVOLUTION: SOLAR + WIND + BATTERIES In addition to AI, we are on the cusp of another important technological revolution—renewable energy. Together, solar photovoltaic, wind power, and lithium-ion battery storage technologies will create the capability of replacing most if not all of our energy infrastructure with renewable clean energy. By 2041, much of the developed world and some developing countries will be primarily powered by solar and wind. The cost of solar energy dropped 82 percent from 2010 to 2020, while the cost of wind energy dropped 46 percent. Solar and onshore wind are now the cheapest sources of electricity. In addition, lithium-ion battery storage cost has dropped 87 percent from 2010 to 2020. It will drop further thanks to the massive production of batteries for electrical vehicles. This rapid drop in the price of battery storage will make it possible to store the solar/wind energy from sunny and windy days for future use. Think tank RethinkX estimates that with a $2 trillion investment through 2030, the cost of energy in the United States will drop to 3 cents per kilowatt-hour, less than one-quarter of today’s cost. By 2041, it should be even lower, as the prices of these three components continue to descend. What happens on days when a given area’s battery energy storage is full—will any generated energy left unused be wasted? RethinkX predicts that these circumstances will create a new class of energy called “super power” at essentially zero cost, usually during the sunniest or most windy days. With intelligent scheduling, this “super power” can be used for non-time-sensitive applications such as charging batteries of idle cars, water desalination and treatment, waste recycling, metal refining, carbon removal, blockchain consensus algorithms, AI drug discovery, and manufacturing activities whose costs are energy-driven. Such a system would not only dramatically decrease energy cost, but also power new applications and inventions that were previously too expensive to pursue. As the cost of energy plummets, the cost of water, materials, manufacturing, computation, and anything that has a major energy component will drop, too. The solar + wind + batteries approach to new energy will also be 100-percent clean energy. Switching to this form of energy can eliminate more than 50 percent of all greenhouse gas emissions, which is by far the largest culprit of climate change.

To which I might add that questions about the psychic, political and social effects of information are as applicable to the computer as to television. Although I believe the computer to be a vastly overrated technology, I mention it here because, clearly, Americans have accorded it their customary mindless inattention; which means they will use it as they are told, without a whimper. Thus, a central thesis of computer technology—that the principal difficulty we have in solving problems stems from insufficient data—will go unexamined. Until, years from now, when it will be noticed that the massive collection and speed-of-light retrieval of data have been of great value to large-scale organizations but have solved very little of importance to most people and have created at least as many problems for them as they may have solved.

[Help® Guide] (1-888-824-4566) How to Fix Norton Slowing Down Your Computer In today’s digital world, having robust cybersecurity is essential, and many users rely on Norton Antivirus and Norton 360 to protect their devices. However, one of the common complaints that Norton users face is a noticeable slowdown in their computer's performance. While Norton’s powerful features work to defend against cyber threats, sometimes it may unintentionally cause your computer to lag or become slower over time. This article provides a comprehensive guide on how to fix Norton slowing down your computer, offering practical steps to troubleshoot the issue. Whether you're experiencing performance dips during web browsing or while running specific applications, the following steps will help you get back to optimal performance. Additionally, if you need further assistance, you can always reach out to Norton Customer Service at 1-888-824-4566 for support.

Yet skill in the most sophisticated applications of laboratory technology and in the use of the latest therapeutic modality alone does not make a good physician. When a patient poses challenging clinical problems, an effective physician must be able to identify the crucial elements in a complex history and physical examination; order the appropriate laboratory, imaging, and diagnostic tests; and extract the key results from densely populated computer screens to determine whether to treat or to “watch.” As the number of tests increases, so does the likelihood that some incidental finding, completely unrelated to the clinical problem at hand, will be uncovered. Deciding whether a clinical clue is worth pursuing or should be dismissed as a “red herring” and weighing whether a proposed test, preventive measure, or treatment entails a greater risk than the disease itself are essential judgments that a skilled clinician must make many times each day. This combination of medical knowledge, intuition, experience, and judgment defines the art of medicine, which is as necessary to the practice of medicine as is a sound scientific base.

It was little things at first. Abby missed a phone call because she had an away game. Then one time Gretchen didn’t write back and never made up for the missing letter. They got busy with SATs and college applications, and even though they both applied to Georgetown, Gretchen didn’t get in, and Abby wound up going to George Washington anyways. At college they went to their computer labs and sent each other emails, sitting in front of black and green CRT screens and pecking them out one letter at a time. And they still wrote, but calling became a once-a-week thing. Gretchen was Abby’s maid of honor at her tiny courthouse wedding, but sometimes a month would go by and they wouldn’t speak. Then two months. Then three. They went through periods when they both made an effort to write more, but after a while that usually faded. It wasn’t anything serious, it was just life. The dance recitals, making the rent, first real jobs, pickups, dropoffs, the fights that seemed so important, the laundry, the promotions, the vacations taken, shoes bought, movies watched, lunches packed. It was a haze of the everyday that blurred the big things and made them feel distant and small.

In the early thirties IBM built a high-speed calculating machine to do calculations for the astronomers at New York’s Columbia University. A few years later it built a machine that was already designed as a computer—again, to do astronomical calculations, this time at Harvard. And by the end of World War II, IBM had built a real computer—the first one, by the way, that had the features of the true computer: a “memory” and the capacity to be “programmed.” And yet there are good reasons why the history books pay scant attention to IBM as a computer innovator. For as soon as it had finished its advanced 1945 computer—the first computer to be shown to a lay public in its showroom in midtown New York, where it drew immense crowds—IBM abandoned its own design and switched to the design of its rival, the ENIAC developed at the University of Pennsylvania. The ENIAC was far better suited to business applications such as payroll, only its designers did not see this. IBM structured the ENIAC so that it could be manufactured and serviced and could do mundane “numbers crunching.” When IBM’s version of the ENIAC came out in 1953, it at once set the standard for commercial, multipurpose, mainframe computers. This is the strategy of “creative imitation.

Bush’s description of how basic research provides the seed corn for practical inventions became known as the “linear model of innovation.” Although subsequent waves of science historians sought to debunk the linear model for ignoring the complex interplay between theoretical research and practical applications, it had a popular appeal as well as an underlying truth. The war, Bush wrote, had made it “clear beyond all doubt” that basic science—discovering the fundamentals of nuclear physics, lasers, computer science, radar—“is absolutely essential to national security.” It was also, he added, crucial for America’s economic security. “New products and new processes do not appear full-grown. They are founded on new principles and new conceptions, which in turn are painstakingly developed by research in the purest realms of science. A nation which depends upon others for its new basic scientific knowledge will be slow in its industrial progress and weak in its competitive position in world trade.” By the end of his report, Bush had reached poetic heights in extolling the practical payoffs of basic scientific research: “Advances in science when put to practical use mean more jobs, higher wages, shorter hours, more abundant crops, more leisure for recreation, for study, for learning how to live without the deadening drudgery which has been the burden of the common man for past ages.”9 Based on this report, Congress established the National Science Foundation.

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Lucid Motors was started under the name Atieva (which stood for “advanced technologies in electric vehicle applications” and was pronounced “ah-tee-va”) in Mountain View in 2008 (or December 31, 2007, to be precise) by Bernard Tse, who was a vice president at Tesla before it launched the Roadster. Hong Kong–born Tse had studied engineering at the University of Illinois, where he met his wife, Grace. In the early 1980s, the couple had started a computer manufacturing company called Wyse, which at its peak in the early 1990s registered sales of more than $480 million a year. Tse joined Tesla’s board of directors in 2003 at the request of his close friend Martin Eberhard, the company’s original CEO, who sought Tse’s expertise in engineering, manufacturing, and supply chain. Tse would eventually step off the board to lead a division called the Tesla Energy Group. The group planned to make electric power trains for other manufacturers, who needed them for their electric car programs. Tse, who didn’t respond to my requests to be interviewed, left Tesla around the time of Eberhard’s departure and decided to start Atieva, his own electric car company. Atieva’s plan was to start by focusing on the power train, with the aim of eventually producing a car. The company pitched itself to investors as a power train supplier and won deals to power some city buses in China, through which it could further develop and improve its technology. Within a few years, the company had raised about $40 million, much of it from the Silicon Valley–based venture capital firm Venrock, and employed thirty people, mostly power train engineers, in the United States, as well as the same number of factory workers in Asia. By 2014, it was ready to start work on a sedan, which it planned to sell in the United States and China. That year, it raised about $200 million from Chinese investors, according to sources close to the company.

Although thrilled that the era of the personal computer had arrived, he was afraid that he was going to miss the party. Slapping down seventy-five cents, he grabbed the issue and trotted through the slushy snow to the Harvard dorm room of Bill Gates, his high school buddy and fellow computer fanatic from Seattle, who had convinced him to drop out of college and move to Cambridge. “Hey, this thing is happening without us,” Allen declared. Gates began to rock back and forth, as he often did during moments of intensity. When he finished the article, he realized that Allen was right. For the next eight weeks, the two of them embarked on a frenzy of code writing that would change the nature of the computer business.1 Unlike the computer pioneers before him, Gates, who was born in 1955, had not grown up caring much about the hardware. He had never gotten his thrills by building Heathkit radios or soldering circuit boards. A high school physics teacher, annoyed by the arrogance Gates sometimes displayed while jockeying at the school’s timesharing terminal, had once assigned him the project of assembling a Radio Shack electronics kit. When Gates finally turned it in, the teacher recalled, “solder was dripping all over the back” and it didn’t work.2 For Gates, the magic of computers was not in their hardware circuits but in their software code. “We’re not hardware gurus, Paul,” he repeatedly pronounced whenever Allen proposed building a machine. “What we know is software.” Even his slightly older friend Allen, who had built shortwave radios, knew that the future belonged to the coders. “Hardware,” he admitted, “was not our area of expertise.”3 What Gates and Allen set out to do on that December day in 1974 when they first saw the Popular Electronics cover was to create the software for personal computers. More than that, they wanted to shift the balance in the emerging industry so that the hardware would become an interchangeable commodity, while those who created the operating system and application software would capture most of the profits.

Key Points: ● Transparency - Blockchain offers significant improvements in transparency compared to existing record keeping and ledgers for many industries. ● Removal of Intermediaries – Blockchain-based systems allow for the removal of intermediaries involved in the record keeping and transfer of assets. ● Decentralization – Blockchain-based systems can run on a decentralized network of computers, reducing the risk of hacking, server downtime and loss of data. ● Trust – Blockchain-based systems increase trust between parties involved in a transaction through improved transparency and decentralized networks along with removal of third-party intermediaries in countries where trust in the intermediaries doesn’t exist. ● Security – Data entered on the blockchain is immutable, preventing against fraud through manipulating transactions and the history of data. Transactions entered on the blockchain provide a clear trail to the very start of the blockchain allowing any transaction to be easily investigated and audited. ● Wide range of uses - Almost anything of value can be recorded on the blockchain and there are many companies and industries already developing blockchain-based systems. These examples are covered later in the book. ● Easily accessible technology – Along with the wide range of uses, blockchain technology makes it easy to create applications without significant investment in infrastructure with recent innovations like the Ethereum platform. Decentralized apps, smart contracts and the Ethereum platform are covered later in the book. ● Reduced costs – Blockchain-based ledgers allow for removal of intermediaries and layers of confirmation involved in transactions. Transactions that may take multiple individual ledgers, could be settled on one shared ledger, reducing the costs of validating, confirming and auditing each transaction across multiple organizations. ● Increased transaction speed – The removal of intermediaries and settlement on distributed ledgers, allows for dramatically increased transaction speeds compared to a wide range of existing systems.

Against this background, we can understand the design of computer applications as a concerned social- and historical-conditioned activity in which tools and their use are envisioned. This is an activity and form of knowledge that is both planned and creative.

And this is why MapReduce is designed to tolerate frequent unexpected task termination: it’s not because the hardware is particularly unreliable, it’s because the freedom to arbitrarily terminate processes enables better resource utilization in a computing cluster.

However, a real implementation may still have to include code to handle the case where something happens that was assumed to be impossible, even if that handling boils down to printf("Sucks to be you") and exit(666) — i.e., letting a human operator clean up the mess [93]. (This is arguably the difference between computer science and software engineering.)

speak to computers in a language that they understand and have them do anything that you want to do. This skill is one whose demand is increasing at an increasing rate the world over. Whether you want to learn code to pursue a career as a programmer, web developer or graphics designer or want to learn code to be able to develop your own web applications and other computerized systems, the one thing you need to do is to start somewhere. What better place to start

My son Aaron, who is a professor of computer science, encountered just such a careless signal when he was on the admissions committee at Carnegie Mellon University. One Ph.D. applicant submitted a passionate letter about why he wanted to study at CMU, writing that he regarded CMU as the best computer science department in the world, that the CMU faculty was best equipped to help him pursue his research interests, and so on. But the final sentence of the letter gave the game away: I will certainly attend CMU if adCMUted. It was proof that the applicant had merely taken the application letter he had written to MIT and done a search-and-replace with “CMU” . . . and hadn’t even taken the time to reread it! Had he done so, he would have noticed that every occurrence of those three letters had been replaced.

Table of Content Chapter 1 - Basic Networking Elements 1) Network Types 2) Network Topologies 3) Network Components A. END DEVICES & MEANS FOR TRANSMISSION B. SWITCH C. ROUTER 4) How can we represent (or “draw”) a network ? 5) How computers communicate over the Internet ? Chapter 2 – Switches, Ethernet and MAC addresses What’s Ethernet ? Chapter 3 – Routers, IPv4 & IPv6 addresses Basic Routing concepts The IPv4 Protocol IPv4 Classes Public IP vs Private IP Configuring an IP address on Windows 7/8/10 The IPv6 Protocol Chapter 4 – TCP, UDP, Ports and Network Applications 1) TCP and UDP 2) Ports 3) Network Applications Chapter 5 - Cisco IOS & Intro to the CLI Introduction to the CLI - Basic Router Configurations LAB #1

Systems Analysis and Design, Fourth Edition 5th Edition - Tilley and Rosenblatt Sams teach yourself C++ in 21 days Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences 4th Edition Milton and Arnold

A few books that I've read.... Pascal, an Introduction to the Art and Science of Programming by Walter Savitch Programming algorithms Introduction to Algorithms, 3rd Edition (The MIT Press) Data Structures and Algorithms in Java Author: Michael T. Goodrich - Roberto Tamassia - Michael H. Goldwasser The Algorithm Design Manual Author: Steven S Skiena Algorithm Design Author: Jon Kleinberg - Éva Tardos Algorithms + Data Structures = Programs Book by Niklaus Wirth Discrete Math Discrete Mathematics and Its Applications Author: Kenneth H Rosen Computer Org Structured Computer Organization Andrew S. Tanenbaum Introduction to Assembly Language Programming: From 8086 to Pentium Processors (Undergraduate Texts in Computer Science) Author: Sivarama P. Dandamudi Distributed Systems Distributed Systems: Concepts and Design Author: George Coulouris - Jean Dollimore - Tim Kindberg - Gordon Blair Distributed Systems: An Algorithmic Approach, Second Edition (Chapman & Hall/CRC Computer and Information Science Series) Author: Sukumar Ghosh Mathematical Reasoning Mathematical Reasoning: Writing and Proof Version 2.1 Author: Ted Sundstrom An Introduction to Mathematical Reasoning: Numbers, Sets and Functions Author: Peter J. Eccles Differential Equations Differential Equations (with DE Tools Printed Access Card) Author: Paul Blanchard - Robert L. Devaney - Glen R. Hall Calculus Calculus: Early Transcendentals Author: James Stewart And more....

She is an applications programmer for the Feds. In the old days, she would have written computer programs for a living. Nowadays, she writes fragments of computer programs. These programs are designed by Marietta and Marietta’s superiors in massive week-long meetings on the top floor. Once they get the design down, they start breaking up the problem into tinier and tinier segments, assigning them to group managers, who break them down even more and feed little bits of work to the individual programmers. In order to keep the work done by the individual coders from colliding, it all has to be done according to a set of rules and regulations even bigger and more fluid than the Government procedure manual.

What is Tableau Tableau Software is a highly scalable client-server architecture. It is an application that resides on your computer and used for individuals and publishing data sources as well as workbooks to tableau server. Which is allows for instantaneous insight by transforming data into interactive visualizations? Read from OnlineITGuru at Tableau Online Course

I was involved in building an early prototype of a machine that pushed back at you, a force-feedback device in which the effort required to move it could be a function of anything you wanted. Under computer control, it could change from moving freely to feeling as if it were being pushed through molasses. In one application, we had a map of Massachusetts with a demographic database. The user could plot plans for a new highway by moving this force-feedback digitizer. However, the amount of force needed to push it varied as a function of the number of families that would be displaced. In fact, you could close your eyes and plot out very literally the path of least resistance to a new highway.

​ Consensus is one of the most important and fundamental problems in distributed computing. On the surface, it seems simple: informally, the goal is simply to get several nodes to agree on something.

In the years before Julia joined the group, People Analytics had determined that Google needed to interview a job applicant only four times to predict, with 86 percent confidence, if they would be a good hire. The division had successfully pushed to increase paid maternity leave from twelve to eighteen weeks because computer models indicated that would reduce the frequency of new mothers quitting by 50 percent.

At heart, Bayes’ theorem is just a simple rule for updating your degree of belief in a hypothesis when you receive new evidence: if the evidence is consistent with the hypothesis, the probability of the hypothesis goes up; if not, it goes down. For example, if you test positive for AIDS, your probability of having it goes up. Things get more interesting when you have many pieces of evidence, such as the results of multiple tests. To combine them all without suffering a combinatorial explosion, we need to make simplifying assumptions. Things get even more interesting when we consider many hypotheses at once, such as all the different possible diagnoses for a patient. Computing the probability of each disease from the patient’s symptoms in a reasonable amount of time can take a lot of smarts. Once we know how to do all these things, we’ll be ready to learn the Bayesian way. For Bayesians, learning is “just” another application of Bayes’ theorem, with whole models as the hypotheses and the data as the evidence: as you see more data, some models become more likely and some less, until ideally one model stands out as the clear winner.

Bayes’ theorem is useful because what we usually know is the probability of the effects given the causes, but what we want to know is the probability of the causes given the effects. For example, we know what percentage of flu patients have a fever, but what we really want to know is how likely a patient with a fever is to have the flu. Bayes’ theorem lets us go from one to the other. Its significance extends far beyond that, however. For Bayesians, this innocent-looking formula is the F = ma of machine learning, the foundation from which a vast number of results and applications flow. And whatever the Master Algorithm is, it must be “just” a computational implementation of Bayes’ theorem. I put just in quotes because implementing Bayes’ theorem on a computer turns out to be fiendishly hard for all but the simplest problems, for reasons that we’re about to see.

mostly unsuccessful attempts to teach grade-school children English using transformational grammar were made during the 1960s and early 1970s. Today it is taught mostly in colleges and graduate schools. Outside linguistics, transformational grammar is used mostly in computer-language-processing applications. It has an alien look and feel to traditionalists, but it can convey interesting insights into how the language works

The Internet of Things First of all, what is the Internet of Things? The Internet of Things is the link between the internet and everyday objects that allows them to send and receive digital information and data. Its potential is huge and some say it could become a multi-trillion-dollar market. One start-up called Slock.it is attempting to tap into this potential by developing an app on the Ethereum blockchain that links physical assets, such as apartments, bikes, or vans, to a smart contract that allows users to rent the item out. The application is called Ethereum Computer and could potentially eliminate fees to rent the assets of others. It is a kind of blockchain version of Airbnb and creates a much cheaper option for both affiliates and users.

Reason #1: Downtime Aids Insights Consider the following excerpt from a 2006 paper that appeared in the journal Science: The scientific literature has emphasized the benefits of conscious deliberation in decision making for hundreds of years… The question addressed here is whether this view is justified. We hypothesize that it is not. Lurking in this bland statement is a bold claim. The authors of this study, led by the Dutch psychologist Ap Dijksterhuis, set out to prove that some decisions are better left to your unconscious mind to untangle. In other words, to actively try to work through these decisions will lead to a worse outcome than loading up the relevant information and then moving on to something else while letting the subconscious layers of your mind mull things over. Dijksterhuis’s team isolated this effect by giving subjects the information needed for a complex decision regarding a car purchase. Half the subjects were told to think through the information and then make the best decision. The other half were distracted by easy puzzles after they read the information, and were then put on the spot to make a decision without having had time to consciously deliberate. The distracted group ended up performing better. Observations from experiments such as this one led Dijksterhuis and his collaborators to introduce unconscious thought theory (UTT)—an attempt to understand the different roles conscious and unconscious deliberation play in decision making. At a high level, this theory proposes that for decisions that require the application of strict rules, the conscious mind must be involved. For example, if you need to do a math calculation, only your conscious mind is able to follow the precise arithmetic rules needed for correctness. On the other hand, for decisions that involve large amounts of information and multiple vague, and perhaps even conflicting, constraints, your unconscious mind is well suited to tackle the issue. UTT hypothesizes that this is due to the fact that these regions of your brain have more neuronal bandwidth available, allowing them to move around more information and sift through more potential solutions than your conscious centers of thinking. Your conscious mind, according to this theory, is like a home computer on which you can run carefully written programs that return correct answers to limited problems, whereas your unconscious mind is like Google’s vast data centers, in which statistical algorithms sift through terabytes of unstructured information, teasing out surprising useful solutions to difficult questions. The implication of this line of research is that providing your conscious brain time to rest enables your unconscious mind to take a shift sorting through your most complex professional challenges. A shutdown habit, therefore, is not necessarily reducing the amount of time you’re engaged in productive work, but is instead diversifying the type of work you deploy.

As we shall see, technology’s increasing inability to predict the future – whether that’s the fluctuating markets of digital stock exchanges, the outcomes and applications of scientific research, or the accelerating instability of the global climate – stems directly from these misapprehensions about the neutrality and comprehensibility of computation.

When we “see,” we are actually applying our accumulated knowledge of the world—everything we’ve learned in our lives about perspective, geometry, common sense, and what we have seen previously. These come naturally to us but are very difficult to teach a computer. Computer vision is the field of study that tries to overcome these difficulties to get computers to see and understand. COMPUTER VISION APPLICATIONS We are already using computer vision technologies every day. Computer vision can be used in real time, in areas ranging from transportation to security. Existing examples include: driver assistants installed in some cars that can detect a driver who nods off autonomous stores like Amazon Go, where cameras recognize when you’ve put a product in your shopping cart airport security (counting people, recognizing terrorists)

This book is a compilation of interesting ideas that have strongly influenced my thoughts and I want to share them in a compressed form. That ideas can change your worldview and bring inspiration and the excitement of discovering something new. The emphasis is not on the technology because it is constantly changing. It is much more difficult to change the accompanying circumstances that affect the way technological solutions are realized. The chef did not invent salt, pepper and other spices. He just chooses good ingredients and uses them skilfully, so others can enjoy his art. If I’ve been successful, the book creates a new perspective for which the selection of ingredients is important, as well as the way they are smoothly and efficiently arranged together. In the first part of the book, we follow the natural flow needed to create the stimulating environment necessary for the survival of a modern company. It begins with challenges that corporations are facing, changes they are, more or less successfully, trying to make, and the culture they are trying to establish. After that, we discuss how to be creative, as well as what to look for in the innovation process. The book continues with a chapter that talks about importance of inclusion and purpose. This idea of inclusion – across ages, genders, geographies, cultures, sexual orientation, and all the other areas in which new ways of thinking can manifest – is essential for solving new problems as well as integral in finding new solutions to old problems. Purpose motivates people for reaching their full potential. This is The second and third parts of the book describes the areas that are important to support what is expressed in the first part. A flexible organization is based on IT alignment with business strategy. As a result of acceleration in the rate of innovation and technological changes, markets evolve rapidly, products’ life cycles get shorter and innovation becomes the main source of competitive advantage. Business Process Management (BPM) goes from task-based automation, to process-based automation, so automating a number of tasks in a process, and then to functional automation across multiple processes andeven moves towards automation at the business ecosystem level. Analytics brought us information and insight; AI turns that insight into superhuman knowledge and real-time action, unleashing new business models, new ways to build, dream, and experience the world, and new geniuses to advance humanity faster than ever before. Companies and industries are transforming our everyday experiences and the services we depend upon, from self-driving cars, to healthcare, to personal assistants. It is a central tenet for the disruptive changes of the 4th Industrial Revolution; a revolution that will likely challenge our ideas about what it means to be a human and just might be more transformative than any other industrial revolution we have seen yet. Another important disruptor is the blockchain - a distributed decentralized digital ledger of transactions with the promise of liberating information and making the economy more democratic. You no longer need to trust anyone but an algorithm. It brings reliability, transparency, and security to all manner of data exchanges: financial transactions, contractual and legal agreements, changes of ownership, and certifications. A quantum computer can simulate efficiently any physical process that occurs in Nature. Potential (long-term) applications include pharmaceuticals, solar power collection, efficient power transmission, catalysts for nitrogen fixation, carbon capture, etc. Perhaps we can build quantum algorithms for improving computational tasks within artificial intelligence, including sub-fields like machine learning. Perhaps a quantum deep learning network can be trained more efficiently, e.g. using a smaller training set. This is still in conceptual research domain.

The winner of that particular honor is an algorithm called Comparison Counting Sort. In this algorithm, each item is compared to all the others, generating a tally of how many items it is bigger than. This number can then be used directly as the item’s rank. Since it compares all pairs, Comparison Counting Sort is a quadratic-time algorithm, like Bubble Sort. Thus it’s not a popular choice in traditional computer science applications, but it’s exceptionally fault-tolerant. This algorithm’s workings should sound familiar. Comparison Counting Sort operates exactly like a Round-Robin tournament. In other words, it strongly resembles a sports team’s regular season—playing every other team in the division and building up a win-loss record by which they are ranked. That Comparison Counting Sort is the single most robust sorting algorithm known, quadratic or better, should offer something very specific to sports fans: if your team doesn’t make the playoffs, don’t whine. The Mergesort postseason is chancy, but the Comparison Counting regular season is not; championship rings aren’t robust, but divisional standings are literally as robust as it gets. Put differently, if your team is eliminated early in the postseason, it’s tough luck. But if your team fails to get to the postseason, it’s tough truth. You may get sports-bar sympathy from your fellow disappointed fans, but you won’t get any from a computer scientist.

The Gausebeck-Levchin test became the first commercial application of a Completely Automated Public Turing Test to Tell Computers and Humans Apart—or CAPTCHA. Today, CAPTCHA tests are common on the internet—to be online is to be subjected to a search for a specific image—a fire hydrant or bicycle or boat—from a lineup. But at the time, PayPal was the first company to force users to prove their humanity in this fashion. Gausebeck and Levchin didn’t invent the CAPTCHA—Carnegie Mellon researchers devised something similar in 1999—but the PayPal version was the first to scale, and among the first to solve the centuries-old challenge of separating human from machine.

Vaccination has made smallpox extinct in the wild, as well as rinderpest, a relative of measles that affects cattle and buffalo, among others. Poliomyelitis, which has in its heyday killed and maimed millions of children and adults alike, is close to eradication, with fewer than 200 wild-type cases documented in 2020. Vaccines are some of the most effective public health interventions against infectious disease.

The term 'natural immunity' has been often used to express post-infectious immunity and differentiate it from vaccine-induced immunity. In practice, this is not necessarily helpful. There is nothing fundamentally "unnatural" in vaccine-induced immunity, and while the minutiae of natural infection and vaccine-induced immunity might differ, this is a quintessentially unhelpful notion.

Cloud Native application developers should never know the physical infrastructure. Cloud is where they experience an infrastructure that is built for their specific service requirements. – Tom Golway

There is an unhelpful tendency to regard superspreaders – and events where superspreading has occurred – as anomalies out of the ordinary. This contributes relatively little to our understanding of infectious dynamics and is bound to exacerbate the stigmatisation of individuals, as it has e.g. during the early years of AIDS, when much sensationalistic and unjustified blame was laid at the feet of early HIV patient Gaetan Dugas (on which see McKay, 2014). Rather, superspreading is one 'tail' of a distribution prominent mainly because it is noticeable – statistical models predict that there are generally an equal number of 'greatly inferior spreaders' who are particularly ineffective in spreading the illness.

Few diseases have had an impact on human evolution, culture and society on par with malaria. It is one of the oldest documented infectious diseases. Indeed, it has been hypothesised that the protective effect bestowed by a heterozygous sickle cell allele explains its survival to the modern day. As such, malaria has left its footprint on human evolution in a profound way few other diseases have. Yet its true origins were the matter of considerable controversy. The clue is in the name – the prevailing theory until Ross's discovery was that malaria resulted from 'mala aria', that is, 'bad air'. It took the advent of modern evidence-based medical science to challenge this 'miasma theory'. Ross's elucidation of the role of mosquitoes in the lifecycle of malaria has opened up a new subject for epidemiological consideration: the vector-borne disease.

MARV serves as a poignant example of the way a pathogen that is highly prevalent in its reservoir host population can hide safely without human notice, until in some unfortunate accident, hosts and vectors cross paths.

higher antimicrobial loads will result in a lower total pathogenic load but also a lower involvement of the immune system and therefore less immunity in the long run (as indeed has been empirically demonstrated in a number of experiments summarised in a sweeping review by Benoun (2016)). Thus, while rapid and aggressive antimicrobial treatment is sometimes appropriate, the long-term absence of ensuing CD4+ immunity is its cost.

The word 'vaccination' comes from vacca, the Latin word for 'cow'. This is a poignant recapitulation of the history of vaccines. The first vaccine properly so called had, as its active ingredient, the cowpox virus, a close relative of smallpox that however was much less likely to cause severe, disfiguring or lethal disease. Edward Jenner observed that milkmaids, who were often exposed to cowpox, suffered a relatively mild disease, but would be immune to the much more serious smallpox. In an experiment that would unlikely pass muster in the modern world, he infected James Phipps, then an 8-year-old, with cowpox. He suffered a mild and transient illness, but when he was later exposed to scabs from a smallpox patient, he proved immune. Unlike the earlier practice of variolation, which has been practised in late Song dynasty China that sought to induce the cutaneous form of smallpox, variola minor, to protect against the more severe forms of smallpox (variola major), Jenner's vaccination used a less pathogenic virus. He relied on what would later be called 'antigenic similarity', but which was at the time hardly understood.

One of the greatest ideas of mathematics is that all time series one is likely to encounter in nature can be described as a superposition of periodic functions.

The same dynamics that keep us safe in a pack, herd or society, and comfortable in our family, friends or neighbours also serves as a way for pathogenic transmissions. The warmth of a human dwelling or the immense complexity of a bee hive is also an opportunity for a pathogen to tap into a susceptible population. Network interdiction is a comprehensive name for algorithms intended to disrupt such connections.

One of the most complex computer games ever devised is called Dwarf Fortress. It is not much to look at: its graphics are the terminal-based structures that were in vogue in the 1980s. What makes Dwarf Fortress an extraordinary game is the depth of agent-based logic: every character, every enemy unit, even pets are endowed with a hugely complex agent-based behavioural model. As an example, cats in Dwarf Fortress can stray into puddles of spilled beer, lick their paws later, and succumb to alcohol poisoning. Yet agent-based modeling is about much more than belligerent dwarves and drunk cats. Agent-based models are powerful computational tools to simulate large populations of boundedly rational actors who act according to preset preferences, although often enough in a stochastic manner.

Computational models of infectious disease can make all the difference in our response to pandemics. As habitat loss and climate change make zoonotic spillover events increasingly more likely, COVID-19 is almost certainly not the last major pandemic of the 21st century.

Atoms, elements and molecules are three important knowledge in Physics, chemistry and Biology. mathematics comes where counting starts, when counting and measurement started, integers were required. Stephen hawking says integers were created by god and everything else is work of man. Man sees pattern in everything and they are searched and applied to other sciences for engineering, management and application problems. Physics, it is required understand the physical nature or meaning of why it happens, chemistry is for chemical nature, Biology is for that why it happened. Biology touch medicine, plants and animals. In medicine how these atoms, elements and molecules interplay with each other by bondage is being explained. Human emotions and responses are because of biochemistry, hormones i e anatomy and physiology. This physiology deals with each and every organs and their functions. When this atom in elements are disturbed whatever they made i e macromolecules DNA, RNA and Protein and other micro and macro nutrients and which affects the physiology of different organs on different scales and then diseases are born because of this imbalance/ disturb in homeostasis. There many technical words are there which are hard to explain in single para. But let me get into short, these atoms in elements and molecules made interplay because of ecological stimulus i e so called god. and when opposite sex meets it triggers various responses on body of each. It is also harmone and they are acting because of atoms inside elements and continuous generation or degenerations of cell cycle. There is a god cell called totipotent stem cell, less gods are pluripotent, multi potent and noni potent stem cells. So finally each and every organ system including brain cells are affected because of interplay of atoms inside elements and their bondages in making complex molecules, which are ruled by ecological stimulus i e god. So everything is basically biology and medicine even for animals, plants and microbes and other life forms. process differs in each living organisms. The biggest mystery is Brain and DNA. Brain has lots of unexplained phenomenon and even dreams are not completely understood by science that is where spiritualism/ soul touches. DNA is long molecule which has many applications as genetic engineering. genomics, personal medicine, DNA as tool for data storage, DNA in panspermia theory and many more. So everything happens to women and men and other sexes are because of Biology, Medicine and ecology. In ecology every organisms are inter connected and inter dependent. Now physics - it touch all technical aspects but it needs mathematics and statistics to lay foundation for why and how it happened and later chemistry, biology also included inside physics. Mathematics gave raise to computers and which is for fast calculation on any applications in any sciences. As physiological imbalances lead to diseases and disorders, genetic mutations, again old concept evolution was retaken to understand how new biology evolves. For evolution and disease mechanisms, epidemiology and statistics was required and statistics was as a data tool considered in all sciences now a days. Ultimate science is to break the atoms to see what is inside- CERN, but it creates lots of mysterious unanswerable questions. laws in physics were discovered and invented with mathematics to understand the universe from atoms. Theory of everything is a long search and have no answers. While searching inside atoms, so many hypothesis like worm holes and time travel born but not yet invented as far as my knowledge. atom is universe, and humans are universe they have everything that universe has. ecology is god that affects humans and climate. In business these computerized AI applications are trying to figure out human emotions by their mechanism of writing, reading, texting, posting on social media and bla bla. Arts is trying to figure out human emotions in art way.

Why mobile app hosting is fundamental for your versatile application? Portable application hosting is fundamental for your site? Also, why it is compulsory to work? To lay it out plainly, you have constructed a versatile application. What would be the best next step? Fostering an application isn't generally so direct as tossing it in the air; it needs a spot to live, or all the more precisely, a hosting supplier. It's better assuming it's done on an outside server since your gadget won't deal with the power. An application that crashes each time won't acquire large number of clients, which youthful new businesses need. Versatile app hosting services is fundamental, with a powerful server is the best arrangement. We'll take a gander at how portable applications create and why composing code isn't the entire story. How would you foster a portable application? It's more convoluted than you likely suspect. It comprises of two sections. Utilizing a telephone or tablet, the client can explore the application's front end by clicking buttons and moving sliders. The server-side, nonetheless, should be answerable for showing buttons and sliders. When you click on the button, a data demand is shipped off the server. Subsequent to handling, you will figure out the outcomes. You ought to have another screen stacked in practically no time, so you will not lose significant clients pausing. Is it important to have a versatile application? Versatile application improvement requires something other than composing code. The client's gadget will clearly contain the whole backend if the application resembles a mini-computer with just rudimentary capacities. Notwithstanding, a backend should exist that offers more complicated capacities, and something should empower solicitations to be satisfied there. In this manner, App Hosting is fundamental. It alludes to introducing an application on the server of a supplier, like Amazon Web Services (AWS) or Google Cloud Platform (GCP). These suppliers put the application on their servers. There are basically no distinctions between Mobile App Hosting and hosting sites. In like manner, the versatile application hosting server processes a solicitation sent by the client. The client makes a move or sends a solicitation. So what precisely is Code Push? It would assist with fixing bugs when they happen toward the front. In AppStore and Google Play, an update requires an audit each time it is made. The interaction requires 30 minutes for Android and could take more time to a day for iOS. You can robotize this and pass the survey by transferring updates to Code Push. Designers can without much of a stretch update their React Native applications utilizing the App Center. Applications can demand refreshes utilizing the gave client SDK from the focal vault, which is a focal store for refreshes. Mechanizing refreshes permits us to fix blunders quicker, setting aside us time and cash. How do these administrations vary? Cloud hosting is one model. It's something we've utilized ourselves first. Then, at that point, on the grounds that a ton of organizations use it, Whence comes this? Rather than regular hosting, cloud hosting utilizes only one server rather than different servers. A virtual and actual organization of cloud servers has the application or site. How much is portable application hosting fundamental in the cloud? Reliability You would lose your item assuming something happened to the server it was facilitated. Another situation includes many machines that are associated. Information will stay on the organization regardless of whether it vanishes from one server. Efficiencies Dissimilar to a normal server, cloud hosting can increment framework assets. This is on the grounds that the server's ability should be expanded assuming the quantity of clients increments abruptly. Assuming you utilize a devoted server, the cycle is more adaptable.

This is a deliberate choice in the design of computers: if an internal fault occurs, we prefer a computer to crash completely rather than returning a wrong result, because wrong results are difficult and confusing to deal with. Thus, computers hide the fuzzy physical reality on which they are implemented and present an idealized system model that operates with mathematical perfection.

React Native, being the most compelling and captivating technology for app development has been growing at fanatic pace since inception. Using this Facebook technology, NicheTech provides customized React Native app development services leveraging its vast skill set and technology expertise.

Ethereum charges a gas fee for every transaction – similar to how driving a car takes a certain amount of gas, which costs money. Imagine Ethereum as one giant computer with many applications (i.e., smart contracts). If people want to use the computer, they must pay for each unit of computation. A simple computation such as sending ether (ETH) requires minimal work to update a few account balances and thus has a relatively small gas fee. A complex computation involving minting tokens and checking various conditions across many contracts requires more gas and thus will have a higher fee. The gas fee may lead to a poor user experience, however. It forces agents to maintain an ETH balance to pay it and leads to worry about overpaying, underpaying, or the transaction not taking place at all. So initiatives are ongoing to eliminate gas fees from end users.

According to technologist David Rosenthal, speculation on cryptocurrencies is the engine that drives Web3—that it can’t work without it. “[A] permissionless blockchain requires a cryptocurrency to function, and this cryptocurrency requires speculation to function,” he said in a talk at Stanford in early 2022.4 Basically, he’s describing a pyramid scheme: Blockchains need to give people something in exchange for volunteering computing power, and cryptocurrencies fill that role—but the system works only if other people are willing to buy them believing that they’ll be worth more in the future. Stephen Diehl, a technologist and vocal critic of Web3, floridly dismissed blockchain as “a one-trick pony whose only application is creating censorship-resistant crypto investment schemes, an invention whose negative externalities and capacity for harm vastly outweigh any possible uses.

As noted previously, there are a number of other algorithms beyond search, prime factors and Monte Carlo methods, though many of these apply only to very specialist mathematical problems and may never have practical applications. As yet, though, the range available is relatively limited. Some of this may be due to the limitations that are imposed in dreaming up algorithms without an actual device to run them on, but it is entirely possible that the list will always be fairly short, as we shouldn’t underestimate the difficulties of getting quantum algorithms that will run. However, Lov Grover commented in an interview with the author a while ago: ‘Not everyone agrees with this, but I believe that there are many more quantum algorithms to be discovered.’ Even if Grover is right, quantum computers are never going to supplant conventional computers as general-purpose machines. They are always likely to be specialist in application. And, as we shall see, it is not easy to get quantum computers to work at all, let alone develop them into robust desktop devices like a familiar PC.

In the world of cloud, scale is the game changer.

Without a computer and with no other way to access the Internet, she had managed to submit fifty job applications online via her iPhone’s tiny touch screen in the past few months. While these applications had generated some interviews, they had not resulted in a single job offer.

Lync has its title altered. And so what sort of computer software is it now? Well, it is identified as Lync Mac Business. The particular motive for carrying this out is a need to combine the familiar experience and level of popularity from consumers associated with Lync Mac along with security regarding Lync as well as control feature set. Yet another thing which Lync has got influenced in this specific new version of Lync happens to be the transformation associated with particular graphical user interface aspects which are used in the popular program of Lync Mac. It has been chose to utilize the same icons as in Lync as an alternative to attempting to make new things. Microsoft Company furthermore included the particular call monitor screen which happens to be applied within Lync in order that consumers could preserve an active call seen inside a small display when customers happen to be focusing on yet another program. It is additionally essential to point out that absolutely no features which were obtainable in Lync are already eliminated. And you should additionally understand that Lync Mac happens to be nevertheless utilizing the foundation regarding Lync. And it is very good that the actual software is nevertheless operating on the previous foundation since it happens to be known for the security. However what helps make Lync Mac a great choice if perhaps you're searching for an immediate texting software? There are a wide range of advantages which this particular application has got and we'll have a look at a few of these. Changing from instantaneous messaging towards document sharing won't take a great deal of time. Essentially, it provides a flawless incorporation associated with the software program. An improved data transfer administration is yet another factor that you'll be in a position enjoy from this program. Network supervisors can assign bandwidth, limit people and also split video and audio streams throughout each application and control the effect of bandwidth. In case you aren't making use of Microsoft Windows operating system and prefer Lync in that case possibly you're concerned that you will not be able to utilize this particular application or it is going to possess some constraints? The reply happens to be no. As we've talked about many times currently, Lync is currently best-known as being Lync For Mac Business .There is nothing that is actually extracted from the main edition therefore the full functionality is actually offered for you. And it is certainly great to understand the fact that Lync that we should simply call Lync For Mac version is actually capable to provide you all the characteristics which you'll need. If you happen to be trying to find a fantastic application for your own organization, in that case this is the one particular you are in search of Lync For Mac which will still be acknowledged as being Lync for a long period edition is actually competent to present you with everything that is actually necessary for your organization even if you decided to not utilize Microsoft operating system. Know about more detail please visit lyncmac.com

Software vendors are building new applications specifically for these new architectures. Third parties are creating tools to monitor and manage these applications and infrastructure areas. As cloud computing begins to become the de facto model for development, deployment, and maintaining application services, this area will expand even further.

One way to track social media is through a tool called Rescue Time, which runs in the background of your computer and gives you a detailed report (broken down by time spent and overall percentages) of the sites and applications that you frequently use.