Campus 365 is a multipurpose school management system which aids in automating the school’s daily operations hassle-free and provide insightful reports and 360-degree tracking so that the stakeholders can make better and faster decisions to escalate the productivity of their institution

Campus 365

102 Stories To Learn About Encryption

379 Stories To Learn About Data Privacy

What the COVID-19 pandemic and the subsequent lockdowns have shown is how ill-prepared the higher education system was for the challenge. Although 97% of universities and colleges have eventually their journeys weren’t smooth — 63% of students say the quality of instructions has worsened. switched to online or blended learning, Now schools across the globe are rushing their digital transformation initiatives adopting to make learning, and remote learning in particular, more efficient and personalized, possibly without spending a fortune on digitizing their operations. educational technology solutions But how do higher education institutions navigate educational innovations? And how can artificial intelligence, cloud computing, intelligent automation, and teleconferencing help schools achieve higher academic performance and drive revenue? Let’s dive in. So, how do education and technology join up? Technology can transform every aspect of how students, professors, and alumni interact and how campuses are running, easing the shift toward cheaper, more accessible, and more engaging education. The key education technology use cases that make this shift happen are: Student lifecycle management Student engagement and motivation Smart campus and smart dorm solutions Assistive learning technology Tech-assisted mental health interventions Student lifecycle management (SLM) With student lifecycle management software, universities and colleges can develop a data-driven approach to education, automate routine processes, and let students access educational resources anywhere, anytime. One of the biggest trends in educational technology, SLM software optimizes the entire student lifecycle, from prospecting and enrollment through creating a nurturing learning environment to graduation and alumni support. Prospecting and enrollment Doing their research about a university, applicants usually visit its website, go through the schools’ social media, weigh out alumni’s impressions, and only then submit an application. SLM solutions optimize the interaction between the potential students and the school at each of these touchpoints. and AI bring in robust insights to universities’ recruitment campaigns. The techs allow monitoring how effective a school’s marketing efforts are in real time to attract the best students. Data analytics Leveraging artificial intelligence and machine learning in education allows processing myriads of social media data to uncover what students, alumni, and parents really think about your school. Competitive intelligence helps to compare a school’s academic performance and its attractiveness for potential applicants against other higher education institutions. To speed up or even automate student enrollment, universities are widely adopting CRM software. CRMs foster application management at every stage — from application receipt and confirmation through analyzing if it meets the set requirements to routing the application for approval and claiming the final verdict. Information and communication technologies in education also ignite the transition to more affordable subscription-based online learning (think: ). Students would soon be able to browse through a school’s available programs, subscribe to the one they like, and connect a credit card for automatic monthly payments. A pioneer in subscription-based learning, Boise State University a year, and almost every learner fully completes their credit commitment. Online students also pay 30% less in tuition fees. Netflix-style smart education platforms enrolls 3,500 fully online students Billing and accounting operations Tech-savvy students of today expect their tuition and other payments to be handled smoothly and quickly, which calls for colleges to adopt billing and accounting technology for education. Such solutions usually feature an accounting portal for the administration and a mobile app for students. The students can use the app to conveniently pay tuition fees or make on-campus purchases, while the accounting portal allows centralized and swift payment processing. The University of Wyoming, for example, used to send out their bills via the postal service with the help of a contractor who manually processed, printed, and mailed out the bills. It took approximately a week before the bills reached the students, which was slow and also rather costly. Today, however, the university uses e-billing software to automatically process thousands of bills, . saving about $45,000 a year Curriculum personalization With , universities can tailor the learning process to a student’s academic achievements, background, interests, and inclinations. To empower academic success, AI analyzes tests, assignments, classroom participation notes, and other data to build a unique student profile and identify what makes the student engage and what causes struggles. AI solutions for education Based on the profile, AI provides tips on how educational materials can be tweaked. For example, AI can tell whether a particular student prefers listening, reading, or watching a video to take in information. As a result, students start benefiting from a personalized learning environment; instructors use reports on students’ academic achievements to further improve the way they teach; curriculum and content designers get useful insight into content usage; college administrations tap in useful statistics on the school’s overall performance and the bottlenecks that may halt it. On-campus communication Key innovative technologies that make it easier for students to engage in campus experiences are chatbots and videoconferencing. Chatbots provide immediate responses to student queries and solve many extra tasks, from helping navigate the campus to reminding about upcoming exams to sending out grades reports, and more. Georgia State University, for instance, has implemented a to help newly admitted students prepare for enrollment. Namely, the chatbot gives answers to the questions about financial aid and housing and helps freshmen register for classes. During the first month after the implementation, the chatbot exchanged about 50,000 texts, and less than 1% of students had to be routed to the university staff for further clarifications. chatbot has become the key enabler of distant and blended learning, but the value this technology drives in education will endure after the pandemic as well. Conferencing apps may help professors make the learning process more engaging, enjoyable, and convenient. They could, for instance, invite subject-matter experts to hold video lectures or consult students via online office hours. Yale University, for example, uses videoconferencing to teach rare languages like Yoruba and Zulu with the students and the instructor being miles away from each other. Video conferencing Smart campus Putting educational innovations to use, universities can create next-gen campus infrastructures that meet the demand of today’s tech-savvy students. Smart campuses embrace technology applications that make up a connected infrastructure and create intuitive experiences for students, professors, prospects, and college administration. Campus safety and security Higher education institutions may leverage AI-powered CCTV cameras, biometric technology, and facial recognition to keep unauthorized people off-campus so that a student can get in a dorm only if they allow their fingerprints or facial features to be scanned by AI. The same technology can be used to automatically track class attendance, identify absentees, or get real-time feedback about which parts of a class make students engage and which fail to arouse interest. But as good as improved safety and automated tracking may sound, AI-powered surveillance and facial recognition cause fierce resistance among students and evoke debate about the . moral implications of modern tech One way of alleviating the ethical concerns while improving security is recognizing violent behaviors and potential threats rather than facial features. Several startups like and Athena claim to rely on such an approach in their safety and security solutions. ZeroEyes Smart dorm and recreation To provide better services and drive cost savings, housing, dining, and recreation facilities can be digitized, too. For instance, relying on the data fetched from motion tracking sensors, smart lighting systems, and connected thermostats can automatically turn off the lights and lower room temperature when no one is around. The University of Arizona has already adopted smart college and campus technologies, but they have gone beyond standard use cases and also deployed a network of plumbing sensors to monitor water lines usage and prevent leaks. When it comes to dining, techs drive student experience here as well. With technology integrated into dining services, students can conveniently look through the available menu options via a self-service kiosk or a mobile app, view nutrition information, and place an order. Many higher education institutions also set up technology to provide for quality recreation. ASU has, too, implemented connected sensors to monitor weather, humidity, temperature, and noise levels inside the university’s sports arena. Student engagement and motivation To liven up the learning process, enhance student engagement, and maintain the sense of community despite the lockdown, colleges and universities have started leveraging smart learning environments, virtual tutors, and gamification. Smart learning environments By bringing whiteboards, 360-degree video tools, and augmented and virtual reality to education, colleges can create immersive learning experiences. Interactive whiteboards, for instance, allow more flexibility in content delivery, support file sharing, and provide simple access to the internet, engaging learners via multiple models of interaction. AR and VR simulations help students grasp complex concepts, reconstruct historical events, engage in practical training, and more. San Diego State University, for instance, has already turned the power of VR in education to their benefit. The smart school uses VR headsets to teach astronomy and make students experience ideas that cannot be explained verbally via visual means. And here’s an interesting use case of augmented reality in education. Rensselaer Polytechnic Institute has built with a 360-degree projection system that “transports” the school’s Mandarin learners to Chinese city streetscapes. Conversing with AI-powered avatars that recognize learners’ speech, gestures, and facial expressions, the students master Mandarin twice as fast as their fellows taught in conventional classrooms. an immersion lab Virtual tutors Virtual tutors are intelligent, AI-powered avatars one can converse with just like with a human. The behavior of a virtual tutor can be tailored to any task, from enhancing medical students training to facilitate foreign language practice. The avatars can even be trained to mimic a person with trauma to, say, act as a patient for psychology students. Among the universities that have already adopted virtual teachers and tutors at the University of Buffalo’s Graduate School of Education. The school uses an avatar named Kevin to enhance the learning experience for students majoring in teaching. Now the students perfect their tutoring and instructing skills talking to a virtual counterpart and already notice an increase in their professional confidence. Gamified virtual campus solutions Having switched to videoconferencing to enable distance learning, universities and colleges are now and augmented reality apps for education to create virtual campuses. embracing gamification features Virtual campuses are interactive environments where students can meet, study, and chat. Just like in video games, a student uses their laptops’ keyboard and a microphone to walk around the campus and talk with other students or professors presented by digital avatars. Stanford’s Graduate School of Business is one of the pioneers in adopting virtual campus technology. The environment they’ve built allows students to navigate the digital copy of the school’s campus, “teleport” from one room to the next and attend online classes with an instructor’s avatar on the virtual stage. In turn, the instructors can put students into private groups, hand out lecture notes, and more. Assistive learning technology In the US, every classroom includes students with special needs, and assistive learning innovations in education can make a difference to how they learn. Writing assistance Students struggling with literacy or those who want to boost their writing skills, for instance, can benefit from , word prediction, and automated text formatting. Apart from that, modern writing assistance tools, like Hemingway Editor, Ghotit, or Ginger, can evaluate the clarity and readability of texts and even provide tailored practice sessions based on the mistakes a student made in the past. AI-powered spelling and grammar checks At the University of Michigan, for example, professors and students already use an AI-powered tool that analyzes students’ papers to let students take their writing skills a step further and help professors streamline grading. Speech-to-text solutions Speech-to-text software can assist students with special needs in communicating with their teachers and peers. Office 365 applications, for instance, feature an AI-based add-in that converts speech into text as a student speaks into a microphone. Another helpful tool is Microsoft’s Immersive Reader. The tool was designed specifically for students with dyslexia and dysgraphia and allows them to have any text read out loud, and even broken into syllables. Tech for students with hearing and vision disabilities Many apps and browsers today come with built-in screen magnifiers, high contrast mode, dictation, and audiovisual assistants that can read the contents of a web page out loud. For the students who need Braille support, colleges and universities can leverage Braille keyboards to improve the learning experience even further. And students with hearing difficulties can benefit from videoconferencing tools with built-in captioning, sound-field systems, as well as FM systems — wireless devices that transmit sounds directly to a hearing aid and help students communicate even in a noisy environment. Technology-assisted mental health interventions In the US, one in three college students reports having some kind of mental health disorder. In addition to offering individual and group therapy, universities can promote the use of tech like mobile apps and chatbots to expand their mental health care to the students who are reluctant to turn to in-person services. Mental health apps relying on cognitive behavioral therapy, for instance, have proven effective in alleviating anxiety, depression, and stress levels. Such apps can also analyze data from a mobile phone’s built-in sensors or wearables to reveal changes in students’ behavior patterns and provide tips on how to prevent worsening of the revealed mental health conditions. Mobile apps and chatbots help freshmen adjust to college, too. Offering personalized exercises and daily activities, the chatbots help build up resilience and increase well-being. The University of Michigan, for example, uses a similar bot that allows students to take a survey and get tailored resources to boost their mental health. Overcoming top challenges of implementing educational technology Innovative in every possible field but paradoxically conservative when it comes to redesigning their own structures, higher education institutions have to battle many challenges on their way to digital transformation. The ones that need special attention are: Overcoming the digital divide Although many students have successfully switched to online learning and already enjoy the improvements brought by technology, there are millions who are deprived of basic facilities like network connectivity and cannot access educational resources online. As the problem is multi-faceted, it can hardly be resolved by higher education institutions alone. Rather, the solution should be a product of collaborative effort. Governments, nonprofit organizations, educational institutes, and education technology companies should team up to provide access to the internet for low-income families, for instance, via non-commercial community networks and community technology centers. Dedicating to continuous improvement Innovation for its own sake makes little difference. To uncover the full potential of technology in education, colleges and universities should adopt tech wisely and, once they have built their IT infrastructures, continuously test and improve them. And to further improve the overall learning experience, enhance operations, and uncover new revenue streams, it is worth dedicating effort to research and development and tapping into new business models that are enabled by technology. Preventing cyberattacks After transitioning to distant learning and amplifying their IT infrastructures with new services, more higher education institutions fall victim to cyberattacks. The University of California, for instance, had to pay $1 million in ransom after their internal system was breached and the University of Utah lost over $400,000. To prevent cyberattacks, higher education institutions need to build security in their IT environments by design, regularly assess security risks and develop mitigation procedures, design security guidelines, and encourage professors, students, and university administration to closely follow them. Settling moral implications. As far as next-gen technologies like AI, smart monitoring, or intelligent automation are concerned, the ethical implications of their adoption should be carefully thought out. As both students and professors may object to digital transformation (the former are often afraid that their role will diminish as AI infiltrates education; the latter disapprove of being monitored and expect technology to surpass their freedoms). To alleviate ethical issues, colleges and universities must use technology responsibly and focus on explainability — that is make sure to inform all parties about how digital solutions would impact the learning process, how they make decisions (if AI is in use), and which data they need to do so. The takeaways Technologies are shaping the future of higher education, and many higher education institutions have already tapped into digital transformation — whether to make education more accessible and fun, improve daily operations, or drive cost savings. But no matter the goals, colleges, and universities should not underestimate the importance of thorough planning. It is with a thought-out digital transformation strategy and the support of an experienced tech partner that higher education institutions get the most from investing in tech. Previously published at https://itrexgroup.com/blog/technology-innovations-in-higher-education/

5 Innovations In Tech That Are Transforming Higher Education

Top 50 App Development Companies: 50 Brands to Look Out For

Every year computers ease deeper into our everyday lives. Traffic lights and water pitchers pack tiny processors to form an entire internet of things. Moore’s Law continues to forge more portable power as computers have migrated from our offices to our homes to our pockets. As companies plan what’s next, some look to tablets like Apple’s iPad or Microsoft’s Surface Pro as the heir apparent. Pay no mind. The future of personal computing is not about subtracting ounces from a device. It’s about dividing objects by identity. The future of personal computing is personalized computing. “When we were an agrarian nation, all cars were trucks, because that’s what you needed on the farm. But as vehicles started to be used in the urban centers, cars got more popular…PCs are going to be like trucks. They’re still going to be around, they’re still going to have a lot of value, but they’re going to be used by one out of X people.”  -Steve Jobs, 2010 That metaphor continues to unfold. Carmakers will soon see their core business model swing from private car ownership to subscription access to a suite of transportation options. Technologies like Tesla’s Self-Driving capability and Uber’s tiered ride sharing platform are accelerating this transition from private transportation to personalized transport. A similar shift will occur as people migrate from owning personal computers to accessing personalized computing experiences. The change is afoot. Network speed, hardware availability, storage size, and security the key levers. Link NYC Hardware Availability Desktops, laptops, and tablets will become more ubiquitous. Offices, cafes, , , , and will continue to put computers in front of us to work, buy, and navigate the world around us. Increased access to capable computing will reduce the need for us to supplement our phones with additional devices. libraries airports malls cities OneWeb satellite constellation Network Speed & Ubiquity . This will allow all internet devices to remain perpetually online. With always-on Gigabit internet, data packets can criss-cross the globe almost instantly. Near-field networking protocols are also becoming faster and more reliable with every iteration. The world will soon be blanketed in reliable, high-speed internet Storage Size The NAND flash memory found in most high-end devices stores more and more data into a smaller and smaller footprint. Apple Watch, for example, has an 8GB chip. It won’t be long before it can hold 128GB. Security + robust encryption will attempt to make transferring information safer. Be it a fingerprint, retina, or DNA, the addition of biometric verification will allow us to securely send data to devices near and far. Biometric security At your best, you are Voltron. Voltron Condense these advancements into the most efficient package and you will see a tablet is not ideal. A watch is. It is more affordable, packs the networking, local storage, and a biometric sensor in a format that leaves both hands free. Imagine a watch with enough storage for your computer settings and passwords. Approach any computer while wearing your watch, verify that you’d like to use it, and boom, your personal computer is unlocked. Your settings, cloud based files, media, and services are ready. Network drives have been available for decades. Most major research universities provide each student with login credentials that summon a personal profile and documents onto any campus computer. Multiply that by 1,000,000. Log into any computer, public or private, and you can temporarily transfer your personal computing assets in the time it takes a modern Mac to boot. As you work, all files and changes are saved back to your watch. Log out and leave no trace. Your computer goes where you go. Culture Shift Service vs Product There’s a larger economic trend playing out today. The shared economy is partially a rejection of the value of private ownership. The Netflix and chill generation has sent shockwaves across business. See Spotify & Hulu (Entertainment), Harry’s & Quip (Personal Care), Office 365 & Adobe Creative Cloud (Productivity), Zipcar & Lyft (Transportation). Still, even with Uber only a few taps away, many New Yorkers still own their own cars. Likewise, some people will continue to own private computers. However as our watches and phones become more powerful, large-screen, high-powered computing will become a service not a product. Personalized Computing A portable device with local storage, high speed networking, and biometric security that can safely store and disperse all of our data means you never have to fill out another form, carry a metro pass, or worry about cancelling a credit card. With a flick of that wrist, you can provide your health history and identification. Double tap your steering wheel and transfer your license and registration without a word. Dab an ATM to remove cash without typing a pin. All of your data is hardware encrypted to your unique device and verified by your biometric signature. Any outward facing information is just an alias. Your driver’s license, debit card, insurance, gym membership, health records, Netflix subscription, addresses, metro passes, all stored securely and backed up to the cloud. But, not the cloud we’re used to. Verifiably You The barrier to the next stage of personal computing is not technology. The barrier is trust. When personal information is sold or hackers compromise Visa, Google, or world governments, the public loses faith in digital systems to manage personal information. For the next stage of personal computing to take shape, we need a system that engenders trust. For some that could mean bringing all of their data onto their personal device. But, what happens when that device is damaged or destroyed? Enter . Instead of using a series of passwords (account numbers, pins, and liscenses are essentially passcodes) on remote servers entrusted to sometimes unreliable agents who verify each transaction, data is stored in encoded cryptographic “blocks” that live across a network of publicly verified ledgers. Any attempt to interact with these blocks requires device-level two-factor authentication and digital signatures. So, Bank of America does not store your data on a private server where it is in danger of manipulation, fraud, or human error. There are not passwords to keep up with because your fingerprint matched to your physical device is the only password you need. Blockchain The Next Wave With every major change, computing has stepped closer to the individual. We can easily forecast a future where computers will exist as chips implanted into the human body. When you consider that, a tablet appears much closer to a desktop than any future computing shift. In fact, the largest clue that tablets are a red herring for the future of personal computing is how ardently tablet makers have worked to make them . Due to the assymetric maturity of the key technologies (blockchain, ubiquitous high speed networking, storage miniaturization, biometric security, hardware availability), the complete solution will also bypass handhelds altogether. So the next time Tim Cook proclaims that the future of personal computing is the iPad… more like their predecessors

What’s Next for Personal Computing

416 Stories To Learn About Crypto Trading

Influenza Vaccines and Data Science in Biology Data science plays a key role in the selection of influenza vaccines. Now, this may sound like an excerpt from a sci-fi novel. But in fact, it is an actual real-life application of modern data science techniques that improves lives today. In this blog post, we will tell you a fascinating (nerd alert!) story. We are going to talk about viruses (the non-computer kind), about influenza, and how the first vaccine was invented. On top of that, we’ll discuss some data science techniques and tools for analyzing biological data. In addition, we’ll also talk about one of the fundamental visualization techniques for genome data: phylogenetic trees. We’ll see how trees can be implemented when predicting changes in influenza and modeling future behavior of viruses. By the end of this article you’ll even learn about platforms, where you can store and analyze gene data or why not your own genome if you’ve got it. But let’s take it one step at a time. First, we’ll take a look at what viruses are in general and how they function. Influenza Vaccines: Flu Mechanism, a.k.a. the Influenza Life Cycle What are viruses? Organisms are complicated systems. We are used to the big and visible ones – mammals, birds, reptiles. But there are also microscopic invisible organisms, that actually live among us, or, to be more precise – inside us. Small bacterial or viral cells can infiltrate our bodies down to our cells and make us sick. However, bacteria and viruses are two different types of organisms. And it is a common misconception that the cause of illnessеs is mainly bacteria. Bacteria are a diverse group of cells, but in fact, only 1% of them cause disease. The rest are completely harmless. What about viruses? Well, they are very much the other side of the coin (if that coin was very unfair), as almost all of them (around 99%) cause illness. And if viruses are so dangerous to other organisms, it certainly makes sense to take a closer look at how they function. How does a virus function? The way a virus functions, is by infiltrating a or It then uses these cells to replicate and spread through an organism and, well, generally wreak all kinds of havoc. Technically, prior to entering a cell, a virus is called . It’s true that almost everyone uses the term virus to describe both stages. Still, it’s a useful fact you can bring up next time the party conversation is running a bit stale. host host cells. a virion Anyway, this is the general mechanism behind how all viruses work. But as you probably guessed, different viruses have specific ways to sneak their way into our cells. And they can vary depending on the virus. Therefore, we’ll see the specifics of how Influenza works in the next paragraphs. How does influenza work? You may have heard about an or an Influenza virus on the news. However, if you’re not a biologist, you’ve probably wondered what these letters and numbers mean. Well, the H stands for , and N – for . Both H and N are proteins and each of them has its own purpose. H3N2 H1N1 hemagglutinin neuraminidase H and N surface proteins -important parts of the influenza life cycle The H and N proteins sit on the surface of the virus and play a vital role in the influenza life cycle. They aid the penetration of the host cell (Hemagglutinin) and the subsequent replication of the virus (Neuraminidase) in the host cells. Now, these two proteins can vary a bit in their structure, so different versions of them are identified by a number. An example of that is the H3N2. It contains the third variant of the H protein and second variant of the N protein. As a matter of fact, H3N2 and H1N1 are the two most common subtypes of influenza viruses to infect humans. So, let’s take a look at what their popular names and characteristics. Hong Kong Flu H3N2, also known as the , caused a pandemic in 1968, which resulted in over a million deaths worldwide. Though not as lethal as the H1N1 strain, it was highly contagious and spread quickly through the population, starting from Asia and later reaching America, via returning troops from Vietnam. By the end of 1969, the virus had reached parts of Africa and South America, as well. Hong Kong flu Spanish Flu H1N1 was responsible for the swine flu pandemic of 2009, as well as the devastating of 1918. The particular H1N1 strain involved in the Spanish flu was extremely lethal, resulting in over 30 million deaths worldwide. However, the reasons for the high mortality rate remain a mystery. While some scientists suggest an unusually aggressive form of the virus was involved, others claim that the circumstances surrounding the infection: overcrowding of camps and lack of sterile environment during World War I, were the cause for the high death toll. Spanish flu You’re probably thinking: “If this virus can be so dangerous or potentially lethal, how can we protect ourselves against it? “ The answer: , commonly known as . influenza vaccines flu shots So… What is a vaccine and how does it work? The first vaccine The first successful vaccine was introduced in 1796 by and it was against the . He observed that people who had previously had a different illness – cowpox, did not contract smallpox. So, if people had the cowpox virus first, they became resistant to the more lethal smallpox. His observations helped create the first . As a result, the smallpox virus has since been eradicated worldwide. Edward Jenner, smallpox virus successful vaccine Nowadays, we have different types of vaccines. They aim to help the body’s immune system recognize and prevent a virus from replicating and causing an infection. The process involves using some form of a which the immune system can train to recognize. It can then create specific for it and inactivate it. weakened virus antibodies Influenza vaccines: what do they contain Influenza vaccines consist of weakened H1N1 and H3N2 strains. When presented with these, our organism can start creating specific antibodies, which target the virus H1N1 and H3N2 cells. Then when a real virus enters the system, our immune system is prepared and can deactivate it. Now that we’ve discussed the influenza vaccines and what they contain, let’s take a look at is responsible for the creation of the vaccine. who Influenza vaccines: manufacturing, selection decides what the influenza vaccines include. And, no, this was not meant to be a question or a Doctor Who reference, it’s just the acronym for the and as it happens, they are the people deciding on what the influenza vaccines will contain each year. WHO – World Health Organization WHO But why the need for change? The reason for an annual flu vaccine: antigenic drift and shift To answer that, we first need to explain two main mechanisms in viral evolution: and . antigenic drift antigenic shift Antigenic drift Imagine you have a group of people, stranded on a raft in the sea. Over time the people on the raft slowly change appearances, they grow a beard, hair gets longer, they get more tanned. In essence, they remain the same people but slightly changed. This is what antigenic drift means, slow changes over time. Antigenic shift Now if those people mix their (as none of the kids are calling it) and create a progeny, a.k.a. a child, it will contain a mixture of both their traits. This is what or means: exchange of genetic material and the creation of a new organism (so a drastic change). In our case, this is a new influenza subtype, such as the H3N1 or H1N1 we talked about earlier. genomes antigenic shift reassortment And that answers our question about vaccine creation and the reason to change it each year. Influenza changes quickly, mutates and transforms. Thus, it’s difficult to find a vaccine to combat all possible circulating influenza virus types. So, when scientists decide how to formulate the vaccine, they need to choose which of the virus to include in order to make it most effective. And the latter depends on how closely the vaccine resembles the influenza viruses, which will dominate during the upcoming flu season. strains Predicting the influenza spread – data science How to predict upcoming influenza virus types? This is where data science comes into play. Based on existing data about former and current virus spread and variants, scientists try to model and predict of viruses, using machine learning algorithms. the future behavior In order to do that they first need an appropriate way to handle information about viruses, or more precisely their genomes. This is done via analysis of genetic data. But what is genetic data, exactly? What are Genomes and Gene Data? Genetic data includes the of organisms or parts of it. It’s usually comprised of , represented in the form of strings. In the case of Influenza, it contains which is what some viruses have as their genetic material. genome DNA RNA, Once we have our data, it’s time to think about how we can make sense of it, which means we first need a way to visualize it. There are quite a few options. However, we’ll focus on one in particular, which is a staple: the . phylogenetic tree Visualization techniques: Phylogenetic trees Phylogenetic trees, also known as evolutionary trees, represent the closeness of different species in terms of their genetics. Basically, they are a showing evolutionary relationships between species. In the case of influenza, such trees can be used to visualize different strains of the virus. diagram Prediction models It’s time to put all of this together and get to the final point. Namely, prediction using machine learning techniques. Imagine you already have your biological data in the form of Influenza genomes or antibodies and have represented it using trees. Using the information obtained from the trees, you can employ different machine learning techniques to model future behavior or spread of the Influenza virus. These include the use of , construction of or the use of scoring methods. Examples of the latter include the construction of similarity classes and substitution matrices to explain antigenic differences of viruses. And we’ll provide an overview of a few different techniques in the next paragraphs. non-negative least squares maximum likelihood trees Nonnegative least squares One common method for prediction is introduced by Steinbrück and McHardy. It uses a optimization, which measures distances between branches of a phylogenetic tree. They use a bidirectional weighted phylogenetic tree and determine sets of coding changes on the surface of the H protein. The model can then identify the antigenic impact of different influenza strains. nonnegative least-squares Phylogenetic Analysis by Maximum Likelihood or PAML Another way to perform phylogenetic analyses is to use the PAML package, which contains programs for phylogenetic analyses of genetic data using .  The way this is done is by taking a set of trees and evaluating their log-likelihood values under different models. These models estimate some parameters while allowing for others to vary. This way they can incorporate the variety of gene types in influenza strains and their surface H protein. maximum likelihood (ML) Comparison of a Tree-based and Substitution Model The third method worth mentioning is… Well, actually there are two different methods: one tree-based and a model, as well as a comparison between the two. It feels like we tricked you, but we promise it makes sense to talk about those two in particular. substitution This last approach to predicting influenza strains was proposed by Neher et al. It includes a tree-based model, which has a and a influenza strain and creates a weighted phylogenetic tree. The substitution model uses sums of contributions associated with amino acid substitutions between reference and test viruses. Through data collected between 2002 and 2015, Neher et al. demonstrated that both the tree-based model and the substitution model perform similarly in terms of prediction accuracy. test reference Choosing the “best” method (in data science) We did say the last two models were mentioned with a specific purpose. And it was to illustrate a very common problem in data science: Machine Learning provides a large variety of tools which allows us to analyze data and make prediction models. In some cases, especially if you are a novice in the field, this can become overwhelming. In the case of Neher, we see two distinct techniques yielding on the same problem. This can often be the case in practice: two or more algorithms perform similarly well on a given data set. The choice of the “right” algorithm then can depend on the specifics of the task we’re given or be determined by other factors ( of the model, the list goes on). similar result speed, scalability, interpretability This is also known as the “No free lunch theorem”, a common problem in machine learning, stating there is no model to solve problems. An important part of the job of data scientists is to know the strength and weaknesses of each method and always choose an appropriate tool to solve the problem at hand. one all Genomes, the up and coming field in data science And that pretty much brings this article to a close. That was quite of a roller coaster, right? We started from learning about the flu and how a works and went through the history of the first and the biggest . And the time when we talked about and ? We had a lot of fun explaining these in particular. virus vaccine flu pandemics antigenic shifts drifts We also discussed different types of biological data and their visualization. Finally, we learned how to make predictions using different machine learning techniques. In conclusion, data science is not just a tool used in the IT Domain or by large corporations. In fact, it plays an increasingly important role in (life) sciences. Moreover, medical and biological applications are becoming increasingly important and widespread. In fact, big tech companies like and started their own genome projects recently, allowing users to store and analyze their own genome on their respective cloud platforms. entered the field as well with the release of Microsoft genomics on their Azure cloud. Google Amazon Microsoft And if they’re doing it, it’s a safe bet to assume that genomes and their analytics using machine learning are worth looking into. The way things are running, genomes and their analytics might soon become part of our everyday lives. So, we believe it makes perfect sense to get acquainted with the field. And, after the introduction we just gave you, we’re sure you’ll have no trouble doing that. Previously published at https://365datascience.com/influenza-vaccines-data-science/

Influenza Vaccines: The Data Science Behind Them

(De rerum secretum) A song to read to. January 28th is Data Privacy Day Exponential trends are incredibly difficult for human beings to rationalise. By now, most people are more or less aware that we are fast approaching a critical from which we are unlikely to return. But what does that mean? threshold of increasing complexity Mankind’s ability to manipulate his environment with increasing proficiency has accelerated us through major evolutionary checkpoints with terrifying speed. Our ability to store, specialise in, and exchange knowledge is the Gutenbergian cheat code behind this. The fact that we must map these rates of change logarithmically is mind-blowing. The Hunter Gatherer Age lasted several million years; The Agricultural Age, several thousand years; The Industrial Age, several hundred years; and The Information Age several decades. We do not know what tomorrow brings, but it is clear that data is the primary ingredient. In 2010 the world reached, for the first time, an astonishing of data. zettabyte 1 ZB = 10^21 bytes = 1 000 000 000 000 000 000 000 bytes = 1000 exabytes = 1 million petabytes = 1 billion terabytes = 1 trillion gigabytes. In 2018 we hit the 33 ZB milestone. In just eight years, we managed to produce 32x more data than all of recorded human history. Even more alarmingly, by 2020 we will produce . 1.7 megabytes of data per person per second The total datasphere on Planet Earth is expected to reach 175 zettabytes of data by 2025 . In a world of exponential data production, , , and the by those we have entrusted it to, it is deeply concerning how few of us actually engage with sensible data practices. Why do we not care enough to alter our behaviour? How many more warning signs do we need before recognising the Orwellian exhortations as more than mere fiction? Memetic warfare government surveillance gross mishandling of data I recently decided to investigate just how thorough Google’s data collection and storage services are. It turns out, that from just Google account they had more than 100 gigabytes of personal data. 345,081,600 seconds, click by click, they had a digital trail of my every action across the 3994 days that have elapsed since 10th February 2008. I was years old! Some of them were relatively amusing: one nine Others are not as humorous… such as recognising that practically every page I have ever visited contained either Google or Facebook Ad Trackers. Or that every single time you open or close an application on your phone it is also recorded. Or that my entire GPS location history for nearly 6 years (until I started to pay attention to such things) had been recorded, as well as coordinates that were frequently visited e.g. “Home”. Roughly three years ago I began to seriously consider the data I make available online, and reviewed all settings across all accounts in order to ensure that I am better in control of my digital trail. That being said, after the above findings I was a little concerned. How should I have known about such things back then? Should Google have made it easier to be aware of their opt-out tracking services? Where does the responsibility lie? Personally, I think the ultimate responsibility should lie on the individual’s end. We live in a weird time where victimhood is seemingly actively encouraged, and accountability is obfuscated. Instead of wasting time on both whinging and the pursuit of those that may have wronged you, why not look forward and focus on preventative measures? We cannot expect the exceptionally bright young technologists who built the services we use today to have anticipated things playing out the way they have. The Internet is still very young, and it is the responsibility of everyone who is a part of it to help shape what we want it to look like. Sir Tim Berners-Lee wrote a to the web at the start of 2017 outlining some of the biggest challenges we face. I would like to politely remind others that most tracking services tend to be . brilliant open letter very easy to opt out from “We cannot expect governments, corporations, or other large, faceless organizations to grant us privacy out of their beneficence. It is to their advantage to speak of us, and we should expect that they will speak. To try to prevent their speech is to fight against the realities of information. Information does not just want to be free, it longs to be free. Information expands to fill the available storage space. Information is Rumor’s younger, stronger cousin; Information is fleeter of foot, has more eyes, knows more, and understands less than Rumor.” — Eric Hughes We need to encourage frank discussion about how data should be collected, stored, and used. Whilst they are often intertwined, we must make a crucial distinction between and , let’s define them as follows: Security Privacy Security — the protection of data from unauthorised access. Privacy — the limitation of derivable information from data if accessed. We can also define privacy more broadly as: the power to selectively reveal oneself to the world . Whilst computer security is generally a highly mature field with a variety of exceptionally well designed and tested practices, protocols, and standards in place — the privacy space leaves a lot to be desired. We can separate privacy into two conceptual camps of identity and . I feel that this framework can be very useful when making decisions about one’s personal privacy. dependency independency During the Age of Enlightenment, theorists explored ideas concerning the relationship between the individual and the state/political order. It is generally assumed that the latter exists in order to protect the liberties of the former. One might suggest that, on the whole, this objective has been fulfilled more often than not over the last several hundred years. Unfortunately a new contender has entered the ring. Historically, there would be few enemies of inidivdual freedoms that the relevant state would have been unable to easily protect from. Now however, the technological gulf that separates those that threaten and those that seek to regulate is not insignificant. It seems, so far, that the relevant incumbents intend to cooperate. But as Congress and Parliament begin to ask the right questions, we must be mindful that they don’t get . Social Contract too many ideas themselves Of course, there are some identity-dependent digital services that governments provide for their citizens, and this is unlikely to change. The manner in which we exchange this information on the other hand, can. The magic of modern cryptography is rarely appreciated by most. We have come a long way from the Caesar cipher of Ancient Rome, so far in fact, that we can now . Zero-knowledge proofs are the types of technology that we should begin to consider when asking questions about what we want privacy to look like in a world of yottabytes. validate information without revealing what it is Outside of governmental identity-dependent digital services, it is impossible, under any circumstance, to justify the level of snooping that most online services require. It is no secret anymore that large data sets are a gold mine. We must minimise our footprint everywhere possible. Geolocation 24/7/365, social media that maps cognitive structures for homogenous character profiling, ad trackers embedded across the entire web, hidden in emails — these should not be part of our experience of the web. Where possible, we should use pseudonymous data so that the trails do not lead directly to us. Our objective should be to . The reality is that none of our data footprints are the ephemeral, immaterial things we understand them to be. They are enduring fixtures in the modern world. The future is uncertain, but data permanence is not. pixel trackers reveal the least amount of real data possible without destroying the browsing experience What can be done without going overkill? Use a that doesn’t store logs VPN Use as your default search engine DuckDuckGo Use on your browser uBlock Origin Use with enabled and 3rd-party cookies disabled Firefox Quantum DNT Disable GPS functionality when not in use on mobile in emails Block pixel tracking Disable all Google Tracking Services Disable Google Ads Disable Facebook location services on mobile Disable Facebook Ads Disable access from non-critical apps Download a data dump and ask for deletion Set up a pseudonymous email with fake information for everything that does not require ID verification on the web Use as much as possible throw away emails Where is the Life we have lost in living?Where is the wisdom we have lost in knowledge?Where is the knowledge we have lost in information? — T.S. Elliot

CAMPUS 365

campus365.io

-- employees

Since n.d.

COMPANY RANKING

CAMPUS 365

EVERGREEN INDEX #2329

Representing this company? Click here to claim and customize this page!

Campus 365 WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

CAMPUS 365

campus365.io

-- employees

Since n.d.

COMPANY RANKING

CAMPUS 365

EVERGREEN INDEX #2329

RELATED COMPANIESRANK

STORIES ABOUT CAMPUS 365

Representing this company? Click here to claim and customize this page!

Campus 365 WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!