These are the world's best universities by subject 06-23

If you want to pick the the best university for your chosen field of study, go to the U.S.

The QS World University Rankings show U.S. universities hold the top spot for virtually all subjects.

Harvard, Stanford and the Massachusetts Institute of Technology dominate in engineering and technology; natural sciences; and social sciences and management.

Arts and humanities and life sciences and medicine are the exceptions, with two UK universities – Oxford and Cambridge – in the top three for those areas.

The rankings group 48 disciplines into the five broad subject categories. They highlight the best universities in each category using research citations and surveys of employers and academics. In total, 1,200 universities in 78 locations are listed.

Outside of the top slots, Asian universities also get a good showing, in particular Nanyang Technological University Singapore and the National University of Singapore. 

Western universities have dominated the top tier of higher education tables for years, but providers in Asia are becoming increasingly visible players in the elite and funding for education is on the rise.

Globalisation is rapidly changing the education sector. As the global middle class expands, there will be increasing demand for higher education, particularly in China and India.

The battle to host international students – and benefit from the income and expertise they bring – is already on. Governments from the UK to Japan are bringing in measures to attract the best minds.

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3 technologies that could define the next decade of cybersecurity 06-22

In little over a decade, cybercrime has moved from being a specialist and niche-crime type to one of the most significant strategic risks facing the world today, according to the World Economic Forum Global Risks Report 2019. Nearly every technologically advanced state and emerging economy in the world has made it a priority to mitigate the impact of financially motivated cybercrime. 

The global experience of the past decade has largely been dominated by the emergence of a professional underground economy that provides scale, significant return-on-investment and entry points for criminals to turn a technical specialist crime into a global volume crime. The cybersecurity landscape in the past decade has been shaped by the targeting of financial institutions, notably with malware configured to harvest payment information and target financial platforms. The early cybercrime market that gave rise to the criminal online ecosystem was centred on the trading of harvested stolen credit cards, and some of the most high-profile and sophisticated global attacks focus on the penetration and manipulation of the internal networks of complex global payment systems. 

The Russian-speaking world has not been immune from these trends. Cyberattacks on financial organizations in Russia, Central Asia and Eastern Europe by some of the most sophisticated cybercrime gangs in the world have targeted clients, digital channels and networks. The Russian-speaking underground economy is one of the most active globally, with hundreds of fora and tens of thousands of users. Criminal groups exploit the margins of co-operation to conduct global campaigns, and their threat capacity is always adapting as groups work together in a borderless environment to combat technical defences. 

The past 10 years mark only the start of the global cybersecurity journey. New architectures and cooperation are required as we stand at the brink of a new era of cybercrime, which will be empowered by new and emergent technology. These three technologies might very well define the next 10 years of global cybersecurity: 

1. 5G networks and infrastructure convergence

A new generation of 5G networks will be the single most challenging issue for the cybersecurity landscape. It is not just faster internet; the design of 5G will mean that the world will enter into an era where, by 2025, 75 billion new devices will be connecting to the internet every year, running critical applications and infrastructure at nearly 1,000 times the speed of the current internet. This will provide the architecture for connecting whole new industries, geographies and communities - but at the same time it will hugely alter the threat landscape, as it potentially moves cybercrime from being an invisible, financially driven issue to one where real and serious physical damage will occur at a 5G pace. 

5G will potentially provide any attacker with instant access to vulnerable networks. When this is combined with the enterprise and operational technology, a new generation of cyberattacks will emerge, some of which we are already seeing. The recent ransomware attack against the US city of Baltimore, for example, locked 10,000 employees out of their workstations. In the near future, smart city infrastructures will provide interconnected systems at a new scale, from transport systems for driverless cars, automated water and waste systems, to emergency workers and services, all interdependent and - potentially - as highly vulnerable as they are highly connected. In 2017, the WannaCry attack that took parts of the UK’s National Health Service down took days to spread globally, but in a 5G era the malware would spread this attack at the speed of light. It is clear that 5G will not only enable great prosperity and help to save people’s lives, it will also have the capacity to thrust cybercrime into the real world at a scale and with consequences yet unknown. 

2. Artificial intelligence

To build cyber defences capable of operating at the scale and pace needed to safeguard our digital prosperity, artificial intelligence (AI) is a critical component in how the world can build global immunity from attacks. Given the need for huge efficiencies in detection, provision of situational awareness and real-time remediation of threats, automation and AI-driven solutions are the future of cybersecurity. Critically, however, the experience of cybercrime to-date shows that any technical developments in AI are quickly seized upon and exploited by the criminal community, posing entirely new challenges to cybersecurity in the global threat landscape. 

The use of AI by criminals will potentially bypass – in an instant – entire generations of technical controls that industries have built up over decades. In the financial services sector we will soon start to see criminals deploy malware with the ability to capture and exploit voice synthesis technology, mimicking human behaviour and biometric data to circumvent authentication of controls for people’s bank accounts, for example. But this is only the beginning. Criminal use of AI will almost certainly generate new attack cycles, highly targeted and deployed for the greatest impact, and in ways that were not thought possible in industries never previously targeted: in areas such as biotech, for the theft and manipulation of stored DNA code; mobility, for the hijacking of unmanned vehicles; and healthcare, where ransomware will be timed and deployed for maximum impact. 

3. Biometrics

To combat these emerging threats, biometrics is being widely introduced in different sectors and with various aims around the world, while at the same time raising significant challenges for the global security community. Biometrics and next-generation authentication require high volumes of data about an individual, their activity and behaviour. Voices, faces and the slightest details of movement and behavioural traits will need to be stored globally, and this will drive cybercriminals to target and exploit a new generation of personal data. Exploitation will no longer be limited to the theft of people’s credit card number, but will target theft of their being – their fingerprints, voice identification and retinal scans. 

Most experts agree that three-factor authentication is the best available option, and that two-factor authentication is a must. ‘Know’ (password), ‘have’ (token) and ‘are’ (biometrics) are the three factors for authentication, and each one makes this process stronger and more secure. For those charged with defending our digital future, however, understanding an entire ecosystem of biometric software, technology and storage points makes it still harder to defend the rapidly and ever-expanding attack surface.

What next?

Over the past decade, criminals have been able to seize on a low-risk, high-reward landscape in which attribution is rare and significant pressure is placed on the traditional levers and responses to crime. In the next 10 years, the cybersecurity landscape could change significantly, driven by a new generation of transformative technology. To understand how to secure our shared digital future we must first understand how the security community believes the cyberthreat will change and how the consequent risk landscape will be transformed. This critical and urgent analysis must be based on evidence and research, and must leverage the expertise of those in academia, the technical community and policymakers 

around the world. By doing this, the security ecosystem can help build a new generation of cybersecurity defences and partnerships that will enable global prosperity. 

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Bill that seeks to lift green card cap amended to protect US 06-21

Eliminating the country quota from the most sought-after Green Cards will end the current discrimination in the US labour market, but would allow countries like India and China to dominate the path to American citizenship, according to the latest Congressional report.
Having a Green Card allows a person to live and work permanently in the United States.
Indian-Americans, most of whom are highly skilled and come to the US mainly on the H-1B work visas, are the worst sufferers of the current immigration system which imposes a seven per cent per country quota on allotment of Green Cards or the Legal Permanent Residency (LPR).

The bipartisan Congressional Research Service (CRS), an independent research wing of Congress, said if the per-country cap for employment-based immigrants was removed, many expects that Indian and Chinese nationals would dominate the flow of new employment-based LPRs for as many years as needed to clear out the accumulated queue of prospective immigrants from those countries.

This queue would include those with approved employment-based immigrant petitions waiting to file either a visa  .. 

The CRS regularly prepares reports on various issues for the lawmakers to take informed decisions.

A copy of the report 'Permanent Employment-Based Immigration and the Per-country Ceiling' dated December 21 was made available to PTI, ahead of the new Congress beginning January 3, wherein several lawmakers are planning to introduce a legislation to eliminate per-country quota for issuing Green Cards to foreign nationals. 

As of April 2018, a total of 306,601 Indian nationals – mostly IT professionals – were waiting in line for Green Cards, according to the USCIS figures. 

Indians constitute 78 per cent of the 395,025 foreign nationals waiting for Green Cards in just one category of employment-based LPR applications.

Due to the cap, the current wait period for the majority of Indians to get a Green Card is nine and half years, the CRS said, adding this could increase or decrease further depending on the number of new applications every year. India is followed by China with 67,031 in line for Green Cards.

Lawmakers favouring eliminating the per-country cap contend that such circumstances effectively encourage employers to sponsor prospective employment-based immigrants primarily from India.

Proponents argue that removing the per-country ceiling from employment-based immigrants would "level the playing field" by making immigrants from all countries more equally attractive to employers, the CRS said. 

According to the CRS, eliminating the per-country ceiling would reduce certain queues of prospective immigrants more quickly, and remove the perceived employer incentive to choose nationals from these countries over other countries. 

"Shorter wait times for LPR status might actually incentivise greater numbers of nationals from India, China and the Philippines to seek employment-based LPR status. If that were to occur, the reduction in the number of approved petitions pending might be short-lived.

"A handful of countries could conceivably dominate employment-based immigration, possibly benefitting certain industries that employ foreign workers from those countries, at the expense of foreign workers from other countries and other industries that might employ them," the CRS said. 

Because the Immigration and Nationality Act (INA) grants LPRs the ability to sponsor family members through its family-sponsorship provisions, removing the per-country ceiling would alter, to an unknown extent, the country-of-origin composition of subsequent family-based immigrants acquiring LPR status each year, it said. 

Changes in the country's demographic profile tilted towards people from one part of the world, was one of the prime reasons for the current per country quota. This, on the other hand, restricts the flow of the best talented foreign workers.

The INA allocates 140,000 visas annually for all five employment-based LPR categories, roughly 12 per cent of the 1.1 million LPRs admitted in fiscal 2017. It further limits each immigrant-sending country to an annual maximum of seven per cent of all employment-based LPR admissions, known as the per-country ceiling, or "cap". 

Two popular employment-based pools of foreign nationals, who have been approved as employment-based immigrants but must wait for statutorily limited visa numbers, totalled in excess of 900,000 as of mid-2018. Most originate from India, followed by China and the Philippines, the CRS said.

Some employers maintain that they continue to need skilled foreign workers to remain internationally competitive and to keep their firms in the US, it said. 

Proponents of increasing employment-based immigration levels argue it is vital for economic growth. Opponents cite the lack of compelling evidence of labour shortages and argue that the presence of foreign workers can negatively impact wages and working conditions in the US, the CRS said.

"Some argue that eliminating the per-country ceiling would increase the flow of high-skilled immigrants from countries such as India and China, who are often employed in the US technology sector, without increasing the total annual admission of employment-based LPRs," it added.

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AI analyzes language to predict schizophrenia 06-21

AI analyzes language to predict schizophrenia.....

A machine learning method found out a hidden clue in people’s language that can predict psychosis episodes. 

A machine learning method uncovered a hidden clue in people’s language predictive of the later manifestation of psychosis: the frequent use of words associated with sound. A paper published by the journal npj Schizophrenia released the findings by scientists from Emory University and Harvard University.

Hidden details

The researchers developed a new machine-learning methodology to more precisely quantify the semantic richness of people’s conversational language (a known indicator for psychosis). Their results indicated that automated analysis of the two language variables (more frequent use of words associated with sound and speaking with low semantic density, or vagueness) can predict if an at-risk person will later develop psychosis with an impressive 93 percent accuracy.

Trained clinicians had not noticed how individuals at risk for psychosis use more words associated with sound than the average population, though abnormal auditory perception is a pre-clinical symptom.

“Voices: Living with Schizophrenia” by WebMD, YouTube.

Machine learning can spot patterns in people’s use of language that even doctors who have undergone training to diagnose and treat those at risk of psychosis may not notice. “Trying to hear these subtleties in conversations with people is like trying to see microscopic germs with your eyes,” says first study author Neguine Rezaii, a fellow in the Department of Neurology at Harvard Medical School. That being said, it is possible to use machine learning to find subtle patterns hiding in people’s language. “It’s like a microscope for warning signs of psychosis,” she adds. Rezaii started working on the study while she was a resident in the Department of Psychiatry and Behavioral Sciences at Emory University School of Medicine.

“Trying to hear these subtleties in conversations with people is like trying to see microscopic germs with your eyes,” Neguine Rezaii, fellow in the Department of Neurology at Harvard Medical School.

Behind the data

Researchers first used machine learning to establish “norms” for conversational language. They fed a computer software program the online

conversations of 30,000 users of Reddit, a popular social media platform where people have informal discussions about a wide array of sujects. The software program, known as Word2Vec, utilizes an algorithm to change individual words to vectors, assigning each one a location in a semantic space based on its meaning. Such with similar meanings are positioned closer together than those with different meanings.

They also developed a computer program to perform “vector unpacking,” or analysis of the semantic density of word usage. Previous work has measured semantic coherence between sentences. Vector unpacking enabled the researchers to quantify how much information was packed into each sentence. After generating a baseline of “normal” data, the researchers applied the same techniques to diagnostic interviews of 40 participants that had been conducted by trained clinicians, as part of the multi-site North American Prodrome Longitudinal Study (NAPLS), funded by the National Institutes of Health. 

Vector unpacking enabled the researchers to quantify how much information was packed into each sentence.

The automated analyses of the participant samples were then compared to the normal baseline sample and the longitudinal data on whether the participants converted to psychosis.

"This research is interesting not just for its potential to reveal more about mental illness, but for understanding how the mind works” concludes senior author Phillip Wolff, a professor of psychology at Emory.

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