Current Learning News and Events

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Psychological factors contributing to language learning
Motivation for language learning is a system of cognitive, emotional, and personality-related characteristics. (2020-11-25)

Newfound ability to change baby brain activity could lead to rehabilitation for injured brains
Researchers from King's College London have identified the brain activity for the first time in a newborn baby when they are learning an association between different types of sensory experiences. Using advanced MRI scanning techniques and robotics, the researchers found that a baby's brain activity can be changed through these associations, shedding new light on the possibility of rehabilitating babies with injured brains and promoting the development of life-long skills such as speech, language and movement. (2020-11-23)

Misinformation or artifact: a new way to think about machine learning
Machine learning has delivered amazing results, but there also have been failures, ranging from the harmless to potentially deadly. New work from University of Houston philosopher Cameron Buckner suggests that common assumptions about the cause behind these supposed malfunctions may be mistaken, information that is crucial for evaluating the reliability of these networks. (2020-11-23)

AI plots sustainable materials
Chemistry computer algorithm does more with less experimental data to reveal the optimal way to make green materials. (2020-11-22)

Deep learning in the emergency department
Harnessing the power of deep learning leads to better predictions of patient admissions and flow in emergency departments (2020-11-22)

Spill-over effects show prioritising education of very poorest improves attainment of all
International development projects that target the education of the world's very poorest children also significantly improve other young people's attainment, University of Cambridge research indicates. The findings are based on a study of a programme targeting marginalised girls in Tanzania, which showed the attainment of other boys and girls at these pupils' schools significantly improved through 'spill-over' effects. For every $100 spent per girl, all students made the equivalent of two years of learning gains. (2020-11-19)

Machine learning innovation to develop chemical library
Purdue University innovators are using machine learning models to create new options for drug discovery pipelines. Purdue innovators have introduced chemical reactivity flowcharts to help chemists interpret reaction outcomes using statistically robust machine learning models trained on a small number of reactions. (2020-11-18)

Machine learning uncovers missing info about ethnicity in population health data: Study
Machine learning can be used to fill a significant gap in Canadian public health data related to ethnicity and Aboriginal status, according to research published in PLOS ONE by a University of Alberta research epidemiologist. (2020-11-18)

Learning a new language changes the brain's division of labor
Learning a language later in life changes how the two halves of the brain contribute. As skills improve, language comprehension changes hemisphere specialization, but production does not, according to new research published in JNeurosci. (2020-11-17)

New method brings physics to deep learning to better simulate turbulence
Deep learning, also called machine learning, reproduces data to model problem scenarios and offer solutions. However, some problems in physics are unknown or cannot be represented in detail mathematically on a computer. Researchers at the University of Illinois Urbana-Champaign developed a new method that brings physics into the machine learning process to make better predictions. The researchers used turbulence to test their method. (2020-11-16)

Physics can assist with key challenges in artificial intelligence
Two challenges in the field of artificial intelligence have been solved by adopting a physical concept introduced a century ago to describe the formation of a magnet during a process of iron bulk cooling. Using a careful optimization procedure and exhaustive simulations, researchers have demonstrated the usefulness of the physical concept of power-law scaling to deep learning. This central concept in physics has also been found to be applicable in AI, and especially deep learning. (2020-11-12)

Machine learning advances materials for separations, adsorption, and catalysis
An artificial intelligence technique -- machine learning -- is helping accelerate the development of highly tunable materials known as metal-organic frameworks (MOFs) that have important applications in chemical separations, adsorption, catalysis, and sensing. (2020-11-09)

Nervous systems of insects inspire efficient future AI systems
Study explores functions of fruit fly's nervous system in food seeking / results valuable for the development and control of artificial intelligence. (2020-11-05)

Learning disorders and Parkinson's disease: tremor predicts effects of medication
The effect of dopaminergic medication on the learning abilities of patients with Parkinson's disease turns out to be linked to the presence of tremor symptoms. In patients who do not experience tremor, dopaminergic medication improves the ability to learn from rewards (reinforcement learning). Remarkably, the medication brings no benefit in reward learning to patients who do exhibit tremor. (2020-11-05)

Machine learning shows similar performance to traditional risk prediction models
Some claim that machine learning technology has the potential to transform healthcare systems, but a study published by The BMJ finds that machine learning models have similar performance to traditional statistical models and share similar uncertainty in making risk predictions for individual patients. (2020-11-04)

AI helps detect brain aneurysms on CT angiography
A powerful type of artificial intelligence known as deep learning can help physicians detect potentially life-threatening cerebral aneurysms on CT angiography, according to a new study. (2020-11-03)

Students develop tool to predict the carbon footprint of algorithms
Within the scientific community, it is estimated that artificial intelligence -- otherwise meant to serve as a means to effectively combat climate change -- will become one of the most egregious CO2 culprits should current trends continue. To raise awareness about the challenge, two University of Copenhagen students have launched a tool to calculate the carbon footprint of developing deep learning models. (2020-11-03)

New UTSA research identifies link between food insecurity and unengaged distance learning
A new study by the UTSA Urban Education Institute found that 26% of local students and parents surveyed said they were experiencing food insecurity, meaning food ran out and they didn't have more. The research during pandemic distance learning indicated that food insecure students were less motivated and engaged in schoolwork compared to their peers, signifying how hunger and larger issues of family instability can harm student growth. (2020-11-02)

Machine learning that predicts anti-cancer drug efficacy
Research on anti-cancer drug response in patient-derived artificial organoids and transcriptome learning of genes associated with anti-cancer target proteins. (2020-11-01)

AI teachers must be effective and communicate well to be accepted, new study finds
The increase in online education has allowed a new type of teacher to emerge -- an artificial one. But just how accepting students are of an artificial instructor remains to be seen. That's why researchers at the University of Central Florida are working to examine student perceptions of artificial intelligence-based teachers. Their latest findings were published recently in the International Journal of Human-Computer Interaction. (2020-10-30)

Artificial intelligence-based algorithm for the early diagnosis of Alzheimer's
In a recent study published in the Journal of Medical Imaging, scientists from Texas Tech University employed machine-learning algorithms to classify fMRI data. (2020-10-28)

Model predicts acute kidney injury requiring dialysis in patients with COVID-19
In a recent study, a new algorithm achieved good performance for predicting which hospitalized patients will develop acute kidney injury requiring dialysis. Results from the study will be presented online during ASN Kidney Week 2020 Reimagined October 19-October 25. (2020-10-24)

New model predicts which patients with kidney disease may develop heartbeat irregularities
* A new model that incorporates a type of artificial intelligence can accurately predict which individuals with chronic kidney disease face a high risk of developing atrial fibrillation. * Results from the study will be presented online during ASN Kidney Week 2020 Reimagined October 19-October 25. (2020-10-24)

Does classroom indoor environmental quality affect teaching and learning?
What impact does a classroom's indoor environment have on teaching, learning, and students' academic achievement in colleges and universities? This is the question researchers set out to answer in their analysis of all relevant published studies. (2020-10-21)

Rethinking the link between cannabinoids and learning
Animals with altered cannabinoid signalling exhibit various motor and cognitive impairments, including deficits in learning and memory. A new study reveals an unexpected culprit for these effects - behavioral state. (2020-10-20)

Researchers at the forefront of developing machine learning methods for chemical discovery
Prof. Alexandre Tkatchenko and his research team at the University of Luxembourg have been awarded grants totalling 500,000 euros to conduct research in the emerging field of machine learning methods for chemical discoveries. (2020-10-20)

Material found in house paint may spur technology revolution
The development of a new method to make non-volatile computer memory may have unlocked a problem that has been holding back machine learning and has the potential to revolutionize technologies like voice recognition, image processing and autonomous driving. (2020-10-19)

Automatic decision-making prevents us harming others - new study
The processes our brains use to avoid harming other people are automatic and reflexive - and quite different from those used when avoiding harm to ourselves, according to new research. (2020-10-15)

Only 7% of US school districts in poorer, ethnic minority populations to reopen this fall
US schools in poor districts with large non-white student populations are less likely to reopen fully this academic year, according to a major new study published in the peer-reviewed Journal of School Choice. (2020-10-14)

Distracted learning a big problem, golden opportunity for educators, students
Although experts say using electronic media while doing schoolwork negatively impacts learning, many students believe they're immune to any ill effects because they're good multitaskers, according to University of Illinois food chemistry professor Shelly Schmidt. (2020-10-14)

Machine learning predicts how long museum visitors will engage with exhibits
In a proof-of-concept study, education and artificial intelligence researchers have demonstrated the use of a machine-learning model to predict how long individual museum visitors will engage with a given exhibit. The finding opens the door to a host of new work on improving user engagement with informal learning tools. (2020-10-13)

Smartphone data helps predict schizophrenia relapses
Passive data from smartphones -- including movement, ambient sound and sleep patterns -- can help predict episodes of schizophrenic relapse, according to new Cornell Tech research. (2020-10-13)

Applying artificial intelligence to science education
A new review published in the Journal of Research in Science Teaching highlights the potential of machine learning--a subset of artificial intelligence--in science education. (2020-10-07)

Researchers exploit weaknesses of master game bots
Researchers at Penn State designed an algorithm to train an adversarial bot, which was able to automatically discover and exploit weaknesses of master game bots driven by reinforcement learning algorithms. (2020-09-30)

Machine learning homes in on catalyst interactions to accelerate materials development
A machine learning technique rapidly rediscovered rules governing catalysts that took humans years of difficult calculations to reveal--and even explained a deviation. The University of Michigan team that developed the technique believes other researchers will be able to use it to make faster progress in designing materials for a variety of purposes. (2020-09-29)

Busy pictures hinder reading ability in children
A new study published by researchers at Carnegie Mellon University shows extraneous images draw attention from text, reducing comprehension in beginning readers (2020-09-28)

AI technology can predict vanadium flow battery performance and cost
A research team led by Prof. LI Xianfeng from the Dalian Institute of Chemical Physics (DICP) of the Chinese Academy of Sciences proposed a machine learning-based strategy to predict and optimize the performance and cost of vanadium flow batteries (VFBs). (2020-09-28)

Similarities and dissimilarities between automatic learning in bees and humans
This study provides the first systematic comparison of automatic visual learning in humans and honeybees, showing that while both species extract statistical information about co-occurrence contingencies of visual scenes, in contrast to humans, bees do not automatically encode predictability information in those scenes. Since access to predictability has long been considered as key for acquiring complex knowledge effectively, this difference might provide hints about what leads to human's versatile learning and superior cognitive abilities. (2020-09-28)

Bioelectronic device achieves unprecedented control of cell membrane voltage
Every living cell maintains a voltage across the cell membrane that results from differences in the concentrations of charged ions inside and outside the cell. In an impressive proof-of-concept demonstration, an interdisciplinary team of scientists has developed a bioelectronic system driven by a machine learning algorithm that can shift the membrane voltage in living cells and maintain it at a set point for 10 hours. (2020-09-24)

Researchers demonstrate how deep learning can advance study of neural degeneration
Researchers have demonstrated the utility of artificial intelligence (AI) in identifying and categorizing neural degeneration in the model organism C. elegans. The tool uses deep learning, a form of AI, and should facilitate and expedite research into neural degeneration. (2020-09-24)

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