A 30-minute guided tour of the latest exhibition in the Milberg Gallery in Firestone Library at Princeton University. Tours meet in the lobby of Firestone Library. The exhibition is open Monday to Friday from 10 a.m. to 6 p.m., and 11 a.m. to 6 p.m. on Saturday and Sunday in the Milberg Gallery, Firestone Library. Open to the public. “Monsters and Machines: Caricature, Visual Satire, and the Twentieth-Century Bestiary” will focus on the use of bestiary – animal or zoological motifs – in visual satire during the period between World War I and the end of the Cold War. Drawing from PUL’s rich collections of 20th-century posters, illustrated periodicals, and ephemera from North America, Europe, Asia, Eurasia, and the Middle East, the exhibition will look at works of weaponized visual humor created by and aimed at exponents of different national cultures and ideologies. The exhibition will run from September 12 to December 8, 2024.

Austrian manufacturer also optimizes creation of assembly documentation and related bills of material

Chief of Defence Staff Gen Anil Chauhan asserted that "we are at the cusp of a major change in warfare".

Microsoft announced it has acquired Semantic Machines, a conversational AI startup providing chatbots and AI chat apps founded in 2014 having $20.9 million in funding from investors. The acquisition will help Microsoft catch up with Amazon Alexa, though the latter is more focused on enabling consumer applications of conversational AI.

Microsoft will use Semantic Machine’s acquisition to establish a conversational AI center of excellence in Berkeley to help it innovate in natural language interfaces.

Microsoft has been stepping up its products in conversational AI. It launched the digital assistant Cortana in 2015, as well as social chatbots like XiaoIce. The latest acquisition can help Microsoft beef up its ‘enterprise AI’ offerings.

As the use of NLP (natural language processing) increases in IoT products and services, more startups are getting traction from investors and established players. In June last year, Josh.ai, avoice-controlled home automation software has raised $8M.

Followed by it was SparkCognition that raised $32.5M Series B for its NLP-based threat intelligence platform.

It appears Microsoft’s acquisition of Semantic Machines was motivated by the latter’s strong AI team. The team includes technology entrepreneur Daniel Roth who sold his previous startups Voice Signal Technologies and Shaser BioScience for $300M and $100M respectively. Other team members include Stanford AI Professor Percy Liang, developer of Google Assistant Core AI technology and former Apple chief speech scientist Larry Gillick.

Devices that let people with paralysis walk and talk are rapidly improving. Some see a future in which we alter memories and download skills – but major challenges remain

Devices that let people with paralysis walk and talk are rapidly improving. Some see a future in which we alter memories and download skills – but major challenges remain

Gears just a few micrometres wide can be carved from silicon using a beam of electrons, enabling tiny robots or machines that could interact with human cells

A very few century in the past seamen were the first person to possess celeb wrist tats. Several mariners were superstitious as well as sea-loving movie star for their hand showed its northern border superstar which was intended to...

It can be seen as part of human nature that over a period of time, people become bored with routine activities, such as eating, drinking and repetitive...

In the range of commercial coffee machines, Espresso is a name which is worth to rely. This Italian flavor rules the heart of the coffee lovers’ right from its origin. Considering its charm throughout the world, Espresso comes...

About a year and a half ago, quantum control startup Quantum Machines and Nvidia announced a deep partnership that would bring together Nvidia’s DGX Quantum computing platform and Quantum Machine’s advanced quantum control hardware. We didn’t hear much about the results of this partnership for a while, but it’s now starting to bear fruit and […]

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Oxlade, Chris, author

Haft, Sheryl, author

The aviation industry’s roller-coaster ride

The device has democratised laundry duty sparing women backaches and making it cool for men to share the load

GST portal introduces forms for manufacturers of pan masala and tobacco to register machines and track inputs/outputs

With this, the foundation completes donating 1,000 ECG machines to many health facilities across India since 2018

It can be seen as part of human nature that over a period of time, people become bored with routine activities, such as eating, drinking and repetitive...

In the range of commercial coffee machines, Espresso is a name which is worth to rely. This Italian flavor rules the heart of the coffee lovers’ right from its origin. Considering its charm throughout the world, Espresso comes...

As autonomous and self-taught machines become part of our everyday lives, what sort of policy and institutional frameworks should guide AI design and use? This event brought together policymakers, civil society representatives and AI experts from industry and academia to discuss the role of policy and international co-operation in ensuring that AI benefits society as a whole.

Archives, Room Use Only - QC573.M47 1874

Simon L. Bullock
Apr 6, 2020; 133:jcs245134-jcs245134
Meeting Report

Full Text:

Machine learning algorithms can sometimes do a great job with a little help from human expertise, at least in the field of materials science. In many specialized areas of science, engineering and medicine, researchers are turning to machine learning algorithms to analyze data sets that have grown too large for humans to understand. In materials science, success with this effort could accelerate the design of next-generation advanced functional materials, where development now usually depends on old-fashioned trial and error. By themselves, however, data analytics techniques borrowed from other research areas often fail to provide the insights needed to help materials scientists and engineers choose which of many variables to adjust -- and the techniques can't account for dramatic changes such as the introduction of a new chemical compound into the process. In a new study, researchers explain a technique known as dimensional stacking, which shows that human experience still has a role to play in the age of machine intelligence. The machines gain an edge at solving a challenge when the data to be analyzed are intelligently organized based on human knowledge of what factors are likely to be important and related. "When your machine accepts strings of data, it really does matter how you are putting those strings together," said Nazanin Bassiri-Gharb, the paper's corresponding author and a scientist at the Georgia Institute of Technology. "We must be mindful that the organization of data before it goes to the algorithm makes a difference. If you don't plug the information in correctly, you will get a result that isn't necessarily correlated with the reality of the physics and chemistry that govern the materials."

Image credit: Rob Felt/Georgia Tech

Full Text:

Machine learning algorithms can sometimes do a great job with a little help from human expertise, at least in the field of materials science. In many specialized areas of science, engineering and medicine, researchers are turning to machine learning algorithms to analyze data sets that have grown too large for humans to understand. In materials science, success with this effort could accelerate the design of next-generation advanced functional materials, where development now usually depends on old-fashioned trial and error. By themselves, however, data analytics techniques borrowed from other research areas often fail to provide the insights needed to help materials scientists and engineers choose which of many variables to adjust -- and the techniques can't account for dramatic changes such as the introduction of a new chemical compound into the process. In a new study, researchers explain a technique known as dimensional stacking, which shows that human experience still has a role to play in the age of machine intelligence. The machines gain an edge at solving a challenge when the data to be analyzed are intelligently organized based on human knowledge of what factors are likely to be important and related. "When your machine accepts strings of data, it really does matter how you are putting those strings together," said Nazanin Bassiri-Gharb, the paper's corresponding author and a scientist at the Georgia Institute of Technology. "We must be mindful that the organization of data before it goes to the algorithm makes a difference. If you don't plug the information in correctly, you will get a result that isn't necessarily correlated with the reality of the physics and chemistry that govern the materials."

Image credit: Rob Felt/Georgia Tech

In June 2012, a network of 16,000 computers trained itself to recognize a cat by looking at 10 million images from YouTube videos.

Sweatshops filled with robots could bring manufacturing of smartphones, computers and TVs to the United States, as well.

After debuting in Nottingham, England, the big-hearted concept catering to 'rough sleepers' is coming to America.

The Porsche 918 Spyder and Ferrari F70 offer split personalities: voracious performance on tap, but eco-driving if you tread lightly. Is it a new era of Dr. Gre

In an effort to save money and labor, a farm in Germany has begun selling fresh, local produce from vending machines.

Xenobots are hybrids of living frog cells and machinery — a unique hybrid of organic and inorganic parts that can power themselves.

Accurately Measure Seal Temperature. Temperature Sensors for Packaging Machines.(E52 (For Packing Machine))

The smaller youth baseball leagues want to contemplate finding as many tools of the pastime that will grant the greatest chance for youngsters to learn correctly and develop their skills as feasible. To begin with, you can discover pitching machine models that weigh just thirty pounds, which are ext

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Humanity Can Be Enslaved Under a Chinese Authoritarian Artificial Intelligence Surveillance State via Drones, Robotics and Bio-Digital Social Programming, Says The AI Organization.

DES MOINES — More than 20 days after Iowa signed a $26 million contract with a Utah company to expand testing in the state, the machines the firm supplied to run the samples still have not...

DES MOINES — More than 20 days after Iowa signed a $26 million contract with a Utah company to expand testing in the state, the machines the firm supplied to run the samples still have not passed muster.

A time frame for completing the validation process for the Test Iowa lab machines is unknown, as the process can vary by machine, University of Iowa officials said Friday.

The validation process is undertaken to determine if the machines are processing tests accurately. To this point, the lab has processed the Test Iowa results using machines the State Hygienic Lab already had, officials told The Gazette.

Running side-by-side testing is part of the validation process. The lab then compares whether the machines yield the same results when the sample is run, officials said Friday. The side-by-side testing means the Test Iowa samples are being run at least twice to compare results.

The state does not break out how many of the 331,186 Iowans who by Friday have completed the coronavirus assessment at TestIowa.com have actually been tested. Test Iowa was initiated last month to ramp up testing of essential workers and Iowans showing COVID-19 symptoms. The state’s fourth drive-though location where people with appointments can be tested opened Thursday at the Kirkwood Continuing Education Training Center in Cedar Rapids.

On Friday, Iowa posted a fourth straight day of double-digit deaths from coronavirus, with the latest 12 deaths reported by the state Department of Public Health bringing the statewide toll to 243 since COVID-19 was first confirmed March 8 in Iowa.

State health officials reported another 398 Iowans tested positive for the respiratory ailment, bringing that count to 11,457 of the 70,261 residents who have been tested — a positive rate of more than 16 percent.

One in 44 Iowans has been tested for COVID-19, with 58,804 posting negative results, according to state data. A total of 4,685 people have recovered from the disease.

During a Thursday media briefing, Gov. Kim Reynolds told reporters a backlog of test results that occurred due to validation of Test Iowa equipment had been “caught up,” but some Iowans who participated in drive-through sites set up around the state indicated they still were awaiting results.

Reynolds spokesman Pat Garrett confirmed Thursday that “a very small percentage” of coronavirus test samples collected under the Test Iowa program could not be processed because they were “potentially damaged,” resulting in incomplete results.

There were 407 Iowans who were hospitalized (with 34 admitted in the past 24 hours) for coronavirus-related illnesses and symptoms with 164 being treated in intensive care units and 109 requiring ventilators to assist their breathing.

Health officials said the 12 deaths reported Friday were: three in Woodbury County, two in Linn County and one each in Black Hawk, Dallas, Dubuque, Jasper, Louisa, Muscatine and Scott counties. No other information about the COVID-19 victims was available from state data.

According to officials, 51 percent of the Iowans who have died from coronavirus have been male — the same percentage that tested positive.

Iowans over the age of 80 represent 46 percent of the COVID-19 victims, followed by 41 percent between 61 and 80.

Of those who have tested positive, state data indicates about 42 percent are age 18 to 40; 37 percent are 41 to 60; 14 percent are 61 to 80 and 5 percent are 81 or older.

Counties with the highest number of positive test results are Polk (2,150), Woodbury (1,532), Black Hawk (1,463) and Linn (813).

Earlier this week, state officials revamped the data available to the public at coronavirus.iowa.gov, with the new format no longer listing the age range of Iowans who died from coronavirus and providing information using a different timeline than before.

The governor did not hold a daily media briefing Friday due to scheduling conflicts created by Vice President Mike Pence’s trip to Iowa. Garrett said Reynolds would resume her COVID-19 briefings next week.

John McGlothlen and Zack Kucharski of The Gazette contributed to this report.

This paper is the first to consider online algorithms to schedule a proportionate flexible flow shop of batching machines (PFFB). The scheduling model is motivated by manufacturing processes of individualized medicaments, which are used in modern medicine to treat some serious illnesses. We provide two different online algorithms, proving also lower bounds for the offline problem to compute their competitive ratios. The first algorithm is an easy-to-implement, general local scheduling heuristic. It is 2-competitive for PFFBs with an arbitrary number of stages and for several natural scheduling objectives. We also show that for total/average flow time, no deterministic algorithm with better competitive ratio exists. For the special case with two stages and the makespan or total completion time objective, we describe an improved algorithm that achieves the best possible competitive ratio $varphi=frac{1+sqrt{5}}{2}$, the golden ratio. All our results also hold for proportionate (non-flexible) flow shops of batching machines (PFB) for which this is also the first paper to study online algorithms.

A server computer system determines that configuring a first virtual machine in a cloud depends on a configuration result of configuring a second virtual machine. The server computer system configures the second virtual machine in the cloud and configures the first virtual machine in the cloud using the configuration result of the second virtual machine.

A system and method for reconfiguring a computing environment comprising a consumption analysis server, a placement server, an infrastructure management client and a data warehouse in communication with a set of data collection agents and a database. The consumption analysis server operates on measured resource utilization data to yield a set of resource consumptions in regularized time blocks, collects host and virtual machine configurations from the computing environment and determines available capacity for a set of target hosts. The placement server assigns a set of target virtual machines to the target set of hosts in a new placement. In one mode of operation the new placement is nearly optimal. In another mode of operation, the new placement is “good enough” to achieve a threshold score based on an objective function of resource capacity headroom. The new placement is implemented in the computing environment.

A method and apparatus are disclosed of monitoring a number of virtual machines operating in an enterprise network. One example method of operation may include identifying a number of virtual machines currently operating in an enterprise network and determining performance metrics for each of the virtual machines. The method may also include identifying at least one candidate virtual machine from the virtual machines to optimize its active application load and modifying the candidate virtual machine to change its active application load.

The refrigerating machine oil of the invention includes an ester of a polyhydric alcohol and a fatty acid, wherein the molar ratio of C4-C6 fatty acid and C7-C9 branched fatty acid in the fatty acid is between 15:85 and 90:10, the C4-C6 fatty acid includes 2-methylpropanoic acid, and the ratio of the total C4-C6 fatty acid and C7-C9 branched fatty acid in the total fatty acids composing the ester is at least 20 mol %. The working fluid composition for a refrigerating machine according to the invention comprises the refrigerating machine oil, a difluoromethane refrigerant and/or an unsaturated fluorinated hydrocarbon refrigerant.