We found 67 results that contain "system management"

Internet of Things (IoT):
The Internet of Things (IoT) is a name for the aggregate collection of network-enabled devices, excluding traditional computers like laptops and servers. Types of network connections can include Wi-Fi connections, Bluetooth connections, and near-field communication (NFC). The IoT includes devices such as "smart" appliances, like refrigerators and thermostats; home security systems; computer peripherals, like webcams and printers; wearable technology, such as Apple Watches and Fitbits; routers; and smart speaker devices, like Amazon Echo and Google Home.

 
In our last post, We had a close look at Credentialing and what it entails. We also gained insight into how healthcare companies and providers manage this very important function in healthcare recruitment. Having understood why healthcare credential management is so crucial not only from a business perspective but also ensures there are no legal implications, the stage is just right to introduce another factor closely related to Credentialing, namely Compliance.
Join me in exploring why Compliance in Credentialing is so important and how this need not be such an onerous task with specialized apps, customized specifically for online healthcare recruitments. Credential compliance is achievable with minimal stress. Let us understand how, but first-a brief background.
What is Compliance in Credentialing, and Why does it matter?
I am using the the term ‘Compliance’ to mean meeting the requirements for Credentialing and participating in effective Compliance programs as set forth by the Office of Inspector General (OIG) and the National Committee for Quality Assurance(NCQA). This includes internal auditing, monitoring, credentialing education and training, developing plans of corrective action in responding to related problems as well as enforcing credentialing standards. Most Compliance programs, while generally operating as independent entities, report to their respective boards of directors or other committees providing assistance and oversight to the process.
So, what happens if a healthcare fails to verify accurately? Without careful oversight and auditing, it is all too possible for omissions or errors to occur before, during, or immediately following the process, which could lead to enrollment issues as well as open a pandora’s box to legal problems if the process is incomplete or the provider’s privacy is compromised. Furthermore, the 1960s case of Darling vs. Charleston Hospital established the responsibility of hospitals and other healthcare facilities in verifying the professional credentials of the physicians and other providers practicing under their roof.
 
 
 
REF : links :https://targetrecruit.com/the-importance-of-compliance-in-credentialing/
 
YouTube: https://youtu.be/C6YrPt1ygX8

An AI that can produce photorealistic videos of sign language interpreters from speech could improve accessibility by removing the need for humans.
Ben Saunders at the University of Surrey, UK, and his colleagues used a neural network that converts spoken language into sign language. The system, called SignGAN, then maps these signs on to a 3D model of the human skeleton.
The team also trained the AI on videos of real sign language interpreters, teaching it how to create a photorealistic video of anyone signing based off an image of …
Read more: https://www.newscientist.com/article/2261113-ai-can-turn-spoken-language-into-photorealistic-sign-language-videos/#ixzz6g1KMybts

Generative AI starts with a prompt that could be in the form of a text, an image, a video, a design, musical notes, or any input that the AI system can process. Various AI algorithms then return new content in response to the prompt. Content can include essays, solutions to problems, or realistic fakes created from pictures or audio of a person.
Early versions of generative AI required submitting data via an API or an otherwise complicated process. Developers had to familiarize themselves with special tools and write applications using languages such as Python.
Now, pioneers in generative AI are developing better user experiences that let you describe a request in plain language. After an initial response, you can also customize the results with feedback about the style, tone and other elements you want the generated content to reflect.

In 1957, people started figuring out new ways to build computer programs. They wanted to make the process better over time, so they came up with iterative and incremental methods.
In the 1970s, people started using adaptive software development and evolutionary project management. This means they were adjusting and evolving how they built software.
In 1990s, there was a big change. Some people didn't like the strict and super-planned ways of doing things in software development. They called these old ways "waterfall." So, in response, lighter and more flexible methods showed up.

Edited

The main principles of the Lean methodology include:

Eliminating Waste
Amplifying Learning
Deciding as Late as Possible
Delivering as Fast as Possible
Empowering the Team
Building Integrity In
Seeing the Whole

Lean development eliminates waste by asking users to select only the truly valuable features for a system, prioritize those features, and then work to deliver them in small batches. It relies on rapid and reliable feedback between programmers and customers, emphasizing the speed and efficiency of development workflows. Lean uses the idea of a work product being “pulled” via customer request. It gives decision-making authority to individuals and small teams since this has been proven to be a faster and more efficient method than a hierarchical flow of control. Lean also concentrates on the efficient use of team resources, trying to ensure that everyone is as productive as possible for the maximum amount of time. It strongly recommends that automated unit tests be written at the same time the code is written.

The main principles of the Lean methodology include:

Eliminating Waste
Amplifying Learning
Deciding as Late as Possible
Delivering as Fast as Possible
Empowering the Team
Building Integrity In
Seeing the Whole

Lean development eliminates waste by asking users to select only the truly valuable features for a system, prioritize those features, and then work to deliver them in small batches. It relies on rapid and reliable feedback between programmers and customers, emphasizing the speed and efficiency of development workflows. Lean uses the idea of a work product being “pulled” via customer request. It gives decision-making authority to individuals and small teams since this has been proven to be a faster and more efficient method than a hierarchical flow of control. Lean also concentrates on the efficient use of team resources, trying to ensure that everyone is as productive as possible for the maximum amount of time. It strongly recommends that automated unit tests be written at the same time the code is written.

The classic egg drop experiment gets reinvented as a driving question for physics students to explore a real-world problem.

By Suzie Boss
July 26, 2018
When a teenager climbs atop his desk and drops an object to the floor, teacher Johnny Devine doesn’t object. Far from it—he’s as eager as the rest of the class to see what happens next.

In a split second, the student and his teammates get positive feedback for the object they have cobbled together by hand. A small parachute made of plastic and held in place with duct tape opens as planned, slowing the descent and easing the cargo to a safe landing. Students exchange quick smiles of satisfaction as they record data. Their mission isn’t accomplished yet, but today’s test run brings them one step closer to success as aspiring aerospace engineers.



To boost engagement in challenging science content, Devine has his students tackle the same problems that professional scientists and engineers wrestle with. “Right away, they know that what they are learning can be applied to an actual career,” Devine says. “Students are motivated because it’s a real task.”

From the start of Mission to Mars, students know that expert engineers from local aerospace companies will evaluate their final working models of Mars landing devices. Their models will have to reflect the students’ best thinking about how to get a payload from orbit onto the surface of the Red Planet without damaging the goods inside. While real Mars landings involve multimillion-dollar equipment, students’ launchers will carry four fragile eggs.

THE ROAD MAP

Although the project gives students considerable freedom, it unfolds through a series of carefully designed stages, each focused on specific learning goals. Having a detailed project plan “creates a roadmap,” Devine explains, “for the students to really track their progress and see how what they’re learning connects back to the guiding question: How can we successfully land a rover on Mars?”

©George Lucas Educational Foundation

Before introducing technical content, Devine wants students to visualize what space scientists actually do. By watching videos of engineers who design entry, descent, and landing systems for spacecraft, students start getting into character for the work ahead.

Devine introduces a series of hands-on activities as the project unfolds to help students put physics concepts into action. They learn about air resistance, for instance, by experimenting with parachute designs and wrestling with a real challenge: How will they slow their landers to a reasonable speed for entry into the thin Martian atmosphere?

To apply the concept of change in momentum, students design airbag systems to go on the bottom of their landers—a location aptly called the crumple zone. They experiment with bubble wrap and other materials as potential cushioners for their cargo.

As the grand finale approaches, students keep using what they learn to test, analyze, and modify their designs. “You have to repeat the equations with different trials,” one student explains. “Being able to use that math over and over again helps it stick.”

Much of the hands-on learning in this PBL classroom “might look like a traditional physics lab,” Devine acknowledges, with students learning concepts through inquiry investigations. What’s different is the teacher’s ongoing reminder “to make sure students stay in character” as systems engineers. Each lab investigation relates back to their driving question and creates more opportunities for Devine to ask probing questions and formatively assess his students’ understanding. “We do a lot of framing in and framing out after each of those lessons so students have the chance to reflect and connect it back,” the teacher explains.

EXPERT CONVERSATIONS

When it is finally time for students to launch their precious cargo off a second-story landing, engineers from local aerospace companies are standing by to assess results. How many eggs in each lander will survive the fall?

Even more important than the test data are the discussions between experts and students. One engineer, for instance, asks to see earlier versions of a team’s design and hear about the tests that led to modifications. A student named Elizabeth perks up when she hears engineers using the same technical vocabulary that she and her classmates have learned. “It was kind of a connection—this is actually a thing that goes on,” she says.

“They had really deep, meaningful conversations so that students could practice communicating their justification for their designs,” Devine says. Hearing them use academic language and apply physics concepts tells the teacher that students deeply understand the science behind their designs. “At the end of the day, that’s what I’m most concerned about,” he says.

https://youtu.be/bKc2shFqLao