CAT-340 study help - CA IdentityMinder r12.x Professional Updated: 2023

CA Technologies (NASDAQ:CA) today announced the latest release of CA Identity Suite, its leading identity and access governance solution. Announced during the KuppingerCole European Identity and Cloud Conference, CA Identity Suite adds real-time analytics to strengthen operational efficiencies. It also provides new personalization and mobility capabilities plus pre-configured deployment scenarios that simplify the business user experience and drive faster implementation and time-to-value.

“The identity and access governance functions that are critical to the security and business operations of an organization are no longer the responsibility of a central IT group; that job is now in the hands of business users who need a streamlined and simple way to process identity-related tasks and workflows,” said Mordecai Rosen, general manager, CA Technologies, Security business. “CA is committed to providing the most robust, scalable and easy-to-use identity and access governance system for our customers and partners, while helping to ensure security, compliance and operational needs are met.”

By adding analytics into CA Identity Suite, customers have real-time insight into how core processes are operating within the identity management workflow. A deep visualization of each process and its status helps the managers responsible for access certifications identify and drill down to the root cause of any bottlenecks for quick remediation. This not only improves efficiency and productivity, it also reduces risk of breach by helping to ensure that access is removed quickly when user roles change or a user status is modified.

In addition to improving operations, CA Identity Suite improves the productivity and user experience of those individuals responsible for access certification. With new personalization options, users control how information is displayed and they have the option to take the workload offline for convenient review and decision-making. Comprehensive mobile support allows users to do everything they can do at their desk on their mobile device, including make access requests and manage the user lifecycle.

CA Identity Suite also has pre-configured the most common identity and access governance business user scenarios. The out-of-the-box configurations supply customers a jump-start to help speed deployment, whether it’s contractor lifecycle management (onboarding, termination), employee lifecycle management (modification, user type conversion) or user self-service. Instead of re-creating those common scenarios, customers simply do minor customization to the pre-packaged scenarios to meet their own unique needs. What can take weeks to configure in some situations with other solutions, can be done in just a few days with CA Identity Suite.

“Simeio Solutions and CA Technologies have been partners for more than eight years, putting the breadth of CA’s robust and highly scalable identity and access management technology into many organizations to address their security, compliance and identity operations needs,” said Shawn Keve, executive vice president, Simeio Solutions. “This new release of CA Identity Suite helps make identity processes even more user friendly for the business user by providing a customized interface and expanded mobility options.”

Artificial intelligence is already revolutionizing law enforcement, which has implemented advanced technology in their investigations, but "society has a moral obligation to mitigate the detrimental consequences," a accurate study says.

AI is in its teenage years, as some experts have said, but law enforcement agencies are already integrating predictive policing, facial recognition and technologies designed to detect gunshots into their investigations, according to a North Carolina State University report published in February.

The report was based on 20 semi-structured interviews of law enforcement professionals in North Carolina, and how AI impacts the relationships between communities and police jurisdictions. 

"We found that study participants were not familiar with AI, or with the limitations of AI technologies," said Jim Brunet, a co-author of the study and director of NC State’s Public Safety Leadership Initiative.

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"This included AI technologies that participants had used on the job, such as facial recognition and gunshot detection technologies," he said. "However, study participants expressed support for these tools, which they felt were valuable for law enforcement."

Law enforcement officials believe AI will Strengthen public safety but could erode trust between police and civilians, according to the study. 

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This comes at a time when American cities are wrestling with this politically divisive issue of curtailing crime while regaining the public's trust in the wake of George Floyd's murder at the hands of disgraced police officers. 

Ed Davis, who was the police commissioner during the Boston Marathon bombing in 2013, told Fox News Digital AI "will ultimately Strengthen investigations and allow many dangerous criminals to be brought to justice."

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But it comes with risks and pitfalls, Davis said, and criminals will have access to the same technology, which could negatively impact police investigations. 

The well-respected commissioner's comments are backed by the study's findings. 

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"Policymaking guided by public consensus and collaborative discussion with law enforcement professionals must aim to promote accountability through the application of responsible design of AI in policing with an end state of providing societal benefits and mitigating harm to the populace," the study concludes. 

"Society has a moral obligation to mitigate the detrimental consequences of fully integrating AI technologies into law enforcement."

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Part of the issue is police officers' general lack of knowledge about AI's capabilities and how they work, said Ronald Dempsey, the first author of the study and a former graduate student at NC State. 

That "makes it difficult or impossible for them to appreciate the limitations and ethical risks," Dempsey said. "That can pose significant problems for both law enforcement and the public."

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Law enforcement's use of facial recognition boomed after the Jan. 6, 2021 Capitol riot.

Twenty out of 42 federal agencies that were surveyed by the Government Accountability Office in 2021 reported they use facial recognition in criminal investigations.

If the emerging AI technologies "are well-regulated and carefully implemented," a public safety good "can potentially increase community confidence in policing and the criminal justice system," the study found. 

"However, the study participants expressed concerns about the risks of algorithm bias (diversity and representativeness challenges), the challenge of replicating the human factor of empathy, and concerns about privacy and trust.

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"In addition, fairness, accountability, transparency, and explainability challenges remain as presented in the broader academic debate," the study says. 

AI has the power to bridge or deepen the divide between police and the public, according to the study, which said it's essential that law enforcement leaders have a seat at the table for all talks about framework for how police can use the tech.

Veljko Dubljević, corresponding author of the study and an associate professor at North Carolina State University, said the guidelines can be used to inform AI decision-making.

"It’s also important to understand that AI tools are not foolproof," Dubljević said. "AI is subject to limitations. And if law enforcement officials don’t understand those limitations, they may place more value on the AI than is warranted – which can pose ethical challenges in itself."

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Police have already made mistakes using facial recognition that led to wrongful arrests. 

AI algorithms falsely identified African American and Asian faces 10 to 100 times more than White faces, according to a 2019 study by the National Institute of Standards and Technology. 

"There are always dangers when law enforcement adopts technologies that were not developed with law enforcement in mind," Brunet said. 

"This certainly applies to AI technologies such as facial recognition. As a result, it’s critical for law enforcement officials to have some training in the ethical dimensions surrounding the use of these AI technologies."

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The study emphasized creating a transparent culture of accountability that shows how AI technologies are being used in police investigations. 

A accurate New York Times report about a wrongful arrest based on facial recognition showed court documents and police reports didn't include any reference to the use of the AI tech, a practice that is reportedly becoming more prevalent. 

"As a final point, AI policing technologies must be explainable, at least generally, in how decisions are reached," the NC State study said. 

"Law enforcement professionals should, at a minimum, have a broad understanding of the AI technologies used in their jurisdictions and the criminal justice system as a whole. Procedural training for police officers who employ artificial intelligence technology."

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The study was focused on North Carolina and is intended as a "snapshot" of an emerging trend and requires more research and education for law enforcement professionals. 

With the work-from-home era in full swing, I’ve found that I still venture out every few days to do my job from a coffee shop. Something about the change of scenery is helpful and gets me in a working mood. It’s hard to live, work, eat, sleep, clean, study, and relax all in the same space; at some point, when you’re stuck in a single room, those things all kind of start to blend together and it becomes all too easy to check personal messages during study time or tidy up when you should be answering emails.

Sometimes, though, you can’t change the scene. If you live in a shared space and are confined to your bedroom or are in a dorm and the library is closed, you can’t just go somewhere else. Hell, you don’t always have the time or energy to go somewhere else. You can still compartmentalize: by simply changing your clothes.

The benefits of compartmentalizing

The idea of compartmentalizing involves focusing on only one thing at a time, ideally in different settings. The advent of online classes and working from home has been great for so many reasons—but it really killed our ability to associate different locations with specific tasks.

Finding a way to compartmentalize is important, but it can be as easy as doing your job from your kitchen table and your homework from your bedroom. Whatever helps you change the setting just a bit to get your brain into “work” or “study” mode. But again, that’s just not always possible.

How changing your clothes can help you compartmentalize

During the pandemic, career advice sites were full of articles insisting you should still “get dressed” for work hours. Without taking it to an extreme, that’s actually a pretty good idea, even if it seemed offensive at the time to consider putting on real-deal business casual when the world was in pandemonium and there were seemingly more important things to think about. No, you don’t have to put on itchy nylons or stiff pants, but when you stay in your sweats from morning until night, you may find you have a lazier type of day.

The test Study Expert says that changing your clothes helps mark the transition between different tasks, so if you have to study for something big, consider having a designated outfit in which to do so. I recommend a “study sweatshirt”—really, just use a hoodie from your school. If you put this on at the same time every day and then get to work, your brain will start to associate that outfit change and time period with studying, even if you don’t alter anything else about your setting. Per USA Today, fashion psychologists say that people attach sentimental meanings to their clothing, even without realizing it.

There’s even a science-y term for this phenomenon: enclothed cognition. A study in 2012 involved giving participants a white lab coat, but telling half of them it was a painter’s jacket and the other half it was a doctor’s coat. The people who thought they were in a doctor’s coat had more sustained attention during tasks.

The researchers there found that the symbolic meaning and the experience of wearing the clothing played a role in the participants’ productivity and attention span, so you have to stick with this for it to be helpful. The repetition of putting on your “study sweatshirt” is just as important as designating the sweatshirt in the first place. Don’t wear the study sweatshirt for anything else or at any other time of day. When study time rolls around, that’s when you break it out. In no time, you’ll be as dedicated to your work as those people in the doctors’ coats.

Founder and CEO of ScaleOut Software.

The accurate spate of major rail accidents in the nation’s freight system, like February’s 50-car derailment in East Palestine, Ohio, have caused serious disruptions to several communities and heightened safety concerns. Is there cost-effective technology that could help prevent these accidents? How difficult would it be to deploy?

The key to preventing railway accidents like these is to detect problems and take action before they lead to derailments. The Ohio accident has been traced to an overheated wheel bearing that is suspected of causing a fire and subsequent derailment. Today’s freight rail system has a series of rail-side “hot box” detectors positioned every few miles that measure bearing temperatures. These detectors can radio an alert to train personnel if they detect an imminent failure. However, as we have seen, these alerts may arrive too late.

What’s needed is technology that can predict impending failures and send alerts earlier, allowing operators to stop trains while there’s time to act. Ironically, the needed data is already stored within the rail-side detectors—it’s just not being continuously harvested and analyzed. A combination of existing technologies can address three key challenges in solving this problem: how to collect the data, how to organize it and how to analyze it. The good news is that the cost to deploy these technologies is modest, especially in comparison to the cleanup costs after an accident.

Cloud Computing

The first challenge is where to send the data, and the answer is the cloud. Rail-side hot box detectors can use cell-based transmitters to send real-time temperature data to a single, cloud-hosted repository where it can be organized and analyzed. The cloud’s vast computing resources can handle the large amounts of data generated by the thousands of freight trains that flow along the rails every day. Having the history of each rail car’s data immediately available enables predictive analytics code to correlate temperature changes from multiple detectors and detect emerging problems before they lead to accidents.

Digital Twins

The next challenge is to organize incoming data from many trains and detectors to perform timely analysis for each wheel bearing and intervene before an accident occurs. With about 500,000 carloads of freight crossing roughly 6,000 hot box detectors every week, that’s a lot of wheel-bearing telemetry flooding into the cloud.

The key to dealing with all this data is found in a software technology called the digital twin. By maintaining a digital twin for each rail car, we can easily keep track of a car’s wheel-bearing temperatures and analyze them for changes as the car moves from detector to detector. Having all of the rail car’s data in one place enables analytics code to watch for abnormal temperature increases, unexpected differences across axles and wheel trucks and other anomalies. The digital twin can even keep track of each car’s service history and other known issues specific to the car that can assist in analyzing the telemetry. This contextual information can prove to be highly valuable in preventing unnecessary alerts that create costly delays.

Machine Learning

The final challenge is how to develop the potentially intricate analytics code that runs in the digital twin and looks for temperature changes that are predictive of an impending failure. The physics of wheel bearings is complex, with temperature fluctuations dependent on many factors. It’s important that analytics code accurately predicts when to signal alerts without unnecessarily disrupting the flow of freight traffic.

Machine learning technology from the field of artificial intelligence can provide the solution here. This software technology can be trained using a technique called “supervised learning” on thousands of temperature measurements and other data collected by rail companies. After training, it can examine incoming measurements for each rail car and accurately discern which trends indicate a likely failure and which do not. As each digital twin receives data from a hot box detector, the machine learning algorithm can automatically track changes in temperature readings and signal alerts when necessary.

By combining the technologies of cloud computing, digital twins and machine learning, rail companies can continuously and automatically keep an eye on the hundreds of thousands of freight cars rolling on their rails. This technology can do a much better job of analyzing data from hot box detectors than human managers, and it never gets fatigued. Given the millions of dollars required to recover from a derailment, the suffering created by a toxic chemical spill, and the legal liability to rail companies, the cost of deploying technology like this should prove to be a worthwhile investment for rail companies.

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One easy way to invest in process is to set goals, both individually and as a family. Try to do this at the beginning of a new school year, the first of the month, or the beginning of a new season.  Keep the discussion light and low-pressure. This process isn’t about getting better grades, it’s about supporting learning as a family. 

Everyone (yes, that means parents, too) sets three short-term, achievable goals oriented around tasks and improvements under your control. For example, “I’m going to get all A's this semester” is too broad and too difficult to control. Instead, try “I’m going to ask for help in math more often,” “I will plan one extra help session a week,” or “I will practice my multiplication three extra times this month.” 

One of those three goals should be a challenge. We can’t hope to convince our children to be emotionally and intellectually brave unless they see us do the same, so set some goals that get you out of your comfort zone. Take guitar or dance or Spanish lessons, try an activity you have never tried before, or pick up a new hobby. This is, after all, how we expand our cognitive potential and make new connections in our brains that can help us become stronger, smarter and more efficient learners. 

A few years ago, one of my sons’ goals was to make a few new friends, a goal that was both challenging and important to him. 

Before you set new goals, take the time to assess how everyone did on past goals. Review these goals once a month or once a semester. If you fail to achieve your goals talk about why, and what you plan to do differently next time. If you succeed, celebrate that achievement! 

Model: Watching a parent set a scary, ambitious goal and talk about the process of achieving it is the most direct way to teach children that learning and striving to be better are human goals, not just school goals.

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