Liza Dzhezhora’s picture

By: Liza Dzhezhora

Having appeared in the early 2000s, connected health technologies have gradually become a game changer in the healthcare industry. Healthcare providers that have embraced smart medical IoT solutions reduce costs, improve patient experience, and ensure preventive care.

The trend is not fading away. According to Research and Markets, the global health and wellness device market will grow threefold and reach around $152 billion in 2027.

The internet of medical things (IoMT) includes many tools, from blood pressure monitors and pulse oximeters to smart pill dispensers. Nevertheless, implementing medical devices and related software has specific challenges.

How do you ensure the integration of IoMT devices in your practice? We consider the four barriers and see how developers can help to overcome them.

Jennifer Lauren Lee’s picture

By: Jennifer Lauren Lee

In a brightly lit subterranean lab at the National Institute of Standards and Technology (NIST) sits a room-sized electromechanical machine called the NIST-4 Kibble balance.

The instrument can already measure the mass of objects of roughly 1 kilogram, about as heavy as a quart of milk, as accurately as any device in the world. But now, NIST researchers have further improved their Kibble balance’s performance by adding a custom-built device that provides an exact definition of electrical resistance. The device is called the quantum Hall array resistance standard (QHARS); it consists of a set of several smaller devices that use a quirk of quantum physics to generate extremely precise amounts of electrical resistance. The researchers describe their work in a Nature Communications paper.

Gleb Tsipursky’s picture

By: Gleb Tsipursky

Disney’s CEO Bob Iger demanded on Jan. 9, 2023, that all employees return to the office for at least four days a week because “in a creative business like ours, nothing can replace the ability to connect, observe, and create with peers that comes from being physically together.” That’s similar to the sentiments expressed by Apple’s CEO Tim Cook, who demanded that employees come to the office for at least three days per week because “Innovation isn’t always a planned activity. It’s bumping into each other over the course of the day and advancing an idea that you just had. And you really need to be together to do that.”

Rupa Mahanti’s picture

By: Rupa Mahanti

Data are an organization’s most valuable asset. However, too much data are inaccurate, incomplete, irrelevant, obsolete, not well defined, or otherwise not fit for use. Bad quality data can lead to operational inefficiencies, poor decision making, non-compliance issues, and lost revenue.

According to Gartner’s research, the average financial impact of bad data quality on organizations is $9.7 million per year. Hence, it is imperative for organizations to manage their data efficiently, and ensure that their data are of high quality.

Data profiling is about discovering and thoroughly reviewing the underlying data available to ascertain the characteristics, the data patterns, and essential statistics about the data1. It is essentially the first step in climbing the ladder of data quality, and it provides a proactive approach to understanding an organization’s data. In this article, we discuss the different data profiling methodologies that can be used to assess the quality of data in an organization.

Gorur N. Sridhar’s picture

By: Gorur N. Sridhar

Obsessive-compulsive disorder (OCD) is an anxiety condition characterized by intrusive thoughts that produce uneasiness, apprehension, fear, or worry (collectively termed obsessions), along with repetitive behaviors (or compulsions) aimed at reducing the associated anxiety.

For team members in quality departments, I personally feel that many OCD traits ought to be a unique selling point for recruitment. In fact, the level of attention to detail inherent in many with OCD is the penchant driving quality systems and processes in most organizations. It’s the compulsive checking-rechecking cycle that teaches the importance of verification and validation.

How can you tell if people with OCD work in your quality department? Symptoms of the disorder include: excessive washing or cleaning, repeated checking, hoarding, relationship-related obsessions, aversion to particular numbers, and nervous rituals such as opening and closing a door a certain number of times before entering or leaving a room.

Jake Mazulewicz’s picture

By: Jake Mazulewicz

Do you lead your team to learn primarily from successes, or from failures? Many leaders argue that their teams are just too busy to spend time discussing why a successful project went well. They just wrap up fast, then dive into the next project. So, the unspoken insights and unwritten lessons learned from that project are rarely shared or discussed. Often, they’re just forgotten in the frenzy of working project after project.

But would you hire an engineer to build you a bridge if all that engineer ever studied was how bridges collapse? Would you hire a recruiter to find you a job if all that recruiter ever studied was how people get fired?

The best leaders help their teams learn regularly from their successes, not just occasionally from their failures. But learning from success happens automatically, doesn’t it? Not necessarily.

Association of Equipment Manufacturers’s picture

By: Association of Equipment Manufacturers

With 2022 firmly in the rearview mirror and the new year now underway, it’s clear many of the opportunities and challenges affecting equipment manufacturers today will remain as relevant as ever in the weeks and months ahead. And while it’s a fool’s errand to try to predict exactly how 2023 will unfold, equipment manufacturers would be wise to pay close attention to a number of trends and how they may evolve in the near term.

With that in mind, the Association of Equipment Manufacturers (AEM) spoke to several staff leaders to hear what’s top of mind for them at the moment.

1. The industrywide emphasis on organizational culture

With so much change taking place in 2022, organizations in many industries, including equipment manufacturing, are being forced to re-examine their business models. Supply chain issues, increased competition, technology advancements, and economic uncertainty have all placed pressure on companies to adapt, innovate, and rethink how they do business.

Donald J. Wheeler’s picture

By: Donald J. Wheeler

The shape parameters for a probability model are called skewness and kurtosis. While skewness at least sounds like something we might understand, kurtosis simply sounds like jargon. Here we’ll use some examples to visualize just what happens to a probability model as kurtosis increases. Then we’ll combine the visible effects of both skewness and kurtosis to see how they combine to “shape” probability models

Last month, we found that while an increase in positive skewness measures a nearly invisible increase in the area of the upper tail, it has two visible manifestations. Specifically, these are a substantially shorter lower tail and an appreciable shift of the mode to the left. Figure 1 summarizes these results for the three comparisons made.


Figure 1: Effects of increasing positive skewness while holding kurtosis constant

Figure 1 shows what happens when we hold the kurtosis constant and increase the skewness. In the comparisons that follow, we’ll look at what happens when we increase the kurtosis while holding the skewness constant.

Zeeshan Hussain’s picture

By: Zeeshan Hussain

Every engineer dreams of having a virtual personal assistant like Jarvis, the disembodied voice that carries out Iron Man’s orders. Smart assistants like Apple’s Siri and Amazon’s Alexa are a step in the right direction, but they can’t help an engineer design a new car. Or can they? Recent progress in voice-controlled design software hints that Jarvis may be just around the corner.

Natural language processing (NLP) comes to design software

Natural language processing, or NLP, is a subfield of artificial intelligence (AI) that allows computer programs to understand human language as it is spoken and written. NLP has progressed in leaps and bounds since the advent of the internet, and by now most of us take it for granted that our smart assistants can decipher what we say and respond appropriately (most of the time, anyway).

Lisa Apolinski’s picture

By: Lisa Apolinski

A not-so-surprising fact, according to HubSpot: 65 percent of consumers state that the experience they encounter on a website is a “very important” factor in recommending a brand. If that statistic’s not enough, HubSpot also reported that 75 percent of consumers expect new technologies to be used to create memorable and better experiences.

The bottom line seems clear; If companies don’t invest in the digital consumer experience, there’s a potential risk of losing those consumers. What are the most important factors in creating those memorable digital consumer experiences? Consider these five must-haves:

Must-have 1: Answer the need of the consumer

Organizations are tempted to choose new technologies that internal staff think are great but have no effect on the consumer experience. Even worse, some new additions to current technologies can make the digital consumer experience worse or more complicated.

When considering adding new technologies, look at what the consumer experiences currently are. Then determine whether the new technology addresses a specific need or improves the experience. If those needs aren’t being addressed, it may be better to continue that new technology search.

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