Category Archive: Engineering

Artificial Intelligence: Get on Board or Get out of the Way

Artificial intelligence – machines’ ability to learn on their own – promises to change the way business is done.

Dedicated Computing Engineers attending MSOE’s grand opening ceremonies of the new Diercks Computational Science Hall

“It really is a new kind of industrial revolution, ” says Derek Riley, Ph.D., computer science program director at Milwaukee School of Engineering (MSOE). “Much the way assembly lines revolutionized how things were made, AI technology is going to change the way people interact with computers, other people, and just about everything.”

Artificial intelligence applications have been around for more than a decade, but their use is reaching a tipping point due to advances in computing technology, the massive amounts of data that have been compiled, and the development of algorithms that are now sophisticated enough to comb through data to identify patterns and solve real problems.

“AI is all about streamlining decision making,” Riley says. “It’s about letting humans do what humans are good at and letting computers do what computers are good at.” Jeff Krueger, director, systems engineering at Waukesha-based Dedicated Computing, agrees. “Data analytics, machine learning, and artificial intelligence are changing how diseases are diagnosed,” he says. “Students training through simulators will have the ability to dynamically adjust to the learning techniques of the individual, creating deeper and engaging environments that will increase overall learning.”

Dedicated Computing designs, develops, tests, and manufactures application-specific, high-performance computational solutions used in life sciences, healthcare, training and simulation, and Industry 4.0. It is sponsoring the Dedicated Computing Data Analytics Laboratory – a data-rich, reconfigurable laboratory space – in MSOE’s new Dwight and Dian Diercks Computational Science Hall.

Krueger says MSOE’s new lab will be critical for giving people the skills needed to fully leverage artificial intelligence.

“For many years, sensors, data collection endpoints and IT systems have logged an incredible amount of data, most of it dark – which means it is stored, but has not been looked at or processed,” he says. “Embedded in this data are potentially patentable ideas, as well as new and unique methods by which a product can surpass the competitors. Data analytics and increased computational capability will make large and small businesses more nimble, allowing them to create impactful and beneficial solutions.” Riley agrees. “In order to be effective, small companies have to understand the general ideas of how these technologies work, so they can make good business decisions around where they should use an AI solution to address a problem,” he says.

MSOE is at the forefront of bringing artificial intelligence into the mainstream.

“Our focus on AI is pretty unique,” Riley says. “The only two schools that I can point to that are doing something in the same vein are the Massachusetts Institute of Technology, which recently realigned their computer science department, and Carnegie Mellon University. Both are much bigger, research-focused universities. What makes us unique is that we are focused on undergraduate students and applied skills.”

“What MSOE is doing is fantastic for Wisconsin, the Midwest, and all those impacted by the migration of knowledge across all domains,” says Krueger. “Investing in the infrastructure, resources, and staff will benefit Wisconsin, as well as current and future students. We hope to aid in increasing the awareness of technology, methods, and our experience in developing and managing similar solutions.”

This article was originally published as a supplement to the Milwaukee Business Journal, Sept. 13, 2019

Dedicated Computing & MSOE – A Bold Step Taken

New 64,000 sq. ft. computational facility will focus on artificial intelligence, machine learning, robotics, and cybersecurity.

DC Engineers at MSOE

Senior Mechanical Engineer, Qilu He, showcases his projects at Dedicated Computing with visitors at the Diercks Computational Science Hall grand opening.

Dedicated Computing recently unveiled the DC Data Analytics Laboratory as part of their on-going partnership with the Milwaukee School of Engineering (MSOE). The unveiling was in conjunction with MSOE’s grand opening ceremonies for the new Dwight and Dian Diercks Computational Science Hall. The Dedicated Computing Data Analytics Laboratory is a data-rich, reconfigurable laboratory which can evolve with the university’s AI-centric curriculum.

DC also announced a Co-Working Internship with MSOE, which provides students the opportunity to apply concepts in real-world situations.

“Dedicated Computing values the collaborative spirit at MSOE,” says Jeff Krueger, Director of System Engineering at Dedicated Computing. “Partnering with MSOE is about learning, growing and benefiting from each other’s knowledge and experience. Diercks Hall specifically provides the ability to harness the power of AI through a partner approach to enhancing business capability. Our work with MSOE’s emerging technology leaders increases our adaptability in the evolution of solutions embodying AI to cure disease, advance military training, and evolve industrial automation systems.”

For more reporting on the grand opening event and Diercks Hall, follow the links below:

MSOE Corporate Partnership

NVIDIA Software Head Helps Transform Alma Mater into Leading AI Center with $34M Gift

MSOE Official Announcement

Extending Security and Reliability: Excellence in Medical Device Support Blends Remote and Onsite Strategies

Proactive Service Demands Real-time Insight Into Medical Device Performance, Balances Costs and Risk

Keeping healthcare systems in the field as long as possible is an exceptional demand for original equipment manufacturers (OEMs). Support strategies can play a critical role, recognizing security as a primary design requirement for connected devices. These concerns must be considered at the earliest stages of development rather than ‘bolted’ on later — which requires the understanding of implementation logistics and goals for achieving the right level of security – acceptable to the manufacturer as well as the device’s operational setting.

Security features can also be built into the software image, allowing systems to be online and less susceptible to security breaches. Early discussions, in advance of the software image being designed, can allow for a greater understanding of security features that may help the system achieve a higher threshold of protection while maintaining connectivity.

Use case: Early planning improves reliability and addresses security with a smart blend of remote and onsite support

One OEM of medical device equipment recognized a key support issue with its systems being returned noted as “no issue found.” Diagnosis was failing because the system was being removed from its environment and the repair depot could not replicate the problem. Remote options added great value here, as the manufacturer’s systems didn’t need to be removed from the field and could be diagnosed in their functional environment.

For this OEM, remote monitoring required connectivity, empowering the system operator with real-time insight on performance issues and system health. This facilitates proactive service, preventing failures before they happen – as well as highly focused service, tapping into better data to reduce costs for unnecessary service calls. Software updates can be handled remotely as well, eliminating the need for service techs to apply patches onsite using physical devices such as USB keys – for a significant cost savings.

At the same time, connectivity flies in the face of security concerns, potentially increasing vulnerability and risk that healthcare providers are keen to reduce and avoid. OEMs must base consideration of the preferred option on costs, comfort level and requirements of the deployment setting – as well as the likelihood of risk. For example, this OEM considered a hospital environment with a number of different infrastructure layers to navigate. In these types of scenarios, policies must be followed even as they vary from facility to facility. In some cases, security protocols may not even allow an IoT-enabled system to function as a connected device; early discussion of these risks and limitations is critical to a balanced and successful support strategy.

Prioritizing lifecycle for a healthy competitive edge

Reliable, long-term performance is crucial in medical equipment design. Nothing is more important to patients than acquiring reliable access to lifesaving treatment. And nothing is more powerful in establishing OEM leadership than creating a reputation for longevity of system performance. For greater insight on how Dedicated Computing is enabling the competitive vision and strategy of global healthcare OEMs, request a meeting with an engineer here.

Understanding Cloud-Based Visual System Architectures

Written by: Jeanette Ling

Understanding Cloud-Based Visual System Architectures

Click image to download the Understanding Cloud-Based Visual System Architectures white paper

The Government’s “Cloud First” policy of 2011 set an accelerated course of government technology migration to cloud resources. The benefits of cloud services and infrastructure are appealing for use in simulation and training for many reasons, including the ability to provide point-of-need (PoN) simulation, freedom from hardware maintenance and upgrades, reduction of capital expenditure and hardware footprint, and practically limitless resources that allow ease of scalability. Evaluation of the fitness of visual system service for migration to the cloud as per the cloud-first guidance of readiness and value is highly dependent on the intended use case and architecture of a cloud-based simulator.

While attractive in concept, serious limitations in training quality and effectiveness can exist depending on the implementation strategy of a cloud-based visual system. This paper explores the technical challenges and functional ramifications of distributing visual system components across the cloud compared to on-premises resources.

Topics include: Latency, performance, distributed visual system architectures, latency tolerance of basic visual system components, and edge device computing.

A wide spectrum of use cases exist within the simulation and training realm, and cloud-based visual systems must provide a flexible and adaptable hybrid cloud architecture to achieve required goals across very diverse training needs and physical infrastructure.

To read the full white paper CLICK HERE

About the author

Jeanette Ling is a Principal Software Engineer in the Visual Systems group of Rockwell Collins with 30 years of experience in the industry. Her career has focused on personal computer (PC)-based visual systems that use consumer-off-the-shelf (COTS) graphics cards, and includes pioneering work on some of the first true 3D graphics cards available for PCs as an engineer with Evans & Sutherland. Ms. Ling has held primary engineering roles in producing visual systems for key military programs that span the range from fast-jet to ground vehicles, including full mission simulator (FMS) dome systems for the F-35 Joint Strike Fighter (JSF), helicopter simulators for Aviation Combined Arms Tactical Trainer (AVCATT), and ground warfare training systems for Close Combat Tactical Trainer (CCTT). Ms. Ling holds a B.S. in Computer Science and has a patent pending related to visual system render performance improvements.

To stay up to date with all the latest Dedicated Computing content, stop by the Dedicated Computing Library to read additional white papers.


Storage at the Edge Competes on Cost and Complexity

In part one of this blog series, we suggested there are scenarios where storage in close proximity to compute systems offered advantages over cloud options.

It certainly is cloudy. That’s the takeaway from RightScale’s 2018 Annual State of the Cloud Report.
• “96% of Respondents Use Cloud”
• “81% of enterprises have a multi-cloud strategy”
• “Organizations Leverage Almost 5 Clouds”

High-performance storage close to the compute source is not only relevant but also much less complex and costly than it once was, thanks in large part to the emergence of software-defined storage. Where cloud technologies rely on virtualized platforms, software-defined advancements allow optimized, scalable storage solutions that offer accessibility, control, data ownership, security, and more.

So what is software-defined storage? In the simplest terms, software-defined storage is a layer of abstraction that hides the complexity of the underlying compute, storage, and in some cases networking technologies. It’s a viable option, as organizations continue to express concerns over data security, leaks, capabilities, and capacity of cloud-based options.

The trend that follows is “software-defined everything,” including software-defined networking or software-defined virtual function. Hyperconvergence is next, which is a strategy that brings together infrastructure components such as compute, storage, virtualization, networking, and bandwidth onto a single platform and defines it in a software context.

For more insight, contact the team at Dedicated Computing to learn more about software-defined storage.

Engineering a Future: Tips for Creating a Career Path in Technology

Engineering is everywhere in our society – it’s a versatile career choice that makes a difference in the world. Students who have committed to this path might be wondering how to get started in their careers, or even how to focus their field of study within a vast array of options. Newly employed engineers may question how to design a path forward, even as they focus on their day-to-day job roles. These issues are relevant for anyone designing a future for themselves in the field of engineering. With some shared insight and common sense tips, you can better refine your interests and be proactive in developing a fruitful career path.


Engineering school.jpgTypically, if you attend a four-year university with an engineering program recognized by ABET (Accreditation Board for Engineering and Technology), your early years include classes such as physics and chemistry. Try to weave in a variety of engineering introduction courses as well. While your first instinct as a student might be to avoid classes of indirect interest, it is wise to invest time in getting a taste of the real differences between fields of engineering study.

Institutions such as MSOE (Milwaukee School of Engineering) do a great job of developing curriculum that allows student to experience entry-level instruction in a range of engineering disciplines without slowing down progress toward a chosen degree. These opportunities can vary greatly from college to college, so take the initiative to go over course selection before locking into a specific university and be sure to capitalize on academic advisement at every step.


Internships and co-ops are critical in distinguishing yourself among the crowd. These real-world experiences can also help further refine your direction in terms of choosing a profession. For example, maybe math has always called to you, but an ‘on-the-job’ experience reveals a greater interest in programming. Taking on outside activities of your own can make a difference as well, for example a project like building a remote-controlled car from the ground up. Develop the design, create the circuit board – these types of activities show you are an engineer at your core. Employers love to see that you love to engineer.

As a student, cover the basics. Carry your resume. When business leaders are on campus, stop by the booth or classroom. They are there to connect, so ask a few questions and take a business card. When more structured settings are offered, participate. For example, several times during the school year MSOE features a local technology business at a hosted dinner event. Embrace the presentation and the opportunity to connect in a mixer setting. Go to the career fairs, even if you’re a freshman. Students can never have too much experience interfacing with future employers. Join the student chapters of professional organizations such as IEEE (Institute of Electrical and Electronics Engineers) and ACM (Association for Computing Machinery). Besides looking good on a resume, these groups connect students with people and information.


Gaining technology experience is another top student goal. MSOE’s software development lab provides an example of how real-world experience can be gained in a classroom setting. Juniors have access to this year-long program – students are teamed up in small groups and matched with local businesses who volunteer to participate at a high level. Each team owns responsibility for development of a product, while the business contact becomes a leader and mentor throughout the process.

Experience here goes beyond development of the actual software, and students get an excellent introduction for how to demo software to a manager. Feedback is typically more critical and in-depth because it comes directly from a business leader accustomed to caring about a product’s level of perfection. Learning how to deliver and present a finished product is an invaluable experience for students preparing to step into the professional world.


Learn more about a career with Dedicated Computing here.  Follow us on LinkedIn and Twitter for regular job posts.  To connect with members of Dedicated hiring team, contact us now, or call 877-333-4848.