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NCEES-FE NCEES - FE Civil Engineering 2023 techniques |

NCEES-FE techniques - NCEES - FE Civil Engineering 2023 Updated: 2024 NCEES-FE Brain Dumps with Real Questions
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NCEES-FE NCEES - FE Civil Engineering 2023

The FE exam includes 110-questions.

The exam appointment time is 6 hours long and includes

Nondisclosure agreement (2 minutes)Tutorial (8 minutes)

Exam (5 hours and 20 minutes)Scheduled break (25 minutes)

The Fundamentals of Engineering (FE) exam is generally your first step in the process to becoming a professional licensed engineer (P.E.). It is designed for recent graduates and students who are close to finishing an undergraduate engineering degree from an EAC/ABET-accredited program. The FE exam is a computer-based exam administered year-round at NCEES-approved Pearson VUE test centers.

Reviewing the FE exam specifications, fees, and requirementsReading the reference materialsUnderstanding scoring and reportingViewing the most up-to-date FE exam pass rates
A $175 exam fee is payable directly to NCEES. Some licensing boards may require you to file a separate application and pay an application fee as part of the approval process to qualify you for a seat for an NCEES exam. Your licensing board may have additional requirements. Special accommodations are available for examinees who meet certain eligibility criteria and sufficiently document their request.

1. Mathematics

A. Analytic geometry

B. Calculus

C. Roots of equations

D. Vector analysis

2. Probability and Statistics

A. Measures of central tendencies and dispersions (e.g., mean, mode, standard deviation)

B. Estimation for a single mean (e.g., point, confidence intervals)

C. Regression and curve fitting

D. Expected value (weighted average) in decision making

3. Computational Tools

A. Spreadsheet computations

B. Structured programming (e.g., if-then, loops, macros)

4. Ethics and Professional Practice

A. Codes of ethics (professional and technical societies)

B. Professional liability

C. Licensure

D. Sustainability and sustainable design

E. Professional skills (e.g., public policy, management, and business)

F. Contracts and contract law

5. Engineering Economics

A. Discounted cash flow (e.g., equivalence, PW, equivalent annual worth, FW, rate of return)

B. Cost (e.g., incremental, average, sunk, estimating)

C. Analyses (e.g., breakeven, benefit-cost, life cycle)

D. Uncertainty (e.g., expected value and risk)

6. Statics

A. Resultants of force systems

B. Equivalent force systems

C. Equilibrium of rigid bodies

D. Frames and trusses

E. Centroid of area

F. Area moments of inertia

G. Static friction

7. Dynamics

A. Kinematics (e.g., particles and rigid bodies)

B. Mass moments of inertia

C. Force acceleration (e.g., particles and rigid bodies)

D. Impulse momentum (e.g., particles and rigid bodies)

E. Work, energy, and power (e.g., particles and rigid bodies)

8. Mechanics of Materials

A. Shear and moment diagrams

B. Stresses and strains (e.g., axial, torsion, bending, shear, thermal)

C. Deformations (e.g., axial, torsion, bending, thermal)

D. Combined stresses

E. Principal stresses

F. Mohr's circle

G. Column analysis (e.g., buckling, boundary conditions)

H. Composite sections

I. Elastic and plastic deformations

J. Stress-strain diagrams

9. Materials

A. Mix design (e.g., concrete and asphalt)

B. Test methods and specifications (e.g., steel, concrete, aggregates, asphalt, wood)

C. Physical and mechanical properties of concrete, ferrous and nonferrous metals, masonry, wood, engineered materials (e.g., FRP, laminated lumber, wood/plastic composites), and asphalt

10. Fluid Mechanics

A. Flow measurement

B. Fluid properties

C. Fluid statics

D. Energy, impulse, and momentum equations

11. Hydraulics and Hydrologic Systems

A. Basic hydrology (e.g., infiltration, rainfall, runoff, detention, flood flows, watersheds)

B. Basic hydraulics (e.g., Manning equation, Bernoulli theorem, open-channel flow, pipe flow)

C. Pumping systems (water and wastewater)

D. Water distribution systems

E. Reservoirs (e.g., dams, routing, spillways)

F. Groundwater (e.g., flow, wells, drawdown)

G. Storm sewer collection systems

12. Structural Analysis

A. Analysis of forces in statically determinant beams, trusses, and frames

B. Deflection of statically determinant beams, trusses, and frames

C. Structural determinacy and stability analysis of beams, trusses, and frames

D. Loads and load paths (e.g., dead, live, lateral, influence lines and moving loads, tributary areas)

E. Elementary statically indeterminate structures

13. Structural Design

A. Design of steel components (e.g., codes and design philosophies, beams, columns, beam-columns, tension members, connections)

B. Design of reinforced concrete components (e.g., codes and design philosophies, beams, slabs, columns, walls, footings)

14. Geotechnical Engineering

A. Geology

B. Index properties and soil classifications

C. Phase relations (air-water-solid)

D. Laboratory and field tests

E. Effective stress (buoyancy)

F. Stability of retaining walls (e.g., active pressure/passive pressure)

G. Shear strength

H. Bearing capacity (cohesive and noncohesive)

I. Foundation types (e.g., spread footings, deep foundations, wall footings, mats)

J. Consolidation and differential settlement

K. Seepage/flow nets

L. Slope stability (e.g., fills, embankments, cuts, dams)

M. Soil stabilization (e.g., chemical additives, geosynthetics)

N. Drainage systems

O. Erosion control

15. Transportation Engineering

A. Geometric design of streets and highways

B. Geometric design of intersections

C. Pavement system design (e.g., thickness, subgrade, drainage, rehabilitation)

D. Traffic safety

E. Traffic capacity

F. Traffic flow theory

G. Traffic control devices

H. Transportation planning (e.g., travel forecast modeling)

16. Environmental Engineering

A. Water quality (ground and surface)

B. Basic tests (e.g., water, wastewater, air)

C. Environmental regulations

D. Water supply and treatment

E. Wastewater collection and treatment

17. Construction

A. Construction documents

B. Procurement methods (e.g., competitive bid, qualifications-based)

C. Project delivery methods (e.g., design-bid-build, design build, construction management, multiple prime)

D. Construction operations and methods (e.g., lifting, rigging, dewatering and pumping, equipment production, productivity analysis and improvement, temporary erosion control)

E. Project scheduling (e.g., CPM, allocation of resources)

F. Project management (e.g., owner/contractor/client relations)

G. Construction safety

H. Construction estimating

18. Surveying

A. Angles, distances, and trigonometry

B. Area computations

C. Earthwork and volume computations

D. Closure

E. Coordinate systems (e.g., state plane, latitude/longitude)

F. Leveling (e.g., differential, elevations, percent grades)
NCEES - FE Civil Engineering 2023
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NCEES - FE Civil Engineering
Question: 92
A line is measured as 1,200 ft at 98 F. Using a standard tape, what is the true
length of the line?
A. 1,197.70 ft
B. 1,199.77 ft
C. 1200.23 ft
D. 1202.30 ft
Answer: C
The true length of a line that is measured as 1,200 ft at 98F is 1,200.23 using a
standard tape. Solution Correction = (steel tape coefficient of expansion)(outside
temperature standard temperature)(measured length) Correction = (0.00000645 *
1/F) (98F - 68F) (1,200) = +0.23 ft True length = distance + correction True
length= 1,200.00 ft + 0.23 ft = 1,200.23 ft
Question: 93
Which of the following statements expresses Hookes Law of simple harmonic
A. Speed of a wave = frequency x wavelength
B. Spring force = -(spring constant x displacement)
C. Average speed = distance traveled / time of travel
D. None of the above
Answer: B
Hookes Law of simple harmonic motion can be expressed as spring force = -
(spring constant x displacement). Spring force always pushes or pulls a mass
towards its original equilibrium position, and as such, is referred to as a restoring
force. Hookes Law describes the relationship of the restoring force as being
directly proportional to the displacement of the mass.
Question: 94
Which of the following sentences provides an example of effective diction?
A. A good writer will only use big words when necessary.
B. The shrewd author will always endorse himself by providing imposing and
superlative language.
C. As I struggled to carry my instruments across the vast expanse of the project
area, I paused to reflect on the magnificence of the setting sun.
D. All of the above
Answer: A
The sentence A good writer will only use big words when necessary. provides
an example of effective diction. Good writers understand that fancy words are
often distracting and condescending. Avoid using overblown vocabulary unless
you are writing the next Great American novel.
Question: 95
A 2.2 kg object is sliding across a smooth surface. If the net force acting on the
object is 1.6 N to the right, what is the acceleration of the object?
A. -3.52 m/s2to the left
B. -0.73 m/s2to the right
C. 3.52 m/s2to the left
D. 0.73 m/s2to the right
Answer: D
The acceleration of a 2.2 kg object sliding across a smooth surface with a net
force of 1.6 N to the right acting on it is 0.73 m/s2 to the right. Solution Use
Newtons Second Law S F = ma Where S F = net force = 1.6 N to the right m =
mass = 2.2 kg a = acceleration S F = ma, so a = S F/m a = 1.6 N / 2.2 kg 1 N = 1
kgm/s2, so a = (1.6 kg m/s2)/2.2 kg = 0.73 m/s2
Question: 96
Which of the following type of error is least likely to affect the measured value
for a horizontal angle?
A. Instrument
B. Environment
C. Terrain
D. Personnel
Answer: C
Terrain errors are the least likely type of errors affecting the measured value for a
horizontal angle when compared to the other listed error types. The impact of
instrument errors can be mitigated by properly adjusting the devices used and by
using systematic observation procedures. Environmental errors affecting
horizontal angle measurement may be due to temperature differentials and the
horizontal refraction of the line of sight. Personnel errors can be prevented
through proper training and following standard procedures.
Question: 97
Which of the following scenarios can be modeled mathematically?
A. Flow of water through a watershed
B. Migration of a pollutant through a groundwater aquifer
C. Dispersion of particulates through the air
D. All of the above
Answer: D
All of the scenarios listed can be modeled mathematically. With technology
available today, engineers and planners are able to model the flow of water,
migration of pollutants, and dispersion of particulates through air. Mathematical
models can be built using specialized computer software linked to geographic
information systems and real-time sampling equipment. These models can be
used for predictive forecasting, planning, and mitigation purposes.
Question: 98
For which of the following is a Digital Terrain Modeling (DTM) application most
A. Planning flight lines
B. Generating high quality cartographic contours
C. Setting slope stakes
D. All of the above
Answer: B
Of the answers listed, Digital Terrain Modeling is most useful for generating high
quality cartographic contours. DTMs are digital representations of a portion of the
Earths surface. The input data, data models, and algorithms required to generate
a digital model of a terrains surface are significantly different from those needed
to represent planimetric data. For example, most DTM data is derived from a
combination of ground surveys, photogrammetric resources, digitized
cartographic data, and altimetry data.
Question: 99
Cross-section measurements were taken at 100 ft intervals along a proposed
roadway alignment. The cross-sectional areas of the material above the proposed
roadway elevation shown in two consecutive sections were found to be 420 sqft
and 332 sq ft. What is the approximate volume (in cubic yards) of the material
that will need to be excavated between the two cross-sections?
A. 1,393
B. 12,640
C. 37,600
D. None of the above
Answer: A
The approximate volume of the material that will need to be excavated between
the two cross-sections is 1,393 cubic yards. Solution Use the volume equation
averaged over the two cross-sections v = L (A1 + A2)/2 Where L = length = 100
ft A1 = 420 sqft and A2 = 332 sqft V = (100 ft) (420 ft2 + 332ft2) / 2 = 37,600 ft3
= 37,600 ft3 x (1 cubic yard/ 27 ft3) = 1,393 cubic yards (approximate)
Question: 100
What is the sum of the exterior angles of an eight-sided traverse?
A. 180
B. 1,440
C. 1,800
D. None of the above
Answer: C
Use the sum of exterior angles of a polygon equation: S = (n+2) x 180 Where n =
8 S = (8+2) x 180 = 1,800
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NCEES Engineering techniques - BingNews Search results NCEES Engineering techniques - BingNews Professional Engineering Exam

As a licensed Professional Engineer, or PE, you can expect many more benefits when compared to other engineers; most employers offer higher salaries and greater opportunities for advancement to PE's. Only PE's can consult in private practice, and seal company documents to be sent to the government. PEs also have more credibility as expert witnesses in court than most engineers.

Steps in obtaining a PE license:

  • Pass the Fundamentals of Engineering (FE) Exam.
  • Graduate with a bachelor's degree from an ABET accredited engineering curriculum (all Engineering curricula at Michigan Tech except Robotics Engineering).
  • Gain four years of engineering experience under the supervision of a registered professional engineer.
  • Pass the Principles and Practice of Engineering (PE) Exam.

During your senior year you should take the Fundamentals of Engineering (FE) exam, which is required prior to sitting for the Professional Engineers (PE) Exam. Some requirements vary by state.

Sun, 04 Sep 2011 15:27:00 -0500 en text/html
Neural Engineering and Rehabilitation

Neural engineering and rehabilitation research applies neuroscience and engineering methods to analyze central and peripheral nervous system function and to design clinical solutions for neurological disorders or injury. Through the application of basic science and engineering techniques, neural engineers develop methods to analyze and control the nervous system and associated organ systems. 

Research in neural engineering at Case Western Reserve University is bolstered through collaboration and proximity to world-class healthcare facilities. Faculty, research associates and students in the Department of Biomedical Engineering work in three national centers of education and research in neural engineering and rehabilitation. Our research teams collaborate with four local major medical facilities: MetroHealth Medical Center, University Hospitals Case Medical Center, Cleveland Clinic and the Louis Stokes Cleveland VA Medical Center. 

The Department of Biomedical Engineering has ongoing research and applications in neural engineering and rehabilitation in several areas that allow our team to move ideas from basic science through experimental testing to clinical deployment. These areas include:

Neuromodulation – Clinical and experimental technologies for treating and managing consequences of stroke, epilepsy, pain, spinal cord injury, genitourinary function, movement disorders, autonomic functions and psychiatric disorders.

Prosthetics and Orthotics – Implanted devices to directly communicate with the  nervous system functions for the control of assistive technologies, as well as provide sensory feedback in amputee prosthetics.

Neural Interfaces – Design of both stimulating and recording electrode technologies for interfacing with the nervous system. In the central nervous system, research is focused on brain computer interfaces and deep brain stimulation to restore function in patients with neurological disorders, such as paralysis. In the peripheral nervous system, novel interfacing technology targets small somatic and autonomic nerves.

Neural and Biomechanical Computation – The use of computational models to simulate the dynamics of the nervous system and musculoskeletal system during movement in order to gain insight into the underlying neural and biomechanical processes. These models are used to develop new treatments and interventions for nervous system disorders disorders, as well as to design more effective prosthetics and other assistive technologies.

Computational tools are also applied to develop and understand neural circuit function and dynamics.

Thu, 17 Aug 2023 05:51:00 -0500 en text/html
Flipping The Script On AI By Using Prompt Engineering Techniques To Have Generative AI Ask You Questions And Get Even Better Answers Out Of The AI

Flipping the script.

This well-known catchphrase refers to turning things on their head and doing nearly the opposite of what is normally done. Up becomes down, down becomes up. There can be lots of good reasons to do this. Maybe the approach will reveal new facets and spark a fresh viewpoint on the world. It could also be something that you do on a lark, just for kicks.

The beauty of flipping the script is that it can have profound outcomes and tremendous possibilities. It all depends on what you are trying to accomplish. Plus, knowing how to best carry out a flip-the-script endeavor is a vital consideration too. You can easily mess up and get nothing in return.

All of this comes to the fore for those using generative AI and wanting to make sure that they are leveraging the latest and boldest of prompt engineering capabilities and techniques.

In today’s column, I am continuing my ongoing series about advances in prompt engineering and will be taking you through a technique known as flipped interaction. Here’s the deal. You flip the script, as it were, getting generative AI to ask you questions rather than having you ask generative AI your questions.

That might seem at first glance rather surprising, and perhaps even has a hint of being nonsensical. We are all accustomed to the idea that you enter prompts to generative AI that contains burning questions you have about the world. The generative AI does its computational and mathematical machinations and produces a generated answer or response. This is the standard way of doing things.

Think of it this way:

  • User enters a prompt that contains a question, and generative AI generates an answer or response.

Boom, rinse and repeat.

The flipped interaction urges you to try doing this:

  • Generative AI generates a question shown to you, and you enter a response or answer to the AI-indicated question.

Is that nutty?

Or is it perhaps ingenious?

I’ll explain that it can be ingenious for a variety of stellar reasons.

You are not alone if you’ve not tried this. Few people who use generative AI seem to realize that this prompting strategy has true value. I would dare say that most people probably have never even heard of the approach. For those people who have perchance seen or read something about the flipped interactions method, they likely got a mere morsel of what this is all about. The typical depiction gives you a paragraph or two. You are otherwise left to your own devices to figure out what flipped interaction can do and how it earns a prized spot in your plethora of prompt engineering-worthy skills.

I want to correct the slew of misimpressions about the flipped interaction method. I also want to showcase the immense potential that flipped interaction has for your daily use of generative AI. We will closely look at the tradeoffs and consider what contexts warrant a flip-the-script prompting strategy. This will require getting into the weeds and making sure you are fully aware of the ins and outs of employing flipped interaction in generative AI.

Before I dive into this in-depth exploration, let’s make sure we are all on the same page when it comes to the keystones of prompt engineering and generative AI. Doing so will put us all on an even keel.

Prompt Engineering Is A Cornerstone For Generative AI

As a quick backgrounder, prompt engineering or also referred to as prompt design is a rapidly evolving realm and is vital to effectively and efficiently using generative AI or the use of large language models (LLMs). Anyone using generative AI such as the widely and wildly popular ChatGPT by AI maker OpenAI, or akin AI such as GPT-4 (OpenAI), Bard (Google), Claude 2 (Anthropic), etc. ought to be paying close attention to the latest innovations for crafting viable and pragmatic prompts.

For those of you interested in prompt engineering or prompt design, I’ve been doing an ongoing series of insightful looks at the latest in this expanding and evolving realm, including this coverage:

  • (1) Practical use of imperfect prompts toward devising superb prompts (see the link here).
  • (2) Use of persistent context or custom instructions for prompt priming (see the link here).
  • (3) Leveraging multi-personas in generative AI via shrewd prompting (see the link here).
  • (4) Advent of using prompts to invoke chain-of-thought reasoning (see the link here).
  • (5) Use of prompt engineering for domain savviness via in-model learning and vector databases (see the link here).
  • (6) Augmenting the use of chain-of-thought by leveraging factored decomposition (see the link here).
  • (7) Making use of the newly emerging skeleton-of-thought approach for prompt engineering (see the link here).
  • (8) Determining when to best use the show-me versus tell-me prompting strategy (see the link here).
  • (9) Gradual emergence of the mega-personas approach that entails scaling up the multi-personas to new heights (see the link here).
  • (10) Discovering the hidden role of certainty and uncertainty within generative AI and using advanced prompt engineering techniques accordingly (see the link here).
  • (11) Vagueness is often shunned when using generative AI but it turns out that vagueness is a useful prompt engineering tool (see the link here).
  • (12) Prompt engineering frameworks or catalogs can really boost your prompting skills and especially bring you up to speed on the best prompt patterns to utilize (see the link here).
  • (13) Additional coverage including the use of macros and the astute use of end-goal planning when using generative AI (see the link here).

Anyone stridently interested in prompt engineering and improving their results when using generative AI ought to be familiar with those notable techniques.

Moving on, here’s a bold statement that pretty much has become a veritable golden rule these days:

  • The use of generative AI can altogether succeed or fail based on the prompt that you enter.

If you provide a prompt that is poorly composed, the odds are that the generative AI will wander all over the map and you won’t get anything demonstrative related to your inquiry. Being demonstrably specific can be advantageous, but even that can confound or otherwise fail to get you the results you are seeking. A wide variety of cheat sheets and training courses for suitable ways to compose and utilize prompts has been rapidly entering the marketplace to try and help people leverage generative AI soundly. In addition, add-ons to generative AI have been devised to aid you when trying to come up with prudent prompts, see my coverage at the link here.

AI Ethics and AI Law also stridently enter into the prompt engineering domain. For example, whatever prompt you opt to compose can directly or inadvertently elicit or foster the potential of generative AI to produce essays and interactions that imbue untoward biases, errors, falsehoods, glitches, and even so-called AI hallucinations (I do not favor the catchphrase of AI hallucinations, though it has admittedly tremendous stickiness in the media; here’s my take on AI hallucinations at the link here).

There is also a marked chance that we will ultimately see lawmakers come to the fore on these matters, possibly devising and putting in place new laws or regulations to try and scope and curtail misuses of generative AI. Regarding prompt engineering, there are likely going to be heated debates over putting boundaries around the kinds of prompts you can use. This might include requiring AI makers to filter and prevent certain presumed inappropriate or unsuitable prompts, a cringe-worthy issue for some that borders on free speech considerations. For my ongoing coverage of these types of AI Ethics and AI Law issues, see the link here and the link here, just to name a few.

With the above as an overarching perspective, we are ready to jump into today’s discussion.

The Purpose Of Flipped Interaction For Generative AI

The simplest way to think about flipped interactions is that you merely tell the generative AI to start asking you questions. Voila, you have flipped the script.

Why do something that seems entirely counterintuitive?

It does strike one as a puzzling head-scratcher.

We conventionally come to use generative AI as a kind of oracle that can spew forth impressive answers. This is certainly not because the AI app is sentient. It is because the generative AI has been vastly data-trained on human written text and garnered a huge pattern-based mimicry of what humans say. The expectation is that all of that mathematical and computational pattern matching will undoubtedly tap into human writings in a manner that can reveal interesting and insightful generated responses.

The logic for why you would use a flipped interaction is actually quite straightforward if you are willing to deliver the curiosity a moment of hurry reflection.

Here are my six major reasons that I expound upon when conducting workshops on the best in prompt engineering:

  • (1) Inform or data-train the generative AI
  • (2) Discover what kinds of questions arise in a given context
  • (3) Learn from the very act of being questioned by the AI
  • (4) Allow yourself intentionally to be tested and possibly scored
  • (5) Do this as a game or maybe just for plain fun
  • (6) Other bona fide reasons

Each of those reasons for invoking a flipped interaction deserves a brief explanation. I will do so, one at a time.

(1) Inform or data-train the generative AI

The foremost reason to flip the script or do a flipped interaction with generative AI is to inform the AI or do a bit of on-the-fly data training into the AI.

Some refer to this as “teaching” generative AI about new things that the AI app hasn’t necessarily already encountered when it was initially data trained. I have an unsettling pit in my stomach when people say that they are “teaching” generative AI, due to the potential anthropomorphizing of the AI.

You see, we usually teach sentient beings such as fellow humans and thus associate teaching with doing so for a sentient being. The problem with claiming you are teaching generative AI is that this implicitly comes across as though the AI is presumably sentient. Anyway, despite that reservation, by and large, the AI community and those outside the AI community tend to proclaim that using a flipped interaction is a form of teaching an AI app. I go along with this though my teeth are gritted.

Back to the matter at hand.

Suppose you know a lot about the dodo bird. You are a world expert on the dodo. That is about the only bird you know. While using generative AI, you discover that upon asking the AI app about the dodo, you get a generated response from the AI that it doesn’t have much if anything to indicate about the dodo. Turns out that the initial data training did not contain substantive materials about the dodo. Ergo, the generative AI has sparse content that was pattern-matched on the subject of the dodo.

You are chagrined at this. First, you believe it is a travesty that generative AI doesn’t have an in-depth capability about the dodo. Everyone and everything need to know about the dodo. Secondly, you wanted to have generative AI compare and contrast the dodo to other birds of a more common nature. This comparison cannot be undertaken because the generative AI is pretty much empty when it comes to the wonderful and greatly prized dodo.

What can you do about this dilemma and worrisome situation?

Easy-peasy is that you can inform or data train the generative AI about the dodo. After doing so, you can then switch into the usual mode of asking the generative AI about things such as comparing the dodo to other more common birds.

You decide to momentarily flip the script.

One path would be to have you type in all the fascinating and teeny tiny details about the dodo that you might have in your mind. You might do this as one gigantic and lengthy prompt. A brain dump for the generative AI.

On the other hand, this might not be especially productive. Maybe a better approach would be to get the generative AI to ask you a series of questions about the dodo. This is helpful to you since you can then merely answer the generated questions. This might also be better for the generative AI in that rather than trying to flood the AI with a bunch of random stuff about the dodo, the AI will be directing step-by-step as to what the AI seemingly needs to be data trained on about dodo birds.

You invoke the flipped interaction.

Doing so is extremely easy. You could enter a prompt that tells the AI app to start asking you questions about dodo birds. The next thing that will happen is that the AI app will pepper you with questions.

I ought to forewarn you that there is a bit more involved in that you should also clue in the AI about a variety of other particulars associated with the Q&A that you want it to undertake. We’ll get to that in the next section herein.

Meanwhile, let’s consider the additional reasons for using a flipped interaction.

(2) Discover what kinds of questions arise in a given context

Discovering the kinds of questions that arise in a given context is another great reason to use the flipped interaction technique of prompting.

Imagine that you are curious about what types of questions might be pertinent to a particular subject or subject area. For example, what kinds of questions usually arise when trying to fix the plumbing in your house? You might have at times gone to the Internet to see what questions people ask when they seek to fix their plumbing. Those questions are a handy-dandy way for you to discover what you likely might need to know or what might suddenly arise while fixing your plumbing.

You can merely tell the generative AI to hit you with the most commonly asked questions about fixing the plumbing in a house. This can be a list that the generative AI generates.

Another akin approach would be to have the generative AI ask you those questions, one at a time. This might prod you to think more closely about the matter at hand.

(3) Learn from the very act of being questioned by the AI

You can potentially learn something by the act of being questioned.

Let’s continue my above description about fixing your plumbing. You get asked a series of questions by the generative AI. For example, the AI asks you if you have the right plumbing tools. Oops, you realize that you assumed that your everyday toolbox would have all the tools you need. The generative AI has sparked your realization that there are specialized tools that plumbers use. You make a note to go to the hardware store and get the needed tools.

Getting asked a question has allowed you to learn something that otherwise you didn’t know or hadn’t considered.

(4) Allow yourself intentionally to be tested and possibly scored

I’ve predicted that people are going to eventually realize that they can use generative AI as a kind of test-taking mechanism, see my discussion at the link here and the link here.

With the flipped interaction, you tell the generative AI to test you on a particular subject or subject of interest. The AI app will ask you a series of questions. If you don’t want to be scored or assessed, you can just say that the AI should not do any rating of your answers (the usual default is that it won’t, thus, you are more likely to need to explicitly say you want to be scored, if that’s what you want).

Suppose you are in college and have a test coming up about the life of Abraham Lincoln. You have studied a bunch of written materials about his life. Are you ready for the test that you’ll be taking tomorrow? All you need to do is flip the script and tell generative AI to ask you questions about Abraham Lincoln. You can do this as much as you like, over and over, until you feel that you are adequately prepared for the test you’ll be taking.

A few quick caveats that I’ll cover more later on herein. It could be that the questions about Abraham Lincoln do not end up covering whatever the teacher comes up with. Maybe the generative AI wasn’t data-trained on certain aspects of Lincoln’s life. You cannot assume that the generative AI is all-encompassing. It isn’t. Furthermore, and quite bothersome, the generative AI might contain errors or falsehoods about Lincoln, and possibly make up stuff or do a so-called AI hallucination about Lincoln. The issue here is that when you see such a question, you might not realize that the question is erroneous. Sadly, you believe the question contains truths and you memorize facts about Lincoln that are incorrect.

Be careful and mindful when using generative AI, including when doing a flipped interaction.

(5) Do this as a game or maybe just for plain fun

Some people enjoy using generative AI for playful purposes. I’ve discussed in my columns that you might tell the AI app to pretend to be a famous character in a play or novel (have it mimic a persona), and then you joyfully interact with that character (see my analysis of this trend, at the link here).

You can use the flipped interaction for game-related purposes or just for plain fun.

Imagine that you want to play a game with the AI app and you are going to make up the rules of the game. This is not checkers, chess, or any conventionally known game. It is a game of your own devising.

How can you get the AI app up-to-speed about your made-up game?

One approach would be to tell the AI that you are going to define a game and that you have a bunch of rules that the AI needs to be data-trained on. You then instruct the AI app to ask you questions about the game. This is similar to my earlier point that you can do data training on generative AI while on the fly.

Similarly, rather than making up a game, you could tell the generative AI to start asking you questions about Abraham Lincoln. You are doing so merely for the fun of it. You aren’t in school, and you aren’t trying to prepare for a test. Instead, this is something being done for simple entertainment.

(6) Other bona fide reasons

A variety of other bona fide reasons to use the flipped interaction prompting technique are floating around. I’ve given you the top ones that are most often identified.

I’m sure you can think of more.

We need to move on and cover the crucial foundations of this promising and valuable technique.

The Foundations Of Employing The Flipped Interaction Technique

I trust that you are convinced that there are some legitimate reasons to consider using the flipped interaction prompting technique. Great, since that means we can dive deeper into the foundations underlying the technique. I most assuredly hope that you are tempted to use the flip-the-script and are now waiting with bated breath to know how to do so.

Fasten your seatbelts and get yourself ready.

Let’s envision that you tell generative AI to start asking you questions.

If that’s all that you stated, there is a tremendous amount of ambiguity at that juncture. What is the subject matter or subject underlying the questions that you want to be asked? How many questions are to be asked? Do you have a preference as to the style or phrasing of the questions? Should the answers you are giving be scored or rated?

On and on the litany of open issues goes.

I would assume that at least the idea of stating the subject matter would normally be at the top of your mind for anyone seeking to do a flipped interaction. Indeed, that is probably the shortest and most minimal of ways to use the flipped interaction. You could merely say that you want to be asked questions about dodo birds. Period, end of story.

The generative AI would likely proceed.

That being said, since generative AI is like a box of chocolates, you never know what you might get. The questions probably will be about dodo birds, though maybe not in the direction you had in mind. Perhaps the AI will ask you questions about whether dodo birds can fly a plane or pilot a rocket ship. I doubt those are the questions you assumed you would be asked.

Okay, we’ve now identified that you can invoke a flipped interaction by the simple act of telling generative AI to start asking you questions. But, if you want this to be productive, you ought to sensibly specify more about what you want to happen.

You can provide a speck of guidance to the AI or you can provide a bushel of guidance to the AI. It’s up to you. Some people aren’t excited about having to specify a bunch of stuff. They just want to get on with the show. Others are more studious and believe that by being detailed in their guidance the effort will turn out more beneficial.

I might also add that you can either specify upfront when you initiate a flipped interaction the details of what you want to do, or you can sprinkle the nuances as you go along. The beneficial thing about generative AI is that you can interactively do things. You don’t necessarily need to disgorge an entire missive at the get-go. You can do as you proceed. For myself, I admit that I lean toward trying to specify as much as possible at the get-go when invoking a flipped interaction. This seems sensible to me. I then will adjust or fine-tune as the Q&A proceeds.

Please use the flipped interaction techniques in whatever style befits your personal preferences.

Here are my twelve foundational recommended indicators that you should consider and possibly convey to the generative AI when invoking the flipped interaction prompting strategy:

  • (1) Tell AI that a flipped interaction is going to be undertaken and either set up the rules or let AI do so by default.
  • (2) Indicate the number of questions to be asked by the AI and when the Q&A is to be initiated.
  • (3) Specify the reason or basis for why the questioning is taking place.
  • (4) Mention the types of questions to be asked and depict the style of questioning involved.
  • (5) Describe the Q&A sequence as to one at a time or some other preferred tempo.
  • (6) Tell the AI what to do with your answers to the questions.
  • (7) Establish whether your answers can be challenged by the AI.
  • (8) Say whether you are possibly going to challenge the questions presented by the AI.
  • (9) Identify a pausing signal so that you can momentarily pause the Q&A.
  • (10) Indicate if you want the AI to echo back your answers and also whether an undo is possible.
  • (11) State a trigger that you will use to end the questioning and also note what should happen afterward of the Q&A.
  • (12) Perform your own follow-on steps such as flipping the flipped interaction back into a conventional mode of you asking questions and the AI answering your questions, etc.

I’ll quickly go over those with you.

Rather than elaborating on each one, and due to space limitations herein, I’ll cover them collectively and deliver just distinct highlights.

First, you need to tell the AI app that you want to flip the interaction. This is easily done. All you need to do is indicate in a prompt that you want the generative AI to start asking you questions. Voila, you are ready to roll. There is though more to the invoking of a flipped interaction. I had mentioned earlier that just saying you want to be questioned is not really sufficient since the AI app won’t be informed as to what you want to be asked about.

Your best bet is to also indicate the rules of the road about the Q&A. One key aspect will be how many questions the AI app ought to ask you. Perhaps you already know how many questions will be required and thus you can deliver an exact count such as five questions or twenty questions. Much of the time you probably won’t in advance know how many questions are going to be needed. You can ergo make the Q&A more open-ended and let the AI app keep asking you questions until you tell it to stop doing so.

Another aspect involves indicating when the Q&A should get underway. The default assumption usually is that you say that you want the questioning to get started and it happens right away. Sometimes you might want to momentarily delay the Q&A and do some other preparatory actions with the generative AI before getting into the questioning mode.

There is no doubt that the most significant element to specify is the subject or subject matter underlying the Q&A endeavor. You should set the context for the questioning. This can range from being extremely specific such as the eating habits of the dodo bird or might be more wide-ranging such as the overall meaning of life.

The tone of the questions can vary quite a bit. Generative AI is usually already pre-tuned to ask questions in a civil manner. If you want the questions to be harder-hitting or have some particular style, make sure to mention this when you indicate that a Q&A is to take place. The AI app will also typically default to asking you one question at a time. This is not a sure bet. If you want the Q&A on a one-at-a-time basis, say so. If you want the Q&A to consist of two questions at a time or maybe a slew of questions all at once, you can get that to happen by saying so.

When you deliver your answers during the Q&A, you don’t know that the AI app will necessarily be attempting to data-train on whatever you have to say. The usual default is that the generative AI will in fact be tracking your answers and be ready to at some point regurgitate or respond accordingly. I like to make this an apparent consideration and normally explicitly tell the AI app to pay attention.

A less often considered facet is whether you can challenge the questions that the AI is giving you. The typical default is that you can do so. If you get a question that you think is off-target, provide a reply saying so. I like to make sure that the AI app is ready for such challenges and therefore tend to mention as such when I initiate the flipped interaction. On a related matter, you can say whether the AI is to challenge your answers. Ordinarily, the AI won’t challenge your answers and will accept them as given. You can tell the generative AI to balk at answers that seem awry. One potential irritant is that the AI app can become ferociously antagonistic and you won’t likely enjoy the Q&A process (you’ll need to tell the AI app to tone things down if that happens).

There are some additional considerations to keep in mind. You might want to temporarily pause the Q&A. This can be done at any time by merely stating as such when responding to a question. You can also establish upfront a pause signal such as a word or catchphrase.

Some people prefer to provide their answers and have the AI app proceed immediately to the next question. For me, I like to have the generative AI echo my answers, doing so after each of the posed questions. I do this because there is always that chance that the AI app makes an error, falsehood, AI hallucination, or other mistake when interpreting your answer. I prefer to catch this straightaway and thus usually tell the AI app to echo back my answers after each question.

Suppose you answer a question and then afterward realize that you made a mistake in your answer. You can usually undo an answer by simply saying this when you are answering the next question. On an upfront basis, I sometimes indicate that I might be doing some undo actions, especially if I am unsure of the subject at hand and might be spitballing for my answers.

Finally, you can either end the Q&A by stating as such when you get the next question, or you can beforehand establish a keyword or phrase that will signal you want to stop the Q&A. At that juncture, upon ending the Q&A, it is handy to mention or state again what you want the AI app to do with the answers that you have provided. You can presumably at that point just go back into the conventional mode of asking questions and the AI answering them. I frequently explicitly state that this is going to occur, just to make sure that the AI app doesn’t go off on a tangent and starts suddenly into Q&A mode again.

Flipping out of a flipped interaction is typically done without having to outrightly say so, other than telling the AI to stop the Q&A. For an added measure of reassurance, a few words telling the AI that the Q&A has ended is probably a worthy remark to make.

Example Of Doing A Flipped Interaction

We’ve covered the basics of undertaking a flipped interaction. I would bet that you are eager to see an example.

Wonderful, since I have one ready to show you.

Let’s imagine that I am an expert in underwater basket weaving. Have you ever heard of underwater basket weaving? There is a bit of a humorous undercurrent. One viewpoint is that underwater basket weaving refers to dipping your hands into a pool of water and weaving a basket in that manner. Another more comical variant is that you are fully immersed in water and are doing basket weaving while completely underwater.

The catchphrase referring to underwater basket weaving gradually became a means of suggesting that someone is doing something of a wasteful nature or otherwise doing a task we might consider silly or unnecessary. For example, college students who take a class of a seemingly vacuous nature are said to be learning how to do underwater basket weaving.

For purposes of carrying out a Q&A with generative AI on a flipped interaction basis, I logged into ChatGPT and tried to seriously engage in a discussion about underwater basket weaving. Admittedly, this is a bit tongue-in-cheek. A human might have right away questioned my sincerity. By and large, generative AI will usually let you lead on such aspects and accept that you are serious and that whatever subject you have chosen is equally of a serious nature.

Here we go.

My prompting setup for getting the flipped interaction underway is this:

  • “I am an expert in underwater basket weaving. I want you to ask me questions about underwater basket weaving so that I can share with you the key principles involved. Let's start by you asking me five questions, doing so one question at a time. After you've asked me the five questions and I've answered them, I want you to recap what I've told you. If I want to end the questioning sooner than the five questions I will say so when I am answering a question. Make sure to ask me questions that are pertinent to underwater basket weaving and do so in a polite and collegial manner. Before we begin, confirm that you understand these instructions.”

Notice that I weaved into my prompt the various parameters of the flipped interaction. I didn’t exhaustively cover every possible consideration. I gave just enough that I thought would ensure that the Q&A would proceed sensibly. I gave the subject to be covered, I indicated I wanted to be asked five questions, doing so on a one-at-a-time basis. I also instructed the generative AI to do a recap at the end. I also mentioned that I might end the Q&A sooner than five questions.

ChatGPT generated this response:

  • “Of course, I understand your instructions. I'm looking forward to learning from your expertise in underwater basket weaving. Let's begin with the first question: Could you please explain the specific challenges posed by weaving baskets underwater compared to traditional basket weaving on land?”

We are now off to the races and ChatGPT has asked me the first of the presumed five questions. I had no idea what questions I would be asked, other than that I had specified they were about underwater basket weaving.

My prompt as a reply to the posed AI question was this:

  • “A key challenge to underwater basket weaving is that you ought to completely immerse yourself in water to perform the basket weaving task, and thus you will likely need to learn how to use scuba diving equipment or at least know to use a snorkel.”

ChatGPT then generated this response to my first answer:

  • “Thank you for explaining the challenge of immersion and the need for scuba diving or snorkeling equipment. It's clear that adapting to the underwater environment is crucial. Now, onto the second question: What are some unique types of plants or materials that are commonly used for underwater basket weaving, and how do they differ from those used in traditional basket weaving?”

I next provide a prompt that answers the question that ChatGPT posed in the above-generated response:

  • “Bamboo and reeds are often used for traditional basket weaving. For underwater basket weaving, I tend to use seaweed or kelp.”

ChatGPT generates a response indicating I have provided an answer to that question and then poses the next question for me to answer:

  • “Got it, the use of seaweed and kelp is interesting and distinct from the plant materials commonly used in traditional basket weaving. Now, let's move on to the third question: How does the process of preparing and treating materials for underwater basket weaving differ from that of land-based basket weaving? Are there any specific techniques to ensure the durability of materials in the underwater environment?”

I provided a prompt that gave my answer to the question, and also decided that I had enough of the Q&A and wanted to stop the flipped interaction:

  • “Since the materials that I use for underwater basket weaving are aquatic plants, they are already suitable for an underwater environment. Little or no preparation is required. Let's make this the last question for now.”

The generated response by ChatGPT said this:

  • “Certainly, I appreciate your willingness to share your expertise. Before we conclude, let me recap the valuable insights you've provided: In underwater basket weaving, one of the primary challenges is the need to immerse oneself in water, necessitating the use of scuba diving equipment or snorkels. Unlike traditional basket weaving on land, where materials like bamboo and reeds are common, underwater basket weaving relies on aquatic plants such as seaweed and kelp. Interestingly, these aquatic plants are already well-suited for underwater conditions, which eliminates the need for extensive material preparation. Thank you for sharing these intriguing details about underwater basket weaving! If you have more to share in the future, please don't hesitate to do so.”

Observe that ChatGPT provided a recap of my answers. This was due to the aspect that I had asked for the AI app to do so, having instructed that this is supposed to occur (mentioned in my initial setup prompt for the Q&A). The chances are that the generative AI might have given me a recap anyway, but I wanted to ensure that I did indeed get one.

The recap looks reasonably on par with my answers. Thankfully so. You cannot assume that the generative AI would have accurately or aptly absorbed the answers. I used the recap to double-check and try to ascertain whether any AI errors, glitches, AI hallucinations, or other misinterpretations occurred. For now, it looks good.

I next thought that it might be advantageous to do an additional double-check by explicitly asking ChatGPT about underwater basket weaving. This will deliver me additional reassurance that the generative AI likely suitably got data-trained on my answers. With the flipped interaction over, I asked this question to ChatGPT:

  • “I am now going to ask you some questions about underwater basket weaving. First, what type of equipment is needed for underwater basket weaving?”

ChatGPT generated this response:

  • “Of course, I'd be happy to answer your questions. To address your first question, the equipment needed for underwater basket weaving typically includes scuba diving gear or snorkeling equipment, depending on the depth and duration of your underwater weaving session. Scuba gear includes a diving mask, fins, a wetsuit or dry suit, a buoyancy control device, a regulator, and a tank of compressed air. Snorkeling equipment involves a snorkel, mask, fins, and exposure protection. These tools enable you to breathe and move comfortably underwater while engaging in the weaving process.”

The generated response goes quite a bit further than my earlier answer about the equipment involved in underwater basket weaving. This shows you that your answer to the posed questions will undoubtedly get embellished and enmeshed into other data that the generative AI has already pattern-matched on. Depending on how things go, this can be a good thing or a bad thing. In this case, the elaboration about the scuba equipment and the snorkeling equipment seems okay.

I asked several additional questions, and the answers were of an akin caliber, namely that ChatGPT was able to use my answer and tended to elaborate on what I had said.

One special aspect to consider is the temporary nature of the data training that you might have done when doing a Q&A during a particular conversation with the generative AI. Keep in mind that this might only last for the course of the specific conversation underway with the generative AI.

Here’s the rub. An AI maker can choose whether to have their generative AI data train on individual conversations or just allow a given conversation to come and go. Sometimes an AI maker might want to permanently incorporate the new data training into the AI, while other times they might not want it to happen (such as a dialogue that is untoward or has other adverse properties).


Congratulations, you are now ready to astutely use flipped interactions.

I urge you to try out this handy capability of generative AI. Your prompt engineering prowess should include the ability to skillfully wield flipped interactions, including knowing how to best invoke a flip of the script and how to squeeze as much value out of doing so.

For those of you who want to get even more advanced with flipped interactions, here are some of the exercises that I do in my workshops on prompt engineering:

  • (a) Have AI adopt a persona when questioning you.
  • (b) Have AI assess your answers in detail and tell you where you are right and wrong.
  • (c) Have AI make questions from your answers and then show you the derived questions.
  • (d) Have AI try to trick you or ask sneaky or off-the-wall questions.
  • (e) Have AI accept that some of your answers might be questions rather than answers per se.
  • (f) Etc.

Each of those variations has a useful purpose. Explore the flipped interaction possibilities and be ready to invoke a flip-the-script whenever suitable.

A final remark for now on this weighty inverse-of-control matter.

We are often told to avoid falling into a rut in life. The same can be said about those who frequently use generative AI. The everyday common rut is that you ask questions of the AI and wait to see the generative answers.

Time to flip the script!

Think about how you can employ flipped interactions when using generative AI. Get yourself out of an altogether mindless rut and leverage these undervalued and underused prompt engineering techniques. You’ll be a better person (well, maybe so) and assuredly a better consumer of generative AI for having done so.

Thu, 24 Aug 2023 23:00:00 -0500 Lance Eliot en text/html
Relaxation Techniques for Anxiety

When I first started my clinical training as a psychologist, some of the first techniques I learned were relaxation exercises. These are concrete, specific behaviors that clients can use to reduce the symptoms of anxiety. Relaxation exercises often target physical symptoms of anxiety such as hyperventilating and muscle tension but can also help with emotional symptoms such as panic and nervousness. One interesting debate has been whether to use relaxation exercises for anxiety or whether they can be counterproductive.

Let’s start with a few examples of relaxation exercises. The most common technique is probably diaphragm breathing, also called belly breathing or deep breathing. Diaphragm breathing has clients breathe using more of their diaphragm, the big muscle that helps the lungs move air in and out of the body. One version of this technique has clients put a hand on their chest and the other on their stomach and try to breathe so that the hand on the chest does not move (or moves minimally) and the hand on the stomach moves more. Diaphragm breathing helps prevent hyperventilating and the other symptoms that go with it such as dizziness. Another technique, one that was a mainstay of my training, is progressive muscle relaxation or PMR. PMR has the client progressively tense and relax different muscle groups until all their muscles are relaxed. Depending on how the muscles are grouped, PMR can take 10 to 30 minutes. Clients will often use a recording to guide them through the muscle groups. Other relaxation techniques include imagery and even some forms of meditation.

Image by Melk Hagelslag from Pixabay

Initially, it can seem like relaxation techniques should be great for anxiety because they reduce anxiety. Reducing anxiety, though, might not always be helpful. I’ve written before about how anxiety is a normal part of life and trying to reduce normal levels of anxiety can be counterproductive. If relaxation techniques are being used to avoid anxiety instead of facing it, then they can be unhelpful. Another situation in which relaxation exercises might not help is during exposure therapy. In exposure therapy, a client gradually faces situations that cause anxiety so they can gain experience showing that they are able to cope with the situation and the anxiety. If relaxation exercises are used too much in exposure therapy to the point that the client does not feel anxiety, then it can cancel out the exposure exercise. Situations with mild to moderate levels of anxiety might not need relaxation exercises.

Relaxation exercises still have many uses. For someone experiencing a high level of anxiety, these techniques can help reduce the anxiety to a more manageable level. For people trying exposure therapy but who have a high level of anxiety even for beginning levels of exposure, relaxation techniques can be extremely helpful so they can get started on facing those feared situations. The key is not necessarily using a specific technique but rather finding one that works for you.

As with any specific therapy technique including relaxation exercises, always check with your mental health provider first. You might have to try several different techniques before you find one that works for you. And you might have to try using relaxation exercises in several different situations before figuring out when it helps you and when it does not help.

Sun, 31 Dec 2023 10:00:00 -0600 en-US text/html
Neuroengineering Minor

NBL 425: Methods in Neuroimaging (3 hours)

Cognitive neuroscience research has provided valuable insights into the workings of the human brain. The techniques used in cognitive neuroscience span from postmortem brain studies to neuroimaging studies. The ability to perform neuroimaging studies on awake human individuals engaged in cognitive, social, sensory, and motor tasks has produced a conceptual revolution in the study of human cognition. This course will comprehensively examine the methods and techniques in neuroimaging with the primary goal of building basic knowledge in the concepts and techniques of neuroimaging. The course will explore techniques, such as single and multi-cell recordings, deep brain stimulation, electroencephalography, magnetoencephalography, functional magnetic resonance imaging, and diffusion tensor imaging. This course will be an apt venue for graduate students interested in neuroscience research to build a platform for continuing studies.

NBL 454: The Body Electric: Electronics for Biologists (3 hours)

Some of the most important aspects of biological systems involve electrical phenomena. From the operation of the nervous system, to the control of cardiac or gut motility, the response of bone to stress, and even the most basic membrane physiology of every cell, the body is electric. Additionally, electronic instrumentation and analysis techniques are a major part of biological research. And yet, the typical biology student has very little background in these topics. Formal engineering courses have too many pre-requisites, and require more mathematical sophistication than is truly needed for most biologists. This course is designed to try and fill this gap.

Sun, 06 May 2018 13:28:00 -0500 en-US text/html
What Is Biomedical Engineering?

Biomedical engineering (BME) focuses on the advances that Boost human health and health care at all levels and is the application of the principles and problem-solving techniques of engineering to biology and medicine. This is evident throughout healthcare, from diagnosis and analysis to treatment and recovery, and has entered the public conscience though the proliferation of implantable medical devices, such as pacemakers and artificial hips, to more futuristic technologies such as stem cell engineering and the 3-D printing of biological organs.

Engineering itself is an innovative field, the origin of ideas leading to everything from automobiles to aerospace, skyscrapers to sonar. Biomedical engineering focuses on the advances that Boost human health and health care at all levels.

How is Biomedical Engineering Different?

Biomedical engineers differ from other engineering disciplines that have an influence on human health in that biomedical engineers use and apply an intimate knowledge of modern biological principles in their engineering design process. Aspects of mechanical engineering, electrical engineering, chemical engineering, materials science, chemistry, mathematics, and computer science and engineering are all integrated with human biology in biomedical engineering to Boost human health, whether it be an advanced prosthetic limb or a breakthrough in identifying proteins within cells.

Biomedical Engineering Subdisciplines

There are many subdisciplines within biomedical engineering, including the design and development of active and passive medical devices, orthopedic implants, medical imaging, biomedical signal processing, tissue and stem cell engineering, and clinical engineering, just to name a few. Request information to become a biomedical engineer today.

What do Biomedical Engineers do?

Biomedical engineers work in a wide variety of settings and disciplines. There are opportunities in industry for innovating, designing, and developing new technologies; in academia furthering research and pushing the frontiers of what is medically possible as well as testing, implementing, and developing new diagnostic tools and medical equipment; and in government for establishing safety standards for medical devices. Many biomedical engineers find employment in cutting-edge start-up companies or as entrepreneurs themselves.

Tissue and stem cell engineers are working towards artificial recreation of human organs, aiding in transplants and helping millions around the world live better lives. Experts in medical devices develop new implantable and external devices such as pacemakers, coronary stents, orthopaedic implants, prosthetics, dental products, and ambulatory devices. Clinical engineers work to ensure that medical equipment is safe and reliable for use in clinical settings. Biomedical engineering is an extremely broad field with many opportunities for specialization.

What Careers are there in Biomedical Engineering?

In the last few years, both Forbes and CNN Money have dubbed biomedical engineering as the best health care career out there. And the possibilities within biomedical engineering are nearly endless. New innovations in technology, materials, and knowledge mean that tomorrow's breakthroughs can barely be conceived of today. After all, a generation ago, biomedical engineering, as a field, did not exist.

Biomedical Engineering Career Paths

Career paths in biomedical engineering tend to be driven by the interests of the individual: the huge breadth of the field allows biomedical engineers to develop specialties in an area that interests them, be it biomaterials, neuromodulation devices, orthopaedic repair, or even stem cell engineering. Biomedical engineers often combine an aptitude for problem solving and technical know-how with focused study in medicine, healthcare, and helping others. It is this hybridization that has led to so much innovation—and so much opportunity—in biomedical engineering.

Biomedical Engineering Job Titles

Biomedical engineers work in various fields, and their job titles can vary based on their specific role or specialization. Some common job titles for biomedical engineers include:

  • Biomedical Engineer
  • Clinical Engineer
  • Biomaterials Engineer
  • Medical Device Engineer
  • Tissue Engineer
  • Rehabilitation Engineer
  • Regulatory Affairs Specialist
  • Research Scientist (Biomedical Engineering)
  • Bioinformatics Engineer
  • Imaging Engineer
  • Biomechanics Engineer
  • Biomedical Equipment Technician
  • Quality Assurance Engineer (Biomedical)
  • Product Development Engineer (Biomedical)
  • Systems Engineer (Biomedical Applications)

How Much do Biomedical Engineers Earn?

Like careers in many other engineering fields, biomedical engineers are well paid. Compared to other fields, they earn well above average throughout each stage of their careers. A typical first job as a biomedical engineer nets a salary around $65,904, with many earning significantly more. More advanced careers are comfortably in six figures.

According to the United States Department of Labor, the mean salary for a biomedical engineer is $108,060 with the top ten percent of biomedical engineers earning $159,130.

The Future of Biomedical Engineering

Economically speaking, medical diagnostics triple in market value each year. Revolutionary advances in medical imaging and medical diagnostics are changing the way medicine is practiced. New medical devices, arising in the research laboratories of biomedical engineers around the world, have completely altered the manner by which disease and trauma is dealt with by physicians, extending the quality and length of human life.

Ultimately, the future of biomedical engineering (BME) is tied to both the issues and obstacles we discover and advances and achievements in fields like chemistry, materials science, and biology. Just as in most other fields, interdisciplinarity means that innovation originates from many directions at the same time.

Our Biomedical Engineering Degrees

The bachelor's degree in biomedical engineering at Michigan Tech offers undergraduate students many unique, hands-on learning opportunities:

Undergraduate Research Opportunities

Undergraduate research opportunities are plentiful. On average, six students work alongside each faculty member, researching biomaterials and tissue engineering; biomechanics; or instrumentation/physiological measurements.

Real-World Experience

Get ready to contribute on the job from day one. Our students benefit from hands-on experiences ranging from to Senior Design to internships/co-ops. Gain real-world experience in the medical device industry, a medical research lab, or a hospital.

Enhance Your Degree with an Emphasis Area

Enhance your degree with an emphasis in mechanical engineering, electrical engineering, materials science and engineering, or biotechnology by taking elective courses in these areas.

Prepare for Graduate Study

Our undergraduate program in biomedical engineering (BME) prepares you for advanced study in the field. Earn your MS or PhD degrees in biomedical engineering or a related field either at Michigan Tech or at another university.

Prepare for Medical School

The curriculum offers excellent preparation for medical school, other health professional programs, and graduate school. Michigan Tech's Director of Pre-Health Professions will help you along the way. Approximately 30 percent of our graduates enroll in a graduate degree program, half of which go on to earn an advanced medical, dental, or veterinary degree.

Early-Admission Opportunities

The University's Early Assurance Program provides early admission to medical school for qualified students, especially those wishing to practice in underserved areas; program partners include Michigan State University College of Human Health, and Wayne State University School of Medicine.

Mon, 16 Dec 2013 06:17:00 -0600 en text/html
Isolation Techniques in Microbiology No result found, try new keyword!Learn about the fundamentals of microbial isolation in our complete guide to microbial isolation techniques. Microbial isolation is a critical component in microbiology, essential for unraveling ... Sun, 17 Dec 2023 10:00:00 -0600 en-us text/html What You Need to Know About Becoming a Biomedical Engineering Major No result found, try new keyword!A biomedical engineering major uses science and engineering techniques to find innovative solutions to issues in medicine and biology. Students learn about ethics and how to account for economic ... Wed, 13 Jan 2021 02:09:00 -0600 Undergraduate Programs in Biomedical Engineering

Biomedical Engineering (BME) is the application of engineering principles and problem-solving techniques to biology and medicine. BME knowledge and skills play important roles in modern healthcare — from diagnosis and analysis to treatment and recovery, and from the proliferation of implantable medical devices (such as pacemakers and artificial hips) to more futuristic technologies (such as stem cell engineering and 3D printing of biological organs).

Biomedical engineers differ from other engineering disciplines that have an influence on human health. How? Biomedical engineers use and apply an intimate knowledge of modern biological principles in their engineering design process. Subdisciplines in BME include design and development of active and passive medical devices, orthopedic implants, medical imaging, biomedical signal processing, tissue and stem cell engineering, and clinical engineering, just to name a few.

Are you looking for a major that can help you adapt to the rapidly changing scientific landscape? Are you interested in entering the biomedical engineering industrial workforce, medical school, health professional programs, or graduate school? Our curriculum helps prepare you for these possibilities.

Get the Most Out of Your Undergraduate Studies

We offer a degree in Biomedical Engineering. You can enhance the degree with concentrations and our new Neuroengineering Minor, or join the honors program and be mentored by faculty members. Your studies will culminate in a capstone design experience — you'll be a member of an interdisciplinary team solving real-world engineering problems. The biomedical engineering B.S. degree program is accredited by the Engineering Accreditation Commission of ABET

If you know you want to go on to graduate school, you should consider our Fifth Year Master's Program.

Download our undergraduate brochure here.

Research and Hands-On Learning

All of our courses are taught by full-time BME faculty members, who are active and productive researchers. Their expertise will be part of your classroom experience. We have high-quality facilities for laboratory experiments, computer simulations, and lab-based projects that deliver you hands-on learning experiences with instrumentation, computer simulations, and lab techniques common to the discipline.

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