Electrical Engineering Crossword (Issue 292)

The answers to Circuit Cellar’s November electronics engineering crossword puzzle are now available.292-crossword-(key)

Across

  1. BITS—A nibble is 4 of these
  2. REPEATER—ELECTRONIC DEVICE THAT RECEIVES AND AMPLIFIES A WEAK SIGNAL BEFORE RETRANSMITTING IT
  3. MICRO—Metric Prefix for 0.000001
  4. PATCH—To re-route a signal to a different circuit
  5. TOKEN—Used for authentication
  6. RELAY—A switch that is actuated by another electrical signal
  7. JITTER—The deviation of some aspect of a digital signal’s pulses
  8. RHEOSTAT—A variable resistor
  9. LUX—Lx
  10. VOLTA—Italian physicist who invented the first batteries
  11. GERMANIUM—Ge
  12. CONDUIT—Wire piping
  13. PIGTAIL—Short wire connecting components
  14. RECTIFIER—A diode, used for converting AC into DC

Down

  1. SCHOTTKY—High-speed diode that has very little junction capacitance
  2. PEERTOPEER—P2P
  3. INRUSH—A sudden input current surge
  4. CRESTFACTOR—The ratio of the peak value to the RMS value (two words)
  5. MICROFARAD—1,000,000 pF
  6. ANALOG—Constant signal processing

 

 

Electrical Engineering Crossword (Issue 291)

The answers to Circuit Cellar’s October electronics engineering crossword puzzle are now available.291crossword (key)

Across

4.     PARAMETRON—Phase-locked oscillator

8.     UNBALANCED—Single-ended

9.     STRAY—Unwanted capacitance

10.   LEYDENJAR—Early capacitor [two words]

12.   ELECTROLYTE—Conducting fluid

14.   CROSSTALK—Caused when one circuit’s signal creates an unwanted effect on another

16.   ANECHOIC—Absorbs sound or electromagnetic wave reflections

17.   BIFILAR—Used in bipolar power-supply transformers to improve output voltage symmetry

18.   CRYSTALRECTIFIER—Semiconductor diode [two words]

19.   DOPPLEREFFECT—Frequency change that occurs when emitter and receiver move in unison [two words]

Down

1.     BLEEDER—A resistor that draws the critical amount of load current

2.     GAUSSMETER—Detects magnetic anomalies

3.     HETERODYNE—Two frequencies combine to produce new ones

5.     SURFACEMOUNT—Place components directly on PCBs [two words]

6.     HASH—Garbage or gibberish

7.     GALVANOMETER—Measures small voltages

11.   RECTIFIER—Passes current in only one direction

13.   CATWHISKER—Sharp, flexible wire that connects to a semiconductor crystal’s surface [two words]

15.   ANOTRON—Cold-cathode-glow discharge diode

 

Electrical Engineering Crossword (Issue 290)

The answers to Circuit Cellar’s September electronics engineering crossword puzzle are now available.CrosswordEmptyGrid (key)

Across 

2.     THREE—Trivalent valence

3.     PHYSICS—Kilby’s Noble Prize in 2000

5.     INVERTER—Converts DC to AC

8.     BATCH—BAT file

9.     MAXIM—Founded ARRL in 1914

10.   KEYBOARD—If you are AFK, what are you away from?

11.   UPENN—University that housed the ENIAC in a 30’ × 40’ room

12.   HERTZ—1 cycle per second

14.   NIBBLE—4 bits

17.   EXPLAINER—Asimov was the great what?

Down

1.     TRACK—PCB path

3.     PATCH—Quick fix

4.     SNIFFER—Used to monitor network traffic

6.     MAXWELL—A Gauss is one of these per square centimeter

7.     IBM—”Big Blue”

8.     BOOLE—“An Investigation of the Laws of Thought” (1854)

13.   TOGGLE—Move from setting A to B

15.   BLUE—Screen of death

16.   NINE—A nonet is a group of what?

17.   EW—Exawatt

Electrical Engineering Crossword (Issue 289)

The answers to Circuit Cellar’s August electronics engineering crossword puzzle are now available.289PuzzleGrid (key)

Across

1.     FAST—Ethernet at 100 Mbps

3.     FAB—IC factory

6.     XOR—Logic gate

7.     VERILOG—HDL created in the early 1980s by Goel and Moorby

9.     MIL—0.001 inches = 25.4 what?

10.   AMPHOUR—Current flow over time [two words]

13.   SANTOS—Greek national soccer team manager with a degree in electrical engineering

14.   NOLEAD—Quad, flat, … [two words]

16.   BUCK—Step-down

17.   FEMTO—0.000000000000001

18.   GND—Ground pin

19.   NULL—Zero

Down

2.     SLICE—Wafer or substrate

3.     FILO—Antonym for FIFO

4.     QUINARY—Base-5

5.     CODERDECODER—CODEC [two words]

7.     VERSORIUM—Gilbert’s static-detection device

8.     DISSIPATION—Release heat

11.   HAPTIC—Relates to touch

12.   JOULE—1 watt second

15.   DOPING—Process of purposely adding impurities

Electrical Engineering Crossword (Issue 288)

The answers to Circuit Cellar’s July electronics engineering crossword puzzle are now available.288Crossword (key)

Across

2.     QUIESCE—Inactive but still available

4.     GLUELOGIC—Used for circuitry interfacing [two words]

7.     AMAYA—Open-source web tool developed by members of the World Wide Web Consortium (W3C)

8.     ROUNDROBIN—A continuous sequence [two words]

9.     FATCLIENT—A tower PC, for example [two words]

11.   LOGICBOMB—Explosive code [two words]

15.   HEISENBUG—A software glitch that changes its conduct when analyzed

16.   STROBOSCOPE—Makes things appear to move slowly or not at all

17.   STATAMPERE—Approximately 0.333 nanoampere

18.   KORNSHELL—Unix command-line interpreter developed by and named after a Bell Labs employee [two words]

19.   VOXEL—Defines a point in 3-D

Down

1.     BEAMFORMING—Signal processing for sensor arrays

3.     SPIBUS—Works in double-duplex mode [two words]

4.     GREP—UNIX-based command-line utility

5.     SUPERHETERODYNE—Used to convert to intermediate frequencies

6.     ENDIAN—Creates data words

10.   PHOTOVOLTAICS—Uses solar power to create energy

12.   BITTORRENT—File sharing protocol

13.   BINARYPREFIX—E.g., gibi [two words]

14.   AUSTRUMI—Linux distribution based on Slackware

 

Electrical Engineering Crossword (Issue 287)

The answers to Circuit Cellar’s April electronics engineering crossword puzzle are now available.287 crossword (key)

Across

1. BEAMFORMING—Signal processing technique

7. HETERODYNERECEIVER—Converts a signal to an intermediate frequency [two words]

8. AMIGA—A high-resolution PC based on Motorola’s 6800 microprocessor family

9. NAGLING—Creates “Russian doll”-type packets to improve a TCP/IP network’s performance

10. SERVERBLADE—A thin circuit board designed for one specific application [two words]

15. FUZZING—Tests for coding and security errors

17. PHASECHANGE—Nonvolatile RAM [two words]

18. WALLEDGARDEN—Restricts access to Web content and services [two words]

19. SERIALBACKPACK—A PCB interface that goes between a parallel LCD and a microcontroller [two words]

20. SLACKWARE—Open-source, Linux-based OS

Down

2. ROOTMEANSQUARE—Determines an AC wave’s voltage [three words]

3. ROENTGEN—IBM’s active matrix LCD

4. KERNELPANIC—Happens when a fatal error is detected [two words]

5. BIPHASEENCODING—Requires a state transition at the end of every data bit [two words]

6. PERMITTIVITY—Ability to be polarized

11. VOODOO—Helps create realistic 3-D graphics

12. FLANGING—An audio process that combines signals to create a comb filter effect

13. BREADBOARDING—Used for circuit design experimentation

14. STATOHM—Five of these equal approximately 4.5 × 1012

16. TELEDACTYL—Utilizes human speech to code

 

Electrical Engineering Crossword (Issue 286)

The answers to Circuit Cellar’s April electronics engineering crossword puzzle are now available.

Crossword-CC286-May14

Across

2. SAMBA—This networking protocol enables you to write to an embedded file system from a Windows PC

7. ELECTROMAGNETICFIELD—Used for data transfer [two words]

8. CAPACITOR—These types of microphones were commonly called “condensers” until about 1970

9. HOMODYNE—A receiver with direct amplification

13. BLENDER—Contains several modeling features and an integrated game engine

15. PULSESHAPING—Used to improve wired or wireless communication link performance [two words]

17. BRILLOUINSCATTERING—Occurs when certain types of light change their frequency and route [two words]

18. CLOCKSIGNAL—Used to coordinate circuits’ actions [two words]

19. RASPBERRYPI—Designed to encourage scholastic computer science lessons [two words]

Down

1. NONRETURNTOZERO—Typically 1s are a positive voltage and 0s are a negative voltage [four words]

3. BITARRAY—Provides compact storage for computing and digital communications [two words]

4. DOUBLEDATARATE—Coordinates the rising and falling edges of an [18 Across] to transfer data [three words]

5. ANECHOIC—Absent of sound

6. FIRSTINFIRSTOUT—Oldest requests receive priority [four words]

10. INTERFERENCE—The “I” in SQUID

11. CROSSTALK—Occurs when accidental coupling causes unwanted signals

12. BINISTOR—An electronic oscillator component

14. NANCY—Receiver that intercepts or demodulates IR radiation

16. BEAGLEA good breed of analyzer for I2C and SPI designs

 

Electrical Engineering Crossword (Issue 285)

The answers to Circuit Cellar’s April electronics engineering crossword puzzle are now available.

285-crossword-keyAcross

2.    STOKESSHIFT—Can reduce photon energy [two words]
8.    HYSTERESISLOOP—Its area measures the energy dispersed during a magnetization cycle [two words]
11.    NANDGATE—A shoe in when playing “true or false?” [two words]
13.    YOCTOPROJECT—An open-source alliance designed to help Linux aficionados [two words]
15.    RANKINE—°R
17.    INTERNALNET—A network that resides in and around you
18.    SEQUENTIALCIRCUIT—Dependent on past input [two words]
19.    NANOHENRY—Its abbreviation is the same as the state bordered by Massachusetts, Maine, and Vermont
20.    BINARYCODEDDECIMAL—Makes good use of a 4- or 8-bit nibble [three words]

Down

1.    BIREFRINGENCE—Divides light into ordinary and extraordinary rays
3.    SQUIRREL—An object-oriented programming language
4.    SMARTMETER—Records and shares energy usage information [two words]
5.    MESHANALYSIS—A circuit evaluation method [two words]
6.    LYOTFILTER—Uses [1. Down] to produce a narrow frequency range of wavelengths [two words]
7.    LINEARREGULATOR—Keeps things steady [two words]
9.    BRAGGDIFFRACTION—Occurs when electromagnetic radiation disperses [two words]
10.    AUTODYNE—An amplifying vacuum tube-based circuit
12.    FEMTOWATT—10–15 W
14.    UNIJUCTION—Can be used to measure magnetic flux
16.    PEAKER—Increases gain at higher frequencies

Electrical Engineering Crossword (Issue 284)

The answers to Circuit Cellar’s March electronics engineering crossword puzzle are now available.

284-crossword-key

Across

1.    CROSSEDFIELDAMPLIFIER—This vacuum tube is capable of high output power [three words]
3.    HYPERVISOR—Produces and runs virtual machines
5.    DYNATRON—Uses negative resistance to keep a tuned circuit oscillating
8.    ULTRAVIOLETLIGHT—Gives some substances “a healthy glow” [two words]
13.    ZEROMOMENTPOINT—A moment of respite for robots [three words]
14.    THERMOSONIC—Connects to silicon ICs
17.    CATSWHISKER—An outdated electronic component mainly used in antique radios [two words]
18.    FLEMINGVALVE—Invented in the early 1900s, this was known as the first vacuum tube [two words]
19.    BACKBONE—Makes LANs connect

Down

2.    DEMODULATOR—Recovers information from a regulated waveform
4.    SQUEGGING—This type of circuit oscillates erratically
5.    DOWNMIXING—Audio manipulation process
6.    REYNOLDSNUMBER—Used for flow pattern predictions [two words]
7.    LATENCY—Used with bandwidth to ascertain network connection speed
9.    THICKFILM—This type of chip resistor is commonly used in electronic and electrical devices [two words]
10.    DYNAMIC—Its memory is volatile
11.    CRYOTRON—Operates via superconductivity
12.    NETMASK—Creates neighborhoods of IP addresses
15.    HOROLOGY—E.g., clepsydras, chronometers, and sundials
16.    SEEBECK—An effect that creates electricity

 

 

Electrical Engineering Crossword (Issue 283)

The answers to Circuit Cellar’s February electronics engineering crossword puzzle are now available.

283-crossword-key

Across

2. LITZWIRE—Separately insulated strands woven together [two words]
4. LINKFIELD—First in a message buffer’s line [two words]
6. PETAFLOPS—Measures a processor’s floating point unit performance
8. ANION—negatively charged atom
9. LISP—Used to manipulate mathematical logic
11. STATCOULOMB—i.e., franklin (Fr)
12. AMBISONICS—Typically requires a soundfield microphone
15. BROUTER—This device can send data between networks and it can forward data to individual systems in a network
16. TRINITRON—This CRT technology was originally introduced the 1960s
17. OXIDE—The “O” in CMOS
18. DETENT—Used to prevent or stop something from spinning

Down

1. ELECTRICSUSCEPTIBILITY—XE [two words]
3. RADECHON—A barrier-grid storage tube
5. COLPITTS—This oscillator uses two-terminal electrical components to create a specific oscillation frequency
7. BEAGLEBOARD—TI’s open-source SBC
10. PICONET—A network that is created using a wireless Bluetooth connection
13. BETATRON—Designed to accelerate electrons
14. TEBIBYTE—More than 1,000,000,000,000 bytes

System Safety Assessment

System safety assessment provides a standard, generic method to identify, classify, and mitigate hazards. It is an extension of failure mode effects and criticality analysis and fault-tree analysis that is necessary for embedded controller specification.

System safety assessment was originally called ”system hazard analysis.” The name change was probably due to the system safety assessment’s positive-sounding connotation.

George Novacek (gnovacek@nexicom.net) is a professional engineer with a degree in Cybernetics and Closed-Loop Control. Now retired, he was most recently president of a multinational manufacturer of embedded control systems for aerospace applications. George wrote 26 feature articles for Circuit Cellar between 1999 and 2004.

Columnist George Novacek (gnovacek@nexicom.net), who wrote this article published in Circuit Cellar’s January 2014 issue, is a professional engineer with a degree in Cybernetics and Closed-Loop Control. Now retired, he was most recently president of a multinational manufacturer of embedded control systems for aerospace applications. George wrote 26 feature articles for Circuit Cellar between 1999 and 2004.

I participated in design reviews where failure effect classification (e.g., hazardous, catastrophic, etc.) had to be expunged from our engineering presentations and replaced with something more positive (e.g., “issues“ instead of “problems”), lest we wanted to risk the wrath of buyers and program managers.

System safety assessment is in many ways similar to a failure mode effects and criticality analysis (FMECA) and fault-tree analysis (FTA), which I described in “Failure Mode and Criticality Analysis” (Circuit Cellar 270, 2013). However, with safety assessment, all possible system faults—including human error, electrical and mechanical subsystems’ faults, materials, and even manuals—should be analyzed. The impact of their faults and errors on the system safety must also be considered. The system hazard analysis then becomes a basis for subsystems’ specifications.

Fault Identification

Performing FMECA and FTA on your subsystem ensures all its potential faults become detected and identified. The faults’ signatures can be stored in a nonvolatile memory or communicated to a display console, but you cannot choose how the controller should respond to any one of those faults. You need the system hazard analysis to tell you what corrective action to take. The subsystem may have to revert to manual control, switch to another control channel, or enter a degraded performance mode. If you are not the system designer, you have little or no visibility of the faults’ potential impact on the system safety.
For example, an automobile consists of many subsystems (e.g., propulsion, steering, braking, entertainment, etc.). The propulsion subsystem comprises engine, transmission, fuel delivery, and possibly other subsystems. A part of the engine subsystem may include a full-authority digital engine controller (FADEC).

Do you have an electrical engineering tip you’d like to share? Send it to us here and we may publish it as part of our ongoing EE Tips series.

Engine controllers were originally mainly mechanical devices, but with the arrival of the microprocessor, they have become highly sophisticated electronic controllers. Currently, most engines—including aircraft, marine, automotive, or utility (e.g., portable electrical generator turbines)—are controlled by some sort of a FADEC to achieve best performance and safety. A FADEC monitors the engine performance and controls the fuel flow via servomotor valves or stepper motors in response to the commanded thrust plus numerous operating conditions (e.g., atmospheric and internal pressures, external and internal engine temperatures in several locations, speed, load, etc.).

The safety assessment mostly depends on where and how essentially identical systems are being used. A car’s engine failure, for example, may be nothing more than a nuisance with little safety impact, while an aircraft engine failure could be catastrophic. Conversely, an aircraft nosewheel steer-by-wire can be automatically disconnected upon a fault. And, with a little increase of the pilots’ workload, it may be substituted by differential braking or thrust to control the plane on the ground. A similar failure of an automotive steer-by-wire system could be catastrophic for a car barreling down the freeway at 70 mph.

Analysis

System safety analysis comprises the following steps: identify and classify potential hazards and associated avoidance requirements, translate safety requirements into engineering requirements, design assessment and trade-off support to the ongoing design, assess the design’s relative compliance to requirements and document findings, direct and monitor specialized safety testing, and monitor and review test and field issues for safety trends.

The first step in hazard analysis is to identify and classify all the potential system failures. FMECA and FTA provide the necessary data. Table 1 shows an example and explains how the failure class is determined.

TABLE 1
This table shows the identification and severity classification of all potential system-level failures.
Eliminated Negligible Marginal Critical Catastrophic
No safety impact. Does not significantly reduce system safety. Required actions are within the operator’s capabilities. Reduces the capability of the system or operators to cope with adverse operating conditions. Can cause major illness, injury, or property damage. Significantly reduces the capability of the system or the operator’s ability to cope with adverse conditions to the extent of causing serious or fatal injury to several people. Total loss of system control resulting in equipment loss and/or multiple fatalities.

The next step determines each system-level failure’s frequency occurrence (see Table 2). This data comes from the failure rates calculated in the course of the reliability prediction, which I covered in my two-part article “Product Reliability” (Circuit Cellar 268–269, 2012) and in “Quality and Reliability in Design” (Circuit Cellar 272, 2013).

TABLE 2
Use this information to determine the likelihood of each individual system-level failure.
Frequent Probability of occurrence per operation is equal or greater than 1 × 10–3
Probable Probability of occurrence per operation is less than 1 × 10–3 or greater than 1 × 10–5
Occasional Probability of occurrence per operation is less than 1 × 10–5 or greater than 1 × 10–7
Remote Probability of occurrence per operation is less than 1 × 10–7 or greater than 1 × 10–9
Improbable Probability of occurrence per operation is less than 1 × 10–9

Based on the two tables, the predictive risk assessment matrix for every hazardous situation is created (see Table 3). The matrix is a composite of severity and likelihood and can be subsequently classified as low, medium, serious, or high. It is the system designer’s responsibility to evaluate the potential risk—usually with regard to some regulatory requirements—to specify the maximum hazard levels acceptable for every subsystem. The subsystems’ developers must comply with and satisfy their respective specifications. Electronic controllers in safety-critical applications must present low risk due to their subsystem fault.

TABLE 3
The risk assessment matrix is based on information from Table 1 and Table 2.
Probability / Severity Catastrophic (1) Critical (2) Marginal (3) Negligible (4)
Frequent (A) High High Serious Medium
Probable (B) High High Serious Medium
Occasional (C) High Serious Medium Low
Remote (D) Serious Medium Medium Low
Improbable (E) Medium Medium Medium Low
Eliminated (F) Eliminated

The system safety assessment includes both software and hardware. For aircraft systems, the required risk level determines the development and quality assurance processes as anchored in DO-178 Software Considerations in Airborne Systems and Equipment Certification and DO-254 Design Assurance Guidance for Airborne Electronic Hardware.

Some non-aerospace industries also use these two standards; others may have their own. Figure 1 shows a typical system development process to achieve system safety.
The common automobile power steering is, by design, inherently low risk, as it continues to steer even if the hydraulics fail. Similarly, some aircraft controls continue to be the old-fashioned cables but, like the car steering, with power augmentation. If the power fails, you just need more muscle. This is not the case with the more prevalent drive- or fly-by-wire systems.

FIGURE 1: The actions in this system-development process help ensure system safety.

FIGURE 1: The actions in this system-development process help ensure system safety.

Redundancy

How can the risk be mitigated to at least 109 probability for catastrophic events? The answer is redundancy. A well-designed electronic control channel can achieve about 105 probability of a single fault. That’s it. However, the FTA shows that by ANDing two such processing channels, the resulting failure probability will decrease to 1010, thus mitigating the risk to an acceptable level. An event with 109 probability of occurring is, for many systems, acceptable as just about “never happening,” but there are requirements for 1014 or even lower probability. Increasing redundancy will enable you to satisfy the specification.
Once I saw a controller comprising three independent redundant computers, with each computer also being triple redundant. Increasing safety by redundancy is why there are at least two engines on every commercial passenger carrying aircraft, two pilots, two independent hydraulic systems, two or more redundant controllers, power supplies, and so forth.

Human Engineering

Human engineering, to use military terminology, is not the least important for safety and sometimes not given sufficient attention. MIL-STD-1472F, the US Department of Defense’s Design Criteria Standard: Human Engineering, spells out many requirements and design constraints to make equipment operation and handling safe. This applies to everything, not just electrical devices.

For example, it defines the minimum size of controls if they may be operated with gloves, the maximum weight of equipment to be located above a certain height, the connectors’ location, and so forth. In my view, every engineer should look at this interesting standard.
Non-military equipment that requires some type of certification (e.g., most electrical appliances) is usually fine in terms of human engineering. Although there may not be a specific standard guiding its design in this respect, experienced certificating examiners will point out many shortcomings. But there are more than enough fancy and expensive products on the market, which makes you wonder if the designer ever tried to use the product himself.

By putting a little thought beyond just the functional design, you can make your product attractive, easy to operate, and safe. It may be as simple as asking a few people who are not involved with your design to use the product before you release it to production.

Test Pixel 1

Electrical Engineering Crossword (Issue 282)

The answers to Circuit Cellar’s January electronics engineering crossword puzzle are now available.

282-Crossword-key

Across

4.    VENNDIAGRAM—Represents many relation possibilities [two words]
5.    PERSISTRON—Produces a persistent display
9.    CODOMAIN—A set that includes attainable values
12.    HOMOPOLAR—Electrically symmetrical
13.    TRUTHTABLE—Determines a complicated statement’s validity [two words]
17.    POWERCAPPING—Controls either the instant or the average power consumption [two words]
18.    MAGNETRON—The first form, invented in 1920, was a split-anode type
19.    MAGNETICFLUX—F
20.    TURINGCOMPLETE—The Z3 functional program-controlled computer, for example [two words]

Down

1.    CHAOSCOMPUTERCLUB—Well-known European hacker association [three words]
2.    LOGICLEVEL—When binary, it is high and low [two words]
3.    LINEARINTERPOLATION—A simple, but inaccurate, way to convert A/D values into engineering units [two words]
6.    SYNCHRONOUSCIRCUIT—A clock signal ensures this device’s parts are in parallel [two words]
7.    BOARDBRINGUP—Design validation process [three words]
8.    HORNERSRULE—An algorithm for any polynomial order [two words]
10.    MEALY—This machine’s current state and inputs dictate its output values
11.    SQUAREWAVE—It is produced by a binary logic device [two words]
14.    THEREMIN—Its electronic signals can be amplified and sent to a loudspeaker
15.    ABAMPERE—10 A
16.    SCOPEPROBE—Connects test equipment to a DUT [two words]

 

Q&A: Andrew Godbehere, Imaginative Engineering

Engineers are inherently imaginative. I recently spoke with Andrew Godbehere, an Electrical Engineering PhD candidate at the University of California, Berkeley, about how his ideas become realities, his design process, and his dream project. —Nan Price, Associate Editor

Andrew Godbehere

Andrew Godbehere

NAN: You are currently working toward your Electrical Engineering PhD at the University of California, Berkeley. Can you describe any of the electronics projects you’ve worked on?

ANDREW: In my final project at Cornell University, I worked with a friend of mine, Nathan Ward, to make wearable wireless accelerometers and find some way to translate a dancer’s movement into music, in a project we called CUMotive. The computational core was an Atmel ATmega644V connected to an Atmel AT86RF230 802.15.4 wireless transceiver. We designed the PCBs, including the transmission line to feed the ceramic chip antenna. Everything was hand-soldered, though I recommend using an oven instead. We used Kionix KXP74 tri-axis accelerometers, which we encased in a lot of hot glue to create easy-to-handle boards and to shield them from static.

This is the central control belt-pack to be worn by a dancer for CUMotive, the wearable accelerometer project. An Atmel ATmega644V and an AT86RF230 were used inside to interface to synthesizer. The plastic enclosure has holes for the belt to attach to a dancer. Wires connect to accelerometers, which are worn on the dancer’s limbs.

This is the central control belt-pack to be worn by a dancer for CUMotive, the wearable accelerometer project. An Atmel ATmega644V and an AT86RF230 were used inside to interface to synthesizer. The plastic enclosure has holes for the belt to attach to a dancer. Wires connect to accelerometers, which are worn on the dancer’s limbs.

The dancer had four accelerometers connected to a belt pack with an Atmel chip and transceiver. On the receiver side, a musical instrument digital interface (MIDI) communicated with a synthesizer. (Design details are available at http://people.ece.cornell.edu/land/courses/ece4760/FinalProjects/s2007/njw23_abg34/index.htm.)

I was excited about designing PCBs for 802.15.4 radios and making them work. I was also enthusiastic about trying to figure out how to make some sort of music with the product. We programmed several possibilities, one of which was a sort of theremin; another was a sort of drum kit. I found that this was the even more difficult part—not just the making, but the making sense.

When I got to Berkeley, my work switched to the theoretical. I tried to learn everything I could about robotic systems and how to make sense of them and their movements.

NAN: Describe the real-time machine vision-tracking algorithm and integrated vision system you developed for the “Are We There Yet?” installation.

ANDREW: I’ve always been interested in using electronics and robotics for art. Having a designated emphasis in New Media on my degree, I was fortunate enough to be invited to help a professor on a fascinating project.

This view of the Yud Gallery is from the installed camera with three visitors present. Note the specular reflections on the floor. They moved throughout the day with the sun. This movement needed to be discerned from a visitor’s typical movement .

This view of the Yud Gallery is from the installed camera with three visitors present. Note the specular reflections on the floor. They moved throughout the day with the sun. This movement needed to be discerned from a visitor’s typical movement .

For the “Are We There Yet?” installation, we used a PointGrey FireFlyMV camera with a wide-angle lens. The camera was situated a couple hundred feet away from the control computer, so we used a USB-to-Ethernet range extender to communicate with the camera.

We installed a color camera in a gallery in the Contemporary Jewish Museum in San Francisco, CA. We used Meyer Sound speakers with a high-end controller system, which enabled us to “position” sound in the space and to sweep audio tracks around at (the computer’s programmed) will. The Meyer Sound D-Mitri platform was controlled by the computer with Open Sound Control (OSC).

This view of the Yud Gallery is from the perspective of the computer running the analysis. This is a probabilistic view, where the brightness of each pixel represents the “belief” that the pixel is part of an interesting foreground object, such as a pedestrian. Note the hot spots corresponding nicely with the locations of the visitors in the image above.

This view of the Yud Gallery is from the perspective of the computer running the analysis. This is a probabilistic view, where the brightness of each pixel represents the “belief” that the pixel is part of an interesting foreground object, such as a pedestrian. Note the hot spots corresponding nicely with the locations of the visitors in the image above.

The hard work was to then program the computer to discern humans from floors, furniture, shadows, sunbeams, and cloud reflections. The gallery had many skylights, which made the lighting very dynamic. Then, I programmed the computer to keep track of people as they moved and found that this dynamic information was itself useful to determine whether detected color-perturbance was human or not.

Once complete, the experience of the installation was beautiful, enchanting, and maybe a little spooky. The audio tracks were all questions (e.g., “Are we there yet?”) and they were always spoken near you, as if addressed to you. They responded to your movement in a way that felt to me like dancing with a ghost. You can watch videos about the installation at www.are-we-there-yet.org.

The “Are We There Yet?” project opens itself up to possible use as an embedded system. I’ve been told that the software I wrote works on iOS devices by the start-up company Romo (www.kickstarter.com/projects/peterseid/romo-the-smartphone-robot-for-everyone), which was evaluating my vision-tracking code for use in its cute iPhone rover. Further, I’d say that if someone were interested, they could create a similar pedestrian, auto, pet, or cloud-tracking system using a Raspberry Pi and a reasonable webcam.

I may create an automatic cloud-tracking system to watch clouds. I think computers could be capable of this capacity for abstraction, even though we think of the leisurely pastime as the mark of a dreamer.

NAN: Some of the projects you’ve contributed to focus on switched linear systems, hybrid systems, wearable interfaces, and computation and control. Tell us about the projects and your research process.

ANDREW: I think my research is all driven by imagination. I try to imagine a world that could be, a world that I think would be nice, or better, or important. Once I have an idea that captivates my imagination in this way, I have no choice but to try to realize the idea and to seek out the knowledge necessary to do so.

For the wearable wireless accelerometers, it began with the thought: Wouldn’t it be cool if dance and music were inherently connected the way we try to make it seem when we’re dancing? From that thought, the designs started. I thought: The project has to be wireless and low power, it needs accelerometers to measure movement, it needs a reasonable processor to handle the data, it needs MIDI output, and so forth.

My switched linear systems research came about in a different way. As I was in class learning about theories regarding stabilization of hybrid systems, I thought: Why would we do it this complicated way, when I have this reasonably simple intuition that seems to solve the problem? I happened to see the problem a different way as my intuition was trying to grapple with a new concept. That naive accident ended up as a publication, “Stabilization of Planar Switched Linear Systems Using Polar Coordinates,” which I presented in 2010 at Hybrid Systems: Computation and Control (HSCC) in Stockholm, Sweden.

NAN: How did you become interested in electronics?

ANDREW: I always thought things that moved seemingly of their own volition were cool and inherently attention-grabbing. I would think: Did it really just do that? How is that possible?

Andrew worked on this project when computers still had parallel ports. a—This photo shows manually etched PCB traces for a digital EKG (the attempted EEG) with 8-bit LED optoisolation. The rainbow cable connects to a computer’s parallel port. The interface code was written in C++ and ran on DOS. b—The EKG circuitry and digitizer are shown on the left. The 8-bit parallel computer interface is on the right. Connecting the two boards is an array of coupled LEDs and phototransistors, encased in heat shrink tubing to shield against outside light.

Andrew worked on this project when computers still had parallel ports. a—This photo shows manually etched PCB traces for a digital EKG (the attempted EEG) with 8-bit LED optoisolation. The rainbow cable connects to a computer’s parallel port. The interface code was written in C++ and ran on DOS. b—The EKG circuitry and digitizer are shown on the left. The 8-bit parallel computer interface is on the right. Connecting the two boards is an array of coupled LEDs and phototransistors, encased in heat shrink tubing to shield against outside light.

Electric rally-car tracks and radio-controlled cars were a favorite of mine. I hadn’t really thought about working with electronics or computers until middle school. Before that, I was all about paleontology. Then, I saw an episode of Scientific American Frontiers, which featured Alan Alda excitedly interviewing RoboCup contestants. Watching RoboCup [a soccer game involving robotic players], I was absolutely enchanted.

While my childhood electronic toys moved and somehow acted as their own entities, they were puppets to my intentions. Watching RoboCup, I knew these robots were somehow making their own decisions on-the-fly, magically making beautiful passes and goals not as puppets, but as something more majestic. I didn’t know about the technical blood, sweat, and tears that went into it all, so I could have these romantic fantasies of what it was, but I was hooked from that moment.

That spurred me to apply to a specialized science and engineering high school program. It was there that I was fortunate enough to attend a fabulous electronics class (taught by David Peins), where I learned the basics of electronics, the joy of tinkering, and even PCB design and assembly (drilling included). I loved everything involved. Even before I became academically invested in the field, I fell in love with the manual craft of making a circuit.

NAN: Tell us about your first design.

ANDREW: Once I’d learned something about designing and making circuits, I jumped in whole-hog, to a comical degree. My very first project without any course direction was an electroencephalograph!

I wanted to make stuff move on my computer with my brain, the obvious first step. I started with a rough design and worked on tweaking parameters and finding components.

In retrospect, I think that first attempt was actually an electromyograph that read the movements of my eye muscles. And it definitely was an electrocardiograph. Success!

Someone suggested that it might not be a good idea to have a power supply hooked up in any reasonably direct path with your brain. So, in my second attempt, I tried to make something new, so I digitized the signal on the brain side and hooked it up to eight white LEDs. On the other side, I had eight phototransistors coupled with the LEDs and covered with heat-shrink tubing to keep out outside light. That part worked, and I was excited about it, even though I was having some trouble properly tuning the op-amps in that version.

NAN: Describe your “dream project.”

ANDREW: Augmented reality goggles. I’m dead serious about that, too. If given enough time and money, I would start making them.

I would use some emerging organic light-emitting diode (OLED) technology. I’m eyeing the start-up MicroOLED (www.microoled.net) for its low-power “near-to-eye” display technologies. They aren’t available yet, but I’m hopeful they will be soon. I’d probably hook that up to a Raspberry Pi SBC, which is small enough to be worn reasonably comfortably.

Small, high-resolution cameras have proliferated with modern cell phones, which could easily be mounted into the sides of goggles, driving each OLED display independently. Then, it’s just a matter of creativity for how to use your newfound vision! The OpenCV computer vision library offers a great starting point for applications such as face detection, image segmentation, and tracking.

Google Glass is starting to get some notice as a sort of “heads-up” display, but in my opinion, it doesn’t go nearly far enough. Here’s the craziest part—please bear with me—I’m willing to give up directly viewing the world with my natural eyes, I would be willing to have full field-of-vision goggles with high-resolution OLED displays with stereoscopic views from two high-resolution smartphone-style cameras. (At least until the technology gets better, as described in Rainbows End by Vernor Vinge.) I think, for this version, all the components are just now becoming available.

Augmented reality goggles would do a number of things for vision and human-computer interaction (HCI). First, 3-D overlays in the real world would be possible.

Crude example: I’m really terrible with faces and names, but computers are now great with that, so why not get a little help and overlay nametags on people when I want? Another fascinating thing for me is that this concept of vision abstracts the body from the eyes. So, you could theoretically connect to the feed from any stereoscopic cameras around (e.g., on an airplane, in the Grand Canyon, or on the back of some wild animal), or you could even switch points of view with your friend!

Perhaps reality goggles are not commercially viable now, but I would unabashedly use them for myself. I dream about them, so why not make them?

Q&A: Marilyn Wolf, Embedded Computing Expert

Marilyn Wolf has created embedded computing techniques, co-founded two companies, and received several Institute of Electrical and Electronics Engineers (IEEE) distinctions. She is currently teaching at Georgia Institute of Technology’s School of Electrical and Computer Engineering and researching smart-energy grids.—Nan Price, Associate Editor

NAN: Do you remember your first computer engineering project?

MARILYN: My dad is an inventor. One of his stories was about using copper sewer pipe as a drum memory. In elementary school, my friend and I tried to build a computer and bought a PCB fabrication kit from RadioShack. We carefully made the switch features using masking tape and etched the board. Then we tried to solder it and found that our patterning technology outpaced our soldering technology.

NAN: You have developed many embedded computing techniques—from hardware/software co-design algorithms and real-time scheduling algorithms to distributed smart cameras and code compression. Can you provide some information about these techniques?

Marilyn Wolf

Marilyn Wolf

MARILYN: I was inspired to work on co-design by my boss at Bell Labs, Al Dunlop. I was working on very-large-scale integration (VLSI) CAD at the time and he brought in someone who designed consumer telephones. Those designers didn’t care a bit about our fancy VLSI because it was too expensive. They wanted help designing software for microprocessors.

Microprocessors in the 1980s were pretty small, so I started on simple problems, such as partitioning a specification into software plus a hardware accelerator. Around the turn of the millennium, we started to see some very powerful processors (e.g., the Philips Trimedia). I decided to pick up on one of my earliest interests, photography, and look at smart cameras for real-time computer vision.

That work eventually led us to form Verificon, which developed smart camera systems. We closed the company because the market for surveillance systems is very competitive.
We have started a new company, SVT Analytics, to pursue customer analytics for retail using smart camera technologies. I also continued to look at methodologies and tools for bigger software systems, yet another interest I inherited from my dad.

NAN: Tell us a little more about SVT Analytics. What services does the company provide and how does it utilize smart-camera technology?

MARILYN: We started SVT Analytics to develop customer analytics for software. Our goal is to do for bricks-and-mortar retailers what web retailers can do to learn about their customers.

On the web, retailers can track the pages customers visit, how long they stay at a page, what page they visit next, and all sorts of other statistics. Retailers use that information to suggest other things to buy, for example.

Bricks-and-mortar stores know what sells but they don’t know why. Using computer vision, we can determine how long people stay in a particular area of the store, where they came from, where they go to, or whether employees are interacting with customers.

Our experience with embedded computer vision helps us develop algorithms that are accurate but also run on inexpensive platforms. Bad data leads to bad decisions, but these systems need to be inexpensive enough to be sprinkled all around the store so they can capture a lot of data.

NAN: Can you provide a more detailed overview of the impact of IC technology on surveillance in recent years? What do you see as the most active areas for research and advancements in this field?

MARILYN: Moore’s law has advanced to the point that we can provide a huge amount of computational power on a single chip. We explored two different architectures: an FPGA accelerator with a CPU and a programmable video processor.

We were able to provide highly accurate computer vision on inexpensive platforms, about $500 per channel. Even so, we had to design our algorithms very carefully to make the best use of the compute horsepower available to us.

Computer vision can soak up as much computation as you can throw at it. Over the years, we have developed some secret sauce for reducing computational cost while maintaining sufficient accuracy.

NAN: You wrote several books, including Computers as Components: Principles of Embedded Computing System Design and Embedded Software Design and Programming of Multiprocessor System-on-Chip: Simulink and System C Case Studies. What can readers expect to gain from reading your books?

MARILYN: Computers as Components is an undergraduate text. I tried to hit the fundamentals (e.g., real-time scheduling theory, software performance analysis, and low-power computing) but wrap around real-world examples and systems.

Embedded Software Design is a research monograph that primarily came out of Katalin Popovici’s work in Ahmed Jerraya’s group. Ahmed is an old friend and collaborator.

NAN: When did you transition from engineering to teaching? What prompted this change?

MARILYN: Actually, being a professor and teaching in a classroom have surprisingly little to do with each other. I spend a lot of time funding research, writing proposals, and dealing with students.

I spent five years at Bell Labs before moving to Princeton, NJ. I thought moving to a new environment would challenge me, which is always good. And although we were very well supported at Bell Labs, ultimately we had only one customer for our ideas. At a university, you can shop around to find someone interested in what you want to do.

NAN: How long have you been at Georgia Institute of Technology’s School of Electrical and Computer Engineering? What courses do you currently teach and what do you enjoy most about instructing?

MARILYN: I recently designed a new course, Physics of Computing, which is a very different take on an introduction to computer engineering. Instead of directly focusing on logic design and computer organization, we discuss the physical basis of delay and energy consumption.

You can talk about an amazingly large number of problems involving just inverters and RC circuits. We relate these basic physical phenomena to systems. For example, we figure out why dynamic RAM (DRAM) gets bigger but not faster, then see how that has driven computer architecture as DRAM has hit the memory wall.

NAN: As an engineering professor, you have some insight into what excites future engineers. With respect to electrical engineering and embedded design/programming, what are some “hot topics” your students are currently attracted to?

MARILYN: Embedded software—real-time, low-power—is everywhere. The more general term today is “cyber-physical systems,” which are systems that interact with the physical world. I am moving slowly into control-oriented software from signal/image processing. Closing the loop in a control system makes things very interesting.

My Georgia Tech colleague Eric Feron and I have a small project on jet engine control. His engine test room has a 6” thick blast window. You don’t get much more exciting than that.

NAN: That does sound exciting. Tell us more about the project and what you are exploring with it in terms of embedded software and closed-loop control systems.

MARILYN: Jet engine designers are under the same pressures now that have faced car engine designers for years: better fuel efficiency, lower emissions, lower maintenance cost, and lower noise. In the car world, CPU-based engine controllers were the critical factor that enabled car manufacturers to simultaneously improve fuel efficiency and reduce emissions.

Jet engines need to incorporate more sensors and more computers to use those sensors to crunch the data in real time and figure out how to control the engine. Jet engine designers are also looking at more complex engine designs with more flaps and controls to make the best use of that sensor data.

One challenge of jet engines is the high temperatures. Jet engines are so hot that some parts of the engine would melt without careful design. We need to provide more computational power while living with the restrictions of high-temperature electronics.

NAN: Your research interests include embedded computing, smart devices, VLSI systems, and biochips. What types of projects are you currently working on?

MARILYN: I’m working on with Santiago Grivalga of Georgia Tech on smart-energy grids, which are really huge systems that would span entire countries or continents. I continue to work on VLSI-related topics, such as the work on error-aware computing that I pursued with Saibal Mukopodhyay.

I also work with my friend Shuvra Bhattacharyya on architectures for signal-processing systems. As for more unusual things, I’m working on a medical device project that is at the early stages, so I can’t say too much specifically about it.

NAN: Can you provide more specifics about your research into smart energy grids?

MARILYN: Smart-energy grids are also driven by the push for greater efficiency. In addition, renewable energy sources have different characteristics than traditional coal-fired generators. For example, because winds are so variable, the energy produced by wind generators can quickly change.

The uses of electricity are also more complex, and we see increasing opportunities to shift demand to level out generation needs. For example, electric cars need to be recharged, but that can happen during off-peak hours. But energy systems are huge. A single grid covers the eastern US from Florida to Minnesota.

To make all these improvements requires sophisticated software and careful design to ensure that the grid is highly reliable. Smart-energy grids are a prime example of Internet-based control.

We have so many devices on the grid that need to coordinate that the Internet is the only way to connect them. But the Internet isn’t very good at real-time control, so we have to be careful.

We also have to worry about security Internet-enabled devices enable smart grid operations but they also provide opportunities for tampering.

NAN: You’ve earned several distinctions. You were the recipient of the Institute of Electrical and Electronics Engineers (IEEE) Circuits and Systems Society Education Award and the IEEE Computer Society Golden Core Award. Tell us about these experiences.

MARILYN: These awards are presented at conferences. The presentation is a very warm, happy experience. Everyone is happy. These things are time to celebrate the field and the many friends I’ve made through my work.

Electrical Engineering Crossword (Issue 281)

The answers to Circuit Cellar’s December electronics engineering crossword puzzle are now available.

281-Crossword-key

Across

4. VENNDIAGRAM—Represents many relation possibilities [two words]
5. PERSISTRON—Produces a persistent display
9. CODOMAIN—A set that includes attainable values
12. HOMOPOLAR—Electrically symmetrical
13. TRUTHTABLE—Determines a complicated statement’s validity [two words]
17. POWERCAPPING—Controls either the instant or the average power consumption [two words]
18. MAGNETRON—The first form, invented in 1920, was a split-anode type
19. MAGNETICFLUX—F
20. TURINGCOMPLETE—The Z3 functional program-controlled computer, for example [two words]

Down

1. CHAOSCOMPUTERCLUB—Well-known European hacker association [three words]
2. LOGICLEVEL—When binary, it is high and low [two words]
3. LINEARINTERPOLATION—A simple, but inaccurate, way to convert A/D values into engineering units [two words]
6. SYNCHRONOUSCIRCUIT—A clock signal ensures this device’s parts are in parallel [two words]
7. BOARDBRINGUP—Design validation process [three words]
8. HORNERSRULE—An algorithm for any polynomial order [two words]
10. MEALY—This machine’s current state and inputs dictate its output values
11. SQUAREWAVE—It is produced by a binary logic device [two words]
14. THEREMIN—Its electronic signals can be amplified and sent to a loudspeaker
15. ABAMPERE—10 A
16. SCOPEPROBE—Connects test equipment to a DUT [two words]