The New Yorker Fiction July 2020

Two of the fiction in the July 2020 issues of The New Yorker are Jack and Della by Marilynne Robinson was published July 20, 2020 and The Lottery by Shirley Jackson, originally published June 26, 1948 was republished July 27, 2020.

The story Jack and Della is a melancholy story about a young man who had recently been released from prison. He meets the teacher Della, and has a positive relationship with her. The story ends very sadly and the desperation and loss really touched me.

In the article, Marilynne Robinson on Expanding the World of ‘Gilead‘ also published July 20 discusses Jack’s position in the “Gilead” series of novels. In the first novel in the series, “Gilead,” Jack is a respectful and mysterious man who comes home to his family and then disappoints his family by leaving abruptly. He isn’t able to explain himself to anyone other than the minister John Ames. The fiction Jack and Della is adapted from the fourth book in the series, “Jack.”

The Lottery is disturbing and has the distinction of generating the most mail for a fiction piece. (“The Lottery” Letters) To me it ends very unsatisfying. The events that conclude the story are taken so matter-of-fact by the community and the anticipation of a horror as if it were a natural fact of life.

[Many of these links may require a subscription to The New Yorker.]

Sirens of Titan

I wanted to explore my speaker’s directionality by making a jig that could hold the microphone in fixed relative positions to the headphone. My overarching goal was to be able to isolate the behavior of the microphone from the behavior of the headphone speaker.

This is what I came up with. The use of hard, rigid, flat surfaces is significant, but not in the way I anticipated.

Jig for holding desktop microphone inside frame and speaker in position.

The slotted food boxes make a rigid frame with holes to allow the microphone to be placed in different positions. The shipping box is marked with a pencil outline so that the headphones can be placed consistently. The edge of the box fits against the slotted structure. I only used the speaker on the side that faces the microphone. I didn’t use the perpendicular speaker nor the microphone on the headphones.

Again, I did a sweeping sine wave. When I analyzed the results, I found an interesting waveform around 120Hz. In the first graph, the frequency was sweeping from about 118.8 Hz to 121.2 Hz. At first I thought that what I saw was some kind of audio interference pattern. But that didn’t make sense because the graph shows large changes between slight frequency changes (and thus slight audio wavelength changes.)

This graph covers about 33.5 seconds of recording. By slowing down the rate of change of the frequency, there are more samples over the course of the transition and noise interferes less. (The spike to the left was due to noise from a car passing or me moving on my chair.)

Magnitude of the sound recorded as the audio frequency swept from 118.8 to 121.2 Hz.

I was trying different adjustments to the configuration to identify the parts that are responsible for the resonance. My first try was apply force to the front wall of the food containers. This had only a small effect on the behavior. My second adjustment was to place crayons on the box out of the line of sight between the speaker and microphone. The resonance was completely gone in that case.

The third adjust I tried making was to put some weight on the box, also out of the line-of-sight. I placed several CD discs on the box. The lower one had some CDs laying on the box and there is an obvious change. The graphs aren’t synchronized.

Top sweep with unmodified setup, bottom with CDs on the shipping box

What I understand now is that these effects are due to resonances within the box that the headphones are on or between the headphone’s strap and the box. Changing the forces on the box caused substantial changes.

Another way that I visualize the data is to break the signal into equal sized blocks of time and perform a Fourier transform of the block and plot them as an image. Pixels closer to the bottom edge of the graph represent lower frequency components of the signal.

I found this strange shape in the first graph I created. I created graphs from other runs and none of them had anything like this.

Part of a chart showing Fourier transform of recording a siren passing

Then I remembered a fire truck siren that I heard a few blocks away when I was recording one of the results. It’s interesting to see the shape. It’s a repeating pattern of the tone rising rapidly, followed by the tone falling more slowly. I notice that that the same shape is repeated twice with difference delays which indicates there were two sound sources cycling at different speeds.

I had other things happen that I wasn’t looking for as well.

A “thump” from me moving the chair or coughing

I received a text while I was recording.

The tone for a text on my phone “Glass”

There were several smudges like this next one in the plots. They are due to cars passing. I was recording in the daytime so there was more traffic than at night.

Car passing

There is an unlimited list of sounds that I could analyze to see more interesting patterns.

I ended up finding another rabbit hole just by looking at one position of the microphone and haven’t explored how other positions differ. However, I may have seen enough to know that I haven’t found the key to need to isolate the speaker from the microphone. Without a more sophisticated setup, the environment is going to be a confounding effect. In addition, my jig only works with one microphone and different speakers can’t be positioned with an equivalent geometry.

Noise?

I’ve been doing new experiments analyzing the results of using the microphones without a pipe for resonance. I was expecting flatter results with less noise because of the removal of the resonator. What I found was a lot different.

There were two directions that my search took. One was to run the same geometric configuration with identical input signals or two that are only different in volume. The other direction was to use different speakers to help tease out what effects are by the frequency response of the microphone, the frequency response of the speakers and variation caused by echoes in my work area.

My audio source was a pure tone swept linearly between 40 Hz and 8000 Hz over a timespan of 4, 8 or 12 minutes. Because the sweep is linear, the right half of each graph covers about one octave while the left half shows about ten. That would indicate that I’m emphasizing only a small part of the sound spectrum. I started working with a linear sweep to show as many resonance peaks as I could. That led to that emphasis.

The first effect I found was that the same configuration creates the same signal. I thought that the oscillating waveforms would an effect of random noise. The surprising part is that although it looks like a noisy waveform, it’s a reproducible and pretty consistent.

This graph shows two runs with the same speaker and microphoone in the same geometry but different volume input signal. There were minimal adjustment to get the graphs to line up. However, if they lined up perfectly, there would be no blue.

One interesting measurement is that temporally stretching the sweep into different duration scans also have a similar consistency in different runs.

The way I get these graphs is to record the microphone and then break the waveform into short chunks that are delimited by zero crossings of the signal. Each chunk has its samples squared and the square root of the average recorded.

Although the graph above looks pretty noisy, because the graph is consistent, there’s more going on. I performed the same chunking with the raw input signal below. There is a little noise, but it is substantially smaller than the variations in the above signal.

The x axis of each graph is indexed by the chunks in sequence.

The other question that I would like to answer is the manner that the speaker or microphone have different frequency response curves. I took three speakers that I have and ran the same input sequence. I couldn’t get the geometry of the speakers identical between the runs, so the effects of reflections off objects in the room are an unexplored effect.

What I saw when I analyzed the graphs and placed them together is that there is a big variation in the sounds recorded from each speaker. I don’t see anything that is obviously due to distortion from the microphone. I can’t say that it isn’t there but the effects of the geometry and the difference between the speakers appear to swamp any effect of the microphone.

I’d like to do more work exploring the effects of changing the geometry on the results as well as trying to identify the frequency response of each part of the system, microphone, speaker and room configuration. I’m not confident that I have enough data streams available to separate them.

One thing I learned is that making recordings during the day is fraught because of noisy traffic, construction work or lawnmowers. In the evening, the external noise sources are much lower. Another thing I learned is that collecting this data is time consuming. Each run takes 4 – 8 minutes which adds up.

One goal is to make some jigs so that I can reproduce the geometry from one day to the next.

Musical instruments and resonance

I’ve started a project exploring musical instruments and the physics controlling their audio properties. Mostly I’m interested in brass instruments like a trumpet or trombone‒instruments that are tubular for much of their length. Brass instruments have a constant diameter at their beginning. As the tube approaches the end, the instruments become more conical until terminating in a flared bell. I chose them because I played the trumpet in high school. It’s familiar.

One book that I’m using to help understand what is happening is “The Physics of Musical Instruments, 2nd edition” by Neville H. Fletcher and Thomas D. Rossing. It has quantitative descriptions of the properties of real instruments.

One interesting idea is to consider brass instruments as “reed instruments.” For a brass instrument, the “reed” is the lips of the performer. This allows brass instruments to use the same equations as woodwinds. As a first approximation, lips and reeds have similar properties of interrupted air flow. It does make a difference whether the opening closes with increasing pressure or opens with increasing pressure so the analogy has its limits.

My first experiments have been with a pipe resonating at different frequencies. My method of creating data is to input a sweeping pitched sound to one end of a pipe with a speaker. The pipe resonates at different frequencies so that the intensity of the sound so the other end varies over time. This is a example configuration with headphones presenting the sound on the right end and a microphone picking up sound on the left. I haven’t calibrated the frequency response curve of the microphone and speakers.

For example, when I sweep the input sine wave from 50 Hz to 2000 Hz over 2 minutes on one end of a 1m 1/2″ PVC tube, the amplitude from the other end creates this graph. I measure the amplitude as rms (root mean square) by squaring the values of each sample in a block and then taking their average. This helps in comparing one block to the next.

time vs. amplitude

One thing I notice with such examples is that as the frequency goes up, there is more and more noise in the wave form. The shapes become more ragged. It should be easy to identify the time of the different peaks and thus their frequency but this and other sources of noise interfere.

If I take above run and make an image of its frequency distribution, I get this. The Y axis isn’t calibrated, but starts at 0Hz at the bottom. This chart has the whole duration of a single observation session. The graph above is trimmed to exclude the times that I wasn’t activating the system.

Time vs. frequency

An interesting feature of the graph are the higher overtones from the input sweep. They show up as lines with higher slopes than the main output. This example, I can see 4 extra lines, but different configurations of microphone and pipe may show only one or two. (The third overtone is barely visible above the middle of the run.) Also, if I look closely, I see very faint equispaced horizontal lines. I suspect that those are from my computer fan but I haven’t verified it.

The gray noise at the bottom of the graph are different noises from within my house. I haven’t identified the causes of those or their frequency. Some of the graph is marked with mechanical bumps that show up as lines starting at zero hertz. The vertical features centered on the main input frequency are a common feature of these charts. I’m not sure whether they are real or are an artifact of my processing.

(This representation doesn’t help me identify the position of the peaks.)

An interesting adjustment is needed when I break the signal into chunks. For the Fourier transform or other analyses, I need to block the chunks so that they end at the zero crossings of the input waveform. I pick a minimum number of samples for a block and then search further for the next positively sloped zero crossing. If I don’t do that, the sharp edges at the ends of a block add artifacts that hide real effects. The software I’m using for FFT, FFTW allows me to have non-power-of-two long blocks which is essential for seeing useful results.

Who do I see in the mirror?

One way to understand a complex system is to locate its holes and find what normally fills them. The brain is a system like that and one way of identifying functions of the brain is to describe deficits.

Examples include aphantasia and face blindness. Aphantasia refers to the inability to form visualizations in ones imagination. Face blindness (prosopagnosia) describes the inability to recognize faces. There are many other deficits, each with a different set of symptoms.

The change in capability could be due to a malfunctioning part of the brain or a disruption in the connection between areas. Perhaps an injury or disorder has damaged part, pointing toward the purpose of that region. Sometimes the affected area of the brain is well understood.

For me, I can recognize people really easily. It doesn’t take me looking at a person ‘s face to identify them. The face is an easy point of access to knowing who a person is. However, looking at a person from behind is often enough for me to know who I’m approaching.

The hole that puzzles me is the difficulty of recognizing myself. I can see photos of me or look at myself in a mirror. I don’t think that it is someone else, but rather it’s a conscious act to recognize that it is me. Old pictures or new, none of them look like “me.” I just don’t feel the same connection to myself that I do with other people.

It seems that this would be something a psychoanalyst might have comments on, but therapists and psychiatrists don’t hear anything alarming in this. It’s more “That’s interesting.”

There isn’t a strong emotional impact on me with the issue, just that it seems atypical of how most people react to their picture. I don’t know.

I can recognize you, but I can’t recognize me.

Gasoline and a Polyester Suit

I was putting away my laundry and realized how little I know about my clothes. It’s a wide span of ignorance covering something I interact with every day. Like my superficial knowledge of transportation, I trust the experts who make high quality garments to know how to create them.

A first level of ignorance involves the fabrics that clothes are made from. Dacron, cotton, linen, polyester, and wool just start the list of fibers. My list is short and shallow. I know some of them are natural, made from plants or animals. Others are synthetic, usually polymers, and are a recent invention. I know fabrics can be made from a combination of these substances. Some shrink when they are washed, others can be damaged in a clothes dryer set too hot.

What started me reminiscing on this began when I was looking at my laundry and wondering “Who designed this garment?” “How was it manufactured?” “What attributes were the designers considering?” “What is the science behind the little differences from one garment to the next?” “Who did the labor to put it together?” “What steps were automated?”

My cousin made a dress in the style of Jane Austen’s time. I also have the tools to make my own shirts, but don’t have the skills to be successful. I’d like to be better able to use my sewing machine, but I haven’t put in the effort. I’ve got thread and know where I can buy yards of cloth, find a pattern, and even get training. The whole exercise isn’t about the economics of clothing but rather the satisfaction of developing a new skill and making something to demonstrate that I have done so.

My Grandmother was skilled at crochet. My sisters, cousins and I have afghans that she made. It is a nice memento to keep her in my mind. The issues involved with those blankets are lost on me but it is a reminder of her love.

Transportation, I start by saying I don’t know the chemistry of gasoline and how it is manufactured. Next, I only have a cursory understanding of the physics behind the internal combustion energy. My vehicle seems like a straightforward object even though I know that it is not. Part metal, part plastic, it does the work to turn the wheels and follow my steering, but I don’t really understand the how and why. A simple example is that I can’t repair a door latch nor explain its mechanical principles.

In another facet of transportation, my knowledge of how roads are made, is mainly gleaned from watching construction teams working on a highway as I drive past–that’s horribly superficial. I know that there are inspections and standards for roads. The purpose of those regulations are to make roads reliable. I don’t see the calculations made in the design of bridges, but I do drive on them.

One of my shirts shows a simple design change that is evidence of its designer’s intervention. The bottom buttonholes of some of my button down shirts have a horizontal opening instead of the vertical buttonhole of the rest. That makes sense to me because it helps prevent the bottom button from popping open. Just as the top button is almost universally horizontal, these horizontal bottom holes were an insight by its clothing engineers. This gives me a a tiny window into the process of design and manufacture.

There’s so much I take for granted that someone else has expertise in. I don’t begrudge those experts and am glad when my car gets me home and my seams don’t rip.

It’s foolish to attack scientists and experts who use their expertise and advanced knowledge. Just because I don’t understand some point of that knowledge, doesn’t validate my rejection of it. Although I can wonder and try to learn more, I don’t reject them as “elites” and deny their science.

Worse than rejection is to impugn bad faith on professionals through conspiracy theories and denial of their commitment to ethical principles. One friend reminds me if you spot it, you got it. Shadowy accusations of bad faith and conspiracy are actually an indictment of their accuser’s bad faith, not a sign of insight, wisdom or superiority.

Plant after the risk of frost is gone

This year, that’s dragging on. The forecast still includes frost every few days.

This weekend, I bought some sunflower, zucchini and radish seeds. I was going to buy some cantaloupe, but the package suggested they should be started a few weeks before the last frost which is probably gone.

I’m climbing up the learning curve for gardening.

My big jump this year is to put down some bricks around the garden. Tomorrow, I need to measure things out. I also might make paths through the middle of the garden so that everything is within arm’s reach of a path.

I’m also looking toward buying peas. I’ve never tried growing them before.

At Home Depot it didn’t seem that there was any run on garden seeds. The racks were completely full. However, the store was really busy Saturday afternoon! It was a bright sunny day and people were coming out of their isolation.

I tried to call 811 but my phone said the service wasn’t available to me. I made my mark-up request on the Indiana web site instead.

Flash and malware

I was looking around recently and found some really despicable ads on websites.

They offer to provide updates to Flash. Since Flash isn’t supported any more, I can only surmise that these are actually trojans trying to attack peoples’ PCs.

People get error messages that their Flash isn’t working and these ads prey on people who don’t know that the purported update is a trick.

There’s so much information to transmit about changes in computer infrastructure. Getting it out to the people who need it is a big job!

Uber Eats and DoorDash for my car

It’s relatively easy to sign up to drive for Uber Eats and DoorDash. The car insurance situation is more fraught. To an insurance company, there are three coverage windows: when you’re logged in and waiting, when you’ve agreed to a job and are on the way to a pickup, and when you’re transporting the food.

I contacted my insurance company, Liberty Mutual. They offer an amendment that removes some exclusions from my original policy. That amendment extends my coverage to the logged in and waiting window.

Uber has done the work needed to provide insurance coverage for its drivers. Uber maintains commercial auto coverage policies for drivers in every state. I’ll always be covered while I’m working for Uber because their insurance is compatible with mine. Uber also offers insurance for damage to my vehicle when I’m earning fares but it’s at a high deductible. I need the amendment to have damage covered while I’m waiting for a call and to have the Indiana mandated under/uninsured motorist coverage for that window.

I believe DoorDash has not thought about it as thoroughly nor with the drivers in mind. They have “excess auto insurance” for the time you’re transporting the food. You can only file with them for liabilities that exceeds your normal insurance company’s limits. This is a problem: my normal insurance company’s limits are zero while I’m underway because of policy exclusions. Also, this isn’t compatible with my amended insurance because it leaves a gap of no coverage between when I’ve agreed to a job and I pick up the food to deliver. Beyond those problems, they don’t cover damage to my auto at any time. Their website doesn’t say that they include the required under/uninsured motorist liability. Reading the text carefully, they don’t even cover my own injuries either!

In addition to the coverage gap, DoorDash’s coverage pays the excess once my regular insurance company settles. Health insurance has rules to handle a first and second payer, but a second payer don’t seem like a “thing” with auto insurance. Normally, when I get coverage by one policy, the old policy ends. With DoorDash, if either insurance company is recalcitrant, I will have (a lot of) trouble getting things settled. Also, I have experience with being sued after an accident. Liberty Mutual took care of everything at the time. Since a lawsuit can come a couple of years after the accident, I’m not confident about DoorDash’s anonymous underwriter.

If there’s an accident, Indiana requires me to provide proof of insurance. I don’t see how to fulfill that with DoorDash if the accident happens in the large window where Liberty Mutual doesn’t cover me. Uber provides a certificate of insurance that I can keep in my car. I don’t have any information about what company DoorDash uses; not even verification that it’s licensed in Indiana.

In conclusion, I can’t drive for DoorDash because I have a gap in coverage between when I accept an order and pick up the food. I won’t have coverage for myself nor my property. In addition, the process of making a claim to them is inherently intimidating. For Uber, I need to weigh out the money earned vs. the exposure of a higher comprehensive deductible.

GPU Divorce

I’ve got a couple common applications on my Window 10 system… Adobe Photoshop and Microsoft Office.

Photoshop is obviously graphic intensive. It benefits from a good GPU. I had assumed that Microsoft Word and Excel wouldn’t care about GPU settings at all.

My system has an on-board Intel HD Graphics 4600 driver. It’s powerful enough for someone who doesn’t play video games. It also has ports for 3 displays. I made a neophyte mistake and didn’t realize that two of the connectors on the motherboard are Display Ports. I hoped to do CUDA development as well as have 3 monitors, so I bought an nVidia card that had two outputs so that neophyte me knew that the PC could handle 3 more monitors. I upgraded it this year with an GeForce GT 1030 nVidia compatible… Not powerful enough for serious game play, but within my budget.

The problem:

Sometimes Photoshop would get in a state that it couldn’t open anything nor create new images. I hoped that an upgrade of the video card and an upgrade of the version of Photoshop would fix the problem but I was left right where I started.

I contacted Adobe support and after some work, found that the solution: Disable the motherboard video drivers and only open photoshop on a monitor tied to the nVidia card. I believe this works because Photoshop now knows which GPU to use and there’s no inter-GPU data transfer.

Then, I had a new problem, Microsoft Word and Excel became horribly sluggish. Really bad! Long story short, the solution to that appears to be only run Word on the monitor connected to the Intel graphics card.

My video cards are not playing nice. I would say they’re getting ready to have a divorce. The nVidia card is going to take custody of Photoshop while the Intel is running away with Microsoft Office.


  • CUDA is a software technology for accessing the parallel resources on nVidia cards in C++. I’ve never actually used it, so my use of CUDA is still only aspirational.