11. CD4000/74HC logic for moving a device with emergency brake

1. DESIGN
1.1. PRODUCT IDEA

Based on the the CD4000 and 74HC-series integrated circuits (and perhaps the 555 timer), I need a schematic that implements the following logic (in general):

1) Move a motor (lift) up or down for a predefined time (in seconds)

2) Time could be configured via 8-stage DIP switch

3) An emergency break should also be included (either in Normal Open or Normal Close manner). It should trigger reset to the time and toggle the direction of the next movement.

4) Start condition should be enabled as series of 3 square pulses.

Expected ICs to be involved include:

NE555P — Timer 555 (at ~2Hz, used as Clock for the entire circuit)

CD4020BE — 14-STAGE BINARY/RIPPLE COUNTER

CD4040BE — 12BIT BIN RIPPL COUNTER

CD4060BE — 14-STAGE COUNTER/DIVIDER AND OSCILLATOR

CD4013BE — 2 D-TYPE FLIP-FLOP

CD4093BE — 4x2-INP NAND SCHMITT TRIGGER

CD4081BE — QUAD 2-INPUT AND GATE

CD4021BE — 8-STAGE STATIC SHIFT REGISTER

74HCT109–2 J-K FLIP-FLOPS WITH PRESET AND CLEAR

SN74HCT00N — 4x2-INP NAND

SN74HCT04N — 6 INVERTER

CD4001BE — 4 x 2 INP NOR

2. DEVELOPMENT ROADMAP
2.1. links
2.1.1. CD4000
https://pdf1.alldatasheet.com/datasheet-pdf/view/26835/TI/CD4000.html
datasheet on this component, seems like a hardcoded part of FPGA with some logic units implemented as hardware parts with inputs, outputs.
2.1.2. 74HC
https://www.futurlec.com/74HC/74HC00.shtml
datasheet for 74HC, same as CD4000.
2.1.3. CMOS examples
https://hackaday.io/projects?page=1&tag=cmos
just cmos projects on hackaday.io
https://hackaday.io/project/9731-blinking-things
https://www.tindie.com/products/davedarko/starblinken-diy-kit/?utm_source=hackadayio&utm_medium=link&utm_campaign=project_buynow#specs
An example of CMOS project with a timer.
https://hackaday.io/project/4271/logs
http://castlerocktronics.com/modular/articles/CR-000_-_Power_Supply_and_System_Overview.pdf
http://castlerocktronics.com/modular/articles/CR-001_-_4xSQUARE.pdf
http://castlerocktronics.com/modular/articles/CR-002_-_Output_Mixer.pdf
http://castlerocktronics.com/modular/articles/CR-003_-_4xLFO.pdf
http://castlerocktronics.com/modular/articles/CR-005_-_R-2R.pdf
Yet another cmos project. Has a good documentation. Seems like required steps are build documents (photos, layout, schematic, bill of materials, drill template), system overview.
https://hackaday.io/project/168157-ttl-binary-clock
Once again cmos project. Pictures of PCB board, schematic, demo.
https://hackaday.io/project/168075-dtl-binary-clock/details
Another cmos project.
https://hackaday.io/project/167443-crystal-tester
CMOS project with some ideas on timer.
https://hackaday.io/project/28602-magnetic-pendulum
Pendulum based on CMOS logic.
https://hackaday.io/project/28344-10-year-led-flasher
CMOS project that has a low power led flasher.
https://github.com/nguyengiahy/EEE40002
Schematic for some IC boards. Can be useless.
2.2. It’s mostly electronic engineering project. It’s hard to reuse some open source components. That’s hard to consider as a product idea as well. As a conclusion may say that CMOS based hardware allows cheap mass manufacturing of simple manipulators that are low power and reliable. To integrate the device into some cloud processing, would require a separate IoT contorller and including communication between two devices into schematics.

12. Odoo api to Wacom STU-430 G in sign module

  1. DESIGN
    1.1. PRODUCT IDEA
    We need to create a api from the sing module in odoo enterprise V14 that enable sign tablet wacom STU-430 G, this can be done by sdk or we foud phyton library.
    2. DEVELOPMENT ROADMAP
    2.1. links
    2.1.1. Odoo signature support
    https://www.emiprotechnologies.com/technical_notes/odoo-technical-notes-59/post/how-digital-signature-works-in-odoo-a-functional-overview-496
    https://www.odoo.com/app/sign-features
    https://github.com/odoo/odoo/issues?q=is%3Aissue+is%3Aopen+signature
    https://github.com/odoo/odoo/search?q=signature
    Seems like signature support is present. Can be available for enterprise version only perhaps.
    2.1.2. Wacom API/SDK
    https://developer-docs.wacom.com/stu/docs/api-guide
    https://gist.github.com/timothyb89/addfa3483ca81c581841
    https://github.com/timothyb89/wacom-configurator
    https://github.com/topics/wacom-tablet?l=python
    https://github.com/Wacom-Developer/
    Wacom tablets have C++/python APIs. But in general its not clear what for it is needed. Since it should operate as a touch device. Frontend of Odoo is web based. Connecting it to a tablet would require some browser extension perhaps.
    2.2. An interesting feature request. But require some more details on the use case. Hard to consider as a startup idea. Since signing functionality in general is widely present. Maybe, someone wants to save up on enterprise version.

13. Golf club annotating app with ai tracking

1. DESIGN
1.1. PRODUCT IDEA

I please need a golf club analysis application developed based on computer vision. Club movement in a video needs to be precisely tracked, graphically reconstructed for reference, and a mathematical solution(s) presented. The project has been failing most recently due to insufficiencies in all auto-tracking features attempted, but this has been greatly simplified now to just a manual tracking system initially. It broadly consists of the following:

1) Inputting a video that could be as long a 10–15 seconds long;

2) Reformatting the video to add frame numbers and/or time code, and converting different input formats into a single workable format as warranted;

3) An ability to analyze the reformatted video. Efficient operational speed and frame-by-frame viewing both forward and backward is crucial, with a feature to download the reformatted video (if a web application) for analysis in a local player if desired;

4) A section to input premeasured data about the club analyzed, including but not limited to club locations where a user attaches tracking markers to reference, and a connected interactive graphic that simulates the club and displays the information input;

5) An ability to select desired frames/times from the reformatted video for further analysis in the application. Selection could be a range of frames or any number of frames individually selected as examples;

6) An ability to view and manually, efficiently place and adjust club tracking points over the reference tracking markers in each of the selected frames. No auto-tracking system is needed as the number of frames to be analyzed will initially be quite limited;

7) Creating an interactive graphic of club movement based upon the tracking points set in 6), and;

8) Using the tracking data to calculate and display rotation point location values along the length of the club for club movement.
2. DEVELOPMENT ROADMAP
2.1. links
2.1.1. golf swing analyzer products
https://outdoormoran.com/best-golf-swing-analyzers/
a review on Arccos, Zepp, Game Golf Live Tracking System, Rapsodo, Voice Caddie Golf SC100
https://buy.garmin.com/en-US/US/p/605172
tracker for a club from garmin
https://www.swinguru.com/golf/
https://www.k-motion.com/
https://www.swingprofile.com/
https://eu.arccosgolf.com/
few more products.
https://apps.apple.com/us/app/swing-profile-golf-analyzer/id1039981052
https://apps.apple.com/us/app/golf-swing-analyzer/id1147297031
https://apps.apple.com/us/app/zepp-golf/id738428692
IOS apps.
2.1.2. research
https://arxiv.org/search/?query=golf+%28swing+or+club%29&searchtype=all&abstracts=show&order=-announced_date_first&size=50
https://arxiv.org/abs/2105.10153
https://arxiv.org/pdf/1903.06528.pdf
https://github.com/wmcnally/GolfDB
https://link.springer.com/article/10.1007/s11042-020-10096-0
Research papers. Mainly GolfDB has been published. Which is about key events detection based on a monocular video of a player doing a kick.
2.2. There’re some hardware products, as well as research on a typical video analysis approach. Models by itself are not that much intersting. A question is what novelty does CV approach would be bring comparing to a hardware one. Original product idea is about building a comfortable annotation application for create something alike to GolfDB dataset. Maybe for a better accuracy when creating a proprietary solution. As initial analysis should be enough to discuss further details.

14. obd2 can bus cars diagnostics

1. DESIGN
1.1. PRODUCT IDEA
I need help with converting CAN bus messages from an OBD2 port from CAN arbitration ID’s to OBD2 pids using dbc files or ISO14229 UDS.
2. DEVELOPMENT ROADMAP
2.1. links
2.1.1. can bus, odb2 open source
https://www.csselectronics.com/screen/page/can-dbc-file-database-intro/language/en
a good documentation on odb2 and can being used to access information from cars, heavy-duty vehicles. Contain protocol description, use cases, ready-to-use tools to access the data, ready-to-use hardware products.
https://github.com/genivi/candb/tree/master/tests/dbc
https://github.com/proemion/candb
https://github.com/skysky97/candb
https://github.com/wangbuhui/candb
https://github.com/oguzbakir/obdiipy
https://github.com/brendan-w/python-obd
Various open source tools to program a custom data analysing tool.
2.2. In general the domain is clear. A question is about what particular issues might happen for paritcular vehicles. Is likely to be discussed in details before doing further steps.

16. Chest Radiography Analysis for COVID-19

1. DESIGN
1.1. PRODUCT IDEA
There’s some kaggle competition with a data published, as well as a set of partially working kernels. Some of those can be used for model ideas, as well as testing quickly performance. That should be way faster to going from arxiv.org papers, or github repos. Much closer to the actual problem.
2. DEVELOPMENT ROADMAP
See more at https://www.kaggle.com/ipythonx/covid-19-segmentation-loss-for-classifier-model#1368009

  1. links
    1.1. https://www.kaggle.com/c/siim-covid19-detection/discussion/245323
    1.2. https://www.kaggle.com/ipythonx/covid19-detection-890pxpng-study
    1.3. https://www.kaggle.com/c/siim-covid19-detection/leaderboard
    https://www.kaggle.com/c/siim-covid19-detection/code?competitionId=26680&sortBy=voteCount
    1.4. http://demos.md.ai/#/bone-age
    1.5. https://pubs.rsna.org/doi/pdf/10.1148/radiol.2021203957
    1.6. https://arxiv.org/abs/2006.01174
    1.7. https://arxiv.org/pdf/2006.01174.pdf
    1.8. https://www.kaggle.com/andradaolteanu/siim-covid-19-box-detect-dcm-metadata
    another kernel, working on the same dataset. would be interesting to compare accuracy and methods with this one. nice histograms on some properties, examples of working dicom format. some advertisement of wandb tool. no models applied though.
    1.9. https://www.kaggle.com/ayuraj/train-covid-19-detection-using-yolov5
    one more kernel. this one has model and some accuracy. still reading it.
    Again advertisement of wandb. Can’t test its predictions file as a submission. Useless.
    Has errors in submission format. Still checking its score on image labels prediction.
    1.10. copy paste of dummy submission gets 0.100 score
    score screenshot
    1.11 kernels created so far to test stuff for the competition
    1.11.1. https://www.kaggle.com/fabienbenot/train-covid-19-detection-using-yolov5
    this generated an output .csv file, uses pretrained weights, works pretty fast. Still the output by itself is wrong, and kaggle complaints with an error upon submission. Wasted 5–6 attempts per day, got set a 15 hours cool down period. Still a question how good only opacity prediction should work with that yolov5 model, Which has got around 0.13MAP. A sample submission scores 0.100. Can’t test this one.
    1.11.2. https://www.kaggle.com/fabienbenot/covid-19-segmentation-loss-for-classifier-model
    tried to add test set predictions with a model from this kernel. Wasted 2–3 days already. Not going to finish with it. Its a separate question what way to score study with multiple images, should it be a majority voting, or something else. A part from that, should be pretty straight forward to apply a pretrained model from this kernel to test set of resized images. It’s also funny, that pydicom library can’t get pixel_array without few more python dependencies, that’re likely to require internet connection to be installed. Which makes a kernel not legitimate to be submitted as result for the competition.
    1.11.3. https://www.kaggle.com/fabienbenot/competition-1-dummy-submission-notebook
    This is a dummy kernel. Tried to copy paste .csv file from yolov5 model training. A sample file has got accepted. Yet the one from yolov5 has issues. Discovered that bounding box order has been violated. Also capital letters for some classes. Definitely an output file is not in correct format for the competition scoring algorithm to process. Also wasted 2–3 days alreayd, not going to continue on it. ALso thought to merge there a classification model for study images as well.
  2. updates
    2.1 still reading the notebook source code. don’t have anyting useful to add on top. Seems like just copy pasting this kernel as a submission is not legit. Nice way to harden the life of others).
    2.2 It’s a pity this code doesn’t generate submission output based on test study images.
    2.3 So in general found image forecasting kernel as well. But a general issue, is that kernels do train some models, do some processing. Yet none of those can be used with a touch of a single button to submit into a competition. Which is a fast way to test, whether a solution has some value. Wasted 2–3 days already.

17. Review on NodeJS malware with UDP writeup

1. DESIGN

1.1. PRODUCT IDEA

Seems like some malware that uses NodeJS for logic scripting, as well as UDP for network communication.

A more detailed review at https://fumik0.com/2021/06/24/lu0bot-an-unknown-nodejs-malware-using-udp/

Not clear what security product might be built with that. Let’s just review anything around and see.

2. DEVELOPMENT ROADMAP

2.1. links

2.1.1. https://medium.com/csis-techblog/gcleaner-garbage-provider-since-2019-2708e7c87a8a
kind of distributor of the malware. have no idea what way to use it.

2.1.2. https://www.ipvoid.com/ip-blacklist-check/
https://www.threatcrowd.org/ip.php?ip=58.158.177.102
https://www.ipvoid.com/ip-blacklist-check/
https://www.blockedservers.com/blocked/ipv4/5.188.206.211/
The report mentions few ip addresses and domains. All of them are black listed by some spam checking platforms. Can be used as an indiciator of malicous activity tracking.

2.2. Would be good to have a malware sample as well as some open source sample analysis like with anyrun platform or cuckoo one. By itself, have no idea what way to continue with it.
2.3 few more links from https://twitter.com/benkow_
2.3.1. https://www.virustotal.com/gui/file/b93b8b99bdc14cb119ca0a51fe57c2da5aaa45d52a3f7121d31d675e4f900400/details
2.3.2. https://malshare.com/sample.php?action=detail&hash=c795c8a54b85afb25448b4a44cd0b3d1
2.3.3. https://www.virustotal.com/gui/file/28918d35a5f4103695d04817fd2ac7de977d316a0cc94dad3b3f124f030686bc/behavior/VirusTotal%20ZenBox
2.3.4. https://malshare.com/sample.php?action=detail&hash=09353c5898ccf513210a58fb9bb369e7
2.3.5. https://www.virustotal.com/gui/file/22934e006b3f1b8225c51a93ce0acaa1874c4f1dc895fa1664bdf16b0065d2e7/detection
2.3.6. https://www.virustotal.com/gui/latest-comments
2.3.7. https://www.virustotal.com/gui/top-users

2.3.8. https://www.virustotal.com/gui/user/benkow_
2.4. well virustotal is a good platform, alike to kaggle but for malware researchers. Has a ranking system, trust system, recent activity tracking, as well as good for networking within security researchers. Also each virustotal report has a good initial coverage of the malware samples, including what products detect it, as wlll as activity fingerprinting to check manually, quite many samples are available for a fetching from malshare.com (requires registration which is free, to download the file actually).

2.5. So a write up by fumik0 can be considered alike to a kaggle kernel. So it is hard to be treated as a product idea. Any one interested in security products can contact for a further discussion.

Freelance for artificial intelligence domain