博士論文の執筆した時に作った,チェックリストをスライドにまとめました.
This slide is only for Japanese speakers
他に参考になるページ
+修士論文の作り方( http://itolab.is.ocha.ac.jp/~itot/lecture/msthesis.html ) by 伊藤先生
+修論(D論)参考( http://d.hatena.ne.jp/rkmt/20101217/1292573279 ) by 暦本純一先生
- Android Direct Boot allows alarms and notifications to function even when the device is rebooting or has been idle for a long period of time. It does this through the use of AlarmManager, setAlarmClock(), Direct Boot APIs like createDeviceProtectedStorageContext, and Foreground Services.
- The app uses AlarmManager, setAlarmClock(), and intents to set repeating alarms that will trigger even when the device reboots or enters Doze mode. It stores persistent data like alarm settings and schedules using Room SQLite database with a Direct Boot compatible context. A Foreground Service plays alarm audio and vibrates even when the app is in the background.
博士論文の執筆した時に作った,チェックリストをスライドにまとめました.
This slide is only for Japanese speakers
他に参考になるページ
+修士論文の作り方( http://itolab.is.ocha.ac.jp/~itot/lecture/msthesis.html ) by 伊藤先生
+修論(D論)参考( http://d.hatena.ne.jp/rkmt/20101217/1292573279 ) by 暦本純一先生
- Android Direct Boot allows alarms and notifications to function even when the device is rebooting or has been idle for a long period of time. It does this through the use of AlarmManager, setAlarmClock(), Direct Boot APIs like createDeviceProtectedStorageContext, and Foreground Services.
- The app uses AlarmManager, setAlarmClock(), and intents to set repeating alarms that will trigger even when the device reboots or enters Doze mode. It stores persistent data like alarm settings and schedules using Room SQLite database with a Direct Boot compatible context. A Foreground Service plays alarm audio and vibrates even when the app is in the background.
Core ML 3 was announced at WWDC with new features for the Core ML API. The Core ML framework allows importing machine learning models in the .mlmodel format, including updates to supported model types and operations defined in protobuf files. Core ML Tools was also updated with over 3500 new models and operations supported for conversion between Core ML and other frameworks like TensorFlow and PyTorch.
1. The presenter compared the graphics rendering performance of Metal to UIImageView to learn about GPU usage.
2. Metal was initially 10-20x faster than UIImageView for rendering images but was found to be slower after further analysis and optimization of the measurement code.
3. Two key problems were identified with the Metal implementation: processing on the CPU was blocking the GPU, and texture loading was a bottleneck.
4. Optimizations including combining operations, caching textures, and ensuring resources were in GPU memory improved the Metal performance.
This document discusses implementing deep learning on iOS using various frameworks. It provides an overview of Metal Performance Shaders (MPSCNN), Accelerate (BNNS), Core ML, and Vision. It then details the 3 step process to implement a deep learning model with MPSCNN: 1) create the model, 2) implement the network, and 3) perform inference. Examples of logo detection and increased performance are shown. Core ML and Vision provide easier implementations compared to needing Metal knowledge for MPSCNN. BNNS may be better for small networks due to reduced CPU-GPU communication costs.
The document discusses client-side deep learning and introduces MPSCNN, a library that allows running convolutional neural networks on iOS devices using Metal Performance Shaders. MPSCNN can import trained models from frameworks like TensorFlow and run them to perform tasks like object detection on images at 60 times per second. Client-side deep learning could enable new mobile applications for areas like self-driving cars, AI assistants, and cancer detection by taking advantage of on-device processing power.
I gave this talk in Jerusalem, Israel, and Palestine in 2016 with following schedule:
- July 25, 2016 Azrieli College, Jerusalem
- July 26, 2016 Google Campus - Tel Aviv, Israel
- July 27, 2016 SigmaLabs - Tel Aviv, Israel
- July 28, 2016 Birzeit University - Palestine
These events were hosted by Embassy of Japan in Israel.
[Description]
While introducing Japanese technologies (products) such as WHILL, Moff, BONX, and etc. which Mr. Tsutsumi was involved in inventing the applications, he will talk about how BLE, a key technology of IoT, is utilized in those products.
Practical Core Bluetooth in IoT & Wearable projects @ AltConf 2016Shuichi Tsutsumi
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n recent years, "IoT" or "Wearable" are one of buzzwords, so you might have interests in building hardware products. But learning how to develop electric circuits, mechanical systems or embedded systems etc. from zero is so difficult.
However, iOS developers can contribute to projects of hardware products with the knowledge of Core Bluetooth / Bluetooth Low Energy (BLE), even if they are not familiar with hardware layer.
In this session, you can learn the basics of Core Bluetooth / BLE (what it is, why we use it, and how it works), and practical knowledges to build apps for hardware products (how to design the apps, how to test without actual hardware prototypes, troubleshooting tips, and how the apps can be reviewed by Apple) which I learned through actual IoT/Wearable projects.
This would be interesting & understandable even if you are not familiar with or have no interests in Core Bluetooth because of the actual examples.
Practical Core Bluetooth in IoT & Wearable projects @ UIKonf 2016Shuichi Tsutsumi
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In recent years, "IoT" or "Wearable" are one of buzzwords, so many people might have interests in building hardware products. But learning how to develop electric circuits, mechanical systems or embedded systems etc. from zero is so difficult. However, iOS developers can contribute to projects of hardware products with the knowledge of Core Bluetooth / Bluetooth Low Energy (BTLE), even if they are not familiar with hardware layer. In this session, he will introduce BTLE, show easy examples of Core Bluetooth, and share knowledges with his experiences developing more than 10 apps for IoT and Wearable products.
What is Bluetooth Low Energy? Why use this?
Very easy examples of how to communicate using Core Bluetooth
What part was my responsibility in the projects? Communication with firmware engineer.
Designing GATT
Designing the behavior of the app in background
Limitations in background. What are possible and impossible?
State Preservation and Restoration
Develop without prototypes of the hardware
BTLE Module's Developer Kit
Prototyping tools
Build emulator apps
Trouble Shootings
Debugging tools
Each cases: Can't find / connect / send or receive information
IoT Devices Compliant with JC-STAR Using Linux as a Container OSTomohiro Saneyoshi
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Security requirements for IoT devices are becoming more defined, as seen with the EU Cyber Resilience Act and Japan’s JC-STAR.
It's common for IoT devices to run Linux as their operating system. However, adopting general-purpose Linux distributions like Ubuntu or Debian, or Yocto-based Linux, presents certain difficulties. This article outlines those difficulties.
It also, it highlights the security benefits of using a Linux-based container OS and explains how to adopt it with JC-STAR, using the "Armadillo Base OS" as an example.
Feb.25.2025@JAWS-UG IoT