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筝錣里燭瓩離好食`トアップ房深 (2) / スタ`トアップの深え圭を仟ﾊI竃とスタ`トアップB亊に試かす
筝錣里燭瓩離好食`トアップ房深 (2) / スタ`トアップの深え圭を仟ﾊI竃とスタ`トアップB亊に試かすTakaaki Umada
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寄二Iでスタ`トアップ議な仟ﾊIやスタ`トアップB亊を佩うための、スタ`トアップ議な深え圭を盾hしました。
(2) では麼にスタ`トアップ議な深え圭を聞った仟ﾊIの_kと、スタ`トアップとのB亊についてまとめています。
際際滷share の否楚オ`バ`のため、1, 2 で蛍護しています。1 はこちら。
/takaumada/startup-thinking-for-change-1/
PikaBreak: 高で俚蹶を陥してくれるスマ`トタイマ`
PikaBreak: 高で俚蹶を陥してくれるスマ`トタイマ`Yuta Takahashi
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幄塀氏芙サポ`タ`ズ瑳紗疾2020
ライトニングト`ク寄氏仝みんなに徭蛸したいoj_k々
にてk燕
- ソ`スコ`ド
https://github.com/yuta-ubiquitous/PikaBreak
- デモ
https://www.youtube.com/watch?v=ciW0fZIznUQ伏試リズムの窃貌來や巓豚來に児づく伉附の宗慎彜蓑の容協と嚠霞
伏試リズムの窃貌來や巓豚來に児づく伉附の宗慎彜蓑の容協と嚠霞Yuta Takahashi
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The document references various studies that investigate the relationship between stress and health outcomes, including mortality and academic performance. It discusses the use of health surveys and models for predicting stress levels and mental health. Key findings highlight the importance of perceptions regarding stress and their impact on overall well-being.Q高嶄の坪議彜蓑容協に鬚韻甚Q高人の涙吭紛議しぐさの蛍裂
Q高嶄の坪議彜蓑容協に鬚韻甚Q高人の涙吭紛議しぐさの蛍裂Yuta Takahashi
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IEICE HPB及18指冩梢氏@|奨C寄でk燕したスライドです
http://ieicehpb.info/index.php?Kenkyukai18
セッション3 : 佩喀睥伏恢來の詰和雙峭のためのウェアラブル字匂による悶距の容協と嚠霞
伏恢來の詰和雙峭のためのウェアラブル字匂による悶距の容協と嚠霞Yuta Takahashi
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The document discusses research on the impact of chronic health conditions on work performance and economic outcomes for employers. It also references studies on academic performance, mental health, and stress prediction using personality traits and machine learning. The insights aim to highlight the relationship between health and productivity in various contexts.DeepRemote: A Smart Remote Controller for Intuitive Control through Home Appl...
DeepRemote: A Smart Remote Controller for Intuitive Control through Home Appl...Yuta Takahashi
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This document describes DeepRemote, a smart remote controller that uses deep learning for intuitive home appliance selection and control. It consists of a control unit with a camera and buttons and a deep learning unit for appliance recognition. The system was tested for classification accuracy of over 80% on average, response time of under 2 seconds, and faster control times than traditional remotes in user tests. Overall, DeepRemote demonstrates an effective deep learning approach for selecting and controlling home appliances intuitively with a single remote controller.An Identification Method of IR Signals to Collect Control Logs of Home Applia...
An Identification Method of IR Signals to Collect Control Logs of Home Applia...Yuta Takahashi
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This document proposes a method to identify infrared (IR) signals from home appliances in order to collect control logs. It involves preprocessing raw IR signals into pulse width sequences, comparing signals using mean absolute error and sum absolute error, and constructing statistical models to identify appliance type with 95.5% accuracy and command type with 92% accuracy based on a database of 1,400 signals from 14 appliances. A simple simulation shows identification stability is achieved when the database includes 6 or more signals per appliance. The method could help automatically understand user preferences from appliance usage logs.TechUP Makersデモデイ - リハビリ屶址のためのIoTデバイス〆UbiCane〇
TechUP Makersデモデイ - リハビリ屶址のためのIoTデバイス〆UbiCane〇Yuta Takahashi
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匯違芙盞繁ブロ`ドバンド容Mfh氏が麼岸するTechUP Makersというプログラムに歌紗しデモデイでk燕したスライドですP伏恢來個鋲に鬚韻織ΕД▲薀屮觧匂を喘いた悶距容協隈の別
P伏恢來個鋲に鬚韻織ΕД▲薀屮觧匂を喘いた悶距容協隈の別Yuta Takahashi
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IPSJ SIG-MBL 及82指 WiPセッション
http://www.ishilab.net/mbl/program/2016/81.html
にてk燕したスライドです堰粥皆遺と安艶一温を聞って佩強範紛
堰粥皆遺と安艶一温を聞って佩強範紛Yuta Takahashi
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2016/10/12(邦)にIoTビジネスブ`ストアッププログラム仝AIDOR々のIoTサ`ビス､琶荒辰靴織魯鵐坤ンスライドです
https://www.sansokan.jp/events/eve_detail.san?H_A_NO=21644住宥並絞デ`タへの撞竃パタ`ンマイニングの癖喘
住宥並絞デ`タへの撞竃パタ`ンマイニングの癖喘Yuta Takahashi
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The document discusses the application of frequent pattern mining to analyze traffic accident data in Saga, Japan, emphasizing the need for a more efficient method of analysis compared to traditional statistical approaches. It outlines the methodologies used, including decision trees and clustering, and presents findings related to time rules, vehicle types, and correlations with age. Future work is suggested to validate the knowledge gained and potentially apply this method to real-world scenarios.階咄襖センサ`を喘いた4泣嬌の聞喘宀のコンテキスト容協隈の戻宛
階咄襖センサ`を喘いた4泣嬌の聞喘宀のコンテキスト容協隈の戻宛Yuta Takahashi
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IPSJ UBISIG42でk燕したパワポのスライドです.
English : Context Estimation for Quad Cane User by using Ultrasonic Sensor More Related Content
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TechUP Makersデモデイ - リハビリ屶址のためのIoTデバイス〆UbiCane〇
TechUP Makersデモデイ - リハビリ屶址のためのIoTデバイス〆UbiCane〇Yuta Takahashi
?
匯違芙盞繁ブロ`ドバンド容Mfh氏が麼岸するTechUP Makersというプログラムに歌紗しデモデイでk燕したスライドですP伏恢來個鋲に鬚韻織ΕД▲薀屮觧匂を喘いた悶距容協隈の別
P伏恢來個鋲に鬚韻織ΕД▲薀屮觧匂を喘いた悶距容協隈の別Yuta Takahashi
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IPSJ SIG-MBL 及82指 WiPセッション
http://www.ishilab.net/mbl/program/2016/81.html
にてk燕したスライドです堰粥皆遺と安艶一温を聞って佩強範紛
堰粥皆遺と安艶一温を聞って佩強範紛Yuta Takahashi
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2016/10/12(邦)にIoTビジネスブ`ストアッププログラム仝AIDOR々のIoTサ`ビス､琶荒辰靴織魯鵐坤ンスライドです
https://www.sansokan.jp/events/eve_detail.san?H_A_NO=21644住宥並絞デ`タへの撞竃パタ`ンマイニングの癖喘
住宥並絞デ`タへの撞竃パタ`ンマイニングの癖喘Yuta Takahashi
?
The document discusses the application of frequent pattern mining to analyze traffic accident data in Saga, Japan, emphasizing the need for a more efficient method of analysis compared to traditional statistical approaches. It outlines the methodologies used, including decision trees and clustering, and presents findings related to time rules, vehicle types, and correlations with age. Future work is suggested to validate the knowledge gained and potentially apply this method to real-world scenarios.階咄襖センサ`を喘いた4泣嬌の聞喘宀のコンテキスト容協隈の戻宛
階咄襖センサ`を喘いた4泣嬌の聞喘宀のコンテキスト容協隈の戻宛Yuta Takahashi
?
IPSJ UBISIG42でk燕したパワポのスライドです.
English : Context Estimation for Quad Cane User by using Ultrasonic Sensor ライフログを已としたユビキタスコンピュ`ティング室宝
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