Log in
Show password
Forgot password ?
Become a member for free
Sign up
Sign up
New member
Sign up for FREE
New customer
Discover our services
Dynamic quotes 
  1. Homepage
  2. Equities
  3. Japan
  4. Japan Exchange
  5. Fujitsu Limited
  6. News
  7. Summary
    6702   JP3818000006


SummaryMost relevantAll NewsAnalyst Reco.Other languagesPress ReleasesOfficial PublicationsSector newsMarketScreener Strategies

Fujitsu : and France's Inria Develop New Time-Series AI Technology to Identify Causes of Data Anomalies

07/15/2021 | 10:54pm EDT

TOKYO, Jul 16, 2021 - (JCN Newswire) - - Fujitsu Limited and Inria, the French national research institute for digital science and technology, today announced the development of a new AI technology that can identify factors contributing to anomalies in time series data.

In recent years, various kinds of time-series data collected in fields including healthcare, social infrastructure, and manufacturing have been leveraged by AI to perform situational judgment and detect anomalies. In the case of time-series data, however, there are a wide range of factors that can contribute to AI decision-making. This means that even experts find it difficult to notice what kind of changes in the data contributed to an anomaly detection making it difficult to take appropriate measures to prevent their occurrence.

Fujitsu and Inria, more specifically the Inria's DATASHAPE Project Team led by Frederic Chazal in France, have now successfully developed a new technology based on Topological Data Analysis (TDA)(1) that can identify the factors contributing to anomaly detections by AI for time series data and visualize the differences in AI decisions during normal and anomalous circumstances.

Fujitsu and Inria anticipate that this will contribute to the analysis of the causes of anomalies in time series data for various phenomena, clarifying the mechanism surrounding the occurrence of anomalies, as well as the discovery of new solutions to these.

This technology will be presented as one of just 3% of total submitted papers as a "Long Talk" presentation at the Thirty-eighth International Conference on Machine Learning (ICML), the leading international conference in the field of machine learning, which opens virtually from July 18th, 2021.

Newly Developed Technology

Fujitsu and Inria have developed an AI technology that can determine the cause of anomalies in time-series data, consisting of the following key features.

1) Using an analysis technology developed by Fujitsu that extract features that affect judgement from time-series data and detects anomalies (2), the characteristics that led to the anomalous judgment as well as the unrelated characteristics from the data that was judged to be anomalous by the AI are mapped onto a plane (TDA space).

2) The technology transforms the point data of the characteristic that is the cause closer to the point data group of the characteristic that is not the cause on the plane.

3) The time-series data is deformed based on the conversion of the characteristics of the point data, and the data judged to be normal is generated.

This allows the waveform of normal and anomalous time-series data to be compared and enables the user to visually investigate the cause of the anomaly.

The newly developed technology was applied to test the possibility of detecting symptoms of delirium (3) using actual electroencephalography (EEG) data (4) collected in strict accordance with ethical guidelines. Using the newly developed technology, it was confirmed that the characteristics of the brain wave of the time series data coincided with the "slowing" phenomenon (5) that at times accompanies the state of delirium. These results offer the potential to help medical professionals interpret the data to help determine the cause of these symptoms. This may one day contribute to important medical developments, including the ability to discover possible precursors to diseases that have been difficult to identify with conventional techniques, as well as the discovery of preventive treatments. The technology could also be applied to shed light on the mechanisms of diseases that are not yet well-understood.

Comments from Dr. Gen Shinozaki, ASSOCIATE PROFESSOR OF PSYCHIATRY AND BEHAVIORAL SCIENCES, Stanford University School of Medicine

Due to the nature of the random signals, it has proven difficult to use EEG data quantitatively and accurately to identify certain disorders. In recent years, advances in data processing technologies, such as AI, have made it possible to better understand the characteristic changes in subtle brain waves. These advances are important not only for diagnosing various disorders, but also for understanding the treatment response and the pathophysiological mechanism. The technology developed by Fujitsu and Inria has successfully captured the unique characteristics of brain waves in patients suffering from delirium. In addition to verifying this, we anticipate that further improvement and practical use of this technology will ultimately offer the potential to achieve accurate diagnosis, monitoring of treatment response and the elucidation of pathophysiology for other disorders.

Future Plans

Fujitsu and Inria plan to encourage the use of the jointly developed technology in field work and experiments at companies and research institutes, and proceed with verifying the technology.

(1) Topological Data Analysis (TDA):

A method for analyzing data in which data are arrayed in a cluster of points in space, and geometric data is extracted from the cluster.

(2) an analysis technology developed by Fujitsu that classifies time-series data by features and detects anomalies:

Fujitsu and France's Inria Jointly Develop Technology to Automatically Create Anomaly-Detecting AI Models (Press Release: 2020/3/16)

(3) delirium:

a syndrome, or group of symptoms, caused by a disturbance in the normal functioning of the brain.

(4) actual EEG data:

the newly developed technology was applied to the electroencephalographic data of approximately 600 patients, who consented to participate in research with Dr. Shinozaki, at the University of Iowa. Professor Shinozaki has been an Associate Professor at Stanford University since June 2021.

(5) slowing phenomenon:

a phenomenon that frequently occurs in the EEG data of patients suffering from delirium.

About Fujitsu

Fujitsu is the leading Japanese information and communication technology (ICT) company offering a full range of technology products, solutions and services. Approximately 126,000 Fujitsu people support customers in more than 100 countries. We use our experience and the power of ICT to shape the future of society with our customers. Fujitsu Limited (TSE:6702) reported consolidated revenues of 3.6 trillion yen (US$34 billion) for the fiscal year ended March 31, 2021. For more information, please see www.fujitsu.com.

About Inria

Inria is the French national research institute for digital science and technology. World-class research, technological innovation and entrepreneurial risk are its DNA. In 200 project teams, most of which are shared with major research universities, more than 3,500 researchers and engineers explore new paths, often in an interdisciplinary manner and in collaboration with industrial partners to meet ambitious challenges.

As a technological institute, Inria supports the diversity of innovation pathways: from open source software publishing to the creation of technological startups (Deeptech).


Copyright 2021 JCN Newswire . All rights reserved.

© Japan Corporate News, source JCN Press Releases

All news about FUJITSU LIMITED
06:21aFUJITSU : Introduces AI technology Enabling Highly Accurate Prediction of Vessel Collision..
09/23FUJITSU : Sources 100% of Energy Needs for Global HQ from Renewables
09/06FUJITSU : Showcases Global Vision for Sustainable Future through Digital Innovation at Fuj..
09/01FUJITSU : and NYK Streamline Stowage Planning for Car Carriers by Leveraging Quantum-Inspi..
08/31Fujitsu FSAS Creative to Become UT Subsidiary After 51% Stake Buy; Shares Rise 5%
08/20FUJITSU : and NEC to develop technologies for interoperability testing between 5G base sta..
08/19FUJITSU : Global Survey Demonstrates Priorities in the Post-pandemic World
08/19NEC : Fujitsu and NEC to develop technologies for interoperability testing between 5G base..
08/16PRESS RELEASE : 75% of Consumers Want an Autonomous Shopping Experience According to Sheke..
08/06FUJITSU : AI Scoring Platform Powers New Galileo XAI Solution from LARUS for Financial Ser..
More news
Analyst Recommendations on FUJITSU LIMITED
More recommendations
Sales 2022 3 663 B 32 844 M 32 844 M
Net income 2022 211 B 1 892 M 1 892 M
Net cash 2022 309 B 2 772 M 2 772 M
P/E ratio 2022 19,4x
Yield 2022 1,08%
Capitalization 4 098 B 36 813 M 36 745 M
EV / Sales 2022 1,03x
EV / Sales 2023 0,96x
Nbr of Employees 126 371
Free-Float 92,0%
Duration : Period :
Fujitsu Limited Technical Analysis Chart | 6702 | JP3818000006 | MarketScreener
Technical analysis trends FUJITSU LIMITED
Short TermMid-TermLong Term
Income Statement Evolution
Mean consensus OUTPERFORM
Number of Analysts 17
Last Close Price 20 680,00 JPY
Average target price 22 637,65 JPY
Spread / Average Target 9,47%
EPS Revisions
Managers and Directors
Takahito Tokita President, CEO & Representative Director
Takeshi Isobe CFO, Director, GM-Finance & Accounting
Hidenori Furuta COO, Representative Director & Vice President
Yuzuru Fukuda Chief Information Officer
Kyoko Mizuguchi General Counsel
Sector and Competitors
1st jan.Capi. (M$)
ACCENTURE PLC28.06%211 745
SNOWFLAKE INC.10.59%93 640