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    NOVELTY MULTISENSORY DECISION GENERATING DEVICE AND METHOD
    1.
    发明申请
    NOVELTY MULTISENSORY DECISION GENERATING DEVICE AND METHOD 有权

    公开(公告)号：US20250153711A1

    公开(公告)日：2025-05-15

    申请号：US18523918

    申请日：2023-11-30

    Applicant: INSTITUTE FOR INFORMATION INDUSTRY

    Inventor： I-Heng MENG ,  Jun-Dong CHANG ,  Ai-Ting CHANG

    IPC: B60W30/095 ,  G06V10/774 ,  G06V20/58 ,  G08G1/01

    Abstract: A decision generating device is configured to execute the following operations. A driving image of a vehicle and a driving status corresponding to the driving image are obtained. An image recognition is performed on the driving image by using an image recognition model to generate object information of objects in the driving image. A predictive driving information is generated based on the object information and the driving status by using a prediction model, the predictive driving information includes object movement predictions of the objects and a movement prediction of the vehicle, and the prediction model is generated based on a trained generative content model. A driving decision is generated based on the predictive driving information.

    TRAINING SYSTEM AND TRAINING METHOD FOR DOMAIN-SPECIFIC DATA MODEL
    2.
    发明申请
    TRAINING SYSTEM AND TRAINING METHOD FOR DOMAIN-SPECIFIC DATA MODEL 有权

    公开(公告)号：US20250139506A1

    公开(公告)日：2025-05-01

    申请号：US18515660

    申请日：2023-11-21

    Applicant: INSTITUTE FOR INFORMATION INDUSTRY

    Inventor： Yu-Chuan YANG ,  Tai-Ta Kuo ,  Ping-I Chen

    IPC: G06N20/00

    Abstract: A training system and a training method for a domain-specific data model are provided. The training method includes configuring a computing device to perform the following processes: generating, by a training set generation module, a training data set based on a domain knowledge graph; updating the data model based on the training data set; generating, by the training set generation module, training input text corresponding to the domain knowledge graph; inputting the training input text into the data model to obtain training output text; evaluating and generating a score by an evaluation module based on a correlation between the training output text and the domain knowledge graph; and adjusting, by a reinforcement learning module, parameters of the data model according to the score and an optimization goal of the reward model until the score meets a training completion condition, taking the data model as the domain-specific data model.

    Anomaly detection model training method, anomaly detection methods, and load detection devices for household electricity
    3.
    发明申请
    Anomaly detection model training method, anomaly detection methods, and load detection devices for household electricity 有权

    公开(公告)号：US20250068884A1

    公开(公告)日：2025-02-27

    申请号：US18378665

    申请日：2023-10-11

    Applicant: INSTITUTE FOR INFORMATION INDUSTRY

    Inventor： Kuang Ping Tseng ,  Wen Jen Ho ,  Chia Wei Tsai ,  Kuei Chun Chiang ,  Yung Chieh Hung

    IPC: G06N3/045 ,  G06N3/084

    Abstract: An anomaly detection model training method, anomaly detection methods, and load detection devices for household electricity are provided. The anomaly detection method is applied to the load detection device, which includes a processing unit and an anomaly detection model. The processing unit trains the anomaly detection model and performs an anomaly detection method. The anomaly detection method includes: extracting user electrical features to obtain feature data; grouping the feature data based on electricity consumption behavior and inputting them into the first and second single classification models respectively to generate detection results corresponding to the first and second single classification models; generating anomaly electricity detection results based on the detection results; differentiating the electricity load data according to unit time to become a plurality segments of sub-electricity load data; and comparing the segments of sub-electricity load data with the historical load data to output a plurality of anomaly electricity consumption periods.

    TRANSMITTER, RECEIVER, AND METHOD FOR WIRELESS COMMUNICATIONS
    4.
    发明申请
    TRANSMITTER, RECEIVER, AND METHOD FOR WIRELESS COMMUNICATIONS 有权

    公开(公告)号：US20250015920A1

    公开(公告)日：2025-01-09

    申请号：US18508256

    申请日：2023-11-14

    Applicant: INSTITUTE FOR INFORMATION INDUSTRY

    Inventor： Hsien Tsung HSU ,  Pei Yu HUNG ,  Wen-Yao CHANG

    IPC: H04L1/00 ,  H04W24/02

    Abstract: A transmitter for wireless communications includes an encoder, a normalizer, a binarizer, and a radio frequency (RF) circuit. The encoder is configured to encode a control message into a channel dimensional vector according to a channel dimension and the number of semantic fields by utilizing a training model. The control message includes at least one of control plane media access control layer information and control plane physical layer information. The normalizer is configured to normalize the channel dimensional vector to generate a normalized channel dimensional vector. The binarizer is configured to binarize the normalized channel dimensional vector to generate a fixed-point number. The RF circuit is configured to modulate the fixed-point number into an RF signal and transmit the RF signal.

    METHOD AND SYSTEM FOR IDENTIFYING OPERATING STATUS OF ELECTRICAL APPLIANCE BASED ON NON-INTRUSIVE LOAD MONITORING
    8.
    发明公开
    METHOD AND SYSTEM FOR IDENTIFYING OPERATING STATUS OF ELECTRICAL APPLIANCE BASED ON NON-INTRUSIVE LOAD MONITORING 审中-公开

    公开(公告)号：US20240085465A1

    公开(公告)日：2024-03-14

    申请号：US17974494

    申请日：2022-10-26

    Applicant: INSTITUTE FOR INFORMATION INDUSTRY

    Inventor： KUANG-PING TSENG ,  WEN-JEN HO ,  YUNG-CHIEH HUNG ,  KUEI-CHUN CHIANG

    IPC: G01R22/06

    CPC classification number: G01R22/06

    Abstract: A method and a system for identifying an operating status of an electrical appliance based on non-intrusive load monitoring are provided. The method includes the following steps. Total power consumption history data of a target field and appliance power consumption history data of target electrical appliances are obtained. The appliance power consumption history data of each target electrical appliance is converted into a binary data set. The total power consumption history data is clustered into cluster samples to obtain first feature data sets, which are then dimensionally reduced into second feature data sets, and a machine learning model is trained by using the second feature data sets and the binary data sets of the target electrical appliances to establish an operation identification model for the target electrical appliances. The operation identification model identifies an operating status of the target electrical appliances according to total power consumption data.

    POSITIONING SYSTEM AND POSITIONING METHOD BASED ON RADIO FREQUENCY IDENTIFICATION TECHNIQUES
    9.
    发明公开
    POSITIONING SYSTEM AND POSITIONING METHOD BASED ON RADIO FREQUENCY IDENTIFICATION TECHNIQUES 审中-公开

    公开(公告)号：US20240073660A1

    公开(公告)日：2024-02-29

    申请号：US17963995

    申请日：2022-10-11

    Applicant: INSTITUTE FOR INFORMATION INDUSTRY

    Inventor： YAO-SHUN YANG ,  HUI-TZU HUANG ,  JIAN-YING CHEN ,  CHUAN-CHUAN WANG

    IPC: H04W4/44 ,  G06V20/56 ,  G06V20/62 ,  H04W4/029

    CPC classification number: H04W4/44 ,  G06V20/588 ,  G06V20/625 ,  H04W4/029

    Abstract: A positioning system and a positioning method based on radio frequency identification techniques (RFID) are provided. The positioning system includes in-vehicle devices, RFID readers and a server. The in-vehicle devices each includes a positioning device, an image capturing device and an image recognition module. The positioning device obtains a positioning location. The image capturing device captures a driving image. The image recognition module identifies adjacent vehicles, adjacent license plate information, and road attributes, and calculates relative location information. Each of the RFID readers reads a vehicle tag of one of the vehicles passing by, so as to mark a reference vehicle and generate reference vehicle information. A positioning adjustment module of the server determines whether the target vehicle is a reference vehicle, has been the reference vehicle or is a non-reference vehicle, and adjusts the positioning location of the target vehicle in different ways, accordingly.

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