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  • 1
    Online Resource
    Online Resource
    Multi-task sequence learning for performance prediction and KPI mining in database management system
    Elsevier BV ; 2021
    In:  Information Sciences Vol. 568 ( 2021-08), p. 1-12
    Details
    In: Information Sciences, Elsevier BV, Vol. 568 ( 2021-08), p. 1-12
    Type of Medium: Online Resource
    ISSN: 0020-0255
    URL: Article
    DOI: 10.1016/j.ins.2021.03.046
    RVK:
    SA 5420
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 218760-7
    detail.hit.zdb_id: 1478990-5
    SSG: 24,1
    SSG: 7,11
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  • 2
    Online Resource
    Online Resource
    AirContour : Building Contour-based Model for In-Air Writing Gesture Recognition
    Association for Computing Machinery (ACM) ; 2019
    In:  ACM Transactions on Sensor Networks Vol. 15, No. 4 ( 2019-11-30), p. 1-25
    Details
    In: ACM Transactions on Sensor Networks, Association for Computing Machinery (ACM), Vol. 15, No. 4 ( 2019-11-30), p. 1-25
    Abstract: Recognizing in-air hand gestures will benefit a wide range of applications such as sign-language recognition, remote control with hand gestures, and “writing” in the air as a new way of text input. This article presents AirContour, which focuses on in-air writing gesture recognition with a wrist-worn device. We propose a novel contour-based gesture model that converts human gestures to contours in 3D space and then recognizes the contours as characters. Different from 2D contours, the 3D contours may have the problems such as contour distortion caused by different viewing angles, contour difference caused by different writing directions, and the contour distribution across different planes. To address the above problem, we introduce Principal Component Analysis (PCA) to detect the principal/writing plane in 3D space, and then tune the projected 2D contour in the principal plane through reversing, rotating, and normalizing operations, to make the 2D contour in right orientation and normalized size under a uniform view. After that, we propose both an online approach, AC-Vec, and an offline approach, AC-CNN, for character recognition. The experimental results show that AC-Vec achieves an accuracy of 91.6% and AC-CNN achieves an accuracy of 94.3% for gesture/character recognition, both outperforming the existing approaches.
    Type of Medium: Online Resource
    ISSN: 1550-4859 , 1550-4867
    URL: Article
    DOI: 10.1145/3343855
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2019
    detail.hit.zdb_id: 2198261-2
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  • 3
    Online Resource
    Online Resource
    GaitTracker: 3D Skeletal Tracking for Gait Analysis Based on Inertial Measurement Units
    Association for Computing Machinery (ACM) ; 2022
    In:  ACM Transactions on Sensor Networks Vol. 18, No. 2 ( 2022-05-31), p. 1-27
    Details
    In: ACM Transactions on Sensor Networks, Association for Computing Machinery (ACM), Vol. 18, No. 2 ( 2022-05-31), p. 1-27
    Abstract: Gait rehabilitation is a common method of postoperative recovery after the user sustains an injury or disability. However, traditional gait rehabilitations are usually performed under the supervision of rehabilitation specialists, which implies that the patients cannot receive adequate gait assessment anytime and anywhere. In this article, we propose GaitTracker, a novel system to remotely and continuously perform gait monitoring and analysis by three-dimensional (3D) skeletal tracking in a wearable approach. Specifically, this system consists of four Inertial Measurement Units (IMU), which are attached on the shanks and thighs of the human body. According to the measurements from these IMUs, we can obtain the motion signals of lower limbs during gait rehabilitation. By adaptively synchronizing coordinate systems of different IMUs and building the geometric model of lower limbs, the exact gait movements can be reconstructed, and gait parameters can be extracted without any prior knowledge. GaitTracker offers three key features: (1) a unified 3D skeletal model to depict the precise gait movement and parameters in 3D space, (2) a coordinate system synchronization scheme to perform space synchronization over all the IMU sensors, and (3) an automatic estimation method for the user-specific geometric parameters. In this way, GaitTracker is able to accurately perform 3D skeletal tracking of lower limbs for gait analysis, such as evaluating the gait symmetry and the gait parameters including the swing/stance time. We implemented GaitTracker and evaluated its performance in real applications. The experimental results show that, the average error for skeleton angle estimation, joint displacement estimation, and gait parameter estimation are 3∘, 2.3%, and 3%, respectively, outperforming the state of the art.
    Type of Medium: Online Resource
    ISSN: 1550-4859 , 1550-4867
    URL: Article
    DOI: 10.1145/3502722
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2022
    detail.hit.zdb_id: 2198261-2
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  • 4
    Online Resource
    Online Resource
    LightGyro: A Batteryless Orientation Measuring Scheme Based on Light Reflection
    Association for Computing Machinery (ACM) ; 2023
    In:  ACM Transactions on Sensor Networks
    Details
    In: ACM Transactions on Sensor Networks, Association for Computing Machinery (ACM)
    Abstract: In industrial production, the orientation of facility components can indicate whether the facility is on a regular operating track. For example, when a component get loose, the orientation variation of the component would exceed the normal range. A common approach for orientation measurement is to attach an inertial measurement unit (IMU) to the target device. However, the IMU requires additional power maintenance. This paper presents LightGyro, a cheap and efficient batteryless scheme to measure the orientation, in which we attach a reflective film to the target device and use a camera to capture the light spot on the reflective film. The basic idea of LightGyro is to extract the light spots in the captured frame and use their pixel coordinates to infer the orientation. It is difficult to recognize a single light spot because the spot lacks distinctive features. To solve the problem, we switch light sources on and off to regulate the appearance of light spots and utilize frame subtraction to extract light spots. The depth of field of light spot is lost in the process of camera projection, which is necessary for the orientation measurement. To address the issue, we propose a light array-based reflection model to extract the depth of field from the relative positions of multiple light spots. To the best of our knowledge, this is the first work to utilize reflection to measure orientation. Experiment results show that the orientation error of LightGyro decreases with the increasing length of the reflection route and the orientation error can achieve less than 1°.
    Type of Medium: Online Resource
    ISSN: 1550-4859 , 1550-4867
    URL: Article
    DOI: 10.1145/3597934
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2023
    detail.hit.zdb_id: 2198261-2
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  • 5
    Online Resource
    Online Resource
    Sleeping Schedule-Aware Local Broadcast in Wireless Sensor Networks
    SAGE Publications ; 2013
    In:  International Journal of Distributed Sensor Networks Vol. 9, No. 12 ( 2013-12-01), p. 451970-
    Details
    In: International Journal of Distributed Sensor Networks, SAGE Publications, Vol. 9, No. 12 ( 2013-12-01), p. 451970-
    Abstract: Broadcast is widely used in applications in wireless sensor networks (WSNs). In the last decade, the broadcast problem in WSNs has been well studied. However, few of existing broadcasting strategies have considered the scenarios with sleeping schedules, which have been emerging as a prevalent energy-saving method for WSNs. In WSNs with sleeping schedule, each node switches on and off periodically, rendering the broadcast problem more difficult. To handle the periodical sleep issue, we focus on designing effective sleeping schedule-aware broadcast algorithms. We practically propose SALB, a sleeping schedule-aware local broadcast algorithm. In SALB, a typical local algorithm for constructing connected dominating set is employed to form the broadcast backbone. To guarantee proper transmission of broadcast messages, a sleep-aware forwarding mechanism is implemented. Moreover, heuristic strategies are used to decrease the number of transmissions and the broadcast latency. Theoretical analysis shows that the number of transmissions for SALB is within 4(min(Δ,[Formula: see text]) ( c is constant) is constant) times of the optimal value. And the broadcast latency of SALB is within 4[Formula: see text] times of the optimal value (Δ is the maximum degree in the network, [Formula: see text] is the scheduling period length). The performance of SALB is evaluated via simulations.
    Type of Medium: Online Resource
    ISSN: 1550-1477 , 1550-1477
    URL: Article
    DOI: 10.1155/2013/451970
    Language: English
    Publisher: SAGE Publications
    Publication Date: 2013
    detail.hit.zdb_id: 2192922-1
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  • 6
    Online Resource
    Online Resource
    STAD-GAN: Unsupervised Anomaly Detection on Multivariate Time Series with Self-training Generative Adversarial Networks
    Association for Computing Machinery (ACM) ; 2023
    In:  ACM Transactions on Knowledge Discovery from Data Vol. 17, No. 5 ( 2023-10-30), p. 1-18
    Details
    In: ACM Transactions on Knowledge Discovery from Data, Association for Computing Machinery (ACM), Vol. 17, No. 5 ( 2023-10-30), p. 1-18
    Abstract: Anomaly detection on multivariate time series (MTS) is an important research topic in data mining, which has a wide range of applications in information technology, financial management, manufacturing system, and so on. However, the state-of-the-art unsupervised deep learning models for MTS anomaly detection are vulnerable to noise and have poor performance on the training data containing anomalies. In this article, we propose a novel Self-Training based Anomaly Detection with Generative Adversarial Network (GAN) model called STAD-GAN to address the practical challenge. The STAD-GAN model consists of a generator-discriminator structure for adversarial learning and a neural network classifier for anomaly classification. The generator is learned to capture the normal data distribution, and the discriminator is learned to amplify the reconstruction error of abnormal data for better recognition. The proposed model is optimized with a self-training teacher-student framework, where a teacher model generates reliable high-quality pseudo-labels to train a student model iteratively with a refined dataset so that the performance of the anomaly classifier can be gradually improved. Extensive experiments based on six open MTS datasets show that STAD-GAN is robust to noise and achieves significant performance improvement compared to the state-of-the-art.
    Type of Medium: Online Resource
    ISSN: 1556-4681 , 1556-472X
    URL: Article
    DOI: 10.1145/3572780
    Language: English
    Publisher: Association for Computing Machinery (ACM)
    Publication Date: 2023
    detail.hit.zdb_id: 2257358-6
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  • 7
    Online Resource
    Online Resource
    Identity Authentication with Association Behavior Sequence in Machine-to-Machine Mobile Terminals
    Springer Science and Business Media LLC ; 2022
    In:  Mobile Networks and Applications Vol. 27, No. 1 ( 2022-02), p. 96-108
    Details
    In: Mobile Networks and Applications, Springer Science and Business Media LLC, Vol. 27, No. 1 ( 2022-02), p. 96-108
    Type of Medium: Online Resource
    ISSN: 1383-469X , 1572-8153
    URL: Article
    DOI: 10.1007/s11036-020-01706-0
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 1342049-5
    detail.hit.zdb_id: 2000637-8
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  • 8
    Online Resource
    Online Resource
    SpeedTalker: Automobile Speed Estimation via Mobile Phones
    Institute of Electrical and Electronics Engineers (IEEE) ; 2022
    In:  IEEE Transactions on Mobile Computing Vol. 21, No. 6 ( 2022-6-1), p. 2210-2227
    Details
    In: IEEE Transactions on Mobile Computing, Institute of Electrical and Electronics Engineers (IEEE), Vol. 21, No. 6 ( 2022-6-1), p. 2210-2227
    Type of Medium: Online Resource
    ISSN: 1536-1233 , 1558-0660 , 2161-9875
    URL: Article
    DOI: 10.1109/TMC.2020.3034354
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2022
    detail.hit.zdb_id: 2082213-3
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  • 9
    Online Resource
    Online Resource
    Adaptive subflow allocation for multipath data transmission in mobile edge networks
    Elsevier BV ; 2021
    In:  Journal of Systems Architecture Vol. 116 ( 2021-06), p. 102012-
    Details
    In: Journal of Systems Architecture, Elsevier BV, Vol. 116 ( 2021-06), p. 102012-
    Type of Medium: Online Resource
    ISSN: 1383-7621
    URL: Article
    DOI: 10.1016/j.sysarc.2021.102012
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 1499743-5
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  • 10
    Online Resource
    Online Resource
    Threshold‐based admission control for a multimedia Grid: analysis and performance evaluation
    Wiley ; 2006
    In:  Concurrency and Computation: Practice and Experience Vol. 18, No. 14 ( 2006-12-15), p. 1747-1758
    Details
    In: Concurrency and Computation: Practice and Experience, Wiley, Vol. 18, No. 14 ( 2006-12-15), p. 1747-1758
    Abstract: In a Grid‐based services system facing a large number of requests with different services and profits significance, there is always a trade‐off between the system profits and the Quality of Service (QoS). In such systems, admission control plays an important role: the system has to employ a proper strategy to make admission control decisions and reserve resources for the coming requests thus to achieve greater profits without violating the QoS of the requests already admitted. In this paper, we introduce three essential admission control strategies with threshold on resource reservation and a newly proposed strategy with layered threshold. Through comprehensive theoretical analyses and extensive simulations, we demonstrate that the strategy with layered threshold is more efficient and flexible than the existing strategies for Grid‐based multimedia services systems. Copyright © 2006 John Wiley & Sons, Ltd.
    Type of Medium: Online Resource
    ISSN: 1532-0626 , 1532-0634
    URL: Issue
    URL: Article
    DOI: 10.1002/cpe.v18:14
    DOI: 10.1002/cpe.1026
    RVK:
    SA 4270
    Language: English
    Publisher: Wiley
    Publication Date: 2006
    detail.hit.zdb_id: 2052606-4
    SSG: 11
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