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  • 1
    Online Resource
    Online Resource
    Dropout Rate Prediction of Massive Open Online Courses Based on Convolutional Neural Networks and Long Short-Term Memory Network
    Hindawi Limited ; 2022
    In:  Mobile Information Systems Vol. 2022 ( 2022-5-16), p. 1-11
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2022 ( 2022-5-16), p. 1-11
    Abstract: Massive open online courses (MOOC) is characterized by large scale, openness, autonomy, and personalization, attracting increasingly students to participate in learning and gaining recognition from more and more people. This paper proposes a network model based on convolutional neural networks and long short-term memory network (CNN-LSTM) for MOOC dropout prediction task. The model selects 43-dimensional behavioral features as input from students’ learning activity logs and adopts the CNN model to automatically extract continuous features over a period of time from students’ learning activity logs. At the same time, considering the time sequence of students’ learning behavior characteristics, a MOOC dropout prediction model was established by using long short-term memory network to obtain students’ learning status at different time steps. The algorithm proposed in this chapter was trained and evaluated on the public dataset provided by the KDD Cup 2015 competition. Compared with the dropout prediction methods based on LSTM and CNN-RNN, the model improved the AUC by 2.7% and 1.4%, respectively. The result in this paper is a good predictor of dropout rates and is expected to provide teaching aid to teachers.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2022/8255965
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2187808-0
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  • 2
    Online Resource
    Online Resource
    Edge-Cloud-Assisted Multiuser Forward Secure Searchable Encryption (EMFSSE) Scheme in the P2P Networking Environment
    Hindawi Limited ; 2021
    In:  Mobile Information Systems Vol. 2021 ( 2021-9-18), p. 1-14
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2021 ( 2021-9-18), p. 1-14
    Abstract: P2P network enables users to share resources effectively. However, with the advent of the big data era, the sensitive data of users in P2P network are also increasing dramatically. In order to solve the contradiction between the huge amount of sensitive data and the limited local storage space, an increasing number of users choose to encrypt their sensitive data and store them in the cloud server. For the problem of the secure storage and flexible access of large amounts of user data in P2P networks, an edge-cloud-assisted multiuser forward secure searchable encryption scheme is proposed. The scheme uses the proxy reencryption technique to optimize the multiuser searchable encryption and prevent the decryption key from being directly transmitted between users. By introducing an edge-cloud architecture, the system achieves efficient communication and timely response capabilities. The security analysis proves that our scheme achieves the CPA (chosen-plaintext attack) security based on DBDH assumption and the forward privacy. Finally, the theoretical and experimental comparisons between this scheme and other schemes show that our scheme has high efficiency in the process of data update, search, and trapdoor generation. In addition, due to the use of edge-cloud architecture, our scheme reduces about 90% and 75% of the user’s consumption in the encryption and token generation process.
    Type of Medium: Online Resource
    ISSN: 1875-905X , 1574-017X
    URL: Article
    DOI: 10.1155/2021/7003252
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2021
    detail.hit.zdb_id: 2187808-0
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  • 3
    Online Resource
    Online Resource
    Congestion Control Mechanism for Intermittently Connected Wireless Network
    Hindawi Limited ; 2016
    In:  Mobile Information Systems Vol. 2016 ( 2016), p. 1-10
    Details
    In: Mobile Information Systems, Hindawi Limited, Vol. 2016 ( 2016), p. 1-10
    Abstract: Based on the “storing-carrying-forwarding” transmission manner, the packets are forwarded flexibly in Intermittently Connected Wireless Network (ICWN). However, due to its limited resources, ICWN can easily become congested as a large number of packets entering into it. In such situation, the network performance is seriously deteriorated. To solve this problem, we propose a congestion control mechanism that is based on the network state dynamic perception. Specifically, through estimating the congestion risk when a node receives packets, ICWN can reduce the probability of becoming congested. Moreover, due to ICWN’s network dynamics, we determine the congestion risk threshold by jointly taking into account the average packet size, average forwarding risk, and available buffer resources. Further, we also evaluate the service ability of a node in a distributed manner by integrating the recommendation information from other intermediate nodes. Additionally, a node is selected as a relay node according to both the congestion risk and service ability. Simulation results show that the network performance can be greatly optimized by reducing the overhead of packet forwarding.
    Type of Medium: Online Resource
    ISSN: 1574-017X , 1875-905X
    URL: Article
    DOI: 10.1155/2016/4819349
    RVK:
    QA 10000
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2016
    detail.hit.zdb_id: 2187808-0
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  • 4
    Online Resource
    Online Resource
    Reviewing investment after completion: an exploratory analysis
    Informa UK Limited ; 1992
    In:  The International Review of Retail, Distribution and Consumer Research Vol. 2, No. 2 ( 1992-04), p. 217-232
    Details
    In: The International Review of Retail, Distribution and Consumer Research, Informa UK Limited, Vol. 2, No. 2 ( 1992-04), p. 217-232
    Type of Medium: Online Resource
    ISSN: 0959-3969 , 1466-4402
    URL: Article
    DOI: 10.1080/09593969200000038
    RVK:
    QA 10000
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 1992
    detail.hit.zdb_id: 1481049-9
    SSG: 3,2
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  • 5
    Online Resource
    Online Resource
    Requirement or Promise? An Analysis of the First‐Mover Advantage in Quality Contracting
    Wiley ; 2015
    In:  Production and Operations Management Vol. 24, No. 6 ( 2015-06), p. 917-933
    Details
    In: Production and Operations Management, Wiley, Vol. 24, No. 6 ( 2015-06), p. 917-933
    Abstract: Quality contracting is critical and challenging due to the many unique issues related to quality. In this study, we analyze the first‐mover right in quality contracting by considering two different strategies for the buyer: the quality requirement strategy (QR) where buyer moves first by posting quality requirement to suppliers and quality promise strategy (QP) where buyer voluntarily gives up the first‐mover right to suppliers to ask them to promise quality. We study which strategy (1) better encourages suppliers' quality improvement efforts and (2) leads to a higher expected profit for the buyer. To analyze the drivers behind the buyer's choice between QR and QP, we start with the basic model where buyer faces only one supplier who has the opportunity to make quality improvements. We then gradually add other business features such as information asymmetry and supplier competition, analyzing how each feature adds/changes the driving forces and how they interact in the buyer's decision between QR and QP. We consider both the case where the wholesale price is fixed (when the buyer has the power to dictate price or price is set by the market) and the case where the wholesale price is included as a variable (when price is part of the negotiation). We find that QP always leads to the first‐best quality efforts from the supplier(s) while QR limits their efforts. However, this does not guarantee higher expected profit for the buyer under QP. We provide insightful guidelines in buyer's choice between QP and QR. This research enriches the limited literature on quality contracting with quality improvement opportunity and asymmetric information.
    Type of Medium: Online Resource
    ISSN: 1059-1478 , 1937-5956
    URL: Issue
    URL: Article
    DOI: 10.1111/poms.2015.24.issue-6
    DOI: 10.1111/poms.12315
    RVK:
    QA 10000
    Language: English
    Publisher: Wiley
    Publication Date: 2015
    detail.hit.zdb_id: 2151364-8
    detail.hit.zdb_id: 1108460-1
    SSG: 3,2
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  • 6
    Online Resource
    Online Resource
    Informal credit markets and economic development in Taiwan
    Elsevier BV ; 1995
    In:  World Development Vol. 23, No. 5 ( 1995-5), p. 845-855
    Details
    In: World Development, Elsevier BV, Vol. 23, No. 5 ( 1995-5), p. 845-855
    Type of Medium: Online Resource
    ISSN: 0305-750X
    URL: Article
    DOI: 10.1016/0305-750X(95)00014-4
    RVK:
    QA 10000
    Language: English
    Publisher: Elsevier BV
    Publication Date: 1995
    detail.hit.zdb_id: 185339-9
    detail.hit.zdb_id: 1500836-8
    SSG: 3,6
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  • 7
    Online Resource
    Online Resource
    How quality reporting reduces accountability deficit and overload
    Informa UK Limited ; 2022
    In:  Public Management Review Vol. 24, No. 12 ( 2022-12-02), p. 2079-2100
    Details
    In: Public Management Review, Informa UK Limited, Vol. 24, No. 12 ( 2022-12-02), p. 2079-2100
    Type of Medium: Online Resource
    ISSN: 1471-9037 , 1471-9045
    URL: Article
    DOI: 10.1080/14719037.2021.1963823
    RVK:
    QA 10000
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2022
    detail.hit.zdb_id: 2094887-6
    SSG: 2
    SSG: 3,2
    SSG: 3,6
    SSG: 3,7
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  • 8
    Online Resource
    Online Resource
    Collectivistic-HRM, firm strategy and firm performance: an empirical test
    Informa UK Limited ; 2012
    In:  The International Journal of Human Resource Management Vol. 23, No. 1 ( 2012-01), p. 190-203
    Details
    In: The International Journal of Human Resource Management, Informa UK Limited, Vol. 23, No. 1 ( 2012-01), p. 190-203
    Type of Medium: Online Resource
    ISSN: 0958-5192 , 1466-4399
    URL: Article
    DOI: 10.1080/09585192.2011.561231
    RVK:
    QV 578
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2012
    detail.hit.zdb_id: 2032106-5
    SSG: 3,2
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  • 9
    Online Resource
    Online Resource
    Category-Adaptive Variable Screening for Ultra-High Dimensional Heterogeneous Categorical Data
    Informa UK Limited ; 2020
    In:  Journal of the American Statistical Association Vol. 115, No. 530 ( 2020-04-02), p. 747-760
    Details
    In: Journal of the American Statistical Association, Informa UK Limited, Vol. 115, No. 530 ( 2020-04-02), p. 747-760
    Type of Medium: Online Resource
    ISSN: 0162-1459 , 1537-274X
    URL: Article
    DOI: 10.1080/01621459.2019.1573734
    RVK:
    QA 10000
    RVK:
    SA 2455
    Language: English
    Publisher: Informa UK Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2064981-2
    detail.hit.zdb_id: 207602-0
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  • 10
    Online Resource
    Online Resource
    Federated Optimization Under Intermittent Client Availability
    Institute for Operations Research and the Management Sciences (INFORMS) ; 2023
    In:  INFORMS Journal on Computing
    Details
    In: INFORMS Journal on Computing, Institute for Operations Research and the Management Sciences (INFORMS)
    Abstract: Federated learning is a new distributed machine learning framework, where numerous heterogeneous clients collaboratively train a model without sharing training data. In this work, we consider a practical and ubiquitous issue when deploying federated learning in mobile environments: intermittent client availability, where the set of eligible clients may change during the training process. Such intermittent client availability would seriously deteriorate the performance of the classical federated averaging algorithm (FedAvg). Thus, we propose a simple distributed nonconvex optimization algorithm, called federated latest averaging (FedLaAvg), which leverages the latest gradients of all clients, even when the clients are not available, to jointly update the global model in each iteration. Our theoretical analysis shows that FedLaAvg achieves guaranteed convergence and a sublinear speedup with respect to the total number of clients. We implement FedLaAvg along with several baselines and evaluate them over the benchmarking MNIST and Sentiment140 data sets. The evaluation results demonstrate that FedLaAvg achieves more stable training than FedAvg in both convex and nonconvex settings and reaches a sublinear speedup. Source code and online supplement are available at the IJOC GitHub site ( http://dx.doi.org/10.1287/ijoc.2022.0057.cd , https://github.com/INFORMSJoC/2022.0057 ). History: Accepted by Ram Ramesh, Area Editor for Data Science & Machine Leaning. Funding: This work was supported by the National Key R & D Program of China [Grant 2022ZD0119100], the National Natural Science Foundation of China (NSFC) [Grants 61972252, 61972254, 62072303, 62025204, 62132018, 62202296, and 62202297] , the Alibaba Innovation Research (AIR) Program, and the Tencent Rhino Bird Key Research Project. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.0057 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2022.0057 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
    Type of Medium: Online Resource
    ISSN: 1091-9856 , 1526-5528
    URL: Article
    DOI: 10.1287/ijoc.2022.0057
    RVK:
    QA 10000
    Language: English
    Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
    Publication Date: 2023
    detail.hit.zdb_id: 2070411-2
    detail.hit.zdb_id: 2004082-9
    SSG: 3,2
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