摘要：
With the rapid development of IoT technology, smart homes have emerged. At the same time, data security and privacy protection are also of great concern. However, the traditional centralized authentication scheme has defects such as single point of failure, poor scalability, center dependence, vulnerability to attacks, etc., and is not suitable for the distributed and dynamically changing smart home environment. Thus, many researchers have proposed decentralized authentication schemes based on blockchain technology. Although many characteristics of blockchain technology such as decentralization, non -tampering, and solving single point of failure have good application scenarios in authentication, the mature integration of the two applications has to be further explored. For example, the introduction of blockchain also brings security issues; the balance between security and performance in most blockchain-based authentication schemes remains to be investigated; and resource -constrained IoT devices tend to perform a large number of intensive computations, which is clearly inappropriate. Consequently, this paper introduces fog computing in blockchain-based authentication schemes, proposes a network architecture in which cloud and fog computing work together, and investigates the security and performance issues of authentication schemes under this architecture. Finally, formal and informal security analysis show that our scheme has multiple security properties, and our scheme has better performance than existing solutions.
摘要：
WaveMLP has demonstrated remarkable performance in various vision tasks, such as dense feature detection and semantic segmentation. However, WaveMLP, as a local model, imposes limitations on fully connected layers by only allowing connections between tokens within the same local window. This constraint makes the model neglect the relationship among tokens in different windows, leading to a local token fusion and a degraded modeling performance. Specially, it poses challenges when dealing with hyperspectral image (HSI) classification tasks that require capturing long-range dependencies. To address this issue, this letter proposes a new position-aware WaveMLP, dubbed PA-WaveMLP, which incorporates a global polar positional encoding module (PPEM) into WaveMLP. PPEM is a lightweight method to encode the spatial relationship between land objects in distance and direction by using the radius and angle. By PPEM, the proposed PA-WaveMLP enables tokens to include their own spatial position information to the fusion process, allowing for the capture of long-range dependencies, while maintaining the excellent modeling capabilities of WaveMLP. The experimental results on three publicly available HSI datasets validate the effectiveness and generalizability of this newly proposed PA-WaveMLP. In particular, PA-WaveMLP model achieved an overall accuracy (OA) of 99.16%, 99.71%, and 99.47% on Indian Pines (IP), Pavia University (PU), and Salinas (SA), respectively.
期刊：
British Journal of Educational Technology,2024年55(5) ISSN：0007-1013
通讯作者：
Ba, S;Hu, X
作者机构：
[Ba, Shen] Educ Univ Hong Kong, Dept Curriculum & Instruct, Hong Kong, Peoples R China.;[Hu, Xiao] Univ Hong Kong, Fac Educ, Hong Kong, Peoples R China.;[Stein, David] Ohio State Univ, Coll Educ & Human Ecol, Columbus, OH USA.;[Liu, Qingtang] Cent China Normal Univ, Sch Educ Informat Technol, Wuhan, Peoples R China.;[Ba, Shen; Ba, S] Educ Univ Hong Kong, Dept Curriculum & Instruct, Tai Po, 10 Lo Ping Rd, Hong Kong, Peoples R China.
通讯机构：
[Ba, S ] E;[Hu, X ] U;Educ Univ Hong Kong, Dept Curriculum & Instruct, Tai Po, 10 Lo Ping Rd, Hong Kong, Peoples R China.;Univ Hong Kong, Fac Educ, Pokfulam, Room 209, Runme Shaw Bldg, Hong Kong, Peoples R China.
关键词：
community of inquiry;epistemic network analysis;learning analytics;online discussion;trajectory tracking
摘要：
<jats:title>Abstract</jats:title><jats:p>Accurate assessment and effective feedback are crucial for cultivating learners' abilities of collaborative problem‐solving and critical thinking in online inquiry‐based discussions. Based on quantitative content analysis (QCA), there has been a methodological evolvement from descriptive statistics to sequential mining and to network analysis for mining coded discourse data. Epistemic network analysis (ENA) has recently gained increasing recognition for modelling and visualizing the temporal characteristics of online discussions. However, due to methodological restraints, some valuable information regarding online discussion dynamics remains unexplained, including the directionality of connections between theoretical indicators and the trajectory of thinking development. Guided by the community of inquiry (CoI) model, this study extended generic ENA by incorporating directional connections and stanza‐based trajectory tracking. By examining the proposed extensions with discussion data of an online learning course, this study first verified that the extensions arecomparable with QCA, indicating acceptable assessment validity. Then, the directional ENA revealed that two‐way connections between CoI indicators could vary over time and across groups, reflecting different discussion strategies. Furthermore, trajectory tracking effectively detected and visualized the fine‐grained progression of thinking. At the end, we summarize several research and practical implications of the ENA extensions for assessing the learning process.<jats:boxed-text content-type="box" position="anchor"><jats:caption><jats:title>Practitioner notes</jats:title></jats:caption><jats:sec><jats:title>What is already known about this topic</jats:title><jats:p>
<jats:list list-type="bullet">
<jats:list-item><jats:p>Assessment and feedback are crucial for cultivating collaborative problem‐solving and critical thinking in online inquiry‐based discussions.</jats:p></jats:list-item>
<jats:list-item><jats:p>Cognitive presence is an important construct describing the progression of thinking in online inquiry‐based discussions.</jats:p></jats:list-item>
<jats:list-item><jats:p>Epistemic network analysis is gaining increasing recognition for modelling the temporal characteristics of online inquiries.</jats:p></jats:list-item>
</jats:list></jats:p></jats:sec><jats:sec><jats:title>What this paper adds</jats:title><jats:p>
<jats:list list-type="bullet">
<jats:list-item><jats:p>Directional connections between discourses can reflect different online discussion strategies of groups and individuals.</jats:p></jats:list-item>
<jats:list-item><jats:p>A pair of connected discourses coded with the community of inquiry model can have different meanings depending on their temporal order.</jats:p></jats:list-item>
<jats:list-item><jats:p>A trajectory tracking approach can uncover the fine‐grained progression of thinking in online inquiry‐based discussions.</jats:p></jats:list-item>
</jats:list></jats:p></jats:sec><jats:sec><jats:title>Implications for practice and/or policy</jats:title><jats:p>
<jats:list list-type="bullet">
<jats:list-item><jats:p>Besides the occurrences of individual discourses, examining the meanings of directional co‐occurrences of discourses in online discussions is worthwhile.</jats:p></jats:list-item>
<jats:list-item><jats:p>Groups and individuals can employ different discussion strategies and follow diverse paths to thought development.</jats:p></jats:list-item>
<jats:list-item><jats:p>Developmental assessment is crucial for understanding how participants achieve specific outcomes and providing adaptive feedback.</jats:p></jats:list-item>
</jats:list></jats:p></jats:sec></jats:boxed-text></jats:p>
作者：
Huang, Yi;Fang, Cong;Yang, Fan;Gong, Senlin;Wang, Xi
期刊：
PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY,2024年88:905-914 ISSN：0141-6359
通讯作者：
Fang, C
作者机构：
[Huang, Yi; Wang, Xi] Xiamen Univ, Dept Prop Engn, Xiamen 361005, Peoples R China.;[Fang, Cong; Fang, C] Hong Kong Polytech Univ, Sch Design, Hong Kong, Peoples R China.;[Yang, Fan] Cent China Normal Univ, Natl Res Ctr Cultural Ind, Wuhan 430079, Peoples R China.;[Gong, Senlin] State Owned Wuhu Machinery Factory, Wuhu 241007, Peoples R China.
通讯机构：
[Fang, C ] H;Hong Kong Polytech Univ, Sch Design, Hong Kong, Peoples R China.
摘要：
Manufacturing internal splines with complex structures in high-hardness materials poses challenges in conventional machining processes. This paper introduced a new electrochemical machining (ECM) method using an assembled tool cathode with a cathode working teeth sheet with circumferential vibration for efficient and stable shaping of involute internal splines of intricate high-hardness components. A detailed design of the assembled tool cathode is presented, accompanied by flow field simulations analysing electrolyte distribution during circumferential vibration. A specific experimental system, fixture, and a used electrolyte filter module were constructed for spline ECM experiments. The results show that with the cathode feed rate of 2.7 mm/min, and the circumferential vibration frequency of 80 Hz, the involute internal spline profiles were successfully shaped with higher precision and efficiency with less appropriate allowance.
作者机构：
[Zhang, Man; Zhang, Jiawei; Zhang, M] Cent China Normal Univ, Sch Foreign Languages, Wuhan, Peoples R China.;[Zhang, Man; Zhang, M] Humboldt Univ, Fac Language Literature & Humanities, Berlin, Germany.
通讯机构：
[Zhang, M ] C;Cent China Normal Univ, Sch Foreign Languages, Wuhan, Peoples R China.;Humboldt Univ, Fac Language Literature & Humanities, Berlin, Germany.
通讯机构：
[Liang, P ] W;Wuhan Univ, Sch Comp Sci, Wuhan, Peoples R China.;Hubei Luojia Lab, Wuhan, Peoples R China.
关键词：
Mining Architectural Information;Software Repositories;Architecting Activity;Software Development;Systematic Mapping Study
摘要：
Mining Software Repositories (MSR) has become an essential activity in software development. Mining architectural information (e.g., architectural models) to support architecting activities, such as architecture understanding, has received significant attention in recent years. However, there is a lack of clarity on what literature on mining architectural information is available. Consequently, this may create difficulty for practitioners to understand and adopt the state-of-the-art research results, such as what approaches should be adopted to mine what architectural information in order to support architecting activities. It also hinders researchers from being aware of the challenges and remedies for the identified research gaps. We aim to identify, analyze, and synthesize the literature on mining architectural information in software repositories in terms of architectural information and sources mined, architecting activities supported, approaches and tools used, and challenges faced. A Systematic Mapping Study (SMS) has been conducted on the literature published between January 2006 and December 2022. Of the 104 primary studies finally selected, 7 categories of architectural information have been mined, among which architectural description is the most mined architectural information; 11 categories of sources have been leveraged for mining architectural information, among which version control system (e.g., GitHub) is the most popular source; 11 architecting activities can be supported by the mined architectural information, among which architecture understanding is the most supported activity; 95 approaches and 56 tools were proposed and employed in mining architectural information; and 4 types of challenges in mining architectural information were identified. This SMS provides researchers with promising future directions and help practitioners be aware of what approaches and tools can be used to mine what architectural information from what sources to support various architecting activities.
摘要：
Entities and relations extraction are the key tasks in the construction of biomedical knowledge graph, which play an important role in the biomedical artificial intelligence. However, extraction of entities and relations from biomedical texts is challenging because of the overlapping triples problem. The previous approaches typically divided the task into two separate sub-tasks. However, these methods failed to address the error propagation problem. Recent methods have been proposed to perform both sub-tasks simultaneously. Nonetheless, most current methods still encounter issues related to imbalanced interactions and independent features. In this paper, we propose a novel method based on feature partition encoding and relative positional embedding to joint extract biomedical entity and relation triples simultaneously. Compared to previous work, our method shows exceptional accurate in extracting entities and relations, while efficiently tackling the challenge of overlapping triples in biomedical texts. Our work has two contributions. Firstly, our method divides the features into task-specific and shared parts through entity, relation and sharing partitions at the encoding stage. And the encoded features will be aggregated according to the subsequent tasks. Secondly, we introduce a relative positional embedding method to capture the relative distance information between token pairs. In this way, our method can effectively deal with the sub-tasks interactions problem and improve entities and relations extraction. The experimental results show that our method improves the F1 scores of relations extraction by 3.2%, 2.1%, 3.4%, and 2.8% on four biomedical datasets, respectively.
期刊：
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS,2024年PP:1-12 ISSN：2168-2194
作者机构：
[Xueli Pan; Frank van Harmelen] Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands;Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan, China;National Engineering Research Center for E-Learning, Central China Normal University, Wuhan, China;National Language Resources Monitor Research Center for Network Media, Central China Normal University, Wuhan, China;School of Computer Science, Central China Normal University, Wuhan, China
摘要：
It is commonly known that food nutrition is closely related to human health. The complex interactions between food nutrients and diseases, influenced by gut microbial metabolism, present challenges in systematizing and practically applying knowledge. To address this, we propose a method for extracting triples from a vast amount of literature, which is used to construct a comprehensive knowledge graph on nutrition and human health. Concurrently, we develop a query-based question answering system over our knowledge graph, proficiently addressing three types of questions. The results show that our proposed model outperforms other state-of-art methods, achieving a precision of 0.92, a recall of 0.81, and an F1 score of 0.86in the nutrition and disease relation extraction task. Meanwhile, our question answering system achieves an accuracy of 0.68 and an F1 score of 0.61 on our benchmark dataset, showcasing competitiveness in practical scenarios. Furthermore, we design five independent experiments to assess the quality of the data structure in the knowledge graph, ensuring results characterized by high accuracy and interpretability. In conclusion, the construction of our knowledge graph shows significant promise in facilitating diet recommendations, enhancing patient care applications, and informing decision-making in clinical research.
摘要：
The current digital speech deletion and insertion tampering detection methods mainly employes the extraction of phase and frequency features of the Electrical Network Frequency (ENF). However, there are some problems with the existing approaches, such as the alignment problem for speech samples with different durations, the sparsity of ENF features, and the small number of tampered speech samples for training, which lead to low accuracy of deletion and insertion tampering detection. Therefore, this paper proposes a tampering detection method for digital speech deletion and insertion based on ENF Fluctuation Super -vector (ENF-FSV) and deep feature learning representation. By extracting the parameters of ENF phase and frequency fitting curves, feature alignment and dimensionality reduction are achieved, and the alignment and sparsity problems are avoided while the fluctuation information of phase and frequency is extracted. To solve the problem of the insufficient sample size of tampered speech for training, the ENF Universal Background Model (ENF-UBM) is built by a large number of untampered speech samples, and the mean vector is updated to extract ENF-FSV. Considering the shallow representation of ENF features with not highlighting important features, we construct an end -toend deep neural network to strengthen the attention to the abrupt fluctuation information by the attention mechanism to enhance the representational power of the ENF-FSV features, and then the deep ENF-FSV features extracted by the Residual Network (ResNet) module are fed to the designed classification network for tampering detection. The experimental results show that the method in this paper exhibits higher accuracy and better robustness in the Carioca, New Spanish, and ENF High -sampling Group (ENF-HG) databases when compared with the state-of-the-art methods.
期刊：
Education and Information Technologies,2024年:1-24 ISSN：1360-2357
通讯作者：
Wang, J
作者机构：
[Yang, Yuqin] Cent China Normal Univ, Fac Artificial Intelligence Educ, Wuhan, Hubei, Peoples R China.;[Sun, Daner; Zheng, Zhizi] Educ Univ Hong Kong, Dept Math & Informat Technol, Hong Kong, Peoples R China.;[Wang, Jing] Zhejiang Univ, Coll Educ, Hangzhou, Zhejiang, Peoples R China.
关键词：
Community of inquiry;Online self-regulation;Empowerment;Motivational beliefs;Cognitive presence
摘要：
This study extends the community of inquiry (CoI) framework and empowerment theory by exploring the relationships between motivational variables, CoI variables, learning presence, and empowerment. We added motivational beliefs (growth mindset, self-efficacy, and task value) as associated variables and learning presence (online self-regulation) as a mediator and examined their contribution to students' cognitive presence and empowerment. The participants were 539 junior middle-school students in rural China who had acquired significant online learning experience as a result of the COVID-19 pandemic. The results showed that motivational variables were associated with students' social presence and online self-regulation, which in turn related to their cognitive presence and empowerment in the online learning environment. Growth mindset and self-efficacy also exhibited a significant correlation with students' cognitive presence. There was a positive correlation between cognitive presence and empowerment. We also found teaching presence has a positive association with social presence but a negative association with online self-regulation. Our research provides a more comprehensive explanatory model of online instruction and student empowerment by introducing the elements of motivational beliefs and learning presence to the CoI framework.
摘要：
Pseudo-label (PL) learning-based methods usually regard class confidence above a certain threshold for unlabeled samples as PLs, which may result in PLs still containing wrong labels. In this letter, we propose a prototype-based PL refinement (PPLR) for semi-supervised hyperspectral image (HSI) classification. The proposed PPLR filters wrong labels from PLs using class prototypes, which can improve the discrimination of the network. First, PPLR uses multihead attentions (MHAs) to extract the spectral-spatial features, and designs an adaptive threshold that can be dynamically adjusted to generate high-confidence PLs. Then, PPLR constructs class prototypes for different categories using labeled sample features and unlabeled sample features with refined PLs to improve the quality of PLs by filtering wrong labels. Finally, PPLR further assigns reliable weights (RWs) to these PLs in calculating their supervised loss, and introduces a center loss (CL) to improve the discrimination of features. When ten labeled samples per category are utilized for training, PPLR achieves the overall accuracies of 82.11%, 86.70%, and 92.50% on the Indian Pines (IP), Houston2013, and Salinas datasets, respectively.
