Journal of Information and Intelligence最新文献

{"title":"Deep learning-based fall detection using commodity Wi-Fi","authors":"Tingwei Chen ,&nbsp;Xiaoyang Li ,&nbsp;Hang Li ,&nbsp;Guangxu Zhu","doi":"10.1016/j.jiixd.2024.04.001","DOIUrl":"10.1016/j.jiixd.2024.04.001","url":null,"abstract":"<div><p>As the phenomenon of an aging population gradually becomes common worldwide, the pressure on the elderly has seen a notable increase. To address this challenge, fall detection systems are important in ensuring the safety of the elderly population, particularly those living alone. Wi-Fi sensing, as a privacy-preserving method of perception, can be deployed indoors for detecting human activities such as falls, based on the reflective properties of electromagnetic waves. Signals generated by transmitters experience reflections from various objects within indoor environments, leading to distinct propagation paths. These signals eventually aggregate at the receiver, incorporating details about the objects’ orientation and their activity states. In this study, within practical experimental environments, we collect dataset and utilize deep learning method to classify the falling events.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 4","pages":"Pages 355-364"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000283/pdfft?md5=f31939e6bf88241fc2bd69185c959aa9&pid=1-s2.0-S2949715924000283-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140775565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural knowledge-driven meta-learning for task offloading in vehicular networks with integrated communications, sensing and computing","authors":"Ruijin Sun ,&nbsp;Yao Wen ,&nbsp;Nan Cheng ,&nbsp;Wei Wang ,&nbsp;Rong Chai ,&nbsp;Yilong Hui","doi":"10.1016/j.jiixd.2024.02.005","DOIUrl":"10.1016/j.jiixd.2024.02.005","url":null,"abstract":"<div><p>Task offloading is a potential solution to satisfy the strict requirements of computation-intensive and latency-sensitive vehicular applications due to the limited onboard computing resources. However, the overwhelming upload traffic may lead to unacceptable uploading time. To tackle this issue, for tasks taking environmental data as input, the data perceived by roadside units (RSU) equipped with several sensors can be directly exploited for computation, resulting in a novel task offloading paradigm with integrated communications, sensing and computing (I-CSC). With this paradigm, vehicles can select to upload their sensed data to RSUs or transmit computing instructions to RSUs during the offloading. By optimizing the computation mode and network resources, in this paper, we investigate an I-CSC-based task offloading problem to reduce the cost caused by resource consumption while guaranteeing the latency of each task. Although this non-convex problem can be handled by the alternating minimization (AM) algorithm that alternatively minimizes the divided four sub-problems, it leads to high computational complexity and local optimal solution. To tackle this challenge, we propose a creative structural knowledge-driven meta-learning (SKDML) method, involving both the model-based AM algorithm and neural networks. Specifically, borrowing the iterative structure of the AM algorithm, also referred to as structural knowledge, the proposed SKDML adopts long short-term memory (LSTM) network-based meta-learning to learn an adaptive optimizer for updating variables in each sub-problem, instead of the handcrafted counterpart in the AM algorithm. Furthermore, to pull out the solution from the local optimum, our proposed SKDML updates parameters in LSTM with the global loss function. Simulation results demonstrate that our method outperforms both the AM algorithm and the meta-learning without structural knowledge in terms of both the online processing time and the network performance.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 4","pages":"Pages 302-324"},"PeriodicalIF":0.0,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000106/pdfft?md5=40b4034f42d124042f5327bc76eb93ca&pid=1-s2.0-S2949715924000106-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140433037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unsupervised meta-learning with domain adaptation based on a multi-task reconstruction-classification network for few-shot hyperspectral image classification","authors":"Yu Liu ,&nbsp;Caihong Mu ,&nbsp;Shanjiao Jiang ,&nbsp;Yi Liu","doi":"10.1016/j.jiixd.2024.06.001","DOIUrl":"10.1016/j.jiixd.2024.06.001","url":null,"abstract":"<div><div>Although the deep-learning method has achieved great success for hyperspectral image (HSI) classification, the few-shot HSI classification deserves sufficient study because it is difficult and expensive to acquire labeled samples. In fact, the meta-learning methods can improve the performance for few-shot HSI classification effectively. However, most of the existing meta-learning methods for HSI classification are supervised, which still heavily rely on the labeled data for meta-training. Moreover, there are many cross-scene classification tasks in the real world, and domain adaptation of unsupervised meta-learning has been ignored for HSI classification so far. To address the above issues, this paper proposes an unsupervised meta-learning method with domain adaptation based on a multi-task reconstruction-classification network (MRCN) for few-shot HSI classification. MRCN does not need any labeled data for meta-training, where the pseudo labels are generated by multiple spectral random sampling and data augmentation. The meta-training of MRCN jointly learns a shared encoding representation for two tasks and domains. On the one hand, we design an encoder-classifier to learn the classification task on the source-domain data. On the other hand, we devise an encoder-decoder to learn the reconstruction task on the target-domain data. The experimental results on four HSI datasets demonstrate that MRCN preforms better than several state-of-the-art methods with only two to five labeled samples per class. To the best of our knowledge, the proposed method is the first unsupervised meta-learning method that considers the domain adaptation for few-shot HSI classification.</div></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"3 2","pages":"Pages 103-112"},"PeriodicalIF":0.0,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143175025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PGCF: Perception graph collaborative filtering for recommendation","authors":"Caihong Mu ,&nbsp;Keyang Zhang ,&nbsp;Jiashen Luo ,&nbsp;Yi Liu","doi":"10.1016/j.jiixd.2024.05.003","DOIUrl":"10.1016/j.jiixd.2024.05.003","url":null,"abstract":"<div><div>Extensive studies have fully proved the effectiveness of collaborative filtering (CF) recommendation models based on graph convolutional networks (GCNs). As an advanced interaction encoder, however, GCN-based CF models do not differentiate neighboring nodes, which will lead to suboptimal recommendation performance. In addition, most GCN-based CF studies pay insufficient attention to the loss function and they simply select the Bayesian personalized ranking (BPR) loss function to train the model. However, we believe that the loss function is as important as the interaction encoder and deserves more attentions. To address the above issues, we propose a novel GCN-based CF model, named perception graph collaborative filtering (PGCF). Specifically, for the interaction encoder, we design a neighborhood-perception GCN to enhance the aggregation of interest-related information of the target node during the information aggregation process, while weakening the propagation of noise and irrelevant information to help the model learn better embedding representation. For the loss function, we design a margin-perception Bayesian personalized ranking (MBPR) loss function, which introduces a self-perception margin, requiring the predicted score of the user-positive sample to be greater than that of the user-negative sample, and also greater than the sum of the predicted score of the user-negative sample and the margin. The experimental results on five benchmark datasets show that PGCF is significantly superior to multiple existing CF models.</div></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 6","pages":"Pages 525-534"},"PeriodicalIF":0.0,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental full-duplex amplify-and-forward relay scheme for OFDM with power gain control","authors":"","doi":"10.1016/j.jiixd.2024.05.001","DOIUrl":"10.1016/j.jiixd.2024.05.001","url":null,"abstract":"<div><p>The fundamental challenges for full-duplex (FD) relay networks are the self-interference cancellation (SIC) and the cooperative transmission design at the relay. This paper presents a practical amplify-and-forward (AF) FD one-way relay scheme for orthogonal frequency division multiplexing (OFDM) transmission with multi-domain SIC. It is found that the residual self-interference (SI) signals at the relay can be regarded as an equivalent multipath model. The effects of the residual SI at the relay are incorporated into the equivalent end-to-end channel model, and the inter-block interference can be removed at the destination by using cyclic prefix (CP) protection. Based on the equivalent multipath model, we present a solution for optimizing the amplification factor on the performance of signal-to-interference-plus-noise ratio (SINR) when the equivalent multipath length is longer than the CP. Furthermore, a practical one way FD relay network with 3 nodes is built and measured. The simulation and measured results verify the superior performance of the proposed scheme.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 5","pages":"Pages 375-387"},"PeriodicalIF":0.0,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000362/pdfft?md5=fe196ceb9fd9ca78d469646703de4d63&pid=1-s2.0-S2949715924000362-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141138652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A lightweight and efficient raw data collection scheme for IoT systems","authors":"Yixuan Huang ,&nbsp;Yining Liu ,&nbsp;Jingcheng Song ,&nbsp;Weizhi Meng","doi":"10.1016/j.jiixd.2024.03.004","DOIUrl":"10.1016/j.jiixd.2024.03.004","url":null,"abstract":"<div><p>With the prevalence of Internet of Things (IoT) devices, data collection has the potential to improve people's lives and create a significant value. However, it also exposes sensitive information, which leads to privacy risks. An approach called N-source anonymity has been used for privacy preservation in raw data collection, but most of the existing schemes do not have a balanced efficiency and robustness. In this work, a lightweight and efficient raw data collection scheme is proposed. The proposed scheme can not only collect data from the original users but also protect their privacy. Besides, the proposed scheme can resist user poisoning attacks, and the use of the reward method can motivate users to actively provide data. Analysis and simulation indicate that the proposed scheme is safe against poison attacks. Additionally, the proposed scheme has better performance in terms of computation and communication overhead compared to existing methods. High efficiency and appropriate incentive mechanisms indicate that the scheme is practical for IoT systems.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 3","pages":"Pages 209-223"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000271/pdfft?md5=51591f30faf1b37d53c6c14d9cec3ea7&pid=1-s2.0-S2949715924000271-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140763826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A two-branch multiscale spectral-spatial feature extraction network for hyperspectral image classification","authors":"Aamir Ali ,&nbsp;Caihong Mu ,&nbsp;Zeyu Zhang ,&nbsp;Jian Zhu ,&nbsp;Yi Liu","doi":"10.1016/j.jiixd.2024.03.002","DOIUrl":"10.1016/j.jiixd.2024.03.002","url":null,"abstract":"<div><p>In the field of hyperspectral image (HSI) classification in remote sensing, the combination of spectral and spatial features has gained considerable attention. In addition, the multiscale feature extraction approach is very effective at improving the classification accuracy for HSIs, capable of capturing a large amount of intrinsic information. However, some existing methods for extracting spectral and spatial features can only generate low-level features and consider limited scales, leading to low classification results, and dense-connection based methods enhance the feature propagation at the cost of high model complexity. This paper presents a two-branch multiscale spectral-spatial feature extraction network (TBMSSN) for HSI classification. We design the multiscale spectral feature extraction (MSEFE) and multiscale spatial feature extraction (MSAFE) modules to improve the feature representation, and a spatial attention mechanism is applied in the MSAFE module to reduce redundant information and enhance the representation of spatial features at multiscale. Then we densely connect series of MSEFE or MSAFE modules respectively in a two-branch framework to balance efficiency and effectiveness, alleviate the vanishing-gradient problem and strengthen the feature propagation. To evaluate the effectiveness of the proposed method, the experimental results were carried out on bench mark HSI datasets, demonstrating that TBMSSN obtained higher classification accuracy compared with several state-of-the-art methods.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 3","pages":"Pages 224-235"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000167/pdfft?md5=d4d6ccaef4c80b7e55681a18aea7102b&pid=1-s2.0-S2949715924000167-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140280893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A new lattice-based partially blind signature with more complete proof","authors":"Peiyu Li ,&nbsp;Juntao Gao ,&nbsp;Xuelian Li","doi":"10.1016/j.jiixd.2024.03.001","DOIUrl":"10.1016/j.jiixd.2024.03.001","url":null,"abstract":"<div><p>Partially blind signatures are introduced on the basis of blind signatures, which not only retain the advantages of blind signatures, but also solve the contradiction between anonymity and controllability in blind signatures. With the development of quantum computing technology, it becomes more urgent to construct secure partially blind signature schemes in quantum environments. In this paper, we present a new partially blind signature scheme and prove the security under the Ring-SIS assumption in the random oracle model. To avoid the restart problem of signature schemes caused by rejection sampling, a large number of random numbers are sampled in advance, so that they only need to be re-selected at the current stage without terminating the whole signature process when the conditions are not met. In addition, the hash tree technology is used to reduce communication costs and improve interactive performance. In order to avoid the errors in the security proof of the previous scheme, our proof builds upon and extends the modular framework for blind signatures of Hauck et al. and the correctness, partial blindness, and one-more unforgeability of the scheme are proved in detail according to the properties of the linear hash function.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 3","pages":"Pages 236-252"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000155/pdfft?md5=b4f02711a72cc18ef1aaa3009a5e29c6&pid=1-s2.0-S2949715924000155-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140272837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Connecting the indispensable roles of IoT and artificial intelligence in smart cities: A survey","authors":"Hoang Nguyen,&nbsp;Dina Nawara,&nbsp;Rasha Kashef","doi":"10.1016/j.jiixd.2024.01.003","DOIUrl":"10.1016/j.jiixd.2024.01.003","url":null,"abstract":"<div><p>The pace of society development is faster than ever before, and the smart city paradigm has also emerged, which aims to enable citizens to live in more sustainable cities that guarantee well-being and a comfortable living environment. This has been done by a network of new technologies hosted in real time to track the activities and provide smart solutions for the incoming requests or problems of the citizens. One of the most often used methodologies for creating a smart city is the Internet of Things (IoT). Therefore, the IoT-enabled smart city research topic, which consists of many different domains such as transportation, healthcare, and agriculture, has recently attracted increasing attention in the research community. Further, advances in artificial intelligence (AI) significantly contribute to the growth of IoT. In this paper, we first present the smart city concept, the background of smart city development and the components of the IoT-based smart city. This is followed up by a literature review of the research literature on the most recent IoT-enabled smart cities developments and breakthroughs empowered by AI techniques to highlight the current stage, major trends and unsolved challenges of adopting AI-driven IoT technologies for the establishment of desirable smart cities. Finally, we summarize the paper with a discussion of future research to provide recommendations for research direction in the smart city domain.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 3","pages":"Pages 261-285"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000039/pdfft?md5=dbe5fc30bdb6ef659aea2a2609e4cf12&pid=1-s2.0-S2949715924000039-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139540673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Constructions of correlation immnue S-boxes with high nonlinearity","authors":"Yanhan Ji ,&nbsp;Zhuo Ma ,&nbsp;Luyang Li ,&nbsp;Yujuan Sun","doi":"10.1016/j.jiixd.2024.01.005","DOIUrl":"https://doi.org/10.1016/j.jiixd.2024.01.005","url":null,"abstract":"<div><p>S-boxes play a central role in the design of symmetric cipher schemes. For stream cipher applications, an S-box should satisfy several criteria such as high nonlinearity, balanceness, correlation immunity, and so on. In this paper, by using disjoint linear codes, a class of S-boxes possessing high nonlinearity and 1st-order correlation immunity is given. It is shown that the constructed correlation immune S-boxes can possess currently best known nonlinearity, which is confirmed by the example 1st-order correlation immune (12, 3) S-box with nonlinearity 2000. In addition, two other frameworks concerning the criteria of balanced and resiliency are obtained respectively.</p></div>","PeriodicalId":100790,"journal":{"name":"Journal of Information and Intelligence","volume":"2 3","pages":"Pages 253-260"},"PeriodicalIF":0.0,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2949715924000052/pdfft?md5=ea4e350f6b9d3b0dd5bb671a433bf976&pid=1-s2.0-S2949715924000052-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141314093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}