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  • 1.
    Kristoffersson, Annica
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Wearable Sensors for Monitoring and Preventing Noncommunicable Diseases: A Systematic Review2020In: Information, E-ISSN 2078-2489, Vol. 11, no 11, p. 1-31, article id 521Article, review/survey (Refereed)
    Abstract [en]

    Ensuring healthy lives and promoting a healthy well-being for all at all ages are listed as some of the goals in Agenda 2030 for Sustainable Development. Considering that noncommunicable diseases (NCDs) are the leading cause of death worldwide, reducing the mortality of NCDs is an important target. To reach this goal, means for detecting and reacting to warning signals are necessary. Here, remote health monitoring in real time has great potential. This article provides a systematic review of the use of wearable sensors for the monitoring and prevention of NCDs. In addition, this article not only provides in-depth information about the retrieved articles, but also discusses examples of studies assessing warning signals that may result in serious health conditions, such as stroke and cardiac arrest, if left untreated. One finding is that even though many good examples of wearable sensor systems for monitoring and controlling NCDs are presented, many issues also remain to be solved. One major issue is the lack of testing on representative people from a sociodemographic perspective. Even though substantial work remains, the use of wearable sensor systems has a great potential to be used in the battle against NCDs by providing the means to diagnose, monitor and prevent NCDs.

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  • 2.
    Nygren, Thomas
    et al.
    Uppsala universitet, Institutionen för pedagogik, didaktik och utbildningsstudier.
    Guath, Mona
    Uppsala universitet, Institutionen för psykologi.
    Axelsson, Carl-Anton Werner
    Uppsala universitet, Avdelningen för visuell information och interaktion.
    Frau-Meigs, Diana
    Digital Humanities, University Sorbonne, Nouvelle, 75006 Paris, France.
    Combatting Visual Fake News with a Professional Fact-Checking Tool in Education in France, Romania, Spain and Sweden2021In: Information, E-ISSN 2078-2489, Vol. 12, no 5, article id 201Article in journal (Refereed)
    Abstract [en]

    Educational and technical resources are regarded as central in combating disinformation and safeguarding democracy in an era of ‘fake news’. In this study, we investigated whether a professional fact-checking tool could be utilised in curricular activity to make pupils more skilled in determining the credibility of digital news and to inspire them to use digital tools to further their transliteracy and technocognition. In addition, we explored how pupils’ performance and attitudes regarding digital news and tools varied across four countries (France, Romania, Spain, and Sweden). Our findings showed that a two-hour intervention had a statistically significant impact on teenagers’ abilities to determine the credibility of fake images and videos. We also found that the intervention inspired pupils to use digital tools in information credibility assessments. Importantly, the intervention did not make pupils more sceptical of credible news. The impact of the intervention was greater in Romania and Spain than among pupils in Sweden and France. The greater impact in these two countries, we argue, is due to cultural context and the fact that pupils in Romania and Spain learned to focus less on ’gut feelings’, increased their use of digital tools, and had a more positive attitude toward the use of the fact-checking tool than pupils in Sweden and France.

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  • 3.
    Wu, Peng
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China..
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Malardalen Univ, Sch Innovat Design & Engn, S-72123 Vasteras, Sweden..
    Xiong, Juxia
    Guangxi Univ Nationalities, Sch Math & Phys, Nanning 530006, Peoples R China..
    Wu, Jinzhao
    Beijing Jiaotong Univ, Sch Comp & Informat Technol, Beijing 100044, Peoples R China.;Guangxi Univ Nationalities, Sch Math & Phys, Nanning 530006, Peoples R China..
    Reasoning Method between Polynomial Error Assertions2021In: Information, E-ISSN 2078-2489, Vol. 12, no 8, article id 309Article in journal (Refereed)
    Abstract [en]

    Error coefficients are ubiquitous in systems. In particular, errors in reasoning verification must be considered regarding safety-critical systems. We present a reasoning method that can be applied to systems described by the polynomial error assertion (PEA). The implication relationship between PEAs can be converted to an inclusion relationship between zero sets of PEAs; the PEAs are then transformed into first-order polynomial logic. Combined with the quantifier elimination method, based on cylindrical algebraic decomposition, the judgment of the inclusion relationship between zero sets of PEAs is transformed into judgment error parameters and specific error coefficient constraints, which can be obtained by the quantifier elimination method. The proposed reasoning method is validated by proving the related theorems. An example of intercepting target objects is provided, and the correctness of our method is tested through large-scale random cases. Compared with reasoning methods without error semantics, our reasoning method has the advantage of being able to deal with error parameters.

  • 4.
    Zhang, L.
    et al.
    Department of Computer Engineering, Taiyuan Institute of Technology, Taiyuan 030008, China.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Gao, W.
    chool of Computer Science and Technology, Taiyuan Normal University, Jinzhong 030619, China.
    Wu, P.
    School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China.
    Improved Detection Method for Micro-Targets in Remote Sensing Images2024In: Information, E-ISSN 2078-2489, Vol. 15, no 2, article id 108Article in journal (Refereed)
    Abstract [en]

    With the exponential growth of remote sensing images in recent years, there has been a significant increase in demand for micro-target detection. Recently, effective detection methods for small targets have emerged; however, for micro-targets (even fewer pixels than small targets), most existing methods are not fully competent in feature extraction, target positioning, and rapid classification. This study proposes an enhanced detection method, especially for micro-targets, in which a combined loss function (consisting of NWD and CIOU) is used instead of a singular CIOU loss function. In addition, the lightweight Content-Aware Reassembly of Features (CARAFE) replaces the original bilinear interpolation upsampling algorithm, and a spatial pyramid structure is added into the network model’s small target layer. The proposed algorithm undergoes training and validation utilizing the benchmark dataset known as AI-TOD. Compared to speed-oriented YOLOv7-tiny, the mAP0.5 and mAP0.5:0.95 of our improved algorithm increased from 42.0% and 16.8% to 48.7% and 18.9%, representing improvements of 6.7% and 2.1%, respectively, while the detection speed was almost equal to that of YOLOv7-tiny. Furthermore, our method was also tested on a dataset of multi-scale targets, which contains small targets, medium targets, and large targets. The results demonstrated that mAP0.5:0.95 increased from “9.8%, 54.8%, and 68.2%” to “12.6%, 55.6%, and 70.1%” for detection across different scales, indicating improvements of 2.8%, 0.8%, and 1.9%, respectively. In summary, the presented method improves detection metrics for micro-targets in various scenarios while satisfying the requirements of detection speed in a real-time system.

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