| 1. |
- Wang, Xinping, et al.
(författare)
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Nature of three episodes of Paleoproterozoic magmatism (2180 Ma, 2115 Ma and 1890 Ma) in the Liaoji belt, North China with implications for tectonic evolution
- 2017
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Ingår i: Precambrian Research. - : Elsevier BV. - 0301-9268. ; 298, s. 252-267
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Tidskriftsartikel (refereegranskat)abstract
- Three episodes of Paleoproterozoic magmatism with distinctively different nature in the Liaoji belt of the Eastern North China Craton are discussed here: the 2200–2140 Ma Liaoji A-type granites, the 2160–2110 Ma Haicheng mafic sills and the ∼1890 Ma Qingchengzi I-type granites. The Mafeng monzogranitic pluton, representative of the Liaoji A-type granites, gives a SIMS U-Pb zircon age of 2181 ± 6 Ma (n = 20, MSWD = 4.3). The Qingchengzi plagiogranitic pluton, representative of the Qingchengzi I-type granites, gives a SIMS U-Pb zircon age of 1891 ± 10 Ma (n = 8, MSWD = 1.8). The Mafeng monzogranites are high in Fe, Ti, K but low in Mg, Al and Ca. They have high abundance of total REEs (ΣREE = 213–346 ppm). They are relatively depleted in feldspar-compatible elements (e.g., Eu and Sr) and HFSEs (e.g., Nb, Ta, P and Ti). They have high 10000 × Ga/Al ratios of 3.19–3.61 and Zr + Nb + Ce + Y concentrations of 472–656 ppm, which are typical for A-type granite. The Qingchengzi plagiogranites have relatively high Al, Ca, Na but low Fe, Ti and K contents. They have low abundance of total REEs (ΣREE = 17.6–21.6 ppm). They are enriched in LILEs (e.g., Ba, K and Sr) but depleted in HFSEs (e.g., Nb, Ta, P, Ti and Y). These features, combined with extremely high Sr/Y ratios (327–413), are comparable with those of typical modern adakites. The Liaoji A-type granites show a source same to that of the Haicheng mafic sills and they originated from the Archean subcontinental lithospheric mantle plus with contamination from the Archean granites. However, the Qingchengzi I-type granites are interpreted to originate from subducted oceanic crust with significant contributions from sediments. The Liaoji A-type granites and the coeval bimodal volcanism in the Liaohe Group as well as the Haicheng mafic sills may represent episodic magmatism which was related to a protracted intra-continental rifting caused by lithospheric extension. The ca. 1890 Ma Qingchengzi I-type granites and coexisting S-type granites as well as the coeval regional metamorphism are favored to represent an active continental magmatism linked to Paleoproterozoic subduction.
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| 2. |
- Li, Xiangdong A., et al.
(författare)
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Design and Evaluation of Cross-Objects User Interface for Whiteboard Interaction
- 2017
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Ingår i: Distributed, Ambient and Pervasive Interactions. - Cham : Springer. - 9783319586960 - 9783319586977 ; , s. 180-191
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Konferensbidrag (refereegranskat)abstract
- Whiteboard has long been an important tool for education and communication, and nowadays it embraces display functions and other interactive features such as pen pointing and selecting of digital contents. Despite the enhanced interactivity, it is often time- and cost-consuming to implement specific apparatus for different whiteboard interactions. Therefore, we aimed at incorporating physical-world objects (e.g. Lego Rubik’s cubes) as the cross-objects user interface for multiple whiteboard interaction tasks without incurring heavy development work. The user interface utilised electromagnetic technique to extract electromechanical signals and recognised normal objects, thus extended the generality. To further understand effectiveness of the user interface, we implemented a low-fidelity prototype and conducted within-subject evaluation. The results showed the cross-objects user interface was natural, responsive, and easy of learning as the conventional whiteboard. Moreover, the user interface outperformed over the conventional one in the perspectives of configuration efficiency and versatility of multiple interaction tasks. Given these findings, practical implications for future tangible user interface design for whiteboard interactions are discussed.
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| 3. |
- Lou, Xianglong, et al.
(författare)
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Effects of User’s Hand Orientation and Spatial Movements on Free Hand Interactions with Large Displays
- 2018
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Ingår i: International Journal of Human-Computer Interaction. - : Informa UK Limited. - 1044-7318 .- 1532-7590. ; 34:6, s. 519-532
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Tidskriftsartikel (refereegranskat)abstract
- In motion-sensing interaction with large displays through bare hands, we can observe that users alternate their hands and move their bodies frequently. What cause such actions and how these actions affect free hand interaction results are less systematically investigated. To address this gap in knowledge, we conducted studies on Pointer-Acceleration (PA)-based free hand interactions of target selection and found that (1) users made more frequent hand alternations when selecting small targets with large movement amplitudes, as in such cases users were not only affected by observable arm fatigue, but were also motivated to switch hands for higher selection accuracy and convenience; (2) hand alternation led to the hand orientation effects: target selection on display areas at the operating hand’s side was more efficient and accurate than that at the opposite side; (3) large movement amplitudes on the user interface increased users’ physical movements in front of the large display, which harmed selection efficiency; (4) selection of small targets led to a closer interaction distance, while large movement amplitudes led to a larger interaction distance; and (5) selection results were affected by interaction distances, as users gained high efficiency, but low accuracy at a large distance and low efficiency, but high accuracy at a close distance. Given these results, this article discusses practical implications for applying PA-based free hand interaction techniques and designing related user interfaces on large displays.
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| 4. |
- Lou, Xiaolong, et al.
(författare)
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Hand-adaptive user interface : improved gestural interaction in virtual reality
- 2021
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Ingår i: Virtual Reality. - : Springer Science and Business Media LLC. - 1359-4338 .- 1434-9957. ; 25, s. 367-382
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Tidskriftsartikel (refereegranskat)abstract
- Most interactive user interfaces (UIs) for virtual reality (VR) applications are based on the traditional eye-centred UI design principle, which primarily considers the user's visual searching efficiency and comfort, but the hand operation performance and ergonomics are relatively less considered. As a result, the hand interaction in VR is often criticized as being less efficient and precise. In this paper, the user's arm movement features, such as the choice of the hand being used and hand interaction position, are hypothesized to influence the interaction results derived from a VR study. To verify this, we conducted a free hand target selection experiment with 24 participants. The results showed that (a) the hand choice had a significant effect on the target selection results: for a left hand interaction, the targets located in spaces to the left were selected more efficiently and accurately than those in spaces to the right; however, in a right hand interaction, the result was reversed, and (b) the free hand interactions at lower positions were more efficient and accurate than those at higher positions. Based on the above findings, this paper proposes a hand-adaptive UI technique to improve free hand interaction performance in VR. A comprehensive comparison between the hand-adaptive UI and traditional eye-centred UI was also conducted. It was shown that the hand-adaptive UI resulted in a higher interaction efficiency and a lower physical exertion and perceived task difficulty than the traditional UI.
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| 5. |
- Peng, Xiangdong, et al.
(författare)
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DSCSSA: A Classification Framework for Spatiotemporal Features Extraction of Arrhythmia Based on the Seq2Seq Model With Attention Mechanism
- 2022
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Ingår i: IEEE Transactions on Instrumentation and Measurement. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9456 .- 1557-9662. ; 71
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Tidskriftsartikel (refereegranskat)abstract
- In the field of arrhythmia classification, classification accuracy has always been a research hotspot. However, the noises of electrocardiogram (ECG) signals, the class imbalance of ECG data, and the complexity of spatiotemporal features of ECG data are all important factors affecting the accuracy of ECG arrhythmias classification. In this article, a novel DSCSSA ECG arrhythmias classification framework is proposed. First, discretewavelet transform (DWT) is used to denoise and reconstruct ECG signals to improve the feature extraction ability of ECG signals.Then, the synthetic minority oversampling technique (SMOTE) oversampling method is used to synthesize a new minority sample ECG signal to reduce the impact of ECG data imbalance on classification. Finally, a convolutional neural network (CNN) and sequence-to-sequence (Seq2Seq) classification model with attention mechanism based on bi directional long short-term memory(Bi-LSTM) as the codec is used for arrhythmias classification, and the model can give corresponding weight according to the importance of heartbeat features and can improve the ability toextract and filter the spatiotemporal features of heartbeats. In the classification of five heartbeat types, including normal beat (N), supraventricular ectopic beat (S), ventricular ectopic beat (V),fusion beat (F), and unknown beat (Q), the proposed method achieved the overall accuracy (OA) value and Macro-F1 score of 99.28% and 95.70%, respectively, in public the Massachusetts Institute of Technology - Boston’s Beth Israel Hospital (MIT-BIH)arrhythmia database. These methods are helpful to improve the effectiveness and clinical reference value of computer-aided ECG automatic classification diagnosis.
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| 8. |
- Wang, Xiaohuan, et al.
(författare)
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Using Machine Learning Method to Discover Hygrothermal Transfer Patterns from the Outside of the Wall to Interior Bamboo and Wood Composite Sheathing
- 2022
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Ingår i: Buildings. - : MDPI AG. - 2075-5309. ; 12:7, s. 898-898
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Tidskriftsartikel (refereegranskat)abstract
- To identify hygrothermal transfer patterns of exterior walls is a crucial issue in the design, assessment, and construction of buildings. Temperature and relative humidity, as sensor monitoring data, were collected from the outside of the wall to interior bamboo and wood composite sheathing over the year in Huangshan Mountain District, Anhui Province, China. Combining the machine learning method of reservoir computing (RC) with agglomerative hierarchical clustering (AHC), a novel clustering framework was built for better extraction of the characteristics of hygrothermal transfer on the time series data. The experimental results confirmed the hypothesis that the change in the temperature and relative humidity of the outside of the wall (RHT12) dominated the change of the interior sheathing (RHT11). The delay time between two adjacent peaks in temperature was 1 to 2 h, while that in relative humidity was 1 to 4 h from the outside of the wall to interior bamboo and wood composite sheathing. There was no significant difference in temperature peak delay time between April and July. Temperature peak delay time was 50 to 120 min. However, relative humidity peak delay time was 100 to 240 min in April, whereas it was 20 to 120 min in July. The impact formed a relatively linear relationship between outdoor temperature and relative humidity peak delay time. The hygrothermal transfer patterns were characterized effectively by the peak delays. The discovery of the hygrothermal transfer patterns for the bamboo and wood composite walls using the machine learning method will facilitate the development of energy-efficient and durable bamboo and wood composite wall materials and structures.
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