In this work, we propose a system to track the clouds and predict relevant events based on all-sky images. To deal with the nature of variable appearance of clouds, we use clusters of feature points ...to perform tracking. We propose an enhanced clustering algorithm that does not require prior knowledge of number of clusters. The proposed clustering algorithm can successfully separate feature points into groups with reasonable sizes and ranges. In the tracking process, merging and splitting of clouds are handled via checking matched pairs of feature points among different clusters. Afterwards, the tracking information is utilized to predict if the sun will be covered or obscured by clouds within the prediction horizon. Features are extracted from the tracked feature points and a Markov chain model is designed to perform ramp-down event prediction. The obscuration and ramp-down events have an important impact on solar irradiance. The experiments have shown that the proposed system can substantially enhance the accuracy of solar irradiance nowcasting on a challenging dataset.
•Cloud tracking is achieved using clusters of feature points.•An enhanced clustering algorithm is proposed to prevent over-clustering or under-clustering.•Obscuration events are predicted with features of clustering and tracking information.•A graph based model is designed to prediction ramp-down events.•Detection results are applied in irradiance nowcasting frameworks to improve accuracy.
In this work, a hybrid solar irradiance now-casting mechanism is proposed. The proposed hybrid predictor fuses the results from both Kalman filter predictor and regressor predictor to benefit from ...the advantages of both techniques. A time-varying adaptive system function for Kalman filter is designed to deal with ramp-down events for more accurate prediction. Three fusion alternatives based on local root mean square error computation are proposed and compared. The experimental results have validated the effectiveness of the proposed method on a challenging dataset.
•The proposed hybrid predictor fuses a Kalman filter predictor and a regressor predictor.•A time-varying adaptive system function for Kalman filter is designed.•Two fusion alternatives based on local root mean square error are proposed and compared.•When the local RMSE of Kalman filter is larger than a threshold, the prediction result from the regressor predictor is chosen.
Extracting the flight trajectory of the shuttlecock in a single turn in badminton games is important for automated sports analytics. This study proposes a novel method to extract shots in badminton ...games from a monocular camera. First, TrackNet, a deep neural network designed for tracking small objects, is used to extract the flight trajectory of the shuttlecock. Second, the YOLOv7 model is used to identify whether the player is swinging. As both TrackNet and YOLOv7 may have detection misses and false detections, this study proposes a shot refinement algorithm to obtain the correct hitting moment. By doing so, we can extract shots in rallies and classify the type of shots. Our proposed method achieves an accuracy of 89.7%, a recall rate of 91.3%, and an F1 rate of 90.5% in 69 matches, with 1582 rallies of the Badminton World Federation (BWF) match videos. This is a significant improvement compared to the use of TrackNet alone, which yields 58.8% accuracy, 93.6% recall, and 72.3% F1 score. Furthermore, the accuracy of shot type classification at three different thresholds is 72.1%, 65.4%, and 54.1%. These results are superior to those of TrackNet, demonstrating that our method effectively recognizes different shot types. The experimental results demonstrate the feasibility and validity of the proposed method.
We present an automatic vehicle detection system for aerial surveillance in this paper. In this system, we escape from the stereotype and existing frameworks of vehicle detection in aerial ...surveillance, which are either region based or sliding window based. We design a pixelwise classification method for vehicle detection. The novelty lies in the fact that, in spite of performing pixelwise classification, relations among neighboring pixels in a region are preserved in the feature extraction process. We consider features including vehicle colors and local features. For vehicle color extraction, we utilize a color transform to separate vehicle colors and nonvehicle colors effectively. For edge detection, we apply moment preserving to adjust the thresholds of the Canny edge detector automatically, which increases the adaptability and the accuracy for detection in various aerial images. Afterward, a dynamic Bayesian network (DBN) is constructed for the classification purpose. We convert regional local features into quantitative observations that can be referenced when applying pixelwise classification via DBN. Experiments were conducted on a wide variety of aerial videos. The results demonstrate flexibility and good generalization abilities of the proposed method on a challenging data set with aerial surveillance images taken at different heights and under different camera angles.
In this paper, we propose a traffic flow estimation system for intelligent highway surveillance applications under rainy conditions. Major contributions of the proposed system include flexible ...feature extraction, robust estimation with adaptive clustering, and effective graph-based traffic flow mapping model. To detect rain-drop tampered scenes, features are extracted via salient region detection and block segmentation. For traffic flow estimation, lane directions are automatically detected for daytime scenes. Foreground moving edges accumulated along the traffic flow direction are used as features. We utilize an adaptive clustering algorithm to estimate vehicle count for each frame. For nighttime scenes, statistical features are extracted from the segmented blocks, and regression models are applied to generate per-frame vehicle count. Finally, an effective graph-based mapping method is incorporated to map the vehicle count sequences to per-minute traffic flow. The accuracy of the traffic flow analysis is satisfying even when the cameras are seriously affected by rain. The experiments demonstrate that the proposed system can effectively analyze traffic flow under rainy conditions for highway surveillance cameras.
For the advancement of smart grids, solar power generation predictions have become an important research topic. In the case of using traditional modeling methods, excessive computational costs may be ...incurred and it is difficult for these methods to learn the multi-variable dependencies of the data. Therefore, in this paper, a deep learning model was used to combine convolutional neural networks and long short-term memory recurrent network predictions. This method enables hourly power generation one day into the future. Convolutional neural networks are used to extract the features of multiple time series, while long short-term memory neural networks predict multivariate outcomes simultaneously. In order to obtain more accurate prediction results, we performed feature selection on meteorological features and combined the selected weather features to train the prediction model. We further distinguished sunny- and rainy-day models according to the predicted daily rainfall conditions. In the experiment, it was shown that the method of combining meteorological features further reduced the error. Finally, taking into account the differences in climate conditions between the northern and southern regions of Taiwan, the experimental results of case studies involving multiple regions were evaluated to verify the proposed method. The results showed that training combined with selected meteorological features can be widely used in regions with different climates in Taiwan.
A lane-detection method aimed at handling moving vehicles in the traffic scenes is proposed in this brief. First, lane marks are extracted based on color information. The extraction of lane-mark ...colors is designed in a way that is not affected by illumination changes and the proportion of space that vehicles on the road occupy. Next, for vehicles that have the same colors as the lane marks, we utilize size, shape, and motion information to distinguish them from the real lane marks. The mechanism effectively eliminates the influence of passing vehicles when performing lane detection. Finally, pixels in the extracted lane-mark mask are accumulated to find the boundary lines of the lane. The proposed algorithm is able to robustly find the left and right boundary lines of the lane and is not affected by the passing traffic. Experimental results show that the proposed method works well on marked roads in various lighting conditions
Severe vascular damage and complications are often observed in cancer patients during treatment with chemotherapeutic drugs such as cisplatin. Thus, development of potential options to ameliorate the ...vascular side effects is urgently needed. In this study, the effects and the underlying mechanisms of far‐infrared radiation (FIR) on cisplatin‐induced vascular injury and endothelial cytotoxicity/dysfunction in mice and human umbilical vein endothelial cells (HUVECs) were investigated. An important finding is that the severe vascular stenosis and poor blood flow seen in cisplatin‐treated mice were greatly mitigated by FIR irradiation (30 minutes/day) for 1‐3 days. Moreover, FIR markedly increased the levels of phosphorylation of PI3K and Akt, and VEGF secretion, as well as the expression and the activity of hypoxia‐inducible factor 1α (HIF‐1α) in cisplatin‐treated HUVECs in a promyelocytic leukemia zinc finger protein (PLZF)‐dependent manner. However, FIR‐stimulated endothelial angiogenesis and VEGF release were significantly diminished by transfection with HIF‐1α siRNA. We also confirmed that HIF‐1α, PI3K, and PLZF contribute to the inhibitory effect of FIR on cisplatin‐induced apoptosis in HUVECs. Notably, FIR did not affect the anticancer activity and the HIF‐1α/VEGF cascade in cisplatin‐treated cancer cells under normoxic or hypoxic condition, indicating that the actions of FIR may specifically target endothelial cells. It is the first study to demonstrate that FIR effectively attenuates cisplatin‐induced vascular damage and impaired angiogenesis through activation of HIF‐1α–dependent processes via regulation of PLZF and PI3K/Akt. Taken together, cotreatment with the noninvasive and easily performed FIR has a therapeutic potential to prevent the pathogenesis of vascular complications in cancer patients during cisplatin treatment.
Far‐infrared radiation (FIR) treatment prevents cisplatin‐induced vascular damage and stenosis in mice. Far‐infrared radiation exposure improves impaired angiogenesis and apoptosis and promotes HIF‐1α induction and VEGF formation in cisplatin‐treated human umbilical vein endothelial cells (HUVECs). The protective effect of FIR against cisplatin‐induced vascular complications may be mediated by the PLZF/PI3K/Akt/HIF‐1α/VEGF pathway.
To evaluate the correlations of clinical symptoms, urodynamic parameters, and long-term treatment outcomes with different findings of cystoscopic hydrodistention (HD) in patients with interstitial ...cystitis/bladder pain syndrome (IC/BPS). This retrospective analysis of 486 patients with IC/BPS investigated baseline clinical symptoms, disease duration, medical comorbidities, urodynamic findings, cystoscopic characteristics including maximal bladder capacity (MBC) and the presence of glomerulations and Hunner's lesions, and outcomes according to the five IC/BPS HD subtypes based on the glomerulation grade, MBC, and the presence of Hunner's lesions. Receiver operation characteristic analysis identified an optimal cutoff value of MBC ≥ 760 ml as a predictor of satisfactory outcomes. Glomerulation grade and MBC were significantly correlated (r = - 0.403, P < 0.001), and both were significantly associated with IC Symptom Index scores. The rate of satisfactory outcomes was better for the patients with low glomerulation grade and MBC ≥ 760 ml (64.2%), and significantly worse for those with Hunner's lesions (36.8%); no significant differences were noted among the other groups. The results suggested that IC/BPS patients can be classified into the following three distinct subgroups: (1) those with low glomerulation grade and MBC ≥ 760 ml; (2) those with low glomerulation grade and MBC < 760 ml, or with high glomerulation grade regardless of MBC; and (3) those with Hunner's lesions. The results showed that three IC/BPS subgroups had distinct bladder characteristics and treatment outcomes. The patients with high MBC and low glomerulation grade after HD had more medical comorbidities but a significantly higher rate of satisfactory treatment outcome.IRB: 105-25-B.
PDF