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Journal articles on the topic 'Dashcam'

Author: Grafiati

Published: 4 June 2021

Last updated: 21 February 2023

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1

Wu, Ming-Che, and Mei-Chen Yeh. "Early Detection of Vacant Parking Spaces Using Dashcam Videos." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 9613–18. http://dx.doi.org/10.1609/aaai.v33i01.33019613.

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A major problem in metropolitan areas is finding parking spaces. Existing parking guidance systems often adopt fixed sensors or cameras that cannot provide information from the driver’s point of view. Motivated by the advent of dashboard cameras (dashcams), we develop neural-network-based methods for detecting vacant parking spaces in videos recorded by a dashcam. Detecting vacant parking spaces in dashcam videos enables early detection of spaces. Different from conventional object detection methods, we leverage the monotonicity of the detection confidence with respect to the distance away of the approaching target parking space and propose a new loss function, which can not only yield improved detection results but also enable early detection. To evaluate our detection method, we create a new large dataset containing 5,800 dashcam videos captured from 22 indoor and outdoor parking lots. To the best of our knowledge, this is the first and largest driver’s view video dataset that supports parking space detection and provides parking space occupancy annotations.

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Adamová, Veronika. "DASHCAM AS A DEVICE TO INCREASE THE ROAD SAFETY LEVEL." Proceedings of CBU in Natural Sciences and ICT 1 (November 16, 2020): 1–5. http://dx.doi.org/10.12955/pns.v1.113.

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In recent years, there has been a huge boom in the market in terms of both supply and demand for dashcams. This stems from the purpose of the camera installed in the vehicle. Dashcams are currently becoming an important aid in solving various adverse incidents, such as detecting violations of traffic regulations and other laws and recording and clarifying the course of a traffic accident or other criminologically relevant event. The purpose of this camera is to monitor the space in front and behind the vehicle, or the situation inside the vehicle. The content of this article is aimed at acquainting the reader with basic information about dashcams. Specifically, the individual parts of the article will discuss the importance and significance of the dashcams, the benefits of its use, and the legislative framework that regulates its use. The paper will conclude with a brief overview of innovative approaches based on the application of a dashcam for the purpose of increasing the level of safety of road users while driving a vehicle.

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3

Lallie, Harjinder Singh. "Dashcam forensics: A preliminary analysis of 7 dashcam devices." Forensic Science International: Digital Investigation 33 (June 2020): 200910. http://dx.doi.org/10.1016/j.fsidi.2020.200910.

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4

Nestler, N. "Verwertbarkeit von Dashcam-Aufzeichnungen." JURA - Juristische Ausbildung 40, no. 11 (October 1, 2018): 1184. http://dx.doi.org/10.1515/jura-2018-0243.

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5

Ahrens, Hans-Jürgen. "Der Beweis des Unfallgeschehens mittels Dashcam-Videos." Monatsschrift für Deutsches Recht 69, no. 16 (August 28, 2015): 926–28. http://dx.doi.org/10.9785/mdtr-2015-1605.

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6

Godlevskii, A. A. "Determining Vehicle Speed from Dashcam Audio Analysis." Theory and Practice of Forensic Science, no. 4(44) (December 30, 2016): 66–72. http://dx.doi.org/10.30764/1819-2785-2016-4-66-72.

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The article offers a method for determining vehicle speed from the audio track recorded by the dashboard camera mounted on the car in question. The author analyzed the operation of a four-stroke internal combustion engine, and established a dependency between the number of rotations (rpm) of the engine crankshaft and the number of rotations transferred to the wheel by the manual transmission. The author presents a formula that helps to determine the static radius of the wheel from its marking symbols on the tire. He looks at examples from forensic casework and offers options for determining the ID number of an engaged gearbox. Furthermore, he reviews the possibilities of applying this method to vehicles with an automatic transmission. In conclusion, the article presents the results of tests of the proposed method conducted by leading experts from various forensic institutions of the Russian Ministry of Justice. They point to the consistency of results when engine rpm is calculated based on cepstral analysis and engine tachometer readings.

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7

Laumen, Hans-Willi. "Beweisrecht: Dashcam-Aufnahmen als Beweismittel im Zivilprozess." Monatsschrift für Deutsches Recht 70, no. 14 (July 1, 2016): 813–14. http://dx.doi.org/10.9785/mdtr-2016-1407.

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Laumen, Hans-Willi. "Die Verwertbarkeit von Dashcam-Aufnahmen im Verkehrsunfallprozess." Monatsschrift für Deutsches Recht 72, no. 16 (August 1, 2018): 966–70. http://dx.doi.org/10.9785/mdtr-2018-721603.

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9

Miyazawa, Haruna, and Yasuo Terayama. "Dashcam-captured moment of right hemispheric stroke." Journal of Stroke and Cerebrovascular Diseases 29, no. 9 (September 2020): 105094. http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2020.105094.

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10

Kellerhoff, Peter. "Kleine Helferlein fürs Auto." VDI nachrichten 75, no. 10 (2021): 40. http://dx.doi.org/10.51202/0042-1758-2021-10-40-3.

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Verkehr: Es sind oft die kleinen Dinge, die Autofahrern eine wichtige Unterstützung sein können. Die VDI nachrichten haben sich auf die Suche nach solchen Helfern gemacht und stellen einige vor – von der Dashcam über Ladegeräte bis zur Starthilfe. Von Peter Kellerhoff

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11

Joshi, D., and C. Witharana. "ROADSIDE FOREST MODELING USING DASHCAM VIDEOS AND CONVOLUTIONAL NEURAL NETS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-M-2-2022 (July 25, 2022): 135–40. http://dx.doi.org/10.5194/isprs-archives-xlvi-m-2-2022-135-2022.

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Abstract. Tree failure is a primary cause of storm-related power outages throughout the United States. Roadside vegetation management is therefore critical to electric utility companies to prevent power outages during extreme weather conditions. It is difficult to execute roadside vegetation management practices, at the landscape level, without proper monitoring of roadside forests’ physical structure and health condition. Remote sensing images and LiDAR are widely used to characterize the forest edge; however, the limitation on the temporal and spatial resolution for most of that dataset is a big challenge. Also, there is a need for a ground-level dataset that provides the vertical profile of the forest trees so that we can more accurately characterize the forest structure and health and recommend the optimal management strategies according to the local forest conditions. For the first time, we introduced Dashcam videos as an alternative to the existing aerial remote sensing data sources to characterize the roadside forest condition using the deep learning (DL) convolutional neural net (CNN) algorithms. In this study, we used dashcam videos taken during the leaf-on and leaf-off conditions and various weather conditions along the roadside. We trained a DLCNN model based on the U-Net and YOLO v5 architectures to classify the multilayer vegetation and detect utility poles and tree trunks alongside the road. Our experiment results suggest that a dashcam can be a viable alternative and complementary way to characterize the roadside vegetation and can be used in the management of roadside forests as a cost-effective data acquisition mechanism for utility companies.

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Boyd, Doreen S., Sally Crudge, and Giles Foody. "Towards an Automated Approach for Monitoring Tree Phenology Using Vehicle Dashcams in Urban Environments." Sensors 22, no. 19 (October 10, 2022): 7672. http://dx.doi.org/10.3390/s22197672.

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Trees in urban environments hold significant value in providing ecosystem services, which will become increasingly important as urban populations grow. Tree phenology is highly sensitive to climatic variation, and resultant phenological shifts have significant impact on ecosystem function. Data on urban tree phenology is important to collect. Typical remote methods to monitor tree phenological transitions, such as satellite remote sensing and fixed digital camera networks, are limited by financial costs and coarse resolutions, both spatially and temporally and thus there exists a data gap in urban settings. Here, we report on a pilot study to evaluate the potential to estimate phenological metrics from imagery acquired with a conventional dashcam fitted to a car. Dashcam images were acquired daily in spring 2020, March to May, for a 2000 m stretch of road in Melksham, UK. This pilot study indicates that time series imagery of urban trees, from which meaningful phenological data can be extracted, is obtainable from a car-mounted dashcam. The method based on the YOLOv3 deep learning algorithm demonstrated suitability for automating stages of processing towards deriving a greenness metric from which the date of tree green-up was calculated. These dates of green-up are similar to those obtained by visual analyses, with a maximum of a 4-day difference; and differences in green-up between trees (species-dependent) were evident. Further work is required to fully automate such an approach for other remote sensing capture methods, and to scale-up through authoritative and citizen science agencies.

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Ariffin, A. H., M. S. Solah, A. Hamzah, M. S. Ahmad, M. A. Mohamad Radzi, Z. H. Zulkipli, A. S. Salleh, and Z. Mohd Jawi. "Exploring Characteristics and Contributory Factors of Road Crashes and Near Misses Recorded via Dashboard Camera." Journal of the Society of Automotive Engineers Malaysia 5, no. 2 (May 1, 2021): 292–305. http://dx.doi.org/10.56381/jsaem.v5i2.173.

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The use of dashboard camera (dashcam), or also known as digital video recorder (DVR) is increasingly becoming popular among personal vehicle owners nowadays due to affordable prices and higher video qualities. Many road-related incidents including vehicle crashes and near-misses can be recorded using dashboard cameras and shared via social media as lessons learned to others. Recorded videos of the incidents in real-time can be observed and used for a variety of purposes, including as supportive evidence for investigation. This paper explores the potential use of recorded dashcam videos in determining the characteristics and factors contributing to road crashes and near-misses under different situations. Selected video records of road crashes and near-misses were obtained from the internet thru social media and were used for analysis. The findings concluded that a dashboard camera is an effective digital video technology for traffic and accident monitoring systems. It has a high potential in providing supportive evidence of many frequently occurring factors and understanding the causes of road crashes and near-miss incidents.

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14

Mukherjee, Prerana, and Brejesh Lall. "Pedestrian Behavior Analytics on Dashcam Videos in Chaotic Environments." IEEE Sensors Journal 21, no. 14 (July 15, 2021): 15660–69. http://dx.doi.org/10.1109/jsen.2021.3062762.

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15

Lee, Kukheon, Jong-Hyun Choi, Jungheum Park, and Sangjin Lee. "Your car is recording: Metadata-driven dashcam analysis system." Forensic Science International: Digital Investigation 38 (October 2021): 301131. http://dx.doi.org/10.1016/j.fsidi.2021.301131.

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16

Stürner, M. "Zur Zulässigkeit sog. Dashcam-Aufzeichnungen als Beweismittel in Zivilverfahren." JURA - Juristische Ausbildung 40, no. 11 (October 1, 2018): 1182. http://dx.doi.org/10.1515/jura-2018-0241.

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Kim, Joohyun, Sangkeun Park, and Uichin Lee. "Dashcam Witness: Video Sharing Motives and Privacy Concerns Across Different Nations." IEEE Access 8 (2020): 110425–37. http://dx.doi.org/10.1109/access.2020.3002079.

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Schumann, Ekkehard. "Das Dashcam-Urteil des BGH: Trotz Rechtswidrigkeit der Aufzeichnung kein Beweisverbot." JURA - Juristische Ausbildung 41, no. 1 (November 30, 2018): 3–14. http://dx.doi.org/10.1515/jura-2018-2030.

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19

Shin, Sang-Hyun. "Verwertbarkeit von Dashcam-Aufnahmen im Strafverfahren unter Berücksichtigung der Rechtsprechungen in Deutschland." Korea Law Review 88 (March 31, 2018): 109–38. http://dx.doi.org/10.36532/kulri.2018.88.109.

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20

Chen, Shao-Chi, Hsin-Yi Chen, Yi-Ling Chen, Hsin-Mu Tsai, and Bing-Yu Chen. "Making in-Front-of Cars Transparent: Sharing First-Person-Views via Dashcam." Computer Graphics Forum 33, no. 7 (October 2014): 289–97. http://dx.doi.org/10.1111/cgf.12497.

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21

Jäschke, Marvin. "Report Und Technik. Bgh: Zulässige Verwertung Von Dashcam-Aufnahmen Im Zivilprozess Als Beweismittel." Computer und Recht 34, no. 6 (June 1, 2018): r68. http://dx.doi.org/10.9785/cr-2018-340624.

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22

Bazilinskyy, P., Y. B. Eisma, D. Dodou, and J. C. F. de Winter. "Risk perception: A study using dashcam videos and participants from different world regions." Traffic Injury Prevention 21, no. 6 (May 13, 2020): 347–53. http://dx.doi.org/10.1080/15389588.2020.1762871.

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23

Na, Dongjun, and Sejin Park. "Blockchain-Based Dashcam Video Management Method for Data Sharing and Integrity in V2V Network." IEEE Access 10 (2022): 3307–19. http://dx.doi.org/10.1109/access.2022.3140419.

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Chung, Yao-Liang, and Chuan-Kai Lin. "Application of a Model that Combines the YOLOv3 Object Detection Algorithm and Canny Edge Detection Algorithm to Detect Highway Accidents." Symmetry 12, no. 11 (November 14, 2020): 1875. http://dx.doi.org/10.3390/sym12111875.

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This study proposed a model for highway accident detection that combines the You Only Look Once v3 (YOLOv3) object detection algorithm and Canny edge detection algorithm. It not only detects whether an accident has occurred in front of a vehicle, but further performs a preliminary classification of the accident to determine its severity. First, this study established a dataset consisting of around 4500 images mainly taken from the angle of view of dashcams from an open-source online platform. The dataset was named the Highway Dashcam Car Accident for Classification System (HDCA-CS) and was developed with the aim of conforming to the setting of this study. The HDCA-CS not only considers weather conditions (rainy days, foggy days, nighttime settings, and other low-visibility conditions), but also various types of accidents, thus increasing the diversity of the dataset. In addition, we proposed two types of accidents—accidents involving damaged cars and accidents involving overturned cars—and developed three different design methods for comparing vehicles involved in accidents involving damaged cars. Canny edge detection algorithm processed single high-resolution images of accidents were also added to compensate for the low volume of accident data, thereby addressing the problem of data imbalance for training purposes. Lastly, the results showed that the proposed model achieved a mean average precision (mAP) of 62.60% when applied to the HDCA-CS testing dataset. When comparing the proposed model with a benchmark model, two abovementioned accident types were combined to allow the proposed model to produce binary classification outputs (i.e., non-occurrence and occurrence of an accident). The HDCA-CS was then applied to the two models, and testing was conducted using single high-resolution images. At 76.42%, the mAP of the proposed model outperformed the benchmark model’s 75.18%; and if we were to apply the proposed model to only test scenarios in which an accident has occurred, its performance would be even better relative to the benchmark. Therefore, our findings demonstrate that our proposed model is superior to other existing models.

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Löffelmann, Markus. "Zur Zulässigkeit der Verwertung von Dashcam-Aufzeichnungen im Zivilprozess und strafprozessuale Konsequenzen aus dieser Entscheidung." Juristische Rundschau 2018, no. 12 (November 7, 2018): 628–40. http://dx.doi.org/10.1515/juru-2018-0116.

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Cao, Minh-Tu, Quoc-Viet Tran, Ngoc-Mai Nguyen, and Kuan-Tsung Chang. "Survey on performance of deep learning models for detecting road damages using multiple dashcam image resources." Advanced Engineering Informatics 46 (October 2020): 101182. http://dx.doi.org/10.1016/j.aei.2020.101182.

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Liu, Tao, and Yong Liu. "Moving Camera-Based Object Tracking Using Adaptive Ground Plane Estimation and Constrained Multiple Kernels." Journal of Advanced Transportation 2021 (July 20, 2021): 1–15. http://dx.doi.org/10.1155/2021/8153474.

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Moving camera-based object tracking method for the intelligent transportation system (ITS) has drawn increasing attention. The unpredictability of driving environments and noise from the camera calibration, however, make conventional ground plane estimation unreliable and adversely affecting the tracking result. In this paper, we propose an object tracking system using an adaptive ground plane estimation algorithm, facilitated with constrained multiple kernel (CMK) tracking and Kalman filtering, to continuously update the location of moving objects. The proposed algorithm takes advantage of the structure from motion (SfM) to estimate the pose of moving camera, and then the estimated camera’s yaw angle is used as a feedback to improve the accuracy of the ground plane estimation. To further robustly and efficiently tracking objects under occlusion, the constrained multiple kernel tracking technique is adopted in the proposed system to track moving objects in 3D space (depth). The proposed system is evaluated on several challenging datasets, and the experimental results show the favorable performance, which not only can efficiently track on-road objects in a dashcam equipped on a free-moving vehicle but also can well handle occlusion in the tracking.

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Zhu, Rixing, Jianwu Fang, Hongke Xu, and Jianru Xue. "Progressive Temporal-Spatial-Semantic Analysis of Driving Anomaly Detection and Recounting." Sensors 19, no. 23 (November 21, 2019): 5098. http://dx.doi.org/10.3390/s19235098.

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For analyzing the traffic anomaly within dashcam videos from the perspective of ego-vehicles, the agent should spatial-temporally localize the abnormal occasion and regions and give a semantically recounting of what happened. Most existing formulations concentrate on the former spatial-temporal aspect and mainly approach this goal by training normal pattern classifiers/regressors/dictionaries with large-scale availably labeled data. However, anomalies are context-related, and it is difficult to distinguish the margin of abnormal and normal clearly. This paper proposes a progressive unsupervised driving anomaly detection and recounting (D&R) framework. The highlights are three-fold: (1) We formulate driving anomaly D&R as a temporal-spatial-semantic (TSS) model, which achieves a coarse-to-fine focusing and generates convincing driving anomaly D&R. (2) This work contributes an unsupervised D&R without any training data while performing an effective performance. (3) We novelly introduce the traffic saliency, isolation forest, visual semantic causal relations of driving scene to effectively construct the TSS model. Extensive experiments on a driving anomaly dataset with 106 video clips (temporal-spatial-semantically labeled carefully by ourselves) demonstrate superior performance over existing techniques.

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Rieger, Simon. "Schadensersatz wegen Verwendung datenschutzrechtlich rechtswidrig erlangter Dashcam-Aufnahmen im Zivilprozess — Zur Reichweite und Geltendmachung eines materiellen Schadensersatzanspruchs nach der DS-GVO." Monatsschrift für Deutsches Recht 75, no. 13 (July 1, 2021): 783–88. http://dx.doi.org/10.9785/mdtr-2021-751308.

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Jain, Vanita, Qiming Wu, Shivam Grover, Kshitij Sidana, Gopal Chaudhary, San Hlaing Myint, and Qiaozhi Hua. "Generating Bird’s Eye View from Egocentric RGB Videos." Wireless Communications and Mobile Computing 2021 (November 8, 2021): 1–11. http://dx.doi.org/10.1155/2021/7479473.

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In this paper, we present a method for generating bird’s eye video from egocentric RGB videos. Working with egocentric views is tricky since such the view is highly warped and prone to occlusions. On the other hand, a bird’s eye view has a consistent scaling in at least the two dimensions it shows. Moreover, most of the state-of-the-art systems for tasks such as path prediction are built for bird’s eye views of the subjects. We present a deep learning-based approach that transfers the egocentric RGB images captured from a dashcam of a car to bird’s eye view. This is a task of view translation, and we perform two experiments. The first one uses an image-to-image translation method, and the other uses a video-to-video translation. We compare the results of our work with homographic transformation, and our SSIM values are better by a margin of 77% and 14.4%, and the RMSE errors are lower by 40% and 14.6% for image-to-image translation and video-to-video translation, respectively. We also visually show the efficacy and limitations of each method with helpful insights for future research. Compared to previous works that use homography and LIDAR for 3D point clouds, our work is more generalizable and does not require any expensive equipment.

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Setiawan, R., A. S. Dammara, B. Cahyadi, B. Widarno, F. H. Njoko, and M. Noviani. "Changes in drivers’ viewing frequency, maneuver duration, and degree of difficulty during back-in parking maneuver with different conditions of parking spaces." IOP Conference Series: Earth and Environmental Science 907, no. 1 (November 1, 2021): 012027. http://dx.doi.org/10.1088/1755-1315/907/1/012027.

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Abstract To some people, back-in parking maneuver is a relatively hard thing to do. However, previous studies have proven that back-in parking is safer than head-in parking because when exiting the parking space (back-out) from head-in parking, the driver's field of view is more limited, thus increasing the chance of an accident. This study aims to determine the changes in the driver's viewing frequency on the rear-view mirror, maneuver duration, and degree of difficulty during back-in parking maneuvers. Data collection was obtained from 45 participants who tried to park their cars in a parking space with an angle of 30°, 45°, 60°, 90°, each with four different conditions of parking spaces. The driver’s viewing frequency on each rear-view mirror (left, right and center) and maneuver duration were obtained from a dashcam and an external camera recording. The difficulty level for maneuvering was filed according to the driver’s opinion during the experiment for each parking space condition. Based on the data analysis, it was proven that the existence of cars parked on either side of that parking space (obstacles), parking space line signs, and both simultaneously increase the driver’s viewing frequency and maneuver duration when doing back-in parking maneuver, but at the same time, ease the parking maneuver, according to the driver.

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Trigo-Rodríguez, Josep M., Joan Dergham, Maria Gritsevich, Esko Lyytinen, Elizabeth A. Silber, and Iwan P. Williams. "A Numerical Approach to Study Ablation of Large Bolides: Application to Chelyabinsk." Advances in Astronomy 2021 (March 27, 2021): 1–13. http://dx.doi.org/10.1155/2021/8852772.

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In this study, we investigate the ablation properties of bolides capable of producing meteorites. The casual dashcam recordings from many locations of the Chelyabinsk superbolide associated with the atmospheric entry of an 18 m in diameter near-Earth object (NEO) have provided an excellent opportunity to reconstruct its atmospheric trajectory, deceleration, and heliocentric orbit. In this study, we focus on the study of the ablation properties of the Chelyabinsk bolide on the basis of its deceleration and fragmentation. We explore whether meteoroids exhibiting abrupt fragmentation can be studied by analyzing segments of the trajectory that do not include a disruption episode. We apply that approach to the lower part of the trajectory of the Chelyabinsk bolide to demonstrate that the obtained parameters are consistent. To do that, we implemented a numerical (Runge–Kutta) method appropriate for deriving the ablation properties of bolides based on observations. The method was successfully tested with the cases previously published in the literature. Our model yields fits that agree with observations reasonably well. It also produces a good fit to the main observed characteristics of Chelyabinsk superbolide and provides its averaged ablation coefficient σ = 0.034 s2 km−2. Our study also explores the main implications for impact hazard, concluding that tens of meters in diameter NEOs encountering the Earth in grazing trajectories and exhibiting low geocentric velocities are penetrating deeper into the atmosphere than previously thought and, as such, are capable of producing meteorites and even damage on the ground.

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Itu, Razvan, and Radu Gabriel Danescu. "A Self-Calibrating Probabilistic Framework for 3D Environment Perception Using Monocular Vision." Sensors 20, no. 5 (February 27, 2020): 1280. http://dx.doi.org/10.3390/s20051280.

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Cameras are sensors that are available anywhere and to everyone, and can be placed easily inside vehicles. While stereovision setups of two or more synchronized cameras have the advantage of directly extracting 3D information, a single camera can be easily set up behind the windshield (like a dashcam), or above the dashboard, usually as an internal camera of a mobile phone placed there for navigation assistance. This paper presents a framework for extracting and tracking obstacle 3D data from the surrounding environment of a vehicle in traffic, using as a sensor a generic camera. The system combines the strength of Convolutional Neural Network (CNN)-based segmentation with a generic probabilistic model of the environment, the dynamic occupancy grid. The main contributions presented in this paper are the following: A method for generating the probabilistic measurement model from monocular images, based on CNN segmentation, which takes into account the particularities, uncertainties, and limitations of monocular vision; a method for automatic calibration of the extrinsic and intrinsic parameters of the camera, without the need of user assistance; the integration of automatic calibration and measurement model generation into a scene tracking system that is able to work with any camera to perceive the obstacles in real traffic. The presented system can be easily fitted to any vehicle, working standalone or together with other sensors, to enhance the environment perception capabilities and improve the traffic safety.

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Reichenbach, Michael. "Dashcams." ATZ - Automobiltechnische Zeitschrift 120, no. 7-8 (July 2018): 3. http://dx.doi.org/10.1007/s35148-018-0083-7.

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Kang, Minhee, Wooseop Lee, Keeyeon Hwang, and Young Yoon. "Vision Transformer for Detecting Critical Situations and Extracting Functional Scenario for Automated Vehicle Safety Assessment." Sustainability 14, no. 15 (August 5, 2022): 9680. http://dx.doi.org/10.3390/su14159680.

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Automated Vehicles (AVs) are attracting attention as a safer mobility option thanks to the recent advancement of various sensing technologies that realize a much quicker Perception–Reaction Time than Human-Driven Vehicles (HVs). However, AVs are not entirely free from the risk of accidents, and we currently lack a systematic and reliable method to improve AV safety functions. The manual composition of accident scenarios does not scale. Simulation-based methods do not fully cover the peculiar AV accident patterns that can occur in the real world. Artificial Intelligence (AI) techniques are employed to identify the moments of accidents from ego-vehicle videos. However, most AI-based approaches fall short in accounting for the probable causes of the accidents. Neither of these AI-driven methods offer details for authoring accident scenarios used for AV safety testing. In this paper, we present a customized Vision Transformer (named ViT-TA) that accurately classifies the critical situations around traffic accidents and automatically points out the objects as probable causes based on an Attention map. Using 24,740 frames from Dashcam Accident Dataset (DAD) as training data, ViT-TA detected critical moments at Time-To-Collision (TTC) ≤ 1 s with 34.92 higher accuracy than the state-of-the-art approach. ViT-TA’s Attention map highlighting the critical objects helped us understand how the situations unfold to put the hypothetical ego vehicles with AV functions at risk. Based on the ViT-TA-assisted interpretation, we systematized the composition of Functional scenarios conceptualized by the PEGASUS project for describing a high-level plan to improve AVs’ capability of evading critical situations. We propose a novel framework for automatically deriving Logical and Concrete scenarios specified with 6-Layer situational variables defined by the PEGASUS project. We believe our work is vital towards systematically generating highly reliable and trustworthy safety improvement plans for AVs in a scalable manner.

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Rose, Edgar. "Datenbrillen, Drohnen, Dashcams …" Datenschutz und Datensicherheit - DuD 41, no. 3 (February 4, 2017): 137–41. http://dx.doi.org/10.1007/s11623-017-0744-9.

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Wagner, Paul Georg, Pascal Birnstill, Erik Krempel, and Sebastian Bretthauer. "Auf dem Weg zu datenschutzfreundlichen Dashcams." Datenschutz und Datensicherheit - DuD 41, no. 3 (February 4, 2017): 159–64. http://dx.doi.org/10.1007/s11623-017-0748-5.

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Hidayat, Muslim. "Pencegahan Kasus Stunting melalui Program Dapur Sehat Stunting (DASHAT) di Desa Tambi." Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat 1, no. 01 (December 31, 2022): 31–37. http://dx.doi.org/10.58641/servis.v1i01.7.

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Tujuan kegiatan adalah untuk mengetahui pengaruh dan dampak yang ditimbulkan dari adanya Dapur Sehat Stunting (DASHAT) sebagai upaya penekanan angka stunting di desa Tambi.Permasalahan stunting di Desa Tambi menjadi permasalahan yang serius, desa Tambi memiliki angka stunting yang tinggi dengan 18 balita dari 400 balita yang terkena kasus stunting. Oleh sebab itu desa Tambi melaksanakan program Dapur Sehat Stunting (DASHAT) dimana hal ini akan menjadi upaya utama dalam menekan angka stunting yang ada di desa Tambi. Salah satu penyebab utama stunting adalah permasalahan gizi atau adanya gizi yang tak terpenuhi pada balita. Metode pelaksanaan yang dilakukan dengan pendataan penerima program Dapur Sehat Stunting (DASHAT), pelaksanaan program Dapur Sehat Stunting (DASHAT), kemudian dilakukan monitoring. Adanya montoring ini untuk pembuktian adanya pengaruh Dapur Sehat Stunting (DASHAT) yang sudah terlaksana. Monitoring dilakukan setiap bulan dari monitoring ini dapat dilihat adanya perubahan terkait pelaksanaan program Dapur Sehat Stunting (DASHAT). Dari 18 anak yang menerima program Dapur Sehat Stunting (DASHAT) di ambil 5 anak sampel acak, 5 anak setelah dilakukanya monitoring ketiga terdapat perkembangan yang positif dengan adanya peningkatan di hasil akhir pengukuran. Menurut penelitian program Dapur Sehat Stunting (DASHAT) memiliki dampak yang positif dan dapat dijadikan upaya untuk menekan angka stunting di Desa Tambi.

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Reibach, Boris. "Private Dashcams & Co. — Household Exemption ade?" Datenschutz und Datensicherheit - DuD 39, no. 3 (March 2015): 157–60. http://dx.doi.org/10.1007/s11623-015-0385-9.

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Stone, Michael E. "The Armenian Vision of Ezekiel." Harvard Theological Review 79, no. 1-3 (July 1986): 261–69. http://dx.doi.org/10.1017/s0017816000020538.

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The document which is presented here is extant in MS no. 31 of the Library of the Mechitarist Fathers in Vienna. It was described by J. Dashian in his magistral catalogue of that collection. The MS is without colophons and so the names of the scribe, as well as the place in which it was copied, remain unknown. Dashian dated it on palaeographic grounds to the 17th-18th centuries. Although the primary document transmitted is a collection of fables, there are many diverse documents interspersed among them. One is the present work, of which Dashian notes no other copy.

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Hopkins, John, and Paul Hawking. "Big Data Analytics and IoT in logistics: a case study." International Journal of Logistics Management 29, no. 2 (May 14, 2018): 575–91. http://dx.doi.org/10.1108/ijlm-05-2017-0109.

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Purpose Advances in technology enable companies to collect and analyse data, which were previously not accessible, to either enhance existing business processes or create new ones. The purpose of this paper is to document the role and impact of Big Data Analytics (BDA), and the Internet of Things (IoT), in supporting a large logistics firm’s strategy to improve driver safety, lower operating costs, and reduce the environmental impact of their vehicles. Design/methodology/approach A single case with embedded units intrinsic case study method was adopted for this research and data were collected from a “real-life” situation, to create new knowledge about this emerging phenomenon. Findings Truck telematics were utilised in order to better understand, and improve, driving behaviours. Remote control centres monitor live sensor data from the company’s fleet of vehicles, capturing the likes of speed, location, braking, and engine data, to inform future training programs. A combination of truck telematics and geo-information are being used to enable proactive alerts to be sent to drivers regarding possible upcoming hazards. Camera-based technologies have been adopted to improve driver safety, and fatigue management, capturing evidence of important driving events and storing data directly to the cloud, and BDA is also being used to improve truck routing, recommend optimal fuel purchasing times/locations, and to forecast predictive and proactive maintenance schedules. Research limitations/implications The type of data collected by Company A, and similar logistics companies, has the potential to greatly inform researchers investigating autonomous vehicles, smart cities, and the physical internet. Practical implications Eco-driving, a practice informed/improved by BDA at Company A, has been linked to reductions in fuel consumption and CO2 emissions, which bring both economic and environmental benefits. Technologies similar to Truckcam are growing in popularity in some parts of the world, to the point where it is now common practice to use dashcam assess of accidents to establish liability. This has implications for logistics firms, in other parts of the world, where such practices might not yet be so commonplace, and for drivers and society more broadly. Social implications Improvements in utilisation and routing have the potential to reduce traffic congestion, which is responsible for losses in productivity, increases in fuel consumption, air pollution and noise, and can incite stress, aggression, anger and unsafe behaviours in drivers. Predictive analytics, which generate refuelling and maintenance schedules, have the potential to be adopted by all vehicle manufacturers, and could generate reductions in customer fuel costs, whilst improving the performance, efficiency, and life expectancy of future motor all vehicles. The high probability of occupations in the logistics industry being replaced by computer automation in the near future is also discussed. Originality/value The findings from this research serve as a valuable case example of a real-world deployment of BDA and IoT technologies in the logistics industry, and present implications for practitioners, researchers, and society more widely.

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DeBuhr, J., B. Zhang, A. Tsueda, V. Tilstra-Smith, and T. Sterling. "DASHMM: Dynamic Adaptive System for Hierarchical Multipole Methods." Communications in Computational Physics 20, no. 4 (October 2016): 1106–26. http://dx.doi.org/10.4208/cicp.030316.310716sw.

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AbstractWe present DASHMM, a general library implementing multipole methods (including both Barnes-Hut and the Fast Multipole Method). DASHMM relies on dynamic adaptive runtime techniques provided by the HPX-5 system to parallelize the resulting multipole moment computation. The result is a library that is easy-to-use, extensible, scalable, efficient, and portable. We present both the abstractions defined by DASHMM as well as the specific features of HPX-5 that allow the library to execute scalably and efficiently.

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DEVI, LAISHRAM HEMANTAKUMARI. "MAHARAAS: SRI SRI GOVINDAJI TEMPLE AND OTHER LOCAL TEMPLES OF MANIPUR." International Journal of Research -GRANTHAALAYAH 9, no. 2 (March 9, 2021): 299–308. http://dx.doi.org/10.29121/granthaalayah.v9.i2.2021.3654.

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The Maharaas Leela is based on the Raas Panchadhyay of Srimad Bhagavata of Maha Kavi Veda Vyas. Sri Sri Raas Panchadhyay is known as the combination of five adhyays viz. 29th, 30th, 31st, 32nd and 33rd adhyays included in the Dasham (10th) Skandha of the great purana of ‘Srimad Bhagavata’. It is an adhyay composed in description of the Raasleela played by the Lord Sri Krishna with those gopis of Vrindavan who practice the worship of goddess Katyayani. The saint Sukadev, son of the sage Veda Vyas narrated to Parikshit Maharaj the contents of Raasleela in the Dasham skandha of Srimad Bhagavata Mahapurana are enumerated as follows: (A) 29th ADHYAY (Discourse OR PART XXIX) A description of the celebrated Rasa Play of the Lord (B) 30th ADHYAY (Discourse OR PART XXX) The Gopis’ quest for Sri Krsna during the Rasa Play (c) 31st aDHYAY (Discourse OR PART XXXI) The Gopis' song at the Lord's disappearance during the Rasa Play (D) 32nd ADHYAY (DISCOURSE OR PART XXXII) The Lord comforts the Gopis during the Rasa play (E) 33rd ADHYAY (DISCOURSE OR PART XXXIII)

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Sanzaro III, Francis. "Dashran as Mode and Critique of Perception." Axis Mundi 4 (October 6, 2017): 24. http://dx.doi.org/10.29173/axismundi75.

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Darshan—as an aid to Hindu liberation—should not be relegated to a religious system, more specifically, to the Hindu, devotional mode of seeing. Rather, using contemporary theorists, this paper argues that darshan provides us with a conceptual model of how ordinary vision, and, more broadly speaking, consciousness, is attained, and conversely, how it may be overcome.

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Stevenson, Deborah. "The 57 Bus by Dashka Slater." Bulletin of the Center for Children's Books 71, no. 3 (2017): 134. http://dx.doi.org/10.1353/bcc.2017.0813.

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Iqbal, Javed, Xinbin Tu, and Wei Gao. "The Impact of Reservoir Fluctuations on Reactivated Large Landslides: A Case Study." Geofluids 2019 (April 15, 2019): 1–16. http://dx.doi.org/10.1155/2019/2374236.

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Filling of Xiangjiaba Reservoir Lake in the Southwest China triggered and reactivated numerous landslides due to water fluctuation. In order to understand the relationship between reservoirs and slope instability, a typical reservoir landslide (Dasha landslide) at the right bank of Jinsha River was selected as a case study for in-depth investigations. The detailed field investigations were carried out to identify the landslide with respect to its surroundings and to find out the slip surface. Boreholes were drilled to find out the subsurface lithology and the depth of failure of Dasha landslide. The in situ geotechnical tests were performed, and the soil samples from exposed slip surface were retrieved for geotechnical laboratory analysis. Finally, stability analysis was done using the 3D strength reduction method under different conditions of reservoir water level fluctuations and rainfall conditions. The in-depth investigations show that the Dasha landslide is a bedding rockslide which was once activated in 1986. The topography of Dasha landslide is relatively flat, while the back scarp and local terrain is relatively steep. The total volume of landslides is about 580×104 m3 with an average thickness of 20 m. Bedrock in the landslide area is composed of Suining Formation of the Jurassic age. The main rock type is silty mudstone with sandstone, and the bedding orientation is 300~310° ∠ 7~22°. The factor of safety (FOS) of Dasha landslide obtained by 3D strength reduction cannot meet the minimum safety requirement under the working condition of reservoir level fluctuation as designed, with effect of rainfall and rapid drawdown.

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Martins, Paulo. "A Concise History of Hindu Astrology and Indian Spirituality." Scholars Journal of Arts, Humanities and Social Sciences 11, no. 02 (February 14, 2023): 33–36. http://dx.doi.org/10.36347/sjahss.2023.v11i02.003.

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This essay refers to the concise history of Hindu astrology, highlighting its symbolism present in its spirituality which is transversal to all cultures. In a summarized way, it also mentions the foundations and main conceptions of Hindu astrology, namely Rasi, Nakshastra, Navagrahas, Bhava, Dashas.

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Zou, Ping. "Facilitators and Barriers to Healthy Eating in Aged Chinese Canadians with Hypertension: A Qualitative Exploration." Nutrients 11, no. 1 (January 8, 2019): 111. http://dx.doi.org/10.3390/nu11010111.

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Objectives: To determine the facilitators and barriers influencing healthy eating behaviours among aged Chinese-Canadians with hypertension. Methods: After attending five weeks of dietary educational training (Dietary Approach to Stop Hypertension with Sodium (Na) Reduction for Chinese Canadians; DASHNa-CC), 30 aged Chinese-Canadian participants partook in a telephone interview. Participants were asked to name three facilitators and three barriers that influenced their ability to follow the DASHNa-CC intervention. Telephone transcripts were then analyzed and coded using computer software and categorized into personal, familial, community, and societal facilitators or barriers. Results: Personal factors included health problems, motivation, effects of healthy diet, health-related careers, and dietary habits. Family factors included family structure, support from family members, and critical health events involving family members or relatives. Community factors consisted of educational materials, friends, primary care physicians, and online social networks. Societal factors included accessibility to grocery stores and restaurants. Conclusions: Aged Chinese-Canadian immigrants experience unique facilitators of and barriers to healthy eating, which may warrant further attention from healthcare professionals when educating patients in a culturally-sensitive manner.

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Wheeler, Charles. "Buddhism in the re-ordering of an early modern world: Chinese missions to Cochinchina in the seventeenth century." Journal of Global History 2, no. 3 (November 2007): 303–24. http://dx.doi.org/10.1017/s1740022807002306.

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AbstractIn the seventeenth century, Chan Buddhist masters from monasteries in South China boarded merchant ships to Chinese merchant colonies in East and Southeast Asian port cities to establish or maintain monasteries. Typically, Chinese seafarers and merchants sponsored their travel, and sovereigns and elites abroad offered their patronage. What were these monks and their patrons seeking? This study will investigate the question through the case of one Chan master, Shilian Dashan, who journeyed to the Vietnamese kingdom of Cochinchina (Dang Trong) in 1695 and 1696. In Dashan, we see a form of Buddhism thought to have vanished with the Silk Road: that is, Buddhism as a ‘missionary religion’ able to propagate branch temples through long-distance networks of merchant colonies, and to form monastic communities within the host societies that welcomed them. This evident agency of seafaring Chan monks in early modern times suggests that Buddhism’s role in commerce, diaspora, and state formation in early modern maritime Asia may compare to religions like Islam and Christianity, and deserves further study.

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Ghaffari Rad, Afsaneh, Sajjad Negahban, Behzad Tokhmechi, and Hossein Mostafavi. "DRILL BIT SELECTION IN A FORMATION WITH DIFFERENT SEDIMENTARY FACIES USING THE MARKOV CHAIN: A CASE STUDY AT ONE OF THE OIL FIELDS IN THE SOUTH OF IRAN." Rudarsko-geološko-naftni zbornik 36, no. 2 (2021): 83–92. http://dx.doi.org/10.17794/rgn.2021.2.8.

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The selection of a drill bit is an essential issue in well planning. Furthermore, identification and evaluation of sedimentary rocks before well drilling plays a crucial role in choosing the drill bit. Moreover, the Markov chain as a stochastic model is one of the powerful methods for identifying lithological units, which is based on the calculation of the transition probability matrix or transition matrix. The Markov chain experiences transitions from one state (a situation or set of values) to another according to specified probabilistic rules. In this paper, the Markov chain was implemented for bit selection in a formation with different sedimentary facies (such as the Dashtak Formation). Therefore, the proper drill bit was proposed by utilizing the transition matrix of rock facies and the available bits. This process was carried out in two wells where the thicknesses of the Dashtak Formation are 960 meters and 1410 meters. Consequently, the results indicate that the Markov chain is a practical method for selecting bits in a sequence of rock facies based on an acceptable matching between the reality mode (the used bits in the well) and the Markov chain results. Besides, in the case of using an improper bit in a well, and using a bit in a washing and reaming operation, there were differences between the used bits and the Markov chain outputs.

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