Academic literature on the topic 'Self-driving databases'
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Journal articles on the topic "Self-driving databases"
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Thompson, Trevor, Damian Poulter, Clare Miles, Marco Solmi, Nicola Veronese, André F. Carvalho, Brendon Stubbs, and Ergun Y. Uc. "Driving impairment and crash risk in Parkinson disease." Neurology 91, no. 10 (August 3, 2018): e906-e916. http://dx.doi.org/10.1212/wnl.0000000000006132.
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ObjectivesTo provide the best possible evidence base for guiding driving decisions in Parkinson disease (PD), we performed a meta-analysis comparing patients with PD to healthy controls (HCs) on naturalistic, on-the-road, and simulator driving outcomes.MethodsSeven major databases were systematically searched (to January 2018) for studies comparing patients with PD to HCs on overall driving performance, with data analyzed using random-effects meta-analysis.ResultsFifty studies comprising 5,410 participants (PD = 1,955, HC = 3,455) met eligibility criteria. Analysis found the odds of on-the-road test failure were 6.16 (95% confidence interval [CI] 3.79–10.03) times higher and the odds of simulator crashes 2.63 (95% CI 1.64–4.22) times higher for people with PD, with poorer overall driving ratings also observed (standardized mean differences from 0.50 to 0.67). However, self-reported real-life crash involvement did not differ between people with PD and HCs (odds ratio = 0.84, 95% CI 0.57–1.23, p = 0.38). Findings remained unchanged after accounting for any differences in age, sex, and driving exposure, and no moderating influence of disease severity was found.ConclusionsOur findings provide persuasive evidence for substantive driving impairment in PD, but offer little support for mandated PD-specific relicensure based on self-reported crash data alone, and highlight the need for objective measures of crash involvement.
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Pawłowska, Justyna, Artur Gądek, and Ewa Wodka-Natkaniec. "Return of TKA knee arthroplasty patients to driving a car. Comparative systematics." Polish Journal of Sports Medicine 37, no. 1 (February 28, 2021): 23–28. http://dx.doi.org/10.5604/01.3001.0014.8688.
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Background. Despite the availability of numerous articles and analyses carried out in many healthcare centres, there is still no specific guidelines for both orthopaedic surgeons, and physical therapists for patients preparation after total knee arthroplasty to return to driving a car. The influence of many factors should be taken into account, such as: the operated side, the pain associated with the injury and surgery, the lack of sufficient force to slow down in extreme conditions, the patient’s reaction time and the lack of self-confidence when making such an important decision. Both the patient and the doctor who decides to let the patient drive a car must be aware that this is a very complex and responsible action. This may have an impact on the safety of the patient himself as well as other road users. The aim of the study was to analyse the research carried out so far and to help doctors and physiotherapists in taking the decision of returning the patient to driving a car. Most of the available studies are based on driving simulators and automatic gearboxes where a safe braking element is achieved in three to six weeks, where left-sided TKA patients can return to driving after 4 weeks. The most promising research seems to be in real driving, which allows them to return to driving just 3 weeks after the procedure. Material and metods. The medical databases, i.e. PubMed and Medline were searched for articles concerning the studied issue. The search have covered all databases until April 2020. Most of the work presented is based on a 1994 study and article made by Spalding, who was the first who conduct a study concerning the return of TKA patients to driving. Results and Conclusions. Safe, possible return to driving in patients after TKA is possible 6 weeks after the procedure.
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Unger, Astrid, Margrit Gelautz, and Florian Seitner. "A Study on Training Data Selection for Object Detection in Nighttime Traffic Scenes." Electronic Imaging 2020, no. 16 (January 26, 2020): 203–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.16.avm-202.
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With the growing demand for robust object detection algorithms in self-driving systems, it is important to consider the varying lighting and weather conditions in which cars operate all year round. The goal of our work is to gain a deeper understanding of meaningful strategies for selecting and merging training data from currently available databases and self-annotated videos in the context of automotive night scenes. We retrain an existing Convolutional Neural Network (YOLOv3) to study the influence of different training dataset combinations on the final object detection results in nighttime and low-visibility traffic scenes. Our evaluation shows that a suitable selection of training data from the GTSRD, VIPER, and BDD databases in conjunction with selfrecorded night scenes can achieve an mAP of 63,5% for ten object classes, which is an improvement of 16,7% when compared to the performance of the original YOLOv3 network on the same test set.
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Pál, Márton, Fanni Vörös, István Elek, and Béla Kovács. "Possibilities of high precision GPS data in autonomous driving." Abstracts of the ICA 1 (July 15, 2019): 1–2. http://dx.doi.org/10.5194/ica-abs-1-286-2019.
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<p><strong>Abstract.</strong> A self-driving car is a vehicle that is able to perceive its surroundings and navigate in it without human action. Radar sensors, lasers, computer vision and GPS technologies help it to drive individually (Figure 1). They interpret the sensed information to calculate routes and navigate between obstacles and traffic elements.</p><p>Sufficiently accurate navigation and information about the current position of the vehicle are indispensable for transport. These expectations are fulfilled in the case of a human driver: the knowledge on traffic rules and signs make possible to navigate through even difficult situations. Self-driving systems substitute humans by monitoring and evaluating the surrounding environment and its objects without the background information of the driver. This analysing process is vulnerable. Sudden or unexpected situations may occur but high precision navigation and background GPS databases can complement sensor-detected data.</p><p>The assistance of global navigation has been used in cars for decades. Drivers can easily plan their routes and reach their destination by using car GPS units. However, these devices do not provide accurate positioning: there may be a difference of several metres from the real location. Self-driving cars also use navigation to complement sensor data. Although there are already autonomous system tests on motorways and countryside roads, in densely built-in areas this technology faces complications due to accuracy problems. The dilution of precision (DOP) values can be extremely high in larger settlements because high buildings may hide southern sky (where satellite signs are sensed from on our latitude).</p><p>We can achieve centimetre-level accuracy (if the conditions are ideal) with geodesic RTK (real-time kinematic) GPS systems. This high-precision position data is derived from satellite-based positioning systems. Measurements of the phase of the signal’s carrier wave are real-time corrected by a single reference or an interpolated virtual station.</p><p>In this research we use RTK GPS technology in order to work out a spatial database. These measurements can also be less precise in dense cities, but there is time during fieldwork to try to eliminate inaccuracy. We have chosen a sample area in the inner city of Budapest, Hungary where we located all traffic signs, pedestrian crossings and other important elements. As self-driving cars need precise position data of these terrain objects, we have tried to work with a maximum error of a few decimetres.</p><p>We have examined online map providers if they have feasible data structure and some base data. The implemented structure is similar to OpenStreetMap DB, in which there are already some traffic lights in important crossings. With this preliminary test database, we would like to filter out dangerous situations. If the camera of the car does not see a traffic sign because of a tree or a truck, information about it will be available from the database. If a pedestrian crossing is hardly visible and the sensor does not recognize it, the background GIS data will warn the car that there may be inattentive people on the road.</p><p>A test application has also been developed (Figure 2.), in which our Postgres/Postgis database records have been inserted. In the next phase of the project we try to test our database in the traffic. We plan to drive through the sample area and observe the GPS accuracy in the recognition of the located signs.</p><p>This research aims to achieve higher safety in the field of autonomous driving. By having a refreshable cartographic GIS database in the memory of a self-driving car, there is a smaller chance of risking human life. However, the maintenance demands a high amount of work. Because of this we should concentrate only on the most important signs. Even the cars can be able to supervise the content of the database if there is a large number of them on the road. The frequent production and analysis of point clouds is also an option to get nearer to safe automatized traffic.</p>
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Holló, Péter, Diána Henézi, and Tamás Berta. "Comparison of Self-reported and Observed Road Safety Performance Indicators." Periodica Polytechnica Transportation Engineering 46, no. 3 (March 20, 2018): 117–21. http://dx.doi.org/10.3311/pptr.12127.
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The first concept of road safety performance indicators was published by European Transport Safety Council, Brussels in 2001. Hungary has long and reliable time series of safety belt wearing and child safety seat usage rates in passenger cars. These rates are based on real roadside observations and representative sample, meeting the requirements of international road accident databases. The methodology of the data collection has been further developed during the recent years, but we paid attention to the possibility of comparison with the earlier data and consistent analysis of time series. Although the roadside observations could not have been organized in each year, the trends can be seen relatively well. Our initial hypothesis was that the self-reported data always show a bit "better" picture about the driving behaviour than the observed ones, since the people are not sure that their data will be handled in an anonym way. Based on these results we can say that the ESRA results are relatively good estimations of the real safety belt wearing rates.
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van der Lijn, Iris, Gera A. de Haan, Famke Huizinga, Fleur E. van der Feen, A. Wijnand F. Rutgers, Catherina Stellingwerf, Teus van Laar, and Joost Heutink. "Self-Reported Visual Complaints in People with Parkinson’s Disease: A Systematic Review." Journal of Parkinson's Disease 12, no. 3 (April 5, 2022): 785–806. http://dx.doi.org/10.3233/jpd-202324.
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Background: Scientific research increasingly focuses on visual symptoms of people with Parkinson’s disease (PD). However, this mostly involves functional measures, whereas self-reported data are equally important for guiding clinical care. Objective: This review provides an overview of the nature and prevalence of self-reported visual complaints by people with PD, compared to healthy controls. Methods: A systematic literature search was performed. Studies from three databases (PubMed, PsycInfo, and Web of Science) were screened for eligibility. Only studies that reported results of visual self-reports in people with idiopathic PD were included. Results: One hundred and thirty-nine eligible articles were analyzed. Visual complaints ranged from function-related complaints (e.g., blurred vision, double vision, increased sensitivity to light or changes in contrast sensitivity) to activity-related complaints (e.g., difficulty reading, reaching, or driving). Visual complaints were more prevalent in people with PD compared to healthy controls. The presence of visual complaints leads to a reduced quality of life (QoL). Increased prevalence and severity of visual complaints in people with PD are related to longer disease duration, higher disease severity, and off-state. Conclusion: A large proportion of people with PD have visual complaints, which negatively affect QoL. Complaints are diverse in nature, and specific and active questioning by clinicians is advised to foster timely recognition, acknowledgement, and management of these complaints.
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Chukwuedozie Francis Nwachukwu. "Inflammatory reaction - A posit to the double-edged sword." International Journal of Biological and Pharmaceutical Sciences Archive 1, no. 2 (May 30, 2021): 197–209. http://dx.doi.org/10.30574/ijbpsa.2021.1.2.0036.
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Response by inflammation is triggered by arrays of causes, which include disrupted cells, toxins, germs, and others. It underlies a wide variety of pathophysiological changes. Many aspects of inflammation as it relates to the pathology of various inflammations are very much understood. Yet the healthy roles of inflammation are widely unknown. Inflammation has a controversial role in health and its meanings are, a matter of viewpoint. It has critical roles in protecting organisms from pathogens and injurious substances likewise causing a driving variety of disease progression. On this ground the research aimed at prescribing the essential needs for effective regulations of inflammatory responses. Efficient control of the inflammatory process will avert a plethora of diseases. Articles used for this review were obtained using appropriate keywords on six electronic databases including nature, advantage, disadvantage, and immune response regarding inflammation and immunological response. Inflammation is self-perpetuating though no disease is caused by inflammation as it is not self-triggering. Additionally, the research did weigh up the merits alongside the demerit of inflammation to advocate for effective regulation of inflammation. Essentially, inflammation is a required mechanism in healthy and unhealthy status in humans hence there is a need for importunate reconsideration, exploring its therapeutic benefits.
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Orlov, Sergey P., Elizaveta E. Bizyukova, and Anastasia E. Iakovleva. "Virtual tests of robotic vehicle units for virtual commissioning." Vestnik of Samara State Technical University. Technical Sciences Series 29, no. 1 (April 23, 2021): 46–57. http://dx.doi.org/10.14498/tech.2021.1.4.
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The creation of robotic vehicles for agricultural purposes is a promising direction in the automotive industry. The complexity of the self-driving truck's design, work in difficult operating conditions, and a large number of measuring devices and processing subsystems determine the relevance of creating a virtual test system. These tests are part of the overall virtual commissioning process for a robotic vehicle. The article discusses a set of basic subsystems that provide virtual tests based on a model-based approach: mathematical modeling, measurement modeling, information subsystem with databases, visualization and documentation subsystem. Metrological models of measuring channels for virtual tests have been developed, allowing simulating random vehicle parameter changes. The testing process covers all the most essential components of a robotic vehicle. For example, the article presents a dynamic model of the braking system of a robotic chassis and shows the results of braking modes' virtual tests. The developed virtual test system is used to create a KAMAZ truck as part of a robotic system for agricultural vehicles.
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Almeida, João, João Rufino, Muhammad Alam, and Joaquim Ferreira. "A Survey on Fault Tolerance Techniques for Wireless Vehicular Networks." Electronics 8, no. 11 (November 16, 2019): 1358. http://dx.doi.org/10.3390/electronics8111358.
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Future intelligent transportation systems (ITS) hold the promise of supporting the operation of safety-critical applications, such as cooperative self-driving cars. For that purpose, the communications among vehicles and with the road-side infrastructure will need to fulfil the strict real-time guarantees and challenging dependability requirements. These safety requisites are particularly important in wireless vehicular networks, where road traffic presents several threats to human life. This paper presents a systematic survey on fault tolerance techniques in the area of vehicular communications. The work provides a literature review of publications in journals and conferences proceedings, available through a set of different search databases (IEEE Xplore, Web of Science, Scopus and ScienceDirect). A systematic method, based on the preferred reporting items for systematic reviews and meta-analyses (PRISMA) Statement was conducted in order to identify the relevant papers for this survey. After that, the selected articles were analysed and categorised according to the type of redundancy, corresponding to three main groups (temporal, spatial and information redundancy). Finally, a comparison of the core features among the different solutions is presented, together with a brief discussion regarding the main drawbacks of the existing solutions, as well as the necessary steps to provide an integrated fault-tolerant approach to the future vehicular communications systems.
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Kossmann, Jan, and Rainer Schlosser. "Self-driving database systems: a conceptual approach." Distributed and Parallel Databases 38, no. 4 (March 16, 2020): 795–817. http://dx.doi.org/10.1007/s10619-020-07288-w.
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Abstract Challenges for self-driving database systems, which tune their physical design and configuration autonomously, are manifold: Such systems have to anticipate future workloads, find robust configurations efficiently, and incorporate knowledge gained by previous actions into later decisions. We present a component-based framework for self-driving database systems that enables database integration and development of self-managing functionality with low overhead by relying on separation of concerns. By keeping the components of the framework reusable and exchangeable, experiments are simplified, which promotes further research in that area. Moreover, to optimize multiple mutually dependent features, e.g., index selection and compression configurations, we propose a linear programming (LP) based algorithm to derive an efficient tuning order automatically. Afterwards, we demonstrate the applicability and scalability of our approach with reproducible examples.
Dissertations / Theses on the topic "Self-driving databases"
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Tan, Kaige. "Building verification database and extracting critical scenarios for self-driving car testing on virtual platform." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-263927.
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This degree project, conducted at Volvo Cars, investigates a method about how to build a test database for an Autonomous Driving (AD) function on a virtual platform and how to extract critical scenarios from the test database to finish test cases reduction through optimization. The virtual platform under study is the model-in-the-loop (MIL) based Simulation Platform Active Safety (SPAS) environment and the optimization tool being used is modeFrontier. The analyzing process, in which three levels of abstraction for scenarios are proposed in order to fulfill all requirements for an AD function, is followed in the project to build the test database. Application is carried out to transform requirements from a specific Operational Design Domain (ODD) and linguistic representation into a test suite which contains concrete scenarios and test cases. A meta-model is built to help analyze system structure and parameter requirements in the level of logical scenarios. The practicability of a scenario-based approach for the design of AD function test cases generation is demonstrated with the example of building Traffic Congestion Support (TCS) test database. Obtaining the test database and the successful analysis of parameters for the TCS function on the MIL platform lead to the main goal of the thesis project, which is finding edge cases in the test database by optimizing objective functions. By defining the objective functions and building the workflow in modeFrontier after trying with different methods, the optimization process is implemented with two different algorithms separately. pilOPT is evaluated as a better solution for AD function than Multi-Objective Simulated Annealing (MOSA) in terms of computational time and edge cases finding. In addition, a noise model is added to ideal sensor model in SPAS to study the influence of noise in real test track. The result shows a big difference in Time-toCollision value, which is a defined objective function in the project. This indicates more test cases are deteriorated to critical scenario if noise is taken into consideration, which shows the influence of noise cannot be neglected during testing.Detta examensarbete, genomfört hos Volvo Cars, undersöker en uppbyggnadsmetod av en testdatabas för Autonomous Driving (AD) på en virtuell plattform och hur man bör extrahera kritiska scenarier från testdatabasen för att reducera antalet testfall genom optimering. Den aktuella virtuella plattformen är den model-in-the-loop (MIL) baserade Simulation Platform Active Safety (SPAS) miljön och optimeringsverktyget som användes är modeFrontier. Analysprocessen, i vilken tre abstraktionsnivåer för scenarier är föreslagna i syfte att satisfiera alla kraven för AD, redogörs för i detta projekt. Tillämpning har genomförts för att transformera krav från en specifik Operational Design Domain (ODD) samt lingvistisk representation till en testsvit som innehåller konkreta scenarier och testfall. En metamodell har konstruerats för att assistera med analysen av systemstrukturen och parameterkraven i nivån av logiska scenarier. Genomförbarheten av en scenariobaserad infallsvinkel för designen av AKF-testfall demonstreras med exemplet av konstruktionen av Traffic Congestion Support (TCS)- testdatabasen. Erhållandet av testdatabasen och den framgångsrika analysen av parametrarna för TCSfunktionen på MIL-plattformen ledde till det huvudsakliga målet med examenarbetet, vilket var att identifiera kantfall i testdatabasen genom att optimera objektfunktioner. Genom att definiera objektfunktionerna och konstruera arbetsflödet i modeFrontier efter flertalet försök med olika metoder, implementerades optimeringsprocessen med tvåseparata algoritmer. pilOPT evalueras som en bättre lösning för AD jämfört med Multi-Objective Simulated Annealing (MOSA) med avseende på beräkningstid och identifiering av kantfall. Dessutom har brus adderats till den ideala sensormodellen i SPAS för att studera inflytandet av brus i en verklig testmiljö. Resultaten visar på en stor skillnad i tid-till-kollisionsvärde, vilket är en väldefinierad objektfunktion i projektet. Detta indikerar att fler testfall har försämrats till ett kritiskt scenario om brus tas man tar hänsyn till brus, vilket visar på att inflytandet av brus inte kan försummas under testning.
Book chapters on the topic "Self-driving databases"
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Show, Arnab Kumar, Abhishek Kumar, Achintya Singhal, Gayathri N., and K. Vengatesan. "Future Blockchain Technology for Autonomous Applications/Autonomous Vehicle." In Advances in Data Mining and Database Management, 165–77. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-3295-9.ch010.
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The autonomous industry has rapidly grown for self-driving cars. The main purpose of autonomous industry is trying to give all types of security, privacy, secured traffic information to the self-driving cars. Blockchain is another newly established secured technology. The main aim of this technology is to provide more secured, convenient online transactions. By using this new technology, the autonomous industry can easily provide more suitable, safe, efficient transportation to the passengers and secured traffic information to the vehicles. This information can easily gather by the roadside units or by the passing vehicles. Also, the economical transactions can be possible more efficiently since blockchain technology allows peer-to-peer communications between nodes, and it also eliminates the need of the third party. This chapter proposes a concept of how the autonomous industry can provide more adequate, proper, and safe transportation with the help of blockchain. It also examines for the possibility that autonomous vehicles can become the future of transportation.
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Rajakumar.R, Pandian.R, and PremJacob.T. "Lane Detection and Tracking Algorithm Based on Curve Fitting Model." In Advances in Parallel Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210009.
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Lane Detection is the fundamental vehicle driving system and self-driving. The proposed concept is to employ the pixel difference in the expected lane and the road backdrop to detach the lane from the road, and then the Curve fitting model is made use of in the segregated lanes to locate the straight line in the image as the lane line. This paper offers a lane detection method based on the Sobel filter and Curve-fitting model for lane line tracking in different conditions. The main objective is to improve the accuracy of the Xi’an city database and the KITTI vision benchmark suite dataset. To achieve this HLS color space was performed which identifies the lane by adding pixel values.
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Dandotiya, Monika, and Madhukar Dubey. "A VGG-16 Framework for an Efficient Indoor-Outdoor." In SCRS CONFERENCE PROCEEDINGS ON INTELLIGENT SYSTEMS, 321–30. Soft Computing Research Society, 2021. http://dx.doi.org/10.52458/978-93-91842-08-6-32.
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Computer vision had reached a new level that allows robots from the limits of laboratories to explore the outside world. Even with progress in this area, robots are struggling to understand their location. The classification of the scene is an important step in understanding the scene. In many applications, a scene classifi- cation can be used such as a surveillance camera, self-driving, a household robot, and a database imaging system. Monitoring cameras are now everywhere installed. The accuracy of scene classification of indoor-outdoor techniques is weak. Using the Convolution Neural Net-work Model in VGG-16, this study attempts to im- prove accuracy. This research presents a new method for classifying images into classes using VGG-16. The algorithm’s outputs are validated using the SUN397 indoor-outdoor dataset, and outcomesdemonstrates that the suggested methodol- ogy outperforms existing technologies for indoor-outdoor scene classification. In this paper, Very Deep Convolutional Networks for Large-Scale Image Recognition” is what we implement. In ImageNet, a dataset of over 14 million images belonging to 1000 classes, the model achieves 92.7 percent top-5 test accuracy. It outperforms Alex Net by sequentially replacing large kernel-sized filters (11 and 5 in the first and second convolutional layers, respectively) with multiple 33 kernel-sized filters. We attain Training loss is 10percent and Training Accuracy is 96 percent in our projected work.
Conference papers on the topic "Self-driving databases"
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Ma, Lin, Dana Van Aken, Ahmed Hefny, Gustavo Mezerhane, Andrew Pavlo, and Geoffrey J. Gordon. "Query-based Workload Forecasting for Self-Driving Database Management Systems." In SIGMOD/PODS '18: International Conference on Management of Data. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3183713.3196908.
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Ma, Lin, William Zhang, Jie Jiao, Wuwen Wang, Matthew Butrovich, Wan Shen Lim, Prashanth Menon, and Andrew Pavlo. "MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems." In SIGMOD/PODS '21: International Conference on Management of Data. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3448016.3457276.
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Tian, Yuan, and Marc Compere. "Monocular Visual Inertial Odometry (VIO) Dataset Collection With a Self-Calibrating Platform for Inertial Measurement Unit (IMU)." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10595.
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Abstract In this study, we built a monocular visual inertial odometry (VIO) dataset with a proposed self-calibrating platform for an inertial measurement unit (IMU). For a learning-based method, lack of database is the biggest limitation. One goal of this study is to generate a high-quality VIO database. Meanwhile, a properly calibrated inertial measurement unit (IMU) is critical for improving VIO system accuracy and precision. However, a professional IMU calibration tool is usually expensive and large. The proposed self-calibrating platform shows its benefits in eliminating the manual work in calibration and reducing the cost of the expensive platform, which brings more opportunities to students and researchers. This self-calibrating system was useful for collecting monocular visual inertial odometry datasets while driving. . The calibrated IMU generates 14 numbers at 100Hz: time, 3-axis accelerometer measurements, 3-axis gyroscope measurements, 3 Euler angles, and 4 quaternions. This VIO system is composed of a monocular camera, GoPro Hero 3, an IMU, BNO055, and a GPS, ANT-555. The sensors are mounted on a John Deere Gator™ Full-Size Crossover Utility Vehicle and are operated on an Intel NUC, a mini-size computer. The final dataset contains monocular images, IMU measurements, and GPS outputs.
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Butrovich, Matthew, Wan Shen Lim, Lin Ma, John Rollinson, William Zhang, Yu Xia, and Andrew Pavlo. "Tastes Great! Less Filling! High Performance and Accurate Training Data Collection for Self-Driving Database Management Systems." In SIGMOD/PODS '22: International Conference on Management of Data. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3514221.3517845.
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Fox, Nicolle, Olivia Canella, and Jeffrey Wardell. "Medicinal versus recreational cannabis use among youth: A systematic review." In 2022 Annual Scientific Meeting of the Research Society on Marijuana. Research Society on Marijuana, 2022. http://dx.doi.org/10.26828/cannabis.2022.02.000.08.
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Background: Adolescents and young adults have high rates of cannabis use. Although a sizeable portion of youth report that they use cannabis for medicinal reasons (Wardell et al., 2020; Wardell, in press), most research on youth cannabis use tends to focus on recreational use. It is important to understand how youth who use cannabis for medicinal reasons differ from those who use for recreational reasons. We aimed to review the limited research comparing youth engaging in medicinal cannabis use to those engaging in recreational cannabis use. Methods: A systematic literature search of three databases (PsychInfo, PubMed, MEDLINE) was conducted to identify studies that compared adolescents and/or young adults who engage in medicinal cannabis to those who engage in recreational cannabis use. Studies that defined medicinal cannabis use either as self-reported use of cannabis for therapeutic reasons or as obtaining authorization/prescription for medical cannabis from a healthcare provider were included. Only quantitative research studies published in a peer-reviewed journal were included. After conducting the initial search and removing duplicates, 748 abstracts were reviewed independently by two researchers. Any discrepancies were resolved by consensus in consultation with a third researcher. Results: A total of 13 articles met inclusion criteria. Outcome variables reported in the literature included cannabis use (frequency and amount), cannabis-related problems, use of other substances including illicit drug use or prescription medication misuse, and health-related variables such as mental health symptoms or physical pain. Overall, the literature suggests that youth who use cannabis medicinally are more likely to use greater amounts of cannabis, to use more frequently, and to use a variety of different forms of cannabis, relative to youth who use cannabis recreationally. Further, several studies reported that medicinal cannabis use among youth was associated with problems related to cannabis use, such as the risk for cannabis use disorder and problematic behaviour (e.g., driving under the influence). Several studies also found that medicinal (vs. recreational) cannabis use was related to poorer mental or physical health, although a couple of studies did not support this finding. However, the results were mixed regarding the associations between medicinal cannabis use and the likelihood of using other drugs. Conclusion: There is evidence that using cannabis for medicinal reasons is associated with greater cannabis consumption, cannabis-related problems, and negative health-related correlates among youth. Although there was some consistency in findings across studies, the limited number of studies make it difficult to draw firm conclusions. Causal inferences are difficult to make owing to the frequent reliance on cross-sectional designs. The findings are further complicated by the heterogeneous definition of medicinal cannabis use (i.e., self-report vs. medically authorized). Given that many young people engage in both medicinal and recreational cannabis use, it is difficult to fully disentangle the differences. Additional research is needed for a complete understanding of the unique outcomes associated with medical cannabis use among youth.
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Svoboda, Jiří, and Vladislav Kocián. "Framework for Virtual and Physical Testing of Automated Vehicle Systems." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2020-acm-046.
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Massive expansion and implementation of Advanced Driver Assistant Systems and advent of Highly Automated Driving functions brings huge challenges in terms of design and development, but also function validation and certification process which is a limiting factor for their market introduction. To ensure safety of such systems, whose complexity is rapidly growing, it is essential to evaluate functionality of automated driving systems within the mandatory certification before it’s deployed on the road. And after their deployment, they must be a subject to periodical technical inspection during life cycle as well. The number of regulations and standards considering safety of AD functions gradually increases, but current safety standards and regulations still have to be adopted and enhanced. For highly automated driving functions and AVs that do not require permanent monitoring by the driver, a theoretically infinite number of possible traffic situations, that a self-driving car could possibly encounter, needs be tested. One promising method to overcome this matter is the scenario-based approach focused on critical, dangerous and extreme situations. Such approach ensures a repeatability and robustness of an approval process if it is supported by a significant sample of harmonized scenarios. Since confronting conventional physical driving tests with this test effort is not feasible anymore, virtualization of testing methods by means of computer simulation needs to be emphasized. To meet above described challenges, TÜV SÜD is developing a methodology for scenario-based evaluation of AD functionality as a supplement for either development or future certification of automated driving systems. The methodology combines virtual-based approach and physical testing and guarantees repeatability of test conditions. Virtual-based testing is provided by an in-house simulation toolchain with an open architecture. The toolchain consists of functional blocks as: database of standardized scenario, virtual environment model, high fidelity physics-based sensor simulation, model of vehicle dynamics, control functions and algorithms, automated and standardized post-processing and reporting. Physical testing provides real-world data measurement used among other purposes for validation of the simulation toolchain and its relevant functional blocks respectively. Physical testing is performed on our own test track using typical equipment as: driving robots, inertial measurement unit, guided soft target, soft VRU targets, master control station and others. In presentation, an overview of the current state of methodology is given and the workflow is demonstrated for a specific operational design domain (ODD). Architecture of simulation toolchain is described and explanation how functional blocks are embedded into overall architecture and how they interact with each other is given. Trustworthiness for virtual test execution will be discussed by means of a comparison and correlation between real-world and virtual-simulation measurement results for a specific operational design domain.
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Kinsey, Thomas, and Guy Dumas. "Testing and Analysis of an Oscillating Hydrofoils Turbine Concept." In ASME 2010 3rd Joint US-European Fluids Engineering Summer Meeting collocated with 8th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2010. http://dx.doi.org/10.1115/fedsm-icnmm2010-30869.
Full textAbstract:
A new concept of hydrokinetic turbine using oscillating hydrofoils to extract energy from water currents (tidal or gravitational) is presented, tested and analyzed in the present investigation. Due to its rectangular extraction plane, this technology is particularly well suited for river beds and shallow waters near the coasts. The present turbine is a 2 kW prototype, composed of two rectangular oscillating hydrofoils of aspect ratio 7 in a tandem spatial configuration. The pitching motion of each hydrofoil is coupled to their cyclic heaving motion through four-link mechanisms which effectively yield a one-degree-of-freedom system driving a speed-controlled electric generator. The turbine has been mounted on a custom-made pontoon boat and dragged on a lake at different velocities. Instantaneous extracted power has been measured and cycle-averaged for several water flow velocities and hydrofoil oscillation frequencies. Results are demonstrated to be self-consistent and validate our extensive 2D flow simulation database. The present data show optimal performances of the oscillating hydrofoils concept at a reduced frequency of about 0.12, at which condition the measured power extraction efficiency reaches 40% once the overall losses in the mechanical system are taken into account. Further measurements of power extraction with a single oscillating hydrofoil have also been performed by taking out the downstream hydrofoil of the tandem pair. Those measurements favorably compare, quantitatively, with available 3D CFD predictions. The 40% hydrodynamic efficiency of this first prototype exceeds expectation and reaches levels comparable to the best performances achievable with modern rotor-blades turbines. It thus demonstrates the promising potential of the oscillating hydrofoils technology to efficiently extract power from an incoming water flow.
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Alremeithi, Humaid. "No One Is Left Behind." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/210837-ms.
Full textAbstract:
Abstract Since ADNOC's LNG business was established in 1973, we have held true to the UAE's founders' vision of continuously supporting and developing our most valuable assets, our people. This has been the driving force behind the company's story of growth and its developing reputation. It is also a significant factor in our retention of talented individuals and our attractiveness for high-performing newcomers. No One Is Left Behind (NOILB) is an inclusive development approach ensuring the development needs of all our employees are met through a series of established processes, services and products. Phase 1 engages employees through a series of divisional and one-to-one awareness and support sessions. We aim to ensure all employees know the development options available, while emphasizing the importance of taking ownership of their own development. Phase 2 is an on-going process, of real-time group or one-to-one follow-up and technical support throughout the year. Phase 3, run in parallel, consists of "specialty programs". These include our "License to Lead" program and an internal subject matter expert (SME) program called "Khebrati", designed to support the quality of our training and ensure its relevance to both our employees and our business, as well as the "My Project program", through which high potential employees are identified and are given the opportunity to highlight challenges within their division. The Khebrati program allows for real return on investment through internal development courses delivered by our most talented and experienced people. These courses include soft and behavioral skills as well as technical skills. The SMEs are identified by their leaders and through self-nomination. We assess their capability in delivering courses, train them if needed and help develop their content. Khebrati was launched in Q3 2021 and (despite pandemic-related restrictions) to-date 12 courses have been delivered to 58 attendees. Our License to Lead program supports employees who either manage teams or have been identified as potential future leaders through our succession planning processes. The program ensures the target audience is equipped with the essential leadership skills, the policies, procedures and systems know-how required to effectively to lead and manage their teams. The program is certified by the Chartered Management Institute and, to-date, 13 of our initial 15 candidates have successfully graduated. Through the "No One Is Left Behind" initiative and its related programs, we ensure our people understand the importance of taking ownership of their development with the targeted and practical support needed to ensure their success. This is an important contribution to our culture of continuous improvement, that enables organic employee development and enhances retention. It also builds a persistent database of skills and experience. NOILB has a direct impact on the business. Its highly cost-effective utilization of in-house resources in competence development boosts employee engagement and productivity, and reduces commercial and operational risks. During the pandemic, up-skilling employees helped to address some of the workforce mobility challenges, supporting business resilience efforts. Overall, customer satisfaction improves, and profitability grows. This paper highlights the significance of talent development strategies and the benefits of maximizing workforce capability, a key process - particularly in challenging times of operational and business risk - for any organization to ensure it is "future-proofed".