Thematische Bibliographien / Car counting

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Auswahl der wissenschaftlichen Literatur zum Thema „Car counting“

Autor: Grafiati

Veröffentlicht am 28. Juni 2021

Zuletzt aktualisiert am 7. Februar 2022

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Zeitschriftenartikel zum Thema "Car counting"

Biswas, Debojit, Hongbo Su, Chengyi Wang, Jason Blankenship und Aleksandar Stevanovic. „An Automatic Car Counting System Using OverFeat Framework“. Sensors 17, Nr. 7 (30.06.2017): 1535. http://dx.doi.org/10.3390/s17071535.

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Fan, Honghui, Hongjin Zhu und Dongming Yuan. „People Counting in Elevator Car Based on Computer Vision“. IOP Conference Series: Earth and Environmental Science 252 (09.07.2019): 032131. http://dx.doi.org/10.1088/1755-1315/252/3/032131.

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Moranduzzo, Thomas, und Farid Melgani. „Automatic Car Counting Method for Unmanned Aerial Vehicle Images“. IEEE Transactions on Geoscience and Remote Sensing 52, Nr. 3 (März 2014): 1635–47. http://dx.doi.org/10.1109/tgrs.2013.2253108.

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Chen, Yuan Been. „Cars Tracking and Counting at Night“. Applied Mechanics and Materials 182-183 (Juni 2012): 1017–22. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1017.

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This work proposes a robust scheme to automatically tracking and counting cars in the traffic surveillance. In the proposed method, pixels at a specific position of successive image frames are first processed by the modified iterative threshold selection technique to establish the background model. Second, an original image is subtracted by this background to obtain a difference image that is performed with the differential image between an original image and its precedent neighboring image to yield an image with initial contour points of moving objects. Third, the robust edge-following scheme manipulates these contour points to produce closed-form objects. Particularly, two headlights of a car are merged with their corresponding reflective lights on the ground to yield two light objects for a car extraction at night. As compared to the conventional methods, the proposed method is demonstrated to have the best accuracy of moving object extraction. Finally, object motion connection is effectively employed to track object paths and compute the number of moving cars. The practical implementation reveals that the proposed method can precisely and reliably estimate a traffic amount.

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Soon, Chin Fhong, Siti Hajar Aminah Ali, See Khee Ye, Munzilah Md Rohani, Kian Sek Tee, Marlia Morsin, Nafarizal Nayan und Chiok Chuan Lim. „Investigation of wireless magnetometer in sensing magnetic field changes at different car direction and speed“. Bulletin of Electrical Engineering and Informatics 10, Nr. 2 (01.04.2021): 668–79. http://dx.doi.org/10.11591/eei.v10i2.2707.

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The embedment of induction loop underground for traffic volume monitoring caused damaging effects to the road and reduced road surface aesthetics. A wireless magnetometer implanted underground in a small uniform area was developed to detect three-axis magnetic flux changes due to the perturbation of vehicle passing over the sensor. In this project, a wireless magnetometer sensor system operating at a radio frequency of 2.4 GHz for detecting and transmitting Z-field data has been developed to investigate the patterns of magnetic field associated with the car directions and speed. This is the first report in revealing the responses of the sensor to different car speed and sensing directions. Field tests were conducted by car passes over in a direction in-line or countering the X and Y axes of the magnetometer. The results showed that the strong magnetic field density as low as -100 to -230 μT could be generated when a car passed over the sensor in a direction countering X and Y axes. The speed detection limit of the sensor is 60 kmph. The X, Y and Z flux patterns obtained is import in designing an algorithm for accurate detection and counting of vehicles.

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Fachrie, Muhammad. „A Simple Vehicle Counting System Using Deep Learning with YOLOv3 Model“. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 4, Nr. 3 (20.06.2020): 462–68. http://dx.doi.org/10.29207/resti.v4i3.1871.

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Deep Learning is a popular Machine Learning algorithm that is widely used in many areas in current daily life. Its robust performance and ready-to-use frameworks and architectures enables many people to develop various Deep Learning-based software or systems to support human tasks and activities. Traffic monitoring is one area that utilizes Deep Learning for several purposes. By using cameras installed in some spots on the roads, many tasks such as vehicle counting, vehicle identification, traffic violation monitoring, vehicle speed monitoring, etc. can be realized. In this paper, we discuss a Deep Learning implementation to create a vehicle counting system without having to track the vehicles movements. To enhance the system performance and to reduce time in deploying Deep Learning architecture, hence pretrained model of YOLOv3 is used in this research due to its good performance and moderate computational time in object detection. This research aims to create a simple vehicle counting system to help human in classify and counting the vehicles that cross the street. The counting is based on four types of vehicle, i.e. car, motorcycle, bus, and truck, while previous research counts the car only. As the result, our proposed system capable to count the vehicles crossing the road based on video captured by camera with the highest accuracy of 97.72%.

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Alkhatib, Ahmad A. A., Adnan Hnaif und Tarek Kanan. „Proposed Simple System for Road Traffic Counting“. International Journal of Sensors, Wireless Communications and Control 9, Nr. 2 (25.10.2019): 269–77. http://dx.doi.org/10.2174/2210327908666181107110441.

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Background & Objective: Traffic congestion is a burning issue in most countries due to the rapid growth of running vehicles and infrastructures with limited capacity. Congestion can be solved with Intelligent Transport Systems (ITS) and traffic management. Most traffic management measurement are aimed to improve the safety and flow of traffic, reduce traffic emissions and utilize traffic artery capacity more effectively. Methods: This paper proposes a new system to collect the required data for traffic management such as, number of vehicles, time and lane location information; using a cheap infrared sensors and timers. Conclusion: The proposed method can take the length of the vehicle into account of traffic statistics by measuring the car speed.

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Van Pham, Huy, und Byung-Ryong Lee. „Front-view car detection and counting with occlusion in dense traffic flow“. International Journal of Control, Automation and Systems 13, Nr. 5 (14.07.2015): 1150–60. http://dx.doi.org/10.1007/s12555-014-0229-7.

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Mazzeo, Pier Luigi, Riccardo Contino, Paolo Spagnolo, Cosimo Distante, Ettore Stella, Massimiliano Nitti und Vito Renò. „MH-MetroNet—A Multi-Head CNN for Passenger-Crowd Attendance Estimation“. Journal of Imaging 6, Nr. 7 (02.07.2020): 62. http://dx.doi.org/10.3390/jimaging6070062.

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Knowing an accurate passengers attendance estimation on each metro car contributes to the safely coordination and sorting the crowd-passenger in each metro station. In this work we propose a multi-head Convolutional Neural Network (CNN) architecture trained to infer an estimation of passenger attendance in a metro car. The proposed network architecture consists of two main parts: a convolutional backbone, which extracts features over the whole input image, and a multi-head layers able to estimate a density map, needed to predict the number of people within the crowd image. The network performance is first evaluated on publicly available crowd counting datasets, including the ShanghaiTech part_A, ShanghaiTech part_B and UCF_CC_50, and then trained and tested on our dataset acquired in subway cars in Italy. In both cases a comparison is made against the most relevant and latest state of the art crowd counting architectures, showing that our proposed MH-MetroNet architecture outperforms in terms of Mean Absolute Error (MAE) and Mean Square Error (MSE) and passenger-crowd people number prediction.

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Huang, Zhi An, Xin Tong Wang, Ying Hua Zhang und Yu Kun Gao. „The R&D of the Emergency Rescue Vehicles Based on Borehole-Type Refuge Chamber“. Advanced Materials Research 881-883 (Januar 2014): 1732–40. http://dx.doi.org/10.4028/www.scientific.net/amr.881-883.1732.

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So far, the control rooms require a lot of manpower and material resources to repair and maintenance. They are above the borehole-type refuge chamber. It is also possible that the equipment in control rooms is aged and the necessities are overdue. When an emergency appears, it can detain the rescue. Therefore, a kind of emergency rescue car for permanent drilling shelters is developed. It can replace the control room. It combines with relevant regulations, through counting, based on the conditions of mines affiliated to Jizhong Fengfeng Energy Group. The air supply system, the power supply system, the flow food system and the communication system of monitoring and controlling are designed in the car. After conducting laboratory experiments, the model of appropriate emergency rescue car, the types of functional equipment are determined. The layout and connections of each system are also designed in the car. These are based on the data and theories concluded from theoretical analysis.

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Dissertationen zum Thema "Car counting"

Uhrín, Peter. „Počítání unikátních aut ve snímcích“. Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2021. http://www.nusl.cz/ntk/nusl-445493.

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Current systems for counting cars on parking lots usually use specialized equipment, such as barriers at the parking lot entrance. Usage of such equipment is not suitable for free or residential parking areas. However, even in these car parks, it can help keep track of their occupancy and other data. The system designed in this thesis uses the YOLOv4 model for visual detection of cars in photos. It then calculates an embedding vector for each vehicle, which is used to describe cars and compare whether the car has changed over time at the same parking spot. This information is stored in the database and used to calculate various statistical values like total cars count, average occupancy, or average stay time. These values can be retrieved using REST API or be viewed in the web application.

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Liese, Jeffrey Edward. „Counting patterns in permutations and words“. Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2008. http://wwwlib.umi.com/cr/ucsd/fullcit?p3307363.

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Thesis (Ph. D.)--University of California, San Diego, 2008.
Title from first page of PDF file (viewed July 22, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 182-183).

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Miller, Wendy L. „Counting points on certain CM elliptic curves modulo primes /“. Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 1998. http://wwwlib.umi.com/cr/ucsd/fullcit?p9906470.

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Wolstenholme, Jane. „Counting the costs of cancer care : breast, cervical and lung cancer in Trent“. Thesis, University of Nottingham, 2001. http://eprints.nottingham.ac.uk/12097/.

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The purpose of this thesis is to explore the theory, practice and application of costing with specific reference to cancer. In part it reviews the theory and guidelines related to costing methods including the recent focus on the analytical techniques used with cost data. In addition it examines how these theories and guidelines are applied in practice, by reviewing the literature on costs and cancer. The empirical research in this thesis applies costing methods to three specific cancer sites; breast, cervix and lung. This analysis provides information on the total burden of these specified cancers in terms of cost to a typical health authority (Trent). It also explores the hypothesis highlighted in previous studies that the cost of cancer increases with the stage of the disease. The final area of contribution for the thesis is in the application of recently suggested analytical techniques for cost data to the breast, cervical and lung cancer data sets; it investigates a number of proposed techniques for the analysis of skewed cost data and methods for data with incomplete patient follow up.

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Mireles-Garcia, Fernando. „Evaluation of 2-PI liquid scintillation whole body counter using MCNP /“. free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9841175.

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Theera-Umpon, Nipon. „Morphological granulometric estimation with random primitives and applications to blood cell counting /“. free to MU campus, to others for purchase, 2000. http://wwwlib.umi.com/cr/mo/fullcit?p9974689.

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Evans, Janet Lynn. „"We'll take care of the counting*": A cultural, rhetorical and critical analysis of electronic voting technology“. Connect to online resource, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3273667.

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Chiarella, Anatilde. „A study of adult day-care facilities in San Bernardino/Riverside counties“. CSUSB ScholarWorks, 1991. https://scholarworks.lib.csusb.edu/etd-project/834.

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Fannin, James Matthew. „The regional spillover effects of knowledge production on Missouri counties /“. free to MU campus, to others for purchase, 2003. http://wwwlib.umi.com/cr/mo/fullcit?p3115542.

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Harris, Kimberly D. „Acceptance of computer-based telemedicine in three rural Missouri counties /“. free to MU campus, to others for purchase, 1999. http://wwwlib.umi.com/cr/mo/fullcit?p9945181.

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Bücher zum Thema "Car counting"

ill, Slack Michael, Hrsg. Race car count. New York, NY: Henry Holt & Company, 2017.

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Jacqui, Hawkins, Hrsg. How many are in this old car?: A counting book. New York: Putnam's, 1988.

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Five little monkeys wash the car. New York: Scholastic Inc., 2001.

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Grosjean, James. Exhibit CAA: Beyond counting. Las Vegas, NV: South Side Advantage Press, LLC, 2007.

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Volke, Gordon. Crazy cars: Counting fun! New York, NY: Scholastic, 2006.

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Grosjean, James. Exhibit CAA: Beyond counting. Las Vegas, NV: South Side Advantage Press, LLC, 2007.

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Alaina, Maria. You can count. Mankato, Minn: Capstone Press, 2012.

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Kalman, Bobbie. I can count. New York: Crabtree Pub. Co., 2010.

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Ann, Ricketts, und Ricketts Michael, Hrsg. I can count. (Newmarket): Brimax, 1987.

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I can count 100 bunnies: And so can you! New York: Scholastic, 1998.

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Buchteile zum Thema "Car counting"

Lupinska-Dubicka, Anna, Marek Tabedzki, Marcin Adamski, Mariusz Rybnik, Miroslaw Omieljanowicz, Maciej Szymkowski, Marek Gruszewski, Adam Klimowicz, Grzegorz Rubin und Khalid Saeed. „In-Car eCall Device for Automatic Accident Detection, Passengers Counting and Alarming“. In Lecture Notes in Computer Science, 36–57. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-61092-3_3.

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Pham, Van-Huy, und Duc-Hau Le. „A Two-Stage Detection Approach for Car Counting in Day and Nighttime“. In Advances in Intelligent Systems and Computing, 159–71. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7512-4_16.

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Nhamo, Godwell, Kaitano Dube und David Chikodzi. „Impact of COVID-19 on Global Car Rental Industry and Ride and Share Transport Services“. In Counting the Cost of COVID-19 on the Global Tourism Industry, 159–81. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-56231-1_7.

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Kolcheck, Kevin, Zheyuan Wang, Haiyan Xu und Jiang Yu Zheng. „Visual Counting of Traffic Flow from a Car via Vehicle Detection and Motion Analysis“. In Lecture Notes in Computer Science, 529–43. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41404-7_37.

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Werthamer, N. Richard. „Card Counting“. In Risk and Reward, 67–80. New York, NY: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0253-5_8.

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Werthamer, N. Richard. „Card Counting“. In Risk and Reward, 75–89. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91385-8_8.

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Werthamer, N. Richard. „Play Strategies with Card Counting“. In Risk and Reward, 115–25. New York, NY: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0253-5_10.

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Werthamer, N. Richard. „Play Strategies with Card Counting“. In Risk and Reward, 133–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91385-8_10.

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Zutis, Krists, und Jesse Hoey. „Who’s Counting? Real-Time Blackjack Monitoring for Card Counting Detection“. In Lecture Notes in Computer Science, 354–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04667-4_36.

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Aalen, Odd O. „Counting Processes and Dynamic Modelling“. In Festschrift for Lucien Le Cam, 1–12. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-1880-7_1.

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Konferenzberichte zum Thema "Car counting"

Hubner, Yvonne, Phil Blythe, Graeme Hill, Myriam Neaimeh, John Austin, Liz Gray, Colin Herron und Josey Wardle. „49,999 electric car journeys and counting“. In 2013 World Electric Vehicle Symposium and Exhibition (EVS27). IEEE, 2013. http://dx.doi.org/10.1109/evs.2013.6914928.

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Xu, Pengyun, und Jigang Li. „Computer Assistance Image Processing Spores Counting“. In 2009 International Asia Conference on Informatics in Control, Automation and Robotics (CAR). IEEE, 2009. http://dx.doi.org/10.1109/car.2009.10.

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Huang, Jingxian, Guanchen Ding, Yujia Guo, Daiqin Yang, Sihan Wang, Tao Wang und Yunfei Zhang. „Drone-Based Car Counting via Density Map Learning“. In 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP). IEEE, 2020. http://dx.doi.org/10.1109/vcip49819.2020.9301785.

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Ming-Yee Chiu, R. Depommier und T. Spindler. „An embedded real-time vision system for 24-hour indoor/outdoor car-counting applications“. In Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. IEEE, 2004. http://dx.doi.org/10.1109/icpr.2004.1334536.

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Ouyang, Yueh, Samir Sahli, Yunlong Sheng und Daniel A. Lavigne. „Robust component-based car detection and counting in aerial imagery based on the mean-shift colour space clustering“. In SPIE Defense, Security, and Sensing, herausgegeben von Daniel J. Henry. SPIE, 2010. http://dx.doi.org/10.1117/12.852613.

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Denk, Marco, und Mark-M. Bakran. „Comparison of counting algorithms and empiric lifetime models to analyze the load-profile of an IGBT power module in a hybrid car“. In 2013 3rd International Electric Drives Production Conference (EDPC). IEEE, 2013. http://dx.doi.org/10.1109/edpc.2013.6689758.

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Suzgun, Mirac, Yonatan Belinkov, Stuart Shieber und Sebastian Gehrmann. „LSTM Networks Can Perform Dynamic Counting“. In Proceedings of the Workshop on Deep Learning and Formal Languages: Building Bridges. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/w19-3905.

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Fordham, John L. A., J. G. Bellis, David A. Bone und Timothy J. Norton. „MIC photon counting detector“. In Electronic Imaging '91, San Jose,CA, herausgegeben von Illes P. Csorba. SPIE, 1991. http://dx.doi.org/10.1117/12.44267.

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Nelson, Jacob T., Alexander R. Murphy, Julie S. Linsey, Matt R. Bohm und Robert L. Nagel. „A Function-Based Scoring Method for Evaluating Student Mental Models of Systems“. In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-86253.

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Mental models are loosely-defined constructs people form to reason and make predictions about their surroundings. These models are an important aspect of systems thinking for engineers, a concept that emphasizes holistic thinking when working with complex systems which is increasingly important in multiple engineering disciplines. Methods to evaluate systems thinking and mental models of systems traditionally rely on questionnaires, or detailed interactive simulations of specific processes. This work presents a method based on functional modules for evaluating student responses to an instrument based on Lawson’s bicycle problem, intended to elicit students’ mental models of two systems. Students were given a simple outline of the two systems, a hair dryer and a car radiator, and were prompted to fill and label the components required for the system to fulfil the functionality described. This was done in two sessions, once before learning functional modeling, and once after, to utilize the method of scoring to evaluate any changes in their mental models due to exposure to functional modeling. The scoring method identifies common functional modules between two systems using Module Heuristics, and then identifies students’ recognition of those modules. This allows a direct comparison of the functional similarity between the two systems identified by the students and can capture a wider variety of correct answers than simply counting the components a student provides.

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Ma, Hao, Baoqun Yin, Luyang Wang und Hao Shi. „Crowd counting on still images with fully convolutional network“. In 2017 Chinese Automation Congress (CAC). IEEE, 2017. http://dx.doi.org/10.1109/cac.2017.8242980.

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Berichte der Organisationen zum Thema "Car counting"

Chipman, Dana K. Countering Terrorism in the Heartland -- Can We Afford Posse Comitatus Any Longer? Fort Belvoir, VA: Defense Technical Information Center, April 2003. http://dx.doi.org/10.21236/ada415647.

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Ostoja, Steven, Tapan Pathak, Katherine Jarvis-Shean, Mark Battany und George Zhuang. Adapt - On-farm changes in the face of climate change: NRCS Area 3. USDA California Climate Hub, April 2018. http://dx.doi.org/10.32747/2018.7444387.ch.

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The agricultural economy is more vulnerable to projected changes in climate in some California counties than in others. This flyer highlights on-farm adaptation strategies to mitigate some of the effects of increased winter temperatures and more frequent summer heatwaves. Projected conditions will put the most strain on heat intolerant crops and crops with high chill requirements. When crops with these characteristics also have a high market value or are grown in large acreage, counties can be at risk for economic declines. Information on this flyer identifies the most vulnerable counties in California Area 3 for some key, climate-sensitive crops.

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Ostoja, Steven, Tapan Pathak, Katherine Jarvis-Shean und Mark Battany. Adapt - On-farm changes in the face of climate change: NRCS Area 1. USDA California Climate Hub, April 2018. http://dx.doi.org/10.32747/2018.7444389.ch.

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Ostoja, Steven, Tapan Pathak, Andre S. Biscaro und Mark Battany. Adapt - On-farm changes in the face of climate change: NRCS area 4. USDA California Climate Hub, April 2018. http://dx.doi.org/10.32747/2018.7435379.ch.

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Ostoja, Steven, Tapan Pathak, Katherine Jarvis-Shean, Mark Battany und Andre S. Biscaro. Adapt - On-farm changes in the face of climate change: NRCS Area 2. USDA California Climate Hub, April 2018. http://dx.doi.org/10.32747/2018.7444388.ch.

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Papier, Leesa J. Countering Propaganda in the Global War on Terrorism: What can a Democracy do? Fort Belvoir, VA: Defense Technical Information Center, Mai 2008. http://dx.doi.org/10.21236/ada531946.

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Wraight, Sarah, Julia Hofmann, Justine Allpress und Brooks Depro. Environmental justice concerns and the proposed Atlantic Coast Pipeline route in North Carolina. RTI Press, März 2018. http://dx.doi.org/10.3768/rtipress.2018.mr.0037.1803.

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This report describes publicly available data sets and quantitative analysis that local communities can use to evaluate environmental justice concerns associated with pipeline projects. We applied these data and analytical methods to two counties in North Carolina (Northampton and Robeson counties) that would be affected by the proposed Atlantic Coast Pipeline (ACP). We compared demographic and vulnerability characteristics of census blocks, census block groups, and census tracts that lie within 1 mile of the proposed pipeline route with corresponding census geographies that lie outside of the 1-mile zone. Finally, we present results of a county-level analysis of race and ethnicity data for the entire North Carolina segment of the proposed ACP route. Statistical analyses of race and ethnicity data (US Census Bureau) and Social Vulnerability Index scores (University of South Carolina’s Hazards & Vulnerability Research Institute) yielded evidence of significant differences between the areas crossed by the pipeline and reference geographies. No significant differences were found in our analyses of household income and cancer risk data.

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Anderson, Andrew, und Mark Yacucci. Inventory and Statistical Characterization of Inorganic Soil Constituents in Illinois: Appendices. Illinois Center for Transportation, Juni 2021. http://dx.doi.org/10.36501/0197-9191/21-007.

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This report presents detailed histograms of data from the Regulated Substances Library (RSL) developed by the Illinois Department of Transportation (IDOT). RSL data are provided for state and IDOT region, IDOT district, and county spatial subsets to examine the spatial variability and its relationship to thresholds defining natural background concentrations. The RSL is comprised of surficial soil chemistry data obtained from rights-of-way (ROW) subsurface soil sampling conducted for routine preliminary site investigations. A selection of 22 inorganic soil analytes are examined in this report: Al, Sb, As, Ba, Be, Cd, Ca, Cr, Co, Cu, Fe, Pb, Mg, Mn, Hg, Ni, K, Se, Na, Tl, V, and Zn. RSL database summary statistics, mean, median, minimum, maximum, 5th percentile, and 95th percentile, are determined for Illinois counties and for recognized environmental concern, non-recognized environmental concern, and de minimis site contamination classifications.

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Scrivens, Ryan, Steven M. Chermak, Joshua D. Freilich, Thomas W. Wojciechowski und Richard Frank. Detecting Extremists Online: Examining Online Posting Behaviors of Violent and Non-Violent Right-Wing Extremists. RESOLVE Network, September 2021. http://dx.doi.org/10.37805/pn2021.21.remve.

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Like most of us, violent extremists often leave a digital footprint behind. Researchers, practitioners, and policymakers raise questions about whether violent individuals can be identified online prior to their attacks offline based on their online posting behaviors. Despite ongoing concerns, few empirically grounded analyses have identified which online users have engaged in violent extremism offline and then assessed their digital footprints, and fewer analyses have identified differences in posting behaviors of those who share extreme ideological beliefs but are violent or non-violent in the offline world. This policy note highlights the importance of both identifying and examining the online behaviors of violent and non-violent extremists in preventing and countering violent extremism (P/CVE) and provides researchers, practitioners, and policymakers with a number of recommendations for detecting and analyzing the online behaviors of violent and non-violent extremists in the future.

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Gomez Garcia, Olga, Henry Mooney, David Rosenblatt, Maria Alejandra Zegarra, Gralyn Frazier, Ariel McCaskie, Victor Gauto et al. Caribbean Quarterly Bulletin: Volume 10: Issue 1, May 2021. Inter-American Development Bank, Mai 2021. http://dx.doi.org/10.18235/0003265.

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Countries around the world have endured over a year of extreme uncertainty in the context of the COVID-19 crisis, and economies in the Caribbean have suffered more than most. But with the increasing availability of vaccines and prospects for a resumption of international travel, light is emerging at the end of the Pandemic tunnel. With this in mind, The Inter-American Development Bank Caribbean1 Departments most recent Quarterly Bulletin reviews the latest available information regarding the crisis impacts on citizens, their economies, and key factors that will determine the speed and depth of recovery. As also discussed in previous editions, prospects for tourism-dependent economies will depend heavily on vaccine penetration and border normalization in source countries particularly the United States and Western Europe, while commodity-intensive economies could benefit from upward revisions to global demand growth estimates. All countries in the region can do much to support a rapid recovery through forward-looking policies aimed at ensuring they are well positioned to take advantage of post-Pandemic preferences with respect to travel and tourism, services trade, and investment. Our latest report considers these issues, what may lie ahead, and how counties can best position themselves for a recovery in 2021 and beyond.

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