Relevant bibliographies by topics / Sensors selection

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Sensors selection'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Sensors selection"

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Wijaya, Tomi, Wahyu Caesarendra, Tegoeh Tjahjowidodo, Bobby K. Pappachan, Arthur Wee, and Muhammad Izzat Roslan. "A Review on Sensors for Real-time Monitoring and Control Systems on Machining and Surface Finishing Processes." MATEC Web of Conferences 159 (2018): 02034. http://dx.doi.org/10.1051/matecconf/201815902034.

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One of the key components in real-time monitoring and control on machining and surface finishing processes are sensors. The advances of such system have triggered interesting questions on sensor selection that act as the fundamental before starting a project. This paper is made to review and answer the questions surrounding sensor selection. The paper first explains on the type of sensors commonly used in practice for real-time monitoring and control systems. After which, the paper discusses on how often the sensors are used on several machining and surface finishing processes and what are the
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Juboor, Saed Sa’deh, Sook-Ling Chua, and Lee Kien Foo. "Informative sensor selection on clustered sensors." Journal of Physics: Conference Series 1192 (March 2019): 012057. http://dx.doi.org/10.1088/1742-6596/1192/1/012057.

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Wentao, Shi, Chen Dong, Zhou Lin, Bai Ke, and Jin Yong. "Sensor Selection Scheme considering Uncertainty Disturbance." Journal of Sensors 2022 (February 16, 2022): 1–11. http://dx.doi.org/10.1155/2022/2488907.

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In multisensor cooperative detection network, some random disturbances, energy carried by sensor, distance between target and sensor node, and so on all affect the sensor selection scheme. To effectively select some sensors for detecting the target, a novel sensor selection method considering uncertainty disturbance is proposed under constraints of estimation accuracy and energy consumption. Firstly, the sensor selection problem is modeled as a binary form optimization problem with a penalty term to minimize the number of sensors. Secondly, some factors (precision, energy, and distance, etc.)
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Reeves, J., R. Remenyte-Prescott, and J. Andrews. "Sensor selection for fault diagnostics using performance metric." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 233, no. 4 (2018): 537–52. http://dx.doi.org/10.1177/1748006x18804690.

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As technology advances, modern systems are becoming increasingly complex, consisting of large numbers of components, and therefore large numbers of potential component failures. These component failures can result in reduced system performance, or even system failure. The system performance can be monitored using sensors, which can help to detect faults and diagnose failures present in the system. However, sensors increase the weight and cost of the system, and therefore, the number of sensors may be limited, and only the sensors that provide the most useful system information should be select
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Abbas, Jabbar, Amin Al-Habaibeh, and Dai Zhong Su. "Sensor Fusion for Condition Monitoring System of End Milling Operations." Key Engineering Materials 450 (November 2010): 267–70. http://dx.doi.org/10.4028/www.scientific.net/kem.450.267.

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This paper describes the utilisation of multi sensor fusion model using force, vibration, acoustic emission, strain and sound sensors for monitoring tool wear in end milling operations. The paper applies the ASPS approach (Automated Sensor and Signal Processing Selection) method for signal processing and sensor selection [1]. The sensory signals were processed using different signal processing methods to create a wide range of Sensory Characteristic Features (SCFs). The sensitivity of these SCFs to tool wear is investigated. The results indicate that the sensor fusion system is capable of dete
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Kulkarni, Amol, Janis Terpenny, and Vittaldas Prabhu. "Sensor Selection Framework for Designing Fault Diagnostics System." Sensors 21, no. 19 (2021): 6470. http://dx.doi.org/10.3390/s21196470.

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In a world of rapidly changing technologies, reliance on complex engineered systems has become substantial. Interactions associated with such systems as well as associated manufacturing processes also continue to evolve and grow in complexity. Consider how the complexity of manufacturing processes makes engineered systems vulnerable to cascading and escalating failures; truly a highly complex and evolving system of systems. Maintaining quality and reliability requires considerations during product development, manufacturing processes, and more. Monitoring the health of the complex system while
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Mehmood, Zahid, Ibraheem Haneef, and Florin Udrea. "Material selection for optimum design of MEMS pressure sensors." Microsystem Technologies 26, no. 9 (2019): 2751–66. http://dx.doi.org/10.1007/s00542-019-04601-1.

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Abstract Choice of the most suitable material out of the universe of engineering materials available to the designers is a complex task. It often requires a compromise, involving conflicts between different design objectives. Materials selection for optimum design of a Micro-Electro-Mechanical-Systems (MEMS) pressure sensor is one such case. For optimum performance, simultaneous maximization of deflection of a MEMS pressure sensor diaphragm and maximization of its resonance frequency are two key but totally conflicting requirements. Another limitation in material selection of MEMS/Microsystems
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Chodorek, Agnieszka, Robert Ryszard Chodorek, and Paweł Sitek. "Response Time and Intrinsic Information Quality as Criteria for the Selection of Low-Cost Sensors for Use in Mobile Weather Stations." Electronics 11, no. 15 (2022): 2448. http://dx.doi.org/10.3390/electronics11152448.

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Smart-city management systems use information about the environment, including the current values of weather factors. The specificity of the urban sites requires a high density of weather measurement points, which forces the use of low-cost sensors. A typical problem of devices using low-cost sensors is the lack of legalization of the sensors and the resulting inaccuracy and uncertainty of measurement, which one can attempt to solve by additional sensor calibration. In this paper, we propose a different approach to this problem, i.e., the two-stage selection of sensors, carried out on the basi
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Su, Shen, Yanbin Sun, Xiangsong Gao, Jing Qiu, and Zhihong Tian. "A Correlation-Change Based Feature Selection Method for IoT Equipment Anomaly Detection." Applied Sciences 9, no. 3 (2019): 437. http://dx.doi.org/10.3390/app9030437.

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Selecting the right features for further data analysis is important in the process of equipment anomaly detection, especially when the origin data source involves high dimensional data with a low value density. However, existing researches failed to capture the fact that the sensor data are usually correlated (e.g., duplicated deployed sensors), and the correlations would be broken when anomalies occur with happen to the monitored equipment. In this paper, we propose to capture such sensor data correlation changes to improve the performance of IoT (Internet of Things) equipment anomaly detecti
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Guan, Fei, Wei-Wei Cui, Lian-Feng Li, and Jie Wu. "A Comprehensive Evaluation Method of Sensor Selection for PHM Based on Grey Clustering." Sensors 20, no. 6 (2020): 1710. http://dx.doi.org/10.3390/s20061710.

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Sensor selection plays an essential and fundamental role in prognostics and health management technology, and it is closely related to fault diagnosis, life prediction, and health assessment. The existing methods of sensor selection do not have an evaluation standard, which leads to different selection results. It is not helpful for the selection and layout of sensors. This paper proposes a comprehensive evaluation method of sensor selection for prognostics and health management (PHM) based on grey clustering. The described approach divides sensors into three grey classes, and defines and quan
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Dissertations / Theses on the topic "Sensors selection"

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Jean, Paul Bambanza. "iSEE:A Semantic Sensors Selection System for Healthcare." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-59635.

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The massive use of Internet-based connectivity of devices such as smartphones and sensors has led to the emergence of Internet of Things(IoT). Healthcare is one of the areas that IoT-based applications deployment is becoming more successful. However, the deployment of IoT in healthcare faces one major challenge, the selection of IoT devices by stakeholders (for example, patients, caregivers, health professionals and other government agencies) given an amount of available IoT devices based on a disease(for ex-ample, Asthma) or various healthcare scenarios (for example, disease management, preve
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De, Mel Geeth R. "Intelligent resource selection for sensor-task assignment : a knowledge-based approach." Thesis, University of Aberdeen, 2014. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=215104.

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Today, sensing resources play a crucial role in the success of critical tasks such as border monitoring and surveillance. Although there are various types of resources available, each with different capabilities, only a subset of these resources are useful for a specific task. This is due to the dynamism in tasks' environment and the heterogeneity of the resources. Thus, an effective mechanism to select resources for tasks is needed so that the selected resources cater for the needs of the tasks. Though a considerable amount of research has already been done in different communities to efficie
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Riedmann, Michael. "Band selection using hyperspectral data from airborne and satellite sensors." Thesis, University of Southampton, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.398728.

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Ferré, Baldrich Joan. "Experimental design applied to the selection of samples and sensors in multivariate calibration." Doctoral thesis, Universitat Rovira i Virgili, 1998. http://hdl.handle.net/10803/9020.

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Els models de calibratge multivariant relacionen respostes instrumentals (per exemple, espectres) d'un conjunt de mostres de calibratge amb quantitats de variables físiques o químiques tals com concentració d'analit, o índexs (per exemple, el nombre d'octà en gasolines). Aquesta relació es fa servir per predir aquestes quantitats a partir de les respostes instrumentals de noves mostres desconegudes, mesurades de la mateixa manera. <br/><br/>La predicció emprant models de calibratge multivariants està esdevenint un pas comú en els procediments analítics. Per tant, l'habilitat del model de donar
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Johnson, Jeremy Ryan. "Fault propagation timing analysis to aid in the selection of sensors for health management systems." Diss., Rolla, Mo. : University of Missouri--Rolla i.e. [Missouri University of Science and Technology], 2008. http://scholarsmine.mst.edu/thesis/pdf/Johnson_09007dcc804bcda7.pdf.

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Thesis (M.S.)--Missouri University of Science and Technology, 2008.<br>Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed May 19, 2008) Degree granted by Missouri University of Science and Technology, formerly known as University of Missouri--Rolla. Includes bibliographical references (p. 39-41).
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Polyzos, Dimitrios. ""Measuring System Properties & Structured Diagnostics for the Selection of Sensors, Actuators Placement & Eigenstructure Assignment"." Thesis, City University London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.524712.

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Akpolat, Hacer. "Improvement of Tomato Breeding Selection Capabilities using Vibrational Spectroscopy and Prediction Algorithms." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574812034661898.

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Lei, Hua. "Modeling and Data Analysis of Conductive Polymer Composite Sensors." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1577.pdf.

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Segal, Aleksandr V. "Iterative Local Model Selection for tracking and mapping." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:8690e0e0-33c5-403e-afdf-e5538e5d304f.

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The past decade has seen great progress in research on large scale mapping and perception in static environments. Real world perception requires handling uncertain situations with multiple possible interpretations: e.g. changing appearances, dynamic objects, and varying motion models. These aspects of perception have been largely avoided through the use of heuristics and preprocessing. This thesis is motivated by the challenge of including discrete reasoning directly into the estimation process. We approach the problem by using Conditional Linear Gaussian Networks (CLGNs) as a generalization o
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Martins, Juliano Araújo. "Dados hiperespectrais para predição do teor foliar de nitrogênio em cana-de-açúcar." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/11/11152/tde-03052016-191304/.

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Uma das alternativas bastante abordada na literatura para a melhoria do gerenciamento da adubação nitrogenada nas culturas é o sensoriamento remoto, tendo destaque a utilização de sensores espectrais na região do visível e infravermelho. Neste trabalho, buscou-se estabelecer as relações existentes entre variações no teor foliar de nitrogênio (TFN) e a resposta espectral da folha de cana-de-açúcar, utilizando um sensor hiperespectral, com avaliações em três áreas experimentais do estado de São Paulo, com diferentes solos e variedades. Cada experimento foi alocado em blocos ao acaso, com parcela
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Books on the topic "Sensors selection"

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Juds, Scott M. Photoelectric sensors and controls: Selection and application. M. Dekker, 1988.

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Norton, Harry N. Sensor and transducer selection guide. Elsevier Advanced Technology, 1990.

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Ryan, Margaret A., Abhijit V. Shevade, Charles J. Taylor, M. L. Homer, Mario Blanco, and Joseph R. Stetter, eds. Computational Methods for Sensor Material Selection. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-73715-7.

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Suzuki, Yasuo. Preparation and application of ion sensors. Meiji Daigaku Kagaku Gijutsu Kenkyūjo, 1987.

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Gaver, Donald Paul. Asymptotic properties of a sensor allocation model. Naval Postgraduate School, 1995.

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Russotti, J. S. Sensor-operated headset selection for Virginia class submarine consoles (C3I). Naval Submarine Medical Research Laboratory, 2001.

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Coșofreț, Vasile V. Pharmaceutical applications of membrane sensors. CRC Press, 1992.

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Drost, Ulrich C. Sensory-motor coupling in musicians. Cuvillier Verlag, 2005.

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Electroanalysis na h'Éireann (International Conference) (1986 Dublin). Electrochemistry, sensors and analysis: Proceedings of the International Conference "Electroanalysis na h'Éireann", Dublin, Ireland, June 10-12, 1986. Elsevier, 1986.

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Tracey, West. 5 senses: Ready-to-go activities, games, literature selections, poetry, and everything you need for a complete theme unit. Scholastic Professional Books, 1997.

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Book chapters on the topic "Sensors selection"

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Van Steenkiste, Régis J., and George S. Springer. "Sensor selection." In Strain and Temperature Measurement with Fiber Optic Sensors. CRC Press, 2025. https://doi.org/10.1201/9781003578994-39.

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Sajid, Memoon, Jahan Zeb Gul, and Kyung Hyun Choi. "Selection of Sensors, Transducers, and Actuators." In Functional Reverse Engineering of Machine Tools. CRC Press, 2019. http://dx.doi.org/10.1201/9780429022876-3.

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Olthuis, W., S. Böhm, G. R. Langereis, and P. Bergveld. "Selection in System and Sensor." In Chemical and Biological Sensors for Environmental Monitoring. American Chemical Society, 2000. http://dx.doi.org/10.1021/bk-2000-0762.ch005.

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Gölz, Jacqueline, and Christian Hatzfeld. "Sensor Design." In Springer Series on Touch and Haptic Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04536-3_10.

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AbstractMultiple sensors are applied in haptic devices designs. Even if they are not closed-loop controlled in a narrow sense of force or torque generation, they are used to detect movement ranges and limits or the detection of the presence of a user and its type of interaction with an object or human-machine-interface (HMI). Almost any type of technical sensor had been applied in the context of haptic devices. The emerging market of gesture based user interaction and integration of haptics due to ergonomic reasons extends the range of sensors potentially relevant for haptic devices. However,
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Best, Lincoln, Ernest Foo, Hui Tian, and Zahra Jadidi. "Client Selection Frameworks Within Federated Machine Learning: The Current Paradigm." In Smart Sensors, Measurement and Instrumentation. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-29845-5_3.

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Leschke, André. "Second Degree of Freedom: Selection of Sensors." In Algorithm Concept for Crash Detection in Passenger Cars. Springer Fachmedien Wiesbaden, 2020. http://dx.doi.org/10.1007/978-3-658-29392-5_10.

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Ben Said, Ahmed, Abdelkarim Erradi, Azadeh Gharia Neiat, and Athman Bouguettaya. "Mobile Crowdsourced Sensors Selection for Journey Services." In Service-Oriented Computing. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03596-9_33.

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Xu, Li, Xia Luo, and Huanzhu Wang. "Efficient Cluster Head Selection for Multimode Sensors in Wireless Sensor Network." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-67514-1_8.

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Pirttikangas, Susanna, Kaori Fujinami, and Tatsuo Nakajima. "Feature Selection and Activity Recognition from Wearable Sensors." In Ubiquitous Computing Systems. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890348_39.

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Subramanian, Arun, Kishan G. Mehrotra, Chilukuri K. Mohan, Pramod K. Varshney, and Thyagaraju Damarla. "Feature Selection and Occupancy Classification Using Seismic Sensors." In Trends in Applied Intelligent Systems. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13025-0_62.

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Conference papers on the topic "Sensors selection"

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Zhang, Zishi, Ye Yuan, Lei Zhu, Jing He, and Wei Yi. "Node Selection for Asynchronous Multi-Target Tracking in Heterogeneous Sensor Networks." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10785115.

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Ettelt, Dirk, Nicolas Dupré, Jeroen Didden, Théo Le Signor, and Gaël Close. "Dynamic Error Reduction in Soft Tactile Sensors by Optimum Material Selection." In 2024 IEEE SENSORS. IEEE, 2024. https://doi.org/10.1109/sensors60989.2024.10785032.

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Sun, Xiaodong. "Online Monitoring of Undercoating Corrosions Utilizing Coupled Multielectrode Sensors." In CORROSION 2004. NACE International, 2004. https://doi.org/10.5006/c2004-04033.

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Abstract Online monitoring of carbon steel corrosion under different commercial coatings was conducted, utilizing coupled multielectrode sensors. The experimental results showed that the coupled multielectrode corrosion sensor is an effective tool for detecting initial defects and real-time degradation of the coatings. Because of their high sensitivity, the coupled multielectrode sensors may also be used as a quick and convenient tool for optimizing the selection of proper coatings for different applications.
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Wendt, James B., and Miodrag Potkonjak. "Medical diagnostic-based sensor selection." In 2011 IEEE Sensors. IEEE, 2011. http://dx.doi.org/10.1109/icsens.2011.6127188.

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Khokhlov, Igor, Akshay Pudage, and Leon Reznik. "Sensor Selection Optimization with Genetic Algorithms." In 2019 IEEE SENSORS. IEEE, 2019. http://dx.doi.org/10.1109/sensors43011.2019.8956579.

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Chuprov, Sergei, Leon Reznik, Igor Khokhlov, and Karan Manghi. "Multi-Modal Sensor Selection with Genetic Algorithms." In 2022 IEEE Sensors. IEEE, 2022. http://dx.doi.org/10.1109/sensors52175.2022.9967296.

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Sowers, T. Shane, George Kopasakis, and Donald L. Simon. "Application of the Systematic Sensor Selection Strategy for Turbofan Engine Diagnostics." In ASME Turbo Expo 2008: Power for Land, Sea, and Air. ASMEDC, 2008. http://dx.doi.org/10.1115/gt2008-50525.

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The data acquired from available system sensors forms the foundation upon which any health management system is based, and the available sensor suite directly impacts the overall diagnostic performance that can be achieved. While additional sensors may provide improved fault diagnostic performance there are other factors that also need to be considered such as instrumentation cost, weight, and reliability. A systematic sensor selection approach is desired to perform sensor selection from a holistic system-level perspective as opposed to performing decisions in an ad hoc or heuristic fashion. T
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Severini, Fabio, Vincenzo Sesta, Francesca Madonini, Alfonso Incoronato, Federica Villa, and Franco Zappa. "dTOF SPAD array with Region-Of-Interest selection and dynamic TDC routing." In Optical Sensors. OSA, 2021. http://dx.doi.org/10.1364/sensors.2021.sf1a.6.

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Nemarich, Christopher P., Henry R. Hegner, and Marjorie Ann E. Natishan. "The Selection of Diagnostic Technologies and Sensors for Condition Based Maintenance Systems." In ASME 1996 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/imece1996-0865.

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Abstract The effective implementation of Condition Based Maintenance (CBM) systems generally requires the use of sensors selected specifically to detect, isolate and diagnose machinery component faults. In order for CBM systems to operate reliably, the diagnostic technologies and sensors used to monitor the machinery must provide repeatable and accurate measurements. The ability of a CBM system to effectively detect and correctly identify component faults at their inception depends largely on the appropriate selection of the fault parameters to be measured and the sensors used to measure them.
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Arar, Malath I. "Gas Turbine Corrected Parameters Control: Humidity Correction – Sensors Evaluation and Selection." In ASME Turbo Expo 2002: Power for Land, Sea, and Air. ASMEDC, 2002. http://dx.doi.org/10.1115/gt2002-30047.

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Gas Turbine, GT, control methodology applied to power generation is being evaluated. Corrected parameter control methodology has been adopted for this purpose. This method uses the corrected physical ambient conditions such as pressure, temperature and humidity in controlling the GT operations. Humidity correction becomes increasingly important in this control scheme. The following are the reasons for accurate and robust humidity measurement: (1) Humidity measurement is important to the operation control of the dry low NOX, DLN, combustor system. (2) GT inlet performance enhancing devices, suc
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Reports on the topic "Sensors selection"

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Ratmanski, Kiril, and Sergey Vecherin. Resilience in distributed sensor networks. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45680.

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With the advent of cheap and available sensors, there is a need for intelligent sensor selection and placement for various purposes. While previous research was focused on the most efficient sensor networks, we present a new mathematical framework for efficient and resilient sensor network installation. Specifically, in this work we formulate and solve a sensor selection and placement problem when network resilience is also a factor in the optimization problem. Our approach is based on the binary linear programming problem. The generic formulation is probabilistic and applicable to any sensor
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Hegarty-Craver, Meghan, Hope Davis-Wilson, Pooja Gaur, Howard Walls, David Dausch, and Dorota Temple. Wearable Sensors for Service Members and First Responders: Considerations for Using Commercially Available Sensors in Continuous Monitoring. RTI Press, 2024. http://dx.doi.org/10.3768/rtipress.2024.op.0090.2402.

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Wearable sensors (“wearables”) provide a mechanism to monitor the health of service members and first responders continuously and remotely. Several wearables are commercially available, with different configurations, sensors, algorithms, and forms of communication. Choosing the “best” wearable depends on the information you need to make decisions, how often you need this information, and the level of accuracy required. In this article, we review six use cases for wearables that are relevant to the military and first responders. We examine the metrics measured and the wearables used. We conclud
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Guo, Ge, Jiageng Liu, and Guangheng Liu. Multi-sensor Fusion-based Vehicle Localization. SAE International, 2024. http://dx.doi.org/10.4271/epr2024023.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;Multi-sensor fusion (MSF) is believed to be a promising tool for vehicular localization in urban environments. Due to the differences in principles and performance of various onboard vehicle sensors, MSF inevitably suffers from heterogeneous sources and vulnerability to cyber-attacks. Therefore, an essential requirement of MSF is the capability of providing a consumer-grade solution that operates in real-time, is accurate, and immune to abnormal conditions with guaranteed performance and quality of service for location-b
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Shavlik, Jude. Selection, Combination, and Evaluation of Effective Software Sensors for Detecting Abnormal Usage of Computers Running Windows NT/2000. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada406316.

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Sonmez Turan, Meltem. Ascon-Based Lightweight Cryptography Standards for Constrained Devices. National Institute of Standards and Technology, 2025. https://doi.org/10.6028/nist.sp.800-232.

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In 2023, the National Institute of Standards and Technology (NIST) announced the selection of the Ascon family of algorithms designed by Dobraunig, Eichlseder, Mendel, and Schläffer to provide efficient cryptographic solutions for resource-constrained devices. This decision emerged from a rigorous, multi-round lightweight cryptography standardization process. The Ascon family includes a suite of cryptographic primitives that provide Authenticated Encryption with Associated Data (AEAD), hash function, and eXtendable Output Function (XOF) capabilities. The Ascon family is characterized by lightw
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Olsen. PR-179-07200-R01 Evaluation of NOx Sensors for Control of Aftertreatment Devices. Pipeline Research Council International, Inc. (PRCI), 2008. http://dx.doi.org/10.55274/r0010985.

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Emissions reduction through exhaust aftertreatment is becoming more common. It is likely to play an important role in meeting new emissions regulations in the future. Currently, the predominate aftertreatment technology for NOX reduction in lean burn natural gas engines appears to be selective catalytic reduction (SCR). In SCR, a reducing agent is injected into the exhaust upstream of a catalyst. Supplying the optimal quantity of reagent is critical to effective application of SCR. If too little reagent is supplied then the NOx reduction efficiency may be too low. If too much reagent is provid
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Solanki, Pranshoo, Haiyan Xie, John Awaitey, and Tejaswi Reddy. State-of-the-Practice Review of Field-Curing Methods for Evaluating the Strength of Concrete Test Specimens. Illinois Center for Transportation, 2023. http://dx.doi.org/10.36501/0197-9191/23-003.

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The American Association of State Highway and Transportation Officials (AASHTO) T 23 standard provides instructions for making and curing concrete test specimens in the field. However, further research is needed to compare the strength of the field-cured specimen with the strength of the actual in-place concrete item. The purpose of this research is to build an understanding of the current state of the practice for field-curing methods. Specifically, the research team conducted a literature review and questionnaire survey to identify the selection criteria and details of field-curing methods.
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Nenoff, Tina M., and Leo J. Small. Tunable Impedance Spectroscopy Sensors via Selective Nanoporous Materials. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1396079.

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Allendorf, Mark D., Aaron Michael Katzenmeyer, Vitalie Stavilla, et al. Selective stress-based microcantilever sensors for enhanced surveillance. Office of Scientific and Technical Information (OSTI), 2012. http://dx.doi.org/10.2172/1057255.

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Beebe, Kenneth R., and Bruce R. Kowalski. Wavelength or Sensor Selection by Minimization of Prediction Error. Defense Technical Information Center, 1988. http://dx.doi.org/10.21236/ada197231.

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