Relevant bibliographies by topics / Detection/location

Contents

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

Academic literature on the topic 'Detection/location'

Author: Grafiati
Published: 26 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Detection/location"

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Baidari, Dr Ishwar, and S. P. Sajjan. "Location Based Crime Detection Using Data Mining." Bonfring International Journal of Software Engineering and Soft Computing 6, Special Issue (October 31, 2016): 208–12. http://dx.doi.org/10.9756/bijsesc.8279.

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Decker, Brooke K., and Tara N. Palmore. "Waterborne Pathogen Detection More than Just “Location, Location, Location…”." Infection Control & Hospital Epidemiology 35, no. 2 (February 2014): 130–31. http://dx.doi.org/10.1086/675067.

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Yinsen Luan, Yinsen Luan, Bing Xu Bing Xu, Ping Yang Ping Yang, and and Guomao Tang and Guomao Tang. "Optic flaws detection and location based on a plenoptic camera." Chinese Optics Letters 15, no. 4 (2017): 041102–41106. http://dx.doi.org/10.3788/col201715.041102.

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Astley, Kenneth Richard. "Bearing anomaly detection and location." Journal of the Acoustical Society of America 122, no. 3 (2007): 1313. http://dx.doi.org/10.1121/1.2781411.

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Raheja, J. L., Ankit Chaudhary, and Shobhit Maheshwari. "Hand gesture pointing location detection." Optik 125, no. 3 (February 2014): 993–96. http://dx.doi.org/10.1016/j.ijleo.2013.07.167.

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Hassoubah, Rawan S., Suhare M. Solaiman, and Manal A. Abdullah. "Intrusion Detection of Hello Flood Attack in WSNs Using Location Verification Scheme." International Journal of Computer and Communication Engineering 4, no. 3 (2015): 156–65. http://dx.doi.org/10.17706/ijcce.2015.4.3.156-165.

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Ko, Daijin, and Judith E. Zeh. "Detection of Migration Using Sound Location." Biometrics 44, no. 3 (September 1988): 751. http://dx.doi.org/10.2307/2531589.

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Schieferdecker, Dennis. "Location-Free Detection of Network Boundaries." ACM Transactions on Sensor Networks 11, no. 4 (December 23, 2015): 1–40. http://dx.doi.org/10.1145/2795232.

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Ray, S., D. Starobinski, A. Trachtenberg, and R. Ungrangsi. "Robust Location Detection With Sensor Networks." IEEE Journal on Selected Areas in Communications 22, no. 6 (August 2004): 1016–25. http://dx.doi.org/10.1109/jsac.2004.830895.

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Ray, S., Wei Lai, and I. C. Paschalidis. "Statistical location detection with sensor networks." IEEE Transactions on Information Theory 52, no. 6 (June 2006): 2670–83. http://dx.doi.org/10.1109/tit.2006.874376.

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Dissertations / Theses on the topic "Detection/location"

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Luo, Anqi, and Lei Ge. "Indoor Location Detection using WLAN." Thesis, KTH, Kommunikationssystem, CoS, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-91200.

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The thesis seeks to improve the accuracy of indoor wireless local area network (WLAN) location detection. The main task of the project is the design and analysis of a solution, which utilizes the packets which are already emitted by WLAN devices. The system consists of a signal receiver and signal processing. The positioning system does not transmit, thus the detection is completely passive. The result of measurements on received frames is used to calculate the WLAN transmitter's position. It does not require any transmissions, thus the detection is completely passive. The result of the measurements can be used to calculate the WLAN transmitter’s position. Location systems are more and more viewed as a necessary element of a WLAN system. Positioning accuracy is the most important issue in location system, especial in the indoor WLAN location detection. Indoor location systems are affected by indoor environment both due to multi-path and man-made effects. To resist these problems, we introduce a way to detect the arrival of the first instance of the signal by detecting the signal header. In our experiment, we timestamp the arrival of an IEEE 802.11b header. In our prototype the logic necessary to do this is implemented in an FPGA, specifically that of the Ettus Research USRP. The additional logic is quite small and might easily be added to the receiver in an access point, thus reducing the deployment cost of a location system in a real network. The proposed solution was experimentally verified. From our experiments, the detection works without requiring any changes to the hardware or software of the mobile device. By exploiting existing IEEE 802.11b transmissions the cost and difficulty of deployment is simplified due to the wide usage of IEEE 802.11b in mobile devices. Additionally, the preamble has good correlation properties making it is easy to detect the arrival of a IEEE 802.11frame. Our implementation is based upon open source hardware and software making it possible to implement this solution. A relatively low cost FPGA can be used as the correlation and timestamp circuit is rather simple (in terms of numbers of gates), making this solution feasible for commercial implementation. The method, implementation, testing, and analysis are presented in detail in the thesis.
Avhandlingen syftar till att förbättra noggrannheten i inomhus trådlösa lokala nätverk (WLAN) placering upptäckt. Huvuduppgiften för projektet är design och analys av en lösning som utnyttjar paketen som redan avges av WLAN-enheter. Systemet består av en signal mottagare och signalbehandling. Det kräver inga transmissioner, alltså upptäckt är helt passiv. Resultatet av mätningarna kan användas för att beräkna WLAN-sändarens läge. Målet är att förbättra noggrannheten i inomhus plats uppskattning. Läge system alltmer ses som en nödvändig del av WLAN system. Positioneringsnoggrannheten ses som den viktigaste frågan i läge system, speciellt för inomhusbruk WLAN baserade location. Läge system påverkas mer av inomhusmiljöer än utemiljön, eftersom det finns mer multi-path fading och konstgjorda effekter. Att minska dessa problem, vi införa ett sätt att känna av signalen ankomst genom att förbättra upptäckten av ankomsten av IEEE 802.11-huvudet. Detta kan bidra till att besegra multipath effekt och enkla metoden skulle kunna minska kostnaderna för placering i framtiden kopplingspunkter. Den föreslagna lösningen har verifierats experimentellt. Från vårt experiment fungerar upptäckt utan att kräva några ändringar i hårdvara eller mjukvara för den mobila enheten. Genom att utnyttja befintliga IEEE 802.11b sändningar kostnaden och svårigheten att utbyggnaden är förenklad på grund av den breda användningen av IEEE 802.11b i mobila enheter. Dessutom "preamble" har god korrelation egenskaper som gör det lätt att upptäcka ankomsten av en IEEE 802.11-ramen. Vår genomfört bygger på öppen källkod maskin-och programvara som gör det möjligt att genomföra denna lösning. En relativt låg kostnad FPGA kan användas som korrelation och tidstämpel kretsen är ganska enkel (i termer av antalet logikelement), vilket gör denna lösning vara möjlig för kommersiell tillämpning. Metoden, implementation, testning och analys presenteras i detalj i avhandlingen.
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Pal, Maninder. "Leak detection and location in polyethylene pipes." Thesis, Loughborough University, 2008. https://dspace.lboro.ac.uk/2134/15181.

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This thesis is focused on the application of cross-correlation technique for leak detection and location in medium density polyethylene (MDPE) pipes. A leaking water pipe generates noise that depends primarily on water pressure, pipe characteristics and the leak size and shape. This noise, commonly called leak signals, can be used for the purpose of leak detection and leak location in MDPE pipes. A correlation technique is typically employed to detect, position and characterise these water leaks and is proved to be very efficient for metallic pipes. However, the same is not true for MDPE pipes where the attenuation rate with distance of the leak/source signal is very high, and the generated leak signals are of low frequency and narrow bandwidth. In order to locate leak with good accuracy in MDPE pipes, the correlation process relies on the estimation of speed of leak signals in water/pipe and the time delay between leak signals measured at two locations. For time delay estimation, a correlation function is used. Its accuracy depends upon the sharpness of the correlation peak, type and positioning of sensor, and the processing of signals obtained, which in turn further depends upon the characteristics of leak signals. In MDPE pipes, leak signals are of low frequency and narrow bandwidth; however, their frequency response is not well characterised. Therefore, this thesis presents an analytical model to explain the acoustic characteristics of leak signals in MDPE pipes. The model is used to study the effects of the cut-off frequencies of low, high and band pass digital filters and the selection of acoustic/vibration sensors for the correlation technique. It detailed the importance of the cut-off frequency of the high pass filter and the insensitivity of the correlation function to the cut off frequency of the low pass filter.
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Lee, Jeong Heon. "Physical Layer Security for Wireless Position Location in the Presence of Location Spoofing." Diss., Virginia Tech, 2011. http://hdl.handle.net/10919/26417.

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While significant research effort has been dedicated to wireless position location over the past decades, most location security aspects have been overlooked. Recently, with the proliferation of diverse wireless devices and the desire to determine their position, there is an increasing concern about the security of location information which can be spoofed or disrupted by adversaries or unreliable signal sources. This dissertation addresses the problem of securing a radio location system against location spoofing, specifically the characterization, analysis, detection, and localization of location spoofing attacks by focusing on fundamental location estimation issues. The objective of this dissertation is four-fold. First, it provides an overview of fundamental security issues for position location, particularly associated with range-based localization. Of particular interest are security risks and vulnerabilities in location estimation, types of localization attacks, and their impact. The second objective is to characterize the effects of signal strength and beamforming attacks on range estimates and the resulting position estimate. The characterization can be generalized to a variety of location spoofing attacks and provides insight into the anomalous behavior of range and location estimators when under attack. Through this effort we can also identify effective attacks that are of particular interest to attack detection and localization. The third objective is to develop an effective technique for attack detection which requires neither prior environmental nor statistical knowledge. This is accomplished by exploiting the bilateral behavior of a hybrid framework using two received signal strength (RSS) based location estimators. We show that the resulting approach is effective at detecting attacks with the detection rate increasing with the severity of the induced location error. The last objective of this dissertation is to develop a localization method resilient to attacks and other adverse effects. Since the detection and localization approach relies solely on RSS measurements in order to be applicable to a wide range of wireless systems and scenarios, this dissertation focuses on RSS-based position location. Nevertheless, many of the basic concepts and results can be applied to any range-based positioning system.
Ph. D.
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Groh, Brittany Nicole. "Impact of Expressive Intensity and Stimulus Location on Emotion Detection." TopSCHOLAR®, 2017. https://digitalcommons.wku.edu/theses/2020.

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Previous research demonstrates that the age of an observer, the peripheral location of a face stimulus on a display, and the intensity of the emotion expressed by the face all play a role in emotion perception. Older individuals have more difficulty identifying emotion in faces, especially at lower expressive intensities. The purpose of the current study was to understand how younger and older adults’ abilities to detect emotion in facial stimuli presented in the periphery would be affected by the intensity of the emotional expressions and the distance that the expressions are presented away from the center of the display. The current study presented facial stimuli for a short duration to bypass reactionary attentional influences. More intense fearful and angry expressions were expected to be easier to classify for both younger and older adults than lower intensity expressions, but all expressions were expected to become more difficult to classify when presented further in the periphery. Older adults and younger adults displayed similar emotion detection for typical and extreme intensity angry expressions and for high intensity fearful expressions. However, older adults struggled to detect typical intensity fear, and this deficit grew with the angle of eccentricity from which the stimuli were presented from the center of the display. Possible explanations for these age differences are discussed.
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Haider, Raja Umair. "Fault Detection in WLAN Location Fingerprinting Systems Using Smartphone Inertial Sensors." Thesis, Linköpings universitet, Kommunikationssystem, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-81940.

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Indoor positioning is a rapidly growing research area, enabling new innovative location-aware applications and user-oriented services. Location Fingerprinting (LF) is the positioning technique of coupling a physical location with observed radio signal measurements. In the terms of indoor LF using Wireless Local Area Network (WLAN) it refers to the use of network measurements from the WLAN Access Points (APs) to tag known locations. A data set is created containing reference fingerprints for the area of interest and is known as a radio map. A radio map can later be used to find a user's location in the area of interest. WLAN infrastructures are vulnerable to many kinds of faults and malicious attacks, including, an attacker jamming the signal from an AP, or an AP becoming unavailable during positioning due to power outage. These faults can be collectively characterized as an AP-failure. In LF positioning systems, AP-failure faults can significantly degrade the performance of a LF system due to the difference between the current fingerprints and radio map created with all APs being available. It is desirable to detect such faulty APs, in order to take actions towards fault-mitigation and restoration, in case of a malicious attack. In this work, we have developed a fault detection algorithm that uses inertial sensors (i.e., accelerometer, magnetometer) available in smartphones to detect AP-failure faults in LF systems. Inertial Measurement Unit (IMU) has become an integral part of all high-end smartphones. IMU can be used to infer location information on the smartphone. The main idea is to have two parallel position streams, the LF positioning and the IMU positioning, and to compare the mean positioning error between the two. Since IMU positioning is fairly accurate once provided with starting coordinates, we use it to detect abnormal behaviour in LF positioning system, such as highly erroneous estimates signifying an AP-failure fault present in the system. The performance of the proposed detection algorithm is evaluated with several real-life AP-related faults. The proposed algorithm exhibits low probability of false alarms in the detection of faulty APs. The conclusion is that using IMU based positioning is an effective and robust solution in terms of fault detection in LF systems.
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Frimpong, George Kwabena. "Acoustic detection and location of partial discharges in power transformer tanks." Diss., Georgia Institute of Technology, 1994. http://hdl.handle.net/1853/15708.

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Gené, Mola Jordi. "Fruit detection and 3D location using optical sensors and computer vision." Doctoral thesis, Universitat de Lleida, 2020. http://hdl.handle.net/10803/669110.

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Per tal de satisfer les necessitats alimentàries d’una població mundial creixent, és necessari optimitzar la producció agrícola, incrementant la productivitat i la sostenibilitat de les explotacions. Per aconseguir-ho, es preveu que els sistemes automàtics de detecció i localització de fruits seran una eina essencial en la gestió de les plantacions fructícoles, amb aplicacions directes a la predicció de la collita, el mapat de la producció i la recol·lecció automatitzada. Malgrat els avenços aconseguits en àmbits com la robòtica o la visió per computador, la localització 3D de fruits continua essent un repte que ha de fer front a problemes com la identificació de fruits oclosos per altres òrgans vegetatius, o la possibilitat de treballar en diferents condicions d’il·luminació. La present tesi pretén contribuir en el desenvolupament de noves metodologies de detecció i localització de fruits mitjançant la combinació de sensors de base fotònica i d’algoritmes de visió artificial. Per tal de minimitzar els efectes produïts per unes condicions d’il·luminació variable, es proposa l’ús de sensors actius que treballen en l’espectre de llum infraroja. En concret, s’han testejat sensors LiDAR (light detection and ranging) i càmeres de profunditat (RGB-D) basades en el principi de temps de vol (time-of-flight), els quals proporcionen els valors d’intensitat de llum reflectida pels diferents elements mesurats. D’altra banda, per minimitzar el número d’oclusions s’han estudiat dues estratègies: (1) l’aplicació forçada d’aire; (2) la utilització de tècniques d’escaneig des de diferents punts de vista, com ara Structure-from-Motion (SfM). Els resultats obtinguts demostren que les dades d’intensitat proporcionades pels sensors actius LiDAR i RGB-D són de gran utilitat per la detecció de fruits, el que suposa un avanç en l’estat de l’art, ja que aquesta capacitat radiomètrica no havia estat estudiada anteriorment. D’altra banda, les dues estratègies testejades per minimitzar el número de fruits oclosos han demostrat incrementar el percentatge de fruits detectats. De totes les metodologies estudiades, la combinació de xarxes neuronals profundes amb tècniques de SfM és la que presenta més bons resultats, amb percentatges de detecció superiors al 90% i menys d’un 4% de falsos positius.
Para satisfacer las necesidades alimentarias de una población mundial creciente, es necesario optimizar la producción agrícola, incrementando la productividad y la sostenibilidad de las explotaciones. Para conseguirlo, se prevé que los sistemas automáticos de detección y localización de frutos serán una herramienta esencial en la gestión de las plantaciones frutícolas, con aplicaciones directas a la predicción de cosecha, al mapeado de la producción y a la recolección automatizada. A pesar de los avances conseguidos en ámbitos como la robótica o la visión artificial, la localización 3D de frutos continua siendo un reto que debe de hacer frente a problemas como la identificación de frutos ocluidos por otros órganos vegetativos, o la posibilidad de trabajar en distintas condiciones de iluminación. La presente tesis pretende contribuir en el desarrollo de nuevas metodologías de detección y localizacion de frutos mediante la combinación de sensores de base fotónica y de algoritmos de visión artificial. A fin de minimizar los efectos producidos por unas condiciones de iluminación variable, se propone el uso de sensores activos que trabajan en espectros de luz infrarroja. En concreto, se han testeado sensores LiDAR (light detection and ranging) y cámaras de profundidad (RGB-D) basadas en el principio de tiempo de vuelo (time-of-flight), los cuales proporcionan valores de intensidad de la luz reflejada por los objetos escaneados. Por otra parte, para minimizar el número de oclusiones se han estudiado dos estrategias: (1) la aplicación forzada de aire; (2) la utilización de técnicas de escaneo desde distintas perspectivas, tales como Structure-from-Motion (SfM). Los resultados obtenidos demuestran que los datos de intensidad proporcionados por los sensores LiDAR y RGB-D son de gran utilidad para la detección de frutos, lo que supone un avance en el estado del arte, ya que esta capacidad radiométrica no había estado estudiada anteriormente. Por otra parte, las dos estrategias testeadas para minimizar el número de oclusiones han demostrado incrementar el porcentaje de detección. De todas las metodologías estudiadas, la combinación de redes neuronales profundas con técnicas de SfM es la que presenta mejores resultados, con porcentajes de detección superiores al 90% y con menos de un 4% de falsos positivos.
To meet the food demands of an increasing world population, farmers are required to optimize agriculture production by increasing crop productivity and sustainability. To do so, fruit detection and 3D location systems are expected to be an essential tool in the agricultural management of fruit orchards, with applications in fruit prediction, yield mapping, and automated harvesting. Despite the latest advances in robotics and computer vision, the development of a reliable system for 3D fruit location remains a pending issue to deal with problems such as the identification of occluded fruits and the variable lighting conditions of agricultural environments. The present thesis aims to contribute to the development of new methodologies for fruit detection and location by combining optical sensors and artificial intelligence algorithms. In order to minimize variable lighting effects, it is proposed the use of active sensors that work in the infrared light spectrum. In particular, light detection and ranging sensors (LiDAR) and depth cameras (RGB-D) based on the time-of-flight principle were evaluated. These sensors provide the amount of backscattered infrared light reflected by the measured objects. With respect to minimizing the number of fruit occlusions, two different approaches were tested: (1) the application of forced air flow; and (2) the use of multi-view scanning techniques, such as structure-from-motion (SfM) photogrammetry. The results have demonstrated the usefulness of the backscattered intensity provided by LiDAR and RGB-D sensors for fruit detection. This supposes an advance in the state-of-the-art, since this feature has not previously been exploited. Both of the strategies tested to minimize fruit occlusions showed an increase in the fruit detection rate. Of all the tested methodologies, the combination of instance segmentation neural networks and SfM photogrammetry gave the best results, reporting detection rates higher than 90% and false positive rates under 4%.
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Farley, Ben. "Optimal sensor placement for detection and location of leak/burst events." Thesis, University of Sheffield, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.541990.

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Tan, Qinling Jeanette Olivia. "Passive coherent detection and target location with multiple non-cooperative transmitters." Thesis, Monterey, California: Naval Postgraduate School, 2015. http://hdl.handle.net/10945/45951.

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Passive bistatic radars (PBR) and passive multistatic radars (PMR) use opportunistic transmitters to detect and locate targets. In this thesis, a maritime scenario was modeled with merchant vessels serving as multiple non-cooperative opportunistic transmitters while a frigate warship equipped with Electronic Warfare (EW) and Direction Finding (DF) receivers takes on the role of the receiver in a PBR/PMR configuration. The targets are assumed to be the generic Formidable-class frigate. A MATLAB model is developed to simulate the operating environment and passive detection and location process. Detection coverage is investigated to propose optimal PBR/PMR configurations and geometry, while elliptical and hyperbolic target location methods are explored to quantify the effects of PBR/PMR parameters and geometry on target estimated location uncertainty.
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Loos, Matthieu. "Single phase to ground fault detection and location in compensated network." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209544.

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This work takes place in the context of distribution power system protection and tries to improve the detection and location of earth faults. The protection problem is vast and many ideas emerge every year to enhance the reliability of the grid. The author has focused his energy into the compensated and isolated network protection in the specific case of single phase earth fault. This PhD thesis is divided in two main parts that might be considered as independent. The first part studies the detection of single phase earth fault and the second analyzes the fault location of such fault.

Pragmatism was asked during these three years because a product development was necessary especially regarding the fault detection problem. The first part of the thesis took 18 months of research and development to obtain a prototype of transient protection able to detect single phase earth fault in compensated and isolated network. The sensitivity of the algorithm has been emphasized regarding the fault impedance and to detect earth fault up to 5 kOhm depending on the network characteristic. The fault location problem has been much more theoretical although the problem links to the accuracy of the algorithm and its robustness regarding wrong fault location indication has been strongly considered.

Compensated networks and in some conditions isolated networks are distribution from 12 kV up to 110 kV mostly used in East and North Europe but also in China. Others areas also work with such networks but they also have others systems and they do not use them on all the territory. These networks have the particularity to obtain very small fault current in case of single phase earth fault. Low current means the difference between a faulty and a sound feeder is not significant. Therefore classic overcurrent protection is completely useless to protect the network, forcing the development of more complex algorithm. A possibility to overcome the problem of the small fault current is to develop a transient protection. The transient occurring at the beginning of the fault has strong information to distinguish a faulty from a sound feeder. In this work I have chosen to use not only the transient but also the steady state to get the best sensitivity.

Then the fault location has been investigated but the small information coming from the faulty feeder is not sufficient to have a precise enough position of the fault. Therefore, active system has been suggested to be implemented in the grid to increase the faulty current and have enough power for a precise location. Different existing algorithms based on the steady state at the nominal frequency are compared using a tool developed during this work. Recommendations are then made depending on the topology, the network parameters, the measurements precision, etc. Due to the complexities of the problem, a simulator has been coded in Matlab .The user of a possible fault location must then use this tool to understand and see the future fault location precision that he could obtain from different algorithm on his network.
Doctorat en Sciences de l'ingénieur
info:eu-repo/semantics/nonPublished

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Books on the topic "Detection/location"

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Forrest, R. N. Notes on search, detection and localization modeling. 2nd ed. Monterey, Calif: Naval Postgraduate School, 1988.

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Kupperman, D. S. Application of acoustic leak detection technology for the detection and location of leaks in light water reactors. Washington. DC: Division of Engineering, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1988.

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Anderson, W. E. Final report: Technical contributions to the development of incipient fault detection, location instrumentation. Gaithersburg, Md: U.S. Department of Commerce, National Bureau of Standards, 1986.

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Anderson, W. E. Final report: Technical contributions to the development of incipient fault detection, location instrumentation. Gaithersburg, Md: U.S. Department of Commerce, National Bureau of Standards, 1986.

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Persily, Andrew K. National carbon monoxide detection research project: Detector location : literature review and test planning : technical report. Quincy, Mass: National Fire protection Research Foundation, 1996.

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Gabler, Hampton Clay. Development of a low-cost automated crash notification system. Trenton, N.J: New Jersey Dept. of Transportation, 2001.

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Detecting the bomb: The role of seismology in the Cold War. Washington, DC: New Academia Pub., 2009.

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Gustafsson, Fredrik. Adaptive filtering and change detection. Chichester: Wiley, 2000.

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Simon, Léa M. Fault detection: Theory, methods and systems. New York: Nova Science Publishers, 2011.

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Gössel, Michael. Error detection circuits. London: McGraw-Hill, 1993.

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Book chapters on the topic "Detection/location"

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Perente, Osman Kerem, and Tacha Serif. "Server-Based Indoor Location Detection System." In Mobile Web and Intelligent Information Systems, 142–53. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97163-6_12.

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Hosseini, Saeid, Sayan Unankard, Xiaofang Zhou, and Shazia Sadiq. "Location Oriented Phrase Detection in Microblogs." In Database Systems for Advanced Applications, 495–509. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-05810-8_33.

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İnci, Mehmet Sinan, Berk Gulmezoglu, Thomas Eisenbarth, and Berk Sunar. "Co-location Detection on the Cloud." In Constructive Side-Channel Analysis and Secure Design, 19–34. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43283-0_2.

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Boulay, J. L. "Detection and Location of Intracloud Lightning Discharges." In Environmental and Space Electromagnetics, 603. Tokyo: Springer Japan, 1991. http://dx.doi.org/10.1007/978-4-431-68162-5_62.

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Jia, Shaoyong, Yuding Liang, Xianyang Chen, Yun Gu, Jie Yang, Nikola Kasabov, and Yu Qiao. "Adaptive Location for Multiple Salient Objects Detection." In Neural Information Processing, 411–18. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26555-1_46.

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Zhang, Shumei, Paul J. McCullagh, Chris Nugent, Huiru Zheng, and Norman Black. "Reliability of Location Detection in Intelligent Environments." In Ambient Intelligence - Software and Applications, 181–88. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19937-0_23.

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Reyes, Fernando Martínez, Luis C. González Gurrola, and Hector Valenzuela Estrada. "Location and Activity Detection for Indoor Environments." In Advances in Artificial Intelligence and Its Applications, 574–82. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-27101-9_44.

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Capdevila, Joan, Jesús Cerquides, and Jordi Torres. "Event Detection in Location-Based Social Networks." In Studies in Big Data, 161–86. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53474-9_8.

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Malmasi, Shervin, and Mark Dras. "Location Mention Detection in Tweets and Microblogs." In Communications in Computer and Information Science, 123–34. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0515-2_9.

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Solomon, Michael G., Vaidy Sunderam, Li Xiong, and Ming Li. "Mutually Private Location Proximity Detection with Access Control." In Data and Applications Security and Privacy XXXI, 164–84. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61176-1_9.

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Conference papers on the topic "Detection/location"

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Heng, Liang, Athindran R. Kumar, and Grace X. Gao. "Location Hash: Enabling Proximity Detection While Preserving Location Privacy." In 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016). Institute of Navigation, 2016. http://dx.doi.org/10.33012/2016.14549.

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Onur, Tugba Ozge, and Rifat Hacioglu. "Ultrasonic location detection with waveguide." In 2014 22nd Signal Processing and Communications Applications Conference (SIU). IEEE, 2014. http://dx.doi.org/10.1109/siu.2014.6830481.

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Colbourn, Charles J., and Violet R. Syrotiuk. "Coverage, Location, Detection, and Measurement." In 2016 IEEE Ninth International Conference on Software Testing, Verification and Validation Workshops (ICSTW). IEEE, 2016. http://dx.doi.org/10.1109/icstw.2016.38.

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Zou, Yanyan, and Wei Lu. "Joint Detection and Location of." In Proceedings of the 2019 Conference of the North. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/n19-1217.

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Alam, M. S., S. Alsharif, and N. Haq. "Efficient wireless location detection system." In SPIE Defense, Security, and Sensing, edited by Sohail A. Dianat and Michael D. Zoltowski. SPIE, 2010. http://dx.doi.org/10.1117/12.850147.

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Lim, Jaehyun, Jonggeun Park, and Chulhee Lee. "Vision-based speaker location detection." In Electronic Imaging 2005, edited by Amir Said and John G. Apostolopoulos. SPIE, 2005. http://dx.doi.org/10.1117/12.587326.

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Young-Jun Song, Dong-Woo Kim, Nam Kim, and Jae-Hyeong Ahn. "Children location detection in school zone." In 2010 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2010. http://dx.doi.org/10.1109/ictc.2010.5674762.

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Fu, Bin, Baiquan Zhao, and Yang Cheng. "Monocular Camera Target Detection and Location." In 2019 IEEE 21st International Workshop on Multimedia Signal Processing (MMSP). IEEE, 2019. http://dx.doi.org/10.1109/mmsp.2019.8901789.

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Mehner, Stefan, Ronny Klauck, and Hartmut Koenig. "Location-independent fall detection with smartphone." In the 6th International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2504335.2504346.

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Goh, Kim Nee, Jafreezal Jaafar, Emy Elyanee Mustapha, and Eddy Tik Earn Goh. "Automatic accident location detection system (AALDS)." In 2014 Fourth World Congress on Information and Communication Technologies (WICT). IEEE, 2014. http://dx.doi.org/10.1109/wict.2014.7077303.

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Reports on the topic "Detection/location"

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Lefave, J. P., and Leslie Karr. Underground Pipeline Leak Detection and Location Technology Application Guide. Fort Belvoir, VA: Defense Technical Information Center, April 1998. http://dx.doi.org/10.21236/adb236170.

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Kvaerna, T., S. Gibbons, F. Ringdal, and D. Harris. Integrated Seismic Event Detection and Location by Advanced Array Processing. Office of Scientific and Technical Information (OSTI), February 2007. http://dx.doi.org/10.2172/902233.

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Balanis, Constantine A., and Mark Frank. Modeling and Reconstruction Algorithms for Detection, Location, and Identification of Subsurface Anomalies. Fort Belvoir, VA: Defense Technical Information Center, June 1990. http://dx.doi.org/10.21236/ada224358.

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Kvaerna, T., Gibbons. S.J., F. Ringdal, and D. B. Harris. Final Scientific Report, Integrated Seismic Event Detection and Location by Advanced Array Processing. Office of Scientific and Technical Information (OSTI), January 2007. http://dx.doi.org/10.2172/898306.

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Zollweg, James E. Detection, Location, and Identification of Regional Seismic Events Using a Small Broadband Array. Fort Belvoir, VA: Defense Technical Information Center, March 2002. http://dx.doi.org/10.21236/ada400518.

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Damiano, B., E. D. Blakeman, and L. D. Phillips. Detection and location of mechanical system degradation by using detector signal noise data. Office of Scientific and Technical Information (OSTI), June 1994. http://dx.doi.org/10.2172/10158070.

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Nuttall, Albert E. Limiting Detection Performance for Random Signals of Unknown Location, Structure, Extent, and Strength. Fort Belvoir, VA: Defense Technical Information Center, March 1995. http://dx.doi.org/10.21236/ada292389.

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Damiano, B. Detection and Location of Mechanical System Degradation by Using Detector Signal Noise Data. Office of Scientific and Technical Information (OSTI), January 1994. http://dx.doi.org/10.2172/814043.

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Nuttall, Albert H. Detection Capability of Linear-and-Power Processor for Random Burst Signals of Unknown Location. Fort Belvoir, VA: Defense Technical Information Center, August 1997. http://dx.doi.org/10.21236/ada640491.

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Riechers, Ronald G. Perform Initial Measurements to Investigate Microwave Detection for Location of Hemorrhage Sites Within the Body. Fort Belvoir, VA: Defense Technical Information Center, August 1998. http://dx.doi.org/10.21236/adb238349.

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