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Spatial anomaly detection in sensor networks using neighborhood information

Hedde HWJ Bosman, Giovanni Iacca, Arturo Tejada, Heinrich J. Wörtche, Antonio Liotta
<span title="">2017</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/u3qqmkiofjejrnpdxh3hdgssm4" style="color: black;">Information Fusion</a> </i> &nbsp;
We study the information gain coming from aggregate neighborhood data, in comparison to performing simple, in-node anomaly detection.  ...  We evaluate the effects of neighborhood size and spatio-temporal correlation on the performance of our new neighborhood-based approach using a range of real-world network deployments and datasets.  ...  In this paper, we address the following question: Can the local detection of anomalies be improved (in terms of precision or recall) by combining data from groups of spatially co-located sensor nodes?  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.inffus.2016.04.007">doi:10.1016/j.inffus.2016.04.007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ra4jdegmanfydczn34g43doqvu">fatcat:ra4jdegmanfydczn34g43doqvu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719042028/https://pure.tue.nl/ws/files/46103390/1_s2.0_S1566253516300252_main.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/3b/6a/3b6aca525abd1f50db2498bad6432991b4b97cf2.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.inffus.2016.04.007"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> elsevier.com </button> </a>

Fault-Tolerant Anomaly Detection Method in Wireless Sensor Networks

Nengsong Peng, Weiwei Zhang, Hongfei Ling, Yuzhao Zhang, Lixin Zheng
<span title="2018-09-18">2018</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dmr4kpn2yreovpdxpdiqtjcrnu" style="color: black;">Information</a> </i> &nbsp;
In this paper, a fault-tolerant anomaly detection method (FTAD) is proposed based on the spatial-temporal correlation of sensor networks.  ...  A key issue in wireless sensor network applications is how to accurately detect anomalies in an unstable environment and determine whether an event has occurred.  ...  Based on this, we propose a fault-tolerant anomaly detection method (FTAD) based on spatial-temporal correlation.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/info9090236">doi:10.3390/info9090236</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/opgvcnxbhzhejjzw6bun25cspy">fatcat:opgvcnxbhzhejjzw6bun25cspy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190218031312/http://pdfs.semanticscholar.org/0a28/6a042673020605ceb94ec498acdfdadb736c.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/0a/28/0a286a042673020605ceb94ec498acdfdadb736c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/info9090236"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Neighborhood based detection of anomalies in high dimensional spatio-temporal sensor datasets

Nabil R. Adam, Vandana Pursnani Janeja, Vijayalakshmi Atluri
<span title="">2004</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/uo6yx5jpgnf2zl7mkrumytd4ti" style="color: black;">Proceedings of the 2004 ACM symposium on Applied computing - SAC &#39;04</a> </i> &nbsp;
In this paper, we address the outlier detection by refining the concept of a neighborhood of an object, which essentially characterizes similarly behaving objects into one neighborhood.  ...  This similarity is quantified in terms of the spatial relationships among the objects and other semantic relationships based on the spatial processes and spatial features in their vicinity.  ...  based outlier detection and the definition of the neighborhood based on spatial and semantic relationships.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/967900.968020">doi:10.1145/967900.968020</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sac/AdamJA04.html">dblp:conf/sac/AdamJA04</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kycxrhyvczb5be736wrd2tgnuu">fatcat:kycxrhyvczb5be736wrd2tgnuu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809141459/https://s2.smu.edu/~mhd/8331sp08/adam.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/65/51/6551fe6d92b0a47b0e4d00962427a22a808b57e3.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/967900.968020"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Spatiotemporal Neighborhood Discovery for Sensor Data [chapter]

Michael P. McGuire, Vandana P. Janeja, Aryya Gangopadhyay
<span title="">2010</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
ABSTRACT The focus of this paper is the discovery of spatiotemporal neighborhoods in sensor datasets where a time series of data is collected at many spatial locations.  ...  The purpose of the spatiotemporal neighborhoods is to provide regions in the data where knowledge discovery tasks such as outlier detection, can be focused.  ...  Acknowledgements This article has been funded in part by the National Oceanic and Atmospheric Administration (Grants NA06OAR4310243 and NA07OAR4170518).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-12519-5_12">doi:10.1007/978-3-642-12519-5_12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bu7aenettjbpfku5vzuk2nzmum">fatcat:bu7aenettjbpfku5vzuk2nzmum</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210428074737/https://mdsoar.org/bitstream/handle/11603/20043/Spatiotemporal_Neighborhood_Discovery_for_Sensor_D.pdf;jsessionid=BBFCF050ACACA6C33F719F40192F9D6F?sequence=5" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2c/5d/2c5d6033b8239e6e78e8d94414ea3f4f705507c0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-12519-5_12"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Discovering Teleconnected Flow Anomalies: A Relationship Analysis of Dynamic Neighborhoods (RAD) Approach [chapter]

James M. Kang, Shashi Shekhar, Michael Henjum, Paige J. Novak, William A. Arnold
<span title="">2009</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
In this paper, we propose a RAD (Relationship Analysis of spatio-temporal Dynamic neighborhoods) approach for steps 2 and 3 to discover teleconnected flow anomalies.  ...  This paper characterizes the computational structure in terms of three critical tasks, (1) detection of flow anomaly events, (2) identification of candidate pairs of events, and (3) evaluation of candidate  ...  Each pair of ST locations is analyzed based on its spatial neighborhood as defined by the W-matrix. For each pair of neighboring sensors, flow anomalies are retrieved using the SWEET 1 method.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-02982-0_6">doi:10.1007/978-3-642-02982-0_6</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wdgepsinibhwbi3et6324qbsiy">fatcat:wdgepsinibhwbi3et6324qbsiy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20100712174200/http://www-users.cs.umn.edu/~jkang/npapers/SSTD09.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/73/90/7390e2e310c4baa296f7cc8a5bb4544d20f593e8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-02982-0_6"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Anomaly Detection in Hyperspectral Imagery Based on Low-Rank Representation Incorporating a Spatial Constraint

Kun Tan, Zengfu Hou, Donglei Ma, Yu Chen, Qian Du
<span title="2019-07-03">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/kay2tsbijbawliu45dnhvyvgsq" style="color: black;">Remote Sensing</a> </i> &nbsp;
In this study, novel low-rank representation methods were developed for anomaly detection from hyperspectral images based on the assumption that hyperspectral pixels can be effectively decomposed into  ...  In order to improve detection performance, we imposed a spatial constraint on the low-rank representation coefficients, and single or multiple local window strategies was applied to smooth the coefficients  ...  The first approach is the SLW_LRRSTO anomaly detection method, which is based on LRRSTO with the combination of spectral and spatial information.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs11131578">doi:10.3390/rs11131578</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/r76ecm5mtba73fp4zpknhiktvq">fatcat:r76ecm5mtba73fp4zpknhiktvq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200208224822/https://res.mdpi.com/d_attachment/remotesensing/remotesensing-11-01578/article_deploy/remotesensing-11-01578.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e1/78/e178f579f6fd6fe7ea309da95f8bc4b3403919df.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/rs11131578"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Unsupervised Feature Selection Based on Low Dimensional Embedding and Subspace Learning

Hadi Zare, Mohsen Ghassemi Parsa, Mehdi Ghatee, Sasan H. Alizadeh, Faculty of New Science and Technology, University of Tehran, Faculty of New Science and Technology, University of Tehran, Department of Computer Science, Amirkabir University of Technology, Department of Information Technology, IRAN Telecommunication Research Center
<span title="2020-09-01">2020</span> <i title="CMV Verlag"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/55pl6zp5mnbhzlelvbnlxe4dfi" style="color: black;">International Journal of Information &amp; Communication Technology Research</a> </i> &nbsp;
Real-time monitoring in order to detect anomalies leads to the intensive data processing and hence requires a new computing scheme to offer large-scale and low latency services.  ...  To evaluate the effectiveness of the hierarchical anomaly detection model in water distribution grids, the data and computing nodes at different layers were executed as docker containers.  ...  We exploited spatial/temporal correlation of data at each layer to detect existing anomalies in the created dataset.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.52547/ijict.12.3.38">doi:10.52547/ijict.12.3.38</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bkhnc6r2czfnxaenqiv4qszphq">fatcat:bkhnc6r2czfnxaenqiv4qszphq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220308160215/https://ijict.itrc.ac.ir/files/site1/user_files_a5272a/saramirzaie-A-10-4367-1-9740603.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/65/70/65706d84ecd15dc8fd821bb2e230f9774facc0d0.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.52547/ijict.12.3.38"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Detecting localized homogeneous anomalies over spatio-temporal data

Aditya Telang, P. Deepak, Salil Joshi, Prasad Deshpande, Ranjana Rajendran
<span title="2014-07-15">2014</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ja54f4dcmzfz7cvlo7o757jdba" style="color: black;">Data mining and knowledge discovery</a> </i> &nbsp;
Our approach differs significantly from traditional methods of spatial outlier detection, and employs two phases -i) discovering homogeneous regions, and ii) evaluating these regions as anomalies based  ...  on their statistical difference from a generalized neighborhood.  ...  However, general clustering techniques usually do not differentiate between spatial and non-spatial (e.g., temperature) attributes; thus, application of clustering to a dataset of sensors could group sensors  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10618-014-0366-x">doi:10.1007/s10618-014-0366-x</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/njpa2odbwngdfga3z45qprioam">fatcat:njpa2odbwngdfga3z45qprioam</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180719104251/https://pure.qub.ac.uk/portal/files/17977954/dami14_1_.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9f/e6/9fe6d2546cb3235f196d3cb68e6805b3b6eb2caa.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s10618-014-0366-x"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

A Weighted Spatial-Spectral Kernel RX Algorithm and Efficient Implementation on GPUs

Chunhui Zhao, Jiawei Li, Meiling Meng, Xifeng Yao
<span title="2017-02-23">2017</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
The effective use of spatial-spectral information in kernel-based anomaly detection is helpful to optimize the kernel mapping in high-dimensional feature space, thereby improving the performance of anomaly  ...  As the growth of the spatial resolution in HSI data, better use of spatial information will be the trend which is the field of anomaly detection.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s17030441">doi:10.3390/s17030441</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/28241511">pmid:28241511</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC5375727/">pmcid:PMC5375727</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lyek5cwh2banldkm3s55ff6nny">fatcat:lyek5cwh2banldkm3s55ff6nny</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180729020843/https://res.mdpi.com/def50200941c311d0e17222ae5c187c1b323c4f1cab4c62c81e2eae85fe4daec992941a03c7b64ed7b8cdf039ba1dfd17294c67c90715e9c7bf64e344cc39adb4dae156a467e1f05694202c0e4c4d77bd4b2e9f6a5519df9eaeb2225edd9881da39d2de97229d23a892bf3023548929de79066c689ca481989df30f54dd28728e73dfcebd195e5abcdb373458f4d5588?filename=&amp;attachment=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/01/60/01603a27e781529d9865a34d847767fa122a30aa.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s17030441"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375727" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Anomaly Detection in Radar Data Using PointNets [article]

Thomas Griebel, Dominik Authaler, Markus Horn, Matti Henning, Michael Buchholz, Klaus Dietmayer
<span title="2021-09-20">2021</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Our method is evaluated on a real-world dataset in urban scenarios and shows promising results for the detection of anomalous radar targets.  ...  To this end, it is desirable to identify anomalous targets as early as possible in radar data. In this work, we present an approach based on PointNets to detect anomalous radar targets.  ...  where the authors propose a model-based detection algorithm for anomalies.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2109.09401v1">arXiv:2109.09401v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rxudnyzpdvedpbadvh53vter5e">fatcat:rxudnyzpdvedpbadvh53vter5e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210926143432/https://arxiv.org/pdf/2109.09401v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9b/65/9b6525a9aaa4d23b71334e70a91f762d67db0af9.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2109.09401v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Advancements of Data Anomaly Detection Research in Wireless Sensor Networks: A Survey and Open Issues

Murad Rassam, Anazida Zainal, Mohd Maarof
<span title="2013-08-07">2013</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/taedaf6aozg7vitz5dpgkojane" style="color: black;">Sensors</a> </i> &nbsp;
We then review the latest advancements of data anomaly detection research in WSNs and classify current detection approaches in five main classes based on the detection methods used to design these approaches  ...  In this review, we present the challenges of anomaly detection in WSNs and state the requirements to design efficient and effective anomaly detection models.  ...  Correlation in sensor data of close neighborhoods was found to enhance the detection effectiveness by the mean of distributed detection in close neighborhoods.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s130810087">doi:10.3390/s130810087</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/23966182">pmid:23966182</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC3812595/">pmcid:PMC3812595</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kyogf3utg5cujoctt6pdhjpo2q">fatcat:kyogf3utg5cujoctt6pdhjpo2q</a> </span>
<a target="_blank" rel="noopener" href="https://archive.org/download/pubmed-PMC3812595/PMC3812595-s130810087.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> File Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/5d/10/5d1076238166aeea8ad53de5865eaa1cc2ec5617.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/s130810087"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3812595" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

A Modified DBSCAN Algorithm for Anomaly Detection in Time-series Data with Seasonality

Praphula Jain, Mani Shankar Bajpai, Rajendra Pamula
<span title="2022-01-01">2022</span> <i title="Zarqa University"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6bcnprgzzje6lknxuwtnnqmhra" style="color: black;">˜The œinternational Arab journal of information technology</a> </i> &nbsp;
Density-Based Spatial Clustering of Applications with Noise (DBSCAN) Algorithm is a density-based clustering algorithm with the capability of identifying anomalous data.  ...  In this paper, a modified DBSCAN algorithm is proposed for anomaly detection in time-series data with seasonality.  ...  A unique algorithm based on DBSCAN for anomaly detection is presented in [9] .  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.34028/iajit/19/1/3">doi:10.34028/iajit/19/1/3</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5exc3qnsw5d3boxkrh3inzfarq">fatcat:5exc3qnsw5d3boxkrh3inzfarq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220131015138/http://iajit.org/portal/images/Year2022/No.1/19023.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/9f/52/9f52a0f411583a8978ea31f8bbc7a3cf5bb715fa.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.34028/iajit/19/1/3"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a>

Knowledge discovery from sensor data (SensorKDD)

Ranga Raju Vatsavai, Olufemi A. Omitaomu, Joao Gama, Nitesh V. Chawla, Mohamed Medhat Gaber, Auroop R. Ganguly
<span title="2008-12-20">2008</span> <i title="Association for Computing Machinery (ACM)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5ptshywu7rdklpcx3m6sfans3e" style="color: black;">SIGKDD Explorations</a> </i> &nbsp;
In this report, we summarize the events of the Second ACM-SIGKDD International Workshop on Knowledge Discovery form Sensor Data (Sensor-KDD 2008).  ...  In addition, emerging societal problems require knowledge discovery solutions that are designed to investigate anomalies, changes, extremes and nonlinear processes, and departures from the normal.  ...  Their innovation and creativity has resulted in a strong technical program.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1540276.1540297">doi:10.1145/1540276.1540297</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/72jirtrxibbrpmpfcwrivmedjm">fatcat:72jirtrxibbrpmpfcwrivmedjm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810041118/https://www3.nd.edu/~nchawla/papers/SIGKDD08.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/28/e5/28e5d3acf60e3520e16414d679ebb2cb998f5de6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1540276.1540297"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

Knowledge discovery from sensor data (SensorKDD)

Olufemi A. Omitaomu, Ranga Raju Vatsavai, Auroop R. Ganguly, Nitesh V. Chawla, Joao Gama, Mohamed Medhat Gaber
<span title="2010-05-27">2010</span> <i title="Association for Computing Machinery (ACM)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/5ptshywu7rdklpcx3m6sfans3e" style="color: black;">SIGKDD Explorations</a> </i> &nbsp;
In this report, we summarize the events of the Second ACM-SIGKDD International Workshop on Knowledge Discovery form Sensor Data (Sensor-KDD 2008).  ...  In addition, emerging societal problems require knowledge discovery solutions that are designed to investigate anomalies, changes, extremes and nonlinear processes, and departures from the normal.  ...  Their innovation and creativity has resulted in a strong technical program.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1809400.1809417">doi:10.1145/1809400.1809417</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jrtrixjfzzgo3bdlelcyldihom">fatcat:jrtrixjfzzgo3bdlelcyldihom</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170810041118/https://www3.nd.edu/~nchawla/papers/SIGKDD08.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/28/e5/28e5d3acf60e3520e16414d679ebb2cb998f5de6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/1809400.1809417"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> acm.org </button> </a>

An isolation principle based distributed anomaly detection method in wireless sensor networks

Zhi-Guo Ding, Da-Jun Du, Min-Rui Fei
<span title="2014-11-05">2014</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nvylz6fxhjaqtckvt4zfwob2qi" style="color: black;">International Journal of Automation and Computing</a> </i> &nbsp;
Anomaly detection plays an important role in ensuring the data quality in wireless sensor networks (WSNs).  ...  Secondly, considering the spatial correlation characteristic of node deployment in WSNs, local sub-detector is built in each sensor node, which is broadcasted simultaneously to neighbor sensor nodes.  ...  Considering the spatial correlation among the neighbor sensor data, a distributed anomaly detection method has been proposed based on the isolation principle.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11633-014-0847-9">doi:10.1007/s11633-014-0847-9</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rd6zp6bdsngvjhyynyzzjoq7sa">fatcat:rd6zp6bdsngvjhyynyzzjoq7sa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20180730112026/https://link.springer.com/content/pdf/10.1007%2Fs11633-014-0847-9.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f6/b8/f6b8bed4538045743e51d34e6d6c57d8cda4a3fc.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/s11633-014-0847-9"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>
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