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EasyEV: Monitoring and Querying System for Electric Vehicle Fleets Using Smart Car Data [chapter]

Gregor Jossé, Matthias Schubert, Ludwig Zellner
2015 Lecture Notes in Computer Science  
In the project Shared E-Fleet, the shared use of a fleet of electric cars by a heterogeneous group of drivers is examined.  ...  However, operating EVs has several drawbacks compared to common combustion engine cars.  ...  By evaluating this data, we are able to detect and predict anomalies, in order to inform the fleet manager about critical situations like expected belated returns or expected range exceedances.  ... 
doi:10.1007/978-3-319-22363-6_29 fatcat:ggl3qicecngrvaj7v3uzmbaqjq

Anomaly Detection in Road Traffic Using Visual Surveillance: A Survey [article]

Santhosh Kelathodi Kumaran, Debi Prosad Dogra, Partha Pratim Roy
2019 arXiv   pre-print
In this paper, we present a survey on relevant visual surveillance related researches for anomaly detection in public places, focusing primarily on roads.  ...  Finally, we discuss the challenges in the computer vision related anomaly detection techniques and some of the important future possibilities.  ...  Car crashes, stalled vehicles. NVDIA CITY. Chebiyyam (2017) [31] Heuristic using SVM and Region Association Graph Parking lot, walk- ways.  ... 
arXiv:1901.08292v1 fatcat:qehtkb2imfbmpfahkgsjrx7544

Proactive Threat Detection for Connected Cars Using Recursive Bayesian Estimation

Haider al-Khateeb, Gregory Epiphaniou, Adam Reviczky, Petros Karadimas, Hadi Heidari
2018 IEEE Sensors Journal  
In this paper, we introduce proactive anomaly detection to a use-case of hijacked connected cars to improve cyber-resilience.  ...  Finally, we simulate the analysis of travel routes in real-time to predict anomalies using predictive modelling.  ...  Threat Detection and Prediction Anomaly detection plays a crucial part in the proactive approach to detect cyber-threats.  ... 
doi:10.1109/jsen.2017.2782751 fatcat:prepadehivdklnogbwuyobdtby

Graph Learning for Fake Review Detection

Shuo Yu, Jing Ren, Shihao Li, Mehdi Naseriparsa, Feng Xia
2022 Frontiers in Artificial Intelligence  
To further compare these graph learning methods in this paper, we conduct a detailed survey on fake review detection.  ...  An important line of research in fake review detection is to utilize graph learning methods, which incorporate both the attribute features of reviews and their relationships into the detection process.  ...  Epinions Epinions (Kumar et al., 2018 ) is a consumers opinion site where users review items such as cars, books, movies, software, etc.  ... 
doi:10.3389/frai.2022.922589 pmid:35795012 pmcid:PMC9251112 fatcat:ae7hq66jgvcxjlt6o27nsgvohm

A Comparison of Propositionalization Strategies for Creating Features from Linked Open Data

Petar Ristoski, Heiko Paulheim
2014 European Conference on Principles of Data Mining and Knowledge Discovery  
, regression, and outlier detection.  ...  However, most data mining tools require features in propositional form, i.e., binary, nominal or numerical features associated with an instance, while Linked Open Data sources are usually graphs by nature  ...  Acknowledgements The work presented in this paper has been partly funded by the German Research Foundation (DFG) under grant number PA 2373/1-1 (Mine@LOD).  ... 
dblp:conf/pkdd/RistoskiP14 fatcat:awmitvm7nzdw3mjspqnpjqkjqu

Anomalous behaviour detection based on heterogeneous data and data fusion

Azliza Mohd Ali, Plamen Angelov
2018 Soft Computing - A Fusion of Foundations, Methodologies and Applications  
These can assist the human expert in processing huge amount of heterogeneous data to detect anomalies.  ...  Then, the new anomaly detection technique which is recently introduced and known as empirical data analytics (EDA) is applied to detect the abnormal behaviour based on the datasets.  ...  distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecomm ons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in  ... 
doi:10.1007/s00500-017-2989-5 fatcat:lzxv7b22bvaa7nxgd6daor7xl4

Towards API Testing Across Cloud and Edge [article]

Samuel Ackerman, Sanjib Choudhury, Nirmit Desai, Eitan Farchi, Dan Gisolfi, Andrew Hicks, Saritha Route, Diptikalyan Saha
2021 arXiv   pre-print
Specifically, five kinds of reliability tests are envisioned: out-of-order execution of APIs, network delays and faults, API performance and throughput, changes in API call graph patterns, and changes  ...  in application topology.  ...  In addition, the OTFA test results, the API logs, the API dependency graph, the fault injection logs and the drift detection analysis are fed to a search algorithm within the test generator.  ... 
arXiv:2109.02540v1 fatcat:otqvq7ksa5hcxpxmfgvwsfgkeq

Graphical and Logical Formalisms for Business Process Modeling and Verification

Henry H. Bi
2004 Social Science Research Network  
For instance, few of existing activity-based methods are capable of both representing a process model that enables customers to "book flight", "book hotel", and/or "book car" in any possible combinations  ...  If FIGURE 37(a) represents the process of booking a flight, booking a hotel, and/or booking a car in any possible combinations, after c\ is activated, one or more leaving arcs of C] will become active,  ... 
doi:10.2139/ssrn.2634608 fatcat:p3timd5gynbrtgmhc2su5dr3tu

Adapted K-Nearest Neighbors for Detecting Anomalies on Spatio–Temporal Traffic Flow

Youcef Djenouri, Asma Belhadi, Jerry Chun-Wei Lin, Alberto Cano
2019 IEEE Access  
This paper explores advances in the outlier detection area by finding anomalies in spatio-temporal urban traffic flow.  ...  Outlier detection is an extensive research area, which has been intensively studied in several domains such as biological sciences, medical diagnosis, surveillance, and traffic anomaly detection.  ...  One of the main applications in urban traffic analysis is detecting anomalies from the traffic flow data.  ... 
doi:10.1109/access.2019.2891933 fatcat:2dwmhrw3kvakjpkpbst4ww2wxe

Anomaly Localization in Topic-Based Analysis of Surveillance Videos

Deepak Pathak, Abhijit Sharang, Amitabha Mukerjee
2015 2015 IEEE Winter Conference on Applications of Computer Vision  
However, while intervals containing anomalies are detected, it has not been possible to localize the anomalous activities in such models.  ...  Using the algorithm, we detect whether the video clip is abnormal and if positive, localize the anomaly in spatio-temporal domain.  ...  Finally, anomaly detection is usu-(a) Traffic Junction Dataset [20] . The left image is usual while right is an anomaly -car stops after the stop-line. (b) Highway Dataset.  ... 
doi:10.1109/wacv.2015.58 dblp:conf/wacv/PathakSM15 fatcat:lhvqa6jcx5etlcj5zno5zsd3fu

Detecting Unusual User Behaviour to Identify Hijacked Internet Auctions Accounts [chapter]

Marek Zachara, Dariusz Pałka
2012 Lecture Notes in Computer Science  
The following paper discusses the methods of identifying the accounts of users participating in internet auctions that have been hijacked (taken over) by malicious individuals and utilised for fraudulent  ...  These methods, utilised together allow for real-time detection of suspicious accounts. The proposed models are validated on real data gathered from an auction web site.  ...  Such clusters are likely to group together the already mentioned jewellery for men and jewellery for women as well as e.g. books → guidebooks and car → manuals.  ... 
doi:10.1007/978-3-642-32498-7_41 fatcat:n462tg4rjbb6vcnwfilo2tu4te

FIRM: An Intelligent Fine-Grained Resource Management Framework for SLO-Oriented Microservices [article]

Haoran Qiu, Subho S. Banerjee, Saurabh Jha, Zbigniew T. Kalbarczyk, Ravishankar K. Iyer
2020 arXiv   pre-print
FIRM leverages online telemetry data and machine-learning methods to adaptively (a) detect/localize microservices that cause SLO violations, (b) identify low-level resources in contention, and (c) take  ...  However, multiplexing of compute resources across microservices is still challenging in production because contention for shared resources can cause latency spikes that violate the service-level objectives  ...  This research was supported in part by the U.  ... 
arXiv:2008.08509v2 fatcat:hytx5hz73bfmxfjw467bwsjbda

Advances in Machine Learning and Deep Neural Networks

Rama Chellappa, Sergios Theodoridis, Andre van Schaik
2021 Proceedings of the IEEE  
it, in order to make predictions and, subsequently, take decisions.  ...  the center of this historical happening, as one of the key enabling technologies, lies a discipline that deals with data and whose goal is to extract information and related knowledge that is hidden in  ...  His research interests span a wide range of areas in the intersection of signal processing and machine learning. Prof. Theodoridis is a Fellow of the IET and EURASIP and a Cor  ... 
doi:10.1109/jproc.2021.3072172 fatcat:j3xryj6jerh45g7zmu37sfuhtu

Mining big data

Wei Fan, Albert Bifet
2013 SIGKDD Explorations  
We present in this issue, a broad overview of the topic, its current status, controversy, and forecast to the future.  ...  We introduce four articles, written by influential scientists in the field, covering the most interesting and state-of-the-art topics on Big Data mining.  ...  It allows to find patterns and anomalies in massive real-world graphs. See the paper by U.  ... 
doi:10.1145/2481244.2481246 fatcat:4desfvwbqrfhpgez4cm7wwxwtu

Word-to-text integration in English as a second language reading comprehension

Evelien Mulder, Marco van de Ven, Eliane Segers, Alexander Krepel, Elise H. de Bree, Peter F. de Jong, Ludo Verhoeven
2020 Reading and writing  
The students performed a self-paced WTI reading task in Fall (T1) and Spring (T2), consisting of three text manipulation types (anaphora resolution, argument overlap, anomaly detection), divided in simple  ...  Longer reading times on complex compared to simple argument overlap and anomaly detection passages predicted offline reading comprehension.  ...  Anomaly detection For the anomaly detection passages, we again found main effects of and an interaction between Word Position and Complexity across Time, which is visually displayed in Fig. 4 .  ... 
doi:10.1007/s11145-020-10097-3 fatcat:25uz536kebdj7emdwzuozetur4
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