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1

A Problem of Detecting Stops While Tracking Moving Objects Under the Stream Processing Regime

Białoń Paweł M.

Journal of Telecommunications and Information Technology

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2023

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nr 4

123—132

EN

The tracking of moving objects with the use of GPS/GNSS or other techniques is relied upon in numerous applications, from health monitoring and physical activity support, to social investigations to detection of fraud in transportation. While monitoring movement, a common subtask consists in determining the object’s moving periods, and its immobility periods. In this paper, we isolate the mathematical problem of automatic detection of a stop of tracking objects under the stream processing regime (ideal data processing algorithm regime) in which one is allowed to use only a constant amount of memory, while the stream of GNSS positions of the tracked object increases in size. We propose an approximation scheme of the stop detection problem based on the fuzziness in the approximation of noise level related to the position reported by GNSS. We provide a solving algorithm that determines some upper bounds for the problem’s complexity. We also provide an experimental illustration of the problem at hand.

2

An Online Stream Monitoring Algorithm for Fraud Detection in the Transport of Goods

Białoń Paweł M.

Journal of Telecommunications and Information Technology

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2020

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nr 4

79--85

EN

The process of monitoring vehicles used in road transports plays an important role in detecting fraud committed by drivers. Algorithm designers face a number of challenges, including large number of vehicles monitored, demands related to online calculations, and ability to easily explain fraud alarms triggered to supervisors who make final decisions about actions to be taken. In this paper, we propose rather general, lightweight stream, online heuristics. The vehicle’s position is periodically controlled by a GNSS device. The algorithm detects potential illegal activities along the route between the origin and the destination. Anomalies in the vehicle’s trajectory are detected, based on a multi-resolution analysis of the economy of routes. The economy metric is easily understood and verifiable by controllers. The solution is also capable of identifying clearly suspicious trajectories that popular geofencing approaches would overlook. The scale on which the solution may be adopted is obtained thanks to the stream – like nature of the algorithm: essentially, the resources used do not increase along with the size of the input stream (the number of GNSS frames generated for the vehicle). An experiment illustrating the algorithm’s viability is presented as well.

3

Usage of the Gstreamer framework for generation, analysis, processing and visualization of sonar signals

Czarnecki K., Dąbrowski D.

Hydroacoustics

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2015

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Vol. 18

33--40

EN

In this paper, the usage of the GStreamer framework in applications of classical digital signal processing is discussed. Especially, its adaptation for the sonar technique is presented. Signal generation, analysis, processing, and visualization are implemented as GStreamer plugins. The new plugins and the structure of data transmitted through a GStreamer pipeline are briefly discussed. The introduced plugins are published as free software under the GROJ project.

4

Solving Support Vector Machine with Many Examples

Białoń P.

Journal of Telecommunications and Information Technology

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2010

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nr 3

65-70

EN

Various methods of dealing with linear support vector machine (SVM) problems with a large number of examples are presented and compared. The author believes that some interesting conclusions from this critical analysis applies to many new optimization problems and indicates in which direction the science of optimization will branch in the future. This direction is driven by the automatic collection of large data to be analyzed, and is most visible in telecommunications. A stream SVM approach is proposed, in which the data substantially exceeds the available fast random access memory (RAM) due to a large number of examples. Formally, the use of RAM is constant in the number of examples (though usually it depends on the dimensionality of the examples space). It builds an inexact polynomial model of the problem. Another author's approach is exact. It also uses a constant amount of RAM but also auxiliary disk files, that can be long but are smartly accessed. This approach bases on the cutting plane method, similarly as Joachims' method (which, however, relies on early finishing the optimization).

5

System przetwarzania strumieniowego: StreamAPAS v5.0

Gorawski M., Chrószcz A.

Studia Informatica

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2009

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Vol. 30, nr 1

7-34

PL

Przedstawiony zostanie prototyp systemu przetwarzania strumieniowego StreamAPAS v5.0. Składnia języka zapytań tego systemu jest utworzona z myślą o zastosowaniach analitycznych, które wymagają obsługi struktur indeksujących oraz możliwości prostego dodawania nowej funkcjonalności. Omówiono implementacje węzłów wyliczających agregaty oraz ich proces definiowania przez kompilator języka zapytań. Połączenie zalet drzewa atrybutów oraz interfejsu funkcji sprawia, że zbudowany system StreamAPAS v5.0 łatwo dostosować do zmieniających się potrzeb aplikacji.

EN

This paper introduces the prototype of the stream processing system StreamAPAS v5.0. The main goal of the engine and the query language is offering the general-purpose stream processing platform for data analysis. The language syntax simplify embedding new indexes and a new functionality. In this paper we focus on the implementation of the nodes calculating aggregates and the compiler algorithms used to define the aggregates. As it is further shown, the combination of hierarchical data structures and user aggregate defined functions makes continuous processing applications easier to develop and maintain.