The goal of this workshop is to introduce open modular hardware and software system "iSES Remote Lab SDK" (iSES -internet School Experimental Studio) designed for easy creation of real remotely controlled laboratories (RCL) that are accessible from PC, tablets and mobile phones. Open modular system iSES Remote Lab SDK consists of approx. 20 freely distributable JavaScript objects in commented source code. Widgets are highly configurable and provide many well documented options and allow to build a complex measurement and control interface with data and video transfer. Open modular system iSES Remote Lab SDK can communicate with different measurement platforms (ISES, Arduino are ready; CMA CoachLab, Vernier etc. are tested), and also common universal measurement devices with a COM or USB port, further universal rotation and linear motion stepper motors, etc.). We will demonstrate our 18 online advanced remote labs accessible at www.ises.info. All participants of the workshop will receive a fully functional lite version of the iSES Remote Lab SDK for Arduino-Uno so they can try to control a physics experiment remotely, download data and process it. Any user may have an access to the RCL on PC and mobile devices (iPad, smart phone, etc.) as well. The workshop participants will build and test several Arduino-Uno Remote experiments by putting selected components of the iSES Remote Lab SDK together, which includes assembling both hardware and software components in a custom way so that any user can control the experiment remotely. Even non-programmers can build up a simple RCL and publish it in 15 minutes on the Internet! We introduce a new measurement system ISES-LAN which is based on Internet of Things.

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This article deals with the use of neural networks for estimation of deceleration model parameters for the adaptive cruise control unit. The article describes the basic functionality of adaptive cruise control and creates a mathematical model of braking, which is one of the basic functions of adaptive cruise control. Furthermore, an analysis of the influences acting in the braking process is performed, the most significant of which are used in the design of deceleration prediction for the adaptive cruise control unit using neural networks. Such a connection using artificial neural networks using modern sensors can be another step towards full vehicle autonomy. The advantage of this approach is the original use of neural networks, which refines the determination of the deceleration value of the vehicle in front of a static or dynamic obstacle, while including a number of influences that affect the braking process and thus increase driving safety.

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Abstract-The present article describes the results of a medium-scale (N = 77) study, using log files from open remote laboratory at Charles University in Prague, Faculty of Mathematics and Physics, to observe students' behavior during their work in virtual environment. Simple data mining and text mining techniques were used to reveal individual user's behavioral patterns, to detect disengagement, and to compare learning outcomes and student preferences.Index Terms-datamining, educational research, log files analysis, remote and virtual laboratories,