Effects of sampling frequency on node mobility prediction in dynamic networks: A spectral view

The field of mobility prediction has been widely investigated in the recent past,especially the reduction of the coverage radius of cellular networks,which led to an increase in hand-over events.Changing the cell coverage very frequently,for example,may lead to service disruptions if a predictive approach is not deployed in the system.Although several works examined mobility prediction in the new-generation mobile networks,all of these studies focused on studying the time features of mobility traces,and the spectral content of historical mobility patterns was not considered for prediction purposes as yet.In the present study,we propose a new approach to mobility prediction by analyzing the effects of a proper mobility sampling frequency.The proposed approach lies in the mobility analysis in the frequency domain,to extract hidden features of the mobility process.Thus,we proposed a new methodology to determine the spectral content of mobility traces(considered as signals)and,thus,the appropriate sampling frequency,which can provide numerous advantages.We considered several types of mobility models(e.g.pedestrian,urban,and vehicular),containing important details in the time and frequency domains.Several simulation campaigns were performed to observe and analyze the characteristics of mobility from real traces and to evaluate the effects of sampling frequency on the spectral content.

A new GIS-compatible methodology for visibility analysis in digital surface models of earth sites

As a GIS tool,visibility analysis is used in many areas to evaluate both visible and non-visible places.Visibility analysis builds on a digital surface model describing the terrain morphology,including the position and shapes of all objects that can sometimes act as visibility barriers.However,some barriers,for example vegetation,may be permeable to a certain degree.Despite extensive research and use of visibility analysis in different areas,standard GIS tools do not take permeability into account.This article presents a new method to calculate visibility through partly permeable obstacles.The method is based on a quasi-Monte Carlo simulation with 100 iterations of visibility calculation.Each iteration result represents 1%of vegetation permeability,which can thus range from 1%to 100%visibility behind vegetation obstacles.The main advantage of the method is greater accuracy of visibility results and easy implementation on any GIS software.The incorporation of the proposed method in GIS software would facilitate work in many fields,such as architecture,archaeology,radio communication,and the military.

Noise Reduction in Industry Based on Virtual Instrumentation

This paper discusses the reduction of background noise in an industrial environment to extend human-machine-interaction.In the Industry 4.0 era,the mass development of voice control(speech recognition)in various industrial applications is possible,especially as related to augmented reality(such as hands-free control via voice commands).As Industry 4.0 relies heavily on radiofrequency technologies,some brief insight into this problem is provided,including the Internet of things(IoT)and 5G deployment.This study was carried out in cooperation with the industrial partner Brose CZ spol.s.r.o.,where sound recordings were made to produce a dataset.The experimental environment comprised three workplaces with background noise above 100 dB,consisting of a laser/magnetic welder and a press.A virtual device was developed from a given dataset in order to test selected commands from a commercial speech recognizer from Microsoft.We tested a hybrid algorithm for noise reduction and its impact on voice command recognition efficiency.Using virtual devices,the study was carried out on large speakers with 20 participants(10 men and 10 women).The experiments included a large number of repetitions(100 times for each command under different noise conditions).Statistical results confirmed the efficiency of the tested algorithms.Laser welding environment efficiency was 27%before applied filtering,76%using the least mean square(LMS)algorithm,and 79%using LMS+independent component analysis(ICA).Magnetic welding environment efficiency was 24%before applied filtering,70%with LMS,and 75%with LMS+ICA.Press workplace environment efficiency showed no success before applied filtering,was 52%with LMS,and was 54%with LMS+ICA.

Data-Driven Self-Learning Controller for Power-Aware Mobile Monitoring IoT Devices

Nowadays,there is a significant need for maintenance free modern Internet of things(IoT)devices which can monitor an environment.IoT devices such as these are mobile embedded devices which provide data to the internet via Low Power Wide Area Network(LPWAN).LPWAN is a promising communications technology which allows machine to machine(M2M)communication and is suitable for smallmobile embedded devices.The paper presents a novel data-driven self-learning(DDSL)controller algorithm which is dedicated to controlling small mobile maintenance-free embedded IoT devices.The DDSL algorithm is based on a modified Q-learning algorithm which allows energy efficient data-driven behavior of mobile embedded IoT devices.The aim of the DDSL algorithm is to dynamically set operation duty cycles according to the estimation of future collected data values,leading to effective operation of power-aware systems.The presented novel solution was tested on a historical data set and compared with a fixed duty cycle reference algorithm.The root mean square error(RMSE)and measurements parameters considered for the DDSL algorithm were compared to a reference algorithm and two independent criteria(the performance score parameter and normalized geometric distance)were used for overall evaluation and comparison.The experiments showed that the novel DDSL method reaches significantly lowerRMSE while the number of transmitted data count is less than or equal to the fixed duty cycle algorithm.The overall criteria performance score is 40%higher than the reference algorithm base on static confirmation settings.

Enhancements of SDR-Based FPGA System for V2X-VLC Communications

This pilot study focuses on a real measurements and enhancements of a software defined radio-based system for vehicle-to everything visible light communication(SDR-V2X-VLC).The presented system is based on a novel adaptive optimization of the feed-forward software defined equalization(FFSDE)methods of the least mean squares(LMS),normalized LMS(NLMS)and QR decomposition-based recursive least squares(QR-RLS)algorithms.Individual parameters of adaptive equalizations are adjusted in real-time to reach the best possible results.Experiments were carried out on a conventional LED Octavia III taillight drafted directly from production line and universal software radio peripherals(USRP)from National Instruments.The transmitting/receiving elements used multistate quadrature amplitude modulation(M-QAM)implemented in LabVIEW programming environment.Experimental results were verified based on bit error ratio(BER),error vector magnitude(EVM)and modulation error ratio(MER).Experimental results of the pilot study unambiguously confirmed the effectiveness of the proposed solution(longer effective communication range,higher immunity to interference,deployment of higher state QAM modulation formats,higher transmission speeds etc.),as the adaptive equalization significantly improved BER,MER and EVM parameters.The best results were achieved using the QR-RLS algorithm.The results measured on deployed QR-RLS algorithm had significantly better Eb/N0(improved by approx.20 dB)and BER values(difference by up to two orders of magnitude).

Thermostability of montmorillonitic clays

Bentonite is one of the most widespread used clays connected with various applications. In the case of foundry technology, bentonite is primarily used as a binder for mold manufacture. Thermal stability of bentonites is a natural property of clay minerals and it depends on the genesis, source and chemical composition of the clay. This property is also closely connected to bentonite structure. According to DTA analysis if only one peak of dehydroxylation is observed(about 600 oC), the cis- isomerism of bentonite is expected, while two peaks of de-hydroxylation(about 550 and 850 oC) are expected in the trans- one. In this overview, the bentonite structure, the water – bentonite interaction and the swelling behavior of bentonite in connection with the general technological properties of bentonite molding mixture are summarized. Further, various types of methods for determination of bentonite thermostability are discussed, including instrumental analytical methods as well as methods that employ evaluation of various technological properties of bentonite binders and/or bentonite molding mixtures.

Integrated interferometers’system for in situ real-time optical signal modulation

Improving the functionality of an optical sensor on a prefabricated platform relies heavily on an optical signal conditioning method that actively modulates optical signals.In this work,we present a method for active modulation of an optical sensor response that uses fiber modal interferometers integrated in parallel.Over a broad frequency range of 1 Hz to 1 kHz,the interferometers’technology allows for adjustable amplification,attenuation,and filtering of dynamic signals.The suggested method is also used to enhance the real-time response of an optical fluid flowmeter.In order to keep tabs on different physical fields,the suggested approach promotes the creation of self-conditioning sensing systems.