A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural langu...A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural language instructions, and motion information condensation with the aid of support vector machine (SVM) theory. Self-organizing fuzzy neural networks are utilized for the collection of control rules, from which support vector rules are extracted to form a final controller to achieve any given control accuracy. In this way, the number of control rules is reduced, and the structure of the controller tidied, making a controller constructed using natural language training more appropriate in practice, and providing a fundamental rule base for high-level robot behavior control. Simulations and experiments on a wheeled robot are carried out to illustrate the effectiveness of the method.展开更多
This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction.Modern vehicles are nowadays increasingly supporting voice commands,which are one of the pillars of autonomous ...This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction.Modern vehicles are nowadays increasingly supporting voice commands,which are one of the pillars of autonomous and SMART vehicles.Robust speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle back-ground noise.This article presents the new concept of a hybrid system which is implemented as a virtual instrument.The highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle background noise reduction.The study also presents a unique concept of an adaptive system using intelligent clusters of distributed next generation 5G data networks,which allows the exchange of interference information and/or optimal hybrid algorithm settings between individual vehicles.On average,the unfiltered voice commands were successfully recognized in 29.34%of all scenarios,while the LMS reached up to 71.81%,and LMS-ICA hybrid improved the performance further to 73.03%.展开更多
The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artifi...The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker’s functionality.In this work,we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming environment.The electrical model of the heart allows signals generation(right atrium,right ventricle)and the monitoring of the stimulation pulses.The LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in real-time.The results demonstrate the capability of proposed system to evaluate the paced and sensed pulses.The proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing mode.In addition,the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.展开更多
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 ada...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).展开更多
This paper proposes a solution to controls warm robots in an effort to avoid obstacles, moving to the goal by the method of Null Space based Behavior (NSB) control of an individual in the swarm. This paper also provid...This paper proposes a solution to controls warm robots in an effort to avoid obstacles, moving to the goal by the method of Null Space based Behavior (NSB) control of an individual in the swarm. This paper also provides the stability analysis of the converging process by investigating the relationship between single agents, and the analysis result is proved by using the Lyapunov theory. Finally, the simulation results in two-dimensional space have confirmed the obtained theoretical results.展开更多
The article analyzes the problems of introducing electric vehicles,as well as their difference from cars with internal combustion engines.This type of transport has long been included in our everyday life.Today,in the...The article analyzes the problems of introducing electric vehicles,as well as their difference from cars with internal combustion engines.This type of transport has long been included in our everyday life.Today,in the era of the heyday of technology,a person understands that cars with an internal combustion engine(ICE)are almost on the edge of their existence.At present,the development of the production of electric vehicles should be considered as a promising direction of the Iranian automobile industry.At the moment,this market in Iran is not yet occupied by foreign companies,and therefore national companies have a chance to use the strategy of“growth together with the market”.展开更多
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...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.展开更多
The massive development of internet of things(IoT)technologies is gaining momentum across all areas of their possible deployment—spanning from Industry 4.0 to eHealth,smart city,agriculture or waste management.This o...The massive development of internet of things(IoT)technologies is gaining momentum across all areas of their possible deployment—spanning from Industry 4.0 to eHealth,smart city,agriculture or waste management.This ongoing development is further pushed forward by the gradual deployment of 5G networks.With 5G capable smart devices,it will be possible to transfer more data with shorter latency thereby resulting in exciting new use cases such as Massive IoT.Massive-IoT(low-power wide area network-LPWAN)enables improved network coverage,long device operational lifetime and a high density of connections.Despite all the advantages of massive-IoT technology,there are certain cases where the original concept cannot be used.Among them are dangerous explosive environments or issues caused by subsurface deployment(operation during winter months or dense greenery).This article presents the concept of a hybrid solution of IoT LoRaWAN(long range wide area network)/IRC-VLC(infrared communication,visible light communication)technology,which combines advantages of both technologies according to the deployment scenario.展开更多
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 indus...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.展开更多
Robots of today are eager to leave constrained industrial environments and embrace unexplored and unstructured areas, for extensive applications in the real world as service and social robots. Hence, in addition to th...Robots of today are eager to leave constrained industrial environments and embrace unexplored and unstructured areas, for extensive applications in the real world as service and social robots. Hence, in addition to these new physical frontiers, they must face human ones, too. This implies the need to consider a human-robot interaction from the beginning oft_he design; the possibility for a robot to recognize users' emotions and, in a certain way, to properly react and "behave". This could play a fundamental role in their integration in society. However, this capability is still far from being achieved. Over the past decade, several attempts to implement automata for different applications, outside of the industry, have been pursued. But very few applications have tried to consider the emotional state of users in the behavioural model of the robot, since it raises questions such as: how should human emotions be modelled for a correct representation of their state of mind? Which sensing modalities and which classification methods could be the most feasible to obtain this desired knowl- edge? Furthermore, which applications are the most suitable for the robot to have such sensitivity? In this context, this paper aims to provide a general overview of recent attempts to enable robots to recognize human emotions and interact properly.展开更多
基金This work was partially supported by the Royal Society of UK and the National Natural Science Foundation of PRC (No. 60175028).
文摘A support vector rule based method is investigated for the construction of motion controllers via natural language training. It is a two-phase process including motion control information collection from natural language instructions, and motion information condensation with the aid of support vector machine (SVM) theory. Self-organizing fuzzy neural networks are utilized for the collection of control rules, from which support vector rules are extracted to form a final controller to achieve any given control accuracy. In this way, the number of control rules is reduced, and the structure of the controller tidied, making a controller constructed using natural language training more appropriate in practice, and providing a fundamental rule base for high-level robot behavior control. Simulations and experiments on a wheeled robot are carried out to illustrate the effectiveness of the method.
基金This research was funded by the European Regional Development Fund in the Research Centre of Advanced Mechatronic Systems project, project number CZ.02.1.01/0.0/0.0/16_019 /0000867by the Ministry of Education of the Czech Republic, Project No. SP2021/32.
文摘This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction.Modern vehicles are nowadays increasingly supporting voice commands,which are one of the pillars of autonomous and SMART vehicles.Robust speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle back-ground noise.This article presents the new concept of a hybrid system which is implemented as a virtual instrument.The highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle background noise reduction.The study also presents a unique concept of an adaptive system using intelligent clusters of distributed next generation 5G data networks,which allows the exchange of interference information and/or optimal hybrid algorithm settings between individual vehicles.On average,the unfiltered voice commands were successfully recognized in 29.34%of all scenarios,while the LMS reached up to 71.81%,and LMS-ICA hybrid improved the performance further to 73.03%.
基金Thework and the contributions were supported by the project SV4502261/SP2022/98‘Biomedical Engineering systems XVIII’.
文摘The usability assessment of a pacemaker is a complex task where the dedicated programmer for testing programmed algorithms is necessary.This paper provides the outcomes of development and complex testing of the artificial cardiac system to evaluate the pacemaker’s functionality.In this work,we used the modular laboratory platform ELVIS II and created graphical user interface in LabVIEW programming environment.The electrical model of the heart allows signals generation(right atrium,right ventricle)and the monitoring of the stimulation pulses.The LabVIEW user interface allows to set the parameters of the generated signals and the simulation of the cardiac rhythm disorders as well as the monitoring and visualization of the pacemaker behavior in real-time.The results demonstrate the capability of proposed system to evaluate the paced and sensed pulses.The proposed solution allows the scientists to test the behavior of any cardiac pacemaker for its pre-programmed settings and pacing mode.In addition,the proposed system can simulate various disorders and test cardiac pacemakers in different working modes.
基金This research was funded by the European Regional Development Fund in the Research Centre of Advanced Mechatronic Systems project,Project Number CZ.02.1.01/0.0/0.0/16_019/0000867 and by 543 the Ministry of Education of the Czech Republic,Project No.SP2021/32.
文摘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).
文摘This paper proposes a solution to controls warm robots in an effort to avoid obstacles, moving to the goal by the method of Null Space based Behavior (NSB) control of an individual in the swarm. This paper also provides the stability analysis of the converging process by investigating the relationship between single agents, and the analysis result is proved by using the Lyapunov theory. Finally, the simulation results in two-dimensional space have confirmed the obtained theoretical results.
文摘The article analyzes the problems of introducing electric vehicles,as well as their difference from cars with internal combustion engines.This type of transport has long been included in our everyday life.Today,in the era of the heyday of technology,a person understands that cars with an internal combustion engine(ICE)are almost on the edge of their existence.At present,the development of the production of electric vehicles should be considered as a promising direction of the Iranian automobile industry.At the moment,this market in Iran is not yet occupied by foreign companies,and therefore national companies have a chance to use the strategy of“growth together with the market”.
基金This work was supported by the project SP2021/29,“Development of algorithms and systems for control,measurement and safety applications VII”of the Student Grant System,VSB-TU Ostrava.This work was also supported by the European Regional Development Fund in the Research Centre of Advanced Mechatronic Systems project,Project Number CZ.02.1.01/0.0/0.0/16_019/0000867 under the Operational Programme for ResearchDevelopment and Education.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N◦856670.
文摘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.
基金This work was supported by the European Regional Development Fund in the Research Centre of Advanced Mechatronic Systems project,Project Number CZ.02.1.01/0.0/0.0/16_-019/0000867 within the Operational Programme Research,Development and Education,and in part by the Ministry of Education of the Czech Republic under Project SP2021/32.
文摘The massive development of internet of things(IoT)technologies is gaining momentum across all areas of their possible deployment—spanning from Industry 4.0 to eHealth,smart city,agriculture or waste management.This ongoing development is further pushed forward by the gradual deployment of 5G networks.With 5G capable smart devices,it will be possible to transfer more data with shorter latency thereby resulting in exciting new use cases such as Massive IoT.Massive-IoT(low-power wide area network-LPWAN)enables improved network coverage,long device operational lifetime and a high density of connections.Despite all the advantages of massive-IoT technology,there are certain cases where the original concept cannot be used.Among them are dangerous explosive environments or issues caused by subsurface deployment(operation during winter months or dense greenery).This article presents the concept of a hybrid solution of IoT LoRaWAN(long range wide area network)/IRC-VLC(infrared communication,visible light communication)technology,which combines advantages of both technologies according to the deployment scenario.
基金This work was supported by the European Regional Development Fund in Research Platform focused on Industry 4.0 and Robotics in Ostrava project CZ.02.1.01/0.0/0.0/17_-049/0008425 within the Operational Programme Research,Development and Education,Project Nos.SP2021/32 and SP2021/45.
文摘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.
文摘Robots of today are eager to leave constrained industrial environments and embrace unexplored and unstructured areas, for extensive applications in the real world as service and social robots. Hence, in addition to these new physical frontiers, they must face human ones, too. This implies the need to consider a human-robot interaction from the beginning oft_he design; the possibility for a robot to recognize users' emotions and, in a certain way, to properly react and "behave". This could play a fundamental role in their integration in society. However, this capability is still far from being achieved. Over the past decade, several attempts to implement automata for different applications, outside of the industry, have been pursued. But very few applications have tried to consider the emotional state of users in the behavioural model of the robot, since it raises questions such as: how should human emotions be modelled for a correct representation of their state of mind? Which sensing modalities and which classification methods could be the most feasible to obtain this desired knowl- edge? Furthermore, which applications are the most suitable for the robot to have such sensitivity? In this context, this paper aims to provide a general overview of recent attempts to enable robots to recognize human emotions and interact properly.