VISIR+ is an Erasmus+ project that aims to develop educational modules for electric and electronic circuits theory and practice following an enquiry-based teaching and learning methodology. The project has installed five new VISIR remote labs in Higher Education Institutions located in Argentina and Brazil, to allow students doing more experiments and hence acquire better experimental skills, through a combination of traditional (hands-on), remote and virtual laboratories. A key aspect for the success of this project was to motivate and train teachers in the underpinning educational methodology. As such, VISIR+ adopted a 3-tier training process to effectively support the use of VISIR in the Institutions that received it. This process is based on the "train the trainer" approach, which required the participating partner institutions to identify and engage a number of associated partners, interested in using their newly installed remote lab. To measure the quality of the training process, the same satisfaction questionnaire was used in all training actions. This paper presents a detailed description of the training actions along with the analysis of the satisfaction questionnaire results. Major conclusions are that the quality level of the training process remained practically the same across all training actions and that trainees sometimes considered the practical use of the VISIR remote lab as difficult, irrespectively of where and when the training action took place.
The present paper focus on the use of remote laboratories in higher education from a sustainability viewpoint. The particular case of engineering education, and, within it, the more specific subject of experiments with electrical and electronic circuits is presented first, to then discuss the benefits of using remote labs, while considering the three dimensions of sustainable development, i.e.: economic practice, environmental protection, and social integration. The paper debates how remote labs address each dimension. © 2018 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
Experimenting is fundamental to the training process of all scientists and engineers. While experiments have been traditionally done inside laboratories, the emergence of Information and Communication Technologies added two alternatives accessible anytime, anywhere. These two alternatives are known as virtual and remote laboratories and are sometimes indistinguishably referred as online laboratories. Similarly to other instructional technologies, virtual and remote laboratories require some effort from teachers in integrating them into curricula, taking into consideration several factors that affect their adoption (i.e., cost) and their educational effectiveness (i.e., benefit). This chapter analyzes these two dimensions and sustains the case where only through international cooperation it is possible to serve the large number of teachers and students involved in engineering education. It presents an example in the area of electrical and electronics engineering, based on a remote laboratory named Virtual Instruments System in Reality, and it then describes how a number of European and Latin American institutions have been cooperating under the scope of an Erasmus+ project, for spreading its use in Brazil and Argentina.
This paper describes the performance of the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter for multiple human tracking in an intelligent vision system. Human movement trajectories were observed with a camera and tracked by the GM-PHD filter. The filter multi-target tracking ability was validated by two random motion trajectories in the paper. To evaluate the filter performance in relation to the target movement, the motion velocity and angular velocity as key evaluation factors were proposed. A circular motion model was implemented for simplified analysis of the filter tracking performance. The results indicate that the mean absolute error defined as the difference between the filter prediction and the ground truth is proportional to the motion speed and angular velocity of the target. The error is only slightly affected by the tracking targets’ number.
This paper evaluates the performance of the Gaussian Mixture Probability Hypothesis Density (GM-PHD) filter for tracking multiple targets in an intelligent vision system. A stereo vision camera is used to get the left and right image sequences in order to extract 3-D coordinates of the targets' positions in the real world scene. The 3-D trajectories of the targets are tracked by a GM-PHD filter. Moreover, the label continuity of the targets is guaranteed by a new method of labeling. Motion speed and angular velocity are proposed for the evaluation of the accuracy and label continuity of the filter in the implemented 3-D test motion model. The simulation results for two moving targets show that the proposed system not only robustly tracks them, but also maintains the label continuity of the two targets.
The depth spatial quantization uncertainty is one of the factors which influence the depth reconstruction accuracy caused by a discrete sensor. This paper discusses the quantization uncertainty distribution, introduces a mathematical model of the uncertainty interval range, and analyzes the movements of the sensors in an Intelligent Vision Agent System. Such a system makes use of multiple sensors which control the deployment and autonomous servo of the system. This paper proposes a dithering algorithm which reduces the depth reconstruction uncertainty. The algorithm assures high accuracy from a few images taken by low-resolution sensors. The dither signal is estimated and then generated through an analysis of the iso-disparity planes. The signal allows for control of the camera movement. The proposed approach is validated and compared with a direct triangulation method. The simulation results are reported in terms of depth reconstruction error statistics. The physical experiment shows that the dithering method reduces the depth reconstruction error.
The Intelligent Vision Agent System, IVAS, is a system for automatic target detection, identification and information processing for use in human activities surveillance. This system consists of multiple sensors, and with control of their deployment and autonomous servo. Finding the optimal configuration for these sensors in order to capture the target objects and their environment to a required specification is a crucial problem. With a stereo pair of sensors, the 3D space can be discretized by an iso-disparity surface, and the depth reconstruction accuracy of the space is closely related to the iso-disparity curve positions. This paper presents a method to enable planning the position of these multiple stereo sensors in indoor environments. The proposed method is a mathematical geometry model, used to analyze the iso-disparity surface. We will show that the distribution of the iso-disparity surface and the depth reconstruction accuracy are controllable by the parameters of such model. This model can be used to dynamically adjust the positions, poses and baselines lengths of multiple stereo pairs of cameras in 3D space in order to get sufficient visibility and accuracy for surveillance tracking and 3D reconstruction. We implement the model and present uncertainty maps of depth reconstruction calculated while varying the baseline length, focal length, stereo convergence angle and sensor pixel length. The results of these experiments show how the depth reconstruction uncertainty depends on stereo pair’s baseline length, zooming and sensor physical properties.
The sensor-shifted stereo camera provides the mechanism for obtaining 3D information in a wide field of view. This novel kind of stereo requires a simpler matching process in comparison to convergence stereo. In addition to this, the uncertainty of depth estimation of a target point in 3D space is defined by the spatial quantization caused by the digital images. The dithering approach is a way to reduce the depth reconstruction uncertainty through a controlled adjustment of the stereo parameters that shift the spatial quantization levels. In this paper, a mathematical model that relates the stereo setup parameters to the iso-disparities is developed and used for depth estimation. The enhancement of the depth measurement accuracy for this kind of stereo through applying the dithering method is verified by simulation and physical experiment. For the verification, the uncertainty of the depth measurement using dithering is compared with the uncertainty produced by the direct triangulation method. A 49% improvement of the uncertainly in the depth reconstruction is proved.
The intelligent multi-sensor system is a system for target detection, identification and information processing for human activities surveillance and ambient assisted living. This paper describes RFID multi-target tracking using the Gaussian Mixture Probability Hypothesis Density, GM-PHD, algorithm. The multi target tracking ability of the proposed solution is demonstrated in a simulation and real environment. A performance comparison of the Levenberg-Marquardt algorithm with and without the GM-PHD filter shows that the GM-PHD algorithm improves the accuracy of tracking and target position estimation significantly. This improvement is demonstrated by a simulation and by a physical experiment.
Wireless sensor networks, WSN, for which development has begun by military applications, are nowadays applied to all human activities; e.g. in medicine for patience monitoring or to reduce the effects of disasters. Therefore, the WSNs area has been also one of the emerging and fast growing scientific fields. Increasing interest of WSNs is even caused by equally intense growth of interest in the Internet of Things domain, IoT, in which WSNs constitute a significant part. These reasons have brought about developing low cost, low-power and multi-function sensor nodes. However, the major fact that sensor nodes run quickly out of energy has been an issue and many energy efficient routing protocols have been proposed to solve this problem. Case study presented in this paper concern design of WSN in IoT concept from system lifetime perspective. A hierarchical routing technique, which shows energy efficiency, has been validated. Simulation results show that chosen technique prolongs the lifetime of the WSN compared to other investigated clustering schemes. The advantages of this method are validated by comparative studies. Index Terms - Energy efficiency; Internet of Things, routing protocol; wireless sensor networks.
The paper presents a new Automatic Waterjet Positioning Vision System (AWPVS) and investigates components of workpiece positioning accuracy. The main purpose of AWPVS is to precisely identify the position and rotation of a workpiece placed on a waterjet machine table. Two webcams form a basis for the system, and constitute its characteristics. The proposed algorithm comprises various image processing techniques to assure a required identification precision. To validate the PVS identification quality, synthetic images were applied under various conditions. The analysis ascertains dependence of an object detection rate and accuracy on a size of cropping frame. Experimental results of the proposed PVS prototype prove that a combination of the vision algorithm and webcams is an alternative to dedicated expensive industrial vision systems. The two main components of AWPVS uncertainty, a machine component and PSV component are discerned and estimated.
Aviation reports indicate that between 1988 and 2019 there were 292 human deaths and 327 injuries that had been reported from wildlife strikes with airplanes. To minimize these numbers, a new approach to airport Wildlife Hazard Management (WHM) is presented in the following article. The proposed solution is based on the data fusion of thermal and vision streams, which are used to improve the reliability and adaptability of the real-time WHM system. The system is designed to operate under all environmental conditions and provides advance information on the fauna presence on the airport runway. The proposed sensor fusion approach was designed and developed using user-driven design methodology. Moreover, the developed system has been validated in real-case scenarios and previously installed at an airport. Performed tests proved detection capabilities during day and night of dog-sized animals up to 300 meters. Moreover, by using machine learning algorithms during daylight, the system was able to classify person-sized objects with over 90 % efficiency up to 300 meters and dog-sized objects up to 200 meters. The general accuracy of the threat level based on the three safety zones was 94 %. © 2022 Kauno Technologijos Universitetas. All rights reserved.
Developing technologies associated with tracking human movement and behaviour enable new applications for competence assessments from training results of professionals, such as medical staff, sportsmen or emergency servicemen. This article considers a methodological approach to design a system for firefighter's skills and competence assessment. Assessed training features such as in-building behaviour and tasks execution are analysed based on data gathered with wireless Ultra-Wideband Real-Time Location System, UWB RTLS, and Inertial Measurement Unit, IMU. The assessment is based on the predefined required training tasks, the expert's expertise and results of the trainee's test. The Unity game engine is used for data processing and visualization. As the comprehensive final map of the trainee's skills, the spider diagram is applied and the single score method provides the conclusive statement. The proposed solution was verified experimentally in real environment.
- Over the last few decades, life expectancy has increased significantly. However, elderly people who live on their own often need assistance due to mobility difficulties, symptoms of dementia or other health problems. In such cases, an autonomous supporting system may be helpful. This paper proposes the Internet of Things (IoT)-based information system for indoor and outdoor use. Since the conducted survey of related works indicated a lack of methodological approaches to the design process, therefore a Design Methodology (DM), which approaches the design target from the perspective of the stakeholders, contracting authorities and potential users, is introduced. The implemented solution applies the three-axial accelerometer and magnetometer, Pedestrian Dead Reckoning (PDR), thresholding and the decision trees algorithm. Such an architecture enables the localization of a monitored person within four room-zones with accuracy; furthermore, it identifies falls and the activities of lying, standing, sitting and walking. Based on the identified activities, the system classifies current activities as normal, suspicious or dangerous, which is used to notify the healthcare staff about possible problems. The real-life scenarios validated the high robustness of the proposed solution. Moreover, the test results satisfied both stakeholders and future users and ensured further cooperation with the project. © 2017 by the authors.
Sustainability is currently a general concern in society and in particular in the use of laboratories for educational purposes. Although laboratories are unavoidable facilities for education, they often produce waste resulting from students' experiments. To contribute for sustainable solutions in education, the use of remote laboratories instead of the traditional hands-on laboratories should be considered in every engineering course. It is precisely this aspect that is discussed in the current paper. Some comments about the importance of sustainability in education are made. Later, it is described the use of a remote laboratory named VISIR in a course held at the Polytechnic of Porto - School of Engineering, for the conduction of an electronic experiment named Schmitt Trigger. At the end, some comments about the contribution of this remote lab for sustainability in education, are provided. © 2019 ACM.
Social demands have promoted an educational approach based on an 'anywhere and anytime' premise. Remote laboratories have emerged as the answer to the demands of technical educational areas for adapting themselves to this scenario. The result has not only benefit distance learning students but has provided new learning scenarios both for teachers and students as well as allowing a flexible approach to experimental topics. However, as any other solution for providing practical scenarios (hands-on labs, virtual labs or simulators), remote labs face several constraints inherited from the subsystems of its deployment - hardware (real instruments, equipment and scenario) and software (analog/digital conversions, communications, workbenches, etc.}. This paper describes the Erasmus+ project Platform Integration of Laboratories based on the Architecture of visiR (PILAR) which deals with several units of the federation installed in different educational institutions and devoted to analog electronics and electrical circuits. Based on the limitations of remote labs, the need for the federation will be justified and its benefits will be described by taking advantage of its strengths. The challenges that have come up during the different stages and the different approaches to design are also going to be described and analyzed. © 2018 IEEE.
The PILAR (Platform Integration of Laboratories based on the Architecture of visiR) Erasmus Plus project started in September 2016 and will last three years. The core of the PILAR project is the VISIR remote laboratory-Virtual Instruments System In Reality-. The project aims for a federation of five of the existing VISIR nodes, sharing experiments, capacity and resources among partners, and to provide access to VISIR remote lab, through PILAR consortium, to students from other educational institutions. PILAR will be the framework from which management tasks will be performed and laboratories/experiments will be shared. PILAR will also foster the Special Interest Group of VISIR under the Global Online Laboratory Consortium (GOLC) of the International Association of Online Engineering (IAOE). © 2018 IEEE.
In 2020, over 10,000 bird strikes were reported in the USA, with average repair costs exceeding $200 million annually, rising to $1.2 billion worldwide. These collisions of avifauna with airplanes pose a significant threat to human safety and wildlife. This article presents a system dedicated to monitoring the space over an airport and is used to localize and identify moving objects. The solution is a stereovision based real-time bird protection system, which uses IoT and distributed computing concepts together with advanced HMI to provide the setup’s flexibility and usability. To create a high degree of customization, a modified stereovision system with freely oriented optical axes is proposed. To provide a market tailored solution affordable for small and medium size airports, a user-driven design methodology is used. The mathematical model is implemented and optimized in MATLAB. The implemented system prototype is verified in a real environment. The quantitative validation of the system performance is carried out using fixed-wing drones with GPS recorders. The results obtained prove the system’s high efficiency for detection and size classification in real-time, as well as a high degree of localization certainty. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
Wind as a clean and renewable energy source has been used by humans for centuries. However, in recent years with the increase in the number and size of wind turbines, their impact on avifauna has become worrisome. Researchers estimated that in the U.S. up to 500,000 birds die annually due to collisions with wind turbines. This article proposes a system for mitigating bird mortality around wind farms. The solution is based on a stereo-vision system embedded in distributed computing and IoT paradigms. After a bird’s detection in a defined zone, the decision-making system activates a collision avoidance routine composed of light and sound deterrents and the turbine stopping procedure. The development process applies a User-Driven Design approach along with the process of component selection and heuristic adjustment. This proposal includes a bird detection method and localization procedure. The bird identification is carried out using artificial intelligence algorithms. Validation tests with a fixed-wing drone and verifying observations by ornithologists proved the system’s desired reliability of detecting a bird with wingspan over 1.5 m from at least 300 m. Moreover, the suitability of the system to classify the size of the detected bird into one of three wingspan categories, small, medium and large, was confirmed. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Cardiovascular pathologies cause 23.5% of human deaths, worldwide. An auto-diagnostic system monitoring heart activity, which can identify the early symptoms of cardiac illnesses, might reduce the death rate caused by these problems. Phonocardiography (PCG) is one of the possible techniques able to detect heart problems. Nevertheless, acoustic signal enhancement is required since it is exposed to various disturbances coming from different sources. The most common denoising enhancement is based on the Wavelet Transform (WT). However, the WT is highly susceptible to variations in the noise frequency distribution. This paper proposes a new adaptive denoising algorithm, which combines WT and Time Delay Neural Networks (TDNN). The acquired signal is decomposed by means of the WT using the coif five-wavelet basis at the tenth decomposition level and then provided as input to the TDNN. Besides the advantage of adaptive thresholding, the reason for using TDNNs is their capacity of estimating the Inverse Wavelet Transform (IWT). The best parameters of the TDNN were found for a NN consisting of 25 neurons in the first and 15 in the second layer and the delay block of 12 samples. The method was evaluated on several pathological heart sounds and on signals recorded in a noisy environment. The performance of the developed system with respect to other wavelet-based denoising approaches was validated by the online questionnaire.
Robotization has become common in modern factories due to its efficiency and cost-effectiveness. Lots of robots and manipulators share their workspaces with humans what could lead to hazardous situations causing health damage or even death. This article presents a real-time safety system applying the distributed computing paradigm for a collaborative robot. The system consists of detection/sensing modules connected with a server working as decision-making system. Each configurable sensing module pre-processes vision information and then sends to the server the images cropped to new objects extracted from a background. After identifying persons from the images, the decision-making system sends a request to the robot to perform pre-defined action. In the proposed solution, there are indicated three safety zones defined by three different actions on a robot motion. As identification method, state-of-the-art of Machine Learning algorithms, the Histogram of Oriented Gradients (HOG), Viola-Jones, and You Only Look Once (YOLO), have been examined and presented. The industrial environment tests indicated that YOLOv3 algorithm outperformed other solutions in terms of identification capabilities, false positive rate and maximum latency.
This paper presents how a plagiarism component has been integrated in a Research Methodology course for Engineering Master students at Blekinge Institute of Technology, Sweden. The plagiarism issue was approached from an educational perspective, rather than a punitive. The course director and librarians developed this part of the course in close collaboration. One part of the course is dedicated to how to cite, paraphrase and reference, while another part stresses the legal and ethical aspects of research. Currently, the majority of the students are international, which means there are intercultural and language aspects to consider. In order to evaluate our approach to teaching about plagiarism, we conducted a survey. The results of the survey indicate a need for education on how to cite and reference properly in order to avoid plagiarism, a result which is also supported by students' assignment results. Some suggestions are given for future development of the course.
I detta bidrag presenterar vi en uppläggning av integrerade kurser i matematik och tillämpningar, vilken använts inom högskoleingenjörsutbildningen vid Högskolan i Kalmar. Kursverksamheten, som bedrivs inom ramen för kurspaketet ingenjörsvetenskap, tillgodoser såväl behovet av att betona matematikens roll som ett generellt och abstrakt verktyg för problemlösning som behovet av att ge studenterna bra baskunskaper i matematik i anslutning till möjliga tillämpningsområden.
The purpose of this research is to improve performance of the Hybrid Scene Analysis - Neural Network indoor localization algorithm applied in Real-time Locating System, RTLS. A properly customized structure of Neural Network and training algorithms for specific operating environment will enhance the system’s performance in terms of localization accuracy and precision. Due to nonlinearity and model complexity, a heuristic analysis is suitable to evaluate NN performance for different environmental conditions. Efficiency of the proposed customization of a Neural Network is verified by simulations and validated by physical experiments. This research also concerns the influence of size of Neural Network training set. The results prove that, better localization accuracy is with a NN system which is properly customized with respect to a training method, number of neurons and type of transfer function in the hidden layer and also type of transfer function in the output layer.
The assessment of skills is essential and desirable in areas such as medicine, security, and other professions where mental, physical, and manual skills are crucial. However, often such assessments are performed by people called “experts” who may be subjective and are able to consider a limited number of factors and indicators. This article addresses the problem of the objective assessment of driving style independent of circumstances. The proposed objective assessment of driving style is based on eight indicators, which are associated with the vehicle’s speed, acceleration, jerk, engine rotational speed and driving time. These indicators are used to estimate three driving style criteria: safety, economy, and comfort. The presented solution is based on the embedded system designed according to the Internet of Things concept. The useful data are acquired from the car diagnostic port—OBD-II—and from an additional accelerometer sensor and GPS module. The proposed driving skills assessment method has been implemented and experimentally validated on a group of drivers. The obtained results prove the system’s ability to quantitatively distinguish different driving styles. The system was verified on long-route tests for analysis and could then improve the driver’s behavior behind the wheel. Moreover, the spider diagram approach that was used established a convenient visualization platform for multidimensional comparison of the result and comprehensive assessment in an intelligible manner. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.
The increased potential and effectiveness of Real-time Locating Systems (RTLSs) substantially influence their application spectrum. They are widely used, inter alia, in the industrial sector, healthcare, home care, and in logistic and security applications. The research aims to develop an analytical method to customize UWB-based RTLS, in order to improve their localization performance in terms of accuracy and precision. The analytical uncertainty model of Angle of Arrival (AoA) localization in a 3D indoor space, which is the foundation of the customization concept, is established in a working environment. Additionally, a suitable angular-based 3D localization algorithm is introduced. The paper investigates the following issues: the influence of the proposed correction vector on the localization accuracy; the impact of the system’s configuration and LS’s relative deployment on the localization precision distribution map. The advantages of the method are verified by comparing them with a reference commercial RTLS localization engine. The results of simulations and physical experiments prove the value of the proposed customization method. The research confirms that the analytical uncertainty model is the valid representation of RTLS’ localization uncertainty in terms of accuracy and precision and can be useful for its performance improvement. The research shows, that the Angle of Arrival localization in a 3D indoor space applying the simple angular-based localization algorithm and correction vector improves of localization accuracy and precision in a way that the system challenges the reference hardware advanced localization engine. Moreover, the research guides the deployment of location sensors to enhance the localization precision.
Real-time Locating Systems (RTLSs) have the ability to precisely locate the position of things and people in real time. They are needed for security and emergency applications, but also for healthcare and home care appliances. The research aims for developing an analytical method to customize RTLSs, in order to improve localization performance in terms of precision. The proposed method is based on Angle of Arrival (AoA), a ranging technique and fingerprinting method along with an analytically defined uncertainty of AoA, and a localization uncertainty map. The presented solution includes three main concerns: geometry of indoor space, RTLS arrangement, and a statistical approach to localization precision of a pair of location sensors using an AoA signal. An evaluation of the implementation of the customized RTLS validates the analytical model of the fingerprinting map. The results of simulations and physical experiments verify the proposed method. The research confirms that the analytically established fingerprint map is the valid representation of RTLS’ performance in terms of precision. Furthermore, the research demonstrates an impact of workspace geometry and workspace layout onto the RTLS’ performance. Moreover, the studies show how the size and shape of a workspace and the placement of the calibration point affect the fingerprint map. Withal, the performance investigation defines the most effective arrangement of location sensors and its influence on localization precision. © 2016 by the authors; licensee MDPI, Basel, Switzerland.
The main purpose of this research is to improve localization accuracy of an active Radio Frequency Identification, RFID tag, in 3D indoor space. The paper presents a new RFID based 3D Indoor Positioning System which shows performance improvement. The proposed positioning system combines two methods: the Scene Analysis technique and Artificial Neural Network. The results of both simulation using Log-Distance Path Loss Model and physical experiments validate that the proposed positioning system improves the localization accuracy of an RFID tag compared with well-known Scene Analysis technique solutions
The purpose of this research is to find an optimal number and configuration of readers in RFID based 3D Indoor Positioning System. The system applies a Hybrid Scene Analysis - Neural Network algorithm to estimate target's position with a desired accuracy. The system's accuracy and cost depend on a number of utilized readers and their arrangement. Readers' deployment is crucial for the localization accuracy too. The system optimization enhances the system cost-efficiency. The arrangement analysis was based on simulations and validated by physical experiment. The results of this research define a trade-off between a number of readers and their deployment and the system performance in terms of localization accuracy.
Emerging digital transformation in industry is noticeable among others in Supply Chain Management (SCM). For instance, applying new-generation digitalized technologies in the Dairy Supply Chain (DSC) enables an increase of manufacturing productivity, improves planning and forecasting, and also enhances competitive capabilities according to Industry 4.0 assumptions. It is worth mentioning, that in modern DSC, high visibility of raw materials, components, products, and processes by all contributors on all stages of DSC is crucial. This article focuses on the transparency aspect of the DSC supported by IoT-based technologies enabling interoperability among all DSC participants. The paper addresses the problem of effective integration of heterogeneous data sources, i.e., deployed new technological IoT solutions with traditional SCM systems and a third-party software component. The main objective of this report is to propose the IoT-based DSC model comprising four chain stages: milk production, milk transportation, milk processing, and dairy products distribution. Moreover, the comprehensive DSC domain ontology as a knowledge model is formulated and described. The ontology aims on improvement of the DSC management efficiency by facilitating interoperability within DSC. The applicability of the proposed ontological model is verified using a sustainable-oriented case study, which estimates the environmental footprint at the milk transportation stage of the DSC. © 2021 Kauno Technologijos Universitetas. All rights reserved.
This paper presents a sensorless algorithm designated for the emergency control of an interior permanent magnet synchronous motor (IPMSM) drive in electric or hybrid vehicle. Special requirements for emergency-activated sensorless algorithms are defined, and shortcomings of state-of-the-art methods in terms of the considered application are discussed. The proposed emergency-activated algorithm is based on analysing the derivatives of motor phase currents measured over the duration of particular inverter states. The method is computationally simple and does not require additional hardware since the derivatives are measured indirectly. A lag between activating the algorithm upon an emergency flying start and re-establishing the torque controllability is defined. The proposed algorithm was implemented in the controller of a laboratory IPMSM vehicle drive and tested under varying operational conditions, including the emergency activation. © 2016 Elsevier Ltd
Speed measurement is one of the key components of intelligent transportation systems. It provides suitable information for traffic management and law enforcement. This paper presents a versatile and analytical model for a video-based speed measurement in form of the probability density function (PDF). In the proposed model, the main factors contributing to the uncertainties of the measurement are considered. Furthermore, a guideline is introduced in order to design a video-based speed measurement system based on the traffic and other requirements. As a proof of concept, the model has been simulated and tested for various speeds. An evaluation validates the strength of the model for accurate speed measurement under realistic circumstances.
The paper focuses on a design of in-situ real time system self-tests of a measurement system. The approach is based on principles of system modelling, pattern identification and validation with several methods presented. These involve several of the aspects of test signals and the design principles are illustrated in two case studies, one in the time domain and the second in the frequency domain. The paper also highlights the significance of rapid prototyping tools. The analysis can be useful as a methodological guide in designing smart sensors with an in-build self-test function.
The wireless sensor networks, which development has begun by military applications, is applied in all human activities; in medicine for patience monitoring, in huge scale environmental monitoring e.g. to reduce the effects of disasters, and even many industrial and everyday applications. Nowadays the area of wireless sensor networks, WSNs is one of the emerging and fast growing fields in the scientific world. This has brought about developing low cost, low-power and multi-function sensor nodes. However, the major fact that sensor nodes run out of energy quickly has been an issue and many energy efficient routing protocols have been proposed to solve this problem and preserve the longevity of the network. This is the reason why routing techniques in wireless sensor network focus mainly on the accomplishment of power conservation. Most of the recent publications have shown many protocols mainly designed to minimize energy consumption in sensor networks. Fast development of wireless sensor networks can also be challenging for a designer, not only due to solution and structure complexities, but first of all due to demanding requirements. Case studies of WSN design are presented in the paper. A hierarchical routing technique which shows energy efficiency has been validated. The technique selects cluster head with highest residual energy in each communication round of transmission but it also takes into account, the shortest distance to the base station from the cluster heads. Simulation results show that hierarchical routing technique with different level of hierarchy prolongs the lifetime of the network compared to other clustering schemes and the residual energy mean value, after some communication rounds of simulation, increases significantly. The presented case study shows the advantages of hierarchical WSN structure. The advantages are validated by comparative studies. The analysis shows that energy efficiency of WSNs can be further improved. For instance the clusters formed dynamically on base of shortest distance to initial cluster head affects the network lifetime of WSN.
The first part of this chapter introduces a mathematical geometry model which is used to analyze the iso-disparity surface. This model can be used to dynamically adjust the positions, poses and baseline lengths of multiple stereo pairs of cameras in 3D space in order to get sufficient visibility and accuracy for surveillance, tracking and 3D reconstruction. The depth reconstruction accuracy is quantitatively analyzed by the proposed model. The proposed iso-disparity mathematical model presents possibility of reliable control of the iso-disparity curves’ shapes and intervals by applying the systems configuration and target properties. In the second part of this chapter, the key factors affecting the accuracy of 3D reconstruction are analysed. It shows that the convergence angle and target distance influence the depth reconstruction accuracy most significantly. The depth accuracy constraints are implemented in the model to control the stereo pair’s baseline length, position and pose. It guarantees a certain accuracy in the 3D reconstruction. The reconstruction accuracy is verified by a cubic reconstruction method. The optimization is implemented by applying the camera, object and stereo pair constraints into the integer linear programming.
The Research Methodology course for postgraduate students is challenging, even for an experienced academic teacher. The primary objective of this course is to prepare participants to conduct scientific research and publish the results. This case study presents an original teaching method applied to Research Methodology with Emphasis on Engineering Science, for international engineering students at Blekinge Institute of Technology in Karlskrona, Sweden. The demanding requirements of the course, a varying number of enrolled students, and a large number of assignments which need to be tracked and guided by the teacher are all conditions that need a custom approach and modern tools. The opportunities offered by e-technologies help to fulfil these course requirements. This article shows how e-tools such Itslearning, Doodle, Zotero or scientific database search engines, can be implemented to support the teaching objectives. Using these tools, a single academic teacher can accomplish the eight-week course of Research Methodology, for up to 180 students working in 60 project groups without compromising teaching quality and students’ satisfaction. The course also has been appreciated by colleagues and mentioned in the Master program evaluation of the Swedish Higher Education Authority.
This paper considers the spectrum sharing network consisting of a pair of primary users (PUs) and a pair of cognitive users (CRs) in a fading channel. The pair of PUs establishes a wireless link as the PU link. The pair of CRs establishes a wireless link as the CR link. The PU link and CR link utilize spectrum simultaneously with different priorities. The PU link has a higher priority to utilize spectrum with respect to the CR link. When the PU link utilizes spectrum, a desired quality of service (QoS) is given to be assured and the CR utilizes spectrum with an opportunistic power scale under this constraint, assuring the desired QoS on the PU link. To compute an optimal opportunistic power scale for the CR link, a fuzzy-based opportunistic power control strategy is proposed based on the Mamdani fuzzy control model using two input variables: the PU’s SNR and PU’s interference channel gain. By the proposed fuzzy-based power control strategy, the desired QoS could be assured on the PU link and the bit error rate (BER) is also reduced compared with the spectrum sharing network without power control strategy.
This paper is focused on the performance evaluation of Accelerated Tests (AT), which are carried out in a rapid manner to estimate life-length of a Device Under Test (DUT). Manufacturers need to preform ATs on the prototype of the product to anticipate its reliability and lifetime. The requirements for higher reliability impose tests of DUT's materials and components in advance. ATs expose products to different stressing environments, which include Electrical Stress, Mechanical Vibration, Temperature Shock, Temperature Cycling, Humidity, and others. An AT profile consists of different parameters, which depend on the DUT, and the most common are: a type of stress, rate of change, stress extreme points. Although these tests are accelerated, they are still time consuming. Furthermore, for large and complex DUTs, the test reliability itself can be doubted due to the involved diversity and uncertainty. In this paper, different experimental methods are applied to optimize the virtual test parameters to obtain reliable results. © 2020 IEEE.
A new method using burial measurements for risk assessment of subsea cable installations is proposed. Only methods comparing the design boundaries have previously been used to verify subsea cable installments. The disadvantage of utilizing design boundaries is the possibility of not fulfilling the risk requirements since the assumed burial depth of the cable and its measurement data can differ, leading to the challenge of assessing how the difference and its uncertainty affect burial risk. We proposed and tested the method for a scenario using seagoing vessel traffic data and sensor characteristics. The analysis is limited to white measurement noise but shows a deviation in risk estimation between the design-and measurement-based assessments. The presented result enables the approximation of the risk assessment for projects of varying specifications. The proposed statistical method is a less conservative way to assess the correct installment of a cable and possibly to evaluate verification specifications. © 2022 IEEE.
Available methods using the burial measurements to assess the subsea cable installations risks compare measurements to the design boundaries. The disadvantage of using this is that the assumed cable burial depths and their measurements can differ. However, it is unclear how the uncertainty in depth affects burial risk; hence, there is a need to verify the burial operations using a proper method to handle this aspect of risk reliability. We proposed a conservative cable burial scenario test, which evaluates the highest deviation between the measured risk and the design risk to indicate differences in risk based on the measurements. The result shows that the most significant deviation could be up to 55%. It proves that measurement uncertainty significantly affects the final risk evaluation. Moreover, this deviation in verifiable risk is not considered in today's boundary-level verification methodology. © 2022 IEEE.
This letter describes an asymmetrical coplanar strip (ACPS) wall to suppress the mutual coupling between two closely spaced 5.8-GHz microstrip antennas. The ACPS wall, which is inserted vertically between the two antennas, introduces an additional coupling path to reduce the antenna coupling, occupying just a small area between the two antennas. The decoupling effect of the proposed structure is verified by the simulation and measurement. The experimental results show that the achieved isolation is better than 35 dB and reaches a maximum of 54.3 dB at 5.8 GHz, with an extremely close antenna distance of 0.03 lambda(0) (edge-to-edge distance). The measured patterns indicate that the proposed structure also improves the radiation of the microstrip antenna.
This paper presents the issue of whispered speech enhancement. Based on multi-band spectral subtraction method where the introduced musical residual noise occurs, the proposed approach performs parametric subtraction according to the WSS (Whispered Sensitive Scale) method that is particular for whispered speech processing and auditory masking model. The algorithm is characterized by a tradeoff mechanism between the amount of the whispered speech distortion, noise reduction, and the level of musical residual noise, which are determined by appropriate adjusting the subtraction parameters. Compared with traditional subtractive-type algorithms, the proposed method results in a significant reduction of musical residual noise. Finally, objective and subjective evaluations are implemented illustrating the improvements over traditional subtractive-type algorithms.
This paper presents results on behavior modeling of a general purpose metal-oxide-semiconductor field-effect transistor (MOSFET) for simulation of power electronics systems requiring accuracy both in steady state and in switching conditions. Methods of parameters extraction, including nonlinearity of parasitic capacitances and steady-state characteristics, are based on manufacturer datasheet and externally measurable characteristics. The MOSFET template is written in the MAST language and simulated in the SABER simulator. Experimental validation of the N-channel power MOSFET-type IRFP240 (Fairchild Semiconductor) rated at 20 A/200 V is performed in a dc/dc boost converter. The main features of the developed model have been compared with the properties of an analytical MOSFET model and a general MOSFET model embedded to a SABER simulator.
In this paper, we discuss a model of quality that makes use of the fuzzily defined variable approach to better understand the concept and, thus, enables the further development of this variable. We propose a general method that may estimate a quality index (QI) that handles both qualitative and quantitative issues. The system further uses a neural network since the system learns how to integrate human factors into a quantitative QI. In our case study, we have examined the measurement of image quality and proposed a theoretical model of pulp quality.
The object of this study is to determine how people interpret measurement data; which factors influence their interpretation and which do not. This study forms part of an investigation series undertaken at the paper pulp company Södra Cell in Sweden (N = 1200 employees), the investigated parameter being "paper pulp quality". The findings presented in the study are the outcomes of a questionnaire that was repeated four times (n1 = 54, n2 = 53, n3 = 43, n4 = 38), an interview (ni = 32) and regular group discussions that included 10 people (nd = 10) and that took place once a month over a three-year period. In order to quantify the quality of the product - paper pulp - different measurements must be combined. This study reveals that different employees prefer different parameters for the quantification of paper pulp quality. This study furthermore shows that there is a correlation between the employees' choice of parameters and their belonging to a particular pulp mill within the company. We also found that external factors, e.g. the opinion of authorities, affected which parameters were favoured when product quality was determined. Furthermore, the data analysis indicates that there is a correlation between the job-position of employees and the way they interpret measurement data related to product quality. Controllers and operators make similar judgments, with the exception of chemists whose opinions appear to deviate. However, the greatest variation found in the study is related to the individual person - independently of education or physical or psychological condition. The study finally proposes a number of preventive measures to improve the uniformity and reliability of measurements conducted at a process company, the most important of which is improved education of all employees who are in a position to influence product quality. © 2007 Elsevier Ltd. All rights reserved.