Constrained visual servoing under uncertain dynamics

In visual servoing, limitations in the field of view of the vision sensors are either ignored or treated at the kinematic level. The former can easily jeopardise task success, while the latter reduces the maximum achievable robotic motion speeds. In this work, the aforementioned literature gap is filled by designing and rigorously analysing a torque controller that guarantees prescribed transient and steady-state performance attributes on the image feature coordinate errors, while respecting the field-of-view constraints. No path planning and no information regarding the actual system dynamics are required. In addition, no approximation structures (i.e. neural networks, fuzzy systems, etc.) are utilised to acquire such knowledge. The proposed visual servo controller is static, involving very few and simple calculations to produce the control signal, making its implementation on embedded control platforms straightforward. Simulation studies are utilised to illustrate the motivation and to clarify–verify the theoretical findings.     

Epipolar line estimation and rectification for stereo image pairs

The assumption that epipolar lines are parallel to image scan lines is made in many algorithms for stereo analysis. If valid, it enables the search for corresponding image features to be confined to one dimension and, hence, simplified. An algorithm that generates a vertically aligned stereo pair by warped resampling is described. The method uses grey scale image matching between the components of the stereo pair but confined to feature points.     

Electrical properties of LiNbO3 (electrolyte)/Cu (anode) bi-layers

In this work specific film structures of Li-Nb-O/Li/Li-Nb-O are investigated by AC Impedance Spectroscopy measurements at different temperatures. This gives the opportunity to investigate properties of the material itself and, at the same time, to consider the influence of the grain boundaries on the ionic behavior of the polycrystalline Lithium Niobate. On the other hand, LiNbO₃/Li/Cu multi-layers are studied as electrolyte/anode bi-layers and potential parts of “Li-free” microbatteries. The Li deficiency in the as deposited Li-Nb-O films is cured by forming a “sandwich” of Li-Nb-O/Li/Li-Nb-O, which after annealing becomes ionic conductor. The electrical behavior of an annealed film depends on two sources. The first is due to properties of the material itself and the second is based on the network of the grain boundaries. The average size of the grains is strongly influenced by the structure of the ohmic-contact/substrate. The electrical behavior of the electrolyte/anode interface of the “Li-free” structure LiNbO₃/Li/Cu/Au is very similar to the impedance measurements of the single LiNbO₃ single films. The whole multilayer structure, though, presents a third relaxation time which is consistent of a small resistance. This resistance is independent of temperature and it seems that is due to the metallic interface Li/Cu/Au.     

Wavelength-Conversion-Based Protocols for Single-Hop Photonic Networks with Bursty Traffic

WDM star networks using fixed lasers and tunable optical filters are favored by the current state-of-the-art in technology over the other WDM star architectural forms. However, networks of this architectural form suffer from low efficiency when the offered traffic is bursty. Under bursty traffic conditions, it is probable that some wavelengths are idle, while some other wavelengths are overloaded. Therefore, the overall network performance is degraded. In this paper, a new MAC protocol which is capable of operating efficiently under bursty traffic conditions is introduced. According to the proposed protocol an array of tunable wavelength converters is placed at the network hub in order to uniformly distribute the incoming packets to the available wavelengths. In this way, the load is balanced between the wavelengths and consequently, the network performance is improved. The performance of the proposed protocol is studied via analytical and simulation results which indicate that a WDM Star network operating under this protocol achieves a high throughput-delay performance under both bursty and non-bursty traffic conditions.     

Massive MIMO Systems for 5G Communications

Massive MIMO will improve the performance of future 5G systems in terms of data rate and spectral efficiency, while accommodating a large number of users. Furthermore, it allows for 3D beamforming in order to provide more degrees of freedom and increase the number of high-throughput users. Massive MIMO is expected to provide more advantages compared to other solutions in terms of energy and spectral efficiency. This will be achieved by focusing the radiation towards the direction of the intended users, thus implementing simultaneous transmission to many users while keeping interference low. It can boost the capacity compared to a conventional antenna solution, resulting in a spectral efficiency up to 50 times greater than that provided by actual 4G technology. However, to take full advantage of this technology and to overcome the challenges of implementation in a real environment, a complicated radio system is required. The purpose of this work is to present the MIMO technology evolution and challenges in a simple introductory way and investigate potential system enhancements.

     

A survey of 14 computed tomography scanners in Greece and 32 scanners in Italy. Examination frequencies,dose reference values,effective doses and doses to organs

A survey of examination frequencies, dose reference values, effective doses and doses to organs involving 14 scanners from Greece and 32 scanners from Italy was carried out for the years 1999 and 2000. Examination frequencies per scanner and per year were found to be 3590 for Greece and 4520 for Italy. For the types of examinations considered, CDTI(W) and DLP measurements were taken. Also scan lengths used for the same types of examinations were monitored. For the same types of examinations effective doses were calculated by two methods, and it was found that their mean values ranged from 13.1 mSv for thoracic spine to 1.6 mSv for the brain examinations. From the data of the 14 Greek laboratories, doses to organs were calculated and it was found that the thyroid receives 50.2 +/- 19.8 mGy during a cervical spine examination while the gonads receive 17.8 +/- 6.9 mGy during a routine pelvis examination.     

Updating robust reliability using structural test data

The concept of robust reliability is defined to take into account uncertainties from structural modeling in addition to the uncertain excitation that a structure will experience during its lifetime. A Bayesian probabilistic methodology for system identification is integrated with probabilistic structural analysis tools for the purpose of updating the assessment of the robust reliability based on dynamic test data. Methods for updating the structural reliability for both identifiable and unidentifiable models are presented. Application of the methodology to a simple beam model of a single-span bridge with soil-structure interaction at the abutments, including a case with a tuned-mass damper attached to the deck, shows that the robust reliabilities computed before and after updating with “measured” dynamic data can differ significantly.     

Leakage detection in water pipe networks using a Bayesian probabilistic framework

A Bayesian system identification methodology is proposed for leakage detection in water pipe networks. The methodology properly handles the unavoidable uncertainties in measurement and modeling errors. Based on information from flow test data, it provides estimates of the most probable leakage events (magnitude and location of leakage) and the uncertainties in such estimates. The effectiveness of the proposed framework is illustrated by applying the leakage detection approach to a specific water pipe network. Several important issues are addressed, including the role of modeling error, measurement noise, leakage severity and sensor configuration (location and type of sensors) on the reliability of the leakage detection methodology. The present algorithm may be incorporated into an integrated maintenance network strategy plan based on computer-aided decision-making tools.     

On statistical inference in time series analysis of the evolution of road safety

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research.     

A GIS-based methodology for identifying pedestrians’ crossing patterns

A pedestrian trip is a spatiotemporal process going through different states and related to different decisions made at certain times and locations on the urban network. The analysis of pedestrian trips in terms of crossing patterns is a complex task, which is often further limited by a lack of appropriate and detailed data. The objective of this research is the development and testing of appropriate indicators of pedestrian crossing behavior along urban trips, and a methodology for collecting and processing the data required for the analysis of this behavior. First, a comprehensive set of indicators for the assessment of pedestrian behavior in urban areas is proposed (i.e. average trip length, number, type and location of crossings). Then, a GIS tool is developed for the storage and integration of information on pedestrian trips, and the crossings made during the trips, with other geographical information (e.g. road network function and geometry, traffic control and pedestrian facilities). The proposed approach is then tested at network level on a sample of pedestrian trips collected by a field survey. The results suggest specific patterns of pedestrian crossing behavior, such as the tendency to cross at the beginning of the trip and the tendency to cross at mid-block locations when signalized junctions are not available. The results are further discussed in terms of urban planning and management implications. It is concluded that the proposed approach is very efficient for the analysis of pedestrian crossing behavior in urban areas.