Parallel modeling of the electric field distribution in the brain

The term "Brain Imaging" identi�es a set of techniques to analyze the structure and/or functional behavior of the brain in normal and/or pathological situations. These techniques are largely used in the study of brain activity. In addition to clinical usage, analysis of brain activity is gaining popularity in others recent �fields, i.e. Brain Computer Interfaces (BCI) and the study of cognitive processes. In this context, usage of classical solutions (e.g. f MRI, PET-CT) could be unfeasible, due to their low temporal resolution, high cost and limited portability. For these reasons alternative low cost techniques are object of research, typically based on simple recording hardware and on intensive data elaboration process. Typical examples are ElectroEncephaloGraphy (EEG) and Electrical Impedance Tomography (EIT), where electric potential at the patient's scalp is recorded by high impedance electrodes. In EEG potentials are directly generated from neuronal activity, while in EIT by the injection of small currents at the scalp. To retrieve meaningful insights on brain activity from measurements, EIT and EEG relies on detailed knowledge of the underlying electrical properties of the body. This is obtained from numerical models of the electric �field distribution therein. The inhomogeneous and anisotropic electric properties of human tissues make accurate modeling and simulation very challenging, leading to a tradeo�ff between physical accuracy and technical feasibility, which currently severely limits the capabilities of these techniques. Moreover elaboration of data recorded requires usage of regularization techniques computationally intensive, which influences the application with heavy temporal constraints (such as BCI). This work focuses on the parallel implementation of a work-flow for EEG and EIT data processing. The resulting software is accelerated using multi-core GPUs, in order to provide solution in reasonable times and address requirements of real-time BCI systems, without over-simplifying the complexity and accuracy of the head models.

On Transport Service Selection in Intermodal Rail/Road Distribution Networks

Intermodal rail/road freight transport constitutes an alternative to long-haul road transport for the distribution of large volumes of goods. The paper introduces the intermodal transportation problem for the tactical planning of mode and service selection. In rail mode, shippers either book train capacity on a per-unit basis or charter block trains completely. Road mode is used for short-distance haulage to intermodal terminals and for direct shipments to customers. We analyze the competition of road and intermodal transportation with regard to freight consolidation and service cost on a model basis. The approach is applied to a distribution system of an industrial company serving customers in eastern Europe. The case study investigates the impact of transport cost and consolidation on the optimal modal split.

Localization and Tracking in Energy-Constrained Networks with Dynamic Connectivity

Systems used for target localization, such as goods, individuals, or animals, commonly rely on operational means to meet the final application demands. However, what would happen if some means were powered up randomly by harvesting systems? And what if those devices not randomly powered had their duty cycles restricted? Under what conditions would such an operation be tolerable in localization services? What if the references provided by nodes in a tracking problem were distorted? Moreover, there is an underlying topic common to the previous questions regarding the transfer of conceptual models to reality in field tests: what challenges are faced upon deploying a localization network that integrates energy harvesting modules? The application scenario of the system studied is a traditional herding environment of semi domesticated reindeer (Rangifer tarandus tarandus) in northern Scandinavia. In these conditions, information on approximate locations of reindeer is as important as environmental preservation. Herders also need cost-effective devices capable of operating unattended in, sometimes, extreme weather conditions. The analyses developed are worthy not only for the specific application environment presented, but also because they may serve as an approach to performance of navigation systems in absence of reasonably accurate references like the ones of the Global Positioning System (GPS). A number of energy-harvesting solutions, like thermal and radio-frequency harvesting, do not commonly provide power beyond one milliwatt. When they do, battery buffers may be needed (as it happens with solar energy) which may raise costs and make systems more dependent on environmental temperatures. In general, given our problem, a harvesting system is needed that be capable of providing energy bursts of, at least, some milliwatts. Many works on localization problems assume that devices have certain capabilities to determine unknown locations based on range-based techniques or fingerprinting which cannot be assumed in the approach considered herein. The system presented is akin to range-free techniques, but goes to the extent of considering very low node densities: most range-free techniques are, therefore, not applicable. Animal localization, in particular, uses to be supported by accurate devices such as GPS collars which deplete batteries in, maximum, a few days. Such short-life solutions are not particularly desirable in the framework considered. In tracking, the challenge may times addressed aims at attaining high precision levels from complex reliable hardware and thorough processing techniques. One of the challenges in this Thesis is the use of equipment with just part of its facilities in permanent operation, which may yield high input noise levels in the form of distorted reference points. The solution presented integrates a kinetic harvesting module in some nodes which are expected to be a majority in the network. These modules are capable of providing power bursts of some milliwatts which suffice to meet node energy demands. The usage of harvesting modules in the aforementioned conditions makes the system less dependent on environmental temperatures as no batteries are used in nodes with harvesters--it may be also an advantage in economic terms. There is a second kind of nodes. They are battery powered (without kinetic energy harvesters), and are, therefore, dependent on temperature and battery replacements. In addition, their operation is constrained by duty cycles in order to extend node lifetime and, consequently, their autonomy. There is, in turn, a third type of nodes (hotspots) which can be static or mobile. They are also battery-powered, and are used to retrieve information from the network so that it is presented to users. The system operational chain starts at the kinetic-powered nodes broadcasting their own identifier. If an identifier is received at a battery-powered node, the latter stores it for its records. Later, as the recording node meets a hotspot, its full record of detections is transferred to the hotspot. Every detection registry comprises, at least, a node identifier and the position read from its GPS module by the battery-operated node previously to detection. The characteristics of the system presented make the aforementioned operation own certain particularities which are also studied. First, identifier transmissions are random as they depend on movements at kinetic modules--reindeer movements in our application. Not every movement suffices since it must overcome a certain energy threshold. Second, identifier transmissions may not be heard unless there is a battery-powered node in the surroundings. Third, battery-powered nodes do not poll continuously their GPS module, hence localization errors rise even more. Let's recall at this point that such behavior is tight to the aforementioned power saving policies to extend node lifetime. Last, some time is elapsed between the instant an identifier random transmission is detected and the moment the user is aware of such a detection: it takes some time to find a hotspot. Tracking is posed as a problem of a single kinetically-powered target and a population of battery-operated nodes with higher densities than before in localization. Since the latter provide their approximate positions as reference locations, the study is again focused on assessing the impact of such distorted references on performance. Unlike in localization, distance-estimation capabilities based on signal parameters are assumed in this problem. Three variants of the Kalman filter family are applied in this context: the regular Kalman filter, the alpha-beta filter, and the unscented Kalman filter. The study enclosed hereafter comprises both field tests and simulations. Field tests were used mainly to assess the challenges related to power supply and operation in extreme conditions as well as to model nodes and some aspects of their operation in the application scenario. These models are the basics of the simulations developed later. The overall system performance is analyzed according to three metrics: number of detections per kinetic node, accuracy, and latency. The links between these metrics and the operational conditions are also discussed and characterized statistically. Subsequently, such statistical characterization is used to forecast performance figures given specific operational parameters. In tracking, also studied via simulations, nonlinear relationships are found between accuracy and duty cycles and cluster sizes of battery-operated nodes. The solution presented may be more complex in terms of network structure than existing solutions based on GPS collars. However, its main gain lies on taking advantage of users' error tolerance to reduce costs and become more environmentally friendly by diminishing the potential amount of batteries that can be lost. Whether it is applicable or not depends ultimately on the conditions and requirements imposed by users' needs and operational environments, which is, as it has been explained, one of the topics of this Thesis.

Propuesta de un marco conceptual para el análisis comparativo de las redes de distribución de dos supermercados online = Proposal of a conceptual framework for the comparative analysis of the distribution networks of two online supermarkets

In this article the network configuration for fulfillment and distribution of online orders of two British retailers is analyzed and compared. For this purpose, it is proposed a conceptual framework that consists of the key following aspects: network configuration, transportation management and location of demand. As a result is not obvious to determine the ideal centralization degree in each case. Finally, it is suggested the future development of an analytic tool that helps to choose the most appropriate model.

A novel ground fault non-directional selective protection method for ungrounded distribution networks

This paper presents a new selective and non-directional protection method to detect ground faults in neutral isolated power systems. The new proposed method is based on the comparison of the rms value of the residual current of all the lines connected to a bus, and it is able to determine the line with ground defect. Additionally, this method can be used for the protection of secondary substation. This protection method avoids the unwanted trips produced by wrong settings or wiring errors, which sometimes occur in the existing directional ground fault protections. This new method has been validated through computer simulations and experimental laboratory tests.

Mesoporous materials for clean energy technologies

Alternative energy technologies are greatly hindered by significant limitations in materials science. From low activity to poor stability, and from mineral scarcity to high cost, the current materials are not able to cope with the significant challenges of clean energy technologies. However, recent advances in the preparation of nanomaterials, porous solids, and nanostructured solids are providing hope in the race for a better, cleaner energy production. The present contribution critically reviews the development and role of mesoporosity in a wide range of technologies, as this provides for critical improvements in accessibility, the dispersion of the active phase and a higher surface area. Relevant examples of the development of mesoporosity by a wide range of techniques are provided, including the preparation of hierarchical structures with pore systems in different scale ranges. Mesoporosity plays a significant role in catalysis, especially in the most challenging processes where bulky molecules, like those obtained from biomass or highly unreactive species, such as CO2 should be transformed into most valuable products. Furthermore, mesoporous materials also play a significant role as electrodes in fuel and solar cells and in thermoelectric devices, technologies which are benefiting from improved accessibility and a better dispersion of materials with controlled porosity.

Energy distribution of gamma rays scattered around a soil density probe.

At head of title: Project report.

Regulations as to the supply of electric energy to be observed by consumers and electrical contractors.

At head of title: Manchester Electricity Department.