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Publisher Copyright: © 1964-2012 IEEE. This article reviews recent standardization activities and scientific studies related to the assessment of human exposure to electromagnetic fields (EMF). The differences of human exposure standards and assessment of consumer products and medical applications are summarized. First, we reviewed human body modeling and tissue dielectric properties. Then, we explain the rationale of current exposure standards from the viewpoint of EMF and the standardization process for product compliance based on these exposure standards. The assessment of wireless power transfer, as an example of emerging wireless devices, and environmental EMFs in our daily lives are reviewed. Safety in magnetic resonance systems, where the EMF exposure is much larger than from typical consumer devices, is also reviewed. Finally, we summarize future research directions and research needs for EMF safety.

Jahresschrift für mitteldeutsche Vorgeschichte, Bd. 98 (2021): Jahresschrift für Mitteldeutsche Vorgeschichte

Jahresschrift für mitteldeutsche Vorgeschichte, Bd. 95 (2016): Jahresschrift für Mitteldeutsche Vorgeschichte

This study aims to investigate how the positions of the feeding sources of the transmit radiofrequency (RF) coil, field orientation direction with respect to the patient, and patient dimensions affect the global and local electromagnetic exposure in human body models.Three RF coil models were implemented, namely a specific two-source (S2) feed and two multisource feed configurations: generic 32-source (G32) and hybrid 16-source (H16). Thirty-two feeding conditions were studied for the S2, whereas two were studied for the G32 and H16. The study was performed using five human body models. Additionally, for two of the body models, the case of a partially implanted lead was evaluated.The results showed an overall variation due to coil feeding conditions of the whole-body specific absorption rate (SAR) of less than 20%, but deviations up to 98% of the magnitude of the electric field tangential to a possible lead path. For the analysis with the partially implanted lead, a variation of local SAR at the tip of the lead of up to 60% was observed with respect to feed position and field orientation direction.The results of this study suggest that specific information about feed position and field orientation direction must be considered for an accurate evaluation of patient exposure. Magn Reson Med 79:1135-1144, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

This presentation was delivered at the 2017 Design of Medical Devices Conferences in a special session that was highlighting papers published in the Journal of Medical Devices, under a special issue for cardiovascular devices.

The advent of detailed computational anatomical models has opened new avenues for computational life sciences (CLS). To date, static models representing the anatomical environment have been used in many applications but are insufficient when the dynamics of the body prevents separation of anatomical geometrical variability from physics and physiology. Obvious examples include the assessment of thermal risks in magnetic resonance imaging and planning for radiofrequency and acoustic cancer treatment, where posture and physiology-related changes in shape (e.g., breathing) or tissue behavior (e.g., thermoregulation) affect the impact. Advanced functionalized anatomical models can overcome these limitations and dramatically broaden the applicability of CLS in basic research, the development of novel devices/therapies, and the assessment of their safety and efficacy. Various forms of functionalization are discussed in this paper: (i) shape parametrization (e.g., heartbeat, population variability), (ii) physical property distributions (e.g., image-based inhomogeneity), (iii) physiological dynamics (e.g., tissue and organ behavior), and (iv) integration of simulation/measurement data (e.g., exposure conditions, “validation evidence” supporting model tuning and validation). Although current model functionalization may only represent a small part of the physiology, it already facilitates the next level of realism by (i) driving consistency among anatomy and different functionalization layers and highlighting dependencies, (ii) enabling third-party use of validated functionalization layers as established simulation tools, and (iii) therefore facilitating their application as building blocks in network or multi-scale computational models. Integration in functionalized anatomical models thus leverages and potentiates the value of sub-models and simulation/measurement data toward ever-increasing simulation realism. In our o2S2PARC platform, we propose to expand the concept of functionalized anatomical models to establish an integration and sharing service for heterogeneous computational models, ranging from the molecular to the organ level. The objective of o2S2PARC is to integrate all models developed within the National Institutes of Health SPARC initiative in a unified anatomical and computational environment, to study the role of the peripheral nervous system in controlling organ physiology. The functionalization concept, as outlined for the o2S2PARC platform, could form the basis for many other application areas of CLS. The relationship to other ongoing initiatives, such as the Physiome Project, is also presented., Frontiers in Physiology, 9, ISSN:1664-042X

This work addresses the challenge of understanding a place in GIScience by investigating visual and spatial (semantic) property in voluntarily collected images with deep learning methods. Two place representations are proposed to unify these properties in a probabilistic perspective of understanding places. The proposed computational models which are based on comparative learning and variational autoencoder are proved to be able to learn the probabilistic place representations from image data. Die vorliegende Arbeit adressiert die Herausforderung, mit „Deep-Learning“-Modellen die ortsbeschreibenden visuellen und räumlichen (semantischen) Eigenschaften zu erkennen. Zwei Ortsdarstellungen werden zur Vereinigung dieser Eigenschaften in Wahrscheinlichkeitsformen vorgeschlagen. Die entwickelten Rechenmodelle basieren auf dem komparativen Lernen und Variationsautokodierer. Sie können die probabilistischen Ortsdarstellungen aus Bilddaten lernen.

In this paper, we propose a navigation approach for smartphones that enables visitors of major events to avoid crowded areas or narrow streets and to navigate out of dense crowds quickly. Two types of sensor data are integrated. Real-time optical images acquired and transmitted by an airborne camera system are used to compute an estimation of a crowd density map. For this purpose, a patch-based approach with a Gabor filter bank for texture classification in combination with an interest point detector and a smoothing function is applied. Furthermore, the crowd density is estimated based on location and movement speed of in situ smartphone measurements. This information allows for the enhancement of the overall crowd density layer. The composed density information is input to a least-cost routing workflow. Two possible use cases are presented, namely (i) an emergency application and (ii) a basic routing application. A prototypical implementation of the system is conducted as proof of concept. Our approach is capable of increasing the security level for major events. Visitors are able to avoid dense crowds by routing around them, while security and rescue forces are able to find the fastest way into the crowd.

In recent years, collection and processing techniques for Digital Elevation Models (DEMs) generation have improved rapidly, allowing surfaces to be represented with more detail and accuracy. Fusion of overlapping DEMs, generated from data captured with different acquisition techniques, or from different times, allows to find inconsistencies, improve density, accuracy and currency, and eliminate gaps. This is of crucial importance for the improvement of global DEMs, like SRTM (Shuttle Radar Topography Mission).Since the DEMs may have substantial differences, simple amalgamation of all available points would not be satisfying and it would degrade the accuracy of the merged model. Any integration approach aiming at high-quality models needs an increased level of robustness. Computational efficiency and global convergence are further preferable properties. In this paper, an approach is presented for DEM fusion. The goal is to use existing DEMs to create automatically a new DEM surface which is: geometrically accurate by depicting the correct height information of the area, clean by eliminating blunders and errors which are present in the initial data and complete by modelling all the area on the highest possible resolution. The method is presented and the first results achieved after fusing a Lidar-based DEM and an IKONOS-based DEM on Thun, Switzerland, are shown and commented., International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII (B2), ISSN:1682-1750, ISSN:2194-9034, ISSN:1682-1777

Poverty in rural areas of developing countries is one of the major global issues. Economic growth in rural areas of Sri Lanka has been significantly lower than in the urban areas, especially around Colombo and principally excluded the agricultural sector. Aconsiderable proportion of rural livelihoods still depend mainly on agriculture, facing soil degradation and erosion. An important contribution towards a sustainable development of rural areas in Sri Lanka is thus to improve soil quality to enable sustainable agricultural development. Meegahakivula is one of such area has been selected to investigate and is highly undulated. The area is investigated in an interdisciplinary approach by three partners such as agronomy, socioeconomic and Photogrammetry, Remote Sensing and Geographic Information System (GIS). The incorporation of Gliricidia sepium leaves as green manure is believed to improve soil quality by rising both soil nitrogen and organic matter content. The by-products of the trees contribute to an improved income. The socioeconomic component deals with the potential enhancement of income and its importance within the farming systems. Incorporation of Gliricidia sepium in lands with different slopes categories will be analyzed by use of image processing in photogrammetric techniques including the integration of spatial data with agronomic and socioeconomic data in GIS., International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII (B2), ISSN:1682-1750, ISSN:2194-9034, ISSN:1682-1777

In this paper, we present an object-oriented approach to modeling mobile data and algorithms operating on such data. Our model is general enough to capture any kind of continuous motion while at the same time allowing for encompassing algorithms optimized for specific types of motion. Such motion may be available in a specific form, e.g., described by polynomials or splines, or implicitly restricted using bounds for speed or acceleration given by the application context.