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Today’s voice-based air-ground communica-tion system for aircraft guidance is suffering from increasing saturation of the VHF band in high den-sity areas. Therefore the European Union strives for a transition from analog voice communication to more spectrum efficient digital communication. This transition shall be realized, among others, through the development and implementation of the L-band Digital Aeronautical Communications System (LDACS). In order to verify the suitability of LDACS for both communications and navigation, a flight trial campaign will be performed within the nationally funded German project MICONAV. The objective of this paper is to present the planned LDACS measurement campaign. LDACS will be validated under realistic conditions: Four ground stations transmit signals; one airborne station onboard an aircraft will receive the communication messages and additionally utilize the signals from the ground stations for navigation.

By the electrification of the drive train, new degrees of freedom also result for the design of new suspension concepts. Especially through the combination of mechanical and electrical components, potentials for future mobility can be raised. These new opportunities offer the potential for electric lightweight suspensions, include integrating drive units into the chassis, creating space through new packaging variations, reducing unsprung mass and incorporating individual wheel drives to apply new driving strategies. However, the processes, methods and process models involved in the development of electric vehicles, drive trains and chassis must be systematically supplemented during the development and applied in the product development process. A possible development approach, which ranges from concept development through optimization of vehicle dynamics and mechanical design to the prototype validation of a concept, was developed within the framework of the project “Lightweight, Energy-efficient Integrative Chassis with Hub-motor Technology” [1, 2, 3, 4]. In particular, the paper presents the development process, the software tools used to develop the mechatronic suspension concept and the prototypical realization and detailing.

Multifunctionalization of fiber-reinforced composites, especially by adding energy storage capabilities, is a promising approach to realize lightweight structural energy storages for future transport vehicles. Compared to conventional energy storage systems, energy density can be increased by reducing parasitic masses of non-energy-storing components and by benefitting from the composite meso- and microarchitectures. In this paper, the most relevant existing approaches towards multifunctional energy storages are reviewed and subdivided into five groups by distinguishing their degree of integration and their scale of multifunctionalization. By introducing a modified range equation for battery-powered electric aircrafts, possible range extensions enabled by multifunctionalization are estimated. Furthermore, general and aerospace specific potentials of multifunctional energy storages are discussed. Representing an intermediate degree of structural integration, experimental results for a multifunctional energy-storing glass fiber-reinforced composite based on the ceramic electrolyte Li1.4Al0.4Ti1.6(PO4)3 are presented. Cyclic voltammetry tests are used to characterize the double-layer behavior combined with galvanostatic charge–discharge measurements for capacitance calculation. The capacitance is observed to be unchanged after 1500 charge–discharge cycles revealing a promising potential for future applications. Furthermore, the mechanical properties are assessed by means of four-point bending and tensile tests. Additionally, the influence of mechanical loads on the electrical properties is also investigated, demonstrating the storage stability of the composites.

Earth observation (EO) has become a valuable source of comprehensive, reliable, and persistent information for a wide number of applications. However, dealing with the complexity of land cover is sometimes difficult, as the variety of EO sensors reflects in the multitude of details recorded in several types of image data. Their properties dictate the category and nature of the perceptible land structures. The data heterogeneity hampers proper understanding, preventing the definition of universal procedures for content exploitation. The main shortcomings are due to the different human and sensor perception on objects, as well as to the lack of coincidence between visual elements and similarities obtained by computation. In order to bridge these sensory and semantic gaps, the paper presents a compound framework for EO image information extraction. The proposed approach acts like a common ground between the user's understanding, who is visually shortsighted to the visible domain, and the machines numerical interpretation of a much wider information. A hierarchical data representation is considered. At first, basic elements are automatically computed. Then, users can enforce their judgement on the data processing results until semantic structures are revealed. This procedure completes a user-machine knowledge transfer. The interaction is formalized as a dialogue, where communication is determined by a set of parameters guiding the computational process at each level of representation. The purpose is to maintain the data-driven observable connected to the level of semantics and to human awareness. The proposed concept offers flexibility and interoperability to users, allowing them to generate those results that best fit their application scenario. The experiments performed on different satellite images demonstrate the ability to increase the performances in case of semantic annotation by adjusting a set of parameters to the particularities of the analyzed data.

Vacant land has recently mostly attracted interest for its ecological and social importance, or its planning possibilities. In this paper, we investigate vacant land in a fast-growing city in an emerging country, namely Cape Town in South Africa. In so doing, we are also pleading for vacant land to be taken seriously as a theoretical notion. When investigating urban fragmentation, we need to examine what lies (and happens) between the urban splinters. We therefore use the Cape Town case as a lens to propose a working definition of vacant land (as space out of place that disrupts the urban fabric and its logic) and visual methods with which to approach it. Les espaces vacants ont récemment attiré l’intérêt scientifique pour leur importance écologique et sociale, comme pour les possibilités qu’ils offrent en matière d’aménagement. Cet article s’y intéresse dans le cas d’une ville à la croissante rapide, au sein d’un pays émergent : Le Cap (Afrique du Sud). Nous y plaidons également pour prendre au sérieux d’un point de vue théorique la notion d’espace vacant. Pour analyser la fragmentation urbaine, il importe d’examiner ce qui se trouve et se passe entre lesdits fragments. Nous utilisons donc le cas du Cap pour proposer une définition de l’espace vacant (un espace qui n’est pas à sa place, qui rompt le tissu urbain et sa logique), ainsi que des méthodes visuelles pour l’appréhender. 近来空置土地引起了人们的兴趣，其生态和社会重要性，以及其规划可能性受到很多关注。 在本文中，我们研究了新兴国家的处于快速发展中的城市，即南非的开普敦的空置土地的状况。我们强调空置土地作为理论概念的重要性。 在研究城市碎片化时，我们需要检验城市碎片之间的存在（和发生的事）。 因此，开普敦案例为我们提供了一个视角，我们在此基础上提出空置土地的定义（错置了的扰乱城市结构及其逻辑的空间）和理解它的视觉方法。

Humans will soon need to adapt to a collaborative setting in which technology becomes a smart collaboration partner that works with a group to achieve its goals. It is therefore time for collaboration researchers to explore the vast opportunities afforded by smart technology and to test its utility for enhancing team processes and outcomes. In this paper, we take a long view on the implications of smart technology for collaboration process design, and propose a research agenda for the next decade of collaboration research. We create a reference model to frame the research agenda.

Increases in extreme weather events associated with climate change have the potential to put currently healthy forests at risk. One option to minimize this risk is the application of forest management measures aimed at generating species mixtures predicted to be more resilient to these threats. In order to apply such measures appropriately, forest managers need up-to-date, accurate and consistent forest maps at relatively fine spatial resolutions. Cost efficiency is a major factor when creating such maps. Taking European spruce ( Picea abies ) and Scots pine ( Pinus sylvestris ) as an example, this paper describes an innovative approach for mapping two tree species using a combination of commercial very high resolution WorldView-2 (WV2) images and Landsat time series data. As a first step, this study used a supervised object-based classification of WV2 images covering relatively small test sites distributed across the region of interest. Using these classification maps as training data, wall-to-wall mapping of fractional coverages of spruce and pine was achieved using multi-temporal Landsat data and Random Forests (RF) regression. The method was applied for the entire state of Bavaria (Germany), which comprises a total forested area of approximately 26,000 km 2 . As applied here, this two-step approach yields consistent and accurate maps of fractional tree cover estimates with a spatial resolution of 1 ha. Independent validation of the fractional cover estimates using 3780 reference samples collected through visual interpretation of orthophotos produced root-mean-square errors (RMSE) of 11% (for spruce ) and 14% (for pine ) with almost no bias, and R 2 values of 0.74 and 0.79 for spruce and pine , respectively. The majority of the validation samples (75% ( spruce ) and 84% ( pine )) were modeled within the assumed uncertainty of ± 15% of the reference sample. Accuracies were significantly better compared to those achieved using a single-step classification of Landsat time series data at the pixel level (30 m), because the two-step approach better captures regional variation in the spectral signatures of target classes. Moreover, the increased number of available reference cells mitigates the impact of occasional errors in the reference data set. This two-step approach has great potential for cost-effective operational mapping of dominant forest types over large areas.

This paper presents experimental measurement methods for the determination and evaluation of process related thermal residual stresses in fiber metal laminates. A cure monitoring system with fiber Bragg grating (FBG) sensors is used to measure the in-plane strains during processing of carbon fiber reinforced plastic (CFRP)-steel laminates. The simultaneous measurement captures the thermal expansion during the heating stages, the cure shrinkage, and the cooling thermal shrinkage. The results enable the characterization of the co-cure bonding process and the stress transfer between the metal and FRP-layers during the creation process. The residual strains, which are used for calculation of the residual stresses, are recorded at room temperature after manufacturing. In addition, an advanced method using FBG-sensors and the deflection of asymmetric hybrid specimens is developed to validate the gained residual stress data. Asymmetrical specimens are created by removing selected layers after cure. Quantitative evaluation is achieved by determination of their curvature and measuring the strain changes with the embedded FBG-sensors. For validation, the methods were successfully demonstrated on two different curing cycles with different resulting residual stress levels. The simultaneous strain measurement enables the investigation of stress development and delivers more in-depth process knowledge for further optimization of the manufacturing process.

With the advent of Smart Grid systems, the digitalization of electrical grid infrastructures aims to improve energy saving and efficiency. The International Electrotechnical Commission (IEC) is one of the organizations that create and manage norms and standards in areas related to electricity and electronics, such as IEC 61850. In recent years, the research community have proposed mappings of different communication protocols to IEC 61850. However, most of the proposals focused on heavyweight interaction paradigms and protocols such as Common Object Request Broker Architecture (CORBA), Data Distribution Service (DDS), HTTP-REST or Web Services. With the proliferation of the Internet of Things (IoT), new lightweight protocols are appearing opening new perspectives to the standard. Hence, this paper firstly presents a validation of a mapping of the IEC 61850 standard to the Constrained Application Protocol (CoAP) and then compares its performance implementing the IEC's mapping against HTTP-REST and Web Services/SOAP. For comparison purposes, the communication latency, the number of total bytes sent, and the size of the overhead are presented for each of the three approaches. To conclude, future perspectives on the suitability of lightweight protocols to the IEC 61850 are provided.

This multi-disciplinary research paper should help solar power plant developers to perform an advanced site assessment in arid locations where the annual irradiance levels are high, but significant quantities of airborne sand and dust increase the risk of optical energy losses due to extinction, soiling, erosion damage (also known as abrasion), etc. Due to these effects sandstorms have a direct consequence on the operation and maintenance (O&M) costs. The work presented in the following characterizes airborne sand and dust material and later focuses on the resulting erosion effects. Some important meteorological and geological parameters for sandstorm occurrence and the resulting erosive damage on glass materials by impacting windblown material are extracted from literature. The respective parameters have been measured at two locations in Morocco (Zagora and Missour). After evaluation of wind and humidity data and a comprehensive soil analysis, the erosion risk was estimated to be higher in Zagora. The specular reflectance loss of exposed silvered-glass reflectors of 5.9% in Zagora and 0.8% in Missour after 25 months of exposure verified this estimation. Additionally, a specular reflectance analysis on a mirror sample that has been exposed for nine months in Kuwait is shown. On that sample specular reflectance losses of more than 40% were measured. A checklist with seven items is given in the conclusion to help solar plant developers to evaluate the risk of component aging due to sand storm erosion.

Purpose Agile software development helps software producing organizations to respond to manifold challenges. While prior research focused on agility as a project or process phenomenon, the authors suggest that agility is an emergent phenomenon on the team level. The paper aims to discuss this issue. Design/methodology/approach Using the theory of complex adaptive systems (CASs), the study captures the multiple influencing levels of software development teams (SDTs) and their interplay with self-organization and emergence. The authors investigate three agile SDTs in different contextual environments that participate with four or more different roles each. Findings The results suggest self-organization as a central process when understanding team agility. While contextual factors often provide restriction on self-organization, they can help the team to enhance its autonomy. Research limitations/implications The theoretical contributions result from the development and test of theory grounded propositions and the investigation of mature agile development teams. Practical implications The findings help practitioners to improve the cost-effectiveness ratio of their team’s operations. Originality/value The study provides empirical evidence for the emergence of team agility in agile SDTs. Using the lens of CAS, the study suggests the importance of the team’s autonomy.

To bridge the gap between users' expectations and technological solutions, a better understanding of human body experience and sensory-motor skills is mandatory. This could pave the way towards a novel generation of robotic hands, which can be successfully employed in everyday life e.g. in prosthetics and assistive robotics. Available robotic hands are still far from matching the requirements of the corresponding experimental and real-world applications, e.g. fast motions might be achieved at the expense of accuracy. Knowledge of the users' sensory-motor skills can guide technical developments, e.g. prosthetic design processes. This paper presents design solutions developed in a Delphi study. Explorative questionnaires are prepared to acquire and elaborate expert opinions to improve the design of previously developed robotic anthropomorphic hands. By gathering and fusing expert opinions, novel robotic hand and wrist concepts specifically optimized regarding body experience and sensory-motor skill ...

This paper presents the development, implementation, and validation of a simplified dynamic modeling approach to describe solid oxide fuel cell gas turbine (SOFC/GT) hybrid systems (HSs) in three real emulator test rigs installed at University of Genoa (Italy), German Aerospace Center (DLR, Germany), and National Energy Technology Laboratory (NETL, USA), respectively. The proposed modeling approach is based on an experience-based simplification of the physical problem to reduce model computational efforts with minimal expense of accuracy. Traditional high fidelity dynamic modeling requires specialized skills and significant computational resources. This innovative approach, on the other hand, can be easily adapted to different plant configurations, predicting the most relevant dynamic phenomena with a reduced number of states: such a feature will allow, in the near future, the model deployment for monitoring purposes or advanced control scheme applications (e.g., model predictive control). The three target systems are briefly introduced and dynamic situations analyzed for model tuning, first, and validation, then. Relevance is given to peculiar transients where the model shows its reliability and its weakness. Assumptions introduced during model definition for the three different test rigs are discussed and compared. The model captured significant dynamic behavior in all analyzed systems (in particular those regarding the GT) and showed influence of signal noise on some of the SOFC computed outputs.

This paper explores how the functional safety of industrial deployments can be improved through emerging Industrie 4.0 approaches. We discuss how new sources of data, that are becoming accessible through advancing digitalization, can be used for this purpose, and how principles from predictive maintenance systems can be applied to industrial fail-safe applications: based on data from the industrial components themselves and from their environment as well as on metadata about interactions between these systems and people, we propose to create a model-based monitoring and controlling system that focuses on preserving the functional safety of the installation as a whole. We expect such a Predictive Fail-Safe system to mitigate or even prevent unsafe consequences of failures even in highly dynamic “smart factories”, thereby reducing or preventing harm to other equipment, the environment, and the involved people.

This paper treats the problem of tracking the global navigation satellite system's (GNSS) signal phase under ionospheric scintillations and to generate an estimate of the scintillation phase and amplitude. In the case of ionospheric scintillations traditional phase locked loop (PLL) based GNSS receivers have problems to track the signal phase accurately. Moreover, these receivers do not estimate the scintillation phase and amplitude, which is evaluated in ionospheric monitoring applications. Therefore, Kalman filter based phase tracking algorithms have been proposed, which track line-of-sight (LOS) phase and scintillation amplitude and phase separately with different state space models. For modeling the scintillation phase and amplitude auto-regressive (AR) models can be used. In this case the parameters for the AR model have to be estimated together with the LOS and scintillation phase and amplitude. We propose to use a second Kalman filter for the estimation of the AR model parameters. This Kalman filter takes the scintillation phase and amplitude estimates from the first Kalman filter as measurement and the AR model parameters as system state. Simulation results for the global positioning system (GPS) show that the proposed algorithm achieves the same estimation performance for scintillation phase and amplitude as an algorithm with a priori knowledge on the AR model parameters.

Summary The acceleration and deceleration of trains are essential for satisfactory performance of train services and for effective utilisation of line capacity by railways for a given network. However, it increases the risk of unbalancing the passengers. Therefore, in this paper, the jerk was analysed in the vehicle in order to examine its effect on safety and comfort to the passengers. For the purpose of this analysis, a rake with 24 ICF coaches fitted with CBC (H type tight lock) and low preload draft gear hauled by WDP4 locomotive was considered. It was modelled using Universal Mechanism – a multibody dynamic software. Also, in addition, the vehicle is considered to be subjected to external forces such as rolling resistance, longitudinal wheel resistance, and gravitational force. The tractive and braking efforts for the locomotives are also considered with realistic track conditions between Lucknow and Kanpur of India. The presented results suggest that the CBC with balanced type draft gear reduces the jerk in the train.

Summary In the recent years, population based meta-heuristic are developed to solve non-linear optimization problems. These problems are difficult to solve using traditional methods. Simple optimization (SOPT) algorithm is one of the simple and efficient meta-heuristic techniques to solve the non-linear optimization problems. In this paper, SOPT is compared with some of the well-known meta-heuristic techniques viz. Artificial Bee Colony algorithm (ABC), Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Differential Evolutions (DE). For comparison, SOPT algorithm is coded in MATLAB and 25 standard test functions for unconstrained optimization having different characteristics are run for 30 times each. The results of experiments are compared with previously reported results of other algorithms. Promising and comparable results are obtained for most of the test problems. To improve the performance of SOPT, an improvement in the algorithm is proposed which helps it to come out of local optima when algorithm gets trapped in it. In almost all the test problems, improved SOPT is able to get the actual solution at least once in 30 runs.

Summary Burst pressure is the pressure at which vessel burst/crack and internal fluid leaks. An accurate prediction of burst pressure is necessary in chemical, medical and aviation industry. Burst pressure is a design safety limit, which should not be exceeded. If this pressure is exceeded it may lead to the mechanical breach and permanent loss of pressure containment. So burst pressure calculation is necessary for all the critical applications. To numerically calculate burst pressure material curve is essential. There are various material models which are used to define material curve, amongst them Ramberg–Osgood is very popular. Ramberg–Osgood accurately capture material curve in strain hardening region. This approach is applicable for different material grades. In this paper a finite element method is used to predict burst pressure using Ramberg–Osgood equation. These results are then compared with results obtained from elasto-plastic curve and true stress strain curve. Results obtained by finite element analysis are validated with experimental data which is considered from open literature.

Summary The laying and commissioning of new transmission line is very difficult due to socio-economic problems, like environmental clearances, right of way, etc. Therefore, there is an emphasis on better utilization of available transmission infrastructure. FACTS devices can provide reactive power compensation, transmission capability enhancement, and voltage and stability improvement. FACTS devices operate under the command of system operator who analyses its demand by the data acquired through traditional SCADA system, state estimation algorithms and PMUs. SCADA together with PMU give accurate information about the operational state of power system. This paper proposes a scheme to automate the FACTS devices in collaboration with PMUs in a more efficient way. Highly precised data from PMUs can be fed to intelligent controllers for effective analyzing and automating the FACTS device through control command. Thus, this combination can provide real time control of reactive power, together with enhancement of power handling capability and stability improvement.

Summary The customer's review plays an important role in deciding the purchasing behaviour for online shopping as a customer prefers to get the opinion of other customers by observing their opinion through online products’ reviews, blogs and social networking sites, etc. The customer's reviews reflect the customer's sentiments and have a substantial significance for the products being sold online including electronic gadgets, movies, house hold appliances and books. Hence, extracting the exact features of the products by analyzing the text of reviews requires a lot of efforts and human intelligence. In this paper we intend to analyze the online reviews available for books and extract book-features from the reviews using human intelligence. We have proposed a technique to categorize the features of books from the reviews of the customers. The extracted features may help in deciding the books to be recommended for readers. The ultimate goal of the work is to fulfil the requirement of the user and provide them their desired books. Thus, we have evaluated our categorization method by users themselves, and surveyed qualified persons for the concerned books. The survey results show high precision of the features categorized which clearly indicates that proposed method is very useful and appealing. The proposed technique may help in recommending the best books for concerned people and may also be generalized to recommend any product to the users.

Summary This research paper depicts the application of highly powerful and accurate semi-analytical methods, Differential transformation method (DTM) to portray the non linear temperature distribution of convective-radiative fin with variable specific heat. With the help of DTM, the nonlinear terms appeared in governing equations are reduced to recurrence relation with non-dimensional terms. A longitudinal fin of constant rectangular profile through which air flows in transverse direction at ambient temperature has been considered for present analysis. The governing differential equation and corresponding boundary conditions are decided based on the heat transfer in longitudinal fin. The governing equation is non-dimensionalised for successful application of DTM with generalised terms. The results of temperature distribution in fin have been obtained for a range of values of several parameters of DTM. The results have indicated that DTM is efficient and convenient tool for analysing nonlinear differential equations of several environments. Present results have been compared and analysed with other analytical methods available in literature.

Summary Mobile is becoming a part of everyone's life and as their power of computation and storage is rising and cost is coming down. Most of mobile phone users have a lot of private data which they want to protect from others ( La Polla et al., 2013 ). It means user must be authenticated properly for accessing the mobile resources. Normally user is authenticated using text passwords, PIN, face recognition or patterns etc. All these methods are used but they have some shortcomings. In this paper we have seen various existing methods of mobile authentications and proposed our improved mobile authentication IPCT scheme. We have compared our Image Pass Code with tapping scheme with existing techniques and shown that our scheme is better than existing techniques.

Summary The objective of the paper is to analyse parametric studies and optimum steam extraction pressures of three different (subcritical, supercritical and ultra-supercritical) coal fired power plant cycles at a particular main steam temperature of 600 °C by keeping the reheat temperature at 537 °C and condenser pressure at 0.09 bar as constant. In order to maximize the heat rate gain possible with supercritical and ultra-supercritical steam conditions, eight stages of feed water heater arrangement with single reheater is considered. The system is optimized in such a way that the percentage exergetic losses are reduced for the increase of the exergetic efficiency and higher fuel utilization. The plant cycles are simulated and optimized by using Cycle Tempo 5.0 simulation software tool. From the simulation study, it is observed that the thermal efficiency of the three different power plant cycles obtained as 41.40, 42.48 and 43.03%, respectively. The specific coal consumption for three different power plant cycles are 0.56, 0.55 and 0.54 Tonnes/MWh. The improvement in feed water temperatures at the inlet of steam generator of respective cycles are 291, 305 and 316 °C.

Summary Network-on-Chip has been a growing design paradigm with the rise in Multi-Processor System on Chip (MPSoCs) primarily due to its scalability. While regular meshes (2 or 3-dimensional) are the usual proposal for such a paradigm, a real chip may not follow it. Heterogeneous cores, hardware failures or manufacturing defects can possibly cause irregular topologies in a Network-on-Chip. Selection of a routing algorithm is an important challenge in NoC design as it affects power consumption, communication latency and overall system performance. Routing can be supported in such faulty environment by use of routing tables. But this is not a scalable solution as table size grows with network size. Logic Based Distributed Routing (LBDR) is proposed as a new routing implementation technique which offers compact routing implementation and fault tolerance without use of routing table. In this paper we propose a Hybrid Fault Tolerant Routing Algorithm (HFTRA), which aims to provide fault tolerance support in presence of on-chip link failures. Proposed routing is implemented with LBDR scheme. Analysis of the method has shown the effectiveness of proposed scheme as compared to routing tables when implemented using LBDR.

Summary The world today is experiencing an exponential growth in cyberspace. Nevertheless, India too has witnessed a significant ascend in Internet activities and it is quite assertive to say that such phenomenal growth in access to information on one hand leads to empowered individuals and organization and on the other hand also poses new challenges to government and citizens. To make the cyber world safe is the need of the hour. Putting up deterrent measures against cybercrime is essential to national cyber security in protecting critical infrastructure of the nation as well as for individuals. In this regard, the prime objective of the government is to prevent cyber attacks and to protect the country's critical infrastructure. It also focuses on reducing vulnerability to cyber attacks so as to reduce and minimize damage and recovery time. To prevent the cyber crimes, individuals and governments need to clearly understand the crime schemes in the cyberspace and the contemporary and continuing Internet trends and behaviours of these criminals. This paper gives a brief outline of categories of cybercrimes. These crimes are categorized as crimes against individuals, property, organizations and governments. Various Internet crime scheme are evaluated and behaviour of criminals to perform the cybercrimes has been analyzed. A critical evaluation of report of cybercrime complaints under IT Act 2000 has been presented.

Summary Selection of a suitable robotic manipulator, out of the available conventional configurations, is one way to employ a robot. However, with the increasing applications of robotic assistance, the concept of task-oriented customised design for prescribed working locations in a given environment, has got attention of several researchers. One of the challenges in this direction is the realisation of specific designs, involving unconventional values of robotic parameters. This paper discusses the D–H parameters based adaptive modules, which can be adjusted according to the given values of robotic parameters. The modules are available in three types with similar architecture. The details of this basic length unit, adaptive twist unit and extended length unit are discussed. Focus of the work is to validate the adaptability of the proposed architecture through the modelling, simulation and development of standard configuration.

Summary Selecting the right vendor is an important business decision made by any organization. The decision involves multiple criteria and if the objectives vary in preference and scope, then nature of decision becomes multiobjective. In this paper, a vendor selection problem has been formulated as an intutionistic fuzzy multiobjective optimization where appropriate number of vendors is to be selected and order allocated to them. The multiobjective problem includes three objectives: minimizing the net price, maximizing the quality, and maximizing the on time deliveries subject to supplier's constraints. The objection function and the demand are treated as intutionistic fuzzy sets. An intutionistic fuzzy set has its ability to handle uncertainty with additional degrees of freedom. The Intutionistic fuzzy optimization (IFO) problem is converted into a crisp linear form and solved using optimization software Tora. The advantage of IFO is that they give better results than fuzzy/crisp optimization. The proposed approach is explained by a numerical example.

Evidenced based planning is a salient issue and evokes questions about the role of expertise and scientific policy advice in spatial planning. The paper considers recent trends in the debate on scientific policy advice (crises of expertise, privatization/democratization of expertise, blurring of boundaries between science and policy) and reflects upon these trends against the background of the particular situation of scientific policy advice in spatial planning in Germany. Many insights from the wider debate on policy advice also hold true for spatial planning. However, spatial planning, at least in Germany, reveals some particularities. The scientific foundation of spatial planning is interdisciplinary and the gap between science and practice is probably less visible compared to other scientific disciplines. This makes dualistic approaches (science ��� policy boundaries) questionable. At the same time recent trends towards Gesellschaftsberatung (advice for society), transformative science and transdisciplinarity are attractive directions in spatial planning., disP - the planning review;Vol. 53. Issue 4, p 21-32

Parabolic trough collectors for concentrating solar sower plants are large scale optical devices with demanding requirements on optical and mechanical properties. Accurate mirror shape and absorber tube alignment are necessary to harness solar radiation with high efficiency. There are several methods to assess the shape of the mirror surface, yet there exist few approaches to effectively measure the position of the absorber tube. This paper provides a comprehensive overview on causes and effects of absorber tube displacement and on state of the art measurement techniques. A new approach on fully automated airborne absorber tube position measurement for parabolic trough collectors is presented, which outperforms existing methods concerning speed, spatial resolution, and level of automation, thereby achieving an accuracy of about 1.5 mm in vertical and lateral direction.

International audience; Because of the cloud-induced variability of the solar resource, the growing contributions of photovoltaic plants to the overall power generation challenges the stability of electricity grids. To avoid blackouts, administrations started to define maximum negative ramp rates. Storages can be used to reduce the occurring ramps. Their required capacity, durability, and costs can be optimized by nowcasting systems. Nowcasting systems use the input of upward-facing cameras to predict future irradiances. Previously, many nowcasting systems were developed and validated. However, these validations did not consider aggregation effects, which are present in industrial-sized power plants. In this paper, we present the validation of nowcasted global horizontal irradiance (GHI) and direct normal irradiance maps derived from an example system consisting of 4 all-sky cameras (“WobaS-4cam”). The WobaS-4cam system is operational at 2 solar energy research centers and at a commercial 50-MW solar power plant. Besides its validation on 30 days, the working principle is briefly explained. The forecasting deviations are investigated with a focus on temporal and spatial aggregation effects. The validation found that spatial and temporal aggregations significantly improve forecast accuracies: Spatial aggregation reduces the relative root mean square error (GHI) from 30.9% (considering field sizes of 25 m2) to 23.5% (considering a field size of 4 km2) on a day with variable conditions for 1 minute averages and a lead time of 15 minutes. Over 30 days of validation, a relative root mean square error (GHI) of 20.4% for the next 15 minutes is observed at pixel basis (25 m2). Although the deviations of nowcasting systems strongly depend on the validation period and the specific weather conditions, the WobaS-4cam system is considered to be at least state of the art.

Background: There is general consensus that the organizational and administrative aspects of academic study programs exert an important influence on teaching and learning. Despite this, no comprehensive framework currently exists to describe the conditions that affect the quality of teaching and learning in medical education. The aim of this paper is to systematically and comprehensively identify these factors to offer academic administrators and decision makers interested in improving teaching a theory-based and, to an extent, empirically founded framework on the basis of which improvements in teaching quality can be identified and implemented. Method: Primarily, the issue was addressed by combining a theory-driven deductive approach with an experience based, “best evidence” one during the course of two workshops held by the GMA Committee on Personnel and Organizational Development in Academic Teaching (POiL) in Munich (2013) and Frankfurt (2014). Two models describing the conditions relevant to teaching and learning (Euler/Hahn and Rindermann) were critically appraised and synthesized into a new third model. Practical examples of teaching strategies that promote or hinder learning were compiled and added to the categories of this model and, to the extent possible, supported with empirical evidence. Based on this, a checklist with recommendations for optimizing general academic conditions was formulated. Results: The Frankfurt Model of conditions to ensure Quality in Teaching and Learning covers six categories: organizational structure/medical school culture, regulatory frameworks, curricular requirements, time constraints, material and personnel resources, and qualification of teaching staff. These categories have been supplemented by the interests, motives and abilities of the actual teachers and students in this particular setting. The categories of this model provide the structure for a checklist in which recommendations for optimizing teaching are given. Conclusions: The checklist derived from the Frankfurt Model for ensuring quality in teaching and learning can be used for quality assurance and to improve the conditions under which teaching and learning take place in medical schools., Hintergrund: Es gilt allgemein als akzeptiert, dass Rahmenbedingungen einen wichtigen Einfluss auf Lehren und Lernen ausüben. Trotzdem existiert für das Studium der Medizin bislang kein umfassendes Rahmenwerk zur Beschreibung von Bedingungen, die Einfluss auf die Lehr-/Lernqualität haben. Ziel der vorliegenden Arbeit war es daher, diese Faktoren systematisch und umfassend zusammenzustellen, um Fakultätsleitungen und allen an der Verbesserung der Lehre interessierten Entscheidungsträgern ein theoriegeleitetes und - in Ansätzen - empirisch fundiertes Rahmenwerk anzubieten, mit dessen Hilfe Maßnahmen zur Optimierung der Lehrqualität begründet und umgesetzt werden können. Vorgehen: In zwei Workshops des GMA-Ausschusses Personal und Organisationsentwicklung in der Lehre (POiL) in München (2013) und Frankfurt (2014) wurde die Thematik zunächst theorie-, dann erfahrungsgeleitet bearbeitet. Zwei Modelle zur Beschreibung von lehr-/lernrelevanten Rahmenbedingungen (von Euler/Hahn und Rindermann) wurden kritisch diskutiert und zu einem neuen Modell zusammengeführt. Zu den Kategorien dieses Modells wurden lernförderliche und -hinderliche Praxisbeispiele zusammengetragen und – soweit möglich – mit empirischen Belegen gestützt. Basierend auf dieser Arbeit wurde eine Checkliste mit Empfehlungen zur Optimierung der Rahmenbedingungen formuliert. Ergebnisse: Das Frankfurter Modell der Rahmenbedingungen zur Sicherung der Lehr- und Lernqualität umfasst die sechs Kategorien: Organisationsstruktur/Kultur der Fakultät, rechtliche Bedingungen, curriculare Vorgaben, zeitliche Bedingungen, materielleund Personalausstattung sowie Qualifizierung des Lehrpersonals. Ergänzt werden diese Kategorien durch die in diesem Kontext agierenden Lehrenden und Studierenden mit ihren Interessen, Motiven und Fähigkeiten. Die Kategorien dieses Modells bilden die Struktur für eine Checkliste, in der Empfehlungen zur Optimierung der Lehre aufgeführt werden. Schlussfolgerungen: Die vom Frankfurter Modell der Rahmenbedingungen zur Sicherung der Lehr- und Lernqualität abgeleitete Checkliste kann zur Qualitätssicherung und Optimierung der der Lehr-/Lernbedingung an medizinischen Fakultäten eingesetzt werden., GMS Journal for Medical Education; 34(4):Doc46

A multipath mitigation technique for GNSS is proposed.The technique exploites the change of polarization when a signal is reflected.A novel statistic based on the outputs of a correlator bank is introduced to estimate the multipath DoA and polarization.Applying the technique increases the estimation performance in the case of highly temporally or spatially correlated multipath and line-of-sight signal. This paper treats the problem of line-of-sight (LOS) parameter estimation in strong multipath environments. In the case of highly temporally and spatially correlated LOS and multipath signals, such as urban canyons, common multipath mitigation methods are highly degraded, as signal separation cannot be performed in the spatio temporal domain. In this case, we exploit the LOS and multipath polarization diversity to decouple the signals using an antenna array with right-hand-circular polarization (RHCP) and left-hand-circular polarization (LHCP) feeds. The multipath direction- of-arrival (DOA) and polarization coefficients can effectively be estimated from the LHCP spatial covariance matrix. The LOS DOA can be estimated from the RHCP spatial covariance matrix. The spatial covariance matrices are calculated from the outputs of a matched correlator bank. The DOA and polarization estimates are used to implement a dual polarization beamformer, which maximizes the LOS energy and suppresses multipath energy over both polarizations. The LOS time-delay is estimated from the beamformer output with a maximum-likelihood estimator with a significantly reduced number of parameters and computational complexity in comparison to a full model estimator. Simulation results for GPS show that the proposed dual polarization beamforming algorithm performs better than an equivalent single-polarization beamformer in a dense multipath environment.

Active control of structural sound radiation is a promising technique to overcome the poor passive acoustic isolation performance of lightweight structures in the low–frequency region. Active structural acoustic control commonly aims at the suppression of the far–field radiated sound power. This paper is concerned with the active control of sound radiation into acoustic enclosures. Experimental results of a coupled rectangular plate-fluid system under stochastic excitation are presented. The amplitudes of the frequency-independent interior radiation modes are determined in real-time using a set of structural vibration sensors, for the purpose of estimating their contribution to the acoustic potential energy in the enclosure. This approach is validated by acoustic measurements inside the cavity. Utilizing a feedback control approach, a broadband reduction of the global acoustic response inside the enclosure is achieved.

Extinction profile (EP) is an effective feature extraction method which can well preserve the geometrical characteristics of a hyperspectral image (HSI) and by extracting the EP from first three independent components (ICs) of an HSI, three correlated and complementary groups of EP features can be constructed. In this paper, an EPs fusion (EPs-F) strategy is proposed for HSI classification by exploring spatial-spectral information within and among three EP features. In general, the EPs-F method includes two stages. In the first stage, within each EP feature, a superpixel-based composite kernel strategy is proposed to adaptively fuse the spatial information of EP and the spectral feature of HSI. Then, the obtained adaptive composite kernel is used to create a classification map for each EP. In the second stage, decision fusion is further applied on different classification maps to create the final classification result. Experiments on two real HSIs verify the effectiveness of the proposed EPs-F algorithm.

To improve the classification of hyperspectral images, this paper proposes an approach for multi-sensor data fusion of LiDAR and hyperspectral data using extinction profiles and Orthogonal Total Variation Component Analysis (OTVCA). Results on the benchmark Houston data indicate the superior performance of the proposed approach compared to other approaches used in the experiments based on classification accuracies.

This paper introduces the concept of a fractionated MirrorSAR which is based on a set of mutually separated transmitter and receiver satellites. As opposed to previously published bi- and multistatic SAR systems, the receiver satellites are considerably simplified, as their main functionality is reduced to a kind of microwave mirror (or space transponder) which routes the radar echoes towards the transmitter. The forwarded radar signals are then coherently demodulated within the transmitter by using the same oscillator that had been used for radar pulse generation. This avoids the necessity of a bidirectional phase synchronization link as currently employed in TanDEM-X. Since the needs for fully equipped radar receivers, on-board memory and downlink are also overcome, the weight and costs of the receiver satellites can be significantly reduced. This allows for a scaling of their number without cost explosion, thereby paving the way for novel applications like multi-baseline SAR interferometry and single-pass tomography. Several additional opportunities make the MirrorSAR concept even more attractive. First, the separation of the transmitter and receiver front-ends reduces not only RF losses by avoiding switches and circulators, but it may also lower the peak power in the transmitter satellite by employing a frequency-modulated continuous wave (FMCW) illumination. This simplifies the design of the high-power amplifier and increases its efficiency. Second, the opportunity for continuous radar data collection enables new modes for the imaging of ultra-wide swaths with very high resolution, thereby overcoming an inherent limitation of conventional monostatic SAR systems. Third, the joint availability of all receiver signals in a centralized node offers new opportunities for efficient data compression, as the multistatic radar signals from close satellite formations are characterized by a high degree of mutual redundancy. Fourth, the use of a sufficiently separated transmitter satellite can avoid the risk for mutual illumination, which challenges the design and operation of fully-active multistatic SAR systems. Further advantages arise from the scalability and reconfigurability, which support new redundancy concepts and pave at the same time the way to new modes like MIMO-SAR tomography.

This paper compares different similarity measures for the matching of very-high-resolution SAR and optical images over urban areas. It is meant to provide guidance about the performance of both signal-based and descriptor-based similarity measures in the context of this non-trivial case of multi-sensor correspondence matching. Using an automatically generated training dataset, thresholds for the distinction between correct matches and wrong matches are determined. It is shown that descriptor-based similarity measures outperform signal-based similarity measures significantly.

A traffic data collection system using wireless radio frequency (RF) technologies, e.g. Bluetooth or Wi-Fi, allows for area wide measurement of traffic. This includes travel times on the whole road network. This paper aims to present the technical overview of a newly developed ITS system called DYNAMIC. This system supports indirect data acquisition by moving detectors, processing and provision of floating observer information on the basis of mobile wireless RF data. DYNAMIC consists of sensor hardware and software components like data collection, data import, transport mode detection, data processing, data fusion and visualization.

Les débats sur la promotion territoriale à l’échelle internationale mettent toujours plus largement en avant la qualité de vie et la durabilité urbaine comme des avantages concurrentiels. Or, peu de travaux ont exploré les interactions entre l’insertion des villes dans la mondialisation et le métabolisme urbain à l’échelle locale. À partir d’une approche en études urbaines et en écologie politique, cet article s’appuie sur le cas de Montréal (Québec, Canada), et explore les mutations du quartier péricentral de Saint-Michel sur plus d’un demi-siècle. Il interroge la métropolisation dans sa dimension spatio-temporelle à la lumière des relations entre économie, politique et environnement dans un espace marqué par l’activité extractive (carrières) et accumulative (déchets). Debates on territorial marketing at an international scale pay more and more attention to quality of life and urban sustainability as competitive advantages to attract international investments. Yet few studies have provided insights into the entanglements between cities’ globalization and urban metabolism at the local scale. This paper aims to understand their long-term impact on the transformations of Saint-Michel, an inner suburb in Montréal (Quebec, Canada). Local extraction (quarries) and accumulation (garbage) have always had a significant place in the more general shaping of the metropolitan area. Those issues question the economic, political and environmental challenges of the globalization process through a situated and contextualized point of view. 有关在国际范围内进行区域推广的辩论越来越强调以生活质量和城市可持续发展作为吸引国际投资的竞争优势。 然而，很少有研究能够深入分析地方层面上城市全球化与城市新陈代谢之间错综复杂的关系。 本文旨在理解城市全球化与城市新陈代谢对蒙特利尔（魁北克省，加拿大）近郊圣米歇尔区（Saint-Michel）的转型的长期影响。 地方开采（采石场）和堆积（垃圾）一直是塑造大都市形态的重要力量。从情景化并植根于具体背景的角度， 这些问题使我们思考全球化进程中的经济，政治和环境方面挑战。

We present two advances in representing variable renewables (VRE) in global energy-economy-climate models: accounting for region-specific integration challenges for eight world regions and considering short-term storage. Both advances refine the approach of implementing residual load duration curves (RLDCs) to capture integration challenges. In this paper we derive RLDCs for eight world regions (based on region-specific time series for load, wind and solar) and implement them into the REMIND model. Therein we parameterize the impact of short-term storage using the highly-resolved model DIMES. All RLDCs and the underlying region-specific VRE time series are made available to the research community. We find that the more accurate accounting of integration challenges in REMIND does not reduce the prominent role of wind and solar in scenarios that cost-efficiently achieve the 2 °C target. Until 2030, VRE shares increase to about 15–40% in most regions with limited deployment of short-term storage capacities (below 2% of peak load). The REMIND model's default assumption of large-scale transmission grid expansion allows smoothening variability such that VRE capacity credits are moderate and curtailment is low. In the long run, VRE become the backbone of electricity supply and provide more than 70% of global electricity demand from 2070 on. Integration options ease this transformation: storage on diurnal and seasonal scales (via flow batteries and hydrogen electrolysis) and a shift in the non-VRE capacity mix from baseload towards more peaking power plants. The refined RLDC approach allows for a more accurate consideration of system-level impacts of VRE, and hence more robust insights on the nature of power sector decarbonization and related economic impacts.

Despite recent advances in prosthetics and assistive robotics in general, robust simultaneous and proportional control of dexterous prosthetic devices remains an unsolved problem, mainly because of inadequate sensorization. In this paper, we study the application of regression to muscle activity, detected using a flexible tactile sensor recording muscle bulging in the forearm (tactile myography—TMG). The sensor is made of 320 highly sensitive cells organized in an array forming a bracelet. We propose the use of Gaussian process regression to improve the prediction of wrist, hand and single-finger activation, using TMG, surface electromyography (sEMG; the traditional approach in the field), and a combination of the two. We prove the effectiveness of the approach for different levels of activations in a real-time goal-reaching experiment using tactile data. Furthermore, we performed a batch comparison between the different forms of sensorization, using a Gaussian process with different kernel distances.

Virtuelle Währungen wie Bitcoins geraten zunehmend in den Blickpunkt des öffentlichen Interesses. Sie funktionieren auf Basis der Blockchain- bzw. Distributed-Ledger-Technologie. Volker Brühl erläutert ihre Funktionsweise und zeigt auf, dass diese Technologien nicht nur den Finanzsektor revolutionieren können. Cryptocurrencies such as bitcoin were invented to facilitate instant payment services without the need for a central bank or financial intermediaries executing payments. Using cryptographic functions, any user of the bitcoin system can transfer units of the virtual currency globally on an anonymous basis. However, fi nancial supervisory authorities are about to increase regulation of virtual currencies due to concerns that the anonymous character of the system facilitates money laundering and the financing of illegal transactions. Nevertheless, the underlying blockchain technology, or in broader terms the distributed ledger technology, may revolutionise several industries. This paper illustrates the functioning and recent market developments in the bitcoin industry as well as the disruptive potential of the underlying technologies.

A major research area in remote sensing is the problem of multi-sensor data fusion. Especially the combination of images acquired by different sensor types, e.g. active and passive, is a difficult task. Over the last years deep learning methods have proven their high potential for remote sensing applications. In this paper we will show how a deep learning method can be valuable for the problem of optical and SAR image matching. We investigate the possible of conditional generative adversarial networks (cGANs) for the generation of artificial templates. Contrary to common template generation approaches for image matching, the generation of templates using cGANs does not require the extraction of features. Our results show the possibility of realistic SAR-like template generation from optical images through cGANs and the potential of these templates for enhancing the matching of optical and SAR images by means of reliability and accuracy.

This paper discusses characteristic multi-disciplinary issues related to quiet short take-off and landing for civil transport aircraft with a typical short to medium range mission. The work reported here is focussing on the noise aspects and is embedded in the collaborative research centre CRC880 in Braunschweig, Germany. This long term aircraft Research initiative focusses on a new transport aircraft segment for operation on airports with shorter runway length in commercial air transport. This calls for a community-friendly aircraft designed for operations much closer to the home of its passengers than today. This Scenario sets challenging, seemingly contradictory aircraft technology requirements, namely those for extreme lift augmentation at low noise. The Research Centre CRC880 has therefore devised a range of technology projects that aim at significant noise reductions and at the generation of e�cffient and flexible high lift. The research also addresses flight Dynamics of aircraft at takeoff and landing. It is envisaged that in general significant noise reduction -compared to a reference turbofan driven aircraft of year 2000 technology- necessarily requires component noise reduction in combination with a low noise a/c concept. Results are presented from all the acoustics related projects of CRC880 which cover the aeroacoustic simulation of the source noise reduction by flow permeable materials, the characterization, development, manufacturing and operation of (porous) materials especially tailored to aeroacoustics, new UHBR turbofan arrangements for minimum exterior noise due to acoustic shielding as well as the prediction of jet noise vibration excitation of cabin noise by UHBR engines compared to conventional turbofans at cruise.

With the Regulations 1215/2012 (Brussels Ia Regulation) and 655/2014 (EAPO Regulation), the European legislator has created two new and very distinct instruments to facilitate cross-border debt recovery in civil and commercial matters. While the Brussels Ia Regulation provides for an easier recognition and enforcement of national interim measures in other EU Member States, the EAPO Regulation creates a single provisional and protective measure enabling creditors to prevent the transfer or withdrawal of the debtors' assets from any bank account located in the EU. This paper provides a comparative analysis of these European legal instruments by evaluating the rules on preconditions, legal remedies and the different effects of national interim measures that shall be recognised and enforced within the Brussels Ia regime and the new EAPO.

The purpose of this paper is helping managers and leaders in healthcare develop viable organizations that deliver high-level services. Health organizations such as hospitals are exceedingly complex. Therefore, we use Integrative Systems Methodology, a framework designed especially as an enabler for coping with complexity. Within that framework, we combine quantitative and qualitative methods to describe and explain organizational phenomena evolving over time. Rather than a large survey, we use a real-life case study. A single-case setting has been chosen, to enable long-term and in-depth exploration. The case spans 30 years, covering the evolution of the oncological care system of Carinthia, which is a federal state of Austria. The contribution of the chapter is in providing deep insights. It lays open the structures underlying the viability of health organizations. The chapter also provides well-grounded advice for how to build a robust health organization in a context of complexity and change.

The side-looking imaging geometry of synthetic aperture radar (SAR) causes inevitable layover in SAR images. Separating the contributions from different scatterers has been the fundamental for many applications. It is typically solved by explicit inversion of the SAR imaging model to retrieve the scattering profile along the mixed dimension (elevation), which is otherwise known as SAR tomography. This paper proposed a robust blind scatterer separation method to demix the layovered scatterers, avoiding the computationally expensive tomographic inversion. We demonstrate that the state-of-the-art principle component decomposition-based methods are heavily influenced by the nonergodicity of the selected samples, especially in urban area, such as point scatterers appearing often on facades. The proposed method is shown to be more robust than the state-of-the-art. Real data example shows that the proposed method outperforms the state-of-the-art by a factor of three in terms of the accuracy of the retrieved phase.

In this paper, we present a method for regularizing noisy 3D reconstructions, which is especially well suited for scenes containing planar structures like buildings. At horizontal structures, the input model is divided into slices and for each slice, an inside/outside labeling is computed. With the outlines of each slice labeling, we create an irregularly shaped volumetric cell decomposition of the whole scene. Then, an optimized inside/outside labeling of these cells is computed by solving an energy minimization problem. For the cell labeling optimization we introduce a novel smoothness term, where lines in the images are used to improve the regularization result. We show that our approach can take arbitrary dense meshed point clouds as input and delivers well regularized building models, which can be textured afterwards.

The launch of the wide-swath SAR missions with short repeat-pass cycles, such as Sentinel-1, will soon lead to an unprecedented large InSAR data archive. Time-series analysis on the rapidly growing data will thus become computationally demanding for a systematic monitoring of earth surface deformation. As the state-of-the-art approach in InSAR time-series analysis, the distributed scatterer interferometric (DSI) techniques shall adapt agile processing schemes to deal with the upcoming big data; an aspect to which limited attention has been dedicated so far. In this contribution, a sequential DSI scheme is proposed to address this demand. Based on SAR data reduction, the scheme allows for batch processing with negligible performance loss compared to the Cramér-Rao Lower Bound. The performance of the proposed sequential estimator is compared to the current DSI algorithms under two contradicting coherence scenarios. The application of the proposed sequential estimator to the real C- and L-band data is ongoing and will be presented in the final paper.

The use of fully polarimetric SAR data for oil spill detection is relatively new and shows great potential for operational off-shore platform monitoring. Greater availability of these kind of SAR data calls for a development of time critical processing chain capable of detecting and distinguishing oil spills from ‘look-alikes’. This paper describes the development of an automated Near Real Time (NRT) oil spill detection processing chain based on quad-pol RADARSAT-2 (RS-2) and quad-pol TerraSAR-X (TS-X) images, wherein we use polarimetric features (e.g. Lexicographic and Pauli Based features) to characterize oil spills and look-alikes. Numbers of TS-X and RS-2 images have been acquired over known off-shore platforms along with some near coincident (spatially and temporally) acquisition. Ten polarimetric feature parameters were extracted from different types of oil (e.g. crude oil, emulsion etc) and ‘look-alike’ (e.g. plant oil, met-oceanic phenomenon etc) spots and divided into training and validation dataset seperately for TerraSAR-X RADARSAT-2. Extracted features were then used for training and validation of a pixel based Artificial Neural Network (ANN) classifier. Initial performance estimation was carried out for the proposed methodology in order to evaluate its suitability for NRT operational service. Mutual information contents among extracted features were assessed and feature parameters were ranked according to their ability to discriminate between oil spills and look- alikes. Polarimetric features such as Scattering Diversity and Pauli-based features proved to be more discriminative than other polarimetric features.