Query: Recurrent World Models Facilitate Policy Evolution

Relevant passages:
Intrinsic Motivation Systems for Autonomous Mental Development <=SEP=> Exploratory activities seem to be intrinsically rewarding for children and crucial for their cognitive development. Can a machine be endowed with such an intrinsic motivation system? This is the question we study in this paper, presenting a number of computational systems that try to capture this drive towards novel or curious situations. After discussing related research coming from developmental psychology, neuroscience, developmental robotics, and active learning, this paper presents the mechanism of Intelligent Adaptive Curiosity, an intrinsic motivation system which pushes a robot towards situations in which it maximizes its learning progress. This drive makes the robot focus on situations which are neither too predictable nor too unpredictable, thus permitting autonomous mental development. The complexity of the robot's activities autonomously increases and complex developmental sequences self-organize without being constructed in a supervised manner. Two experiments are presented illustrating the stage-like organization emerging with this mechanism. In one of them, a physical robot is placed on a baby play mat with objects that it can learn to manipulate. Experimental results show that the robot first spends time in situations which are easy to learn, then shifts its attention progressively to situations of increasing difficulty, avoiding situations in which nothing can be learned. Finally, these various results are discussed in relation to more complex forms of behavioral organization and data coming from developmental psychology

Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images <=SEP=> We introduce Embed to Control (E2C), a method for model learning and control of non-linear dynamical systems from raw pixel images. E2C consists of a deep generative model, belonging to the family of variational autoencoders, that learns to generate image trajectories from a latent space in which the dynamics is constrained to be locally linear. Our model is derived directly from an optimal control formulation in latent space, supports long-term prediction of image sequences and exhibits strong performance on a variety of complex control problems.

PowerPlay: Training an Increasingly General Problem Solver by Continually Searching for the Simplest Still Unsolvable Problem <=SEP=> Most of computer science focuses on automatically solving given computational problems. I focus on automatically inventing or discovering problems in a way inspired by the playful behavior of animals and humans, to train a more and more general problem solver from scratch in an unsupervised fashion. Consider the infinite set of all computable descriptions of tasks with possibly computable solutions. Given a general problem-solving architecture, at any given time, the novel algorithmic framework PowerPlay (Schmidhuber, 2011) searches the space of possible pairs of new tasks and modifications of the current problem solver, until it finds a more powerful problem solver that provably solves all previously learned tasks plus the new one, while the unmodified predecessor does not. Newly invented tasks may require to achieve a wow-effect by making previously learned skills more efficient such that they require less time and space. New skills may (partially) re-use previously learned skills. The greedy search of typical PowerPlay variants uses time-optimal program search to order candidate pairs of tasks and solver modifications by their conditional computational (time and space) complexity, given the stored experience so far. The new task and its corresponding task-solving skill are those first found and validated. This biases the search toward pairs that can be described compactly and validated quickly. The computational costs of validating new tasks need not grow with task repertoire size. Standard problem solver architectures of personal computers or neural networks tend to generalize by solving numerous tasks outside the self-invented training set; PowerPlay's ongoing search for novelty keeps breaking the generalization abilities of its present solver. This is related to Gödel's sequence of increasingly powerful formal theories based on adding formerly unprovable statements to the axioms without affecting previously provable theorems. The continually increasing repertoire of problem-solving procedures can be exploited by a parallel search for solutions to additional externally posed tasks. PowerPlay may be viewed as a greedy but practical implementation of basic principles of creativity (Schmidhuber, 2006a, 2010). A first experimental analysis can be found in separate papers (Srivastava et al., 2012a,b, 2013).

Overcoming catastrophic forgetting in neural networks <=SEP=> The ability to learn tasks in a sequential fashion is crucial to the development of artificial intelligence. Until now neural networks have not been capable of this and it has been widely thought that catastrophic forgetting is an inevitable feature of connectionist models. We show that it is possible to overcome this limitation and train networks that can maintain expertise on tasks that they have not experienced for a long time. Our approach remembers old tasks by selectively slowing down learning on the weights important for those tasks. We demonstrate our approach is scalable and effective by solving a set of classification tasks based on a hand-written digit dataset and by learning several Atari 2600 games sequentially.

Three Approaches to the Quantitative Definition of Information in an Individual Pure Quantum State <=SEP=> In analogy of classical Kolmogorov complexity we develop a theory of the algorithmic information in bits contained in any one of continuously many pure quantum states: quantum Kolmogorov complexity. Classical Kolmogorov complexity coincides with the new quantum Kolmogorov complexity restricted to the classical domain. Quantum Kolmogorov complexity is upper bounded and can be effectively approximated from above. With high probability a quantum object is incompressible. There are two alternative approaches possible: to define the complexity as the length of the shortest qubit program that effectively describes the object, and to use classical descriptions with computable real parameters.

High Beam Steering in Fabry–Pérot Leaky-Wave Antennas <=SEP=> A high-gain low-profile Fabry-Perot (FP) leaky-wave antenna (LWA) presenting one-dimensional high beam steering properties is proposed in this letter. The structure consists of a ground plane and a varying inductive partially reflective surface (PRS). A microstrip patch antenna is embedded into the cavity to act as the primary feed. As design examples, antennas are designed to operate at 9.5 GHz. Subwavelength FP cavities with fixed overall thickness of λ0 /6 (where λ0 is the free-space operating wavelength) are fabricated and measured. The impact of varying the PRS inductance is analyzed. It is shown that a high beam steering angle from broadside toward endfire direction close to 60 can be obtained when judiciously designing the inductive grid of the PRS.

Intentional rounding: facilitators, benefits and barriers. <=SEP=> AIMS AND OBJECTIVES
To describe the implementation, practice and sustainability of Intentional Rounding (IR) within two diverse settings (aged care and maternity).


BACKGROUND
The profile of patients in hospitals has changed over time, generally being more severe, placing heavy demands on nurses' time. Routine non-urgent care is often provided only when there is time. IR has been found to increase both patient and staff satisfaction, also resulting in improved patient outcomes such as reduced falls and call bell use. IR is also used as a time management tool for safe and reliable provision of routine care.


METHODS
This descriptive qualitative research study comprised of three focus groups in a metropolitan hospital.


RESULTS
Fifteen nurses participated in three focus groups. Seven main themes emerged from the thematic analysis of the verbatim transcripts: implementation and maintenance, how IR works, roles and responsibilities, context and environment, benefits, barriers and legal issues.


CONCLUSION
IR was quickly incorporated into normal practice, with clinicians being able to describe the main concepts and practices. IR was seen as a management tool, facilitating accountability and continuity of management support being essential for sustainability. Clinicians reported increases in patient and staff satisfaction, and the opportunity to provide patient education. While patient type and acuity, ward layout and staff experience affected the practice of IR, the principles of IR are robust enough to allow for differences in the ward specialty and patient type. However, care must be taken when implementing IR to reduce the risk of alienating experienced staff. Incorporation of IR charts into the patient health care record is recommended.


RELEVANCE TO CLINICAL PRACTICE
Engaging all staff, encouraging ownership and stability of management are key factors in the successful implementation and maintenance of IR. IR is flexible and robust enough to accommodate different patient types and acuity.

Adding Semantic Role Annotation to a Corpus of Written Dutch <=SEP=> We present an approach to automatic semantic role labeling (SRL) carried out in the context of the Dutch Language Corpus Initiative (D-Coi) project. Adapting earlier research which has mainly focused on English to the Dutch situation poses an interesting challenge especially because there is no semantically annotated Dutch corpus available that can be used as training data. Our automatic SRL approach consists of three steps: bootstrapping from a syntactically annotated corpus by means of a rulebased tagger developed for this purpose, manual correction on the basis of the PropBank guidelines which have been adapted to Dutch and training a machine learning system on the manually corrected data.

Impacts of increasing volume of digital forensic data: A survey and future research challenges <=SEP=> 

Comparison and Analysis of Single-Phase Transformerless Grid-Connected PV Inverters <=SEP=> Leakage current minimization is one of the most important considerations in transformerless photovoltaic (PV) inverters. In the past, various transformerless PV inverter topologies have been introduced, with leakage current minimized by the means of galvanic isolation and common-mode voltage (CMV) clamping. The galvanic isolation can be achieved via dc-decoupling or ac-decoupling, for isolation on the dc- or ac-side of the inverter, respectively. It has been shown that the latter provides lower losses due to the reduced switch count in conduction path. Nevertheless, leakage current cannot be simply eliminated by galvanic isolation and modulation techniques, due to the presence of switches' junction capacitances and resonant circuit effects. Hence, CMV clamping is used in some topologies to completely eliminate the leakage current. In this paper, several recently proposed transformerless PV inverters with different galvanic isolation methods and CMV clamping technique are analyzed and compared. A simple modified H-bridge zero-voltage state rectifier is also proposed, to combine the benefits of the low-loss ac-decoupling method and the complete leakage current elimination of the CMV clamping method. The performances of different topologies, in terms of CMV, leakage current, total harmonic distortion, losses and efficiencies are compared. The analyses are done theoretically and via simulation studies, and further validated with experimental results. This paper is helpful for the researchers to choose the appropriate topology for transformerless PV applications and to provide the design principles in terms of common-mode behavior and efficiency.

Lane-Change Fuzzy Control in Autonomous Vehicles for the Overtaking Maneuver <=SEP=> The automation of the overtaking maneuver is considered to be one of the toughest challenges in the development of autonomous vehicles. This operation involves two vehicles (the overtaking and the overtaken) cooperatively driving, as well as the surveillance of any other vehicles that are involved in the maneuver. This operation consists of two lane changes-one from the right to the left lane of the road, and the other is to return to the right lane after passing. Lane-change maneuvers have been used to move into or out of a circulation lane or platoon; however, overtaking operations have not received much coverage in the literature. In this paper, we present an overtaking system for autonomous vehicles equipped with path-tracking and lane-change capabilities. The system uses fuzzy controllers that mimic human behavior and reactions during overtaking maneuvers. The system is based on the information that is supplied by a high-precision Global Positioning System and a wireless network environment. It is able to drive an automated vehicle and overtake a second vehicle that is driving in the same lane of the road.

Why do you play World of Warcraft? An in-depth exploration of self-reported motivations to play online and in-game behaviours in the virtual world of Azeroth <=SEP=> Massively multiplayer online role-playing games (MMORPGs) are video games in which players create an avatar that evolves and interacts with other avatars in a persistent virtual world. Motivations to play MMORPGs are heterogeneous (e.g. achievement, socialisation, immersion in virtual worlds). This study investigates in detail the relationships between self-reported motives and actual in-game behaviours. We recruited a sample of 690 World of Warcraft players (the most popular MMORPG) who agreed to have their avatar monitored for 8 months. Participants completed an initial online survey about their motives to play. Their actual in-game behaviours were measured through the game’s official database (the Armory website). Results showed specific associations between motives and in-game behaviours. Moreover, longitudinal analyses revealed that teamworkand competition-oriented motives are the most accurate predictors of fast progression in the game. In addition, although specific associations exist between problematic use and certain motives (e.g. advancement, escapism), longitudinal analyses showed that high involvement in the game is not necessarily associated with a negative impact upon daily living. 2012 Elsevier Ltd. All rights reserved.

Linked data on the web (LDOW2008) <=SEP=> The Web is increasingly understood as a global information space consisting not just of linked documents, but also of Linked Data. More than just a vision, the resulting Web of Data has been brought into being by the maturing of the Semantic Web technology stack, and by the publication of an increasing number of datasets according to the principles of Linked Data.
 The Linked Data on the Web (LDOW2008) workshop brings together researchers and practitioners working on all aspects of Linked Data. The workshop provides a forum to present the state of the art in the field and to discuss ongoing and future research challenges. In this workshop summary we will outline the technical context in which Linked Data is situated, describe developments in the past year through initiatives such as the Linking Open Data community project, and look ahead to the workshop itself.

(Leader/Randomization/Signature)-free Byzantine Consensus for Consortium Blockchains <=SEP=> This paper presents a new resilience optimal Byzantine consensus algorithm targeting consortium blockchains. To this end, it first revisits the consensus validity property by requiring that the decided value satisfies a predefined predicate, which does not systematically exclude a value proposed only by Byzantine processes, thereby generalizing the validity properties found in the literature. Then the paper presents a simple and modular Byzantine consensus algorithm that relies neither on a leader, nor on signatures, nor on randomization. It consists of a reduction of multivalued Byzantine consensus to binary Byzantine consensus satisfying this validity property. This reduction terminates after a constant-sized sequence of binary Byzantine consensus instances. The idea is to spawn concurrent instances of binary consensus but to decide only after a sequence of two of these instances. The binary consensus instances result in a bitmask that the reduction applies to a vector of multivalued proposals to filter out a valid proposed value that is decided. The paper then presents an underlying binary Byzantine consensus algorithm that assumes eventual synchrony to terminate.

Social Interactions and Social Preferences in Social Networks <=SEP=> We extend the utility specification in Ballester et al. (2006) to study social interactions when individuals hold altruistic preferences in social networks. We show that more enriched network features can be captured in the best response function derived from the maximization of the extended utility which incorporates altruism, providing microfoundation for studies which investigate how network features mediate peer effects or other important features in social interactions. We demonstrate that often ignored altruism is another serious confounding factor of peer effects. Our results show that the estimates of peer affects are about 36% smaller under altruistic preferences. Furthermore, we are able to separate the two different types of effects generated by peers: the (usually positive) spillover effects from peers and the (negative or positive) externality effects directly generated from peers’ outcomes, which is not possible in conventional social interactions model based on self-interest hypothesis. JEL Classification: I10 I20 C31

Beating the adaptive bandit with high probability <=SEP=> We provide a principled way of proving Õ(√T) high-probability guarantees for partial-information (bandit) problems over arbitrary convex decision sets. First, we prove a regret guarantee for the full-information problem in terms of “local” norms, both for entropy and self-concordant barrier regularization, unifying these methods. Given one of such algorithms as a black-box, we can convert a bandit problem into a full-information problem using a sampling scheme. The main result states that a high-probability Õ(√T) bound holds whenever the black-box, the sampling scheme, and the estimates of missing information satisfy a number of conditions, which are relatively easy to check. At the heart of the method is a construction of linear upper bounds on confidence intervals. As applications of the main result, we provide the first known efficient algorithm for the sphere with an Õ(√T) high-probability bound. We also derive the result for the n-simplex, improving the O(√nT log(nT)) bound of Auer et al [3] by replacing the log T term with log log T and closing the gap to the lower bound of Ω(√nT). While Õ(√T) high-probability bounds should hold for general decision sets through our main result, construction of linear upper bounds depends on the particular geometry of the set; we believe that the sphere example already exhibits the necessary ingredients. The guarantees we obtain hold for adaptive adversaries (unlike the in-expectation results of [1]) and the algorithms are efficient, given that the linear upper bounds on confidence can be computed.

Current Methods in the Automatic Tissue Segmentation of 3D Magnetic Resonance Brain Images <=SEP=> Accurate segmentation of magnetic resonance (MR) images of the brain is of interest in the study of many brain disorders. In this paper, we provide a review of some of the current approaches in the tissue segmentation of MR brain images. We broadly divided current MR brain image segmentation algorithms into three categories: classificationbased, region-based, and contour-based, and discuss the advantages and disadvantages of these approaches. We also briefly review our recent work in this area. We show that by incorporating two key ideas into the conventional fuzzy cmeans clustering algorithm, we are able to take into account the local spatial context and compensate for the intensity nonuniformity (INU) artifact during the clustering process. We conclude this review by pointing to some possible future directions in this area.

Inventory of Transcribed and Translated Talks <=SEP=> We describe here a Web inventory named WIT3 that offers access to a collection of transcribed and translated talks. The core of WIT3 is the TED Talks corpus, that basically redistributes the original content published by the TED Conference website (http://www.ted.com). Since 2007, the TED Conference, based in California, has been posting all video recordings of its talks together with subtitles in English and their translations in more than 80 languages. Aside from its cultural and social relevance, this content, which is published under the Creative Commons BYNC-ND license, also represents a precious language resource for the machine translation research community, thanks to its size, variety of topics, and covered languages. This effort repurposes the original content in a way which is more convenient for machine translation researchers.

Microservices approach for the internet of things <=SEP=> The microservice approach has created a hype in the domain of cloud and enterprise application business. Before, grown, monolithic, software has been pushed to the limits of maintainability and scalability. The microservice architecture approach utilizes the service oriented architecture together with best practices and recent developments in software virtualization to overcome those issues. One monolithic application is split up into a set of distributed services. Those are strongly decoupled to enable high maintainability and scalability. In this case an application is split up in a top down manner. In the internet of things, applications need to be put together from a set of small and independent services. Thus, creating value added services would require to freely combine services of different vendors to fully make use of the IoT's heterogeneity. Even though the direction is different, many of the requirements in microservices are similar to those of the internet of things. This paper investigates patterns and best practices that are used in the microservices approach and how they can be used in the internet of things. Since the companies using microservices have made considerations on how services have to be designed to work together properly, IoT applications might adopt several of these design decisions to improve the ability to create value added applications from a multitude of services.

Blood pressure-lowering effect of Shinrin-yoku (Forest bathing): a systematic review and meta-analysis <=SEP=> BACKGROUND
Shinrin-yoku (experiencing the forest atmosphere or forest bathing) has received increasing attention from the perspective of preventive medicine in recent years. Some studies have reported that the forest environment decreases blood pressure. However, little is known about the possibility of anti-hypertensive applications of Shinrin-yoku. This study aimed to evaluate preventive or therapeutic effects of the forest environment on blood pressure.


METHODS
We systematically reviewed the medical literature and performed a meta-analysis.Four electronic databases were systematically searched for the period before May 2016 with language restriction of English and Japanese. The review considered all published, randomized, controlled trials, cohort studies, and comparative studies that evaluated the effects of the forest environment on changes in systolic blood pressure. A subsequent meta-analysis was performed.


RESULTS
Twenty trials involving 732 participants were reviewed. Systolic blood pressure of the forest environment was significantly lower than that of the non-forest environment. Additionally, diastolic blood pressure of the forest environment was significantly lower than that of the non-forest environment.


CONCLUSIONS
This systematic review shows a significant effect of Shinrin-yoku on reduction of blood pressure.

Origins of narcissism in children. <=SEP=> Narcissism levels have been increasing among Western youth, and contribute to societal problems such as aggression and violence. The origins of narcissism, however, are not well understood. Here, we report, to our knowledge, the first prospective longitudinal evidence on the origins of narcissism in children. We compared two perspectives: social learning theory (positing that narcissism is cultivated by parental overvaluation) and psychoanalytic theory (positing that narcissism is cultivated by lack of parental warmth). We timed the study in late childhood (ages 7-12), when individual differences in narcissism first emerge. In four 6-mo waves, 565 children and their parents reported child narcissism, child self-esteem, parental overvaluation, and parental warmth. Four-wave cross-lagged panel models were conducted. Results support social learning theory and contradict psychoanalytic theory: Narcissism was predicted by parental overvaluation, not by lack of parental warmth. Thus, children seem to acquire narcissism, in part, by internalizing parents' inflated views of them (e.g., "I am superior to others" and "I am entitled to privileges"). Attesting to the specificity of this finding, self-esteem was predicted by parental warmth, not by parental overvaluation. These findings uncover early socialization experiences that cultivate narcissism, and may inform interventions to curtail narcissistic development at an early age.

Synthesis of a compound T-junction for a two-way splitter with arbitrary power ratio <=SEP=> We have developed a simple and efficient procedure to design H-plane rectangular waveguide T-junctions for equal and unequal two-way power splitters. This synthesis procedure is scalable, renders manufacturable structures, applicable to any arbitrary power split-ratio, and can offer wide band operation. In our implementation, we utilized wedges and inductive windows (being an integral part of the T-junctions), to provide more degrees of freedom, thus, excellent match at the input port, flat power-split ratio over the band with equal phase, where phase balance is essential for various antenna feeds.

Question Generation Shared Task and Evaluation Challenge - Status Report <=SEP=> The First Shared Task Evaluation Challenge on Question Generation took place in 2010 as part of the 3 workshop on Question Generation. The campaign included two tasks: Question Generation from Sentences and Question Generation from Paragraphs. This status report briefly summarizes the motivation, tasks and results. Lessons learned relevant to future QG-STECs are also offered.

Brain MRI Findings of Nitrogen Gas Inhalation for Suicide Attempt: a Case Report <=SEP=> According to the Organization for Economic Cooperation and Development (OECD) report in 2015, South Korea had the highest suicide rate among all countries that belong to the OECD. In contrast to the pattern in most OECD countries, death rates from suicide in Korea have risen significantly in the last decade (1). Recently, several organizations and internet communities in favor of assisted suicide have promoted the use of nitrogen (N2) gas to that end (2). Nitrogen gas has caused accidental deaths in industrial or laboratory explosion, and during scuba diving and anesthesia (2). Although it is reported that industrial nitrogen asphyxiation hazards resulted in 80 deaths during the period 1992 through 2002, there is a paucity of documentation regarding nitrogen gas as a means of committing suicide (2, 3). Nitrogen is a colorless, odorless, nontoxic, and generally inert gas that is a normal component (78.09%) of the atmosphere, at standard temperature and pressure (4). However, nitrogen can be hazardous when it displaces oxygen resulting in hypoxic damage (2, 3). Nitrogen intoxication manifests with various symptoms such as progressive fatigue, loss of coordination, purposeful movement and balance, nausea, a complete inability to move and unconsciousness (2, 4). Here, we describe a case of brain magnetic resonance imaging (MRI) findings associated with nitrogen gas inhalation, which have been rarely reported previously. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/ by-nc/3.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. Received: September 18, 2017 Revised: October 1, 2017 Accepted: October 12, 2017

Classification using Hybrid SVM and KNN Approach <=SEP=> Phishing is a potential web threat that includes mimicking official websites to trick users by stealing their important information such as username and password related to financial systems. The attackers use social engineering techniques like email, SMS and malware to fraud the users. Due to the potential financial losses caused by phishing, it is essential to find effective approaches for phishing websites detection. This paper proposes a hybrid approach for classifying the websites as Phishing, Legitimate or Suspicious websites, the proposed approach intelligently combines the K-nearest neighbors (KNN) algorithm with the Support Vector Machine (SVM) algorithm in two stages. Firstly, the KNN was utilized as a robust to noisy data and effective classifier. Secondly, the SVM is employed as a powerful classifier. The proposed approach integrates the simplicity of KNN with the effectiveness of SVM. The experimental results show that the proposed hybrid approach achieved the highest accuracy of 90.04% when compared with other approaches. Keywords—Information security; phishing websites; support vector machine; K-nearest neighbors

The Practical Use of BI Visualizations in Decision-making <=SEP=> Type of thesis: Master Degree Project in Accounting, 30 credits University: University of Gothenburg, School of Business, Economics and Law Semester: Spring 2017 Author: Kevin Larsson & Philip Kaber Supervisor: Elisabeth Frisk Title: The Practical Use of BI Visualizations in Decision-making Background and problem: Due to the constantly altering business environment, firms are trying to find ways of combining information technology (IT) and decision-making in order to grasp information of the complex and dynamic business environment. As a solution to this strenuousness; business intelligence (BI) systems serve to conduct more efficient and reliable decisions by the means of visualizations. One existing gap in the research of BI concerns the sociotechnical effects involved in the decision-making, in which knowledge of how BI visualizations are used and may be used in practice to support the decision-making have remained limited. Research aim: The research aim of the study is to investigate how BI visualizations are and may be used to support strategic and operational decisions. Further, the study addresses how BI visualizations are used in various decision contexts. Research questions: The following questions are addressed in order to achieve the research aim: (1) How are and may BI visualizations be used in strategic and operational decisions? (1a) Which visual elements are used depending on the task and decision category? (2) How are BI visualizations used in different decision contexts? Research design: A qualitative study was made through semi-structured interviews. In-depth interviews with six people from the purchasing company were conducted in order to understand how BI and visualizations are and may be used. Two people from the consultancy company were interviewed in order to understand how BI and visualizations may be used. Discussion and conclusion: The primary purpose of BI systems in the purchasing company is to support decision-making from a strategic perspective by providing the business with new insights and monitor business processes. However, the findings in this study also suggest that BI visualizations are used for operational errands. Strategic decisions are primary based on graphical representations, whereas operational decisions are based on data derived from tables and additional calculations in Excel. By creating more interactive, initiative, and humanizing visualizations, the end-users may discover new patterns of information and enhance the cognitive fit without being overwhelmed by data. BI visualizations may also be used in a larger extent to detect errors in data. The usage depends on the decision situation, in which decisions made in the fact-based contexts domains tend to be based on intuitions and BI visualizations, before responding to the business problem. This differs from the pattern-based management domains, in which actions are done prior to the analysis as there is lack of data. Further the findings indicate that several people are often involved in the decisions. The mental model of the respondents is not entirely fit in a cognitive aspect.

Electric Flight – Potential and Limitations <=SEP=> During the last years, the development of electric propulsion systems is pushed strongly, most notably for automotive applications. For ground based transportation, the system mass is relevant, but of relatively low importance. This paper addresses the application of electric propulsion systems in aeronautics, where all systems are much more constrained by their mass. After comparing different propulsion system architectures the focus is cast on the energy storage problem and here especially on battery storage systems. Using first order principles the limitations and required technology developments are demonstrated by introducing battery powered electric propulsion systems to small and medium sized aircraft. Abbreviations and Symbols b = wing span [m] C = capacity [Wh] D = drag force [N] * E = mass specific energy content [Wh/kg] e f = empty mass fraction e m /m g = gravity acceleration [m/s] L = lift force [N] m = mass [kg] initial m = initial mass at takeoff [kg] e m = empty mass without fuel and payload [kg] final m = final mass at landing [kg] battery m = battery mass [kg] payload m = payload mass [kg] pax m = mass per passenger [kg] PAX = number of passengers P = power [W] battery P = electric power provided by battery [W] R = range [m] t = time [s] T = thrust [N] * V = volume specific energy content [Wh/m] v¥ = flight speed [m/s] h = efficiency ¥ r = density of air [kg/m ]

ANANAS - A Framework for Analyzing Android Applications <=SEP=> Android is an open software platform for mobile devices with a large market share in the smart phone sector. The openness of the system as well as its wide adoption lead to an increasing amount of malware developed for this platform. ANANAS is an expandable and modular framework for analyzing Android applications. It takes care of common needs for dynamic malware analysis and provides an interface for the development of plugins. Adaptability and expandability have been main design goals during the development process. An abstraction layer for simple user interaction and phone event simulation is also part of the framework. It allows an analyst to script the required user simulation or phone events on demand or adjust the simulation to his needs. Six plugins have been developed for ANANAS. They represent well known techniques for malware analysis, such as system call hooking and network traffic analysis. The focus clearly lies on dynamic analysis, as five of the six plugins are dynamic analysis methods.

Motion tracking and gait feature estimation for recognising Parkinson's disease using MS Kinect. <=SEP=> BACKGROUND
Analysis of gait features provides important information during the treatment of neurological disorders, including Parkinson's disease. It is also used to observe the effects of medication and rehabilitation. The methodology presented in this paper enables the detection of selected gait attributes by Microsoft (MS) Kinect image and depth sensors to track movements in three-dimensional space.


METHODS
The experimental part of the paper is devoted to the study of three sets of individuals: 18 patients with Parkinson's disease, 18 healthy aged-matched individuals, and 15 students. The methodological part of the paper includes the use of digital signal-processing methods for rejecting gross data-acquisition errors, segmenting video frames, and extracting gait features. The proposed algorithm describes methods for estimating the leg length, normalised average stride length (SL), and gait velocity (GV) of the individuals in the given sets using MS Kinect data.


RESULTS
The main objective of this work involves the recognition of selected gait disorders in both the clinical and everyday settings. The results obtained include an evaluation of leg lengths, with a mean difference of 0.004 m in the complete set of 51 individuals studied, and of the gait features of patients with Parkinson's disease (SL: 0.38 m, GV: 0.61 m/s) and an age-matched reference set (SL: 0.54 m, GV: 0.81 m/s). Combining both features allowed for the use of neural networks to classify and evaluate the selectivity, specificity, and accuracy. The achieved accuracy was 97.2 %, which suggests the potential use of MS Kinect image and depth sensors for these applications.


CONCLUSIONS
Discussion points include the possibility of using the MS Kinect sensors as inexpensive replacements for complex multi-camera systems and treadmill walking in gait-feature detection for the recognition of selected gait disorders.

BackIP : Backpressure Routing in IPv 6-Based Wireless Sensor Networks <=SEP=> Wireless sensor networks are increasingly being deployed in real-world applications ranging from energy monitoring to water-level measurement. To better integrate with existing network infrastructure, they are being designed to communicate using IPv6. The current de-facto standard for routing in IPv6-based sensor networks is the shortest-path-based RPL, developed by the IETF 6LoWPaN working group. This paper describes BackIP, an alternative routing protocol for data collection in IPv6-based wireless sensor networks that is based on the backpressure paradigm. In a backpressure-based protocol, routing decisions can be made on-the-fly on a perpacket basis by nodes based on the current locally observed state, and prior work has shown that they can offer superior throughput performance and responsiveness to dynamic conditions compared to shortest-path routing protocols. We discuss a number of design decisions that are needed to enable backpressure routing to work in a scalable and efficient manner with IPv6. We implement and evaluate the performance of this protocol on a TinyOS-based real wireless sensor network testbed.