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Mobile expressive rendering gained increasing popularity among users seeking casual creativity by image stylization and supports the development of mobile artists as a new user group. In particular, neural style transfer has advanced as a core technology to emulate characteristics of manifold artistic styles. However, when it comes to creative expression, the technology still faces inherent limitations in providing low-level controls for localized image stylization. This work enhances state-of-the-art neural style transfer techniques by a generalized user interface with interactive tools to facilitate a creative and localized editing process. Thereby, we first propose a problem characterization representing trade-offs between visual quality, run-time performance, and user control. We then present MaeSTrO, a mobile app for orchestration of neural style transfer techniques using iterative, multi-style generative and adaptive neural networks that can be locally controlled by on-screen painting metaphors. At this, first user tests indicate different levels of satisfaction for the implemented techniques and interaction design.
Logical modeling has been widely used to understand and expand the knowledge about protein interactions among different pathways. Realizing this, the caspo-ts system has been proposed recently to learn logical models from time series data. It uses Answer Set Programming to enumerate Boolean Networks (BNs) given prior knowledge networks and phosphoproteomic time series data. In the resulting sequence of solutions, similar BNs are typically clustered together. This can be problematic for large scale problems where we cannot explore the whole solution space in reasonable time. Our approach extends the caspo-ts system to cope with the important use case of finding diverse solutions of a problem with a large number of solutions. We first present the algorithm for finding diverse solutions and then we demonstrate the results of the proposed approach on two different benchmark scenarios in systems biology: (1) an artificial dataset to model TCR signaling and (2) the HPN-DREAM challenge dataset to model breast cancer cell lines.
The influence of chemical composition and crystallisation conditions on the ferroelectric and paraelectric phases and the resulting morphology in Poly(vinylidene fluoride-trifluoroethylene-chlorofluoroethylene) (P(VDF-TrFE-CFE)) terpolymer films with 55.4/37.2/7.3 mol% or with 62.2/29.4/8.4 mol% of VDF/TrFE/CFE was studied. Poly(vinylidene fluoride trifluoroethylene) (P(VDF-TrFE)) with 75/25 mol% VDF/TrFE was employed as reference material. Fourier-Transform Infrared Spectroscopy (FTIR) was used to determine the fractions of the relevant terpolymer phases, and X-Ray Diffraction (XRD) was employed to assess the crystalline morphology. The FTIR results show an increase of the fraction of paraelectric phases after annealing. On the other hand, XRD results indicate a more stable paraelectric phase in the terpolymer with higher CFE content.
Business process simulation is an important means for quantitative analysis of a business process and to compare different process alternatives. With the Business Process Model and Notation (BPMN) being the state-of-the-art language for the graphical representation of business processes, many existing process simulators support already the simulation of BPMN diagrams. However, they do not provide well-defined interfaces to integrate new concepts in the simulation environment. In this work, we present the design and architecture of a proof-of-concept implementation of an open and extensible BPMN process simulator. It also supports the simulation of multiple BPMN processes at a time and relies on the building blocks of the well-founded discrete event simulation. The extensibility is assured by a plug-in concept. Its feasibility is demonstrated by extensions supporting new BPMN concepts, such as the simulation of business rule activities referencing decision models and batch activities.
Minimising Information Loss on Anonymised High Dimensional Data with Greedy In-Memory Processing
(2018)
Minimising information loss on anonymised high dimensional data is important for data utility. Syntactic data anonymisation algorithms address this issue by generating datasets that are neither use-case specific nor dependent on runtime specifications. This results in anonymised datasets that can be re-used in different scenarios which is performance efficient. However, syntactic data anonymisation algorithms incur high information loss on high dimensional data, making the data unusable for analytics. In this paper, we propose an optimised exact quasi-identifier identification scheme, based on the notion of k-anonymity, to generate anonymised high dimensional datasets efficiently, and with low information loss. The optimised exact quasi-identifier identification scheme works by identifying and eliminating maximal partial unique column combination (mpUCC) attributes that endanger anonymity. By using in-memory processing to handle the attribute selection procedure, we significantly reduce the processing time required. We evaluated the effectiveness of our proposed approach with an enriched dataset drawn from multiple real-world data sources, and augmented with synthetic values generated in close alignment with the real-world data distributions. Our results indicate that in-memory processing drops attribute selection time for the mpUCC candidates from 400s to 100s, while significantly reducing information loss. In addition, we achieve a time complexity speed-up of O(3(n/3)) approximate to O(1.4422(n)).
The overhead of moving data is the major limiting factor in todays hardware, especially in heterogeneous systems where data needs to be transferred frequently between host and accelerator memory. With the increasing availability of hardware-based compression facilities in modern computer architectures, this paper investigates the potential of hardware-accelerated I/O Link Compression as a promising approach to reduce data volumes and transfer time, thus improving the overall efficiency of accelerators in heterogeneous systems. Our considerations are focused on On-the-Fly compression in both Single-Node and Scale-Out deployments. Based on a theoretical analysis, this paper demonstrates the feasibility of hardware-accelerated On-the-Fly I/O Link Compression for many workloads in a Scale-Out scenario, and for some even in a Single-Node scenario. These findings are confirmed in a preliminary evaluation using software-and hardware-based implementations of the 842 compression algorithm.
High-throughput RNA sequencing (RNAseq) produces large data sets containing expression levels of thousands of genes. The analysis of RNAseq data leads to a better understanding of gene functions and interactions, which eventually helps to study diseases like cancer and develop effective treatments. Large-scale RNAseq expression studies on cancer comprise samples from multiple cancer types and aim to identify their distinct molecular characteristics. Analyzing samples from different cancer types implies analyzing samples from different tissue origin. Such multi-tissue RNAseq data sets require a meaningful analysis that accounts for the inherent tissue-related bias: The identified characteristics must not originate from the differences in tissue types, but from the actual differences in cancer types. However, current analysis procedures do not incorporate that aspect. As a result, we propose to integrate a tissue-awareness into the analysis of multi-tissue RNAseq data. We introduce an extension for gene selection that provides a tissue-wise context for every gene and can be flexibly combined with any existing gene selection approach. We suggest to expand conventional evaluation by additional metrics that are sensitive to the tissue-related bias. Evaluations show that especially low complexity gene selection approaches profit from introducing tissue-awareness.
In the course of patient treatments, psychotherapists aim to meet the challenges of being both a trusted, knowledgeable conversation partner and a diligent documentalist. We are developing the digital whiteboard system Tele-Board MED (TBM), which allows the therapist to take digital notes during the session together with the patient. This study investigates what therapists are experiencing when they document with TBM in patient sessions for the first time and whether this documentation saves them time when writing official clinical documents. As the core of this study, we conducted four anamnesis session dialogues with behavior psychotherapists and volunteers acting in the role of patients. Following a mixed-method approach, the data collection and analysis involved self-reported emotion samples, user experience curves and questionnaires. We found that even in the very first patient session with TBM, therapists come to feel comfortable, develop a positive feeling and can concentrate on the patient. Regarding administrative documentation tasks, we found with the TBM report generation feature the therapists save 60% of the time they normally spend on writing case reports to the health insurance.
An Information System Supporting the Eliciting of Expert Knowledge for Successful IT Projects
(2018)
In order to guarantee the success of an IT project, it is necessary for a company to possess expert knowledge. The difficulty arises when experts no longer work for the company and it then becomes necessary to use their knowledge, in order to realise an IT project. In this paper, the ExKnowIT information system which supports the eliciting of expert knowledge for successful IT projects, is presented and consists of the following modules: (1) the identification of experts for successful IT projects, (2) the eliciting of expert knowledge on completed IT projects, (3) the expert knowledge base on completed IT projects, (4) the Group Method for Data Handling (GMDH) algorithm, (5) new knowledge in support of decisions regarding the selection of a manager for a new IT project. The added value of our system is that these three approaches, namely, the elicitation of expert knowledge, the success of an IT project and the discovery of new knowledge, gleaned from the expert knowledge base, otherwise known as the decision model, complement each other.
We describe how inversion symmetry separation of electronic state manifolds in resonant inelastic soft X-ray scattering (RIXS) can be applied to probe excited-state dynamics with compelling selectivity. In a case study of Fe L3-edge RIXS in the ferricyanide complex Fe(CN)63−, we demonstrate with multi-configurational restricted active space spectrum simulations how the information content of RIXS spectral fingerprints can be used to unambiguously separate species of different electronic configurations, spin multiplicities, and structures, with possible involvement in the decay dynamics of photo-excited ligand-to-metal charge-transfer. Specifically, we propose that this could be applied to confirm or reject the presence of a hitherto elusive transient Quartet species. Thus, RIXS offers a particular possibility to settle a recent controversy regarding the decay pathway, and we expect the technique to be similarly applicable in other model systems of photo-induced dynamics.
Published results on LDPE/MgO nanocomposites (3wt%) show that they promise to be good electrical-insulation materials. In this work, the nanocomposites are examined as a potential (ferro-)electret material as well. Isothermal surface-potential decay measurements show that charged LDPE/MgO films still exhibit significant surface potentials after heating for 4 hours at 80 degrees C, which suggests good capabilities of LDPE/MgO nanocomposites to hold electric charges of both polarities. Open-tubular-channel ferroelectrets prepared from LDPE/MgO nanocomposite films show significant piezoelectricity with d(33) coefficients of about 20 pC/N after charging and are stable up to temperatures of at least 80 degrees C. Thus LDPE/MgO nanocomposites may become available as a new ferroelectret material. To increase their d(33) coefficients, it is desirable to optimize the charging conditions and the ferroelectret structure.
An efficient Design Space Exploration (DSE) is imperative for the design of modern, highly complex embedded systems in order to steer the development towards optimal design points. The early evaluation of design decisions at system-level abstraction layer helps to find promising regions for subsequent development steps in lower abstraction levels by diminishing the complexity of the search problem. In recent works, symbolic techniques, especially Answer Set Programming (ASP) modulo Theories (ASPmT), have been shown to find feasible solutions of highly complex system-level synthesis problems with non-linear constraints very efficiently. In this paper, we present a novel approach to a holistic system-level DSE based on ASPmT. To this end, we include additional background theories that concurrently guarantee compliance with hard constraints and perform the simultaneous optimization of several design objectives. We implement and compare our approach with a state-of-the-art preference handling framework for ASP. Experimental results indicate that our proposed method produces better solutions with respect to both diversity and convergence to the true Pareto front.
Utilizing quad-trees for efficient design space exploration with partial assignment evaluation
(2018)
Recently, it has been shown that constraint-based symbolic solving techniques offer an efficient way for deciding binding and routing options in order to obtain a feasible system level implementation. In combination with various background theories, a feasibility analysis of the resulting system may already be performed on partial solutions. That is, infeasible subsets of mapping and routing options can be pruned early in the decision process, which fastens the solving accordingly. However, allowing a proper design space exploration including multi-objective optimization also requires an efficient structure for storing and managing non-dominated solutions. In this work, we propose and study the usage of the Quad-Tree data structure in the context of partial assignment evaluation during system synthesis. Out experiments show that unnecessary dominance checks can be avoided, which indicates a preference of Quad-Trees over a commonly used list-based implementation for large combinatorial optimization problems.
Introduction
(2018)
Microstructure Characterisation of Advanced Materials via 2D and 3D X-Ray Refraction Techniques
(2018)
3D imaging techniques have an enormous potential to understand the microstructure, its evolution, and its link to mechanical, thermal, and transport properties. In this conference paper we report the use of a powerful, yet not so wide-spread, set of X-ray techniques based on refraction effects. X-ray refraction allows determining internal specific surface (surface per unit volume) in a non-destructive fashion, position and orientation sensitive, and with a nanometric detectability. We demonstrate showcases of ceramics and composite materials, where microstructural parameters could be achieved in a way unrivalled even by high-resolution techniques such as electron microscopy or computed tomography. We present in situ analysis of the damage evolution in an Al/Al2O3 metal matrix composite during tensile load and the identification of void formation (different kinds of defects, particularly unsintered powder hidden in pores, and small inhomogeneity’s like cracks) in Ti64 parts produced by selective laser melting using synchrotron X-ray refraction radiography and tomography.
Low back pain (LBP) is a leading cause of activity limitation. Objective assessment of the spinal motion plays a key role in diagnosis and treatment of LBP. We propose a method that facilitates clinical assessment of lower back motions by means of a wireless inertial sensor network. The sensor units are attached to the right and left side of the lumbar region, the pelvis and the thighs, respectively. Since magnetometers are known to be unreliable in indoor environments, we use only 3D accelerometer and 3D gyroscope readings. Compensation of integration drift in the horizontal plane is achieved by estimating the gyroscope biases from automatically detected initial rest phases. For the estimation of sensor orientations, both a smoothing algorithm and a filtering algorithm are presented. From these orientations, we determine three-dimensional joint angles between the thighs and the pelvis and between the pelvis and the lumbar region. We compare the orientations and joint angles to measurements of an optical motion tracking system that tracks each skin-mounted sensor by means of reflective markers. Eight subjects perform a neutral initial pose, then flexion/extension, lateral flexion, and rotation of the trunk. The root mean square deviation between inertial and optical angles is about one degree for angles in the frontal and sagittal plane and about two degrees for angles in the transverse plane (both values averaged over all trials). We choose five features that characterize the initial pose and the three motions. Interindividual differences of all features are found to be clearly larger than the observed measurement deviations. These results indicate that the proposed inertial sensor-based method is a promising tool for lower back motion assessment.
High storage density magnetic devices rely on the precise, reliable and ultrafast switching times of the magnetic states. Optical control of magnetization using femtosecond laser without applying any external magnetic field offers the advantage of switching magnetic states at ultrashort time scales, which has attracted a significant attention. Recently, it has been reported and demonstrated the,so-called, all-optical helicity-dependent switching (AO-HDS) in which a circularly polarized femtosecond laser pulse switches the magnetization of a ferromagnetic thin film as function of laser helicity [1]. Afterward, in more recent studies, it has been reported that AO-HDS is a general phenomenon existing in magnetic materials ranging from rare earth - transition metals ferrimagnetic (e.g. alloys, multilayers and hetero-structures system) to even ferromagnetic thin films. Among numerous studies in the literature which are discussing the microscopic origin of AO-HDS in ferromagnets or ferrimagnetic alloys, the most renowned concepts are momentum transfer via Inverse Faraday Effect (IFE) [1-3]and the concept of preferential thermal demagnetization for one magnetization direction by heating close to Tc (Curie temperature) in the presence of magnetic circular dichroism (MCD) [4-6]. In this study, we investigate all-optical magnetic switching using a stationary femtosecond laser spot (3-5 μm) in TbFe alloys via photoemission electron microscopy (PEEM) and x-ray magnetic circular dichroism (XMCD) with a spatial resolution of approximately 30 nm. We spatially characterize the effect of laser heating and local temperature profile created across the laser spot on AO-HDS in TbFe thin films. We find that AO-HDS occurs only in a `ring' shaped region surrounding the thermally demagnetized region formed by the laser spot and the formation of switched domains relies further on thermally induced domain wall motion. Our temperature dependent measurements highlight the importance of attainin...
Beyond Surveys
(2018)
Scrum2kanban
(2018)
Using university capstone courses to teach agile software development methodologies has become commonplace, as agile methods have gained support in professional software development. This usually means students are introduced to and work with the currently most popular agile methodology: Scrum. However, as the agile methods employed in the industry change and are adapted to different contexts, university courses must follow suit. A prime example of this is the Kanban method, which has recently gathered attention in the industry. In this paper, we describe a capstone course design, which adds the hands-on learning of the lean principles advocated by Kanban into a capstone project run with Scrum. This both ensures that students are aware of recent process frameworks and ideas as well as gain a more thorough overview of how agile methods can be employed in practice. We describe the details of the course and analyze the participating students' perceptions as well as our observations. We analyze the development artifacts, created by students during the course in respect to the two different development methodologies. We further present a summary of the lessons learned as well as recommendations for future similar courses. The survey conducted at the end of the course revealed an overwhelmingly positive attitude of students towards the integration of Kanban into the course.
Scenograph
(2018)
When developing a real-walking virtual reality experience, designers generally create virtual locations to fit a specific tracking volume. Unfortunately, this prevents the resulting experience from running on a smaller or differently shaped tracking volume. To address this, we present a software system called Scenograph. The core of Scenograph is a tracking volume-independent representation of real-walking experiences. Scenograph instantiates the experience to a tracking volume of given size and shape by splitting the locations into smaller ones while maintaining narrative structure. In our user study, participants' ratings of realism decreased significantly when existing techniques were used to map a 25m2 experience to 9m2 and an L-shaped 8m2 tracking volume. In contrast, ratings did not differ when Scenograph was used to instantiate the experience.
Embedded smart home — remote lab MOOC with optional real hardware experience for over 4000 students
(2018)
MOOCs (Massive Open Online Courses) become more and more popular for learners of all ages to study further or to learn new subjects of interest. The purpose of this paper is to introduce a different MOOC course style. Typically, video content is shown teaching the student new information. After watching a video, self-test questions can be answered. Finally, the student answers weekly exams and final exams like the self test questions. Out of the points that have been scored for weekly and final exams a certificate can be issued. Our approach extends the possibility to receive points for the final score with practical programming exercises on real hardware. It allows the student to do embedded programming by communicating over GPIO pins to control LEDs and measure sensor values. Additionally, they can visualize values on an embedded display using web technologies, which are an essential part of embedded and smart home devices to communicate with common APIs. Students have the opportunity to solve all tasks within the online remote lab and at home on the same kind of hardware. The evaluation of this MOOCs indicates the interesting design for students to learn an engineering technique with new technology approaches in an appropriate, modern, supporting and motivating way of teaching.
When students watch learning videos online, they usually need to watch several hours of video content. In the end, not every minute of a video is relevant for the exam. Additionally, students need to add notes to clarify issues of a lecture. There are several possibilities to enhance the metadata of a video, e.g. a typical way to add user-specific information to an online video is a comment functionality, which allows users to share their thoughts and questions with the public. In contrast to common video material which can be found online, lecture videos are used for exam preparation. Due to this difference, the idea comes up to annotate lecture videos with markers and personal notes for a better understanding of the taught content. Especially, students learning for an exam use their notes to refresh their memories. To ease this learning method with lecture videos, we introduce the annotation feature in our video lecture archive. This functionality supports the students with keeping track of their thoughts by providing an intuitive interface to easily add, modify or remove their ideas. This annotation function is integrated in the video player. Hence, scrolling to a separate annotation area on the website is not necessary. Furthermore, the annotated notes can be exported together with the slide content to a PDF file, which can then be printed easily. Lecture video annotations support and motivate students to learn and watch videos from an E-Learning video archive.
Grußwort
(2018)
This paper presents the concept of a community-accessible stratospheric balloon-based observatory that is currently under preparation by a consortium of European research institutes and industry. We present the technical motivation, science case, instrumentation, and a two-stage image stabilization approach of the 0.5-m UV/visible platform. In addition, we briefly describe the novel mid-sized stabilized balloon gondola under design to carry telescopes in the 0.5 to 0.6 m range as well as the currently considered flight option for this platform. Secondly, we outline the scientific and technical motivation for a large balloon-based FIR telescope and the ESBO DS approach towards such an infrastructure.
This book aims at understanding the diversity of planetary and lunar magnetic fields and their interaction with the solar wind. A synergistic interdisciplinary approach combines newly developed tools for data acquisition and analysis, computer simulations of planetary interiors and dynamos, models of solar wind interaction, measurement of terrestrial rocks and meteorites, and laboratory investigations. The following chapters represent a selection of some of the scientific findings derived by the 22 projects within the DFG Priority Program Planetary Magnetism" (PlanetMag). This introductory chapter gives an overview of the individual following chapters, highlighting their role in the overall goals of the PlanetMag framework. The diversity of the different contributions reflects the wide range of magnetic phenomena in our solar system. From the program we have excluded magnetism of the sun, which is an independent broad research discipline, but include the interaction of the solar wind with planets and moons. Within the subsequent 13 chapters of this book, the authors review the field centered on their research topic within PlanetMag. Here we shortly introduce the content of all the subsequent chapters and outline the context in which they should be seen.
Preface
(2018)
Foreword
(2018)
CurEx
(2018)
The integration of diverse structured and unstructured information sources into a unified, domain-specific knowledge base is an important task in many areas. A well-maintained knowledge base enables data analysis in complex scenarios, such as risk analysis in the financial sector or investigating large data leaks, such as the Paradise or Panama papers. Both the creation of such knowledge bases, as well as their continuous maintenance and curation involves many complex tasks and considerable manual effort. With CurEx, we present a modular system that allows structured and unstructured data sources to be integrated into a domain-specific knowledge base. In particular, we (i) enable the incremental improvement of each individual integration component; (ii) enable the selective generation of multiple knowledge graphs from the information contained in the knowledge base; and (iii) provide two distinct user interfaces tailored to the needs of data engineers and end-users respectively. The former has curation capabilities and controls the integration process, whereas the latter focuses on the exploration of the generated knowledge graph.
OpenLL
(2018)
Today's rendering APIs lack robust functionality and capabilities for dynamic, real-time text rendering and labeling, which represent key requirements for 3D application design in many fields. As a consequence, most rendering systems are barely or not at all equipped with respective capabilities. This paper drafts the unified text rendering and labeling API OpenLL intended to complement common rendering APIs, frameworks, and transmission formats. For it, various uses of static and dynamic placement of labels are showcased and a text interaction technique is presented. Furthermore, API design constraints with respect to state-of-the-art text rendering techniques are discussed. This contribution is intended to initiate a community-driven specification of a free and open label library.
Organic or inorganic (A) metal (M) halide (X) perovskites (AMX(3)) are semiconductor materials setting the basis for the development of highly efficient, low-cost and multijunction solar energy conversion devices. The best efficiencies nowadays are obtained with mixed compositions containing methylammonium, formamidinium, Cs and Rb as well as iodine, bromine and chlorine as anions. The understanding of fundamental properties such as crystal structure and its effect on the band gap, as well as their phase stability is essential. In this systematic study X-ray diffraction and photoluminescense spectroscopy were applied to evaluate structural and optoelectronic properties of hybrid perovskites with mixed compositions.
For theoretical analyses there are two specifics distinguishing GP from many other areas of evolutionary computation. First, the variable size representations, in particular yielding a possible bloat (i.e. the growth of individuals with redundant parts). Second, the role and realization of crossover, which is particularly central in GP due to the tree-based representation. Whereas some theoretical work on GP has studied the effects of bloat, crossover had a surprisingly little share in this work. We analyze a simple crossover operator in combination with local search, where a preference for small solutions minimizes bloat (lexicographic parsimony pressure); the resulting algorithm is denoted Concatenation Crossover GP. For this purpose three variants of the wellstudied Majority test function with large plateaus are considered. We show that the Concatenation Crossover GP can efficiently optimize these test functions, while local search cannot be efficient for all three variants independent of employing bloat control.
For the last ten years, almost every theoretical result concerning the expected run time of a randomized search heuristic used drift theory, making it the arguably most important tool in this domain. Its success is due to its ease of use and its powerful result: drift theory allows the user to derive bounds on the expected first-hitting time of a random process by bounding expected local changes of the process - the drift. This is usually far easier than bounding the expected first-hitting time directly. Due to the widespread use of drift theory, it is of utmost importance to have the best drift theorems possible. We improve the fundamental additive, multiplicative, and variable drift theorems by stating them in a form as general as possible and providing examples of why the restrictions we keep are still necessary. Our additive drift theorem for upper bounds only requires the process to be nonnegative, that is, we remove unnecessary restrictions like a finite, discrete, or bounded search space. As corollaries, the same is true for our upper bounds in the case of variable and multiplicative drift.
One of the most important aspects of a randomized algorithm is bounding its expected run time on various problems. Formally speaking, this means bounding the expected first-hitting time of a random process. The two arguably most popular tools to do so are the fitness level method and drift theory. The fitness level method considers arbitrary transition probabilities but only allows the process to move toward the goal. On the other hand, drift theory allows the process to move into any direction as long as it move closer to the goal in expectation; however, this tendency has to be monotone and, thus, the transition probabilities cannot be arbitrary. We provide a result that combines the benefit of these two approaches: our result gives a lower and an upper bound for the expected first-hitting time of a random process over {0,..., n} that is allowed to move forward and backward by 1 and can use arbitrary transition probabilities. In case that the transition probabilities are known, our bounds coincide and yield the exact value of the expected first-hitting time. Further, we also state the stationary distribution as well as the mixing time of a special case of our scenario.
This paper proposes an education approach for master and bachelor students to enhance their skills in the area of reliability, safety and security of the electronic components in automated driving. The approach is based on the active synergetic work of research institutes, academia and industry in the frame of joint lab. As an example, the jointly organized summer school with the respective focus is organized and elaborated.
802.15.4 security protects against the replay, injection, and eavesdropping of 802.15.4 frames. A core concept of 802.15.4 security is the use of frame counters for both nonce generation and anti-replay protection. While being functional, frame counters (i) cause an increased energy consumption as they incur a per-frame overhead of 4 bytes and (ii) only provide sequential freshness. The Last Bits (LB) optimization does reduce the per-frame overhead of frame counters, yet at the cost of an increased RAM consumption and occasional energy-and time-consuming resynchronization actions. Alternatively, the timeslotted channel hopping (TSCH) media access control (MAC) protocol of 802.15.4 avoids the drawbacks of frame counters by replacing them with timeslot indices, but findings of Yang et al. question the security of TSCH in general. In this paper, we assume the use of ContikiMAC, which is a popular asynchronous MAC protocol for 802.15.4 networks. Under this assumption, we propose an Intra-Layer Optimization for 802.15.4 Security (ILOS), which intertwines 802.15.4 security and ContikiMAC. In effect, ILOS reduces the security-related per-frame overhead even more than the LB optimization, as well as achieves strong freshness. Furthermore, unlike the LB optimization, ILOS neither incurs an increased RAM consumption nor requires resynchronization actions. Beyond that, ILOS integrates with and advances other security supplements to ContikiMAC. We implemented ILOS using OpenMotes and the Contiki operating system.
TrussFormer
(2018)
We present TrussFormer, an integrated end-to-end system that allows users to 3D print large-scale kinetic structures, i.e., structures that involve motion and deal with dynamic forces. TrussFormer builds on TrussFab, from which it inherits the ability to create static large-scale truss structures from 3D printed connectors and PET bottles. TrussFormer adds movement to these structures by placing linear actuators into them: either manually, wrapped in reusable components called assets, or by demonstrating the intended movement. TrussFormer verifies that the resulting structure is mechanically sound and will withstand the dynamic forces resulting from the motion. To fabricate the design, TrussFormer generates the underlying hinge system that can be printed on standard desktop 3D printers. We demonstrate TrussFormer with several example objects, including a 6-legged walking robot and a 4m-tall animatronics dinosaur with 5 degrees of freedom.
Beware of SMOMBIES
(2018)
Several research evaluated the user's style of walking for the verification of a claimed identity and showed high authentication accuracies in many settings. In this paper we present a system that successfully verifies a user's identity based on many real world smartphone placements and yet not regarded interactions while walking. Our contribution is the distinction of all considered activities into three distinct subsets and a specific one-class Support Vector Machine per subset. Using sensor data of 30 participants collected in a semi-supervised study approach, we prove that unsupervised verification is possible with very low false-acceptance and false-rejection rates. We furthermore show that these subsets can be distinguished with a high accuracy and demonstrate that this system can be deployed on off-the-shelf smartphones.