Computer Aided Systems Theory - EUROCAST 2013

This paper proposes a proper combination of on the one hand a local time-optimal path planner fulfilling the basic kinematic and dynamic constraints of wheeled vehicles, and on the other hand, a continuous and bounded curvature derivative Bézier closed-form metrics. As a result of this, a nearly time-optimal path with continuous and bounded curvature profile will be generated, if possible, to connect two configurations while avoiding obstacles.

This work introduces the notion of

Wifigrams

, i.e., visual Wi-Fi maps which comprise hundreds of topological positions (nodes) linked in accordance with their co-visibility degree of Wi-Fi Access Points (APs). Both design and analysis of

Wifigrams

are guided by the most popular Social Network Analysis (SNA) techniques. Thus, the structure of a hierarchical topology-based Wi-Fi indoor localization system emerges naturally when looking carefully to the related

Wifigram

. It shows graphically the closeness among topological positions in terms of their pattern of AP co-visiblity, yielding several zones of interest which are automatically discovered through community mining techniques. This novel proposal has been successfully tested in a large real-world environment, namely the first floor of the west wing in the Polytechnic School at the University of Alcalá (UAH), yielding encouraging results.

In this paper, different representations of WiFi access point signal information are tested on a hierarchical indoors localization system to identify the one that yields the least amount of localization error. Four representations were considered: Received Signal Strength (RSS) in dBm, RSS in

mW

, Visibility and both RSS in dBm and Visibility. The localization system was tested in two different real world environments and encouraging results were obtained for the combination of RSS in dBm and Visibility. The results point to increased accuracy in localization, especially in environments where signal is greatly distorted by the multipath effect.

Dealing with the control of autonomous vehicles on urban environments is a highly complex task due to the number of possible scenarios to consider. On this work, we present a virtual vehicle approach for the management of several urban manoeuvres by considering them as an Adaptive Cruise Control (ACC) problem, from the longitudinal point of view. This solution is based on a centralised communication system which manages and analyses all the information incoming from the vehicles and the infrastructure on a limited area. In order to validate the performance of the proposal, an experiment has been carried out at the test track of the AUTOPIA program. On the experiment, several vehicles over an intersection were controlled by the central system.

This paper shows the current status of an implementation with a composed device of depth and color camera. From the color image, a set of points associated with the face is obtained; later the main features of a human face are identified. The 3D model is constructed based on a previous 2D analysis using the haar-like features for detecting the human face. This application will be a part of a more complex system designed to assist the driver by monitoring both inside and outside the vehicle, i.e. intelligent systems of transportation.

There are several algorithms to avoid local obstacles for mobile robots. Usually, these algorithms use only the information provided by range sensors. The goal of this paper is to compare some of these algorithms, from classic to modern ones, in order to evaluate the strengths and weakness of each one.

Platoon vehicles coordination is an important topic at Intelligent Transportation Systems these days. For coordinating two or more vehicles, it is needed both a communication method between them, and an environment sensing strategy enabling the triangulation and correction, when needed, of each vehicle relative position within the desired platoon.

In this research we present a new strategy to keep a group of vehicles in a fixed platoon, that may complement classic approaches. Usually, in a platoon, every follower vehicle try to keep a distance to the vehicle right ahead. That lateral and longitudinal control is kept considering the sensed distances by using laser, radar or vision.

In the present paper we want to propose a new concept that consists on sharing the leader’s acceleration signal all across the whole vehicle platoon. In a few words, all the followers try to implement the leader’s sensed and transmitted acceleration. Theoretically, two solids experiencing the same accelerations will reproduce identical trajectories while keeping the initial relative distances, if they start from the same initial non-zero constant speed.

In this paper we present this new concept, we list what are some of the technological challenges to be addressed before its implementation, and we finally share some initial simulation results.

Using existing technology, nowadays it is possible to solve, or at least to reduce, most of the possible negative effects caused by the mismanagement of the supply chain process. In such industry, automation in product monitoring and control, inventory, customer relationship management, fleet tracking, etc., is a typical issue dealt by the companies who offer solutions for the individual problems. Transportation and logistics involves the delivery, movement and collection of goods through roads, and in the international case also through ports and airports. Consequently, it usually includes many actors, what complicates their management, efficiency and effectiveness. Therefore, time, boundaries, and interdependencies are the main difficulties in a chain supply. Besides, it raises several security challenges due to unintentional errors or intentional attacks. This paper presents a secure system to control the goods from their manufacture until their delivery to the end customer, which makes the work easier for custom authorities and all people responsible for goods in transit. In particular, we describe an innovative solution for the management of the complete supply chain process, which makes use of many different current IoT technologies such as RFID, EPC, Wi-Fi, GPS, QR codes, etc. in a safe and efficient way.

The methodology proposed in this paper considers the uncertainty present in modeling the probability of collision between ships on a route. The proposal allows representing and quantifying uncertainty, and ensures rigorous propagation of this uncertainty from the input variables to the output variable.

This proposal complements the analysis of risk and helps the decision maker to know the degree of confidence associated with the results of the analysis.

Pedersen’s model has been selected to estimate the probability of collision, using the information provided by the AIS, and Dempster-Shafer Theory has been selected for the treatment of uncertainty.

This methodology has been applied to maritime traffic in the Canary Islands and has been validated using the Kullback-Leibler divergence. The results are consistent with those obtained with the software IWRAP recommended by IALA.

This paper describes an automatic system that detects thermal insulation properties of the different components of buildings envelope by combining laser data with thermal images. Sensor data is obtained from a moving vehicle equipped with a GPS sensor. Range data is integrated to obtain the 3D structure of the building facade, and combined with thermal images to separate components such as walls, windows frames and glasses. Thermal leakage is detected by detecting irregularities in the thermal measurements of each building component separately (window glasses, window frames and walls).

Surface quality inspection is applied in the process of manufacturing products where the appearance is crucial for the product quality and customer acceptance, like for woven fabrics. The predominating approaches to detect defects are feature-based. Recently we investigated an alternative approach utilizing template matching in the context of regular or near-regular textured surface inspection. This paper reveals that the template matching approach belongs to the class of approximate nearest neighbour field (ANNF) algorithms which are common in a different field of image processing, namely structural image editing. By modifying a state-of-the-art ANNF algorithm the advantage of template matching algorithms for defect detection can be shown. Furthermore the importance of the chosen distance function is demonstrated in an explorative study and a concept to determine if the template matching approach is suitable for a given texture and defect type is demonstrated on a set of defect classes and texture types.

In order to play georeferenced videos, The Oceanic Platform of the Canary Islands (PLOCAN) is currently using a desktop-based software. In this paper, a port to a web-based video player is reviewed. In addition to its main advantages, new features are also discussed, such as the download of super-resolved frames.

Traffic light recognition in night conditions is explored throughout this paper. A system detecting suspended traffic lights in urban streets is proposed. Images are acquired by a color camera installed on the roof of a car. Fuzzy logic-based clustering provides robust color detection. Additionally, other techniques end up recognizing the traffic light state. The detection rate is quite high and the false positive proportion is really low.

The necessity to improve image resolution is of great concern in multiple diverse fields such as: medicine, communications, or satellite and underwater applications. A high variety of techniques for image enhancement has been proposed in the literature, being a trade-off the relation between the computation time and the quality of the obtained results. This work is focused on a test environment that permits to objectively compare the quality enhancement of images processed by two different improvement methods: bilinear interpolation and Super-Resolution (SR), presenting how these results relate to the computation time. The objective comparison is based on the PSNR (Peak Signal-to-Noise Ratio) and the SSIM (Structural SIMilarity).

Processing of aerial imagery is a broadly topic discussed nowadays. An Unmanned Aerial Vehicles (UAV) developed in our laboratory was used as experimental platform for the present research. An analysis of the possible application of SURF feature-based algorithm to match outdoor images is introduced. Experimental data comprise selected images taken from different heights (100 and 150 m), different lighting conditions, different pitch, roll and yaw angles, among others effects. The obtained results are validated by using low cost equipment and a low quality video sequence.

The aim of this paper is to analyze the discontinuity preserving behavior of two methods in optical flow. With this objetive, we have implemented a well-known optical flow method that uses isotropic TV-

L

1

regularization. For the second approach, we have modified this method, by adding a decreasing function in the regularization term, to avoid smoothing at flow discontinuities. As a consequence, we see a high improvement and a very accurate discontinuities detection in some sequences but not good enough in others. Adapting the weight of the decreasing function allows us to better define the flow discontinuities. Nevertheless, the experimental results show that the parameters that yield a good segmentation of the motion field, may also introduce important unstabilities. In this sense, the results seem promising, but it is very difficult to set a unified parameter configuration that works fine for all the sequences. We evaluate the performance of these approaches with some standard test sequences, such as the Middlebury benchmark database or the Yosemite sequence. Looking for the best parameters configuration, which provides the best contour definition, does not typically mean a solution which is closer to the ground truth.

This paper is based on a methodology for segmentation of the main retinal layers in Optical Coherence Tomography (OCT) images. The input image is transformed into a geometric graph and the layers to be detected will be given by its minimum-cost closed set. The main problem in this method is the selection of the appropriate cost functions associated to the graph, because of the variety of anomalies that images from patients might have.

Patients with severe cognitive impairment are not capable of interacting with the audiologist during an audiology test. However, these patients often show gestural reaction to the auditory stimuli that can be interpreted by audiologists with comprehensive experience in this type of case. In this study, we analyze the area around the eyes and the movements that occur within it, since is in this area where most of gestural reactions take place for these patients.

Dry eye is a symptomatic disease which can be diagnosed by several clinical tests. One of them is the evaluation of the interference lipid pattern and its classification into one of the Guillon categories. Previous researches have automatised this manual test, saving time for experts and providing unbiased results. However, the heterogeneity of the tear film lipid layer makes its classification into a single category per eye impossible. For this reason, this paper presents a first approximation to segment tear film images into the Guillon categories, in order to detect several categories in each patient. The adequacy of the methodology was demonstrated since it achieves reliable results in comparison with the annotations done by optometrists.

How is it possible that when talking about technological developments in surgery and specifically in endovascular surgery no one thinks that without the other sciences: engineers, physicists, ITs etc, we wouldnt have the evolution we have now?

Why is medicine separated from the rest of the campus and the society, when its the only business that affects 100% of the people on this planet? And in addition considering that the economical aspect has more than ever a starring role?

Remember: we are more than twice the population we were 50 years ago on the planet; therefore no one can be invisible in health.

Cloud computing is a Web-based processing, that allow to share resources, software, and information over the Internet. Cloud computing helps enterprises and other institutions like schools, universities, etc. transform business and technology. Most cloud computing infrastructures consist of services delivered through common centers and built on servers.

The vendor specific interfaces and heterogeneous hardware of VR-devices is a major drawback for planning and realizing a VR-environment, necessitating an intermediate layer between the hardware and software interfaces, the hardware abstraction layer (

HAL

). In this work we present the implementation of a device server for generic and simple integration of devices like tracking tools, force sensors, micro controllers or 3D interaction devices. Utilizing this device server, harmonization of the message formats, data representations and transmission protocols is achieved. Furthermore, device-specific communication threads allow for precise timing capitalizing multi-core architecture of the host server. For application development, device-specific API code is automatically generated as a specific network proxy, thus allowing independence from programming language and platform. The presented device server is currently used for modern teaching aspects in the academic domain, as well in a research project developing a surgical training environment for kyphoplasty and vertebroplasty in the medical domain.

This paper describes novel approaches for assessing the quality of mote partitioning in Wireless Sensor and Actuators Networks (WSANs) that allows optimization of the topology of WSANs. The proposed solution aims to supports node placement and activation strategies both at the time of sensor deployment and during the network normal operation. A blend of statistical and unsupervised learning techniques is proposed to test the quality of the WSAN organisation. A formal review and interpretation of various metrics is provided. These metrics can be used to improve management of resources in WSAN infrastructures.

Laparoscopic surgical training systems limit the users’ depth perception and hand-eye coordination due to the use of a 2D camera image. In this paper, we present an approach to enhance visualization using augmented reality which aids in hand-eye coordination and depth perception in the operating environment. An optimal path is calculated in a 3D space and projected onto a 2D camera image. The mapping from the 3D to 2D coordinate system is calculated using least squares camera calibration method. Instrument tip location in space is calculated using feedback from encoders attached to them. We combine the information about the instrument tip and optimal path to achieve robust visualization.

Modern myoeletric prostheses necessitate more powerful control algorithms to derive hand movement information from sensor data. Common approaches utilize classifiers for recognizing motion or grip patterns from input data like myoeletric signals (MES). The selection of features for the classification process and the classifiers themselves impact the detection accuracy of the control schemes. In this contribution, we present a MATLAB

TM

movement classification toolbox for sensor data recorded during hand movements. By covering different feature calculation- and classification-algorithms, the toolbox supports the modeling of select prostheses control schemes. In addition to MES, novel near-infrared (NIR) sensor input is equally supported by the toolbox. A modular development approach allows the integration of new features, classifiers as well as the extension to other types of sensor data.

The main goal of Motion Capture based modeling is to understand the essence of human gait phenomenon. Actually the following methods can propose to recognize gaits: The Dynamic Time Warping. method is based on dynamic programming and is widely used for different time-series comparison applications (like voice recognition. Spectrum analysis of the motion signal leads to interesting results concerning person identification The proposed method for gait recognition that uses various techniques of comparing the surface areas under the motion curves offers very accurate results. One of the most challenging problems in markerless motion capture, but offering a widespread application potential is that of estimation of body pose from single video sequence.

Computer-based technology has been sufficiently developed in medical training and education. However, as well as in other areas (flight pilots, nuclear energy operators, drivers, etc.) this technology has been included in other educational plans, in medicine it is a pending task yet. We present our work on the introduction of computer-based technology, mainly virtual simulation, into the university teaching plans at University of Las Palmas Medical School, the medicine residency programme and the update of physicians at the four Teaching Hospitals in Canary Islands. Through the realization of virtual simulation courses we have managed to introduce the technology into the health environment as an educational tool. Using commercial haptics devices and customizing and adapting its software, we have developed custom curricula for several medicine specialities.

In order to measure the impact of the use of virtual simulation technology at the different levels of the medical environment, we have been using an evaluation survey in our training workshops, that aims to show an impression on the use of this technology. The survey focuses on general perception of the technology and how it may affect to their own professional career and work environment. As a consequence of the madurity of the educational program we have been working, with local and national institutions, on the accreditation of these courses to provide a certification of competencies obtained through the realization of virtual simulation courses.

Simultaneously, we have improved our software framework intended for the development of surgical simulation applications [1].

The main goal of this paper is to demonstrate our experience itself and disseminate the results in order to be helpful to other similar groups. Also to share our open platform for development that could make scalable and sustainable this teaching model based on technology.

This paper presents a fast algorithm for discretization of decision tables. An important novelty of the proposed solution is the application of the original algorithm of Boolean function complementation, which is a basic procedure of the field of logic synthesis, in the process of discretizing the data. This procedure has already been used by the author to calculate reducts of decision tables, where the time of calculation has been significantly reduced. It yields the idea of using the algorithm of complementation in the process of discretization. The algorithm has been generalized for the discretization of inconsistent decision tables and is used in the processing of numerical data from various fields of technology, especially for multimedia data.

In a chemotherapy scheduling process a chemotherapy is a treatment of cancer using a set of toxic drugs. In the paper we propose a Decision Support System for the anti-cancer medical treatment to improve physicians’ decisions about drugs doses selection and scheduling. A hybrid meta-heuristic algorithm has been applied to the problem of bi-criteria optimization allowing to find effective chemotherapy drugs dose scheduling as the minimization of a tumor size at a fixed period of time and maximization of Patient Survival Time. The numerical tests of proposed algorithm gives the possibility of producing a set of alternative treatment scenarios according to the final decision.

The calculation of an exact minimal cover of a Boolean function [2] is an

NP

-complete problem, which has an important application in circuit design. The required time for the calculation could be reduced by a factor of more than 3.5 ∗ 10

7

in [8] and even 8 ∗ 10

8

in [7].

In this paper we give a introduction into the definition of this problem and its basic solution. The main contribution of this paper are algorithms which enlarge the improvement factor mentioned above on this very high level for 32 variables

p

i

and 1024 clauses furthermore to 1.8 ∗ 10

10

using a single CPU-core and finally 1.2 ∗ 10

11

using a GPU.

This paper proposes to implement an automatic detection system for the heart diseases over a Field Programmable Gate Array (FPGA). The system is able to process, analyze and classify the cardiac pathologies in real time from electrocardiogram (ECG). Firstly, the pulses of the ECG signals have been extracted from electrocardiographic registers. After that, digital signal processing, normalization and heart pulse features extraction algorithms have been used. These algorithms principally are based on Digital Wavelet Transform (DWT) techniques, and Principal Component Analysis (PCA). Finally, cardiac pulse detection and classification algorithms have been implemented in an Artificial Neural Network (ANN). In this way, the subjectivity problem in the heart disease diagnosis is solved, and the task of heart specialist is facilitated.

Hyper-bent functions constitute a subset of bent functions and are harder to approximate than bent functions, making them particularly attractive for cryptographic applications. In the multiple-valued world, up to now, characterization and generation of hyper-bent functions represent an interesting challenging mathematical problem. We show that multiple-valued hyper-bent functions constitute a reduced subset of the multiple-valued bent functions and give a simple characterization lemma. Finally we introduce a new concept, that of strict hyper-bent functions, and study some of the properties of these functions. The only mathematical requirements of the paper are college algebra and a basic knowledge of Galois fields.

Beads are a particular class of binary sequences with interesting properties due to which they can be related to Binary decision diagrams. Recently, the concept of beads was extended to integer sequences and sequences over finite fields and used in the classification of logic functions in terms of decision diagrams. In this paper, sets of beads and integer beads are used to estimate the equality of structure of digital systems implementing logic functions.

Two automatic statistical methods for the classification of the obstructive sleep apnoea syndrome based on the cepstrum coefficients of the RR series obtained from the Electrocardiogram (ECG) are presented. We study the effect of working with Linear Discriminant Analysis (LDA) and compare its performance with a reference detector based on Support Vector Machines (SVM). These classifications methods require two previous stages: preprocessing and feature extraction. Firstly, R instants are detected previous to the feature extraction phase thanks to a preprocessing over the ECG. Secondly, Cepstrum Coefficients over the RR signal is applied to extract the relevant characteristics specially those related to the system modelled by the filter-type elements concentrated in the low time lag region.

This contribution deals with the optimization of a tractor’s cab’s vertical acceleration. The mathematical model of the simplified system is derived. The acceleration of the chassis is considered as the actuating variable. In the optimization the acceleration of the tractor’s cab is minimized under the constraint of a maximum displacement between the cab and the chassis. The optimization result is used to get a smallest limit for the maximum of acceleration in case of active damping and acausal damping control. So the optimization result is a lower bound.

This contribution deals with the modelling and control of an injection moulding process. In injection moulding especially the appearance of a work piece depends much on the exact compliance with certain trajectories of temperature or pressure in the mould. First a mathematical is presented, which turns out to be input to state linearisable resp. differentially flat. So trajectory planning is easily feasible and a flatness based controller is presented.

Since the parameters of the process depend on the actual form of the work piece and the several pieces which are manufactured on one machine differ from each other an automatic identification of the interesting parameters is desirable.

This paper treats the nonlinear control of a laboratory model of a gantry crane, where a trolley can be moved on a rail and the load is fixed at the end of a rope of variable length. The system is differentially flat, and the coordinates of the load, which also are the variables to be controlled, are a flat output. This fact allows us to determine a feedforward control law in a straightforward manner. Because of friction, the results achievable by a pure feedforward law are, as expected, not satisfying. This does not apply to the “pendulum subsystem”, with the position of the trolley and the length of the rope as input, since it is almost free of friction. Therefore, a feedforward control for the “pendulum subsystem” is designed such that it shows an excellent tracking behavior. Finally, cascaded control is used for the guidance of the overall system.

Many applications in the field of robotics require a high positioning accuracy of the robot end-effector. This accuracy strongly depends on the resolution of the position sensors and on manufacturing tolerances of the machine like length errors or misalignment of axes (geometric error parameters). With a static calibration process, these error parameters can be obtained by least squares error minimization. The least squares solution depends on the choice of the robots poses that are chosen for the calibration process. These poses are optimized with a special selection algorithm. The calibration, including the calculation of the optimal poses is discussed for a seven-axes redundant robot. Special emphasis is laid on the dependency of the geometric parameters on temperature changes and on absolute position errors due to temperature changes.

This contribution introduces three sensorless vibration suppression methods for flexible, fast moving linear robots. After some investigations concerning the required mathematical models of the flexible linear robot, several vibration suppression techniques are derived in detail. The main idea of all concepts is the specific modification of an arbitrary trajectory in real time. Therefore, all conventional control concepts of the robot may remain unchanged. The application of each technique leads nearly to a complete annihilation of the TCP vibrations immediately after the end of the trajectory. For this reason, the implementation of these methods allows much higher velocities and therefore lower cycle times in nearly every manipulation process. Over and above, these vibration suppression methods enable light-weight construction and therefore lower energy consumption and represent an important step to increase velocity and energy efficiency in automation processes.

The AVORA team went for the first time to the SAUC-E competition. The AUV was built from scratch with low-cost components. We made watertight cases, as for the servos of a pan-tilt camera aligned with a laser pointer, used for active vision and depth estimation. The navigation and localization use robust algorithms for noisy low-cost sensors. On top of it, the competition tasks are solved with visual and acoustic techniques. A great part of the software was developed and several field test performed at the arena, winning one prize.

In the present work we propose a method for generating ocean glider trajectories that optimize the sampling of mesoscale eddy structures based on a given objective function and the predictions available from ROMS maps. The eddy structure is modeled as a 3D volume discretized into sectors rotating around its center at different velocities. The objective functions can then be expressed in terms of those temporal evolving sectors. A set of simulation experiments have been carried out in order to validate the proposal.

Development of a robotic tourist assistant that allows tourist getting information about relevant places inside a hotel, a museum, a theme park, a zoo or wherever they be, using their voice and cards to interact.

In this paper we describe our proposal for humanoid robotic system to develop a football team that compete in the Robocup, describing hardware components used and software components developed.

New monitoring technologies are key components of ocean observatories, also called marine research infrastructures being implemented in the worlds oceans. As a result, new capabilities to characterise, in quasi-real time, the ocean state and its variability at small scales exist today. The challenge is the integration of theses multiplatform observing and forecasting systems to (a) monitor the variability at small scales (e.g. mesoscale/weeks) in order to (b) resolve the sub-basin/seasonal and inter-annual variability and by this (c) establish the decadal variability, understand the associated biases and correct them. The challenge is also to change focus and now monitor from small to large scales. SOCIB is leading this new small to large-scale multi-platform approach in ocean observation. Some examples are presented and discussed together with initial ideas on the optimal design of an observational network in the world oceans, responding to science priorities, technology development and response to strategic society needs.

This paper introduces a method for the navigation of autonomous underwater vehicles (AUVs) and tracking of submersible targets that relies on analytic inversion of magnetic field anomalies. The magnetic sensor arrangement proposed configures a gradiometer array whose nodes may correspond to a set of collaborative AUVs deployed in a formation of adaptable geometry. The solution presented envisions applications to scientific, industrial, and military activities.

Research related to diver safety, navigation and monitoring has been identified as crucial for advancing diving activities. These issues are usually dealt with by pairing up divers and adopting well defined rules for diving operations to reduce the chance of accidents. However, during more challenging dives (such as technical dives) these procedures may not be sufficient to ensure almost accident-free operations, for the divers must manoeuvre in complex 3D environments, carry cumbersome equipment, and focus attention on operational details. In this work it is stated that research and technological development in the area of cognitive robotics can significantly contribute to the effectiveness and safety of diving operations. The current research performed in LABUST is based on an autonomous surface platform for following divers and transmitting GPS signal to the underwater. Future envisioned applications include the development of a cognitive autonomous diving buddy consisting of both the surface platform and an underwater vehicle that will serve as diving ”guide”, ”slave” and ”observer”.

The proposed paper is part of a research program centered on CNR-ISSIA Unmanned Surface Vehicles. It focuses on the definition of good experimental methodologies and practices as well as suitable metrics for performance evaluation in order to carry out repeatable experiments for Unmanned Marine Vehicles. Preliminary theoretical results, validated on field data collected with Charlie USV, are presented.

Currently, special attention is being paid to scenarios where the interconnection of devices with heterogeneous computational and communication capabilities it is required. It is essential to integrate security services during the stages of design and deployment of these networks since many of these scenarios provide critical services such as medical health, payment systems, military affairs, access control, e-banking, etc. This work analyses several cryptographic primitives related to entity authentication providing robust solutions according to device capabilities.

The digital compass on mobile devices plays an important role in the mobile computing domain where applications have to rely on the accuracy of this sensor. In this paper we investigate the difficulties that occur with a digital compass in an industrial environment especially concerning indoor localization systems using the digital compass in mobile devices. We focus on two dependencies of the accuracy of this sensor type: device and location.

We present a novel approach to authenticate and authorize a user, using her personal smartphone. The presented architecture is complemented with a proof-of-concept implementation. The implemented system architecture is based on a single sign-on solution (SSO), extended to allow the usage of the smartphone as authentication and authorization device. We evaluated the system within real-world scenarios, observing users’ behavior using the novel technique. Based on our experiences, we summarize advances, made both in usability and security, for novel implementations using the proposed concept.

User satisfaction is one of the most important measures regarding the success of an application. However, using questionnaires to measure end-user satisfaction in the field of mobile applications becomes really complex. Mobile surveys tend to be ineffective and inefficient due to high costs, extensive preparation times and low retention rates. Thus, we present an approach as well as a prototype for measuring end-user satisfaction of mobile applications in the field. In this paper, we show how questionnaires can be directly integrated in native mobile applications without modifying the application’s source code, and how developers are provided with more control on when and where test participants have to fill them out.

Cross-platform development is a very interesting topic since mobile devices grow increasingly popular and mobile applications offer great possibilities. In addition, a new type of powerful applications is emerging as an attractive option, more specifically applications that use Cloud backends for computation and storage. However, targeting multiple mobile platforms is difficult due to the heterogeneities that exist between technologies.

This paper advances the use of Model-Driven Software Development to increase the level of abstraction to which an application is specified. Using a custom defined Domain-Specific Language and multiple code generators, it is possible to produce cloud-connected native applications for each targeted platform thus improving cross-platform development process.

Personal mobile devices hold sensitive data and can be used to access services with associated cost. For security reasons, most mobile platforms hence implement automatic device locking after a period of inactivity. Unlocking them using approaches like PIN, password or an unlock pattern is both problematic in terms of usability and potentially insecure, as it is prone to the shoulder surfing attack: an attacker watching the display during user authentication. Therefore,

face unlock

– using biometric face information for authentication – was developed as a more secure as well as more usable personal device unlock. Unfortunately, when using frontal face information only, authentication can still be circumvented by a photo attack: presenting a photo/video of the authorized person to the camera. We propose a variant of face unlock which is harder to circumvent by using all face information that is available during a 180° pan shot around the user’s head. Based on stereo vision, 2D and range images of the user’s head are recorded and classified along with sensor data of the device movement. We evaluate different classifiers for both grayscale 2D and range images and present our current results based on a new stereo vision face database.

When developing new protocols for Wireless Sensor Networks (WSN) the ability to observe generated wireless traffic and inspect packets sent between sensor nodes is a crucial part of the process. In this work a new methodology is presented, in which a single protocol description in XML files can be a source of various data needed for protocol development and testing. A set of tools is presented that allows automated generation of headers in nesC language as well as protocol dissectors for Wireshark – a popular network analysing tool. Although the described technique has been mainly used for the development of WSN applications, the principles and details can also be applied to the development of any protocol-oriented applications on mobile computing platforms.

Wizard of Oz studies, where a human replaces a system’s functionality, are often applied in evaluations focusing on the area of UbiComp, pervasive, and mobile Contexts. One of the major problems for such studies is that the Wizard of Oz system is usually developed as a throw-away system and needs to be developed for each study separately. We address this by investigating in a generic approach to conduct Wizard of Oz studies enabled by the ConWIZ framework.The ConWIZ protocol, which defines the communication requirements necessary for this approach, is defined to ensure a generic and generally applicable way of setting up and conducting Wizard of Oz studies. It allows to control the Wizard of Oz prototype as well as objects residing in the environment. We applied and evaluated the protocol in contextual studies and showed the applicability of the protocol within laboratory and mobile settings.

In the last years the number of platforms has increased dramatically – especially in the mobile sector. Developing a native mobile application for each platform is costly. There are common approaches to develop within one code base for many platforms. So-called

cross-platform-tools

can help developers to decrease the effort of making platform specific versions. However, most of these tools are dealing with JavaScript and therefore an existing native application, which is written in Java, C# or Objective-C can hardly be reused. This paper shows an automated conversion of platform specific Android applications to platform independent Web applications by using the

Google Web Toolkit

(GWT). This converter provides

code reusability

of existing Android applications and

platform independence

. The converter uses the

Eclipse Java Development Tools

(JDT) for processing the source code. On the one hand, Android wrapper classes provide the API calls, which access internally GWT code or directly HTML5 features. On the other hand, source code, which does not fulfill the GWT’s requirements, is converted. A case study confirms that this converter can be easily applied to a range of Android applications for converting them to platform independent Web applications.

We present a novel user interface concept for indoor navigation which uses directional arrows and panorama images of decision points, such as turns, along the route. The interface supports the mental model of landmark-based navigation, can be used on- and offline, and is highly tolerant to localization inaccuracy.

We evaluated the system in a real-world user study where decision points proved to be as efficient for navigation as continuous route instructions and panorama updates. We gained valuable insights on the role of feedback and of the frequency of decision points with relation to user confidence and satisfaction. Based on our experiences, we summarize lessons learned that inspire and guide the further design of UIs for pedestrian navigation systems in indoor environments.

An experimental approach to improve the user interface of an application is A/B testing, where two groups of subjects are tested with different variations of a user interface. While A/B testing has quite a long history in web development, it is considerably more difficult to apply for native mobile applications. For websites, different versions of the user interface can be provided on the server, and the website traffic is simply split between them. For native mobile applications however, even the smallest changes like the relocation of a button requires to recompile and republish the application. This is a considerable drawback though, as it is more time-consuming and less flexible compared to A/B testing of web applications. In this paper, we present an approach for exchanging the user interface of native Android applications at runtime. It just requires to include a library in the application, which is able to load new user interface versions from a server.

The colossal growth of volatile online text data evokes the demand for automatic text analysis tools to identify worthwhile information. Documents, as well as text streams, can be structured beyond the concept of frequency distributions.

Here we introduce a novel method that provides a relative measure for information value over a time series that is mapped by a dynamic trie structure. We adapt the concept of entropy for textual data and employ a compression-based estimation method. The algorithm can perform in a real-time scenario because of its linear complexity and since it is based on a dynamic history of predefined size.

We show the suitability of our method with an experimental dataset and compare our results to an existing approach. Our results reveal structural properties of the texts and permit for deeper analysis of the presumably information peaks.

In recent years, the wireless Body Area Network (BAN) technology has made significant advances. There is a tremendous need for the development of this technology. However, wireless BANs require much higher reliability than other similar types of networks as they need to operate at lower levels of user interaction and impose much stricter compliance to various regulatory requirements and technical standards. The aim is to discuss differences and reasoning behind the distinction of the two main types of sensor network tchnologies. The use of new wireless technologies and open standards can greatly extend and improve the functionality of BANs leading to new type of applications. This article, covers a number of issues related to the adaption of the wireless BAN technology in pervasive healthcare.

Multimodal Sensor Vision is a technique for detecting objects in dynamic and uncertain environmental conditions. In this research, a new approach for automated feature subset selection-mechanism is proposed that combines a set of features acquired from multiple sensors. Based on changing environmental conditions, the merits of respective sensory data can be assessed and the feature subset optimized, using genetic operators. Genetic Algorithms (GAs) with problem specific modifications improve reliability and adaptability of the detection process. In the new approach, a traditional GA is customized by combining the problem profiled encoding with a specialized operator. Application of an additional operator prioritizes and switches within the feature subsets of the algorithm, allowing a feature level aggregation that uses the most prominent features. The approach offers a more robust and a better performing Machine Vision processing.

The functionality and complexity of real-world engineering control systems is increasing significantly due to continuous growth in requirements and their details. Since this trend is predicted to grow even stronger, the old control solutions will be becoming less and less efficient. There are several approaches to designing modern control systems that meet the current and future needs. In this paper, we focus on one of the promising ways to control engineering: Embedded Systems. We describe categories of embedded systems and an engineering approach to control systems design based on the embedded systems. All related challenges are presented considering weaknesses of traditional systems. For the described embedded control system, a design methodology is given as well. Our discussion focuses on approach based on Field-Programmable Gate Array (FPGA) as a solution with huge potential. Finally, we share our thoughts on further trends in modern embedded control systems.

Bond Graphs theory can assist in tracking power movements in a system that is defined by effort and flow variables. An electronic circuit uses the network where flow (current) moves when affected by the effort (voltage). Morphotronics uses multidimensional vector space and transformations in this space to model bond graphs and the electronic circuit. Specifically, the flow (current) vector space or the effort (voltage) vector space is applied. In Morphotronics, an electronic circuit is a vector transformation operator in the space of voltage or current. Morphotronics offers a unique computational apparatus to create bond graphs and compute the power which moves through the graph. At the same time, Bond Graphs assist to visualise how the distance changes in the morphotronic system.

Given a set of sensors or cluster of sensors

S

located at different points or nodes in the ordinary space. Any sensor measures one or more values, such as Temperature. We assume that the information from all sensors at different positions in the space is transmitted to a Gateway node as a probabilistic phenomena, not in a deterministic way. The measured value

X

at the Gateway sensor node is a random value. Noise in the network randomly changes the original measurements. Information at the gateway is given by a distribution of the probability at the gateway sensor. We can show that given the values at the sensor node the distribution of the probability at the gateway changes. So the sensor measurements are parameters that define the distribution of the values at the gateway. The probability at the gateway is conditioned by the original measures at the sensor node. The probability approach cannot take care of the topology of the network but only of the conditional probability at the gateway conditioned by the sensors. Now we compute the derivative of the conditional Boltzmann entropy for any variation of the sensor value and for any value at the gateway

X

. This matrix gives us the sensor situation so we can compute the Fisher information of the sensor. It is the Hessian of the entropy average function in the space of the sensors

S

. The Fisher information gives us the geometry or form of the sensor space

S

. Sensor information is very important to obtain the form of the phenomena that we want to measure with the different sensors. Networks of sensors with their geometry go beyond the individual sensor that measures only one value and cannot discover the field or form of the physical phenomena.

Cost calculation models are being improved continuously. The advanced methods of cost calculation use such techniques like activity-based costing or full cost allocation. These methods are based on the modelling of operation processes. This paper aims to introduce a new methodology of circuit diagrams by using the operational models as starting points. The operational models are improved through circuit models based on the morphotronic theory. In the circuit diagram profit objects are sources of activity fluxes that are consumed or dissipated inside the cost objects. The intensity of the fluxes is determined by the structure of the network. It consists of the profit objects and the cost objects that are connected with each other, furthermore, of the cost driver units (price or effort) that profit objects must pay and of the intensity of the bonds (resistances) or connections between economic objects (profit and cost objects). The circuit diagram computation of the flow computes in a way that the total cost of the system assumes the minimum value. The circuit diagram defines the independent fluxes and also how to compute the dependent fluxes by the superposition of the independent fluxes. The circuit diagram is included in a more general theory denoted morphotronic.

The paper shows the possibility of Hierarchical Systems (HS) technology use in the tasks of Printed Circuit Boards (PCB) geometric design and interconnections (conductive pathways) quality testing. It gives formal description of the PCB construction and both the design and testing processes. Presented HS technology allows easy correction of interconnections topology of PCB, the mechanism of information aggregation permits reduction of computer memory, availability of coordinator allows performing decision making tasks on its layers. Possibility of HS technology realization using standard computer program and technical means is shown in the work as well.

As needed as testing is in software development to ensure the construction of quality products, it has also been traditionally forgotten or neglected, mostly due to its cost. However, in the recent past industry is acknowledging the far greater costs of not testing, or testing in a non-efficient and non-effective manner, particularly when the

monetization

of a software product is involved. This has lead to new approaches, techniques and tools for software testing, such as property-based testing. In this paper, we present how we applied this advanced technique, property-based testing, to verify a system where the handling of temporal information is critical: a distributed system for advertisement transmission over a digital TV network.