Showing papers presented at "Computer Aided Systems Theory in 2013"

A PILOT/VND/GRASP Hybrid for the Static Balancing of Public Bicycle Sharing Systems

Abstract: Due to varying user demands in bicycle sharing systems, operators need to actively shift bikes between stations by a fleet of vehicles. We address the problem of finding efficient vehicle tours by an extended version of an iterated greedy construction heuristic following the concept of the PILOT method and GRASP and applying a variable neighborhood descend (VND) as local improvement. Computational results on benchmark instances derived from the real-world scenario in Vienna with up to 700 stations indicate that our PILOT/GRASP hybrid especially scales significantly better to very large instances than a previously proposed variable neighborhood search (VNS) approach. Applying only one iteration, the PILOT construction heuristic followed by the VND provides good solutions very quickly, which can be potentially useful for urgent requests.

Evolution of Covariance Functions for Gaussian Process Regression Using Genetic Programming

Abstract: In this contribution we describe an approach to evolve composite covariance functions for Gaussian processes using genetic programming. A critical aspect of Gaussian processes and similar kernel-based models such as SVM is, that the covariance function should be adapted to the modeled data. Frequently, the squared exponential covariance function is used as a default. However, this can lead to a misspecified model, which does not fit the data well. In the proposed approach we use a grammar for the composition of covariance functions and genetic programming to search over the space of sentences that can be derived from the grammar. We tested the proposed approach on synthetic data from two-dimensional test functions, and on the Mauna Loa CO 2 time series. The results show, that our approach is feasible, finding covariance functions that perform much better than a default covariance function. For the CO 2 data set a composite covariance function is found, that matches the performance of a hand-tuned covariance function.

Petri Net Dynamic Partial Reconfiguration in FPGA

Abstract: The rigorous digital design of embedded Application Specific Logic Controllers starts from algorithm designed with concurrent hierarchical control interpreted Petri net and then implemented into FPGA. But, there could be required to have several contexts of work mode of such device. The classic design flows includes all contexts in one control algorithm together with switching handling. The design flow proposed in this paper uses feature of dynamic partial reconfiguration of new FPGA devices. There is proposed a way of design of a top level Petri net and subnets describing particular contexts and its connections. The rules of implementation are also formed.

Control System Design Based on Modern Embedded Systems

Abstract: 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.

Boolean Function Complementation Based Algorithm for Data Discretization

Abstract: 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.

On a Bilateral Linear Birth and Death Process in the Presence of Catastrophes

Abstract: A bilateral linear birth-death process with disasters in zero is considered. The Laplace transforms of the transition probabilities are determined and the steady-state distribution is analyzed. The first-visit time to zero state is also studied.

Traffic Light Recognition During the Night Based on Fuzzy Logic Clustering

Abstract: 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.

Formal Definition of Service Availability in Cloud Computing Using OWL

Abstract: Fulfilling cloud customers needs entails describing a quality of service on top of the services functional description. Currently, the only guarantees that are offered by cloud providers are imprecise and incomplete Service Level Agreements (SLA). We present a model to describe one of the main attributes discussed in SLAs which is availability. The model is developed using Web Ontology Language OWL. And it aims at covering the different concepts of availability and availability-related attributes that should be present in a service contract in order to guarantee the quality of service the consumer is expecting.

Enhancing a Genetic Algorithm with a Solution Archive to Reconstruct Cross Cut Shredded Text Documents

Abstract: In this work the concept of a trie-based complete solution archive in combination with a genetic algorithm is applied to the Reconstruction of Cross-Cut Shredded Text Documents (RCCSTD) problem. This archive is able to detect and subsequently convert duplicates into new yet unvisited solutions. Cross-cut shredded documents are documents that are cut into rectangular pieces of equal size and shape. The reconstruction of documents can be of high interest in forensic science. Two types of tries are compared as underlying data structure, an indexed trie and a linked trie. Experiments indicate that the latter needs considerably less memory without affecting the run-time. While the archive-enhanced genetic algorithm yields better results for runs with a fixed number of iterations, advantages diminish due to the additional overhead when considering run-time.

IoT Application in the Supply Chain Logistics

Abstract: 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.

Analysis of Compass Sensor Accuracy on Several Mobile Devices in an Industrial Environment

Abstract: 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.

Efficient Multi-Objective Optimization Using 2-Population Cooperative Coevolution

Abstract: We propose a 2-population cooperative coevolutionary optimization method that can efficiently solve multi-objective optimization problems as it successfully combines positive traits from classic multi-objective evolutionary algorithms and from newer optimization approaches that explore the concept of differential evolution. A key part of the algorithm lies in the proposed dual fitness sharing mechanism that is able to smoothly transfer information between the two coevolved populations without negatively impacting the independent evolutionary process behavior that characterizes each population.

A Memetic Algorithm with Two Distinct Solution Representations for the Partition Graph Coloring Problem

Abstract: In this paper we propose a memetic algorithm (MA) for the partition graph coloring problem. Given a clustered graph G = (V,E), the goal is to find a subset V * i¾? V that contains exactly one node for each cluster and a coloring for V * so that in the graph induced by V *, two adjacent nodes have different colors and the total number of used colors is minimal. In our MA we use two distinct solution representations, one for the genetic operators and one for the local search procedure, which are tailored for the corresponding situations, respectively. The algorithm is evaluated on a common benchmark instances set and the computational results show that compared to a state-of-the-art branch and cut algorithm, our MA achieves solid results in very short run-times.

Towards Secure Personal Device Unlock Using Stereo Camera Pan Shots

Abstract: 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.

Structural Synthesis of Dispatching Rules for Dynamic Dial-a-Ride Problems

Abstract: The dial-a-ride problem consists of designing vehicle routes in the area of passenger transportation. Assuming that each vehicle can act autonomously, the problem can be modeled as a multi-agent system. In that context, it is a complex decision process for each agent to determine what action to perform next. In this work, the agent function is evolved using genetic programming by synthesizing basic bits of information. Specialized dispatching rules are synthesized automatically that are adapted to the problem environment. We compare the evolved rules with other dispatching strategies for dynamic dial-a-ride problems on a set of generated benchmark instances. Additionally, since genetic programming is a whitebox-based approach, insights can be gained about important system parameters. For that purpose, we perform a variable frequency analysis during the evolutionary process.

Nonlinear Least Squares Optimization of Constants in Symbolic Regression

Abstract: In this publication a constant optimization approach for symbolic regression by genetic programming is presented. The Levenberg-Marquardt algorithm, a nonlinear, least-squares method, tunes numerical values of constants in symbolic expression trees to improve their fit to observed data. The necessary gradient information for the algorithm is obtained by automatic programming, which efficiently calculates the partial derivatives of symbolic expression trees. The performance of the methodology is tested for standard and offspring selection genetic programming on four well-known benchmark datasets. Although constant optimization includes an overhead regarding the algorithm runtime, the achievable quality increases significantly compared to the standard algorithms. For example, the average coefficient of determination on the Poly-10 problem changes from 0.537 without constant optimization to over 0.8 with constant optimization enabled. In addition to the experimental results, the effect of different parameter settings like the number of individuals to be optimized is detailed.

Glider Path-Planning for Optimal Sampling of Mesoscale Eddies

Abstract: 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.

The Smartphone as Mobile Authorization Proxy

Abstract: We present a novel approach to use a mobile device for authentication and authorization purposes, where the user is able to authenticate and authorize himself for access on a public terminal. The concept is based on an extension of a Single-Sign On solution for mobile and public terminals. 1 Motivation for Intuitive Mobile SSO Internet services have become an integral element in daily activities. Cloud-based services like Google, Facebook or other social community platforms make use of a lot of personalized information of its users. It is essential for the users of these services to protect their data, their data’s integrity and their privacy by protecting the access to the account. As many users are using many different services, they usually have to use different logins for the different services – but, due to comfort reasons, often only have one password and probably only one login (typically the email address). Approaches like OAuth [1], OpenID [2], ‘Facebook Connect‘ or Shibboleth [3] can reduce the duplicate usernames and thereby duplicate vulnerable passwords. The basic idea is to move the authentication to a trusted IDentity Provider (IDP). The user authenticates himself against a well known login mask of the IDP and gets redirected to the calling Resource Provider (RP) that is requesting the authentication. Single Sign-On (SSO) is one possible option facilitating both comfort and safety requirements. A single action makes it possible to achieve user authentication and authorization and thereby permit a user to access all services he has permission to, without the need to enter credentials multiple times. With the rise of mobile devices, the classical webor software-based SSO solutions are not adequate anymore. Instead of a single desktop computer, multiple personal and private displays might become part of the interaction. We provide an intuitive SSO solution via mobile devices to access all kinds of services, ranging from data access to interaction with public terminals. 2 Implementation and Technical Background The idea of token-based service-login is that the user provides his credentials (commonly his user name and password) to his trusted authentication service. Due to the trustchain between the IDP and the RP, the token can grant the service to access the RP with the user’s identity. Every participating RP must have been trusted before by the IDP. With the negotiation between RP and IDP, the service gets an unique Service ID (SID) which is used to identify the resource in the QR code in our approach (cf. Fig. 1). This reduces the possibilities of token hijacking. Furthermore, the token can easily be revoked and renegotiated. Comparing to other standards, the RP can also communicate during the authentication process with the SSO server. This connection builds up the backbone of the system and helps protecting the users’ privacy and security.

Cost Function Selection for a Graph-Based Segmentation in OCT Retinal Images

Abstract: 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.

Towards Platform Independence of Mobile Applications

Abstract: 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.

The impact of new multi-platform observing systems in science, technology development and response to society needs; from small to large scales

Abstract: 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.

Photogrammetric Analysis of Images Acquired by an UAV

Abstract: 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.

Fast Calculation of Exact Minimal Unate Coverings on Both the CPU and the GPU

Abstract: 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 ∗ 107 in [8] and even 8 ∗ 108 in [7].

Cepstrum Coefficients of the RR Series for the Detection of Obstructive Sleep Apnea Based on Different Classifiers

Abstract: 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.

A Hybrid Cloud Computing Approach for Intelligent Processing and Storage of Scientific Data

Abstract: This paper covers a new approach on Cloud Computing for Scientific Data Storage and Processing using a hybrid system with both on-site and on-the-cloud systems. The system analyzes use cases which are not resolved by either one of the single systems themselves.

Model-Driven Development of Cloud-Connected Mobile Applications Using DSLs with Xtext

Abstract: 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.

An Analysis of the Intensification and Diversification Behavior of Different Operators for Genetic Algorithms

Abstract: Intensification and diversification are two driving forces in genetic algorithms and are frequently the subject of research. While it seemed for decades that a genetic operator can be classified as either the one or the other, it has been shown in the last few years that this assumption is an oversimplified view and most operators exhibit both, diversification and intensification, to some degree. Most papers in this field focus on a certain operator or algorithm configuration as theoretical and generalizable foundations are hard to obtain. In this paper we therefore use a wide range of different configurations and behavior measurements to study the intensification and diversification behavior of genetic algorithms and their operators.

Enabling A/B Testing of Native Mobile Applications by Remote User Interface Exchange

Abstract: 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.

Optimization as a Service: On the Use of Cloud Computing for Metaheuristic Optimization

Abstract: Cloud computing has emerged as a new technology that provides on-demand access to a large amount of computing resources. This makes it an ideal environment for executing metaheuristic optimization experiments. In this paper, we investigate the use of cloud computing for metaheuristic optimization. This is done by analyzing job characteristics from our production system and conducting a performance comparison between different execution environments. Additionally, a cost analysis is done to incorporate expenses of using virtual resources.

Delta Analysis of Role-Based Access Control Models

Abstract: Role-based Access Control (RBAC) is de facto standard for access control in Process-aware Information Systems (PAIS); it grants authorization to users based on roles (i.e. sets of permissions). So far, research has centered on the design and run time aspects of RBAC. An evaluation and verification of a RBAC system (e.g., to evaluate ex post which users acting in which roles were authorized to execute permissions) is still missing. In this paper, we propose delta analysis of RBAC models which compares a prescriptive RBAC model (i.e. how users are expected to work) with a RBAC model (i.e. how users have actually worked) derived from event logs. To do that, we transform RBAC models to graphs and analyze them for structural similarities and differences. Differences can indicate security violations such as unauthorized access. For future work, we plan to investigate semantic differences between RBAC models.