BodyCloud: a SaaS approach for community body sensor networks

Body Sensor Networks (BSNs) have been recently introduced for the remote monitoring of human activities in a broad range of application domains, such as health care, emergency management, fitness and behaviour surveillance. BSNs can be deployed in a community of people and can generate large amounts of contextual data that require a scalable approach for storage, processing and analysis. Cloud computing can provide a flexible storage and processing infrastructure to perform both online and offline analysis of data streams generated in BSNs. This paper proposes BodyCloud, a SaaS approach for community BSNs that supports the development and deployment of Cloud-assisted BSN applications. BodyCloud is a multi-tier application-level architecture that integrates a Cloud computing platform and BSN data streams middleware. BodyCloud provides programming abstractions that allow the rapid development of community BSN applications. This work describes the general architecture of the proposed approach and presents a case study for the real-time monitoring and analysis of cardiac data streams of many individuals.

Motor imagery induced EEG patterns in spinal cord injury patients and their impact on Brain-Computer Interface accuracy

OBJECTIVE: Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no 'cure' at the present time. Brain-computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI. APPROACH: Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups. MAIN RESULTS: It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%). SIGNIFICANCE: The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals.

A novel approach for distributed application scheduling based on prediction of communication events

The evolution of commodity computing lead to the possibility of efficient usage of interconnected machines to solve computationally-intensive tasks, which were previously solvable only by using expensive supercomputers. This, however, required new methods for process scheduling and distribution, considering the network latency, communication cost, heterogeneous environments and distributed computing constraints. An efficient distribution of processes over such environments requires an adequate scheduling strategy, as the cost of inefficient process allocation is unacceptably high. Therefore, a knowledge and prediction of application behavior is essential to perform effective scheduling. In this paper, we overview the evolution of scheduling approaches, focusing on distributed environments. We also evaluate the current approaches for process behavior extraction and prediction, aiming at selecting an adequate technique for online prediction of application execution. Based on this evaluation, we propose a novel model for application behavior prediction, considering chaotic properties of such behavior and the automatic detection of critical execution points. The proposed model is applied and evaluated for process scheduling in cluster and grid computing environments. The obtained results demonstrate that prediction of the process behavior is essential for efficient scheduling in large-scale and heterogeneous distributed environments, outperforming conventional scheduling policies by a factor of 10, and even more in some cases. Furthermore, the proposed approach proves to be efficient for online predictions due to its low computational cost and good precision. (C) 2009 Elsevier B.V. All rights reserved.

Single Synapse Information Coding in Intraburst Spike Patterns of Central Pattern Generator Motor Neurons

Burst firing is ubiquitous in nervous systems and has been intensively studied in central pattern generators (CPGs). Previous works have described subtle intraburst spike patterns (IBSPs) that, despite being traditionally neglected for their lack of relation to CPG motor function, were shown to be cell-type specific and sensitive to CPG connectivity. Here we address this matter by investigating how a bursting motor neuron expresses information about other neurons in the network. We performed experiments on the crustacean stomatogastric pyloric CPG, both in control conditions and interacting in real-time with computer model neurons. The sensitivity of postsynaptic to presynaptic IBSPs was inferred by computing their average mutual information along each neuron burst. We found that details of input patterns are nonlinearly and inhomogeneously coded through a single synapse into the fine IBSPs structure of the postsynaptic neuron following burst. In this way, motor neurons are able to use different time scales to convey two types of information simultaneously: muscle contraction (related to bursting rhythm) and the behavior of other CPG neurons (at a much shorter timescale by using IBSPs as information carriers). Moreover, the analysis revealed that the coding mechanism described takes part in a previously unsuspected information pathway from a CPG motor neuron to a nerve that projects to sensory brain areas, thus providing evidence of the general physiological role of information coding through IBSPs in the regulation of neuronal firing patterns in remote circuits by the CNS.

Road Sign Recognition based onInvariant Features using SupportVector Machine

Since last two decades researches have been working on developing systems that can assistsdrivers in the best way possible and make driving safe. Computer vision has played a crucialpart in design of these systems. With the introduction of vision techniques variousautonomous and robust real-time traffic automation systems have been designed such asTraffic monitoring, Traffic related parameter estimation and intelligent vehicles. Among theseautomatic detection and recognition of road signs has became an interesting research topic.The system can assist drivers about signs they don’t recognize before passing them.Aim of this research project is to present an Intelligent Road Sign Recognition System basedon state-of-the-art technique, the Support Vector Machine. The project is an extension to thework done at ITS research Platform at Dalarna University [25]. Focus of this research work ison the recognition of road signs under analysis. When classifying an image its location, sizeand orientation in the image plane are its irrelevant features and one way to get rid of thisambiguity is to extract those features which are invariant under the above mentionedtransformation. These invariant features are then used in Support Vector Machine forclassification. Support Vector Machine is a supervised learning machine that solves problemin higher dimension with the help of Kernel functions and is best know for classificationproblems.

Automatic and objective assessment of alternating tapping performance in Parkinson’s disease

This paper presents the development and evaluation of a method for enabling quantitative and automatic scoring of alternating tapping performance of patients with Parkinson’s disease (PD). Ten healthy elderly subjects and 95 patients in different clinical stages of PD have utilized a touch-pad handheld computer to perform alternate tapping tests in their home environments. First, a neurologist used a web-based system to visually assess impairments in four tapping dimensions (‘speed’, ‘accuracy’, ‘fatigue’ and ‘arrhythmia’) and a global tapping severity (GTS). Second, tapping signals were processed with time series analysis and statistical methods to derive 24 quantitative parameters. Third, principal component analysis was used to reduce the dimensions of these parameters and to obtain scores for the four dimensions. Finally, a logistic regression classifier was trained using a 10-fold stratified cross-validation to map the reduced parameters to the corresponding visually assessed GTS scores. Results showed that the computed scores correlated well to visually assessed scores and were significantly different across Unified Parkinson’s Disease Rating Scale scores of upper limb motor performance. In addition, they had good internal consistency, had good ability to discriminate between healthy elderly and patients in different disease stages, had good sensitivity to treatment interventions and could reflect the natural disease progression over time. In conclusion, the automatic method can be useful to objectively assess the tapping performance of PD patients and can be included in telemedicine tools for remote monitoring of tapping.

Optimization of cable cycles : a trade-off between reliability and cost

This paper elaborates the routing of cable cycle through available routes in a building in order to link a set of devices, in a most reasonable way. Despite of the similarities to other NP-hard routing problems, the only goal is not only to minimize the cost (length of the cycle) but also to increase the reliability of the path (in case of a cable cut) which is assessed by a risk factor. Since there is often a trade-off between the risk and length factors, a criterion for ranking candidates and deciding the most reasonable solution is defined. A set of techniques is proposed to perform an efficient and exact search among candidates. A novel graph is introduced to reduce the search-space, and navigate the search toward feasible and desirable solutions. Moreover, admissible heuristic length estimation helps to early detection of partial cycles which lead to unreasonable solutions. The results show that the method provides solutions which are both technically and financially reasonable. Furthermore, it is proved that the proposed techniques are very efficient in reducing the computational time of the search to a reasonable amount.

Controle em tempo real de robôs através de redes IP

Com o intuito de utilizar uma rede com protocolo IP para a implementação de malhas fechadas de controle, este trabalho propõe-se a realizar um estudo da operação de um sistema de controle dinâmico distribuído, comparando-o com a operação de um sistema de controle local convencional. Em geral, a decisão de projetar uma arquitetura de controle distribuído é feita baseada na simplicidade, na redução dos custos e confiabilidade; portanto, um diferencial bastante importante é a utilização da rede IP. O objetivo de uma rede de controle não é transmitir dados digitais, mas dados analógicos amostrados. Assim, métricas usuais em redes de computadores, como quantidade de dados e taxa de transferências, tornam-se secundárias em uma rede de controle. São propostas técnicas para tratar os pacotes que sofrem atrasos e recuperar o desempenho do sistema de controle através da rede IP. A chave para este método é realizar a estimação do conteúdo dos pacotes que sofrem atrasos com base no modelo dinâmico do sistema, mantendo o sistema com um nível adequado de desempenho. O sistema considerado é o controle de um manipulador antropomórfico com dois braços e uma cabeça de visão estéreo totalizando 18 juntas. Os resultados obtidos mostram que se pode recuperar boa parte do desempenho do sistema.

Um sistema para gestão do conhecimento em ameaças, vulnerabilidades e seus efeitos

Attacks to devices connected to networks are one of the main problems related to the confidentiality of sensitive data and the correct functioning of computer systems. In spite of the availability of tools and procedures that harden or prevent the occurrence of security incidents, network devices are successfully attacked using strategies applied in previous events. The lack of knowledge about scenarios in which these attacks occurred effectively contributes to the success of new attacks. The development of a tool that makes this kind of information available is, therefore, of great relevance. This work presents a support system to the management of corporate security for the storage, retrieval and help in constructing attack scenarios and related information. If an incident occurs in a corporation, an expert must access the system to store the specific attack scenario. This scenario, made available through controlled access, must be analyzed so that effective decisions or actions can be taken for similar cases. Besides the strategy used by the attacker, attack scenarios also exacerbate vulnerabilities in devices. The access to this kind of information contributes to an increased security level of a corporation's network devices and a decreased response time to occurring incidents

BMMobile: uma linha de produtos para dimensionamento de bombeio mecânico em dispositivos móveis

With the increase of processing ability, storage and several kinds of communication existing such as Bluetooth, infrared, wireless networks, etc.., mobile devices are no longer only devices with specific function and have become tools with various functionalities. In the business field, the benefits that these kinds of devices can offer are considerable, because the portability allows tasks that previously could only be performed within the work environment, can be performed anywhere. In the context of oil exploration companies, mobile applications allow quick actions could be taken by petroleum engineers and technicians, using their mobile devices to avoid potential catastrophes like an unexpected stop or break of important equipment. In general, the configuration of equipment for oil extraction is performed on the work environment using computer systems in desktop platforms. After the obtained configuration, an employee goes to equipment to be configured and perform the modifications obtained on the use desktop system. This management process equipment for oil extraction takes long time and does not guarantee the maintenance in time to avoid problems. With the use of mobile devices, management and maintenance of equipment for oil extraction can be performed in a more agile time once it enables the engineer or technician oil can perform this configuration at the time and place where the request comes for example, near in the oil well where the equipment is located. The wide variety of mobile devices creates a big difficulty in developing mobile applications, since for one application can function in several types of devices, the application must be changed for each specific type of device, which makes the development quite costly. This paper defines and implements a software product line for designing sucker-rod pumping systems on mobile devices. This product line of software, called BMMobile, aims to produce products that are capable of performing calculations to determine the possible configurations for the equipment in the design suckerrod pumping, and managing the variabilities of the various products that can be generated. Besides, this work performs two evaluations. The first evaluation will verify the consistency of the products produced by the software product line. The second evaluation will verify the reuse of some products generated by SPL developed

Time-dependent non-Hermitian Hamiltonians with real energies

In this work we intend to study a class of time-dependent quantum systems with non-Hermitian Hamiltonians, particularly those whose Hermitian counterparts are important for the comprehension of posed problems in quantum optics and quantum chemistry. They consist of an oscillator with time-dependent mass and frequency under the action of a time-dependent imaginary potential. The wave functions are used to obtain the expectation value of the Hamiltonian. Although it is neither Hermitian nor PT symmetric, the Hamiltonian under study exhibits real values of energy.

Fuzzy distributed artificial intelligence systems

In this paper, we introduce a DAI approach called hereinafter Fuzzy Distributed Artificial Intelligence (FDAI). Through the use of fuzzy logic, we have been able to develop mechanisms that we feel may effectively improve current DAI systems, giving much more flexibility and providing the subsidies which a formal theory can bring. The appropriateness of the FDAI approach is explored in an important application, a fuzzy distributed traffic-light control system, where we have been able to aggregate and study several issues concerned with fuzzy and distributed artificial intelligence. We also present a number of current research directions necessary to develop the FDAI approach more fully.

Algorithms for network piecewise-linear programs: A comparative study

Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

Utilizing the CORBA platform in the construction of a highly immersive virtual environment

This article presents the implementation of a distributed system of virtual reality, through the integration of services offered by the CORBA platform (Common Object Request Broker Architecture) and by the environment of development of 3D graphic applications in real time, the WorldToolkit, of Sense8. The developed application for the validation of this integration is that of a virtual city, with an emphasis on its traffic ways, vehicles (movable objects) and buildings (immovable objects). In this virtual world, several users can interact, each one controlling his/her own car. Since the modelling of the application took into consideration the criteria and principles of the Transport Engineering, the aim is to use it in the planning, project and construction of traffic ways for vehicles. The system was structured according to the approach client/server utilizing multicast communication among the participating nodes. The chosen implementation for the CORBA was the Iona's ORBIX software. The performance results obtained are presented and discussed in the end.