Computer Science Journal (AGH University of Science and Technology, Krakow)
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Computer Aided Distributed Post-Stroke Rehabilitation Environment
Get PDFIn this paper we present the results of a two-year study aimed at developing a full-fledged computer environment supporting post-stroke rehabilitation. The system was designed by a team of computer scientists, psychologists and physiotherapists. It adopts a holistic approach to rehabilitation. In order to extend the rehabilitation process, the applied methods include a remote rehabilitation stage which can be carried out of at the patient’s home. The paper presents a distributed system architecture as well as results achieved by patients prior to and following a three-month therapy based on the presented system
On a workflow model based on generalized communicating P systems
Get PDFThis paper introduces a new formal mathematical model for investigating workflows from dynamical and behavioural point of view. The model is designed on the basis of a special variant of the biology-inspired formal computational model called membrane systems, where the jobs or services are represented by membrane objects whose behaviour is defined by communication and generalization rules. The model supports running computations in a massive parallel manner, which makes it ideal to model high throughput workflow interpreters. Among the variants introduced in the literature, we have selected the Generalized Communicating P Systems, as it focuses on the communication among the membranes.Most of the workflow languages, based on different formal models like Petri nets or Communicating Sequential Processes, support several predefined structures – namely workflow patterns – to control the workflow interpretation such as conditions, loops etc. In this paper we show how these patterns are adapted into the membrane environment which, taking into account that membrane systems can be used to study complex dynamic systems’ runtime behaviour, makes this model a relevant alternative for the current model
SCALING EVOLUTIONARY PROGRAMMING WITH THE USE OF APACHE SPARK
Get PDFOrganizations across the globe gather more and more data, encouraged by easy-to-use and cheap cloud storage services. Large datasets require new approaches to analysis and processing, which include methods based on machine learning. In particular, symbolic regression can provide many useful insights. Unfortunately, due to high resource requirements, use of this method for large-scale dataset analysis might be unfeasible. In this paper, we analyze a bottleneck in the open-source implementation of this method we call hubert. We identify that the evaluation of individuals is the most costly operation. As a solution to this problem, we propose a new evaluation service based on the Apache Spark framework, which attempts to speed up computations by executing them in a distributed manner on a cluster of machines. We analyze the performance of the service by comparing the evaluation execution time of a number of samples with the use of both implementations. Finally, we draw conclusions and outline plans for further research
Competition-based rating system for medical website credibility
Get PDFIn this paper, we propose a new approach to the aggregation of monadic ratings (5-step scale) done by crowdsourcing users for the evaluation of medical websites. We compare them pairwise with other evaluations done by the same users for other websites (whether they are higher or lower), and we will use an Elo rating algorithm to calculate website “credibility” values. Results show that this method of crowdsourcing evaluation is highly correlated with expert evaluations. As proposed, a competition-based model uses a 5-step scale as ordinal and only compares which website is rated higher or lower by the same user. This approach can solve many problems associated with a 5-point scale, such as different understanding by users, user bias, and distribution skewness that can be clearly observed in results
Data mining and neural network simulations can help to improve Deep Brain Stimulation effects in Parkinson\u27s Disease
Get PDFParkinsons disease (PD) is primary related to substantia nigra degeneration and, thus, dopamine insufficiency. L-DOPA as a precursor of dopamine is the standard medication in PD. However, disease progression causes L-DOPA therapy efficiency decay (on-off symptom fluctuation), and neurologists often decide to classify patients for DBS (Deep Brain Stimulation) surgery. DBS treatment is based on stimulating the specific subthalamic structure: subthalamic nucleus (STN) in our case. As STN consists of parts with different physiological functions, finding the appropriate placement of the DBS electrode contacts is challenging. In order to predict the neurological effects related to different electrode-contact stimulations, we have tracked connections between the stimulated part of STN and the cortex with the help of diffusion tensor imaging (DTI). By changing a contacts number and amplitude of stimulus (proportional in size to stimulated area), we have determined connections to cortical areas and related neurological effects. We have applied data mining methods to predict which contact (and at what amplitude) should be stimulated in order to improve a particular symptom. We have compared different data mining methods: Wekas Random Forest classifier and Rough Set Exploration System (RSES). We have demonstrated that the Weka classifier was more accurate when predicting the effects of stimulations on general neurological improvements, while RSES was more accurate when using specific neurological symptoms. We have simulated other effects of stimulation related to the interruption of pathological oscillation in the basal ganglia found in PD. Our model represents possible STN neural population with inhibitory and excitatory connections that have pathologically synchronized oscillations. High-frequency electrical stimulation has interrupted synchronization. something that is also observed in PD patients
What affects web credibility perception? An analysis of textual justifications
Get PDFIn this paper, we present the findings of a qualitative analysis of 15,750 comments left by 2,041 participants in a Reconcile web credibility evaluation study. While assessing the credibility of the presented pages, respondents of the Reconcile studies were also asked to justify their ratings in writing. This work attempts to give an insight into the factors that affected the credibility assessment. To the best of our knowledge, the presented study is the most-recent large-scale study of its kind carried out since 2003, when the Fogg et al. How do users evaluate the credibility of Web sites? A study with over 2,500 participants’ paper was published. The performed analysis shows that the findings made a decade ago are still mostly valid today despite the passage of time and the advancement of Internet technologies. However we report a weaker impact of webpage appearance. A much bigger dataset (as compared to Fogg’s studies) allowed respondents to reveal additional features, which influenced the credibility evaluations
Towards A Novel Environment for Simulation of Quantum Computing
Get PDFIn this paper, we analyze existing quantum computer simulation techniques and their realizations to minimize the impact of the exponential complexity of simulated quantum computations. As a result of this investigation, we propose a quantum computer simulator with an integrated development environment – QuIDE – supporting the development of algorithms for future quantum computers. The simulator simplifies building and testing quantum circuits and understanding quantum algorithms in an efficient way. The development environment provides flexibility of source code edition and ease of the graphical building of circuit diagrams. We also describe and analyze the complexity of algorithms used for simulation as well as present performance results of the simulator as well as results of its deployment during university classes
HYPERGRAMMAR BASED PARALLEL MULTI-FRONTAL SOLVER FOR GRIDS WITH POINT SINGULARITIES
Get PDFThis paper describes the application of hypergraph grammars to drive linear computationalcost solver for grids with point singularities. Such graph grammar productions are the rstmathematical formalism used to describe solver algorithm and each of them indicates thesmallest atomic task that can be executed in parallel, which is very useful in case of parallelexecution. In particular the partial order of execution of graph grammar productions can befound, and the sets of independent graph grammar productions can be localized. They canbe scheduled set by set into shared memory parallel machine. The graph grammar basedsolver has been implemented with NIVIDIA CUDA for GPU. Graph grammar productionsare accompanied by numerical results for 2D case. We show that our graph grammar basedsolver with GPU accelerator is order of magnitude faster than state of the art MUMPSsolver
DISTRIBUTED WEB SERVICE REPOSITORY
Get PDFThe increasing availability and popularity of computer systems has resulted in a demand for new, language- and platform-independent ways of data exchange. That demand has in turn led to a significant growth in the importance of systems based on Web services. Alongside the growing number of systems accessible via Web services came the need for specialized data repositories that could offer effective means of searching of available services. The development of mobile systems and wireless data transmission technologies has allowed the use of distributed devices and computer systems on a greater scale. The accelerating growth of distributed systems might be a good reason to consider the development of distributed Web service repositories with built-in mechanisms for data migration and synchronization
Solution of Linear and Nonlinear Diffusion Problems via Stochastic Differential Equations
Get PDFThe equation for nonlinear diffusion can be rearranged to a form that immediately leads to its stochastic analog. The latter contains a drift term that is absent when the diffusion coefficient is constant. The dependence of this coefficient on concentration (or temperature) is handled by generating many paths in parallel and approximating the derivative of concentration with respect to distance by the central difference. This method works for one-dimensional diffusion problems with finite or infinite boundaries and for diffusion in cylindrical or spherical shells. By mimicking the movements of molecules, the stochastic approach provides a deeper insight into the physical process. The parallel version of our algorithm is very efficient. The 99% confidence limits for the stochastic solution enclose the analytical solution so tightly that they cannot be shown graphically. This indicates that there is no systematic difference in the results for the two methods. Finally, we present a direct derivation of the stochastic method for cylindrical and spherical shells