Numer czasopisma
Computer Science
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ISSN: 1508-2806
e-ISSN:
Data wydania
2016
Rocznik
Vol. 17
Numer
No. 1
Prawa dostępu
Dostęp: otwarty dostęp
Uwagi:
Prawa: CC BY 4.0 
Uznanie autorstwa 4.0 Międzynarodowe (CC BY 4.0)
Strony
Opis
Rocznik czasopisma (rel.)
Rocznik czasopisma
Computer Science
Vol. 17 (2016)
Artykuły numeru (rel.)
Artykuł
Dostęp ograniczony
Computer aided distributed post-stroke rehabilitation environment
(2016) Wrzeszcz, Michał; Otfinowski, Janusz Stanisław; Słota, Renata; Kitowski, Jacek
In 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.
Artykuł
Dostęp ograniczony
Adapting a constituency parser to user-generated content in polish opinion mining
(2016) Pluwak, Agnieszka; Korczyński, Wojciech; Kisiel-Dorohinicki, Marek
The paper focuses on the adjustment of NLP tools for Polish, e.g., morphological analyzers and parsers, to user-generated content (UGC). The authors discuss two rule-based techniques applied to improve their efficiency: pre-processing (text normalization) and parser adaptation (modified segmentation and parsing rules). A new solution to handle OOVs based on inflectional translation is also offered.
Artykuł
Dostęp ograniczony
On a workflow model based on generalized communicating P systems
(2016) Balaskó, Ákos
This 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 models.
Artykuł
Dostęp ograniczony
Scaling evolutionary programming with the use of apache spark
(2016) Funika, Włodzimierz; Koperek, Paweł
Organizations 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.
Artykuł
Dostęp ograniczony
Parallel patterns for agent-based evolutionary computing
(2016) Stypka, Jan; Anielski, Piotr; Mentel, Szymon; Krzywicki, Daniel; Turek, Wojciech; Byrski, Aleksander; Kisiel-Dorohinicki, Marek
Computing applications such as metaheuristics-based optimization can greatly benefit from multi-core architectures available on modern supercomputers. In this paper, we describe an easy and efficient way to implement certain population-based algorithms (in the discussed case, multi-agent computing system) on such runtime environments. Our solution is based on an Erlang software library which implements dedicated parallel patterns. We provide technological details on our approach and discuss experimental results.
Artykuł
Dostęp ograniczony
Implementing graph representation model for parallel and distributed systems using Erlang
(2016) Petrov, Ûrij, K.
This paper describes a new model of graph representation using the Erlang actor model. Benefits of using lightweight processes instead of traditional passive data structures are given. Examples of using this model are shown. The experimental part gives two examples of using early implementations of the offered model. As a conclusion, an analysis of applicability for tasks from different branches of science is given.