Showing papers in "Procedia Computer Science in 2014"

TL;DR: This paper from the 9th International Conference on Future Networks and Communications, FNC 2014 conference proceedings describes a wireless sensor network system developed using open-source hardware platforms, Arduino and Raspberry Pi.

TL;DR: In this paper, a low-pass filter was designed to isolate the component of gravity acceleration from that of body acceleration in the raw data, and five classifiers were tested using various statistical features.

TL;DR: A hybrid model for information system security threat classification is defined in order to propose a classification architecture that supports all threat classification principles and helps organizations implement their information security strategies.

TL;DR: The security issues and challenges on the IoT-based SG are investigated, and the major security services that should be considered when dealing with SG security are defined.

TL;DR: A low-cost indoor air quality monitoring wireless sensor network system developed using Arduino, XBee modules, and micro gas sensors that is capable of collecting six air quality parameters from different locations simultaneously.

TL;DR: Five common and important denoising methods are presented and applied on real ECG signals contaminated with different levels of noise, including discrete wavelet transform, adaptive filters, LMS and RLS, and Savitzky-Golay filtering.

TL;DR: A set of guidelines to keep in mind in order to achieve accessibility in mobile interfaces for older people is provided, a review study of the literature, standards and best practices that are being performed in this area of knowledge is reviewed.

TL;DR: The methodology, environment setup, design choices, implementation, results of the preliminary evaluation and assessment of “EasyLexia”, a mobile application for children with learning difficulties, show the promising prospects mobile learning holds in such contexts.

TL;DR: The design and evaluation process of the user interface of a smartphone application designed to promote exercise and prevent falls amongst older adults and recommendations regarding inclusive design and designing for older adults are described.

TL;DR: A better understanding of the security challenges of cloud computing is provided to identify approaches and solutions which have been proposed and adopted by the cloud service industry.

TL;DR: This research aims to develop a driver drowsiness monitoring system by analyzing the electroencephalographic (EEG) signals in a software scripted environment and using a driving simulator, and unsupervised learning through K-means clustering is employed.

TL;DR: Random sampling method is used to improve SVM model, considering the imbalance characteristics of customer data sets, and the results show that this method can effectively enhance the prediction accuracy of the selected model.

TL;DR: A computer-aided systems is proposed to automate the process of detection and identification of RBC from blood smear image and demonstrates a reliable and effective system for classifying normal and abnormal RBC.

TL;DR: The contribution is the proposal for accurate short term electricity load forecasting for 24 hours ahead, not on the aggregate but on the individual household level.

TL;DR: Novel insights are presented about the resilience of the Bitcoin ecosystem, the unambiguousness of the blockchain in use, and the propagation and verification of transaction blocks about Bitcoin's peer-to-peer (P2P) network.

TL;DR: The open source OM2-M project is proposed, an autonomic ETSI-compliant M2 M service platform that proposes a modular architecture running on top of an OSGi layer, making it highly extensible via plugins.

TL;DR: The properties and tradeoffs for engineered resilient systems in the military context are explored and promising research themes that need to be pursued by the research community to help the DoD realize the vision of affordable, adaptable, and effective systems are presented.

TL;DR: Moodle was used as interactive e-learning tool to motivate students and involve them in resolving single and collaborative homework tasks and proved the importance of using e- learning platforms in higher education.

TL;DR: In this article, a new method is proposed to optimize Low Energy Adaptive Clustering Hierarchy (O- LEACH) to improve existing LEACH and LEACH-C by selecting cluster according to the residual energy of nodes dynamically.

TL;DR: A machine learning method of support vector machine is introduced to construct a stock selection model, which can do the nonlinear classification of stocks and contributes the annual earnings of stock portfolio to outperforming those of A- share index of Shanghai Stock Exchange, significantly.

TL;DR: A sports data mining approach is presented, which helps discover interesting knowledge and predict outcomes of sports games such as college football, and makes predictions based on a combination of four different measures on the historical results of the games.

TL;DR: This paper introduces Vehicle as a Mobile Sensor (VaaMS), a concept that shows how sensor-equipped vehicles can be considered a pivotal, mobile resource of sensory data and sensor-related applications/services.

TL;DR: The research work presented here is twofold: first, it attempts to secure the inter-sensor communication by multi-biometric based key generation scheme in WBANs; and secondly, the electronic medical records are securely stored in the hospital community cloud and privacy of the patients’ data is preserved.

TL;DR: Performance evaluation of seven active companies in the petrochemical industries was evaluated using combined method of fuzzy and analytic hierarchy process, in the nest stage fuzzy set and fuzzy AHP is described and results of analysis have been presented.

TL;DR: The use of Kinect as a learning auxiliary tool for children with autism is suggested and the use of the game “Kinect Adventures” following the norms of the learning model “Mnemonic Techniques” for best results is recommended.

TL;DR: This work presents an extensive measurement campaign of the positions of a fleet of 370 taxi cabs moving around the city of Rome, Italy, to assess the performance of a simple epidemic protocol that is compared with the basic random waypoint model.

TL;DR: A series of indicators, which derive from user's interactions with mouse and keyboard, are proposed, to evaluate their use in identifying affective states and behavior changes in an e-learning platform by means of non-intrusive and low cost methods.

TL;DR: This paper introduces EcoHealth (Ecosystem of Health Care Devices), a Web middleware platform for connecting doctors and patients using attached body sensors, thus aiming to provide improved health monitoring and diagnosis for patients.

TL;DR: A Nonlinear Autoregressive Network with Exogenous Inputs (NARX) approach was applied to the Vichy-Rolla National Airport's photovoltaic station and results show that the NARX neural network notably outperformed the other models and is better than the linear regression model.

TL;DR: Three popular Neural Network models are implemented to help improve the performance of the GJR(1-1) method for estimating volatility over the next forty-four trading days.