Showing papers in "Information Sciences in 2017"

TL;DR: A convolutional neural network algorithm is implemented for the automated detection of a normal and MI ECG beats (with noise and without noise) and can accurately detect the unknown ECG signals even with noise.

TL;DR: A convolutional neural network (CNN) technique to automatically detect the different ECG segments and can serve as an adjunct tool to assist clinicians in confirming their diagnosis is presented.

TL;DR: A brief overview of distributed networked control systems regarding system configurations, challenging issues and methodologies is presented and some potential research directions are suggested.

TL;DR: A novel fuzziness based semi-supervised learning approach by utilizing unlabeled samples assisted with supervised learning algorithm to improve the classifier's performance for the IDSs is proposed.

TL;DR: Two undersampling strategies in which a clustering technique is used during the data preprocessing step are introduced, one of which outperformed five state-of-the-art approaches and the other combined with a single multilayer perceptron classifier and C4.5 decision tree classifier ensembles delivered optimal performance over both small- and large-scale data sets.

TL;DR: Experiments show that a classifier training on the augmented set outperforms the same classifier trained on the original data, especially as far the sensitivity is concerned, resulting in an effective fraud detection mechanism.

TL;DR: An axiomatic approach to describe three-way concepts by means of multi-granularity is put forward and a three- way cognitive computing system is designed to find composite three-Way cognitive concepts.

TL;DR: A novel image fusion scheme based on image cartoon-texture decomposition and sparse representation is proposed, which outperforms the state-of-art methods, in terms of visual and quantitative evaluations.

TL;DR: This paper investigates the problem of network-based leader-following consensus of nonlinear multi-agent systems via distributed impulsive control by taking network-induced delays into account and derives a general consensus criterion.

TL;DR: This paper aims at developing a consensus building process in opinion dynamics, based on the concept leadership, by analyzing the structure of the social network in which all agents can form a consensus.

TL;DR: A new FA variant called FA with neighborhood attraction (NaFA) is proposed, where each firefly is attracted by other brighter fireflies selected from a predefined neighborhood rather than those from the entire population.

TL;DR: Formal security analysis and performance comparisons indicate that the proposed solutions simultaneously ensure attribute privacy and improve decryption efficiency for outsourced data storage in mobile cloud computing.

TL;DR: It is shown that it is possible to get a single convolutional neural network to segment these pathological features on a wide range of fundus images with reasonable accuracy, and that the net achieved a sensitivity of 0.7158 for exudates and dark lesions on the CLEOPATRA database.

TL;DR: Experimental results demonstrate that the proposed p-CNN is competitive with or even outperforms the state-of-the-art methods in terms of both subjective visual perception and objective evaluation metrics.

TL;DR: A novel predictor named Local-DPP, which combines the local Pse-PSSM (Pseudo Position-Specific Scoring Matrix) features with the random forest classifier, is established, which demonstrates the efficacy and effectiveness of Local- DPP in predicting DNA-binding proteins.

TL;DR: An intelligent cryptography approach, by which the cloud service operators cannot directly reach partial data is proposed, and experimental results depict that the approach can effectively defend main threats from clouds and requires with an acceptable computation time.

TL;DR: A model for determining the criteria weights is established, which considers both the individual effect of each hesitant fuzzy linguistic element (HFLE) and the interactive effect between any two HFLEs with respect to each criterion.

TL;DR: Wang et al. as discussed by the authors proposed the notion of Authenticated Encryption with Keyword Search (PAEKS), in which the data sender not only encrypts a keyword, but also authenticates it, so that a verifier would be convinced that the encrypted keyword can only be generated by the sender.

TL;DR: In this study, ECG signals are subjected to DCT, DWT and EMD to obtain respective coefficients, which are reduced using Locality Preserving Projection (LPP) data reduction method, and ranked using F-value to achieve the best classification performance.

TL;DR: An effective feature selection method based on firefly algorithm (FFA), called return-cost-based binary FFA (Rc-BBFA), which has the capability of preventing premature convergence and is particularly efficient attributed to the following three aspects.

TL;DR: A novel MAGDM method for IFNs is proposed, and some examples are used to compare the experimental results of the proposed method with the ones of the existing methods.

TL;DR: This work empirically explore a neural network model to learn document-level representation for detecting deceptive opinion spam and shows that the proposed method outperforms state-of-the-art methods.

TL;DR: This paper focuses on the consensus reaching process for GDM with PLPRs, which introduces the aggregation operators for the probabilistic linguistic term sets (PLTSs) and an application case about medical information presented on search engine is discussed.

TL;DR: This paper presents a comprehensive survey of different security and privacy threats that target every user of social networking sites, and separately focuses on various threats that arise due to the sharing of multimedia content within a social networking site.

TL;DR: A scheme that supports CBIR over the encrypted images without revealing the sensitive information to the cloud server is proposed and the security and efficiency of the proposed scheme are shown.

TL;DR: The theoretical analysis proves the convergence of a proposed algorithm and efficient convergence during the first and second steps of the algorithm to effectively prevent parking navigation from a gridlock situation and demonstrates that the proposed algorithm performs more efficiently than existing algorithms.

TL;DR: A novel hybrid method is presented for MCDM with two-level criteria under interval 2-tuple linguistic environment and a novel hybrid process integrating TL-ANP and IT-ELECTRE II is developed.

TL;DR: CiteSpace, a data visualization software, was used to make the comprehensive analysis of the 153,606 citations and construct the co-citation network maps, which can illustrate salient patterns and emerging trends.

TL;DR: A new information fusion method is constructed by transforming the original information of each object into a triangular fuzzy information granule, and some uncertainty measures of this fusion process are studied.

TL;DR: Simulation results show that IC-BSIF can encrypt different kinds of images into noise-like ones, and security evaluations demonstrate that it can achieve better performance than several state-of-the-art encryption schemes.