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  Subjects -> COMPUTER SCIENCE (Total: 1991 journals)
    - ANIMATION AND SIMULATION (29 journals)
    - AUTOMATION AND ROBOTICS (98 journals)
    - COMPUTER ARCHITECTURE (9 journals)
    - COMPUTER ENGINEERING (9 journals)
    - COMPUTER GAMES (16 journals)
    - COMPUTER PROGRAMMING (24 journals)
    - COMPUTER SCIENCE (1158 journals)
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    - DATA BASE MANAGEMENT (13 journals)
    - DATA MINING (32 journals)
    - E-BUSINESS (22 journals)
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    - IMAGE AND VIDEO PROCESSING (39 journals)
    - INFORMATION SYSTEMS (105 journals)
    - INTERNET (91 journals)
    - SOCIAL WEB (50 journals)
    - SOFTWARE (34 journals)
    - THEORY OF COMPUTING (8 journals)

COMPUTER SCIENCE (1158 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 13)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 22)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 9)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 13)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 16)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 6)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 4)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 13)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 4)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 1)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 20)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 8)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 8)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 11)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 25)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 3)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 26)
Advanced Science Letters     Full-text available via subscription   (Followers: 8)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 8)
Advances in Artificial Intelligence     Open Access   (Followers: 16)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 15)
Advances in Computer Science : an International Journal     Open Access   (Followers: 14)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 51)
Advances in Engineering Software     Hybrid Journal   (Followers: 25)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 10)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 26)
Advances in Human-Computer Interaction     Open Access   (Followers: 20)
Advances in Materials Sciences     Open Access   (Followers: 16)
Advances in Operations Research     Open Access   (Followers: 11)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 7)
Advances in Porous Media     Full-text available via subscription   (Followers: 4)
Advances in Remote Sensing     Open Access   (Followers: 37)
Advances in Science and Research (ASR)     Open Access   (Followers: 6)
Advances in Technology Innovation     Open Access   (Followers: 2)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 8)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
Air, Soil & Water Research     Open Access   (Followers: 9)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 6)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 4)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 7)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 11)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 7)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 12)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 2)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 14)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Clinical Informatics     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 12)
Applied Computer Systems     Open Access   (Followers: 1)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 11)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 132)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 4)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 6)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 4)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 11)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 8)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 52)
Bioinformatics     Hybrid Journal   (Followers: 302)
Biomedical Engineering     Hybrid Journal   (Followers: 16)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 17)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 32)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 45)
British Journal of Educational Technology     Hybrid Journal   (Followers: 128)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 2)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal  
Cell Communication and Signaling     Open Access   (Followers: 1)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access  
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 15)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 12)
Circuits and Systems     Open Access   (Followers: 16)
Clean Air Journal     Full-text available via subscription   (Followers: 2)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combustion Theory and Modelling     Hybrid Journal   (Followers: 13)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 20)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 53)
Communications of the Association for Information Systems     Open Access   (Followers: 18)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access  
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 9)
Computación y Sistemas     Open Access  
Computation     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 12)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 14)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 4)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 13)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 31)
Computer     Full-text available via subscription   (Followers: 87)
Computer Aided Surgery     Hybrid Journal   (Followers: 3)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 7)
Computer Communications     Hybrid Journal   (Followers: 10)
Computer Engineering and Applications Journal     Open Access   (Followers: 5)
Computer Journal     Hybrid Journal   (Followers: 7)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 22)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 10)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 1)
Computer Music Journal     Hybrid Journal   (Followers: 16)
Computer Physics Communications     Hybrid Journal   (Followers: 6)
Computer Science - Research and Development     Hybrid Journal   (Followers: 7)
Computer Science and Engineering     Open Access   (Followers: 17)
Computer Science and Information Technology     Open Access   (Followers: 11)
Computer Science Education     Hybrid Journal   (Followers: 12)
Computer Science Journal     Open Access   (Followers: 20)
Computer Science Master Research     Open Access   (Followers: 10)
Computer Science Review     Hybrid Journal   (Followers: 10)

        1 2 3 4 5 6 | Last

Journal Cover Applied Informatics
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   ISSN (Online) 2196-0089
   Published by SpringerOpen Homepage  [226 journals]
  • Multiscale recurrent regression networks for face alignment

    • Abstract: In this paper, we propose an end-to-end multiscale recurrent regression networks (MSRRN) approach for face alignment. Unlike conventional face alignment methods by utilizing handcrafted features which require strong prior knowledge by hand, our MSRRN aims to seek a series of hierarchical feature transformations directly from image pixels, which exploits the nonlinear relationship between the face images to the positions of facial landmarks. To achieve this, we carefully design a recurrent regression network architecture, where the parameters across different stages are shared to memorize the shape residual descents between the initial shape and the ground-truth. To further improve the performance, our MSRNN learns to exploit the context-aware information from multiscale face inputs in a coarse-to-fine manner. Experimental results on the benchmarking face alignment datasets show the effectiveness of our approach.
      PubDate: 2017-11-02
  • Learning scene-aware image priors with high-order Markov random fields

    • Abstract: Many methods have been proposed to learn image priors from natural images for the ill-posed image restoration tasks. However, many prior learning algorithms assume that a general prior distribution is suitable for over all kinds of images. Since the contents of the natural images and the corresponding low-level statistical characteristics vary from scene to scene, we argue that learning a universal generative prior for all natural images may be imperfect. Although the universal generative prior can remove artifacts and reserve a natural smoothness in image restoration, it also tends to introduce unreal flatness and clutter textures. To address this issue, in this paper, we present to learn a scene-aware image prior based on the high-order Markov random field (MRF) model (SA-MRF). With this model, we jointly learn a set of shared low-level features and different potentials for specific scene contents. In prediction, a good prior can be adapted to the given degenerated image with the scene content perception. Experimental results on the image denoising and inpainting tasks demonstrate the efficiency of the SA-MRF on both numerical evaluation and visual compression.
      PubDate: 2017-10-30
  • An integrated decision-making prototype based on OLAP systems and
           multicriteria analysis for complex decision-making problems

    • Abstract: OLAP (Online Analytical Processing) system appears as a revolutionary technology that provides adequate analytic solutions for decision support. Using OLAP, analysts and policymakers are able to process and analyze data in an interactive, fast, and effective way according to several axes. This provides a clear vision of their business at any time and in real time. However, these systems suffer from certain limitations related to the consideration of both the multicriteria and fuzzy aspects of multidimensional data when making decisions. To overcome these limitations, we propose an integrated decision-making prototype based on OLAP system and multicriteria analysis (MCA) to generate a hybrid analysis process dealing with complex multicriteria decision-making situations. This proposed solution, based on our previous contributions, allows the analyst to extract data from OLAP data cube model and analyze them using OLAP operators and MCA methods.
      PubDate: 2017-10-30
  • Using frequency-following responses (FFRs) to evaluate the auditory
           function of frequency-modulation (FM) discrimination

    • Abstract: Precise neural encoding of varying pitch is crucial for speech perception, especially in Mandarin. A valid evaluation of the listeners’ auditory function which accounts for the perception of pitch variation can facilitate the strategy of hearing compensation for hearing-impaired people. This auditory function has been evaluated by behavioral test in previous studies, but the objective measurement of auditory-evoked potentials, for example, is rarely studied. In this study, we investigated the scalp-recorded frequency-following responses (FFRs) evoked by frequency-modulated sweeps, and its correlation with behavioral performance on the just-noticeable differences (JNDs) of sweep slopes. The results showed that (1) the indices of FFRs varied significantly when the sweep slopes were manipulated; (2) the indices were all strongly negatively correlated with JNDs across listeners. The results suggested that the listener’s subjective JND could be predicted by the objective index of FFRs to tonal sweeps.
      PubDate: 2017-10-23
  • Community detection based on influence power

    • Abstract: Nowadays, more and more people use social network to share their lives and communicate with each other. In real social network, a person is influenced by others and also influences others at the same time. So the status of a person in the network can be determined by his influence power. In other words, a person with larger influence power always plays more important role and is more likely to act as a core of a community. Different from most of existing community detection algorithms which concentrate on the topology of networks, we propose an algorithm based on influence power to discover potential core members from which the community structure can be revealed. Extensive experiments confirm that our proposed algorithm has good performance in detecting community in real social network.
      PubDate: 2017-10-05
  • Cross-media residual correlation learning

    • Abstract: Due to the progress of deep neural networks (DNN), DNN has been employed to cross-media retrieval. Existing cross-media retrieval methods based on DNN can convert separate representation of each media type to common representation by inter-media and intra-media constraints. By using common representation, we can measure similarities between heterogeneous instances and perform cross-media retrieval. However, it is challenging to optimize common representation learning due to the inter-media and intra-media constraints, which is a multi-objective optimization problem. This paper proposes residual correlation network (RCN) to address this issue. RCN optimizes common representation learning with a residual function, which can fit the optimal mapping from separate representation to common representation and relieve the multi-objective optimization problem. The experiments show that proposed approach achieves the best accuracy compared with 10 state-of-the-art methods on 3 datasets.
      PubDate: 2017-10-05
  • Modularity in complex multilayer networks with multiple aspects: a static

    • Abstract: Complex systems are usually illustrated by networks which capture the topology of the interactions between the entities. To better understand the roles played by the entities in the system, one needs to uncover the underlying community structure of the system. In recent years, systems with interactions that have various types or can change over time between the entities have attracted much research attention. However, algorithms aiming at solving the key problem—community detection—in multilayer networks are still limited. In this work, we first introduce the multilayer network model representation. Then based on this model, we naturally derive the multilayer modularity—a widely adopted objective function of community detection in networks—from a static perspective to evaluate the quality of the communities detected in multilayer networks. It enables us to better understand the essence of the modularity by pointing out the specific kind of communities that will lead to a high modularity score. We also propose a spectral method called mSpec for the optimization of the proposed modularity function based on the supra-adjacency representation of the multilayer networks. Experiments on the electroencephalograph network and the comparison results on several empirical multilayer networks demonstrate the feasibility and reliable performance of the proposed method.
      PubDate: 2017-05-08
  • Acceptance of homegrown enterprise resource planning (ERP) systems in

    • Abstract: In the current competitive global market, organizations are implementing information and communication technology (ICT) that could add value to their products, processes, and satisfaction of their users. The adoption, implementation and use of homegrown enterprise resource planning (ERP) systems is one of these mechanisms being globally used for recording, processing, storing, and exchanging organizational information anytime anywhere. Although organizations have been utilizing ERP systems, the acceptance of homegrown ERP systems is given less attention as compared to commercial off-the shelf (COTS) software. Hence, this research studied factors that determine acceptance of homegrown ERP through the extension of unified theory of acceptance and use of technology (UTAUT) model. The finding revealed that performance expectancy, effort expectancy, social influence, competitive advantage, cost effectiveness, and facilitations functions are determinants of homegrown ERP system acceptance in Ethiopia. Moreover, experience and voluntariness are found to be significant moderators of the study.
      PubDate: 2017-03-14
  • Balancing decoding speed and memory usage for Huffman codes using
           quaternary tree

    • Abstract: In this paper, we focus on the use of quaternary tree instead of binary tree to speed up the decoding time for Huffman codes. It is usually difficult to achieve a balance between speed and memory usage using variable-length binary Huffman code. Quaternary tree is used here to produce optimal codeword that speeds up the way of searching. We analyzed the performance of our algorithms with the Huffman-based techniques in terms of decoding speed and compression ratio. The proposed decoding algorithm outperforms the Huffman-based techniques in terms of speed while the compression performance remains almost same.
      PubDate: 2017-01-07
  • Logistic regression analysis differentiates high from low computer users
           by facial skin conditions in a population of Chinese women

    • Abstract: In the past few decades, video display terminals (VDTs) and computer use have been associated with various skin symptoms in several published reports. In addition, internet beauty sites report that extended computer use leads to acne or accelerated facial aging. For example, the term “computer face” is used to describe premature aging caused by sitting for long periods of time in front of the screen ( We wished to determine, using instrumental and expert assessment, if prolonged/extended computer use could be associated with certain skin conditions. This study focused on long-term (10 years or more) office VDT work and was designed to include a wide range of confounding variables. One hundred Chinese women were recruited, 50 in each of two groups characterized as either (a) computer users with 8 or more hours per day, or (b) non-users who use computers 1 h or less per day. All subjects lived in Guangzhou and worked in the same building. Confounders were assessed by survey, and included age, smoking, sun exposure history, exercise, and other factors. Skin conditions, which included acne, sebum, wrinkles, and pigment spots, were assessed by instrumental measurements and blinded dermatologist assessment. Age and skin conditions were subjected to logistic regression analysis to determine major contributors which could separate, or distinguish, the computer group from the non-computer group. From this analysis, the office computer users were found to be statistically significantly associated with a higher incidence of acne, higher sebum levels, and a higher risk of self-reported sensitive skin when compared with the non-computer group. The final model suggests that the major contributors in separating the two groups are acne and pigmented spots (UV and brown). These results indicate that facial skin of women within the Chinese population who use computers for 8 h or more a day may be at higher risk for acne; however, they had lower levels of attributes associated with photoaging, such as lentigines and facial wrinkles. Separate pairwise assessment of other variables such as lifetime cumulative sun exposure, sleep quality, smoking behavior, exercise, and cosmetic product use or procedures showed no significant differences between the two groups. This indicates that the results obtained from objective and subjective measurements were not biased due to these potential confounders, but does not reveal the mechanism for the observed differences in skin conditions between computer/VDT users and non-users.
      PubDate: 2017-01-07
  • A novel framework for 3D shape retrieval

    • Abstract: The ability to accurately and effectively search for 3D shape is crucial for many applications. In this study, we proposed a novel framework for 3D shape retrieval. We compensate the loss of high frequencies of heat kernel signature from two aspects. One is to introduce the weight for each point to highlight the details of the salient points. The other is to directly capture microgeometry structure through wave kernel’s access to high frequencies. Thus, our method can capture geometric features at different frequencies of a shape, which satisfy the property of an ideal descriptor. We conduct shape retrieval experiments on a standard benchmark and compared with another heat kernel-based method. Experimental results demonstrate that the proposed method is effective and accurate.
      PubDate: 2017-01-06
  • Impact of order set use on outcome of patients with sepsis

    • Abstract: In an effort to improve outcome of patients with sepsis, we developed and implemented a disease-specific alert and order set for our computerized physician order entry system. This alert and order set were implemented in 2015. We have produced a progressive decrease in mortality for patients at our hospital with diagnosis of sepsis. We see a significant decrease in mortality for patients who had the sepsis order set used compared to those who did not have the order set used. We recommend use of an order set for patients with sepsis.
      PubDate: 2017-01-05
  • A modified approach for solving a fuzzy multi-objective programming

    • Abstract: Based on ranking of fuzzy numbers which deals with fuzzy-valued multi-objective programming problem and the modified crisp model, a modified approach is proposed. Also, two algorithms that play a pivotal role in the proposed method are introduced. The first one returns a ranking function to a given fuzzy number and the second algorithm uses the modified crisp model to deliver a Pareto optimal solution. Moreover, we investigate the stability of the first kind of the solution which is obtained using these algorithms. Finally, a numerical example is given to illustrate our modified approach, using Maple program.
      PubDate: 2017-01-05
  • An adaptive random compressive partial sampling method with TV recovery

    • Abstract: Different from standard sampling strategy in compressive sensing (CS), we present a compressive partial sampling framework called adaptive-random sampling and recovery (ASR) for image. It could faithfully recover images by hybridizing random samples with edge-extracted pixels with much lower sampling rate. The new framework preserves edge pixels containing essential information of images, and meanwhile employs the edge-preserving total variation (TV) regularizer. Assisted with the edges, three steps are adopted to recover the high-quality image. First, we extract the edges of a coarse image recovered with completely random measurements in our sampling framework. Then, the TV algorithm in the CS theory is employed for solving the Lagrangian regularization problem. Finally, we refine the coarse image to obtain a high-quality one with both the extracted edges and previous random measurements. Experimental results show that the novel ASR strategy achieves significant performance improvements over the current state-of-the-art schemes.
      PubDate: 2016-12-28
  • Enhanced automatic sleep spindle detection: a sliding window-based wavelet
           analysis and comparison using a proposal assessment method

    • Abstract: Sleep spindles are thought to be related to some sleep diseases and play an important role in memory consolidation. They were traditionally identified by physiology experts based on rules and recently detected by automatic algorithms. However, many automatic approaches were validated on the different electroencephalogram (EEG) using various assessment methods, making it difficult to appraised a method objectively and fairly. In this paper, we proposed a sliding window-based probability estimation (SWPE) method for sleep spindle detection. We performed a continuous wavelet transform with Mexican hat wavelet function, following by a sliding window to find out the candidate spindle points corresponding to the large wavelet coefficients at the frequencies of spindles and estimated their probabilities. To enhance the results, we used the envelope of the rectified signal to reject some false sleep spindle candidates. This was an enhanced method and we called it SWPE-E in this paper. Finally, we compared our approaches with four approaches on the same public available EEG database, and the result showed the significative improvement of our proposed approaches.
      PubDate: 2016-12-08
  • A spatial-constrained multi-target regression model for human brain
           activity prediction

    • Abstract: Analyzing functional magnetic resonance imaging (fMRI) data from the encoding perspective provides a powerful tool to explore human vision. Using voxel-wise encoding models, previous studies predicted the brain activity evoked by external stimuli successfully. However, these models constructed a regularized regression model for each single voxel separately, which overlooked the intrinsic spatial property of fMRI data. In this work, we proposed a multi-target regression model that predicts the activities of adjacent voxels simultaneously. Different from the previous models, the spatial constraint is considered in our model. The effectiveness of the proposed model is demonstrated by comparing it with two state-of-the-art voxel-wise models on a publicly available dataset. Results indicate that the proposed method can predict voxel responses more accurately than the competing methods.
      PubDate: 2016-11-24
  • Object segmentation by saliency-seeded and spatial-weighted region merging

    • Abstract: In this paper, we present a region merging-based method for object segmentation in natural images. The method consists of three separate steps: (1) initial over-segmentation such that pixels in each region are as homogeneous as possible and therefore likely to be from the same object; (2) saliency-seeded interaction to provide proper prior input to guide the segmentation; (3) region merging by an introduced maximal spatially weighted similarity (MSWS) criterion. Saliency-seeded interaction can well reflect the human intention but does not require any manual user editing, which makes our method applicable to increasingly large-scale image databases. The MSWS criterion takes into account both the color similarity and spatial distance of the candidate regions for merging, which allows the region merging-based method to achieve better performance. Extensive experiments show that our method can reliably and automatically segment the objects from a great variety of natural images.
      PubDate: 2016-11-22
  • Altered effective connectivity network of the thalamus in post-traumatic

    • Abstract: Post-traumatic stress disorder (PTSD) is an anxiety disorder that can develop following a traumatic event. Previous studies have found abnormal functional connectivity between the thalamus and other brain regions. However, the traditional functional connectivity method cannot investigate the directional flow of the influence in PTSD. In the present study, we used an effective connectivity method based on Granger causality to explore altered direction of causal information flow within a network associated with the thalamus in PTSD. Employing this method, we found that PTSD patients exhibited increased influence from thalamus to middle/inferior frontal gyrus and insula, and increased bidirectional influences between thalamus and medial prefrontal cortex compared to healthy controls. This is the first study to reveal a network of abnormal effective connectivity in PTSD. In addition, using the machine learning approach, we found that the altered functional measurements could differentiate patients from healthy controls. Our findings may have important implications for the pathophysiological basis underlying PTSD.
      PubDate: 2016-11-15
  • Structural covariance model reveals dynamic reconfiguration of triple
           networks in autism spectrum disorder

    • Abstract: The data open sharing provides us opportunity to investigate mechanisms underlying autism spectrum disorder (ASD) by employing advanced techniques. In the current study, we employed structural covariance (SC) model to investigate the development of triple networks in ASD. Three hundred and seven ASD and 337 typical controls were collected and further classified into four distinct age cohorts. Night brain seeds belonging to default modal network, salience network, and central executive network were obtained. SC between those seeds, as well as its topological properties, was calculated for each group within each age cohort. Statistical analysis revealed that ASD had dynamic reconfigurations of SC of the triple networks, especially the right fronto-insular cortex. The results might indicate that ASD had specific mechanism within distinct age cohort. Additionally, the big data sharing, together with the SC modal, was able to facilitate understanding of the mechanism underlying ASD.
      PubDate: 2016-10-21
  • Techniques for the suppression of sidelobes in a non-contiguous orthogonal
           frequency division multiplexing framework

    • Abstract: In orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems, high out-of-band radiation (OOBR) results in severe interference to the neighboring users, including licensed users (LUs) and cognitive radio users (CRUs). To tackle that issue, a framework of non-contiguous orthogonal frequency division multiplexing (NCOFDM) is presented in this paper that has the ability of describing any OOBR reduction techniques, regardless of whether a single or multiple techniques are applied. Based on this framework, we proposed four new different schemes that can be viewed as two-level suppression schemes. In the first level, the OOBR is reduced by techniques represented by precoding matrices, while in the second level further reduction of OOBR is done by using generalized sidelobe canceller (GSC). Numerical results show that the proposed schemes can suppress the OOBR significantly in terms of power spectral density (PSD), thus allowing the successful coexistence of LUs, as well as CRUs in a spectrum-sharing environment.
      PubDate: 2016-08-26
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
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