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  Subjects -> ENGINEERING (Total: 2160 journals)
    - CHEMICAL ENGINEERING (186 journals)
    - CIVIL ENGINEERING (168 journals)
    - ELECTRICAL ENGINEERING (93 journals)
    - ENGINEERING (1165 journals)
    - ENGINEERING MECHANICS AND MATERIALS (355 journals)
    - HYDRAULIC ENGINEERING (55 journals)
    - INDUSTRIAL ENGINEERING (57 journals)
    - MECHANICAL ENGINEERING (81 journals)

ENGINEERING (1165 journals)                  1 2 3 4 5 6 7 8 | Last

3 Biotech     Open Access   (Followers: 4)
3D Research     Hybrid Journal   (Followers: 21)
AAPG Bulletin     Full-text available via subscription   (Followers: 4)
AASRI Procedia     Open Access   (Followers: 10)
Abstract and Applied Analysis     Open Access  
Aceh International Journal of Science and Technology     Open Access   (Followers: 1)
ACS Nano     Full-text available via subscription   (Followers: 187)
Acta Geotechnica     Hybrid Journal   (Followers: 9)
Acta Metallurgica Sinica (English Letters)     Hybrid Journal   (Followers: 5)
Acta Polytechnica : Journal of Advanced Engineering     Open Access  
Acta Scientiarum. Technology     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Active and Passive Electronic Components     Open Access   (Followers: 4)
Adaptive Behavior     Hybrid Journal   (Followers: 9)
Adsorption     Hybrid Journal   (Followers: 7)
Advanced Science     Open Access   (Followers: 1)
Advanced Science Focus     Free   (Followers: 1)
Advanced Science Letters     Full-text available via subscription   (Followers: 5)
Advanced Science, Engineering and Medicine     Partially Free   (Followers: 8)
Advanced Synthesis & Catalysis     Hybrid Journal   (Followers: 4)
Advances in Artificial Neural Systems     Open Access   (Followers: 4)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 3)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Complex Systems     Hybrid Journal   (Followers: 8)
Advances in Engineering Software     Hybrid Journal   (Followers: 22)
Advances in Fuel Cells     Full-text available via subscription   (Followers: 13)
Advances in Fuzzy Systems     Open Access   (Followers: 6)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 12)
Advances in Heat Transfer     Full-text available via subscription   (Followers: 13)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 15)
Advances in Magnetic and Optical Resonance     Full-text available via subscription   (Followers: 5)
Advances in Natural Sciences: Nanoscience and Nanotechnology     Open Access   (Followers: 15)
Advances in Operations Research     Open Access   (Followers: 10)
Advances in OptoElectronics     Open Access   (Followers: 3)
Advances in Physics Theories and Applications     Open Access   (Followers: 8)
Advances in Polymer Science     Hybrid Journal   (Followers: 37)
Advances in Porous Media     Full-text available via subscription   (Followers: 3)
Advances in Remote Sensing     Open Access   (Followers: 9)
Advances in Science and Research (ASR)     Open Access   (Followers: 7)
Aerobiologia     Hybrid Journal   (Followers: 2)
African Journal of Information & Communication Technology     Open Access   (Followers: 4)
African Journal of Science, Technology, Innovation and Development     Hybrid Journal   (Followers: 5)
Afrique Science : Revue Internationale des Sciences et Technologie     Open Access   (Followers: 1)
AIChE Journal     Hybrid Journal   (Followers: 21)
Ain Shams Engineering Journal     Open Access   (Followers: 5)
Alexandria Engineering Journal     Open Access   (Followers: 1)
AMB Express     Open Access  
American Journal of Applied Sciences     Open Access   (Followers: 28)
American Journal of Engineering and Applied Sciences     Open Access   (Followers: 11)
American Journal of Engineering Education     Open Access   (Followers: 4)
American Journal of Environmental Engineering     Open Access   (Followers: 8)
American Journal of Industrial and Business Management     Open Access   (Followers: 19)
Analele Universitatii Ovidius Constanta - Seria Chimie     Open Access  
Annals of Combinatorics     Hybrid Journal   (Followers: 6)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Science     Hybrid Journal   (Followers: 6)
Antarctic Science     Hybrid Journal   (Followers: 2)
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applicable Analysis: An International Journal     Hybrid Journal   (Followers: 1)
Applied Catalysis A: General     Hybrid Journal   (Followers: 5)
Applied Catalysis B: Environmental     Hybrid Journal   (Followers: 5)
Applied Clay Science     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 9)
Applied Magnetic Resonance     Hybrid Journal   (Followers: 3)
Applied Nanoscience     Open Access   (Followers: 8)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 7)
Applied Physics Research     Open Access   (Followers: 6)
Applied Sciences     Open Access   (Followers: 2)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 2)
Arabian Journal for Science and Engineering     Hybrid Journal   (Followers: 4)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
Archives of Foundry Engineering     Open Access  
Archives of Thermodynamics     Open Access   (Followers: 4)
Arkiv för Matematik     Hybrid Journal  
ASEE Prism     Full-text available via subscription   (Followers: 1)
Asian Journal of Applied Science and Engineering     Open Access  
Asian Journal of Applied Sciences     Open Access   (Followers: 3)
Asian Journal of Biotechnology     Open Access   (Followers: 3)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Current Engineering & Maths     Open Access  
Asian Journal of Technology Innovation     Hybrid Journal   (Followers: 8)
Assembly Automation     Hybrid Journal   (Followers: 1)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 2)
ATZagenda     Hybrid Journal  
ATZextra worldwide     Hybrid Journal   (Followers: 1)
Australasian Physical & Engineering Sciences in Medicine     Hybrid Journal   (Followers: 1)
Australian Journal of Multi-Disciplinary Engineering     Full-text available via subscription   (Followers: 1)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 5)
Avances en Ciencias e Ingeniería     Open Access  
Bangladesh Journal of Scientific and Industrial Research     Open Access  
Basin Research     Hybrid Journal   (Followers: 2)
Batteries     Open Access   (Followers: 1)
Bautechnik     Hybrid Journal   (Followers: 1)
Bell Labs Technical Journal     Hybrid Journal   (Followers: 9)
Beni-Suef University Journal of Basic and Applied Sciences     Open Access   (Followers: 3)
BER : Manufacturing Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Motor Trade Survey     Full-text available via subscription   (Followers: 1)
BER : Retail Sector Survey     Full-text available via subscription   (Followers: 2)
BER : Retail Survey : Full Survey     Full-text available via subscription   (Followers: 2)
BER : Survey of Business Conditions in Manufacturing : An Executive Summary     Full-text available via subscription   (Followers: 3)

        1 2 3 4 5 6 7 8 | Last

Journal Cover   Autonomous Mental Development, IEEE Transactions on
  [5 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1943-0604
   Published by Institute of Electrical and Electronics Engineers (IEEE) Homepage  [176 journals]
  • IEEE Transactions on Autonomous Mental Development information for authors
    • Abstract: These instructions give guidelines for preparing papers for this publication. Presents information for authors publishing in this journal.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • IEEE Computational Intelligence Society Information
    • Abstract: Provides a listing of board members, committee members and society officers.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • Table of Contents
    • Abstract: Presents the table of contents for this issue of the publication.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • IEEE Transactions on Autonomous Mental Development publication information
    • Abstract: Provides a listing of the editors, board members, and current staff for this issue of the publication.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • Sparsity-Constrained fMRI Decoding of Visual Saliency in Naturalistic
           Video Streams
    • Authors: Xintao Hu;Cheng Lv;Gong Cheng;Jinglei Lv;Lei Guo;Junwei Han;Tianming Liu;
      Pages: 65 - 75
      Abstract: Naturalistic stimuli such as video watching have been increasingly used in functional magnetic resonance imaging (fMRI)-based brain encoding and decoding studies since they can provide real and dynamic information that the human brain has to process in everyday life. In this paper, we propose a sparsity-constrained decoding model to explore whether bottom-up visual saliency in continuous video streams can be effectively decoded by brain activity recorded by fMRI, and to examine whether sparsity constraints can improve visual saliency decoding. Specifically, we use a biologically-plausible computational model to quantify the visual saliency in video streams, and adopt a sparse representation algorithm to learn the atomic fMRI signal dictionaries that are representative of the patterns of whole-brain fMRI signals. Sparse representation also links the learned atomic dictionary with the quantified video saliency. Experimental results show that the temporal visual saliency in video stream can be well decoded and the sparse constraints can improve the performance of fMRI decoding models.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • Motor-Primed Visual Attention for Humanoid Robots
    • Authors: Lukic; L.;Billard, A.;Santos-Victor, J.;
      Pages: 76 - 91
      Abstract: We present a novel, biologically inspired, approach to an efficient allocation of visual resources for humanoid robots in a form of a motor-primed visual attentional landscape. The attentional landscape is a more general, dynamic and a more complex concept of an arrangement of spatial attention than the popular “attentional spotlight” or “zoom-lens” models of attention. Motor-priming of attention is a mechanism for prioritizing visual processing to motor-relevant parts of the visual field, in contrast to other, motor-irrelevant, parts. In particular, we present two techniques for constructing a visual “attentional landscape”. The first, more general, technique, is to devote visual attention to the reachable space of a robot (peripersonal space-primed attention). The second, more specialized, technique is to allocate visual attention with respect to motor plans of the robot (motor plans-primed attention). Hence, in our model, visual attention is not exclusively defined in terms of visual saliency in color, texture or intensity cues, it is rather modulated by motor information. This computational model is inspired by recent findings in visual neuroscience and psychology. In addition to two approaches to constructing the attentional landscape, we present two methods for using the attentional landscape for driving visual processing. We show that motor-priming of visual attention can be used to very efficiently distribute limited computational resources devoted to the visual processing. The proposed model is validated in a series of experiments conducted with the iCub robot, both using the simulator and the real robot.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • A Probabilistic Concept Web on a Humanoid Robot
    • Authors: Celikkanat; H.;Orhan, G.;Kalkan, S.;
      Pages: 92 - 106
      Abstract: It is now widely accepted that concepts and conceptualization are key elements towards achieving cognition on a humanoid robot. An important problem on this path is the grounded representation of individual concepts and the relationships between them. In this article, we propose a probabilistic method based on Markov Random Fields to model a concept web on a humanoid robot where individual concepts and the relations between them are captured. In this web, each individual concept is represented using a prototype-based conceptualization method that we proposed in our earlier work. Relations between concepts are linked to the cooccurrences of concepts in interactions. By conveying input from perception, action, and language, the concept web forms rich, structured, grounded information about objects, their affordances, words, etc. We demonstrate that, given an interaction, a word, or the perceptual information from an object, the corresponding concepts in the web are activated, much the same way as they are in humans. Moreover, we show that the robot can use these activations in its concept web for several tasks to disambiguate its understanding of the scene.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • Action Priors for Learning Domain Invariances
    • Authors: Rosman; B.;Ramamoorthy, S.;
      Pages: 107 - 118
      Abstract: An agent tasked with solving a number of different decision making problems in similar environments has an opportunity to learn over a longer timescale than each individual task. Through examining solutions to different tasks, it can uncover behavioral invariances in the domain, by identifying actions to be prioritized in local contexts, invariant to task details. This information has the effect of greatly increasing the speed of solving new problems. We formalise this notion as action priors, defined as distributions over the action space, conditioned on environment state, and show how these can be learnt from a set of value functions. We apply action priors in the setting of reinforcement learning, to bias action selection during exploration. Aggressive use of action priors performs context based pruning of the available actions, thus reducing the complexity of lookahead during search. We additionally define action priors over observation features, rather than states, which provides further flexibility and generalizability, with the additional benefit of enabling feature selection. Action priors are demonstrated in experiments in a simulated factory environment and a large random graph domain, and show significant speed ups in learning new tasks. Furthermore, we argue that this mechanism is cognitively plausible, and is compatible with findings from cognitive psychology.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • Staged Development of Robot Skills: Behavior Formation, Affordance
           Learning and Imitation with Motionese
    • Authors: Ugur; E.;Nagai, Y.;Sahin, E.;Oztop, E.;
      Pages: 119 - 139
      Abstract: Inspired by infant development, we propose a three staged developmental framework for an anthropomorphic robot manipulator. In the first stage, the robot is initialized with a basic reach-and- enclose-on-contact movement capability, and discovers a set of behavior primitives by exploring its movement parameter space. In the next stage, the robot exercises the discovered behaviors on different objects, and learns the caused effects; effectively building a library of affordances and associated predictors. Finally, in the third stage, the learned structures and predictors are used to bootstrap complex imitation and action learning with the help of a cooperative tutor. The main contribution of this paper is the realization of an integrated developmental system where the structures emerging from the sensorimotor experience of an interacting real robot are used as the sole building blocks of the subsequent stages that generate increasingly more complex cognitive capabilities. The proposed framework includes a number of common features with infant sensorimotor development. Furthermore, the findings obtained from the self-exploration and motionese guided human-robot interaction experiments allow us to reason about the underlying mechanisms of simple-to-complex sensorimotor skill progression in human infants.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • Structural Bootstrapping—A Novel, Generative Mechanism for Faster
           and More Efficient Acquisition of Action-Knowledge
    • Authors: Worgotter; F.;Geib, C.;Tamosiunaite, M.;Aksoy, E.E.;Piater, J.;Hanchen Xiong;Ude, A.;Nemec, B.;Kraft, D.;Kruger, N.;Wachter, M.;Asfour, T.;
      Pages: 140 - 154
      Abstract: Humans, but also robots, learn to improve their behavior. Without existing knowledge, learning either needs to be explorative and, thus, slow or-to be more efficient-it needs to rely on supervision, which may not always be available. However, once some knowledge base exists an agent can make use of it to improve learning efficiency and speed. This happens for our children at the age of around three when they very quickly begin to assimilate new information by making guided guesses how this fits to their prior knowledge. This is a very efficient generative learning mechanism in the sense that the existing knowledge is generalized into as-yet unexplored, novel domains. So far generative learning has not been employed for robots and robot learning remains to be a slow and tedious process. The goal of the current study is to devise for the first time a general framework for a generative process that will improve learning and which can be applied at all different levels of the robot's cognitive architecture. To this end, we introduce the concept of structural bootstrapping-borrowed and modified from child language acquisition-to define a probabilistic process that uses existing knowledge together with new observations to supplement our robot's data-base with missing information about planning-, object-, as well as, action-relevant entities. In a kitchen scenario, we use the example of making batter by pouring and mixing two components and show that the agent can efficiently acquire new knowledge about planning operators, objects as well as required motor pattern for stirring by structural bootstrapping. Some benchmarks are shown, too, that demonstrate how structural bootstrapping improves performance.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • Imagine a community hopeful for the future
    • Pages: 155 - 155
      Abstract: Advertisement, IEEE.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
  • Imagine a teenager excited about technology
    • Pages: 156 - 156
      Abstract: Advertisement, IEEE.
      PubDate: June 2015
      Issue No: Vol. 7, No. 2 (2015)
       
 
 
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