ICAS 2019 || June 2 – 6, 2019 – Athens, Greece

October 8th, 2018 Daniela Lopez de Luise

Please consider to contribute to and/or forward to the appropriate groups the following opportunity to submit and publish original scientific results to:

– ICAS 2019, The Fifteenth International Conference on Autonomic and Autonomous Systems

The submission deadline is January 20, 2019.

Proceedings will be submitted for indexing in Web of Science (WoS) (ISI Thompson Reuters) by Filodiritto/InFOROmatica Publisher, Italy

Note that ICAS 2017 has been indexed in Web of Science, ICAS 2018 has been submitted for indexing, and ICAS 2019 will also be submitted.

Authors of selected papers will be invited to submit extended article versions to one of the IARIA Journals: http://www.iariajournals.org

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============== ICAS 2019 | Call for Papers ===============

CALL FOR PAPERS, TUTORIALS, PANELS

ICAS 2019, The Fifteenth International Conference on Autonomic and Autonomous Systems

General page: http://www.iaria.org/conferences2019/ICAS19.html

Submission page: http://www.iaria.org/conferences2019/SubmitICAS19.html

Event schedule: June 2 – 6, 2019 – Athens, Greece

Contributions:

– regular papers [in the proceedings, digital library]

– short papers (work in progress) [in the proceedings, digital library]

– ideas: two pages [in the proceedings, digital library]

– extended abstracts: two pages [in the proceedings, digital library]

– posters: two pages [in the proceedings, digital library]

– posters:  slide only [slide-deck posted at www.iaria.org]

– presentations: slide only [slide-deck posted at www.iaria.org]

– demos: two pages [posted at www.iaria.org]

– doctoral forum submissions: [in the proceedings, digital library]

Proposals for:

– mini symposia: see http://www.iaria.org/symposium.html

– workshops: see http://www.iaria.org/workshop.html

– tutorials:  [slide-deck posed on www.iaria.org]

– panels: [slide-deck posed on www.iaria.org]

Submission deadline: January 20, 2019

Sponsored by IARIA, www.iaria.org

Extended versions of selected papers will be published in IARIA Journals:  http://www.iariajournals.org

Print proceedings will be available via Curran Associates, Inc.: http://www.proceedings.com/9769.html

Articles will be archived in the free access ThinkMind Digital Library: http://www.thinkmind.org

The topics suggested by the conference can be discussed in term of concepts, state of the art, research, standards, implementations, running experiments, applications, and industrial case studies. Authors are invited to submit complete unpublished papers, which are not under review in any other conference or journal in the following, but not limited to, topic areas.

All tracks are open to both research and industry contributions, in terms of Regular papers, Posters, Work in progress, Technical/marketing/business presentations, Demos, Tutorials, and Panels.

Before submission, please check and comply with the editorial rules: http://www.iaria.org/editorialrules.html

ICAS 2019 Topics (for topics and submission details: see CfP on the site)

Call for Papers: http://www.iaria.org/conferences2019/CfPICAS19.html

============================================================

SELFTRENDS: Toward brain-like autonomic and autonomous systems

Adaptive robust resource allocation; Optimal self-organized collective actions; Collective adaptation; Active learning;  Opportunistic collaborative interactive learning; Adaption fairness; Social and biometric data-aware adaptation; Brain connectivity models;  Using unbalanced Datasets;  Quantum-inspired optimization; Automated (industrial) assembly environments; Deep neural networks; Multimodal knowledge of the brain; Self-organization in M2M infrastructures; Self-organizing socio-technical systems; Context-aware data self-adaptation; Multi-level loop encapsulation in smart systems; Uncertainty in self-adaptive systems; Adaptive Software defined systems (SDS) scalability; Adaptability in multi-tenant Clouds; Self-aware model-driven systems; Proactive self-adaptation; Self-adaptive urban traffic; Adaptive power profiling; Run-time for self-adaptive systems; Distributed adaptive systems; Self-improving system integration; Self-improving activity recognition systems; Feedback computing; Optimal feedback control; Dynamic adaptive applications; Self-managing Clouds;  Decentralized autonomic behavior; Market-adaptive trust;  Semantics of self-behavior;  Self-organizing patterns; Stability propagation in self-organizing systems; Inconsistency in self-deciding systems; Reasoning problems tractability; Decidability in self-organizing systems

ROBOTRENDS: Robot-related trends

Autonomous aquatic agents; Aerial autonomous robots; Drones control and management; Knowledge-based robot motions; Autonomous mobile robot interaction; Humanoid robots; Intelligent robots; Self-reconfigurable mobile robots; Humanoid imitative learning; Robots in unknown environments; Human centric robots; Adjustable robust optimizations; Moral autonomous agents and human evolution; Cognitive robotics; Robot partnership; Affective communication robots; Human-centric robotics; Visually-impaired and robots; Evolutionary swarm robotics; Robots and human advices; Universal robot hands

SYSAT: Advances in system automation

Methods, techniques ant tools for automation features; Methodologies for automating of design systems; Industrial automation for production chains; Nonlinear optimization and automation control; Nonlinearities and system stabilization; Automation in safety systems; Structured uncertainty; Open and closed automation loops; Test systems automation; Theory on systems robustness; Fault-tolerant systems

UNMANNED: Driver-less cars and unmanned vehicles

Self-driving cars; Drones; Terrestrial unmanned vehicles; Unmanned aerial vehicles; Underwater unmanned vehicles; Unmanned sea surface vehicles; Collision control; Traffic surveillance challenges; Path planning and estimation; Communication between unmanned vehicles; Integration of unmanned aerial vehicles in civil airspace; Unmanned vehicular clusters; Designing unmanned vehicular-based systems; Safety of unmanned vehicles; Commercial and surveillance applications; Emergency applications; Legal aspects of unmanned vehicular systems; Testbeds and pilot experiments

AUTSY: Theory and Practice of Autonomous Systems

Design, implementation and deployment of autonomous systems; Frameworks and architectures for component and system autonomy; Design methodologies for autonomous systems; Composing autonomous systems; Formalisms and languages for autonomous systems; Logics and paradigms for autonomous systems; Ambient and real-time paradigms for autonomous systems; Delegation and trust in autonomous systems; Centralized and distributed autonomous systems; Collocation and interaction between autonomous and non-autonomous systems; Dependability in autonomous systems; Survivability and recovery in autonomous systems; Monitoring and control in autonomous systems; Performance and security in autonomous systems; Management of autonomous systems; Testing autonomous systems; Maintainability of autonomous systems

AWARE: Design and Deployment of Context-awareness Networks, Services and Applications

Context-aware fundamental concepts, mechanisms, and applications; Modeling context-aware systems; Specification and implementation of awareness behavioral contexts; Development and deployment of large-scale context-aware systems and subsystems; User awareness requirements and design techniques for interfaces and systems; Methodologies, metrics, tools, and experiments for specifying context-aware systems; Tools evaluations, Experiment evaluations

AUTONOMIC: Autonomic Computing: Design and Management of Self-behavioral Networks and Services

Theory, architectures, frameworks and practice of self-adaptive management mechanisms; Modeling and techniques for specifying self-ilities; Self-stabilization and dynamic stability criteria and mechanisms; Tools, languages and platforms for designing self-driven systems; Autonomic computing and GRID networking; Autonomic computing and proactive computing for autonomous systems; Practices, criteria and methods to implement, test, and evaluate industrial autonomic systems; Experiences with autonomic computing systems

CLOUD: Cloud computing and Virtualization

Hardware-as-a-service; Software-as-a-service [SaaS applicaitions]; Platform-as-service; On-demand computing models; Cloud Computing programming and application development; Scalability, discovery of services and data in Cloud computing infrastructures; Privacy, security, ownership and reliability issues; Performance and QoS; Dynamic resource provisioning; Power-efficiency and Cloud computing; Load balancing; Application streaming; Cloud SLAs, business models and pricing policies; Custom platforms; Large-scale compute infrastructures; Managing applications in the clouds; Data centers; Process in the clouds; Content and service distribution in Cloud computing infrastructures; Multiple applications can run on one computer (virtualization a la VMWare); Grid computing (multiple computers can be used to run one application); Virtualization platforms; Open virtualization format; Cloud-computing vendor governance and regulatory compliance

MCMAC: Monitoring, Control, and Management of Autonomous Self-aware and Context-aware Systems

Agent-based autonomous systems; Policy-driven self-awareness mechanisms and their applicability in autonomic systems; Autonomy in GRID networking and utility computing; Studies on autonomous industrial applications, services, and their developing environment; Prototypes, experimental systems, tools for autonomous systems, GRID middleware

CASES: Automation in specialized mobile environments

Theory, frameworks, mechanisms and case studies for satellite systems; Spatial/temporal constraints in satellites systems; Trajectory corrections, speed, and path accuracy in satellite systems; Mechanisms and case studies for nomadic code systems; Platforms for mobile agents and active mobile code; Performance in nomadic code systems; Case studies systems for mobile robot systems; Guidance in an a priori unknown environment; Coaching/learning techniques; Pose maintenance, and mapping; Sensing for autonomous vehicles; Planning for autonomous vehicles; Mobile networks, Ad hoc networks and self-reconfigurable networks

ALCOC: Algorithms and theory for control and computation

Control theory and specific characteristics; Types of computation theories; Tools for computation and control; Algorithms and data structures; Special algorithmic techniques; Algorithmic applications; Domain case studies; Technologies case studies for computation and control; Application-aware networking

MODEL: Modeling, virtualization, any-on-demand, MDA, SOA

Modeling techniques, tools, methodologies, languages; Model-driven architectures (MDA); Service-oriented architectures (SOA); Utility computing frameworks and fundamentals; Enabled applications through virtualization; Small-scale virtualization methodologies and techniques; Resource containers, physical resource multiplexing, and segmentation; Large-scale virtualization methodologies and techniques; Management of virtualized systems; Platforms, tools, environments, and case studies; Making virtualization real; On-demand utilities; Adaptive enterprise; Managing utility-based systems; Development environments, tools, prototypes

SELF: Self-adaptability and self-management of context-aware systems

Novel approaches to modeling and representing context adaptability, self-adaptability, and self-manageability; Models of computation for self-management context-aware systems; Use of MDA/MDD (Model Driven Architecture / Model Driven Development) for context-aware systems; Design methods for self-adaptable context-aware systems; Applications of advanced modeling languages to context self-adaptability; Methods for managing adding context to existing systems and context-conflict free systems; Architectures and middleware models for self-adaptable context-aware systems; Models of different adaptation and self-adaptation mechanisms (component-based adaptation approach, aspect oriented approach, etc.); System stability in the presence of context inconsistency; Learning and self-adaptability of context-aware systems; Business considerations and organizational modeling of self-adaptable context-aware systems; Performance evaluation of self-adaptable context-aware systems; Scalability of self-adaptable context-aware systems 

KUI: Knowledge-based user interface

Evolving intelligent user interface for WWW; User interface design in autonomic systems; Adaptive interfaces in a knowledge-based design; Knowledge-based support for the user interface design process; Built-in knowledge in adaptive user interfaces; Requirements for interface knowledge representation; Levels for knowledge-based user interface; User interface knowledge on the dynamic behavior; Support techniques for knowledge-based user interfaces; Intelligent user interface for real-time systems; Planning-based control of interface animation; Model-based user interface design; Knowledge-based user interface migration; Automated user interface requirements discovery for scientific computing; Knowledge-based user interface management systems; 3D User interface design; Task-oriented knowledge user interfaces; User-interfaces in a domestic environment; Centralised control in the home; User-interfaces for the elderly or disabled; User-interfaces for the visually, aurally, or mobility impaired; Interfacing with ambient intelligence systems; Assisted living interfaces; Interfaces for security/alarm systems

AMMO: Adaptive management and mobility

QoE and adaptation in mobile environments; Content marking and management (i.e. MPEG21); Adaptive coding (H.265, FEC schemes, etc.. ); Admission control resource allocation algorithms; Monitoring and feedback systems; Link adaptation mechanisms; Cross layer approaches; Adaptation protocols (with IMS and NGNs scenarios); QoE vs NQoS mapping systems; Congestion control mechanisms; Fairness issues (fair sharing, bandwidth allocation…); Optimization/management mechanisms (MOO, fuzzy logic, machine learning, etc.)

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ICAS 2019 Committee: http://www.iaria.org/conferences2019/ComICAS19.html

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International Journal of Wireless & Mobile Networks (IJWMN)

October 4th, 2018 Daniela Lopez de Luise

International Journal of Wireless & Mobile Networks (IJWMN)

 

ISSN: 0975-3834 [Online]; 0975-4679 [Print]

 

http://airccse.org/journal/ijwmn.html

 

 

 

Scope & Topics

 

The International Journal of Wireless & Mobile Networks (IJWMN) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Wireless & Mobile Networks. The journal focuses on all technical and practical aspects of Wireless & Mobile Networks. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on advanced wireless & mobile networking concepts and establishing new collaborations in these areas.

 

Authors are solicited to contribute to this journal by submitting articles that illustrate research results,

projects, surveying works and industrial experiences that describe significant advances in Wireless and Mobile Networks.

 

Topics of interest include, but are not limited to, the following

 

  • Architectures, protocols, and algorithms to cope with mobile & wireless Networks
  • Distributed algorithms of mobile computing
  • OS and middleware support for mobile computing and networking
  • Routing, and communication primitives in ad-hoc and sensor networks
  • Synchronization and scheduling issues in mobile and ad hoc networks
  • Resource management in mobile, wireless and ad-hoc networks
  • Data management on mobile and wireless computing
  • Integration of wired and wireless networks
  • Broadband access networks
  • Energy saving protocols for ad hoc and sensor networks
  • Complexity analysis of algorithms for mobile environments
  • Information access in wireless networks
  • Algorithms and modeling for tracking and locating mobile users
  • Satellite communications
  • Cryptography, security and privacy of mobile & wireless networks
  • Performance of mobile and wireless networks and systems
  • Mobile ad hoc and sensor networks
  • Wireless multimedia systems
  • Service creation and management environments for mobile/wireless systems

Paper submission

 

Authors are invited to submit papers for this journal through e-mail ijwmn@airccse.org. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this Journal.

 

Important Dates

  • Submission Deadline       : October 13, 2018
  • Acceptance Notification  : November 13, 2018
  • Final Manuscript Due      : November 21, 2018
  • Publication Date              : Determined by the Editor-in-Chief

                        

 

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ELM2018: Information on Keynotes and Tutorial

October 4th, 2018 Daniela Lopez de Luise

 

The 9th International Conference on Extreme Learning Machines (ELM2018)

Marina Bay Sands, Singapore, November 21 – 23, 2018

 

Organized by: Nanyang Technological University, Singapore

Co-organized by: Tsinghua University, China; Shanghai Jiaotong University, China; University of New South Wales, Australia; City University of Hong Kong

 

Registration Link: http://elm2018.extreme-learning-machines.org

 

Confirmed Keynotes:

Evangelos S Eleftheriou, IBM Zurich Research Laboratory, Switzerland, “In-memory Computing: Accelerating AI Applications”

Guang-Bin Huang, Nanyang Technological University, Singapore, “Hierarchical ELM for Big Data Analysis”

Amir Hussain, University of Stirling, UK, “Clustering with ELM” (TBC)

Zhiping Lin, Nanyang Technological University, Singapore, “Sequential Extreme Learning Machines for Class Imbalance and Concept Drift”

Hongbin Ma, Beijing Institute of Technology, China, “Fusion of Adaptive Control, Artificial Intelligence and Computational Geometry – How Extreme Learning Machines (ELM) Improve Control Performance”

Zhihong Man, Swinburne University of Technology, Australia, “A New Intelligent Pattern Classifier Based on Deep-Thinking”

Sigeru Omatu, Osaka Institute of Technology, Japan, “Smell Classification of Human Body by Learning Vector Quantization”

David E. Stewart, University of Iowa, USA, “ELMVIS+ and GradSwaps for Visualizing Complex Datasets”

Kay Chen Tan, City University of Hong Kong, Hong Kong, title to be confirmed

Jonathan Wu, University of Windsor, Canada, “Complex Action Recognition in Constrained and Unconstrained Videos”

Tutorial:

“Tutorial on Deep Learning and Extreme Learning Machines (ELM),” Gao Huang, Tsinghua University, China, (Author of well-known deep learning network: DenseNet, influential papers on Unsupervised ELM and tutorial on ELM)

 

 

Extreme Learning Machines (ELM) aims to enable pervasive learning and pervasive intelligence. As advocated by ELM theories, it is exciting to see the convergence of machine learning and biological learning from the long-term point of view. ELM may be one of the fundamental `learning particles’ filling the gaps between machine learning and biological learning (of which activation functions are even unknown). ELM  represents a suite of (machine and biological) learning techniques in which hidden neurons need not be tuned: inherited from their ancestors or randomly generated. ELM learning theories show that effective learning algorithms can be derived based on randomly generated hidden neurons (biological neurons, artificial neurons, wavelets, Fourier series, etc) as long as they are nonlinear piecewise continuous, independent of training data and application environments. Increasingly, evidence from neuroscience suggests that similar principles apply in biological learning systems. ELM theories and algorithms argue that “random hidden neurons” capture an essential aspect of biological learning mechanisms as well as the intuitive sense that the efficiency of biological learning need not rely on computing power of neurons. ELM theories thus hint at possible reasons why the brain is more intelligent and effective than current computers.

 

The main theme of ELM2018 is: Hierarchical ELM, AI for IoT, Synergy of Machine Learning and Biological Learning

 

Organized by Nanyang Technological University, Singapore, and co‐organized by Tsinghua University, Shanghai Jiaotong University, China, University of New South Wales, Australia and City University of Hong Kong, ELM2018 will be held in Singapore. This conference will provide a forum for academics, researchers and engineers to share and exchange R&D experience on both theoretical studies and practical applications of the ELM technique and biological learning.

 

Tutorial proposals:

All interesting topics on general artificial intelligence and machine learning techniques are welcome, which include but not limited to: deep learning, hierarchical learning, reinforcement learning, sparse coding, clustering, extreme learning machines, etc.

 

Accepted papers presented in this conference will be published in conference proceedings and selected papers will be recommended to reputable ISI indexed international journals:  Cognitive Computation, International Journal of Machine Learning and Cybernetics, Memetic Computing, Machine Learning and Knowledge Extraction, Neural Computing and Applications, etc.

 

Topics of interest:

All the submissions must be related to ELM technique.  Topics of interest include but are not limited to:

Theories

•         Universal approximation, classification and convergence, robustness and stability analysis

•         Biological learning mechanism and neuroscience

•         Machine learning science and data science

Algorithms

•         Real-time learning, reasoning and cognition

•         Sequential/incremental learning and kernel learning

•         Clustering and feature extraction/selection/learning

•         Random projection, dimensionality reduction, and matrix factorization

•         Closed form and non-closed form solutions

•         Hierarchical solutions, and combination of deep learning and ELM

•         Parallel and distributed computing / cloud computing

Applications

•         AI in IoT (Internet of Things)

•         Financial data analysis

•         Smart grid and renewable energy systems

•         Biometrics and bioinformatics, security and compression

•         Human computer interface and brain computer interface

•         Cognitive science/computation

•         Sentic computing, natural language processing and speech processing

•         Big data analytics

Hardware

•         Lower power, low latency hardware / chips

•         Artificial biological alike neurons / synapses

 

Paper submission:

Manuscripts can be submitted via http://elm2018.extreme-learning-machines.org.

 

Important dates:

Paper submission deadline:    July 1, 2018 July 31, 2018

Notification of acceptance:     August 1, 2018 August 15, 2018

Registration deadline:              September 1, 2018 September 30, 2018

 

pdf icon ELM2018-3rd.pdf
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MACI 2019

October 3rd, 2018 Daniela Lopez de Luise
pdf icon VII-MACI-2019-Primer-Anuncio-.pdf
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Elixir International Journal

October 1st, 2018 Daniela Lopez de Luise
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