Next generation keyboards: The importance of cognitive compatibility

The computer keyboard of today is essentially the same as it has been for many years. Few advances have been made in keyboard design even though computer systems in general have made remarkable progress in improvements. This paper discusses the future of keyboards, their competition and compatibility with voice input systems, and possible special-application intelligent keyboards for controlling complex systems

Mathematical control of complex systems 2013

Mathematical control of complex systems have already become an ideal research area for control engineers, mathematicians, computer scientists, and biologists to understand, manage, analyze, and interpret functional information/dynamical behaviours from real-world complex dynamical systems, such as communication systems, process control, environmental systems, intelligent manufacturing systems, transportation systems, and structural systems. This special issue aims to bring together the latest/innovative knowledge and advances in mathematics for handling complex systems. Topics include, but are not limited to the following: control systems theory (behavioural systems, networked control systems, delay systems, distributed systems, infinite-dimensional systems, and positive systems); networked control (channel capacity constraints, control over communication networks, distributed filtering and control, information theory and control, and sensor networks); and stochastic systems (nonlinear filtering, nonparametric methods, particle filtering, partial identification, stochastic control, stochastic realization, system identification)

Advances in Intelligent Vehicle Control

This book is a printed edition of the Special Issue Advances in Intelligent Vehicle Control that was published in the journal Sensors. It presents a collection of eleven papers that covers a range of topics, such as the development of intelligent control algorithms for active safety systems, smart sensors, and intelligent and efficient driving. The contributions presented in these papers can serve as useful tools for researchers who are interested in new vehicle technology and in the improvement of vehicle control systems

Parametric identification of the dynamics of inter-sectoral balance: modelling and forecasting

This work is devoted to modelling and identification of the dynamics of the inter-sectoral balance of a macroeconomic system. An approach to the problem of specification and identification of a weakly formalized dynamical system is developed. A matching procedure for parameters of a linear stationary Cauchy problem with a decomposition of its upshot trend and a periodic component, is proposed. Moreover, an approach for detection of significant harmonic waves, which are inherent to real macroeconomic dynamical systems, is developed.Comment: This is a preprint of a paper accepted for publication 29-March-2019 as a book chapter in 'Advances in Intelligent Systems and Computing' [https://www.springer.com/series/11156], Springe

Mobile Agents for Mobile Tourists: A User Evaluation of Gulliver's Genie

How mobile computing applications and services may be best designed, implemented and deployed remains the subject of much research. One alternative approach to developing software for mobile users that is receiving increasing attention from the research community is that of one based on intelligent agents. Recent advances in mobile computing technology have made such an approach feasible. We present an overview of the design and implementation of an archetypical mobile computing application, namely that of an electronic tourist guide. This guide is unique in that it comprises a suite of intelligent agents that conform to the strong intentional stance. However, the focus of this paper is primarily concerned with the results of detailed user evaluations conducted on this system. Within the literature, comprehensive evaluations of mobile context-sensitive systems are sparse and therefore, this paper seeks, in part, to address this deficiency

A Large-scale Distributed Video Parsing and Evaluation Platform

Visual surveillance systems have become one of the largest data sources of Big Visual Data in real world. However, existing systems for video analysis still lack the ability to handle the problems of scalability, expansibility and error-prone, though great advances have been achieved in a number of visual recognition tasks and surveillance applications, e.g., pedestrian/vehicle detection, people/vehicle counting. Moreover, few algorithms explore the specific values/characteristics in large-scale surveillance videos. To address these problems in large-scale video analysis, we develop a scalable video parsing and evaluation platform through combining some advanced techniques for Big Data processing, including Spark Streaming, Kafka and Hadoop Distributed Filesystem (HDFS). Also, a Web User Interface is designed in the system, to collect users' degrees of satisfaction on the recognition tasks so as to evaluate the performance of the whole system. Furthermore, the highly extensible platform running on the long-term surveillance videos makes it possible to develop more intelligent incremental algorithms to enhance the performance of various visual recognition tasks.Comment: Accepted by Chinese Conference on Intelligent Visual Surveillance 201

RETRACTED: RCE-Kmeans Method for Data Clustering

RETRACTEDFollowing a rigorous, carefully concerns and considered review of the article published in International Journal of Advances in Intelligent Informatics to article entitled “RCE-Kmeans Method for Data Clustering” Vol 1, No 2, pp. 107-114, July 2015, DOI: http://dx.doi.org/10.26555/ijain.v1i2.38.This paper has been found to be in violation of the International Journal of Advances in Intelligent Informatics Publication principles and has been retracted.The article contained redundant material, the editor investigated and found that the paper published in Indonesian Journal of Computing and Cybernetics Systems, Vol. 9, No. 2 (July 2015), pp. 157-166, DOI: http://doi.org/10.22146/ijccs.7544, entitled "Metode RCE-Kmeans untuk Clustering Data".The document and its content has been removed from International Journal of Advances in Intelligent Informatics, and reasonable effort should be made to remove all references to this article