554,195 research outputs found
Machine learning paradigms for modeling spatial and temporal information in multimedia data mining
Multimedia data mining and knowledge discovery is a fast emerging interdisciplinary applied research area. There is tremendous potential for effective use of multimedia data mining (MDM) through intelligent analysis. Diverse application areas are increasingly relying on multimedia under-standing systems. Advances in multimedia understanding are related directly to advances in signal processing, computer vision, machine learning, pattern recognition, multimedia databases, and smart sensors. The main mission of this special issue is to identify state-of-the-art machine learning paradigms that are particularly powerful and effective for modeling and combining temporal and spatial media cues such as audio, visual, and face information and for accomplishing tasks of multimedia data mining and knowledge discovery. These models should be able to bridge the gap between low-level audiovisual features which require signal processing and high-level semantics. A number of papers have been submitted to the special issue in the areas of imaging, artificial intelligence; and pattern recognition and five contributions have been selected covering state-of-the-art algorithms and advanced related topics. The first contribution by D. Xiang et al. “Evaluation of data quality and drought monitoring capability of FY-3A MERSI data” describes some basic parameters and major technical indicators of the FY-3A, and evaluates data quality and drought monitoring capability of the Medium-Resolution Imager (MERSI) onboard the FY-3A. The second contribution by A. Belatreche et al. “Computing with biologically inspired neural oscillators: application to color image segmentation” investigates the computing capabilities and potential applications of neural oscillators, a biologically inspired neural model, to gray scale and color image segmentation, an important task in image understanding and object recognition. The major contribution of this paper is the ability to use neural oscillators as a learning scheme for solving real world engineering problems. The third paper by A. Dargazany et al. entitled “Multibandwidth Kernel-based object tracking” explores new methods for object tracking using the mean shift (MS). A bandwidth-handling MS technique is deployed in which the tracker reach the global mode of the density function not requiring a specific staring point. It has been proven via experiments that the Gradual Multibandwidth Mean Shift tracking algorithm can converge faster than the conventional kernel-based object tracking (known as the mean shift). The fourth contribution by S. Alzu’bi et al. entitled “3D medical volume segmentation using hybrid multi-resolution statistical approaches” studies new 3D volume segmentation using multiresolution statistical approaches based on discrete wavelet transform and hidden Markov models. This system commonly reduced the percentage error achieved using the traditional 2D segmentation techniques by several percent. Furthermore, a contribution by G. Cabanes et al. entitled “Unsupervised topographic learning for spatiotemporal data mining” proposes a new unsupervised algorithm, suitable for the analysis of noisy spatiotemporal Radio Frequency Identification (RFID) data. The new unsupervised algorithm depicted in this article is an efficient data mining tool for behavioral studies based on RFID technology. It has the ability to discover and compare stable patterns in a RFID signal, and is appropriate for continuous learning. Finally, we would like to thank all those who helped to make this special issue possible, especially the authors and the reviewers of the articles. Our thanks go to the Hindawi staff and personnel, the journal Manager in bringing about the issue and giving us the opportunity to edit this special issue
INTRODUCTION
This special issue of the Journal of Energy is dedicated to the establishment of today
the Department for Energy and Power Systems (ZVNE), University of Zagreb Faculty
of Electrical Engineering and Computing in 1934. in that time the High Voltage
Department as part of the Technical Faculty. For this reason, the history of the Department
for Energy and Power Systems is presented in the introductory article, while the
other articles are part of a broad scientific and professional work of the employees of the
Department and some of the articles were created in wide cooperation with experts from the
companies, that graduated from the Department.
Journal of Energy special issue: present 17 papers selected for publication in Journal of
Energy after having undergone the peer review process. We would like to thank the authors
for their contributions and the reviewers who dedicated their valuable time in selecting and
reviewing these papers. We hope this special issue will provide you valuable information of
some achievements at Department of Energy and Power Systems, Faculty of Electrical Engineering
and Computing.
Short introduction of scientific and expert work of the Department for Energy and Power
Systems (ZVNE):
Besides educational energy related programmes for undergraduate, graduate and postgraduate
students, DEPARTMENT OF ENERGY AND POWER SYSTEMS has been actively involved
for many years in many scientific and expert studies. Studies on scientific projects include
collaboration with industry, national institutions, electric utilities, and many foreign universities.
The Department has developed valuable international cooperation with many research institutions
around the world, either directly or through inter-university cooperation.
The Department is the leading institution in the field of electrical power engineering in the
region, it has a long lasting cooperation with the economic sector, and it is recognized for
its scientific activities and a large number of published scientific papers in globally relevant
journals, as well as numerous national and international scientific projects.
Main Department areas of activities are:
a) Power Engineering and Power Technologies,
b) Energy, Environment, Energy Management and
c) Nuclear Power Engineering
In Power Systems Engineering the research is focused to development of both fundamental
knowledge and applications of electrical power engineering. The research is generally directed
to increasing the availability and the reliability of a power system with an emphasis on the
adjustment to the open market environment. Specific goals include: improving models and
methodologies for power system analysis, operation and control; development, production
and application of models and methodologies for power systems planning, maintenance and
development; application of soft-computing (artificial intelligence, meta-heuristics, etc.), information
technologies (web-oriented technologies, geographic information systems, enterprise
IT solutions, etc.) and operational research in improving processes of planning, development,
exploitation and control of power systems; investigation on applications for coordinated control
of power system devices and exploring the power system stability, security and economic
operation; integration of intelligent devices and agents in energy management systems
and distribution management systems equipment and software; advanced modelling of
dynamics, disturbances and transient phenomena in transmission and distribution networks
(in particular regarding distributed generation); advances in fault detection, restoration and
outage management. The researches also cover high voltage engineering. At time of global
changes in the energy sector, with emphasis on sustainable development, significant efforts
are devoted to liberalization efforts, facilities revitalization, improved legislation and adoption
of new standards.
In area of Power Technologies, Energy and Environment, Energy Management the main
framework for the research are: sustainable electricity generation on a liberalized market, modelling
ETS and electricity market; energy security and climate change; power system optimization
with emission trading; rational use of energy and energy savings; energy management
in industry and buildings; energy conservation and energy auditing in industry and buildings.
General objective of the research is to develop methodologies for quantitative assessment
of the environmental impact of applicable energy technologies (electric power producing
plants and their technology chains), as a base for estimating optimal long-term development
strategy of the Croatian power system. Research work includes new strategies of energy
sector and power system development; preparing medium and long-term electricity generation
expansion plan for power system; comparison of energy, economic and environmental
characteristics of different options for electric
power generation; studies for rational use of energy and energy savings, assuming a centralized
structure of the electricity market. Research work also includes renewable energy sources
and its role in power sector, as well as electricity production considering cap on CO2 emissions.
Research covers development of new models for power system generation optimization
and planning under uncertainties on the open electricity market. The goal of that research is
to create analytical and software tools which will enable a successful transition to liberalized
electricity market and ensure healthy and efficient power system operation in compliance with
environmental requirements.
In the Nuclear Energy Field research cover nuclear physics reactor theory, nuclear power
plants. fuel cycles and reactors materials and general objective of the research is to develop
methodologies for reliable assessment of nuclear power plants operational safety. In the
nuclear energy field the specific analysis cover calculations of transients and consequences
of potential accidents in NPP Krško. In the field of safety analyses of nuclear power plants the
research activities are oriented to the mathematical modelling of nuclear power plant systems
and components
ADVANCED MATERIALS AND NANOTECHNOLOGY CLUSTER
Buildings are the largest consumer of energy demand and the largest emitter of greenhouse gases. More than the 50% of the residential buildings in Europe were built before 1970; the renovation and upgrading of the existing buildings is a priority in the EU energy policies and in all the EU member states. Increasing focus on energy conservation necessitates the adoption of innovative materials. Government regulations and support for zero energy buildings provide an impetus to the adoption of innovative materials (Directive 2010/31/EU)
AMANAC is a collaboration and coordination platform across all the Advanced Materials and Nanotechnology EU funded projects functioning in the frame of the Energy Efficiency in Buildings public Private Partnership (EeB-PPP), whose activities address development of advanced materials, components and systems for the improvement of the energy efficiency in the built environment. AMANAC is the cluster of 29 projects, representing 255 project partners, out of which 63% are Large Enterprises or SMEs. AMANAC aims to maximize the impact of the AMANAC projects towards the European Industry and Society. More information about AMANAC can be found at http://amanac.eu/
The adoption of innovative materials in building envelopes offers a great potential for future design and construction. This is why the Journal of Facade Design and Engineering dedicates this special issue to this topic. JFDE is a firm partner for the distribution of scientific knowledge of the ICAE2015 International Congress on Architectural Envelopes (www.icae2015.com/en), organised by Tecnalia in San Sebastian, Spain.
The papers presented in this current issue originate from five AMANAC research projects that researched new advanced materials and systems for energy efficient buildings. The works have been selected among the AMANAC project research results, initially presented in a special Session at the ICAE2015. The extended papers have been subjected to the regular double, blind review process of the journal
Editorial Special Issue on Enhancement Algorithms, Methodologies and Technology for Spectral Sensing
The paper is an editorial issue on enhancement algorithms, methodologies and technology for spectral sensing and serves as a valuable and useful reference for researchers and technologists interested in the evolving state-of-the-art and/or the emerging science and technology base associated with spectral-based sensing and monitoring problem. This issue is particularly relevant to those seeking new and improved solutions for detecting chemical, biological, radiological and explosive threats on the land, sea, and in the air
ARDUINO Tutor: An Intelligent Tutoring System for Training on ARDUINO
This paper aims at helping trainees to overcome the difficulties they face when dealing with Arduino platform by describing the design of a desktop based intelligent tutoring system. The main idea of this system is a systematic introduction into the concept of Arduino platform. The system shows the circuit boards of Arduino that can be purchased at low cost or assembled from freely-available plans; and an open-source development environment and library for writing code to control the board topic of Arduino platform.
The system is adaptive with the trainee’s individual progress. The system functions as a special tutor who deals with trainees according to their levels and skills. Evaluation of the system has been applied on professional and unprofessional trainees in this field and the results were good
Guest Editorial: Nonlinear Optimization of Communication Systems
Linear programming and other classical optimization techniques have found important applications in communication systems for many decades. Recently, there has been a surge in research activities that utilize the latest developments in nonlinear optimization to tackle a much wider scope of work in the analysis and design of communication systems. These activities involve every “layer” of the protocol stack and the principles of layered network architecture itself, and have made intellectual and practical impacts significantly beyond the established frameworks of optimization of communication systems in the early 1990s. These recent results are driven by new demands in the areas of communications and networking, as well as new tools emerging from optimization theory. Such tools include the powerful theories and highly efficient computational algorithms for nonlinear convex optimization, together with global solution methods and relaxation techniques for nonconvex optimization
Web Application for Generating a Standard Coordinated Documentation for CS Students’ Graduation Project in Gaza Universities
The computer science (CS) graduated students suffered from documenting their projects and specially from coordinating it. In addition, students’ supervisors faced difficulties with guiding their students to an efficient process of documenting. In this paper, we will offer a suggestion as a solution to the mentioned problems; that is an application to make the process of documenting computer science (CS) student graduation project easy and time-cost efficient. This solution will decrease the possibility of human mistakes and reduce the effort of documenting process
The Novel Approach of Adaptive Twin Probability for Genetic Algorithm
The performance of GA is measured and analyzed in terms of its performance
parameters against variations in its genetic operators and associated
parameters. Since last four decades huge numbers of researchers have been
working on the performance of GA and its enhancement. This earlier research
work on analyzing the performance of GA enforces the need to further
investigate the exploration and exploitation characteristics and observe its
impact on the behavior and overall performance of GA. This paper introduces the
novel approach of adaptive twin probability associated with the advanced twin
operator that enhances the performance of GA. The design of the advanced twin
operator is extrapolated from the twin offspring birth due to single ovulation
in natural genetic systems as mentioned in the earlier works. The twin
probability of this operator is adaptively varied based on the fitness of best
individual thereby relieving the GA user from statically defining its value.
This novel approach of adaptive twin probability is experimented and tested on
the standard benchmark optimization test functions. The experimental results
show the increased accuracy in terms of the best individual and reduced
convergence time.Comment: 7 pages, International Journal of Advanced Studies in Computer
Science and Engineering (IJASCSE), Volume 2, Special Issue 2, 201
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