Filters
cris logo
-
New search Filters
Select from list
Displayed from Show more
You have reached the maximum number of displayed search results.
All results displayed
No results are available for the search performed
Displayed from
You have reached the maximum number of displayed search results.
All results displayed
Loading results
Obtaining statistical data

Projects / Programmes source: ARIS

Computer Structures and Systems

Edit
Periods
January 1, 2015 - December 31, 2018
Research activity

Code Science Field Subfield
2.07.00  Engineering sciences and technologies  Computer science and informatics   

Code Science Field
T120  Technological sciences  Systems engineering, computer technology 

Code Science Field
1.02  Natural Sciences  Computer and information sciences 
Keywords
Computing structure, Embedded system, High-performance computing, Algorithms, Massive-data processing, Multi-level and many-objective approach, Prediction, Optimisation, Human-computer interaction, Self-adaptivity, Self-reparability, Context-awareness
Evaluation (rules)
source: COBISS
Evaluation of bibliographic research performance indicators according to ARIS methodology
Citations Citations for bibliographic records in COBIB.SI that are linked to records in citation databases
source: WoS source: Scopus source: COBISS
Researchers (16)
no. Code Name and surname Research area Role Period No. of publications
1.  11983  PhD Anton Biasizzo  Computer science and informatics  Researcher  2015 - 2018  149 
2.  33582  PhD Bojan Blažica  Communications technology  Researcher  2015 - 2018  69 
3.  50854  PhD Tome Eftimov  Computer science and informatics  Researcher  2018  233 
4.  39138  Rok Hribar  Computer science and informatics  Junior researcher  2016 - 2018  21 
5.  22314  PhD Peter Korošec  Computer science and informatics  Researcher  2015 - 2018  238 
6.  10824  PhD Barbara Koroušić Seljak  Computer science and informatics  Researcher  2015 - 2018  339 
7.  06856  PhD Stanislav Kovačič  Systems and cybernetics  Researcher  2015 - 2018  390 
8.  05601  PhD Franc Novak  Computer science and informatics  Researcher  2015 - 2018  316 
9.  18291  PhD Gregor Papa  Computer science and informatics  Head  2015 - 2018  352 
10.  16034  PhD Marko Pavlin  Metrology  Researcher  2015 - 2018  110 
11.  37955  PhD Veljko Pejović  Computer science and informatics  Researcher  2018  132 
12.  04378  PhD Marina Santo Zarnik  Electronic components and technologies  Researcher  2015 - 2018  374 
13.  09862  PhD Jurij Šilc  Computer science and informatics  Researcher  2015 - 2018  359 
14.  51348  PhD Urban Škvorc  Computer science and informatics  Junior researcher  2018  18 
15.  11972  PhD Drago Torkar  Computer science and informatics  Researcher  2015 - 2018  91 
16.  30891  PhD Vida Vukašinović  Computer science and informatics  Researcher  2015 - 2018  58 
Organisations (1)
no. Code Research organisation City Registration number No. of publications
1.  0106  Jožef Stefan Institute  Ljubljana  5051606000  90,706 
Abstract
The research programme Computer Structures and Systems is a combination of the advanced computing structures and efficient algorithms for complex-data processing that is the basis for reconfigurable computer systems. Reconfigurable systems are able to change their internal structure and function in response to external or internal stimuli. Increased performance and reduced power consumption are their widely recognized features, while their architectures provide the means for developing advanced computer systems that function autonomously most of the time without human intervention and have an ability to correct data, and to adapt and repair themselves. Due to the explosion of data (e.g., complex massive-data) in real-life processing, re-configurable computer systems require new and innovative approaches to run, and manage processes. As a consequence, systems must become more versatile, resilient, dependable, energy-efficient, recoverable, customizable and adaptable to changing operational contexts, environments or system characteristics. In high-performance/exascale computing the research involves the integration of reconfiguration and self-adaptivity with worst-case design principles in the development of the algorithms for distributed computing to be performed on clouds, clusters, multi-core CPUs, GPGPUs, FPGAs. In algorithm engineering a multi-level approaches related to complex and massive-data are needed to allow the original complex problem to be decomposed into a set of low-order optimization sub-problems. Furthermore, many-objective approach should be introduced, since the state-of-the-art techniques often fail to find a solution of real-world problems with many objectives. When uncertainty affects the feasibility of a solution, resilience ensures a solution that will be feasible for any realization taken by the unknown conditions. To implement the solutions where the user does not need any specific knowledge about control parameter setting, the self-adaptive approaches for controlling the predictive and the optimisation algorithms are needed. The highest usability of the approach is seen in connection with coordination, where the collective functioning of the system is achieved by indirect interactions among the elements of the system. The proposed research programme follows the main research objectives of the EU's Horizon 2020, within the mission of the Slovenian research agency. The results of the research will combine new and efficient computing structures, efficient systems for massive-data processing, and systems for effective human-computer interaction into a comprehensive unity to support the development of the most advanced computer systems. These systems will be used in production, transport, energy distribution, environmental sustainability, bioinformatics, health, and medicine, with the aim to ensure their social and technological progress.
Significance for science
The role of the proposed Programme is in achieving scientific excellence and in setting new research trends in connection with European and other international/national research projects. In the past we have significantly contributed to the advancement of science, on the national as well as on the international level, and to the transfer of scientific results into practice, as well as to education transfer in Slovenia and Europe. We have several top-level journal publications in the areas of self-reparable hardware structures, metahauristic approaches to optimisation and modelling, pattern recognition, etc. We have organized several prominent international conferences and workshops in the areas of bio-inspired optimisation algorithms and human-computer interactions. We have the intention to contribute further to setting the innovative research directions in the fields that are relevant to our research. Computer systems are nowadays hot topics that are mentioned in different contexts, which require some critical and detailed investigation. The proposed research therefore represents a challenging issue. Based on our research experience we know that the coupling of several research areas (like computing structures, algorithms and interaction systems) demands an investigation of the interrelations among areas. Even though the areas themselves are more or less mature, there is a lot of research to be done when studying and implementing the solutions for their efficient interconnection. Furthermore, these research areas still possess several new aspects, mainly caused by the emergence of new hardware structures and/or computing paradigms (cloud computing, big-data accessing and processing, non-invasive context detection, etc.). Following the roadmaps on advanced computing, embedded systems, exascale initiative and the ubiquitous world we will carry on research to implement the advanced computer systems to meet the: energy efficiency, system complexity, dependability, architectures for data-intensive systems, hardware/software co-design, resource planning and scheduling to deal with an increasing degree of parallelism, code scalability, adaptive and learning control methodologies, dynamic adaptation to changing contexts, decision and control in uncertain and changing contexts. The proposed research on advanced computing structures will focus on new hardware structures: that allow their self-testing during operation, that allow self-reparability when faulty behaviour is detected, and that allow self-configurability when new behaviour of the system is required. These are the necessities to allow the development of advanced self-organising structures. The proposed research on efficient massive-data processing algorithms will focus on self-adaptivity, to allow the adaptation of the algorithms to a changed environment or process conditions. This will influence the development of metaheuristic stochastic, as well as deterministic scalable algorithms being able to cope with massive data, and having a low-latency response. The explosion of data in the real-life processing causes advanced computer systems to require new and innovative approaches for running and managing processes. Namely, only through the collaboration of different approaches can some new and better result be obtained. The effort will be given to studies on the self-adaptivity of the systems. This can be approached either from the structure-adaptivity, or from the algorithm-adaptivity point-of-view. Since we have proven expertise in metaheuristic algorithms and their adaptivity and good practical skills in the low-level programming of reconfigurable systems we are confident that the proposed research will lead to efficient solutions that will contribute to the advancement of re-configurable and self-adaptive computing. With our research in advanced computing structures and efficient massive-data processing algorithms we are addressing several Horizon 2020 objecti
Significance for the country
The most important contributions will be made in collaboration with production companies through the implementation of our solutions for better energy and transportation/logistics efficiency, and in the health sector through the implementation of our solutions for effective nutritional data processing. We have already developed and applied several versions of the advanced algorithms and structures for data processing:  - applications for product planning and management;  - a tool for the simulation and optimisation (e.g., temperatures inside a refrigerator);  - a quality-control machine-vision solution for various parts (e.g., rubber parts);  - extending the product functionalities and improving their usability (e.g., household appliances);  - a machine-vision system for the health-care support (e.g., human-knee pendulum test);  - the open platform for clinical nutrition for supporting the health and agri-food sectors. They have an essential role in confronting the challenges of many real-world areas, like production, transport, energy distribution, environmental sustainability, bio-informatics, health, and medicine. With the progress in our research on computer systems we will be able to further develop the services and applications to create an additional increase in energy and transportation efficiency, to reduce errors in health diagnosis and to improve the collaboration of citizens with their authorities. Our research will further directly influence the following socio-economic objectives:  - Planning of infrastructure and transport systems: the developed simulation and multi-level stigmergic optimization procedures applied to developed computing structures will allow the low-latency, large-scale planning of national infrastructure systems, with the possibility to handle the dynamic nature of transportation systems.  - Rational distribution and utilization of energy: the developed simulation and many-objective stigmergic optimization procedures will allow the low-latency large-scale optimization of energy distribution to improve its utilization by following the dynamic nature of energy production and consumption.  - Increase in industrial competitiveness through new processing techniques: the developed massive-data processing algorithms in coordination with effective user interfaces will form new self-organising processing techniques to improve the production efficiency and competitiveness of the industry.  - Nutritional influence on human health: the developed massive-data processing algorithms and techniques for high-performance computing for open and big food data will allow the wide availability of important food-composition data to prevent an increase in the extent of life-style diseases. In connection with the interaction approaches, the system will be more context-aware.  - Patents: our innovative research results will be patented and offered to companies to establish their position in the market. We will continue with our active role in the transfer of new technologies and innovative solutions to Slovenian companies, as we already successfully collaborated with BSH, Domel, Ema, Eta Cerkno, Gorenje, Harpha Sea, Hidria, Hyb, Luka Koper, Sonce.net, Tesnila, Trimo, Xlab, and others. The basic principles of self-organising stigmergic systems will be used in the implementation of solutions for optimization procedures within the ARTEMIS project Adaptive Cooperative Control in Urban (sub) Systems – ACCUS, where we are developing a platform for the integration and coordination of urban systems (transportation, outdoor lighting, energy) to build applications across urban systems, to provide adaptive and cooperative control for urban subsystems, and to optimize the combined performance. Within the Elixir initiative for a massive-data infrastructure we will create an infrastructure that integrates research (biological) data from all corners of Europe and ensures a seamless service provision that is easily access
Most important scientific results Annual report 2015, 2016, 2017, final report
Most important socioeconomically and culturally relevant results Annual report 2015, 2016, 2017, final report
Confirmation required
Views history
Favourite