Computational intelligence for measuring macro-knowledge competitiveness

The aim of this research is to investigate the utilisation of Computational Intelligence methods for constructing Synthetic Composite Indicators (SCI). In particular for delivering a Unified Macro-Knowledge Competitiveness Indicator (UKCI) to enable consistent and transparent assessments and forecasting of the progress and competitiveness of Knowledge Based Economy (KBE). SCI are assessment tools usually constructed to evaluate and contrast entities performance by aggregating intangible measures in many areas such as economy, education, technology and innovation. SCI key value is inhibited in its capacity to aggregate complex and multi-dimensional variables into a single meaningful value. As a result, SCIs have been considered as one of the most important tools for macro-level and strategic decision making. Considering the shortcomings of the existing SCI, this study is proposing an alternative approach to develop Intelligent Synthetic Composite Indicators (iSCI). The suggested approach utilizes Fuzzy Proximity Knowledge Mining technique to build the qualitative taxonomy initially, and Fuzzy c-mean is employed to form the new composite indicators

Car Industry developments – oil industry challenges

Automotive industry of Europe is one of the greatest economical powers, the „engine of Europe”. It employs directly 2.2 million people and 10 million in related industries and services. Combined turnover of automotive manufacturers reaches 700 billion EUR (retail another 520 billion EUR). The industry is the largest R&D investor in EU. On the other hand the transport sector carries a huge safety and environmental risk. Thanks to this fact the automotive industry is one of the most regulated sectors in the EU. As a result of these regulations: one average car built in 1970s produced as many pollutant elements as one hundred cars manufactured today. These achievements are based on struggles of both the auto and oil industry as parallel with technology development in car industry fuel quality developments achieved by the oil industry drove to a much “cleaner” fuel quality (unleaded sulphur free petrol, reduction of aromatics, benzene; sulphur free diesel, reduction of density, poly-aromatics, etc.). In the end of the 1990s, and especially for the last few years new challenges came into the focus of the auto and oil industry of the EU and the world. Concerns about high energy prices and price volatility, security of worldwide oil supply and climate change became a main policy agenda of the EU and the world. This new policy is reflected in new regulatory initiatives requiring cars using less energy more efficiently, emitting less carbondioxide and using growing proportion of renewable fuels. The European Commission declared the idea of “Cars for Fuels” instead of “Fuels for Cars”. This article discusses in detail the regulations and challenges that rose towards oil and car industry during the recent years. It describes the possible solutions in order to fulfil the requirements of the EU. After that a wide picture is presented without going into much detail on developments of the automotive industry. Developments are divided between vehicle level, engine level and fuel level technologies, also paying attention to technologies that are less known or rather futuristic

LiDAR aided simulation pipeline for wireless communication in vehicular traffic scenarios

Abstract. Integrated Sensing and Communication (ISAC) is a modern technology under development for Sixth Generation (6G) systems. This thesis focuses on creating a simulation pipeline for dynamic vehicular traffic scenarios and a novel approach to reducing wireless communication overhead with a Light Detection and Ranging (LiDAR) based system. The simulation pipeline can be used to generate data sets for numerous problems. Additionally, the developed error model for vehicle detection algorithms can be used to identify LiDAR performance with respect to different parameters like LiDAR height, range, and laser point density. LiDAR behavior on traffic environment is provided as part of the results in this study. A periodic beam index map is developed by capturing antenna azimuth and elevation angles, which denote maximum Reference Signal Receive Power (RSRP) for a simulated receiver grid on the road and classifying areas using Support Vector Machine (SVM) algorithm to reduce the number of Synchronization Signal Blocks (SSBs) that are needed to be sent in Vehicle to Infrastructure (V2I) communication. This approach effectively reduces the wireless communication overhead in V2I communication

Recent Advances in the Development of Smart and Active Biodegradable Packaging Materials

Interest in the development of smart and active biodegradable packaging materials is increasing as food manufacturers try to improve the sustainability and environmental impact of their products, while still maintaining their quality and safety. Active packaging materials contain components that enhance their functionality, such as antimicrobials, antioxidants, light blockers, or oxygen barriers. Smart packaging materials contain sensing components that provide an indication of changes in food attributes, such as alterations in their quality, maturity, or safety. For instance, a smart sensor may give a measurable color change in response to a deterioration in food quality. This article reviews recent advances in the development of active and smart biodegradable packaging materials in the food industry. Moreover, studies on the application of these packaging materials to monitor the freshness and safety of food products are reviewed, including dairy, meat, fish, fruit and vegetable products. Finally, the potential challenges associated with the application of these eco-friendly packaging materials in the food industry are discussed, as well as potential future directions

TEchMA2020: 3rd International Conference on Technologies for the Wellbeing and Sustainable Manufacturing Solutions: book of abstracts

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