Why High-Performance Modelling and Simulation for Big Data Applications Matters

Modelling and Simulation (M&S) offer adequate abstractions to manage the complexity of analysing big data in scientific and engineering domains. Unfortunately, big data problems are often not easily amenable to efficient and effective use of High Performance Computing (HPC) facilities and technologies. Furthermore, M&S communities typically lack the detailed expertise required to exploit the full potential of HPC solutions while HPC specialists may not be fully aware of specific modelling and simulation requirements and applications. The COST Action IC1406 High-Performance Modelling and Simulation for Big Data Applications has created a strategic framework to foster interaction between M&S experts from various application domains on the one hand and HPC experts on the other hand to develop effective solutions for big data applications. One of the tangible outcomes of the COST Action is a collection of case studies from various computing domains. Each case study brought together both HPC and M&S experts, giving witness of the effective cross-pollination facilitated by the COST Action. In this introductory article we argue why joining forces between M&S and HPC communities is both timely in the big data era and crucial for success in many application domains. Moreover, we provide an overview on the state of the art in the various research areas concerned

Forecasting Cryptocurrency Value by Sentiment Analysis: An HPC-Oriented Survey of the State-of-the-Art in the Cloud Era

This chapter surveys the state-of-the-art in forecasting cryptocurrency value by Sentiment Analysis. Key compounding perspectives of current challenges are addressed, including blockchains, data collection, annotation, and filtering, and sentiment analysis metrics using data streams and cloud platforms. We have explored the domain based on this problem-solving metric perspective, i.e., as technical analysis, forecasting, and estimation using a standardized ledger-based technology. The envisioned tools based on forecasting are then suggested, i.e., ranking Initial Coin Offering (ICO) values for incoming cryptocurrencies, trading strategies employing the new Sentiment Analysis metrics, and risk aversion in cryptocurrencies trading through a multi-objective portfolio selection. Our perspective is rationalized on the perspective on elastic demand of computational resources for cloud infrastructures

Unpublished Mediterranean and Black Sea records of marine alien, cryptogenic, and neonative species

To enrich spatio-temporal information on the distribution of alien, cryptogenic, and neonative species in the Mediterranean and the Black Sea, a collective effort by 173 marine scientists was made to provide unpublished records and make them open access to the scientific community. Through this effort, we collected and harmonized a dataset of 12,649 records. It includes 247 taxa, of which 217 are Animalia, 25 Plantae and 5 Chromista, from 23 countries surrounding the Mediterranean and the Black Sea. Chordata was the most abundant taxonomic group, followed by Arthropoda, Mollusca, and Annelida. In terms of species records, Siganus luridus, Siganus rivulatus, Saurida lessepsianus, Pterois miles, Upeneus moluccensis, Charybdis (Archias) longicollis, and Caulerpa cylindracea were the most numerous. The temporal distribution of the records ranges from 1973 to 2022, with 44% of the records in 2020–2021. Lethrinus borbonicus is reported for the first time in the Mediterranean Sea, while Pomatoschistus quagga, Caulerpa cylindracea, Grateloupia turuturu, and Misophria pallida are first records for the Black Sea; Kapraunia schneideri is recorded for the second time in the Mediterranean and for the first time in Israel; Prionospio depauperata and Pseudonereis anomala are reported for the first time from the Sea of Marmara. Many first country records are also included, namely: Amathia verticillata (Montenegro), Ampithoe valida (Italy), Antithamnion amphigeneum (Greece), Clavelina oblonga (Tunisia and Slovenia), Dendostrea cf. folium (Syria), Epinephelus fasciatus (Tunisia), Ganonema farinosum (Montenegro), Macrorhynchia philippina (Tunisia), Marenzelleria neglecta (Romania), Paratapes textilis (Tunisia), and Botrylloides diegensis (Tunisia)

Harmful Elements in Estuarine and Coastal Systems

Estuaries and coastal zones are dynamic transitional systems which provide many economic and ecological benefits to humans, but also are an ideal habitat for other organisms as well. These areas are becoming contaminated by various anthropogenic activities due to a quick economic growth and urbanization. This chapter explores the sources, chemical speciation, sediment accumulation and removal mechanisms of the harmful elements in estuarine and coastal seawaters. It also describes the effects of toxic elements on aquatic flora and fauna. Finally, the toxic element pollution of the Venice Lagoon, a transitional water body located in the northeastern part of Italy, is discussed as a case study, by presenting the procedures adopted to measure the extent of the pollution, the impacts on organisms and the restoration activities

Energy Sector Vulnerability to Climate Change: Adaptation Options to Increase Resilience

The U.S. Department of Energy is conducting an assessment of vulnerabilities of the U.S. energy sector to climate change and extreme weather. Emphasizing peer reviewed research, it seeks to quantify vulnerabilities and identify specific knowledge or technology gaps. It draws upon a July 2012 workshop, ?Climate Change and Extreme Weather Vulnerability Assessment of the US Energy Sector?, hosted by the Atlantic Council and sponsored by DOE to solicit industry input

How unconventional chaotic pseudo-random generators influence population diversity in differential evolution

This research focuses on the modern hybridization of the discrete chaotic dynamics and the evolutionary computation. It is aimed at the influence of chaotic sequences on the population diversity as well as at the algorithm performance of the simple parameter adaptive Differential Evolution (DE) strategy: jDE. Experiments are focused on the extensive investigation of totally ten different randomization schemes for the selection of individuals in DE algorithm driven by the default pseudo random generator of Java environment and nine different two-dimensional discrete chaotic systems, as the chaotic pseudo-random number generators. The population diversity and jDE convergence are recorded for 15 test functions from the CEC 2015 benchmark set in 30D. © Springer International Publishing AG, part of Springer Nature 2018.2018/177; IC406; MSMT-7778/2014, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; LO1303, MŠMT, Ministerstvo Školství, Mládeže a Tělovýchovy; 710577, Horizon 2020; CA15140; IGA/CebiaTech/2018/003; CZ.1.05/2.1.00/03.0089, FEDER, European Regional Development FundMinistry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2018/003]; COST ActionEuropean Cooperation in Science and Technology (COST) [CA15140, IC406]; SGS [2018/177]; VSB-TUO; EU's Horizon 2020 research and innovation programme [710577

Population diversity analysis in adaptive differential evolution variants with unconventional randomization schemes

This research represents a detailed insight into the modern and popular hybridization of unconventional quasiperiodic/chaotic sequences and evolutionary computation. It is aimed at the influence of different randomization schemes on the population diversity, thus on the performance, of two selected adaptive Differential Evolution (DE) variants. Experiments are focused on the extensive investigation of totally ten different randomization schemes for the selection of individuals in DE algorithm driven by the default pseudo-random generator of Java environment and nine different two-dimensional discrete chaotic systems, as the unconventional chaotic pseudo-random number generators. The population diversity is recorded for 15 test functions from the CEC 2015 benchmark set in 10D. © 2019, Springer Nature Switzerland AG.Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the Project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]; Internal Grant Agency of Tomas Bata University [IGA/CebiaTech/2019/002]; COST (European Cooperation in Science & Technology) under Action (ImAppNIO) [CA15140]; COST (European Cooperation in Science & Technology) under Action (cHiPSet) [IC1406]; VSB-Technical University of Ostrava [SGS 2019/137