ALBERT

Description: Nowadays, it has been recognized that blockchain can provide the technological infrastructure for developing decentralized, secure, and reliable smart energy grid management systems. However, an open issue that slows the adoption of blockchain technology in the energy sector is the low scalability and high processing overhead when dealing with the real-time energy data collected by smart energy meters. Thus, in this paper, we propose a scalable second tier solution which combines the blockchain ledger with distributed queuing systems and NoSQL (Not Only SQL database) databases to allow the registration of energy transactions less frequently on the chain without losing the tamper-evident benefits brought by the blockchain technology. At the same time, we propose a technique for tamper-evident registration of smart meters’ energy data and associated energy transactions using digital fingerprinting which allows the energy transaction to be linked hashed-back on-chain, while the sensors data is stored off-chain. A prototype was implemented using Ethereum and smart contracts for the on-chain components while for the off-chain components we used Cassandra database and RabbitMQ messaging broker. The prototype proved to be effective in managing a settlement of energy imbalances use-case and during the evaluation conducted in simulated environment shows promising results in terms of scalability, throughput, and tampering of energy data sampled by smart energy meters.

Description: What factors influence students to start their own business? What are the implications at the university level? This paper aims to answer to these questions and investigates, at a micro level (university), the motivation for entrepreneurial intentions among students in 10 universities from the United Arab Emirates (UAE). An online inquiry has been conducted among 500 students between April and June 2018, and 157 fully completed questionnaires were retained. Factor Analysis with Varimax (with Kaizer Normalization) rotation and logistic regression were used to identify what factors motivate students to start their own business and, from those factors, which one is determinant in this decision. Also, age and parental self-employment status were used to determine the influence of these factors. Four factors have been identified as determinants for students to start their own business: entrepreneurial confidence, entrepreneurial orientation, university support for entrepreneurship, and cultural support for entrepreneurship. Surprisingly, the only factor significantly correlated with the intention in starting a business is entrepreneurial confidence. This factor becomes even stronger when it is associated with age (20–25 years old) and parents’ self-employment status. These conclusions involve specific challenges on the university level, related to the role of entrepreneurial education and on country level, in link with the effectiveness of governmental programs to enhance entrepreneurial endeavours. Further research can explore and test these findings on a representative sample for the UAE, and for other countries.

Description: In this paper, the concept of smart battery pack is introduced. The smart battery pack is based on wireless feedback from individual battery cells and is capable to be applied to electric vehicle applications. The proposed solution increases the usable capacity and prolongs the life cycle of the batteries by directly integrating the battery management system in the battery pack. The battery cells are connected through half-bridge chopper circuits, which allow either the insertion or the bypass of a single cell depending on the current states of charge. This consequently leads to the balancing of the whole pack during both the typical charging and discharging time of an electric vehicle and enables the fault-tolerant operation of the pack. A wireless feedback for implementing the balancing method is proposed. This solution reduces the need for cabling and simplifies the assembling of the battery pack, making also possible a direct off-board diagnosis. The paper validates the proposed smart battery pack and the wireless feedback through simulations and experimental results by adopting a battery cell emulator.

Description: To achieve sustainable development, massive changes towards fostering a clean and pollution-reducing industrial sector are quintessential. The textile industry has been one of the main contributors to water pollution all over the world, causing more than 20% of the registered levels of water pollution in countries like Turkey, Indonesia and China (among the G20 group of countries) and also in Romania and Bulgaria (in the Eastern European area), with even more than 44% in Macedonia. Given the controversy created by the textile industry’s contribution to pollution at a global level and also the need to diminish pollution in order to promote sustainable development, this paper comparatively investigates the contribution of the textile industry to the water pollution across Central and Eastern European countries, as well as developed countries. In addition, we employ the Holt–Winters model to forecast the trend of the total emissions of organic water pollutants, as well as of the textile industry’s contribution to pollution for the top polluters in Eastern Europe, i.e., Poland and Romania. According to our estimates, both countries are headed towards complete elimination of pollution caused by the textile industry and, hence, toward a more sustainable industrial sector, as Greenpeace intended with the release of its 2011 reports.

Description: Herein we describe poly(ionic liquid) hydrogel actuators that are capable of responding to multiple stimuli, namely temperature, ionic strength and white light irradiation. Using two starting materials, a crosslinked poly ionic liquid (PIL) and a linear poly(N-isopropylacrylamide-co-spiropyran-co-acrylic acid), several semi-interpenetrating (sIPN) hydrogels were synthesised. The dimensions of hydrogels discs were measured before and after applying the stimuli, to quantify their response. Samples composed of 100% crosslinked PIL alone showed an average area reduction value of ~53% when the temperature was raised from 20 °C to 70 °C, ~24% when immersed in 1% w/w NaF salt solution and no observable photo-response. In comparison, sIPNs containing 300% w/w linear polymer showed an average area reduction of ~45% when the temperature was raised from 20 °C to 70 °C, ~36% when immersed in 1% NaF w/w salt solution and ~10% after 30 min exposure to white light irradiation, respectively. Moreover, by varying the content of the linear component, fine-control over the photo-, thermo- and salt response, swelling-deswelling rate and mechanical properties of the resulting sIPN was achieved.

Description: This paper addresses the problem of data centers’ cost efficiency considering the potential of reusing the generated heat in district heating networks. We started by analyzing the requirements and heat reuse potential of a high performance computing data center and then we had defined a heat reuse model which simulates the thermodynamic processes from the server room. This allows estimating by means of Computational Fluid Dynamics simulations the temperature of the hot air recovered by the heat pumps from the server room allowing them to operate more efficiently. To address the time and space complexity at run-time we have defined a Multi-Layer Perceptron neural network infrastructure to predict the hot air temperature distribution in the server room from the training data generated by means of simulations. For testing purposes, we have modeled a virtual server room having a volume of 48 m3 and two typical 42U racks. The results show that using our model the heat distribution in the server room can be predicted with an error less than 1 °C allowing data centers to accurately estimate in advance the amount of waste heat to be reused and the efficiency of heat pump operation.

Description: In order to obtain bioenergy (biogas, biofuel) or pellets, different types of lignocellulosic biomass are subjected to a mechanical pretreatment, first by size reduction, then by separating, and ultimately by fracturing or bio-refining. Biomass processing mainly refers to a grinding process that occurs until reaching certain limits. The size reduction process, such as grinding, is an operation that is executed with different levels of energy consumption, considering biomass mechanical characteristics and the necessary grinding level. This paper, illustrates a comparative analysis of experimental results obtained by grinding multiple types of vegetal biomass (Miscanthus, corn stalks, alfalfa, willow) used in the process of bio-refining and bio-fracturing. Experiments were realized using both a laboratory knife mill Grindomix GM200 (Retsch GmbH, Haan, Germany), and a 22 kW articulated hammer mill, using different grinding system speeds and different hammer mill sieves. Results have shown that biomass mechanical pre-processing grinding leads to supplementary costs in the overall process through bio-refining or bio-fracturing in order to obtain bio-products or bio-energy. So, specific energy consumption for grinding using a hammer mill can reach 50–65 kJ/kg for harvested Miscanthus biomass, and 35–50 kJ/kg for dried energetic willow, using a 10 mm orifice sieve, values which increase processing costs.

Description: In the present paper some different types of boundedness in fuzzy normed linear spaces of type ( X , N , ∗ ) , where ∗ is an arbitrary t-norm, are considered. These boundedness concepts are very general and some of them have no correspondent in the classical topological metrizable linear spaces. Properties of such bounded sets are given and we make a comparative study among these types of boundedness. Among them there are various concepts concerning symmetrical properties of the studied objects arisen from the classical setting appropriate for this journal topics. We establish the implications between them and illustrate by examples that these concepts are not similar.

Description: Online collaboration and web-based knowledge sharing have gained momentum as major components of the Web 2.0 movement. Consequently, knowledge embedded in such platforms is no longer static and continuously evolves through experts’ micro-contributions. Traditional Information Retrieval and Social Network Analysis techniques take a document-centric approach to expertise modeling by creating a macro-perspective of knowledge embedded in large corpus of static documents. However, as knowledge in collaboration platforms changes dynamically, the traditional macro-perspective is insufficient for tracking the evolution of knowledge and expertise. Hence, Expertise Profiling is presented with major challenges in the context of dynamic and evolving knowledge. In our previous study, we proposed a comprehensive, domain-independent model for expertise profiling in the context of evolving knowledge. In this paper, we incorporate Language Modeling into our methodology to enhance the accuracy of resulting profiles. Evaluation results indicate a significant improvement in the accuracy of profiles generated by this approach. In addition, we present our profile visualization tool, Profile Explorer, which serves as a paradigm for exploring and analyzing time-dependent expertise profiles in knowledge-bases where content evolves overtime. Profile Explorer facilitates comparative analysis of evolving expertise, independent of the domain and the methodology used in creating profiles.

Description: Environments, Vol. 5, Pages 99: An Analysis of the Risk Posed by Leachate from Dumpsites in Developing Countries Environments doi: 10.3390/environments5090099 Authors: Mentore Vaccari Giovanni Vinti Terry Tudor The disposal of municipal solid waste into primarily dumpsites in developing countries causes a number of potential public and environmental health risks. While there have been various studies that have evaluated the contaminants that cause the risks, these studies have generally not examined in a holistic way the manner in which these contaminants move. This study therefore sought to model the flow of a range of contaminants in dumpsites (As, Cd, Cu, Pb, Ni, Zn), and potential health risks as a means of enabling the more effective siting of facilities to reduce the risks posed. The study proposes a conservative model, using well consolidated equations and assumption, taking into account the path the pollutant makes to reach the water table and the point of exposure. The modelling may be useful to easily identify the boundaries of the area of risk related to the presence of a dumpsite in a Developing Country, beyond which a local community may use or build a safe well for drinking water. The results show as the area of risk is large and varies significantly with changes in input parameters, suggesting that without site-specific information it is better to follow conservative assumptions.