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In this study, Call Detail Records (CDRs) from downtown Budapest were analysed, focusing on a large-scale event in August 2014. The attendees of the main event of the Hungarian State Foundation Day have been analysed based on their Socioeconomic Status (SES). This paper proposes an approach to estimating SES by the price and age of the subscribers' phones, obtained by fusing a mobile phone property database with the CDRs. We have found some tendencies between the attendees based on the location, from where they watched the fireworks. However, the results do not show significant differences in this geographical granularity.

Investigations of novel and high-performance transparent conducting electrodes (TCEs) are required to substitute currently widely used tin-doped indium oxide (ITO) due to the low abundance of indium and constantly increasing demand on ITO in the optoelectronic industry. Here we synthesised In-Sn-O thin films from inexpensive and air-stable precursors by facile aerosol-assisted chemical vapour deposition (AACVD). These films presented a high level of electro-optical properties, of which the optimum sample possessed a low resistivity of 8.7 × 10−4 Ω cm and an excellent optical transmission (~80%) across the visible light spectrum, which is similar to the industry standard. More importantly, the analysis of elemental composition illustrated considerably lower indium content (70 at.%) in the best coatings as compared to those in commercial ITO (commonly ＞90 at.% of indium), which contributes to TCEs with reduced indium content. Scanning electron microscopy (SEM) images displayed dense and continuous crystal grains and uniform thickness distribution. This work shows the promising potential of AACVD to prepare alternatives to ITO under simple, safe and cost-effective conditions.

Advancement of accurate models for predicting real estate price is of utmost importance for urban development and several critical economic functions. Due to the significant uncertainties and dynamic variables, modeling real estate has been studied as complex systems. In this study, a novel machine learning method is proposed to tackle real estate modeling complexity. Call detail records (CDR) provides excellent opportunities for in-depth investigation of the mobility characterization. This study explores the CDR potential for predicting the real estate price with the aid of artificial intelligence (AI). Several essential mobility entropy factors, including dweller entropy, dweller gyration, workers&rsquo, entropy, worker gyration, dwellers&rsquo, work distance, and workers&rsquo, home distance, are used as input variables. The prediction model is developed using the machine learning method of multi-layered perceptron (MLP) trained with the evolutionary algorithm of particle swarm optimization (PSO). Model performance is evaluated using mean square error (MSE), sustainability index (SI), and Willmott&rsquo, s index (WI). The proposed model showed promising results revealing that the workers&rsquo, entropy and the dwellers&rsquo, work distances directly influence the real estate price. However, the dweller gyration, dweller entropy, workers&rsquo, gyration, and the workers&rsquo, home had a minimum effect on the price. Furthermore, it is shown that the flow of activities and entropy of mobility are often associated with the regions with lower real estate prices.

Several epidemiological models are being used around the world to project the number of infected individuals and the mortality rates of the COVID-19 outbreak. Advancing accurate prediction models is of utmost importance to take proper actions. Due to a high level of uncertainty or even lack of essential data, the standard epidemiological models have been challenged regarding the delivery of higher accuracy for long-term prediction. As an alternative to the susceptible-infected-resistant (SIR)-based models, this study proposes a hybrid machine learning approach to predict the COVID-19 and we exemplify its potential using data from Hungary. The hybrid machine learning methods of adaptive network-based fuzzy inference system (ANFIS) and multi-layered perceptron-imperialist competitive algorithm (MLP-ICA) are used to predict time series of infected individuals and mortality rate. The models predict that by late May, the outbreak and the total morality will drop substantially. The validation is performed for nine days with promising results, which confirms the model accuracy. It is expected that the model maintains its accuracy as long as no significant interruption occurs. Based on the results reported here, and due to the complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research.

Materials for electronics that function as electrical and/or thermal conductors are often rigid, expensive, difficult to be sourced and sometimes toxic. An electrically and thermally conductive nanocomposite that is lightweight, flexible and eco-friendly could improve the environmental friendliness of the electronics sector and enable new applications. Considering this, we have fabricated electrically and thermally conductive flexible materials by functionalizing paper with nanocarbon conductive inks. Carnauba wax is emulsified in isopropyl alcohol and mixed with graphene nanoplatelets (GNPs) or with hybrids of GNPs and carbon nanofibers (CNFs). The percolation threshold of the hybrid samples is lowered compared with the pure GNPs composites, due to their increased filler aspect ratio. The hybrid samples also exhibit superior bending and folding stability. Densification of the coating to decrease their sheet resistance enables them to achieve as low as ~ 50 {\Omega} sq-1 for the GNP-based paper. The densification procedure improves the bending stability, the abrasion resistance, and the electromagnetic interference shielding of the paper-based conductors. Finally, the compressed samples show an impressive enhancement of their thermal diffusivity. The flexible and multifunctional nanocarbon coated paper is a promising electronic conductor and thermally dissipative material and, at the same time, can increase the environmental sustainability of the electronics sector., Comment: 27 pages, 4 figures

Along with environmental pollutions, urban planning has been connected to public health. The research indicates that the quality of built environments plays an important role in reducing mental disorders and overall health. The structure and shape of the city are considered as one of the factors influencing happiness and health in urban communities and the type of the daily activities of citizens. The aim of this study was to promote physical activity in the main structure of the city via urban design in a way that the main form and morphology of the city can encourage citizens to move around and have physical activity within the city. Functional, physical, cultural-social, and perceptual-visual features are regarded as the most important and effective criteria in increasing physical activities in urban spaces based on literature review. The environmental quality of urban spaces and their role in the physical activities of citizens in urban spaces were assessed by using the questionnaire tool and analytical network process (ANP) of structural equation modeling. Further, the space syntax method was utilized to evaluate the role of the spatial integration of urban spaces on improving physical activities. Based on the results, the consideration of functional diversity, spatial flexibility and integration, security, and the aesthetic and visual quality of urban spaces plays an important role in improving the physical health of citizens in urban spaces. Further, more physical activities, including motivation for walking and consequently, the sense of public health and happiness, were observed in the streets having higher linkage and space syntax indexes with their surrounding texture.

Along with environmental pollution, urban planning has been connected to public health. The research indicates that the quality of built environments plays an important role in reducing mental disorders and overall health. The structure and shape of the city are considered as one of the factors influencing happiness and health in urban communities and the type of the daily activities of citizens. The aim of this study was to promote physical activity in the main structure of the city via urban design in a way that the main form and morphology of the city can encourage citizens to move around and have physical activity within the city. Functional, physical, cultural-social, and perceptual-visual features are regarded as the most important and effective criteria in increasing physical activities in urban spaces, based on literature review. The environmental quality of urban spaces and their role in the physical activities of citizens in urban spaces were assessed by using the questionnaire tool and analytical network process (ANP) of structural equation modeling. Further, the space syntax method was utilized to evaluate the role of the spatial integration of urban spaces on improving physical activities. Based on the results, consideration of functional diversity, spatial flexibility and integration, security, and the aesthetic and visual quality of urban spaces plays an important role in improving the physical health of citizens in urban spaces. Further, more physical activities, including motivation for walking and the sense of public health and happiness, were observed in the streets having higher linkage and space syntax indexes with their surrounding texture.

[enter Abstract Body]Sustainability has become one of the challenges of today’s banks. Since sustainable business models are responsible for the environment and society along with generating economic benefits, they are an attractive approach to sustainability. Sustainable business models also offer banks competitive advantages such as increasing brand reputation and cost reduction. However, no framework is presented to evaluate the sustainability of banking business models. To bridge this theoretical gap, the current study using A Delphi-Analytic Hierarchy Process method, firstly, developed a sustainable business model to evaluate the sustainability of the business model of banks. In the second step, the sustainability performance of sixteen banks from eight European countries including Norway, The UK, Poland, Hungary, Germany, France, Spain, and Italy, assessed. The proposed business model components of this study were ranked in terms of their impact on achieving sustainability goals. Consequently, the proposed model components of this study, based on their impact on sustainability, are respectively value proposition, core competencies, financial aspects, business processes, target customers, resources, technology, customer interface, and partner network. The results of the comparison of the banks studied by each country disclosed that the sustainability of the Norwegian and German banks’ business models is higher than in other counties. The studied banks of Hungary and Spain came in second, the banks of the UK, Poland, and France ranked third, and finally, the Italian banks ranked fourth in the sustainability of their business models.

Mammography is often used as the most common laboratory method for the detection of breast cancer, yet associated with the high cost and many side effects. Machine learning prediction as an alternative method has shown promising results. This paper presents a method based on a multilayer fuzzy expert system for the detection of breast cancer using an extreme learning machine (ELM) classification model integrated with radial basis function (RBF) kernel called ELM-RBF, considering the Wisconsin dataset. The performance of the proposed model is further compared with a linear-SVM model. The proposed model outperforms the linear-SVM model with RMSE, R2, MAPE equal to 0.1719, 0.9374 and 0.0539, respectively. Furthermore, both models are studied in terms of criteria of accuracy, precision, sensitivity, specificity, validation, true positive rate (TPR), and false-negative rate (FNR). The ELM-RBF model for these criteria presents better performance compared to the SVM model., 7 pages, 5 figures

A numerical method has been developed to solve of transient Inverse Heat Transfer Problem (IHCP) occurring during transient heat transfer conditions. The method is derived to an optimization problem where the objective function to be minimized includes the quadratic difference of temperature signals measured and estimated in the given locations of a cylindrical bar. The particle Swarm optimization method is used to mind the minimum of the objective function. The Heat Transfer Coefficients (HTC) on selected surfaces of the work piece are estimated. The method has been parallelized and implemented on a Graphic Accelerators architecture. The applicability of the proposed technique is proven by computational tests based on cooling curves obtained during quenching experiments.

During the last decade, mobile phones have become an integral part of urban life. Today the number of mobile phones worldwide is over 1 billion units, and have reached a penetration of over 70% of total adult population in several countries. Mobile devices became an ’extension of human body’ and provide ubiquitous possibilities of nearly anytime/anywhere one-to-one communication. Their footprints in the mobile network could help to understand the socioeconomic aspects of urban life. In this paper, we are applying metrics by which mobility and life style characteristics of urban area can be evaluated. Our proposed approach relies on time series analysis of Call Data Records acquisited by a Hungarian Mobile Telecommunication Operator.

The relevant information of heat trasnfer properties of cooling media required to maintain the heat treatement processes are mostly available in off line sources. Thses data include the cooling curves recorded in quenchnats, predicted Heat Flux or Heat Trasnfer Coefficients and other thermophysical properties. The International Federation for Heat Treatment and Surface Engineering (IFHTSE) initiated a project aiming to collect and share cooling curves acquisited during the quenching processes. The Liquid Quenchant Database is a global project with more the 30 contributors from 14 countries is led by the. The Database of Liquid Quenchants is available on the webpage of the IFHTSE.

By carrying mobile phones, people leaves digital footprints in the mobile phone network that provides rich information about the transportation customs. To understand the behavior of urban environments this data, provided by a Hungarian mobile network operator, is analyzed. The behavior of the city parts has been analyzed using the number of mobile phone activities including calls, texting and data transfer. The proposed approach is to identify regions of a city with similar behavior in mobile phone activity. This paper demonstrates the introduced method using a public demonstration event as a case study. It is clear from the data that the demonstrators caused an increase in the mobile phone network load at the places of the demonstration, so it was possible to identify their path.

Electrically conductive, polymeric materials that maintain their conductivity even when under significant mechanical deformation are needed for actuator electrodes, conformable electromagnetic shielding, stretchable tactile sensors and flexible energy storage. The challenge for these materials is that the percolated, electrically conductive networks tend to separate even at low strains, leading to significant piezoresistance. Herein, deformable conductors were fabricated by spray-coating a nitrile substrate with a graphene-elastomer solution. The coatings showed only slight increase in electrical resistance after thousands of bending cycles and repeated folding-unfolding events. The deformable conductors doubled their electrical resistance at 12% strain and were washable without changing their electrical properties. The conductivity-strain behaviour was modelled by considering the nanofiller separation upon deformation. To boost the conductivity at higher strains, the production process was adapted by stretching the nitrile substrate before spraying, after which it was released. This adaption meant that the electrical resistance doubled at 25 % strain. The electrical resistance was found sufficiently low to give a 1.9 dB/{\mu}m shielding in the 8-12 GHz electromagnetic band. The physical and electrical properties, including the EM screening, of the flexible conductors, were found to deteriorate upon cycling but could be recovered through reheating the coating., Comment: 29 pages, 6 figures

The cellular networks including the millions of mobile devices generate a huge volume (mobile phone call records) of data by which the movements of people could be sensed. In this paper, a method (based on mobile phone call records) applied to characterize the patterns of urban population during a big social event is underlined. The proposed method is also to show the regions in the city where the similar trend of mobility takes place. This paper demonstrates the applicability of the approach on the data provided by a Hungarian mobile network operator during a public demonstration event. The results obtained can be helpful in understanding the structure of the city in the sense of human mobility related to large-scale events.

We share almost all segments of our lives on the web, including our to-do's, meetings, events related to work or leisure. Not only we share with the world where we are going to be, but also how we are feeling in a given situation and with whom we are attending a certain event. If we ignore the individual aspect and look at a city as a whole, the people, who work and enjoy their free time in the city produce a sensor network. This network is continuously reporting about the current status of the city, in some cases even about its near future. These pieces of information are scattered on social media platforms, but most importantly, they pile up in an unprocessed manner. By collecting this information about a city and especially, about its traffic as a unit, we can expect a relatively accurate picture. If we complement this with data from other sources — such as weather forecast data, which can significantly influence our activities — we can estimate the tendency of urban citizens' movement, predict which traffic junctions can become overladen. In our article, we use the data from latest time period to prove our concept.