The paper proposes a comparative analysis of the influence of volatility spasms of Gas and Oil market on Inflation for six European countries during the last two years. We attempted to measure the impact of Oil and Gas price variation on short term Inflation Rate for the selected countries using a non-linear regression model, derived with the help of a genetic optimization algorithm.

The potential threat of Near Earth Objects (NEO) requires a constant survey of the night sky to discover potentially dangerous objects and assess their future impact odds. Several ongoing surveys relying on human operators or automated techniques exist. One such example is the EURONEAR blink mini-survey project which over time developed from a pure manual approach to detecting asteroids to semi-automatic methods (NEARBY) using image processing and service-oriented approaches. In this paper, we propose an extension of NEARBY based on an ensemble model comprising three state-of-art machine learning models, some used in similar approaches. The proposed model is designed for a binary classification problem where candidate images may contain an asteroid in their center. Validation on a real-life dataset comprising 11,000 images shows that our ensemble model is capable of recovering about 55% of the asteroids missed by the previous NEARBY automated process while at the same time having a 0.88 recall on the asteroids already detected by NEARBY. Used together with NEARBY our model increased the detection rate from 89% to 95%.

The paper proposes a new method to simulate the variation of the prices of agricultural products on the stock market, using a co-web evolutionary adaptive model of concurrent sales strategies.

This study examines the response of the Consumer Price Index (CPI) in local currency to the COVID-19 pandemic using monthly data (March 2020–February 2022), comparatively for six European countries. We have introduced a model of multivariate adaptive regression that considers the quasi-periodic effects of pandemic waves in combination with the global effect of the economic shock to model the variation in the price of crude oil at international levels and to compare the induced effect of the pandemic restriction as well and the oil price variation on each country’s CPI. The model was tested for the case of six emergent countries and developed European countries. The findings show that: (i) pandemic restrictions are driving a sharp rise in the CPI, and consequently inflation, in most European countries except Greece and Spain, and (ii) the emergent economies are more affected by the oil price and pandemic restriction than the developed ones.

Context. Near-Earth asteroids (NEAs) that may evolve into impactors deserve detailed threat assessment studies. Early physical characterization of a would-be impactor may help in optimizing impact mitigation plans. We first detected NEA 2023 DZ2 on 27 February 2023. After that, it was found to have a minimum orbit intersection distance (MOID) with Earth of 0.00005 au as well as an unusually high initial probability of becoming a near-term (in 2026) impactor. Aims. We perform a rapid but consistent dynamical and physical characterization of 2023 DZ2 as an example of a key response to mitigating the consequences of a potential impact. Methods. We used a multi-pronged approach, drawing from various methods (observational-computational) and techniques (spectroscopy-photometry from multiple instruments), and bringing the data together to perform a rapid and robust threat assessment. Results. The visible reflectance spectrum of 2023 DZ2 is consistent with that of an X-type asteroid. Light curves of this object obtained on two different nights give a rotation period P = 6.2743 ± 0.0005 min with an amplitude A = 0.57 ± 0.14 mag. We confirm that although its MOID is among the smallest known, 2023 DZ2 will not impact Earth in the foreseeable future as a result of secular near-resonant behaviour. Conclusions. Our investigation shows that coordinated observation and interpretation of disparate data provides a robust approach from discovery to threat assessment when a virtual impactor is identified. We prove that critical information can be obtained within a few days after the announcement of the potential impactor.

"The paper compares four variants of algorithms that solve the problem of Convex Feasibility using affine combinations of projections, two classical variants of Parallel Projection Method (PPM) and two modified variants that involve variable weight, in terms of their effectiveness in inpainting a convex polygon, as well as in terms of their convergence in a finite a number of step. We also present a numerical study of the dependence of the efficiency and the execution speed of these algorithms on the shape of the inpainted convex set, as well as on the values of the relaxation parameter."

The SARS-COV2 pandemic had a strong impact on the Romanian and European e-Market, manifested by the explosive increase in online sales, especially at the beginning of the two waves of epidemic, in spring and autumn. Using a statistical regressive analysis of monthly change in the volume of online sales in Romania, we propose a non-linear regression model of growth of this commercial sector that take into account the economic and socials effects of the three pandemic waves in 2020-2021, combining logistic equations of growth with attenuated quasi-periodical variations of market. The model allows a prediction of the overall behavior of online buyers for 2021 and 2022, similar to last year, but with annual growth peaks slightly less pronounced than in 2020.

"The emergence and accelerated spread of COVID-19 has severely affected Romanian and European e-Market, manifested by the explosion of sales of basic products. We propose in this paper a non-linear model of growth of e-Commerce observed in the Romanian retail sector that consider the economic and socials effects of the two pandemic Waves in 2020. Starting from the hypothesis, statistically verified, that the effect of a Pandemic crisis can be strongly related to the global increase of sales in e-Market and the accentuation of seasonal variation of this sector, we obtained a first nonlinear model that can simulate with a high level of confidence (95%) the chaotically effects of a pandemic crisis on the very volatile sector of digital retailing and allows a prediction of the general behaviour of Romanian e-Market for 2021 and 2022."

In 2015 we started a PhD thesis aiming to write a moving objects processing system (MOPS) aimed to detect near Earth asteroids (NEAs) in astronomical surveys planned within the EURONEAR project. Based on this MOPS experience, in 2017 we proposed the NEARBY project to the Romanian Space Agency, which awarded funding to the Technical University of Cluj-Napoca (UTCN) and the University of Craiovafor building a cloud-based online platform to reduce survey images, detect, validate and report in near real time asteroid detections and NEA candidates. The NEARBY platform was built and is available at UTCN since Feb 2018, being tested during 5 pilot surveys observed in 2017-2018 with the Isaac Newton Telescope in La Palma. Two NEAs were discovered in Nov 2018 (2018 VQ1 and 2018 VN3), being recovered and reported to MPC within 2 hours. Other 4 discovered NEAs were found from a few dozen possible NEA candidates promptly being followed, allowing us to discover 22 Hungarias and 7 Mars crossing asteroids using the NEARBY platform. Compared with other few available software, NEARBY could detect more asteroids (by 8-41%), but scores less than human detection (by about 10%). Using resulted data, the astrometric accurancy, photometric limits and an INT NEA survey case study are presented as guidelines for planning future surveys.

Given the profound transformations that have suffered monetary systems under the action of powerful movements due to the technological innovation, liberalization and globalization, one of the new challenge s that they face today’s economy is promoting new forms of payment including electronic money with dee p, long-term implications on the development of sustainable security. Accepting a new economic paradigm makes no sense in the absence of specific values, principles and tools. Electronic money seems to be a tool that is compatible with the (still diffuse) values and principles of the g lobal economy in the sense of bottom-up systems. Skepticism about electronic currency is a natural reacti on of those who came to enjoy global system policy rules tailored top down. The research paper is desire d to identify the role of currency in social development starting from the analysis of interpersonal values to social values and human psychology for each individual. Table of

The survey of the nearby space and continuous monitoring of the Near Earth Objects (NEOs) and especially Near Earth Asteroids (NEAs) are essential for the future of our planet and should represent a priority for our solar system research and nearby space exploration. More computing power and sophisticated digital tracking algorithms are needed to cope with the larger astronomy imaging cameras dedicated for survey telescopes. The paper presents the NEARBY platform that aims to experiment new algorithms for automatic image reduction, detection and validation of moving objects in astronomical surveys, specifically NEAs. The NEARBY platform has been developed and experimented through a collaborative research work between the Technical University of Cluj-Napoca (UTCN) and the University of Craiova, Romania, using observing infrastructure of the Instituto de Astrofisica de Canarias (IAC) and Isaac Newton Group (ING), La Palma, Spain. The NEARBY platform has been developed and deployed on the UTCN's cloud infrastructure and the acquired images are processed remotely by the astronomers who transfer it from ING through the web interface of the NEARBY platform. The paper analyzes and highlights the main aspects of the NEARBY platform development, and the results and conclusions on the EURONEAR surveys.

We propose in this paper a new method of image reconstruction by inpainting small pattern over a damaged scratch, using a variant of the parallel projection method (PPM) for solving the convex feasibility problem. The method is based on a fragmentation of the damaged region in small quadrilaterals and reconstruct the image by filling the scratch with PPM generated pattern. The algorithm is fast and directly parallelizable.

The paper presents a new method to forecast the variation of the exchange rate Euro-RON on a short period of time, using an evolutionary adaptative model of the behavior of the market and a genetic algorithm to forecast the variation of the exchange rate.

E-learning is considered in present as an important research area in the domain of education's sciences, as it has opened new ways of learning for many people. E-assessment has been widely used since the development of e-learning exist. However, what most electronic exercises and test do, is to transform the paper exercises and exams into electronic format. This is clear from the types of questions used by most e-learning and e-assessment platforms. In order to overcome such limitations and gain more control over types of questions, we have developed a model of classifying, indexing and selecting the topics for multiple choice questions. Our model was inspired from the graph theoretical knowledge model of Kasyanov and uses a graduate hierarchical representation of knowledge, from basic definitions of simple notions, concepts or principia until the relationship understanding. We used the following four grades which divide all students on novices, beginners, advanced students and expert. The novice are possess only knowledge of basic notions; the beginners can define composite concepts and exemplify them, eventually to identify connection relationship between concepts related at distance <= 2 , the advanced are able to to identify connection relationship between concepts, methods or principia related at distance grater that 2, and the experts can compare different methods or principia, by putting in evidence similarities and differences, or can propose generalizations of some concepts or methods. This classification moves the accent of the knowledge evaluation of a student from the concept definition understanding to relationship understanding. We also proposed a random computer-based selection of questions' topics in order to propose a graduated questionnaire to the students, where the questions are classified in the four levels of difficulties according with the above classification of the student's knowledge: novice questions, beginner's questions, advanced questions and, expert's questions. The final tests will contain a pondered selection of questions, from the lowest level of difficulty to the highest one. This method moves the accent of the knowledge evaluation of a student from the concept definition understanding to relationship understanding.

This paper proposes an algorithm for the Lie symmetries investigation in the case of a high order evolution equation. General Lie operators are deduced and, in the next step, the associated conservation laws are derived. Due to the large number of equations derived from the symmetries conditions, the use of mathematical software is necessary, and we employed a MAPLE application. Some models arising from physics was chosen to test the method.

The stigmergy, witch describes a class of mechanisms that mediate animal to animal interaction through the environment has used in modelling multi-agent systems, as it provides a simple framework for agent interaction and coordination. In this paper stigmergetic mechanisms are combined with the Nash's theory of non-cooperative games in order to model a concurrent multi-player transport problem. A new version of Ant Colony Optimization using multiple species is proposed.

Elliptic curve cryptography provides a higher performance than the classic cryptography mainly because shorter keys are used. This paper presents the basics of the elliptic curves, emphasizing the advantage of using them in ecommerce cryptography, this implies a certain level of fields definition for them. We also present several algorithms for scalar multiplication point and for generating strong elliptic curves. Starting from the existing ones, we present an open problem about the weakness of such a systems, in the field of large key computations.

Databases are a central component of e-business applications. They provide the storage and functional facilities (i.e. accessing transactional information) of commercial systems. This paper analyzes database models for e-commerce applications, and studies access constraints necessary to preserve the consistency of data; in particular, access scenarios in which phantoms appear are investigated.

A genetic algorithm method was used to study the economic and ecological impact of hunting activities using a Genetic Algorithm approach, applied for a version of the Stauffer - Newmann model, adapted for a particular case of a Natural Resource Economics problem: the decision about the intensity of exploitation of hunted species.

Using an evolutionary algorithm for simulation, we investigate the effects of risk-aversion and physical jumps in option pricing, especially for medium- and short-term options.