Agora University Editing House: Journals
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A NEW RELATIONSHIP FOR ECONOMICS AND EDUCATIONAL SCIENCES: FINANCIAL EDUCATION
Full text linkAmong the many areas of dialogue between economics and educational sciences, one common object of study has now clearly emerged: economic and financial education, which was created to raise the literacy levels of the adult population and young people. Indeed, more and more decisions in everyday life are linked to economic and financial aspects. The current economic and financial knowledge of the population is not adequate to the needs as it comes mainly from financial socialisation processes; it is instead necessary for schools and not only the banking and insurance world to deal with these new educational processes. However, in order to introduce these topics, schools must train teachers who do not have adequate knowledge. In Romania, this is a recent issue, which is why it was decided to launch a new research project
Some issues on the correlation between wage income and labour productivity
Full text linkIn Romania, both the business environment stakeholders and the academics consider that the path on reaching the average level of development of the European Union and implicitly the adoption of the Euro currency, can be achieved only by improving the standard of living that is the citizens’ income, which can be reached only by increasing labour productivity. One of the objectives of the European Union is to reduce the disparities between regions, as confirmed by the evolution of GDP/ capita in the less prosperous Eastern Europe countries in comparison with the more developed EU Members States from Western Europe. There are a number of factors impacting the labour productivity and wage incomes, and the onset of the COVID 19 pandemic has accelerated the adoption of automation, digitalisation and remote work, which will significantly contribute to the disappearance of less skilled jobs and the consolidation of those who are highly qualified ones, the latter being less sensitive to the adoption of new technologies.  
NOTES ON THE ASSIGNMENT OF CONTRACT IN THE NEW ROMANIAN CIVIL CODE
Full text linkReduced to its basic functioning, the legal operation of assignment of contract implies a global transfer of the contractual position of one party, assignor, from a contract concluded with the ceded contractor, to a third party, assignee. If the legal operation as such does not seem to raise complications, it was an object of dispute in Romanian civil law even before the New Romanian Civil Code in force since 2011, considering the personal nature of the obligation relationship, especially with regard to the passive element of the obligation. Considering the debates around this topic in the legal doctrine of the Romanian Civil Code of 1864 and following certain arguments advanced in French civil law, the New Romanian Civil Code explicitly recognizes the assignment of contract as a distinct legal figure with specific effects in Articles 1315-1320. This article intends to analyse the legal regime of the assignment of contract, from the debates in the legal doctrine around this topic in both Romanian and other legal systems to the specific legal provisions which address the assignment of contract, starting with the notion of assignment of contract, the form of the assignment, the moment in which the assignment occurs, the effects the transfer has on the assignor, the legal exceptions which can be formulated by the ceded contractor and the warranty obligations of the assignor
THE IMPORTANCE OF ANALYZING THE MAIN ANTI-COMPETITIVE PRACTICES IN VIEW OF CREATING AN UNDISTORTED COMPETITIVE ENVIRONMENT
Full text linkProtecting fair competition by suppressing anti-competitive practices is a topical issue and a priority in the context of a functional market economy, the final stated goal in competition matters being to protect the interests of consumers by creating and developing a normal competitive environment
Sentiment Analysis using Improved Novel Convolutional Neural Network (SNCNN)
Full text linkSentiment Analysis is an important method in which many researchers are working on the automated approach for extraction and analysis of huge volumes of user achieved data, which are accessible on social networking websites. This approach helps in analyzing the direct falls under the domain of SA. SA comprises the vast field of effective classification of user-initiated text under defined polarities. The proposed work includes four major steps for solving these issues: the first step is preprocessing which holds tokenization, stop word removal, stemming, cleaning up of unwanted text information like removing of Ads from Web pages, Text normalization for converting binary format. Secondly, the Feature extraction is based on the Bag words, Word2Vec and TF-ID which is a Term Frequency-Inverse Document Frequency. Thirdly, this feature selection includes the procedure for examining semantic gaps along with source features using teaching models and this involves target task characteristic application for Improved Novel Convolutional Neural Network (INCNN). The Feature Selection accompanies the procedure of Information Gain (IG) and PCC which is a Pearson Correlation Coefficient. Finally, the classification step INCNN gives out sentiment posts and responses for the user-based post aspects which helps in enhancing the system performance. The experimental outcome proposes the INCNN algorithm and provides higher performance rather than the existing approach. The proposed INCNN classifier results in highest accuracy
Cassava Leaf Disease Identification and Detection Using Deep Learning Approach
Full text linkAgriculture is the primary source of livelihood for about 60% of the world's total population according to the Food and Agricultural Organization (FAO). The economy of the developing countries is solely dependent on agriculture commodities. As the world population is increasing at faster pace, the demand for food is also escalating tremendously. In recent days, agriculture is experiencing an automation revolution. Hence the introduction of disruptive technologies like Artificial Intelligence plays a major role in increasing agricultural productivity. AI enabled approaches would help in overcoming the traditional challenges faced in agriculture practices, by automating various agriculture related tasks. Nowadays, farmers adopt precision farming which uses AI techniques namely in crop health monitoring, weed detection, plant disease identification and detection, and forecast weather, commodity prices to increase the yield. As there is scarcity of manpower in agriculture sector, AI based equipment like bots and drones are used widely. Crop diseases are a major threat to food security and the manual identification of the diseases with the help of experts will incur more cost and time, especially for larger farms. The machine-vision based techniques provide image based automatic process control, inspection, and robot guidance for pest and disease control. It provides automated process in agriculture, paving way for improved efficiency and profitability. Various factors contribute for plant diseases, which includes soil health, climatic conditions, species and pests. The proposed chapter elaborates on the use of deep learning techniques in the leaf disease detection of Cassava plants. The chapter initially describes the evolution of various neural network techniques used in classification and prediction. It describes the significance of using Convolutional Neural Network (CNN) over deep neural networks. The chapter focuses on classification of leaf disease in Cassava plants using images acquired real time and from Kaggle dataset. In the final part of the chapter, the results of the models with original and augmented data were illustrated considering accuracy as performance metric
A Personalized mHealth Monitoring System for Children and Adolescents with T1 Diabetes by Utilizing IoT Sensors and Assessing Physical Activities
Full text linkThe problem of diabetes mellitus is becoming alarming due to the increase in morbidity among children. Patients are undergoing vital insulin replacement therapy, the dose depends on the level of glucose in the blood. The glucose level prediction program, taking into account the impact of physical activity on the body, the use of mobile health capabilities will allow us to develop personalized tactics for a child patient and minimize the risks of a critical health condition. The target group of this study are children and adolescents with type 1 diabetes. This study provides an IoT based mHealth monitoring system, including sensors, medical bracelets, mobile devices with applications. The mobile healthcare application for personalized monitoring can implement the functions of more effectively targeting young users to support their own health and improve the quality of life. In addition to monitoring blood glucose levels, the effect of physical activity on the condition of patients is also taken into account. The use of the proposed method for calculating the probable change in the patient’s blood glucose level after the end of physical activity will allow the doctor to make individual recommendations for the diet before the start of physical activity and its intensity
Application of B2C digital marketing
Full text linkThe purpose of this paper is to understand the application of digital B2C marketing. Companies market directly to end customers or decision-makers through B2C marketing. Most B2C customers base their decisions on how they feel about a product or service, not on facts or how useful it is. B2C marketers can take advantage of this by developing customized content that appeals to the emotions of their target audience
Modern options for financing real estate investments
Full text linkThe realities of the period we live in with limited resources, uncertainties, speculations, radical upheavals, put their mark on the entities in many respects. The situation requires a rethinking of the business so that it can remain viable, to meet the needs of customers and to obtain a maximum profit. The decision-making process is one that thus outlines the major importance it has for each entity. The options that the entity can use to finance its investments are the objective of this material, our analysis aims to present the main characteristics of these options
Optimization of Three-dimensional Face Recognition Algorithms in Financial Identity Authentication
Full text linkIdentity authentication is one of the most basic components in the computer network world. It is the key technology of information security. It plays an important role in the protection of system and data security. Biometric recognition technology provides a reliable and convenient way for identity authentication. Compared with other biometric recognition technologies, face recognition has become a hot research topic because of its convenience, friendliness and easy acceptance. With the maturity and progress of face recognition technology, its commercial application has become more and more widespread. Internet finance, e-commerce and other asset-related areas have begun to try to use face recognition technology as a means of authentication, so people’s security needs for face recognition systems are also increasing. However, as a biometric recognition system, face recognition system still has inherent security vulnerabilities and faces security threats such as template attack and counterfeit attack. In view of this, this paper studies the application of threedimensional face recognition algorithm in the field of financial identity authentication. On the basis of feature extraction of face information using neural network algorithm, K-L transform is applied to image high-dimensional vector mapping to make face recognition clearer. Thus, the image loss can be reduced