In this paper we propose an experimental content-based track recommendation system, which relies on audio feature values from Spotify Data Catalogue track lyrics and popularity ratings. In order to assess the utility of the system, we considered evaluating its accuracy on users’ list of listened tracks, by computing the precision as performance measure. However, before evaluating this performance measure, we also had to take into account the assessment of a few parameters related to feature engineering required for the functioning of both the experimental system and, ultimately, the recommendation algorithm.

Digitalization and the use of artificial intelligence (AI) in education could help both learners and teachers. In fact, young people can be considered digital natives, having, and using digital technologies from an early age to play, communicate and access information. Teachers can use these digital technologies to create attractive teaching activities, to streamline and optimize their teaching work, but also to help learners cope with the digital transformation (known as digit(all)ization - a portmanteau for two trending terms, digitization and digitalization) inherent in digital literacy. The barriers of resistance to change and digital transformation can be overcome through digital literacy, as well as the correct understanding and application of digitalization and artificial intelligence, but also providing confidence to users of digital technologies. A study was conducted on the perception of digitization, digital transformation, and the use of artificial intelligence in two Romanian universities.

Internet of Things (IoT) interference in our lives is based on the large amount of sensor data, from complex and various sources (smart cities, industrial sensors, wearable devices, Health Care IoT), collected over time but also gathered every moment. All this data came in an amazing variety of formats and values. What we can do with all this data ? There are, mainly, two directions 1) act when values thresholds were exceeded (heart rate, blood pressure, industrial critical values) or, 2) detect evolution patterns that can lead to dangerous situations (detect an increasing heart rate for a patient that can lead to critical situation in, say 5 minutes). Considering a large variety of sensors, up to past years, 2) was much more difficult to achieve but with greater impact (consider only the management of resources that can be directed to most critical situation). This paper proposes and discusses a system architecture using relational database (SQL) to store critical data, non-relational database (NoSQL) to store all data and IoT programmable gateways or a Critical Data Layer to send selected data to SQL database. Two strategies in detecting critical evolutions are discussed.

A Graphical Programming Environment is a software tool that allows developers to create, design, and manipulate code using visual elements, such as blocks, diagrams, and flowcharts. The proposed solution allows the creation for the simulation scenarios using visual blocks, and the execution of these scenarios on specific microcontrollers. This paper presents the stages of the environment: the configuration of the simulation tests, the generation of the source code, the compilation of the code, and the running of the generated executable to evaluate the results.

Apache Kafka is a distributed event streaming platform used by thousands of companies worldwide for online data exchange. The system accepts any type of data, and this means that it can be used for varied types of applications. This paper presents an application that allows the user to send or receive different messages via Apache Kafka, either immediately or based on a schedule, using a Javascript-like language for programming.

This paper investigates the requirements for a system capable to authenticate (or certify) the content that is available online. Based on an analysis of the approaches used to fight against fake news and fake online content, our proposal is based on digital signatures, and integrates several key components to fulfill the determined functional requirements. This implies that both the origin of the text (the source) and the textual online content, can be trusted by anyone that is able to verify the applied electronic signature.

Virtualization solutions used within Cloud computing have proven over time to address the problem of inefficient use of physical computing resources. Virtualization can provide high-level availability to critical applications with, thus streamlining the operation of IT infrastructure and responding quickly to changes. The paper proposes a mathematical model based on Queuing Theory aimed at ensuring a certain level of Quality of Service (QoS).

Correlating the education and training system with the evolution of today’s technologies is a complex but necessary process for training, improvement, and lifelong learning. Digital technologies are present today in all fields, and have become increasingly necessary in higher education institutions, not only to attract students, to bring them into a familiar environment, but also to initiate and improve their skills in what is an evolution in science. The digitalization of education services is necessary to have a more accessible, interactive, and personalized educational process and this also involves the use of digital technologies, elements that contribute to people’s self-education, and education outside of schools’ walls. In this paper we present aspects related to the digitalization of education, both from the perspective of educators and learners. It is a study carried out in two Romanian universities, the University of Craiova and the “Constantin Brâncuși” University of Târgu Jiu. The purpose of this work is to emphasize the necessity of digitalization, its importance, but also to emphasize the stage in which the two universities are now, in relation to what is meant by digitalization, who should be involved in the digitalization of the institution, what activities should be digitalized, knowledge of the digital signature concept or whether respondents use machine learning tools such as ChatGPT, or others. The results of this study reflect the opinion of the teachers and students of the two universities.

The pandemic crisis has meant a challenge for SMEs and a factor that can change the way of doing business. The current paper analyses the correlations between financial resources, turnover, sustainability, and digital technologies and how these components can be adapted to changes in the economy triggered by the pandemic crisis in the structure of activities carried out by SMEs. Resting on the importance of integrating the innovative, digital component to the activities of SMEs, in close connection with the financial resources component, a multicriteria research model for business has been developed, assessing the correlations between key variables and their influence on European SMEs. In order to fully define the concepts envisaged and to emphasise these correlations, multiple linear regression, clustering techniques, and correlation analysis were used. In the end, the proposed solution provided a common language through which companies can evaluate traditional processes and bring together the research components into business activities.

In this paper we present, as a case study, how the authors conducted online educational activities in some of the study programs followed by students of the Faculty of Automation, Computers and Electronics (F.A.C.E.) at University of Craiova (UCV), what were the academic results of students, and what were their opinions (expressed by answers to specific questionnaires). With this paper we want to present the impact of the COVID-19 pandemic on education and engineering skills acquired by students for the subjects taught by the three authors of this paper. We are also questioning whether important lessons can be learned from this crisis. We addressed some relevant topics: issues related to the transition from face-to-face teaching to online teaching; problems related to the online examination activity; problems related to the acquisition of practical skills by students. These issues were addressed from both the teachers’ and the students’ point of view, and the paper presents both the authors' and students' opinions (acquired during online classes or obtained through questionnaires).

The topic of cloud computing is becoming of extreme interest for trust service providers willing to move their services from a desktop-oriented approach into a more interconnected, mobile world. In our paper, we investigate and present from this perspective, several architectures that are currently available on the commercial market. The analysis covers some of the well-known commercial cloud platforms available: Amazon Web Services, Google Cloud Platform, IBM Cloud, Microsoft Azure, and Oracle Cloud. We have analyzed and identified several advantages associated with the use of these commercially available platforms with the objective of pondering the potential use of the Software-as-a-Service (SaaS) approach within an innovative Digital Enterprise making use of the traditional services of a trust service provider (including here digital signatures, digital notary, time stamping, etc.) The analysis of the above-mentioned commercial platforms is not only addressing their own intrinsic SaaS architectures but also the derived or personalized architectures that are provided for their tenants and clients.

The evolution of sensors, over a short period of time, just couple of decades, produced the rise and fast evolution of IoT (Internet of Things), from isolated "things" to "networks of things", storing data and using this data. Some of the common fields with IoT direct impact are industry, health, transportation, smart cities and smart buildings. The challenge on this new evolution is how to use the gathered data. Reports and data analysis are used from long time over big set of data and they will still remain an important purpose of this data. Recently, data received from sensors is used not only to trigger decision based on instant values but also to perform analysis on data stored and take decisions in real time, based on the data analysis. Because the data stored is huge and very diverse as format, various solutions to extract potentially dangerous data patterns in real time were studied. noSQL (non-relational database) and SQL (relational database) are used to store data in IoT systems. noSQL based solutions will store sensor data not depending on their type and format while a SQL one will keep the format with the main advantage of speed. This paper proposes two interconnected systems based on both databases: a noSQL for all data received from sensors, used later for reports and a SQL one with critical data, used to detect critical data patterns. The detection of critical data is performed on programmable gateway level and directed to the corresponding server. This paper discusses an architecture aiming to optimize critical pattern detection using jobs running on specific, customized, time interval. The time interval is chosen depending on data type. Simulation results are presented.

In this paper we present the challenges that have contributed to changes in the administrative and educational domains in our faculty, starting with the workflow for the admission process, continuing with the learning process (courses, seminars, projects, and laboratory), the evaluation methods, and eventually with the collaboration between professors and students for the implementation of diploma/dissertation projects. Also, in this paper we present the way students interact with teachers, secretary office, and faculty management. These issues were addressed from several points of view (of the professor, of the faculty management, of the administrative staff i.e. secretary office, as well as of the students). The paper presents the opinions of the authors as well as those of the students. The purpose of this paper was to study the impact of online education on the entire engineering training process. The results highlight the experiences of authors and students in our faculty.

Accurate diagnosis using histopathology images re-quires experienced pathologists, a large amount of work and time. Recent studies show that AI could be a solution to help pathologist by offering a fast and reliable help for setting a diagnosis. This paper offers a review of the latest advancements in renal cancer diagnosis using advanced AI methods, especially Convolutional Neural Networks. It includes both Computer Aided Diagnosis solutions and algorithms or frameworks that use histopathology images as input. It provides extensive data about the input databases, preprocessing methods, feature extraction, classifier architectures and results quantification. Further, it elaborates on the type of classification each algorithm offers, ranging from segmentation to benign-malignant classification and up to renal cancer subtypes differentiation or Fuhrman grade determination.

Internet of Things (IoT) impact in our daily life quickly evolves from recording basic data to process and take decisions based on complex data. Data provided by various sources (Health Care IoT, life quality, smart cities etc) came in many formats and will be used for statistical analysis and decision making, often based on data evolution and machine learning. Decisions involving data analysis over a huge database can be very time consuming. In critical time situations, system response time needs to be highly improved. This paper discusses a proposed architecture, suitable to improve the response time on systems using data analysis and decision based on data evolution. Simulation results for a system using sensors, gateways and persistence layers are presented and discussed. Considering all sensor data is sent to a non-relational database (NoSQL) suitable to store various data formats, this paper discusses the particularities of using IoT programmable gateways to send data used in critical time analysis to a fast relational database (SQL) database. In such databases, queries are very fast and, as a result, the decisions based on data evolution have an improved time response. Analysis to detect critical data patterns is triggered when data is inserted in SQL database or based on a time interval. Both strategies are discussed and analysed.

We compare multiple implementations of Dijkstra's single source shortest paths algorithm using two different data structures. The algorithms are implemented in Python programming language and the test data consisted of graphs with 1,000 vertices and up to 900,000 edges, split into sparse and dense graphs. These implementations have different theoretical time orders of complexity and the experiment aims to test if any of them is more suitable for certain types of graphs. The min-max binary heap implementation uses a min binary tree to keep the distances to the vertices. The distances to all vertices are held in an array, but their positions change, so extra logic is required to access them. The Fibonacci heap (FH) implementation uses a Fibonacci forest to keep the distances to the vertices. While implementing this data structure is more elaborate, it offers a good theoretical time order of complexity.

This paper presents a subsystem of a semi-autonomous wheelchair controlled by eye gaze. The control decision is based on video and laser scanning acquisition. Data fusion between the information provided by the two systems was used. The obtained data are processed, adapted and provided to the Eye Gaze Control system. Various configurations for the proposed system were studied. Experiments conducted using RGB-D images and on points cloud provided by the LIDAR system demonstrated the reliability and the robustness of the proposed method. The next step will involve obstacles detecting, the objects that can block a specific given path. The two systems complement each other eliminating the disadvantages of each system. In case of removing one of them, the obtained system suffers from the lack of redundancy and safety in the event of a fault (essential condition for a semi-autonomous wheelchair).

Among the agent-oriented methodologies that use goals for specication of multi-agent systems, the Goal Model for Dynamic Systems (GMoDS) method allows to specify goals during requirements engineering process and then to use them throughout the system development and at runtime. Because the semantics of the GMoDS models involves the use of object-oriented concepts we choose to express a GMoDS model in an object-oriented specication. We use Event-B as a method for both specifying the GMoDS models and implementing the semantics of the runtime model of GMoDS. Because Event-B is not an object-oriented language, the goal of our research is to add support to Event-B for object-oriented modeling by using the modularization plug-in of the Rodin framework. This aim of paper is twofold: (a) to describe an object-oriented specication in Event-B, and (b) to express a GMoDS model into an object-oriented Event-B specication.

In the pre-processing phase the video sources are split into images sequences. The salient objects are detected for the first image of each sequence and it is applied a descendent recursive video processing algorithm for construction an hypergraph structure. The salient regions correspond to the hypernodes which are built dynamically step by step as a result of the tracking algorithm. Hyperedges proper information refers to both spatial and temporal relations between two or more salient regions; these data are used for events detection. The final goal is events detection and classification on the hypergraph based. Experiments conducted using videos from sport domain demonstrated the reliability and the robustness of the proposed method. The next step will involve incidents detecting (abnormal events) within the hypergraph (corresponding to a video source).

This paper presents efforts in the direction of teaching computer programming concepts to young students (kids in the range 8-15 years old). This work is both innovative and attractive for Romanian primary and secondary schools in the field of computer programming. The authors believe that involvement in this work field could prove beneficial for the national educational policy, and consequently, for turning the interest of young generations to STEM-oriented careers.