<abstract>
<title style='display:none'>Abstract</title>
The authors of this paper are bringing a fresh look on the challenges and opportunities for the tech companies and the technical education institutions in the aftermath of the COVID-19 pandemic and the impact that this event had on the society on a global scale, for all demographic categories. As being the first pandemic, which had to be faced by the “digitized society”, during two or so years of physical distancing various challenges have arisen for our highly interconnected fast-paced and dynamic world, but in an equal manner, several opportunities and revelations were discovered amid the necessary sanitary measures. This material aims to highlight both the strong points and the weak points that our society has shown during the last few years, but also the highly interesting social and psychological studies resulted after these events.
</abstract>

Digital Competences and Digital Life in the Post Pandemic World

<abstract>
<title style='display:none'>Abstract</title>
Sound is the result of mechanical vibrations that set air molecules in motion, causing variations in air pressure that propagate as pressure waves. Represented as waveforms, these visual snapshots of sound reveal some of its characteristics. While waveform analysis offers limited insights, audio features provide a quantitative and structured way to describe sound, enabling data-driven analysis and interpretation. Different audio features capture various aspects of sound, facilitating a comprehensive understanding of the audio data. By leveraging audio features, machine learning models can be trained to recognize patterns, classify sounds, or make predictions, enabling the development of intelligent audio systems. Time-domain features, e.g., amplitude envelope, capture events from raw audio waveforms. Frequency domain features, like band energy ratio and spectral centroid, focus on frequency components, providing distinct information. In this paper, we will describe three time-domain and three frequency-domain features that we consider crucial and widely used. We will illustrate the suitability of each feature for specific tasks and draw general conclusions regarding the significance of sound features in the context of machine learning.
</abstract>

An Overview on Sound Features in Time and Frequency Domain

<abstract>
<title style='display:none'>Abstract</title>
In order to gain insight into how to create a successful game, a developer should learn about the end user of the product, the player. For this exact reason, there must be a deeper understanding of the effects games can have on the one who plays them. The main question addressed in this paper is “How can the games positively affect the player on a psychological and emotional level?”. This question has been divided into 3 different sub-question. To answer them, a combination of thematic analysis and literature study was used. Multiple studies have been previously made on the relationship between video games and the human mind, either focusing on the negative or on the positive effects. This paper has a new approach, consisting of dividing the benefits into categories determined by the main reason a player chooses to play games. The main 6 categories were established empirically, and 200 answers were arranged under the category most fitting for each. A total of 14 benefits were found for the previously mentioned categories. Additionally, 5 less noticeable benefits have been included into a new category.
</abstract>

The Positive Effects of Video Games on the Human Mind

<abstract>
<title style='display:none'>Abstract</title>
The Smart City is not a new concept. In fact, the digital city appeared in the information era and the wireless city emerged in the Internet era, but the Smart City had not been clearly defined until the digital era. Unlike traditional informatization, a Smart City is not simply the combination of informatization in all industries. Not only is a smart city a top-leadership project, it reshapes the digital capabilities of all industries in a city, while also addressing systematic challenges.
This paper presents Huawei perspective on Smart City development, including the conceptual framework, governance, type, connectivity, structural enablers. The paper also describes the strategic vision and a Smart City construction path, from the strategic planning, solution design and implementation.
</abstract>

Key Success Factors for Smart City Construction

<abstract>
<title style='display:none'>Abstract</title>
This paper will explore how Metaverse will facilitate the acceleration of industrial innovation and help the industry digitalize their global high-volume manufacturing environment. The authors conducted a live workshop (with around 30 participants) as part of the international conference Sibiu Innovation Days 2022. The workshop’s proceedings and output is described here below.
</abstract>

How Metaverse will influence Industrial Innovation (Extended Abstract SID2022)

<abstract>
<title style='display:none'>Abstract</title>
The purpose of this paper is to highlight the importance of active and continued public engagement in the debate regarding the regulation of artificial intelligence (AI). The results of several studies are presented, in reference to the benefits of this technology, its risks and limitations, and the shortcomings of traditional and hybrid approaches. Certain conceptual and practical approaches are presented, that aim to facilitate the participation of citizens and other stakeholders in the decision-making process of AI governance.
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Data, governance and tackling the “tragedy of the commons”

<abstract>
<title style='display:none'>Abstract</title>
Various studies on local crop monitoring are presented in the literature, however there is insufficient research on low-cost IoT weather stations that can obtain weather information over a long period of time. To overcome the difficulties described above, this paper proposes the development of an IoT weather station for low-cost, sustainable and multi-functional agricultural crop monitoring.
The objective of the work is to develop a local weather observation device for agricultural crops, to set up a server for storing and providing meteorological information and to perform an analysis of the acquired weather data.
The weather station architecture developed and proposed in this project consists of four main blocks: sensor and controller module, power module, local data storage module and data communication module (gateway).
</abstract>

Implementation of a weather station to monitor agricultural crops

<abstract>
<title style='display:none'>Abstract</title>
In a reactive Kripke model, evaluation of logical operators can cause reconfiguration of the model in which the formula is evaluated. Therefore, in reactive Kripke frames, the evaluation of a logical formula in a world depends both on the world in which the evaluation is made and on the worlds it has passed through previously. The result is an extended semantics, which can specify a class of modal logics more comprehensive than the class specified by ordinary Kripke frames. This paper introduces a metamodel for reactive Kripke frames, based on the concept of categorical sketch. We believe that the categorical sketch is an appropriate metamodel for specifying a Kripke frame model.
</abstract>

A Categorical Metamodel for Reactive Kripke Frames

<abstract>
<title style='display:none'>Abstract</title>
This paper describes step by step the modelling and simulation of the open loop scalar command for a three-phase induction machine with known parameters, which operates in motor regime. In order to change the electromagnetic torque and implicitly the rotor speed, in this paper the solution of applying a positive mechanical torque from outside the machine was chosen, without dynamically adjusting the supply voltage. The chosen mathematical model for the induction machine is the one described by Krause’s equations, written in a stationary reference frame. The simulations were done on the Matlab/Simulink simulation environment and the behaviour of the machine was monitored under the working conditions listed above.
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Simulink implementation of the open-loop scalar command for a three-phase induction machine model

<abstract>
<title style='display:none'>Abstract</title>
Nowadays saving the planet’s resources plays a very important role in improving our life conditions. The purpose of the paper is to supply the separately excited dc motor by using different chopper circuits. A very sustainable solution is to replace the resistors from classic theory with dc choppers for better efficiency. The armature voltage can be controlled by using IGBT chopper and the PWM signal received from controller is done with a dedicated block created by MATLAB environment. The advantages of developing this technique are that the speed changes proportionally with armature voltage and inversely with field voltage by keeping field and armature voltage constant respectively. The chopper designed with IGBT and Diode modules offers good control at any frequency value and the speed, the armature current and electromagnetic torque of DC motor can be control. In this paper, different choppers had been simulating were working in four quadrants for supply an excited dc motor by using Matlab program.
</abstract>

Different Chopper Types for Supply Separately Excited DC Motor

<abstract>
<title style='display:none'>Abstract</title>
This article aims to elaborate on a few strategies designed for validating data encoded as a QR code. As the use-cases for such validation schemes vary widely as the demand for such practices is continuously increasing, the present article will represent a comparative study of checksum, hashing, as well as asymmetric encryption algorithms for the offline validation of claims transmitted through the payload of the exchanged data. Results are evaluated based on different criteria impacting the reliability, such as the size of the QR code and the resulting security.
</abstract>

Methods for data validation using QR codes

<abstract><title style='display:none'>Abstract</title>The Corona period created great challenges in the teaching and learning process. This presentation describes a research based on studying the subject of big data using virtual escape rooms. Due to the period it was decided that the final task in the Big Data course would be to build a virtual escape room that deals with a topic from the world of Big Data. The aim of the study was to examine how the understanding of various topics related to Big Data is sharpened when they are taught through virtual escape rooms. Each group of students chose a topic from the world of big data and built a virtual escape room around it. Peer learning was then performed, and each group edited rooms of other groups, so that each group learned about a variety of topics related to the big data world. By monitoring peer learning it was possible to assess the nature of the learning process experienced by the group. This unique learning allows for flexibility in terms of time and place in holding meetings. The interactions between the various group members contribute to enrichment the knowledge and the development of creative ideas.According to the results of the study, this type of learning sharpened different skills among the participants - social, communicative and thinking. It also developed a deep understanding when the escape room practically demonstrates the topic of big data in an optimal way through a variety of representations. During the activity in the escape room there is created an interesting and original connection between the materials and the ideas, open to a variety of interpretations. Digital tools are used effectively and creatively that contribute to understanding the message (Kemp, 2018).</abstract>

Studying big data using virtual escape rooms

<abstract><title style='display:none'>Abstract</title>Document clustering is a problem of automatically grouping similar document into categories based on some similarity metrics. Almost all available data, usually on the web, are unclassified so we need powerful clustering algorithms that work with these types of data. All common search engines return a list of pages relevant to the user query. This list needs to be generated fast and as correct as possible. For this type of problems, because the web pages are unclassified, we need powerful clustering algorithms. In this paper we present a clustering algorithm called DBSCAN – Density-Based Spatial Clustering of Applications with Noise – and its limitations on documents (or web pages) clustering. Documents are represented using the “bag-of-words” representation (word occurrence frequency). For this type o representation usually a lot of algorithms fail. In this paper we use Information Gain as feature selection method and evaluate the DBSCAN algorithm by its capacity to integrate in the clusters all the samples from the dataset.</abstract>

DBSCAN Algorithm for Document Clustering

<abstract><title style='display:none'>Abstract</title>The extensive implementation of Internet of Things (IoT) solutions and its wide popularity to the public over the past decade enabled emergent applications that provide sophisticated, proactive health care solutions that can improve the quality of life of individuals. This work proposes an IoT architecture and implements a prototype solution that allows its users to improve their physical activity by collecting vital signs using wearables and other environmental and habitual information in order to monitor their activity and propose behaviors in a smart way that will allow them to achieve their preset goals. The focus is on the increased usability of the system employing refined solutions like voice recognition and smart visualization to enable its seamless use while offering an interoperable architecture that will enhance its flexibility. The prototype implementation offers a proof of concept evaluation of the proposed system, applying state of the art technologies and using existing hardware and popular gadgets..</abstract>

FitPi: Wearable IoT solution for a daily smart life

<abstract><title style='display:none'>Abstract</title>This paper presents a forecasting method of the electricity consumption and production in a household equipped with photovoltaic panels and a smart energy management system. The prediction is performed with a Long Short-Term Memory recurrent neural network. The datasets collected during five months in a household are used for the evaluations. The recurrent neural network is configured optimally to reduce the forecasting errors. The results show that the proposed method outperforms an earlier developed Multi-Layer Perceptron, as well as the Autoregressive Integrated Moving Average statistical forecasting algorithm.</abstract>

Modeling Electricity Consumption and Production in Smart Homes using LSTM Networks

<abstract>
<title style='display:none'>Abstract</title>
This paper presents a "smart" clothing product implemented as a jacket that contains sensors, a processing unit for display and interaction. The system has the ability to remotely read the data provided by the sensors, ensuring the monitoring of several parameters of the wearer.
The following characteristics have been considered: body temperature and humidity, atmospheric temperature, pressure and altitude, the heart beat and number of steps converted into the number of calories consumed and traveled distance.
The data is acquired and processed by an Arduino AT Mega 2560, via the I2C bus, digital ports and analog to digital converters, depending on the type of sensors. The processed information is printed on a 128x64 pixel display. To be able to view more pages of information, one can interact with the 4-key keyboard that has been connected to the digital input ports or through a proximity sensor, which will function as a gesture sensor.
The processed information can also be accessed from a web server, built on the ESP8266 Wi-Fi module, connected to Arduino's TX/RX lines. A mobile phone or another device can connect to the Access Point and open a web page which displays the values of all sensors, as well as other information. The embedded system was inserted on a jacket and wired according to the sensors and modules usage.
</abstract>

Development of a smart clothing product using an Arduino platform

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International Journal of Advanced Statistics and IT&C for Economics and Life Sciences

 Publishing House and Owner: Lucian Blaga University of Sibiu, Romania  The International Journal of Advanced Statistics and IT&amp;C for Economics...

 Publishing House and Owner: Lucian Blaga University of Sibiu, Romania  The International Journal of Advanced...