SQL and NoSQL Databases in the Context of Industry 4.0

The data-oriented paradigm has proven to be fundamental for the technological transformation process that characterizes Industry 4.0 (I4.0) so that big data and analytics is considered a technological pillar of this process. The goal of I4.0 is the implementation of the so-called Smart Factory, characterized by Intelligent Manufacturing Systems (IMS) that overcome traditional manufacturing systems in terms of efficiency, flexibility, level of integration, digitalization, and intelligence. The literature reports a series of system architecture proposals for IMS, which are primarily data driven. Many of these proposals treat data storage solutions as mere entities that support the architecture’s functionalities. However, choosing which logical data model to use can significantly affect the performance of the IMS. This work identifies the advantages and disadvantages of relational (SQL) and non-relational (NoSQL) data models for I4.0, considering the nature of the data in this process. The characterization of data in the context of I4.0 is based on the five dimensions of big data and a standardized format for representing information of assets in the virtual world, the Asset Administration Shell. This work allows identifying appropriate transactional properties and logical data models according to the volume, variety, velocity, veracity, and value of the data. In this way, it is possible to describe the suitability of relational and NoSQL databases for different scenarios within I4.0.

A novel user review-based contextual recommender system

Recommendation systems are shrewd applications for knowledge mining that profoundly handle the problem of data overload. Various literature explores different philosophies to create ideas and recommends different strategies according to the needs of customers. Most of the work in the suggested structure space focuses on extending the accuracy of the recommendation by using a few possible methods where the principle purpose remains to improve the accuracy of suggestions while avoiding other plan objectives, such as the particular situation of a client. By using appropriate customer rating data, the biggest test for a suggested system is to generate substantial proposals. A setting is an enormous concept that can think of numerous points of view: for example, the community of friends of a client, time, mindset, environment, organization, type of day, classification of an item, description of the object, place, and language. The rating behavior of customers typically varies in different environments. We have proposed a new review-based contextual recommender (RBCR) system application from this line of analysis, in particular a novel recommender system, which is an adaptable, quick, and accurate piece planning framework that perceives the significance of setting and fuses the logical data using piece stunt while making expectations. We have contrasted our suggested calculation with pre- and post-sifting methods as they have been the most common methodologies in writing to illuminate the issue of setting conscious suggestion. Our studies show that considering the logical data, the display of a system will increase and provide better, appropriate and important results on various evaluation measurements.

SQL and NoSQL Databases in the Context of Industry 4.0

The data-oriented paradigm has proven to be fundamental for the technological transformation process that characterizes Industry 4.0 (I4.0) so that Big Data & Analytics is considered a technological pillar of this process. The literature reports a series of system architecture proposals that seek to implement the so-called Smart Factory, which is primarily data-driven. Many of these proposals treat data storage solutions as mere entities that support the architecture's functionalities. However, choosing which logical data model to use can significantly affect the performance of the architecture. This work identifies the advantages and disadvantages of relational (SQL) and non-relational (NoSQL) data models for I4.0, taking into account the nature of the data in this process. The characterization of data in the context of I4.0 is based on the five dimensions of Big Data and a standardized format for representing information of assets in the virtual world, the Asset Administration Shell. This work allows identifying appropriate transactional properties and logical data models according to the volume, variety, velocity, veracity, and value of the data. In this way, it is possible to describe the suitability of SQL and NoSQL databases for different scenarios within I4.0.

Wikidata como herramienta para elaborar ontologías y vocabularios controlados

The possibilities that Wikidata offers for the creation of ontologies and controlled vocabularies for specific knowledge domains are presented. The first step consists of exploring the properties of Wikidata items that are used to define their membership to a knowledge domain. It then becomes possible to retrieve the structure of the classes and superclasses to which the domain items belong. Finally, all the Wikidata properties used to describe the items are retrieved. This work considers a new paradigm for the processes used to create and manage controlled vocabularies, since a high degree of integration of these instruments is currently required for the management of data and digital content, which implies the application of controlled vocabularies in logical data analysis processes. For this reason, a more dynamic approach is required, being closer to the design of ontologies than to the creation of traditional documentary languages. Resumen Se muestran las posibilidades que ofrece Wikidata para la creación de ontologías y vocabularios controlados sobre dominios de conocimiento específicos. El primer paso consiste en la exploración de las propiedades utilizadas por los ítems de Wikidata para definir la pertenencia a un dominio de conocimiento. Posteriormente es posible recuperar la estructura de clases y superclases a las que pertenecen los ítems del dominio. Finalmente se recuperan todas las propiedades de Wikidata utilizadas para describir los ítems. El autor incluye una serie de reflexiones sobre el cambio de paradigma en el campo de los vocabularios controlados, puesto que en la actualidad se requiere un alto grado de integración de estos instrumentos en entornos de datos y contenidos digitales. Esta realidad implica una participación de los vocabularios controlados en procesos lógicos de análisis de datos. Por este motivo se requiere un enfoque más dinámico y cercano a las ontologías que a los lenguajes documentales tradicionales.

Theoretical and methodological aspects of personal brand formation in the digital environment

The article considers the theoretical and methodological aspects of the formation of a personal brand, describes modern approaches to the interpretation of the concepts of brand and personality brand. The main structural elements of a personal brand are analysed, its socio-psychological essence is determined. The emphasis is made on the practical significance of the formation of a personal brand, the components, properties and areas of application of a personal brand are considered.The models of personality brand formation in both offline and online environment are described in accordance with the structural and substantive transformations currently taking place in the information sphere and the factors that influence the effectiveness of communication through a personal brand. These are, first of all, such factors as the widespread of artificial intelligence technologies into everyday life, tools for logical data integration, a significant increase in the number of Internet users. All of the above factors largely determine the nature and degree of social influence of influencers on the behavior of individuals in society.In addition, much attention is paid to the analysis of existing models of personal brand formation, which form the theoretical and methodological basis of a personal brand. If we consider a brand as a tool that stimulates the consumer to a certain action, then in the case of a product brand, such an action will be the fact of buying a product or service directly. If we are talking about a personal brand, then the frequency of consumption of content created by a particular media personality will act as an action. In turn, it is possible to increase the frequency of content consumption by choosing the optimal model of brand communication with consumers. That is why it is especially relevant to study the theoretical and methodological aspects of the formation of a personal brand through online tools in the process of creating a personal brand.

Logical theory revision through data underdetermination: an anti-exceptionalist exercise

The anti-exceptionalist debate brought into play the problem of what are the relevant data for logical theories and how such data affects the validities accepted by a logical theory. In the present paper, I depart from Laudan's reticulated model of science to analyze one aspect of this problem, namely of the role of logical data within the process of revision of logical theories. For this, I argue that the ubiquitous nature of logical data is responsible for the proliferation of several distinct methodologies for logical theories. The resulting picture is coherent with the Laudanean view that agreement and disagreement between scientific theories take place at different levels. From this perspective, one is able to articulate other kinds of divergence that considers not only the inferential aspects of a given logical theory, but also the epistemic aims and the methodological choices that drive its development.

A Review on Impact Analysis of Accident Using AI

In recent years, road collisions have become a global problem and have been classified as the 10th leading cause of death in the world. Due to the large number of road losses consistently, it has become a major problem in Bangladesh. It is totally unacceptable and sad to allow a citizen to kill in a road accident. The purpose is to show you how to extract logical data from a raw database and visualize it. The results show that hourly planning, day-to-day intelligence, lunar intelligence and year-round planning allow you to look at how road accidents change over time. Two types of road accidents have occurred in particular, and data analysis of road accidents have led to conclusions that will help reduce the number of accidents.

DEVELOPMENT OF A MODEL FOR ACCOUNTING THE MATERIAL VALUES OF THE WAREHOUSE DEPOT

The methodology for calculating the total area of the warehouse of the carriage depot and the optimal size of the stock of inventory items in the carriage depot of the Joint Stock Company "Uzpasstrans". Defined formulas for determining the costs of placing and receiving all orders, costs of storing stock for a certain period, total costs. A logical data scheme is proposed that reflects the main entities necessary to automate the process of determining the inventory of goods and materials in the warehouse of the carriage depot.