Web-Based Online Queue Design at Puskesmas Siak Hulu I Kabupaten Kampar-Riau

Increasing patient satisfaction in this case, especially Puskesmas as the government agency that provides health services for the community, will certainly have an impact on the quality of service from the Puskesmas Itself. One of them with an efficient queuing system. A good queue will support regularity in an agency. Previously, analysis and calculation of queuing time had been carried out using the Kolgomorov-Smirnov compatibility test at the Puskesmas Siak Hulu I Kabupaten Kampar- Riau, and the results obtained an average of six working hours of patient care. This research is a pilot project that was carried out as a form of increasing effectiveness and efficiency in Puskesmas. The research has been completed and the results are the basis for this research and further research. The purpose of the current research is to make an online queuing system design, where later the results of this design are used to create a web-based online queuing system. The design is adapted to the existing queuing model at the Puskesmas, namely the Sigle Channel-Multi Steps queuing model. System development using System Development Life Cycle (SDLC) consisting of, analysis, design, implementation, and maintenance. The design phase is carried out in three stages, namely conceptual modeling, database design, and interface design. The design starts from making the proposed Rich-Picture, then carries out the predetermined design stages. With this design, it is hoped that in the future it will facilitate the process of developing a web-based online queuing system.

Аlgorithmization of the knowledge base in service of passenger cars

The article considers the architecture of conceptual modeling of the knowledge base, which creates a model of the subject area in the form of many concepts and relationships between them. This approach is based on the concept of a mobile software agent, which is implemented and functions as an independent specialized computer program or an element of artificial intelligence. Ensuring the use of subject area knowledge has become one of the driving forces of the recent surge in the study of artificial intelligence. For example, for models of many different subject areas it is necessary to formulate the concept of time. This representation includes the concepts of time intervals, time points, relative measures of time, etc. If one group of scientists develops a detailed knowledge base, others can simply reuse it in their subject areas using their own database. Creating explicit assumptions in the subject area, which underlie the implementation, makes it easy to change the assumptions when changing our knowledge of the subject area. The process of conceptualization of TO and P, first of all, involves the development of databases in research areas for the formalization and systematization of knowledge about the characteristics of this area of entities and phenomena. That is, the use of concepts in the field of maintenance in a consistent manner in relation to theories of knowledge. Ultimately, the paper updated mathematical modeling, algorithmization and implementation of intelligent systems in the field of maintenance, which will help automate the process of diagnosis and inspection of all car systems, facilitate fault prevention and improve the maintenance process and modernize the maintenance system itself. The approach of algorithmization of the base of knowledge of a condition of the car in each moment of time considered in work gives the chance to reduce time of stay of the car in the service center and to reduce considerably expenses for passing of MOT at service of cars.

Techniques of Linguistic Cognitive Manipulation in the Information and Psychological Confrontation Environment

The article is devoted to the scientific understanding of the linguistic and cultural factors of shaping external ideology of governance in Ukraine during the preparation and conduct of a series of low-intensity conflicts (“color revolutions”) in 2004-2014. Using linguistic methods of semantic, structural, contextual, discourse and communicative analysis, the author studies verbal forms of linguistic cognitive manipulation with the public opinion of the Ukrainian society focusing on the techniques of polyphonic attack, conceptual modeling and reframing. Communicative strategies and methods of indoctrination of the population are viewed in the environment of the information and psychological war launched by the US-led collective West in the digital space of mass media and the worldwide web with the aim of alienating Ukraine from the geopolitical space of Russia and turning it into an antipode state of the Russian Federation. The author focuses on verbal forms and means of indoctrination identified in communicative strategies of disinformation, data blocking, falsifying truth, fake messages, tabooing of signs, distortion of the true semantic meaning and substitution of concepts that are used by subjects of information and psychological influence in the synergetic coupling of media resources of the media of Ukraine and the collective West. The author concludes that some processes are underway in the interdiscursive environment of the “post-Maidan” Ukraine that structure a new dominant information need of the society around the image of Russia as an enemy and aggressor. Russian linguistic and cultural pattern holders demonstrate speech behavior in Ukraine that has been formed under the external ideology of governance and illustrates the destructive changes in the values of Russian self-identity, which is a consequence of linguistic cognitive manipulation of the public opinion under the imposed information model of total Russophobia.

Capturing the Basics of the GDPR in a Well-Founded Legal Domain Modular Ontology

The primary goal of the General Data Protection Regulation (GDPR) is to regulate the rights and duties of citizens and organizations over personal data protection. Implementing the GDPR is recently gaining much importance for legal reasoning and compliance checking purposes. In this work, we aim to capture the basics of GDPR in a well-founded legal domain modular ontology named OPPD (Ontology for the Protection of Personal Data). Ontology-Driven Conceptual Modeling (ODCM), ontology layering, modularization, and reuse processes are applied. These processes aim to support the ontology engineer in overcoming the complexity of the legal knowledge and developing an ontology model faithful to reality. ODCM is used for grounding OPPD in the Unified Foundational Ontology (UFO). Ontology modularization and layering aim to simplify the ontology building process. Ontology reuse focuses on selecting and reusing Conceptual Ontology Patterns (COPs) from UFO and the legal core ontology UFO-L. OPPD intends to overcome the lack of a representation of legal procedures that most ontologies encountered. The potential use of OPPD is proposed to formalize the GDPR rules by combining ontological reasoning and Logic Programming.

Biologically Feasible Generative Neural Network Architecture with Effective Concept Learning Capacity

Representations play an essential role in the learning of artificial and biological systems due to their capacity to identify characteristic patterns in the sensory environment. In this work we examined latent representations of several sets of images, such as basic geometric shapes and handwritten digits, produced by generative models in the process of unsupervised generative learning. A biologically feasible neural network architecture based on bi-directional synaptic connection equivalent in training and processing to a symmetrical autoencoder was proposed and defined. It was demonstrated that conceptual representations with good decoupling of concept regions can be produced with generative models of limited complexity; and that incremental evolution of architecture can result in improved ability to learn data of increasing conceptual complexity, including realistic images such as handwritten digits. The results demonstrate potential of conceptual representations produced as a natural platform for conceptual modeling of sensory environments and other intelligent behaviors.

UFO: Unified Foundational Ontology

The Unified Foundational Ontology (UFO) was developed over the last two decades by consistently putting together theories from areas such as formal ontology in philosophy, cognitive science, linguistics, and philosophical logics. It comprises a number of micro-theories addressing fundamental conceptual modeling notions, including entity types and relationship types. The aim of this paper is to summarize the current state of UFO, presenting a formalization of the ontology, along with the analysis of a number of cases to illustrate the application of UFO and facilitate its comparison with other foundational ontologies in this special issue. (The cases originate from the First FOUST Workshop – the Foundational Stance, an international forum dedicated to Foundational Ontology research.)

Multilevel Privacy Assurance Evaluation of Healthcare Metadata

Healthcare providers are legally bound to ensure the privacy preservation of healthcare metadata. Usually, privacy concerning research focuses on providing technical and inter-/intra-organizational solutions in a fragmented manner. In this wake, an overarching evaluation of the fundamental (technical, organizational, and third-party) privacy-preserving measures in healthcare metadata handling is missing. Thus, this research work provides a multilevel privacy assurance evaluation of privacy-preserving measures of the Dutch healthcare metadata landscape. The normative and empirical evaluation comprises the content analysis and process mining discovery and conformance checking techniques using real-world healthcare datasets. For clarity, we illustrate our evaluation findings using conceptual modeling frameworks, namely e3-value modeling and REA ontology. The conceptual modeling frameworks highlight the financial aspect of metadata share with a clear description of vital stakeholders, their mutual interactions, and respective exchange of information resources. The frameworks are further verified using experts’ opinions. Based on our empirical and normative evaluations, we provide the multilevel privacy assurance evaluation with a level of privacy increase and decrease. Furthermore, we verify that the privacy utility trade-off is crucial in shaping privacy increase/decrease because data utility in healthcare is vital for efficient, effective healthcare services and the financial facilitation of healthcare enterprises.