Logical Tools Research Articles

Economic Assessment of Seasonal Unevenness in Railway Infrastructure Loading

The article considers the problem of seasonal uneven transportation and its impact on transport infrastructure loading. The objective of the study is to develop scientifically sound recommendations for monitoring seasonal unevenness of transportation and infrastructure loading based on its adequate assessment; conducting economic assessment of the impact of seasonality of transportation on the indicators of current and investment activity of railway transport; making recommendations to further reduce unevenness of transportation, or at least prevent its growth. The authors solved the following tasks: a reasoned, logically structured sequence of economic assessment of the impact of seasonality of transportation on the indicators of current and investment activities of railway transport was formed, and scientifically based recommendations were proposed to further reduce uneven transportation (toprevent its growth). The following methods were used: logical and analytical tools, methods of statistical analysis, economic-mathematical modelling and technical and economic calculations. As a result of the study, the authors revealed that seasonal uneven loading of railway infrastructure leads to a decrease in quality of transportation and a deterioration in the market image of the railway industry, an increase in operating costs and cost of transportation, that is, to a decrease in efficiency and competitiveness of railways. The uneven transportation negatively affects the effectiveness of investments in development of railway transport. The analysis made it possible to formulate a theoretical model of influence of seasonal unevenness of railway infrastructure loading on efficiency of its use and development. It is advisable to use the methodological toolkit for assessing seasonal unevenness of railway infrastructure loading for its in-depth retrospective analysis, identifying the main factors affecting unevenness indicators and determining the maximum permissible level of seasonal unevenness. The developed model of influence of seasonal unevenness of loading on use and development of railway infrastructure allows to carry out economic assessment of seasonal unevenness, is a tool to improve planning and management of transportation activities and development of railways. The reduction in seasonal unevenness of transportation should be considered as a factor increasing the economic efficiency of not only the current, but also investment activity of the railway transport, while its growth should be considered as a specific type of risk for effectiveness of implementation of railway infrastructure development projects.

A formally verified authentication protocol in secure framework for mobile healthcare during COVID-19-like pandemic

Existing schemes in the realm of mobile healthcare (also, e-Healthcare) based on cloud and IoMT (Internet of Medical Things) do not ensure end-to-end security and are not compliant with HIPAA (Health Insurance Portability and Accountability Act). It is also very difficult often for these schemes to obtain evidence from the cloud in case of security breaches. In addition to these issues, mobile healthcare applications are prone to various types of attacks and formal proof is often unavailable. In this work, we propose our community cloud framework in an IoMT setting that ensures end-to-end security and circumvents many of the existing negative aspects using the Trusted Platform Module (TPM). We provide necessary proofs using BAN logic and Scyther tool. Also, we show that the energy consumption and the costs of communication and computation for our proposed protocol are far less than that of the existing protocols. We have implemented our protocol using Kotlin language in Android Studio ensuring all the required security properties.

Modeling the possibilities of economic adaptation of trade enterprises and hospitality industry in the context of epidemiological zoning

The article identifies the negative impact of the coronavirus crisis on the expected efficiency of retail, hotel, restaurant and tourism businesses. The aim of the paper is to develop a methodological algorithm for short-term forecasting of opportunities to restore the effective activity of enterprises under quarantine restrictions.Seasonal component adjustments were performed in the Demetra+ software. Modeling the recovery of effective activity included an assessment of the influence of macroparameters on the dynamics of an enterprise’s sales volumes under pre-quarantine conditions, defining the size of economic losses, determining coefficients of macroindicators’ dynamic influence under conditions of differentiation of quarantine restrictions, constructing a matrix of multiple regression equations, which clearly demonstrates the forecast prospects for restoring the effective activity of enterprises, depending on the quarantine zoning. A situational model of the possible scenario dynamics of enterprises’ trade turnover was built taking into account the quarantine zoning and the logical transformational algorithms of influence on variable system parameters caused by it. The thermometer principle was used as a fuzzy logic tool to consider the specifics of the dynamics of various linguistic variables and bring the forecast model as close as possible to the epidemiological zoning logic. Approbation of the methodology revealed a clear correlation between the severity of quarantine restrictions and the expected growth of enterprise activity amounts. In a more advanced form, the method should be used for short-term macroeconomic forecasting when determining quarantine restrictions and epidemiological zoning.

A strategy of quick hierarchization of road bridge maintenance activities

The control and maintenance of infrastructures is a crucial aspect for the sustainability and development of the economic and social activities of a country. The managing authorities, in order to preserve the efficiency and safety of the traffic flows, have to deal with a rather old infrastructure asset that is often in a non-optimal conservation state with an increasing degradation process induced by the increment of the traffic loads and by the environmental actions. The situation is exacerbated by the limited economic resources and reduced workforces at disposal with the consequence that an order of priority in the maintenance plain is anavoidable. This work provides a logical tool to define the hierarchy of the maintenance plain of the infrastructural heritage based on one hand on the structure state of conservation and on the other hand on the context in which the construction is integrated

Scenarios as a tool supporting decisions in urban energy policy: The analysis using fuzzy logic, multi-criteria analysis and GIS tools

At present, cities characterised by high building intensity, which requires a sufficiently large amount of energy for proper functioning. This necessity means that energy planning should focus on the one hand on saving and reducing energy consumption, but also on introducing renewable energy sources (RES) in a way that ensures sustainable urban development. Social and economic issues that condition equality in access to energy and allow its rational use are a severe problem in cities. The article proposes a way of identifying the criteria that have the most significant impact on energy policy effects and the use of renewable energy in cities. The tests results affecting the energy potential of cities were analysed using various energy scenarios. The fuzzy logic and the Geographic Information System (GIS) were used to assess them. To show the differences between the scenarios, the Energy Potential Index (EPI) was developed to determine the feasibility of implementing individual energy scenarios in six urban districts. The results of this study present the importance of different criteria that influence the decisions made and the applied energy policy scenarios in the city areas. The approach that is important regardless of the goals is the intensity of development. The most desirable area for the implementation of the energy policy, taking into account renewable energy sources, is the city quarter with high-intensity multi-family housing. The study conclusions provide guidelines for decision-makers shaping the energy policy in the city in the form of the EPI indicator - a comparative assessment of the location and development of renewable energy systems to increase energy potential, equality in access to energy and mitigation of the effects of climate change.

Jørgen Jørgensen’s Relation to Logical Positivism

Between the two World Wars, Jørgen Jørgensen was a central figure in Danish philosophy and internationally recognized, as his teacher Harald Høffding had been before World War 1. When in the late 1920s Jørgensen established contact with the movement that would later be called logical positivism, he found a group of philosophers of his own age who advocated empiricism, the tools of formal logic and the Unity of Science, and who shared his anti-metaphysical approach to philosophy. He became one of the movement’s organizers and wrote its history, but he was only for a short period influenced by especially Rudolf Carnap’s philosophy of logic. Although Jørgensen was never an uncritical member of the movement, he is often considered as a central representative of logical positivism in Scandinavia.

Development the models of oil Formation volume factor using artificial neural networks and fuzzy logic models

The oil formation volume factor with high accuracy method is a key role in the petroleum industry due to the wide use of it in the petroleum industry. It is readily obtained from laboratory PVT measurements or may be calculated from correlations such as Vasquez. Nevertheless, these measurements are either not available, or very costly to require. Thus, there is an essential need for a reliable method for obtaining the oil formation volume factor. The aim of this paper is predicting the oil formation volume factor using Artificial Neural Networks (ANN) and Fuzzy Logic (FL) tools. It is worth noticing that a data set consisting 800 of laboratory measurements on oil formation volume factor was gathered from different published resources. The paper also will use the current available models presented in the literature for predicting the oil formation volume factor and compare the average percent error of these models with the new base models. The results obtained depicted that new models were able to find the oil formation volume factor with higher accuracy than the current models for predicting oil formation volume factor. It is conspicuous results that the Artificial Neural Networks (ANN) model with coefficient 0.994 and Fuzzy Logic (FL) with coefficient 0.9993 provide the oil formation volume factor. The new developed models from the ANN and Fl models outperformed the prior models for the oil formation volume factor. It is obviously observed that the new models can be used to predict the oil formation volume factor with a high accuracy as compared with the other models used to be calculated from correlations such as Vasquez and Beggs.

Scaling exact inference for discrete probabilistic programs

Probabilistic programming languages (PPLs) are an expressive means of representing and reasoning about probabilistic models. The computational challenge ofprobabilistic inferenceremains the primary roadblock for applying PPLs in practice. Inference is fundamentally hard, so there is no one-size-fits all solution. In this work, we target scalable inference for an important class of probabilistic programs: those whose probability distributions arediscrete. Discrete distributions are common in many fields, including text analysis, network verification, artificial intelligence, and graph analysis, but they prove to be challenging for existing PPLs.We develop a domain-specific probabilistic programming language called Dice that features a new approach to exact discrete probabilistic program inference. Dice exploits program structure in order to factorize inference, enabling us to perform exact inference on probabilistic programs with hundreds of thousands of random variables. Our key technical contribution is a new reduction from discrete probabilistic programs to weighted model counting (WMC). This reduction separates the structure of the distribution from its parameters, enabling logical reasoning tools to exploit that structure for probabilistic inference. We (1) show how to compositionally reduce Dice inference to WMC, (2) prove this compilation correct with respect to a denotational semantics, (3) empirically demonstrate the performance benefits over prior approaches, and (4) analyze the types of structure that allow Dice to scale to large probabilistic programs.

Maximality Principles in the Hyperuniverse Programme

In recent years, one of the main thrusts of set-theoretic research has been the investigation of maximality principles for V, the universe of sets. The Hyperuniverse Programme (HP) has formulated several maximality principles, which express the maximality of V both in height and width. The paper provides an overview of the principles which have been investigated so far in the programme, as well as of the logical and model-theoretic tools which are needed to formulate them mathematically, and also briefly shows how optimal principles, among those available, may be selected in a justifiable way.

PROBLEMATIKA, PERANAN DAN FUNGSI PERENCANAAN PENDIDIKAN DI INDONESIA

This research is a literature study related to problems, the role and function of education planning in Indonesia. Data collection was carried out through various sources that can be used in relation to the problems of Islamic multicultural education in Indonesia. In searching some literature using a search engine or maybe it is easier to index any type of document. For example, we use Google Scholar with a query containing Social Network clauses, of course the number of clauses will be generated with a list of related documents. The conclusion in this study is that the existence of problems in education in Indonesia also causes constraints in education planning in Indonesia. The education system in Indonesia must be planned by considering various things. Planning is an activity to see the future in terms of determining policies, priorities and costs of education by prioritizing the existing realities in the economic, social and political fields to develop the state education system and students served by this system. This means that in planning the national education system must consider economic, social, political and cultural factors. The education system in our country has undergone many changes, this may be due to educational planning that does not understand the aspects involved in it, so that our national education system is unable to match the conditions of Indonesian society and the resulting graduates are not relevant to the needs of the workforce. This makes it difficult for our country's human resources (HR) to compete with foreign human resources. The functions and roles of educational planning are as follows: 1) As a guide for the implementation of educational development activities. 2) As a means of controlling the implementation of education development. 3) As a tool to ensure the quality of educational development. 4) As a means of achieving educational goals effectively and efficiently. 5) As a means to ensure the smooth achievement of educational development goals. 6) As a means of clarifying the vision, mission and strategy of education development. 7) As a logical and systematic tool to change the education system for the better.

Social circular economy indicators: Selection through fuzzy delphi method

• The FDM reduces uncertainty associated with data collection and judgement elicitation. • The formulation of social circular indicators is relevant to increase sustainability. • Eradicating poverty and hungry are now priority for circular economy experts. • Social indicators proposed can help monitor progress of sustainable development goals. • This work could be integrated in the SLCA method for the selection of the indicators. Circular economy (CE) promotes better resource use by reducing waste and keeping products and materials in use and supports natural system regeneration. However, the social dimension of CE is virtually non-existent. Moreover, there is no holistic framework to select the social indicators to be used to assess the positive or negative impacts of CE strategies. Thus, this paper proposes an approach to identify key social indicators of CE through qualitative (Delphi) and quantitative (fuzzy logic) tools that objectively account for the uncertainty associated with data collection and judgement elicitation and number of attributes (indicators) by considering the vagueness of the data. The research includes a hybrid approach to explore multiple social indicators, a survey of social indicators for CE experts to arrive at a consensus regarding the social measures that are required and an analysis of the resulting survey data to converge on the key social indicators relevant to CE.. The results show that the most relevant social indicators for CE experts are consumer health and safety, followed by poverty, food security and governance. These findings suggest that indicators such as the eradication of poverty and hunger are priorities for CE experts. This could be attributed to the power of CE practices to help achieve several Sustainable Development Goals (SDGs) targets, particularly those that are most directly related to CE strategies.

Maximizing durability of vanadium redox flow battery by evaluating electrolyte-repair-point

• Electrolyte repair is a key operation to tackle capacity fade in VRFB. • Estimation of logical timing of electrolyte repair is pivotal for durability of VRFB. • Proposition of ERP Max is vital. • Electrolyte repair before ERP Max imparts durability to VRFB. Repairing of imbalanced electrolytes is a key process, responsible for durable operation of vanadium redox flow battery (VRFB). The scientific community is aware and capable of repairing the imbalanced electrolytes using various remixing techniques. However, till date, no technical rationale is available to know, when the remixing operation should be carried out during operation of the flow battery. This study addresses the issue by assessing degree of imbalance of the vanadium redox flow battery by measuring in-situ state-of-charge of positive and negative electrolytes represented by SoC e+ , and SoC e- , respectively. Interestingly, it is found that during the operation of the flow battery, there is existence of two operational regimes; the first where SoC e+ < SoC e- and the second where SoC e+ > SoC e- . This inflection point is proposed as electrolyte-repair-point (ERP Max ), which is a logical tool to identify right time for the electrolyte repair operation to maximize the efforts of repairing process. Information of ERP Max maximizes the outcome of remixing or repairing process and is instrumental to recognize the regime of battery operation to harness durability of VRFB by designing suitable battery management system.

Application of Dissolved Gas Analysis in Assessing Degree of Healthiness or Faultiness with Fault Identification in Oil-Immersed Equipment

The healthiness and or faultiness of oil-immersed electrical equipment using dissolved gas characterization has remained a critical and challenging task in power systems. Dissolved gas analysis (DGA) continues to be the utmost preferred technique of detecting mainly slow evolving thermal and electrical faults. However, DGA can reveal more than just faults in equipment. This research looks at broad areas where DGA can be applied to determine the healthiness or faultiness of equipment in addition to fault identification. In equipment considered normal—i.e., fault-free—DGA can give the degree of healthiness (DOH) based on Rogers ratios C2H2/C2H4 &lt; 0.1, 0.1 &lt; CH4/H2 &lt; 1, and C2H4/C2H6 &lt; 1, plus the 3 &lt; CO2/CO &lt; 10 ratio for identifying fault-free devices. This answers the question: How healthy or normal is the equipment? Similarly, when these ratios are violated, it signifies the presence of faults, and two things ought to be determined. One is to identify the type of fault(s), which has been the norm. The other thing that can be evaluated is the degree of faultiness (DOF), based on the extent to which the ratios have been violated. Rarely has this been done. This might answer the question for the same fault class: How severe is the fault? To synthesize the DOH and/or DOF, fuzzy logic is applied. To diagnose faults, fuzzy logic and fuzzy-evidential tools are proposed. The accuracy and effectiveness of the proposed fuzzy techniques are better than those of the IEC60599 and Rogers methods, and they are comparable to those of the Duval Triangle 1 and Pentagon 1 methods using the six IEC faults. Results from DOF evaluation have shown electrical faults to be more impactful relative to the rest.

13.C. Workshop: Epistemic and ethical innovations in public health research

Abstract About 90% of the biomedical data accessible to researchers was created in the last two years. These data have a very meaningful impact both in creating public policies on health, as well as public health research. This certainly implies complex technical problems on how to store, analyse and distribute data, but it also brings relevant epistemological issues. In this workshop we will present some of such problems and discuss how epistemic innovation is key in order to tackle ethical issues related to the use of big data in public health research. Databases implied in public health research are so huge that they rise relevant questions about how scientific method is applied, such as what counts as evidence of a hypothesis when data can not be directly apprehended by humans, how to distinguish correlation from causation, or in which cases the provider of a database can be considered co-author of a research paper. To consider such issues nowadays, current protocols do not hold, and we need innovation in methodological and epistemic procedures. At the same time, due to the fact that a relevant deal of such biomedical data is linked to individual people, and how medical data can be used to predict and transform human behavior, there are ethical questions difficult to solve as they imply new challenges. Some of them are related to communication issues, so patients and citizens understand these new ethical problems that didn't arise before the development of big data; others relate to the way in which public health researchers can and can't store, analyse and distribute information, and some others relate to the limits on which technologies are ethically, safe and which ones bring erosion of basic human rights. The four contributions in the workshop analyse these questions in some detail. During the workshop we will present a coherent understanding on what is epistemic innovation, some logical tools necessary for its development, and then we will discuss several cases on how epistemic innovation applies to different aspects of public health research, also commenting its relevance when tackling ethical problems that may arise. Key messages The workshop deepens the ethical and epistemological innovations involved in public health policies and research, specially related to big data. The workshop analyses novel aspects of public health ethics

НЕ-факторы, темпоральная логика и нечетко-логические инструменты в гибридных моделях управления рисками импортозамещения

НЕ-факторы, темпоральная логика и нечетко-логические инструменты в гибридных моделях управления рисками импортозамещения

SCIENTIFIC RESEARCH COMPONENT OF TRAINING FUTURE PhDs IN THE CONDITION OF GRADUATE EDUCATION

The article actualizes the problem of improving the quality of scientific-pedagogical research and further description and systematization of the obtained results and data by applicants for higher education of the third (educational-scientific) level. An important way to solve the issue of organizational principles of pedagogical experiment in terms of training applicants for the third (educational-scientific) level of higher education specialty 015 Vocational education, fields of knowledge 01 Education / Pedagogy on educational and professional programme "Theory and methods of vocational education" for new educational scientific programmes determine the necessity of graduate students to study the relevant specialty of the discipline "Methods of organization and mathematical methods of processing the results and data of pedagogical experiments." Peculiarities of structure of the mentioned course are analyzed, as well as its practice-oriented context, educational and organizational measures of introduction in the conditions of preparation of applicants of the third (educational-scientific) level of higher education are outlined. The general strategy of teaching the course, based on the semantic and comparative characteristics of the concepts "methods of organizing a pedagogical experiment" and "methods of pedagogical experiment", is revealed. The implementation of this approach is established on the allocation of three conceptual spaces ("pedagogical experiment", "organization", "methodology") and their pairwise coordination through the following concepts: "experiment", "pedagogical experiment", "organization of pedagogical experiment", "method of organization of pedagogical experiment", "methods of pedagogical experiment". Based on a comparative analysis of the concept of "pedagogical experiment organizing methods" on strategic (programmatically-organized historical, logical, technical, organizational, informational, procedural and other tools aimed at achieving the goals and objectives of pedagogical research) and tactical (complex of theoretical and empirical methods, combination of which allows to investigate the pedagogical process in its structural units and parts, comprehensively review the problem under research, all its aspects and parameters) levels diluted didactic tasks of the discipline. Effective mastering of methods of planning of experimental work, mathematical methods of modeling and optimization of research processes by postgraduate students is predicted.

The political uses of prohibitionist "science:" The case of cannabis and psychedelics

This article analyzes the use of science as a political tool in prohibitionist logic, adopting an externalist perspective. Prohibitionism strives to have its political-moral precepts be considered scientific, that is, the result of an ideologically neutral research process. The article analyzes the case of cannabis and psychedelics to show how prohibitionism has only resorted to "science" to hide its political-moral agenda, while ignoring the results of scientific research that did not fit its apriorisms. Finally, we argue that drug policies should be based on scientific evidence and on certain basic values - the defense of public health, social cohesion, Human Rights - such that an analysis in terms of power relations would allow us to better understand the contradictory relationships between science and drug policies.

Ordered models for concept representation

AbstractBasic notions linked with concept theory can be accounted for by partial order relations. These orders translate the fact that, for an agent, an object may be seen as a better or a more typical exemplar of a concept than anyother. They adequately model notions linked with categorial membership, typicality and resemblance, without any of the drawbacks that are classically encountered in conjunction theory. An interesting consequence of such a concept representation is the possibility of using the tools of non-monotonic logic to address some well-known problems of cognitive psychology. Thus, conceptual entailment and concept induction can be reexamined in the framework of preferential inference relations. This leads to a rigorous definition of the basic notions used in the study of category-based induction.

Development of a dress design knowledge base (DDKB) based on sensory evaluation and fuzzy logic

PurposeThe purpose of this paper is to develop a dress design knowledge base (DDKB), which is expected to be further applied to a personalized dress recommendation system.Design/methodology/approachDress design knowledge can be expressed as the relationship between designer's fashion perceptions of different dress elements. In order to extract dress design knowledge, a dress shape ontology (DSO) is firstly developed, which can be further used to form a dress element matrix (DEM). A perceptual descriptive space of the dress (DPDS) is developed for the description of the designer's fashion perception of dress. Through a standard sensory evaluation procedure performed by experienced experts (designers), the expected relationship can be obtained. This relationship is then mathematically simulated by fuzzy logic tools for the expected DDKB.FindingsIn this paper, a DDKB has been developed. The established knowledge base has been validated, and it can be further applied to dress recommendation system for a specific consumer.Originality/valueThis study introduces the concept of knowledge base to the area of dress individualized design. The knowledge-based design process based on sensory evaluation and fuzzy logic can efficiently solve the individualization of dress design in traditional design processes, which can provide a novel way to dress design individualization.

Logic simulation tool for RSFQ circuits accepting arrivals of multiple pulses in a clock period

A logic simulation tool for RSFQ circuits is proposed. It can treat RSFQ logic circuits containing signal lines accepting multiple pulses in a clock period. Logic circuits can be implemented in compact area by utilizing RSFQ specific gates and feeding multiple pulses into a gate input in a clock period. For treating circuits containing signal lines accepting multiple pulses in a clock period, a new description method is proposed. A logic simulation tool treating netlists described based on the proposed method was implemented. Examples of designs having signal lines accepting multiple pulses to be implemented in compact area are shown, and simulation results obtained with the tool are shown.