Logical Structure Research Articles

Facilitating Knowledge Transfer during Code Compliance Checking Using Conceptual Graphs

The rules in building codes are composed of language, logic structure, and the embedded knowledge that requires further articulation from rule experts. This greatly increases the complexity of rule interpretation. The conceptual graph (CG) is used as a graph-based representation method to capture such knowledge and transfer it to other actors in the compliance checking process. However, due to its subjectivity, it is difficult to ensure the quality of the CG to achieve minimal knowledge loss. This paper proposes a method using reusable CG patterns to reduce the knowledge loss caused by the opacity of concepts in rules, hence better facilitating knowledge transfer using CGs. The rules and their corresponding CGs are analyzed and compared. An assessment framework is used to assess CGs for correctness, completeness, complexity, and comprehensibility. A group of reusable CG patterns is then generated based on the analysis results of concepts in existing CGs. In a case study, rules selected from two types of building codes are used to validate the proposed methods. The results successfully demonstrate the effectiveness of the CG in facilitating knowledge transfer. Moreover, the comparison of quality between original CGs and improved CGs shows that using reusable CG patterns can effectively ease the creation of new CGs and improve its consistency.

Can I Own Your NFTs? Understanding the New Attack Surface to NFTs

Recent years have witnessed the increasing popularity and market value of Non-Fungible Tokens (NFTs), along with the burgeoning of blockchains and metaverse. The media hypes often imply that NFTs are as secure as the underlying blockchains. In this work, we take a first look into the building blocks of NFTs (i.e., ownership certificates stored onchain and the metadata and digital assets stored onchain or off-chain), focusing on understanding the new attack surface and safety of these digital assets (rather than the traditional attacks on blockchains). For this purpose, we provide a detailed analysis of the logical structure of the dominant off-chain NFTs, followed by the attack surface analysis. Our study indicates that specific new attacks could be easily mounted on them. To validate our findings, we experiment by minting our own NFTs on Ethereum and demonstrate that we can successfully mount the attacks with trivial or even no cost. The cause of these new attacks is rooted in the current design of NFTs where the digital assets are decoupled from the contracts deployed on the blockchains.We discuss some future research to address these vulnerabilities.

애덤 스미스와 민주주의

The name of Adam Smith is inextricably linked with modern economics. The most fundamental goal of his academic life, however, was the study of the principles of law and government. He formally declared this goal, pursued it throughout his life, and wrote The Wealth of Nations as a partial fulfilment, contributing to his immortality as a thinker. Although Smith was not a scholar dedicated to the study of democracy, he did explore the principles of law and goverment, and his writings contain rich discussions of political decision-making issues from which we can infer his understanding of democracy. This paper reconstructs them through the lens of realising and limiting majoritarianism.
 While Smith's view was that majoritarianism should be at the centre of political decision-making, and he emphasised the role of elections as a means of realising majoritarianism, this does not mean that the path to majoritarianism is limited to elections. Rather, this paper argues that Smith saw the role of public opinion in influencing public deliberation as an important means of realising majoritarianism. In this regard, Smith identified the problem of class bias in public opinion based on socioeconomic conditions as a reason for the adoption of mercantilism, and recognized the role of the state in addressing this problem. Smith's discussion has significant relevance to the problem of the limited political role of the people in today's democracies, and the need for the active exercise of political liberty to prevent the implementation of unjust policies that violate liberty.
 At the same time, Smith also touched on the possibility of the limiting majoritarianism. Majoritarianism is typically realised through representative legislation, and Smith recognized the existence of a higher normative content that guided statutory law by regarding such parliamentary legislation as aiming to be consistent with the rules of natural justice that arise from the sympathy of human nature. Smith also emphasized the existence of the state's duty of equal treatment as a normative principle that guides legislation in the area of police. Essentially, Smith recognized that representative decision-making is constrained by more fundamental norms. On the other hand, by locating the source of this limitation in the moral principles or political will emanating from the members of the state as a whole, Smith is credited with showing that the limitation of representative decision-making and the ideology of majoritarianism may not be incompatible. By viewing a constitution based on popular sovereignty as a product of the will of the majority, being higher democratic law-making than ordinary legislation, Smith's position has a similar logical structure to the current debate that even if a constitution appears to limit representative legislation, it can ultimately be reconciled with the ideology of majoritarianism.

A general framework for modelling trade-offs in adaptive behaviour.

An animal's behaviour can influence many variables, such as its energy reserves, its risk of injury or mortality, and its rate of reproduction. To identify the optimal action in a given situation, these various effects can be compared in the common currency of reproductive value. While this idea has been widely used to study trade-offs between pairs of variables, e.g. between energy gain versus survival, here we present a unified framework that makes explicit how these various trade-offs fit together. This unification covers a wide range of biological phenomena, highlighting similarities in their logical structure and helping to identify knowledge gaps. To fill one such gap, we present a new model of foraging under the risk of predation and damage accumulation. We conclude by discussing the use and limitations of state-dependent optimisation theory in predicting biological observations.

Administrative Discretion: Questions and Answers (Part 3)

This article completes a series of three scientific publications planned by the Editorial Board of the Siberian Law Review, the Authors of which discuss the problem of administrative discretion, which is very relevant for Russian administrative legal theory and legal practice, in a question-answer format. Contrary to the opinion justified by Petr P. Serkov in the previous article about the impossibility of a fruitful study of administrative discretion without referring to the “analytical potential of the mechanism of administrative legal relations”, Yuri P. Solovey gives arguments indicating the unsuitability of this “logical structure” for studying legal realities. From his point of view, the use of this artificial and meaningless concept, without a doubt, is a violation of the well-known methodological principle “Occam’s Razor”: one should not multiply things unnecessarily. In this regard, PetrP. Serkov was asked two questions: firstly, could he conduct, within the framework of this article, an indicative analysis of a specific discretionary administrative act using the “logical structure of the mechanism of administrative legal relations”, which would make it possible to draw a conclusion about the legality (illegality ) of such an act, and, secondly, what is its relation to the principles of administrative procedures as legal means of control over administrative discretion and the need for their extensive legislative consolidation. Anticipating the answers to the questions posed, Petr P. Serkov critically analyzes the arguments of “discretionary disagreement” of the specified Author. It is concluded that the phenomenon of administrative discretion covers any managerial decision made by any official of state executive bodies and local governments in the exercise of any of the powers assigned to him. Such a vision of administrative discretion implies a significant adjustment of the method of its research, the priorities of which should be a person, his consciousness and psyche. Concerning the first of the questions asked, Petr P. Serkov, using the “analytical potential of the mechanism of legal relations”, analyzes a hypothetical situation in which a police officer performs a discretionary administrative action by stopping a vehicle. The Author argues that the named “potential” clarifies not only what administrative discretion is, but also how it is formed and what it is intended for. Answering the second question, Petr P. Serkov notes that the procedural legal regulation of the activities of state executive bodies will certainly bring positive effects to the phenomenon of administrative discretion, but it is not clear to what extent the principles of administrative procedures are able to prevent illegal administrative discretion. It should be taken into account that scientific controversy regarding the understanding of legal principles has been going on for decades without the prospect of reaching a doctrinal consensus. In general, the discussion of the essence of administrative discretion shows, according to Petr P. Serkov, the imperfection of the current state and the conceptual vulnerability of the methodology of conducting scientific research and scientific controversy.

Epidemic spreading dynamics on two-layer complex networks

Recent studies have shown that many real-world systems can be described by multi-layer complex networks. In this paper, the concept of layers is introduced to construct a traffic-driven SIR epidemic spreading model on “logical-physical” layered network. Based on the peak density of infected nodes and the ultimate density of recovered nodes, we investigate the features of epidemic spreading on layered network. Through numerical simulations, it is shown that traffic flow greatly influences the intensity and scope of epidemic spreading. By comparing the effects of four kinds of two-layer networks generated by ER random network model and BA scale-free network model on epidemic spreading, we found that the homogeneity of logical or physical network structure can promote the spread of epidemic more than heterogeneous networks. This work may be of service to design traffic-driven epidemic prevention and control strategies.

Dyslexic Aba: a game to help children with dyslexia

This article presents a game to help professionals in the field of Education and Psychology using the Applied Behavior Analysis methodology in teaching literacy to children with dyslexia. The game is aimed at dyslexic children, aiming to improve learning and the achievement of reading and writing, aiming to challenge the user to form scrambled words with inverted, similar or facing down letters according to a picture shown, such as the word "car”, which for the dyslexic will show “artrph”. together with some inverted or rotated "r", the word size increases as the user changes levels, the game uses a "drag and drop" style, in which the user drags the letter from the shuffled frame and places it in the proper position to form the word. The methodology does not adopt negative stimuli "Game Over" and in parallel works with positive stimuli using sound and visual effects and obtaining points. The application has a functional logical structure that is easy to use, contextualizing different environments of a house, with personalized design, standardized, animated and colorful objects, uniting gameplay, education, teaching and positive stimuli in the literacy process of dyslexic people.

Multi-level autonomous integrity monitoring method for multi-source PNT resilient fusion navigation

For the integrity monitoring of a multi-source PNT (Positioning, Navigation, and Timing) resilient fusion navigation system, a theoretical framework of multi-level autonomous integrity monitoring is proposed. According to the mode of multi-source fusion navigation, the framework adopts the top-down logic structure and establishes the navigation source fault detection model based on the multi-combination separation residual method to detect and isolate the fault source at the system level and subsystem level. For isolated non-redundant navigation sources, the system level recovery verification model is used. For the isolated multi-redundant navigation sources, the sensor fault detection model optimized with the dimension-expanding matrix is used to detect and isolate the fault sensors, and the isolated fault sensors are verified in real-time. Finally, according to the fault detection and verification results at each level, the observed information in the fusion navigation solution is dynamically adjusted. On this basis, the integrity risk dynamic monitoring tree is established to calculate the Protection Level (PL) and evaluate the integrity of the multi-source integrated navigation system. The autonomous integrity monitoring method proposed in this paper is tested using a multi-source navigation system integrated with Inertial Navigation System (INS), Global Navigation Satellite System (GNSS), Long Baseline Location (LBL), and Ultra Short Baseline Location (USBL). The test results show that the proposed method can effectively isolate the fault source within 5 s, and can quickly detect multiple faulty sensors, ensuring that the positioning accuracy of the fusion navigation system is within 5 m, effectively improving the resilience and reliability of the multi-source fusion navigation system.

Application of fuzzy controllers in automatic ship motion control systems

Automatic ship heading control is a part of the automatic navigation system. It is charged with the task of maintaining the actual ship’s course angle or actual ship’s course without human intervention in accordance with the set course or setting parameter and maintaining this condition under the effect of disturbing influences. Thus, the corrective influence on deviations from a course can be rendered by the position of a rudder or controlling influence that leads to the rotary movement of a vessel around a vertical axis that represents a problem, which can be solved with the use of fuzzy logic. In this paper, we propose to consider the estimation of the efficiency of fuzzy controllers in systems of automatic control of ship movement, obtained by analysis of a method of the formalized record of a logic conclusion and structure of the fuzzy controller. The realization of this allows to carry out effective stabilization of a course angle of a vessel taking into account existing restrictions.

Approach to knowledge management and the development of a multi-agent knowledge representation and processing system

Objectives. A multi-agent knowledge representation and processing system (MKRPS) comprises a distributed artificial intelligence system designed to solve problems that are difficult or impossible to solve using monolithic systems. Solving complex problems in an MKRPS is accomplished by communities of intelligent software agents that use cognitive data structures, logical inference, and machine learning. Intelligent software agents are able to act rationally under conditions of incompleteness and ambiguity of incoming information. The aim of the present work is to identify models and methods, as well as software modules and tools, for use in developing a highly efficient MKRPS.Methods. Agent-based modeling methods were used to formally describe and programmatically simulate the rational behavior of intelligent agents, expert evaluation methods, the mathematical apparatus of automata theory, Markov chains, fuzzy logic, neural networks, and reinforcement learning.Results. An MKRPS structure diagram, a multi-agent solver, and microservices access control diagram were developed. Methods for distribution of intelligent software agents on the MKRPS nodes are proposed along with algorithms for optimizing the logical structure of the distributed knowledge base (DKB) to improve the performance of the MKRPS in terms of volume, cost and time criteria.Conclusions. The proposed approach to the development and use of intelligent software agents combines knowledge-based reasoning mechanisms with neural network models. The developed MKRPS structure and DKB control diagram includes described methods for optimizing the DKB, determining the availability of microservices used by the agents, ensuring the reliability assurance and coordinated functioning of the computing nodes of the system, as well as instrumental software tools to simplify the design and implementation of the MKRPS. The results demonstrate the effectiveness of the presented approach to knowledge management and the development of a high-performance problem-oriented MKRPS.

A Learned Query Rewrite System

Query rewriting is a challenging task that transforms a SQL query to improve its performance while maintaining its result set. However, it is difficult to rewrite SQL queries, which often involve complex logical structures, and there are numerous candidate rewrite strategies for such queries, making it an NP-hard problem. Existing databases or query optimization engines adopt heuristics to rewrite queries, but these approaches may not be able to judiciously and adaptively apply the rewrite rules and may cause significant performance regression in some cases (e.g., correlated subqueries may not be eliminated). To address these limitations, we introduce LearnedRewrite, a query rewrite system that combines traditional and learned algorithms (i.e., Monte Carlo tree search + hybrid estimator) to rewrite queries. We have implemented the system in Calcite, and experimental results demonstrate LearnedRewrite achieves superior performance on three real datasets.

Системный подход к процессу обучения

This article is addressed to teachers with technical education. It considers an important aspect of pedagogical science related to the systemic approach of the learning process. It shows how the systemic approach is interrelated with the regularities of the learning process in higher education, as it is more qualitative and modern. It provides more opportunities for assimilation of learning information, which improves assessments in controlling the quality of knowledge. It is noted in the article that the logical structure of the training course obeys systemic laws and increases the efficiency of learning. An example of the logical structure of the discipline “Engineering Graphics” is given. It is shown that learning, as well as any pedagogical action, always has a goal.

Hierarchical Motion Planning and Tracking for Autonomous Vehicles Using Global Heuristic Based Potential Field and Reinforcement Learning Based Predictive Control

The autonomous vehicle is widely applied in various ground operations, in which motion planning and tracking control are becoming the key technologies to achieve autonomous driving. In order to further improve the performance of motion planning and tracking control, an efficient hierarchical framework containing motion planning and tracking control for the autonomous vehicles is constructed in this paper. Firstly, the problems of planning and control are modeled and formulated for the autonomous vehicle. Then, the logical structure of the hierarchical framework is described in detail, which contains several algorithmic improvements and logical associations. The global heuristic planning based artificial potential field method is developed to generate the real-time optimal motion sequence, and the prioritized Q-learning based forward predictive control method is proposed to further optimize the effectiveness of tracking control. The hierarchical framework is evaluated and validated by the numerical simulation, virtual driving environment simulation and real-world scenario. The results show that both the motion planning layer and the tracking control layer of the hierarchical framework perform better than other previous methods. Finally, the adaptability of the proposed framework is verified by applying another driving scenario. Furthermore, the hierarchical framework also has the ability for the real-time application.

Unravelling the enablers of Industry 4.0 in Indian automobile industry amid COVID-19: an integrated TISM and fuzzy MICMAC approach

PurposeThis study aims to identify the key enablers for the adoption of Industry 4.0 (I4.0) in the automobile industry of India, which has been severely impacted by COVID-19. Adopting I4.0 will provide organizations greater flexibility and resilience during the COVID-19 pandemic.Design/methodology/approachBased on the literature review and experts’ opinions, 21 enablers were identified. Further, contextual relationships among the identified factors and a hierarchical digraph was developed by using the total interpretive structural modelling (TISM) technique. Finally, fuzzy cross-impact matrix multiplication applied to classification (MICMAC) analysis was conducted to classify the enablers into different categories based on their dependence and driving power.FindingsThe results indicate that top management support, clarity on government policy, strategic vision on I4.0 and development of new industrial policy are the most influential factors, with the highest driving power placed at the bottom of the TISM hierarchical model. Furthermore, agile workforce, smart HR practices and IT standardization and security are identified as linkage enablers with the most driving and dependency power.Practical implicationsThe hierarchical TISM model and fuzzy MICMAC approach provide a comprehensive understanding of the I4.0 implementation process through a visual, logical structure to the managers. It will help the researchers and practitioners understand the contextual relationship among various enablers in fostering the I4.0 adoption process and digital reorganization in the automobile industry during the COVID-19 pandemic.Originality/valueThis study provides a holistic TISM hierarchical framework on I4.0 adoption that will elevate the next maturity level of innovation adoption and may act as a blueprint for automobile industries during the COVID-19 pandemic.

On Novel Results about the Algebraic Properties of Symbolic 3-Plithogenic and 4-Plithogenic Real Square Matrices

Symbolic n-plithogenic sets are considered to be modern concepts that carry within their framework both an algebraic and logical structure. The concept of symbolic n-plithogenic algebraic rings is considered to be a novel generalization of classical algebraic rings with many symmetric properties. These structures can be written as linear combinations of many symmetric elements taken from other classical algebraic structures, where the square symbolic k-plithogenic real matrices are square matrices with real symbolic k-plithogenic entries. In this research, we will find easy-to-use algorithms for calculating the determinant of a symbolic 3-plithogenic/4-plithogenic matrix, and for finding its inverse based on its classical components, and even for diagonalizing matrices of these types. On the other hand, we will present a new algorithm for calculating the eigenvalues and eigenvectors associated with matrices of these types. Also, the exponent of symbolic 3-plithogenic and 4-plithogenic real matrices will be presented, with many examples to clarify the novelty of this work.

Temporalities of Aged Care: Time Scarcity, Care Time and Well-Being in Danish Nursing Homes

ABSTRACT Aged care staff in Danish nursing homes feel the pressures of time scarcity acutely. But what does this mean for the well-being of residents? Using the concept “care time” we consider subjective experiences of time to make sense of the multiplicity of temporal experiences in nursing home care. We will show how the temporal structures of a neoliberal institutional care logic is at odds with what residents expect from care time. Finally, drawing on a phenomenological understanding of well-being, we explore how residents’ temporal orientation to the present and the past can be drawn on to enhance well-being.

Boolean Logic Computing Based on Neuromorphic Transistor

AbstractGeneral‐purpose computers usually use logic gate computing units based on complementary metal oxide semiconductors (CMOS). Due to the separate memory and computing units in Von Neumann architecture, data transmission requires great energy and time consumption. Developing novel neuromorphic devices and comprehensively investigating their logical computing mode are crucial to achieve high‐performance and low‐power neuromorphic computation. Here, a systematic summary of Boolean logic computing based on emerging neuromorphic transistors is presented. This summary encompasses logical operation modes, materials, device structures, and working mechanisms. The input mode of Boolean logic operation is classified into electrical input, optical input, and synergistic optical/electrical input. Besides, additional modulation strategies to construct programmable logic functions by electrical, optical, and thermal signals are also summarized. These strategies hold great significance as they enable dynamic reconfiguration of logic operations and provide neuromorphic devices with decision‐making capabilities. Finally, the application prospects and current challenges to Boolean logic computing based on dendritic integration are discussed from the aspects of device integration, synergistic input/modulation modes, auxiliary peripheral circuit, software/hardware system, etc. It is believed that comprehensive investigations on neuromorphic Boolean logic operations are crucial to push forward the development of future neuromorphic computing toward high efficiency and high integration density.

On Validity

The way in which validity has been conceptualized has changed throughout the years. The focus in validation studies shifted from evaluating distinct components of validity to developing a comprehensive argument for the use and interpretations of test scores. The argument-based approach to validity incorporates the distinct types of the componential approach, underscores Messick’s attention to construct validity, highlights the need for evidence of the evidence-gathering approach, and combines it all into one logical argumentative structure. Such a comprehensive argument is now an indispensable part of validity studies (Dursun & Li, 2021).

Task-driven cleaning and pruning of noisy knowledge graph

Many knowledge graphs, especially those that are collaboratively or automatically generated, are prone to noise and cross-domain entries, which can impede domain-specific applications. Existing methods for pruning inaccurate or out-of-domain information from knowledge graphs often rely on topological graph-pruning strategies. However, these approaches have two major drawbacks: they may discard logical structure and semantic information, and they allow multiple inheritance. To address these limitations, this study introduces KGPruning, which is a novel approach that can effectively clean and prune noisy knowledge graphs by guiding tasks with a given set of concepts and automatically generating a domain-specific taxonomy. Specifically, KGPruning employs a graph hierarchy inference method that is based on the Agony model to precisely identify and eliminate noisy entries while striving to preserve the underlying hierarchy of semantic relations as much as possible. Furthermore, to establish a tree-structured taxonomy, KGPruning integrates semantic relations and structural characteristics to effectively eliminate out-of-domain information and multiple inheritance. Through extensive experimental evaluations conducted on open benchmark datasets as well as large-scale real-world problems, the superior performance of KGPruning over state-of-the-art methods is demonstrated on the task of pruning noisy knowledge graphs.

OpenFog-Compliant Application-Aware Platform: A Kubernetes Extension

Distributed computing paradigms have evolved towards low latency and highly virtualized environments. Fog Computing, as its latest iteration, enables the usage of Cloud-like services closer to the generators and consumers of data. The processing in this layer is performed by Fog Applications, which are decomposed into smaller components following the microservice paradigm and encapsulated into containers. Current state-of-the-art container orchestrators can manage hundreds of simultaneous containers. However, Kubernetes, being the de facto standard, does not consider the application itself as a top-level entity, which limits its orchestration capabilities. This raises the need to rearchitect Kubernetes to benefit from application-awareness, which refers to an orchestration method optimized for managing the applications and the set of components that comprise them. Thus, this paper proposes an application-aware and OpenFog-compliant architecture that manages applications as first-level entities during their lifecycle. Furthermore, the proposed architecture allows the definition of organizational structures to group subordinated applications based on user-defined hierarchies. This logical structuring makes it possible to outline how orchestration should be shaped to reflect the operating model of a system or an organization. The proposed architecture is implemented as a Kubernetes extension and provided as an operator.