Active Rules Research Articles

Calculation of cSW at one-loop order for Brillouin fermions

The Brillouin action is a Wilson-like lattice fermion action with a 81-point stencil, which was found to ameliorate the Wilson action in many respects. The Sheikholeslami-Wohlert coefficient cSW of the clover improvement term has a perturbative expansion cSW=cSW(0)+g02cSW(1)+O(g04). At tree-level cSW(0)=r holds for Wilson and Brillouin fermions alike. We present the Feynman rules for the Brillouin action in lattice perturbation theory, and employ them to calculate the one-loop coefficient cSW(1) with plaquette or Lüscher-Weisz gluons. Numerically its value is found to be about half that of the Wilson action. Published by the American Physical Society 2024

Scalable Action Mining Hybrid Method for Enhanced User Emotions in Education and Business Domain

Education sector ,Business field,Medical domain and SocialMedia,huge amounts of data in a single day . Mining this data can provide a lot of meaningful insights on how to improve user experience in social media, users engage in these domains collect and cherish the data as they hope to find patterns and trends and the golden nuggets that help them to accomplish their goal. For example: How to improve student learning; how to increase business profit ability; how to improve user experience in social media; and how to heal patients and assists hospital administrators. Action Rule Miningmines actionable patterns which are hidden in various datasets. Action Rules provide actionable suggestions on how to change the state of an object from an existing state to a desired state for the benefit of the user. There are two major frameworks in the literature of Action Rule mining namely Rule-Based method where the extraction of Action Rules is dependent on the pre-processing step of classification rule discovery and Object-Based method where it extracts the Action Rules directly from the database without the use of classification rules.Hybrid Action rule mining approach combines both these frame works and generates complete set of Action Rules. The hybrid approach shows significant improvement in terms computational performance over the Rule-Based and Object-Based approach. In this work we propose a novel Modified Hybrid Action rule method with Partition Threshold Rho, which further improves the computational performance with large datasets.

Mit Prinzipienethik aus der Plattformfalle. Ein Verfahren für Digitalstrategie und erneuerte Legitimation der öffentlich-rechtlichen Medien

Based on the conflicts that arise for journalism due to platformization, the article presents an approach with which it should be possible to justify, in terms of media ethics, whether and how public service media (PSM) may create content for commercial platforms. Principlism is proposed as a suitable method for this purpose, in which values function as goals for action and are specified as rules for action in the form of norms. This approach provides a framework both for specific use cases and for strategic digital legitimisation issues. The integration of ethical principles into organisational structures and processes of PSM is presented here as a promising perspective to ensure sustainable legitimacy and to better identify and reduce dependencies upon platforms.

Emergent communication enhances foraging behavior in evolved swarms controlled by spiking neural networks

Social insects such as ants and termites communicate via pheromones which allow them to coordinate their activity and solve complex tasks as a swarm, e.g. foraging for food or finding their way back to the nest. This behavior was shaped through evolutionary processes over millions of years. In computational models, self-coordination in swarms has been implemented using probabilistic or pre-defined simple action rules to shape the decision of each agent and the collective behavior. However, manual tuned decision rules may limit the emergent behavior of the swarm. In this work we investigate the emergence of self-coordination and communication in evolved swarms without defining any explicit rule. For this purpose, we evolve a swarm of agents representing an ant colony. We use an evolutionary algorithm to optimize a spiking neural network (SNN) which serves as an artificial brain to control the behavior of each agent. The goal of the evolved colony is to find optimal ways to forage for food and return it to the nest in the shortest amount of time. In the evolutionary phase, the ants are able to learn to collaborate by depositing pheromone near food piles and near the nest to guide other ants. The pheromone usage is not manually encoded into the network; instead, this behavior is established through the optimization procedure. We observe that pheromone-based communication enables the ants to perform better in comparison to colonies where communication via pheromone did not emerge. Furthermore, we assess the foraging performance of the ant colonies by comparing the SNN-based model to a multi-agent rule-based system. Our results show that the SNN-based model can efficiently complete the foraging task in a short amount of time. Our approach illustrates that even in the absence of pre-defined rules, self-coordination via pheromone emerges as a result of the network optimization. This work serves as a proof of concept for the possibility of creating complex applications utilizing SNNs as underlying architectures for multi-agent interactions where communication and self-coordination is desired.

The historical evolution of the crime of hooliganism

The foundation of a harmonious community is the mutual respect offered by each individual, right as a sign of recognition of the existing values within the society. Respect is one of the most important moral values of every human being, because it is the key to a harmonious social interaction. However, in recent decades there has been an alarming increase in the rate of violation of the rules of social coexistence, through demonstrations and brutal actions to disturb public order, a fact that denotes a lack of respect and good sense towards the moral norms promoted by society. The first legislative acts in which some regulations of acts of hooliganism were found date back to ancient times.

Performance assessment of surgical tracking systems based on statistical process control and longitudinal QA

A system for performance assessment and quality assurance (QA) of surgical trackers is reported based on principles of geometric accuracy and statistical process control (SPC) for routine longitudinal testing. A simple QA test phantom was designed, where the number and distribution of registration fiducials was determined drawing from analytical models for target registration error (TRE). A tracker testbed was configured with open-source software for measurement of a TRE-based accuracy metric ε and Jitter ( J ). Six trackers were tested: 2 electromagnetic (EM – Aurora); and 4 infrared (IR − 1 Spectra, 1 Vega, and 2 Vicra) – all NDI (Waterloo, ON). Phase I SPC analysis of Shewhart mean ( x ¯ ) and standard deviation ( s ) determined system control limits. Phase II involved weekly QA of each system for up to 32 weeks and identified Pass, Note, Alert, and Failure action rules. The process permitted QA in <1 min. Phase I control limits were established for all trackers: EM trackers exhibited higher upper control limits than IR trackers in ε (EM: x ¯ ε ∼ 2.8–3.3 mm, IR: x ¯ ε ∼ 1.6–2.0 mm) and Jitter (EM: x ¯ jitter ∼ 0.30–0.33 mm, IR: x ¯ jitter ∼ 0.08–0.10 mm), and older trackers showed evidence of degradation – e.g. higher Jitter for the older Vicra (p-value < .05). Phase II longitudinal tests yielded 676 outcomes in which a total of 4 Failures were noted − 3 resolved by intervention (metal interference for EM trackers) – and 1 owing to restrictive control limits for a new system (Vega). Weekly tests also yielded 40 Notes and 16 Alerts – each spontaneously resolved in subsequent monitoring.

Robot Arm Control Using Hybrid intelligent

The design of a fuzzy logic control suffers from select parameters of the membership functions, scaling factors, defuzzification action, Inference engine and base rules. speaking generally, such prosecutions are executed by traditionally techniques which do not assure an robust fuzzy control system design. There are various techniques introduced in literatures that used Genetic Algorithms to optimize a fuzzy logic control component. . In this paper, the suggested control law consists of Fuzzy Logic Control (FLC) tuning via Geneticn Algorithm (GA). The FLC used because it is efficient tools for control of nonlinear and uncertain parameters systems. GA is mainly presented to find a simultaneous near optimum design of the membership functions, scaling factors, defuzzification Method, Inference engine and control base rules. GA with different fitness functions in a form of the cumulative response error which are widely used as an efficient optimization technique. This paper also introduce a new methodology with new multi-objective function to improve fuzzy control parameters based on Genetic Algorithm techniques. The dynamic model of the robot manipulator its done by differential equations, these equations are hardly nonlinear, parameters uncertainty and time varying with multiple input and multiple output (MIMO).The manipulator robot and the fuzzy genetic control are modeled in MATLAB SIMULINK; the manipulator robot model driven nonlinear controller to draw a circle in the space with and without parameters uncertainties. The proposed techniques showed that the proposed fuzzy controller gives superior response in the output performance. When the parameter uncertainties including in the system, given satisfactory response.

Reinforcement learning for sequential decision making in population research

AbstractReinforcement learning (RL) algorithms have been long recognized as powerful tools for optimal sequential decision making. The framework is concerned with a decision maker, the agent, that learns how to behave in an unknown environment by making decisions and seeing their associated outcome. The goal of the RL agent is to infer, through repeated experience, an optimal decision-making policy, i.e., a sequence of action rules that would lead to the highest, typically long-term, expected utility. Today, a wide range of domains, from economics to education and healthcare, have embraced the use of RL to address specific problems. To illustrate, we used an RL-based algorithm to design a text-messaging system that delivers personalized real-time behavioural recommendations to promote physical activity and manage depression. Motivated by the recent call of the UNECE for government-wide actions to adapt to population ageing, in this work, we argue that the RL framework may provide a set of compelling strategies for supporting population research and informing population policies. After introducing the RL framework, we discuss its potential in three population-study applications: international migration, public health, and fertility.

Презумпция в пользу устойчивого развития: эколого-правовой аспект

Introduction. The 2030 Agenda for Sustainable Development is aimed at minimizing modern threats to the universe, the natural environment, and man. The mobilization of financial resources, public administration, and environmental institutions for sustainable development should eliminate the consumer attitude of man toward nature and meet human needs in the context of rational use of natural resources, ensuring ecological balance for future generations. Instrumentally and meaningfully, such tasks are fixed by the principles of sustainable development, which regulate the principles, beliefs, and rules for action, predicting the provisions of sustainable development. The purpose of the study is to reveal the concept and meaning of the presumption in favor of sustainable development and the features of its implementation. Methods. The methods used in the research are analysis (allowed to determine the signs and the fundamental features of the concept of “presumption”), synthesis (used to generalize the typological features of presumptions), and the method of analogies (the identification of the meaning of “presumptions” from the study of legal relations, including examples of judicial enforcement). The comparative legal method of the study provided an analysis of the presumption in favor of sustainable development, regulated by the legislation of the United Kingdom, as well as the search for similar features in the Russian legislation. The formal legal method made it possible to identify the features and specifics of normative regulation and the implementation of presumption as a means of ensuring sustainable development. Results. Presumptions (refutable and irrefutable) as means of legal regulation and the implementation of environmental legislation represent an inference (argument, conclusion) from a specific fact in the form of a rational assumption in accordance with the principles and goals of sustainable development, through legislative consolidation or enforcement. Presumptions in favor of sustainable development are aimed at resolving socio-economic problems, problems of preserving a favorable environment, and natural resource potential in order to meet the needs of current and future generations of people; they ensure sustainable development in a three-dimensional interdependent dimension: social, economic, and environmental. The emphasizing of the “economic” component in decision-making in the field of social development is unacceptable and is not aimed at the implementation of environmental objectives that form the basis of sustainable development policy. Conclusions. The significance of the presumption in favor of sustainable development lies in the fact that sustainable development can be achieved through growth in its three-sided socioeconomic and environmental dimensions, with an emphasis on the environmental component. Another meaning of the presumption in favor of sustainable development, implemented in legal practice, is that it is not aimed at sustainable development in its traditional environmental purpose.

Pull-out failure capacities of cold-formed steel batten screw connections at sub-zero temperatures

Cold-formed steel (CFS) roof and wall cladding systems are used worldwide, and are constructed using high-strength, thin steel battens and claddings. In North American countries, which are frequently subjected to blizzards (winter storms), these cladding systems are particularly vulnerable to pull-out failures during combined windstorm and snowy conditions. Despite extensive research studies investigating the pull-out failure mechanism and the critical parameters of screw connections between cladding and battens at ambient temperature, the behaviour of these connections under blizzard conditions has not been experimentally investigated. To fill this knowledge gap, an experimental study was undertaken that included 144 laboratory tests of screw connections in battens of varying grades and thicknesses, and three distinct types of screws. The pull-out failure capacities of screw connections in battens were evaluated under wind suction loading at four different temperatures, including ambient and sub-zero temperatures. The results of the study provided insights into the pull-out failure mechanisms of screw connections in battens and enabled the development of suitable design rules for combined wind action and sub-zero temperature conditions. The findings of this study are expected to be of significant value to engineers and building designers who are involved in the construction of lightweight cold-formed steel buildings.

History of creation and development of emergency medical care in City of Moscow

The article is devoted to the history of the creation and development of emergency medical care for the population of Moscow. The stages of the activity of the home care centers, the night emergency room at the Ambulance Station and their subsequent organization in the district emergency centers are considered. The main regulatory and legal documentation is indicated, in the development of which the heads of the Station n. a. A. S. Puchkov and A. M. Nechaev took part. The work on the creation of a system of emergency and emergency medical care for adults and children in Moscow, the rules of action of the doctor of the emergency room upon receipt of appeals is shown. The article describes the search for effective ways to solve organizational and material problems in the field of emergency and emergency medical care at different stages of the development of the emergency service. The role of the Moscow Ambulance and Emergency Medical Care Station in the development and implementation of organizational and methodological measures to improve the work of emergency departments in the capital is shown. A description of a major project is given, the purpose of which was the full integration of emergency medical care for adults and children into the structure of the Ambulance and emergency Medical Care Station in Moscow at the present stage, the organization of a Single city dispatch center for emergency and emergency medical care with the formation of a single information space, the previous preparatory work for receiving calls on a single federal number 103 on the base of the Station. During its history, the Moscow emergency medical Service has passed a difficult path. Thanks to the efforts made, the service is now an integral part of the Ambulance n. a. A. S. Puchkov and Emergency Medical Care Station in Moscow.

Dual deep reinforcement learning agents-based integrated order acceptance and scheduling of mass individualized prototyping

Coordinating order acceptance decisions with production scheduling to maximize revenue is challenging for Mass Individualized Prototyping (MIP) service providers. This paper presents a dual deep reinforcement learning agents-based (DDRLA) integrated order acceptance and scheduling (IOAS) for improving revenue. Firstly, a deep reinforcement learning-based virtual production scheduling (VPS) agent together with 8 state features and 11 action rules is designed. The VPS agent quickly and virtually reschedules a dynamically-arriving accepted order to evaluate the overall impact of accepting this order, including consumed capacity and increased revenue. Then, a deep reinforcement learning-based order acceptance decision (OAD) agent is designed. Based on the information guidance resulting from an interaction with the VPS agent, the OAD agent selectively accepts orders to maximize long-term gains, as well as to improve system resilience in the presence of a high ratio of urgent orders. The experiment results show that the proposed DDRLA method has better performance, compared with other IOAS approaches.

Separate-and-conquer survival action rule learning

Action mining is a data mining method that aims to identify recommendations for changing attribute values that can lead to the classification of data instances as examples of another class. Action mining algorithms extract rules containing recommendations in the premises and class changes in the conclusion. To the best of the authors’ knowledge, no method has been proposed yet for generating action rules based on censored data. This study introduces the first method for survival action rule generation. The method stems from the covering rule induction algorithm but generates rules defining the actions required to change not the class but the survival curve of the covered examples. Thus, this study poses a new research problem: generating action rules for censored data and survival analysis. This study evaluated the proposed method using 22 data sets in which two application domains of survival analysis were distinguished: medicine and predictive maintenance. In addition, more detailed analyses of the generated survival action rules were presented in the form of case studies for the two selected data sets. The results show that the proposed method generates good-quality survival action rules and changes in the survival curves, resulting from the identified actions are significant.

Experimental study on influence mechanism of fiber orientation angle in AFRP cutting

The experimental study on aramid fiber-reinforced composites (AFRP) was carried out. The milling experiments of AFRP were carried out from different fiber orientations. The changes in surface quality, fiber section, and chip shape in mPIC1195147illing under different fiber orientations were studied, and the action law of the blade and tooth was analyzed from the micro perspective. The response surface are used to analyze the cutting force. The mathematical model is established to predict the minimum cutting force. The variance analysis method is used to analyze the influencing factors and their weights of cutting force. The research shows that the cutting force is the smallest when the fiber orientation angle is 0° or 90°, the milling surface quality is good, and the chips are primarily powdery. The cutting force is the largest when the fiber orientation angle is 45° and the milling surface quality is poor. The chips are mainly flocculent. At this angle, the cutting force is affected by three factors, and the interaction has the most significant proportion. When the fiber orientation angle is 30° or 60°, the cutting force, the fiber cross-section, and the surface quality are between the former two, and most of the chips are mixed chips (powdery and flocculent). The evolution and distribution law of burr is obtained. During AFRP milling, the milling surface is always sheared on one side and accompanied by extrusion. The fibers are sheared and broken, the surface burrs are few, the side is stretched, the fibers are stretched and broken, and the surface burrs are many. The action rule of the cutting tool on transverse and longitudinal fibers is summarized.

A decentralized decision-making algorithm of UAV swarm with information fusion strategy

Centralized and decentralized unmanned aerial vehicle (UAV) swarms rely on networked communication to exchange information among individuals and generate cooperative behaviors. This study proposes an Information-Fusion based Decentralized Swarm Decision Algorithm (IFDSDA) to coordinate UAV swarms when communication is interfered with or fails. Each UAV has the ability to perceive the area ahead using a monocular camera. An information fusion strategy is presented to unify the two types of information obtained from communication and visual perception in a standardized manner. This mechanism enables UAVs to fully utilize different information in cases of communication failure. Each UAV is controlled by a decentralized swarm decision module that takes the fused information as inputs and generates the heading orientation by combining basic action rules of UAVs. The weight parameters of the combination are optimized using the heuristic genetic algorithm in an offline manner. The collision/obstacle avoidance and area search missions are used as test scenarios for the proposed IFDSDA. Simulations with high confidence are conducted, which demonstrate the effectiveness, inherent scalability, and robustness of the proposed method, comparing it with the state-of-the-art ISOA method and its variant. This study reduces the dependence on network communication within the swarm and improves the adaptability of UAV swarms in complex battlefield environments.

Effects of structural characteristics of phenolic compounds on oxidation of glycerol trioleate: Action rule and mechanism

Effects of structural characteristics of phenolic compounds on the oxidation of glycerol trioleate were investigated, and the action rule and mechanism were further explored. By using thermal and multispectral analyses, all tested phenolic compounds significantly inhibited the oxidation of glycerol trioleate, and reduced the decomposition of CC and ester bonds of glycerol trioleate, which were attributed to their capability to inhibit the production of free radicals. Quercetin and gallic acid were the most effective among the condensed and hydrolyzable phenolic compounds in present study, respectively. For condensed phenolic compounds, the hydroxyl groups in B ring, substitution in C ring, and the structure of C ring played a crucial role in their inhibitory action. For hydrolyzable phenolic compounds, the amount of hydroxyl groups and their molecular weight had obvious effects on their inhibitory action. According to the measurement of molecular electrostatic potential and frontier molecular orbitals by density functional theory, the large maximum electrostatic potential and the small energy gap value were beneficial to enhance the inhibitory capability of phenolic compounds on the oxidation of glycerol trioleate. All present results suggested the potential action rule and molecular mechanism about the inhibitory effects of phenolic compounds on the oxidation of glycerol trioleate.

Resilient digital twin modeling: A transferable approach

High-fidelity digital twin models include not only concrete geometric models but also intrinsic models such as mechanism models and data models, which require high information dimensionality. Consequently, modeling, validation, and implementation cycles become challenging and time-consuming. The reuse of existing digital twin models to achieve rapid transference and utilization of models is becoming one of the hot topics in digital twin modeling. To this effect, aiming at how to reuse the multi-dimensional information of existing models to improve modeling efficiency and resilience, this paper proposes a rapid transferable modeling approach for digital twin models. The approach proposes a unified mapping and digital representation of physical entities based on information metamodels, which can rapidly instantiate digital twin assets. Then, the transferable approaches from the geometry dimension, behavior dimension, and algorithm dimension are given respectively, which include the information model reuse, action feature query and rule generation, as well as fine-tuning of data-driven mechanisms and domain adaptive of digital twins. Finally, through a practical case study, the result shows that the efficiency of modeling improves by 60.39%, and the effectiveness of the model after domain adaptation improves by 6.94%.

Convergence of mechanistic modeling and artificial intelligence in hydrologic science and engineering

Hydrology is a mature physical science based on application of first principles. However, the water system is complex and its study requires analysis of increasingly large data available from conventional and novel remote sensing and IoT sensor technologies. New data-driven approaches like Artificial Intelligence (AI) and Machine Learning (ML) are attracting much “hype” despite their apparent limitations (transparency, interpretability, ethics). Some AI/ML applications lack in addressing explicitly important hydrological questions, focusing mainly on “black-box” prediction without providing mechanistic insights. We present a typology of four main types of hydrological problems based on their dominant space and time scales, review their current tools and challenges, and identify important opportunities for AI/ML in hydrology around three main topics: data management, insights and knowledge extraction, and modelling structure. Instead of just for prediction, we propose that AI/ML can be a powerful inductive and exploratory dimension-reduction tool within the rich hydrological toolchest to support the development of new theories that address standing gaps in changing hydrological systems. AI/ML can incorporate other forms of structured and non-structured data and traditional knowledge typically not considered in process-based models. This can help us further advance process-based understanding, forecasting and management of hydrological systems, particularly at larger integrated system scales with big models. We call for reimagining the original definition of AI in hydrology to incorporate not only today’s main focus on learning, but on decision analytics and action rules, and on development of autonomous machines in a continuous cycle of learning and refinement in the context of strong ethical, legal, social, and economic constrains. For this, transdisciplinary communities of knowledge and practice will need to be forged with strong investment from the public sector and private engagement to protect water as a common good under accelerated demand and environmental change.

Migration of phenolic compounds in meat during marinating process: Action rule, mass transfer and mechanism

Migration of phenolics in meat is an important procedure for their valuable applications in meat production, which affects their modification effects on meat quality and safety. So, in present study, the migration process and regulations of phenolics in marinaded meat were investigated, and the mechanism was further explored. 50% KCl mass substitution and 30 g/L chloride were determined as optimal conditions for the marinating of phenolics (gallic acid, chlorogenic acid, epigallocatechin gallate and tannic acid) in meat. Migration of chloride and phenolics in marinating process were fitted well with exponential time-variant function. With different concentrations (6–10 μmol/mL), migration of phenolics in meat was mainly promoted by their concentration gradient. With the same concentration, order of diffusivity coefficient value for phenolics in meat was: epigallocatechin gallate > gallic acid > chlorogenic acid > tannic acid, which was attributed to their different capability to change the microstructure and water distribution of meat by interacting with myofibrillar protein. All results suggested that the migration of phenolics in meat depended on their marinating concentration, molecule size, structure characteristic and reactivity, which provided some beneficial information for the potential applications of phenolics in food industries to ameliorate meat quality and safety.

ON ERICH FROMM’S VIRTUE ETHICS

Fromm’s ethics can be viewed as a form of virtue ethics, which emphasizes the importance of developing one’s true self and reducing one's false self. By doing so, one can change their psychological state in terms of character and psychological tendencies, leading to an improved moral life and higher moral standards. While some criticisms have been raised about virtue theory, including its perceived inability to guide one on how to act properly, Fromm's virtue ethics is unique in that it does not focus on establishing universal rules for specific actions. Instead, it seeks to establish universal laws for human behavioral tendencies or trends. Through his unique social psychology, Fromm provides an in-depth analysis of the inner world of man, which can serve as a valuable guide to the general direction of human development and freedom. In addition, Fromm’s virtue ethics also highlights the importance of social relationships and the impact they have on our moral development. He argues that our relationships with others can have a profound effect on our psychological state and our ability to live virtuously. Overall, Fromm’s virtue ethics provides a unique perspective on human development and morality. By focusing on the development of one’s true self and the importance of social relationships, his approach offers a valuable guide to living a fulfilling and virtuous life.