This paper proposes a novel Hierarchical Deep Reinforcement Learning (HRL) framework for wake homing torpedo guidance, applying the Discrete Event System Specification (DEVS) formalism to design high-level policies and reward shaping functions. Wake homing torpedo guidance generates course commands to enable the torpedo to follow the wake trajectory of a target ship. When the target ship evades the incoming torpedo, the wake trajectory becomes curved, often causing the torpedo to lose track due to the narrow detection range of the wake detection sensor. This necessitates a sophisticated algorithm to consistently track the target ship, particularly in scenarios where the torpedo exits and re-enters the wake trajectory in noisy environments. While heuristic algorithms can handle typical wake trajectories, developing a robust solution for unknown trajectories remains a significant challenge. To address this, we apply a novel reinforcement learning approach to develop the guidance logic and compare its performance with a conventional algorithm-based method. The performance and effectiveness of the proposed approach are demonstrated through numerical simulations.
User experience (UX) is crucial for interactive system design. To improve UX, one method is to identify failure modes related to UX and then take action on the high-priority failure modes to decrease their negative impacts. For the UX of interactive system design, the failure modes under consideration are human errors or difficulties, and thus the risk factors concerning failure modes are subjective and even subconscious. Existing methods are not sufficient to deal with these issues. In this paper, a fuzzy failure mode and effect analysis (FMEA)-based hybrid approach is proposed to improve the UX of interactive system design. First, hierarchical task analysis (HTA) and systematic human error reduction and prediction approach (SHERPA) are combined to identify potential failure modes concerning UX. Subsequently, fuzzy linguistic variables are employed to assess the risk parameters of the failure modes, and the similarity aggregation method (SAM) is adopted to aggregate the fuzzy opinions. Then, on the basis of the aggregation results, fuzzy logic is adopted to compute the fuzzy risk priority numbers that can prioritize the failure modes. Finally, the failure modes with high priorities are considered for corrective actions. An in-vehicle information system was employed as a case study to illustrate the proposed approach. The findings indicate that, compared with other methods, our approach can provide more accurate results for prioritizing failure modes related to UX, and can successfully deal with the subjective and even subconscious nature of the risk factors associated with failure modes. This approach can be universally utilized to enhance the UX of interactive system design.
The paper documents some of the results of the research program Smart Yard: Industry 4.0 Production Process aimed at reducing inefficiencies in construction site procedures by developing new management methods supported by digitisation processes that can memorise and monitor computational data and guide them towards specific purposes of production processes optimisation. In particular, the aim of the study is to propose evolved, highly efficient and innovative organisational and information management models that enable more reliable control of processes in the construction sector, mitigating unavoidable uncertainties while pursuing a more rational use of resources. The products developed to support the programme include two newly designed pieces of equipment with advanced functions, which can be configured as examples of site management systems such as a “smart factory” in the logic of Industry 4.0, illustrated below. One is a high-performance charging system for power banks to be used with portable power tools, while the other concerns a work standing desk that employs wireless communication protocols to dialogue with other devices at the construction site.
The work examines the problem of adjusting the adjustable parameters of the axial-rotor threshing-separating device (ARTSD) of the TORUM grain harvester. A general block diagram of the solution has been constructed. To formalize the problem, a linguistic approach was used, which makes it possible to describe complex multi-level systems with ambiguous dependencies between input factors and controlled parameters. The feasibility of using an intelligent information system based on fuzzy logic to solve the problem of setting the adjustable parameters of a combine harvester is substantiated. The article presents the implementation of the first stage of solving the problem of designing an intelligent information system for setting the adjustable parameters of a combine harvester, constructing a formal logical scheme for solving the problem, and creating a fuzzy knowledge base that forms the basis of this information system. Options for pre-setting for harvesting various crops are considered. Models of the considered features in the form of membership functions are proposed. Basic and extended term sets are established. The consistency of the models was analyzed and the optimal models were selected. The results of the solutions obtained are illustrated. Based on expert information about the system of complex relationships between environmental factors and the adjustable parameters of the combine, a fuzzy knowledge base was created that establishes rules for the deductive conclusion of decisions about the values of parameters in various combinations of external conditions.
Abstract In the current digital social environment, social media platforms have become an important position for user behavior insights and precision marketing. User behavioral data on social media contain rich information, but they are often fuzzy, uncertain and highly complex. Fuzzy neural network (FNN), as an advanced model combining fuzzy logic and neural network theory, provides a powerful tool for processing and analyzing social media user behavioral features. This study is dedicated to exploring the application of fuzzy neural networks in social media user behavior analysis and their key role in the design of accurate online marketing strategies. We construct and optimize a fuzzy neural network model by meticulously classifying and quantifying user behavioral features, including behavioral frequency features, content topic features, social interaction features, and time series features, as well as applying fuzzy set theory to deal with fuzzy features such as emotional states. Through empirical analysis, we will show how fuzzy neural networks can reveal the intrinsic laws behind user behaviors, and how these insights can be used to design and implement precise online marketing strategies to improve advertising effectiveness, user engagement, and brand loyalty.
Rana Jabbar Kasid Jalhoom, Ahmed Mohammed Raoof Mahjoob
This study looks into the many methods that are used in the risk assessment procedure that is used in the construction industry nowadays. As a result of the slow adoption of novel assessment methods, professionals frequently resort to strategies that have previously been validated as being successful. When it comes to risk assessment, having a precise analytical tool that uses the cost of risk as a measurement and draws on the knowledge of professionals could potentially assist bridge the gap between theory and practice. This step will examine relevant literature, sort articles according to their published year, and identify domains and qualities. Consequently, the most significant findings have been presented in a manner that is consistent with logic and is predicated on the temporal evolution between 1990 and 2015.
The positive effect of decarbonizing the transport sector by using bio-based fuels is high. Currently, biodiesel and ethanol are the two biofuels that are blended with fossil fuels. Another technology, namely, hydroprocessing, is also gaining momentum for producing biofuels. Hydrotreated vegetable oil (HVO) produced using this process is a potential drop-in fuel due to its improved physiochemical properties. This study aimed to reduce the fossil diesel content by blending 20% and 30% HVO and 5%, 10% and 15% waste cooking oil biodiesel on a volume basis. The blends were used to conduct a thorough performance examination of a single-cylinder compression ignition engine. The thermal efficiency of the engine was enhanced by the addition of biodiesel to the blend. The efficiency increased as the proportion of biodiesel in the mix increased, although it was still less efficient than diesel. The maximum improvement in thermal efficiency of 4.35% was observed with 20% blending of HVO and 15% blending of biodiesel compared with 20% blending of HVO and diesel. However, the HC (decrease of 30%), CO (decrease of 23.5%) and smoke (decrease of 21.1%) emissions were observed to be the lowest with 30% blending of HVO and 15% blending of biodiesel. A fuzzy-logic-based Taguchi method and Grey’s method were then applied to find the best blend of HVO, biodiesel and diesel. The combination of the two methods made it easier to carry out multi-objective optimization. The brake thermal efficiency (BTE), smoke and NO emissions were selected as the output parameters to optimize the HVO and biodiesel blend. The optimization study showed that 30% blending of HVO and 15% blending of biodiesel was the best blend, which was authenticated using the confirmation experiment.
The article is devoted to the study of climate claims, including new types of such claims, recorded in a number of countries in 2020-2021. They involve claims for the protection of human rights and claims against private companies. In addition, the author analyzes the most common grounds for argumentation of the plaintiffs positions in climate claims based on international, constitutional, administrative, and tort law. The most common legal doctrines that were used by courts as the ground for decisions on climate claims have been studied. The purpose of the study is to form an idea of a new type of claims (claims in the field of climate protection or climate claims) based on the analysis of regulations, judicial practice of foreign countries and scientific sources. The methodology includes empirical methods of comparison, description, and interpretation, theoretical methods of formal and dialectical logic, special methods such as legal-dogmatic and legal norms interpretation. The study showed that judicial and arbitration proceedings on climate issues have become an effective tool used by citizens and non-governmental organizations to ensure compliance with or strengthening of the climate commitments made by governments in accordance with the 2015 Paris Agreement.
Ashwin Kumar Devarakonda, Natarajan Karuppiah, Tamilselvi Selvaraj
et al.
The characteristics of a PV (photovoltaic) module is non-linear and vary with nature. The tracking of maximum power point (MPP) at various atmospheric conditions is essential for the reliable operation of solar-integrated power generation units. This paper compares the most widely used maximum power point tracking (MPPT) techniques such as the perturb and observe method (P&O), incremental conductance method (INC), fuzzy logic controller method (FLC), neural network (NN) model, and adaptive neuro-fuzzy inference system method (ANFIS) with the modern approach of the hybrid method (neural network + P&O) for PV systems. The hybrid method combines the strength of the neural network and P&O in a single framework. The PV system is composed of a PV panel, converter, MPPT unit, and load modelled using MATLAB/Simulink. These methods differ in their characteristics such as convergence speed, ease of implementation, sensors used, cost, and range of efficiencies. Based on all these, performances are evaluated. In this analysis, the drawbacks of the methods are studied, and wastage of the panel’s available output energy is observed. The hybrid technique concedes a spontaneous recovery during dynamic changes in environmental conditions. The simulation results illustrate the improvements obtained by the hybrid method in comparison to other techniques.
Based on today’s compromises with human rights and the numerous violations of them, which for several countries seems to be the rule rather than an exception, this article discusses the cause of the delusions that in today’s politics are attached to human rights. An analysis is made of the nature of human rights understood as something common and universal for all people. On this basis, a division of human rights is proposed, which at the same time means limiting them to perfect, imperfect and adventitious rights. Central to the discussion is the question of how the normative element of human rights should be understood. This article distinguishes between two approaches to the question, where one is identified as a source of current misconceptions about human rights, while the other is highlighted as a possible answer to key challenges facing democracy.
Craft therapy (or ergotherapy) in a physical rehabilitation of children with musculoskeletal system disorders has a great importance both as a method of overcoming existing motor disorders and as the basis for the future successful socialization of these children. In the available literature, the issues of craft therapy use in combination with physical education of pre-schoolers in various institutions of preschool education are insufficiently and non-systematically covered. This makes this article relevant. The article discusses the methodological possibilities of using the author's work simulator the "Ant" for the correction of hand dysfunctions of pre-schoolers by means of physical education and craft therapy. The main technical characteristics of the simulator and the features of its manufacture are presented. The characteristics of the "Ant" versatility and its multifunctionality are given, which ensures the success of its use in a kindergarten of any kind. The properties of the "Ant" stand for improving the psychophysical development of pre-schoolers are listed. The formulated methods of using the “Ant” simulator and the methodological techniques for correcting the main hand functions of the pre-schoolers (tested in the process of the ascertaining experiment) have a particular value. The main methods included the ones as follows: game stimulation, objectivity (subject-manipulative activity), instrumental logic, hand-eye coordination, an individually differentiated approach to the correction of hand disorders of children by means of physical education and craft therapy. Each of the listed methods includes a number of methodological techniques that increase the effectiveness of corrective instrumental-subject manipulations. The prospects of further research in this area are seen in the elaboration of new work simulators for preschool children suffering from disorders of the musculoskeletal system alongside the creation of the necessary methodological support for their effective use.
Christine M. Bond, Richard Holland, David P. Alldred
et al.
Abstract Background Prescribing, monitoring and administration of medicines in care homes could be improved. A cluster randomised controlled trial (RCT) is ongoing to evaluate the effectiveness of an independent prescribing pharmacist assuming responsibility for medicines management in care homes compared to usual care. Aims and Objectives To conduct a mixed-methods process evaluation of the RCT, in line with Medical Research Council (MRC) process evaluation guidance, to inform interpretation of main trial findings and if the service is found to be effective and efficient, to inform subsequent implementation. Objectives 1. To describe the intervention as delivered in terms of quality, quantity, adaptations and variations across triads and time. 2. To explore the effects of individual intervention components on the primary outcomes. 3. To investigate the mechanisms of impact. 4. To describe the perceived effectiveness of relevant intervention components [including pharmacist independent prescriber (PIP) training and care home staff training] from participant [general practitioner (GP), care home, PIP and resident/relative] perspectives. 5. To describe the characteristics of GP, care home, PIP and resident participants to assess reach. 6. To estimate the extent to which intervention delivery is normalised among the intervention healthcare professionals and related practice staff. Methods A mix of quantitative (surveys, record reviews) and qualitative (interviews) approaches will be used to collect data on the extent of the delivery of detailed tasks required to implement the new service, to collect data to confirm the mechanism of impact as hypothesised in the logic model, to collect explanatory process and final outcome data, and data on contextual factors which could have facilitated or hindered effective and efficient delivery of the service. Discussion Recruitment is ongoing and the trial should complete in early 2020. The systematic and comprehensive approach that is being adopted will ensure data is captured on all aspects of the study, and allow a full understanding of the implementation of the service and the RCT findings. With so many interrelated factors involved it is important that a process evaluation is undertaken to enable us to identify which elements of the service were deemed to be effective, explain any differences seen, and identify enablers, barriers and future adaptions. Trial registration ISRCTN17847169 . Date registered: 15 December 2017.
Mining and analyzing the information and structure of DNA sequences is an important method of exploring and explaining the mysteries of biology. In addition to traditional biological detection methods for DNA sequences, technological advances have allowed researchers to utilize computers to analyze DNA sequences, such as in DNA visualization. However, DNA visualization techniques have disadvantages, such as difficult operation and complex calculation. Therefore, in this paper, we propose an algorithm called VARCH based on a variant map that is a part of variant logic construction. VARCH is a high-efficiency and concise visualization algorithm for DNA sequences. The principle of this approach is that the number of base combinations in each DNA subsequence is counted, and a matrix is constructed based on the full arrangement of different base combinations. Finally, the matrix is mapped to the 2D coordinate plane, obtaining the image of DNA sequences. The experimental results demonstrate that VARCH can effectively display features of DNA sequences.
Team Semantics generalizes Tarski's Semantics for First Order Logic by allowing formulas to be satisfied or not satisfied by sets of assignments rather than by single assignments. Because of this, in Team Semantics it is possible to extend the language of First Order Logic via new types of atomic formulas that express dependencies between different assignments.
Some of these extensions are much more expressive than First Order Logic proper; but the problem of which atoms can instead be added to First Order Logic without increasing its expressive power is still unsolved.
In this work, I provide an answer to this question under the additional assumptions (true of most atoms studied so far) that the dependency atoms are relativizable and non-jumping. Furthermore, I show that the global (or Boolean) disjunction connective can be added to any strongly first order family of dependencies without increasing the expressive power, but that the same is not true in general for non strongly first order dependencies.