Rule-based Research Articles

ExaGRyPE: Numerical general relativity solvers based upon the hyperbolic PDEs solver engine ExaHyPE

ExaGRyPE describes a suite of solvers and solver ingredients for numerical relativity that are based upon ExaHyPE 2, the second generation of our Exascale Hyperbolic PDE Engine. Numerical relativity simulations are crucial in resolving astrophysical phenomena in strong gravitational fields and are fundamental in analyzing and understanding gravitational wave emissions. The presented generation of ExaGRyPE solves the Einstein field equations in the standard CCZ4 formulation under a 3+1 foliation and focuses on black hole space-times. It employs a block-structured Cartesian grid carrying a higher-order Finite Difference scheme with full support of adaptive mesh refinement (AMR), it facilitates massive parallelism combining message passing, domain decomposition and task parallelism, and it supports the injection of particles into the grid as static data probes or as moving tracers. We introduce the ExaGRyPE-specific building blocks within ExaHyPE 2, and discuss its software architecture and compute-n-feel.For this, we formalize the creation of any specific astrophysical simulation with ExaGRyPE as a sequence of lowering operations, where a few abstract logical tasks are successively broken down into finer and finer tasks until we obtain an abstraction level which can directly be mapped onto a C++ executable. The overall program logic is fully specified via a domain-specific Python interface, we automatically map this logic onto a more detailed set of numerical tasks, subsequently lower this representation onto technical tasks that the underlying ExaHyPE engine uses to parallelize the application, before eventually the technical tasks in turn are mapped onto small task graphs including the actual astrophysical PDE term evaluations, initial conditions, boundary conditions, and so forth. These can be injected manually by the user, or users might instruct the solver on the most abstract user interface level to use out-of-the-box ExaGRyPE implementations. We end up with a rigorous separation of concerns which shields ExaGRyPE users from technical details and hence simplifies the development of novel physical models. We present the simulations and data for the gauge wave, static single black holes and rotating binary black hole systems, demonstrating that the code base is mature and usable. However, we also uncover domain-specific numerical challenges that need further study by the community in future work.

Evolving to find optimizations humans miss: using evolutionary computation to improve GPU code for bioinformatics applications

GPUs are used in many settings to accelerate large-scale scientific computation, including simulation, computational biology, and molecular dynamics. However, optimizing codes to run efficiently on GPUs requires developers to have both detailed understanding of the application logic and significant knowledge of parallel programming and GPU architectures. This paper shows that an automated GPU program optimization tool, GEVO, can leverage evolutionary computation to find code edits that reduce the runtime of three important applications, multiple sequence alignment, agent-based simulation and molecular dynamics codes, by 28.9%, 29%, and 17.8% respectively. The paper presents an in-depth analysis of the discovered optimizations, revealing that (1) several of the most important optimizations involve significant epistasis, (2) the primary sources of improvement are application-specific, and (3) many of the optimizations generalize across GPU architectures. In general, the discovered optimizations are not straightforward even for a GPU human expert, showcasing the potential of automated program optimization tools to both reduce the optimization burden for human domain experts and provide new insights for GPU experts.

Research on the construction of campus football teaching content hierarchical system and flexible management

In response to the national requirements for the development of campus football and addressing the current imbalance in the development of campus football teaching in China, this study discusses the construction of a football teaching content hierarchical system and flexible management that aligns with China's national conditions. It also elaborates on management strategies for the implementation of categorized guidance, flexible management, and enhanced inspection and evaluation in football teaching. Based on the systematic principles of constructing a campus football teaching content hierarchical system, as well as the basic rules of football tactics and teaching practice, campus football teaching content is divided into three levels: primary, intermediate, and advanced, with ten proficiency levels. The content at each level includes corresponding basic theoretical knowledge of football, football techniques and tactics, mental health education, and physical development. When arranging the teaching content at each level, it is essential to fully consider the matching of football knowledge and tactics, and to organically integrate football knowledge, skills with physical training, and comprehensive quality education. The implementation of flexible management should be practical, proposing different requirements for football teaching in schools of different types and regions, implementing categorized guidance and management; it is necessary to strengthen institutional construction, and use inspection and evaluation as a driving force to promote the sustainable development of football teaching.

Content diversity under a digital regime: a case study of the television broadcasting industry in Indonesia

This study explores the impact of digitalization on public space by examining Indonesia’s content diversity after television broadcasting digitalization, which comes late due to challenges posed by competing interests. Content diversity has an important role in fulfilling the public’s rights over information. Broadcasting digitalization can multiply the number of broadcasters which may increase the content diversity. Unfortunately, existing regulations have yet to regulate content diversity clearly. The market structure also remained the same despite digitalization. Thus, this qualitative research aims to empirically assess content diversity by observing television programs in Yogyakarta and Jakarta. This study demonstrates that the broadcast transition to digital has not been proven to encourage content diversity. This is because the concentration of ownership and digital broadcasting networks has an impact on the emergence of similar content with limited type of program variations. Thus, without clear regulations on content diversity and ownership, digital shift cannot change the fundamental structure of the Indonesian broadcasting industry and perpetuate the system dominated by old stakeholders. Recognizing the limited contribution of broadcast digitalization in improving content diversity will contribute to a review of basic rules regarding ownership, business network, and genre-based content production.

PLC based laser scanning system for conveyor belt surface monitoring

This paper presents the design, implementation, and testing of an advanced conveyor belt surface monitoring system, specifically engineered for harsh and complex industrial environments. The system integrates multiple cutting-edge technologies, including programmable logic controllers (PLC), laser scanning, industrial-grade cameras, and deep learning algorithms, particularly YOLOv7, to achieve real-time, high-precision monitoring of conveyor belt conditions. Key innovations include optimized detection location based on failure modes, advanced PLC integration for seamless automation, and intelligent dust-proof features to maintain accuracy in challenging conditions. Through strategic placement of detection devices and multi-mode control strategies (local, remote, and automatic), the system offers unparalleled adaptability and responsiveness. The system leverages robust data management for trend analysis and predictive maintenance, enhancing operational efficiency. The hardware architecture comprises PLC-based control systems, high-resolution industrial cameras, and laser emitters, while the software features a two-tier structure combining human-machine interaction (HMI) with real-time data processing capabilities. Experimental results show that the system is highly effective in detecting common belt defects such as foreign objects, tears, and shallow scratches, ensuring optimal operational efficiency and minimizing downtime. The system’s scalability, robust data management, and adaptability to low-light and dusty conditions make it ideal for deployment in large-scale industrial operations, where continuous monitoring and early fault detection are critical to maintaining productivity and safety.

Design and verification of monitoring system of DC microgrid based on Ethernet communication

AbstractReal‐time acquisition of microgrid (MG) operation data and remote control play a crucial role in the safe and stable operation of MG. A design scheme of monitoring system is proposed for the wind/photovoltaic/energy storage islanded direct current MG. The core controllers used in direct current MG system are programmable logic controller and digital signal processor. The monitoring system mainly adopts Ethernet communication, together with serial port communication mode Recommend Standard 232 (RS232) and Recommended Standard 485 (RS485) communication modes. A heterogeneous networking is built with controllers and data display instruments. Different monitoring interfaces are designed, the important information can be real‐time detected, collected and displayed. The multi‐energy and multi‐load dispatching operation control are realized according to scheduling operation plan. The parameters of the inverter can be adjusted, and the output voltage waveform and sinusoidal pulse width modulation waveform of the inverter can be measured. The communication of the proposed monitoring system is reliable, flexible and expandable, and easy to realize remote operation control. Moreover, the detection and control functions can be extended further. Through experiments, the effective control and monitoring of the designed monitoring system is verified, and the intelligent management is realized.

AN APPROACH OF DOM RECORD MANAGEMENT COMPONENT UI CREATION

This paper presents an approach of Document Object Model database record management component user interface (UI) creation. Mainstream of UI development approaches concentrates in few directions, omitting holistic view on the fundamental database operations. The proposed solution uses method lay on of standard clauses adopted by the ECMA Script edition sixth and above. The program logic for the UI component was built with the intention - The existing functionality of such UI component to be extended and complemented.

Thermal characterization methodologies for experimental minichannel heat sink designs in printed circuit board assemblies

There has been a growing demand for novel, highly efficient, power-saving cooling solutions in recent years. In many cases, standard cooling techniques offer only limited opportunities to prevent the overheating of circuits. Such issues concern high-speed Printed Circuit Board Assemblies (PCBA) in data centers and telecommunication racks, where the flow of the cooling medium is obstructed due to the lack of space. Size limitations can also be a serious problem when cooling high-power devices because the devices consume a large space. Since the heat sink-based cooling solutions and the sophisticated IC packages only deal with one possible heat flow path, we were given the idea of enhancing the secondary heat flow path towards the Printed Circuit Board (PCB). Led by this intention, the idea of creating an embedded minichannel system inside the circuit board and circulating the cooling agent was realized. Through this method, we could decrease the board-to-ambient thermal resistance significantly. This paper presents the demonstration and feasibility study of this method. One of the main aims of this study is to demonstrate the applicability of the proposed concept in PCBAs, where the primary concerns are the low-cost manufacturability and available space. The other goal is to create an adaptation of the standard thermal characterization methodologies to deal with the specific dissipating components in the PCBA demonstrators. In the first part, the manufacturing technology is elaborated on, and its efficiency is characterized by thermal transient testing and Computational Fluid Dynamics (CFD) simulations. For these use cases, it was noted that the cumulative thermal resistance decreased by approximately 60 % when a volumetric flow rate of 100 ccm was applied in the minichannels. In the second part, a more sophisticated technology demonstration is realized and characterized by adding the proposed embedded minichannel heat sink to an existing high-speed PCBA. A specific thermal transient testing was implemented specifically for this use case, and it was carried out on programmable logic devices by utilizing general-purpose programmable logic to construct the necessary measurement methods. In the future, this feature can be used in different logic circuit designs where it is not possible to determine the junction temperature directly.

Development of Multimedia Teaching Content for Basketball in High School

Background and Aim: In the continuous development of information technology, the global education sector has been greatly impacted by the globalization of information, the application of modern information technology can be seen everywhere, which will profoundly change education. Modern information technology with network and multimedia technology as the core has been applied in physical education teaching in schools and universities. It is necessary to reform and upgrade the traditional education mode and develop multimedia teaching methods. Therefore, this research was to develop multimedia teaching content for basketball in high school, to promote the use of multimedia technology in physical education teaching. Materials and Methods: The survey included 516 students and 35 teachers from 10 high schools in Guangzhou, questionnaire was used to investigate the current situation of basketball teaching. Then, 7 teachers were interviewed to consult the problem solutions, and the indicator contents of multimedia teaching content for basketball in high school was constructed by literature review and content analysis. Through 19 Delphi experts’ consensus, multimedia teaching content for basketball in high school was established. Finally, 9 experts were invited to confirm the developed multimedia teaching content by the Connoisseurship method. In this research, mean, standard deviation and coefficient of variation were used to analyze the data. Results: After two rounds of Delphi method investigation, statistics, and modification, there are 92 indicators suitable for using multimedia in high school basketball teaching content. The content of high school multimedia basketball teaching is designed and includes the origin and development of basketball, sports injuries, and prevention, basic movement of a basketball player, dribble technique, one-handed marching shot, basic movement of a basketball player, basic basketball rules, shoot technique, pass technique, defend technique, breakthrough technique, advanced dribbling, steal technique, zone cooperation, pick and roll and defense, attacking match, fast break and defense, one-on-one check, offensive zone defense. Conclusion: The multimedia teaching content for basketball high school in Guangzhou was effective and appropriate, and can be integrated into the teaching plan.

Представления сотрудников полиции о взаимодействии с суицидентами

Currently, the problem of suicide prevention is not losing its relevance. In many countries of the world, there remains a need to take measures to prevent suicide, provide access to quality psychological help and create a supportive environment for people. The purpose of this article is to analyze the perception of police officers about interaction with suicides and offer practical recommendations for organizing effective communication between police officers and suicides. The subject of the study is the perception of police officers about the peculiarities of behavior when interacting with suicides. The study involved 41 respondents aged 19 to 37 years. It should also be noted that police officers have an idea of the basic rules of behavior with citizens prone to suicide. It was revealed that police officers have a general idea of the behavioral characteristics of individuals showing signs of suicidal behavior, and the awareness of officers of the general rules of behavior with suicides is noted. At the same time, it is necessary to constantly expand knowledge, improve the skills of interaction of police officers with potential suicides.

A Proposal for a Best-evidence Model of Care and Program Logic for Supported Accommodation for People Released From Prison.

This paper describes the development of a proposed best-evidence model of care (MoC) and program logic (PL) for supported accommodation (SA) for people released from prison. Evidence from a systematic review, interviews with clients of SA, and consultation with service providers were synthesized to develop a draft MoC that was embedded into a PL. The MoC and PL were refined in a workshop with researchers and SA providers. The MoC comprised five best-evidence core components to be standardized across any SA, operationalized by flexible activities that need to be determined by services to suit their circumstances. The PL comprised client needs that the program targets, a rationale for why core components would be effective and appropriate process and outcome measures. The development and uptake of a best-evidence MoC and clearly defined PL will help engender a larger and more rigorous SA evidence-base, and improve outcomes for people released from prison.

Application of torque observer based on belief rule base to power redistribution process

When navigating in ice zones, broken ice can be drawn into the propeller by the wake current, significantly altering the propeller load and causing severe fluctuations in the power grid of electrical propulsion ship. To address this issue, this paper presents two kinds of power redistribution control (PRC) strategies, which utilises the dynamic feedback from the ship's generator sets to the electric propulsion system to improve the frequency control. The PRC strategy #2, which receives feedback from generator's torque deviation, has better control effect than PRC strategy #1 with feedback from speed deviation. Since the accuracy of the estimated mechanical torque directly affects the control effect of strategy #2, this paper designs a torque observer based on the Belief Rule Base (BRB) by matching the PRC strategy to regulate the grid frequency in real-time. Given the power grid's fluctuations primarily caused by aft propellers, the power will be partly redistributed to the bow thruster to stabilise the ship's grid. Experiments show that this method can maintain the stability of the grid frequency by quickly correcting the power distribution during the process of sudden shedding propeller load.

Vehicular Traffic Flow Detection and Monitoring for Implementation of Smart Traffic Light: A Case Study for Road Intersection in Limeira, Brazil

This paper proposes the development of a smart traffic light prototype based on vehicular traffic flow measurement in the stretch between two avenues in the city of Limeira, SP, Brazil, focusing on the stretch towards UNICAMP’s School of Technology. To this end, we initially developed a Python code using the OpenCV library in order to detect and count vehicles. With the counting in operation, programming logic was inserted, aiming at preparing traffic light timers based on vehicular traffic. Finally, the traffic lights were added to display video via a code change to show the ongoing color changes, also obtaining a code for identifying vehicles and flow, in addition to the virtual traffic light system itself in the system. Vehicle counting accuracy was 75% for large vehicles, 90% for passenger cars, and 100% for motorcycles. The simulation of a smart traffic light implementation worked satisfactorily according to the post-processing of the video recorded for validation.

PLC/HMI Based Portable Workbench for PLC and Digital Logic Learning and Application Development

A Programmable logic controller (PLC) uses the digital logic circuits and their operating concepts in its hardware structure and its programming instructions and algorithms. Therefore, the deep understanding of these two items is staple for the development of control applications using the PLC. This target is only possible through the practical sensing of the various components or instructions of these two items and their applications. In this work, a user-friendly and re-configurable ladder, digital logic learning and application development design and testing platform has been designed and implemented using a Programmable Logic Controller (PLC), Human Machine Interface panel (HMI), four magnetic contactors, one Single-phase power line controller and one Variable Frequency Drive (VFD) unit. The PLC role is to implement the ladder and digital logic functions. The HMI role is to establish the virtual circuit wiring and also to drive and monitor the developed application in real time mode of application. The magnetic contactors are to play the role of industrial field actuators or to link the developed application control circuit to another field actuator like three phase induction motor. The Single -phase power line controller is to support an application like that of the soft starter. The VFD is to support induction motor driven applications like that of cut-to-length process in which steel coils are uncoiled and passed through cutting blade to be cut into required lengths. The proposed platform has been tested through the development of 14 application examples. The test results proved the validity of the proposed platform.

A Security Situation Prediction Model for Industrial Control Network Based on Explainable Belief Rule Base

Industrial Control Systems (ICSs) are vital components of industrial production, and their security posture significantly impacts operational safety. Given that ICSs frequently interact with external networks, cyberattacks can disrupt system symmetry, thereby affecting industrial processes. This paper aims to predict the network security posture of ICSs to ensure system symmetry. A prediction model for the network security posture of ICSs was established utilizing Evidence Reasoning (ER) and Explainable Belief Rule Base (BRB-e) technologies. Initially, an evaluation framework for the ICS architecture was constructed, integrating data from various layers using ER. The development of the BRB prediction model requires input from domain experts to set initial parameters; however, the subjective nature of these settings may reduce prediction accuracy. To address this issue, an ICS network security posture prediction model based on the Explainable Belief Rule Base (BRB-e) was proposed. The modeling criteria for explainability were defined based on the characteristics of the ICS network, followed by the design of the inference process for the BRB-e prediction model to enhance accuracy and precision. Additionally, a parameter optimization method for the explainable BRB-e prediction model is presented using a constrained Projection Equilibrium Optimization (P-EO) algorithm. Experiments utilizing industrial datasets were conducted to validate the reliability and effectiveness of the prediction model. Comparative analyses indicated that the BRB-e model demonstrates distinct advantages in both prediction accuracy and explainability when compared to other algorithms.

Generative AI Prompt Engineering for Educators: Practical Strategies

Generative AI, such as ChatGPT, produces personalized and contextually relevant content based on user prompts (inputs provided by users). These prompts act as the primary form of interaction between users and AI models, making their quality essential for generating the most relevant outputs. The process of writing, refining, and optimizing prompts, known as prompt engineering, is key to obtaining high-quality desired outputs from generative AI. For educators, proficiency in prompt engineering is crucial for effective interaction with AI as it enhances efficiency and produces the most relevant information. In this paper, we introduce practical strategies for prompt engineering for educators: (a) include essential components, including Persona, Aim, Recipients, Theme, and Structure (PARTS); (b) develop prompts using Concise, Logical, Explicit, Adaptive, and Restrictive (CLEAR) languages; (c) evaluate output and refine prompts: Rephrase key words, Experiment with context and examples, Feedback loop, Inquiry questions, Navigate by iterations, Evaluate and verify outputs (REFINE); and (d) apply with accountability. Examples for special educators and online resources are included.

UTILIZAÇÃO DE MAPAS CONCEITUAIS PARA VERIFICAÇÃO DE APRENDIZAGEM SIGNIFICATIVA EM ATIVIDADES INTERDISCIPLINARES NO TÉCNICO INTEGRADO EM AUTOMAÇÃO INDUSTRIAL

This article presents the results of an investigation into the use of concept maps to assess meaningful learning in interdisciplinary activities with students from a Technical Course in Industrial Automation integrated into High School at a Federal Institute campus in the interior of Rio de Janeiro state. Based on David Ausubel's Theory of Meaningful Learning and using Joseph Novak's Concept Maps, this work adopted a qualitative approach with a pedagogical intervention through an Interdisciplinary Didactic Sequence. Concepts from Physics, Programmable Logic Controllers, Instrumentation, Process Control, and Pneumatic Commands were integrated, using the Flipped Classroom and practical activities on a Didactic Bench. The analysis of the concept maps, created by students before and after the intervention, revealed a significant increase of 32.56% in the quality of cross-links, indicating deep integrative reconciliations and improved assimilation of interdisciplinary concepts.

On the Equivalence between Logic Programming and SETAF

Abstract A framework with sets of attacking arguments ( $\textit{SETAF}$ ) is an extension of the well-known Dung’s Abstract Argumentation Frameworks ( $\mathit{AAF}$ s) that allows joint attacks on arguments. In this paper, we provide a translation from Normal Logic Programs ( $\textit{NLP}$ s) to $\textit{SETAF}$ s and vice versa, from $\textit{SETAF}$ s to $\textit{NLP}$ s. We show that there is pairwise equivalence between their semantics, including the equivalence between $L$ -stable and semi-stable semantics. Furthermore, for a class of $\textit{NLP}$ s called Redundancy-Free Atomic Logic Programs ( $\textit{RFALP}$ s), there is also a structural equivalence as these back-and-forth translations are each other’s inverse. Then, we show that $\textit{RFALP}$ s are as expressive as $\textit{NLP}$ s by transforming any $\textit{NLP}$ into an equivalent $\textit{RFALP}$ through a series of program transformations already known in the literature. We also show that these program transformations are confluent, meaning that every $\textit{NLP}$ will be transformed into a unique $\textit{RFALP}$ . The results presented in this paper enhance our understanding that $\textit{NLP}$ s and $\textit{SETAF}$ s are essentially the same formalism.

Artificial Intelligence Techniques for Sustainable Reconfigurable Manufacturing Systems: An AI-Powered Decision-Making Application Using Large Language Models

Artificial intelligence (AI) offers a promising avenue for developing sustainable reconfigurable manufacturing systems. Although there has been significant progress in these research areas, there seem to be no studies devoted to exploring and evaluating AI techniques for such systems. To address this gap, the current study aims to present a deliberation on the subject matter, with a particular focus on assessing AI techniques. For this purpose, an AI-enabled methodological approach is developed in Python, integrating fuzzy logic to effectively navigate the uncertainties inherent in evaluating the performance of techniques. The incorporation of sensitivity analysis further enables a thorough evaluation of how input variations impact decision-making outcomes. To conduct the assessment, this study provides an AI-powered decision-making application using large language models in the field of natural language processing, which has emerged as an influential branch of artificial intelligence. The findings reveal that machine learning and big data analytics as well as fuzzy logic and programming stand out as the most promising AI techniques for sustainable reconfigurable manufacturing systems. The application confirms that using fuzzy logic programming in Python as the computational foundation significantly enhances precision, efficiency, and execution time, offering critical insights that enable more timely and informed decision-making in the field. Thus, this study not only addresses a critical gap in the literature but also offers an AI-driven approach to support complex decision-making processes.

A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base.

With the rapid advancements in information technology and industrialization, the sustainability of industrial production has garnered significant attention. Industrial control systems (ICS), which encompass various facets of industrial production, are deeply integrated with the Internet, resulting in enhanced efficiency and quality. However, this integration also introduces challenges to the continuous operation of industrial processes. This paper presents a novel security assessment model for ICS, which is based on evidence-based reasoning and a library of belief rules. The model consolidates diverse information within ICS, enhancing the accuracy of assessments while addressing challenges such as uncertainty in ICS data. The proposed model employs evidential reasoning (ER) to fuse various influencing factors and derive security assessment values. Subsequently, a belief rule base is used to construct an assessment framework, grounded in expert-defined initial parameters. To mitigate the potential unreliability of expert knowledge, the chaotic mapping adaptive whale optimization algorithm is incorporated to enhance the model's accuracy in assessing the security posture of industrial control networks. Finally, the model's effectiveness in security assessment was validated through experimental results. Comparative analysis with other assessment models demonstrates that the proposed model exhibits superior performance in ICS security assessment.