Rule-based Research Articles

Ontological description method for building service-oriented distributed learning systems

The subject of the research is the analysis and justification of the use of software engineering processes based on ontologies of data access and representation of access to knowledge bases and knowledge reuse in the language of algebra of finite predicates, which is a class of descriptive logics. This approach allows you to use the advantages of ontologies and logic programming in the refactoring of distributed distance learning systems. The purpose of the work is to create a formalism for describing the interaction of services and algorithms for building web service interfaces for the implementation of an effective SOA system using the paradigm of access to data based on ontologies. To achieve the goal, the following tasks were solved: an analysis of the main types of interaction structures of SOA services, an overview of implementations of systems working with a family of descriptive logic languages, namely, algebra of finite predicates, and a description of the structure of the ontology necessary for the operation of service-oriented systems, which has the markup of the Semantic Web standard using finite predicate algebra equations. The task is an urgent task of ensuring the organization of interaction of Internet resources in the development of distributed virtual learning systems, and such interaction is enabled by the service-oriented architecture of software development. The article examines modern technologies of the Semantic Web and their role in ensuring the creation of applied software systems of distributed learning resources built using distributed interactive services. The considered methods and materials include methods of algebra of finite predicates, theory of algorithms, object-oriented design, theory of unification. The results. The semantics of the SOA system is obtained, which makes it possible to describe SOA systems in the languages of descriptive logic. The effectiveness of the mathematical formalism of the algebra of finite predicates for the tasks of logical analysis of applied ontologies, the use of knowledge reuse methods, and the description of service-oriented systems is shown. The necessity of using algorithms for automatic construction of web interfaces is shown. The conclusions of the work highlight the advantages of the researched solution, namely, algorithms for the automated construction of web service interfaces for SOA architecture, which make it possible to automatically build web service interfaces. Algorithms differ in a more general model and speed of work and require an assessment of complexity.

FP-tracer: Fine-grained Browser Fingerprinting Detection via Taint-tracking and Entropy-based Thresholds

Browser fingerprinting is an effective technique to track web users by building a fingerprint from their browser attributes. It is also stealthy because the tracker uses legitimate JavaScript API calls offered by the browser engine, which can be obfuscated before they are sent to a (third-party) server. Current browser fingerprinting methodologies employ coarse-grained collection and classification techniques, such as binary classification of fingerprinters based on the number of non-obfuscated exfiltrated attributes. As a result, they produce inconsistent findings. Meanwhile, the privacy of millions of web users is at risk daily. We address this gap by presenting FP-tracer, a novel methodology to detect and classify browser fingerprinters based on dynamic taint tracking and joint entropy classification. Our methodology enables detecting first- and third-party fingerprinters even when they use obfuscation by tainting attributes, propagating them, and logging when they are leaked (via 62 sources and 25 sinks). Moreover, it discriminates the invasiveness of fingerprinting activities, even from the same service, by measuring the joint entropy of the collected attributes and clustering them. We implement FP-tracer by extending Foxhound, a privacy-oriented Firefox fork with numeric type tainting, more taint tracking sources and sinks, support for multiple sources, and better logging capabilities. We embed our implementation in our automated crawling infrastructure, which is capable of testing websites in parallel using programmable and reproducible logic. We will open-source our implementation. We evaluate FP-tracer by performing a large-scale crawl over the Tranco Top 100K, and detect, amongst others, audio, canvas, and storage fingerprinting on the web. Among others, we find high fingerprinting activities in 8% of domains, with more moderate activity reaching 75%. Notably, fingerprinting is almost five times more likely to be performed by third-party scripts for high activity levels. In addition, we measure that the most severe category of fingerprinting obfuscates 46% of transmitted attributes, and 38% of fingerprinters involve two or more domains. Finally, we find that existing consent banners do not provide an effective defense against browser fingerprinting

Modeling Enterprise Software with UAF

AbstractSystems and Software Engineers often have an uneasy relationship. The job of the systems engineer is to work with the stakeholders to define a set of requirements that meet their needs. These are then allocated to various solution spaces such as electronic hardware, mechanical, procedural, and software among others. For many systems, the functional requirements are almost exclusively software requirements. Correspondingly, as an increasing amount of project manpower, schedule time, and budget are allocated to software, it becomes increasingly important that systems and software engineers communicate effectively. The Systems Modeling Language (SysML) has helped in this regard in that it can provide executable behavioral models with precise semantics to express software requirements in a model. These models define “What is required” without overly constraining the implementation. In addition, SysML can be used to define performance constraints, required concurrency, hardware memory and processor budgets, interfaces, safety critical requirements, etc. These aspects are essential for software engineers to understand the constraints and limitations of their environment. At the System of Systems (SoS)/Enterprise level, defining software/systems employs a similar pattern, but at a higher level of abstraction. In the Unified Architecture Framework, capabilities are defined for the enterprise, with systems and software allocated to realize the capabilities. In the same way that capabilities depend on one another, the implementing systems and software interact to support each other. In the past, enterprise software would be modeled as residing in mainframes in a federated software pattern. Modern software can be modeled throughout the enterprise in a distributed network that can adapt to the changing needs of the enterprise to do load leveling, dynamic and late binding, reconfiguration, and reallocation of hardware resources as necessary. If the domain includes the Industrial Internet of Things (IIOT), then deployment could include edge devices, embedded software, Programmable Logic Controllers (PLC), PCs, servers, cloud computing, and of course mainframes. The Object management Group (OMG) Data Distribution Services (DDS) standard enables these capabilities across these devices in a universal format implemented by multiple vendors. However, before this complex system of systems can be implemented, it must first be architected and designed to ensure that it will be fit for purpose both now and as the complex system of systems expands and evolves. This paper will examine the aspects of modeling software in the UAF, and how it can help guide enterprise and system and software architecture.

State of the Art and Future Trends in Monitoring for Industrial Induction Heating Applications

Induction surface hardening (ISH) processes are widely used in the heat treatment of numerous industrial components, especially in the automotive industry. Since this industry operates under very demanding quality standards, it is crucial for these heat treatment processes to meet rigorous specifications to ensure the safety and reliability of the produced components. This implies the precise and repeatable control of certain parameters throughout the manufacturing process of each of the parts treated, through precise and reliable instrumentation in electromagnetically harsh environments. The main objective of this work is to define the monitoring process for an industrial IHS application, determining the control needs and the methods of measurement, recording, and verification of the parameters that ensure the quality of the process. This paper describes the monitoring process of induction surface hardening, emphasizing the use of sensors and modern measurement and control systems. A comprehensive monitoring system supported by a programmable logic controller (PLC) and mixed acquisition and instrumentation systems (analog and digital) implemented with a high-performance Field Programmable Gate Array (FPGA) will be presented.

Development of All Solid State Nanosecond Pulse Transformer Fault Detection Device Based on Marx Circuit

Abstract a nanosecond pulse generator with a fast leading edge for transformer fault diagnosis is developed. The device is composed of a full solid-state nanosecond pulse generator based on Marx circuit and with a tail cut switch and a field programmable logic gate array (FPGA) device. Among them, the nanosecond pulse source is mainly composed of DC power supply, control circuit and main circuit. The main circuit is a 9-level modular Marx circuit, using MOSFET as the main switch and tail cut switch; The control circuit generates a synchronous trigger pulse signal, which drives the MOSFET to work synchronously after being isolated through the optical fiber. The output nanosecond pulse voltage parameters are adjustable amplitude 0-8kv, pulse width 100˜1000ns, repetition frequency 1hz˜1000hz, rising edge 30ns and falling edge 40ns. The transformer fault diagnosis platform is built, and the transformer off-line and on-line fault diagnosis is carried out, which paves the way for further exploration of transformer fault diagnosis technology.

Sistem Otomasi Untuk Menyortir Barang Pada Ruang Produksi Menggunakan Scada dan PLC

The development of the industrial revolution is progressing. Especially on production performance or machine parts. Industrial revolution 4.0 uses the internet and digitalization. So there are lots of new innovations. In a large-scale company, of course there are many tools and machines that need to be regulated whether they are on or not with regular supervision. With regular supervision, it is impossible for human workers to check one by one, thereby wasting time and reducing production levels. Therefore, it is necessary to develop a control system using PLC and HMI (Human Machine Interface) as the brain or control center for the company. In the industrial sector, PLC (Programmable Logic Controller) is an important factor in the operation of automatic machines in factories replacing relay control systems. So that PLC as a control system in the industrial sector can move machines according to needs. One part of the industry is the production room. The production room is the part where there are manufacturing materials or goods up to packaging. This research aims to design and implement a PLC (Programmable Logic Controller) and SCADA by adding sensors and actuators as output. The method used is a rule base system, the system runs according to a predetermined sequence and flow. The results of this research are the PLC, the SHT 20 temperature and humidity sensor can produce temperature and humidity values, the capacitive photosensor can detect items with 35 trials accurately but the distance is limited to only 27cm, the proximity sensor can only detect metal objects by attaching to the sensor and The actuator in the form of a stepper motor can run according to the commands given and is well integrated into the HMI (Human Machine Interface).

Study of an auxiliary trimming device for cracked carrots

AbstractCracked carrots account for a large proportion of defective carrots, which are usually discarded or used as feed, resulting in resource waste and economic benefit loss. Cracked carrots can be used as raw materials for further processed carrot products after being trimmed. So, an auxiliary device was developed combining PLC (Programmable Logic Controller) and machine vision to achieve clamping and crack defect localization for intelligent trimming of crack defect. The carrot was orientated based on the area method, rotated by flexible jaws and a rotating cylinder to make the carrot head and tail aligned. The clamping device could non‐destructively clamp carrot in axial and radial direction with a force threshold of 10 and 22 N respectively, and rotate carrot to make the crack defect upwards. The results showed that the recognition accuracy of carrot head and tail orientation was 98%, the average deviation of carrot centroid clamping position was less than 9 mm at a speed of 300 mm/s, the rotational positioning time was less than 3 s and the number of adjustments were no more than 2 at a motor speed of 180 rpm, which could meet the subsequent trimming requirements.Practical applicationsTrimming the cracked area of carrots can reduce bacterial growth and decay, which is beneficial for subsequent processing and reduces resource waste. This article designs a carrot auxiliary trimming device, which uses image processing technology to recognize the orientation of the head and tail of carrots and the cracked area, and uses automated equipment to achieve stable clamping of carrots and make the cracked area face the trimming tool. This study is beneficial for the refined management of agricultural products.

Trustworthy Fault Diagnosis Method Based on Belief Rule Base With Multisource Uncertain Information for Vehicle

This paper develops a new trustworthy fault diagnosis (TFD) method based on belief rule base expert system with combining multi-source uncertainty information for vehicle, such as flying machine. To improve the performance of fault diagnosis for vehicle, a new belief rule base expert system with multi-source uncertainty information (BRB-MU) is developed, where the influence of the random environment disturbance is addressed by introducing uncertain factors of input characteristics. In BRB-MU, the uncertain factors of input characteristics are calculated by the signal to noise ratio based method. The new developed BRB-MU model aims to handle three problems: unbalanced observation data of system states, uncertain expert knowledge and random environment disturbance. The first two problems are solved by the combination of expert knowledge and observation data. In parallel, the third problem is handled by the new introduced uncertain factors based on singular value decomposition (SVD) in BRB-MU. To quantitatively analyze the influence of the uncertain information to the TFD output, the traceability analysis of BRB-MU is conduced that can provide support for decision making of vehicle optimization design. It is analyzed based on the modeling traceability and parameters interpretability. To demonstrate the effectiveness of the TFD method, an experiment illustration is conduced.

Virtual Machinations: Using Large Language Models as Neural Computers

We explore how Large Language Models (LLMs) can function not just as databases, but as dynamic, end-user programmable neural computers. The native programming language for this neural computer is a Logic Programming-inspired declarative language that formalizes and externalizes the chain-of-thought reasoning as it might happen inside a large language model.

Analisis Sistem Kinerja PLC Pada Air Dryer di Unit Utilities PT. X

The refinery process in PT. X relies on several supporting units, including the air dryer in the utilities section, which is essential for removing water content from compressed air to support refinery operations. This research aimed to analyze the performance of the Programmable Logic Controller (PLC) system in the air dryer units (A, B, C, and D), each comprising two towers that can operate alternately or simultaneously. The conventional TM series controller was replaced with a Schneider Electric Modicon M340 PLC to enhance system reliability and digitization. A methodical approach was adopted, beginning with data collection from sensors connected to the PLC, followed by processing the data using predefined logic instructions. The research findings indicated significant improvements in operational efficiency, response time, and energy consumption with the PLC system compared to the TM series. The PLC system also facilitated continuous and precise control of the drying and regeneration processes. These findings underscore the importance of adopting advanced PLC systems to ensure higher operational efficiency and reliability in industrial applications. Consequently, this research advocates for the comprehensive upgrade of conventional control systems to PLCs in similar industrial settings.

PLC Based Automatic Bottle Filling System

Abstract: Introducing a cutting-edge solution for beverage industries, our paper unveils a revolutionary bottle filling machine employing state-of-the-art Programmable Logic Controller (PLC) technology. Crafted with simplicity and efficiency in mind, this compact system seamlessly integrates a conveyor belt for bottle transportation and a precision DC pump to regulate water flow with unparalleled accuracy Operating with finesse, an infrared sensor precisely detects bottle positions, triggering the pump to commence filling precisely at the opportune moment. Once the bottle is detected, a secondary sensor halts the conveyor, initiating a 15-second pump operation optimized for filling up to 800ml bottles swiftly and flawlessly. Upon completion, the pump gracefully ceases, and the conveyor resumes its smooth operation Notably, our system is designed with user convenience at its core. A dedicated stop button empowers operators to halt operations instantly, ensuring safety and control. With each component meticulously optimized for performance and reliability, our cost-effective filling machine stands as a beacon of innovation, poised to revolutionize small-scale beverage enterprises, from cozy coffee shops to bustling juice bars and beyond.

Social Cohesion in Islam and the Role of Family in Enhancing it among its Children (An Analytical Study)

The study aimed to discuss social cohesion in Islam and the role of family in educating its children about its mechanisms “an analytical study”. The study used the descriptive method. It consists of a general framework, which included the study introduction, problem, questions, objectives, importance, methodology, terminology, previous studies with comment on it, and three themes. The first theme is the conceptual framework of social cohesion in Islam, it discussed the concept of social cohesion in Islam, the objectives of social cohesion in Islam, the importance of social cohesion in Islam, the main roles of social cohesion in Islam, the basic rules for building the required social relations for social cohesion. The second theme is the concept of the family in Islam and its importance in achieving social cohesion, and included the concept of family in Islam, the importance of family in achieving social cohesion. The third theme is the role of family in educating its children about mechanisms of social cohesion, and it included the following: First: activating the elements of social cohesion, second: educating its children on citizenship and belonging to enhance their social cohesion, and third: Educating its children on social solidarity, and Fourth: activating the Islamic approach in family relations. Finally, it is a conclusion with the most prominent results, recommendations and suggestions of the study.

A Hardware Approach For Accelerating Inductive Learning In Description Logic

The employment of Machine Learning (ML) techniques in embedded systems has seen constant growth in recent years, especially for black-box ML techniques (such as Artificial Neural Networks (ANNs)). However, despite the successful employment of ML techniques in embedded environments, their performance potential is constrained by the limited computing resources of their embedded computers. Several hardware-based approaches were developed (e.g., using FPGAs and ASICs) to address the constraints of limited computing resources. The scope of this work focuses on improving the performance for Inductive Logic Programming (ILP) on embedded environments. ILP is a powerful logic-based ML technique that uses logic programming to construct human-interpretable ML models, where those logic-based ML models are capable of describing complex and multi-relational concepts. In this work, we present a hardware-based approach that accelerates the hypothesis evaluation task for ILPs in embedded environments that use Description Logic (DL) languages as their logic-based representation. In particular, we target the \(\mathcal {ALCQ}^{\mathcal {(D)}}\) language. According to experimental results (through an FPGA implementation), our presented approach has achieved speedups up to 48.7-fold for a disjunction of 32 concepts on 100 M individuals, where the baseline performance is the sequential CPU performance of the Raspberry Pi 4. For role and concrete role restrictions, the FPGA implementation achieved speedups up to 2.4-fold (for MIN cardinality role restriction on 1M role assertions); all FPGA implemented role and concrete role restrictions have achieved similar speedups. In the worst-case scenario, the FPGA implementation achieved either a similar or slightly better performance than the baseline (for all DL operations); the worst-case scenario resulted from using small datasets such as: using conjunction and disjunction on < 100 individuals, and using role and concrete (float/string) role restrictions on < 100,000 assertions.

Expert Twin: A Digital Twin with an Integrated Fuzzy-Based Decision-Making Module

Digitalization and the application of modern Industry 4.0 solutions are becoming increasingly important to remain competitive as product ranges expand and global supply chains grow. This paper presents a new Digital Twin framework to achieve robustness in manufacturing process optimization and enhance the efficiency of decision support. Most digital twins in the literature synchronously represent the real system without any control elements despite the bidirectional data link. The proposed approach combines the advantages of traditional process simulations with a real-time communication and data acquisition method using programmable logic controllers designed to control automated systems. In addition, it complements this by utilizing human experience and expertise in modeling using Fuzzy Logic to create a control-enabled digital twin system. The resulting "Expert Twin" system reduces the reaction time of the production to unexpected events and increases the efficiency of decision support; it generates and selects alternatives, therefore creating smart manufacturing. The Expert Twin framework was integrated, tested, and validated on an automated production sample system in a laboratory environment. In the experimental scenarios carried out, the method production increased production line utility by up to 28% and the number of re-schedules can be halved.

Geometric reasoning on the euclidean traveling salesperson problem in answer set programming1

The Traveling Salesperson Problem (TSP) is one of the best-known problems in computer science. Many instances and real world applications fall into the Euclidean TSP special case, in which each node is identified by its coordinates on the plane and the Euclidean distance is used as cost function. It is worth noting that in the Euclidean TSP more information is available than in the general case; in a previous publication, the use of geometric information has been exploited to speedup TSP solving for Constraint Logic Programming (CLP) solvers. In this work, we study the applicability of geometric reasoning to the Euclidean TSP in the context of an ASP computation. We compare experimentally a classical ASP approach to the TSP and the effect of the reasoning based on geometric properties. We also compare the speedup of the additional filtering based on geometric information on an ASP solver and a CLP on Finite Domain (CLP(FD)) solver.

РОЛЬ СЛОВАРЯ ПОНЯТИЙ В АВТОМАТНОМ ПРОГРАММИРОВАНИИ НА ПРИМЕРЕ РАЗРАБОТКИ СИСТЕМЫ УПРАВЛЕНИЯ АВТОМАТИЗИРОВАННОГО АКВАРИУМА

The paper considers the issue of using automa-based programming technology methods for developing software for an automated aquarium. The technological process of operating the aquarium is analyzed in detail and the choice of cer-tain hardware solutions included in the automated aquarium control system is substantiated. The need to write a con-trol system for the object (aquarium) is justified and the methods of its use are proved. The control system structure is analyzed, where each new piece of code in this program is given an explanation of its functionality and application possibilities for reference, taken from the concept dictionary of automa-based programming techniques. The result is presented in the form of a program code and block diagrams that translate the rules of this system operation into the language of logic, based on the knowledge about the technological structure of the aquarium. This software develop-ment method is a “machine” translation of a clearly written human text, being an attempt to show that the process of writing a program code is a process of translating a text from one language into another, and also that this method of programming is easy to learn and convenient in operation. In this case, the first language is understandable to hu-mans, and the second language is adapted for computers. For a stable operation of this translation technique, a dic-tionary is needed that allows the user to create a task for the computer.

Error Analysis of English Writing in Final Year Projects in Malaysia: The Case of IIUM

This study conducted an Error Analysis (EA) on written dissertations by undergraduates from the English Language and Literature (BENL) department at International Islamic University Malaysia (IIUM). Despite the abundance of research on EA conducted with multiple samples and backgrounds, only a few studies concerning EA can be found and accessed in a Malaysian context. Thus, this paper aims to find the most common errors committed by undergraduates in Malaysia, focusing on their theses that adhered strictly to academic writing. Using Stephen Pit Corder's EA framework, a qualitative approach was employed to find the errors in the written samples. Additionally, this research synthesised the results of the Lunsford & Connors' study in 1988 with several studies on the Malaysian context that were compared and contrasted with findings from the interview session with lecturers from the BENL department to find the most common errors in writing among Malaysians. This paper's results demonstrate that the most common errors from IIUM undergraduates are word choice, punctuation, prepositions, plurality and singularity, verbs, articles, pronoun, ambiguity, adverbs, and subject-verb agreement. Similar to the synthesis, word choice remains the most highlighted classification of errors. In contrast, it is revealed that subject-verb agreement (SVA) is not the most frequent error. One possible justification for this finding is accessible online grammar checkers that revise students' writing with basic grammar rules. Therefore, this paper has contributed to Error Analysis in theses to benefit language learners, both learners and teachers and researchers interested in the Second Language Acquisition (SLA) field in Malaysia.

Design and Development of Fractional Order Convolutional Neural Network Based Fractional Order Nonlinear Reactor Power Simulator for CANDU-PHWR

A highly complex nonlinear Reactor Regulating System (RRS) of Canadian Deuterium Uranium Pressurized Heavy Water Reactor (CANDU-PHWR) based Nuclear Power Plant (NPP) simulated in the present research. The internal design of RRS is secured and vendor controlled which is embedded in AC-132 Programmable Logic Controller (PLC). Therefore, the problem of the identification of the RRS controller model is addressed. A data-driven Fractional Order Nonlinear MIMO Hammerstein Model (FO-NC-MIMO-HM) of NPP is identified using an Adaptive Immune Algorithm (AIA) based on a Global Search Strategy (GSS) and Auxiliary Model Recursive Least Square Method (AMRLSM). Parameters of FO-MIMO-HM are identified using Innovative Real-Time Plant Operational Data (IRTPOD). The original PLC-based controller is replaced with a new Fractional Order Convolutional Neural Network (FO-CNN) based Fractional Order Nonlinear Controller (FO-NC). Therefore, a visual Simulator is developed for detailed modeling, control, simulation, and analysis of the proposed design scheme for RRS in Visual Basic (VB) Software. The performance of the proposed design scheme is tested and validated for different modes of RRS against benchmark data obtained from Plant Data Recorder (PDR) and found in close agreement well within the design bounds.

Development of programmable logic controller algorithms for database communication

The present paper provides a brief overview of the possibilities which can arise when outsourc-ing some of the more advanced functionalities usually developed for computers to a programma-ble logic controller. This approach is still being examined to fulfil its aim of improved communi-cation capabilities and provision of effective tools for advanced intelligent control systems. The paper, further, sets out to give an example of one such algorithm which is built upon the MySQL protocol.

Development and Integration of a Digital Twin Model for a Real Hydroelectric Power Plant.

In this study, a digital twin model of a hydroelectric power plant has been created. Models of the entire power plant have been created and malfunction situations of a sensor located after the inlet valve of the plant have been analyzed using a programmable logic controller (PLC). As a feature of the digital twin (DT), the error prediction and prevention function has been studied specifically for the pressure sensor. The accuracy and reliability of the data obtained from the sensor are compared with the data obtained from the DT model. The comparison results are evaluated and erroneous data are identified. In this way, it is determined whether the malfunction occurring in the system is a real malfunction or a malfunction caused by measurement or connection errors. In the case of sensor failure or measurement-related malfunction, this situation is determined through the digital twin-based control mechanism. In the case of actual failure, the system is stopped, but in the case of measurement or connection errors, since the data are calculated by the DT model, the value in the specified region is known and thus there is no need to stop the system. This prevents production loss in the hydroelectric power plant by ensuring the continuity of the system in case of errors.