Object Model Research Articles

Adaptive fuzzy finite-time PID backstepping control for chaotic systems with full states constraints and unmodeled dynamics

To solve the problem that the controlled object and system model cannot be fully mastered or the system parameters cannot be well obtained through conventional measurement methods, in this paper, a novel adaptive fuzzy finite-time PID backstepping control method is developed for a class of nonlinear chaotic systems with full state constraints and unmodeled dynamics. The unmodeled dynamics are handled by employing a dynamic signal. To avoid the violations of full state constraints (FSCs), a barrier Lyapunov function is used to implement a PID backstepping framework, whose merit consists in that three control gain constants KP, KI and KD with corresponding proportional relationships are designed to further improve control precision. Besides, the PID control method also embodies three dynamic gain components ΔKP, ΔKI and ΔKD, all of which are free functions that can be self-tuning online, and have a significant link with the adaptive law and modify accordingly. Finally, theoretical analysis confirms that all signals are ultimately uniformly bounded, the error signal converges to a nearby area near the origin in a finite-time, and the FSCs are not smashed. The practicality of the proposed method is confirmed by two simulation studies using the second-order Duffing chaotic system and third-order Chua's circuit.

On‐demand JSON: A better way to parse documents?

SummaryJSON is a popular standard for data interchange on the Internet. Ingesting JSON documents can be a performance bottleneck. A popular parsing strategy consists in converting the input text into a tree‐based data structure—sometimes called a Document Object Model or DOM. We designed and implemented a novel JSON parsing interface—called On‐Demand—that appears to the programmer like a conventional DOM‐based approach. However, the underlying implementation is a pointer iterating through the content, only materializing the results (objects, arrays, strings, numbers) lazily. On recent commodity processors, an implementation of our approach provides superior performance in multiple benchmarks. To ensure reproducibility, our work is freely available as open source software. Several systems use On Demand: for example, Apache Doris, the Node.js JavaScript runtime, Milvus, and Velox.

Stability analysis and evaluation of a highway slope in the high and cold mountain area and suggestions for prevention and control

In order to ensure the stability of a rocky slope on a highway in a high cold mountainous area, this paper evaluates the stability of the right high slope in the section from K155+320 to K155+460 using the Chi Ping projection method and the fuzzy evaluation method based on game theory-cloudified object model. Firstly, the geological, geomorphological, hydrological and other natural profile information of the slope is obtained through field investigation, and these indicators are transformed into evaluation indicators for qualitative evaluation using the Chi Ping projection method. Then, the fuzzy evaluation method based on game theory-cloudified object model is used to transform the qualitative evaluation results into quantitative data, taking into account the mutual influence between different factors. The results show that the results obtained by the two evaluation methods are consistent. Finally, based on the stability analysis and evaluation results, it is proposed to use the method of clearing the surface dangerous rocks and applying active protective nets to deal with the slope problem in that area. At the same time, the slope stability analysis and evaluation method and the prevention and control suggestions provide reference for the subsequent slope governance.

KDSMALL: A lightweight small object detection algorithm based on knowledge distillation

With the development of computer vision, small object detection has become a research pain point and difficulty in computer vision. Feature acquisition and accurate localization of small objects are two serious challenges that exist for small objects at present. In this paper, a generalized small object detection algorithm is formed based on a multi-scale feature extractor, a feature search network with hybrid attention mechanism, and knowledge distillation. The algorithm firstly performs feature extraction of small objects based on multi-scale feature extractor, secondly uses CBAM attention mechanism and Efficient network to perform feature search on features obtained from the feature map to help obtain more features of the small object, and finally performs knowledge distillation on the baseline model based on the idea of teacher–student knowledge distillation to help the baseline model locate the detected object. In this paper, YOLOv5s is selected as the benchmark experiment, and the designed algorithm is fused to YOLOv5s, compared with the baseline model, the fused model’s experimental metrics mAP on the VOC mixed dataset is improved by 14.45% on average. The experimental results show that the designed algorithm can effectively improve the detection performance of the object detection model for small objects.

An Effective GDP-LSTM and SDQL-Based Finite State Testing of GUI

The Graphical User Interface (GUI) is the most promising factor in the Software Development Lifecycle (SDL), which allows the users to interact with the system. To ensure user-friendliness, GUI Testing (GT) is required. The traditional testing techniques attained flawed results due to having inappropriate functions. Hence, Global Decaying Probabilistic Long Short-Term Memory (GDP-LSTM) and Standard Deviation Q-Learning (SDQL)-based automatic testing for GUI are proposed as solutions. Initially, the Test Case (TC) and GUI are extracted from the historical data and are subjected to Region of Interest (ROI) analysis. Here, an appropriate ROI is analyzed by Module Coupling Slice (MCS), and it is fed into Hadoop Parallelization (HP). Now, Spectral Kernelized Gaussian Clustering (SKGC) and Non-Linear Elite Guided Optimized Ant Colony (NE-GO-AC) are used to perform mapping and reducing, respectively. Likewise, the parallelized output is utilized to construct the Document Object Model (DOM) tree. Then, the attributes are extracted and given to the GDP-LSTM classifier that effectively predicts whether GUIs are desirable or undesirable. Then, the undesirable results are inputted into a SDQL-based deviation analysis. If the deviation is low, it is assumed as an update; otherwise, it is considered as an error. The experimental analysis depicted that the proposed system attained high dominance with 98.89% accuracy in the prevailing models.

SemiRS-COC: Semi-Supervised Classification for Complex Remote Sensing Scenes with Cross-Object Consistency.

Semi-supervised learning (SSL), which aims to learn with limited labeled data and massive amounts of unlabeled data, offers a promising approach to exploit the massive amounts of satellite Earth observation images. The fundamental concept underlying most state-of-the-art SSL methods involves generating pseudo-labels for unlabeled data based on image-level predictions. However, complex remote sensing (RS) scene images frequently encounter challenges, such as interference from multiple background objects and significant intra-class differences, resulting in unreliable pseudo-labels. In this paper, we propose the SemiRS-COC, a novel semi-supervised classification method for complex RS scenes. Inspired by the idea that neighboring objects in feature space should share consistent semantic labels, SemiRS-COC utilizes the similarity between foreground objects in RS images to generate reliable object-level pseudo-labels, effectively addressing the issues of multiple background objects and significant intra-class differences in complex RS images. Specifically, we first design a Local Self-Learning Object Perception (LSLOP) mechanism, which transforms multiple background objects interference of RS images into usable annotation information, enhancing the model's object perception capability. Furthermore, we present a Cross-Object Consistency Pseudo-Labeling (COCPL) strategy, which generates reliable object-level pseudo-labels by comparing the similarity of foreground objects across different RS images, effectively handling significant intra-class differences. Extensive experiments demonstrate that our proposed method achieves excellent performance compared to state-of-the-art methods on three widely-adopted RS datasets.

Hand gesture recognition based on CNN and YOLO techniques

Communication is essential for humanity today and in the past. However, some individuals lack verbal communication due to their innate disability and physical losses from accidents. There are sign-language communication methods developed for such people to communicate. Artificial intelligence solutions are offered to remove the disadvantaged situations of people with disabilities due to communication in daily life. Nowadays, rapidly developing image processing and artificial intelligence methods are proper solutions for the problem focused on in this study. Convolution neural network techniques, which have become very popular recently, offer solutions to many problems. On the other hand, the YOLO algorithm shows very high performance in real-time object detection. In this study, we proposed a method for identifying the alphabets which each gesture delivers. This work studied hand detection on images and classification according to hand movements. The American Sign Language (ASL) standard was used as the sign language. The most recent version of YOLO, known as YOLOv5x, is used for gesture detection. Concentrating on the Static Sign-language problem, a study was conducted on the definition of hand movements. The letters “J” and “Z” are not included in the data set because movable hand signals are required. Apart from these two letters, a total number of 24 letters are classified. The proposed model achieved a training performance of 99.45% mAP@.5. Moreover, the proposed model has a performance of 97.9% mAP@.5 on the test dataset. The results demonstrate that the model's object detection performance is excellent. A statistical analysis of the training time shows that the training time has been drastically decreased, 4.5 hours with the current model as compared to the existing models in the literature.

Architecture of a digital twin for container shipping monitoring

The developing problem of the digital twin information model of the railway rolling stock objects for a transport and logistics enterprise is considered. The architecture of the digital twin model for a cyber-physical production system is analyzed. An example of a transporting products means with a controlled temperature regime is given. An architecture for cargo transportation business processes based on digital twin model of a transport facility with managed online modes is developed. Keywords domain model, digital twin, transport logistics, information model architecture, cargo transportation management, specialized software

DISTRIBUTION OF RESOURCES TO ENSURE ANTI-TERRORIST SECURITY OF SOCIALLY SIGNIFICANT FACILITIES

A new software package ‒ electronic testing ground ‒ designed to increase the anti-terrorist protection of socially significant objects is presented. The complex supports mathematical modeling of antagonistic conflict between the offender and risk recipients in the context of a terrorist attack. The complex is based on the author’s methodology for increasing security, based on countering a terrorist attack through the controlled movement of human flows (controlled evacuation) to security zones along safe trajectories. Active protection of risk recipients under attack conditions takes into account the capabilities of engineering and technical means of protection. Algorithms for modeling controlled movement are built on the conditions of minimizing damage to risk recipients in conditions of a terrorist attack. Active protection is advisable when the attack time horizon is about 10 minutes. The most important feature of the presented electronic test site is the design of movement trajectories of risk recipients in automatic mode, taking into account the dynamics of the development of a terrorist attack. A digital model of the protected object is built using the domestic BIM system Renga. To simulate the activity of the intruder and the movement of human flows in real time the building model is represented as a topological graph. Quantitative assessment of the level of terrorist security of each socially significant object is based on a comparison of the levels of threats and security. Correspondence between the level of security and the level of threats is decisive for identifying a set of objects whose protection system requires modernization. The software package is focused on solving practical problems. In particular, the distribution of limited resources allocated to improve anti-terrorist security. The practical orientation of the electronic training ground is demonstrated by the example of the distribution of funds for the modernization of the anti-terrorism security system for the buildings of an educational institution.

Streamlining LEGO® model design: an automated optimisation approach

LEGO® models have become increasingly popular beyond their traditional toy and entertainment applications, and are now used in fields such as education, cognitive science, engineering and robotics. However, designing LEGO® models for such diverse applications poses new challenges in terms of automation and optimisation. To address such issues, this paper proposes a design support system that automatically generates LEGO® models from any 3D model of a target object using a specific set of standard LEGO® bricks in a layer-by-layer fashion. The system converts the 3D model into a LEGO® model using the minimum number of LEGO® bricks required. The core of the proposed system lies in the use of a greedy algorithm for merging optimisation of each layer of bricks and a depth-first search algorithm for optimising the connection between multiple layers of bricks. Experimental results on several 3D graphics validate the effectiveness of the proposed methodology and its ability to output the corresponding LEGO® model and detailed layout illustrations for each layer of bricks. The proposed system can provide LEGO® builders with an automated optimisation approach for designing LEGO® models, minimising errors compared to manual design.

FAILURE MODEL OF NON-RESTORABLE COMPLEX TECHNICAL OBJECT OF MILITARY EQUIPMENT

Maintenance (MT) is a necessary component the process of operating a complex technical object of military equipment, intended for long-term operation in wartime and harsh operating conditions. The volume, content and timing of maintenance must be completely determined by the reliability properties of the object, conditions and modes of its use. Effective implementation of any maintenance operation is possible only if the design of the object provides special means for this purpose (for measuring the defining parameters) and ensures the accessibility and convenience of performing the operation. Complex technical objects in modern society are extremely important. Such objects belong to the class of restored objects long-term repeated use. They are usually expensive and require significant operating costs. To ensure the required level of failure-free operation during their operation, maintenance is usually carried out, the essence of which is the timely preventive replacement of elements that are in a pre-failure state, which is very important for military equipment. A characteristic feature of complex technical objects for special purposes (military equipment) is the presence in their composition of a large number (tens, hundreds of thousands) different types of components that have different levels of reliability, different patterns of their wear and aging processes. This feature requires a more subtle approach to organizing and planning maintenance during operation (of military equipment). The above statements fully justify the conclusion about need to determine the main characteristics of the maintenance system in early stages of its design, when it is still possible to make changes to design of the object. In this work, a model of failure-free operation non-repairable complex technical object of military equipment is developed. The work also confirms the general idea that data obtained fully confirm the assumption that a maintenance strategy that is not restored is more preferable in the case of unreliable (inaccurate) information about the reliability indicators of elements of a military equipment object.

Modeling reflection in artificial intelligence systems: state of art and prospects

Abstract. The paper is devoted to analyzing the current state of research and assessing the prospects for modeling reflexive processes using artificial intelligence systems, in particular, multi-agent systems for relevant simulation of collective problem solving. Reflexive modeling of each other by agents will ensure the development of a coherent model of the control object, the purpose of collective work and norms of interaction, as well as the developing of effective interaction between agents. This will allow the system, by self-organizing, to adapt to the characteristics of arising problems, in particular, to take into account their complex structure, the network nature of conditions and goals, opacity, subjectivity and dynamism.

Редукция модели обменных процессов при идентификации электромеханических объектов

The issues of justification and calculation of the Green's function, as a model of an electromechanical object, from ordinary differential equations are considered. For this purpose, issues of reduction of the main model are discussed: idealization of the measuring and control device and requirements for the object model based on equations. During the calculation process, the complexity of the analytical derivation of the Green's function of an object is revealed, which is demonstrated by an example. In the «discussion of results» section, an analysis of the features of the Green's function obtained by calculation from ordinary differential equations is carried out in comparison with the Green's function obtained by identification.

Matching visually observed 3D model to original reference object

In the development of a visual environment simulator or a thermal imager simulator, one of the challenges encountered when assessing the external appearance of engineering structures is the need to ensure the correspondence of the developed 3D model of a reference object to the original 3D object. Since creating a complete model is currently impractical, the criterion for assessment is based on the conformity of forming specified components of the cognitive model of a human observer necessary in their professional activities. Research has shown that to address this challenge, it is advisable to choose one of the artificial intelligence methods to entrust it with the task of evaluating the developed 3D model and minimize the subjectivity in the decision-making process of “whether the external appearance of the 3D model meets the client's requirements.” The article proposes using deductive reasoning in ChatGPT to assess the conformity of the external appearance of a 3D model to a specified 3D object by representing the model as incomplete sequences and evaluating its ability to complete them in accordance with conclusions made by humans.The suggested approach involves solving the problem based on scenarios where humans formulate logical conclusions from provided information, followed by the application of ChatGPT in processing the presented sequences of conclusions. A comparative analysis is presented to determine the extent to which ChatGPT demonstrates deductive reasoning and how closely it aligns with human deductive models. This allows for the creation of a model with deductive reasoning and contributes to discussions on the competencies of artificial intelligence.

Cost formation of the digital information model of agricultural objects

Cost formation of the digital information model of agricultural objects

Выбор оптимального варианта проекта разработки месторождений углеводородов с учетом риска при отклонении запасов

Monitoring of a large number of hydrocarbon fields in the Russian Federation has shown a significant deviation of project development indicators from the actually achieved ones, which undoubtedly determines a high level of risk that can’t lead to rationality of the project and to serious collisions between the subsoil owner, investor and subsoil user. The multi-variability and multifactor nature of the problem to be solved determine the complexity of the methodology for selecting a variant of the oil deposit development system. The project is considered sustainable and profitable for the parties if, in case of possible changes in the main technological parameters of the project - oil, gas, condensate recovery factor [ORF, CIG, CIC] and its economic component – net discounted income [NDI] – it turns out to be financially effective, and possible adverse effects are eliminated by measures provided for by organizational, technological and economic mechanisms within the project. In the process of selecting the optimal variant of projects for the development of hydrocarbon deposits (HCS) it is necessary to take into account the incompleteness and inaccuracy of the used information about the conditions of the project implementation. The most difficult task is a priori testing of the project sensitivity under the expected deviation of geological and recoverable reserves from the reserves approved in the project. The research conducted within the framework of the first stage showed that the search for an optimal solution is possible by jointly taking into account and synthesising the results of probabilistic and statistical methods, game theory methods, including the Laplace criterion, Sevidge’s minimax risk criterion, Hurwitz’s pessimism-optimism criterion, Hodge-Lehman criterion, maximum expected utility criterion, as well as their convergence using the apparatus of L. Zadeh’s fuzzy set theory and building a strategic decision-making scenario. The basis for such a decision, are the results calculated using a geological and hydrodynamic model of the development object, including technological and economic indicators, summarised in profit or risk matrices. The choice of the optimal development variant is carried out on the basis of fuzzy logic by computational selection of the maximum value of the belonging function. On the basis of the developed methodology and software product ‘OPTIMAX’ the selection of the optimal variant of the hydrocarbon deposit development project is provided.

МЕТОДИКА СИНТЕЗА ОПТИМАЛЬНОЙ ПО ВРЕМЕНИ ТРАЕКТОРИИ ПОЛЕТА БЕСПИЛОТНОГО ВОЗДУШНОГО СУДНА

The article considers the method of synthesis of an optimal UAV flight path and an algorithm of the flight control system. The system and algorithm are designed for four-dimensional (4D) trajectory-based operations (TBO) in the context of the CNS/ATM and PBN concepts, which will increase the operational efficiency of the UAV navigation and piloting processes. The paper presents a mathematical model of the control object and algorithms for forming a time-optimal flight path. An assessment of the proposed methodology is also presented by verifying and validating the system software using simulation modeling. The results obtained demonstrate the functional capabilities of the control system to create time-optimal profiles of trajectories that meet operational requirements.

Research Anti‐Impact Mechanism of Roof Presplitting Blasting in Deep Composite Thick and Hard Key Strata

As an important means to control the hard roof, presplitting blasting is the main measure for controlling rock burst disaster in the key strata of the deep mine in the west. Taking the typical thick and hard key layer, Menkeqing Coal Mine as the analysis object, the mechanical and FLAC3D numerical models of roof presplitting blasting energy release are established. The structural characteristics and evolution laws of key layers during mining operations are analyzed, and the mechanism of rock burst behavior in thick and hard key layers is revealed. The influence of combined blasting scheme on the evolution law of roof stress field and energy field was studied. The engineering practice and the control effect of presplitting blasting on roof were carried out and evaluated. The results show that (1) in view of the characteristics of “difficult to collapse and strong energy storage” of composite thick and hard key strata in a deep stope, the targeted low‐high combined blasting measures can realize the transformation of overburden structure from “F” type to “Γ” type, effectively shorten the exposed length of key strata, reduce the in‐plane static load stress, weaken the dynamic load strength, and reduce the impact risk. (2) After adopting the low‐high combined blasting measures, the maximum vertical stress reduction on both sides and above the goaf is 70% and 90%, respectively, and the energy release is up to 106 J, which greatly reduced the stress concentration inside the coal body and weakened the energy intensity when the overlying strata structure in the goaf was broken. (3) The total energy and frequency of microseismic events during the mining period, as well as the pressure strength and pressure step of the support, were significantly reduced. The effectiveness of the combined roof presplitting blasting technology in preventing and controlling rock burst was verified by FLAC3D numerical simulation and field monitoring. The research results have been successfully applied to the Menkeqing Coal Mine.

Определительные полипредикативные конструкции в хакасском языке

In the Khakass language, modifying constructions tend to incorporate nonfinite forms as dependent predicates. The dependent modifier precedes the main part of the whole phrase. Prototypical modifying constructions are represented by models with relativization of the core units of the modifying system: subject, object, localizer, and possessor. The subject relativization models are characterized by the absence of the subject position in the dependent predicative unit (DPU). The object, localizer, or possessor relativization models feature the presence of the subject position of the DPU. The dependent predicate is represented by nonfinite forms of the present (on =chatkhan), present-future (on =han), past (on =gan), and future (on =ar). Khakass modifying constructions are formed from analytical bifinite constructions where conjunctive words connect the main and dependent parts. Such sentences, commonly found in translated, poetic, and paremic texts, are rarely used in the spoken language. In terms of semantics, the structures under study can be divided into explanatory-modifying, restrictive-modifying, and circumstantial-modifying phrases. The explanatorymodifying phrases follow three models, with the connection between the noun being modified and the modifying DPU performed by the adverbial participle of the verb tip combined with the words being modified, by the causative, and by the conjunctionless connection. In the restrictive-modifying phrases, the nature of semantic relations between the DPU and the main predicative unit (MPU) is strongly connected with the noun being defined. The circumstantial-modifying phrases are based mainly on the models of Russian compound sentences with a modifying clause, with MPU structurally occupying always a prepositive position.

Interoperability Challenges in Multivendor IEC 61850 Devices for Parallel Power Transformer Differential Protection

Interoperability of GOOSE messages is essential for the proper operation of protection schemes such as the parallel power transformer (PTRF) differential protection scheme, especially when using multivendor IEC 61850 devices. GOOSE messages allow for fast and reliable communication between intelligent electronic devices (IEDs) and are based on Ethernet communication. To ensure the interoperability of GOOSE messages between multivendor devices, adherence to the IEC 61850 standard specifications is crucial. The standard defines the format and content of GOOSE messages, including the data object model, data types, and communication protocols. Third-party testing and certification programs can also ensure compliance with the standard and help guarantee interoperability between different vendors. Device conformance with these standards does not ensure interoperability when devices from various manufacturers are utilized. Interoperability is necessary between the relevant devices from various vendors to provide system power stability and protection. If multivendor device interoperability is achieved, power utilities will be able to utilize multivendor devices in substations. The study investigates and provides comprehensive methods for achieving IEC 61850 standard-based interoperability problems in parallel with PTRF’s current differential protection schemes between IEDs (SEL-487E and MiCOM-P645) produced by different vendors under fault conditions. In a lab-scale environment with RTDS for real-time simulation in Hardware-in-the-Loop (HIL), the designed technique is simulated and tested.