Configuration Information Research Articles

The impact of visual working memory constraints on object recognition

ABSTRACT We explored the impact of visual working memory (VWM) constraints on the processing of complex objects, with a VWM task where participants (N = 75) adjusted the orientation of a bar to match a previously viewed one. Additionally, they performed a delayed match-to-sample task involving faces, houses, and pseudowords, where individual features or feature configurations were manipulated. Results showed a robust link between VWM precision for simple stimuli and memory for configural information in houses, beyond faces and pseudowords. Expert categories (faces, words) reduce VWM demands, while non-expert categories (houses) impose greater demands, especially for configural processing. Featural processing of non-expert categories places less demand on VWM. Extensive experience with an object category allows creating integrated chunks, facilitating rapid recognition and processing. Overall, configural processing of non-expert categories may place more demands on visual working memory than both featural processing of such categories and featural and configural processing of expert categories.

Feasibility Study on the Applicability of Intelligent Well Completion

The relevance of assessing the applicability of intelligent wells using autonomous inflow control devices lies in the active development of the relevant sector of the oil and gas industry and the limited understanding of the economic efficiency of intelligent wells. The use of autonomous inflow control devices allows for a change in the composition of flow to the well, thus contributing to delaying the breakthrough of undesirable formation fluids, but at the same time, such an effect affects the dynamics of formation fluid production, which undoubtedly has a huge impact on the economic effect of the project. The analysis of scientific publications on the topic of “intelligent well completion” as a downhole production monitoring and remote production control system has shown that the vast majority of researchers pay attention to the evaluation of technological efficiency, ignoring the economic aspects of the proposed solutions. This study considered the dependence of the economic effect on the geological reservoir and technological well characteristics for variant 1—intelligent horizontal well (HW) completion using autonomous inflow control devices and variant 2—conventional horizontal well completion using the open hole. Calculations of production levels and dynamics in the two variants were performed on a created sector hydrodynamic model of a horizontal well operating in the depletion mode. The analysis of the obtained results allowed us to determine the applicability criteria of the proposed configuration of formation and well characteristics at the object of study, as well as to establish general dependencies of the net discounted income of an intelligent well. As a result of this study, it was determined that the economic efficiency of intelligent well completion with the use of autonomous inflow control devices relative to conventional well completion increases with decreasing permeability and drawdown pressure on the reservoir and reaches maximum values at the object of study at the thickness of the oil-saturated part of the reservoir about 5–6 m and the location of the wellbore in it at 35–40% of the thickness of the oil-saturated part below the gas–oil contact (GOC). This article covers the research gap in evaluating the economic efficiency of intelligent HW completion using AICD relative to conventional HW completion in oil rims.

Excitation configuration analysis for divide-and-conquer excited-state calculation method using dynamical polarizability.

The authors previously developed a divide-and-conquer (DC)-based non-local excited-state calculation method for large systems using dynamical polarizability [Nakai and Yoshikawa, J. Chem. Phys. 146, 124123 (2017)]. This method evaluates the excitation energies and oscillator strengths using information on the dynamical polarizability poles. This article proposes a novel analysis of the previously developed method to obtain further configuration information on excited states, including excitation and de-excitation coefficients of each excitation configuration. Numerical applications to simple molecules, such as ethylene, hydrogen molecule, ammonia, and pyridazine, confirmed that the proposed analysis could accurately reproduce the excitation and de-excitation coefficients. The combination with the DC scheme enables both the local and non-local excited states of large systems with an excited nature to be treated.

Supporting Mixed-Presence Awareness across Wall-Sized Displays Using a Tracking Pipeline based on Depth Cameras

One of the main benefits of large interactive surfaces (e.g. wall-sized displays) lies in their support for collocated collaboration by facilitating simultaneous interactions with the displays and high awareness of other group members' actions. In the context of remote collaboration, this awareness information needs to be acquired through digital means such as video feeds, which typically offer very limited information on non-verbal communication aspects, including on workspace awareness. We describe a new approach we have implemented to tackle that challenge through a multimodal pipeline that deals with tracking, attributing, transmitting, and visualising non-verbal information through what we refer to as workspace awareness cues, across wall-sized displays placed at distant locations. Our approach relies on commodity depth cameras combined with screen configuration information to generate deictic cues such as pointing targets and gaze direction. It also leverages recent artificial intelligence breakthroughs to attribute such cues to identified individuals and augment them with additional gestural interactions. In the present paper, we expand on the details and rationale behind our approach, describe its technical implementation, validate its novelty with regards to the existing literature, and report on early but promising results from an evaluation we conducted based on a mixed-presence decision-making scenario across two distant wall-sized displays.

Identification of low-voltage phase lines using IEC 61850 and K-means clustering

Accurate phase line topology identification of LV lines facilitates the handling of line faults, which is of great significance for the safe and stable operation of distribution networks. In this paper, we model and analyze the LV lines based on graph theory, and propose a phase line relationship identification scheme based on the combination of HPLC and k-means clustering for the problem of missing or dynamically changing phase line relationships of LV lines in the station area. Aiming at the known phase-line relationship in the station area such as distribution panel, two phase-line configuration schemes, Terminal extension and new phase-line description logical node PPLD, are proposed. The area is divided by combining the configuration information of IEC 61850 SCL and the information of metering automation system. If HPLC is configured in the unknown region, HPLC is used to identify the phase line relationship. If HPLC is not configured, k-means based algorithm is used for correlation analysis between voltage measurements. Example results from a place in Shandong show that the accuracy of the method proposed in this paper is 93.96 % on average, which is higher compared to the existing methods.Significance: Accurate identification of phase-line relationships in LV lines is essential for optimising load through phase-change switches. In this study, we propose a novel phase line relationship identification scheme that combines HPLC and k-means algorithm based on the existing equipment in the station area. Leveraging the known topology within the existing equipment (LTU, switchboard, etc.) in the station area, we introduce two phase line configuration schemes, Terminal extension (extending the known phase line relationship) and the new phase line description logical node PPLD (a novel approach for configuring known phase line relationships). Additionally, we suggest a method of regional division to recognise phase line relationships in unknown regions. If HPLC is configured, it is used for phase line identification; otherwise, a k-means based algorithm analyses voltage measurements. By tailoring identification schemes to the actual characteristics of the station area, we significantly reduce the amount of data to be identified, improving accuracy and resource efficiency.

An ontology for automated fault detection & diagnostics of HVAC using BIM and machine learning concepts

This paper presents an ontology for AFDD (Automated Fault Detection and Diagnostics) of HVAC (Heating, Ventilation, and Air conditioning) systems in buildings called “AFDDOnto”. Presently, the AFDD models are mainly data-centric and often lack semantic information such as contextual information and spatial information; additionally, configuration information, analysis, and results used for model development are lost once developed. This impedes an effective mechanism for tracking changes and updating the model for future developments and use cases. The Proposed ontology can be used for AFDD model development, tracking changes, analytics, visualization, and digital twinning by enabling integration of BIM with BAS/BMS (Building Automation System/Building Management System) concepts and secondly to store AFDD configuration and analytics in the AFDDOnto. Select competency questions are constructed using SPARQL queries to access the proposed knowledge model. The proposed ontology has been tested against different measures using multiple metrics and a case study and further validated using a semi-structured survey of experts. Applied AI engineers, Facility managers, Asset managers, and building owners aiming to develop AFDD models for HVAC systems can benefit from adopting this ontology for HVAC maintenance, including analysis, model development, and knowledge management.

Bridge the gap or mind the gap? The role of leader coaching and communication technologies in configurationally dispersed teams

Configurational dispersion describes the distribution of team members across sites. Two of its dimensions include how unevenly members are distributed—i.e., configurational imbalance—and the extent to which members work in isolation from other team members—i.e., configurational isolation. We examine the combined influence of configurational dispersion, information and communication technologies (ICTs) use, and leader coaching on team performance mediated by interpersonal process asymmetry. The model is tested via a year-long field study of 88 teams and their leaders with members dispersed across China, India, and the United States. Results show that leaders should minimize their coaching when configurationally isolated teams use synchronous ICTs and when configurationally imbalanced teams use asynchronous ICTs.

Adaptive Formation Tracking Control of Multiple Vertical Takeoff and Landing UAVs With Bearing-Only Measurements.

This article studies the leader-following formation tracking control problem of multiple vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAVs) subject to uncertain parameters, in which the target formation configuration is defined by using the interneighbors' bearing vectors. An adaptive formation control algorithm with bearing-only measurements is proposed under a hierarchical control framework. More specifically, a saturated adaptive distributed control force is developed in the position loop with bearing-only measurements. Since the bearing vectors with respect to the neighbors can be directly measured by low-cost onboard cameras, the proposed formation algorithm can be implemented without interagent communication. Subsequently, in the attitude loop, an adaptive hybrid control scheme via two modified Rodrigues parameters (MRPs) sets is proposed, which achieves the command attitude tracking globally and also avoids the unwinding problem of MRPs. Based on the Lyapunov stability analysis and hybrid theory, we prove that the overall closed-loop error system is globally asymptotically stable. Finally, we provide a numerical example to demonstrate the effectiveness of the proposed control algorithm.

Wave drag and wave patterns by ships moving in a single-file formation

To minimize energy expenditure for each individual, animals adopt distinctive formations, such as fish schooling, “V” formation by flying birds, and single-file formation by waterfowls. The phenomenon of ducklings following their mothers in a single-file configuration has been revealed by the mechanisms of wave-riding and wave-passing. Drawing inspiration from this phenomenon, an investigation is undertaken on ships moving in a single-file formation. The objective is to quantify how much energy can be saved in different configurations. In this study, a three-dimensional boundary element method incorporating linear free-surface boundary conditions is used to obtain the wave drag and wave patterns. It is found that when constructive wave interference occurs in a two-ship formation, the wave resistance of the trailing ship increases and the leading ship experiences a decrease in its wave drags, especially when the two ships are in close proximity. Mutual benefit arises when destructive wave interference occurs between two ships. In addition, increasing the size of the trailing vessel facilitates the effect of wave-riding by the leading ship, but this effect becomes less pronounced as the speed increases. In a multi-ship formation configuration, changing the size of the leading ship will have a localized effect on the wave-passing, but the fleet will eventually tend to a dynamic equilibrium. When the position of the first trailing vessel is changed, there is similarly a localized effect on the wave-passing. Adjusting the first trailing ship to the position of the constructive wave interference is not favorable to reducing its own drag but enhances the wave-riding effect of its close follower. Finally, to achieve wave-passing, the trailing ship does not necessarily have to occupy an optimum position. This can still be accomplished if the trailing ship moves backward by an integer multiple of wavelength.

Perspective on electrically active defects in β-Ga2O3 from deep-level transient spectroscopy and first-principles calculations

The ultra-wide bandgap of gallium oxide provides a rich plethora of electrically active defects. Understanding and controlling such defects is of crucial importance in mature device processing. Deep-level transient spectroscopy is one of the most sensitive techniques for measuring electrically active defects in semiconductors and, hence, a key technique for progress toward gallium oxide-based components, including Schottky barrier diodes and field-effect transistors. However, deep-level transient spectroscopy does not provide chemical or configurational information about the defect signature and must, therefore, be combined with other experimental techniques or theoretical modeling to gain a deeper understanding of the defect physics. Here, we discuss the current status regarding the identification of electrically active defects in beta-phase gallium oxide, as observed by deep-level transient spectroscopy and supported by first-principles defect calculations based on the density functional theory. We also discuss the coordinated use of the experiment and theory as a powerful approach for studying electrically active defects and highlight some of the interesting but challenging issues related to the characterization and control of defects in this fascinating material.

Secure and Scalable Internet of Things Model Using Post-Quantum MACsec

For the secure deployment of network platforms tailored for IoT devices, the encryption of data transmission is equally as crucial as the process of authentication. In this context, we introduce the Secure and Scalable IoT network (SSI) network platform, designed to accommodate a diverse range of IoT devices. It provides scalability and implements effective many-to-many and end-to-end encryption across extensive regions. With the emergence of quantum computing, secure public key exchange mechanisms have become important. Among the various post-quantum cryptography (PQC) algorithms assessed, Nth Degree Truncated Polynomial Ring Units (NTRUs) have emerged as an optimally suited PQC algorithm for IoT devices constrained by limited computational capabilities. We have integrated NTRUs with SSI as a lightweight PQC solution. Moreover, SSI-PQM (Post-Quantum MACsec) enhances the SSI’s initial authentication structure to minimize PQC-TLS session attempts and protect the SSI’s important configuration information. When applying TLS with PQC for secret key exchange purposes, it was verified that this approach ensures stable performance in IoT environments. Upon the implementation of our proposed SSI-PQM on Raspberry Pi 3B+ based IoT devices, SSI-PQM exhibited acceptable performance at security levels from 80 to 128 and achieved a minimum speed improvement of 161% over RSA at security levels above 160. It can be concluded that SSI-PQM stands out as an effective Zero Trust-based IoT network platform, demonstrating its viability and efficiency in safeguarding data transmission against potential quantum computing threats.

Orbital Stability Study of the Taiji Space Gravitational Wave Detector

Space-based gravitational wave detection is extremely sensitive to disturbances. The Keplerian configuration cannot accurately reflect the variations in spacecraft configuration. Planetary gravitational disturbances are one of the main sources. Numerical simulation is an effective method to investigate the impact of perturbation on spacecraft orbits. This study shows that, in the context of the Taiji project, Earth’s gravity is an essential factor in the change in heliocentric formation configuration, contributing to the relative acceleration between spacecrafts in the order of O(10−6)m·s−2. Considering 00:00:00 on 27 October 2032 as the initial orbiting moment, under the influence of Earth’s gravitational perturbation, the maximum relative change in armlengths and variation rates of armlengths for Taiji is 1.6×105km, 32m·s−1, respectively, compared with the unperturbed Keplerian orbit. Additionally, by considering the gravitational perturbations of Venus and Jupiter, the armlength and relative velocity for Taiji are reduced by 16.01% and 17.45%, respectively, compared with when only considering that of Earth. The maximum amplitude of the formation motion indicator changes with the orbit entry time. Results show that the relative velocity increase between the spacecrafts is minimal when the initial orbital moment occurs in July. Moreover, the numerical simulation results are inconsistent when using different ephemerides. The differences between ephemerides DE440 and DE430 are smaller than those between DE440 and DE421.

A hierarchical LFFC control scheme for underactuated unmanned surface vessels based on unreliable communication interaction

This article investigates the leader-follower formation-containment (LFFC) control issue of underactuated unmanned surface vessels (USVs) system subject to unreliable communication interaction and the external disturbances. Firstly, an adaptive control scheme is established for the leaders to track the desired trajectory associated with preset formation configuration. Subsequently, by means of convex hull theory, a formation-containment control algorithm is developed to guide the followers into the specific area generated by the leaders. Nevertheless, the communication interaction among USVs is frequently unreliable, which is constrained by communication distance, equipment quality, and indeterminate cyber-attack. Worse still, this unreliability will magnify the unpredictable impact on system stability. Moreover, the signals generally undergo multilevel transmission from virtual leader to followers under LFFC structure, which will result in the amplification of unreliable ratio during the information transmissions. To address the aforementioned issues, an online-update auxiliary signal is constructed through the quasi-sliding mode manifold, which can suppress the impact of unreliable communication interaction. Theoretical analysis and numerical simulations are demonstrated to verify the feasibility and validity of the proposed control strategies.

Distributed Optimal Solutions for Multiagent Pursuit-Evasion Games for Capture and Formation Control

In this paper, distributed optimal solutions are designed for networked multiagent pursuit-evasion (MPE) games for capture and formation control. In the games, the pursuers aim to minimize the distance from their target evaders while the evaders attempt to maximize it, and at the same time, all players desire to maintain cohesion with their teammates. The goals of agents are obviously reflected in the obtained optimal control strategies which consist of an attracting term and/or a repelling term. Nash equilibrium is obtained by means of optimal strategies using the solutions of the HJI equations. Furthermore, three scenarios are considered in the MPE game: one-pursuer-one-evader, multiple-pursuer-one-evader, and multiple-pursuer-multiple-evader, where sufficient conditions are given for pursuers in achieving exponential capture or formation control with ultimate zero or bounded errors. It is shown that the conditions depend on the structure of the communication graph, the parameters in the controllers, and the expected formation configurations. Finally, both simulations and real flight experiments successfully demonstrate the effectiveness of the proposed strategies.

Distributed event-triggered formation control of UGV-UAV heterogeneous multi-agent systems for ground-air cooperation

Within the context of ground-air cooperation, the distributed formation trajectory tracking control problems for the Heterogeneous Multi-Agent Systems (HMASs) is studied. First, considering external disturbances and model uncertainties, a graph theory-based formation control protocol is designed for the HMASs consisting of Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs). Subsequently, a formation trajectory tracking control strategy employing adaptive Fractional-Order Sliding Mode Control (FOSMC) method is developed, and a Feedback Multilayer Fuzzy Neural Network (FMFNN) is introduced to estimate the lumped uncertainties. This approach empowers HMASs to adaptively follow the expected trajectory and adopt the designated formation configuration, even in the presence of various uncertainties. Additionally, an event-triggered mechanism is incorporated into the controller to reduce the update frequency of the controller and minimize the communication exchange among the agents, and the absence of Zeno behavior is rigorously demonstrated by an integral inequality analysis. Finally, to confirm the effectiveness of the proposed formation control protocol, some numerical simulations are presented.

Multi-Table Programmable Parser with online flow-level update consistency for satellite networks

Programmable packet parsers in the space data plane, responsible for identifying protocols and extracting keywords on demand, are significant to realize protocol upgrading for satellite networks. Because flow-level update consistency is significant, onboard resources are limited, and space radiation may cause errors in packet parsers, programmable packet parsers with online flow-level update consistency, low complexity, and high reliability are urgently needed. In our previous work, a Multi-Table Programmable Parser (MTPP) [1] is designed for fast configuration and low storage cost by networking configuration and multiple tables. In this paper, we propose a Multi-Table Programmable Parser with Online Flow-Level Update Consistency (MTPP-OFLUC), consisting of five tables and eight models. To guarantee the flow-level update consistency, each table consists of a main table and a backup table. Moreover, to improve the reliability of MTPP-OFLUC, a fault tolerance mechanism is designed. Furthermore, an Online Configuration based on Super Parse Graph Segmentation (OC-SPGS) is proposed to achieve fast configuration with flow-level update consistency. The numerical analysis under typical parse graphs demonstrates that MTPP-OFLUC uses less storage than that of PISA-based parser. Due to backup tables adapted to guarantee the flow-level update consistency, the storage cost of MTPP-OFLUC is only 11.53% more than that of MTPP. Through OC-SPGS, the parsing success ratio of MTPP-OFLUC is up to 66.7% larger than that of MTPP. Finally, a prototype of MTPP-OFLUC is implemented on Xilinx Virtex-7 FPGA. The response time of MTPP-OFLUC and the network is 1.460 us and 4.196 ms, respectively. The size of configuration information is less than that of PISA-based parser. In summary, rapid response and flow-level update consistency are realized by MTPP-OFLUC. Moreover, security risks, user-friendly interfaces, potential capacity of upgrades, and supports for higher data rates still need to be considered in the future works.

Indoor view graph: A model to capture route and configurational information

This paper presents a graph model that simultaneously stores route and configurational information about indoor spaces. Existing indoor information models either capture route information to compute shortest paths and to generate route descriptions (i.e., answering how-to-get-to questions), or they store configurational information about objects and places and their spatial relationships to enable spatial querying and inference (i.e., answering where-questions). Consequently, multiple representations of an indoor environment must be stored in information systems to address the various information needs of their users. In this paper, we propose a graph that can capture both configurational and route information in a unified manner. The graph is the dual representation of connected lines of sight, or views. Views can represent continuous movement in an indoor environment, and at the same time, the visible configurational information of each view can be explicitly captured. In this paper, we discuss the conceptual design of the model and an automatic approach to derive the view graph from floorplans. Finally, we demonstrate the capabilities of our model in performing different tasks such as calculating shortest paths, generating route descriptions, and deriving place graphs.

Fuel-optimal satellite formation reconfiguration method with best passive safety parameters

This paper investigates the problem of satellite formation reconfiguration from the best passive safety parameters while ensuring the minimum fuel cost and desired formation configuration. Based on the relative eccentricity and inclination vectors, a hybrid method is proposed that combines the analytical solution and the genetic algorithm optimization method. It transforms the fuel-optimal conditions into the constraints of optimization model, which theoretically ensures the optimal fuel cost. The proposed hybrid approach is applicable to satellite formation reconfiguration problems with variable relative eccentricity and inclination vectors and passive safety concerns. Compared with the optimal three-impulse strategy and the analytical method in two different reconfiguration scenarios, the proposed method is proven to be more general and has advantages in passive safety performance.

Fixed-Time Coordinated Attitude Control for spacecraft formation flying via event-triggered and delayed communication

This article tackles the challenge of achieving fixed-time coordinated attitude control for spacecraft formation flying when dealing with event-triggered and delayed communication. First and foremost, we introduce a fixed-time observer that leverages event-triggered, time-delayed information to enable follower spacecraft to access the leader’s commands within a directed, switching topology. In particular, the observer possesses the ability to effectively mitigate the impact of communication delays on information propagation. Following this, a fixed-time controller that empowers each follower to precisely follow the leader’s trajectory while maintaining the formation configuration is devised. Ultimately, we validate the feasibility and superiority of the proposed algorithm through numerical simulations and practical spacecraft ground experiments conducted with planar air-floating robots.

Decoding the complexity of the Brazilian pork supply chain

Purpose This research examines the impact of governance structures within the Brazilian pork supply chain on the necessary controls for exportation. Specifically, the goal is to unravel the intricacies of this supply chain and decode its complexity.Design/methodology/approach Using transaction cost economics as a theoretical lens, we surveyed the main bodies responsible for the export and quality assurance sectors of Brazilian organizations that trade and export pork. Our sample comprises 53.5% of the country’s pork exporting companies during the period analyzed.Findings The presence of vertical and horizontal governance structures in the pork export chain stands out. While the vertical structure enables greater control due to command relations, there are trust and cooperation relations in the horizontal structure. This makes it possible to establish mechanisms to control health, quality, safety and traceability in both structures. We also identified each company’s characteristics: formation configuration (if the cooperative, publicly traded company, or other modality), capital stock, location, the average daily slaughter of pigs for export and sows per producer. We conclude that the organizations have concerns related to the food safety programs, as there are programs that seek transparency throughout the process in many supply chain stages.Research limitations/implications Studies that relate the level of orientation to the export market with the occurrence or risk of corrupt and opportunistic behavior and the coordination mechanisms adopted may represent an interesting and important opportunity for studies.Originality/value This study helps to understand the complexity of the Brazilian pork supply chain.