Operator Actions Research Articles

Duality of averaging of quantum states over arbitrary symmetry groups revealing Schur–Weyl duality

It is a well-established fact in quantum information theory, that uniform averaging over the collective action of a unitary group on a multipartite quantum state projects the state to a form equivalent to a permutation operator of the subsystems. Hence states equivalent to permutation operators are untouched by collective unitary noise. A trivial observation shows that uniform averaging over permutation operators projects the state into a form with block-diagonal structure equivalent to the one of the collective action of the unitary group. We introduce a name for this property: duality of averaging. The mathematical reason behind this duality is the fact that the collective action of the unitary group on the tensor product state space of a multipartite quantum system and the action of the permutation operations are mutual commutants when treated as matrix algebras. Such pairs of matrix algebras are known as dual reductive pairs. In this work we show, that in the case of finite dimensional quantum systems such duality of averaging holds for any pairs of symmetry groups being dual reductive pairs, regardless of whether they are compact or not, as long as the averaging operation is defined via iterated integral over the Cartan decomposition of the group action. Although our result is very general, we focus much attention on the concrete example of a dual reductive pair consisting of collective action of special linear matrices and permutation operations, which physically corresponds to averaging multipartite quantum states over non-unitary SLOCC-type (Stochastic Local Operations and Classical Communication) operations. In this context we show, that noiseless subsystems known from collective unitary averaging persist in the case of SLOCC averaging in a conditional way: upon postselection to specific invariant subspaces.

Machine-learning-assisted prediction and optimized kinetic modelling of residual chlorine decay for enhanced water quality management

The quality of water changes from source to tap, presenting challenges in maintaining consistent water quality across the system. Predicting water quality in distribution systems, including disinfectant residual loss and by-product formation, has been the subject of research since the early 1990s. Although numerous models have been proposed to predict residual chlorine decay, disputes exist among researchers and experts over the superiority of certain models. Accordingly, this study modified the existing process-based bulk decay models by replacing the initial Total Residual Chlorine (TRC) concentration parameter with TRC demand, leading to an improvement in the models' performance. The modification resulted in a 38.03%, 28.02%, 23.11%, and 33.29% average improvement in Mean Squared Error (MSE) values for the First Order Model (FOM), Parallel First Order Model (PFOM), Second Order Model (SOM), and Parallel Second Order Model (PSOM), respectively. The study also introduced an online predictive method based on a Machine Learning (ML) algorithm that predicts the first-order TRC bulk decay rate by using water quality parameters as inputs. A Gaussian Process Regression (GPR) model was used to predict the kinetic parameters in FOM, which accurately predicted the test sets for most of the cases. In addition, a new methodology was proposed in this study for predicting TRC in water distribution systems that incorporates the variability of source natural organic matter, operational actions, and water demands. This method seeks to develop high-fidelity and robust water quality predictions that provide operational decision support for optimized distribution system management. In conclusion, this study emphasizes the importance of understanding water quality changes from source to tap and the challenges of maintaining consistent water quality across the system. The study suggests modifying existing models and introducing a novel methodology for predicting residual chlorine in water distribution systems that can improve water quality management and, ultimately, better public health outcomes.

The Quality of Life Supports Model as a major component in applying the quality of life paradigm

AbstractSocial change is built on paradigms and models. A paradigm needs an operational action model to successfully implement the paradigm, and an operational model needs a paradigm to give it credibility and content. This article describes the Quality of Life Supports Model (QOLSM) as a major pathway for applying the quality of life (QOL) paradigm. The QOLSM integrates the concepts of QOL and individualized supports. The article describes and illustrates: (a) the four elements of the QOLSM (core values, individual and family QOL domains, systems of supports, and facilitating conditions); and (b) the use of the QOLSM in the field of intellectual and developmental disabilities (IDDs) as a framework for supports provision. The article also discusses how the QOLSM represents a value‐based and actionable model that should be effective for solving problems regarding services and supports to people with IDD, developing new knowledge, making meaningful change, being evaluated, and contributing both theoretically and operationally to the field.

Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs

Monitoring water quality in reservoirs is essential for the maintenance of aquatic ecosystems and socioeconomic services. In this scenario, the observation of abrupt elevations of physicochemical parameters, such as turbidity and other indicators, can signal anomalies associated with the occurrence of critical events, requiring operational actions and planning to mitigate negative environmental impacts on water resources. This work aims to integrate Machine Learning methods specialized in anomaly detection with data obtained from remote sensing images to identify with high turbidity events in the surface water of the Três Marias Hydroelectric Reservoir. Four distinct threshold-based scenarios were evaluated, in which the overall performance, based on F1-score, showed decreasing trends as the thresholds became more restrictive. In general, the anomaly identification maps generated through the models ratified the applicability of the methods in the diagnosis of surface water in reservoirs in distinct hydrological contexts (dry and wet), effectively identifying locations with anomalous turbidity values.

Correlation between Age, Type of Fracture and Location of Long Bone Fracture on Length of Hospitalization of Post Op Patients

Fracture is a problem with a fairly high incidence, one of the treatments is operative action. This study aims to determine the relationship between age, type of fracture, and location of long bone fractures on the length of postoperative hospitalization at Makassar City Government Hospital. This research is a type of observational analytic research using a cross sectional technique. The sampling technique used was purposive sampling with a total of 50 respondents recorded in the medical records of the Makassar City Government Hospital. The results of this study found that respondents in the category of elderly and non-elderly had no relationship to the length of stay in the Post-Operative (p = 0.361). As for the type of fracture experienced by the respondent, it had a relationship to the length of postoperative hospitalization (p = 0.004). The location of the fracture experienced by the respondent also had a relationship to the length of postoperative hospitalization (p = 0.030).

Quantum error correction in the black hole interior

We study the quantum error correction properties of the black hole interior in a toy model for an evaporating black hole: Jackiw-Teitelboim gravity entangled with a non-gravitational bath. After the Page time, the black hole interior degrees of freedom in this system are encoded in the bath Hilbert space. We use the gravitational path integral to show that the interior density matrix is correctable against the action of quantum operations on the bath which (i) do not have prior access to details of the black hole microstates, and (ii) do not have a large, negative coherent information with respect to the maximally mixed state on the bath, with the lower bound controlled by the black hole entropy and code subspace dimension. Thus, the encoding of the black hole interior in the radiation is robust against generic, low-rank quantum operations. For erasure errors, gravity comes within an O(1) distance of saturating the Singleton bound on the tolerance of error correcting codes. For typical errors in the bath to corrupt the interior, they must have a rank that is a large multiple of the bath Hilbert space dimension, with the precise coefficient set by the black hole entropy and code subspace dimension.

Smart Agricultural–Industrial Crop-Monitoring System Using Unmanned Aerial Vehicle–Internet of Things Classification Techniques

Unmanned aerial vehicles (UAVs) coupled with machine learning approaches have attracted considerable interest from academicians and industrialists. UAVs provide the advantage of operating and monitoring actions performed in a remote area, making them useful in various applications, particularly the area of smart farming. Even though the expense of controlling UAVs is a key factor in smart farming, this motivates farmers to employ UAVs while farming. This paper proposes a novel crop-monitoring system using a machine learning-based classification with UAVs. This research aims to monitor a crop in a remote area with below-average cultivation and the climatic conditions of the region. First, data are pre-processed via resizing, noise removal, and data cleaning and are then segmented for image enhancement, edge normalization, and smoothing. The segmented image was pre-trained using convolutional neural networks (CNN) to extract features. Through this process, crop abnormalities were detected. When an abnormality in the input data is detected, then these data are classified to predict the crop abnormality stage. Herein, the fast recurrent neural network-based classification technique was used to classify abnormalities in crops. The experiment was conducted by providing the present weather conditions as the input values; namely, the sensor values of temperature, humidity, rain, and moisture. To obtain results, around 32 truth frames were taken into account. Various parameters—namely, accuracy, precision, and specificity—were employed to determine the accuracy of the proposed approach. Aerial images for monitoring climatic conditions were considered for the input data. The data were collected and classified to detect crop abnormalities based on climatic conditions and pre-historic data based on the cultivation of the field. This monitoring system will differentiate between weeds and crops.

A Simple Analytical Model to Predict the Freeze Plug Opening Time in Molten Salt Reactors

Abstract The Freeze plug is an important passive safety system used in molten salt reactor (MSR). It enables automatic drainage of the liquid fuel from the core to the storage tanks in an emergency to stop the nuclear fission chain reaction without any operator's action or electric power supply. The opening time, that is the time taken for the freeze plug to open, is therefore of considerable importance to ensure passive safety of MSR. In our previous studies, systematic numerical simulations were carried out to understand how the fundamental design parameters such as the tube diameter and wall thickness of the freeze plug affected the opening time. In this work, a simple analytical model was developed for rough estimation of the opening time. It was shown that the opening time calculated by the present simple model was in fairly good agreement with that by the full simulation using the mass, momentum, and energy conservation equations for the salt and the heat conduction equation within the wall material. The present simple model was hence shown to be useful particularly for the schematic design of the improved MSR freeze plugs.

Exploring servitization and digital transformation of manufacturing enterprises: evidence from an industrial internet platform in China

Servitization is vital to manufacturing enterprises’ competitive advantages and financial performance in contemporary digitalisation environments. Enterprises are increasingly relying on industrial Internet platforms to satisfy potential customers’ needs as well as to create superior value, but the literature has neglected to explain how enterprises can leverage such digital platform to improve the efficiency and effectiveness of servitization. This study aims at describing how the industrial Internet platform can enable servitization of manufacturers. Based upon the meta-theoretical foundations of service-dominant logic, we identify the ‘sense and respond’ servitization strategy enabled by the industrial Internet platform. By performing a questionnaire survey, we find that the industrial Internet platform approach based on the connectivity and compatibility architecture can enable manufacturers to improve the efficiency of resource integration and resource reconfiguration, which facilitates the implementation of servitization via market perception . We argue that the industrial Internet platform affects an organisation’s ability to sense the market and resource management actions; these operational resource actions are a significant antecedent of the servitization strategy.

A framework for designing visitor experiences in branded tourist attractions: Insights from a luxury Cognac brand

Setting up a tourist attraction provides brands with the opportunity to offer visitors an experience that promotes their brand image. This paper explores how to design such an experience by focusing on the tourist attraction of a famous luxury brand, Hennessy Cognac. Through an in-depth case study, the paper contributes to the tourism literature by developing a framework for experience design in branded tourist attractions. This framework bridges the gap between abstract design principles and corresponding operational actions in practice to support the realization of visitor experiences that improve brand perceptions. Moreover, it suggests a requirement for congruency between the characteristics of the brand and the design of the visitor experience.

Problems of interaction in the investigation of corruption crimes in the field of official activity and professional activity related to the provision of public services

Modern realities and the state of the criminogenic situation in the country require fundamentally new approaches to the interaction of law enforcement agencies. Today, the interaction of the investigator with other bodies and units is more and more actively carried out at all possible levels, departmental, interdepartmental, international. Interaction in the detection and investigation of criminal offences is a rather complex and comprehensive form that involves a number of interrelated procedural and operational search actions and measures aimed at maximising the achievement of the goals of the criminal process. Cooperation in the investigation of crimes, in particular in the field of official activity, is one of the methods of combating crime, which consists in the coordination and combination in order and on the basis of the law, the efforts of several persons, divisions, bodies, etc. in order to ensure the optimization of the pre-trial investigation of criminal offenses. The specified activity is objectively necessary and often begins from the moment of checking the received information about the commission of a crime. This activity by its nature is very complex, which finds its expression in its phasing. Among the latter, we suggest making a decision about the necessity and expediency of interaction, choosing the form and methods of interaction, procedural consolidation of the decision, direct interaction, and registration of the results of the indicated cooperation. However, the structural clarity of the interaction does not relieve it of the difficulties faced by its participants. This situation is mainly due to the lack of clear regulation of issues related to the organisation and implementation of cooperation in the Criminal Procedure Code of Ukraine. In connection with this, it would be expedient to supplement the specified legal act with a separate section, which would define the concepts, principles, types, forms, methods and procedure of interaction during criminal proceedings.
 Having analysed the legal acts, the author concludes that there is no clear regulation of such interaction.

Инструментально-операциональная стратегия реализации когнитивно-прагматической программы: общие положения (статья 1)

The present article proposes a comprehension of the original author's concept of cognitive-pragmatic programs (CPP) in the context of the theory of intentionality. Intentionality is realized as a plan that forms an intention and utilizes the form of a signal. A special role here is played by the system of instrumental attitudes of the CPP, which make up the cognitive-mental strategy of one’s actions and interactions on the basis of the target and self-identification CPS subsystems (cognitive-pragmatic sets). An instrumental-operational strategy is a cognitive project (action plan) of the source subject aimed at the successful implementation of one / several strategic goals of the CPP. The dynamic instrumental-operational model of the intentional P-D(S) functioning can be represented as a formula: instrumental-operational strategy of the intentional P-D(S) (“how”) = tool - method - operation (action). The instrumental-operational strategy acquires the properties of the intentional-discursive space in which it is actualized. This is the reason for the internal (cognitive-mental) harmonization and integrity of the discourse signal. Each of the components of the instrumental-operational strategy P-D(S) (tool, method, operation (action)) can be considered both as part of the general dynamic signal of the actual discourse / CPP, and as an independent signal. There are two options for describing the functional activity of software Р-D(S): instrumental signal P-D(S) (“how”) = the first component of the general signal (instrument) + the second component of the general signal (the way the instrument is implemented) + the third component of the general signal (operation / action); instrumental signal Р-D(S) (“as”) = signal 1 (instrument) + signal 2 (method of representation / mechanism for implementing the instrument) + signal 3 (operation / action). This model has two main forms of actualization — “direct” and “reverse”. The “direct” form is relevant for the source subject, the generator of CPP / P-D(S). The source subject begins the operation of functionalizing the program discourse signal by searching for an instrument, and ends this process by performing an action. The subject-interpreter, when interacting with the discourse, performs the reverse operation.

Passive User Authentication Utilizing Two-Dimensional Features for IIoT Systems

Passive user authentication is critical for the secure operation of Industrial Internet of Things (IIoT) systems. By jointly utilizing both the time-varying characteristics of the user sequential operation actions and spatial variation characteristics of channel state information (CSI) caused by these actions, this paper proposes a novel two-dimensional passive authentication framework for IIoT systems. In particular, we construct the time-varying operation action sequences from the routine work process of a user and apply the Hidden Markov Model to characterize behavioral biometric characteristics of the user, and also employ the eXtreme Gradient Boosting model to depict the spatial variation characteristics of CSI related to the user. By designing two classifiers corresponding these two characteristics and assigning each classifier an appropriate weight, we propose a two-dimensional user authentication framework for continuous and non-intrusive user authentication in IIoT scenarios. Extensive experiments are conducted to illustrate the authentication performance of the proposed authentication framework in terms of false acceptance rate, false rejection rate and equal-error rate. We further investigate the related authentication efficiency issues like the sensitivity to the weights for classifiers, the sensitivity to authentication time and the capability of resisting against impersonation attacks.

Отбранителните способности на механизираните и танковите форми- рования – предизвикателства и значимост

Defense policy objectives are achieved by building and continuously developing appropriate defense capabilities to counter contemporary challenges, risks and threats and achieving defense capabilities to effectively participate in the full range of NATO and EU-led operations. To ensure that the development of defense capabilities is directed to the operational needs identified by the armed forces and is consistent with the missions of the Armed Forces, it is necessary to determine the importance of each of the imperatives/capability elements, as well as the extent to which the proposed directions for their improvement. For the purposes of research on the topic: „Directions for improving the capabilities of mechanized and tank formations in planning and conducting tactical actions in a defensive operation” the method of expert evaluation was applied and the results of the study are presented.

Urban sustainability assessment at the neighborhood scale: Integrating spatial modellings and multi-criteria decision making approaches

Urban sustainability is a highly complex concept that requires integrative assessment frameworks to determine the measures that should be adopted to achieve a sustainable city. The present study aimed to conduct a spatially-based sustainability assessment at the neighborhood scale in Isfahan Metropolitan, a rapidly urbanizing region in the center of Iran, using an integrated framework of spatial modeling and multi-criteria decision-making analysis (MCDA). As a first step, the spatial distribution of a set of indicators was provided in three distinct categories, ecosystem service, environmental hazard, and urban structure using various spatial modeling approaches. After standardizing the indicators and assigning appropriate weights to them, different multi-criteria decision analysis models were used to aggregate the indicator layers. The sustainability layers based on ecosystem services, environmental hazards, and urban structure were integrated using MCDA models. The results indicated that less than 3% of the total neighborhood area were categorized as almost sustainable, while 36.1% and 59.4% were respectively scored as poor and moderate sustainable area. None of the neighborhoods was categorized in the sustainably good class, whereas 1.73% of the area was unsustainable. Moreover, the urban structure-based aspect was found to be the most sustainable, while the urban environmental hazards dimension exhibited the lowest sustainability, with 71.98% falling into the poor and unsustainable category. The spatial investigation showed that the central parts of the city were more sustainable than the urban periphery. In conclusion, a spatially-based sustainable assessment of Isfahan City at the neighborhood level can provide urban planners with valuable insights to undertake operational actions and achieve sustainable development goals.

Cyber hardening of Nuclear Power Plants with real-time nuclear reactor operation, 1. Preliminary operational testing

Maintaining and extending the lifetime of the domestic Nuclear Power Plant fleet is predicated on digitalization. However, digitalization also gives rise to increasing vulnerabilities. This paper is the first in a body of novel research at the Idaho Falls Center for Higher Education focusing on the cyber hardening of currently operating and aging Nuclear Power Plants that uses the Western Services Corporation Generic Pressurized Water Reactor real-time operational platform. The Western Services Corporation platform was used here natively to collect data during atypical plant events that could be initiated by cyberattacks. The goals of this first phase of work is to identify data ‘fingerprints’ unique to each of the initiating events, determine when or if the reactor trips, and suggest operator actions that could mitigate the cyberattack and possibly avoid a trip and maintain operations. First, a cyber-informed Preliminary Hazards Analysis was conducted to determine plant systems most vulnerable to a cyberattack. Then, the associated malfunction as an analogue to a potential cyberattack on the selected system was executed during operation of the reactor. Relevant data was collected during these events until the reactor tripped. The data was then processed to determine if a fingerprint could be crafted, and mitigating operator actions were formulated. Finally, we demonstrate a proof-of-concept for simulating cyberattacks on the Western Services Corporation platform in real-time during reactor operation. This development will open possibilities for ‘Red Team/Blue Team’ exercises for cyber hardening of the domestic Nuclear Power Plant fleet.

Causes of proof construction failure in proof by contradiction

Failure to deduce false suppositions in proof by contradiction is still considered “more difficult” than proving the conditional to in proof by contraposition. This study aims to identify the types of proof construction failures based on the action steps of proof by contradiction, then offer a framework of construction failure hypothesis specifically used in proof by contradiction. The research data were collected and analyzed from the work of students who have agreed to be research participants, a total of 83 students. The results of the analysis of student work successfully identified four types of failures, namely formulating suppositions, constructing and manipulating suppositions, identifying contradictions, and disproving suppositions. These four types of failures then became the material for the development of the hypothesis framework of a failure to construct proof by contradiction, which consists of 17 hypothesis nodes divided into three main hypotheses, namely: operational (action), affective (emotional), and foundational (logical reasoning). The failure hypothesis framework justifies that the sources of the failure of proof construction in proof by contradiction are understanding of the act of producing a proof by contradiction, emotionality towards the coherence of the construction steps, disproving suppositions, beliefs, use of appropriate definitions-theorems and axioms, and cognitive tension in proof by contradiction; and formal logic of the act of producing a proof by contradiction, as well as differences in the underlying logic with other acts.

Statistical Evaluation of the Impacts Detection Methodology (IDM) to Detect Critical Damage Occurrences during Quay Cranes Handling Operations

During various marine container handling operations, performed mainly in larger-scale container terminals, containers get damaged regularly. Our previous studies showed that each physical impact results in some form of physical deformation of the backbone structure. Even at low accelerations, the spreaders of the quay cranes impact the containers with enough force to substantially bend the metal parts of the corners of the containers, when additional hooking procedures are required. This means that the first time resulted in the metal rods hitting the metal frame with an average 15-ton mass at the average speed of 1.7 m/s. The metal rods of the hooking mechanisms’ impact areas of the containers are structurally important, and each impact surely damages the containers, diminishing their total operational time. We have already proposed the Impacts Detection Methodology (IDM) and its application system, tested in Klaipeda City port, and it proved to be efficient in real-time operations, detecting concurrent impacts with each new handling cycle. In this paper, we provide a summarisation of a larger number of detections using the IDM, and as a result of this analysis, we have detected that more impact events happen when containers are taken from the upper parts of the ship, in comparison to the ones taken from the shafts. Results suggest that more critical events occur due to operator actions and experiences working with the machinery, yet the same operators tend to make fewer impact mistakes taking the containers from the shafts as the vertical cell guides tend to direct the movements and lower the levels of the natural sway of the spreader inside closed environments. This surely damages the metal infrastructure of the shafts, as seen in our previous study, but minimizes the chances of secondary impacts occurring during hooking.

The role of human factors in aviation ground operation-related accidents/incidents: A human error analysis approach

Aviation is a complex socio-technical system with interconnected and interdependent subsystems, such as flight operations, air traffic control, aircraft maintenance and ground operations. However, safety and risk research has not paid, thus far, adequate attention to all subsystems, resulting in possibly undetected or underestimated risks. This study focuses on Ground Operations (GO) as a subsystem and analyses the role of human factors in ground operations related accidents and incidents. 87 accident and incident reports (from 2000 to 2020) were analysed in three stages, using the Human Factors Dirty Dozen (HF DD) Model and the Human Factors Analysis and Classification Scheme (HFACS) as a basis for the third stage, a systematic thematic analysis. The findings indicate that lack of situational awareness and failure to follow prescribed procedures are the main causal and contributing factors in GO-related accidents and incidents. Three operational actions were identified as most critical: aircraft pushback/towing, aircraft arrival and departure, and aircraft weight and balance. An agenda for future research and recommendations for industry corrective action are proposed.

Application of supervisor synthesis methods in designing a discrete-event group control system for mobile robots

This paper discusses the features of methods used to synthesize a discrete-event supervisor for a group control system of mobile robots. We consider the upper levels of a group control system as a discrete-event system. Su-pervisor synthesis methods for such a system and the evaluation of their computational complexity are presented. The paper highlights the limitations of the best method in terms of computational complexity and proposes a modi-fication that allows to remove these limitations without increasing the computational complexity. The application of the modified method is demonstrated on the example of synthesizing a supervisor for the group action of a fire-fighting operation by three robots.