Operational Tasks Research Articles

Article: Reflections on the New Rules of Origin of Mercosur*

This article analyses to what extent the new Mercosur’s Rules of Origin contribute to facilitating trade from the perspective of commercial operators. It reflects on whether this compilation and updates help simplify the tasks of commercial operators. For this purpose, specific characteristics of some chapters of the New Rules of Origin (NRO) will be addressed, briefly detailing their structure and analysing the wording and impact of certain articles considered crucial for an operator to declare a product as originating

Dynamic Analysis of Metamorphic Mechanisms with Impact Effects During Configuration Transformation

Metamorphic mechanisms have attracted considerable attention owing to their capability to switch their topology to adapt to different operational tasks. One feature of topological change is the re-contact of different bodies, which inevitably causes collisions affecting operation accuracy and service life. Consequently, in this study, a collision incidence matrix was introduced to describe the topology of a system involved in collisions, and a method for reducing the closed-loop system to an open-loop system was proposed. The complex movement of the metamorphic mechanism in a changing topology was classified into two different running stages of the source metamorphic mechanism. Based on the relative coordinate method, dynamic modeling of the source metamorphic mechanism considering the impact effects was conducted. Combining the classical collision theory and Newton–Euler equation, the generated impact impulse and the motion after collision were determined. Subsequently, a dynamic analytical method for the full configuration of metamorphic mechanisms was proposed to reflect the changes in the topological structure in the dynamic model. Finally, two typical metamorphic mechanisms used in packaging and spinning were considered as examples to verify the correctness and effectiveness of the proposed method, and their impact characteristics during configuration transformation were analyzed. The proposed analytical method of internal impact for a variable topology process provides effective theoretical guidance for the stability analysis of configuration transformation and structural design aimed at minimizing impacts.

Features of the use of throws in the section demonstration of applied technology hand-to-hand combat

Actuality. A characteristic feature of hand-to-hand combat is the technique demonstration section. Applied hand-to-hand combat fully corresponds to the specifics of solving operational tasks without and with the use of weapons by representatives of various military and law enforcement agencies. It is known that in certain types of martial arts, throwing is a means of achieving an advantage over an opponent, so these technical elements are often used to solve competitive or operational-service tasks. Athletes from hand-to-hand combat during competitive activities, as well as law enforcement officers during the performance of operative tasks quite often use throwing equipment. But, despite the similarity of technical performance, the use of throwing technique in the application section of hand-to-hand combat has its own characteristics. It is clear that the characteristics of hand- to-hand combat require new approaches to the construction of the training process of the combat direction, which differ from the classical types of martial arts. Research results. Competitive activity from the applied section of hand-to-hand combat fully corresponds to the specifics of solving operational-service tasks without and with the use of weapons by representatives of various power structures. Throwing technique is one of the main tools for solving a competitive task. The use of the throwing technique depends on the type of attack and has its own characteristics and patterns for effective execution. The most versatile throwing action is the rear leg throw. In certain types of threats: with a knife or a gun - the use of throwing techniques is impractical. Catching and reaching create conditions for the use of a large number of options for various throws, most of which are performed with the help of the body. Conclusions. It has been established that in hand-to-hand combat, throws are an important component of the technical arsenal for solving competitive tasks, both in the duel section and in the technique demonstration section, but the features of hand-to-hand combat do not create an opportunity to immediately throw the opponent, it is necessary to carry out preliminary offensive or defensive actions with a simultaneous reduction of the distance and by capturing or covering individual parts of the opponent's body or clothing. The main feature of the performance is maintaining balance in the rack position for further technical actions. The use of throws from certain classification groups depends on the type of attack. Threats in the form of captures and captures have the greatest variability for the use of throws, and a universal and effective means of using counterattacking actions (throws) from various types of attack from a practical point of view is the back step. In case of a threat with a knife or a gun, taking into account the specifics of this type of attack, the use of throwing techniques to repel the attack is impractical.

Nonzero-sum game-based decentralized approximate optimal control of modular robot manipulators with coordinate operation tasks using value iteration

Nonzero-sum game-based decentralized approximate optimal control of modular robot manipulators with coordinate operation tasks using value iteration

Gaze transition entropy as a measure of attention allocation in a dynamic workspace involving automation

Real-world work environments require operators to perform multiple tasks with continual support from an automated system. Eye movement is often used as a surrogate measure of operator attention, yet conventional summary measures such as percent dwell time do not capture dynamic transitions of attention in complex visual workspace. This study analyzed eye movement data collected in a controlled a MATB-II task environment using gaze transition entropy analysis. In the study, human subjects performed a compensatory tracking task, a system monitoring task, and a communication task concurrently. The results indicate that both gaze transition entropy and stationary gaze entropy, measures of randomness in eye movements, decrease when the compensatory tracking task required more continuous monitoring. The findings imply that gaze transition entropy reflects attention allocation of operators performing dynamic operational tasks consistently.

Empowering Women's Business Groups through Microfinance in Village Enterprises

Background: Effective management of microfinance institutions is essential for rural economic development. Specific Background: This study examines BUMDesa Bersama “Gempol Sejahtera,” focusing on its application of microfinance principles in financial management. Knowledge Gap: There is limited research on how structured bureaucracies affect the success of microfinance programs in community organizations. Aims: The research evaluates the impact of organizational structure on microfinance initiatives and resource management. Results: Findings show that a clear bureaucratic structure enhances efficiency and role clarity, facilitating successful program implementation. Clear Standard Operating Procedures (SOPs) and task fragmentation are critical for optimal execution. Novelty: This study offers new insights into the link between organizational structure and microfinance effectiveness in community enterprises, enriching the literature on rural empowerment. Implications: The results underscore the importance of strong organizational frameworks to improve resource management and program responsiveness, thereby promoting economic empowerment, especially among women. Highlights : Organizational Efficiency: A clear bureaucratic structure enhances operational effectiveness and role clarity. Critical Procedures: Implementing Standard Operating Procedures (SOPs) is essential for program success. Economic Empowerment: Strong frameworks promote responsiveness and resource management, benefiting community initiatives. Keywords: microfinance, organizational structure, community empowerment, financial management, bureaucratic efficiency

Flight Arrival Scheduling via Large Language Model

The flight arrival scheduling problem is one of the critical tasks in air traffic operations, aiming to ensure that the flight arrive in the correct sequence safely. Existing methods primarily focus on the terminal area and often overlook the presence of training flight at the airport. Due to the limited generalization of traditional methods and varying control practices at different airports, training flight at airports still rely on manual control for arrival sorting. To effectively address these issues, we propose a novel method for slot allocation that leverages the strong reasoning capabilities and generalization potential of large language models (LLMs). Our method conceptualizes the dynamic scheduling problem for training flight as a language modeling problem, a perspective not previously explored. Specifically, we represent the allocator’s inputs and outputs as language tokens, utilizing LLMs to generate conflict-free results based on a language description of requested landing information and assigned training flight information. Additionally, we employ a reset strategy to create a small dataset for scenario-specific samples, enabling LLMs to quickly learn allocation schemes from the dataset. We demonstrated the capability of LLMs in addressing time conflicts by evaluating metrics such as answer accuracy, conflict rate, and total delay time (without the wrong answer). These findings underscore the feasibility of employing LLMs in the field of air traffic control.

An Operations Chain Model for Automatic Assessment of Operation Procedure for Equipment Operators

Automatic assessment of the operation ability of operators based on computers is an essential approach for improving the effectiveness of equipment operation training and enhancing equipment safety. Present methods primarily focus on the operation results but pay less attention to the operation procedure. One reason is that there is a lack of a model that has the ability to describe all probable paths to accomplish the same task. Therefore, an operations chain model is put forward for the first time to describe the standard operation procedure and relationships among operations based on the decomposition of operational tasks and the relationships among the various operations required to fulfill the task. A specific operation task corresponds to an operations chain, which will form one or multiple standard operation sequences that will allow trainees to complete the same task through different paths. The Needleman–Wunsch sequence alignment algorithm is introduced to match the trainees’ operation sequence with all standard sequences. The maximum alignment result is the score of the trainees’ operations. An example shows that the operations chain model can accurately describe the complex structure of the standard operating procedures. The Needleman–Wunsch sequence alignment algorithm can objectively evaluate the trainee’s operation capabilities. The combination of the operations chain model and sequence alignment algorithm can form a complete operation procedure assessment method that is friendlier to trainees and has more objective evaluation results. The method will help to improve the effectiveness of the competency assessment of equipment operators.

Gym Management System Using Python Django

An inventive software program called the Gym Management System (GMS) was created to maximize and simplify the functioning of gyms and fitness centers. In a time when fitness and health are more important than ever, effective management tools are essential. By making use of the Django web framework, this project makes it possible to create a solid, user-friendly platform that meets the various needs of gym management, employees, and patrons. The GMS includes all of the necessary features, including class scheduling, attendance monitoring, member registration, and payment processing. The initiative intends to increase member involvement and operational efficiency by combining these features into a single system. The fitness sector has grown quickly, and this has made effective gym management systems more and more necessary. Conventional methods of managing gyms, which frequently depend on manual procedures, are ineffective and prone to mistakes, especially when the number of memberships and services offered increases. The design, development, and implementation of a comprehensive Gym Management System (GMS) are presented in this paper. The GMS automates a number of operational tasks, including scheduling fitness sessions, tracking attendance, accepting payments, and managing trainers. Through the use of an intuitive interface, the suggested system seeks to increase data accuracy, optimize member experience, and streamline administrative processes.

Postural Control Changes When Performing Explosive Ordnance Disposal (eod) Operational Tasks With Eod Personal Protection Equipment (PPE): Bending Over At The Waist

Postural Control Changes When Performing Explosive Ordnance Disposal (eod) Operational Tasks With Eod Personal Protection Equipment (PPE): Bending Over At The Waist

DIANA: An underwater analog space mission

The DIANA mission represents an underwater analog space mission designed to simulate and study the impact of long-duration spaceflight and extraterrestrial habitation on crew performance, psychosocial dynamics, and technological systems. The mission utilized an underwater habitat, the Hydronaut H03 DeepLab, to mimic the isolated, confined, and extreme (ICE) environment of space. Over eight days, a six-member crew lived and worked in underwater (3) and water surface (3) habitats, performing scientific experiments and operational tasks. The mission schedule encompassed a variety of activities such as drone exploration, extravehicular activities (EVAs), soil sampling, and media interactions, culminating in a simulated departure from the lunar surface. Data collection methods included continuous biomedical monitoring, cognitive task assessments, and sociomapping to analyze team communication and cooperation. This paper provides an overview of the mission architecture and outcomes, offering valuable insights into the challenges of future human space exploration and informing improvements in crew selection, training, and support systems.

Mapping percent canopy cover using individual tree- and area-based procedures that are based on airborne LiDAR data: Case study from an oak-hickory-pine forest in the USA

Canopy cover (CC) is the proportion of a forest floor covered by the vertical projection of tree crowns. Recently, it has become common to utilize LiDAR (light detection and ranging) canopy metrics to estimate CC over large areas. However, these metrics are primarily related to canopy density rather than the specific definition of CC. Here, two processes that employed individual tree segmentation (ITS) and area-based procedures based on LiDAR data are presented to estimate CC across the Talladega Division of the Talladega National Forest (93,694 ha) at the plot, stand, and landscape levels. The two analytical procedures were assessed using the results of a plot/grid method as a reference dataset, which focused on CC estimates within 255 field measurement fixed-area sample plots. The accuracy of a third process, employing an imagery-based visual CC assessment, was also compared against the two procedures and the reference dataset. The LiDAR-based analytical procedures were able to provide estimates of CC with an RMSE of approximately 15 %, which is acceptable for landscape-level assessments. Based on the results of this study, we conclude that CC maps, when created using LiDAR data, may be suitable for various operational tasks such as assessing the impact of forest disturbances and helping to determine the habitat suitability for certain wildlife species.

Self-adaptive fault diagnosis for unseen working conditions based on digital twins and domain generalization

In recent years, intelligent fault diagnosis based on domain adaptation has been used to address domain shifts in cyber–physical systems; however, the need for acquiring target data sufficiently limits their applicability to unseen working conditions. To overcome such limitations, domain generalization techniques have been introduced to enhance the capacity of fault diagnostic models to operate under unseen working conditions. Nevertheless, existing approaches assume access to extensive labeled training data from various source domains, posing challenges in real-world engineering scenarios due to resource constraints. Moreover, the absence of a mechanism for updating diagnostic models over time calls for the exploration of self-adaptive generalized diagnosis models that are capable of autonomous reconfiguration in response to new unseen working conditions. In such a context, this paper proposes a self-adaptive fault diagnosis system that combines several paradigms, namely Monitor-Analyze-Plan-Execute over a shared Knowledge (MAPE-K), Domain Generalization Network Models (DGNMs), and Digital Twins (DT). The MAPE-K loop enables run-time adaptation to dynamic industrial environments without human intervention. To address the scarcity of labeled training data, digital twins are used to generate supplementary data and continuously tune parameters to reflect the dynamics of new unseen working conditions. DGNM incorporates adversarial learning and a domain-based discrepancy metric to enhance feature diversity and generalization. The introduction of multi-domain data augmentation enhances feature diversity and facilitates learning correlations among multiple domains, ultimately improving the generalization of feature representations. The proposed fault diagnosis system has been evaluated on three publicly available rotating machinery datasets to demonstrate its higher performance in cross-work operation and cross-machine tasks compared to other state-of-the-art methods.

A new approach on the management of landfill leachate reverse osmosis concentrate: Solar distillation coupled with struvite recovery and biological treatment

The management of reverse osmosis (RO) concentrate remains a challenging task for operators of Landfill Leachates Treatment Plants. In this article we suggest an integrated treatment scheme for RO concentrate that combines solar distillation, struvite precipitation to reduce ammonia content of the distillate and biological treatment of the supernatant either with mixed cultures of bacteria or with microalgae. Experiments in a pilot-scale solar still, equipped with underfloor heating system, showed that the production rate of the distillate ranged up to 3.17 L/d m2. The distillate was characterized by elevated average concentrations of ammonium nitrogen; 2028 mg/L and 1358 mg/L in the two experiments conducted, respectively. A decreasing trend on concentrations of NH4+-N was noticed during these experiments, while the opposite was observed for COD. Struvite recovery experiments showed that the optimum Mg:NH4:PO3 ratio was that of 2:1:5.8. Under these conditions, the NH4+-N removal reached 88%. Further treatment of the process supernatant into a 4-L hybrid sequencing batch reactor with biocarriers and activated sludge achieved NH4+-N removal higher than 98% in Phases C and D, where 450 and 600 mL of supernatant were added, respectively. Similar removal was also observed in a 2-L bioreactor with microalgae Chlorella sorokiniana when 150 mL of struvite supernatant were added (Phase B) while further increase of the amount of added supernatant to 200 mL resulted to a sharp stop of NH4+-N consumption (Phase C). Calculations for a landfill serving 20,000 inhabitants and a daily RO concentrate production of 6 m3/d showed that the required area for the construction of the solar still was 1893 m2 and the volumes of the hybrid and the microalgae reactor were 54 m3 and 60 m3, respectively. The recovered solid material of struvite process, after characterization for heavy metals and organic micropollutants, could be reused to the fertilizers industry.

Differential Kinematics of a Single-point-suspended Manipulator with Center-of-mass Shift Compensation

The single cable-suspended manipulator is suitable for special occasions such as aerial operation tasks of unmanned aerial vehicles (UAVs) and deep-well search and rescue. However, due to the lack of complete constraints at the base, the manipulator will have errors in end position due to the center-of-mass offset during the motion. In this paper, the model of CoM shifting is established, and the Jacobian matrix is improved based on this model, to realize the differential kinematics solution for the single cable-suspended manipulator. In addition, by introducing the constraint of CoM shift in the Jacobian matrix, it makes it possible to synchronize the planning of the motion of the end and the center of mass. This can effectively avoid the wobbling of the manipulator in the presence of elasticity or instability at the suspension point. Both simulation and prototype experiments effectively verify the effectiveness of the proposed method. Using the method of this paper, the average error of the trajectories in the z-axis and x-axis can be reduced from 27.0±2.6 mm to 5.6±3.4 mm, and 43.0±64.2 mm to 3.3±4.8 mm, respectively.

A novel cross-receptive field fusion cascade network with adaptive mask update for transfer health state diagnosis of manipulators

Manipulators, particularly planar parallel manipulators, are widely employed in high-end precision equipment to conduct precise positioning and operation tasks due to their advantages of high stiffness, high precision, and high load. Moreover, they are also frequently exposed to changeable working circumstances, which significantly cause inconsistent health state data distribution. Although transfer learning can successfully offset the above distribution discrepancies, it remains unclear how to identify and quantify the source domain knowledge’s contribution to the transfer process. To overcome these challenges, a novel transfer health state diagnosis framework, named cross-receptive field fusion cascade network with adaptive mask update (CFFCN-AMU), is developed and employed for manipulators. Specifically, a unique cross-receptive field fusion cascade module (CFFCM), in which the receptive field self-evaluator and channel attention mechanism are jointly designed, is constructed initially to achieve adaptive extraction and fusion of cascaded features. Subsequently, in the target domain fine-tuning stage, an adaptive mask update (AMU) strategy is implemented to evaluate the contribution of source domain knowledge and selectively guide the parameter updating process. Finally, some mechanistic model-driven cross-working condition transfer scenarios are investigated. Multiple sets of excellent transfer diagnosis results fully illustrate the transferability and superiority of the constructed CFFCN-AMU model.

Manually operated microtube automatic capper/decapper system for clinical laboratory and biological laboratory personnel

Polymerase chain reaction (PCR) is an effective method for diagnosing infectious diseases and has been the primary method throughout the novel coronavirus disease (COVID-19) pandemic. PCR tests (from specimen collection to result acquisition) involve sample pretreatment, nucleic acid extraction, and PCR procedure. Automating the pretreatment process is crucial to mitigate the risk of infection for workers and to reduce the likelihood of sample contamination-triggered misdiagnosis, particularly when handling centrifuge tubes, cryopreservation tubes, and microtubes. Robotic systems have been engineered to automate cell culture and PCR-based diagnosis, predominantly designed for use with screw-capped containers. However, this leaves a notable gap in automation solutions for microtubes equipped with press-type caps. To address this gap, we developed a versatile microtube capper/decapper system. On the other hand, many tasks of manual operation using microtubes, which are routinely conducted in clinical tests and biological experiments, are performed. Compared to screw-type caps for centrifuge and cryopreservation tubes, press-type caps for microtubes present a considerably higher risk of the worker's fingers contacting the inside of the cap and/or generating airborne droplets. Despite the risks of contamination and infection derived from the manual handling of microtube caps, which can compromise diagnosis/experiment accuracy and worker safety, devices for manually opening and closing microtube caps without direct contact remain lacking. Therefore, leveraging the technology from the developed versatile microtube capper/decapper system for laboratory automation, we created a manually operated microtube equipped with an automatic capper/decapper system tailored for personnel in clinical and biological laboratories.In this study, we first examined the required specifications and prerequisites for a manual microtube capper/decapper and clarified the operating methods, operating procedures, operation environment, device size, accompanying functions, etc. Based on the required specifications and preconditions, we proceeded with the mechanical and control design of the conceptual model, manufactured a prototype, and confirmed its basic functions and performance. The compliant to the required specifications and preconditions and the usefulness of the proposed manual microtube capper/decapper were validated through various experiments and demonstrations. Using the proposed microtube capper/decapper, even small-scale operations, which are challenging to streamline, can be performed nearly as efficiently as full manual operations. Although operation time was not reduced, the ability to open and close microtubes without manual contact is crucial for improving diagnostic and experimental accuracy and for reducing the burden on and enhancing the safety of laboratory personnel. Because microtubes are used in various clinical tests and biological experiments, we believe that the proposed system can markedly reduce the workload for personnel across numerous clinical and biological laboratories.

Optimizing the economic dispatch of weakly-connected mini-grids under uncertainty using joint chance constraints

AbstractIn this paper, we deal with a renewable-powered mini-grid, connected to an unreliable main grid, in a Joint Chance Constrained (JCC) programming setting. In several rural areas in Africa with low energy access rates, grid-connected mini-grid system operators contend with four different types of uncertainties: forecasting errors of solar power and load; frequency and outages duration from the main-grid. These uncertainties pose new challenges to the classical power system’s operation tasks. Three alternatives to the JCC problem are presented. In particular, we present an Individual Chance Constraint (ICC), Expected-Value Model (EVM) and a so called regular model that ignores outages and forecasting uncertainties. The JCC model has the capability to guarantee a high probability of meeting the local demand throughout an outage event by keeping appropriate reserves for Diesel generation and battery discharge. In contrast, the easier to handle ICC model guarantees such probability only individually for different time steps, resulting in a much less robust dispatch. The even simpler EVM focuses solely on average values of random variables. We illustrate the four models through a comparison of outcomes attained from a real mini-grid in Lake Victoria, Tanzania. The results show the dispatch modifications for battery and Diesel reserve planning, with the JCC model providing the most robust results, albeit with a small increase in costs.

Bi-level task planning strategy for blended-wing-body underwater gliders

ABSTRACT This study focuses on the task planning problem of the blended-wing-body underwater glider (BWBUG), which must autonomously navigate through a sequence of underwater visitation points while ensuring safety and economy. Firstly, the task planning problem of the BWBUG is analysed, with attention given to operational space and task requirements. Subsequently, a bi-level planning framework that incorporates both the bottom-level and top-level planners is proposed. The bottom-level planner optimises the glide path between any two visit points by considering safety and glide angle constraints, with the objective of minimising energy usage. The top-level planner focuses on the task constraints and optimises the global visitation path of the BWBUG to achieve the objective of global energy minimisation. Simulations demonstrate the effectiveness of the bi-level based task planning strategy proposed in this study. The solution algorithms are highly competitive, capable of planning rational global visitation paths for the BWBUG.

Data integrity cyber-attack mitigation using linear quadratic regulator based load frequency control in hybrid power system

Abstract Hybrid power systems are the contemporary solution to meet the stiff climate change targets and also hold future for implementing distributed generation and microgrids. These systems have renewable sources as their key elements which in turn have high level of intermittency due to weather conditions and other reasons. At the same time, these hybrid power systems are also vulnerable to cyber threats owing to the intense adoption of various IoT Technologies (Internet of Things). Load frequency control (LFC) is a formidable task for the system operators under such scenario and robust control strategies are required to achieve the load frequency within tolerable limits. In this work Linear quadratic controller (LQR) has been proposed to address the challenges of hybrid power systems. Two area interconnected power systems are considered in this work with each one having different configuration with respect to source of power generation. Solar, wind, geo-thermal, electric vehicle charging infrastructure and pumped storage power plant are integrated together with conventional thermal power plant for showcasing the LQR based controller under data integrity cyber-attack scenario. The frequency response of the hybrid power system is demonstrated through MATLAB simulations.