System Input Research Articles

Degumming and bleaching process troubleshooting in a palm oil refining process using fuzzy expert system with thematic analysis

AbstractDegumming and bleaching are critical steps in the palm oil refining process, as they are the precursors to the qualities of refined, bleached, and deodorized palm oil. In practice, plant operators often face oil rejections in these processes and solve the problem by trial and error. Hence, a fuzzy expert system is developed to troubleshoot the degumming and bleaching process, for identifying failures and suggesting actions. However, developing the knowledge base and inference engine in the fuzzy expert system for troubleshooting the degumming and bleaching process is challenging because the data in the actual palm oil refining process are poorly documented and must be obtained from various sources, including field observation, document analysis, and interviews, and need to be analyzed using thematic analysis. The results from the thematic analysis were represented as input and output variables of the fuzzy expert system. The developed fuzzy expert system is tested and validated against different data sets and industrial data to identify faults and suggest necessary actions. To evaluate the robustness of the troubleshooting system, the membership functions of the fuzzy expert system are adjusted based on the distributed control system (DCS). The results show that the troubleshooting system can effectively diagnose potential faults and provide necessary actions and can serve as a useful guidance for failures in the degumming and bleaching process.

Future flight deck design: Developing an innovative touchscreen inceptor combined with the primary flight display

The touchscreen has the potential to optimize the space usage and efficiency of the flight deck. Currently, touchscreens can combine the input and output functions of different systems. However, it does not yet serve as an inceptor to replace the sidestick or control column for aircraft manoeuvres. This study aims to examine the potential of a touchscreen as a flight inceptor compared with a traditional sidestick and gamepad. This research recruited 72 participants who interacted with three inceptors for both an instrument landing with disturbance and without disturbance using the Future System Simulator. The findings demonstrated that pilot performance, system usability and pilots’ situation awareness of touchscreen inceptors were significantly inferior to those of traditional sidesticks and gamepads. Compared to the sidestick and gamepad, the touchscreen provided a poorer situation awareness with the highest supply and demand. In addition, the performance of all inceptors was significantly influenced by disturbance. There is still a long way to go for certification of a touchscreen as an inceptor on the future flight deck. This research showed that even though the touchscreen inceptor scored the lowest on both SUS and SART, the majority of pilots agreed that the touchscreen inceptor provided a better attentional supply in challenging disturbance circumstances, providing proof of concept for its possible inclusion in flight deck design. There is a potential that the emerging touchscreen as an inceptor may develop further along with human-system integration flight deck design.

Recognition method for biomimetic camouflage communication signal imitating cetacean click in underwater multipath channels

Focusing on the need of biomimetic camouflage communication signal recognition in underwater multipath channels, we propose a recognition method for biomimetic camouflage click communication train (BCCCT) based on time delay difference (TDD) coding in multipath channels. For the problem of multipath interference, we perform multipath determination on the received signal by autocorrelation, filter relevant peak points, determine the time delays between multipaths, and remove the multipath interference signals according to the determined time delays. A click extraction method based on the double sliding window is proposed, which locates the boundary of click by signal envelope. By analyzing the distribution characteristics of the time interval of adjacent clicks (TIAC) of BCCCT and real click train (RCT), we model the TIACs based on Gaussian kernel probability density estimation (PDE), and recognize the BCCCTs by the Convolutional Neural Networks (CNN), which takes the PDE curve as the system input. The numerical simulations and a lake experiment are carried out to measure the effectiveness of the recognition method proposed under different signal-to-noise ratios (SNR), coding parameters, and channels. The recognition accuracy can achieve 80 % at 0 dB in the constructed channels. Moreover, in the real underwater communication environment, the recognition accuracy can achieve 95 %.

Augmented Virtual Mouse System with Enhanced Gesture Recognition

This paper presents the development of a contactless system designed to serve as an alternative to the traditional physical input device, such as a computer mouse or touchpad, utilized in human-computer interaction. The proposed system aims to offer a more convenient and hygienic way of interacting with computer devices by using hand gestures instead of physical contact with the mouse system or machine interface. The system has potential applications in various fields including healthcare, public interfaces, and gaming. Existing gesture-controlled input systems lack a comprehensive touchless and accurate system capable of performing almost every operation of a physical mouse. The proposed approach involves recognising the hand and its gestures. Hand tracking and dynamic gesture recognition are incorporated to ensure a smooth and hassle-free user experience during interaction. The efficient Mediapipe framework is used to detect and track hand movements from video frames captured through a computing device Camera.Computer vision algorithms are employed for gesture recognition within each frame, along with Python libraries for processing gestures. Sufficient gestures are added into the system, enabling it to execute a wide range of mouse functions with substantial precision metrics. This paper provides details regarding the development and overall performance of the system. Key Words: hands, mouse, contactless, gesture, OpenCV, mediapipe

Control-oriented thermal model and load identification for circulating cooling water system in precision process applications

With the increasing precision in machining and measurement, there is a growing demand for improved temperature stability in cooling water systems used in industrial processes. Accurate thermal models and load states are essential for developing efficient controllers to enhance temperature performance. This paper focuses on the development of thermal models for various components of circulating water systems in precision water-cooling processes. It presents a control-oriented thermal model framework that segregates the water circulation cycles and defines system inputs and processes. A novel identification algorithm is proposed to address thermal inertia and cyclic nonlinearity by extracting the cyclic period and cycle change rate. The algorithm can simultaneously estimate the state–space model and unmeasurable load disturbances. A validation experimental setup was constructed, and the results demonstrate that, for different flow scenarios, the estimated load and thermal model parameters align well, with correlations exceeding 0.85 and error ratios close to 10%. Additionally, the circulating water output temperature can be accurately predicted. The fitting degrees surpass 84% within five cycles, with correlations exceeding 0.97 and error standard deviations below 0.22 °C.

An approach to nonlinear optimisation via set stabilisation of dynamical systems with an application to synchronous machines

An approach to constraint nonlinear optimisation is proposed, where the variables of the objective function and of the constraint function belong to the state of a nonlinear dynamical system. A nonlinear closed-loop feedback system is designed, whose solutions converge to a target set consisting of the optimal points of the underlying optimisation problem. The feedback law for the control input of the nonlinear dynamical system is designed by exact linearisation of a dynamical formulation of a first-order optimality condition. For the problem formulation and the stability analysis of the nonlinear closed-loop feedback system, the notion of V-detectability is considered. An application to energy-optimal feed-forward torque control for different types of synchronous machines is presented, which demonstrates the usefulness of the method. In this regard, anisotropic permanent magnet synchronous machines and electrically excited synchronous machines are covered.

Fast Newton-like extremum seeking with asymptotic convergence guarantees

Extremum seeking denotes control approaches to steer the input of a dynamical system towards the optimizer of an associated cost function. The main strength of those schemes is to achieve their objective without any prior knowledge of the mathematical expression of the cost, nor the value of its gradient. However, those algorithms typically suffer from a slow convergence speed. In this paper, we propose a novel class of Newton-like extremum seeking systems separating the gradient and Hessian estimation from the update of the cost input towards the optimizer. The stability properties of the proposed schemes, including the ability of some of them to enforce the asymptotic convergence of the cost inputs to the optimizer, are proved. Their performances are also examined via some numerical examples. The latter will demonstrate the ability of the presented schemes to significantly reduce the convergence time compared with existing Newton-like schemes.

The Design and Evaluation of CAD Custom Batik User Interface

The popularity of batik reflects consumer demands for purchasing fulfillment. Digital technology can bring several advantages and new opportunities to the custom batik design process. Computer-Aided Design (CAD) is a popular digital tool used. This paper will provide the new User Interface (UI) design of CAD custom design batik, namely Batik 4.0. It’s software developed to provide services, such as pattern customization in various sizes, batik character input system, pricing, and production time estimation utilized by the batik industry in Indonesia that can be directly forwarded to the manufacturing process. Research in UI design for CAD batik has not been studied, and this paper will fill the significant gap and upgrade the usability. This evaluation will test the usability of the test, employing the performance matrix and RTA towards UI that already exists. Improvement was made with a wireframe using human-computer interaction (HCI) and usability testing data. User-centered design (UCD) focuses on the role of the user in the process of system development as the wireframe design method. This research shows UI wireframe design for several types of users. In making the UI wireframe design, a usability evaluation was performed again. The evaluation result shows that the new user prototypes have fewer errors and exceed the usability value compared to the previous one. The new design is more user-friendly and can be used as a reference for the future development and improvement of CAD custom batik.

Finite-time consensus control of second-order multi-agent systems with input saturation constraint

A novel finite-time consensus technique is derived for second-order linear multi-agent systems with input saturation constraints. The hyperbolic tangent–based saturation function is presented for achieving input saturation while reducing the chattering issue of classical saturation functions. The leader-following consensus controller with a single saturation function is constructed to address the issue of saturation level partition between position feedback and velocity feedback. Theoretically, the property of finite-time consensus, bounded input, and smoothness of a closed-form system are proved by the Lyapunov theory in detail. Numerical simulations are conducted to exhibit the effectiveness of the proposed method fully.

Integrated omics approach reveals the molecular pathways activated in tomato by Kocuria rhizophila, a soil plant growth-promoting bacterium

Plant microbial biostimulants application has become a promising and eco-friendly agricultural strategy to improve crop yields, reducing chemical inputs for more sustainable cropping systems. The soil dwelling bacterium Kocuria rhizophila was previously characterized as Plant Growth Promoting Bacteria (PGPB) for its multiple PGP traits, such as indole-3-acetic acid production, phosphate solubilization capability and salt and drought stress tolerance. Here, we evaluated by a multi-omics approach, the PGP activity of K. rhizophila on tomato, revealing the molecular pathways by which it promotes plant growth. Transcriptomic analysis showed several up-regulated genes mainly related to amino acid metabolism, cell wall organization, lipid and secondary metabolism, together with a modulation in the DNA methylation profile, after PGPB inoculation. In agreement, proteins involved in photosynthesis, cell division, and plant growth were highly accumulated by K. rhizophila. Furthermore, “amino acid and peptides”, “monosaccharides”, and “TCA” classes of metabolites resulted the most affected by PGPB treatment, as well as dopamine, a catecholamine neurotransmitter mediating plant growth through S-adenosylmethionine decarboxylase (SAMDC), a gene enhancing the vegetative growth, up-regulated in tomato by K. rhizophila treatment. Interestingly, eight gene modules well correlated with differentially accumulated proteins (DAPs) and metabolites (DAMs), among which two modules showed the highest correlation with nine proteins, including a nucleoside diphosphate kinase, and cytosolic ascorbate peroxidase, as well as with several amino acids and metabolites involved in TCA cycle. Overall, our findings highlighted that sugars and amino acids, energy regulators, involved in tomato plant growth, were strongly modulated by the K. rhizophila-plant interaction.

Making Order in Household Accounting - Digital Invoices as Domestic Work Artifacts

AbstractThe digitization of financial activities in consumers' lives is increasing, and the digitalization of invoicing processes is expected to play a significant role, although this area is not well understood regarding the private sector. Human-Computer Interaction (HCI) and Computer Supported Cooperative Work (CSCW) research have a long history of analyzing the socio-material and temporal aspects of work practices that are relevant for the domestic domain. The socio-material structuring of invoicing work and the working styles of consumers must be considered when designing effective consumer support systems. In this ethnomethodologically-informed, design-oriented interview study, we followed 17 consumers in their daily practices of dealing with invoices to make the invisible administrative work involved in this process visible. We identified and described the meaningful artifacts that were used in a spatial-temporal process within various storage locations such as input, reminding, intermediate (for postponing cases) buffers, and archive systems. Furthermore, we identified three different working styles that consumers exhibited: direct completion, at the next opportunity, and postpone as far as possible. This study contributes to our understanding of household economics and domestic workplace studies in the tradition of CSCW and has implications for the design of electronic invoicing systems.

A modified sliding mode controller based on fuzzy logic to control the longitudinal dynamics of the autonomous vehicle

This article delves into the intricate world of controlling the longitudinal dynamics of autonomous vehicles. In the first part, we studied two distinct controllers: the Super Twisting Sliding Mode Control and its modified version enriched with the integration of fuzzy logic, applied to the longitudinal dynamics of the autonomous automobile to follow a desired speed longitudinal profile, the two controllers are compared with a Neural Network-Based Non-singular Terminal Sliding-Mode Control, the system takes the throttle and brake as its inputs and delivers speed and acceleration as outputs. The overarching objective is to ensure that the controlled vehicle maintains a close and precise alignment with the desired speed profile. The second part of our research is dedicated to the development of adaptive cruise control systems and cruise control according to the safety conditions. This controller consists of two blocks low and upper controller, in upper controller the inputs are the speeds of the automobile in front and of the autonomous automobile itself, the safety distance, the measured distance. The output is the desired acceleration. The objective is to maintain a distance between the front vehicles, greater than or equal to the safety distance. For this, to achieve this task, we have implemented a control system known as the Proportional Integral Derivative (PID) controller in the adaptive cruise control system to control this system. In the low controller block, the same controllers used in the first part: the Super Twisting Sliding Mode Control and its modified version based on fuzzy logic, are applied, the system inputs are throttle and brake, and the outputs are speed and acceleration. This system is processed by MATLAB code, we obtained a better result with our proposed controller such that the maximum absolute speed error is equal to 0.0144 m/s in the first case of speed tracking, and to 0.006 m/s in the second case of the using adaptive cruise control, the illustrations below show the efficiency and robustness of these controllers.

Australian Fire Danger Rating System: implementing fire behaviour calculations to forecast fire danger in a research prototype†

Background The Australian Fire Danger Rating System (AFDRS) was implemented operationally throughout Australia in September 2022, providing calculation of fire danger forecasts based on peer-reviewed fire behaviour models. The system is modular and allows for ongoing incorporation of new scientific research and improved datasets. Aims Prior to operational implementation of the AFDRS, a Research Prototype (AFDRSRP), described here, was built to test the input data and systems and evaluate the performance and potential outputs. Methods Fire spread models were selected and aligned with fuel types in a process that captured bioregional variation in fuel characteristics. National spatial datasets were created to identify fuel types and fire history in alignment with existing spatial weather forecast layers. Key results The AFDRSRP demonstrated improvements over the McArthur Forest and Grass Fire Danger systems due to its use of improved fire behaviour models, as well as more accurately reflecting the variation in fuels. Conclusions The system design was robust and allowed for the incorporation of updates to the models and datasets prior to implementation of the AFDRS.

Minimum Information Variability in Linear Langevin Systems via Model Predictive Control.

Controlling the time evolution of a probability distribution that describes the dynamics of a given complex system is a challenging problem. Achieving success in this endeavour will benefit multiple practical scenarios, e.g., controlling mesoscopic systems. Here, we propose a control approach blending the model predictive control technique with insights from information geometry theory. Focusing on linear Langevin systems, we use model predictive control online optimisation capabilities to determine the system inputs that minimise deviations from the geodesic of the information length over time, ensuring dynamics with minimum "geometric information variability". We validate our methodology through numerical experimentation on the Ornstein-Uhlenbeck process and Kramers equation, demonstrating its feasibility. Furthermore, in the context of the Ornstein-Uhlenbeck process, we analyse the impact on the entropy production and entropy rate, providing a physical understanding of the effects of minimum information variability control.

Event-triggered iterative learning control for discrete parabolic distributed parameter systems

Iterative learning control (ILC) is an intelligent control strategy which can achieve the desired trajectory tracking by continuously renewing the control signal based on the previous experience. In this article, an event-triggered condition that can save system resources by reducing the number of iterative updates is proposed. Moreover, an event-triggered ILC algorithm is designed for linear discrete parabolic distributed parameter systems, the system input is updated with the learning law only when the derived triggered condition is met. Through rigorous mathematical analysis, the tracking error can converge to zero when the iterative batch approaches infinity under the given sufficient condition. Then, we also extended the above ideas to nonlinear case. By simulation, the effectiveness of the designed algorithm are illustrated.

Allocating the fixed cost as a complementary input in two-stage system: A DEA approach

The existing research on fixed cost allocation (FCA) in two-stage system data envelopment analysis (DEA) models typically regards the fixed cost as an additional input for each decision-making unit (DMU). However, these models overlook the prevalent real-world scenario where fixed costs act as complementary inputs in actual production processes. This study proposes a general two-stage network DEA model that incorporates the fixed cost as a complementary input to optimize the allocation scheme. First, we construct a functional relationship between the efficiency scores of DMUs and their allocated fixed costsusing a modified super-efficiency DEA model, which effectively classifies DMUs and solves infeasible solutions within the variable returns to scale (VRS) framework. Then, we propose a fair and unique allocation model based on fairness and efficiency maximization principles. Specifically, we allocate fixed costs based on the operational scale for inelastic DMUs while equitably increasing the efficiency scores for elastic DMUs. Finally, a numerical example and an empirical study on subsidy allocation among 30 provinces demonstrate the rationality and acceptability of our approach.

Assessment of non-revenue water in the urban water distribution system network in Cameroon (Central Africa)

ABSTRACT This paper aims to assess non-revenue water (NRW) in the urban water distribution system in Cameroon. The methodological approach used in this study was based on online searches using the databases such as Google Scholar, Web of Science, PubMed, and the International Water Association. These online searches have been completed through field observations and interviews with institutional and non-institutional stakeholders in the urban water sector. Results indicate that the total volume of NRW in the urban area of Cameroon was 100.26 million m3/year, which represents 52.5% of the total system input volume. About 2 million people could be supplied by cutting Cameroon's NRW to half the present level. Findings also suggest that the water utility (Camwater) practices passive leakage control, meaning that Camwater repairs only those leaks that are visible. Reducing NRW can be achieved through leakage detection and pipe replacement, pressure management, water metering, and a program to identify, remove, and replace illegal connections.

PENGUJIAN BLACKBOX PADA SISTEM PEMESANAN UNTUK SALES ORDER DI PT BUKIT MURIA JAYA BERBASIS EQUIVALENCE PARTITIONS

This research aims to conduct blackbox testing on the sales order booking system at PT. BMJ based on the concept of equivalence partitions. The blackbox testing method is employed to assess the functionality of the system without considering its internal implementation. The study identifies representative equivalence partitions within the input and output domains of the sales order booking system and utilizes these partitions to design test cases. Through a series of tests, the system's performance is analyzed under various input conditions representing each partition. The testing results provide a better understanding of the system's reliability, identify potential defects, and offer recommendations for further improvement. This study contributes to enhancing the quality of the sales order booking system at PT. BMJ through a systematic and structured blackbox testing approach.

VR interactive input system based on INS and binocular vision fusion

In virtual reality interactive input systems, real-time and accurate spatial position and pose measurement is key to achieving a natural user interface. This study explores the application of inertial measurement units and binocular vision fusion technology in virtual reality interactive input systems, with the aim of improving the tracking accuracy of the system through optimized pose models and visual algorithms. A virtual reality measurement technology that integrates inertial measurement units and binocular vision is proposed by using an improved Kalman filtering algorithm to process inertial measurement units data, and combining it with the SURF algorithm optimized binocular vision system. Experimental results showed that fusion technology could reduce sensor noise and bias, improve the accuracy of pose estimation, and promote stable and robust motion tracking in virtual reality systems. In the angle range of -90 ° to 90 °, the average absolute error of the fusion system compared to the simple inertial measurement units pose calculation decreased from 3.371 ° to 1.369 ° In the experiment of measuring distance with a binocular vision system, the average absolute error value decreased to 1.532 mm, and the error range of the marker within the distance range of 500 mm to 650 mm was controlled within -1.3 mm to 1.2 mm. This study provides an effective solution for achieving high-precision virtual reality interactive input systems and is meaningful for the advancement of virtual reality technology.

Finite-Time Adaptive Fuzzy Backstepping Control for Quadrotor UAV With Stochastic Disturbance

This paper proposes an adaptive fuzzy output feedback control approach for quadrotor unmanned aerial vehicles (QUAV) with stochastic disturbances, besides which we consider the unmeasurable states and unknown nonlinear functions. The QUAV system contains stochastic terms which are not bounded and not differentiable. By combining the It <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\hat{\rm \textbf{o}}$</tex-math> </inline-formula> differential equation with finite-time theory, a novel stochastic finite-time stability controller for QUAV is raised for the first time. The fuzzy logic system (FLS) is utilized to approximate the unknown nonlinear functions in the model. Dynamic surface control technology is introduced to reduce the complexity of differential. Furthermore, an observer with FLS is designed through the adaptive backstepping technique to estimate the immeasurable states. It is proved that this control approach can ensure that all states of the closed-loop QUAV system are semi-global and finite-time stable in probability. Meanwhile, the errors of system outputs and observer converge to a small neighborhood of origin. The simulation results show the effectiveness of the proposed method. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —In practical applications, many systems are often affected by internal and external disturbances, and not all of them can be described by mathematical models, so they are called stochastic disturbances. Taking the QUAV as an example, when the system is disturbed by internal parameters, external environment, system input, sensor error, and other stochastic factors, the deterministic system can no longer accurately describe the controlled object. In this paper, the QUAV is regarded as a stochastic system for the first time, and a novel controller is designed to solve the above problems. In addition, the QUAV needs fast action in some applications, such as emergency collision avoidance, which has high requirements for the convergence performance of the controller. Therefore, studying the finite-time control for QUAV systems with stochastic disturbances is necessary. At the same time, this paper also considers the problem that the state is not measurable and the system contains unknown nonlinear equations.