Limited Interval Research Articles

Predefined time fuzzy adaptive control for stochastic nonlinear systems with limited time interval output constraints

This article investigates the problem of fuzzy adaptive predefined time tracking control for stochastic nonlinear systems with limited time interval output constraints. Firstly, the considered output constraints occur within a finite time interval after the system starts running. By constructing shift functions and barrier Lyapunov functions (BLFs), the constrained system is converted into an unconstrained system, which solves the problem of function discontinuity resulting from output constraints within limited time intervals. Then, with the help of adaptive backstepping technique and predefined time control method, which reduces the parameters to be designed and removes the limitation of relatively large initial control input in existing approaches. The designed control technique ensures the boundedness of all variables of the stochastic system, the tracking error converges within a predetermined time, and the outputs do not exceed their constraint boundaries in a finite time interval. And this algorithm is applicable to both infinite time constraints and unconstrained outputs cases. Finally, the validity of this approach is demonstrated through simulation examples.

Iterative learning resilient consensus of uncertain nonlinear multi-agent systems vulnerable to false data injection attacks

This work investigates the iterative learning resilient consensus of uncertain nonlinear high-order multi-agent systems (MASs) against false data injection (FDI) attacks. First, in order to reduce the impact of FDI attacks on the nonlinear MASs, a novel coordinate transformation technique is proposed, which is composed of the states after being attacked, and the Nussbaum gain technique is adopted to address the problem of unknown attack gains resulting from FDI attacks. Then, by employing compromised state variables, a fuzzy adaptive iterative learning resilient control method is presented based on the composite energy function, where unknown nonlinear functions are handled using fuzzy logic systems. The presented approach can guarantee that the outputs of all followers precisely track the leader in a limited time interval while ensuring that all closed-loop signals are bounded. Finally, a numerical simulation is provided to demonstrate the efficacy of the designed control strategy.

Two sunspot group populations and Gnevyshev-Waldmeier rule

Based on the materials of the Royal Greenwich Observatory catalog, the study of two different sunspot group populations continued: LLG – large long-lived, and SSG – small short-lived groups. The task of achieving a higher accuracy of the population separation parameter than before (Nagovitsyn & Pevtsov 2016, 2021) is being solved. A procedure for randomizing the lifetimes of sunspot groups observed once a day is proposed, which allows for statistical studies to achieve a higher time resolution. The form of the Gnevyshev-Waldmeier Rule is taken, which linearly connects the logarithm of the logS area and the lifetime of the sunspot group LT (over limited time intervals). It is shown that it has coefficients significantly different for SSG and LLG populations. The range of values of the group lifetime parameter separating the populations was found as LT∗=4.75±0.53 days, which is in agreement with the threshold values obtained earlier for the number of days of sunspot group observation: mSSG⩽5 days and mLLG>5 days. It is shown that the parameters of the bilognormal distribution of the sunspot group areas, obtained from their common grouped sample statistically by Levenberg–Marquardt method and with a preliminary division into lognormal distributions by lifetime, correspond to each other. It was clarified that, with an accuracy of up to a tenth of a day, the SSG population corresponds to the lifetimes of groups ⩽4.6 days, and the LLG population corresponds to times ⩾4.7 days. The results obtained make it possible to study various physical properties of SSG and LLG populations independently of each other in order to compare them and study their nature.

Multivariate analysis of long-term climate data in connection with yield, earliness and the problem of global warming.

Climate change is the key challenge to agriculture in the XXI century. Future agricultural techniques in the Russian Federation should involve the optimization of land utilization. This optimization should apply algorithms for smart farming and take into consideration possible climate variations. Due to timely risk assessment, this approach would increase profitability and production sustainability of agricultural products without extra expenditures. Also, we should ground farming optimization not on available empirical data encompassing limited time intervals (month, year) or human personal evaluations but on the integral analysis of long-term information bodies using artificial intelligence. This article presents the results of a multivariate analysis of meteorological extremes which caused crop failures in Eastern and Western Europe in last 2600 years according to chronicle data and paleoreconstructions as well as reconstructions of heliophysical data for the last 9000 years. This information leads us to the conclusion that the current global warming will last for some time. However, subsequent climate changes may go in any direction. And cooling is more likely than warming; thus, we should be prepared to any scenario. Plant breeding can play a key role in solving food security problems connected with climate changes. Possible measures to adapt plant industry to the ongoing and expected climate changes are discussed. It is concluded that future breeding should be based on the use of highly adapted crops that have already been produced in pre-breeding programs, ready to meet future challenges caused by potential climate change.

Wind Speed Variations at the Venus Cloud Top above Aphrodite Terra According to Long-term UV Observations by VMC/VENUS Express and UVI/AKATSUKI

Series of consecutive UV (365 nm) images of Venus cloud coverage provide a way to investigate dynamics of the mesosphere. An unprecedented series of such images was obtained by the VMC/Venus Express (ESA) and UVI/Akatsuki (JAXA) cameras from 2006 to 2022. At 10°S long-term variations in the mean zonal and meridional wind speed are observed with a period of 12.5 ± 0.5 years. Analysis of the of the mean zonal wind behavior around noon (12 ± 1 h) at phase angles of 60°–90° in limited observation time intervals shows that near the minimum of the long-term dependence the deceleration of the horizontal flow is observed above the highest part of Aphrodite Terra, Ovda Regio, for both VMC and UVI. Conversely, acceleration is observed above the Ovda Regio near the maximum of the long-term dependence. The considered longitudinal variations of the zonal wind speed extend from the equator to middle latitudes (0°–40°). The meridional wind speed shows longitudinal variations associated with the topography of the underlying surface, regardless of whether the horizontal flow is slowing down or accelerating above the highlands of Aphrodite Terra.

Air pollution related adverse respiratory health outcomes in California’s San Joaquin Valley: evidence from 2016 linked emergency department and hospital records

The San Joaquin Valley (SJV) of California has been consistently identified as having one of the highest levels of air pollution in the US. Despite federal and state standards, the SJV has been in non-attainment status for daily PM2.5 concentrations, extreme non-attainment for 8 hr O3 levels, and attainment for NO2. An epidemiological time-stratified case-crossover design was used to estimate the relationship between exposure to NO2, O3, PM2.5 and adverse health outcomes in asthma and upper respiratory infections (URIs). This study compared pollutant exposure effects for each case during limited time intervals and adjusted for seasonality. Elevated concentrations of three criteria outdoor air pollutants are associated with increased asthma and URI-related ED visits and hospitalizations in the SJV for all ages. NO2 exposure increased the odds of having an ED visit by 2.4% in lag 1 (95% CI: 1.017, 1.031). Lags 2, 3, 4, 5, 7, 9, and 14 were statistically significant. O3 modestly increased the odds of ED visits by 0.3% (95% CI:1.000, 1.006) after immediate exposure in the warm season. In the cold season, PM2.5 estimates were significant for all lags except for lags 4 and 12. The two-week lag increased the odds by 28% (95% CI:1.218, 1.345) for ED visits, and 16.5% (95% CI:1.009, 1.345) increased the odds of being hospitalized after cumulative exposure to PM2.5. Findings suggest that SJV residents experience adverse health effects due to elevated exposure to NO2 despite attainment of federal and state pollutant standards. This study provides new evidence about the effects of three criteria air pollutants and adverse health outcomes in the SJV region. The air quality regulatory and public health governing bodies should consider revisions to regional pollutant thresholds and local public health strategies to prevent adverse health outcomes during short and prolonged periods of air pollution exposure.

Implementasi Penggunaan Generalisasi Thinning Process pada Penduga Fungsi Ragam Proses Poisson Periodik Majemuk

This article implements the thinning process algorithm, which has been generalized for estimators of compound periodic Poisson processes. The use of generalizations in the algorithm has been prepared with a linear trend in the periodic elements. This research aims to discuss estimators of the variance function. The method used in this research is the simulation method. Simulation results using a generalized algorithm thinning process show that in the case of a limited observation time interval, some estimators are good enough to approach the actual value. As the value of n increases, the simulated value of the estimator moves towards the predicted value. This is following the lemmas, theorems, and consequences that have been discussed. It was also found that several estimators were quite slow. This results in the movement of the bias, variance, and MSE values of the estimators being slow, even though they are moving towards 0. So that further modifications can be made to the model being studied.

Relative error-based time-limited [formula omitted] model order reduction via oblique projection

In time-limited model order reduction, a reduced-order approximation of the original high-order model is obtained that accurately approximates the original model within the desired limited time interval. Accuracy outside that time interval is not that important. The error incurred when a reduced-order model is used as a surrogate for the original model can be quantified in absolute or relative terms to access the performance of the model reduction algorithm. The relative error is generally more meaningful than an absolute error because if the original and reduced systems’ responses are of small magnitude, the absolute error is small in magnitude as well. However, this does not necessarily mean that the reduced model is accurate. The relative error in such scenarios is useful and meaningful as it quantifies percentage error irrespective of the magnitude of the system’s response. In this paper, the necessary conditions for a local optimum of the time-limited H2 norm of the relative error system are derived. Inspired by these conditions, an oblique projection algorithm is proposed that ensures small H2-norm relative error within the desired time interval. Unlike the existing relative error-based model reduction algorithms, the proposed algorithm does not require solutions of large-scale Lyapunov and Riccati equations. The proposed algorithm is compared with time-limited balanced truncation, time-limited balanced stochastic truncation, and time-limited iterative Rational Krylov algorithm. Numerical results confirm the superiority of the proposed algorithm over these existing algorithms.

Adaptive optimal backstepping control for strict-feedback nonlinear systems with time-varying partial output constraints

This paper investigates the optimal backstepping control strategy for strict-feedback nonlinear systems subject to input saturation and time-varying partial output constraints. Compared with the existing results on output constraints, the time-varying partial output constraint is a more general constraint that can start and end at any time during the system operation, or remain unconstrained, which can be called as output constraints occurring in a limited time interval (OCOLT). A special barrier function is embedded into the optimal performance index function to satisfy the OCOLT condition under the optimal control framework, and a shift function is introduced to address the function discontinuity caused by the OCOLT problem. Then, an auxiliary system and a disturbance observer are respectively constructed to handle the influence of the input saturation and compounded disturbances. Meanwhile, the simplified reinforcement learning algorithm, employing the identifier-critic-actor architecture, is developed to achieve the optimal control objective within the framework of the backstepping technology. Moreover, the proposed optimal control method ensures the semi-globally uniformly ultimately bounded of all signals within the closed-loop system. Finally, two simulation examples are given to further prove the effectiveness of the presented optimal control approach.

ТОЧНІСТЬ КООРДИНАТ ВИЗНАЧЕННЯ МІСЦЯ СУДНА, РОЗРАХОВАНИХ МЕТОДОМ НАЙМЕНШИХ КВАДРАТІВ, ПРИ НАЯВНОСТІ НАДЛИШКОВИХ ЛІНІЙ ПОЛОЖЕННЯ

This article discusses the accuracy of the vessel’s position coordinates, calculated using the least squares method, in the presence of redundant line positions (LP) over time, assuming the LP error is normally distributed. It is stated that for a normal error distribution, the least squares method is the maximum likelihood method, thus the norm of the positional error covariance matrix is minimized, ensuring the highest accuracy of the vessel’s position coordinates. Field observation results are presented, where experimental data were obtained, demonstrating the possibility of altering navigational parameters. Following the adjustment of navigational parameters, a series of tests were conducted, exceeding 100 in total. The analysis of these results indicates that deviations in navigational parameterization, achieved over a limited time interval, conform to the normal law of variability distribution. Adjustments to the parameters over a larger interval are subject to changes in the laws of change, with the degree of power of some of the normal law proportional to the interval of the series value of the navigational parameter. It is demonstrated that the efficiency of observing the vessel’s coordinates, calculated by the least squares method during times of redundant LP, the errors of which can be calculated according to different laws, is less than one. To evaluate the efficiency of coordinate observation derived from overly large LP and gaps using the least squares method, a computer simulation was performed. During this simulation, efficiency values were compared with the highest theoretically achievable efficiency values, as outlined in the article, and the difference between them in the case of high-technological parameters was less than 22.0%. The simulations conducted showed good agreement between the efficiency assessments derived from analytical expressions and those obtained from the simulations, thereby confirming the validity of the analytical method for evaluating the efficiency of observed coordinates, calculated by the least squares method. Keywords: navigational safety, accuracy of coordinates assignment, change of law and subdivision, simulation modelling.

Optimization of the Pedagogical Process in Teaching Chemistry to First-Year Students of the Ural State Medical University

The purpose of research is to determine directions for optimizing the educational process with the introduction of new methodological approaches. For this purpose, the paper set the tasks to analyze the current methodological aspects of the component of the pedagogical process of teaching chemistry to first-year students of the medical and preventive faculty of the Ural State Medical University (USMU, Yekaterinburg); asess the impact of new methodological approaches in teaching on the performance of students. The discipline “Chemistry” is studied in the first semester, classroom hours for the discipline include lectures (32 hours), practical exercises and laboratory work (34 hours), which are conducted at the department of general chemistry of USMU.Materials and methods. The methodology for teaching chemistry to first-year students of the medical and preventive faculty of USMU (Ekaterinburg) is analyzed. The largest faculty was selected for the study. Over the course of 10 years, during the period of Federal State Educational Standard-3, the number of students at this faculty increased from two streams in the 2012-2013 academic year (300 people) up to four streams in the 2022-2023 academic year (700 people). Attestation in the discipline takes place in the form of a written test with an assessment (exam). Statistical processing of data on exam results and rating scores in the semester was carried out in the Microsoft Excel 2019 program. The obtained indexes are presented as arithmetic mean values and standard error of the mean (M±m).Results. Pearson's r-correlation coefficients were calculated to assess the linear relationship of variables: the percentage of correct answers in the exam ticket, the final student rating in the semester, the exam rating, the certification grade. To test the hypothesis about the effectiveness of the chosen teaching methodology, Pearson's test of agreement (χ2 ) was calculated for the sample size of students (n ≥ 100). The pedagogical process carried out in teaching chemistry to first-year students of the medical and preventive faculty is a complex system that includes target, content, activity, performance, resource components. The activity component of the organization of the pedagogical process was modified as follows: a new form of the examination card was developed, as close as possible to the form of control materials for the unified state exam in chemistry, the structure of the practical lesson was rationalized, and a new laboratory workshop was created and tested. The results of the exam in chemistry were analyzed using Pearson's goodness-of-fit test at a significance level of p<0, 05 in two groups of questions: 1 - on topics covered by a laboratory workshop and 2 - on topics not provided with laboratory work. The rating indexes of students when performing tasks related to the first group of questions are significantly higher than in the second group. ><0,05 in two groups of questions: 1 - on topics covered by a laboratory workshop and 2 - on topics not provided with laboratory work. The rating indexes of students when performing tasks related to the first group of questions are significantly higher than in the second group.Conclusion. When using an optimized laboratory practice in chemistry, the most rational form of the lesson is chosen, in which laboratory experiments are included. Comprehensive planning of such classes is carried out differently. The didactic tasks of the lesson are subordinated to highlighting what is essential in the content of the educational material. The presence of an optimized workshop significantly contributes to the choice of the most effective methods and forms of training for a given lesson, leading to an increase in student performance. It is shown that the updated form of the laboratory workshop in chemistry, along with the rationalization of the structure of the lesson and the form of the exam make it possible to achieve maximum learning outcomes with a limited time interval for classroom work. The new form of the examination card, along with the modernized practicum, contributed to the high marks in the exam. It is shown that a properly organized form of passing the exam allows you to adjust the progress of each student and set an objective assessment in chemistry.

Neural oscillations reflect the individual differences in the temporal perception of audiovisual speech.

Multisensory integration occurs within a limited time interval between multimodal stimuli. Multisensory temporal perception varies widely among individuals and involves perceptual synchrony and temporal sensitivity processes. Previous studies explored the neural mechanisms of individual differences for beep-flash stimuli, whereas there was no study for speech. In this study, 28 subjects (16 male) performed an audiovisual speech/ba/simultaneity judgment task while recording their electroencephalography. We examined the relationship between prestimulus neural oscillations (i.e. the pre-pronunciation movement-related oscillations) and temporal perception. The perceptual synchrony was quantified using the Point of Subjective Simultaneity and temporal sensitivity using the Temporal Binding Window. Our results revealed dissociated neural mechanisms for individual differences in Temporal Binding Window and Point of Subjective Simultaneity. The frontocentral delta power, reflecting top-down attention control, is positively related to the magnitude of individual auditory leading Temporal Binding Windows (auditory Temporal Binding Windows; LTBWs), whereas the parieto-occipital theta power, indexing bottom-up visual temporal attention specific to speech, is negatively associated with the magnitude of individual visual leading Temporal Binding Windows (visual Temporal Binding Windows; RTBWs). In addition, increased left frontal and bilateral temporoparietal occipital alpha power, reflecting general attentional states, is associated with increased Points of Subjective Simultaneity. Strengthening attention abilities might improve the audiovisual temporal perception of speech and further impact speech integration.

Matching intraoperative teaching and learning for medical undergraduates via modified briefing-intraoperative teaching-debriefing (BID) model

Intraoperative teaching is a challenging task. The briefing–intraoperative teaching–debriefing (BID) model, which is based on guided discovery learning at limited time intervals, has rarely been investigated. This study validated the benefits of the modified BID model on medical clerks. This study involved 37 first-year medical clerks enrolled from September 2019 to May 2020. Every learner scrubbed in one the totally implantable venous access device placement surgery and completed a pre-/posttest survey on surgical procedures and associated anatomy conducted through an intraoperative teaching questionnaire. Of these participants, 15 merely observed throughout the entire procedure (observation group), whereas the remaining 22 performed simple suturing under supervision (suturing group). All participants underwent an objective structured assessment of simple interrupted suturing skills at the end of the observership. Correlations were tested using a two‐tailed paired t-test, with a p-value < 0.05 indicating statistical significance. The response rate was 100% and participants could reconfirm the precise venous access, catheter tip location, and suture materials for portal fixation after totally implantable venous access device placement (p < 0.05). Although a relatively higher satisfaction of the intraoperative teaching environment and educator attitude was reported in the suturing group than in the observation group, the difference in scores on the objective structured assessment was not statistically significant (8.7 ± 1.8 vs. 7.2 ± 3.7; p = 0.104). Our findings indicate that the modified BID model with hands-on experience is a practicable module for matching intraoperative teaching and learning via learning perception enhancement for medical undergraduates during totally implantable venous access device placement.

VR Traffic Dataset on Broad Range of End-User Activities

With the emergence of new internet traffic types in modern transport networks, it has become critical for service providers to understand the structure of that traffic and predict peaks of that load for planning infrastructure expansion. Several studies have investigated traffic parameters for Virtual Reality (VR) applications. Still, most of them test only a partial range of user activities during a limited time interval. This work creates a dataset of captures from a broader spectrum of VR activities performed with a Meta Quest 2 headset, with the duration of each real residential user session recorded for at least half an hour. Newly collected data helped show that some gaming VR traffic activities have a high share of uplink traffic and require symmetric user links. Also, we have figured out that the gaming phase of the overall gameplay is more sensitive to the channel resources reduction than the higher bitrate game launch phase. Hence, we recommend it as a source of traffic distribution for channel sizing model creation. From the gaming phase, capture intervals of more than 100 s contain the most representative information for modeling activity.

Fully Dynamic Online Selection through Online Contention Resolution Schemes

We study fully dynamic online selection problems in an adversarial/stochastic setting that includes Bayesian online selection, prophet inequalities, posted price mechanisms, and stochastic probing problems subject to combinatorial constraints. In the classical ``incremental'' version of the problem, selected elements remain active until the end of the input sequence. On the other hand, in the fully dynamic version of the problem, elements stay active for a limited time interval, and then leave. This models, for example, the online matching of tasks to workers with task/worker-dependent working times, and sequential posted pricing of perishable goods. A successful approach to online selection problems in the adversarial setting is given by the notion of Online Contention Resolution Scheme (OCRS), that uses a priori information to formulate a linear relaxation of the underlying optimization problem, whose optimal fractional solution is rounded online for any adversarial order of the input sequence. Our main contribution is providing a general method for constructing an OCRS for fully dynamic online selection problems. Then, we show how to employ such OCRS to construct no-regret algorithms in a partial information model with semi-bandit feedback and adversarial inputs.

Adaptive Tracking Control With Global Performance for Output-Constrained MIMO Nonlinear Systems

In this paper, a novel adaptive tracking control technique is developed for multiple-input-multiple-output (MIMO) nonlinear systems with model uncertainty and under output constraints occurring in a limited time interval (OCOLT). The OCOLT, which is a type of constraints occurring some time after (rather than from the beginning of) system operation and with limited duration, can be found in many practical systems and has not been effectively addressed in the literature up to now. By designing a new shift function and with the aid of barrier functions, the constrained system is transformed into an unconstrained one. A new disturbance observer then is designed to estimate unknown disturbances. The resultant control method is able to not only address the OCOLT, but also deal with the constraint-free output case and the infinite-time constrained one (i.e., constraints existing for all <inline-formula><tex-math notation="LaTeX">$t\geq 0$</tex-math></inline-formula>) without the need to revise the control structure. Finally, The effectiveness of the proposed technique is assessed in simulation.

Application of a Blockchain Model in the Energy Market for Social Goodness: A Simulator to Generate Transactions

An application of blockchain technology to manage electricity flows in a Microgrid (MG) is studied. The grid is considered for civil use, equipped with generation and storage systems, and interfaced with the national grid. It is composed of energy nodes such as user, generator, accumulator, and customs officer node, each characterized by its own time profile, in a limited time interval, of energy flow (consumption, generation, charge/discharge, purchase/sold). The proposed management strategy is based on the principle of free trade managed through blockchain. A simulation tool is developed to evaluate the electricity flows for different scenarios. The blockchain of energy transactions is generated by means of a dedicated software and having as reference a set of ethical/economical rules. It is demonstrated that it is possible to design energy management and exchange systems that allow in an economic way, within the delicate balance between energy availability, technology, market, safety, freedom and needs of individual users, to optimize the exchange of resources and to decrease waste. This blockchain exchange strategy can be implemented without building new plants and avoiding expensive and complex systems, by installing only bidirectional meters equipped with telecommunication, in addition to a common computer management system. The aim of this work is to demonstrate importance and technical feasibility of enforcing rules on the correct use of energy. The peer-to-peer operating mode is different from the technique currently in force in conventional energy systems, in which always a control body (energy, economic, financial) supervises and manages any transaction between users.

Near-optimal interpolation-based time-limited model order reduction

This paper presents an interpolatory framework for model order reduction of linear time-invariant (LTI) systems over limited time intervals of the form , with . We give a new proof for deriving interpolation-based first-order necessary conditions for time-limited optimality. Based on these optimality conditions, we propose a time-limited rational Krylov framework for time-limited rational interpolation. The interpolatory framework is used to present an iterative algorithm that yields reduced-order models satisfying the optimality conditions approximately. The distance to optimality is quantified in terms of the interpolation errors. The errors depend primarily on the interpolating model's poles and the time interval size. We test the proposed algorithm in three numerical examples and compare its performance with various time-limited model reduction algorithms available in the literature.

Team Competition in Informatics and Mathematics “Cēsis”

Team competition in informatics and mathematics for high-school students “Cēsis” still is a rare competition where usage of Internet resources is allowed. Internet availability puts additional requirements for competition tasks. We give a brief overview of used task types together with task examples. Fast and accurate evaluation and grading of solutions to non-standard tasks in a limited time interval is challenging, and automated evaluation tools used at the competition are described.

Advances in high-voltage supercapacitors for energy storage systems: materials and electrolyte tailoring to implementation.

To achieve a zero-carbon-emission society, it is essential to increase the use of clean and renewable energy. Yet, renewable energy resources present constraints in terms of geographical locations and limited time intervals for energy generation. Therefore, there is a surging demand for developing high-performance energy storage systems (ESSs) to effectively store the energy during the peak time and use the energy during the trough period. To this end, supercapacitors hold great promise as short-term ESSs for rapid power recovery or frequency regulation to improve the quality and reliability of power supply. In particular, the electrical double layer capacitor (EDLC) which offers long and stable cycle retention, high power densities, and fast charge/discharge characteristics with a moderate operating voltage window, is a suitable candidate. Yet, for implementation of the EDLC in ESSs, further research effort is required in terms of increasing the operating voltage and energy densities while maintaining the long-term cycle stability and power densities which are desirable aspects for ESS operation. Here, we examine the advances in EDLC research to achieve a high operating voltage window along with high energy densities, covering from materials and electrolytes to long-term device perspectives for next-generation supercapacitor-based ESSs.