Fixed Time Interval Research Articles

Parameterizing Haverkamp Model From the Steady‐State of Numerically Generated Infiltration: Influence of Algorithms for Steady‐State Selection

ABSTRACTBEST (Beerkan Estimation of Soil Transfer parameters) methods of soil hydraulic characterisation are widely applied for estimating sorptivity, S, and saturated hydraulic conductivity, Ks. Calculating these properties requires choosing the β and γ parameters of the Haverkamp infiltration model. These parameters can be obtained from numerically simulated three‐dimensional (3D) infiltration runs reaching steady‐state. This investigation tested dependence of the estimated β and γ parameters on the algorithm for steady‐state selection using simulated 3D cumulative infiltrations for different soils and initial conditions. Two algorithms used the original simulation outputs and included using (i) a threshold defining steadiness (T‐algorithm) and (ii) the last four data points, yielding a reference value of steady‐state infiltration rate (R‐algorithm). A third algorithm, similar to the R‐algorithm, was applied to previously re‐sampled infiltration data at fixed time intervals (RR‐algorithm). The intercept, bs, of the straight line fitted to the data describing steady‐state on the cumulative infiltration plot depended on the applied algorithm more than the slope of this line. Consequently, β varied with the applied algorithm more than γ. The RR‐algorithm, yielding 0.62 ≤ β ≤ 1.99 and 0.74 ≤ γ ≤ 0.98, was preferred since it mediated between advantages and disadvantages of T‐ and R‐algorithms. The influence of the choice of proper values for β and γ on the estimates of S and Ks was evaluated using BEST. Using the default values of β (0.6) and γ (0.75) yielded accurate estimates of S but not of Ks. Soil dependent β and γ values should be used in this case. A check of the reliability of the estimates of bs can be made by a sequential analysis of the cumulative infiltration data. Future developments include considering sources differing in size and establishing if the suggested β and γ values apply in general to the available BEST algorithms.

Condition-based maintenance for multi-component systems: A scalable optimization model with two thresholds

Many original equipment manufacturers (OEMs) provide customized after-sales service contracts tailored to their customers’ specific requirements. While these customized offerings may increase customer satisfaction and loyalty, they are likely more expensive, and that in times that OEMs are striving to reduce maintenance costs and ease the workload of their service engineers. To address this challenge, we introduce a quantitative methodology for shaping maintenance policies that minimize overall maintenance costs for systems comprising multiple heterogeneous components over a finite lifespan. Our proposed two-threshold condition-based maintenance policy incorporates scheduled visits and semi-urgent interventions, using component-level control thresholds to preventively trigger component replacements. Scheduled visits provide opportunities for grouping component replacements, capitalizing on positive economic dependencies.Our optimization model and solution methodology are tailored to systems consisting of numerous components. We assume a fixed time interval between consecutive scheduled visits, allowing us to employ a decomposition approach that ensures model scalability. The optimal policy for each component is determined by formulating a single-unit replacement model as a finite horizon Markov Decision Problem solved via dynamic programming. Simultaneously, at system level, we optimize the maintenance interval for the entire system using an iterative approach.The results of our case study highlight that complementing scheduled visits with semi-urgent interventions - both triggering preventive replacements - leads to a reduction in the volume of corrective maintenance. From a practical standpoint, our findings offer valuable insights for OEMs seeking to enhance their after-sales service contracts while concurrently reducing maintenance-related costs. Specifically, our model is particularly valuable for OEMs that service systems with high shutdown costs, rely heavily on customer satisfaction, and favor more attractive policies for their service engineers (i.e., reducing the number of emergency corrective interventions).

Reaction-diffusion for fish populations with realistic mobility

Nonlinear reaction-diffusion equations, with Fisher logistic growth and constant diffusion coefficient, have been used in fisheries research to estimate sustainable harvesting rates and critical domain sizes of no-take areas. However, constant diffusivity in a population density corresponds to standard Brownian motion of individuals, with a normal distribution for displacement over a fixed time interval. For available good data sets on mobile fish populations, the distribution is certainly not normal. The data can be fitted with a long-tailed stable Lévy distribution that results from diffusion by fractional Laplacian. Exact multidimensional solutions are developed here for realistic Fisher–Kolmogorov–Petrovski-Piscounov models with diffusion by fractional Laplacian. These can also account for a delay in the reaction term. It is then shown how to modify critical domain sizes of protected areas with Dirichlet and Robin boundary conditions for populations.

Group Response-Adaptive Randomization With Delayed and Missing Responses.

Response-adaptive randomization (RAR) procedures have been extensively studied in the literature, but most of the procedures rely on updating therandomization after each response, which is impractical in many clinical trials. In this article, we propose a new family of RAR procedures that dynamically update based on the responses of a group of individuals, either when available or at fixed time intervals (weekly or biweekly). We show that the proposed design retains the essential theoretical properties of Hu and Zhang's doubly adaptive biased coin designs (DBCD), and performs well in scenarios involving delayed and randomly missing responses. Numerical studies have been conducted to demonstrate that the new proposed group doubly adaptive biased coin design has similar properties to the Hu and Zhang's DBCDs in different situations. We also apply the new design to a real clinical trial, highlighting its advantages and practicality. Our findings open the door to studying the properties of other group response adaptive designs, such as urn models, and facilitate the application of response-adaptive randomized clinical trials in practice.

Make or Break: The Influence of Expected Challenges and Rewards on the Motivation and Experience Associated with Cognitive Effort Exertion.

Challenging goals can induce harder work but also greater stress, in turn potentially undermining goal achievement. We sought to examine how mental effort and subjective experiences thereof interact as a function of the challenge level and the size of the incentives at stake. Participants performed a task that rewarded individual units of effort investment (correctly performed Stroop trials) but only if they met a threshold number of correct trials within a fixed time interval (challenge level). We varied this challenge level (Study 1, n = 40) and the rewards at stake (Study 2, n = 79) and measured variability in task performance and self-reported affect across task intervals. Greater challenge and higher rewards facilitated greater effort investment but also induced greater stress, whereas higher rewards (and lower challenge) simultaneously induced greater positive affect. Within intervals, we observed an initial speed up then slowdown in performance, which could reflect dynamic reconfiguration of control. Collectively, these findings further our understanding of the influence of task demands and incentives on mental effort exertion and well-being.

Estimation-based event-triggered fixed-time fuzzy tracking control for high-order nonlinear systems

This paper investigates adaptive-estimation-based dynamic event-triggered fuzzy tracking control scheme for high-order nonlinear systems in fixed-time interval. The growing assumptions of coexistence unknown nonlinear uncertainties are removed with the aid of fuzzy logic systems. Contrary to the existing results, an adaptive estimation tactic is formulated to estimate the severe coexistence uncertainties online such that no boundaries are needed for the adaptive parameters, despite approximation errors, unknown virtual control gains and time-varying disturbances. On this estimation mechanism, the virtual control gains have been relaxed to unknown, which is more applicable. In view of controller and actuator, the communication burden is reduced with the aid of dynamic event-triggered rule, and Zeno behavior can be prevented successfully during dynamic sampling and updating of the control signal. Moreover, the singularity problem has been conquered by using the inequality transformation technique and all signals are bounded in fixed-time interval. Finally, two examples are used to verify the feasibility and rationality.

Make or break: The influence of expected challenges and rewards on the motivation and experience associated with cognitive effort exertion.

Challenging goals can induce harder work but also greater stress, in turn potentially undermining goal achievement. We sought to examine how mental effort and subjective experiences thereof interact as a function of challenge level and the size of the incentives at stake. Participants performed a task that rewarded individual units of effort investment (correctly performed Stroop trials) but only if they met a threshold number of correct trials within a fixed time interval (challenge level). We varied this challenge level (Study 1, N = 40), and the rewards at stake (Study 2, N = 79), and measured variability in task performance and self-reported affect across task intervals. Greater challenge and higher rewards facilitated greater effort investment but also induced greater stress, while higher rewards (and lower challenge) simultaneously induced greater positive affect. Within intervals, we observed an initial speed up then slowdown in performance, which could reflect dynamic reconfiguration of control. Collectively, these findings further our understanding of the influence of task demands and incentives on mental effort exertion and wellbeing.

An Insight into Practices Associated with the Control of Internal Parasites in the Dairy Goat Herds of Romania: A Questionnaire Survey.

The widespread and uncontrolled use of anthelmintic products has contributed to the emergence of anthelmintic resistance (AR). This phenomenon globally threatens the productivity and welfare of small ruminants. A questionnaire consisting of 34 questions was handed to 234 goat farmers across Romania to gain insight into control practices against internal parasites and the farmers' perception of the parasitic infections present in their herds and the efficacy of anthelmintic treatments. The majority of farmers (88.5%) admitted they had never submitted fecal samples for parasitological laboratory analysis, and 77.4% had treated the animals on their own. In general, the farmers dewormed their goats based on visual body weight estimation. Prophylactic anthelmintic treatment was practiced by more than 85% of the farmers. A traditional control approach based on treating the entire herd at fixed time intervals is widespread among Romanian goat and sheep farmers. The most commonly used anthelmintic drugs in the previous 3 years (2021-2023) were benzimidazoles (85.5%) and macrocyclic lactones (81.6%). Poor anthelmintic efficacy was suspected by 14.5% of farmers, and the minority (18.0%) considered internal parasites as a problem in their herds. Regarding the farmers' perception of the presence of parasites, there was a significant level of uncertainty. This is the first survey carried out in Romanian goat herds, and it provides up-to-date information on practices aimed at controlling internal parasites.

Video stalling identification for web live streaming under HTTP-FLV

Live broadcasts have become one of the most popular forms of entertainment. Quality of user Experience (QoE) is a vital quantitative criterion for evaluating user satisfaction while watching live broadcasts, and it is positively correlated with the increase in the income of Internet Service Providers (ISPs). Video stalling identification plays a crucial role in the evaluation of QoE. However, encrypted live streaming hides video content, which makes identifying video stalling challenging. Existing studies primarily detect video stalling in a fixed time interval and focus on high-dimensional features. However, the capacity of the client byte buffer is dynamic, resulting in the stalling and non-stalling existing in a certain and fixed stalling time. In addition, the handling time of abundant features causes further latency. We propose Truncation of Dynamic Bytes and non-linear Integrated Modification based on Double Buffers (DB2) to identify video stalling under HTTP-FLV protocol in various network conditions and live types. We pull real-time video to get client buffer parameters and build a dynamic mapping based on the double buffer between network packets and the video playing states. This allows a more objective and precise evaluation of video stalling. We design a new network feature by creating a non-linear relationship between network packets and the client buffer. This is achieved by combining non-linear convergent distribution with basic traffic features. The feature is fed into a lightweight machine learning model to train the classifier, achieving low processing latency and high identification accuracy. The experimental results show that DB2 can achieve 98.91% stalling identification accuracy with 1.256 ms operation time in a mixture of live video types, outperforming state-of-the-art techniques.

To assess the effect of selected locally available beverages on salivary pH, flow rate, and oral clearance rate among adults

Aim: The aim of this study is to assess the effect of selected locally available beverages on salivary pH, flow rate, and oral clearance rate among adults. Materials and Methods: A quantitative diagnostic method for dental caries would improve oral health, which directly affects the quality of life. The pH scale measures how acidic or basic a solution is, with 7 being neutral. When the pH of plaque drops below normal, or <5.5, the acidity starts to dissolve minerals and destroy the tooth’s enamel. This clinical trial will be conducted on 40 subjects. Test beverages will be Red Bull, mixed fruit juice, tea, and sweetened milk. Unstimulated salivary samples will be collected for each study subject at least 1 h after their breakfast. After the collection of baseline salivary samples, the subjects will be given one beverage to drink, and then stimulated saliva samples will be collected at fixed time intervals. A digital pH meter will be used to measure the pH at every step. Statistical Analysis: This will be carried out using SPSS version 17, one-way ANOVA, and post hoc Tukey’s test will be applied in the statistical tests. Results: The maximum drop in pH was seen in the case of carbonated beverage (Red Bull), the oral clearance for all the liquid food items was achieved at 14 minutes. Conclusions: Liquids had a considerable cariogenic and erosive potential despite their quick clearance from the mouth cavity. it is always recommended to limit beverage consumption to maintain good dental health.

Early mitigation of CPU-optimized ransomware using monitoring encryption instructions

Ransomware attacks pose a significant threat to information systems. Server hosts, including cloud infrastructure as a service, are prime targets for ransomware developers. To address this, security mechanisms, such as antivirus software, have proven effective. Moreover, research on ransomware detection advocates for behavior-based finding mechanisms while ransomware is in operation. In response to evolving detections, ransomware developers are now adapting an optimized design tailored for CPU architecture (CPU-optimized ransomware). This variant can rapidly encrypt files, potentially evading detection by traditional antivirus methods that rely on fixed time intervals for file scans. In ransomware detection research, numerous files can be encrypted by CPU-optimized ransomware until malicious activity is detected. This study proposes an early mitigation mechanism named CryptoSniffer, which is designed specifically to counter CPU-optimized ransomware attacks on server hosts. CryptoSniffer focuses on the misuse of CPU architecture-specific encryption instructions for swift file encryption by CPU-optimized ransomware. This can be achieved by capturing the ciphertext in user processes and thwarting file encryption by scrutinizing the content intended for writing. To demonstrate the efficacy of CryptoSniffer, the mechanism was implemented in the latest Linux kernel, and its security and performance were systematically evaluated. The experimental results demonstrate that CryptoSniffer successfully prevents real-world CPU-optimized ransomware, and the performance overhead is well-suited for practical applications.

Fixed‐time adaptive event‐triggered fault‐tolerant control of nonlinear systems with actuator failures

AbstractThe problem of fixed‐time adaptive event‐triggered fault‐tolerant control (FTC) is investigated for a class of nonlinear systems with actuator failures in this paper. Firstly, by utilizing back‐stepping algorithm and the fixed‐time stable criterion, a novel fixed‐time adaptive fault‐tolerant controller and parameter updated laws in forms of nonlinear differential equations are developed to counteract actuator faults and parameter uncertainties in fixed time. Then, the event‐triggered mechanism based on the relative threshold method is applied to the proposed control scheme to save network resources. Furthermore, by the Lyapunov stability theory, it can be proven that all the closed‐loop signals of system remain bounded, and the tracking error converges into a small neighborhood of the origin within fixed time interval. Finally, the simulation examples are shown to verify the feasibility and efficiency of the presented strategy.

Global–local spatio-temporal graph convolutional networks for video summarization

Video summarization aims to create concise and accurate summary to enable users to quickly grasp the key content of the original video for facilitating efficient video browsing. Most existing video summarization methods mainly employ recurrent neural networks to capture long-term dependencies in videos, yielding remarkable results. Nevertheless, these methods overlook the potential spatial features inside the video when modeling the video. To tackle this issue, we introduce a global–local spatio-temporal graph convolutional networks for video summarization (GL-STGCN). Initially inspired by the concept of 3-D convolution, we segment the video into non-overlapping segments to capture localized spatial features of sequential frames. Subsequently, a spatial graph is constructed for each segment, with a fixed time interval between neighboring spatial graphs. Then we use the pooling method to randomly delete the redundant nodes in the graph. We then leverage a temporal gating convolutional network to extract the global temporal relationships within the video. Employing the spatial features, a spatial graph convolutional network is utilized to capture the spatial connections among frames. As the graph node information evolves, the node features furnish a more precise depiction of the video content. Consequently, we employ the temporal gating convolutional network once more to refine the global temporal relations within the video. Extensive experiments on two public datasets are conducted in this paper, showing that our proposed method outperforms most state-of-the-art video summarization methods in terms of performance. Experimental results demonstrate the effectiveness of integrating global temporal and local spatial relationships.

Risk prediction model for gastric cancer within 5 years in healthy Korean adults.

Although endoscopy is commonly used for gastric cancer screening in South Korea, predictive models that integrate endoscopy results are scarce. We aimed to develop a 5-year gastric cancer risk prediction model using endoscopy results as a predictor. We developed a predictive model using the cohort data of the Kangbuk Samsung Health Study from 2011 to 2019. Among the 260,407 participants aged ≥20years who did not have any previous history of cancer, 435 cases of gastric cancer were observed. A Cox proportional hazard regression model was used to evaluate the predictors and calculate the 5-year risk of gastric cancer. Harrell's C-statistics and Nam-D'Agostino χ2 test were used to measure the quality of discrimination and calibration ability, respectively. We included age, sex, smoking status, alcohol consumption, family history of cancer, and previous results for endoscopy in the risk prediction model. This model showed sufficient discrimination ability [development cohort: C-Statistics: 0.800, 95% confidence interval (CI) 0.770-0.829; validation cohort: C-Statistics: 0.799, 95% CI 0.743-0.856]. It also performed well with effective calibration (development cohort: χ2=13.65, P=0.135; validation cohort: χ2=15.57, P=0.056). Our prediction model, including young adults, showed good discrimination and calibration. Furthermore, this model considered a fixed time interval of 5years to predict the risk of developing gastric cancer, considering endoscopic results. Thus, it could be clinically useful, especially for adults with endoscopic results.

Verification of the person’s dynamic signature on a limited number of samples

Objectives. The goal of the research is to develop a new person-dependent method for verification of a signature of one person made on a tablet with a stylus in the presence of a limited number of signature samples of this person.Methods. The paper shows how to construct an individual pattern of the dynamic signatures of any person, which is described by points in a multidimensional feature space and is intended for subsequent verification of the authenticity of the signatures of a given person. It is constructed using 5<N<20 samples of genuine human signatures. The pattern forms a convex object in a multidimensional feature space. It describes the peculiar properties of a signature performed by a specific person.Results . The dynamics of signature execution is represented by three discrete parametric functions: coordinates of the stylus X, Y and its pressure on the tablet P, recorded at fixed time intervals. In the process of research, a number of secondary functions-features were selected and calculated from them. Since these data sets have different lengths, the dynamic time warping algorithm is used to compare them. The results of this transformation are distances between the dynamic features of two signatures, which serve as coordinates of a point in the feature space that describes the similarity of these signatures. The set of such points describes similarity of all pairs of genuine human signatures presented for verification in a multidimensional feature space. The convex hull of the cloud of these points is used as a pattern of a particular person's signature. The genuine signatures of any person are always different from each other; significant differences between them can distort the verification result.Conclusion. Experimental studies performed on genuine and fake signatures of 498 people from the largest available database of dynamic signatures, DeepSignDB, showed a verification accuracy of about 98 % when analyzing 24,900 signatures. Half of them are genuine, half are fake

Assessment of atmospheric corrosivity based on exposure of concrete airfield pavement samples

Many research areas focus on atmospheric corrosion based on the exposure of material samples, monitoring them periodically, and determining their size at fixed time intervals. The article presents an innovative approach to the atmospheric corrosion affecting the pavement, specifically the cement concrete samples. Tests in natural conditions involve the corrosion resistance assessment of specially prepared samples of the tested material in natural atmospheric conditions at a given airport facility. The manuscript proposes an atmospheric corrosion assessment method.

Study of Two Different Field Measurement Methods of Infiltration: Falling Head and Constant Head, at Various Hydraulic Head

Two field measurement of infiltration rate methods had been performed on Latosol (Oxic dystrudept) Dramaga Bogor in order to investigate the opportunity to generate different result due to the different of hydraulic head applied and the different way of water was supplied. They were constant head and falling head methods. Falling head method was done in two different ways, namely within a certain time interval and within a certain water level interval. Hydraulic head used during measurement were of 10 cm, 15 cm, and 20 cm. The falling head and constant head method, clearly, generated different minimum infiltration rate values The falling head method measured on a fixed time interval generated almost the same values of minimum infiltration rate, respectively of 4.8 cm hour -1, 5.5 cm hour -1, and 4.8 cm hour -1 at 10 cm, 15 cm, and 20 cm hydraulic head. The falling head method based on bulk water level interval at 10 cm, 15 cm, and 20 cm generated minimum infiltration rate values respectively of 13.2 cm/hour, 12.8 cm/hour, and 18.8 cm/hour. The constant head method at 10 cm, 15 cm, and 20 cm hydraulic head generated minimum infiltration rate values respectively of 11.0 cm/hour, 18.5 cm/hour, and 19.0 cm/hour. The values were higher than of the fixed time interval based falling head method. Infiltration field measurement using the falling head method either based on time interval or water level interval did not show an increasing trend of minimum infiltration rate values due to the increase of hydraulic head. However, the infiltration field measurement using constant head showed an increasing trend of the minimum infiltration rate values due to the increase of hydraulic head.

Degradation Processes of Two Compound Layers on Nitrided Surfaces During the Wear Test by “Block on Hot Al Cylinder”

The results obtained in the study help to explain the degradation process of the nitrided steel compound layer. Compound layers with different properties on gas-nitrided H10 tool steel blocks were tested for wear with “block on hot Al cylinder”. Degradation processes were observed on both compound layers with different properties and at three contact pressures. In order to observe the degradation processes in the compound layers, the wear tests were interrupted at various fixed time intervals and the resulting changes were closely monitored. The comprehensive analysis highlighted the complexity of the degradation process in the compound layers and emphasized the existence of complex relationships between the above-mentioned parameters. The reaction of the nitrided steel surface with hot Al is more pronounced in areas with lower contact pressure, while adhesive removal and furrow formation are pronounced in areas with low and medium contact pressure. This process begins with a sufficient density of the areas where islands of adhesive removal are located, their enlargement during the test, the breaking up of the walls between them, and finally the removal of the compound layer in the sliding direction, which appears as furrowing in the final phase of wear.

Equation-free data-driven synchronization of rod-type plasma torch systems with a Koopman approach

This study explores equation-free data-driven synchronization of a rod-type plasma torch by employing the Koopman approach. In the data-driven methodology, we systematically extract information from driving-driven systems at fixed time intervals within a specific range. Utilizing the data, the Koopman operator is applied to attain observables for both driving and driven systems. Parameter estimation is employed to construct a flexible model capable of capturing subtle changes. The error system is derived from these models, and parameter optimization is performed to achieve synchronization. Leveraging Julia packages, system synchronization is achieved by dynamically controlling parameters, providing insights without relying on explicit equations.

Effect of polymerisation protocols on water sorption, solubility and hygroscopic expansion of fast-cure bulk-fill composite

ObjectiveThis study examines the effect of two light-curing protocols from a LED polywave light curing unit (LCU) on water sorption, solubility, and hygroscopic expansion of fast and conventional bulk-fill resin-based composites (RBCs) aged in distilled water for 120 d. MethodsThree bulk-fill RBCs materials were studied: Tetric PowerFill® (fast photo-polymerised composite) (TPF), Tetric EvoCeram bulk-fill (EVO), and GrandioSo x-tra bulk-fill (GSO) (conventional photo-polymerised composites). Specimens were prepared within a 3D-printed resin mold (8-mm diameter x 4-mm height) and light-cured from one side only with 2 modes of polywave LCU (Bluephase® PowerCure): 3 s mode and for 20 s in “Standard” mode. Water sorption and solubility were measured at fixed time intervals for 120 d of distilled water storage, then reconditioned to dry to measure desorption for 75 d, all at 37 ± 1 °C. Hygroscopic (volumetric) expansion was recorded at the same time intervals up to 120 d. Data were analysed through SPSS using Two-way ANOVA, One-way ANOVA, independent t-tests, and Tukey’s post-hoc correction tests (p < 0.05). ResultsTPF, when irradiated for 3 s demonstrated minimal water sorption (0.83%), solubility (1.01 μg/mm3), and least volumetric expansion (1.64%) compared to EVO and GSO. While EVO showed the highest water sorption (1.03%) and solubility (1.95 μg/mm3) at 3 s. GSO had the lowest sorption (0.67%) and (0.56%) in 3 s and 20 s protocols, respectively. Nevertheless, all the sorption and solubility data were within the ISO 4049 limits. SignificanceFor TPF, fast (3 s) polymerisation did not increase either water sorption or solubility, compared with 20 s irradiation. However, with the two comparative bulk-fill composites, fast cure increased water sorption by 15–25% and more than doubled solubility. These findings were consistent with the lesser volumetric expansions observed for Tetric PowerFill at both the fast and standard protocols, indicating its relative stability across polymerisation protocols.