Update Interval Research Articles

DATA INVESTIGATION OF PK-LQP AIRPLANE VERTICAL DEVIATION USING CLASS 1 AND TIER 1 DATASETS

The vertical deviation is one of the important stages in commercial aircraft flights because indications of malfunction can be detected faster by the pilot rather than in other flight phases. The purpose of this study is to investigate whether the PK-LQP airplane experienced unusual altitude movements during the vertical deviation phase since the airplane taking off from Seattle (Boeing Manufacture's home base) until the airplane crash. The airplane, which is of the type B737 MAX8, had operated for 83 days, during which it completed 438 flights using a total of 107 flight codes, and it travelled to 36 airports. According to the findings of an investigation of the data, we found that only 69 (39%) were included in tier 1, which had an ADS-B data update interval message below 10 seconds, complying with ICAO and FAA-AVN standards. With this class 1 and tier 1 dataset, we conducted an EDA to find the data insight, which revealed that there was a disturbance in the speed and altitude indications on the airplane instrumentation, causing a misperception for the pilot and causing the airplane to drastically drop in altitude (more than 100 feet).

Intelligent algorithm selection for efficient update predictions in social media feeds

Efficiently synchronizing data with social media feeds while minimizing unnecessary requests presents a significant challenge in various fields. This paper investigates prediction algorithms for determining the optimal update intervals for Facebook and Twitter (now X) feeds, focusing on metrics such as delay (the time between a post’s publication and its retrieval) and requests per post. Variations in update intervals result in different algorithms producing varying results, making the selection of the most suitable algorithm for each feed crucial yet time-intensive. To address this, we propose three strategies for algorithm selection: baseline (applying a single algorithm to all feeds), optimum (identifying the best algorithm for each individual feed), and classification (selecting algorithms through a classification process based on each feed’s unique update patterns and context). Our strategies leverage various prediction algorithms, including static and adaptive algorithms, and inhomogeneous Poisson processes. We evaluate these strategies using real-world data from Facebook and Twitter, thoroughly assessing their performance in terms of delay and request efficiency. The findings demonstrate that the strategy Optimum effectively identifies the best algorithms for each feed, ensuring the highest prediction quality, though at a considerable computational cost. On the other hand, the strategy Classification offers superior runtime performance required to select algorithms. This research highlights the trade-offs between delay and request efficiency and presents a comprehensive solution for optimizing update predictions in social media feeds.

Select Venous Analytes and Fibrinogen Determination Using Two Methods in Brown Pelicans.

The brown pelican (Pelecanus occidentalis) is a species often affected by natural and man-made disasters such as hurricanes and oil spills, as well as general human activities; that subsequently receives medical care and rehabilitation. During rehabilitation, blood may be collected for various tests to help with diagnosis, treatment, and monitoring. Reference intervals for this species are limited, dated, and typically from small sample sizes. Seventy-one presumed healthy brown pelicans were sampled as part of their pre-release examination from rehabilitation at the Wildlife Center of Texas after a large volume stranding from December 2014 to January 2015, and various venous analytes were measured to establish updated reference intervals for brown pelicans. Fibrinogen was measured via heat precipitation and the Abaxis VSPro equine fibrinogen cartridge to determine reference intervals and in an attempt to validate the VSPro for use in avian species. Abaxis VS2 Avian/Reptile Chemistry panel, iSTAT CG4+, and iSTAT Chem8+ results, in addition to body condition score, spun PCV, cloacal temperature, and fibrinogen were measured. Proposed reference intervals for brown pelicans are presented. Fibrinogen results were not comparable between the gold standard method and the VSPro, indicating that the VSPro is not appropriate for use in brown pelicans.

Invariance-based control for cyber-physical electrical distribution grids

Voltage control in low-voltage distribution grids gain importance due to integration of renewable energies and introduction of smart grids. However, the presence of disturbances and communication non-idealities make the problem hard to solve. In addition, lack of integration of converter-based devices caused non-controllability of the grid. In this paper, an updated invariance-based control approach is presented to address these shortcomings. The updated version of the invariance method addresses the non-controllability of the system. In addition, the control approach is discussed in a hybrid formalism in which the long update intervals of the communications are considered. Finally, results show the effectiveness of the approach.

Robust arbitrary trajectory tracking of multiple heterogeneous Euler–Lagrange systems under directed graphs: A fully distributed event‐triggered control

AbstractIn this paper, the robust arbitrary trajectory tracking problem of multiple heterogeneous Euler–Lagrange (EL) systems with disturbances under a directed graph is investigated via a novel fully distributed event‐triggered control (ETC) strategy. Firstly, for an arbitrary tracked trajectory, the Fourier transform technique is employed to approximately obtain its linear form, which represents the leader of multiple EL systems. Since the dynamics and state of the leader are not available to all followers, fully distributed adaptive ETC‐based observers are proposed for each follower to reconstruct the leader's trajectory, where the global information requirements are avoided, and the Zeno behavior is excluded by giving the minimum triggering intervals. Armed with the observed information, a robust adaptive ETC protocol is further developed such that the position‐like state of each follower can track the leader with the intermittent controller updating, where a minimum control update interval is obtained theoretically. Moreover, the adaptive technique is used to eliminate the influence of the parameter uncertainties of multiple EL systems, thus the tracking is achieved asymptotically. Finally, simulation results are illustrated to show the feasibility and effectiveness of the proposed control strategy.

Online battery scheduling for enhanced profitability and longevity in pay-for-performance frequency regulation markets

Batteries participating in frequency regulation (FR) markets earn revenue at the expense of longevity. The declining reward prices and highly stochastic automatic generation control (AGC) signals with short update intervals necessitate research into aging-aware real-time FR strategies for the battery. To address these challenges, this paper develops an online battery dispatch strategy based on Lyapunov optimization, accounting for Ah-throughput, C-rate, and temperature aging effects to enhance the service profitability of the battery. The strategy operates independently of probabilistic data from random processes, with its optimality gap inversely correlated with the control parameter. A systematic and intuitive approach is established for constructing virtual queues and determining the maximum feasible parameter. The proposed method is validated through extensive numerical simulations using actual lithium-ion battery aging data, along with year-long regulation signal and market price data from Pennsylvania-New Jersey-Maryland (PJM). Results show that the strategy can extend the battery lifespan by 83.41% and increase the net present value (NPV) by 172.67% compared to the conventional Ah-based strategy.

Path planning of mobile robot based on improved TD3 algorithm in dynamic environment

This paper proposes an improved TD3 (Twin Delayed Deep Deterministic Policy Gradient) algorithm to address the flaws of low success rate and slow training speed, when using the original TD3 algorithm in mobile robot path planning in dynamic environment. Firstly, prioritized experience replay and transfer learning are introduced to enhance the learning efficiency, where the probability of beneficial experiences being sampled in the experience pool is increased, and the pre-trained model is applied in an obstacle-free environment as the initial model for training in a dynamic environment. Secondly, dynamic delay update strategy is devised and OU noise is added to improve the success rate of path planning, where the probability of missing high-quality value estimate is reduced through changing the delay update interval dynamically, and the correlated exploration of the mobile robot inertial navigation system in the dynamic environment is temporally improved. The algorithm is tested by simulation where the Turtlebot3 robot model as a training object, the ROS melodic operating system and Gazebo simulation software as an experimental environment. Meanwhile, the result shows that the improved TD3 algorithm has a 16.6 % increase in success rate and a 23.5 % reduction in algorithm training time. A generalization experiment was designed finally, and it indicates that superior generation performance has been acquired in mobile robot path planning with continuous action spaces through the improved TD3 algorithm.

Dynamic output feedback control of uncertain nonlinear systems based on co-design adaptive event-triggered scheme

This paper presents a framework to design a robust dynamic output feedback (DOF) controller for a class of nonlinear systems, based on the adaptive event-triggered control (AETC) method. The considered system contains parametric uncertainty and to design the event-triggered mechanism (ETM) Finite-gain L2 stability criteria are used. In this paper, a robust adaptive event-triggered mechanism (AETM) is first designed using a pre-designed controller. Then, in a co-design approach, the AETM and the DOF controller are designed together to increase the closed-loop performance. Indeed, the matrices of the DOF controller and the sufficient conditions for the AETM are obtained simultaneously. These conditions are represented as linear matrix inequalities (LMIs) and lead to a significant increase in the update interval. Moreover, the proposed design method guarantees the stability of the closed-loop system in the presence of the proposed triggering event. Finally, to illustrate the performance of the controller three examples are simulated.

Updated Reference Intervals for Alanine Aminotransferase in a Metabolically and Histologically Normal Population

Background and AimsThis study aims to reevaluate upper reference limit (URL) for alanine aminotransferase (ALT) by considering the changing epidemiology of major liver diseases. We employed histological and metabolic parameters in Asian living liver donors. MethodsWe performed a retrospective analysis of 5,455 potential living liver donors from 2005 to 2019. Participants were screened for hepatitis B, C, HIV, and alcohol use. Histologically and metabolically healthy participants were assessed using the Prati criteria (body mass index <23 kg/m2, triglyceride ≤200 mg/dL, fasting glucose ≤105 mg/dL, total cholesterol ≤220 mg/dL). The updated ALT-URL was determined as the 95th percentile among participants without hepatic steatosis and who met the Prati criteria. ResultsThe median age was 30 years, with a male predominance (66.2%). Among 5,455 participants, 3,162 (58.0%) showed no hepatic steatosis, with 1,553 (49.1%) meeting both the criteria for no steatosis and the Prati criteria for metabolic health. The updated URL for ALT in these participants was 34 U/L for males and 22 U/L for females, which was significantly lower than conventionally accepted values. Using this revised ALT-URL, 72.8% of males with ALT levels ≥34 U/L and 55.0% of females with ALT levels ≥22 U/L showed signs of steatosis, while 32.7% of males and 22.2% of females met the criteria for metabolic syndrome. ConclusionsOur study provided the newly established reference intervals for ALT levels in a metabolically and histologically verified Asian population. The proposed URL for ALT are 34 U/L and 22 U/L for males and females, respectively.

Updated adult ferritin reference intervals based on a large, healthy UK sample, measured on Roche Cobas series analysers.

There is a lack of standardization of reference intervals (RIs) for ferritin across laboratories, particularly for postmenopausal women. Depending on the RI used, there can be more than a 4-fold difference in the upper limit of normal between laboratories, resulting in potential misinterpretation. This retrospective study used a large dataset of blood test results from 25,425 healthy participants aged 18 to 97 over a 7-year period. Exclusion criteria were used to screen out individuals with conditions known to affect iron metabolism or raise ferritin as part of the acute phase response. Distributions were assessed using density and Q-Q plots, and age-banded cut-offs were determined. The non-parametric method was used to establish RIs for sex and age bands. For females, 4 age bands were established (18-39, 40-49, 50-59 and 60+). For males, 2 bands were identified (18-39 and 40+). Performance against a validation dataset, followed by an expansive validation against an inclusive dataset, demonstrated the robustness of the derived RIs. This study addresses the inconsistency in serum ferritin RIs by presenting intervals based on demographic parameters. This approach can potentially enhance the accuracy of interpreting serum ferritin levels, assisting clinicians in identifying patients requiring further evaluation.

Age- and deviation-of-information of hybrid time- and event-triggered systems: What matters more, determinism or resource conservation?

Age-of-information is a metric that quantifies the freshness of information obtained by sampling a remote sensor. In signal-agnostic sampling, sensor updates are triggered at certain times without being conditioned on the actual sensor signal. Optimal update policies have been researched and it is accepted that periodic updates achieve smaller age-of-information than random updates. We contribute a study of a signal-aware policy, where updates are triggered randomly by a defined sensor event. By definition, this implies random updates and as a consequence inferior age-of-information. Considering a notion of deviation-of-information as a signal-aware metric, our results show, however, that event-triggered systems can perform equally well as time-triggered systems while causing smaller mean network utilization. We use the stochastic network calculus to derive bounds of age- and deviation-of-information that are exceeded at most with a small, defined probability. We include simulation results that confirm the tail decay of the bounds. We also evaluate a hybrid time- and event-triggered policy where the event-triggered system is complemented by a minimal and a maximal update interval.

Research on the "shape-performance-control" integrated digital twin system for boom-type roadheaders

The boom-type roadheader plays a crucial role in coal mining. However, conducting the real-time monitoring of the mechanical performance and comprehensive adaptive cutting in the dynamic cutting process are challenging. To address these issues, a digital twin system that integrates the elements of “shape, performance, and control” for roadheaders is presented in this paper. The system comprises three components: physical space, service space, and twin space. The service space forms the core of the entire system. Within this space, twin models and control models are created using numerical simulation, artificial intelligence and multi-source data fusion technology. These models serve the purpose of predicting the roadheader’s mechanical performance and controlling the swing speed of the cutting arm. The physical space is built using technologies such as robot kinematics, electrical systems, hydraulic transmission, and other relevant techniques. This approach facilitates the transmission of multi-sensor data to twin models. The control model then manages the roadheader’s function based on the output signals from the control model. The twin space is constructed utilizing physical rendering engines, databases, and 3D modelling tools. This space visualizes and stores the movement, performance, and control parameters of the roadheader. The results demonstrate that the average absolute error between the measured data from the test’s three position strain gauges and the predicted data from the twin system is 10.38 MPa. Furthermore, the twin system achieves an average update interval of 0.34 s, allowing real-time stress monitoring of the structural components of the roadheader and preventing damage caused by overload. The proposed control model enables adaptive adjustment of the swing speed of the cutting arm in approximately 0.3 s. This improvement significantly enhances the adaptive cutting capabilities of roadheaders when dealing with complex coal and rock formations.

Circulating Nucleated Red Blood Cells: An Updated Reference Interval.

Nucleated red blood cells (nRBCs) are not identified in the peripheral blood in healthy individuals beyond the neonatal period. Their presence in children and adults is traditionally considered pathologic. Contemporary hematology analyzers measure nRBCs at very low levels compared to traditional manual morphometric methods. The original launch of the Sysmex XN analyzer in this study's clinical laboratory verified the previously used nRBC reference interval of 0.00 to 0.01 × 106/μL. However, nRBC results from apparently healthy patients were flagged as abnormal (high), subsequently causing patient anxiety and increased subspecialty referrals. To determine whether current reference intervals (RIs) for nRBCs were clinically relevant. We performed a prospective analysis of 405 300 specimens from nonhospitalized individuals who received a complete blood count. Applying inclusion/exclusion criteria produced a total specimen pool of 66 498. Of the 66 498 samples with otherwise normal complete blood count results from healthy, nonhospitalized individuals, 338 showed results outside the previously established RI; 336 of 66 498 (0.5%) had nRBC results greater than 0.01 × 106/μL. Two samples had nRBC values greater than 0.10 ×106/μL. Based on statistical analysis of our results, we concluded that the upper limit of the RI could be updated from 0.01 × 106/μL to 0.10 × 106/μL. Increasing the upper limit of normal for the nRBC RI should decrease patient consternation from an abnormal laboratory value and significantly decrease costs through reducing unnecessary follow up care, and without causing patient harm.

Hematological and Serum Biochemical Reference Intervals for Alphaxalone Sedated Common Marmosets (Callithrix jacchus).

Marmosets are routinely used in biomedical research, therefore there is an increasing need for updated reference intervals calculated using a large sample size, correct statistics, and considering different variables. Hematological and biochemical values from 472 healthy common marmosets sedated with alphaxalone were collected over a ten-year period (2013-2023). The variables assumed to have influenced the blood-based parameters were compared, i.e., sex, age, housing condition, pregnancy, and contraceptive use. Reference intervals were calculated based on observed percentiles without parametric assumptions, and with parametric assumptions following Box-Cox transformation. Juvenile marmosets showed increased ALP, phosphate, WBC, lymphocyte count, and basophil count and decreased levels of GGT and Fe compared to adults. Marmosets housed strictly indoors showed increased ALT and GGT levels and decreased levels of total bilirubin and neutrophil count compared to marmosets housed with outdoor access. Pregnant marmosets showed increased ALP, total bilirubin, neutrophil count, monocyte count, and basophil count, and decreased levels of AST, ALT, cholesterol, Fe, and lymphocyte count compared to non-pregnant marmosets. Etonogestrel contracepted marmosets showed decreased P-LCR compared to females who were not contracepted. Updated reference intervals will aid researchers and veterinarians in identifying physiological and pathological changes, as well as improve the reproducibility of research in this species.

Let Us Build a MQTT Pub-Sub Client In C# For IoT Research

Purpose: MQTT stands for Message Queuing Telemetry Transport. It is a lightweight protocol specifically designed for IoT applications. Nowadays, most IoT projects exchange sensor data over the MQTT protocol. It is simple to integrate and can run on low hardware resources. To test MQTT, the researcher needs MQTT publisher subscriber client software. There are several free and paid software available on the web. But sometimes, researchers need some custom interface or functionality not available in the free version. The paid version demands vast amounts of money for customization. Occasionally, they want to avoid customization for specific projects. Here, we provide a procedure to create our MQTT pub-sub client software interface, which the researcher can easily customize. The project is available to download. Methodology/Approach: We installed Microsoft Visual Studio in our working system. Using C# language, we create a GUI (graphical user interface). Inside the GUI, we segregate the info into two. The left is for publishing clients, and the right is for subscribing clients. We installed the M2MQTT package using the NuGet package manager to communicate with the MQTT broker. Findings/Result: Using our built application, we test to exchange the sensor data between two clients. We found the data exchanged in almost real-time. In a couple of scenarios, we observed that the data propagation could have been faster when we set the update interval below 500 milliseconds. There may be a network delay, or the MQTT broker we used is a free service. It may be the limited capacity of the accessible mode of the server we used. If the application is not time-critical, we can utilize this communication route to exchange the sensor data. Originality/Value: Every day, new researchers are introduced to the IoT field and integrate MQTT into their projects. They feel one customizable software they can use according to their project requirements. So, using this project, the researcher can fulfill their need. The code is freely available on the web. And scope to customize. This project provides value to them. Type of Paper: Experimental-based Research.

Advancing Process Control in Fluidized Bed Biomass Gasification Using Model-Based Deep Reinforcement Learning

This study presents a model-based deep reinforcement learning (MB-DRL) controller for the fluidized bed biomass gasification (FBG) process. The MB-DRL controller integrates a deep neural network (DNN) model and a reinforcement learning-based optimizer. The DNN model is trained with operational data from a pilot-scale FBG plant to approximate FBG process dynamics. The reinforcement learning-based optimizer employs a specially designed reward function, determining optimal control policies for FBG. Moreover, the controller includes an online learning component, ensuring periodic updates to the DNN model training. The performance of the controller is evaluated by testing its control accuracy for regulating synthetic gas composition, flow rate, and CO concentration in the FBG. The evaluation also includes a comparison with a model predictive controller. The results demonstrate the superior control performance of MB-DRL, surpassing MPC by over 15% in regulating synthetic gas composition and flow rate, with similar effectiveness observed in synthetic gas temperature control. Additionally, this study also includes systematic investigations into factors like DNN layer count and learning update intervals to provide insights for the practical implementation of the controller. The results, presenting a 50% reduction in control error with the addition of a single layer to the DNN model, highlight the significance of optimizing MB-DRL for effective implementation.

Satellite Navigation Message Authentication in GNSS: Research on Message Scheduler for SBAS L1.

SBAS is mainly used in civil aviation and navigation, and will be applied to autonomous driving in the future. Given the open signal format of the Satellite Based Augmentation System (SBAS), which exposes security threats such as spoofing attacks, the utilization of SBAS navigation message authentication technology can improve the SBAS anti-spoofing ability from the system side. SBAS message authentication technology has become the future direction of SBAS system development. However, during the initial design of SBAS on L1, message authentication technology was not considered, and the addition of authentication messages will lead to further strain on existing message bandwidth resources. Therefore, in response to the issue of insufficient bandwidth resources after adding authentication messages to SBAS L1, a study on message scheduler for SBAS L1 authentication was conducted. A fixed time sequence dynamic message scheduler for incorporating authentication messages was proposed. This scheduler reduces the frequency of broadcasting clock error parameters to mitigate the impact of adding authentication messages. Furthermore, an optimized fixed time sequence dynamic message scheduler based on SBAS clock error messages was introduced. The results show that the message scheduler can not only improve the flexibility of SBAS message broadcasting, but also shorten the update interval of various types of messages under the premise of meeting the maximum update interval requirement. With minimal impact on the maximum message update interval, it improves the integrity, authenticity, and availability of messages. This approach can increase the effective message ratio in SBAS to over 91%, and the optimal solution reduces the initial user positioning time to 26 s.

Energy Aware Optimisation of Topology Update Interval and Routing Based On Adaptive Chimp Optimization Algorithm in k-Connected MANETs

Energy Aware Optimisation of Topology Update Interval and Routing Based On Adaptive Chimp Optimization Algorithm in k-Connected MANETs

Energy-aware optimisation of topology update interval and routing based on the adaptive chimp optimisation algorithm in k-connected MANETs

Energy-aware optimisation of topology update interval and routing based on the adaptive chimp optimisation algorithm in k-connected MANETs

Performance evaluation of real-time orbit determination for LUTAN-01B satellite using broadcast earth orientation parameters and multi-GNSS combination

Real-time orbit determination (RTOD) for spacecraft using the space-borne GNSS technique needs earth orientation parameters (EOPs) for the required coordinate transformation between earth-fixed and inertial reference frames. GPS and BDS transmit EOPs in modernized navigation messages, which enables GNSS-equipped spacecraft to update EOPs onboard and improves the RTOD automaticity. However, the impact of broadcast EOP errors on RTOD has not yet been evaluated. With the GPS and BDS-3 observations collected from a Chinese low-earth orbit (LEO) mission, the LUTAN-01B satellite, we analyze the LEO RTOD performance with broadcast EOPs and GPS/BDS-3 combination for the first time. In RTOD, we parameterize the ephemeris signal-in-space range error (SISRE) to account for its slow-varying signature and to compensate for the EOP errors. Without estimating SISRE, the RTOD precision using broadcast EOPs is 70.1 cm with only GPS observations and 42.4 cm with only BDS-3, revealing degradations of 5.1 cm (7.8%) and 3.3 cm (8.4%) compared to those using the precise C04 EOPs, respectively. With SISRE estimated, the impact of broadcast EOP error is compensated and the RTOD precisions with broadcast EOPs show identical results to those with C04, reaching 36.3 cm with GPS and 25.8 cm with BDS-3. Combining GPS and BDS-3 further improves the RTOD precision to 23.9 cm. Furthermore, we show that the RTOD precision can be further improved by using GPS and BDS broadcast EOPs’ differences to correct ephemeris rotation errors. With this correction, the precision improvement of BDS-3 independent and GPS/BDS-3 combined RTOD increases significantly when BDS-3 broadcast EOPs suffer large errors due to long update intervals. During the experiment period, their maximum orbital improvements reach 10.2 and 7.7 cm, respectively, while the average improvements are both around 1.5 cm.