Arrival Time Research Articles

Extreme wave impacts on a suspended box above free surface

A systematic approach incorporating precision-controlled experiments and high-fidelity numerical simulations has been employed to delve deeper into the physics of extreme wave impact pressures. Using a suite of high-speed imaging and high-resolution pressure sensing techniques that are accurately synchronized with the wave generation, a consistent and well-correlated set of data providing details of the focusing incident wave front, flow velocities, and impact pressure time histories has been successfully obtained. The numerical simulations using a validated incompressible smoothed particle hydrodynamics (ISPH) provided further details that were not tractable in the experiments. Based on the results obtained, there were five broad impact scenarios identified, ranging from focusing crest impacts to plunging jet impacts with varying entrapped air. Among these impact types, the highest impact pressures were those associated with a focusing wave crest. It has been found that high impact pressures were correlated with a convergence of the horizontally impinging overturning crest and the vertical surge of the wall boundary water mass, but with the overturning crest impingement just ahead of the arrival of the wall boundary water mass, which in essence amounted to the impingement of a focusing wave front. Depending on the relative arrival times of the impinging crest and the wall boundary upsurge, the impact scenarios could vary from an up-slosh to a jet impingement with a clear entrapped air pocket, followed by a flip-through of the incident crest. For the scenario with the highest impact pressures, broadly classified as type II impact in this paper, the peak pressures could reach as high as 85ρC2, an order of magnitude higher than impact scenarios without the focusing effect, such as the scenario with a plunging jet impact with entrapped air (classified as types III and IV impact in this study). As the volume of entrapped air for this scenario was relatively small, the one-phase ISPH model used in this study was able to capture the peak pressure characteristics, including the peak pressure amplitudes. However, in scenarios with significantly highly entrapped air during impact, a two-phase model would be necessary.

Effect of Signal Features and Model Variables on Energy-Traced Arrival Time Picking of Acoustic Signals Used for Structural Damage Detection

To monitor damage developments in structures, various structural health monitoring methods based on different principles are used. The common aspect of elastic wave-based methods is to place appropriate sensors on the structure, to detect acoustic wave propagation and to analyze these signals the sensors transformed. The arrival time of these recorded signals to the sensors is the most significant parameter used to determine critical information such as the time and location of the damage. Therefore, the accurate calculation of the arrival time affects the accuracy of the damage detection. In this study, effects of the signal-to-noise ratio (SNR), sampling frequency, length of the signal, and length of the focal window on determining the arrival time of the signals to the sensors were investigated. For this purpose, an energy-traced arrival time picking approach (Akaike Information Criterion, AIC), which is the frequently used method in the literature, has been applied to a typical acoustic signal originated from a concrete cracking. The results of the study suggest the necessity of noise elimination, the optimum level of data logging and the ratios of focal window lengths for accurate time of arrival detection in the field monitoring of the structures using acoustic methods.

The Latium acute stroke registry: data quality and validation of the NIH Stroke Scale in predicting in-hospital death

Background and Purpose: The experimental phase of the stroke registry for the region of Lazio, completed in 2003, collected clinical data using an ad hoc survey on emergency room (ER) patients who presented with suspected stroke. We evaluated the accuracy and completeness of the data collected and assessed the validity of the National Institute of Health Stroke Scale (NIHSS) in predicting in-hospital mortality. Methods and Results: Two different indicators were developed to evaluate the quality of the registry: the response (% ER patients surveyed with suspected stroke) and the coverage rates (% ER patients surveyed discharged with stroke). Their values by type of emergency service were respectively: first aid ER =59.3% and 45.5%; level one ER =39.7% and 27.6%; level two ER =17.2% e 12.0%. Stroke severity, age, type of emergency facility and time of arrival at the ER were associated with the accuracy and completeness of the registry. The in-hospital mortality predictive model showed good discriminative ability (area under the receiveroperating characteristic (ROC) curve (AUC)=0.79 (95%CI 0.75, 0.84)) and good calibration (Hosmer- Lemeshow’s goodness-of-fit (HL) test p=0.48). AUC and HL tests, estimated after applying the linear predictor to an external validation cohort, were 0.79 (95%CI 0.74, 0.84) and p=0.23 respectively. Conclusions: Survey completeness and accuracy were associated with patient and facility characteristics, suggesting that it could be improved. The NIHSS calculated at ER admission is a good predictor of inhospital mortality.

Reference-free dual-comb spectroscopy with inbuilt coherence.

We demonstrate a simple system for dual-comb spectroscopy based on two inherently coherent optical frequency combs generated via seeded parametric downconversion. The inbuilt coherence is established by making the two combs share a common comb line. We show that the inbuilt coherence makes it possible to use a simple numerical post-processing procedure to compensate for small drifts of the dual-comb interferogram arrival time and phase. This enables long-time coherent averaging of the interferograms.

Garbage Collection Android Application

Abstract: The "Android Garbage Collection Application" stands as an innovative solution tailored for Android devices, with the objective of revolutionizing waste management in smart cities. Conventional waste collection methods frequently result in missed pickups, litter accumulation, and potential public health risks. This project harnesses seamless integration with Firebase to create a user-friendly Android app. It provides real-time notifications to residents as garbage collection trucks approach their locations. A central feature of this app is its live tracking system, enabling users to monitor the precise location of the garbage truck in real-time. Additionally, it offers estimated arrival times, effectively reducing waiting times for residents and optimizing the waste collection process. What truly sets this application apart is its focus on community engagement. By actively involving residents in the waste management process, it encourages shared responsibility and cooperation among city dwellers, fostering a cleaner environment and ensuring timely and efficient waste collection. Furthermore, this project serves as a testament to the transformative power of modern technology in enhancing traditional municipal services. It exemplifies how integrating cuttingedge technology can effectively address longstanding challenges and enhance the quality of life for residents in smart cities. The scalability and adaptability of this application make it a valuable asset for optimizing waste management in various urban settings. Its data analytics capabilities provide city officials with valuable insights, enabling more informed decision-making and a proactive approach to waste management

Implementasi Sistem Kehadiran Guru Berbasis Internet of Thing di SDIT Darul Hikmah

The teacher attendance system currently implemented at SDIT Darul Hikmah Jakarta still uses the manual method by filling in the arrival time and signing the attendance book available in the office. The system has several drawbacks such as manipulation of attendance, damaged or missing attendance books, and ineffective reporting because the general coordinator needs to copy back attendance data to be submitted to the principal and chairman of the foundation as material for evaluating teacher performance. Therefore, this study aims to create an Internet of Thing-based presence system using NodeMCU ESP 32 and a fingerprint sensor. This research process uses the Prototype method. This research produced a teacher attendance recorder that teachers can use as proof of attendance when they arrive at class. In addition, the website utilized to manage teacher attendance data to make reports and is used by teachers to fill out learning agendas that can provide feedback to student parents regarding student participation in learning through the Telegram application.

Six Sigma Technique to Reduce Waiting Time: A Practical Application in Passport Affairs Directorate

This study investigates the impact of the Six Sigma methodology on improving waiting times in passport directorates. The Six Sigma methodology is crucial for enhancing efficiency and effectiveness in passport directorates, aiming to reduce waiting times and increase customer satisfaction by organizing services more effectively. The research was conducted in the Passport Affairs Department (Mansour Passports) from November 8, 2022, to April 19, 2023, with a sample size of 53 employees and citizens. The problem of this study is to shed light on the role played by the Six Sigma methodology in improving waiting time at the Passport Affairs Department. The study adopted the DMAIC methodology (Define, Measure, Analyze, Improve, and Control) and used statistical software (SPSS) to calculate Six Sigma levels for both citizens and employees. Access and service data analysis was conducted using Win QSB software, and arrival and service times were calculated for all stages (counter employees, accounts, and manager's computer). The most significant results indicate that the directorate operates at the first level of Sigma levels, while citizens are at the second level. There is a significant and inverse effect of Six Sigma principles on waiting. The total time a citizen waits from entering the passport office to receiving their passport is very long. Paper type: Research Paper

Potential effects of a mobile stroke unit on time to treatment and outcome in patients treated with thrombectomy or thrombolysis: A Danish-German cross-border analysis.

A mobile stroke unit (MSU) reduces delays in stroke treatment by allowing thrombolysis on board and avoiding secondary transports. Due to the beneficial effect in comparison to conventional emergency medical services, current guidelines recommend regional evaluation of MSU implementation. In a descriptive study, current pathways of patients requiring a secondary transport for mechanical thrombectomy were reconstructed from individual patient records within a Danish (n = 122) and an adjacent German region (n = 80). Relevant timestamps included arrival times (on site, primary hospital, thrombectomy centre) as well as the initiation of acute therapy. An optimal MSU location for each region was determined. The resulting time saving was translated into averted disability-adjusted life years (DALYs). For each region, the optimal MSU location required a median driving time of 35 min to a stroke patient. Time savings in the German region (median [Q1; Q3]) were 7 min (-15; 31) for thrombolysis and 35 min (15; 61) for thrombectomy. In the Danish region, the corresponding time savings were 20 min (8; 30) and 43 min (25; 66). Assuming 28 thrombectomy cases and 52 thrombolysis cases this would translate to 9.4 averted DALYs per year justifying an annual net MSU budget of $0.8M purchasing power parity dollars (PPP-$) in the German region. In the Danish region, the MSU would avert 17.7 DALYs, justifying an annual net budget of PPP-$1.7M. The effects of an MSU can be calculated from individual patient pathways and reflect differences in the hospital infrastructure between Denmark and Germany.

Direct Medical Cost for Acute Ischemic Stroke Patients in Vietnam

Ischemic stroke is one of the leading causes of global disease burden. Vietnam, among other low- and middle-income countries, bears nearly 90% of the ischemic stroke burden. This study was a cost-of-illness study conducted from the healthcare system perspective to estimate the direct medical costs and associated factors for acute ischemic stroke patients at Bach Mai Hospital, a major hospital in Hanoi, Vietnam. A total of 500 eligible patients with acute ischemic stroke at the Neurology Department of Bach Mai Hospital from July 2021 to December 2021 were included. Patient characteristics and treatment information were collected via medical records and patient interviews. The majority of the patients were men (65.8%), with a mean age of 65.3 years. The average direct medical cost per patient was 10.5 ± 7.3 million Vietnam Dong (~454.2 ± 313.8 US dollars). The cost of hospital beds accounted for most of the total cost (34.6%), followed by medications and infusion fluid costs (27%) and diagnostic imaging (12.6%). Factors significantly associated with higher direct medical costs were the duration of stay, stroke severity, complications, number of comorbidities, and intravenous thrombolysis treatment. The study highlighted the need for a reduction in the duration of hospital stay and an improvement in onset-to-hospital arrival time.

Proactive real-time scheduling method for apron service vehicles based on mixed strategies

Due to the uncertainty of flight arrival and departure times, the scheduling of apron vehicles in airports has always faced significant challenges. This paper considers the real-time scheduling problem of apron vehicles under dynamic requests, establishing a new parking rule to allow apron vehicles to dynamically adjust parking areas. In order to maximize service level and minimize operational costs, this paper proposes a proactive real-time scheduling method for apron vehicles based on mixed strategies. Through strategies such as flexible waiting and dynamic relocation, this paper responds proactively to future requests. The proposed strategies are validated through implementation in large and medium-sized scale cases at Beijing Capital International Airport and Nanjing Lukou International Airport in China, respectively. Numerical results indicate that the proposed scheduling method is effective and applicable. The flexible waiting strategy significantly reduces vehicle travel distance, while the dynamic relocation strategy is significant in shortening request response times.

DEVS: Secure and optimal decentralized energy trading scheme for Electric Vehicle and Charging Station using game theory

SummaryWith the advent and popularity of electric vehicles (EVs), the intelligent transportation system has adopted them as an alternative to fossil fuel or gasoline vehicles owing to their benefits of reduced greenhouse gas emissions. However, it becomes critical to schedule the vast EVs at the charging station (CS) efficiently while maintaining security, privacy, and optimality during the energy trading. Therefore, we propose a blockchain and zero‐sum game theory‐based energy trading scheme, that is, DEVS, for optimal and secure EV charging at the CS. We incorporate the Interplanetary File System with the blockchain to ameliorate the cost‐efficiency and reliability of EV energy trading. Furthermore, we implement the zero‐sum game theory between players EV and CS to yield an optimal payoff based on pure and mixed strategies during the energy trading procedure. Moreover, we deploy and execute the smart contract (SC) of the blockchain‐based proposed DEVS scheme in the Remix integrated development environment to secure EV energy trading transactions. Additionally, the security of the proposed DEVS scheme is checked and analyzed using a fuzzing‐based Echidna tool for protected energy trading. Finally, the performance evaluation of the proposed DEVS scheme is analyzed using various standard metrics such as profit comparison based on strategies, energy price comparison, CS profit comparison for pure strategy (based on arrival time), convergence comparison, and profit (EV and CS) at saddle point and mixed strategy to avail preserved and optimal energy trading for EVs.

Optimizing lightning location accuracy: A study of propagation velocity and time of arrival in long-range lightning location algorithms

The propagation velocity (v) and time of arrival (Ta) are the primary factors affecting long-range lightning location. In this paper, we have enhanced the Very Low Frequency Long-range Lightning Location Network (VLF-LLN) in China in terms of both pulse pairing methods and location algorithms. Then, the algorithm utilized in the VLF-LLN, and four other long-range lightning location algorithms were compared using lightning strike accidents, simulated lightning strike, and other lightning data as the reference values. Building on this foundation, the discussion centers on the effect of v and Ta on location accuracy, with the results showing that an appropriate Ta yields a more significant improvement in location accuracy compared to v. VLF-LLN uses the peak time of the ground wave as Ta avoids the significant lag caused by sky wave, which is present in other algorithms, and therefore has the best location accuracy with a median location accuracy of 1.81 km.

The NANOGrav 12.5-Year Data Set: Dispersion Measure Misestimations with Varying Bandwidths

Noise characterization for pulsar-timing applications accounts for interstellar dispersion by assuming a known frequency dependence of the delay it introduces in the times of arrival (TOAs). However, calculations of this delay suffer from misestimations due to other chromatic effects in the observations. The precision in modeling dispersion is dependent on the observed bandwidth. In this work, we calculate the offsets in infinite-frequency TOAs due to misestimations in the modeling of dispersion when using varying bandwidths at the Green Bank Telescope. We use a set of broadband observations of PSR J1643−1224, a pulsar with unusual chromatic timing behavior. We artificially restricted these observations to a narrowband frequency range, then used both the broad- and narrowband data sets to calculate residuals with a timing model that does not account for time variations in the dispersion. By fitting the resulting residuals to a dispersion model and comparing the fits, we quantify the error introduced in the timing parameters due to using a reduced frequency range. Moreover, by calculating the autocovariance function of the parameters, we obtained a characteristic timescale over which the dispersion misestimates are correlated. For PSR J1643−1224, which has one of the highest dispersion measures (DM) in the NANOGrav pulsar timing array, we find that the infinite-frequency TOAs suffer from a systematic offset of ∼22 μs due to incomplete frequency sampling, with correlations over about one month. For lower-DM pulsars, the offset is ∼7 μs. This error quantification can be used to provide more robust noise modeling in the NANOGrav data, thereby increasing the sensitivity and improving the parameter estimation in gravitational wave searches.

Modelling of Propagation Characteristics of Acoustic Pulse from Partial Discharge in Polymeric Insulating Materials

The partial discharge (PD) event in high-voltage insulation releases energy, exerts mechanical pressure, and generates elastic waves. Detecting and locating these PD events through short-duration acoustic pulses is well established, particularly in gas-insulated systems and oil-insulated transformers. However, its full potential remains untapped in solid insulation systems, where the propagation capability of the acoustic pulse and the acoustic reflections pose fundamental challenges to the acoustic emission (AE) detection technique. This study investigates the influence of reflections and multiple paths on the propagating acoustic pulse in polymeric insulating materials using a finite element method (FEM) in COMSOL. It was observed that the reflections from the boundary influence the propagating pulse’s shape, peak magnitude, and arrival time. An analytical MATLAB model further quantifies the impact of multiple propagation paths on the shape, magnitude, and arrival time of the pulse travelling in a cylinder. Additionally, a Perfect Matched Layer (PML) was implemented in the COMSOL model to eliminate the reflections from the boundary, and it revealed that the acoustic pulse magnitude decreases with distance following the inverse square law. In essence, the models aid in measuring how reflections contribute to the observed signals, facilitating the precise identification of the source of the PD event in the tested system.

Significant Earth’s responses of the 2022 Tonga eruption across Taiwan from multiple sensor observations

On 15 January 2022, a massive underwater volcano erupted in the Tonga region, releasing a significant amount of volcanic ash and gases into the atmosphere. The United States Geological Survey (USGS) estimated the seismic source to have a surface wave magnitude (Ms) of 5.8. This eruption was observed from space, and the resulting atmospheric shockwave swept across the Pacific Ocean. Reports from various locations worldwide indicated rapid fluctuations in air pressure following this event. Taiwan, situated in the western Pacific, approximately 8,500 km from the eruption source, observed significant changes. During this volcanic eruption, both rapid air pressure changes and several significant changes in the Earth’s physical parameters were observed in Taiwan. The Tonga eruption is a unique event, and comprehensive observations provide an opportunity to explore and explain the mechanisms behind this extreme event. Data from ground surface air pressure gauges, coastal tide gauges, underwater pressure gauges, infrasound sensors, digital microphones, and seismometers were collected. These data were analyzed to identify their origin and explain their interactions. The results of this study first present the detailed propagation characteristics of air pressure waves in the Taiwan region and verify the occurrence of a specific tsunami phenomenon caused by the atmospheric disturbance from the Tonga eruption. It follows a distinct mechanism, explaining its arrival time and wave height distribution around Taiwan, which is different from conventional tsunamis of tectonic origins, which are formed by rapid changes in water caused by earthquakes or underwater landslides.

Message from the editor in Chief

The year 2024 promises many exciting developments for the Global Journal of Computer Sciences: Theory and Research (GJCS). In addition, every year, the number of citations continues to rise strongly in proportion to the increase in the number of articles published. In this respect, first of all, we would like to thank all our authors who have contributed to the success of our journal. While reviewing our new issue, we saw articles from different authors from different countries: Turkey, India The multiculturalism policy followed in our globally-focused journal makes us happy with every new issue. We examine the following research areas in the current issue; “Determination of reinforcement diameters of reinforced concrete deep beams with genetic algorithms”, “Single server queueing model with Poisson arrival and gamma service time distribution”, “Sustainable innovation policy in non-walled technoparks” . We will continue to contribute to literature within the scope of Computer Science with our strong team. Thanks to all our authors the contributors to this issue. Hope to see you in our new issue. Assoc. Prof. Dr. Ezgi Pelin YILDIZ Global Journal of Computer Sciences: Theory and Research (GJCS) CHEF EDITOR

Single server queueing model with Poisson arrival and gamma service time distribution

Queueing theory is pivotal in understanding waiting lines and their pervasive role in everyday life. Its profound application spans across diverse sectors, including computer programming networks, healthcare, transportation, and so on. Researchers have applied many statistical distributions in analyzing queueing data. This article focuses on the analysis of a single server queueing system with Poisson input and service times distributed according to a two-parameter gamma distribution. The study elaborates on the construction and estimation of key queueing properties such as steady state equations, average number of customers in the system, average queue length, expected size of the non-empty queue, distribution of waiting time, average waiting time in the system, and average waiting time in the queue of the M/Gamma/1 queueing model using the two-parameter gamma distribution. Keywords: Gamma distribution; Poisson; service; single server; queuing model.

Wasatch Fault Structure from Machine Learning Arrival Times and High-Precision Earthquake Locations

Abstract On 18 March 2020, a magnitude 5.7 earthquake hit the Salt Lake valley in the state of Utah, United States. Using a dense geophone deployment and machine learning (ML), an additional several thousand events were detected and located. Currently, both the mainshock and the majority of the aftershocks are suspected to have occurred on or near a deeper portion of the Salt Lake segment of the Wasatch fault—part of a large range-bounding fault system thought to be capable of generating an Mw 7.2 earthquake. However, a small subset of aftershocks may have occurred on a portion of the more steeply, eastward dipping, and poorly understood West Valley fault. Unfortunately, the catalog locations and lack of focal mechanisms for this subset of aftershocks provide only a crude constraint on the true fault structure. To better illuminate fault structure, we relocate the ML-generated catalog with a range of magnitudes from −2 to 4.6, using: (1) NonLinLoc, a nonlinear location algorithm, (2) source-specific station terms, and (3) waveform coherence. We further compute first-motion focal mechanisms for 68 events. Results of the relocation suggest a simpler, minimally listric Wasatch fault geometry, contrary to what has been previously proposed. We also find that analysis of the focal mechanisms and waveform similarity indicates minimal event similarity throughout the Magna sequence, suggesting a highly complex and heterogeneous rupture zone, as opposed to rupture on a single plane. These findings suggest an increased seismic hazard due to the overall shallowness of the earthquake sequence and highly varied rupture mechanisms.

A New Data Processing Approach for the SHPB Test Based on PSO-TWER

This study addresses the challenge of accurately determining the arrival time of stress wave signals in SHPB test data processing. To eliminate human error, we introduce the time-window energy ratio method and evaluate six filters for noise reduction using box fractal dimensions. A mathematical model is established to optimize the stress equilibrium and impact process, which is solved using particle swarm optimization, resulting in the PSO-TWER method. We explore the impact of inertia weight and calculation methods on optimization outcomes, defining a stress equilibrium evaluation index. The results indicate that time-window length significantly affects arrival-time outputs, and the dynamic inertia weight factor enhances optimization convergence. The method accurately determines arrival times and effectively screens test data, providing a robust approach for SHPB test data processing.

A novel method for analyzing the leakage and diffusion of hydrogen: First arrival time distribution

Hydrogen energy plays an important role in achieving the carbon peak and carbon neutrality goals. However, owing to its flammability and explosiveness, hydrogen leakage during transportation and use can easily cause severe consequences. Therefore, research on the safety of hydrogen leakage is particularly important. This study proposes a novel method for analyzing the diffusion behavior of hydrogen leakage called first arrival time distribution (FATD). The spatial distribution of the first arrival times of specific concentration values (such as explosion limit and alarm concentration) at each coordinate point in the calculation domain was obtained by processing the concentration field of hydrogen leakage and diffusion via computational fluid dynamics simulations. The hydrogen leakage and diffusion processes were simulated for multiple scenarios using Fluent software, and the method of obtaining the FATD based on the simulations was detailed. The study also analyzed the hydrogen leakage and diffusion processes as well as the effects of mesh quantity and sampling time interval on the FATD; the FATD was additionally applied in actual scenarios to obtain an alarm time distribution for guiding sensor deployment. The results show that the FATD intuitively displays the hydrogen diffusion and evolution processes via specific concentration values in the calculation domain while describing the detailed influences of obstacles on the hydrogen diffusion process. Moreover, the FATD can serve as an indicator of grid independence analysis. This provides a new method for understanding diffusion behavior, reference for accident risk and consequence assessments, and safety guidance for the utilization of hydrogen energy.