Delay Operator Research Articles

Hierarchical deployment of deep neural networks based on fog computing inferred acceleration model

With the widespread adoption of deep neural network approaches in mobile devices, the drawbacks of traditional cloud-based or local deployment solutions are becoming apparent. The high latency caused by cloud-based inferred neural networks and the high power consumption caused by local inference of mobile devices greatly reduce the actual user experience of neural network applications. To solve this problem, this paper proposes a hierarchical deployment and inference acceleration model for deep neural networks based on fog computing. Firstly, a search reallocation of the solution space of a deep neural network is performed, and a Solution Space Tree Pruning (SSTP) based deployment algorithm is designed to select the appropriate network layer for deployment in order to reduce the overall inferred delay of a deep neural network. Next, an algorithm for Maximizing Accuracy based on Guaranteed Latency (MAL) is designed. On the pruned solution-space tree of the SSTP algorithm, the appropriate fog computation nodes are selected for mobile devices in different geographic locations to achieve early exit from the inference task according to the operational delay and inference accuracy requirements of real device terminals. The experimental results show that the proposed solution reduces the average latency of the fog computing-based inference acceleration model by 44.79% compared to the traditional cloud-deployed deep neural network inference, and by 28.75% compared to the edge computing acceleration framework in existing studies. The model meets the minimum latency and accuracy of neural network inference in multiple fog computing scenarios. At the same time, it greatly reduces the performance occupation and case cost of the cloud under the traditional cloud computing model.

25 Operative Delay in Neck of Femur Fracture Management During the COVID 19 Pandemic Lockdown; Reasons and Impact

All NOF patients beyond 24-hour window over the COVID Lockdown period From April 2020 to July 2020 were identified and causes of delay to theatre were stratified. Manual Data collection over a time period of April 2020 to July 2020, when lockdown was introduced. All patients with NOF who had surgery within 24 hours were excluded. Cases not within 24 hours were included. A total of 70 patients were included in the study. Cause for Delay beyond 24 hours included No list space 30, Medically unfit 20, Anticoagulation 18, COVID related 2 needing ventilatory support. Causes of medical Delay include chest infection (not COVID related), High anaesthetic risk, Cardiac, Anaemia, Electrolyte imbalance. Covid19 accounted for 2 % of operative delays of NOF patients. Other causes include medical optimization, theatre efficiency and use of anticoagulation. However, our study proved there is a vital requirement for robust protocols and pathways in the management of NOF especially during a global pandemic. This is important for the reduction of overall Morbidity and Mortality. Local Strategies should be put in place to address these with the importance of a MDT approach including the Anaesthetic and Orthogeriatic team.

208 Assessment of The Impact Of COVID-19 On the Management of Patients with Neck of Femur Fractures in A Major Trauma Center In Wales

IntroductionNeck of femur (NOF) fractures form a significant proportion of trauma. Especially since they do not benefit from COVID-19 social isolation policies. Surgery and hospital admissions present risks to patients during the COVID-19 pandemic.MethodRetrospective analysis of all NOF fractures from 24/3/20 to 26/6/20 in Morriston Hospital. Directly compared with 2019, allowing assessment of COVID-19’s impact.Results179 NOF fractures were admitted, 158 had an operation. Increased from 127 patients in 2019. Average time to surgery increased from 39 to 67 hours. There were operation delays for 98 patients, and non-operative treatment increased from 2 to 21 patients. Prompt orthogeriatric reviews completed in 80.4% patients in 2020, up from 72.5%. Prompt physiotherapy review increased from 66.9% to 74.6%. Mortality remained similar at 8.6% (2019) and 8.5% (2020). Average length of stay reduced; 17.4 to 11 days in 2020.Conclusions2020 saw increased waits for operations. There was reduction in length of stay and improved promptness of orthogeriatric and physiotherapy reviews. Increased non-operative treatment in 2020, reflecting decisions about risks and benefits of surgery in the pandemic. Mortality remained stable. This department improved some aspects of care, potentially due to pressures of COVID-19 heightening awareness of patient's needs.

A data-driven flight schedule optimization model considering the uncertainty of operational displacement

The slot allocation mechanism aims to match flight demand and airport resources from a strategic perspective. However, current research mainly focused on airlines' interests, ignoring the influencing factors that lead to primary delays, which makes the temporal and spatial distribution of flight schedules unreasonable. This paper proposes a data-driven approach to reduce operational delays at a strategic level by considering operational efficiency and airline interests. The displacement probability distribution between the actual execution time and the scheduled time is first mined from the historical operation data. We then develop a model with the ultimate objective of improving the punctuality rate and reducing the actual operational delays by minimizing the total operational displacement. In addition to considering the basic operational restrictions of airports, the model also introduces the corridor capacity of the terminal airspace surrounding an airport, reducing the delay caused by the corridor flow control to a certain extent. The proposed model is applied to Hangzhou Xiaoshan International Airport in China. The experimental results suggest that the optimized flight schedule can significantly reduce flight delay, conforms to airport operational restrictions, and maintains flight connectivity.

Global Comparisons of ERA5 and the Operational HRES Tropospheric Delay and Water Vapor Products With GPS and MODIS

AbstractPrecipitable water vapor (PWV) from numerical weather models, such as the latest generation of European Centre for Medium‐Range Weather Forecasts (ECMWF) reanalysis (ERA5) and the ECMWF High RESolution (HRES) models, are important to meteorological studies and to error mitigation of geodetic observations such as Interferometric Synthetic Aperture Radar. In this study, we provide global validations of these new weather models with respect to Global Positioning System (GPS, ∼13,000 stations) and Moderate Resolution Imaging Spectrometer (MODIS, ∼1 km resolution) using data from January 2016 to December 2018 of every 1 h. The global standard deviations of the Zenith Tropospheric Delay (ZTD) differences (DSTDs) between weather models and GPS are 1.69 cm for ERA5 and 1.54 cm for HRES. The global PWV DSTDs between weather models and MODIS are 0.34 cm for ERA5 and 0.32 cm for HRES. The two weather models generally perform better in western North America, Europe, and Arctic by having low ZTD DSTDs (<1.3 cm) or PWV DSTDs (<0.3 cm). HRES also has a low ZTD DSTD of less than 1.3 cm in Antarctic, Japan, New Zealand, and Africa and outperforms ERA5 in most regions of the world, despite the fact that 83% of the HRES PWV values are temporally interpolated (from 6 to 1‐h). However, under extreme weather conditions, ERA5 performs better owing to its high temporal resolution (1 h). Our results can be used as a global reference for evaluating uncertainties when utilizing these weather models.

SIMULATED ANNEALING GENETIC ALGORITHM-BASED HARVESTER OPERATION SCHEDULING MODEL

To address problems involving the poor matching ability of supply and demand information and outdated scheduling methods in agricultural machinery operation service, in this study, we proposed a harvester operation scheduling model and algorithm for an order-oriented multi-machine collaborative operation within a region. First, we analysed the order-oriented multi-machine collaborative operation within the region and the characteristics of agricultural machinery operation scheduling, examined the revenue of a mechanized harvesting operation and the components of each cost, and constructed a harvester operation scheduling model with the operation income as the optimization goal. Second, we proposed a simulated annealing genetic algorithm-based harvester operation scheduling algorithm and analysed the validity and stability of the algorithm through experimental simulations. The results showed that the proposed harvester operation scheduling model effectively integrated the operating cost, transfer cost, waiting time cost, and operation delay cost of the harvester, and the accuracy of the harvester operation scheduling model was improved; the harvester operation scheduling algorithm based on simulated annealing genetic algorithm (SAGA) was able to obtain a global near-optimal solution of high quality and stability with high computational efficiency.

Cleft Lip and Palate in Infants With Prenatal Opioid Exposure.

This study examines phenotypic presentation and perioperative outcomes of cleft-related procedures for infants with cleft lip and/or palate (CL/P) and prenatal opioid exposure. This is a retrospective review of infants with prenatal opioid exposure treated for CL/P from 2008 to 2018. Patients cared for at a tertiary center from 2008 to 2018. Eighteen patients with documented prenatal opioid exposure and CL/P had primary repairs in our unit. The phenotypes of CL/P were characterized. Demographic data regarding additional exposures, as well as associated medical and social comorbidities were recorded. Outcome variables included operative delays, perioperative complications, and loss of follow-up. Isolated cleft palate (CP; 67%) was overrepresented among patients with prenatal opioid exposure and CL/P, as was Robin sequence (50% in isolated CP). Fifty-six percent had exposure to additional substances. A majority (67%) had other medical conditions or anomalies, and 17% had known genetic syndromes. Seventy-two percent were in state custody. Thirty-nine percent of exposed patients had delays in their planned operative dates due to medical and/or social factors. There were no postoperative readmissions following cleft procedures. Lack of follow-up was noted in 33% of patients. Infants with CL/P who have prenatal opioid exposure are likely to have additional medical conditions and complex social challenges.

Evaluation of hand injury management at the emergency department - are we getting better?

Background/Aim. Hand injuries are one of the most common injuries seen in emergency departments. Inadequate treatment can lead to prolonged healing, complications, significant morbidity, and serious disability. The aim of this study was to evaluate the epidemiology, risk factors, and treatment of hand injuries in one tertiary care level clinical center. Methods. This study was designed as a descriptive retrospective epidemiological study that involved all patients with hand injuries treated at the University Clinical Center of Vojvodina, Novi Sad, Serbia for seven years. The authors collected sociodemographic and clinical data such as age, gender, mechanism of injury, type of injury, days of hospitalization, type of defect reconstruction, the time of in-jury, the timing of surgery, and reasons for operative treatment delay. For every hospitalized patient the Modified Hand Injury Severity Score (MHISS) was calculated. All data were analyzed using SPSS IBM 21.0 software. Results. From 2012 to 2018, 34,796 patients were treated for hand injury at the University Clinical Center of Vojvodina, with 554 (1.6%) hospitalized patients. The mean age of patients was 43.2 years; the majority of them (87.55%) were men, and most (47.2%) were injured at home. Most injuries occurred during knife handling. The average length of stay for hospitalized patients was 4 days. MHISS score for most patients was over 50 and was classified a s severe. It was noticed that the waiting time for operation became shorter throughout the selected years. Conclusion. Hand injuries present a complex problem that can sometimes be underestimated by patients. The requirement of highly specialized hand surgeons, sometimes special equipment (e.g., microscope), multiple operations, prolonged rehabilitation, possible invalidity, and high cost of treatment calls for careful evaluation of the problem and the development of proper strategies in order to be able to lower the costs and obtain better medical care for all people with higher injury risk.

An Efficient and Optimized Converter for Fast Binary to Decimal Conversion

ABSTRACT Decimal converter plays an essential role in decimal arithmetic operations. A decimal converter is used to convert binary partial products to Binary Coded Decimal. Here, the use of the converter cell decreases the delay of operation. In contrast to the previous shift + add3 implementations, the proposed cell is much more efficiently optimised due to which the speed of the overall conversion process is increased. The proposed cell shows an improvement in the delay of 9.33 and a power-delay product of 11.96 when compared to the previously proposed work. So, the proposed work can be a better substitute where faster conversions are required.

Predictive Model of Gait Recovery at One Month after Hip Fracture from a National Cohort of 25,607 Patients: The Hip Fracture Prognosis (HF-Prognosis) Tool.

The aim of this study was to develop a predictive model of gait recovery after hip fracture. Data was obtained from a sample of 25,607 patients included in the Spanish National Hip Fracture Registry from 2017 to 2019. The primary outcome was recovery of the baseline level of ambulatory capacity. A logistic regression model was developed using 40% of the sample and the model was validated in the remaining 60% of the sample. The predictors introduced in the model were: age, prefracture gait independence, cognitive impairment, anesthetic risk, fracture type, operative delay, early postoperative mobilization, weight bearing, presence of pressure ulcers and destination at discharge. Five groups of patients or clusters were identified by their predicted probability of recovery, including the most common features of each. A probability threshold of 0.706 in the training set led to an accuracy of the model of 0.64 in the validation set. We present an acceptably accurate predictive model of gait recovery after hip fracture based on the patients’ individual characteristics. This model could aid clinicians to better target programs and interventions in this population.

HTS FCL Module With Voltage of 500 V for DC Circuit Breaker

We have studied the operation of the circuit breaker for 15 kV DC power grid with the combination of the breaker and the HTS Fault Current Limiter (FCL). The HTS FCL limits the fault current by introduce of the impedance under the fault condition, so the circuit breaker with the HTS FCL module can be expected to be able to break the higher prospective fault current successfully. As an attached module to the DC circuit breaker, we performed a design work for a DC resistive HTS FCL module with SuNAM's REBCO conductor with the stainless-steel stabilizer. Considering the operation delay time of the DC circuit breaker, the HTS FCL module should generate a proper impedance for 16 milliseconds at most without any damages. To verify the design results, we designed and make scaled-down model of the HTS FCL module. We also carried out the DC short-circuit test to check the feasibility and the fault current limiting characteristics of the suggested model.

An Optimization Model for Tramp Ship Scheduling considering Time Window and Seaport Operation Delay Factors

The quantity of electrical coal transported through the tramp shipping network is increasing due to the high demands. This trend has increased the scheduling difficulty combined with the underdevelopment of the private thermal power plant port. The high coal consumption and low port storage capacity requires the scheduling of the tramp ship to be on a strict time window to ensure the continuous operation of the thermal power plant. The low port unloading capacity often leads to the port congestion and delay of the unloading operation. This paper develops a mixed-integer-programming model for the optimization of the tramp ship scheduling to reduce the total operation cost, including the transportation cost and the unloading waiting cost, and the branch-and-price algorithm is adopted to solve this large-scale model. The model and algorithm are tested with historical operation data from the thermal power plant in the southern coastal areas of China. The optimized scheme significantly reduces the total operation cost by reducing the unloading waiting time and the number of active vessels in certain periods. The results also demonstrate the algorithm improvement in the aspects of the optimization quality and efficiency comparing with the heuristic solution.

Power grid automatic dispatching method considering renewable energy fluctuation

In the process of power supply, the abnormal fluctuation of renewable energy leads to the increase of economic cost of power grid dispatching. Therefore, this paper proposes a power grid automatic dispatching method considering the fluctuation of renewable energy. According to the fluctuation of renewable energy, the power of renewable energy is predicted, and the power balance is judged by combining with other power related parameters in power grid operation. According to the change of peak load regulation, the power grid control center issues dispatching instructions and adjusts power related parameters to achieve the purpose of power automatic dispatching. The experimental results show that the proposed power grid automatic dispatching method considering renewable energy fluctuation has small operation delay and low economic cost, the economic benefit of which is higher than that of the traditional dispatching method.

Multiple-Target Low-Thrust Interplanetary Trajectory of

is a medium-class interplanetary mission, selected by the Japan Aerospace Exploration Agency for potential launch windows in the first half of 2020s. The mission will demonstrate innovative spacecraft subsystem technologies, including a new type of ion engine for future missions. The mission will also collect scientific data through high-speed flyby observations and dust measurements from asteroid (3200) Phaethon and its related body (155140) 2005 UD, to understand their origin and reveal the content of extraterrestrial dust in the context of origin of life. The limited control authority on the spacecraft, the orbits of the target asteroids, and the specific mission requirements pose a challenging task for the trajectory design of . Multiple-target low-thrust optimal trajectories are explored in this paper to fulfill the goals of the mission. An effective methodology is presented to convert feasible impulsive transfer solutions into low-thrust initial guesses and combine with gravity-assist maneuvers to reveal new high-fidelity optimal trajectories in real ephemeris models. The early mission analysis results demonstrate multitudes of flyby opportunities that provide robustness against programmatic and operational delays in the mission schedule.

Research on Workflow Task Scheduling Strategy in Edge Computer Environment

In recent years, with the rapid development of science and technology, edge technology has been gradually applied to many fields, such as computer cloud environment. Through edge computing, we can schedule cloud workflow tasks, which can allocate the workflow tasks submitted by users to appropriate computing resources. Then, based on the amount of resources used, we can pay for it immediately. For most ordinary users, workflow task scheduling is to balance the completion time and execution cost reasonably, which can coordinate the two into the optimal. With the continuous development of science and technology, intelligent mobile terminal equipment has gradually replaced the electronic computer, which has become the main computing platform for consumers. At the same time, with the development of natural language processing and video analysis technology, the world’s mobile data traffic has become an explosive growth. “Mobile edge computing” is a way for mobile network edge to provide IT service environment and cloud computing capability, which will reduce the delay of network operation and service delivery. By emphasizing proximity to mobile users, we can improve the user experience. Firstly, this paper analyzes the related concepts. Then, this paper mainly studies the workflow task scheduling strategy.

Potential of a repair system for grouted connections in offshore structures: Development and experimental verification

Grouted connections are intensively used in offshore rigs, platforms as well as jacket and monopile offshore wind turbine structures. Being located in remote offshore conditions, these connections can experience considerable adverse loading during their lifetimes. Degradation was reported inside similar connections, which were installed in the last three decades. Grouting in the offshore sites may often be proven difficult, which eventually leads to reduced load-bearing capacity of connections in the long run. Thus, repair and rehabilitation of such connections should be planned ahead to minimize operational delays and costs. In this study, scaled grouted connections were manufactured using a novel mould, whose integrity were monitored using digital image correlation (DIC). The connections were loaded under static load to visualize the main failure pattern using distributed fibre optic sensors and acoustic emission (AE) analysis. Grouted connections were then repaired using a cementitious injectable grout. The effectiveness of the grout injection was monitored using dye penetration technique. Finally, specimens are reloaded to identify the potential of such repair for grouted connections.

Prototype Current-Limiting Hybrid DC Circuit Breaker Incorporating a Fuse and a Semiconductor Device

Owing to the increased demand for DC interruption, a prototype current-limiting hybrid DC circuit breaker incorporating a fuse and a semiconductor device was developed, based on a completely novel design concept. Recently, hybrid DC breakers have been attracting attention because of their low conduction loss and high-speed current interruption capability. The superiority of this hybrid DC circuit breaker lies in the simultaneous use of the high-speed current-limiting performance of the fuse and the highly reliable current-interruption performance of the semiconductor device. Furthermore, the hybrid DC circuit breaker performs the current interruption without any mechanical contact, thus preventing any delay in operation induced by the mechanical contact. The feasibility of the proposed concept was demonstrated by the successful application of the circuit breaker in a 1 kA fault current interruption procedure. Hence, the current-limiting hybrid DC circuit breaker is suitable for low voltage and medium voltage DC system protection. As the fuses and semiconductor modules progress, the hybrid DC circuit breaker may also adapt to HVDC systems.

Structural Analysis of a Barge Midship Section Considering the Still Water and Wave Load Effects

Structural failures in the barge midship sections can cause operational delay, sinking, cargo loss and environmental damage. These failures can be generated by the barge and cargo weights, and wave load effects on the midships sections. These load types must be considered in the design of the barge midship sections. Here, we present the structural analysis of a barge midship section that has decreased up to 36.4% of its deck thickness caused by corrosion. This analysis is developed using finite element method (FEM) models that include the barge and cargo weights, and wave load effects. The FEM models regarded three cargo tanks in the midship section, containing the main longitudinal and transverse structural elements. In addition, the hull girder section modulus and the required deck thickness of the barge were calculated using Lloyd’s Register rules. These rules were applied to estimate the permissible bending stresses at deck and bottom plates under sagging and hogging conditions, which agreed well with those of the FEM models. Based on FEM models, the maximum compressive normal stress and von Mises stress of the hull girder structure were 175.54 MPa and 215.53 MPa, respectively. These stress values do not overcome the yield strength (250 MPa) of the barge material, allowing a safe structural behavior of the barge. The structural modeling of the barge midship section can predict its structural behavior under different sagging and hogging conditions, considering the cargo, weight and wave loads.

Integrating risk management concepts into the drilling non-productive time

Introducing the non-productive time (NPT) concepts in the 1960s was a necessity dictated by the ever-increasing cost and complexity of the oil and gas well drilling. The NPT definition stayed unsettled until two decades later, the definition converged toward its accepted current definition of “the time when planned or out-of-plans drilling-related activities do not add value to the operation objectives.” NPT as it is defined in drilling nowadays is a form of time waste or loss which adversely impacts the overall efficiency of the drilling operation. Since the 1980s, risk management (RM) has become a sound technique to evaluate operational losses or wastes of many resources, including time. This paper presents an attempt to couple RM techniques with NPT philosophy together with other concepts such as Systems Thinking, Synergy, Continuous Improvement, and Total Quality. These concepts and derived techniques suit well controlling the intolerable waste that shows up in the form of delay in operations and materializes into most of the undesirable costs of drilling. These concepts, adopted herein, were applied on data from 60 rigs which were used to drill 250 wells for a period of 1 year of operation. In all 19 types of NPT were considered. A Java software model was developed and used to express NPT as an undesired event with probability of happening, in order to follow with RM terminology. The probability levels (related to the NPT values) for each rig were then defined and further classified into the four familiar ranks and their colors as used in RM: Acceptable (green), Tolerable (yellow), Inadmissible (orange), and Unacceptable (red). A matrix was established for all NPT categories and for the 60 rigs and was then named Rig-NPT Risk Matrix. A maximum probability ceiling was established as a reference for unacceptable risks of all NPT categories and for all the 60 rigs. Finally, sets of risk control recommendations were proposed to minimize the NPT in order to improve rigs performance. The concept of NPT and the science of RM when integrated gave a new approach to minimize the drilling losses. Using NPT analysis coupled with risk management was used to indicate where to optimize exerted efforts in order to synergize improvement of overall drilling performance.

Impact of Weather Conditions on Airport Arrival Delay and Throughput

Weather events have a significant impact on airport arrival performance and may cause delays in operations and/or constraints in airport capacity. In Europe, almost half of all regulated airport traffic delay is due to adverse weather conditions. Moreover, the closer airports operate to their maximum capacity, the more severe is the impact of a capacity loss due to external events such as weather. Various weather uncertainties occurring during airport operations can significantly delay some arrival processes and cause network-wide effects on the overall Air Traffic Management (ATM) system. Quantifying the impact of weather is, therefore, a key feature to improve the decision-making process that enhances airport performance. It would allow airport operators to identify the relevant weather information needed, and help them decide on the appropriate actions to mitigate the consequences of adverse weather events. We present a methodology to evaluate the impact of adverse weather events on airport arrival performance (delay and throughput) and to define operational thresholds for significant weather conditions. Our results are computed from a dataset of over 750,000 flights on a major European hub and from local weather data during the period 2015-2018. We combine delay and capacity metrics at different airport operational stages for the arrival process (final approach, taxi-in and in-block). We introduce a new approach for modelling causal relationships between airport arrival performance indicators and meteorological events, which can be used to quantify the impact of weather in airport arrival conditions, predict the evolution of airport operational scenarios and support airport decision-making processes.