Reduce Delay Time Research Articles

Effect of the Uncertainty Level of Vehicle-Position Information on the Stability and Safety of the Car-Following Process

In recent years, the adaptive cruise control (ACC) system has become widely adopted. The vehicle-positioning system plays an important role in automotive platoon driving and can provide vehicle-position information through vehicle-to-vehicle communication. However, the acquired vehicle-position information often presents uncertainties given the existence of variations in the traffic environment and of noise in the vehicle-positioning system. These uncertainties, in turn, influence the car-following performance of a vehicle platoon. In this study, we employ the desired safety margin (DSM) model, an ACC control strategy, to investigate the influence of the uncertainty level of vehicle-position information (ULVPI) on string stability and car-following safety. The stability criterion of the DSM model with ULVPI is derived through linear stability theory. Theoretical analysis results are verified by numerical simulations. Analytical results indicate that a negative ULVPI value can expand the stable region and improve string stability and that a positive ULVPI value can reduce delay time. Moreover, a negative ULVPI value can improve car-following safety during the stopping and evolution processes, whereas a positive ULVPI values can increase the safety margins of vehicles during the starting process. In the car-following process, a negative ULVPI value can improve car-following safety and reduce rear-end collision risk. The variation in ULVPI values can improve string stability and reduce the risk of rear-end collisions when mean and standard deviation are reasonable. Therefore, the improvement of a vehicle’s dynamic performance, string stability, and safety relies on the effect of ULVPI in different traffic scenarios. These results are useful in designing different control strategies that stabilize traffic flow and improve traffic safety for vehicles with ACC systems.

Effect of straw-incorporation into farming soil layer on surface runoff under simulated rainfall

Returning crop straw into farmland is an important application and effective soil amendment method as it can increase soil organic matter to improve soil fertility and crop yield. In addition, this practice can help retain soil moisture and slow down the rainfall runoff rate, particularly on sloping farmland. This study uses laboratory experiments with a silt loam soil to examine the effects of wheat straw incorporation into cultivated farmland soil on rainfall-runoff. The experiments involved four straw incorporation rates (0 (control), 2, 4, and 8 t/ha), three rainfall intensities (80, 120 and 160 mm/h) and three slope gradients (10, 15 and 20°), carried out by a completely randomized combination design, with three repetitions. In all the experimental runs, the total rainfall amount was 100 mm per event. Our experimental results showed that the duration of runoff initiation time at straw incorporation rates of 2, 4 and 8 t/ha were increased by 1.63% to 104.93%, 6.16% to 111.67% and 15% to 141.25%, while the total runoff amounts decreased by 11.74% to 28.81%, 24.21% to 49.67% and 38.90% to 65.93%, compared with those of our control group (0 t/ha). The effects of straw incorporation on the runoff initiation delay time and runoff reduction were significant, particularly when the rainfall intensity was 120 mm/h and the slope was 10°. With increases in rainfall intensity and slope gradient, the runoff initiation time durations were decreased and the runoff rate increased. In conclusion, incorporating wheat straw into the farmland soil can delay the runoff initiation time and reduce runoff volume, to significantly increase rainwater storage into soil, thereby increasing the rainwater utilization rate and to benefit soil erosion control. This study can provide a data basis for farmland soil and water conservation research and practice.

Layout improvement of railway workshop using systematic layout planning (SLP) – A case study

Railways workshop is responsible for periodic overhauling of coaching stock and serves as a base for manufacturing, repairing and supply parts to Sheds/Depots. With increasing demand for rolling stock, workshop needs to increase its potential in maintenance and effectiveness to satisfy the demand of passengers. At the same time, the maintenance process needs to be equipped with the ability to have lower cost with higher effectiveness. Plant layout is one of the most effective ways to reduce the cost of maintenance for the improvement in productivity. It also increases good workflow in the production route. This Paper describes existing workshop layout, coach flow analysis that will include areas and distances among different shops. After studying the present layout, it has been found that there is scope of reduction in time delay in maintenance. Problems of movement of coaches in a long line, interrupted flow and useless area of the plant are existing. Considering these problems, Systematic layout planning (SLP) is the best method to improve workshop layout, which shows step-by-step improvement in layout and evaluation of layout. This method suggests a new workshop layout that improves the flow among the shops and helps to decrease movement in the workshop.

Adaptive Software-defined Network Controller for Multipath Routing based on Reduction of Time

Software-defined network (SDN) is a new paradigm in the networking that makes a programmability and intelligence the networks. The main SDN characterize is separating network management (control plane) from the forwarding device (data plane). SDN logically centralizes the network with the programmable controller which collects global knowledge about the network. The SDNs can improve the performance of the routing packets in the networks because of agility and the ability to create a policy for a driven network. In the multipath routing, the SDNs controller is responsible to calculate the routes of optimum path and alternative path wherever a link is failed. However, a high delay time calculation of selecting optimum and alternative paths in multipath routing by the SDN controller is observed in the recent investigations. In this paper, we propose an efficient algorithm for SDN multipath routing controller. The mechanism of the proposed approach calculates the best path from the source to the destination which is based on using adaptive packet size and observing network link capacity. The proposed algorithm considers reducing delay time of the link handling when the flow traffic switches from the main path to the recovery path. As a result, this approach is compared to some state of the arts according to the delay time of choosing the best path and alternative paths in a given network topology. SDN based on the proposed algorithm consumed approximately 1 ms for selecting recovery routes. On the other hand, the proposed algorithm can be integrated to an SDN controller which provides better consolidation of transmission for sensitive applications as video streaming.

Research and implementation of no-tillage information monitoring strategy based on Hadoop

Based on the Hadoop, this paper uses linear regression algorithm to study the intelligent monitoring strategy of no-tillage information. In this paper, the regional computers in this system use Flume and Kafka to transfer large amounts of farming information from local node databases to HDFS (Hadoop Distributed File System), then process this data with Spark, whatever, the system uses time series linear regression algorithm to predict the fault of no-tillage. Compared with the no-tillage designed before, the system described in this paper not only reduces time delay but also improves the fault tolerance of data storage and the system stability. Field experiments have proved that the research of this strategy has an accuracy rate of up to 90%, which reduces the huge economic losses caused by machine failure.

Application of Hybrid SWARA–BIM in Reducing Reworks of Building Construction Projects from the Perspective of Time

One of the major issues of the construction industry has been the “reworks” that affect the time, quality, and cost of projects. Therefore, reworks and the ineffective use of site resources and materials will always result in significant losses on projects. The development of information technology has led to the widespread use of Building Information Modelling (BIM) to enhance the delivery of more sustainable building construction projects. The purpose of this study is to combine the Step-wise Weight Assessment Ratio Analysis (SWARA) method and BIM technologies to identify and reduce time delays caused by reworks in construction projects. Firstly, 49 rework causes in residential buildings were identified and ranked. Then, BIM was generated and compared to the initial model. It was observed that working hours were reduced by 4.6%. Moreover, using an Earned Value Management (EVM) system, a 0.06 increase in Schedule Performance Index (SPI) factor was illustrated. Results obtained by this study provide an effective step in reducing a project’s time in the construction industry.

A collaborative cloud-edge computing framework in distributed neural network

The emergence of edge computing provides a new solution to big data processing in the Internet of Things (IoT) environment. By combining edge computing with deep neural network, it can make better use of the advantages of multi-layer architecture of the network. However, the current task offloading and scheduling frameworks for edge computing are not well applicable to neural network training tasks. In this paper, we propose a task model offloading algorithm by considering how to optimally deploy neural network model into the edge nodes. An adaptive task scheduling algorithm is also designed to adaptively optimize the task assignment by using the improved ant colony algorithm. Based on them, a collaborative cloud-edge computing framework is proposed, which can be used in the distributed neural network. Moreover, this framework sets up some mechanisms so that the cloud can collaborate with edge computing in the work. The simulation results show that the framework can reduce time delay and energy consumption, and improve task accuracy.

Reducing neurosurgical theatre start time delays by seventy minutes through application of the ‘Golden Patient’ initiative

Background This project’s focus was on improving neurosurgical theatre efficiency through the application of Javed et al's Golden Patient initiative to the emergency theatre setting. This initiative has not previously been used in neurosurgery, so we have had to consider how to adapt it. Phase I’s primary objective was to quantify theatre start time delays. Phase II assessed whether introducing the initiative reduced the delays. Methodology We performed an observational retrospective service evaluation project. Data was collected on weekday theatre start times over 12-week periods pre- and post-initiative. We quantified the delay in theatre start times and recorded the reasons for delays. Following the initiative's introduction, we repeated the evaluation process. Mean and median theatre start times were compared. An ANOVA test was used to confirm statistical significance. Results Data was collected on 49 days and on 48 days over 12-week periods in both Phase I and II respectively. Phase I of this project identified that there was on average an 86.7 minute delay in starting the theatre each day. The theatre start time was delayed in 91.7% of cases. A 72.3 minute reduction in the theatre start time delay was noted following the initiative’s introduction (p < .0005), with an improvement in the average emergency theatre start time from 09:56 to 08:44 (08:30 is the recognised theatre start time). We have identified hospital-wide and doctor-related contributing factors which require further attention, most notably, relating to issues around transferring patients from the ward to theatre. Conclusions We have identified a statistically significant improvement in reducing theatre start time delays following the introduction of the initiative. This relatively simple intervention improved communication amongst the multidisciplinary team and led to a notable improvement in the service provided to patients by reducing start time delays. Through tackling identified areas, we hope to further reduce theatre start time delays leading not only to financial savings but also to further improvements in the quality of care provided to our neurosurgical patients.

Finding the Reasons for the Delay Time in a Highway by Analyzing the Travel Time, Delay Time and Traffic Flow Data

The objectives of this study are to show a comparison among travel time, running time, delay in peak and off-peak hours on different days of a week, and reasons behind the delay time. Moving car observer method has been carried out to count the traffic flow, journey time, running time, and delay time. Total vehicle flow, and comparative vehicle flow during the peak hour and off-peak hour for workdays and weekend days were surveyed to show a relationship between delay time and traffic flow. As the traffic flow increases the delay time also will increase. To measure the reasons behind the delay time of Fulbarigate-Daulatpur road, spot speed study was done in two intersections of the road. The 15th percentile speed for Religate intersection road is 10 K.P.H. That means 85% of vehicles tends to go faster than 10 K.P.H. in this section. And hence vehicles with less than or equal 10 K.P.H. are responsible for increasing the delay time in this area. This speed limit should be prohibited in this section to reduce delay time and congestion. For the Mohosin More road intersection, the prohibited speed is also 10 K.P.H. Easy bike and Mahindra account for the congestion of these intersections and tend to stop in these intersections to collect passengers which creates unwanted queue in this study area. Controlling traffic flow at intersections can be a possible way to reduce the congestion rate of Fulbarigate-Daulatpur road.

Stroke patient's alarm choice: General practitioner or emergency medical services.

ObjectivesStroke patients should be treated as soon as possible since the benefit of reperfusion therapies is highly time‐dependent. The proportion of patients eligible for reperfusion therapy is still limited, as many patients do not immediately alarm healthcare providers. The choice of healthcare system entrance influences the time of arrival in the hospital. Therefore, we assessed differences in these choices to obtain insight for strategies to reduce time delays in acute stroke patients.Materials and MethodsPatients with suspected acute stroke admitted to the participating hospitals received a questionnaire. We assessed differences between patients who initially alarmed the general practitioner (GP) and patients who directly alarmed the emergency medical services (EMS). Additionally, we assessed regional differences and patient trajectories after medical help was sought.ResultsWe included 163 patients. Most patients alarmed the GP as primary healthcare provider (n = 104; 64%), and median onset‐to‐door times were longer in these patients (466 minutes [IQR 149–1586]) compared to patients directly alarming the EMS (n = 59; 36%) (90 minutes [IQR 45–286]). This was even more pronounced in less densely populated areas. Patients who alarmed the GP first, more often had patient delay >15 minutes, hesitated to burden healthcare providers and underestimated symptomatology.ConclusionsOur results showed that patients who alarmed the GP first instead of the EMS differed in several factors that are potentially modifiable. Strategies to achieve reduction of vital prehospital time delays and to improve patient outcome are optimizing public awareness campaigns and GP triage along with adjusting current guidelines by enabling and focusing on immediate involvement of the EMS once acute stroke is suspected.

Reliable and Efficient Content Sharing for 5G-Enabled Vehicular Networks

Conditional privacy preservation and message authentication serve as the primary research issues in terms of security in vehicular networks. With the arrival of 5G era, the downloading speed of network services and the message transmission speed have significantly improved. Consequently, the content exchanged by users in vehicular networks is not limited to traffic information, and vehicles moving at high speeds can share a wide variety of contents. However, sharing content reliably and efficiently remains challenging owing to the fast-moving character of vehicles. To solve this problem, we propose a reliable and efficient content sharing scheme in 5G-enabled vehicular networks. The vehicles with content downloading requests quickly filter the adjacent vehicles to choose capable and suitable proxy vehicles and request them for content services. Thus, the purpose of obtaining a good hit ratio, saving network traffic, reducing time delay, and easing congestion during peak hours can be achieved. The security analysis indicates that the proposed scheme meets the security requirements of vehicular networks. Our cryptographic operations are based on the elliptic curve, and finally, the proposed scheme also displays favorable performance compared to other related schemes.

Reducing Delay Time at Signal Controlled Junction with the Help of Actuated Control

Reducing Delay Time at Signal Controlled Junction with the Help of Actuated Control

A Time-Delay-Bounded Data Scheduling Algorithm for Delay Reduction in Distributed Networked Control Systems

As a key feature of networked control systems (NCSs), the time delays induced by communication medium sharing and data exchange over the system components could largely degrade the NCS performances or may even cause system instability, and thus, it is of critical importance to reduce time delays within NCSs. This paper studies the time-delay reduction problem in distributed NCSs and presents a dual-way data scheduling mechanism for time-delay reductions in delay-bounded NCSs with time-varying delays. We assess the time delays and their influences on the NCSs first with various delay factors being considered and then describe a one-way scheduling mechanism for network-delay reductions in NCSs. Based upon such a method, a dual-way scheduling algorithm is finally proposed for distributed NCSs with different types of transmitted data packets. Experiments are conducted on a remote teaching platform to verify the effectiveness of the proposed dual-way scheduling mechanism. Results demonstrate that, with the stability time-delay bound considered within the scheduling process, the proposed mechanism is effective for NCS time-delay reductions while addressing the stability, control accuracy, and settling time issues efficiently. Such a proposed mechanism could also be implemented together with some other existing control algorithms for time-delay reductions in NCSs. Our work could provide both useful theoretical guidance and application references for stable tracking control of delay-bounded NCSs.

Implementation of parallel computing and adiabatic logic in full adder design for ultra-low-power applications

In this work, the idea of parallel computing for a full adder has been proposed. Based on parallel computing, a new architecture of full adder (A-I) has been proposed in which the input needs to pass through only two transistors to reach the output node which results in reduced delay time. The second design of full adder (A-II) has been proposed with two-phase clocked adiabatic static complementary metal oxide logic which results in decreased power dissipation. The third design of full adder (A-III) uses parallel computing for both sum and carry generation. In A-III, a buffer has been introduced to restore the logic level which proves the drive capability of parallel computing logic. The adiabatic logic-based proposed design A-II shows a 61.95% improved power delay product (PDP) as compared to the best-reported body biasing approach-based adder, whereas the fully parallel computing-based design A-III shows a 53.29% improved PDP as compared to double pass transistor-based full adder. Post layout results of the proposed design A-III verified the functionality of proposed parallel computing logic. The proposed designs also perform well under varied temperature conditions. These designs show satisfactory performance at low voltages, whereas the use of adiabatic logic makes these designs energy efficient for low power applications.

Systems analysis for deployment of internet of things (IoT) in the maritime industry

Various industries are undergoing transformation given recently available pervasive sensors, low-cost and low-latency digital communication, and distributed control technologies. The objective of this paper is to support the introduction of Internet of things (IoT) technologies in the maritime industry. The maritime industry is analyzed as a system of systems to define performance criteria and functions to be modeled and analyzed through simulation. In this case, the simulation of a shipping system includes models of operation, cargo loading, fuel loading, and docking for maintenance. In the simulation, various kinds of IoT technologies are defined by several input parameters. By changing the parameters, the simulator evaluates the impact of those technologies quantitatively. As a case study, 11 IoT technologies are evaluated and compared. The result reveals several insights that weight of the ship is the most impactful for the profit, controlling damage of the ship’s hull by operation is the most important for safety, and improvement in efficiency at ports is the key to reducing delay time in operation. Moreover, this paper shows that the sensitivity analysis by changing the input parameters can support the decision making of how much investment will be effective in considering the technologies’ levels.

New genetic algorithm for structural active control by considering the effect of time delay

This study focuses on a new active control method by improving specification of a well-known intelligent numerical search method, that is the genetic algorithm. The proposed scheme modifies the specifications of the common genetic algorithm by using two strategies. First, a new constrained objective function is proposed. Then, a procedure is designed for evaluating and reducing time delay in control process. These procedures lead to a new generation of the genetic algorithm, which is more reliable. For verifying the efficiency of the proposed method, vibrations of several structures are controlled, and results are compared with other well-known methods such as the common genetic algorithm, linear quadratic regulator, and equivalent critical damping. Numerical results clearly prove the accuracy and efficiency of the proposed control process in comparison with other methods.

Bureaucratic Competence and Procurement Outcomes

Abstract To what extent does a more competent public bureaucracy contribute to better economic outcomes? We address this question in the context of the US federal procurement of services and works, by combining contract-level data on procurement performance and bureau-level data on competence and workforce characteristics. We use the death occurrences of specific types of employees as instruments and find that an increase in bureau competence causes a significant and economically important reduction in (a) time delays, (b) cost overruns, and (c) number of renegotiations. Cooperation within the office appears to be a key driver of the findings. (JEL D73, H11, H57, L26).

Stepwise stroke recognition through clinical information, vital signs, and initial labs (CIVIL): Electronic health record-based observational cohort study.

Stroke recognition systems have been developed to reduce time delays, however, a comprehensive triaging score identifying stroke subtypes is needed to guide appropriate management. We aimed to develop a prehospital scoring system for rapid stroke recognition and identify stroke subtype simultaneously. In prospective database of regional emergency and stroke center, Clinical Information, Vital signs, and Initial Labs (CIVIL) of 1,599 patients suspected of acute stroke was analyzed from an automatically-stored electronic health record. Final confirmation was performed with neuroimaging. Using multiple regression analyses, we determined independent predictors of tier 1 (true-stroke or not), tier 2 (hemorrhagic stroke or not), and tier 3 (emergent large vessel occlusion [ELVO] or not). The diagnostic performance of the stepwise CIVIL scoring system was investigated using internal validation. A new scoring system characterized by a stepwise clinical assessment has been developed in three tiers. Tier 1: Seven CIVIL-AS3A2P items (total score from -7 to +6) were deduced for true stroke as Age (≥ 60 years); Stroke risks without Seizure or psychiatric disease, extreme Sugar; "any Asymmetry", "not Ambulating"; abnormal blood Pressure at a cut-off point ≥ 1 with diagnostic sensitivity of 82.1%, specificity of 56.4%. Tier 2: Four items for hemorrhagic stroke were identified as the CIVIL-MAPS indicating Mental change, Age below 60 years, high blood Pressure, no Stroke risks with cut-point ≥ 2 (sensitivity 47.5%, specificity 85.4%). Tier 3: For ELVO diagnosis: we applied with CIVIL-GFAST items (Gaze, Face, Arm, Speech) with cut-point ≥ 3 (sensitivity 66.5%, specificity 79.8%). The main limitation of this study is its retrospective nature and require a prospective validation of the CIVIL scoring system. The CIVIL score is a comprehensive and versatile system that recognizes strokes and identifies the stroke subtype simultaneously.

A hybrid approach for scheduling applications in cloud computing environment

Cloud computing plays an important role in our daily life. It has direct and positive impact on share and update data, knowledge, storage and scientific resources between various regions. Cloud computing performance heavily based on job scheduling algorithms that are utilized for queue waiting in modern scientific applications. The researchers are considered cloud computing a popular platform for new enforcements. These scheduling algorithms help in design efficient queue lists in cloud as well as they play vital role in reducing waiting for processing time in cloud computing. A novel job scheduling is proposed in this paper to enhance performance of cloud computing and reduce delay time in queue waiting for jobs. The proposed algorithm tries to avoid some significant challenges that throttle from developing applications of cloud computing. However, a smart scheduling technique is proposed in our paper to improve performance processing in cloud applications. Our experimental result of the proposed job scheduling algorithm shows that the proposed schemes possess outstanding enhancing rates with a reduction in waiting time for jobs in queue list.

A priority-based queuing model approach using destination parameters forreal-time applications on IPv6 networks

In the early days of the Internet architecture, the most important aim is to transmit data over packet switched networks. The traditional Internet architecture used in these networks lacks quality of service. However, today, as realtime applications increase, it is needed. There are approaches to improving the quality of service using the flow label field in the Internet Protocol version 6 header. In this study, a novel algorithm that uses destination network parameters to reduce queuing and end-to-end delay is created. A round-robin-based time-aware priority queue new model is used within this algorithm. Data packets using this proposed queue are prioritized with metric values of the destination network. In order to provide end-to-end service quality, the prioritization value is used by placing it in the flow label field. For this purpose, a new approach to the use of this field is proposed. Delay, one of the most important factors affecting quality of service, is reduced with the proposed algorithm and flow label usage approach. As a result, the reduction in delay times between 22 and 39 ms resulted in various improvement rates between 16.79% and 35.13%.