Throughput Delay Research Articles

Cooperative MAC Protocol based on Best Data Rate (CMAC-DR)

As wireless signals are broadcast in nature, which implies that, a broadcast communication purposive to a predetermined destination may be received by a non-intended intermediate station. Cooperative transference, which employ interposed stations to pass on the eavesdropped data to attain the contrast gains, has a substantial capability to revamp the channeling effectiveness in wireless systems. In this it is evident that having cooperation amid stations in a wireless system can accomplish higher throughput with enhanced network lifetime. Proffered work bestows a model for medium access layer called Cooperative MAC protocol based on optimal Data Rate (CMAC-DR). In the proffered work, stations with more data rate aid stations having lesser data rate in their communication by redirecting their congestion. In CMAC-DR model, utilizing the conveyance of eavesdropped information, potential helper stations with more data rate Send out Helper Ready to Send (HRTS), the stations with less data rate maintains a table, called Co-op table of potential helper stations, that can aid in its transmissions. During communication, the source station with low data rate chooses either transmitting by the way of a helper station, so that it lowers the end to end transference delay and increases the throughput or opt only direct transmission, if no potential helper is found or if CMAC-DR becomes an overhead. By analyzing varied simulated scenarios, CMAC-DR evaluates the elevation in the overall network lifetime, throughput and minimization of delay. The CMAC-DR protocol is unambiguous and in accordant with legacy 802.11 also when compared to this, we find improved performance in terms of delay throughput and network lifetime since data rate is considered as relay selection condition.

Don't Let the Sun Rise on Small Bowel Obstruction Without Surgical Consultation-Redefining Nonoperative Management Pathways.

Introduction: Small bowel obstruction (SBO) is a common cause of hospital admission leading to resource utilization. The majority of these patients require non-operative management (NOM) which can lead to increased length of stay (LOS), readmissions, resource utilization, and throughput delays. Early surgical consultation (SC) for SBO may improve efficiency and outcomes. Methods: We implemented an institution-wide intervention (INT) to encourage early SC (<1day of diagnosis) for SBO patients in July 2022. A retrospective analysis was performed on all patients with SBO requiring NOM from January 2021 to June 2023, categorized into pre- and post-INT groups. The primary outcome was the number of SC's and secondary outcomes were early SC (<1day of diagnosis), utilization of SBFT, LOS, 30-day readmission, and costs of admission. Results: A total of 670 patients were included, 438 in the pre-INT and 232 in the post-INT group. Overall, SBFT utilization was significantly higher in cases with SC (17.2% vs 41.4%, P < .001). Post-INT patients were more likely to receive SC (94.0% vs 83.3%, P < .001) and increased SBFT utilization (47.0% vs 33.6%, P = .001). Additionally, early SC improved significantly in the post-INT group (74.3% vs 65.7%, P = .03). There was no difference in LOS between groups (4.0 vs 3.8 days, P = .48). There was a trend toward decreased readmission rates in the INT group at 30days (7.3% vs 11.0%, P = .13) and reduced direct costs in the INT group (US$/admission = 8467 vs 8708, P = .1). Conclusion: Hospital-wide interventions to increase early surgical involvement proved effective by improving early SC, increased SBFT utilization, and showed a trend towards decreased readmission rates and direct costs.

Weighted cluster in mobile ad hoc network using enhanced long short‐term memory‐based squid game optimizer concept

SummaryA collection of autonomous frameworks will most likely make up a wireless mobile network. They are not solely dependent on a wireless network with no established infrastructure. In the mobile ad hoc network, it is highly challenging to safeguard the viability of the cluster head (CH) within a cluster; therefore, this research provides a big scope for routing utilizing enhanced long short‐term memory–squid game optimizer (ELSTM‐SGO). The quality of service attribute of the nodes determines which CH is chosen within them. How long the CH will hold will depend on the weight applied to it. The best CH is chosen using an ELSTM‐SGO routing method within a cluster, and the best CH will improve the routing. The three procedures that make up the developed ELSTM‐SGO protocol are SGO, CH selection, and cluster's gateway. The wireless system's energy consumption, buffer size, packet delivery ratio, routing overhead and end‐to‐end delay throughput represent the characteristics used in the suggested approach. Weighted clustering approach is evaluated on the system. According to the results of the experimental research, ELSTM‐SGO yields superior results for preserving the resiliency of the CH.

Characteristics and patient impact of boarding in the pediatric emergency department, 2018–2022

ObjectivesBoarding admitted patients in the emergency department is an important cause of throughput delays and safety risks in adults, though has been less studied in children. We assessed changes in boarding in a pediatric ED (PED) from 2018 to 2022 and modeled associations between boarding and select quality metrics. MethodsWe performed a retrospective analysis of PED patients admitted to non-psychiatric services, broken into four periods: pre-COVID-19 (Period I, 01/2018–02/2020), early pandemic (II, 03/2020–06/2021), COVID-19 variants (III, 07/2021–06/2022), and non-COVID respiratory viruses (IV, 07/2022–12/2022). Patients were classified as critical (intensive care units (ICU)) or acute care (non-ICU inpatient services) based on their initial bed request. We compared median boarding times with Kruskal-Wallis tests. We assessed the relationship between boarding time and hospital length-of-stay (LOS) through hazard regression models, and the association between boarding time and PED return visit, readmission, and patient safety events through adjusted logistic regressions. ResultsMedian PED boarding time significantly increased from Period I (acute: 2.4 h; critical: 3.0 h) to Period II (acute: 3.0 h, critical: 4.0 h) to Period III (acute: 4.4 h, critical: 6.6 h) to Period IV (acute: 6.2 h; critical: 9.5 h). On survival analysis, as boarding time increased, hospital LOS increased for acute admissions and decreased for critical admissions. Increased acute care boarding time was associated with higher odds of a filed safety report. ConclusionsSince July 2021, PED boarding time increased for admitted children across acute and critical admissions. The relationship between acute care boarding and longer hospital LOS suggests a resource-inefficient, self-perpetuating cycle that demands multi-disciplinary solutions.

Identifying delays in the outpatient interventional radiology department: a quality improvement study.

In the post-COVID 19 environment, it has become increasingly important for healthcare services to optimise service delivery for the benefit of both patients and staff. The project purpose was to quantify and determine causes of throughput delays in a newly established outpatient angiography service in a public hospital setting. This single-centre study obtained quantitative and qualitative data for 81 consecutive outpatient interventional radiology (IR) examinations over a 3-month period via survey and retrospective analysis of electronic medical records. Staff participating in data collection were able to record multiple causes for delay in a single case and were also able to include comments, allowing for more detailed descriptions of the delays that occurred. A total of 93 delay factors were identified in 73 of the 81 outpatient interventional examinations and grouped into six categories via thematic analysis. Availability of the IR room (40%), availability of the radiologist (28%) and insufficient documentation (18%) were identified as the most frequent causes for delay. Linear regression analysis showed that documentation (P = 0.0002) and room unavailability (P = 0.022) were independently associated with procedural starting delay. Delays to the IR procedural start time occurred in 90% of cases (73/81). This study identified the causes for delays in outpatient interventional procedures. This information can be used to improve service delivery in IR departments.

Throughput delays: causes, predictors, and outcomes – observational cohort in a Swiss emergency department

Optimal throughput times in emergency departments can be adjudicated by emergency physicians. Emergency physicians can also define causes of delays during work-up, such as waiting for imaging, clinical chemistry, consultations, or exit blocks. For adequate streaming, the identification of predictors of delays is important, as the attribution of resources depends on acuity, resources, and expected throughput times. This observational study aimed to identify the causes, predictors, and outcomes of emergency physician-adjudicated throughput delays. Two prospective emergency department cohorts from January to February 2017 and from March to May 2019 around the clock in a tertiary care centre in Switzerland were investigated. All consenting patients were included. Delay was defined as the subjective adjudication of the responsible emergency physician regarding delay during emergency department work-up. Emergency physicians were interviewed for the occurrence and cause of delays. Baseline demographics, predictor values, and outcomes were recorded. The primary outcome - delay - was presented using descriptive statistics. Univariable and multivariable logistic regression analyses were performed to assess the associations between possible predictors and delays and hospitalization, intensive care, and death with delay. In 3656 (37.3%) of 9818 patients, delays were adjudicated. The patients with delays were older (59 years, interquartile range [IQR]: 39-76 years vs 49 years, IQR: 33-68 years) and more likely had impaired mobility, nonspecific complaints (weakness or fatigue), and frailty than the patients without delays. The main causes of delays were resident work-up (20.4%), consultations (20.2%), and imaging (19.4%). The predictors of delays were an Emergency Severity Index of 2 or 3 at triage (odds ratio [OR]: 3.00; confidence interval [CI]: 2.21-4.16; OR: 3.25; CI: 2.40-4.48), nonspecific complaints (OR: 1.70; CI: 1.41-2.04), and consultation and imaging (OR: 2.89; CI: 2.62-3.19). The patients with delays had an increased risk for admission (OR: 1.56; CI: 1.41-1.73) but not for mortality than those without delays. At triage, simple predictors such as age, immobility, nonspecific complaints, and frailty may help to identify patients at risk of delay, with the main reasons being resident work-up, imaging, and consultations. This hypothesis-generating observation will allow the design of studies aimed at the identification and elimination of possible throughput obstacles.

Design and Optimization Method of Intelligent Interconnection Decision System Based on Blockchain Technology

Blockchain, as the application of distributed computing and data storage, point-to-point transmission, encryption algorithm, consensus mechanism, and other technologies, has become an important hotspot of data technology in banks, securities, and other Internet enterprises. In view of the problems of delay and large throughput in the current intelligent interconnection system of block chain, this paper proposes an optimization method of intelligent interconnection of block chain technology, so as to improve the performance of the system. In this paper, firstly, the development of intelligent interconnection and the related concepts of intelligent interconnection system optimization are put forward. Then, the related algorithms of blockchain are proposed, including the consensus algorithm of blockchain and the throughput delay algorithm of blockchain. Finally, in the experimental part, the blockchain technology is deeply studied, and the advantages and internal structure of blockchain are clearly analyzed. Then, by comparing the consensus of blockchain to optimize intelligent interconnected system and comparing blockchain technology with ordinary technology to optimize intelligent interconnected system, it is concluded that blockchain plays a positive role in optimizing intelligent interconnected system and also promotes the optimization of intelligent system. Therefore, we should introduce the related technologies of blockchain into the optimization of intelligent interconnection system, and its blockchain technology analysis can make up for the shortcomings of intelligent interconnection system. It also shows that blockchain technology is suitable for many information research fields and plays an irreplaceable role. The blockchain system consists of six different hierarchies, mainly network data layer and blockchain consensus layer. The data layer mainly encrypts the data related to blockchain. The consensus layer recognizes the main algorithms of blockchain, which can encapsulate the network information nodes of blockchain. Therefore, when blockchain carries out relevant information analysis algorithms, it mainly relies on blockchain consensus algorithm. It is beneficial to analyze the complex information of the system and promote the optimal development of blockchain.

Optimized Energy-Efficient Routing Protocol for Wireless Sensor Network Integrated with IoT: An Approach Based on Deep Convolutional Neural Network and Metaheuristic Algorithms

Wireless sensor networks (WSNs) have emerged as a significant architecture for data collection in various applications. However, the integration of WSNs with IoT poses energy-related challenges due to limited sensor node energy, increased energy consumption for wireless data sharing, and the necessity of energy-efficient routing protocols for reliable transmission and reduced energy consumption. This paper proposes an optimized energy-efficient routing protocol for wireless sensor networks integrated with the Internet of Things. The protocol aims to improve network lifetime and secure data transmission by identifying the optimal Cluster Heads (CHs) in the network, selected using a Tree Hierarchical Deep Convolutional Neural Network. To achieve this, the paper introduces a fitness function that takes into account cluster density, traffic rate, energy, collision, delay throughput, and distance from the capacity node. Additionally, the paper considers three factors, including trust, connectivity, and QoS, to determine the best course of action. The paper also presents a novel optimization approach, using the hybrid Marine Predators Algorithm (MPA) and Woodpecker Mating Algorithm (WMA), to optimize trust, connectivity, and QoS parameters for optimal path selection with minimal delay. The simulation process is implemented in MATLAB, and the developed method’s efficiency is evaluated using several performance metrics. The results of the simulation demonstrate the effectiveness of the proposed method, which achieved significantly lower delay (99.67%, 98.38%, 89.34%, and 97.45%), higher delivery ratio (89.34%, 89.34%, 83.12%, and 88.96%), and lower packet drop (93.15%, 91.25%, 79.90%, and 92.88%) in comparison to existing methods. These outcomes indicate the potential of the optimized energy-efficient routing protocol to improve network lifetime and ensure secure data transmission in WSNs integrated with IoT.

Association between Covid-19 surge and emergency department patient flow and experience

BackgroundPreparations for Covid-19 in the Netherlands included hospital reconfigurations to increase capacity for the expected surge at the emergency department (ED). We describe patients’ ED length of stay (LOS), crowding and experiences of patients with respiratory complaints during the first Covid-19 peak. MethodsRetrospective analysis of demand, ED LOS, crowding, and a patient experience survey during a 12-week period in 2020 and similar periods in 2018 and 2019. Crowding levels were calculated using the National ED OverCrowding Scale. ResultsThe number of patients with respiratory complaints increased significantly, while total ED numbers were unchanged. Although presentation during the Covid-19 peak and needing hospital admission were associated with a longer ED LOS in patients with respiratory complaints, significantly less crowding occurred compared with the 2018 and 2019 periods. Increased ED LOS was associated with lower patient experience scores. ConclusionAdvanced warning and its associated preparation within the hospital and the community prevented significant delays in ED throughput during the first Covid-19 peak.

Sandwich Hybridization Assay for In Situ Real-Time Cyanobacterial Detection and Monitoring: A Review.

As cyanobacterial harmful algal bloom (cHAB) events increase in scale, severity, frequency, and duration around the world, rapid and accurate monitoring and characterization tools have become critically essential for regulatory and management decision-making. The composition of cHAB-forming cyanobacteria community can change significantly over time and space and be altered by sample preservation and transportation, making in situ monitoring necessary to obtain real-time and localized information. Sandwich hybridization assay (SHA) utilizes capture oligonucleotide probes for sensitive detection of target-specific nucleic acid sequences. As an amplification-free molecular biology technology, SHA can be adapted for in-situ, real-time or near real-time detection and qualitatively or semi-quantitatively monitoring of cHAB-forming cyanobacteria, owing to its characteristics such as being rapid, portable, inexpensive, and amenable to automation, high sensitivity, specificity and robustness, and multiplexing (i.e., detecting multiple targets simultaneously). Despite its successful application in the monitoring of marine and freshwater phytoplankton, there is still room for improvement. The ability to identify a cHAB community rapidly would decrease delays in cyanotoxin analyses, reduce costs, and increase sample throughput, allowing for timely actions to improve environmental and human health and the understanding of short- and long-term bloom dynamics. Real-time detection and quantitation of HAB-forming cyanobacteria is essential for improving environmental and public health and reducing associated costs. We review and propose to apply SHA for in situ cHABs monitoring.

AI-federated novel delay-aware link-scheduling for Industry 4.0 applications in IoT networks

Purpose With the advent of AI-federated technologies, it is feasible to perform complex tasks in industrial Internet of Things (IIoT) environment by enhancing throughput of the network and by reducing the latency of transmitted data. The communications in IIoT and Industry 4.0 requires handshaking of multiple technologies for supporting heterogeneous networks and diverse protocols. IIoT applications may gather and analyse sensor data, allowing operators to monitor and manage production systems, resulting in considerable performance gains in automated processes. All IIoT applications are responsible for generating a vast set of data based on diverse characteristics. To obtain an optimum throughput in an IIoT environment requires efficiently processing of IIoT applications over communication channels. Because computing resources in the IIoT are limited, equitable resource allocation with the least amount of delay is the need of the IIoT applications. Although some existing scheduling strategies address delay concerns, faster transmission of data and optimal throughput should also be addressed along with the handling of transmission delay. Hence, this study aims to focus on a fair mechanism to handle throughput, transmission delay and faster transmission of data. The proposed work provides a link-scheduling algorithm termed as delay-aware resource allocation that allocates computing resources to computational-sensitive tasks by reducing overall latency and by increasing the overall throughput of the network. First of all, a multi-hop delay model is developed with multistep delay prediction using AI-federated neural network long–short-term memory (LSTM), which serves as a foundation for future design. Then, link-scheduling algorithm is designed for data routing in an efficient manner. The extensive experimental results reveal that the average end-to-end delay by considering processing, propagation, queueing and transmission delays is minimized with the proposed strategy. Experiments show that advances in machine learning have led to developing a smart, collaborative link scheduling algorithm for fairness-driven resource allocation with minimal delay and optimal throughput. The prediction performance of AI-federated LSTM is compared with the existing approaches and it outperforms over other techniques by achieving 98.2% accuracy. Design/methodology/approach With an increase of IoT devices, the demand for more IoT gateways has increased, which increases the cost of network infrastructure. As a result, the proposed system uses low-cost intermediate gateways in this study. Each gateway may use a different communication technology for data transmission within an IoT network. As a result, gateways are heterogeneous, with hardware support limited to the technologies associated with the wireless sensor networks. Data communication fairness at each gateway is achieved in an IoT network by considering dynamic IoT traffic and link-scheduling problems to achieve effective resource allocation in an IoT network. The two-phased solution is provided to solve these problems for improved data communication in heterogeneous networks achieving fairness. In the first phase, traffic is predicted using the LSTM network model to predict the dynamic traffic. In the second phase, efficient link selection per technology and link scheduling are achieved based on predicted load, the distance between gateways, link capacity and time required as per different technologies supported such as Bluetooth, Wi-Fi and Zigbee. It enhances data transmission fairness for all gateways, resulting in more data transmission achieving maximum throughput. Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation. Findings Our proposed approach outperforms by achieving maximum network throughput, and less packet delay is demonstrated using simulation. It also shows that AI- and IoT-federated devices can communicate seamlessly over IoT networks in Industry 4.0. Originality/value The concept is a part of the original research work and can be adopted by Industry 4.0 for easy and seamless connectivity of AI and IoT-federated devices.

Congestion-free routing based on a hybrid meta-heuristic algorithm to provide an effective routing protocol by analyzing the significant impacts of QoS parameters in a dynamic VANET environment

Abstract A definitive form of Mobile Ad-hoc Network (MANET) is the Vehicular Ad-hoc Network (VANET), which delivers data communication using wireless transmission with the collection of vehicular nodes in a vehicular environment. The main goal of this VANET is to improve the Quality of Service (QoS) which is road safety, environmental kindliness, and logistics in intelligent transport. Moreover, mobility and routing play an important challenge for information interchange to the process in the VANET environment. In developing countries, smart cities are encountering problematic traffic congestion. Furthermore, in cluster communications, stable cluster formation and maintenance with the guarantying QoS has always remained a great challenge. In order to overcome the above-mentioned issue, this article proposes a congestion-free routing process ensuring QOS parameters. The main objective of the proposed scheme is to analyze the impact of QOS parameters while choosing the best routing path in Vehicular communication. The scheme also introduces the Hybrid-Harris Hawks Black Widow optimization-based VANET (H-HHBW-VANET) algorithm to improve QoS for routing between nodes. This algorithm differs from other algorithms in terms of optimal solution generation, which makes it more efficient. The proposed work is implemented in the working platform of NS2 to analyze the parameters such as Drop, Delay, Energy Consumption, Throughput, and Fairness Index. The simulation results provide better QOS service in terms of low energy consumption with higher throughput and low delay.

Improved Priority-based Congestion Control Protocol for Multi-Access Edge Computing (MAEC) Using IoT-based Wearable Devices for Neurological Diseases Diagnosis

Stroke is one of the fatal diseases that affect the brain and causes death within 3 to 10 hours. However, most of the deaths caused by a stroke can be avoided with the identification of the nature of stroke and react to it in a timely manner by intelligent health systems. Internet of Things (IoT) has become an important aspect in medical industry for monitoring of stroke related data/information using various wearable devices. Moreover, Multiple-Access Edge Computing (MAEC) is playing a major role for processing, analysing, and storing of data which leads to several researchers to compete in improving the mechanism of congestion control. In this paper, an improved Priority-based Congestion Control Protocol (iPCCP) is proposed for obtaining increased throughput, decreasing delay, effective resource utilization, and longer network lifetime by optimal energy consumption among IoT based sensor nodes. The proposed method categorizes the data-traffic into emergency and normal data. The packet delivery rate is considered for the normal data-traffic and retains the size of the buffer to improve the throughput and avoids the packet drops due to congestion. The energy consumption and network traffic load is reduced using the data aggregation and filtration technique. For emergency situations, priority-based routing scheme is used to have greater throughput and lesser delay. The performance of the proposed technique outperforms in term of traffic load, lifespan, energy consumption, and network throughput and simulation results are compared with other existing methods to show the improvement of the proposed work.

Effect of service differentiation on QoS in IEEE 802.11e enhanced distributed channel access: a simulation approach

The enhanced distributed channel access (EDCA) protocol is a supplement to IEEE 802.11 medium access control (MAC), ratified by IEEE 802.11e task group to support quality of service (QoS) requirements of both data and real-time applications. Previous research show that it supports priority scheme for multimedia traffic but strict QoS is not guaranteed. This can be attributed to inappropriate tuning of the medium access parameters. Thus, an in-depth analysis of the EDCA protocol and ways of tuning medium access parameters to improve QoS requirements for multimedia traffic is presented in this work. An EDCA model was developed and simulated using MATLAB to assess the effect of differentiating contention window (CW) and arbitration inter-frame space (AIFS) of different traffic on QoS parameters. The optimal performance, delay, and maximum sustainable throughput for each traffic type were computed under saturation load. Insight shows that traffic with higher priority values acquired most of the available channels and starved traffic with lower priority values. The AIFS has more influence on the QoS of EDCA protocol. It was also observed that small CW values generate higher packet drops and collision rate probability. Thus, EDCA protocol provides mechanism for service differentiation which strongly depends on channel access parameters: CW sizes and AIFS.

Handover evaluation of UMTS-WiMAX networks

Recently, data traffic movement through a wireless channel is assisted by suggesting and implementing many mechanisms, to achieve the speedy increasing importunity and popularity of the wireless networks. Various wireless technologies can be copulated to develop a heterogeneous network, which is a candidate towards (4G) networks. OPNET modeler (14.5) is used to design simulation modules of the heterogeneous network. During device connection between the worldwide interoperability for microwave access (WiMAX) and universal mobile telecommunication system (UMTS) networks, Performance metrics such as; Jitter end-to-end delay (E-2-E) Throughput is used. The results of the simulation are measured to determine the efficiency of the transfer using WiMAX-UMTS according to the selected metrics. The WiMAX-UMTS has shown valuable improvement in Process Durability, reduction of E-2-E delay, and Jitter. The maximum amount of data transfer and the least amount of delay and Jitter is at 250 sec. Because of the handover operations and data transfer momentum, the worst-case passes in the network when 618 sec is the minimum amount. The efficiency of throughput for WiMAX equal to 0.092666% as for the efficiency of throughput for UMTS equal to 4.633333*10-6 % whereas the E-2-E efficiency a delay equal to 0.5466%.

QMMAC: Quorum-Based Multichannel MAC Protocol for Wireless Sensor Networks.

In wireless sensor networks, energy conservation is a critical task. Thus, it is crucial to design an effective MAC protocol that minimizes energy consumption while guaranteeing high network throughput and low delay. In this article, we propose a quorum-based multichannel MAC protocol (QMMAC) for corona-based WSNs. QMMAC utilizes the multichannel communication feature and the quorum concept to greatly increase the throughput while conserving energy. The aim of this protocol is to allow each node and all its forwarders to wake up at the same time while avoiding collision and overhearing by separating their simultaneous communications using the multichannel feature. More precisely, the main idea of QMMAC is twofold. First, QMMAC wakeup scheduling is designed to minimize the end-to-end delay by allowing nodes to wake up at exactly the same time as their potential forwarders, whereas nodes that are not acting as forwarders for each other wake up at a completely different time, and thus overhearing, idle listening and collisions are avoided. Second, channel assignment, which also uses the concept of quorums, is used to share data channels so that there is no conflict or additional packet exchange required to negotiate the availability of channels. Thus, the end-to-end delay is further minimized as well as collisions between conflicting neighbors are avoided. Simulation results indicate that the network performance is improved by QMMAC in terms of energy efficiency, throughput and end-to-end delay.

Emergency department provider in triage: assessing site-specific rationale, operational feasibility, and financial impact.

Emergency department (ED) crowding is recognized as a critical threat to patient safety, while sub‐optimal ED patient flow also contributes to reduced patient satisfaction and efficiency of care. Provider in triage (PIT) programs—which typically involve, at a minimum, a physician or advanced practice provider conducting an initial screening exam and potentially initiating treatment and diagnostic testing at the time of triage—are frequently endorsed as a mechanism to reduce ED length of stay (LOS) and therefore mitigate crowding, improve patient satisfaction, and improve ED operational and financial performance. However, the peer‐reviewed evidence regarding the impact of PIT programs on measures including ED LOS, wait times, and costs (as variously defined) is mixed. Mechanistically, PIT programs exert their effects by initiating diagnostic work‐ups earlier and, sometimes, by equipping triage providers to directly disposition patients. However, depending on local contextual factors—including the co‐existence of other front‐end interventions and delays in ED throughput not addressed by PIT—we demonstrate how these features may or may not ultimately translate into reduced ED LOS in different settings. Consequently, site‐specific analysis of the root causes of excessive ED LOS, along with mechanistic assessment of potential countermeasures, is essential for appropriate deployment and successful design of PIT programs at individual EDs. Additional motivations for implementing PIT programs may include their potential to enhance patient safety, patient satisfaction, and team dynamics. In this conceptual article, we address a gap in the literature by demonstrating the mechanisms underlying PIT program results and providing a framework for ED decision‐makers to assess the local rationale for, operational feasibility of, and financial impact of PIT programs.

MAC Layer Communication Protocol design using Stochastic Network Calculusfor Underwater Agriculture Farming

: The hazardous in seawater network, channel utilization, and MAC layer protocol design induces the research challenges and opportunities of underwater acoustic communications, particularly in terms of throughput and transmission delay. In this research work, we propose the delay-tolerant MAC protocol with collision avoidance. Under_Water Medium Access control and Collision Avoidance -Wireless protocol (UWMACA-W) proposed for underwater Agriculture Farming. This research work also has compared the performance of the UWMACA-Wireless protocol with and without SNC. The growth of the plants inside the bubble can be exchanged to the base station by using the UWMACA-wireless protocol and also increases interface efficiency by taking account of the underwater acoustic channel's long delay time, as well as fixing the issues related to uncovered terminal issues. UWMACA-W method has higher performance than MACA-Wireless protocol, according to simulation testing on Riverbed modeler.

WITHDRAWN: Effective adaptive routing for Lossy networks using enhanced RPL in the heterogeneous network

Abstract In this network environment, the different applications of sensor have to generate a huge data traffic which includes basic sensing methods such as air pollution or environment checking. In this huge congested network, the two-standard objective methods, that are objective method 0 (OM0) and objective method 1 OM1 for Congested Networks that has to perform deprived routing paths by picking an already congested parental node and a greater number of retransmissions happened between the networks. So, it is required that to design a new effective Routing Protocol for various congested environments. In our paper, I observe the RPL protocol for various congested networks and developed a new routing protocol technique (QWL-RPL) related with information of queue and node-wise workload. Objective of our developed Routing protocol has to attain an Optimum shortest path in challengeable performance. Our proposed Objective method has to consider connectivity capacity and also representing status of congestion in particular node or device using information of queue in data or packet. Our proposed routing technique was implemented in Cooja environment for comparing with the existing techniques. The results of simulation are shown through Queue status information and balanced Workload routing protocol of RPL that can reduce the data traffic of a various networks as related with OM0 and OM1, exactly specified terms of average delay, ratio of packets transmission and reception, jitter delay and header overhead information. At last, the results shown as on average, 30%–50% reduced header overhead information, 15%–30% reduced in average throughput delay, 10%–30% improvement in PRR and 25%–40% reduced in jitter delay.

Data-Driven Construction of User Utility Functions from Radio Connection Traces in LTE

In recent years, the number of services in mobile networks has increased exponentially. This increase has forced operators to change their network management processes to ensure an adequate Quality of Experience (QoE). A key component in QoE management is the availability of a precise QoE model for every service that reflects the impact of network performance variations on the end-user experience. In this work, an automatic method is presented for deriving Quality-of-Service (QoS) thresholds in analytical QoE models of several services from radio connection traces collected in an Long Term Evolution (LTE) network. Such QoS thresholds reflect the minimum connection performance below which a user gives up its connection. The proposed method relies on the fact that user experience influences the traffic volume requested by users. Method assessment is performed with real connection traces taken from live LTE networks. Results confirm that packet delay or user throughput are critical factors for user experience in the analyzed services.