Optimal Response Time Research Articles

Controllable dynamics of complex DNA nanostructures.

In the past four decades, a variety of self-assembly design frameworks have led to the construction of versatile DNA nanostructures with increasing complexity and controllability. The controllable dynamics of DNA nanostructures has garnered much interest and emerged as a powerful tool for conducting sophisticated tasks at the molecular level. In this minireview, we summarized the controllable reconfigurations of complex DNA nanostructures induced by nucleic acid strands, environmental stimuli and enzymatic treatments. We also envisioned that with the optimization of response time, sensitivity and specificity, dynamic DNA nanostructures have great promise in applications ranging from nanorobotics to life sciences.

Equally Spread Current Execution Load Modelling with Optimize Response Time Brokerage Policy for Cloud Computing

Cloud computing is one of the significant technologies that is used to provide seamless internet surfing for large-scale applications and data storing purposes. The cloud is described as a large platform that enables users to access data from the internet without needing to buy storing space in their equipment such as a computer. Many studies have analysed the load-balancing technique on the cloud to distribute tasks equally between servers using the Equally Spread Current Execution (ESCE) algorithm. ESCE, which is a dynamic load balancer, has quite a few problems such as average level performance and too long of response time which affected the Quality of Services. This research has simulated a cloud computing concept using the ESCE Load Modelling technique with the CloudAnalyst simulator for three servers of Data Center (DC) locations. The ESCE was simulated to enhance its algorithm’s performance as a load balancer and higher throughput in the cloud environment. The result shows that ESCE average overall response time is shortest when the DC is located at R0 with response times of 15.05s, 13.05s with 10 VMs, and 8.631s with the Optimize Response Time brokerage policy. This research is significant to promote notable load-balancing technique testing for virtualized cloud machines data centers on Quality of Services (QoS) aware tasks for Internet of Things (IoT) services.

Load Balancing Analysis Using Round-Robin and Least-Connection Algorithms for Server Service Response Time

Today's internet network is expanding quickly, which encourages consumers to connect to more server services. A reliable server system is required to handle these circumstances. One approach that can be taken is to implement multiple servers. However, using many servers affects the response time of the server to be able to serve requests. Improving server system services through the load balancing method needs to be balanced with analysis, testing and evaluation of the network architecture and algorithms used in order to produce an optimal server system. In order to determine the algorithm to be tested optimal response time value, this study compares and analyses the load balancing approach utilizing the least-connection algorithm and the round-robin algorithm. Based on the test results using a request value of 500 connections/second for 1000 requests and 600 connections/second for 1200 requests, the round-robin algorithm looks slightly better than the least-connection algorithm. However, in the test scenario for the value of 700 connections/second for 1400 requests, 800 connections/second for 1600 requests, and 900 connections/second for 1800 requests, the least-connection algorithm looks superior. So that the average response time of the least-connection algorithm is smaller when there is an increase in connections. This condition has an impact on the faster the server responds to requests from users so that server performance can be continuously improved.

PBIS-based system integrated with zinc–silver nanocomposite for the detection of Chikungunya virus

The advancement of systems for efficient, specific, rapid, and sensitive chikungunya virus (CHIKV) detection is critical in developing nations. To the extent of our familiarity, there have been no reports on the electro-chemical paper based immunosensing of CHIKV antigen. Therefore, the study aims to create a nanocomposite-based biosensor for CHIKV at point-of-care diagnostics. Briefly, Ag–ZnO nanocomposites were fabricated by chemical methods and characterized by FTIR analysis, UV–Vis spectroscopy, scanning electron microscopy, EDX analysis, and X-Ray Diffraction (XRD). Ag–ZnO nanocomposites provide bio-compatibility to the biological recognition element on the surface of in-house fabricated screen-printed paper electrodes. The sensor demonstrated an extensive dynamic range (1ng/ml-100 μg/ml) while employing a voltametric detection in the presence of 0.5 mM ferro/ferri cyanide as a redox couple, with an estimated detection limit in the range of 1 ng/ml with optimal response time approximately 25 s. The applicability of the developed immunosensor is established by spiking CHIKV-Antigen into blood-serum samples. The constructed sensor has a shelf life of approximately thirty days. A portable platform for detecting CHIKV-Antigen provides rapid response and extreme sensitivity. Therefore, the suggested paper based immunosensor, i.e., PBIS offers a cost-effective diagnostic platform in scarce resource areas.

Discovery of a novel visible-light-active photodetector based on bismuth ferrite: constructing and optimizing the Cr-doped-BiFeO3/NiO thin film heterostructure

Bismuth ferrite (BFO) with narrow bandgap (<2.70 eV) is an uprising star in the application of optoelectronic conversion in visible (Vis) region. Fe-site doping by transition metals is a recognized strategy to reduce leakage current in order to create more qualified BFO-based optoelectronic devices. We aim to constitute the heterostructure of BiFe1-xCrxO3 (BFCO) coupling to hole-transporter NiO, serving as Vis-active photodetector with superior photoresponse speed. The influence of Cr doping ratio on BFCO is systematically investigated, indicating that doping Cr can effectively restrain not only the reduction of Fe3+ state but also the generation of oxygen vacancies. Moreover, by taking advantage of desirable energy-band alignment, BFCO/NiO heterojunction can reach the optimized response time constants of photocurrent rising and decay, i.e., τr and τd are, respectively, lowered down to 0.23 and 0.38 ms, which are almost two order-of-magnitude lower than that of pure-BFO/NiO and also more than one order-of-magnitude lower than that of single-layer BFCO film. It confirms an overwhelming photoresponse performance over other Vis-active counterparts. Herein, we for the first time achieve the Vis photodetector based on BFCO, by virtue of functional interfacial structure of BFCO-NiO to energetically separate photogenerated electron–hole pairs as well as improve charge carrier transportation.

An efficient broadband white-light photodetector: Combining visible-light-active ferroelectrics with 2D conductive intermediary RGO

Hitherto, “smart” functional bismuth ferrite (BFO) has triggered intensive research to develop novel visible-light photodetectors to substitute silicon-based detectors. However, current BFO-based detectors still fall short of the requirements for white-light (WL) detection due to unsatisfactory sensitivity and response speed. In pursuit of simple and efficient BFO-based device paradigm, we propose an effective strategy to fill empty space among metallic silver electrode dot-matrix with continuous transparent conductive material by decorating reduced graphene oxide (RGO) nanosheets on top of semiconducting layer. The hybrid device structures, BFO/RGO/Ag and BFO/NiO/RGO/Ag, are systematically explored in comparison to pure BFO. The RGO sheet stands out as qualified transparent conductive intermediary to disrupt the potential barrier caused by ubiquitous metal-semiconductor contact. It is the synergistic action of RGO facilitating charge collection and heterostructure pattern of BFO/NiO that eventually contribute to boost optical-electrical response performances of BFO/NiO/RGO structure. Accordingly, the optimized response time constants of photocurrent rising and decay are lowered down to 16.01 ms and 11.76 ms, respectively. Such response speed can exceed most of BFO-based counterparts especially in the WL-detection. Consequently, we deliver a green and facile approach to push forward the high-speed WL photoelectric detection by combining visible-light-active ferroelectrics BFO with two-dimensional conductive RGO.

Subsurface heat conduction along the CHINARE traverse route, East Antarctica

AbstractUsing data from three automatic weather stations (LGB69, Eagle and Dome A) from distinctly different climatological zones along the CHINARE (Chinese National Antarctic Research Expedition) traverse route from Zhongshan Station to Dome A, we investigated the characteristics of meteorological conditions and subsurface heat conduction. Spatial analysis indicated decreasing trends in air temperature, relative humidity and wind speed from the coastal katabatic wind zone to the inland plateau region, and air temperatures clearly showed a strong daily variability in winter, suggesting the effect from the fluctuation in the Antarctic atmospheric system. We also analyzed the optimal response time of the 1 and 3 m depth snow temperatures to the 0.1 m depth snow temperature for each site under clear/overcast and day/night situations. This showed an important enhancement to the heat transfer from shortwave radiation penetration. Using an iterative optimization method, we estimated the subsurface heat conduction variations along the transect. This was ~3–5 W m–2. Multiple maxima in daily mean subsurface fluxes were found in winter, with a typical value above 2 W m–2, while a single minimum value under –2 W m–2was found in summer. On an annual scale, a larger mean loss of subsurface heat conduction was observed in the inland plateau compared to in the coastal katabatic area. Finally, we discussed the possible influences of turbulent and radiant transport on the vertical heat response and confirmed the wind enhancement on the growth of thermal conductivity. This preliminary study provides a brief perspective and an important reference for studying subsurface heat conduction in inland areas of Antarctica.

Dynamic Fresh Weight Prediction of Substrate-Cultivated Lettuce Grown in a Solar Greenhouse Based on Phenotypic and Environmental Data

The fresh weight of vegetables is an important index for the accurate evaluation of growth processes, which are affected by factors such as temperature and radiation fluctuation, especially in a passive solar greenhouse. Predicting dynamic growth indexed by fresh weight in a solar greenhouse remains a challenge. A novel method for predicting the dynamic growth of leafy vegetables based on the in situ sensing of phenotypic and environmental data of batches is proposed herein, enabling prediction of the dynamic fresh weight of substrate-cultivated lettuce grown in a solar greenhouse under normal water and fertilizer conditions. Firstly, multibatch lettuce cultivation experiments were carried out and batch datasets constructed by collecting growth environmental data and lettuce canopy images in real time. Secondly, the cumulative environmental factors and instantaneous fresh weights of the lettuce batches were calculated. The optimum response time in days was then explored through the most significant correlations between cumulative environmental factors and fresh weight growth. Finally, a dynamic fresh weight prediction model was established using a naive Bayesian network, based on cumulative environmental factors, instantaneous fresh weight, and the fresh weight increments of batches. The results showed that the computing time setpoint of cumulative environmental factors and instantaneous fresh weight of lettuce was 8:00 AM and the optimum response time was 12 days, and the average R2 values among samples from three batches reached 95.95%. The mean relative error (MRE) of fresh weight prediction 4 days into the future based on data from the current batch was not more than 9.57%. Upon introducing another batch of data, the prediction 7 days into the future dropped below 8.53% MRE; upon introducing another two batches, the prediction 9 days into the future dropped below 9.68% MRE. The accuracy was improved by the introduction of additional data batches, proving the model’s feasibility. The proposed dynamic fresh weight growth prediction model can support the automatic management of substrate-cultivated leafy vegetables in a solar greenhouse.

Evaluating nurses' time to response by severity and cancer stage in a remote symptom monitoring program.

341 Background: Remote symptom monitoring (RSM) using electronic patient reported outcomes (ePROs) allow for patients with cancer to communicate symptoms to their clinical team between clinic visits. Prior randomized control trials of RSM focused on advanced cancer, and less data are available for patient with early stage cancers. The University of Alabama at Birmingham (UAB) implemented RSM for early stage (I-III) and advanced stage (IV) patients on active treatment. This study evaluates nurses’ real-world response time to alerts by varying severity and by patients cancer stages. Methods: This study included women with stage I-IV breast cancer who received care at UAB from October 2020 through May 2022. The program was first implemented in the breast clinic allowing for larger patient numbers with early and advanced stage breast cancer. A composite score for symptom severity is automatically calculated in the Carevive® platform for moderate, severe, or worsening symptoms using patient responses for frequency, severity, and interference. The nurse receives an alert if a symptom is moderate or severe. Surveys with at least one severe alert were categorized as severe and response time was categorized as optimal if the survey was closed within 48 hours (goal time for phone message follow-up). Odds ratios (OR), predicted probabilities, and 95% confidence intervals (CI) were estimated using a patient nested logistic regression evaluating time to response comparing surveys with at least one severe alert notification to those with no severe, adjusting for age at enrollment, race, cancer stage, provider who closed the surveys, and quarter from study start and date. An interaction between severity and cancer stage was evaluated. Results: Of 137 patients included in this study, 64% were White; 86% were diagnosed with early-stage breast cancer. The median age at diagnosis was 54 (27-79). Of 802 surveys included, 38% reported at least one severe symptom and 70% had an optimal response time. Similar results were seen when stratified by early vs. advanced stage with 39% and 38% reporting at least one severe alert and 68% and 71% an optimal response time, respectively. In our adjusted analysis, when compared with surveys that had no severe alerts, surveys with at least one severe alert had similar odds of having an optimal response time (OR, 1.29; 95%CI, 0.88, 1.89). No significant interaction between severity and stage was observed on the odds of optimal response time. Conclusions: Response times to alerts were similar regardless of the severity of the alert and cancer stage, suggesting alert management is incorporated into routine workflows and not prioritized based on disease or alert severity. Additional research is needed to understand factors contributing to non-optimal response times.

On Continuity of Optimal Response Time as a Function of the Initial State of the Controlled System

On Continuity of Optimal Response Time as a Function of the Initial State of the Controlled System

EDF scheduling for distributed systems built upon the IEEE 802.1AS clock - A theoretical-practical comparison

Existing response time analysis and optimization techniques for real-time distributed systems show that EDF schedulers feature better scheduling capabilities when a global clock reference can be used; this form of scheduling is known as global-clock EDF. In this context, precise clock synchronization is an enabling technology for future distributed real-time systems that want to leverage EDF scheduling. The IEEE 802.1AS protocol can be considered a stable technology for this purpose, as it is part of the Time-Sensitive Networking (TSN) family of standards to provide real-time communication over Ethernet. This paper presents a system architecture for applying global-clock EDF scheduling in distributed systems with soft real-time requirements. It also presents experiments to (1) assess the synchronization capabilities of the clock synchronization mechanism in the proposed architecture, (2) evaluate the performance of different scheduling deadline assignment techniques, and (3) contrast the theoretical results obtained by the schedulability analysis against those obtained through the execution of these experiments.

Monitoring System of the Mar Menor Coastal Lagoon (Spain) and Its Watershed Basin Using the Integration of Massive Heterogeneous Data.

The tool created aims at the environmental monitoring of the Mar Menor coastal lagoon (Spain) and the monitoring of the land use of its watershed. It integrates heterogeneous data sources ranging from ecological data obtained from a multiparametric oceanographic sonde to agro-meteorological data from IMIDA’s network of stations or hydrological data from the SAIH network as multispectral satellite images from Sentinel and Landsat space missions. The system is based on free and open source software and has been designed to guarantee maximum levels of flexibility and scalability and minimum coupling so that the incorporation of new components does not affect the existing ones. The platform is designed to handle a data volume of more than 12 million records, experiencing exponential growth in the last six months. The tool allows the transformation of a large volume of data into information, offering them through microservices with optimal response times. As practical applications, the platform created allows us to know the ecological state of the Mar Menor with a very high level of detail, both at biophysical and nutrient levels, being able to detect periods of oxygen deficit and delimit the affected area. In addition, it facilitates the detailed monitoring of the cultivated areas of the watershed, detecting the agricultural use and crop cycles at the plot level. It also makes it possible to calculate the amount of water precipitated on the watershed and to monitor the runoff produced and the amount of water entering the Mar Menor in extreme events. The information is offered in different ways depending on the user profile, offering a very high level of detail for research or data analysis profiles, concrete and direct information to support decision-making for users with managerial profiles and validated and concise information for citizens. It is an integrated and distributed system that will provide data and services for the Mar Menor Observatory.

Niyama: Node scheduling for cloud workloads with resource isolation

SummaryCloud providers place tasks from multiple applications on the same resource pool to improve the resource utilization of the infrastructure. The consequent resource contention has an undesirable effect on latency‐sensitive tasks. In this article, we present Niyama—a resource isolation approach that uses a modified version of deadline scheduling to protect latency‐sensitive tasks from CPU bandwidth contention. Conventionally, deadline scheduling has been used to schedule real‐time tasks with well‐defined deadlines. Therefore, it cannot be used directly when the deadlines are unspecified. In Niyama, we estimate deadlines in intervals and secure bandwidth required for the interval, thereby ensuring optimal job response times. We compare our approach with cgroups: Linux's default resource isolation mechanism used in containers today. Our experiments show that Niyama reduces the average delay in tasks by 3–20 when compared to cgroups. Since Linux's deadline scheduling policy is work‐conserving in nature, there is a small drop in the server‐level CPU utilization when Niyama is used naively. We demonstrate how the use of core reservation and oversubscription in the inter‐node scheduler can be used to offset this drop; our experiments show a 1.3–2.24 decrease in delay in job response time over cgroups while achieving high CPU utilization.

Blockchain and Double Auction-Based Trustful EVs Energy Trading Scheme for Optimum Pricing

Electric vehicles (EVs) have gained prominence in smart transportation due to their unparalleled benefits of reduced carbon footprints, improved performance, and intelligent energy trading mechanisms. These potential benefits have increased EV adoption at massive scales, but energy management in EVs is a critical study problem. The problem is further intensified due to the scarcity of charging stations (CSs) in near EV proximity. Moreover, as energy transactions occur over open channels, it presents critical security, privacy, and trust issues among decentralized channels. To address the open limitations of trusted energy management and optimize the pricing control among EV entities (i.e., prosumers and consumers), the paper proposes a scheme that integrates blockchain and a truthful double auction strategy for trustful EV trading. To address the transaction scalability, we integrate an Interplanetary File System (IPFS) with a double auction mechanism handled through the Remix Smart Contract environment. The double auction leverages an optimal payoff condition between peer EVs. To address the communication latency, we present the scheme at the backdrop of Fifth Generation (5G) networks that minimizes the optimal payoff response time. The scheme is simulated against parameters such as convergence, profit for consumers, computation time, and blockchain analysis regarding node commit latency, collusion attacks, and EV energy consumption. The results indicate the scheme’s viability against traditional (non-blockchain) approaches with high reliability, scalability, and improved cost-efficiency.

“Killing two birds with one stone”: A fluorescent hybrid nanoparticle modified with BODIPY for efficiently detection and removal of toxic Cu (II) ion from aqueous solutions

In this paper, we successfully synthesized a fluorescent hybrid material (f-Silica gel) for the removal and recognition of cations. A Bodipy derivative was used as a source of fluorescent material. The characterization of Bodipy derivative and the modified surfaces were performed by some techniques like NMR, XRD, SEM, and FT-IR. The spectroscopic studies (complex stoichiometry, pH effect, response time) were carried out with fluorescence spectroscopy for the sensitive and selective recognition of Cu (II) ions. The LOD (limit of detection) was calculated as 4.63 μM and the most optimum response time was determined as 25 min. Moreover, the complex interaction between f-Silica gel and Cu (II) ions stables generally in the range of pH: 1–12. f-Silica gel can be also used as a solid support surface to remove Cu (II) ions from the wastewater. The adsorption kinetics and isotherms of Cu (II) on the f-Silica gel were determined with several parameters such as the amount of adsorbent, temperature, and pH. Langmuir adsorption isotherm model was performed for the adsorption of Cu (II) ions and the maximum capacity was found to be 19. 920 mg/g. The kinetic data ensured that the R2 value was obtained as 0.9941 from the kinetic model (pseudo-second-order). Thus, it is very close to the desired value (1) and the value of qe(expe) is very close to the value of qe(calc). The thermodynamic results support the spontaneous, random, and endothermic adsorption process. All results indicated that the hybrid material can be used as both a sensor and an adsorbent for the detection and removal of Cu (II) ions in environmental processes.

Efficient Smart Grid Load Balancing via Fog and Cloud Computing

As the cloud data centers size increases, the number of virtual machines (VMs) grows speedily. Application requests are served by VMs be located in the physical machine (PM). The rapid growth of Internet services has created an imbalance of network resources. Some hosts have high bandwidth usage and can cause network congestion. Network congestion affects overall network performance. Cloud computing load balancing is an important feature that needs to be optimized. Therefore, this research proposes a 3-tier architecture, which consists of Cloud layer, Fog layer, and Consumer layer. The Cloud serves the world, and Fog analyzes the services at the local edge of network. Fog stores data temporarily, and the data is transmitted to the cloud. The world is classified into 6 regions on the basis of 6 continents in consumer layer. Consider Area 0 as North America, for which two fogs and two cluster buildings are considered. Microgrids (MG) are used to supply energy to consumers. In this research, a real-time VM migration algorithm for balancing fog load has been proposed. Load balancing algorithms focus on effective resource utilization, maximum throughput, and optimal response time. Compared to the closest data center (CDC), the real-time VM migration algorithm achieves 18% better cost results and optimized response time (ORT). Realtime VM migration and ORT increase response time by 11% compared to dynamic reconFigure with load (DRL) with load. Realtime VM migration always seeks the best solution to minimize cost and increase processing time.

Analysis of optimized response time in a new disaster management model by applying metaheuristic and exact methods

Purpose The purpose of this paper is to maximize the total demand covered by the established additive manufacturing and distribution centers and maximize the total literal weight assigned to the drones. Design/methodology/approach Disaster management or humanitarian supply chains (HSCs) differ from commercial supply chains in the fact that the aim of HSCs is to minimize the response time to a disaster as compared to the profit maximization goal of commercial supply chains. In this paper, the authors develop a relief chain structure that accommodates emerging technologies in humanitarian logistics into the two phases of disaster management – the preparedness stage and the response stage. Findings Solving the model by the genetic and the cuckoo optimization algorithm (COA) and comparing the results with the ones obtained by The General Algebraic Modeling System (GAMS) clear that genetic algorithm overcomes other options as it has led to objective functions that are 1.6% and 24.1% better comparing to GAMS and COA, respectively. Originality/value Finally, the presented model has been solved with three methods including one exact method and two metaheuristic methods. Results of implementation show that Non-dominated sorting genetic algorithm II (NSGA-II) has better performance in finding the optimal solutions.

When Does the Gittins Policy Have Asymptotically Optimal Response Time Tail?

We consider scheduling in the M/G/1 queue with unknown job sizes. It is known that the Gittins policy minimizes mean response time in this setting. However, the behavior of the tail of response time under Gittins is poorly understood, even in the large-response-time limit. Characterizing Gittins's asymptotic tail behavior is important because if Gittins has optimal tail asymptotics, then it simultaneously provides optimal mean response time and good tail performance. In this work, we give the first comprehensive account of Gittins's asymptotic tail behavior. For heavy-tailed job sizes, we find that Gittins always has asymptotically optimal tail. The story for light-tailed job sizes is less clear-cut: Gittins's tail can be optimal, pessimal, or in between. To remedy this, we show that a modification of Gittins avoids pessimal tail behavior while achieving near-optimal mean response time.

SSD internal cache management policies: A survey

SSDs are now increasingly being adopted as primary nonvolatile storage in diverse domains. The internal caches in the SSDs boost SSD performance, lifetime, and robustness. There are three types of internal caches: data cache and mapping cache in the SSD front-end, and flash-based cache in the SSD back-end; they are designed to meet specific requirements like controlling traffic to the back-end, optimization of response time, improving SSD lifetime etc. The underlying memory technology also influences cache design decisions. This work aims to present a methodological survey of cache management policies for these three types of internal caches in SSD. In particular, our work (a) makes a taxonomical classification of cache management policies for each of the cache types and performs a comparative analysis of the research works in each micro-category, (b) derives a set of guidelines that can be helpful for a future cache designer, and (c) enumerates a number of future research directions for designing an optimal SSD internal cache management policy. Our work is distinct from other studies in that we analyze policies for all three types of SSD internal caches, whereas this has not been done in the prior surveys.

Performance evaluation of an EMS system using queuing theory and location analysis: A case study.

In emergency medical services (EMS), response time is a key factor that shows the performance of the system. This factor is composed of two parts including activation time and travel time. The activation time of an emergency call is the time a call center spends on taking an incoming call for EMS and decides whether an ambulance should be dispatched or the emergency can be resolved by giving some medical advices. Having a good number of call center operators including call takers and dispatchers can help to reduce this time and thus the response time. However, this alone may not be enough to have a reasonable cycle time. In fact, having idle ambulances located in right places when emergency calls occur is an influential factor to reduce the travel time and thus have an optimal response time and save people's lives. Although many researchers have studied improving either the activation time or the travel time, to the best of our knowledge, there exists no study focusing on both. Motivated by this gap, in this study, a framework is proposed which uses queuing theory and location analysis to address both activation and travel times. In this regard, first, queuing theory is applied to evaluate the performance of an EMS call center and reduce the average activation time. Then, three mathematical models including mobile stations, MEXCLP and MECRP are applied to locate ambulances such that the average travel time is minimized. To shed light on the merits of using queuing theory and location models, computational results based on the real-world data from Tehran EMS Center are provided. The proposed methodology can reduce the average response time by approximately four minutes and increase the average coverage by 35%. This work is an example of the tremendous positive impact that the application of queuing theory and mathematical modeling can have. The proposed framework can significantly decrease the cycle time and increase the ambulance coverage level. The findings of this study help the policy makers of EMS centers with evaluating the performance of their systems and determining the optimal number of operators and locations of ambulances in a way that enhances the quality of emergency services.