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In this paper we propose five mathematical formulations for the multiple minimum latency problem. The first three mathematical models are straight derived from classical formulations and from a flow-based formulation to the multiple travelling salesman problem. The last two are obtained as generalizations of time-dependent formulations to the minimum latency problem. We carry out an extensive computational experimentation to evaluate the performance of the proposed models using routing and scheduling instances. These experiments evidence that the time-dependent formulations show a much better performance than the other formulations, regarding to the size of instances that can be solved and the elapsed computational time to reach the optimal solutions. The obtained results suggest to consider the development of time-dependent formulations for other problems that consider the latency as objective function.

Background: In this study, therefore, we directed our attention to motion images of badminton and evaluated the effects of the presence or absence of actual hitting of the shuttle on F waves from the short abductor muscle of the thumb to collect information about the excitability of spinal motor neurons. Methods: The subjects were 10 male and female college students with no experience in playing badminton. F waves were recorded under 3 different conditions: 1) having the subject raise their arm without holding the racket and take a posture ready to return the flying shuttle by imagining the motion (non-racket posture; NRP), 2) having the subject hold the racket and take a posture ready to return the flying shuttle by imagining the movement (racket posture; RP), and 3) having the subject actually keep rallies for 2 minutes and, then take a posture to return the flying shuttle by imagining the movement (stroke posture; SP). Results: The amplitude of F waves relative to the maximum M wave was significantly larger in RP and SP than in NRP. The minimum latency of the F waves was significantly shorter in SP than in NRP. Conclusion: The results suggest that the excitability of spinal motor neurons is suppressed by holding the racket and that the conduction velocity of excitation in muscle fibers is increased by actually performing strokes.

One of the well-known challenges in Edge Computing is strategic placement of cloudlets. The fundamental goals of this challenge are to minimize the deployment cost and to guarantee minimum latency for the users of edge services. We address this challenge by designing a cost-aware cloudlet placement approach that fully maps user applications to appropriate cloudlets while ensuring their latency requirements. We investigate the effectiveness of our proposed approach by performing extensive experiments based on New York City OpenData. The results show that our approach obtains close to optimal cost solutions with significantly reduced execution time.

The 21st century has been the era of the Internet of Things (IoT), With a lot of problems bothering different sections of mankind, IoT shows a lot of promise to give permanent and future-proof solutions to the same. An IoT solution leverages a lot of powerful concepts constituting modern day technology and therefore has intense potential to solve problems of any multitude. Air quality monitoring inside a vehicle is of prime importance given that a deviation in pollutant concentrations away from their allowed values, can be a cause of accidents and casualities. It is not just sufficient for the driver to be aware of the air quality inside. A combined knowledge of the air quality both inside and outside the vehicle and real time contextual suggestions on what has to be done to counter air quality deviations is what an IoT solution should aim to deliver. This work is centered around this idea. Pushing pollutant values to the cloud is also accompanied with drawing intelligent, context-specific inferences about the air quality. Inferences drawn are notified to the drivers in real time, with minimum latency. Amazon Web Services (AWS) has been leveraged to achieve this end.

In this paper, we focus on improving the reliability of high critical tasks in Mixed Criticality Systems (MCS) running on a Hardware/Software codesign environment. Assuming the system is operating in low criticality mode, we first find the minimum execution latency by mapping the tasks to the processing elements considering the reliability and execution latency values in the technology library. When the system switches to high criticality mode, the proposed algorithm maps high critical tasks to the highest reliable components, and then, schedules low critical tasks without exceeding the minimum latency. The results of the experimental evaluation clearly show the viability of the proposed approach.

Many time-sensitive applications require data to be aggregated from wireless sensor networks with minimum latency. However, the minimum latency aggregation scheduling problem has not been optimally solved due to its NP-hardness. Most existing ideas rely on local information (e.g., node degree, number of children) to organize the schedule order, hence results in solutions that might be far from optimal. In this work, we propose RADAS: a delay-aware Reverse Approach for Data Aggregation Scheduling that determines the transmissions sequence of sensors in a reverse order. Specifically, RADAS iteratively finds the transmissions starting from the last time slot, in which the last sender delivers data to the sink, down to the first time slot, when the data aggregation begins. In each time slot, RADAS intends to maximize the number of concurrent transmissions, while giving higher priority to the sender with potentially higher aggregation delay. Scheduling such high-priority sender first would benefit the maximum selections in subsequent time slots and eventually shorten the schedule length. Simulation results show that our proposed algorithm dominates the existing state-of-the-art schemes, especially in large and dense networks, and offers up to 30% delay reduction.

Unmanned Aerial Systems (UAS) are an operational tool for monitoring and assessment of oil spills. At the same time, satellite imagery has been used almost entirely to detect oil presence/absence, yet its ability to discriminate oil emulsions within a detected oil slick has not been fully exploited. Additionally, one of the challenges in the past has been the ability to deliver strategic information derived from satellite remote sensing in a timely fashion to responders in the field. This study presents UAS and satellite methods for the rapid classification of oil types and thicknesses, from which information about thick oil and oil emulsions (i.e., "actionable" oil) can be delivered in an operational timeframe to responders in the field. Experiments carried out at the OHMSETT test facility in New Jersey demonstrate that under specific viewing conditions satellites can record a signal variance between oil thicknesses and emulsions and non-emulsified oil. Furthermore, multispectral satellite data acquired by RADARSAT-2 and WorldView-2 were combined with data from a UAS field campaign to generate an oil/emulsion thickness classification based on a multispectral classification algorithm. Herein we present the classification methods to generate oil thickness products from UAS, validated by sea-truth observations, and quasi-synoptic multispectral satellite images acquired by WorldView-2. We tested the ability to deliver these products with minimum latency to responding vessels. During field operations in the Gulf of Mexico, we utilized the UAS multispectral system to identify areas of shoreline impacted by the oil spill. This proof-of-concept test using multispectral UAS data to detect emulsions and deliver a derived information product to a vessel in near-real-time sheds light on how UAS assets could be used in the near future for oil spill tactical response operations.

The Minimum Latency Aggregation Scheduling (MLAS) problem in Wireless Sensor Networks (WSNs) targets to attain aggregation schedules that satisfy the two desirable properties: minimum latency and no collisions. Researchers adapt the conventional homogeneous and heterogeneous WSNs to address the MLAS problem in Internet of Things (IoTs) as WSN technology is an essential component of an IoT. However, usual WSNs assume devices to use one single protocol, while some IoTs require heterogeneous devices to use different protocols. Therefore, calling a WSN an IoT is a misnomer and accordingly existing approaches may not properly realize broader IoT environments. In this paper, we clarify the distinction between WSNs and IoTs in terms of types of devices and protocols. Then, we provide a constant-factor approximation algorithm that can fully address the MLAS problem in IoTs. To the best of our knowledge, it is the first constant factor algorithm that addresses the NP-hard problem.

This paper presents a novel IEEE 802.16e (WiMAX) based decoder that performs close to the 5G code but without the expensive hardware re-development cost. The design uses an extension of the existing WiMAX parity check code to reduce the initial decoding latency and power consumption while keeping the decoder throughput at maximum. It achieves similar Frame Error Rate (FER) compared to 5G (0.1 dB off), and most notably the error curves trend down like 5G instead flooring. At FER= 10−3 there is 0.1 dB gain in the FER code performance compared to WiMAX. An implementation of the design is a modified version of the existing fully-parallel WiMAX decoder that supports multi-rate codeword size and reduces the initial latency by 33%. Additionally, for SNR greater than 3 dB, decoding only the shorter code reduces the power consumption by 34%.

We consider a Minimum-Latency Aggregation Scheduling problem in wireless sensor networks when aggregated data from all sensors are required to be transferred to the sink. During one time slot (time is discrete) each sensor can either send or receive one message or be idle. Moreover, only one message should be sent by each sensor during the aggregation session, and the conflicts caused by interference of radio waves must be excluded. It is required to find a min-length conflict-free schedule for transmitting messages along the arcs of the desired spanning aggregation tree (AT) with the root in the sink. This problem is NP-hard in a general case, and also remains NP-hard in a case when AT is given. In this paper, we present a new heuristic algorithm that uses a genetic algorithm and contains the local search procedures and the randomized mutation procedure. The extensive simulation demonstrates a superiority of our algorithm over the best of the previous approaches.

The Minimum Back-Walk-Free Latency Problem (MBLP) is an extension of the Minimum Latency Problem (MLP). It aims to find a tour with minimum latency while ignoring the back-walking costs. One of the justifications for ignoring the back-walking costs is in applications of message broadcasting for mobile devices. Obviously, the MBLP is NP-hard problem because it is a particular variant of MLP. Therefore, metaheuristic needs to be developed to provide near-optimal solutions within a short computation time. However, the main issue of metaheuristics is that they fall into local optima in some cases since the search space of the problem is combinatorial explosion. To overcome the drawback, we propose a metaheuristic algorithm combined between the Variable Neighbourhood Search (VNS) and shaking technique to solve the problem. The aim of VNS is to generate diverse neighbourhoods by using various neighbourhood searches while the shaking technique guides the search towards an unexplored part of the solution space. Moreover, a technique called Adaptive Memory (AM) is applied to balance between diversity and intensification. The computational results show that the effectiveness and efficiency of the proposed algorithm are comparable with the state-of-the-art algorithms.

Bit reversal is an essential part of the fast Fourier transform (FFT). However, compared to the amount of works on FFT architectures, far fewer works are dedicated to bit-reversal circuits until recent years. In this brief, the minimum latency and memory required for calculating the bit reversal of continuous-flow parallel data are formulated. The formulas are generic for all power of two parallelism, including the serial bit reversal. Furthermore, an efficient circuit for calculating the parallel bit reversal is proposed. The circuit not only achieves the lowest latency but also uses the minimum memory. This is achieved by breaking the bit-reversal permutation into two subpermutations, which are implemented by a sub-bit-reversal module and a group of $P$ buffer banks. In addition, two commutators are adopted to access the $P$ buffer banks efficiently. The proposed circuit is simple and efficient for reordering the output samples of parallel pipelined FFT processors.

In this paper, we consider a new selective routing problem, where a subset of customers should be serviced by a limited fleet of vehicles with the aim of minimizing the total latency. A service level constraint is added to guarantee that a minimum system performance is achieved. Assuming that the travel times are uncertain, we address the problem through a mean-risk approach. The inclusion of risk in the objective function makes the problem computationally challenging. To solve it, we propose an efficient heuristic, relying on a variable neighbourhood search mechanism, able to strike the balance between service level and latency. A detailed discussion of the model, which includes simulation tests and a sensitivity analysis, is carried out to illustrate the applicability of our approach in a post-disaster scenario, taking as a case study the Haiti earthquake in 2010. Additional computational experiments show that the proposed heuristic is effective for this difficult problem and often matches optimal solutions for small and medium-scale benchmark instances.

This study aims to investigate the impact on the user's performance when there is latency between the user's physical input to the system and the visual feedback. We developed a video latency control system to film the user's hand movements and control the latency when displaying the video (The standard deviation is 0.38 ms). The minimum latency of the system is 4.3 ms, hence this enables us to investigate the performance for unknown low latency ranges. Using this system, we conducted experiments wherein 20 subjects performed a pointing task based on Fitts' law to clarify the effect of video latency, particularly for low latency. Experimental results showed that when the latency is over 24.3 ms, the user performance begins to decrease. This result will be applied to determine a standard limit for video latency in interactive video devices.

In this paper we present a population based metaheuristic for solving the Minimum Latency Problem, which is the combination of bacterial evolutionary algorithm with local search techniques. The algorithm was tested on TSPLIB benchmark instances, and the results are competitive in terms of accuracy and runtimes with the state-of-the art methods. Except for two instances our algorithm found the best-known solution, and for the biggest tested instance it outperformed the best-known solution. The runtime was on average 30% faster than the most efficient method in the literature.

This paper presents a novel technique of factorization for 2-D non-separable quaternionic paraunitary filter banks (2-D NSQ-PUFB). Two-dimensional factorization structures called “16in-16out” and “64in-64out” respectively for 4-channel and 8-channel $\boldsymbol{Q}$ -PUFB based on the proposed technique are shown. The given structures can be mapped to parallel-pipeline processor architecture with a minimum latency time $2 (\boldsymbol{N}+1)$ quaternion multiplication operations, where $\boldsymbol{N}$ is transform order of the $Q$ -PUFB. The latency of parallel-pipeline processing does not depend on the size of the original image in contrast to the conventional 2-D transform. The coding gains $\boldsymbol{CG_{MD}}$ of 2-D non-separable Q-PUFBs for the isotropic auto-correlation function model with the correlation factor $\boldsymbol{\rho}=0.95$ are the following: $\boldsymbol{C}\boldsymbol{G}_{MD}=13.4\ \text{dB}$ for “16in-16out” structure and $\boldsymbol{C}\boldsymbol{G}_{MD}=15.6\ \text{dB}$ for “64in-64out” structure.

A bidirectional polarization-multiplexed system for access networks requires a single polarization controller at OLT, without PBSs and DSP polarization recovery at the receiver (for minimum latency). $2\times 10$ Gb/s transmissions is demonstrated exploiting Jones matrix reciprocity.

International audience; This paper deals with the Minimum Latency Problem (MLP), a variant of the well-known Travel- ing Salesman Problem in which the objective is to minimize the sum of waiting times of customers. This problem arises in many applications where customer satisfaction is more important than the total time spent by the server. This paper presents a novel branch-and-price algorithm for MLP that strongly relies on new features for the ng-path relaxation, namely: (1) a new labeling algo- rithm with an enhanced dominance rule named multiple partial label dominance; (2) a generalized definition of ng-sets in terms of arcs, instead of nodes; and (3) a strategy for decreasing ng-set size when those sets are being dynamically chosen. Also, other elements of efficient exact algorithms for vehicle routing problems are incorporated into our method, such as reduced cost fixing, dual stabilization, route enumeration and strong branching. Computational experiments over TSPLIB instances are reported, showing that several instances not solved by the current state-of-the-art method can now be solved.

In this paper we prove that the Minimum Latency Aggregation Scheduling (MLAS) problem in the Signal-to-Interference-Noise-Ratio (SINR) model is APX-hard in the uniform power model.

The DSP blocks on modern FPGAs are highly capable and support a variety of different multiplication operation. High level synthesis is one of the important DSP block development tools. the tool needs accurate estimation latency of the DSP block application circuit in order to produce good design solutions while converts the C++ code to Verilog code. Especially DSP blocks have pipeline structure, the latency estimation is more important. We propose a machine learning method which can accurate estimation minimum latency of DSP block multiplication application circuit in high level synthesis. The experiments show that the proposed approach is more accurate than Vivado-Hls to estimate the latency of DSP block application circuit. Sometimes the same clock frequency, using the method of this paper, the DSP application circuit can save 50% latency than the Vivado HLS tool.

The use of Ethernet in the fronthaul permits convergence and exploitation of statistical multiplexing gains of the new interfaces, but minimum latency and latency variation requirements may become challenging. The techniques proposed to meet these challenges are summarized.

In the minimum latency broadcasting problem with interference in concern, some previously proposed heuristics where broadcasting nodes with an ability to reduce their transmission range to their farthest nodes have shown an improvement in decreasing interference thus decreasing latency. In this paper, we propose an enhancing scheme for the problem by allowing nodes, which are not selected to be the broadcasting nodes, to decrease their transmission range to their nearest node. As a result, more nodes have more possibility to simultaneously broadcast, hence decreasing latency. By additionally applying this scheme, we achieve 8.37% less latency by average, compared to doing only the previous heuristics alone.

Nowadays, sustainability is a major factor to consider in the decision-making process. Specifically, for companies trying to stay competitive and having some advantage in the market it is a vital issue. In this study, we introduce a multi objective problem which aims to minimize distance and latency of a route with enough capacity to serve a set of clients. We assume that a vehicle leaves an established depot, visits all clients and returns to the depot before the end of the workday. With this bi-objective problem, we aim to improve the sustainability of the company by improving their economic and environmental contribution, through the minimization of the traveled distance of the vehicle along with the improvement of their social service by the minimization of the total waiting time of the customers. We call this problem Minimum Latency-Distance Problem (mldp) and in this paper, we introduce a mathematical formulation which describes it.

The multiple traveling repairman problem (kTRP) is a generalization of the traveling repairman problem which is also known as the minimum latency problem and the deliveryman problem. In these problems, waiting time or latency of a customer is defined as the time passed from the beginning of the travel until this customer's service completed. The objective is to find a Hamiltonian Tour or a Hamiltonian Path that minimizes the total waiting time of customers so that each customer is visited by one of the repairmen. In this paper, we propose a new mixed integer linear programming formulation for the multiple traveling repairman problem where each repairman starts from the depot and finishes the journey at a given node. In order to see the performance of the proposed formulation against existing formulations, we conduct computational analysis by solving benchmark instances appeared in the literature. Computational results show that proposed model is extremely effective than the others in terms of CPU times. (C) 2016 The Authors. Published by Elsevier

The minimum latency problem (MLP) is a prominent variant of the traveling salesman problem, which is \(\mathsf {APX}\)-hard and currently has the best approximation ratio about 3.59 on metric graphs [14]. In this paper, we consider several reoptimization variants of the metric MLP. In a reoptimization problem, an optimal solution to an instance is given, the goal is to obtain a good solution for a locally modified instance. Here, we consider four common local modifications: adding (resp., removing) a vertex and increasing (resp., decreasing) the cost of an edge. First, we prove that these four reoptimization problems are \(\textsf {NP}\)-hard. Then, we provide 7 / 3-approximation and 3-approximation algorithms for adding and removing a vertex respectively. As for changing the cost of an edge \(e^*\), we study them by parameterizing the position of \(e^*\). For increasing the cost, our approximation ratios range from 2.1286 to 4 / 3 during \(e^*\) moving from the first edge of the given optimal tour to the last edge. About decreasing the cost, we show that if the given optimal tour visits \(e^*\) as the i-th edge then the problem is \(\textsf {NP}\)-hard and 2-approximable for \(i\ge 3\), while it has a \(\textsf {PTAS}\) but not \(\textsf {FPTAS}\) for a constant i. However, if \(e^*\) is not in the given optimal solution, the problem for decreasing the edge cost is approximable by at least \(2.1286+\mathcal {O}(1/n)\), where n is the number of vertices in the given optimal solution. Moreover, we show that relaxing the optimality of the given solution causes the approximability of the problem to remove a vertex to be as hard as the metric MLP itself.

A substantial increase of the thyroid cancer incidence has been observed after the Chernobyl accident in the whole of Belarus and northwestern Ukraine, and the four most affected regions of the Russian Federation among those exposed as children or adolescents. The dominant risk factor was thyroid exposure to 131I resulting from the ingestion of milk. The baseline cancer incidence among males who were 10 years old at the time of the accident was more than a factor of four lower than among females. A minimum latency period for the identification of the thyroid cancer incidence of 4–5 years has been observed. About 60% of the Belarusian thyroid cancer cases and 30% of the Ukrainian cases identified about 20 years after the accident among those who were children or adolescents at the time of the accident may be related to radiation exposure. The increase in thyroid cancer incidence showed no signs of diminishing up to 30 years after exposure.

We study the minimum latency data broadcast problem under the signal-to-interference-plus-noise-ratio (SINR) model, which is known to capture wireless interference more accurately and realistically than the widely used graph-based models. Previous work mainly involves building a broadcast tree first and then computing interference-aware TDMA schedules for the links on the tree. Observing that the separation of routing and scheduling may lead to unsaturated transmissions in each time slot, we develop a polynomial-time heuristic algorithm, namely PRS, by advocating a parallel way of constructing routing and transmission schedules. Theoretical analysis indicates that PRS generates correct schedules under the SINR constraints. Simulation results demonstrate that PRS outperforms state-of-the-art algorithms in terms of broadcast latency under various network conditions.

Our work is to study the Minimum Latency Broadcast Scheduling problem in the geometric SINR model with power control. With power control, sensor nodes have the ability to adjust transmitting power. While existing works studied the problem assuming a uniform power assignment or allowing unlimited power levels, we investigate the problem with a more realistic power assignment model where the maximum power level is bounded. To the best of our knowledge, no existing work formally proved the NP-hardness, though many researchers have been assuming that this fact holds true. In this paper, we provide a solid proof for this result.

Purpose MR imaging and spectroscopy require a highly stable, uniform background field. The field stability is typically limited by hardware imperfections, external perturbations, or field fluctuations of physiological origin. The purpose of the present work is to address these issues by introducing spatiotemporal field stabilization based on real-time sensing and feedback control. Methods An array of NMR field probes is used to sense the field evolution in a whole-body MR system concurrently with regular system operation. The field observations serve as inputs to a proportional-integral controller that governs correction currents in gradient and higher-order shim coils such as to keep the field stable in a volume of interest. Results The feedback system was successfully set up, currently reaching a minimum latency of 20 ms. Its utility is first demonstrated by countering thermal field drift during an EPI protocol. It is then used to address respiratory field fluctuations in a T2*-weighted brain exam, resulting in substantially improved image quality. Conclusion Feedback field control is an effective means of eliminating dynamic field distortions in MR systems. Third-order spatial control at an update time of 100 ms has proven sufficient to largely eliminate thermal and breathing effects in brain imaging at 7 Tesla. Magn Reson Med 73:884–893, 2015. © 2014 Wiley Periodicals, Inc.

Data aggregation is a key, yet time-consuming functionality in wireless sensor networks (WSNs). Multi-channel design is a promising technique to alleviate interference as a primary reason for long latency of TDMA aggregation scheduling. Indeed, it provides more potential of parallel transmissions over different frequency channels, thus minimizing time latency. In this paper, we focus on designing a multi-channel minimum latency aggregation scheduling protocol, named MC-MLAS, using a new joint approach for tree construction, channel assignment, and transmission scheduling. To our best knowledge, this is the first work in the literature which combines orthogonal channels and partially overlapping channels to consider the total latency involved in data aggregation. Extensive simulations verify the superiority of MC-MLAS in WSNs.

Task scheduling is one of the key mechanisms to ensure timeliness in embedded real-time systems. Such systems have often the need to execute not only application tasks but also some urgent routines (e.g. error-detection actions, consistency checkers, interrupt handlers) with minimum latency. Although fixed-priority schedulers such as Rate-Monotonic (RM) are in line with this need, they usually make a low processor utilization available to the system. Moreover, this availability usually decreases with the number of considered tasks. If dynamic-priority schedulers such as Earliest Deadline First (EDF) are applied instead, high system utilization can be guaranteed but the minimum latency for executing urgent routines may not be ensured. In this paper we describe a scheduling model according to which urgent routines are executed at the highest priority level and all other system tasks are scheduled by EDF. We show that the guaranteed processor utilization for the assumed scheduling model is at least as high as the one provided by RM for two tasks, namely $2(\sqrt{2}-1)$ . Seven polynomial time tests for checking the system timeliness are derived and proved correct. The proposed tests are compared against each other and to an exact but exponential running time test.

Real-time data aggregation is one of the most important issues in wireless sensor networks. Using directional antenna to transmit data can save energy and reduce interference. In this paper, we study the minimum latency data aggregation problem with the given two directional antenna models (the steering beam and the switch beam) under protocol interference model. We propose an approximation directional data aggregation algorithm to schedule data transmissions under two directional antenna models, respectively. At last, we evaluate the proposed schedule algorithms through simulations, and simulation results show that the proposed schedule's latency is close to the depth of BFS tree, which is the lower bound of schedule latency, and the proposed schedules achieve extremely good performance.

In this paper we address a minimum latency problem and propose a multi-start strategy for solving it. For constructing initial solutions two procedures are designed, which are based on metaheuristic GRASP. We also develop a post-processing procedure based on Path Relinking to improve the obtained solutions. We carry up an extensive experimentation with 225 symmetrical instances to evaluate our procedures. In addition, using instances from literature, we compare our best procedure with previously reported methods, showing that the proposed procedure outperforms them in terms of solution quality and in elapsed CPU time to reach the solution.

Objectives To ascertain the practical electrodiagnostic value of F-waves in chronic inflammatory demyelinating polyneuropathy (CIDP). Methods We evaluated the diagnostic utility of F-waves in 18 prospectively-recruited patients with typical CIDP. Minimum/maximum/mean F-wave latencies, F-wave chronodispersion and F-wave persistence, were determined in median/ulnar/fibular/tibial nerves in patients and compared to controls with axonal neuropathy. Results All latencies were significantly more delayed in CIDP patients. F-wave chronodispersion was significantly greater in median and ulnar nerves and F-wave persistence significantly more reduced in tibial nerves in CIDP patients. Use of these supplementary F-wave parameters was of value in identifying CIDP nerves. However F-wave studies were only of additional benefit to other demyelinating parameters in about 15% of all studied CIDP nerves. Conclusions F-waves may be diagnostically helpful in CIDP in a minority of nerves without other nerve conduction abnormalities. Analysis of F-wave chronodispersion in upper limb nerves and possibly of F-wave persistence in tibial nerves, may add value to basic minimum F-wave latency studies. Significance These results suggest F-wave analysis may not need to be systematic, for all nerves, in patients with suspected CIDP, especially those intolerant to electrical stimulation. Chronodispersion and persistence may be helpful parameters to consider in addition to minimum latency.

Demand for mobile networks with high capacity and increased data rates for the up-coming 5G scenarios will require a capillary presence of antennas and a tight coordination between macro-cells and small-cells. A new technique to distribute radio signals over fiber is presented. It offers 10-times the radio bandwidth compared with digital radio over fiber (e.g. CPRI), full radio coordination and minimum latency.

Recent developments in Big Data are increasingly focusing on supporting computations in higher data velocity environments, including processing of continuous data streams in support of the discovery of valuable insights in real-time. In this work we investigate performance of streaming engines, specifically we address a problem of identifying optimal parameters that may affect the throughput (messages processed/second) and the latency (time to process a message). These parameters are also function of the parallelism property, i.e. a number of additional parallel tasks (threads) available to support parallel computation. In experimental evaluation we identify optimal cluster performance by balancing the degree of parallelism with number of nodes, which yield maximum throughput with minimum latency.

Query scheduling as one of the most important technologies used in query processing has been widely studied recently. In this paper, we investigate the Minimum Latency Multi-Regional Query Scheduling ML-MRQS problem in wireless Sensor Networks WSNs, which aims to generate a scheduling plan with minimum latency under a more practical query model called Multi-Regional Query MRQ. An MRQ targets at interested data from multiple regions of a WSN, where each region is a subarea. Because the ML-MRQS problem is NP-hard, we propose a heuristic scheduling algorithm Multi-Regional Query Scheduling Algorithm MRQSA to solve this problem. Theoretical analysis shows that the latency of MRQSA is upper bounded by 23A+B+C for an MRQ with m query regions R1,R2,',Rm, where A=maxi=1mDileft is the maximum latency for non-overlapped regions, B=maxi=1m{23Di+5Δ+21ki} is the maximum latency for overlapped regions, and C=i¾?i=1mHi+5Δ-m+17 is the accumulated latency for data transmission from the accessing nodes to the sink. Simulation results show that MRQSA reduces latency by 42.7% to 51.63% with respect to different number of query regions, network density, region size, and interference/transmission range compared with C-DCQS, while guaranteeing energy efficiency. Copyright © 2012 John Wiley & Sons, Ltd.

The minimum latency of potentiated startle after delay and trace fear conditioning was investigated. Delay conditioning is hypothesized to be mediated by automatic processes, whereas trace conditioning is hypothesized to involve controlled cognitive processes. In a group receiving delay conditioning, a tone conditioned stimulus (CS) signaled an electric shock unconditioned stimulus (US) presented 1,000 ms after CS onset. In a group receiving trace conditioning, a 200 ms tone CS was followed by an 800 ms gap prior to US presentation. Two control groups received unpaired CS/US presentations. It was hypothesized that fear-potentiated startle should be observed at shorter time intervals after CS onset in the group receiving delay conditioning compared to the group receiving trace conditioning. The results showed increased startle at 100 and 150 ms after CS onset in the group receiving delay conditioning compared to the unpaired group. In the group receiving trace conditioning, increased startle was observed at 1,500 ms after CS onset compared to the unpaired group. This supports the idea that conditioned fear after delay conditioning may be due to automatic processes, whereas trace conditioning is dependent on controlled processes.

Scheduling wireless links under the SINR model has attracted increasing attention in the past few years [1–6, 8–15, 18–20, 23–25, 27, 28, 33–36, 39, 41, 42, 45, 46]. However, most of previous work did not account for the precedence constraint that might exist among the wireless links. Precedence constraints are common in data aggregation problems where a sensor can not send data to its parent node before it has received data from all of its children. Existing solutions to the so-called minimum latency aggregation scheduling problem [7, 16, 21, 26, 29, 30, 32, 40, 43, 44] mainly focus on specific tree topologies rooted at the sink node. In this paper, we study the minimum latency link scheduling problem for arbitrary directed acyclic networks under both precedence and SINR constraints. Our formulation allows multiple sinks, and each sensor may transmit data to more than one parent node. We first show that the problem is NP-hard, and then propose a linear power assignment based polynomial time approximation algorithm and a dynamic labeling based heuristic algorithm. We have carried out extensive simulations for both dense and sparse arbitrary directed acyclic networks. The simulation results show that: (1) compared with both uniform and linear power assignments based algorithms, we can achieve much shorter scheduling lengths using our proposed labeling algorithm, and (2) the dynamic labeling based heuristic algorithm can lead to significantly shorter scheduling lengths than the heuristic algorithm which does not use labeling.

Minimum-Latency Aggregation Scheduling is a significant problem in wireless sensor networks. The key challenge is to find an effective solution to aggregate data from all sensors to the sink with minimum aggregation latency. In this article, we propose a novel data aggregation scheduling algorithm under the physical interference model. First, the algorithm partitions the network into square cells according to the communication range of a sensor. Second, a node is selected randomly as the aggregated node to receive the data from the other nodes in the same cell. Finally, a data aggregation tree, which consists of multiple disjoint paths, is constructed to aggregate data from all aggregated nodes to the sink. We empirically proved that the delay of the aggregation schedule generated by our algorithm is ( K+1)2Δ− K−1+2λ time-slots at most, where K is a constant depending on the sensors transmitting power, the signal-to-interference-plus-noise-ratio threshold, and the path-loss exponent; [Formula: see text] represents the maximal number of nodes in a cell; and [Formula: see text] denotes the number of cells at a row/column in a square network area. Simulation results also show that our algorithm achieves lower average latency than the previous works.

When does your computer need a slide rule? When it is the UNIVAC II. This 1950s circular slide rule from Remington Rand was used by programmers to optimize how the mainframe executed instructions. The computer had a drum memory that was constantly rotating, and the most efficient program would position the drum so that the next instruction would begin executing wherever the current instruction finished. Instructions were thus scattered across the drum and not physically adjacent to one another. To minimize rotational delays, a programmer had to figure out each instruction’s execution time in order to queue up the next command, an approach called minimum latency programming. Though the slide rule wasn’t strictly necessary to make those calculations, it probably helped

summary Electromyographic recordings (EMGs) were made using skin surface electrodes placed over the anterior digastric muscle in seven subjects. In every case, short bursts of electrical stimuli to the upper lip produced a response in the EMG that had a minimum latency of 62.0 ± 10.8 ms (mean ± SD). By contrast, no responses were seen when single pulse stimuli were applied. In 6/7 subjects, the minimum stimulation intensity that produced the reflex was described as being sharp or painful. In three additional experiments, single motor units were recorded within the digastric muscle using needle electrodes. In two of these experiments, there was evidence of reflex activity 60–110 ms after the application of painful electrical stimuli to the lip. These findings confirm that perioral stimuli can evoke a digastric reflex in humans and suggest that this reflex requires the summation that results from successive volleys of impulses in a large number of nociceptive afferent neurones.