Replay Speed Research Articles

Simulation Method for Blockchain Systems with a Public Chain

The potential security problems of blockchain technology are constantly restricting the development process of related industrial applications. The cost of deploying a blockchain system in a real environment to conduct research on security issues is relatively high, and the related security analysis and verification are also destructive and irreproducible. Therefore, based on the idea of layered design, this paper proposes a blockchain system simulation platform. The blockchain system is divided into four layers in the simulation platform: the consensus layer, network layer, contract layer, and storage layer. In the consensus layer, the problem of computing resource waste is solved. In the network layer, a peer-to-peer network topology simulation is implemented. In the storage layer, the problem of redundant storage is solved. In the contract layer, the contract replay speed is accelerated. Finally, a prototype of an efficient blockchain simulation system is implemented based on the above methods.

Sequence learning, prediction, and replay in networks of spiking neurons

Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm realizes these forms of computation. It learns sequences in an unsupervised and continuous manner using local learning rules, permits a context specific prediction of future sequence elements, and generates mismatch signals in case the predictions are not met. While the HTM algorithm accounts for a number of biological features such as topographic receptive fields, nonlinear dendritic processing, and sparse connectivity, it is based on abstract discrete-time neuron and synapse dynamics, as well as on plasticity mechanisms that can only partly be related to known biological mechanisms. Here, we devise a continuous-time implementation of the temporal-memory (TM) component of the HTM algorithm, which is based on a recurrent network of spiking neurons with biophysically interpretable variables and parameters. The model learns high-order sequences by means of a structural Hebbian synaptic plasticity mechanism supplemented with a rate-based homeostatic control. In combination with nonlinear dendritic input integration and local inhibitory feedback, this type of plasticity leads to the dynamic self-organization of narrow sequence-specific subnetworks. These subnetworks provide the substrate for a faithful propagation of sparse, synchronous activity, and, thereby, for a robust, context specific prediction of future sequence elements as well as for the autonomous replay of previously learned sequences. By strengthening the link to biology, our implementation facilitates the evaluation of the TM hypothesis based on experimentally accessible quantities. The continuous-time implementation of the TM algorithm permits, in particular, an investigation of the role of sequence timing for sequence learning, prediction and replay. We demonstrate this aspect by studying the effect of the sequence speed on the sequence learning performance and on the speed of autonomous sequence replay.

Can Slow-Motion Footage of Forehand Strokes Be Used to Immediately Improve Anticipatory Judgments in Tennis?

Slow-motion footage of sports actions is widely used as a visual learning tool in observing the dynamic motor behaviors of athletes. Recent studies on action observation have reported that extending the observation time in slow-motion footage provides benefits of understanding the intention of an opponent’s action, at least when observing rapid movements. As such, the use of slow-motion footage may have the potential to improve the anticipatory judgments of an opponent’s action outcome without training (or feedback). To verify this possibility, we examined the effects of the replay speed of slow-motion footage on the anticipatory judgments of shot directions and recognition of kinematic positions of opponents’ forehand strokes in tennis. Nine skilled and nine novice tennis players were asked to anticipate the direction of their opponent’s shots (left or right) and then attempted to recognize proximal (trunk center) and distal (ball) kinematic positions. Computer graphic animations of forehand strokes were used as visual stimuli, which were presented at four different replay speeds (normal, three-quarter, half, and quarter speeds). We failed to show the immediate effect of the use of slow-motion footage on the anticipatory performance of the skilled and novice players, although the anticipatory performance of the skilled players was superior to that of the novice players. Instead, we found an effect of the use of slow-motion footage in terms of promoting recognition of important kinematic cues (trunk center) for effective anticipation by skilled players. Moreover, no significant correlations were observed between the anticipatory judgments and motion recognition in all experimental conditions. These results suggest that even if the use of slow-motion footage enhances the recognition of key kinematic cues, it may not immediately improve anticipatory judgments in tennis.

Penguin: Efficient Query-Based Framework for Replaying Large Scale Historical Data

In the big data era, there are many demands for efficient and easy to use data replay services over large scale historical data. For example, stock security trading and on-line e-business services need historical data replay services to conduct system testing or ex-post review and analysis, just like replaying videos for security monitoring. Stream processing systems are designed for processing stream data, thus can not perform complex replay jobs over the static historical data. Database management systems support easy to use complex queries, but lack stream processing abilities. In this paper, we present a data replay model that combines the stream replay and complex query ability together, to allow the applications to replay large scale historical data from various data sources. First, to meet the demands of flexible replay semantics, we designed a set of easy to use replay operators to describe various replay behaviors and semantics. Users can use these operators to build up their complex replay jobs with diversified requirements. Then, we proposed a query mechanism to provide a flexible data loading service. Next, we presented the Penguin framework to support the proposed query-based replay model along with the replay operators. Penguin enables users to develop high-throughput and easy to use replay services over various large scale data sources with tunable replay speeds. To further improve the data replay performance, we proposed four system-level optimizations, including caching loading task results, cascading merging intermediate record queues, producing the replay queue in parallel, and caching remote file streams. Experimental results over replaying millions of records demonstrate that Penguin can achieve up to $4\times$ and $144\times$ speedup in data preparation and up to $16\times$ and $9\times$ speedup in replay speed compared to Apache Phoenix and Apache Hive respectively. As a case study, Penguin has been deployed in production environments of some Securities companies to provide online historical stock data replay services to large number of stock market users.

The impact of video speed on the decision-making process of sports officials

There is an increasing trend in association football (soccer) to assist referees in their decision-making with video technology. For decisions such as whether a goal has been scored or which player actually committed a foul, video technology can provide more objective information and be valuable to increase decisional accuracy. It is unclear, however, to what extent video replays can aid referee decisions in the case of foul-play situations in which the decision is typically more ambiguous. In this study, we specifically evaluated the impact of slow-motion replays on decision-making by referees. To this end, elite referees of five different countries (n = 88) evaluated 60 different foul-play situations taken from international matches, replayed in either real time or slow motion. Our results revealed that referees penalized situations more severely in slow motion compared to real time (e.g. red card with a yellow card reference decision). Our results provide initial evidence that video replay speed can have an important impact on the disciplinary decision given by the referee in case of foul play. The study also provides a real-life test-case for theories and insights regarding causality perception.

Real-time Simultaneous DKG and 2D DKG Using High-speed Digital Camera

For the evaluation of voice disorders, direct observation of vocal cord vibration is important. Among the various methods, laryngeal videostroboscopy (LVS) is widely used, but it was not a true image because it collects images from different cycles. In contrast, high-speed videoendoscopy and videokymography have much higher frame rates and can assess functional and mobility disorders. The purpose of the study is to describe real-time, simultaneous digital kymography (DKG), two-dimensional scanning (2D) DKG, and multi-frame (MF) LVS system using a high-speed digital camera, and identify the efficacy of this system in evaluating vibratory patterns of pathologic voice. The pattern of vocal fold vibration was evaluated in a vocally healthy subject and in subjects with vocal polyp, vocal nodules, vocal cord scar, and vocal cord paralysis. We used both quantitative (left-right phase symmetry, amplitude symmetry index) and qualitative (anterior-posterior phase symmetry) parameters for assessment of vocal fold vibration. Our system could record videos within seconds and required relatively little memory. The speed of replay in the DKG, 2D DKG, MF LVS, and high-speed videoendoscopy was controllable. The number of frame per cycle with MF LVS was almost the same as the fundamental frequency. Our system can provide images of various modalities simultaneously in real time and analyze morphological and functional vibratory patterns. It can be possible to provide a greater level of information for the diagnosis and treatment of vibratory disorders.

Slow motion increases perceived intent.

To determine the appropriate punishment for a harmful action, people must often make inferences about the transgressor's intent. In courtrooms and popular media, such inferences increasingly rely on video evidence, which is often played in "slow motion." Four experiments (n = 1,610) involving real surveillance footage from a murder or broadcast replays of violent contact in professional football demonstrate that viewing an action in slow motion, compared with regular speed, can cause viewers to perceive an action as more intentional. This slow motion intentionality bias occurred, in part, because slow motion video caused participants to feel like the actor had more time to act, even when they knew how much clock time had actually elapsed. Four additional experiments (n = 2,737) reveal that allowing viewers to see both regular speed and slow motion replay mitigates the bias, but does not eliminate it. We conclude that an empirical understanding of the effect of slow motion on mental state attribution should inform the life-or-death decisions that are currently based on tacit assumptions about the objectivity of human perception.

Spike-Based Bayesian-Hebbian Learning of Temporal Sequences.

Many cognitive and motor functions are enabled by the temporal representation and processing of stimuli, but it remains an open issue how neocortical microcircuits can reliably encode and replay such sequences of information. To better understand this, a modular attractor memory network is proposed in which meta-stable sequential attractor transitions are learned through changes to synaptic weights and intrinsic excitabilities via the spike-based Bayesian Confidence Propagation Neural Network (BCPNN) learning rule. We find that the formation of distributed memories, embodied by increased periods of firing in pools of excitatory neurons, together with asymmetrical associations between these distinct network states, can be acquired through plasticity. The model’s feasibility is demonstrated using simulations of adaptive exponential integrate-and-fire model neurons (AdEx). We show that the learning and speed of sequence replay depends on a confluence of biophysically relevant parameters including stimulus duration, level of background noise, ratio of synaptic currents, and strengths of short-term depression and adaptation. Moreover, sequence elements are shown to flexibly participate multiple times in the sequence, suggesting that spiking attractor networks of this type can support an efficient combinatorial code. The model provides a principled approach towards understanding how multiple interacting plasticity mechanisms can coordinate hetero-associative learning in unison.

"Diagnosis by behavioral observation" home-videosomnography - a rigorous ethnographic approach to sleep of children with neurodevelopmental conditions.

Introduction: Advanced video technology is available for sleep-laboratories. However, low-cost equipment for screening in the home setting has not been identified and tested, nor has a methodology for analysis of video recordings been suggested.Methods: We investigated different combinations of hardware/software for home-videosomnography (HVS) and established a process for qualitative and quantitative analysis of HVS-recordings. A case vignette (HVS analysis for a 5.5-year-old girl with major insomnia and several co-morbidities) demonstrates how methodological considerations were addressed and how HVS added value to clinical assessment.Results: We suggest an “ideal set of hardware/software” that is reliable, affordable (∼$500) and portable (=2.8 kg) to conduct non-invasive HVS, which allows time-lapse analyses. The equipment consists of a net-book, a camera with infrared optics, and a video capture device. (1) We present an HVS-analysis protocol consisting of three steps of analysis at varying replay speeds: (a) basic overview and classification at 16× normal speed; (b) second viewing and detailed descriptions at 4–8× normal speed, and (c) viewing, listening, and in-depth descriptions at real-time speed. (2) We also present a custom software program that facilitates video analysis and note-taking (Annotator©), and Optical Flow software that automatically quantifies movement for internal quality control of the HVS-recording. The case vignette demonstrates how the HVS-recordings revealed the dimension of insomnia caused by restless legs syndrome, and illustrated the cascade of symptoms, challenging behaviors, and resulting medications.Conclusion: The strategy of using HVS, although requiring validation and reliability testing, opens the floor for a new “observational sleep medicine,” which has been useful in describing discomfort-related behavioral movement patterns in patients with communication difficulties presenting with challenging/disruptive sleep/wake behaviors.

The Influence of Film Replay Speed during Exercise Observation on the Intermanual Transfer Effect of Subjects Doing Ball Revolutions

The Influence of Film Replay Speed during Exercise Observation on the Intermanual Transfer Effect of Subjects Doing Ball Revolutions

Prediction of shot success for basketball free throws: Visual search strategy

In ball games, players have to pay close attention to visual information in order to predict the movements of both the opponents and the ball. Previous studies have indicated that players primarily utilise cues concerning the ball and opponents' body motion. The information acquired must be effective for observing players to select the subsequent action. The present study evaluated the effects of changes in the video replay speed on the spatial visual search strategy and ability to predict free throw success. We compared eye movements made while observing a basketball free throw by novices and experienced basketball players. Correct response rates were close to chance (50%) at all video speeds for the novices. The correct response rate of experienced players was significantly above chance (and significantly above that of the novices) at the normal speed, but was not different from chance at both slow and fast speeds. Experienced players gazed more on the lower part of the player's body when viewing a normal speed video than the novices. The players likely detected critical visual information to predict shot success by properly moving their gaze according to the shooter's movements. This pattern did not change when the video speed was decreased, but changed when it was increased. These findings suggest that temporal information is important for predicting action outcomes and that such outcomes are sensitive to video speed.

Cyrus

Architectures for deterministic record-replay (R&R) of multithreaded code are attractive for program debugging, intrusion analysis, and fault-tolerance uses. However, very few of the proposed designs have focused on maximizing replay speed -- a key enabling property of these systems. The few efforts that focus on replay speed require intrusive hardware or software modifications, or target whole-system R&R rather than the more useful application-level R&R. This paper presents the first hardware-based scheme for unintrusive, application-level R&R that explicitly targets high replay speed. Our scheme, called Cyrus , requires no modification to commodity snoopy cache coherence. It introduces the concept of an on-the-fly software Backend Pass during recording which, as the log is being generated, transforms it for high replay parallelism. This pass also fixes-up the log, and can flexibly trade-off replay parallelism for log size. We analyze the performance of Cyrus using full system (OS plus hardware) simulation. Our results show that Cyrus has negligible recording overhead. In addition, for 8-processor runs of SPLASH-2, Cyrus attains an average replay parallelism of 5, and a replay speed that is, on average, only about 50% lower than the recording speed.

Cyrus

Architectures for deterministic record-replay (R&R) of multithreaded code are attractive for program debugging, intrusion analysis, and fault-tolerance uses. However, very few of the proposed designs have focused on maximizing replay speed -- a key enabling property of these systems. The few efforts that focus on replay speed require intrusive hardware or software modifications, or target whole-system R&R rather than the more useful application-level R&R. This paper presents the first hardware-based scheme for unintrusive, application-level R&R that explicitly targets high replay speed. Our scheme, called Cyrus , requires no modification to commodity snoopy cache coherence. It introduces the concept of an on-the-fly software Backend Pass during recording which, as the log is being generated, transforms it for high replay parallelism. This pass also fixes-up the log, and can flexibly trade-off replay parallelism for log size. We analyze the performance of Cyrus using full system (OS plus hardware) simulation. Our results show that Cyrus has negligible recording overhead. In addition, for 8-processor runs of SPLASH-2, Cyrus attains an average replay parallelism of 5, and a replay speed that is, on average, only about 50% lower than the recording speed.

An efficient deterministic record-replay with separate dependencies

Shared-memory multithreaded programs running on chip multiprocessors (CMPs) tend to be nondeterministic. Two-phase deterministic record-replay is an effective approach to resolve this problem. This paper proposes an efficient separate memory race record-replay (SMRR) based on point-to-point logging approach. During recording, SMRR logs predecessors and successors of memory races separately and uses an optimized log entry format for each log entry, achieving small log size and low bandwidth overhead. During replay, SMRR actively produces wakeup messages to trigger stalled successors in time, achieving low communication overhead and fast replay speed. The simulation shows that SMRR writes a small memory race log for SPLASH-2 and PARSEC workloads, and has good scalability in log size. More importantly, SMRR can achieve the lowest bandwidth overhead in the recording phase, and a replay speed within 1–18% of the native execution speed without record-replay.

CCTR: An efficient point-to-point memory race recorder implemented in chunks

Memory race recording is a key technology to replay multithreaded programming deterministically. Modern computers supply efficient communication mechanism and memory races occur frequently. So it is significant to develop an efficient memory race recording algorithm with low log growth rate and rapid replay speed. This paper proposes a new efficient point-to-point memory race recording algorithm, called CCTR, which writes a small race log with small hardware state, operates well as the number of cores per system scales, and can replay multithreaded programs at production run speed. CCTR uses a new relative indirect dependency to present each memory race instead of its precise dependency. In this dependency, CCTR need not store any timestamp for each memory block and detects memory races in chunks. Through simulation on 4-core chip multiprocessor (CMP), a good result is achieved which includes smallest log growth rate (∼5 bytes per thousand memory instructions), small hardware state (∼504 bytes per core), low runtime overhead (less than 2%), low bandwidth overhead (∼7%) and good scalability.

Spectral clustering in multi-agent systems

We examine the application of spectral clustering for breaking up the behavior of a multi-agent system in space and time into smaller, independent elements. We propose clustering observations of individual entities in order to identify significant changes in the parameter space (like spatial position) and detect temporal alterations of behavior within the same framework. Available knowledge of important interactions (events) between entities is also considered. We describe a novel algorithm utilizing iterative subdivisions where clusters are pre-processed at each step to counter spatial scaling, rotation, replay speed, and varying sampling frequency. A method is presented to balance spatial and temporal segmentation based on the expected group size, and a validity measure is introduced to determine the optimal number of clusters. We demonstrate our results by analyzing the outcomes of computer games and compare our algorithm to K-means and traditional spectral clustering.

自己運動感覚を誘導する視覚刺激に対する生体反応の分析

Visual stimuli during motion can induce a sense of physical discomfort. To examine the influence of visual stimuli on the human body, we studied autonomic responses when subjects watched videos of a roller-coaster ride and computer graphics at three different replay speeds. We measured the subjects' heart rates, mean blood pressures, respiration rates, and tidal volumes while they watched the video, and we focused on the relationship between the reaction and replay speeds. As a result, we found that the replay speed influences the heart rate, which changed greatly during a curve scene at double speed. Subjects' respiration rates increased the most when the replay speed was quadrupled during a curve scene.

Dynamics of spatio-temporal patterns in associative networks of spiking neurons

This paper studies dynamical properties of spatio-temporal pattern sequences (‘synfire chains’) in associative networks of spiking neurons. Employing postsynaptic potentials with a finite rise time, the replay speed of stored sequences can be controled by unspecific background signals. In addition, the speed also depends on the number of co-activated sequences, but balanced inhibition can prevent this dependency. An implicit equation is derived and solved numerically which relates the speed to the network parameters. Simulations reveal instabilities for low and high control signals, which are traced back to four different destabilizing mechanisms.

Computerized analysis of epileptic activity and sleep in mobile long-term EEG monitoring.

Implemented on a LSI 11/73 microcomputer, an approach is presented to perform pattern recognition of one channel in high speed (factor 20). A mimetic algorithm, acting in time domain, continuously tests the signal with respect to the occurrence of spike-wave-like patterns and calculates a low frequency index describing the time of sleep. Those epochs suspected of containing paroxysmal activity are stored on disk for subsequent editing. In a similar way, 8-channel analysis is possible if the replay speed is less than 20 times real time.

Use of magnetic tape for recording radioactivity.

Radioactive isotopes are frequently used as tracer material for diagnostic purposes. The principle employed for determining rate of blood flow is based on a dilution or elimination rate of the administered tracer dose. Activity rate is measured with a suitable detector and recording system. Interpretation of disappearance curves is at times rendered difficult because of a weak dose of radioactive material introduced into the system or inadequate settings of the rate meter as to scaling and time factors. To obviate loss of valuable data, a recording system that could register all impulses emitted by the detector probe would be of value. These could then be reproduced at leisure through a scaler or integrating rate meter. Commercial tape recorders have proved adaptable for registering radioactive disintegration impulses. Method A suitable detector probe is activated to the proper voltage level by an appropriate power supply source, either from a scaler or rate-meter unit. The output from the scaler or rate meter is directly attached to the microphone input of the tape recorder. The simultaneous use of tape recording does not interfere with the routine recording system obtained directly from a rate meter or while the counting of radioactivity is in progress. Rate Meter 1. Nuclear-Chicago Rate Meter, Labitron, or Survey Meter. The speaker leads, or phone plugs, are tapped and connected directly to the microphone input of the tape recorder (Fig. 1). 2. Picker Rate Meter. The amplifier output, contact point 8 on the J4 amplifier plug in the socket, is tapped and connected to the microphone input of the tape recorder. Settings of the rate meter, sensitivity, and scaling rate are immaterial for magnetic tape recording purposes (Fig. 2). Tape Speed for Recording Tape speed for recording is dependent on activity rate. A three-speed Norelco Phillips tape recorder offers wider flexibility in recording and for replay. Normally a 3 3/4 inch per second tape recording is adequate. Replay of Tape Recording Tape recordings can be replayed by simply connecting the tape recorder output to the input of the rate meter. For counting purposes, it may be connected to the input of a scaler. 1. Nuclear-Chicago Rate Meter (Model #1620): A small Fisher transistor preamplifier is employed. The tape recorder speaker output is connected to the preamplifier input and the preamplifier output to the scaler or rate-meter input (Fig. 3). 2. Nuclear-Chicago Labitron (Model #1619A): No preamplifier is necessary. The recorder output is directly connected to the input. 3. Picker Counting Rate Meter (Model #2805): Tape recorder output is attached directly to the rate-meter preamplifier input; contact point 2 on the J4 amplifier plug in socket. The count rate can be doubled or halved depending on the tape speed at which the recording is replayed. With a replay speed twice the recording speed, counts are doubled and counting time is halved.