Rate Of Performance Improvement Research Articles

Metaverse Space Ecological Scene Design Based on Multimedia Digital Technology

Yuan cosmos is a virtual world linked and created by scientific and technological means, which is mapped and interacted with the real world, and a digital living space with a new social system. With the increasing popularity of data acquisition and production equipment, people are increasingly convenient to produce multimedia data such as images, graphics, audio, video, animation, and three-dimensional models. In addition to the rapid development of digital technology itself, the biological information technology related to digital technology also greatly promotes the emergence of the metauniverse. This paper aims to study the application of multimedia digital technology to the ecological scene design of metauniverse space, introduces the related concepts of metauniverse and multimedia digital technology, expounds the related methods of multimedia digital technology and neural network related algorithms, and then takes the three-dimensional simulation of the auditory system in the interactive multisensory simulation system of the constituent elements of metauniverse as an example. The mel-frequency cepstrum coefficient (MFCC) is used to simulate the auditory characteristics of the auditory periphery (cochlea) as the perceptual end of the model. A variety of bionic mechanisms are used in the model, such as designing the connection mode of neurons, learning state and release effect, and the regeneration mechanism of neurons. For the verification of the performance of the model, the speech sample database, including English words and phrases, is recorded and the speech content information recognized by the model by means of speech recognition is experimented. The experimental results show that, in terms of phrase accuracy, the DN-1 model improves 2.59% and the DN-2 model improves 2.77% compared with MFCC feature on the basis of mixed features. When only DBN features are used, the performance improvement rate of the developmental network model is small.

Technological improvement rates and recent innovation trajectories in automated advanced composites manufacturing technologies: A patent-based analysis

The importance of advanced composites in industries such as aerospace, defense, automotive, clean energy, and hydrogen has grown at a fast pace and is expected to keep enlarging its strategic importance. Using objective patent-based methodologies, this paper estimates the yearly performance improvement rates and traces the most recent technological trajectories of Automated Tape Laying (ATL), Automated Fiber Placement (AFP) and Additive Manufacturing (AM) for advanced composites. For each technology, a set of representative patents is retrieved. A robust predictor based on the centrality of patents within the citation network is used to estimate yearly performance improvement rates. A knowledge persistence algorithm is applied to trace the most important technological trajectories. Results show that ATL (13.0%) and AFP (9.3%) are improving faster than milling technology (3.4%), a high grade metal technology, which indicates that composites applications should continue to grow relative to metal based components. AM for advanced composites is improving at a substantially faster rate (31.5%) suggesting potential to penetrate further as a viable solution in the advanced manufacturing landscape. ATL and AFP trajectories show developments mainly targeted to increase process productivity and reliability. Productivity increases are fostered primarily by innovations in automatic inspection, tow/tape heating, and material dispensing. Improvements over tow/tape cutting and steering systems and closed-loop control of operations contribute to reliability increase. AM appears to be evolving from cartesian motion to robotic arms machines. These allow for deposition over three dimensional paths which greatly increase component design freedom and mechanical properties further fostering AM's penetration.

Data Partitioning and Asynchronous Processing to Improve the Embedded Software Performance on Multicore Processors

Nowadays, ensuring information security is extremely inevitable and urgent. We are also witnessing the strong development of embedded systems, IoT. As a result, research to ensure information security for embedded software is being focused. However, studies on optimizing embedded software on multi-core processors to ensure information security and increase the performance of embedded software have not received much attention. The paper proposes and develops the embedded software performance improvement method on multi-core processors based on data partitioning and asynchronous processing. Data are used globally to be retrieved by any threads. The data are divided into different partitions, and the program is also installed according to the multi-threaded model. Each thread handles a partition of the divided data. The size of each data portion is proportional to the processing speed and the cache size of the core in the multi-core processor. Threads run in parallel and do not need synchronization, but it is necessary to share a general global variable to check the executing status of the system. Our research on embedded software is based on data security, so we have tested and assessed the method with several block ciphers like AES, DES, etc., on Raspberry PI3. The average performance improvement rate achieved was 59.09%.

Research on Seismic Acceleration Waveform Reproduction Based on Time-Frequency Hybrid Integration Algorithm

For the quadratic integration of seismic acceleration signal with noise and unknown initial velocity and displacement, the obtained displacement signal has serious trend error, which leads to the problem that the electrodynamic seismic simulation shaker under displacement control mode cannot accurately reproduce the seismic wave. This paper proposes the time-frequency hybrid integration algorithm based on time domain and frequency domain integration characteristics. The algorithm mainly includes two steps. The first step is to use the improved low-frequency attenuation algorithm to integrate the seismic acceleration for the first time in the frequency domain to obtain the corresponding velocity signal. The second step is to integrate the velocity signal directly in the time domain and combine it with the removal of the constant and linear terms algorithm to obtain the corresponding displacement signal. The accuracy and effectiveness of the algorithm are verified by numerical analysis and shaking table test. The results show that compared with the traditional hybrid integral algorithm, the performance improvement rates of displacement peak error and absolute error of the proposed time-frequency hybrid integral algorithm are 31.75% and 26.01%, respectively, and the accuracy of acceleration waveform reproduction is improved by 27.29%. Furthermore, when using this algorithm for the shaking table test of the seismic acceleration signal, the maximum peak error rate is only 4.92%. Therefore, this algorithm can effectively suppress the baseline drift and error accumulation caused by low-frequency noise and unknown initial state to realize the accurate reproduction of the acceleration waveform of the seismic simulation shaking table.

Defining and demonstrating a smart technology configuration to improve energy performance and occupant comfort in existing buildings: a conceptual framework

PurposeTo achieve the building and property by 2050, decarbonisation goals will now require a significant increase in the rate of improvement in the energy performance of buildings. Occupant behaviour is crucial. This study seeks to guide the application of smart building technology in existing building stock to support improved building energy performance and occupant comfort.Design/methodology/approachThis study follows a logical partitioning approach to the development of a schema for building energy performance and occupant comfort. A review of the literature is presented to identify the characteristics that label and structure the problem elements. A smart building technology framework is overlaid on the schema. The framework is then applied to configure and demonstrate an actual technology implementation for existing building stock.FindingsThe developed schema represents the key components and relationships of building energy performance when combined with occupant comfort. This schema provides a basis for the definition of a smart building technologies framework for existing building stock. The study demonstrates a viable configuration of available smart building technologies that couple building energy performance with occupant comfort in the existing building stock. Technical limitations (such as relatively simple building management control regimes) and pragmatic limitations (such as change management issues) are noted for consideration.Originality/valueThis is the first development of a schema to represent how building energy performance can be coupled with occupant comfort in existing building stock using smart building technologies. The demonstration study applies one of many possible technology configurations currently available, and promotes the use of open source applications with push-pull functionality. The schema provides a common basis and guide for future studies.

Dynamic modeling and damping performance improvement of two stage ISD suspension system

In this paper, the dynamics of the vehicle suspension system under the random excitation and the periodic excitation are investigated. To improve the damping performance of the vehicle suspension system, a two stage ISD suspension with “Inerter-Spring-Damper” in each stage is proposed based on electromechanical similarity theory. A vehicle dynamic model with two stage ISD suspension is established in this paper. The dynamic equation is solved by the Runge-Kutta method and the dynamic response of the whole vehicle system is obtained. Taking the traditional suspension as the comparison object, the dynamic characteristics of the system under random excitation and periodic excitation are studied in the time domain, and the suppression effect of the suspension designed in this paper on the resonance peak is verified in the frequency domain. The influence of the inertia coefficient on the damping performance of the vehicle suspension system is analyzed. The effects of excitation amplitude and vehicle speed on ride comfort improvement of vehicle system with two stage ISD suspension are discussed respectively. The results show that, the resonance peak values of body acceleration, dynamic travel of rear suspension and rear tire dynamic load frequency response are reduced by 59.1%, 21.6%, and 60.3% respectively. With the increase of excitation amplitude in the range of 0.02–0.04 m, the ride comfort improvement of two stage ISD suspension system is always more than 61%. With the increase of vehicle speed in the range of 10–25m/s, the performance improvement rate of two stage ISD suspension system can reach more than 34.1%.

Factors influencing rehabilitation effect in prelingually deafened late-implanted cochlear implant users, and the construction of a nomogram.

Our study aimed to identify potential factors that may influence rehabilitation outcomes in late-implanted adolescents and adults with prelingual deafness and to construct a user-friendly nomogram. This cross-sectional study included 120subjects under 30years of age who had received cochlear implantation at a single medical centre. The Categories of Auditory Performance (CAP) scale was used to evaluate the rehabilitation outcomes. A nomogram was constructed by using the R and EmpowerStats software. Univariate analysis indicated higher rates of auditory performance improvement in younger aged subjects. Residual hearing and regular implant use were more frequently seen among subjects with auditory performance improvement. Multivariate analysis identified residual hearing (Hazard Ratio, 6.11; 95% Confidence Interval, 1.83-20.41; p<.01), age group (Hazard Ratio, 0.31; 95% Confidence Interval, 0.14-0.83; p=.02) and regular CI use (Hazard Ratio, 7.79; 95% Confidence Interval, 2.50-24.20; p<.01) as independent predictors for auditory performance improvement. The nomogram's predictive performance was satisfactory as shown by the calibration curve and receiver operating characteristic (ROC) curve. Factors such as residual hearing, younger age and regular CI use are associated with auditory performance improvement in this cochlear implant user population. The nomogram model also demonstrates a satisfactory predictive performance.

Alternative Method to Evaluate Performance Improvement Rate in Athletics Middle Distance Events

PurposeThe aims of this study were to propose an alternative method to assess an optimal performance improvement rate (PIR) that would be used as a tool for coaches and elite athletes willing to reach their personal best, mainly those seeking for national, continental or even world record (WR) in middle-distance events. We further compared the improvement rate of women vs. men of the top-10 ranked athletes in the IAAF running these middle-distance eventsMethodThe top 10 athletes in the IAAF ranking of 800 m, 1500 m, and 3000 m events for each sex were assessed for their history of race times before achieving their personal record (PR). The difference between PR (‘actual’ season) and the best race time in the last season was defined as the 1st season improvement rate (1-SIR), whereas the average improvement rate in the last and preceding seasons was the multi-season improvement rate (M-SIR). 1-SIR and M-SIR were calculated for each athlete.ResultThere were sex differences in the 1500 m with a large effect size (d = − 0.746) in 1-SIR (P = 0.001) and very large (d = − 2.249) in M-SIR (P = 0.001). Women improved more than men before the PR/WR achievements in the 800 m and 1500 m events (P = 0.001) and had similar improvement rates before performing PR/WR in 3000 m events (P = 0.533).ConclusionWomen improve more before PR/WR achievement in 800 m and 1500 m races. However, in the 3000 m men and women have similar improvement rates in previous seasons before the PR/WR achievement.

Buoyancy effect on the stagnation point flow of a hybrid nanofluid toward a vertical plate in a saturated porous medium

The mixed convection on a stagnation-point flow of a thermo micropolar hybrid nanofluid through a vertical surface in a saturated porous medium having inertial and microstructure characteristics is investigated using Darcy–Brinkman model. The impact of convective inertia along with the porous-Forchheimer inertia is also considered. This study is designed to distinguish the influence of the two distinct nanoparticles such as magnesium oxide (MgO) nanoparticle and Silver (Ag) nanoparticle along with the regular base fluid (water) to form the MgO–Ag/water hybrid nanofluid. These hybrid nanofluids can be traced back to their unique enhancement in the rate of heat transfer and improvement in thermal performance as applicable in the dynamics of fuel and coolant in the automobile. The leading equations of the present problem are transformed into a system of ordinary differential equations by the use of appropriate similarity transformations. We employ a MATLAB solver called the boundary-value problem of fourth-order (bvp4c) to solve the resulting equations. The outcomes are unique for the buoyancy aiding flow (λc>0) while dual or multiple outcomes are marked and existed under buoyancy opposing flow (λc<0).

Detection Model of Occluded Object Based on YOLO Using Hard-Example Mining and Augmentation Policy Optimization

A study on object detection utilizing deep learning is in continuous progress to promptly and accurately determine the surrounding situation in the driving environment. Existing studies have tried to improve object detection performance considering occlusion through various processes. However, recent studies use R-CNN-based deep learning to provide high accuracy at slow speeds, so there are limitations to real-time. In addition, since such previous studies never took into consideration the data imbalance problem of the objects of interest in the model training process, it is necessary to make additional improvements. Accordingly, we proposed a detection model of occluded object based on YOLO using hard-example mining and augmentation policy optimization. The proposed procedures were as follows: diverse augmentation policies were applied to the base model in sequence and the optimized policy suitable for training data were strategically selected through the gradient-based performance improvement rate. Then, in the model learning process, the occluded objects and the objects likely to induce a false-positive detection were extracted, and fine-tuning using transfer learning was conducted. As a result of the performance evaluation, the model proposed in this study showed an mAP@0.5 value of 90.49% and an F1-score value of 90%. It showed that this model detected occluded objects more stably and significantly enhanced the self-driving object detection accuracy compared with existing model.

Technological improvement rate predictions for all technologies: Use of patent data and an extended domain description

In this work, we provide predicted yearly performance improvement rates for nearly all definable technologies for the first time. We do this by creating a correspondence of all patents within the US patent system to a set of 1757 technology domains. A technology domain is a body of patented inventions achieving the same technological function using the same knowledge and scientific principles. These domains contain 97.2% of all patents within the entire US patent system. From the identified patent sets, we calculated the average centrality of the patents in each domain to predict their improvement rates, following a patent network-based methodology tested in prior work. They vary from a low of 2% per year for the Mechanical Skin treatment- Hair Removal and wrinkles domain to a high of 216% per year for the Dynamic information exchange and support systems integrating multiple channels domain, but more that 80% of technologies improve at less than 25% per year. Fast improving domains are concentrated in a few technological areas. The domains that show improvement rates greater than the predicted rate for integrated chips, from Moore's law, are predominantly based upon software and algorithms. In addition, the rates of improvement were not a strong function of the patent set size.

Modeling talent development pathways in alpine ski racers

We explore developmental pathways to excellence in sub-elite adolescent alpine ski racing by exploring athletes' engagement in practice activities that characterize sport specialization and/or diversification. Moreover, we extend previous research by using more refined linear mixed-effects models to examine changes in practice and performance data over time rather than relying on the less sensitive repeated measures ANOVAs typically used in previous research. Altogether, 174 individuals (M = 15.9 yrs, women = 91) from professional development academies in the United States completed a sport-specific Practice History Questionnaire (PHQ). We recorded national rankings in technical events to assess performance. Mixed-effects models indicated that hours in ski-related activities generally increased over time (linear β = 1.38, p's < 0.001), except time spent in play, which decreased over time (β = 102.8, p = 0.002). Performance rankings also improved over time (β = 30.99, p < 0.001), with more time spent in ski-activity associated with greater rates of improvement, particularly in younger skiers (β = 9.77, p's < 0.001). The effects were largely driven by time spent in coach-led group practice (β = 2.16, p < 0.001). Overall, an earlier age of first engagement was associated with better rankings (β = −15.40, p = 0.024), and accumulating more hours in other sports was also associated with greater rates of performance improvement (β = −8.87, p = 0.014). Sub-elite alpine ski racers engage early in the sport, with higher-ranked athletes spending more time in ski-specific practice, particularly group practice, during development. However, these athletes generally continued to participate in other sports across development, providing greater support for the early engagement hypothesis rather than early specialization per se.

Relationship between technological improvement and innovation diffusion: an empirical test

ABSTRACT Different technological domains have significantly different rates of performance improvement. Prior theory indicates that such differing rates should influence the relative speed of diffusion of the products embodying the different technologies, since the improvement in performance during the diffusion process increases the diffusing desirability of the product. However, there has been no broad empirical attempt to examine this effect and clarify its underlying cause. Therefore, this study reviews the theoretical basis and focuses upon empirical tests of this effect across multiple products and their underlying technologies. The results for 18 diffusing products show the expected relationship (faster diffusion for products based on more rapidly improving technological domains) between technological improvement and diffusion with vital statistical significance. The empirical examination also demonstrates that technological improvement does not slow down in the later stages of diffusion when penetration slows down. This finding indicates that the diffusion slowdown in the later stages is due to market saturation effects and not to a slowdown in performance improvement.

Serotonergic Facilitation of Forelimb Functional Recovery in Rats with Cervical Spinal Cord Injury.

Serotonergic agents can improve the recovery of motor ability after a spinal cord injury. Herein, we compare the effects of buspirone, a 5-HT1A receptor partial agonist, to fluoxetine, a selective serotonin reuptake inhibitor, on forelimb motor function recovery after a C4 bilateral dorsal funiculi crush in adult female rats. After injury, single pellet reaching performance and forelimb muscle activity decreased in all rats. From 1 to 6weeks after injury, rats were tested on these tasks with and without buspirone (1-2mg/kg) or fluoxetine (1-5mg/kg). Reaching and grasping success rates of buspirone-treated rats improved rapidly within 2weeks after injury and plateaued over the next 4weeks of testing. Electromyography (EMG) from selected muscles in the dominant forelimb showed that buspirone-treated animals used new reaching strategies to achieve success after the injury. However, forelimb performance dramatically decreased within 2weeks of buspirone withdrawal. In contrast, fluoxetine treatment resulted in a more progressive rate of improvement in forelimb performance over 8weeks after injury. Neither buspirone nor fluoxetine significantly improved quadrupedal locomotion on the horizontal ladder test. The improved accuracy of reaching and grasping, patterns of muscle activity, and increased excitability of spinal motor-evoked potentials after buspirone administration reflect extensive reorganization of connectivity within and between supraspinal and spinal sensory-motor netxcopy works. Thus, both serotonergic drugs, buspirone and fluoxetine, neuromodulated these networks to physiological states that enabled markedly improved forelimb function after cervical spinal cord injury.

Physical performance development in a female national team soccer program

ObjectivesSignificant resources are invested in maximizing player performance without extensive knowledge of the athletic progression of elite female soccer players during their career. The aim of the current study was therefore to investigate the change in physical performance characteristics in 12- to 34-year-old female soccer players in a national team program. DesignMixed-longitudinal study. MethodsPhysical performance was assessed across five years and 657 testing occasions (n = 143) using anthropometrics, 40 m sprint (10 m split), broad jump, countermovement jump, squat jump, and 30-15 intermittent fitness test (IFT). ResultsUsing a Gaussian mixture model, Youth and Senior groups were bifurcated at approximately 23 years old. Subsequent linear mixed models for each group and variable identified significant improvements in the Youth group in maximal speed (30−40 m split), broad jump, countermovement jump, and final velocity30−15IFT (p ≤ 0.002), and a decrease in squat jump height with increasing age (p = 0.04). The Senior group recorded slower 10 m sprint time and a decrease in squat jump height with increasing age (p < 0.001). Body mass increased from 12 to 34 years old (Youth and Senior: p ≤ 0.001). The Youth group significantly differed in the rate of change compared to the Senior group in body mass, 10 m sprint time, countermovement jump, squat jump, and final velocity30-15IFT (p ≤ 0.001). ConclusionsThis information can be used to identify average rates of physical performance improvement and decay to help guide optimal physical training and maximize the longevity of a female soccer players’ career.

Learning curve of robotic-assisted transabdominal preperitoneal repair (rTAPP) for inguinal hernias.

Learning curves describe the rate of performance improvements according to the surgeon's caseload, followed by a plateau where limited additional improvements are observed. The aim of this study was to evaluate the learning curve for robotic-assisted transabdominal preperitoneal repair (rTAPP) for inguinal hernias in surgeons already experienced in laparoscopic TAPP. The study was approved by local ethic committee. Male patients undergoing rTAPP for inguinal hernia from October 2017 to December 2019 at the Bellinzona Regional Hospital were selected from a prospective database. Demographic and clinical data, including operative time, conversion to laparoscopic or open surgery, intra- and postoperative complications were collected and analyzed. Over the study period, 170 rTAPP were performed by three surgeons in 132 patients, and mean age was 60.1 ± 13.7years. The cumulative summation (CUSUM) test showed a significant operative time reduction after the 43rd operation, once the 90% proficiency on the logarithmic tendency line was achieved. The corrected operative time resulted 71.1 ± 22.0 vs. 60.8 ± 13.5min during and after the learning curve (p = 0.011). Only one intraoperative complication occurred during the learning curve and required an orchiectomy. Postoperatively, three complications (one seroma, one hematoma, and one mesh infection) required invasive interventions during the learning curve, while no cases were recorded after it (p = 0.312). Our study shows that the rTAPP, performed by experienced laparoscopists, has a learning curve which requires 43 inguinal hernia repairs to achieve 90% proficiency and to significantly reduce the operative time.

Impact of Crowdsourcee’s Vertical Fairness Concern on the Crowdsourcing Knowledge Sharing Behavior and Its Incentive Mechanism

This paper examines in detail the impact of the crowdsourcee’s vertical fairness concern on the knowledge sharing incentive mechanism in crowdsourcing communities. The conditions for the establishment of the incentive mechanism are analyzed and the impact of fairness concern sensitivity on expected economic revenues of both sides as well as the crowdsourcing project performance is studied by game theory and computer simulation. The results show that the knowledge sharing incentive mechanism can only be established if the ratio between the performance improvement rate and the private cost reduction rate caused by shared knowledge is within a certain range. The degree of the optimal linear incentives, the private solution efforts, and the improvement of knowledge sharing level are positively correlated with the sensitivity of vertical fairness concern. In the non-incentive mode, the ratio between the performance conversion rate of private solution effort and the performance conversion rate of knowledge sharing effort plays an important role in moderating a crowdsourcing project’s performance. The authors find that the number of participants is either conducive or non-conducive to the improvement of performance. The implementation of knowledge sharing incentive can achieve a win-win situation for both the crowdsourcer and the crowdsourcee.

Improvement of Thermal Performance using Spineloxides/Water Nanofluids in the Heat Recovery Unit with Air-to-Air Thermosiphone Mechanism

Heat recovery units are used for pre-heating the fresh air in waste heat plants. The nanofluid used as working fluid in the heat pipe will allow the heat recovery unit to benefit from the waste heat at lower temperatures, since it can evaporate at a temperature lower than the temperature of the base fluid. Therefore, the range of the operating temperature of the heat recovery unit will be increased. Different temperatures and flow rates of waste heat were used to find the optimum conditions for the evaporation of spinel nanofluid in the evaporator region of the heat pipe. Similar conditions were investigated for both of the cold fluid and optimal conditions on the condensation of nanofluid in the condenser region. In this study, an experimental setup was designed to improve the thermal performance of the air-to-air containing heat pipe heat recovery unit. The experiments were carried out using pure water-based nanofluids containing nano-sized ZnOAl2O3, MgOAl2O3, FeOAl2O3 particles, and the efficiencies of the heat transfer were investigated in this experiment. A thermosiphon mechanism that consists of five heat pipes, the length of each one is equal to 1 m, and the inner and the outer diameter of them is equal to 23.4 mm and 25.4 mm, respectively, those pipes are vacuumed, without wick and copper material. Heat pipes in the experimental setup; the evaporation zone is positioned to form 450 mm, the condensation zone 400 mm and the middle 150 mm parts to form the adiabatic region. At the beginning of the experiments, the working fluid charged to fill the 1/3 of the evaporation zone volumes of the heat pipes. Two different cooling air flow rates, 30 g·s−1 and 60 g·s−1, and three different heating air flow rates, 50 g·s−1, 70 g·s−1, 90 g·s−1 have been used, to calculate the heat obtained from the condensation zone. All the experiments were carried out by applying two different heaters with a power of, 1000 W and 2000 W, in the evaporation zone. Thus, the optimum temperatures and flow rates were found for all Reynolds numbers in the hot and cold fluid region, and its helps to determining the ranges of the operating temperature in the heat recovery unit. The experimental results that obtained from the two different working fluids (pure water and nanofluid) are compared. The best thermal performance of the system was found in the hot and cold air duct, when the Reynolds number was equal to 12 000. The thermal performance improvement rate was found as 92.8 % when the FeOAl2O3/water nanofluid used as working fluid, and 1000 W heater power and 60 g·s−1 cooling air flow applied.

Functional performance improvement data and patent sets for 30 technology domains with measurements of patent centrality and estimations of the improvement rate.

This article accompanies the study presented in Triulzi et al. (2020) [1]. It briefly describes and makes available the data on functional performance for 30 technology domains, their patent sets, the measurement of patent centrality and the method to estimate the yearly technology performance improvement rate (TIR) that underly that study. Some of this data (performance time series and the lists of patents for 28 domains) has been collected by other authors for previous studies but were previously unavailable to the public. Measurements of patent centrality and other patent-based indicators for the 30 domains, and for 5.259.906 utility patents granted by the United States Patent and Trademark Office between 1976 and 2015 are novel data contributed by Triulzi et al. (2020) [1]. Here we organize, describe and make available the collection of data in its entirety. This allows anyone interested to replicate the study or use the method to estimate the improvement rate of a given technology for which patents can be identified. For a detailed description of the data and methods see Triulzi et al. (2020) [1].

Breaking the athletics world record in the 100 and 400 meters: an alternative method for assessment.

The top 10 athletes in the International Association of Athletic Federations in 100-m and 400-m ranking for each sex were assessed for their history of race times before achieving their personal record (PR). The main goal of this study was to create a new method for optimal performance improvement rate assessment for coaches and athletes aiming the World Record. The difference between PR ('current' season) and the best race time in the last season was defined as the first season improvement rate (1-SIR), whereas the average improvement rate in the last and preceding seasons was the multi-season improvement rate (M-SIR). 1-SIR and M-SIR were calculated for each athlete. The sex comparison for the 100 m event showed a significant difference in the M-SIR in favor of women. No statistical differences were identified for the 400 m event, with a trivial effect in both 1-SIR and M-SIR. As a practical applicability, graph plots were designed to help verifying the improvement rate of athletes and to evaluate whether a long-term training strategy induced an acceptable performance improvement or whether some adjustments needed and check within the plots if the improvement rate is within the average of the top-10 athletes of their event.