Video-Based Rope Skipping Repetition Counting with ResNet Model

Video Repetition Counting is one of the important research areas in computer vision. It focuses on estimating the number of repeating actions. In this paper, we propose a method for video-based rope skipping repetition counting that combines the ResNet Model and a counting algorithm. Each frame in the given video is first classified into two categories: upward and downward, describing its current motion status. Then the classification sequence of the video is processed by a statistical counting algorithm to obtain the final repetition number. The experiments on real-world videos show the efficiency of our model.

Numerous Factors Affecting Performance of NOMA for Massive Machine Type Communications in B5G Systems

Massive machine type communications (mMTC) are one of the critical requirements for beyond fifth generation (B5G) communication systems. Services for a huge number of user terminals should be provided simultaneously due to the explosive development of mMTC. It is proved that non-orthogonal multiple access (NOMA) is effective in satisfying such a requirement. In this paper we evaluate the impacts of numerous factors, such as channel encoding, channel decoding, repetition number, multi-user detector, and number of receiver antennas, on the performance of NOMA. It is surprised to find that some conclusions drawn from orthogonal multiple access system may do not hold anymore for NOMA systems. The factors which have significant impact on the performance of NOMA should be paid more attention to in the system design. The analysis and evaluation results shine more light on how to design an effect NOMA scheme by considering both transmitter and receiver to fulfill the requirements of mMTC for B5G systems.

Link Between Topographic Memory and the Combined Presentation of ADHD (ADHD-C): A Pilot Study

Background: Topographic memory is the ability to reach various places by recognizing spatial layouts and getting oriented in familiar environments. It involves several different cognitive abilities, in particular executive functions (EF), such as attention, working memory, and planning. Children with attention deficit hyperactivity disorder (ADHD) show impairments in inhibitory control, regulation of attention, planning, and working memory.Aim: The aim of this study was to evaluate the topographic memory in children with ADHD-combined subtype (ADHD-C).Method: Fifteen children (8–10 years) with a diagnosis of ADHD-C (DSM-5) (ADHD-C group) were compared to 15 children with typical development (TD group) of the same age. All children performed Raven's colored progressive matrices (CPM) test to obtain a measure related with cognitive functioning. The walking Corsi test (WalCT), a large-scale version of the Corsi block-tapping test, was used to assess topographic memory in experimental environment.Results: A higher impairment was observed in ADHD-C than TD with significant differences in the WalCT, in particular on the topographic short-term memory (TSTM) task, on the topographic learning (TL) task, and on the repetition number (RN) task during the TL task. Perseverative errors were reported in performing the square-sequence in the WalCT. Zero-order correlations showed a positive correlation between TSTM and auditory attention, and memory of design of NEPSY-II and digit span of WISC-IV. No statistically significant differences were found between the ADHD-C group and TD group in the TL task in the WalCT condition.Conclusion: In ADHD-C, initial topographic learning was compromised whereas the long-term retention of learned topographical material seemed to not be impaired. In particular, these impairments seem to be linked with difficulties in sustained attention, in spatial memory for novel visual materials, in a poor working memory, and in perseverative behaviors.

LoRa Channel Characterization for Flexible and High Reliability Adaptive Data Rate in Multiple Gateways Networks

We characterize the LoRa channel in terms of multi-path fading, loss burstiness, and assess the benefits of Forward Error Correction as well as the influence of frame length. We make these observations by synthesizing extensive experimental measurements realized with The Things Network in a medium size city. We then propose to optimize the LoRaWAN Adaptive Data Rate algorithm based on this refined LoRa channel characterization and taking into account the LoRaWAN inherent macro-diversity from multi-gateway reception. Firstly, we propose ADRopt, which adjusts Spreading Factor and frame repetition number to maintain the communication below a target Packet Error Rate ceiling with optimized Time-On-Air. Secondly, we propose ADRIFECC, an extension of ADRopt in case an Inter-Frame Erasure Correction Code is available. The resulting protocol provides very high reliability even over low quality channels, with comparable Time on Air and similar downlink usage as the currently deployed mechanism. Simulations corroborate the analysis, both over a synthetic random wireless link and over replayed real-world packet transmission traces.

Number of progenies and repetitions for reciprocal full-sib recurrent selection programs in maize

ABSTRACT For a reciprocal recurrent selection (RRS) program to succeed, it is essential to maintain genetic variability throughout the selection cycles and to obtain accurate estimates of genetic parameters, which in turn are directly related to the number of progenies and repetitions evaluated. This study evaluates the potential of maize progenies of the sixth cycle of RRS and proposes, using simulation methods, the ideal combination of the number of progenies and repetitions to employ in reciprocal full-sib recurrent selection. A total of 163 full-sib progenies were evaluated in a randomized block design with six repetitions. Based on the yield data, analysis of variance was carried out, and different scenarios were simulated using the Monte Carlo chain method. These scenarios varied in the number of repetitions (two, four, and six) and progenies (30 to 163). The contrast between progenies and controls was significant, revealing the potential of the progenies of the sixth cycle of RRS. The high magnitude of the selective accuracy (0.77) was reflected in high estimates of heritability, which allowed for efficient phenotypic selection, obtaining selection gains of 14.07%. From the estimates of phenotypic and genotypic variance, heritability, accuracy, and standard error, it was found that a repetition number above two results in drastic changes in the estimates of these parameters; however, with the use of 130 progenies, these estimates tend to stabilize, implying that a high number of progenies does not interfere decisively in the quality of most parameters, except for the limits of maximum and minimum variation.

Elderly perform lower number of repetitions maximum than young at low instead high load resistance exercise

Aging process is characterized by reduction of muscle mass and strength, named sarcopenia. To attenuate these declines, resistance training has been purposed. The use 1RM test has been applied to define the maximal strength and prescription of exercise. Otherwise, it is not safe and it has not shown good practical applicability. Thus, the present study aim to compare the repetitions number for high and low load resistance exercise performed until failure between a young and elderly men groups. Methods: We compared (Mann-Whitney test) the repetitions number performed until muscle failure by 9 young and 9 elderly men at four sets 45ºleg press exercise for high (80% 1RM) and low load (30% 1RM). Results: Both groups reached maximum values for rate of perceived exertion, ensuring the muscle failure were achieved and no differences were seen between groups. The repetitions numbers were higher for young men with similar delta of reduction throughout sets between groups at low load resistance exercise. Otherwise, the delta of repetitions number reduction throughout sets at high load resistance exercise was higher for young men than elderly. Conclusions: We conclude elderly people need to perform lower number of repetition to reach muscle failure and thus achieve the desired training stimulus, mainly in low load resistance exercise. Furthermore, as they have better resistance to fatigue along sets the reduction of repetition number along sets is lower for them mainly when high load resistance exercise is performed.

An Energy-Efficient and Adaptive Channel Coding Approach for Narrowband Internet of Things (NB-IoT) Systems

Most of the current research work on the Narrowband Internet of Things (NB-IoT) is focused on enhancing its network coverage. Many of the existing NB-IoT channel coding techniques are based on repeating transmission data and control signals as a way of enhancing the network’s reliability and therefore, enabling long-distance transmissions. Although most of these efforts are made at the expense of reducing the energy consumption of the NB-IoT network, they do not always consider the channel conditions. Therefore, this work proposes a novel NB-IoT Energy-Efficient Adaptive Channel Coding (EEACC) scheme. The EEACC approach is a two-dimensional (2D) approach which not only selects an appropriate channel coding scheme based on the estimated channel conditions (dynamically classified as bad, medium or good from initial based on a periodically assessed BLER performance outcome) but also minimizes the transmission repetition number under a pre-assessed probability of successful transmission (based on the ratio of previous successful transmissions over the total number of transmissions). This results in creating a single mixed gradient based on which a higher or lower Modulating Coding Scheme (MCS) is selected on each transmission. It is aimed at enhancing the overall energy efficiency of the network by dynamically selecting the appropriate Modulation Coding Scheme (MCS) number and efficiently minimizing the transmission repetition number. Link-level simulations are performed under different channel conditions (good, medium, or bad) considerations to assess the performance of the proposed up-link adaptation technique for NB-IoT. The obtained results demonstrate that the proposed technique outperforms the existing Narrowband Link Adaptation (NBLA) as well as the traditional repetition schemes in terms of the achieved energy efficiency as well as network reliability, latency, and scalability.