The Interactions Between“Business”Culture,“Professional”Culture and Training

Ultimately,the fundamental issues of educational sciences remain economic and societal.The interactions between“business”culture,“professional”culture and training are part of this.This contribution is a reflection resulting from a longitudinal empirical research entitled:“Professionalization of an establishment in the social and medico-social field:a French monograph after the law 2002-02 of January 02,2002”.Three concepts were used:“making sense”(Weick,1995);the“strategic paradigm”(Jonhson,1987);and“cultures of action”(Sorel&Wittorski,2005;Barbier,2010;Ardouin,2015).

Effective distributed convolutional neural network architecture for remote sensing images target classification with a pre-training approach

How to recognize targets with similar appearances from remote sensing images(RSIs) effectively and efficiently has become a big challenge. Recently, convolutional neural network(CNN) is preferred in the target classification due to the powerful feature representation ability and better performance. However,the training and testing of CNN mainly rely on single machine.Single machine has its natural limitation and bottleneck in processing RSIs due to limited hardware resources and huge time consuming. Besides, overfitting is a challenge for the CNN model due to the unbalance between RSIs data and the model structure.When a model is complex or the training data is relatively small,overfitting occurs and leads to a poor predictive performance. To address these problems, a distributed CNN architecture for RSIs target classification is proposed, which dramatically increases the training speed of CNN and system scalability. It improves the storage ability and processing efficiency of RSIs. Furthermore,Bayesian regularization approach is utilized in order to initialize the weights of the CNN extractor, which increases the robustness and flexibility of the CNN model. It helps prevent the overfitting and avoid the local optima caused by limited RSI training images or the inappropriate CNN structure. In addition, considering the efficiency of the Na¨?ve Bayes classifier, a distributed Na¨?ve Bayes classifier is designed to reduce the training cost. Compared with other algorithms, the proposed system and method perform the best and increase the recognition accuracy. The results show that the distributed system framework and the proposed algorithms are suitable for RSIs target classification tasks.

QoE Assessment of Fairness between Players in Networked Virtual 3D Objects Identification Game Using Haptic, Olfactory, and Auditory Senses

In this paper, we carry out QoE (Quality of Experience) assessment to investigate influences of olfactory and auditory senses on fairness for a networked virtual 3D object identification game with haptics. In the game, two players try to identify objects which are placed in a shared 3D virtual space. In the assessment, we carry out the game in four cases. Smells and sounds are presented in the first case, only sounds are done in the second case, and only smells are done in the third case. In the last case, we present neither smell nor sound. As a result, we demonstrate that the fairness deteriorates more largely as the difference in conditions between two users becomes larger.

Fairness Assessment in Networked Games with Olfactory and Haptic Senses

In this paper, we carry out QoE (Quality of Experience) assessment of fairness between players in a networked balloon bursting game with olfactory and haptic senses. We also make a comparison of the fairness among different types of networked games with olfactory and haptic senses in the assessment. Then, we clarify the differences owing to usage of olfactory and haptic senses among the games. As a result, we illustrate that the fairness is largely affected by the delay difference, and we also demonstrate that the allowable range depends on the type of games, type of senses which are employed in the games, and the play methods.

Resilience Training of Preschool Children Based on Traditional Folk Games

Traditional folk games inherit the history,culture and identity of a country and nation,and they have even more important meanings for China,which has a long history and many ethnic groups.However,with the rapid globalization of modem technology and economy,many Chinese traditional folk games are facing the crisis of disappearing.This article discusses how to develop and utilize the new functions of traditional folk games.That is to use them to train the resilience of preschool children,thus to initiate a new understanding of traditional folk games by teachers and parents.The article firstly discusses the importance of cultivating preschool children's resilience,then analyzes the role of games in cultivating preschool children's resilience,studies the traditional folk game classification method for preschool children's resilience,and gives the development orientation traditional folk game teaching strategies and steps for the cultivation of resilience.This research not only inherits Chinese traditional culture in preschool education,but also trains preschool children's resilience and strengthens their minds.It has important practical significance and reference value for the current training and education of preschool children in China and East Asia.

Research on the evolutionary game of the supervision of civil aviation dangerous goods transportation training

This study is carried out to promote the precise supervision of dangerous goods transportation training,improve the efficiency of civil aviation supervision and further ensure the safety of air transportation.First,from the perspective of behaviour interaction and interest demands,evolutionary game theory is used to construct a tripartite evolutionary game model of dangerous goods transportation training institutions,the Civil Aviation Administration of China(CAAC)and the public.Then,the evolutionary game equilibrium of the system is further analysed under the joint action of the three parties.Finally,the influences of important parameters of the model on the behavioural strategy selection of the three parties are investigated via MATLAB numerical simulation.The conclusions reveal that the system has three evolutionarily stable strategies under different parameters,namely(non-compliant training,supervision,non-participation in supervision),(non-compliant training,supervision,participation in supervision)and(compliant training,supervision,non-participation in supervision).Moreover,the CAAC supervision cost,the fine amount,the supervision cost of public participation,the supervision success rate and the reporting reward amount are the main parameters that affect the behavioural strategy selection of the tripartite game players.The conclusions and suggestions of this study provide a decision-making basis and guidance for the supervision and management of civil aviation dangerous goods transportation training.

A NOVEL COOPERATIVE SPECTRUM SENSING METHOD BASED ON COOPERATIVE GAME THEORY

A novel cooperative sensing method is proposed in this paper. The proposed scheme adopts sensing creditability degree to characterize the impact of the distance and the channel parameters on the sensing result,and considers that each user has different average SNR and different decision threshold,by using General Nash Bargaining Solution (GNBS) strategy in Cooperative Game Theory (CGT),the detection performance for two-user case are derived. For multi-user case,the sensing performance is obtained with Hungarian method. Compared with the traditional schemes such as Nash Bargaining Solution (NBS) and AND,the proposed scheme covers all the factors mentioned above,and enhances the sensing rationality and reliability. Simulation results show that the proposed scheme can further improve the sensing performance and creditability.

Effects of soccer training on health-related physical fitness measures in male adolescents

Purpose: The aims of this study were to(1) investigate the health-related physical fitness profile of untrained adolescent boys in comparison to adolescent soccer players,(2) determine the intensity and enjoyment of 6 v 6 and 4 v 4 small-sided games, and(3) evaluate the health-related effects of a short-period of soccer training in the untrained group.Methods: Forty-one adolescent boys(untrained, n = 24: age = 15.9 ± 0.6 years; trained, n = 17: age = 15.7 ± 0.7 years) were recruited. For Purpose 1,the players(n = 17) and the untrained(n = 24) boys were tested for speed, jumping power, postural balance, flexibility, and aerobic capacity. After baseline testing, Purposes 2 and 3 were addressed by randomly assigning the untrained boys to either a soccer-training group(small-sided games,2 sessions per week for 8 weeks) or to a control group, followed by identical retesting.Results: At baseline, physical fitness was higher(p < 0.001) in trained players than in untrained for aerobic fitness, sprinting, jumping power, and postural balance. Small-sided games using 6 v 6 or 4 v 4 elicited similar heart rate(HR)(mean: ~ 85% peak heart rate, HR_(peak)), rate of perceived exertion, and enjoyment responses. Over 8 weeks, the between-group analysis revealed that soccer training had a large beneficial effect on postural balance(45%) when compared with control group with unclear effects on other fitness parameters.Conclusion: Adolescent soccer players had markedly higher physical fitness compared with untrained adolescents. Small-sided soccer games practiced by untrained adolescents elicited high exercise intensity. While 8 weeks of twice-weekly soccer training sessions induced significant improvement in postural balance, the short duration of the study was not sufficient to result in between-group differences in sprint and jump performance or aerobic fitness.

Impact of Virtual RealityTraining on Real-World Hockey Skill: An Intervention Trial

Training specificity is imperative for successful performance of the elite athlete.Virtual reality(VR)has been successfully applied to a broad range of training domains.However,to date there is little research investigating the use of VR for sport training.The purpose of this study was to address the question of whether virtual reality(VR)training can improve real world hockey shooting performance.Twenty four volunteers were recruited and randomly selected to complete the virtual training intervention or enter a control group with no training.Four primary types of data were collected:(1)participant’s experience with video games and hockey,(2)participant’s motivation toward video game use,(3)participant’s technical performance on real-world hockey,and(4)participant’s technical performance in virtual hockey.One-way multivariate analysis of variance(ANOVA)indicated that the intervention group demonstrated significantly more real-world hockey accuracy(F(1,24)=15.43,p<0.01,E.S.=0.56)while shooting on goal than their control group counterparts(intervention M accuracy=54.17%,SD=12.38,control M accuracy=46.76%,SD=13.45).One-way multivariate analysis of variance(MANOVA)repeated measures indicated significantly higher outcome scores on real-world accuracy(35.42%versus 54.17%;ES=1.52)and velocity(51.10 mph versus 65.50 mph;ES=0.86)of hockey shooting on goal.This research supports the idea that virtual training is an effective tool for increasing real-world hockey skill.

A Novel Training Sequence Applied to DCS-Based Channel Estimation

Studies have indicated that the distributed compressed sensing based(DCSbased) channel estimation can decrease the length of the reference signals effectively. In block transmission, a unique word(UW) can be used as a cyclic prefix and reference signal. However, the DCS-based channel estimation requires diversity sequences instead of UW. In this paper, we proposed a novel method that employs a training sequence(TS) whose duration time is slightly longer than the maximum delay spread time. Based on proposed TS, the DCS approach perform perfectly in multipath channel estimation. Meanwhile, a cyclic prefix construct could be formed, which reduces the complexity of the frequency domain equalization(FDE) directly. Simulation results demonstrate that, by using the method of simultaneous orthogonal matching pursuit(SOMP), the required channel overhead has been reduced thanks to the proposed TS.

面向多源异质遥感影像地物分类的自监督预训练方法

近年来,深度学习改变了遥感图像处理的方法。由于标注高质量样本费时费力,标签样本数量不足的现实问题会严重影响深层神经网络模型的性能。为解决这一突出矛盾,本文提出了用于多源异质遥感影像地物分类的自监督预训练和微调分类方案,旨在缓解模型对于标签样本的严重依赖。具体来讲,生成式自监督学习模型由非对称的编码器-解码器结构组成,其中深度编码器从多源遥感数据中学习高阶关键特征,任务特定的解码器用于重建原始遥感影像。为提升特性表示能力,交叉注意力机制模型用于融合异源特征中的信息,进而从多源异质遥感影像中学习更多的互补信息。在微调分类阶段,预训练好的编码器作为无监督特征提取器,基于Transformer结构的轻量级分类器将学习到的特征与光谱信息结合并用于地物分类。这种自监督预训练方案能够从多源异质遥感影像中学习到刻画原始数据的高级关键特征,并且此过程不需要任何人工标注信息,从而缓解了对标签样本的依赖。与现有的分类范式相比,本文提出的自监督预训练和微调方案在多源遥感影像地物分类中能够取得更优的分类结果。

全国民族运动会铸牢中华民族共同体意识的价值内涵与实践路径

全国民族运动会的成功举办是党和国家立足国情,汲取历史滋养,将民族传统体育与民族工作相结合的具体实践。全国民族运动会已成为各民族交往交流交融历史事实的有效载体,成为促进民族团结、增强中华文化认同、传承中华优秀传统文化的重要平台。进入新时代,全国民族运动会在培养社会主义核心价值观、构建民族传统体育传承体系、坚持“以人民为中心”、融入全民健身、推进乡村文明建设等诸多方面发挥着积极作用,为铸牢中华民族共同体意识提供实践路径。

基于演化博弈的民航危险品运输培训监管

为促进民航危险品运输培训精准监管,提升民航监管效能,实现合规培训与监管的最佳局面,进一步保障航空运输安全。首先从行为交互和微观经济学的角度,运用演化博弈方法,构建危险品运输培训机构和民航局双方演化博弈模型,定量分析博弈双方行为策略选择的情境条件及形成原因;然后运用MATLAB软件对重要参数的敏感性进行数值仿真分析,探讨受训者能力不足造成不安全事件概率、查处成功率、处罚力度和监管成本4个重要参数对系统演化路径及结果的影响效应;最后从管理层面对民航危险品运输培训监管提出有针对性的建议及措施。结果表明:受训者能力不足造成不安全事件概率、查处成功率和处罚力度3个参数对博弈双方行为选择具有正效应,而监管成本对博弈双方行为选择具有负效应。

体育游戏在体育运动训练中的应用价值与实施策略研究

体育游戏是一种以游戏形式进行的体育活动,不仅具有娱乐性和趣味性,同时还能有效地提高参与者的身体素质和运动技能。在体育运动训练中,体育游戏的应用可以丰富训练内容,提高运动员的兴趣和参与度,从而提升训练效果。因此,为了进一步提升运动员的体育运动训练效果,该文利用文献资料法、逻辑分析法等研究方法,在对体育游戏在体育运动训练中的价值进行深入认识的基础上,探索体育游戏在体育运动训练中的具体实施策略,以期能够增加体育运动训练的趣味性与有效性。

东京奥运会国家步枪射击运动员体能训练实证研究

目的:对东京奥运会我国步枪射击运动员基础体能和专项体能数据进行系统梳理和深度挖掘,总结和提炼体能训练备战策略,以期为我国高水平步枪射击运动员体能训练向着专业化、精细化和精准化方向高质量发展提供参考。方法:通过专家访谈和问卷调查形成步枪射击运动员专项体能测试指标;对运动员10项基础体能指标和4项专项体能指标进行测试,并根据前测结果制订16周集训计划;通过独立样本T检验和配对样本T检验对训练效果进行组间和组内差异性检验;采用曲线回归探索基础体能和专项成绩间的关系。结果:1)东京奥运会入选队员和未入选队员基础体能整体无显著性差异;2)东京奥运会获奖运动员各项基础体能测试数据互有高低,呈现出明显的个性化特征;3)步枪射击运动员基础体能(X)和专项成绩(Y)之间呈倒U形关系,二次曲线回归方程Y=0.331+-0.14*X+-0.038*X2,校正R2=0.27;4)集训后组内比较发现男女子运动员各专项体能测试指标均非常显著性的高于训练前。结论:1)步枪射击运动员基础体能与专项成绩或呈“倒U形”关系;2)步枪射击运动员专项体能水平满足项目特征需求后,专项体能水平的高低不再是影响其专项成绩的关键因素,而不同专项体能间发展的均衡程度或成为影响专项成绩的关键因素;3)步枪射击运动员专项体能训练策略应重点考虑核心力量耐力、下肢力量耐力、有氧能力和平衡能力4个方面。

基于博弈论组合赋权-云模型的消防员训练损伤风险评估

为降低消防员训练损伤发生率,从个人因素、环境因素和组织管理因素3个方面,提出包含19个指标的消防员训练损伤风险评估指标体系;采用Bonferroni有序加权平均算子(BON-OWA算子)修正层次分析法(AHP)的误差,获得各指标的主观权重;引用基于指标相关性的权重确定法(CRITIC)确定各指标的客观权重;基于博弈论组合赋权法确定各指标的组合权重;引入云模型理论,建立消防员训练损伤风险评估模型,并以河南省某消防救援大队消防员的训练为例,验证该模型的科学性。结果表明:训练装备的战技性能状况指标对消防员的训练损伤风险等级影响最大;该风险评估模型通过数据处理,可以确定消防员训练损伤风险等级;案例中,消防员在5种不同情景下的训练损伤风险等级均为一般风险,这与模糊综合评价法所得结果一致。

铸牢中华民族共同体意识下视唱练耳课程建设

在铸牢中华民族共同体意识的大背景下,视唱练耳课程建设对于音乐表演专业具有深远意义。本文将从以铸牢中华民族共同体意识为主线进行视唱练耳课程专业方向分类建设,结合区域特色进行多声部训练与即兴创编在视唱练耳课程中的实践,中国民族音乐作品在视唱练耳课程中的运用与传承团队建设与视唱练耳课程发展的关系四个方面来对铸牢中华民族共同体意识下视唱练耳课程建设进行探讨。旨在探讨帮助学生将理论知识转化为实际表演能力。通过引导关注本土音乐的独特魅力、加强国际交流与合作,为中国音乐的传承与创新发展创造条件。通过不断总结实践经验、深化研究与实践,提高视唱练耳课程的教学质量,为中华民族的伟大复兴贡献力量。

轨道交通列车新一代健康管理系统架构研究

科学维护运营车辆、保障列车运行安全一直以来都是轨道交通领域的核心问题。近年来,随着列车预测性维修和无人驾驶等重大需求的提出,迫切需要实现全息状态感知、精细诊断预测、及时反馈处置的列车健康管理功能。现有系统架构存在着感知低效、融合深度不足、模型优化动态差、计算协同弱、自主化决策水平低等问题,先进的物联网、大数据、人工智能、数字孪生等技术的发展,推动了列车健康管理系统架构向更高水平智能化演进。文章对列车健康管理系统技术发展阶段进行了梳理划分,在此基础上提出了基于泛在感知与协同计算的轨道交通列车健康管理系统4.0架构,详细阐述了其内涵概念、系统架构和关键技术,归纳出泛在感知、协同计算与健康管理深度融合的解决途径、技术手段和预期效果,明确了现阶段技术攻关的主要方向,进而支撑列车安全保障和运维品质的提升。

三分球投篮技术及其训练方法的研究

研究旨在探讨三分球投篮技术及训练方法,以提高球员的投篮命中率。基础训练包括站位、姿势校正和出手动作练习,瞄准训练通过目标设定提高准确性,力量训练增强上肢和核心稳定性,节奏训练则通过反复练习提高投篮的连贯性和效率。此外,提高命中率的技巧包括控制情绪、增强自信心、模拟比赛场景、利用录像回放分析和持续练习。通过这些方法,球员可以在比赛中更有效地执行三分球投篮。