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.

A Study of Application of Games in Children English Teaching Taking Children English Class in Education First Training School for Example

As a teaching aid, games are vital to facilitate every part in learning process. They are easy to arouse learners＇ attention and are accessible to achieve teaching objectives compared with traditional teaching. The author did two-month classroom observations in Education First Training School in Ningbo. This paper discusses and shares useful and effective games provided in English class.

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.

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.

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.

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.

Principles and practices of training for soccer

The complexity of the physical demands of soccer requires the completion of a multi-component training programme. The development, planning, and implementation of such a programme are difficult due partly to the practical constraints related to the competitive schedule at the top level. The effective planning and organisation of training are therefore crucial to the effective delivery of the training stimulus for both individual players and the team. The aim of this article is to provide an overview of the principles of training that can be used to prepare players for the physical demands of soccer. Information relating to periodisation is supported by an outline of the strategies used to deliver the acute training stress in a soccer environment. The importance of monitoring to support the planning process is also reviewed.

A game-theory approach against Byzantine attack in cooperative spectrum sensing

In order to solve the Byzantine attack problem in cooperative spectrum sensing,a non-cooperative game-theory approach is proposed to realize an effective Byzantine defense.First,under the framework of the proposed non-cooperative game theory,the pure Byzantine attack strategy and defense strategy in cooperative spectrum sensing are analyzed from the perspective of the Byzantine attacker and network administrator.The cost and benefit of the pure strategy on both sides are defined. Secondly,the mixed attack and defense strategy are also derived. The closed form Nash equilibrium is obtained by the Lemke-Howson algorithm. Furthermore,the impact of the benefit ratio and penalty rate on the dynamic process of the noncooperative game is analyzed. Numerical simulation results show that the proposed game-theory approach can effectively defend against the Byzantine attack and save the defensive cost.

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.

Study on Features of Interpreting Courses and Interpreting Teaching Strategy of Postgraduate Interpreting Majors from the perspective of the Theory of Sense

With the ever-spreading of international globalization and much frequent communication among countries in politics, economics and culture. Interpretation which serves as communicative bridge between different languages, which has become an important inter-lingual communicative device. In order to meet the demand of the growing need for interpreting talents, more and more institutions of higher learning begin to set up translation and interpretation courses for undergraduate and graduate students. The thesis focuses on making a brief analysis on the present situation of interpreting courses of graduate students in Inner Mongolian Autonomous Region. The thesis is composed of three parts： the first part is a brief analysis of the interpreting features of graduate students in Inner Mongolia, the second part analyzes the principles of interpreting training from the perspective of interpretive theory. The third part is the suggestions for interpreting training so as to make a contribution to the teaching of interpreting in Inner Mongolia.

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).

校园足球教学与训练方法--基于国外足球Small-Sided Games的解读

教学与训练方法的落后已经成为我国校园足球高质量发展和高效率普及的瓶颈。基于丰富我国足球教学与训练方法,提高校园足球普及质量与效率的现实需要,对国外足球小场训练赛(SSGs)的概念、特点、理论基础、训练效果影响因素及实践操作过程等进行解读。以期增进广大中小学足球专项教师和教练对该方法的理解和掌握,同时,引导和提高他们对该方法的科学使用。

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.

Oh Language Sense Training in College English Teaching Practice

The author supposes that there is a big gap between vocabulary and text in the course of second languageacquisition.Ignorance of individual sentence training to acquire language sense in the CET coursemight be one of the reasons to account for the failure of many students to be speakers of English afterthey graduate.Students should be encouraged to read and recite some model sentences and articles so asto gain a certain language sense as hardware and supporting materials in linguitic communication.Thus confidence is obtained and the gap between vocabulary and text can be easily jumped over.

Remote sensing image classification based on BP neural network model

Aiming at the characteristics of remote sensing image classification, the mixed pixel problem is one of the main factors that affect the improvement of classifying precision in remote sensing classification. A BP neural network was established to solve mixed pixel classifying problems. The aim of our work is to improve the BP network algorithm and set the intensity of training, which changes with training process, because the BP algorithm converyging speed of learning algorithm is rather slow, it is possible to fall into the local minimum, and because the algorithm makes the learning result poor, the global minimum value can’t be reached. The results show that this method effectively solves mixed pixel classifying problem, improves learning speed and classification accuracy of BP network classifier,so it is one kind of effective remote sensing imagery classifying method.

Application of Neural Network to Game Algorithm

Intelligent was very important for command decision model, and it was also the key to improve the quality of simulation training and combat experiment. The decision-making content was more complex in the implementation of tasks and the nature of the problem was different, so the demand for intelligence was high. To solve better the problem, this paper presented a game method and established a game neural network model. The model had been successfully applied in the classification experiment of winning rate between chess game, which had good theoretical significance and application value.

Remote Sensing Education for Life Long Learning across the East Midlands Region

Over the last decade, remote sensing technologies have provided useful tools for a diverse range of sectors. G-STEP （GMES--space technology exchange partnership） is the University of Leicester＇s flagship project for innovation, training and education in GMES （global monitoring for environment and security） and GIS （geographical information systems） based technologies. G-STEP （part funded by the ERDF） is the first GMES accelerator initiative in the UK and is breaking new ground in the application of GMES and GIS. The core G-STEP team initiates and develops Knowledge Exchange Practices between the University and Life Long Learning partners in the East Midlands Region, through training packages and collaborative research projects. The programme integrates innovative research, to direct downstream applied training, supported by analytical processing of attendee assessment data. Collated information derived from these sources presents a unique opportunity to incorporate a statistically viable feedback cycle, making G-STEP the interface between pure and applied research, thus initiating downstream dissemination to groups and small business. In this paper, we outline the GMES and GIS training packages, and the route to market to increase uptake of underused data streams via university and regional entrepreneurs （start-ups） and established small business with a core interest in utilisation and dissemination of novel technologies in sustainable lifelong learning.

Metric-based Few-shot Classification in Remote Sensing Image

Target recognition based on deep learning relies on a large quantity of samples,but in some specific remote sensing scenes,the samples are very rare.Currently,few-shot learning can obtain high-performance target classification models using only a few samples,but most researches are based on the natural scene.Therefore,this paper proposes a metric-based few-shot classification technology in remote sensing.First,we constructed a dataset(RSD-FSC)for few-shot classification in remote sensing,which contained 21 classes typical target sample slices of remote sensing images.Second,based on metric learning,a k-nearest neighbor classification network is proposed,to find multiple training samples similar to the testing target,and then the similarity between the testing target and multiple similar samples is calculated to classify the testing target.Finally,the 5-way 1-shot,5-way 5-shot and 5-way 10-shot experiments are conducted to improve the generalization of the model on few-shot classification tasks.The experimental results show that for the newly emerged classes few-shot samples,when the number of training samples is 1,5 and 10,the average accuracy of target recognition can reach 59.134%,82.553%and 87.796%,respectively.It demonstrates that our proposed method can resolve few-shot classification in remote sensing image and perform better than other few-shot classification methods.