A Deep Learning Based Broadcast Approach for Image Semantic Communication over Fading Channels

We consider an image semantic communication system in a time-varying fading Gaussian MIMO channel,with a finite number of channel states.A deep learning-aided broadcast approach scheme is proposed to benefit the adaptive semantic transmission in terms of different channel states.We combine the classic broadcast approach with the image transformer to implement this adaptive joint source and channel coding(JSCC)scheme.Specifically,we utilize the neural network(NN)to jointly optimize the hierarchical image compression and superposition code mapping within this scheme.The learned transformers and codebooks allow recovering of the image with an adaptive quality and low error rate at the receiver side,in each channel state.The simulation results exhibit our proposed scheme can dynamically adapt the coding to the current channel state and outperform some existing intelligent schemes with the fixed coding block.

Multi-Perspective Data Fusion Framework Based on Hierarchical BERT: Provide Visual Predictions of Business Processes

Predictive Business Process Monitoring(PBPM)is a significant research area in Business Process Management(BPM)aimed at accurately forecasting future behavioral events.At present,deep learning methods are widely cited in PBPM research,but no method has been effective in fusing data information into the control flow for multi-perspective process prediction.Therefore,this paper proposes a process prediction method based on the hierarchical BERT and multi-perspective data fusion.Firstly,the first layer BERT network learns the correlations between different category attribute data.Then,the attribute data is integrated into a weighted event-level feature vector and input into the second layer BERT network to learn the impact and priority relationship of each event on future predicted events.Next,the multi-head attention mechanism within the framework is visualized for analysis,helping to understand the decision-making logic of the framework and providing visual predictions.Finally,experimental results show that the predictive accuracy of the framework surpasses the current state-of-the-art research methods and significantly enhances the predictive performance of BPM.

An Improved Ensemble Learning Approach for Heart Disease Prediction Using Boosting Algorithms

Cardiovascular disease is among the top five fatal diseases that affect lives worldwide.Therefore,its early prediction and detection are crucial,allowing one to take proper and necessary measures at earlier stages.Machine learning(ML)techniques are used to assist healthcare providers in better diagnosing heart disease.This study employed three boosting algorithms,namely,gradient boost,XGBoost,and AdaBoost,to predict heart disease.The dataset contained heart disease-related clinical features and was sourced from the publicly available UCI ML repository.Exploratory data analysis is performed to find the characteristics of data samples about descriptive and inferential statistics.Specifically,it was carried out to identify and replace outliers using the interquartile range and detect and replace the missing values using the imputation method.Results were recorded before and after the data preprocessing techniques were applied.Out of all the algorithms,gradient boosting achieved the highest accuracy rate of 92.20%for the proposed model.The proposed model yielded better results with gradient boosting in terms of precision,recall,and f1-score.It attained better prediction performance than the existing works and can be used for other diseases that share common features using transfer learning.

A Communicative Approach to College English Grammar Teaching and Learning

In response to the misconception that Communicative Language Teaching means no teaching of grammar,it is argued that grammar is as important as traffic rules for safe and smooth traffic on the road.To achieve appropriate and effective communication,a communicative approach to college grammar teaching and learning is proposed.Both teachers and learners should change their attitudes toward and conceptions about grammar teaching and learning;additionally,teaching grammar in the company of reading and writing helps learners learn and acquire grammar in meaningful contexts.

Application of Student-centered Learning Approach to English Listening and Speaking Class in Vocational Schools

Student-centered learning approach is focused on the students' demands and interests.Applying student-centered approach puts forward higher requirement to English teachers.This article first analyzes the theory of student-centered learning approach and compares teacher-centered approach with it.Based on the research information and teaching experience,the author summarizes four strategies about how to apply student-centered learning approach to English listening and speaking class in vocational schools.

基于改进Q-learning算法和DWA的路径规划

针对传统Q-learning算法出现的规划路线转折点多,探索效率低,以及无法实现动态环境下的路径规划问题,提出一种基于改进Q-learning算法和动态窗口法(DWA)的融合算法。首先,改变传统Q-learning算法的搜索方式,由原先的8方向变成16方向;利用模拟退火算法对Q-learning进行迭代优化;通过路径节点优化算法进行节点简化,提高路径平滑度。然后,提取改进Q-learning算法规划路径的节点,将其作为DWA算法的临时目标,前进过程中,能够实时躲避环境中出现的动静态障碍物。最终实验结果表明:融合算法具有较好的路径规划能力,实现了全局最优和有效避障的效果。

Feedback iterative learning control for time-delay systems based on 2D analysis approach

This paper deals with the iterative learning control （ILC） design for multiple-input multiple-output （MIMO）,time-delay systems （TDS）.Two feedback ILC schemes are considered using the so-called two-dimensional （2D） analysis approach.It shows that continuous-discrete 2D Roesser systems can be developed to describe the entire learning dynamics of both ILC schemes,based on which necessary and sufficient conditions for their stability can be provided.A numerical example is included to validate the theoretical analysis.

A Sensorless State Estimation for A Safety-Oriented Cyber-Physical System in Urban Driving:Deep Learning Approach

In today's modern electric vehicles,enhancing the safety-critical cyber-physical system(CPS)'s performance is necessary for the safe maneuverability of the vehicle.As a typical CPS,the braking system is crucial for the vehicle design and safe control.However,precise state estimation of the brake pressure is desired to perform safe driving with a high degree of autonomy.In this paper,a sensorless state estimation technique of the vehicle's brake pressure is developed using a deep-learning approach.A deep neural network(DNN)is structured and trained using deep-learning training techniques,such as,dropout and rectified units.These techniques are utilized to obtain more accurate model for brake pressure state estimation applications.The proposed model is trained using real experimental training data which were collected via conducting real vehicle testing.The vehicle was attached to a chassis dynamometer while the brake pressure data were collected under random driving cycles.Based on these experimental data,the DNN is trained and the performance of the proposed state estimation approach is validated accordingly.The results demonstrate high-accuracy brake pressure state estimation with RMSE of 0.048 MPa.

Dragonfly Optimization with Deep Learning Enabled Sentiment Analysis for Arabic Tweets

Sentiment Analysis(SA)is one of the Machine Learning(ML)techniques that has been investigated by several researchers in recent years,especially due to the evolution of novel data collection methods focused on social media.In literature,it has been reported that SA data is created for English language in excess of any other language.It is challenging to perform SA for Arabic Twitter data owing to informal nature and rich morphology of Arabic language.An earlier study conducted upon SA for Arabic Twitter focused mostly on automatic extraction of the features from the text.Neural word embedding has been employed in literature,since it is less labor-intensive than automatic feature engineering.By ignoring the context of sentiment,most of the word-embedding models follow syntactic data of words.The current study presents a new Dragonfly Optimization with Deep Learning Enabled Sentiment Analysis for Arabic Tweets(DFODLSAAT)model.The aim of the presented DFODL-SAAT model is to distinguish the sentiments from opinions that are tweeted in Arabic language.At first,data cleaning and pre-processing steps are performed to convert the input tweets into a useful format.In addition,TF-IDF model is exploited as a feature extractor to generate the feature vectors.Besides,Attention-based Bidirectional Long Short Term Memory(ABLSTM)technique is applied for identification and classification of sentiments.At last,the hyperparameters of ABLSTM model are optimized using DFO algorithm.The performance of the proposed DFODL-SAAT model was validated using the benchmark dataset and the outcomes were investigated under different aspects.The experimental outcomes highlight the superiority of DFODL-SAAT model over recent approaches.

FIRST LANGUAGE ACQUISITION AS A MODEL FOR SECOND LANGUAGE ACQUISITION: THE TOTAL PHYSICAL RESPONSE APPROACH IN SECOND LANGUAGE LEARNING AND TEACHING

L1 and L2 acquisition, in some respects, are similar. Language development in children goes hand in hand with physical and cognitive development. Children learn their first language by imitation, but not always and not only by imitation. There seems to be some "innate capacities" that make children start to speak at the same time they do and in the way they do it. Adults learning a second language usually are controlled more by their motivation. But language input is important for both L1 and L2 acquisition. Though there are differences between CL1 and between CL2 and AL2, the way in which these learners acquire some of the grammatical morphemes is similar. This, together with some other evidence, shows that it is not only children who can acquire language. Adults can also acquire a language. But when adults acquire a language, they should also learn it. Some of the ways in which children acquire their language can be used as a model for L2 acquisition, even for Chinese students whose language is unrelated to English and whose culture is different. Learning the culture of the English-speaking countries will benefit the learning of the language. Like children, listening should also be well in advance of speaking in L2 acquisition. To train listening comprehension skills, Asher’s TPR approach proves more effective. TPR approach is at the moment limited to the beginning stage only. In order for students to gain all the five skills in a second language learning, namely, listening, speaking, reading, writing, and interpreting/translating, other methods should be used at the same time, or at later stages.

A novel machine learning approach(svm Somatic) to distinguish somatic and germline mutations using next-generation sequencing data

DEAR EDITOR,Somatic mutations are a large category of genetic variations,which play an essential role in tumorigenesis. Detection of somatic single nucleotide variants(SNVs) could facilitate downstream analysis of tumorigenesis. Many computational methods have been developed to detect SNVs, but most require normal matched samples to differentiate somatic SNVs from the normal state, which can be difficult to obtain.

Fathers’Parenting Practices and the Children’s Approaches to Learning From Three Through Five Years;A Case of Mityana District,Uganda

The Approaches to Learning addresses how children learn-this includes children’s attitudes and interests in learning.This domain reflects behaviours and attitudes such as curiosity,problem-solving,maintaining attention and persistence.The research study focused on examining the fathers’parenting practices and the children’s approaches to learning from three through five years.The study used a cross sectional research design and data was generated using focal group discussions,interview guides and child behaviour rating scale on how fathers’parenting practices contribute to children’s approaches to learning.Results revealed that,Fathers’parenting practices and Children’s curiosity were found to have a very positive relationship(r=0.396,p<0.05).Fathers’parenting practices and children’s learning were found to have a significant positive relationship(r=0.420,p<0.05).Findings also indicated that fathers’parenting practices and children’s creativity were found to have an average positive relationship(r=0.379,p<0.05).Arising out of the findings,the study recommended that fathers’parenting programs be put in place to help them up bring the child in holistic manner.

Applying machine learning approaches to improving the accuracy of breast-tumour diagnosis via fine needle aspiration

Diagnosis and treatment of breast cancer have been improved during the last decade; however, breast cancer is still a leading cause of death among women in the whole world. Early detection and accurate diagnosis of this disease has been demonstrated an approach to long survival of the patients. As an attempt to develop a reliable diagnosing method for breast cancer, we integrated support vector machine (SVM), k-nearest neighbor and probabilistic neural network into a complex machine learning approach to detect malignant breast tumour through a set of indicators consisting of age and ten cellular features of fine-needle aspiration of breast which were ranked according to signal-to-noise ratio to identify determinants distinguishing benign breast tumours from malignant ones. The method turned out to significantly improve the diagnosis, with a sensitivity of 94.04%, a specificity of 97.37%, and an overall accuracy up to 96.24% when SVM was adopted with the sigmoid kernel function under 5-fold cross validation. The results suggest that SVM is a promising methodology to be further developed into a practical adjunct implement to help discerning benign and malignant breast tumours and thus reduce the incidence of misdiagnosis.

Learning curve for a surgeon in robotic pancreaticoduodenectomy through a“G”-shaped approach:A cumulative sum analysis

BACKGROUND Robotic pancreaticoduodenectomy(RPD)can achieve similar surgical results to open and PD;however,RPD has a long learning curve and operation time(OT).To address this issue,we have summarized a surgical path to shorten the surgical learning curve and OT.AIM To investigate the effective learning curve of a“G”-shaped surgical approach in RPD for patients.METHODS A total of 60 patients,who received“G”-shaped RPD(GRPD)by a single surgeon in the First Hospital of Shanxi Medical University from May 2017 to April 2020,were included in this study.The OT,demographic data,intraoperative blood loss,complications,hospitalization time,and pathological results were recorded,and the cumulative sum(CUSUM)analysis was performed to evaluate the learning curve for GRPD.RESULTS According to the CUSUM analysis,the learning curve for GRPD was grouped into two phases:The early and late phases.The OT was 480±81.65 min vs 331±76.54 min,hospitalization time was 22±4.53 d vs 17±6.08 d,and blood loss was 308±54.78 mL vs 169.2±35.33 mL in the respective groups.Complications,including pancreatic fistula,bile leakage,reoperation rate,postoperative death,and delayed gastric emptying,were significantly decreased after this surgical technique.CONCLUSION GRPD can improve the learning curve and operative time,providing a new method for shortening the RPD learning curve.

Investigating the Relationship Between Teaching Approach and Language Learning Motivation of College English Classrooms in China

The study was aimed at exploring the relationship between teaching approach and students'learning motivation.The participants were two college English teachers and their fixed group of students.The research lasted 16 weeks.The instruments used in the study were Attitude/Motivation Test Battery(AMTB) and classroom observation.Analyzing by the mean of the AM TB result,researchers got the popular tendencies of students'learning motivation level every four weeks.Comparing the change of students'learning motivation level and teacher participants'frequency of using the recommended teaching approach,this arti cle intends to achieve two purposes:1) Is students'learning motivation related to their teachers'teaching approach? 2) Among the approach recommended by literature,which works the best in the colleges in China?

The Model of Open and Distance Learning for Teaching Indonesian Through Socio-Cultural Approach and Psychological Aspects to Students of Indonesian for Foreign

This study aims to find out the effect of the model of ODL （Open and Distance Learning） for teaching Indonesian for foreign and whether this model of ODL implements socio-cultural and psychological approaches. The students＇ learning of Indonesian for foreign is in so many aspects that it must be considered from both psychological aspects of students＇ language and cultural aspects. The research was carried out on foreign students＇ studying Indonesian language. The research method used action research. ODL model developed this concerning how the students are anxious in foreign language learning and language use in accordance with Indonesian culture. The model of ODL for teaching foreign Indonesian uses the Internet facilities such as email, Skype, VolP, Google Talk, circulating document with comments, chat, forum, CD, audio-video, stream media player, and e-learning system. Based on the results of this study which is that students study the model ODL for teaching Indonesian through socio-cultural approach and psychological aspects and students of Indonesian for foreign improve their ability to use the Indonesian language, students are able to converse fluently in Indonesian in accordance with Indonesian culture

Intercultural Education in a Technology-Enhanced Foreign Language Learning Environment Implementing the TPACK Approach:Challenges and Possibilities

In the plurilingual and multicultural contemporary international setting,the educational systems opt for successfully meeting as well as adapting to the rapid social,economic,and technological changes.Based on the premise that intercultural communicative competence holds a significant potential for foreign language instruction,focus should throw into combining teachers’intercultural knowledge with pedagogy and technology.The prospect of introducing intercultural material within the context of teaching scenarios in the curricula of a technology-enhanced foreign language learning environment where the Technological Pedagogical Content Knowledge(TPACK)approach is implemented,can positively contribute to the teaching process.Under this perspective,cultural and digitally competent teachers can create a framework which will enable learners to fully develop their interactive and linguistic skills and to effectively communicate in a foreign language promoting its social and multicultural dimension whatever the intercultural context.

A Discussion On the Range of Meaning of English Words──An Approach to English Words Learning

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PBL(Project-based Learning)教学模式在高职英语自主学习课程中的应用研究

本文采用行动研究的方法,以武汉职业技术学院的英语听说过级自主学习课程为例,探讨如何在自主学习课程中应用PBL的教学模式改进自主学习课程的考核方式,提高学生的自主学习能力和意识。文章首先分析了自主学习课程在实施过程中遇到的问题,详细描述了PBL教学模式的总体设计构想和具体的实施步骤,并对实施的结果进行了讨论。经过统计和问卷调查结果发现,应用PBL模式后,实验班的学生的学习兴趣有了很大的提高,有利于培养他们的自主学习能力和合作精神。同时,试验前后的听力测试表明,实验班听力成绩较对照班也有了显著的提高。可见,PBL模式的应用能在一定程度上改进目前在自主学习课程中所遇到的一些问题。

基于利益相关者理论的企业E-learning管理研究

作为现代企业培训的主要方式,E-learning在得到普遍应用的同时,其管理中存在的问题也日益暴露出来。只有通过利益相关者理论实现"以人为本"的理念,才能充分发挥企业E-learning的作用,让员工在自己的工作岗位上获得成功的同时,实现共同的商业目的。