Green Communication: An Effective Approach to Minimize Risk of Forgetfulness from Mobile Phone Usage

The usage of mobile-phone among children increased significantly. Children are in their growing phase and cells of their body are rapidly dividing, therefore propagation of electro-magnetic (EM) radiation occurs quickly in children. The aim of the present study was to evaluate the extent of mobile-phone usage as well as its possible health effect. A total number of 455 (398 children and 57 adults, 396 urban and 59 rural) students of age group ranging from 10-29 years participated in this study. An “Information Gathering Chronological (IGC) model” was used for the collection and evaluation of information. The four major parameters, i.e. demographic and public uniqueness, mobile-phone consumption patterns, grievance of the “forgetfulness” symptom to the subjects and awareness about the safety measures were included to get the concise information from participants. We have observed that the prevalence of “forgetfulness” was 23.95% among mobile-phone users. The incidence of overall “forgetfulness” symptoms was 23.59%, 17.46%, 25.00% and 37.50% in low (LU), normal (NU), moderate (MU) and heavy (HU) mobile-phone users respectively. A trend for risk for “forgetfulness” was observed in HU as compared to LU in overall mobile-phone users. Three folds and nearly five folds increased risk for “forgetfulness” was found among HU as compared to LU in children (p ≤ 0.0210) and urban area mobile-phone users respectively. No significant difference for “forgetfulness” symptoms was found in other categories (i.e. adult and rural mobile-phone users). These results suggested that the incidences of “forgetfulness” among children from urban area mobile-phone users were significantly increased.

Improved Variable Forgetting Factor Proportionate RLS Algorithm with Sparse Penalty and Fast Implementation Using DCD Iterations

The proportionate recursive least squares(PRLS)algorithm has shown faster convergence and better performance than both proportionate updating(PU)mechanism based least mean squares(LMS)algorithms and RLS algorithms with a sparse regularization term.In this paper,we propose a variable forgetting factor(VFF)PRLS algorithm with a sparse penalty,e.g.,l_(1)-norm,for sparse identification.To reduce the computation complexity of the proposed algorithm,a fast implementation method based on dichotomous coordinate descent(DCD)algorithm is also derived.Simulation results indicate superior performance of the proposed algorithm.

Prediction of lime utilization ratio of dephosphorization in BOF steelmaking based on online sequential extreme learning machine with forgetting mechanism

The machine learning models of multiple linear regression(MLR),support vector regression(SVR),and extreme learning ma-chine(ELM)and the proposed ELM models of online sequential ELM(OS-ELM)and OS-ELM with forgetting mechanism(FOS-ELM)are applied in the prediction of the lime utilization ratio of dephosphorization in the basic oxygen furnace steelmaking process.The ELM model exhibites the best performance compared with the models of MLR and SVR.OS-ELM and FOS-ELM are applied for sequential learning and model updating.The optimal number of samples in validity term of the FOS-ELM model is determined to be 1500,with the smallest population mean absolute relative error(MARE)value of 0.058226 for the population.The variable importance analysis reveals lime weight,initial P content,and hot metal weight as the most important variables for the lime utilization ratio.The lime utilization ratio increases with the decrease in lime weight and the increases in the initial P content and hot metal weight.A prediction system based on FOS-ELM is applied in actual industrial production for one month.The hit ratios of the predicted lime utilization ratio in the error ranges of±1%,±3%,and±5%are 61.16%,90.63%,and 94.11%,respectively.The coefficient of determination,MARE,and root mean square error are 0.8670,0.06823,and 1.4265,respectively.The system exhibits desirable performance for applications in actual industrial pro-duction.

Identification of time-varying system and energy-based optimization of adaptive control in seismically excited structure

The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.

Deep learning algorithm featuring continuous learning for modulation classifications in wireless networks

Although modulation classification based on deep neural network can achieve high Modulation Classification(MC)accuracies,catastrophic forgetting will occur when the neural network model continues to learn new tasks.In this paper,we simulate the dynamic wireless communication environment and focus on breaking the learning paradigm of isolated automatic MC.We innovate a research algorithm for continuous automatic MC.Firstly,a memory for storing representative old task modulation signals is built,which is employed to limit the gradient update direction of new tasks in the continuous learning stage to ensure that the loss of old tasks is also in a downward trend.Secondly,in order to better simulate the dynamic wireless communication environment,we employ the mini-batch gradient algorithm which is more suitable for continuous learning.Finally,the signal in the memory can be replayed to further strengthen the characteristics of the old task signal in the model.Simulation results verify the effectiveness of the method.

2nd Supply Chain Expo Made Important Progress in Supply and Demand Matchmaking

"Ware very honored to be here,discussing the prospect of global supply chain cooperation with distinguished changemakers from all around the world.""This is such a valuable opportunity to meet so many friends and share our plans for the coming Expo."What an inspiring and unforgettable evening!"

Chasing Winter Dreams in the Frozen Charm of Harbin

Harbin is where winter goes to show off.Known as the“Ice City”,Harbin,located in Heilongjiang Province in northeastern China,is a frosty paradise that feels like stepping into a magical wonderland.The cold here is no joke,especially if you forget your gloves.However,once you brave the chill,you’re rewarded with the breathtaking Ice and Snow Festival,where ice sculptures look like something out of a frosty dream.Every year,it attracts countless adventurers eager to experience its iconic ice sculptures,European-inspired architecture,and unique local cuisine.

An Unforgettable Trip Into an Intangible Cultural Heritage at Quanzhou

Quanzhou,as the only starting point of the Maritime Silk Road recognized by the United Nations,was praised as"the most prosperous city in the world"by Marco Polo.On July 25th,2021,China's"Quanzhou:Emporium of the World in Song-Yuan China"was added to the UNESCO World Heritage List as a cultural site,bringing the total number of the country's UNESCO World Heritage sites to 56.The twentytwo world heritage sites in Quanzhou.

Robust Parameter Identification Method of Adhesion Model for Heavy Haul Trains

A robust parameter identification method based on Kiencke model was proposed to solve the problem of the parameter identification accuracy being affected by the rail environment change and noise interference for heavy-duty trains. Firstly, a Kiencke stick-creep identification model was constructed, and the parameter identification task was transformed into a quadratic programming problem. Secondly, an iterative algorithm was constructed to solve the problem, into which a time-varying forgetting factor was added to track the change of the rail environment, and to solve the uncertainty problem of the wheel-rail environment. The Granger causality test was adopted to detect the interference, and then the weights of the current data were redistributed to solve the problem of noise interference in parameter identification. Finally, simulations were carried out and the results showed that the proposed method could track the change of the track environment in time, reduce the noise interference in the identification process, and effectively identify the adhesion performance parameters.

My Unforgettable Middle School Life

How time flies!My colorful middle school life now comes to an end.Here is what I think about my middle school life.In the past,I was busy with my subjects and worked hard at them.I got on well with my classmates.I was good at English.I liked playing basketball.But now I am interested in history,because it is very interesting.

Illuminating the Future

Two hydroelectric power stations built by China have considerably improved the quality of life for Guineans.For Sonkou Condé,28 September is an unforgettable date,because that is when the Kaléta dam,a project in which he was actively involved as an employee,was inaugurated.On this day,traditional Guinean music resounded over the construction site,accompanied by singing and dancing,which vividly displayed the joy and satisfaction of the local people.

I Love Collecting

love collecting,because it can enrich my knowledge,edify my temperament and also make me more careful.I love collecting.When I enjoyed it,I coudld pour all the unhappy things into the deep sea and I couldd even forget myself.When I enjoyed it,I was completely free and at that time I think that I was one of the happiest people in the world,as I owned the whole world in my collections.

An Effective Multiple Model Least Squares Method in Tracking of a Maneuvering Target

A polynomial model, time origin shifting model(TOSM, is used to describe the trajectory of a moving target .Based on TOSM, a recursive laeast squares(RLS) algorithm with varied forgetting factor is derived for tracking of a non-maneuvering target. In order to apply this algorithm to maneuvering targets tracking ,a tracking signal is performed on-line to determine what kind of TOSm will be in effect to track a target with different dynamics. An effective multiple model least squares filtering and forecasting method dadpted to real tracking of a maneuvering target is formulated. The algorithm is computationally more effcient than Kalman filter and the percentage improvement from simulations show both of them are considerably alike to some extent.

翻转课堂如同自己下厨

有一句英文"Tell me,and I will forget;show me,and I may remember;involve me,and I can learn"(直译为:告诉我,我会忘记;展示给我看,我也许能记得;让我参与其中,我才能学会)。无论它的来源是谁,这句话阐述了一个简单而深刻的道理:老师进行完整而高效的知识讲授,和学生真正掌握了这些知识之间,

在操作中体验,从过程中感悟,在感悟中建构——对APOS理论操作、过程阶段的思考

学生只有在亲历中体验思考，才会有真正意义上的理解建构，这早巳成为共识．正如一句格言所言：“I hear，I forget；I see，I remember，I do ,I understand．”（我听到的，忘记了；我看到的，记住了；我做过的，理解了）．而中学数学概念教学实践与资料反馈却显示，从定义出发，介绍符号表达，再讨论一系列性质，便匆匆进入解题环节，重结论轻过程短平快的教学方式仍普遍地存在，寄希望学生能在熟能生巧中达到对概念的深入理解．虽然也有用情境的意识，但常常只是作为引子匆匆呈现，概念课成为习题课，此时“在做中学”被异化为了反复的解题，这种快节奏教学过多的以教师的抽象替代了学生的抽象，造成学生对概念运用不灵活，迁移能力差。甚至很快便记忆模糊的情况屡见不鲜．

定语从句专题配套练习

解析：1．先行词the days虽为时间名词，但从句中forget缺少宾语，故不能用关系副词when，要用that／which；逗号后是非限制性定语从句，从句中缺主语，指代前面内容，用which。注意：解定语从句题一般要用“拆句法＋成分分析法”，将复合句拆为几个简单句，再作句子成分分析，确定关系词。

2001年美国统行词集锦

ground zero:世贸中心废墟'9.11' / 'September 11' : '9.11'恐怖事件terrible Tuesday:恐怖星期二,指2001年9月11日美国遭恐怖袭击的当天post-September 11:后9.11时代evil doers:恐怖分子Let’s roll.:我们开始行动吧.(“9.11”事件中,美联航93次航班上的乘客和机组人员喊出了这句话。

英语幽默故事选萃(英文)

1. The Notes An elderly husband and wife noticed that they were beginning to forget many little things around the house. They were afraid that this

Test 8

Part One: Quick Responses Please make a quick response to the sentence you will hear.1. Where did you get this MTV disc?2. Don’t forget to mail the letter for me on your way back.