1.The price of a desk is 10 times the price of a chair.The desk costs 288 yuan more than the chair.How much does one desk and one chair cost?2.A and B start from two different places and walk toward each other.After 4...1.The price of a desk is 10 times the price of a chair.The desk costs 288 yuan more than the chair.How much does one desk and one chair cost?2.A and B start from two different places and walk toward each other.After 4 hours,they meet at a point that is 4 kilometres away from the midpoint between their starting points.A walks faster than B.How many more kilometres per hour does A walk than B?展开更多
In maths,some calculations are just as hard as word problems.Actually,they are word problems.Strategies of solving problems must be applied,while you are doing such calculations.Now,let's discuss a few questions a...In maths,some calculations are just as hard as word problems.Actually,they are word problems.Strategies of solving problems must be applied,while you are doing such calculations.Now,let's discuss a few questions as examples.展开更多
1.Because it’s a maths problem about rain!因为这是一道关于下雨的数学题Mom:Why is your homework wet?Child:Because it’s a maths problem about rain!妈妈:为什么你的家庭作业湿了?孩子:因为这是一道关于下雨的数学题。
Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satell...Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satellite images of several bands at various frequencies,the mix of high-and low-resolution images that make object classification difficult because of the mixed pixel problem.Accuracy is impacted by the mixed pixel problem,which occurs when pixels belong to different classes and makes detection challenging.To identify mixed pixels,Band Math is used to merge numerous bands to generate a new band NDVI.Thresholding is used to analyze the edges of deforested and non-deforested areas.Segmentation is then used to analyze the pixels which helps to identify the number of mixed pixels to compute the deforested and non-deforested areas.Segmented image pixels are used to categorize the deforestation of the Brazilian Amazon Forest between 2019 and 2023.Verify how many pixels are mixed to improve accuracy and identify mixed pixel issues;compare the mixed and pure pixels of fuzzy clustering with the subtracted morphological image pixels.With the help of segmentation and clustering researchers effectively validate mixed pixels in a specific area.The proposed methodology is easy to analyze and helpful for an appropriate calculation of deforested and non-deforested areas.展开更多
Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the fo...Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the following issues:Models relying on such structures exhibit fixed-order reasoning(e.g.,left-to-right),limiting flexibility and increasing error susceptibility;prior models rely on autoregressive reasoning in a single pass,accumulating minor errors(e.g.,incorrect math symbols)during generation,resulting in reduced accuracy.To address the above issues,we emulate the human“check and modify”process in reasoning and propose a unified M-tree self-correction solver(UTSCSolver)by iterative inference with self-correction mechanism.First,we use an iterative,non-autoregressive process for generating mathematical expressions,free from fixed generation orders to handle complex and diverse problems.Additionally,we design a self-correction mechanism based on alternating execution between a generator and a discriminator.This module iteratively detects and rectifies errors in generated expressions,leveraging previous iteration information for subsequent generation guidance.Experimental results show that our UTSC-Solver outperforms traditional models in accuracy on two popular datasets,while it improves the interpretability of mathematical reasoning.展开更多
I have a best friend・His name is Li Xuan・We live in the same neighborhood and go to the same school.Li Xuan is a kind and clever boy.He always smiles and is ready to help others.One day,I had a problem with my math ho...I have a best friend・His name is Li Xuan・We live in the same neighborhood and go to the same school.Li Xuan is a kind and clever boy.He always smiles and is ready to help others.One day,I had a problem with my math homework and I was very worried.展开更多
Words are like magic.They can lift you up,or they can knock you down.They are the most powerful tool we have.When I was in Grade 7,I performed badly in a math test.
1・absorb vt.吸收;使引人入胜.absorbed adj.全神贯注的.If you want to absorb all knowledge,you must be absorbed.2.abstract adj.抽象的v.抽象.abstracted adj.心不在焉的.Feeling abstracted,he couldn't tackle this abstrac...1・absorb vt.吸收;使引人入胜.absorbed adj.全神贯注的.If you want to absorb all knowledge,you must be absorbed.2.abstract adj.抽象的v.抽象.abstracted adj.心不在焉的.Feeling abstracted,he couldn't tackle this abstract math problem.展开更多
The extent to which schools in a country or region prioritize the professional development of mathematics teachers influences the quality of these teachers,thereby affecting students’mathematics learning and performa...The extent to which schools in a country or region prioritize the professional development of mathematics teachers influences the quality of these teachers,thereby affecting students’mathematics learning and performance.Over the years,the PISA test has evolved into the largest and most influential international educational assessment program.This study,based on PISA 2022 questionnaire data,examines the relationship between the professional growth of mathematics teachers and students’mathematics performance by analyzing samples from sixteen countries/economies.The research focuses on schools’support for mathematics teachers’professional growth,investigating the correlation with students’mathematics literacy test scores through metrics such as the average proportion of teachers who participated in professional development training courses in the past three months and the average proportion of schools offering different types of in-house professional growth training.Based on the findings,recommendations are proposed,including placing greater emphasis on the professional development and growth of mathematics teachers,as well as anchoring this growth in students’learning and development.This study provides multinational insights and scientific evidence for educational management related to mathematics teachers’professional development,offering theoretical support for improving the quality of secondary mathematics education,fostering students’mathematical literacy,and promoting educational equity.展开更多
Deforestation is the purpose of converting forest into land and reforestation compared to deforestation is very low.That’s why closely and accurately deforestation monitoring using Sentinel-1 and Sentinel-2 satellite...Deforestation is the purpose of converting forest into land and reforestation compared to deforestation is very low.That’s why closely and accurately deforestation monitoring using Sentinel-1 and Sentinel-2 satellite images for better vision is required.This paper proposes an effective image fusion technique that combines S-1/2 data to improve the deforested areas.Based on review,Optical and SAR image fusion produces high-resolution images for better de-forestation monitoring.To enhance the S-1/2 images,preprocessing is needed as per requirements and then,collocation between the two different types of images to mitigate the image registration problem,and after that,apply an image fu-sion machine learning approach,PCA-Wavelet.As per analysis,PCA helps to maintain spatial resolution,and Wavelet helps to preserve spectral resolution,gives better-fused images compared to other techniques.As per results,2019 S-2 pre-22 processed collocated image enhances 42.2508 km deforested area,S-1 preprocessed collocated image enhances 23.7918 km^(2) deforested area,and after fusion of the 2019 S-1/2 images,it enhances 16.5335 km deforested area.Similarly,the 20232 S-2 preprocessed collocated image enhances 49.2216 km deforested area,S-1 preprocessed collocated image enhances 2223.8459 km deforested area after fusion of the 2023 S-1/2 images,enhancing 35.9185 km deforested area.These im-provements show that combining data sources gives a clearer and more reliable picture of forest loss over time.The overall paper objective is to apply effective techniques for image fusion of Brazil’s Amazon Forest and analyze the difference between collocated image pixels and fused image pixels for accurate analysis of deforested area.展开更多
文摘1.The price of a desk is 10 times the price of a chair.The desk costs 288 yuan more than the chair.How much does one desk and one chair cost?2.A and B start from two different places and walk toward each other.After 4 hours,they meet at a point that is 4 kilometres away from the midpoint between their starting points.A walks faster than B.How many more kilometres per hour does A walk than B?
文摘In maths,some calculations are just as hard as word problems.Actually,they are word problems.Strategies of solving problems must be applied,while you are doing such calculations.Now,let's discuss a few questions as examples.
文摘1.Because it’s a maths problem about rain!因为这是一道关于下雨的数学题Mom:Why is your homework wet?Child:Because it’s a maths problem about rain!妈妈:为什么你的家庭作业湿了?孩子:因为这是一道关于下雨的数学题。
文摘Brazil’s deforestation monitoring integrates accuracy and current monitoring for land use and land cover applications.Regular monitoring of deforestation and non-deforestation requires Sentinel-2 multispectral satellite images of several bands at various frequencies,the mix of high-and low-resolution images that make object classification difficult because of the mixed pixel problem.Accuracy is impacted by the mixed pixel problem,which occurs when pixels belong to different classes and makes detection challenging.To identify mixed pixels,Band Math is used to merge numerous bands to generate a new band NDVI.Thresholding is used to analyze the edges of deforested and non-deforested areas.Segmentation is then used to analyze the pixels which helps to identify the number of mixed pixels to compute the deforested and non-deforested areas.Segmented image pixels are used to categorize the deforestation of the Brazilian Amazon Forest between 2019 and 2023.Verify how many pixels are mixed to improve accuracy and identify mixed pixel issues;compare the mixed and pure pixels of fuzzy clustering with the subtracted morphological image pixels.With the help of segmentation and clustering researchers effectively validate mixed pixels in a specific area.The proposed methodology is easy to analyze and helpful for an appropriate calculation of deforested and non-deforested areas.
基金supported by the National Natural Science Foundation of China(62106244)the Fundamental Research Funds for the Central Universities(WK2150110021)the University Synergy Innovation Program of Anhui Province(GXXT-2022-042).
文摘Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the following issues:Models relying on such structures exhibit fixed-order reasoning(e.g.,left-to-right),limiting flexibility and increasing error susceptibility;prior models rely on autoregressive reasoning in a single pass,accumulating minor errors(e.g.,incorrect math symbols)during generation,resulting in reduced accuracy.To address the above issues,we emulate the human“check and modify”process in reasoning and propose a unified M-tree self-correction solver(UTSCSolver)by iterative inference with self-correction mechanism.First,we use an iterative,non-autoregressive process for generating mathematical expressions,free from fixed generation orders to handle complex and diverse problems.Additionally,we design a self-correction mechanism based on alternating execution between a generator and a discriminator.This module iteratively detects and rectifies errors in generated expressions,leveraging previous iteration information for subsequent generation guidance.Experimental results show that our UTSC-Solver outperforms traditional models in accuracy on two popular datasets,while it improves the interpretability of mathematical reasoning.
文摘I have a best friend・His name is Li Xuan・We live in the same neighborhood and go to the same school.Li Xuan is a kind and clever boy.He always smiles and is ready to help others.One day,I had a problem with my math homework and I was very worried.
文摘Words are like magic.They can lift you up,or they can knock you down.They are the most powerful tool we have.When I was in Grade 7,I performed badly in a math test.
文摘1・absorb vt.吸收;使引人入胜.absorbed adj.全神贯注的.If you want to absorb all knowledge,you must be absorbed.2.abstract adj.抽象的v.抽象.abstracted adj.心不在焉的.Feeling abstracted,he couldn't tackle this abstract math problem.
文摘The extent to which schools in a country or region prioritize the professional development of mathematics teachers influences the quality of these teachers,thereby affecting students’mathematics learning and performance.Over the years,the PISA test has evolved into the largest and most influential international educational assessment program.This study,based on PISA 2022 questionnaire data,examines the relationship between the professional growth of mathematics teachers and students’mathematics performance by analyzing samples from sixteen countries/economies.The research focuses on schools’support for mathematics teachers’professional growth,investigating the correlation with students’mathematics literacy test scores through metrics such as the average proportion of teachers who participated in professional development training courses in the past three months and the average proportion of schools offering different types of in-house professional growth training.Based on the findings,recommendations are proposed,including placing greater emphasis on the professional development and growth of mathematics teachers,as well as anchoring this growth in students’learning and development.This study provides multinational insights and scientific evidence for educational management related to mathematics teachers’professional development,offering theoretical support for improving the quality of secondary mathematics education,fostering students’mathematical literacy,and promoting educational equity.
文摘Deforestation is the purpose of converting forest into land and reforestation compared to deforestation is very low.That’s why closely and accurately deforestation monitoring using Sentinel-1 and Sentinel-2 satellite images for better vision is required.This paper proposes an effective image fusion technique that combines S-1/2 data to improve the deforested areas.Based on review,Optical and SAR image fusion produces high-resolution images for better de-forestation monitoring.To enhance the S-1/2 images,preprocessing is needed as per requirements and then,collocation between the two different types of images to mitigate the image registration problem,and after that,apply an image fu-sion machine learning approach,PCA-Wavelet.As per analysis,PCA helps to maintain spatial resolution,and Wavelet helps to preserve spectral resolution,gives better-fused images compared to other techniques.As per results,2019 S-2 pre-22 processed collocated image enhances 42.2508 km deforested area,S-1 preprocessed collocated image enhances 23.7918 km^(2) deforested area,and after fusion of the 2019 S-1/2 images,it enhances 16.5335 km deforested area.Similarly,the 20232 S-2 preprocessed collocated image enhances 49.2216 km deforested area,S-1 preprocessed collocated image enhances 2223.8459 km deforested area after fusion of the 2023 S-1/2 images,enhancing 35.9185 km deforested area.These im-provements show that combining data sources gives a clearer and more reliable picture of forest loss over time.The overall paper objective is to apply effective techniques for image fusion of Brazil’s Amazon Forest and analyze the difference between collocated image pixels and fused image pixels for accurate analysis of deforested area.
