Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskde...Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskdelay and cost while ensuring the data security and reliable communicationof edge computing remains a challenge. To solve this problem, this paperestablishes a task scheduling model with joint blockchain and task cachingin the industrial internet and designs a novel blockchain-assisted cachingmechanism to enhance system security. In this paper, the task schedulingproblem, which couples the task scheduling decision, task caching decision,and blockchain reward, is formulated as the minimum weighted cost problemunder delay constraints. This is a mixed integer nonlinear problem, which isproved to be nonconvex and NP-hard. To solve the optimal solution, thispaper proposes a task scheduling strategy algorithm based on an improvedgenetic algorithm (IGA-TSPA) by improving the genetic algorithm initializationand mutation operations to reduce the size of the initial solutionspace and enhance the optimal solution convergence speed. In addition,an Improved Least Frequently Used algorithm is proposed to improve thecontent hit rate. Simulation results show that IGA-TSPA has a faster optimalsolution-solving ability and shorter running time compared with the existingedge computing scheduling algorithms. The established task scheduling modelnot only saves 62.19% of system overhead consumption in comparison withlocal computing but also has great significance in protecting data security,reducing task processing delay, and reducing system cost.展开更多
The paper takes 2076 undergraduate students majoring in foreign languages from 15 Chinese universities as the research subjects to investigate their demand for ideological and political education elements in foreign l...The paper takes 2076 undergraduate students majoring in foreign languages from 15 Chinese universities as the research subjects to investigate their demand for ideological and political education elements in foreign language courses.The results show that:(1)Students have high needs for ideological and political education elements in foreign language courses;(2)There are differences in students’needs for ideological and political education elements across different dimensions.Students have higher demand for dimensions such as personal qualities,cultural literacy,moral cultivation,and patriotism,while their demand for dimensions related to constitutional law and political identity is relatively low.Therefore,foreign language majors in Chinese universities should optimize the supply of ideological and political education elements in their courses according to students’needs,and improve the effectiveness of moral education in these courses.展开更多
Pollution by polycyclic aromatic hydrocarbons（PAHs） is widespread due to tmsuitable disposal of industrial waste. They are mostly defined as priority pollutants by environmental protection authorities worldwide. Phe...Pollution by polycyclic aromatic hydrocarbons（PAHs） is widespread due to tmsuitable disposal of industrial waste. They are mostly defined as priority pollutants by environmental protection authorities worldwide. Phenanthrene, a typical PAH, was selected as the target in this paper. The PAH-degrading mixed culture, named ZM, was collected from a petroleum contaminated river bed. This culture was injected into phenanthrene solutions at different concentrations to quantify the biodegradation process. Results show near-complete removal of phenanthrene in three days of biodegradation if the initial phenanthrene concentration is low. When the initial concentration is high, the removal rate is increased but 20%-40% of the phenanthrene remains at the end of the experiment. The biomass shows a peak on the third day due to the combined effects of microbial growth and decay. Another peak is evident for cases with a high initial concentration, possibly due to production of an intermediate metabolite. The pH generally decreased during biodegradation because of the production of organic acid. Two phenomenological models were designed to simulate the phenanthrene biodegradation and biomass growth. A relatively simple model that does not consider the intermediate metabolite and its inhibition of phenanthrene biodegradation cannot fit the observed data. A modified Monod model that considered an intermediate metabolite （organic acid） and its inhibiting reversal effect reasonably depicts the experimental results.展开更多
Quantized training has been proven to be a prominent method to achieve deep neural network training under limited computational resources.It uses low bit-width arithmetics with a proper scaling factor to achieve negli...Quantized training has been proven to be a prominent method to achieve deep neural network training under limited computational resources.It uses low bit-width arithmetics with a proper scaling factor to achieve negligible accuracy loss.Cambricon-Q is the ASIC design proposed to efficiently support quantized training,and achieves significant performance improvement.However,there are still two caveats in the design.First,Cambricon-Q with different hardware specifications may lead to different numerical errors,resulting in non-reproducible behaviors which may become a major concern in critical applications.Second,Cambricon-Q cannot leverage data sparsity,where considerable cycles could still be squeezed out.To address the caveats,the acceleration core of Cambricon-Q is redesigned to support fine-grained irregular data processing.The new design not only enables acceleration on sparse data,but also enables performing local dynamic quantization by contiguous value ranges(which is hardware independent),instead of contiguous addresses(which is dependent on hardware factors).Experimental results show that the accuracy loss of the method still keeps negligible,and the accelerator achieves 1.61×performance improvement over Cambricon-Q,with about 10%energy increase.展开更多
基金supported by theCommunication Soft Science Program of Ministry of Industry and Information Technology of China (No.2022-R-43)the Natural Science Basic Research Program of Shaanxi (No.2021JQ-719)Graduate Innovation Fund of Xi’an University of Posts and Telecommunications (No.CXJJZL2021014).
文摘Deploying task caching at edge servers has become an effectiveway to handle compute-intensive and latency-sensitive tasks on the industrialinternet. However, how to select the task scheduling location to reduce taskdelay and cost while ensuring the data security and reliable communicationof edge computing remains a challenge. To solve this problem, this paperestablishes a task scheduling model with joint blockchain and task cachingin the industrial internet and designs a novel blockchain-assisted cachingmechanism to enhance system security. In this paper, the task schedulingproblem, which couples the task scheduling decision, task caching decision,and blockchain reward, is formulated as the minimum weighted cost problemunder delay constraints. This is a mixed integer nonlinear problem, which isproved to be nonconvex and NP-hard. To solve the optimal solution, thispaper proposes a task scheduling strategy algorithm based on an improvedgenetic algorithm (IGA-TSPA) by improving the genetic algorithm initializationand mutation operations to reduce the size of the initial solutionspace and enhance the optimal solution convergence speed. In addition,an Improved Least Frequently Used algorithm is proposed to improve thecontent hit rate. Simulation results show that IGA-TSPA has a faster optimalsolution-solving ability and shorter running time compared with the existingedge computing scheduling algorithms. The established task scheduling modelnot only saves 62.19% of system overhead consumption in comparison withlocal computing but also has great significance in protecting data security,reducing task processing delay, and reducing system cost.
基金This paper represents the interim achievement of Shandong Provincial Education Science“14th Five-Year Plan”General Research Project“Research on the Practice and Enhancement Path of Ideological and Political Education in Foreign Language Professional Courses in Universities” (Project Number:2021ZC060).
文摘The paper takes 2076 undergraduate students majoring in foreign languages from 15 Chinese universities as the research subjects to investigate their demand for ideological and political education elements in foreign language courses.The results show that:(1)Students have high needs for ideological and political education elements in foreign language courses;(2)There are differences in students’needs for ideological and political education elements across different dimensions.Students have higher demand for dimensions such as personal qualities,cultural literacy,moral cultivation,and patriotism,while their demand for dimensions related to constitutional law and political identity is relatively low.Therefore,foreign language majors in Chinese universities should optimize the supply of ideological and political education elements in their courses according to students’needs,and improve the effectiveness of moral education in these courses.
基金The National Natural Science Foundation of China （No. 50178040） the Royal Society of UK and the Hi-Tech Research and Development Program（863） of China（No. 2003AA601080）
文摘Pollution by polycyclic aromatic hydrocarbons（PAHs） is widespread due to tmsuitable disposal of industrial waste. They are mostly defined as priority pollutants by environmental protection authorities worldwide. Phenanthrene, a typical PAH, was selected as the target in this paper. The PAH-degrading mixed culture, named ZM, was collected from a petroleum contaminated river bed. This culture was injected into phenanthrene solutions at different concentrations to quantify the biodegradation process. Results show near-complete removal of phenanthrene in three days of biodegradation if the initial phenanthrene concentration is low. When the initial concentration is high, the removal rate is increased but 20%-40% of the phenanthrene remains at the end of the experiment. The biomass shows a peak on the third day due to the combined effects of microbial growth and decay. Another peak is evident for cases with a high initial concentration, possibly due to production of an intermediate metabolite. The pH generally decreased during biodegradation because of the production of organic acid. Two phenomenological models were designed to simulate the phenanthrene biodegradation and biomass growth. A relatively simple model that does not consider the intermediate metabolite and its inhibition of phenanthrene biodegradation cannot fit the observed data. A modified Monod model that considered an intermediate metabolite （organic acid） and its inhibiting reversal effect reasonably depicts the experimental results.
基金the National Key Research and Devecopment Program of China(No.2022YFB4501601)the National Natural Science Foundation of China(No.62102398,U20A20227,62222214,62002338,U22A2028,U19B2019)+1 种基金the Chinese Academy of Sciences Project for Young Scientists in Basic Research(YSBR-029)Youth Innovation Promotion Association Chinese Academy of Sciences。
文摘Quantized training has been proven to be a prominent method to achieve deep neural network training under limited computational resources.It uses low bit-width arithmetics with a proper scaling factor to achieve negligible accuracy loss.Cambricon-Q is the ASIC design proposed to efficiently support quantized training,and achieves significant performance improvement.However,there are still two caveats in the design.First,Cambricon-Q with different hardware specifications may lead to different numerical errors,resulting in non-reproducible behaviors which may become a major concern in critical applications.Second,Cambricon-Q cannot leverage data sparsity,where considerable cycles could still be squeezed out.To address the caveats,the acceleration core of Cambricon-Q is redesigned to support fine-grained irregular data processing.The new design not only enables acceleration on sparse data,but also enables performing local dynamic quantization by contiguous value ranges(which is hardware independent),instead of contiguous addresses(which is dependent on hardware factors).Experimental results show that the accuracy loss of the method still keeps negligible,and the accelerator achieves 1.61×performance improvement over Cambricon-Q,with about 10%energy increase.
