A Multi-Feature Weighting Based K-Means Algorithm for MOOC Learner Classification

Massive open online courses(MOOC)have recently gained worldwide attention in the field of education.The manner of MOOC provides a new option for learning various kinds of knowledge.A mass of data miming algorithms have been proposed to analyze the learner’s characteristics and classify the learners into different groups.However,most current algorithms mainly focus on the final grade of the learners,which may result in an improper classification.To overcome the shortages of the existing algorithms,a novel multi-feature weighting based K-means(MFWK-means)algorithm is proposed in this paper.Correlations between the widely used feature grade and other features are first investigated,and then the learners are classified based on their grades and weighted features with the proposed MFWK-means algorithm.Experimental results with the Canvas Network Person-Course(CNPC)dataset demonstrate the effectiveness of our method.Moreover,a comparison between the new MFWK-means and the traditional K-means clustering algorithm is implemented to show the superiority of the proposed method.

Robust decentralized adaptive output feedback fuzzy controller design and application to AHS

A novel decentralized indirect adaptive output feedback fuzzy controller is developed for a class of large-scale uncertain nonlinear systems using error filtering.By the properly filtering of the observation error dynamics,the strictly positive-real condition is guaranteed to hold such that the proposed output feedback and adaptation mechanisms are practicable in practice owing to the fact that its implementation does not require the observation error vector itself any more,which corrects the impracticable schemes in the previous literature involved.The presented control algorithm can ensure that all the signals of the closed-loop large-scale system keep uniformly ultimately bounded and that the tracking error converges to zero asymptotically.The decentralized output feedback fuzzy controller can be applied to address the longitudinal control problem of a string of vehicles within an automated highway system（AHS） and the effectiveness of the design procedure is supported by simulation results.

MOOC Learner’s Final Grade Prediction Based on an Improved Random Forests Method

Massive Open Online Course(MOOC)has become a popular way of online learning used across the world by millions of people.Meanwhile,a vast amount of information has been collected from the MOOC learners and institutions.Based on the educational data,a lot of researches have been investigated for the prediction of the MOOC learner’s final grade.However,there are still two problems in this research field.The first problem is how to select the most proper features to improve the prediction accuracy,and the second problem is how to use or modify the data mining algorithms for a better analysis of the MOOC data.In order to solve these two problems,an improved random forests method is proposed in this paper.First,a hybrid indicator is defined to measure the importance of the features,and a rule is further established for the feature selection;then,a Clustering-Synthetic Minority Over-sampling Technique(SMOTE)is embedded into the traditional random forests algorithm to solve the class imbalance problem.In experiment part,we verify the performance of the proposed method by using the Canvas Network Person-Course(CNPC)dataset.Furthermore,four well-known prediction methods have been applied for comparison,where the superiority of our method has been proved.

Impact of Demographic Transition on Household Energy Consumption: A Case from China

Understanding how aging population and low fertility affect household energy consumption is important for optimizing household energy consumption and reaching effective policies.This paper studies the impacts of demographic transition on household energy consumption based on panel data of 30 provinces in China from 2005 to 2016.Child-age dependency rate(CDR)and old-age dependency rate(ODR)are selected to track the shifts in age structure.They are introduced into a STIRPAT model to measure their impacts on household energy consumption.Besides,8 representative regions are additionally chosen and investigated to find some regional characteristics.The results show that current demographic transition to aging population expands household energy consumption.The aging population and low fertility cause additional challenges for energy saving and emission reduction.Household energy consumption in less developed areas is more likely to be affected by CDR and ODR.Regions with large population are also more easily influenced by demographic transitions especially CDR.This study emphases the effects of demographic elements on household energy consumption.It indicates that continuous optimization of household energy consumption structures should be based on population dynamics.

Prized edible Asian mushrooms: ecology, conservation and sustainability

Mushrooms can be found in forests worldwide and have long been exploited as resources in developed economies because of their important agro-industrial,medicinal and commercial uses.For less developed countries,such as those within the Greater Mekong Subregion,wild harvesting and mushroom cultivation provides a much-needed alternative source of income for rural households.However,this has led to over-harvesting and ultimately environmental degradation in certain areas,thus management guidelines allowing for a more sustained approach to the use of wild mushrooms is required.This article addresses a selection of the most popular and highly sought after edible mushrooms from Greater Mekong Subregion:Astraeus hygrometricus,Boletus edulis,Morchella conica,Ophiocordyceps sinensis,Phlebopus portentosus,Pleurotus giganteus,Termitomyces eurhizus,Thelephora ganbajun,Tricholoma matsuake,and Tuber indicum in terms of value,ecology and conservation.The greatest threat to these and many other mushroom species is that of habitat loss and over-harvesting of wild stocks,thus,by creating awareness of these issues we wish to enable a more sustainable use of these natural products.Thus our paper provides baseline data for these fungi so that future monitoring can establish the effects of continued harvesting on mushroom populations and the related host species.

The families Distoseptisporaceae fam.nov.,Kirschsteiniotheliaceae,Sporormiaceae and Torulaceae,with new species from freshwater in Yunnan Province,China

During a north–south latitudinal survey of aquatic fungi on submerged wood and herbaceous material in streams in the Asian region,we collected several hyphomycetous taxa.This paper is part of a series where we provide illustrated accounts of these taxa and place them in a natural classification in the fungi.DNA sequence based phylogenies in recent literature have shown that Dendryphion,Sporidesmium and Torula-like species are polyphyletic in the phylum Ascomycota and their taxonomyhas been problematic due to a lack of understanding of the importance of morphological characters used to delimit taxa,as well as the lack of ex-type or reference strains.Based on multi-locus phylogenies together with morphology,we propose the novel family Distoseptisporaceae(Sordariomycetes)and three novel genera Neotorula(Pleosporales,Dothideomycetes),Distoseptispora(Sordariomycetes)and Pseudosporidesmium(Sordariomycetes).In addition,Dendryphion aquaticum,D.submersum,Distoseptispora fluminicola,D.aquatica,Kirschsteiniothelia submersa,Neotorula aquatica,Sporidesmium aquaticum,S.submersum and S.fluminicola are introduced as new species.Pseudosporidesmium knawiae comb.nov.is proposed to accommodate Sporidesmium knawiae in Sordariomycetes.The polyphyletic nature of Dendryphion,Sporidesmium and Torula-like species are partially resolved,but further sampling with fresh collections and molecular data of species are needed to obtain a natural classification.

Literature review on renewable energy development and China’s roadmap

The low carbon energy transition has attracted worldwide attention to mitigate climate change.Renewable energy(RE)is the key to this transition,with significant developments to date,especially in China.This study systematically reviews the literature on RE development to identify a general context from many studies.The goal is to clarify key questions related to RE development from the current academic community.We first identify the forces driving RE development.Thereafter,we analyze methods for modeling RE developments considering the systematic and multiple complexity characteristics of RE.The study concludes with insights into the target selection and RE development roadmap in China.

Climate change effects fruiting of the prize matsutake mushroom in China

Climate change affects various facets of life but there is little data on its effects on wild mushroom fruiting.Yunnan Province in China is a rich source of wild mushrooms and has experienced a temperature rise over recent decades.This has resulted in warmer temperatures but the impacts of these changes on mushroom production lack documentation.We collected data on the fruiting of the highly prized matsutake mushroom(Tricholoma matsutake)in West Yunnan,China over an 11 year period from 2000 to 2010.Fruiting phenology and productivity were compared against the driving meteorological variables using Projection to Latent Structure regression.The mushrooms appeared later in the season during the observation period,which is most likely explained by rising temperatures and reduced rain during May and June.High temperature and abundant rain in August resulted in good productivity.The climate response of matsutake production results from a sequence of processes that are possibly linked with regulatory signals and resource availability.To advance the knowledge of this complex system,a holistic research approach integrating biology,ecology,genetics,physiology,and phytochemistry is needed.Our results contribute to a general model of fungal ecology,which can be used to predict the responses of fungi to global climate change.

Using agrophotovoltaics to reduce carbon emissions and global rural poverty

Poverty-alleviation programs using solar energy(PAPSE)are poised to unlock unprecedented capital investments with significant potential to reconcile the energy–poverty–climate nexus.1 These programs are economically feasible because the costs of generating renewable energy have declined precipitously over the past decade;between 2010 and 2019,solar photovoltaiccosts decreased by 82%.Furthermore,the number of annual equivalent-use hours of sunlight in most countries exceeds 1200,meaning that PAPSE approaches are feasible in many places and can be undertaken independently from the power grid.