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| 1 | ApplianceBricks: A Scalable Network Appliance Architecture for Network Functions Virtualization显示文摘Network Functions Virtualization(NFV) is an attempt to help operators more effectively manage their networks by implementing traditional network functions embedded in specialized hardware platforms in term of virtualized software instances. But, existing novel network appliances designed for NFV infrastructure are always architected on a general-purpose x86 server, which makes the performance of network functions limited by the hosted single server. To address this challenge, we propose ApplianceB ricks, a novel NFV-enable network appliance architecture that is used to explore the way of consolidating multiple physical network functions into a clustered network appliance, which is able to improve the processing capability of NFV-enabled network appliances. | MA Shicong WANG Baosheng ZHANG Xiaozhe GAO Xianming | 2016 | China Communications2016，13，S1： | 2 |
| 2 | Water-filling algorithm based approach for management of responsive residential loads显示文摘Integration of large number of electric vehicles(EVs)with distribution networks is devastating for conventional power system devices such as transformers and power lines etc.This paper proposes a methodology for management of responsive household appliances management and EVs with water-filling algorithm.With the proposed scheme,the load profile of a transformer is retained below its rated capacity while minimally affecting the associated consumers.When the instantaneous demand at transformer increases beyond its capacity,the proposed methodology dynamically allocates demand curtailment limit(DCL)to each home served by transformer.The DCL allocation takes convenience factors,load profile and information of flexible appliances into account to assure the comfort of all the consumers.The proposed scheme is verified by modeling and simulating five houses and a distribution transformer.The smart appliances such as an HVAC,a water heater,a cloth dryer and an EV are also modeled for the study.Results show that the proposed scheme performs to reduce overloading effects of the transformer efficiently and assures comfort of the consumers at the same time. | Zunaib Maqsood HAIDER Khawaja Khalid MEHMOOD Muhammad Kashif RAFIQUE Saad Ullah KHAN Soon-Jeong LEE Chul-Hwan KIM | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，1： | 1 |
| 3 | Fiscal Subsidy Policy on Home Appliances: Its Effects on Domestic Consumption and Exports in China显示文摘This paper evaluates the effects of the Home Appliances Going to the Countryside (HAGC) policy, afiscal subsidy program implemented in China to boost private consumption of home appliances in rural areas from 2007 to 2012. Using the policy as anatural experiment and employing the difference-in-difference estimator, we find that the policy did not increase domestic sales of relevant goods as expected;instead, it actually reduced domestic sales and significantly promoted exports. These surprising results are robust across regressions of alternative datasets, more controls, and different regions. We further provide detailed information of undisclosed audit data for acounty in Zhejiang province to shed light on the underlying mechanism of such unexpected results, suggesting loopholes in the HAGC and changes in export tax rebate rates. | Ting Ji Ningyuan Jia Faqin Lin Hang Wu | 2019 | China & World Economy2019，27，4： | 0 |
| 4 | Energy Efficiency of Washing Machines显示文摘This paper makes a technical analysis of the methods to increase the energy efficiency of washing machines for student education.Starting from the definition given by the Energy Efficiency Index,the present analysis proposes two methods for increasing the energy efficiency of the washing machines by modifying the standard annual energy consumption(SAEc)and by modifying the annual energy consumption(AEc).These two methods are made per kilogram of clothes for washing machines from the same brand in different energy classes and for washing machines of two different brands.The models analyzed were chosen according to their energy rating A++and A+++.The results of this analysis propose the energy savings as an energy indicator to inform buyers in choosing a brand and energy class of the washing machine. | Nicolae Badea Andreia Podasca | 2018 | Journal of Energy and Power Engineering2018，12，9： | 0 |
| 5 | Influence of the 60 Hz Magnetic Field on the Airborne Microbial Distribution of Indoor Environments显示文摘The aim of this work was to analyze the effect of the magnetic field generated by the household appliances on the airborne microbial surrounding these equipment located on indoor environments with particular interest in the environmental fungi.A simultaneous environmental study was carried out in locals of three different geographical places of Havana,Cuba,which have televisions,computers and an electric generator.The air samples were made by a sedimentation method using Malt Extract Agar.The concentration of total aerobic mesophilic as well as fungi and yeasts were determined in rainy and little rainy seasons by applying as factors:exposure time of dishes(5 to 60 min)and distance to the wall(0 and 1 m)at a height of 1 m above the floor.The predominant fungal genera were Cladosporium,Penicillium and Aspergillus.In the dishes that were placed at 0 and 0.5 m from the emitting sources were observed that some bacteria colonies formed inhibition halos,a great diversity of filamentous fungi and an increase in the mycelium pigmentation as well as the pigments excretion.In the rainy season,the highest amounts of fungi were obtained in all samples.In the little rain season the count of the Gram-negative bacilli increased three times the Gram-positive cocci. | Matilde Anaya Sofia F.Borrego Miguel Castro Oderlaise Valdés Alian Molina | 2020 | Journal of Atmospheric Science Research2020，3，3： | 0 |
| 6 | A comprehensive analysis of smart home energy management system optimization techniques显示文摘Development of smart grid technology provides an opportunity to various consumers in context for scheduling their energy utilization pattern by themselves.The main aim of this whole exercise is to minimize energy utilization and reduce the peak to average ratio (PAR) of power.The two way flow of information between electric utilities and consumers in smart grid opened new areas of applications.The main component is this management system is energy management controller (EMC),which collects demand response (DR) i.e.real time energy price from various appliances through the home gateway (HG).An optimum energy scheduling pattern is achieved by EMC through the utilization of DR information.This optimum energy schedule is provided to various appliances via HG.The rooftop photovoltaic system used as local generation micro grid in the home and can be integrated to the national grid.Under such energy management scheme,whenever solar generation is more than the home appliances energy demand,extra power is supplied back to the grid.Consequently,different appliances in consumer premises run in the most efficient way in terms of money.Therefore this work provides the comprehensive review of different smart home appliances optimization techniques,which are based on mathematical and heuristic one. | Tesfahun Molla Baseem Khan Pawan Singh | 2018 | Journal of Autonomous Intelligence2018，1，1： | 0 |
| 7 | Forecasting of Appliances House in a Low-Energy Depend on Grey Wolf Optimizer显示文摘This paper gives and analyses data-driven prediction models for the energy usage of appliances.Data utilized include readings of temperature and humidity sensors from a wireless network.The building envelope is meant to minimize energy demand or the energy required to power the house independent of the appliance and mechanical system efficiency.Approximating a mapping function between the input variables and the continuous output variable is the work of regression.The paper discusses the forecasting framework FOPF(Feature Optimization Prediction Framework),which includes feature selection optimization:by removing non-predictive parameters to choose the best-selected feature hybrid optimization technique has been approached.k-nearest neighbors(KNN)Ensemble Prediction Models for the data of the energy use of appliances have been tested against some bases machine learning algorithms.The comparison study showed the powerful,best accuracy and lowest error of KNN with RMSE=0.0078.Finally,the suggested ensemble model’s performance is assessed using a one-way analysis of variance(ANOVA)test and the Wilcoxon Signed Rank Test.(Two-tailed P-value:0.0001). | Hatim G.Zaini | 2022 | Computers, Materials & Continua2022，，5： | 0 |
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