PARE:Privacy-Preserving Data Reliability Evaluation for Spatial Crowdsourcing in Internet of Things

The proliferation of intelligent,connected Internet of Things(IoT)devices facilitates data collection.However,task workers may be reluctant to participate in data collection due to privacy concerns,and task requesters may be concerned about the validity of the collected data.Hence,it is vital to evaluate the quality of the data collected by the task workers while protecting privacy in spatial crowdsourcing(SC)data collection tasks with IoT.To this end,this paper proposes a privacy-preserving data reliability evaluation for SC in IoT,named PARE.First,we design a data uploading format using blockchain and Paillier homomorphic cryptosystem,providing unchangeable and traceable data while overcoming privacy concerns.Secondly,based on the uploaded data,we propose a method to determine the approximate correct value region without knowing the exact value.Finally,we offer a data filtering mechanism based on the Paillier cryptosystem using this value region.The evaluation and analysis results show that PARE outperforms the existing solution in terms of performance and privacy protection.

A decentralized data evaluation framework in federated learning

Federated Learning(FL)is a type of distributed deep learning framework in which multiple devices train a local model using local data,and the gradients of the local model are then sent to a central server that aggregates them to create a global model.This type of framework is ideal where data privacy is of utmost importance because the data never leave the local device.However,a major concern in FL is ensuring the data quality of local training data.Since there is no control over the local training data,ensuring that the local model is trained on clean data becomes challenging.A model trained on poor-quality data can have a significant impact on its accuracy.In this paper,we propose a decentralized approach using blockchain to ensure local model data quality.We use miners to validate each local model by checking its accuracy against a secret testing dataset.This is done using a smart contract that the miners invoke during the mining process.The local model is aggregated with the global model only if it passes a preset accuracy threshold.We test our proposed method on two datasets:the Brain Tumor Classification dataset from Kaggle,comprised of 7000 MRI images divided into two classes(Tumor/No Tumor),and the Medical MNIST dataset,which includes 58,954 images classified into six different classes:AbdomenCT,BreastMRI,ChestCT,Chest X-ray,Hand X-ray,and HeadCT.Our results show that our method outperforms the original FL approach in all experiments.

Benchmark experiment on slab^(238)U with D-T neutrons for validation of evaluated nuclear data

A benchmark experiment on^(238)U slab samples was conducted using a deuterium-tritium neutron source at the China Institute of Atomic Energy.The leakage neutron spectra within energy levels of 0.8-16 MeV at 60°and 120°were measured using the time-of-flight method.The samples were prepared as rectangular slabs with a 30 cm square base and thicknesses of 3,6,and 9 cm.The leakage neutron spectra were also calculated using the MCNP-4C program based on the latest evaluated files of^(238)U evaluated neutron data from CENDL-3.2,ENDF/B-Ⅷ.0,JENDL-5.0,and JEFF-3.3.Based on the comparison,the deficiencies and improvements in^(238)U evaluated nuclear data were analyzed.The results showed the following.(1)The calculated results for CENDL-3.2 significantly overestimated the measurements in the energy interval of elastic scattering at 60°and 120°.(2)The calculated results of CENDL-3.2 overestimated the measurements in the energy interval of inelastic scattering at 120°.(3)The calculated results for CENDL-3.2 significantly overestimated the measurements in the 3-8.5 MeV energy interval at 60°and 120°.(4)The calculated results with JENDL-5.0 were generally consistent with the measurement results.

Study of ADS-B Data Evaluation

In western China, the terrain and meteorological conditions are so complex that it is not suitable to construct new radar stations. Automatic dependent surveillance-broadcast （ADS-B） is a totally new surveillance method, so before practically applied and operated in China, abundant tests and evaluations are necessary to validate the performance of ADS-B and guarantee the operational security. During the flight tests, we collect the data of radar, ADS-B and high accuracy position and compare the performance of ADS-B with radar based on high accuracy position. To solve the asynchronous problem among radar data, ADS-B data and real-time kinematic （RTK） data caused by different update rates, this artic.le proposes the technique of synchronizing multi-surveil- lance data by extrapolating from the data of low update rate to high update rate according to velocity and heading. Meanwhile, because radar data, ADS-B data and RTK data are expressed in different coordinates and cannot be compared each other, this article provides a method to unifying the coordinates of multi-surveillance data. By the analysis and evaluation, we can conclude that the performance of ADS-B is better than radar.

Quantitative credibility evaluation of Global Energy Interconnection data

The development of Global Energy Interconnection(GEI)is essential for supporting a wide range of basic data resources.The Global Energy Interconnection Development and Cooperation Organization has established a comprehensive data center covering six major systems.However,methods for accurately describing and scientifically evaluating the credibility of the massive amount of GEI data remain underdeveloped.To address this lack of such methods,a GEI data credibility quantitative evaluation model is proposed here.An evaluation indicator system is established to evaluate data credibility from multiple perspectives and ensure the comprehensiveness and impartiality of evaluation results.The Cloud Model abandons the hard division of comments to ensure objectivity and accuracy in evaluation results.To evaluate the suitability of the proposed method,a case analysis is conducted,wherein the proposed method demonstrates sufficient validity and feasibility.

Analysis of Evaluation Data Collected on Likert Type Items: Humanities-Courses

To improve high quality and/or retain achieved high quality of an academic program, time to time evaluation for quality of each covered course is often an integrated aspect considered in reputed institutions, however, there has been little effort regarding humanities courses. This research article deals with analysis of evaluation data collected regarding humanities course from a College of Commerce & Economics, Mumbai, Maharashtra, India, on Likert type items. Appropriateness of one parametric measure and three non-parametric measures are discussed and used in this regard which could provide useful clues for educational policy planners. Keeping in view of the analytical results using these four measures, regardless of the threshold regarding satisfaction among students, overall performance of almost every subject has been un-satisfactory. There is a need to make a focused approach to take every course at the level of high performance. The inconsistency noticed under every threshold further revealed that under such poorly performing subjects globally, one needs to analyze merely at the global level item. Once the global level analysis reveals high performance of a course, then only item specific analysis may need to be focused to find out the items requiring further improvements.

The City Intelligence Quotient （City IQ） Evaluation System＂ Conception and Evaluation

After a systematic review of 38 current intelligent city evaluation systems （ICESs） from around the world, this research analyzes the secondary and tertiary indicators of these 38 ICESs from the perspec- tives of scale structuring, approaches and indicator selection, and determines their common base. From this base, the fundamentals of the City Intelligence Quotient （City IOD Evaluation System are developed and five dimensions are selected after a clustering analysis. The basic version, City IQ Evaluation System 1.0, involves 275 experts from 14 high-end research institutions, which include the Chinese Academy of Engineering, the National Academy of Science and Engineering （Germany）, the Royal Swedish Academy of Engineering Sciences, the Planning Management Center of the Ministry of Housing and Urban-Rural Development of China, and the Development Research Center of the State Council of China. City IQ Evaluation System 2.0 is further developed, with improvements in its universality, openness, and dy- namic adjustment capability. After employing deviation evaluation methods in the IQ assessment, City IQ Evaluation System 3.0 was conceived. The research team has conducted a repeated assessment of 41 intelligent cities around the world using City IQ Evaluation System 3.0. The results have proved that the City IQ Evaluation System, developed on the basis of intelligent life, features more rational indicators selected from data sources that can offer better universality, openness, and dynamics, and is more sen- sitive and precise.

Use of a Land Surface Model to Evaluate the Observed Soil Moisture of Grassland at the Tongyu Reference Site

A land surface model driven by the continuous three-year observed meteorological data with a time interval of 30 minutes at the Tongyu station, a reference site of the Coordinated Enhanced Observing Period （CEOP）, was used to evaluate the observation bias of soil moisture （SM） data and analyze the variation of SM at different time scales. The saline-alkaline soil of the grassland at the Tongyu site makes the measured SM too high, especially in boreal summer of 2003-05. The simulated annual mean SM has the lowest value in 2004 and its three-year variation corresponds to the change of precipitation, whereas the observation shows the increasing trend from 2003 to 2005. Compared to the variation range between -60% and 40% for the anomaly percentage of the simulated daily mean SM during May-October of 2004, the measured data show the higher values more than 40%. The magnitude of the variation trend of the observed daily mean SM in 2003 and 2005 is generally consistent with the simulation. The largest deficiency for the soil moisture observation of the grassland is the overestimated value in the drought year with less precipitation. The simulated monthly mean SM has the lowest value in March due to the large contribution of evaporation relative to precipitation and this phenomenon can not be reproduced in the observation.

Evaluation of FY-3B Reprocessed OLR Data in the Asian–Australian Monsoon Region during 2011–2019:Comparison with NOAA OLR

The present study evaluates spatial and temporal characteristics of the Fengyun-3 B(FY-3 B)’s outgoing longwave radiation(OLR)data based on NOAA OLR data and the GPCP(Global Precipitation Climatology Project)precipitation data over the Asian-Australian region during 2011-2019.In terms of climatological distribution patterns and interannual standard deviation,FY-3 BOLR are quite consistent with NOAA OLR,with annual and seasonal pattern correlation coefficients all exceeding 0.93.There are some discrepancies in the OLR magnitude between FY-3 B and NOAA,especially for the OLR climatology;the climatological OLR from FY-3 B are systematically larger than those from NOAA over the whole study region.In addition,examination of the temporal correlation coefficients between OLR and precipitation over the Asian-Australian monsoon(AAM)region reveals that both of the OLR datasets have captured the widespread negative correlation with precipitation,and FY-3 BOLR exhibits a stronger relationship to precipitation over land.Moreover,FY-3 BOLR exhibits better responses to the precipitation anomalies over India during the extreme El Nino and La Nina events.These results suggest that the FY-3 B OLR dataset is of high quality and worthy of further global application.

Discrepancies in boreal summer monsoon rainfall between GPCP and CMAP products during 1979–2014

This study compares the boreal summer monsoon （BSM） precipitation between the GPCP and CMAP products during 1979-2014. The authors apply temporal, spatial correlation and error evaluation methods to evaluate their discrepancies in terms of BSM distribution and summer rainfall interannual variability over the five BSM regions. The results suggest that the climatology of the seasonal evolution of BSM rainfall is reflected well in both datasets, and the summer rainfall anomalies of the two products are highly correlated. However, major diversity is found in the rainfall pattern and the magnitude in climatology over the oceanic monsoon areas, especially the western North Pacific monsoon region, as well as in the interannual variability of summer rainfall anomalies over the North Africa and India monsoon regions. Although inconsistency between the two datasets is evident before the 1990s, the use of their arithmetic mean is demonstrated to be an efficient way to reduce the uncertainty between them.

Evaluation of the Madden–Julian Oscillation in Fengyun-3B Polar-Orbiting Satellite Reprocessed OLR Data

The present study compares the spatial and temporal characteristics of the Madden-Julian Oscillation(MJO)in Fengyun-3B(FY-3B)polar-orbiting satellite reprocessed outgoing longwave radiation(OLR)data and NOAA OLR data during 2011-2020.The spatial distributions of climatological mean and intraseasonal standard deviation of FY-3B OLR during boreal winter(November-April)and boreal summer(May-October)are highly consistent with those of NOAA OLR.The FY-3B and NOAA OLRs display highly consistent features in the wavenumber-frequency spectra,the occurrence frequency of MJO active days,the eastward propagation of MJO along the equator,and the interannual variability of MJO according to diagnoses using the all-season multivariate EOF analysis.These results indicate that the FY-3B OLR produced by the polar-orbiting satellites is of high quality and worthy of global application.

The AME2012 atomic mass evaluation(Ⅰ).Evaluation of input data,adjustment procedures

This paper is the second part of the new evaluation of atomic masses, AME2012. From the results of a leastsquares calculation, described in Part I, for all accepted experimental data, we derive here tables and graphs to replace those of AME2003. The first table lists atomic masses. It is followed by a table of the influences of data on primary nuclides, a table of separation energies and reaction energies, and finally, a series of graphs of separation and decay energies. The last section in this paper lists all references to the input data used in Part I of this AME2012 and also to the data included in the NUBASE2012 evaluation （first paper in this issue）.

Evaluation of the applicability of climate forecast system reanalysis weather data for hydrologic simulation： A case study in the Bahe River Basin of the Qinling Mountains, China

In recent years, global reanalysis weather data has been widely used in hydrological modeling around the world, but the results of simulations vary greatly. To consider the applicability of Climate Forecast System Reanalysis（CFSR） data in the hydrologic simulation of watersheds, the Bahe River Basin was used as a case study. Two types of weather data（conventional weather data and CFSR weather data） were considered to establish a Soil and Water Assessment Tool（SWAT） model, which was used to simulate runoff from 2001 to 2012 in the basin at annual and monthly scales. The effect of both datasets on the simulation was assessed using regression analysis, Nash-Sutcliffe Efficiency（NSE）, and Percent Bias（PBIAS）. A CFSR weather data correction method was proposed. The main results were as follows.（1） The CFSR climate data was applicable for hydrologic simulation in the Bahe River Basin（R^2 of the simulated results above 0.50, NSE above 0.33, and ｜PBIAS｜ below 14.8. Although the quality of the CFSR weather data is not perfect, it achieved a satisfactory hydrological simulation after rainfall data correction.（2） The simulated streamflow using the CFSR data was higher than the observed streamflow, which was likely because the estimation of daily rainfall data by CFSR weather data resulted in more rainy days and stronger rainfall intensity than was actually observed. Therefore, the data simulated a higher base flow and flood peak discharge in terms of the water balance, except for some individual years.（3） The relation between the CFSR rainfall data（x） and the observed rainfall data（y） could berepresented by a power exponent equation： y=1.4789x0.8875（R2=0.98,P〈0.001）. There was a slight variation between the fitted equations for each station. The equation provides a theoretical basis for the correction of CFSR rainfall data.

Using MAN and Coastal AERONET Measurements to Assess the Suitability of MODIS C6.1 Aerosol Optical Depth for Monitoring Changes from Increased Arctic Shipping

Collocated data of the moderate resolution imaging spectroradiometer (MO-DIS) Collection 6.1 aerosol optical depths (AOD) at 3 km × 3 km north of 59.9°N over ocean were assessed at 550 nm by aerosol robotic network (AERONET) data from coastal sites and marine aerosol network (MAN) data from vessels during June to October 2006 to 2018. Typically, MODIS AOD was higher at low and lower at high values than the AERONET AOD. Discrepancies were largest for sites where the Earth’s surface around the site is very heterogeneous (Canadian Archipelago, coast of Greenland). Due to the higher likelihood for sea-ice, MAN and MODIS AOD differed stronger west of Greenland and over the Beaufort Sea than at location in the Greenland and Norwegian Seas and Atlantic. MODIS AOD well captured the inter-seasonal variability found in the AERONET AOD data (R = 0.933). At all sites, MO-DIS and AERONET AOD agreement improved as time progressed in the shipping season, hinting at errors in sea-ice vs. open water classification. Overall 75.3% of the MODIS AOD data fell within the limits of the error envelops of the AERONET/MAN AOD data with MAN ranging between 87.5% and 100%. Changes in both MODIS and AERONET mean AOD between two periods of same length (2006-2011, 2013-2018) were explainable by changes in emissions for all sites.

An Evaluation of Chinese Human-Computer Dialogue Technology

The human-computer dialogue has recently attracted extensive attention from both academia and industry as an important branch in the field of artificial intelligence(AI).However,there are few studies on the evaluation of large-scale Chinese human-computer dialogue systems.In this paper,we introduce the Second Evaluation of Chinese Human-Computer Dialogue Technology,which focuses on the identification of a user’s intents and intelligent processing of intent words.The Evaluation consists of user intent classification(Task 1)and online testing of task-oriented dialogues(Task 2),the data sets of which are provided by iFLYTEK Corporation.The evaluation tasks and data sets are introduced in detail,and meanwhile,the evaluation results and the existing problems in the evaluation are discussed.

An Evaluation of Chinese Human-Computer Dialogue Technology

There is a growing interest in developing human-computer dialogue systems which is an important branch in the field of artificial intelligence(AI).However,the evaluation of large-scale Chinese human-computer dialogues is still a challenging task.To attract more attention to dialogue evaluation work,we held the fourth Evaluation of Chinese Human-Computer Dialogue Technology(ECDT).It consists of few-shot learning in spoken language understanding(SLU)(Task 1)and knowledge-driven multi-turn dialogue competition(Task 2),the data sets of which are provided by Harbin Institute of Technology and Tsinghua University.In this paper,we will introduce the evaluation tasks and data sets in detail.Meanwhile,we will also analyze the evaluation results and the existing problems in the evaluation.

Cross-sectional rainfall observation on the central-western Tibetan Plateau in the warm season:System design and preliminary results

The central and western Tibetan Plateau(CWTP)is characterized by harsh environment and strong interactions among the spheres of earth as well as significant changes in climate and water cycles over the past four decades.The lack of precipitation observations is a bottleneck for the study of land surface processes in this region.Over the past six years,we have designed and established two observation transects across the south-north and the west-east in this region to obtain hourly rainfall data during the warm season(May-September).The south-north transect extends from Yadong Valley on the southern slope of the Himalayas to Shuanghu County in the hinterland of the plateau,with a total of 31stations;the west-east transect extends from Shiquanhe in the west to Naqu in the central TP,with a total of 22 stations.The observation dataset has been applied to clarify the spatiotemporal characteristics of precipitation in the CWTP,to evaluate the quality of typical gridded precipitation products,to support the development of regional climate models,and to reveal the processes of summertime lake-air interactions.The observation dataset has been released in the National Tibetan Plateau Data Center.