Earthquake loss estimation by using Gross Domestic Product and population data

In the traditional method of earthquake loss estimation, all the social wealthes are classified according to their structural type and occupational use. Inventory data is collected and the total loss is estimated from each facility class separately. For many regions of the world, however, the vast amount of data required by this method is difficult or impossible to obtain. The traditional method is also unable to estimate quickly the loss from an unexpected disaster earthquake. It is difficult to give the necessary risk information to help the government to rescue and relief the earthquake disaster. This paper proposes a simple estimation method of earthquake loss based on macroscopic economical index of Gross Domestic Product (GDP) and population distribution data. A preliminary nonlinear relation among hazard loss, seismic intensity and social wealth was developed by means of some earthquake disaster records during 1980～1995. This method was applied to analyze several assumed earthquakes. The preliminary analysis results show that the new method is effective and reasonable for quick assessment of earthquake loss.

Feedback control and quantum error correction assisted quantum multi-parameter estimation

Quantum metrology provides a fundamental limit on the precision of multi-parameter estimation,called the Heisenberg limit,which has been achieved in noiseless quantum systems.However,for systems subject to noises,it is hard to achieve this limit since noises are inclined to destroy quantum coherence and entanglement.In this paper,a combined control scheme with feedback and quantum error correction(QEC)is proposed to achieve the Heisenberg limit in the presence of spontaneous emission,where the feedback control is used to protect a stabilizer code space containing an optimal probe state and an additional control is applied to eliminate the measurement incompatibility among three parameters.Although an ancilla system is necessary for the preparation of the optimal probe state,our scheme does not require the ancilla system to be noiseless.In addition,the control scheme in this paper has a low-dimensional code space.For the three components of a magnetic field,it can achieve the highest estimation precision with only a 2-dimensional code space,while at least a4-dimensional code space is required in the common optimal error correction protocols.

Explosion limits estimation and process optimization of direct propylene epoxidation with H2 and O2

Direct propylene epoxidation with H2 and O2,an attractive process to produce propylene oxide(PO),has a potential explosion danger due to the coexistence of flammable gases(i.e.,C3 H6 and H2)and oxidizer(i.e.,O2).The unknown explosion limits of the multi-component feed gas mixture make it difficult to optimize the reaction process under safe operation conditions.In this work,a distribution method is proposed and verified to be effective by comparing estimated and experimental explosion limits of more than 200 kinds of flammable gas mixture.Then,it is employed to estimate the explosion limits of the feed gas mixture,some results of which are also validated by the classic Le Chatelier’s Rule and flammable resistance method.Based on the estimated explosion limits,process optimization is carried out using commercially high and inherently safe reactant concentrations to enhance reaction performance.The promising results are directly obtained through the interface called gOPT in gPROMS only by using a simple,easy-constructed and mature packed-bed reactor,such as the PO yield of 13.3%,PO selectivity of 85.1%and outlet PO fraction of 1.8%.These results can be rationalized by indepth analyses and discussion about the effects of the decision variables on the operation safety and reaction performance.The insights revealed here could shed new light on the process development of the PO production based on the estimation of the explosion limits of the multi-component feed gas mixture containing flammable gase s,inert gas and O2,followed by process optimization.

The study of productivity in the Bohai Sea-Ⅱ. Primary productivity and estimation of potential fish catch

-On the basis of the data obtained from the surveys in the Bohai Sea during 1982-1983, this paper analysed and discussed the distribution and seasonal variation of primary productivity in the Bohai Sea, and the correlations between the primary productivity and environmental factors. The organic carbon production and prospect of fishery production in the waters of this sea are estimated. It is shown that, there exists production patential in the Bohai Sea, the primary production is 112 gC/ (m2 ?a)the production of organic carbon being 10 million ton per year, the fishery yields 1 million ton and the maximum catch of sea products 0. 5 million ton. The results of the investigation can serve as the basic data for the exploitation, utilization and management of the fishery resources in the Bohai Sea.

Rainfall Estimation using Image Processing and Regression Model on DWR Rainfall Product for Delhi-NCR Region

Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall data is available at various important locations in and around Delhi-NCR.However,the 24-hour rainfall data observed by Doppler Weather Radar(DWR)for entire Delhi and surrounding region(up to 150 km)is readily available in a pictorial form.In this paper,efforts have been made to derive/estimate the rainfall at desired locations using DWR hydrological products.Firstly,the rainfall at desired locations has been estimated from the precipitation accumulation product(PAC)of the DWR using image processing in Python language.After this,a linear regression model using the least square method has been developed in R language.Estimated and observed rainfall data of year 2018(July,August and September)was used to train the model.After this,the model was tested on rainfall data of year 2019(July,August and September)and validated.With the use of linear regression model,the error in mean rainfall estimation reduced by 46.58% and the error in max rainfall estimation reduced by 84.53% for the year 2019.The error in mean rainfall estimation reduced by 81.36% and the error in max rainfall estimation reduced by 33.81%for the year 2018.Thus,the rainfall can be estimated with a fair degree of accuracy at desired locations within the range of the Doppler Weather Radar using the radar rainfall products and the developed linear regression model.

Distribution of chlorophyU a and estimation of primary productivity in the eastern waters of Balingtang Channel in summer

Oceanographical features on both sides of Balingtang Channel (17°55′-20°06′N, 122°55′-126°57′E) were comprehensively investigated on board of R/V "Experiment 3" in June. 1984. The pre-sent paper reports the chlorophyll data collected and primary productivity estimated there. Water sam-ples were taken with a glass bottle of Model HQMat the depth of 0, 10. 25, 50, 75, 100 and 150m, separately. Chlorophyll was determined according to the spectrophotometry proposed by UNESCO(1966) and calculated with the trichromatic equations of Jeffrey-Humphrey(1975). Estimations ofprimary productivity were carried out using a simplified equation (Q = 1.5) given by Cadee(1975).

Time-Frequency Bandwidth Product Estimation of Sinusoidal Non-Linear Chirp Keying Scheme

Sine Non-linear Chirp Keying(SNCK) is a kind of high-efficient modulation scheme, which provides a potential new beamforming method in communication and radar systems. It has been proved to have advantages in some parameter estimation issues over conventional modulation schemes. In this paper, a novel transform termed as Discrete Sinusoidal Frequency Modulation transform(DSFMT) is proposed. Then, the DSFMT of SNCK signal is deduced and classified into three types, based on which, the time-bandwidth product is estimated by the proposed algorithm. Simulation results show that the noise has a signifi cant impact on the localization of the peak value and the time-bandwidth product can be estimated by using local ratio values when.

A Non-Destructive Time Series Model for the Estimation of Cherry Coffee Production

Coffee plays a key role in the generation of rural employment in Colombia.More than 785,000 workers are directly employed in this activity,which represents the 26%of all jobs in the agricultural sector.Colombian coffee growers estimate the production of cherry coffee with the main aim of planning the required activities,and resources(number of workers,required infrastructures),anticipating negotiations,estimating,price,and foreseeing losses of coffee production in a specific territory.These important processes can be affected by several factors that are not easy to predict(e.g.,weather variability,diseases,or plagues.).In this paper,we propose a non-destructive time series model,based on weather and crop management information,that estimate coffee production allowing coffee growers to improve their management of agricultural activities such as flowering calendars,harvesting seasons,definition of irrigation methods,nutrition calendars,and programming the times of concentration of production to define the amount of personnel needed for harvesting.The combination of time series and machine learning algorithms based on regression trees(XGBOOST,TR and RF)provides very positive results for the test dataset collected in real conditions for more than a year.The best results were obtained by the XGBOOST model(MAE=0.03;RMSE=0.01),and a difference of approximately 0.57%absolute to the main harvest of 2018.

The depletion of nutrients and the estimation of the new production in the ice-edge of the Prydz Bay,Antarctica

The distributions and changes of nutrients in the Prydz Bay were investigated during CHINARE 6(the 6th Chinese National Antarctic Research Expedition) and CHINARE 9, and the new productions were estimated by using mass balance method. The results showed that in CHINARE 6, the depletion of NO 3 N, PO 4 P, SiO 3 Si were 1064.8, 69.2, 2196.9 mmol/m 2 ,respectively, the uptake ratios of N and Si to P were 15.3, 31.7, respectively, and new production was 992.4 mgC/(m 2·d) ; in CHINARE 9, the depletion of NO 3 N, PO 4 P were 551.9 , 41.2 mmol/m 2 , respectively, the uptake ratio of N to P was 13.4,and the new production was 390.1 mgC/(m 2·d) , indicating significant annual and/or seasonal variation. New productions were both greater than the primary production determined by 14 C trace method, demonstrating there existed rather higher new production in the Prydz Bay in austral summer. The uptake ratio of nutrients in the Prydz Bay, however, is different from the previous values obtained from the open sea, showing the regional difference of uptake and regeneration of nutrients in the Southern Ocean. Finally the annual change of new production and the characteristics of phytoplankton production were discussed.

An improved activity-based costing model for product cost estimation applied in a complex manufacturing environment

In order to evaluate and estimate me cosEs oi prouuct~ plt, uu^u e vironment properly, an improved activity-based costing （ABC） model is presented. By utilizing the input-output analysis method, the complex consumption relationships in a complex manufacturing environment are first expressed. The consumption characteristics （mainly presented by the activity rates） of all production activities are extracted by solving these relationships. Then with the con- sumption characteristics and operating parameters of these activities, the detailed cost consumption of a product in its manufacturing process is estimated. A case study is finally given based on the compressor products of a manufacturing company, and its effectiveness is shown. As the cost influ- ence of complex consumption relationships is fully considered, the limitation of traditional ABC method is overcome, and therefore a high accuracy in product cost estimation under the complex manufacturing environment can be achieved.

STRONG EMBEDDING OF PRODUCT－LIMIT ESTIMATOR OF BIVARIATE SURVIVAL DISTRIBUTION FUNCTION UNDER RANDOM CENSORSHIP

Let (X0,Y0), be i. i. d nonnegative random vectors with continuous survival distribution function be the product-limit estimator of S(s,t) suggested by Campbell and Foldes (1980). In this paper it is shown that under some conditions a sequence of Gaussian processes Gn(s,t) can be constructed such that sup a. s.,for S,T which together satisfy a certain condition.

Statistical Diagnosis for Random Right Censored Data Based on Kaplan-Meier Product Limit Estimate

In this work, we consider statistical diagnostic for random right censored data based on K-M product limit estimator. Under the definition of K-M product limit estimator, we obtain that the relation formula between estimators. Similar to complete data, we define likelihood displacement and likelihood ratio statistic. Through a real data application, we show that our proposed procedure is validity.

Product Assembly Cost Estimation Based on Artificial Neural Networks

This paper proposes a method for assembly cost estimation in actual manufacture during the design phase using artificial neural networks(ANN). It can support the designers in cost effectiveness, then help to control the total cost. The method was used in the assembly cost estimation of the crucial parts of some railway stock products. As a comparison, we use the linear regression (LR) model in the same field. The result shows that ANN model performs better than the LR model in assembly cost estimation.

Almost sure central limit theory for products of sums of partial sums

Consider a sequence of i.i.d.positive random variables.An universal result in almost sure limit theorem for products of sums of partial sums is established.We will show that the almost sure limit theorem holds under a fairly general condition on the weight dk= k-1 exp（lnβk）,0≤β〈1.And in a sense,our results have reached the optimal form.

Reproduction of Hedysarum scoparium (Fabaceae) in patched habitat is pollen limited,but not just pollinator limited

Pollen limitation of plant reproduction occurs across Angiosperms, particularly those in patched habitats We investigated the, relationship between pollen limitation and patch variables （patch size, visitation frequency） in the desert plant Hedysarum scoparium （Fabaceae）, which is an important xerophyte in the arid and semi-arid regions of Northwest China and can grow well as a pioneer plant in shifting sand dunes. We observed insect visitation to H. scoparium over two flowering seasons and estimated pollen limitation using fruit set and seed production. Our results indicate that fruit set and seed production increased significantly with pollen supplementation compared with open pollination. Hedysarum scoparium was pollinated by over 8 species of bees, with 88.4% of visits made by introduced honeybees （Apis mellifera）. Bee visitation varied significantly among the patches of habitats, but not associated with patch size of habitat. In general, pollen limitation occurred more strongly during fruit set than during seed production. The patches that received higher rates of pollinator visits were less pollen limited for fruit set. Pollen limitation for seed production, however, was not associated with pollinator visitation frequency. We conclude that pollen limitation in H. scoparium was caused by more than one reason, not just pollinator visits.

Correlation method estimation of the modulation signal in the weak equivalence principle test

In a test of the weak equivalence principle （WEP） with a rotating torsion pendulum, it is important to estimate the amplitude of the modulation signal with high precision. We use a torsional filter to remove the free oscillation signal and employ the correlation method to estimate the amplitude of the modulation signal. The data analysis of an experiment shows that the uncertainties of amplitude components of the modulation signal obtained by the correlation method are in agreement with those due to white noise. The power spectral density of the modulation signal obtained by the correlation method is about one order higher than the thermal noise limit. It indicates that the correlation method is an effective way to estimate the amplitude of the modulation signal and it is instructive to conduct a high-accuracy WEP test.

Meta-projective Modules, Tensor Products and Limits

In this paper twe prove that the inverse limit of metra-projective modules (meta-injective modules resp. ) is also meta-projective (meta-injective resp. ). Let K be a field f R1, R2 be K-algebras, we also obtain a sufficient condition for lgldim (R1 R2,)≥lgldim R1+lgldimR2, and wgldim (R1 R2) ≥wgldimR1 +wgldimR2

Optimized algorithm in mine production planning, mined material destination, and ultimate pit limit

An integral connection exists among the mine production planning, the mined material destination, and the ultimate pit limit （UPL） in the mining engineering economy. This relation is reinforced by real information and the benefits it engenders in the mining economy. Hence, it is important to create optimizing algorithms to reduce the errors of economic calculations. In this work, a logical mathematical algorithm that considers the important designing parameters and the mining economy is proposed. This algorithm creates an optimizing repetitive process among different designing constituents and directs them into the maximum amount of the mine economical parameters. This process will produce the highest amount of ores and the highest degree of safety. The modeling produces a new relation between the concept of the cutoff grade, mine designing, and mine planning, and it provides the maximum benefit by calculating the destination of the ores. The proposed algorithm is evaluated in a real case study. The results show that the net present value of the mine production is increased by 3% compared to previous methods of production design and UPL.

A New Rayleigh Distribution:Properties and Estimation Based on Progressive Type-II Censored Data with an Application

In this paper,we propose a new extension of the traditional Rayleigh distribution called the modified Kies Rayleigh distribution.The new distribution contains one scale and one shape parameter and its hazard rate function can be increasing and bathtub-shaped.Some mathematical properties of the new distribution are derived including quantiles and moments.The parameters of modified Kies Rayleigh distribution are estimated based on progressively Type-II censored data.For this purpose,we consider two estimation methods,namely maximum likelihood and maximum product of spacing estimation methods.To compare the efficiency of the proposed estimators,a simulation study is carried out.To show the applicability of the new model as well as the estimation methods,one real data for failure times of software is analyzed.Based on the empirical parts,we can conclude that the proposed model can be considered as a good model in the field of life testing and reliability analysis compared with other competing models.

Direction-of-arrival estimation of quasi-stationary signals using two-level Khatri-Rao subspace and four-level nested array

The Khatri-Rao(KR) subspace method is a high resolution method for direction-of-arrival(DOA) estimation.Combined with 2q level nested array,the KR subspace method can detect O(N2q) sources with N sensors.However,the method cannot be applicable to Gaussian sources when q is equal to or greater than 2 since it needs to use 2q-th order cumulants.In this work,a novel approach is presented to conduct DOA estimation by constructing a fourth order difference co-array.Unlike the existing DOA estimation method based on the KR product and 2q level nested array,the proposed method only uses second order statistics,so it can be employed to Gaussian sources as well as non-Gaussian sources.By exploiting a four-level nested array with N elements,our method can also identify O(N4) sources.In order to estimate the wideband signals,the proposed method is extended to the wideband scenarios.Simulation results demonstrate that,compared to the state of the art KR subspace based methods,the new method achieves higher resolution.