High Estimation Quality Research Articles

Selecting Tetradic Short Forms of the Taiwan Wechsler Adult Intelligence Scale IV.

Factor-based Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) tetrads were investigated using the Taiwan WAIS-IV standardization sample of 1,105 normal adults aged between 16 and 90 years. Various psychometric characteristics, time constraints, and qualities of estimation were compared among 90 tetrads using linear equation procedures. Among the tetrads, the Information-Visual Puzzle-Digit Span-Digit Symbol combination had higher performance than the other combinations with respect to overall estimation quality and time saved. Moreover, the Similarities-Visual Puzzle-Digit Span-Digit Symbol, Information-Matrix Reasoning-Digit Span-Digit Symbol, and Information-Visual Puzzle-Letter Number Sequencing-Digit Symbol combinations obtained the most efficient estimates. For clinicians who value the utility of Block Design, the Information-Block Design-Digit Span-Digit Symbol combination was found to provide high estimation quality. The findings also revealed that the previously recommended Wechsler Adult Intelligence Scale-Third Edition tetrads are no longer the best solutions for the WAIS-IV. Furthermore, even the selected WAIS-IV tetrads had substantial misclassification rates; the four-factor short forms tend to underestimate the full-scaled IQ for highly intelligent adults. Therefore, these short forms should be used cautiously and for screening purposes only.

Development of Estimation Model for Corrosion Rate of Silver in Hydrogen Sulfide Gas

1. Introduction Silver is one of the most useful materials which are used as the part of electronics equipments because of its high electric and thermal conductivity, while sulfur compounds in the air easily corrode silver in the form of silver sulfide causing a defective continuity. Thus, reliability of electronics equipments consisting of silver should be secured by enough corrosion resistance tests. Corrosion resistance test time are usually decided using field condition and test condition corrosion rate data, however, reported corrosion rate data are limited1. Thus, in order to decide corrosion resistance test time, year-long time tests have been applied under conditions at which the corrosion rate of silver is unknown. The purpose of this study is to get corrosion rate data quickly by an estimation model for the corrosion rate of silver. The factors which are known to be related to silver corrosion are temperature, humidity and corrosive gas concentration. In this study, relations among these three factors and the corrosion rate were defined by making a corrosion rate estimation model which was consist of these factors. 2. Experimental 2.1. Samples Pure silver plates (99.99%) which used in this study were about 30 x 30 x 0.3mm in size. The weights of the plates were precisely measured before the tests. 2.2. Setting of factors Hydrogen Sulfide (H2S) gas was selected as the corrosive gas because of its high reactivity toward silver. Considered diversity field which electronics are installed, the ranges of each factors were decided in the following. H2S concentration : 0.05 to 1.05ppm. Temperature : 25 to 45℃. Humidity : 60 to 90%RH. In this range, three levels (max., med., and min.) were selected for the each factor, and totally 27 (3 x 3 x 3) condition tests were settled for the tests. 2.3. Exposure experiments Silver plates were exposed by H2S in gas concentration, temperature and humidity controlled. After exposure, weights of silver plates were measured. The exposure tests were performed 30 days in maximum. 2.4. Method of analysis The measured 27 corrosion rate data by the exposure tests were analyzed, and the regression equation, that is, the corrosion rate estimation model were made with analysis software (Design Director Version 1.0, NHK Spring Co., LTD.2). This estimation model was composed of three factors, temperature, humidity, and corrosive gas concentration. 3. Results and Discussions 3.1. Development of estimation model The weights of silver plates showed liner increase with exposure time for all the 27 tests, and these increasing patterns followed the famous classic research3. Thus, it was defined that the weight increase of the silver plates shows the amounts of corrosion, and that the liner slopes show the corrosion rates V. From the 27 tests, relations among the factors and the corrosion rates V were analyzed and significant factors were selected. As a result, we got estimation model shown in the following. Corrosion rate estimation model; V=36.0-1.5T+0.021T2-0.12[H2O]-489.2[H2S]+396.6[H2S]2+28.2T[H2S]-0.39T2[H2S]-25.1T[H2S]2+0.36T2[H2S]2+0.65[H2O][H2S] V: corrosion rate (g/m2･h), T: temperature (℃), [H2O]: humidity (%RH), [H2S]: hydrogen sulfide concentration (ppm) From the amount of coefficient, it was clarified that the three factors, especially H2S concentration, have influence on the corrosion rate of silver, and there are interactions among these factors. 3.2. Check of validity of estimation model Another exposure test under a different condition from the 27 sets was performed in order to check the validity of the estimation model. The Vest. (given by the estimation model) to Vexp.(given by the test) ratio was 1.21, it was said that developed estimation model shows high estimation quality. 4. Conclusion In this study, estimation model for the corrosion rate of silver in H2S gas was developed. This model enabled us to get corrosion rate data quickly without having long time test. Reference 1. R. Minamitani, Zairyo-to-kankyo, 64, 14 (2015). 2. NHK Spring Co., LTD., “Features of Design Director”, http://www.nhkspg.co.jp/eng/products/industry/dd/aboutdd.html. 3. D. W. Rice, P. Peterson, E. B. Rigby, P. B. P. Phipps, R.J. Cappell, and R. Tremoureux, J. Electrochem. Soc., 128, 275 (1981).

Evaluating Performance of the DGM(2,1) Model and Its Modified Models

The direct grey model (DGM(2,1)) is considered for fluctuation characteristics of the sampling data in Grey system theory. However, its applications are quite uncommon in the past literature. The improvement of the precision of the DGM(2,1) is only presented in few previous researches. Moreover, the evaluation of forecasted performance of the DGM(2,1) model and its applications was not conducted in previous studies. As the results, this study aims to evaluate forecasted performance of the DGM(2,1) and its three modified models, including the Markov direct grey model MDGM(2,1), the Fourier direct grey model FDGM(2,1), and the Fourier Markov direct grey model FMDGM(2,1) in order to determine the application of the DGM(2,1) model in practical applications and academic research. The results demonstrate that the DGM(2,1) model has lower precision than its modified models, while the forecasted precision of the FDGM(2,1) is better than that of MDGM(2,1). Additionally, the FMDGM(2,1) model presents the best performance among all of the modified models of DGM(2,1), which can effectively overcome the fluctuating of the data sample and minimize the predicted error of the DGM(2,1) model. The finding indicated that the FMDGM(2,1) model does not only have advantages with regard to the sample size requirement, but can also be flexibly applied to the large fluctuation and random sequences with a high quality of estimation.

Inferring presynaptic population spiking from single-trial membrane potential recordings

BackgroundThe time-varying membrane potential of a cortical neuron contains important information about the network activity. Extracting this information requires separating excitatory and inhibitory synaptic inputs from single-trial membrane potential recordings without averaging across trials. New methodWe propose a method to extract the time course of excitatory and inhibitory synaptic inputs to a neuron from a single-trial membrane potential recording. The method takes advantage of the differences in the time constants and the reversal potentials of the excitatory and inhibitory synaptic currents, which allows the untangling of the two conductance types. ResultsWe evaluate the applicability of the method on a leaky integrate-and-fire model neuron and find high quality of estimation of excitatory synaptic conductance changes and presynaptic population spikes. Application of the method to a real cortical neuron with known synaptic inputs in a brain slice returns high-quality estimation of the time course of the excitatory synaptic conductance. Application of the method to membrane potential recordings from a cortical pyramidal neuron of an intact brain reveals complex network activity. Comparison with existing methodsExisting methods are based on repeated trials and thus are limited to estimating the statistical features of synaptic conductance changes, or, when based on single trials, are limited to special cases, have low temporal resolution, or are impractically complicated. ConclusionsWe propose and test an efficient method for estimating the full time course of excitatory and inhibitory synaptic conductances from single-trial membrane potential recordings. The method is sufficiently simple to ensure widespread use in neuroscience.

Influence of the optimization methods on neural state estimation quality of the drive system with elasticity

The paper deals with the implementation of optimized neural networks (NNs) for state variable estimation of the drive system with an elastic joint. The signals estimated by NNs are used in the control structure with a state-space controller and additional feedbacks from the shaft torque and the load speed. High estimation quality is very important for the correct operation of a closed-loop system. The precision of state variables estimation depends on the generalization properties of NNs. A short review of optimization methods of the NN is presented. Two techniques typical for regularization and pruning methods are described and tested in detail: the Bayesian regularization and the Optimal Brain Damage methods. Simulation results show good precision of both optimized neural estimators for a wide range of changes of the load speed and the load torque, not only for nominal but also changed parameters of the drive system. The simulation results are verified in a laboratory setup.

A scalable algorithm for molecular property estimation in high dimensional scaffold-based libraries

An algorithm is presented for the estimation of molecular properties over a library built around a scaffold, which has N sites for functionalization with Mi moieties at the ith scaffold site, corresponding to a library of \({\prod_{i=1}^N M_i}\) molecules. The algorithm relies on a series of operations involving (i) synthesis and property measurement of a minimal number of T randomly sampled members of the library, (ii) expression of the observed property in terms of a high-dimensional model representation (HDMR) of the moiety → property map, (iii) optimization of the ordered sequence of moieties on each site to regularize the HDMR map and (iv) interpolation using the map to estimate the properties of as yet unsynthesized compounds. The set of operations is performed iteratively aiming to reach convergence of the predictive HDMR map with as few synthesized samples as possible. Through simulation, the number T of required random molecular samples is shown to scale very favorably with \({T < < \prod^N_{i=1} M_i}\) for cases up to N = 20 and Mi = 20. For example, high estimation quality was attained for simulated libraries with T ~ 5,000 sampled compounds for a library of 2012 members and T ~ 12,500 sampled compounds for a library of 2020 members. The algorithm is based on the assumption that a systematic pattern exists in the moiety → property map provided that the moieties are optimally ordered on the scaffold sites within the context of HDMR. The overall procedure is referred to as the substituent reordering HDMR algorithm (SR-HDMR). The technique was also successfully tested with laboratory data for estimating C13-NMR shifts in a tri-substituted benzene library and for lac operon repression binding.

Modeling Road Traffic Demand of Container Consolidation in a Chinese Port Terminal

This paper models road traffic demand of container trucks in a Chinese container port. The model is helpful for road planning and traffic management in the port. First, we analyze the attributes of road traffic in the port, to distinguish the differences between port area traffic and surrounding urban area traffic. It is found that port area traffic is generated from vessel operations and fluctuates corresponding to two major factors: operation time schedule and the truck arrival pattern within an operation time window. Since the first factor is available from terminal operators, the truck arrival pattern is the key for modeling port area traffic demand. Second, we conduct a comprehensive survey to collect truck traffic and vessel operation data, which is used to explore the probability distribution of truck arrivals during the consolidation periods. Third, we develop a traffic demand model based on the probability distribution with unknown parameters, and modify this model by taking the effects of some external factors into account. At last, we estimate the parameters with the collected data, and the result indicates that this traffic demand model has a high quality of estimation especially for peak traffic times.

Prediction of δ13C and δ15N in plant tissues with near‐infrared reflectance spectroscopy

Isotope measurements associated with critical plant resources, such as carbon and nitrogen, have helped deepen the ecological understanding of plant resource acquisition and plant interactions. In this study, we tested the appropriateness of near-infrared reflectance spectroscopy for the estimation of stable isotope ratios for nitrogen and carbon of plant tissues. delta(13)C and delta(15)N, as well as total carbon (Ct) and nitrogen (Nt), in leaf tissues of a heterogeneous set of 72 samples of seven bog species from southern Patagonia were determined. Near-infrared reflectance spectroscopy calibrations were developed using partial least-squares regressions and tested by a cross-validation procedure. For each variable, three calibrations were calculated: one with nontransformed data and two with transformations (first and second derivative). Ct and Nt, as well as delta(13)C and delta(15)N, were well predicted by our calibration models. The correlation coefficients of predicted vs actual values of the best calibration models were as follows: 0.95 (Ct), 0.99 (Nt), 0.89 (delta(13)C) and 0.99 (delta(15)N). The cross-validation procedure confirmed the high estimation quality of the calibrations. The results obtained underpin the great potential of the near-infrared reflectance spectroscopy technique in ecological studies as an alternative to more expensive and time-consuming standard methods.