Deviation Criterion Research Articles

A multi-objective optimization algorithm for feature selection problems

Feature selection (FS) is a critical step in data mining, and machine learning algorithms play a crucial role in algorithms performance. It reduces the processing time and accuracy of the categories. In this paper, three different solutions are proposed to FS. In the first solution, the Harris Hawks Optimization (HHO) algorithm has been multiplied, and in the second solution, the Fruitfly Optimization Algorithm (FOA) has been multiplied, and in the third solution, these two solutions are hydride and are named MOHHOFOA. The results were tested with MOPSO, NSGA-II, BGWOPSOFS and B-MOABC algorithms for FS on 15 standard data sets with mean, best, worst, standard deviation (STD) criteria. The Wilcoxon statistical test was also used with a significance level of 5% and the Bonferroni–Holm method to control the family-wise error rate. The results are shown in the Pareto front charts, indicating that the proposed solutions' performance on the data set is promising.

Jacking precision control of pipe roof and large box culvert below urban expressway-a case study of a large underpass in Shanghai

Pipe roof-culvert box method is an effective way for shallow buried tunnel passing beneath important facilities. In soft ground, the culvert can be jacked under the pre-reinforcement of pipe roof. This paper presents an investigation on the precision analysis and control of a large- scale pipe roof jacking (the scale of this structure is 21.648m*8.148m) of an underpass, which passes beneath the Mid-Ring expressway in Shanghai. The conclusions drawn from this paper show that: (1) In this project, more than 70 percent of the deflection values of jacking machines and pipes are controlled within 20mm. (2) During the process of pipe jacking, the deflections of pipes tend to lag behind the machines’ about 3~10m. 68 percent of the rangeability of pipes’ deflection are 50%~100% of the corresponding machines’ deflection. (3) Due to Stiffness effect of pipeline, posture of pipe is difficulty to be rectified during the stages of pipe starting and receiving. A compelling rectification will result in overlarge deviation and increase the difficulty of subsequent operation. (4) For two adjacent pipes, the posture of latter pipe is positively related by the stiffness of prior pipe. The Pearson correlation coefficient of horizontal pipes and vertical pipes can be 0.46 and 0.68 respectively. (5) Considering the interspace between top pipes and box culvert, the control criterion of vertical deviation of box culvert is recommended as 5cm.

Evaluation of the Pesticide analysis in Agricultural Products Using the Self-Cleaning Ion Source GC-MS/MS

We evaluated an analytical method to detect pesticide residues in agricultural products through the use of a self-cleaning ion source GC-MS/MS. The self-cleaning ion source minimizes ion source contamination by ensuring that hydrogen is pumped into the source at a fixed pressure after or during measurement. When we employed our self-cleaning ion source GC-MS/MS technique to analyze pesticides residues in agricultural products, we observed that pollution of the ion source surface was considerably reduced. Good peak sensitivity was obtained for 251 pesticides, and a calibration curve with a coefficient of determination (R2) of 0.990 or higher was obtained for 253 pesticides. In the recovery test with 6 types of agricultural products, the acceptability criteria of recovery (70-120%) and standard deviation of repeatability (RSD<25%) was met in 180-221 pesticides.

Modeling Salmonella spp. inactivation in chicken meat subjected to isothermal and non-isothermal temperature profiles

Salmonella genus has foodborne pathogen species commonly involved in many outbreaks related to the consumption of chicken meat. Many studies have aimed to model bacterial inactivation as a function of the temperature. Due to the large heterogeneity of the results, a unified description of Salmonella spp. inactivation behavior is hard to establish. In the current study, by evaluating the root mean square errors, mean absolute deviation, and Akaike and Bayesian information criteria, the double Weibull model was considered the most accurate primary model to fit 61 datasets of Salmonella inactivation in chicken meat. Results can be interpreted as if the bacterial population is divided into two subpopulations consisting of one more resistant (2.3% of the total population) and one more sensitive to thermal stress (97.7% of the total population). The thermal sensitivity of the bacteria depends on the fat content of the chicken meat. From an adapted version of the Bigelow secondary model including both temperature and fat content, 90% of the Salmonella population can be inactivated after heating at 60 °C of chicken breast, thigh muscles, wings, and skin during approximately 2.5, 5.0, 9.5, and 57.4 min, respectively. The resulting model was applied to four different non-isothermal temperature profiles regarding Salmonella growth in chicken meat. Model performance for the non-isothermal profiles was evaluated by the acceptable prediction zone concept. Results showed that >80% of the predictions fell in the acceptable prediction zone when the temperature changes smoothly at temperature rates lower than 20 °C/min. Results obtained can be used in risk assessment models regarding contamination with Salmonella spp. in chicken parts with different fat contents.

Fuzzy logic-based power control system of a supercritical-pressure light water fast reactor

Supercritical-pressure light water fast reactor is one of the current concepts of the Generation IV reactors which have significant improvement on the efficiency, safety and economy. A change of power to flow ratio leads to a change of the outlet coolant temperature in second. The temperature deviation must be suppressed as small as possible to keep the integrity of the reactor structures, like the reactor outlet nozzles, main steam line, etc. The plant dynamics analysis was carried out by giving perturbations of power to flow ratio, and then its influence on the reactor power and outlet coolant temperature were observed. A fuzzy logic-based power control system was designed and applied to the plant to compensate the effects of the perturbations. The control’s parameters, like the member functions of fuzzification were optimized to satisfy the criteria of allowable outlet coolant temperature deviation and stability. The power could be controlled stably by the optimized control design and the criterion of the outlet coolant temperature deviation is satisfied against perturbations of power to flow ratio.

Single-photon emission computed tomography in the scattering medium with the property of “scattering straight back”

The problem of radiation scattering in integral reconstruction algorithms for single-photon emission computed tomography (SPECT) has not been completely solved. This is primarily due to the fact that the radiation transport equation (RTE) does not have an exact analytical solution in general form for a scattering indicatrix corresponding to a real medium. A special form of the scattering indicatrix is proposed here that corresponds to a scattering medium with a property named “scattering straight back.” With this scattering indicatrix, it is possible to obtain an exact analytical solution of the RTE with exact boundary conditions for an arbitrary distribution of radiation sources. From this exact solution, a new expression can be obtained for the measured data, named as generalized attenuated exponential Radon transform. A new definition of projections is proposed to obtain an exact solution of the inverse tomographic problem. This solution has the same level of rigor as the exponential Radon transform for a purely absorbing medium. The proposed algorithm is compared with the traditional SPECT algorithm (the inverse exponential Radon transform) using Monte Carlo simulation based on the nuclear physics software package Geant4. It is demonstrated that the new method is superior to the traditional method in terms of both the standard deviation criterion and better visual distinction of the details in the reconstructed tomogram. The results obtained can be used to improve the existing algorithms for image reconstruction in SPECT, as well as to aid in developing new designs of emission tomographs.

Bearing Fault Diagnosis under Variable Working Conditions Based on Deep Residual Shrinkage Networks and Transfer Learning

Nowadays, deep learning has made great achievements in the field of rotating machinery fault diagnosis. But in the practical engineering scenarios, when facing a large number of unlabeled data and variable operating conditions, only using a deep learning algorithm may reduce the performance. In order to solve the above problem, this paper uses a method of combining transfer learning with deep learning. First, the deep shrinkage residual network is constructed by adding soft thresholds to extract the characteristics of bearing vibration data under noise redundancy. Then, the joint maximum mean deviation (JMMD) criterion and conditional domain adversarial (CDA) learning domain adapting network are used to align the source and target domains. At the same time, adding transferable semantic augmentation (TSA) regular items improves alignment performance between classes. Finally, the proposed model is verified by three experiments: variable load, variable speed, and variable noise, which overcomes the shortcomings of traditional deep learning and shallow transfer learning algorithms.

Impact of the Gross Regional Product and Total Monetary Income of the Population on Savings Behavior in the Regions of Russia

The search for factors that could explain the formation of stable savings behavior of the population while taking into account regional conditions, remains relevant for ensuring the sustainability of a country's banking system. The aim of the study is to identify possible relationships between the indicators of gross regional product, total monetary income and deposits of the population in the regions of Russia. Within the framework of the study, the hypothesis is set and tested about the existence of a pattern between the savings behavior of the population and the share of its income relative to the gross regional product. An index method is used to determine the ratio of the indicators under consideration. Three indices are calculated: the ratio of the increase in deposits of the population, the ratio of the increase in deposits of the population to the volume of monetary income of the population of the region, and the ratio of the volume of monetary income of the population of the region to gross regional product. The latter index has not been used previously in studies of the savings behavior of the population. Additionally, the method of graphical matching of indices with scattering chart construction is applied. The indicators of the regions of Russia are divided into four clusters according to the criterion of deviation from the average values in the country. As a result, various models of behavior of depositors are determined. In 21 regions classified under cluster I and IV, there is a direct proportional relationship between the indicators considered, namely, a low tendency to save with a low share of per capita income to gross regional product. In 64 regions classified as clusters II and III, an inverse relationship between the indicators under consideration was formed, which indicates the predominance of such a model in Russia as a whole and confirms the hypothesis put forward for most regions. The distribution of the regions of the clusters according to relativity criteria from the average Russian values allows you to quickly assess the state of savings behavior of the population and predict this factor when analyzing the stability of regional banking systems within the practical activities of the territorial administrations of the Central Bank of Russia. It can also be used by credit organizations to develop interregional expansion programs.

Evaluation of an Analytical Method Using GC-MS/MS and a 3-Layer Solid Phase Extraction Mini-Column for Pesticide Residues in Agricultural Products

We developed a simple rapid analysis of multi-pesticide residues in agricultural products. In this study, we attempted to simplify the purification process, and reduce the amount and type of solvent used. The test solution was prepared by clean-up, a 0.5 mL aliquot of QuEChERS extract solution of agricultural products using a 3-layer solid-phase (C18/SAX/PSA) extraction mini-column, and the test solution was subjected to GC-MS/MS analysis, modified with a large volume injection and a stomach-type glass-lined injector. This method met the acceptability criteria of recovery (70-120%) and standard deviation of repeatability (RSD<25%) in 241-331 pesticides in 8 types of agricultural products.

An Empirical Assessment of Alternative Methods of Variance-Covariance Matrix

The current study aims at the estimation of a group of variance-covariance methods using the data set of the non-financial sector of the Pakistan stock exchange. The study compares nine covariance estimators using two assessment criteria of root mean square error and standard deviation of minimum variance portfolios to gauge on accuracy and effectiveness of estimators. The findings of the study based on RMSE and risk behaviour of MVPs suggest that portfolio managers receive no additional benefit for using more sophisticated measures against equally weighted variance-covariance estimators in the construction of portfolios. Keywords: Variance-Covariance Estimators, Portfolio Construction, Mean-Variance Optimization.

Broadband Beam-Forming Circuit Using Microstrip Multilayer Couplers

Multipath antenna arrays require broadband small-sized beam-forming circuits for their implementation. For Butler matrix circuits implemented by means of directional couplers, the models have been developed of the broadband power tap devices using coupled lines. However, as a rule, the current topologies feature relatively large amplitude imbalance within the working frequency band. In order to reduce the flatness of both the working attenuation and the transient attenuation, a microstrip topology of the multilayer directional coupler is introduced using coupled lines. Distinctive feature of this topology is the uncommon configuration of the coupling aperture. The coupling aperture shape is optimized within the 4-8 GHz frequency band according to the criterion of the minimum deviation of the amplitude-frequency characteristics from the ideal values. Within the octave band, the developed coupler features the flatness of the working attenuation and the transient attenuation of 0.6 dB as well as the phase imbalance equal to 1.2°. The maximum overall size of the coupler topology does not exceed a quarter of the wavelength. A four-beam beam-forming Butler circuit based on this coupler is presented. The results of both electrodynamic simulation of the circuit and the experimental studies of the mock-up produced are also demonstrated. It is determined that they are in good agreement with each other. The experimental values of the transient droop and the working attenuation of the matrix circuit deviate from the level of 6 dB by no more than 2.5 dB. The maximum phase imbalance does not exceed 8° from the nominal value.

Determination of parameters of models of signal deviation from neighboring samples by convex functions

The paper considers the Nyquist-Shannon-Kotelnikov theorem, the Khlistunov criterion of the greatest deviation, the corresponding deterministic formulas for finding a constant sampling interval of a signal in time and their drawbacks in traditional applications in real-time control systems. Mathematical models of the behavior of a signal or a controlled process between two adjacent samples from it along the trajectory of the greatest deviation in the form of convex functions (half-wave of a sinusoid, a power function of the modulus of time), which are free from these shortcomings, are considered. Constraints are found on the number and magnitude of the time parameters of these models, such as maximum speed, acceleration and sharpness, which are determined by analyzing the signal spectrum and the Nyquist interval. Formulas are obtained, examples of calculations and graphs are given, which illustrate the dependence of the time sampling interval on the accuracy of the linear approximation of the signal and allow increasing the number of signals processed in the system without increasing requirements for its performance.

Locating a discrete subtree of minimum variance on trees: New strategies to tackle a very hard problem

In this paper we study the problem of finding a discrete subtree of minimum variance with bounded size of a given tree. We show that the problem is NP-hard on very simple trees and it remains difficult even if we consider the Mean Absolute Deviation criterion on star graphs. Referring to the variance criterion, we first propose a reformulation of the problem as an Integer Quadratic Program that, however, does not have particular structural properties that may help in finding good lower bounds on the optimal value of the problem. Then, basing on recent results on conic optimization, we investigate alternative reformulations of the problem in order to obtain some lower bounds. In particular, we exploit a continuous linear, conic, reformulation of the problem and show that this is, in fact, an exact linear reformulation of the Integer Quadratic Program. Alternatively, by referring to the upper envelope approach, we show how to obtain a lower bound for the optimal objective function value of our discrete tree-shaped facility location problem in pseudo-polynomial time.

Goat Milk Nutritional Quality Software-Automatized Individual Curve Model Fitting, Shape Parameters Calculation and Bayesian Flexibility Criteria Comparison.

Simple SummaryThe high costs of genotyping normally compel researchers to work with reduced sample sizes. Contextually, population observations may no longer compensate for the lack of sufficient data to fit lactation curves, hindering model efficiency, explicative ability, and predictive potential. Individualized lactation curve analyses may save these drawbacks, but may be time-demanding, which may be prevented through computational automatization. An SPSS model syntax was defined and used to evaluate the individual performance of 49 linear and non-linear models to fit the curve described by the milk components of the milk of 159 Murciano-Granadina does selected for genotyping analyses. Protein, fat, dry matter, lactose, and somatic cell counts curves were evaluated and modelled, while peak and persistence were estimated to maximize the ability to understand and anticipate productive responses in Murciano-Granadina goats, which may translate into improved profitability of goat milk as a product.SPSS syntax was described to evaluate the individual performance of 49 linear and non-linear models to fit the milk component evolution curve of 159 Murciano-Granadina does selected for genotyping analyses. Peak and persistence for protein, fat, dry matter, lactose, and somatic cell counts were evaluated using 3107 controls (3.91 ± 2.01 average lactations/goat). Best-fit (adjusted R2) values (0.548, 0.374, 0.429, and 0.624 for protein, fat, dry matter, and lactose content, respectively) were reached by the five-parameter logarithmic model of Ali and Schaeffer (ALISCH), and for the three-parameter model of parabolic yield-density (PARYLDENS) for somatic cell counts (0.481). Cross-validation was performed using the Minimum Mean-Square Error (MMSE). Model comparison was performed using Residual Sum of Squares (RSS), Mean-Squared Prediction Error (MSPE), adjusted R2 and its standard deviation (SD), Akaike (AIC), corrected Akaike (AICc), and Bayesian information criteria (BIC). The adjusted R2 SD across individuals was around 0.2 for all models. Thirty-nine models successfully fitted the individual lactation curve for all components. Parametric and computational complexity promote variability-capturing properties, while model flexibility does not significantly (p > 0.05) improve the predictive and explanatory potential. Conclusively, ALISCH and PARYLDENS can be used to study goat milk composition genetic variability as trustable evaluation models to face future challenges of the goat dairy industry.

CFD simulation of impeller shape effect on quality of mixing in two-phase gas–liquid agitated vessel

Abstract Mixing efficiency in two-phase gas–liquid agitated vessel is one of the important challenges in the industrial processes. Computational fluid dynamics technique (CFD) was used to investigate the effect of four different pitched blade impellers, including 15°, 30°, 45° and 60°, on the mixing quality of gas–liquid agitated vessel. The multiphase flow behavior was modeled by Eulerian–Eulerian multiphase approach, and RNG k − e was used to model the turbulence. The CFD results showed that a strong global vortex plays the main role on the mixing quality of the gas phase in the vessel. Based on the standard deviation criterion, it was observed that the axial distribution of the gas phase in the 30° impeller is about 55% better than the others. In addition, the results showed that the 30° impeller has a uniform radial distribution over the other impellers and the maximum gas phase holdup in the vessel. Investigation of the power consumption of the impellers showed that the 30° impeller has the highest power consumption among the other pitched blade impellers. Also, examine the effect of same power condition for pitched blade impellers showed that the 30° impeller has the best mixing quality in this condition.

Optimization Scheme of the Orientation Relationship from Crystallographic Statistics of Variants and its Application to Lath Martensite

In crystallographic theory of martensitic transformation, a slightly change of orientation relationship between lath martensite and prior austenite may indicate a different transformation mechanism and a change of mechanical property. Nevertheless, when the retained austenite can be hardly found in specimen, it is a great challenge to establish an accurate determination method for orientation relationship from the variant orientations only. Although some methods have been proposed, a reasonable evaluation of the solution accuracy is still waiting to be performed, and two further attentions should be addressed clearly: 1) significant improvement of calculation efficiency without sacrificing any solution accuracy; 2) effective elimination of the influence of the random cross-sections on the calculation. After an in-depth analysis of these issues, a new approach was developed involving two key steps in this paper. Firstly, an accurate clustering algorithm was developed to perform a statistic of all variants, which can give the most probable orientation and area fraction for each variant. Different from previous methods, the second step is to perform an optimization scheme established in this work, which takes variant fractions into consideration, to determine the optimal orientation relationship and orientation of prior austenite. In addition, the influence of the random cross-sections can be effectively eliminated by inputting the equally-weighted variants into the optimization scheme. Furthermore, in-situ high temperature EBSD examinations were first performed to validate solution accuracy, the corresponding results clearly indicated that the orientation of austenite obtained from this approach exhibited a high accuracy (with an error less than 1°), exceeding the accuracy achieved by the previous methods in addition to avoiding the possible deviation of using distorted retained austenite at room temperature. Indeed, the solution accuracy is contributed by the robust optimization scheme which strictly satisfies the criterion of a minimum average deviation between the measured and predicted orientation of martensitic variants. Another contributor to the accuracy is the good agreement between the clustered variant orientations and the measured data. Under the high accuracy, the variant-level calculation, which can save much computational time compared with pixel/domain-level calculation, is beneficial for the efficiency promotion.

FACSCanto II and LSRFortessa flow cytometer instruments can be synchronized utilizing single-fluorochrome-conjugated surface-dyed beads for standardized immunophenotyping.

BackgroundMultiparameter flow cytometry is the preferred method to determine immunophenotypic features of cells present in a wide variety of sample types. Standardization is key to avoid inconsistencies and subjectivity of interpretations between clinical diagnostic laboratories. Among these standardization requirements, synchronization between different flow cytometer instruments is indispensable to obtain comparable results. This study aimed to investigate whether two widely used flow cytometers, the FACSCanto II and LSRFortessa, can be effectively synchronized utilizing calibration bead–based synchronization.MethodTwo FACSCanto II and two LSRFortessa flow cytometers were synchronized with both multicolor hard‐dyed and single‐fluorochrome–conjugated surface‐dyed beads according to the manufacturer's instructions. Cell staining was performed on five whole‐blood samples obtained from healthy controls and were analyzed upon synchronization with the respective synchronization protocols.ResultsComparability criteria (defined as <15% deviation from the reference instrument) were met with both bead sets when synchronizing different FACSCanto II or LSRFortessa instruments. However, we observed that the criteria could not be met when synchronizing FACSCanto II with LSRFortessa instruments with multicolor hard‐dyed beads. By utilizing single‐fluorochrome–conjugated surface‐dyed beads to determine and adjust PMT voltages, the accepted comparability criteria were successfully met. The protocol has been validated using five different eight‐parameter stained samples.ConclusionWe show that FACSCanto II and LSRFortessa instruments can effectively be synchronized using single‐fluorochrome–conjugated surface‐dyed beads in case deviation criteria cannot be met using multicolor hard‐dyed beads. Synchronization with single‐fluorochrome–conjugated surface‐dyed beads results in decreased deviations between instruments, allowing comparability criteria to become stricter.

GARCH Ailesi Modelleri ve ANN Entegrasyonu ile BİST 100 Endeks Getirisinin Volatilite Tahmini

To avoid market risk, besides portfolio diversification, investors are trying to model the volatility in the best way to reduce uncertainty. The most commonly used methods to model volatility are Autoregressive Conditional Heteroscedasticity family models. However, some studies published in recent years show that semi-parametric hybrid models which consist of the integration of Autoregressive Conditional Heteroscedasticity family models with the Artificial Neural Networks algorithm perform better than these simple models. In this study, the volatility of the Borsa Istanbul 100 price index return is estimated by the aforementioned simple and hybrid models, and the success of the hybrid models is compared with the success of their components. Two different distributions - Normal Distribution and Generalized Error Distribution - are assumed through the estimation process. Comparisons are performed using Mean Squared Error and Mean Absolute Deviation criteria. According to both criteria, the hybrid model composed of Exponential Generalized Autoregressive Conditional Heteroscedasticity - Artificial Neural Networks performed the best. In line with these findings, it is recommended to evaluate the advantages of hybrid models in dynamic risk analysis of financial instruments.

Influence of the Mechanical Error on Performance of Beta Thickness Gauging and the Prediction of System Operation Time

The thickness gauge systems based on beta radiation were widely used in the industry for online, continuous and non-contact measurements. One of the important parameters in beta thickness gauge is the accuracy which the system was evaluated based on it. The effective factors in the measurement accuracy of these systems consist of the mechanical and detection sections. In the mechanical section, the detection system (source and detector) was moved throughout the factory line (without sheet) in order to measure the mechanical error. In the detection part, the detection set-up was stopped in its parking lot and the biaxially oriented polypropylene sheets with different thicknesses were placed between the source and detector to determine the contribution of detection error. In this research, a beta thickness gauge with a 147Pm source (half-life of 31 months) was evaluated in biaxially oriented polypropylene sheet production lines in order to determine the mechanical and detection errors. The contribution of the mechanical error due to system motion and the contribution of the system’s detection error were measured individually. The total error is the sum of the acquired errors of two mechanical and detection sections. In this study, the 2sigma (standard deviation) criterion was used as a system error. The mechanical error was calculated 0.12 by moving of system and without the sheet. Also, the detection error was determined 0.1 by placing the sheet between source and detector and stopping of the system. The total error was estimated 0.16 using the error correlation relation. The acquired results showed for producing of biaxially oriented polypropylene sheets with 15-µm thickness and the maximum acceptable error of ±0.2 µm, the system can be used for 40 months at the precision measurement time (zero time). If the mechanical error is reduced by 50%, the using time of the radioactive source increases to 16 months (56 months). The reducing of the mechanical error can minimize cost, radiation safety, and shielding requirements.

Граничні випадки критерію мінімуму протяжності

Представлені граничні випадки критерію мінімуму протяжності, які відбивають його зв'язок з вiдомими критерiями обробки даних. Установленi вiдповiдностi мiж критерієм мiнiмуму протяжностi й критерiями найменших квадратiв, найменших модулiв, максимуму правдоподiбностi в задачi оцiнювання параметра зсуву за умови фiксованого параметра масштабу для незалежних однаково розподiлених випадкових величин iз законами розподiлу Гаусса, Лапласа, Кошi, "гостровершинним" меридiанним законом розподiлу, законами узагальнених розподiлiв Гаусса й Кошi, критерієм узагальненої максимальної правдоподібності з вартісними функціями Мішалкіна й Демиденка, а також критеріїм максимуму гістограми. Крім цього, у рамках концепції функціонала протяжності представлено кілька варіантів граничного переходу від критерію мінімуму квазіпротяжності до критерію мінімуму строгої протяжності, де останній критерій для дискретного випадку дає постановку NP-складної задачі мінімізації квазінорми простору l0. Підкреслено, що більшість із зазначених критеріїв приводить до постановки задач оптимізації з неопуклою та неунімодальною цільовою функцією.