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The present study is set to determine the controlling factors of the length of permanent gullies in the Khalili watershed, Larestan, southern Iran. Hence, 17 causative factors were measured for 60 recorded gullies. The factors included length, the slope above the head cut, discharging point slope, head cut slope, creation area, development area, surface closed grain, bare soil, vegetation cover, surface litter, permeability, the electrical conductivity of extracts saturation, acidity, organic matter, sodium adsorption ratio, soil texture, runoff height, and shear stress. The most suitable equation between gullies' length as the response variable and other measured parameters as independent variables was obtained using stepwise multivariate regression. The results revealed that the creation area, development area, and bare soil had the most crucial role in increasing gullies' length, while the form factor has a decreasing role. Also, critical inferences of this work revealed that, based on Pearson's correlation coefficient and the attained significance level, the gully length was significantly affected by surface closed grain, shear stress in discharging point, and form factor, and, to a lesser degree, discharging point slope and runoff height. Based on the inferences derived from this study, controlling gully erosion in its head cut and reducing the longitudinal advance of permanent gullies by restoring vegetation cover are recommended. [ABSTRACT FROM AUTHOR]

Copyright of Eastern Mediterranean Health Journal is the property of World Health Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim was to find out the preferences of dentists in Iraq regarding strategies of carious tissue removal in management of deep carious lesions (CR) in asymptomatic teeth and how demographics (sex, years of experience, qualification, specialty, place of work) influences these preferences. An online questionnaire of two months duration was constructed and distributed randomly via social media (Facebook). The questionnaire' questions investigated the demographics, CR (included non-selective removal to hard dentine (NS), stepwise (SW) and selective (SE) removal). 238 dentists participated in the study, 164 (69%), 56 (23.5%) and 18 (7.5%) of respondents prefer NS, SW and SE removal, respectively. Significantly both GDP and males prefer NS more than Endodontists and females (P<0.05), Percent of respondents work in private clinics who perform non-selective removal (53.6%) significantly lower than those who work in hospitals (73.6%) (p<0.01). less invasive CR significantly associated with being an endodontist or female or work in a private clinic (OR=2.02, CI 95% 1.02-4.0), (OR=2.04, CI 95% 1.12-3.7) and (OR=2.1, CI 95% 1.0-4.0), respectively. In conclusion Iraqi GDPs prefer invasive strategy of carious tissue removal in management of deep carious lesions. Specialty, place of work and sex of respondents affected these choices significantly. [ABSTRACT FROM AUTHOR]

Copyright of Revista Salud Bosque is the property of Universidad El Bosque and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Objective: To compare multiple‐procedure catheter ablation outcomes of a stepwise approach versus left atrial posterior wall isolation (LA PWI) in patients undergoing nonparoxysmal atrial fibrillation (NPAF) ablation. Background: Unfavorable outcomes for stepwise ablation of NPAF in large clinical trials may be attributable to proarrhythmic effects of incomplete ablation lines. It is unknown if a more extensive initial ablation strategy results in improved outcomes following multiple ablation procedures. Methods: Two hundred twenty two consecutive patients with NPAF underwent first‐time ablation using a contact‐force sensing ablation catheter utilizing either a stepwise (Group 1, n = 111) or LA PWI (Group 2, n = 111) approach. The duration of follow‐up was 36 months. The primary endpoint was freedom from atrial arrhythmia >30 s. Secondary endpoints were freedom from persistent arrhythmia, repeat ablation, and recurrent arrhythmia after repeat ablation. Results: There was similar freedom from atrial arrhythmias after index ablation for both stepwise and LA PWI groups at 36 months (60% vs. 69%, p =.1). The stepwise group was more likely to present with persistent recurrent arrhythmia (29% vs. 14%, p =.005) and more likely to undergo second catheter ablation (32% vs. 12%, p <.001) compared to LA PWI patients. Recurrent arrhythmia after repeat ablation was more likely in the stepwise group compared to the LA PWI group (15% vs. 4%, p =.003). Conclusions: Compared to a stepwise approach, LA PWI for patients with NPAF resulted in a similar incidence of any atrial arrhythmia, lower incidence of persistent arrhythmia, and fewer repeat ablations. Results for repeat ablation were not improved with a more extensive initial approach. [ABSTRACT FROM AUTHOR]

Herein we disclose the radical cation Diels–Alder reaction of aryl vinyl ethers by electrocatalysis, which is triggered by an oxidative SET process. The reaction clearly proceeds in a stepwise fashion, which is a rare mechanism in this class. We also found that two distinctive pathways, including “direct” and “indirect”, are possible to construct the Diels–Alder adduct.

Primary focal hyperhidrosis is a common reason for dermatology outpatient visit and has significant impact on patient's social and professional activities. The study describes the clinical profile of those patients and response with aluminum chloride hexahydrate lotion (ACH 20%) and oral glycopyrrolate (OGP). A retrospective study was carried out at a tertiary care center between the year 2016 and 2018. Details of history, baseline assessment, treatment response recorded in specially designed proformas were analyzed. Initially, the patients received topical ACH daily at night. Non‐responders were advised OGP 1 mg BD and increased to 2 mg BD if they did not respond. Response was measured according to patient global assessment and objective evaluation of sweating. Among total 69 patients 57 had onset <10 years of age. There was male preponderance and most common trigger was situations causing anxiety (n = 15). Around 15.3% patients got adequate response with ACH lotion. The cumulative response increased to 45.8% by addition of OGP 1 mg BD and to 55.9% by increasing the dose to 2 mg BD. Addition of OGP to topical ACH increases the treatment efficacy in patients with primary focal hyperhidrosis. Increasing the glycopyrrolate dose augments the response further. However, the current medical treatment options are able to give moderate response. [ABSTRACT FROM AUTHOR]

Introduction: Clinical trials have failed to reliably show improved outcomes with utilization of contact-force sensing (CFS) radiofrequency (RF) ablation catheters. It is unknown whether the unfavorable outcomes observed in these trials are attributable to inexperience with CFS technology.Objectives: To compare catheter ablation outcomes of stepwise linear ablation with versus without CFS technology and to assess the impact of operator experience with CFS technology on procedural outcomes.Methods: Clinical outcomes were evaluated in 228 consecutive NPAF patients undergoing first-time left atrial ablation using a stepwise linear approach. Arrhythmia recurrence was assessed using 2-week event monitors at 3-month intervals following index ablation.Results: A total of 228 patients were included in our study. There was no statistically significant difference in risk of recurrent atrial arrhythmias at 12 and 24 months between CFS and non-CFS patients (p = 0.5 and p = 0.169). The time to recurrence of atrial arrhythmias at 24 months in the second half of CFS patients was significantly lower when compared to both the first half of CFS patients (p = 0.002) and non-CFS patients (p = 0.005).Conclusion: While there was no difference in overall outcomes between CFS and non-CFS ablation using a stepwise linear approach in patients with NPAF, procedural efficacy of the second half of CFS patients was significantly improved compared to both the first half of CFS patients and all non-CFS patients. Lack of benefit seen in clinical trials using CFS technology may be related to operator inexperience with CFS ablation catheters at the time of the trials. [ABSTRACT FROM AUTHOR]

Copyright of Eastern Mediterranean Health Journal is the property of World Health Organization and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As a core component of most cognitive diagnosis models, the Q‐matrix, or item and attribute association matrix, is typically developed by domain experts, and tends to be subjective. It is critical to validate the Q‐matrix empirically because a misspecified Q‐matrix could result in erroneous attribute estimation. Most existing Q‐matrix validation procedures are developed for dichotomous responses. However, in this paper, we propose a method to empirically detect and correct the misspecifications in the Q‐matrix for graded response data based on the sequential generalized deterministic inputs, noisy 'and' gate (G‐DINA) model. The proposed Q‐matrix validation procedure is implemented in a stepwise manner based on the Wald test and an effect size measure. The feasibility of the proposed method is examined using simulation studies. Also, a set of data from the Trends in International Mathematics and Science Study (TIMSS) 2011 mathematics assessment is analysed for illustration. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the fatigue failure load of distinct lithium disilicate restoration designs cemented on a chairside titanium base for maxillary anterior implant‐supported restorations. Materials and Methods: A left‐maxillary incisor restoration was virtually designed and sorted into 3 groups: (n = 10/group; CTD: lithium disilicate crowns cemented on custom‐milled titanium abutments; VMLD: monolithic full‐contour lithium disilicate crowns cemented on a chairside titanium‐base; VCLD: lithium disilicate crowns bonded to lithium disilicate customized anatomic structures and then cemented onto a chairside titanium base). The chairside titanium base was air‐abraded with aluminum oxide particles. Subsequently, the titanium base was steam‐cleaned and air‐dried. Then a thin coat of a silane agent was applied. The intaglio surface of the ceramic components was treated with 5% hydrofluoric acid (HF) etching gel, followed by silanization, and bonded with a resin cement. The specimens were fatigued at 20 Hz, starting with a 100 N load (5000× load pulses), followed by stepwise loading from 400 N up to 1400 N (200 N increments) at a maximum of 30,000 cycles each. The failure loads, number of cycles, and fracture analysis were recorded. The data were statistically analyzed using one‐way ANOVA, followed by pairwise comparisons (p < 0.05). Kaplan‐Meier survival plots and Weibull survival analyses were reported. Results: For catastrophic fatigue failure load and the total number of cycles for failure, VMLD (1260 N, 175,231 cycles) was significantly higher than VCLD (1080 N, 139,965 cycles) and CDT (1000 N, 133,185 cycles). VMLD had a higher Weibull modulus demonstrating greater structural reliability. Conclusion: VMLD had the best fatigue failure resistance when compared with the other two groups. [ABSTRACT FROM AUTHOR]

The quantitative structure activity relationship (QSAR) of the novel pyrazole derivatives as inhibitors of p38α mitogen activated protein (MAP) kinase was studied. The suitable set of the molecular descriptors was calculated and the important descriptors using the variable selections of the stepwise (SW) and the genetic algorithm (GA) were selected. The predictive quality of the QSAR models was tested for an external set of nine compounds, randomly chosen out of 44 compounds. A comparison between the attained results indicated the superiority of the genetic algorithm over the stepwise method in the feature selection. The genetic algorithm-multiple linear regression (GA-MLR) model with six selected descriptors was obtained. The accuracy of the proposed model is illustrated using the following evaluation techniques: cross-validation, validation through an external test set, applicability domain, and Y-randomization. The analyses may be used to design more potent pyrazole derivatives and predict their activity prior to synthesis.

Including auxiliary variables such as antecedent and consequent variables in mixture models provides valuable insight in understanding the population heterogeneity embodied by a latent class variable. The model building process regarding how to include predictors/correlates and outcomes of the latent class variables into mixture models is an area of active research. As such, new methods of including these variables continue to emerge and best practices for the application of these methods in real data settings (including simple guidelines for choosing amongst them) are still not well established. This paper focuses on one type of auxiliary variable—distal outcomes—providing an overview of the methods currently available for estimating the effects of latent class membership on subsequent distal outcomes. We illustrate the recommended methods in the software packages Mplus and Latent Gold using a latent class model to capture population heterogeneity in students' mathematics attitudes, linking latent class membership to two distal outcomes. [ABSTRACT FROM AUTHOR]

The mechanism of 1,4-, 1,2-, and 3,4-cyclization reactions of cyclic 1-azadiene 1 with an organocatalyst 4 has been studied theoretically using DFT method. The reactions proceed in a stepwise fashion, with zwitterionic intermediates. The most favorable cyclization reaction takes place along the C–C pathway of the 1,4-cyclization reaction, under a combination of kinetic and thermodynamic control. The reaction is characterized by the nucleophilic attack of 4 (C5) to the electrophilic center of 1 (C1), leading to the formation of cycloadduct 6, which correctly explains the source of the regioselectivity. [ABSTRACT FROM AUTHOR]

Copyright of Cientifica is the property of Fundacao de Apoio a Pesquisa e Extensao and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The shape of the mesoporous silica particles is rich and colorful. It has long been believed that the macroscopic structure of mesoporous silica particles is formed by continuously building microstructural units and growing them step by step. However, in this work, it is found that the growth process of mesoporous silica particles is not linear but stepped. The mesoporous silica particles grow up by repeating the process of "rapid construction of framework structure first and then slow construction of fine structure". The size of the mesoporous silica particles only grows stepwise when constructing the framework structure, but remains almost unchanged during subsequent fine structure construction. During the growth of the mesoporous silica particles, about one-sixth of the time is used to construct the framework structure, and the rest of the time is spent on the construction of fine structure. [ABSTRACT FROM AUTHOR]

A series of 2-benzoxazolinone, diazocoumarin and quinazoline derivatives have been shown to inhibit HIV replication in cell culture. To understand the pharmacophore properties of selected molecules and design new anti-HIV agents, quantitative structure--activity relationship (QSAR) study was developed using a descriptor selection approach based on the stepwise method. Multiple linear regression method was applied to relate the anti-HIV activities of dataset molecules to the selected descriptors. Obtained QSAR model was statistically significant with correlation coefficient R² of 0.84 and leave one out coefficient Q² of 0.73. The model was validated by test set molecules giving satisfactory prediction value (R²test) of 0.79. Molecules also were docked on HIV integrase enzyme and showed important interactions with the key residues in enzyme active site. These data might be helpful for design and discovery of novel anti-HIV compounds. [ABSTRACT FROM AUTHOR]

Copyright of Revista Salud Bosque is the property of Universidad El Bosque and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Increasing temperature from climate change can bring a number of different risks such as more droughts and heat waves, and increasing sea level rise. Assessment of climate change with future scenarios is essential to adapt these impacts. To provide climate change information through the outputs of general circulation models at finer resolution, a reliable and accurate downscaling model has always been of great interest. Meeting this need, artificial neural network (ANN) has been commonly employed in downscaling for nonlinear models. Extreme learning machine (ELM), a recently developed ANN, is an efficient learning algorithm for generalized single hidden layer feedforward neural networks. In light of its simple learning algorithm, we introduced a useful approach to combine the stepwise feature selection method into ELM for temperature downscaling, as stepwise ELM (SWELM), since model complexity and computational time consumption of a traditional ANN impedes application of stepwise feature selection. This SWELM is able to identify the most influential predictors in a dataset and use them to train a nonlinear model while removing the irrelevant ones. The ELM and SWELM as well as regular ANN were tested in a simulation study. Results indicated that ELM even with randomness of weights and biases in the nodes of input and hidden layers better performed than did ANN. Also, SWELM presents a capability to select the influential predictors and remove the unrelated variables. A case study with downscaling temperature of Wisconsin, USA, showed that ELM was a comparable alternative to ANN. SWELM outperformed the ANN algorithm for temperature downscaling and sometimes predicted the temperature increase larger than did others for future scenarios. The current study of temperature downscaling with the statistical tool allows assessing the possible impacts of climate change in a local scale and some developing countries where sophisticate research cannot be eligible. [ABSTRACT FROM AUTHOR]

In Malaysia, more than 330 000 individuals are estimated to be chronically infected with hepatitis C virus (HCV), but less than 2% have been treated to date. To estimate the required coverage and costs of a national screening strategy to inform the launch of an HCV elimination program. We designed an HCV screening strategy based on a "stepwise" approach. This approach relied on targeting of people who inject drugs in the early years, with delayed onset of widespread general population screening. Annual coverage requirements and associated costs were estimated to ensure that the World Health Organization elimination treatment targets were met. In total, 6 million individuals would have to be screened between 2018 and 2030. Targeting of people who inject drugs in the early years would limit annual screening coverage to less than 1 million individuals from 2018 to 2026. General population screening would have to be launched by 2026. Total costs were estimated at MYR 222 million ($58 million). Proportional to coverage targets, 60% of program costs would fall from 2026 to 2030. This exercise was one of the first attempts to conduct a detailed analysis of the required screening coverage and costs of a national HCV elimination strategy. These findings suggest that the stepwise approach could delay the onset of general population screening by more than 5 years after the program's launch. This delay would allow additional time to mobilize investments required for a successful general population screening program and also minimize program costs. This strategy prototype could inform the design of effective screening strategies in other countries. • With only 10% of infected individuals diagnosed globally, screening to identify patients with undiagnosed hepatitis C virus (HCV) infections is one of the most prominent barriers to achieving HCV elimination. • In this article, we describe our efforts to design a "stepwise" national screening strategy for Malaysia that allows a sufficient number of patients to be identified to meet the World Health Organization 2030 treatment targets and proposes how HCV screening could be decentralized over time. • This exercise represents one of the first costing exercises of a national HCV screening program in a low- to middle-income country. This approach could serve as a prototype for other countries wishing to design effective and feasible screening strategies. [ABSTRACT FROM AUTHOR]

Copyright of Boletín Latinoamericano y del Caribe de Plantas Medicinales y Aromáticas is the property of Universidad de Santiago de Chile and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

During rough rice drying, gradients of moisture content and glass transition temperature cause thermal and mechanical stresses inside the kernel. These stresses eventuate to kernel fissuring during the milling process. In this study, convective drying of Hashemi (long grain) rough rice was applied to investigate the effect of continuous and stepwise changes in air temperature on stress cracking index and process duration. Toward this objective, the concepts of glass transition and analysis of moisture contents distributions within the rice kernel were determined through a numerical modeling of mass transfer. For stepwise temperature change, the drying experiments were conducted at temperatures above the glass transition temperature. Results indicated that the stress cracking index under stepwise temperature change conditions (i.e., within the rubbery state) was reduced compared to the continuous mode probably due to a drip in the moisture content gradients created inside the kernels during the drying process. Moreover, the drying duration significantly was shortened when the kernel was dried within the rubbery state due to faster diffusion moisture within the kernel. [ABSTRACT FROM AUTHOR]

Copyright of Revista Colombiana de Ciencias Hortícolas is the property of Revista Colombiana de Ciencias Horticolas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The LiF synthesis industry produces a large amount of wastewater that contains ∼0.36 g/L lithium and ∼1.10 g/L fluorine. The traditional treatment solidified fluoride by excessive CaO, resulting in waste of lithium resources and generation of CaF 2 -CaO solid waste. To recover the Li and F from the LiF wastewater, a two-section solvent extraction process using acidic solvent and mixed solvent as organic solvent was designed and the extraction mechanism were systematically investigated. The result showed that Li extraction was extracted by a cation exchange mechanism with D2EHPA (di-2-ethyl hexyl phosphoric acid), 99.72% Li recovery and battery-grade LiCl solution (3.40 g/L) were achieved by mixed the LiF aqueous with the saponified D2EHPA at 25 ℃ for 6 mins with 4.60 equilibrium pH. After then, F was recovered by mixed neutral solvent system, which coordination binding with HF molecule. The ultimately residue contains ∼1 mg/L Li and < 6 mg/L F. Besides, high-purity LiF products (LiF>99.95%) was generated by stripping with LiOH, F recovery is 99.45%. 2-stage extraction process realizes lithium and fluoride recovery with short process, no pollution and great prospect of industrialization. [Display omitted] • Li recovered as high purity LiCl solution by D2EHPA-sulphonated kerosene system. • F was recovered by mixed neutral solvent system to generate LiF production. • The tailwater is neutral salt solution can directly discharge after Li & F recovery. • The whole process is short, green and environmentally friendly, with promising for industrialization. [ABSTRACT FROM AUTHOR]

Resumo O objetivo deste trabalho foi o desenvolvimento de modelos com diferentes conjuntos de dados, para estimar a densidade de solos de regiões tropicais montanhosas, a partir de atributos de solos comumente encontrados nas análises de perfis de solos descritos nos levantamentos regionais. O conjunto total de dados compõe-se de 163 amostras e foi dividido em seis grupamentos, dos quais três com 73 amostras, com o máximo de 32 covariáveis, e três com 163 amostras, com o máximo de 18 covariáveis. Testaram-se modelos de regressão linear múltipla (RLM) e randomForest (RF). A menor incerteza entre os modelos foi alcançada pelo RLM2, com R2 de 0,56, 13 covariáveis e 73 amostras. Nos grupamentos com 163 amostras, os melhores modelos foram os RF, com R2 médio de 0,48. A raiz quadrada da média do erro ao quadrado variou entre 0,09 e 0,14. As covariáveis mais importantes no modelo RF foram: carbono orgânico, hidrogênio, areia fina e grossa, saturação por bases e capacidade de troca catiônica. Pelo método "stepwise regression", as variáveis mais importantes foram: a relação silte/argila; areia grossa e fina; carbono orgânico; saturação por bases; e potássio.

Abstract Background This paper explores the importance of electronic medical records (EMR) for predicting 30-day all-cause non-elective readmission risk of patients and presents a comparison of prediction performance of commonly used methods. Methods The data are extracted from eight Advocate Health Care hospitals. Index admissions are excluded from the cohort if they are observation, inpatient admissions for psychiatry, skilled nursing, hospice, rehabilitation, maternal and newborn visits, or if the patient expires during the index admission. Data are randomly and repeatedly divided into fitting and validating sets for cross validations. Approaches including LACE, STEPWISE logistic, LASSO logistic, and AdaBoost, are compared with sample sizes varying from 2,500 to 80,000. Results Our results confirm that LACE has moderate discrimination power with the area under receiver operating characteristic curve (AUC) around 0.65-0.66, which can be improved to 0.73-0.74 when additional variables from EMR are considered. These variables include Inpatient in the last six months, Number of emergency room visits or inpatients in the last year, Braden score, Polypharmacy, Employment status, Discharge disposition, Albumin level, and medical condition variables such as Leukemia, Malignancy, Renal failure with hemodialysis, History of alcohol substance abuse, Dementia and Trauma. When sample size is small (≤5000), LASSO is the best; when sample size is large (≥20,000), the predictive performance is similar. The STEPWISE method has a slightly lower AUC (0.734) comparing to LASSO (0.737) and AdaBoost (0.737). More than one half of the selected predictors can be false positives when using a single method and a single division of fitting/validating data. Conclusions True predictors can be identified by repeatedly dividing data into fitting/validating subsets and referring the final model based on summarizing results. LASSO is a better alternative to the STEPWISE logistic regression, especially when sample size is not large. The evidence for adequate sample size can be explored by fitting models on gradually reduced samples. Our model comparison strategy is not only good for 30-day all-cause non-elective readmission risk predictions, but also applicable to other types of predictive models in clinical studies.

The stepwise and concerted Ionic Diels-Alder reaction between phenyl (pyridin-2-ylmethylene) oxonium and styrene derivatives are explored using theoretical method. The results support using computational method via persistent intermediates. The DFT method was essential to reproduce a reasonable potential energy surface for these challenging systems.

This paper presents the results of a numerical study using the finite element method in geometrical nonlinear on camped shallow spherical shells under uniform pressure. The shell structure was modelled by finite axisymmetric thin shell elements and quadrilateral elements. The geometrical nonlininear problem was solved by a scheme of incremental iterative procedures applying Newton-Raphson method in combination with arch length methods. The results of finite element analysis compared with the experimental results of previous reseacher.

Information of water resources in the form of information on hydrological and hydro meteorological conditions, necessary to support the management of water resources in the basin (Law No.7/2004 SDA). This information is obtained from hydro-meteorological network that represents of these Basin. Rationalization aims to obtain efficient and effective hydrological network and can represent the hydrologic conditions of Seram Island Maluku Province both present and future. Therefore the selection of a method that only suggest the number, density or distribution of the post is not the final answer and directly elected, but the integration between the methods used by the method of Kagan, weight factor, and Stepwise with rules (standard, guidance, and manual) and considering spesific infrastructure needs existing and planned development in accordance with the pattern of river basin management. Proposed hydrology network for Seram Island is to maintain the existing number of hydrological station with the notes necessary of improvement efforts for hydrological management, such as to the amount of rainfall station are as many as 46 stations. Kagan analysis results for the basin with an area 4,873,382 km², has an error rate of 5% and 10% for the analysis, relatively small and good enough to be maintained.

Compared to supervised machine learning (ML), the development of feature selection for unsupervised ML is far behind. To address this issue, the current research proposes a stepwise feature selection approach for clustering methods with a specification to the Gaussian mixture model (GMM) and the k -means. Rather than the existing GMM and k -means which are carried out based on all the features, the proposed method selects a subset of features to implement the two methods, respectively. The research finds that a better result can be obtained if the existing GMM and k -means methods are modified by nice initializations. Experiments based on Monte Carlo simulations show that the proposed method is more computationally efficient and the result is more accurate than the existing GMM and k -means methods based on all the features. The experiment based on a real-world dataset confirms this finding.