Search results

Automatic segmentation of brain tumor from medical images is a challenging task because of tumor's uneven and irregular shapes. In this paper, the authors propose an attention-based nested segmentation network, named DAU-Net. In total, two types of attention mechanisms are introduced to make the U-Net network focus on the key feature regions. The proposed network has a deep supervised encoder–decoder architecture and a redesigned dense skip connection. DAU-Net introduces an attention mechanism between convolutional blocks so that the features extracted at different levels can be merged with a task-related selection.

In the coding layer, the authors designed a channel attention module. It marks the importance of each feature graph in the segmentation task. In the decoding layer, the authors designed a spatial attention module. It marks the importance of different regional features. And by fusing features at different scales in the same coding layer, the network can fully extract the detailed information of the original image and learn more tumor boundary information.

To verify the effectiveness of the DAU-Net, experiments were carried out on the BRATS 2018 brain tumor magnetic resonance imaging (MRI) database. The segmentation results show that the proposed method has a high accuracy, with a Dice similarity coefficient (DSC) of 89% in the complete tumor, which is an improvement of 8.04 and 4.02%, compared with fully convolutional network (FCN) and U-Net, respectively.

The experimental results show that the proposed method has good performance in the segmentation of brain tumors. The proposed method has potential clinical applicability.

The precise segmentation of brain tumors is the most important and crucial step in their diagnosis and treatment. Due to the presence of noise, uneven gray levels, blurred boundaries and edema around the brain tumor region, the brain tumor image has indistinct features in the tumor region, which pose a problem for diagnostics. The paper aims to discuss these issues.

In this paper, the authors propose an original solution for segmentation using Tamura Texture and ensemble Support Vector Machine (SVM) structure. In the proposed technique, 124 features of each voxel are extracted, including Tamura texture features and grayscale features. Then, these features are ranked using the SVM-Recursive Feature Elimination method, which is also adopted to optimize the parameters of the Radial Basis Function kernel of SVMs. Finally, the bagging random sampling method is utilized to construct the ensemble SVM classifier based on a weighted voting mechanism to classify the types of voxel.

The experiments are conducted over a sample data set to be called BraTS2015. The experiments demonstrate that Tamura texture is very useful in the segmentation of brain tumors, especially the feature of line-likeness. The superior performance of the proposed ensemble SVM classifier is demonstrated by comparison with single SVM classifiers as well as other methods.

The authors propose an original solution for segmentation using Tamura Texture and ensemble SVM structure.

To ensure the stable operation of ironmaking process and the quality and output of sinter, the multi-objective optimization of sintering machine batching process was carried out.

The purpose of this study is to establish a multi-objective optimization model with iron taste content and batch cost as targets, constrained by field process requirements and sinter quality standards, and to propose an improved balance optimizer algorithm (LILCEO) based on a lens imaging anti-learning mechanism and a population redundancy error correction mechanism. In this method, the lens imaging inverse learning strategy is introduced to initialize the population, improve the population diversity in the early iteration period, avoid falling into local optimal in the late iteration period and improve the population redundancy error correction mechanism to accelerate the convergence rate in the early iteration period.

By selecting nine standard test functions of BT series for simulation experiments, and comparing with NSGA-?, MOEAD, EO, LMOCSO, NMPSO and other mainstream optimization algorithms, the experimental results verify the superior performance of the improved algorithm. The results show that the algorithm can effectively reduce the cost of sintering ingredients while ensuring the iron taste of sinter, which is of great significance for the comprehensive utilization and quality assurance of sinter iron ore resources.

An optimization model with dual objectives of TFe content and raw material cost was developed taking into account the chemical composition and quality indicators required by the blast furnace as well as factors such as raw material inventory and cost constraints. This model was used to adjust and optimize the sintering raw material ratio. Addressing the limitations of existing optimization algorithms for sintering raw materials including low convergence accuracy slow speed limited initial solution production and difficulty in practical application we proposed the LILCEO algorithm. Comparative tests with NSGA-III MOEAD EO LMOCSO and NMPSO algorithms demonstrated the superiority of the proposed algorithm. Practical applications showed that the proposed method effectively overcomes many limitations of the current manual raw material ratio model providing scientific and stable decision-making guidance for sintering production operations.

The face-centered cubic structured single-phase FeCoNiCrMn high-entropy alloys (HEAs) were prepared to study the friction and wear behavior of HEAs under MoS₂-oil lubrication.

FeCoNiCrMn alloys were subjected to ball-on-disc reciprocating sliding against the GCr15 ball. L₂₅(5⁶) orthogonal wear tests were designed for velocity V_rel (4.167-20.833 mm/s), load F_N (10-50 N), temperature T (RT-140 °C) and time t (5-20 min). Based on orthogonal test results, multivariate repeated measures ANOVA was performed, and further comparative experiments were conducted for V_rel, F_N and T. Energy dispersive spectrometer and scanning electron microscope were applied to characterize the surface morphology of wear scar and its element distribution.

V_rel, F_N and t exerted the most significant influence (p < 0.01) on the average friction coefficient f. V_rel and F_N were identified as the momentous effect (p < 0.01) on wear volume ΔV. T (≥50 °C) had positive correlation with f and ΔV, and both V_rel and F_N correlated negatively with f. The dominant abrasive wear was attributed to the large hardness difference of the friction pair. Fatigue wear and delamination wear were experienced at higher speeds (V_rel  ≥ 12.5 mm/s) and loading levels (F_N ≥ 40 N). Elevated temperature weakens the lubrication effect of MoS₂-oil and the mechanical properties of FeCoNiCrMn matrix, intensifying abrasive wear.

This study is expected to provide references for exploration on the wear behavior of single-phase HEAs under complex working conditions with lubrication and hence will help develop the application of HEAs in practical engineering.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2019-0303

The purpose of this article is to put forward China’s Hanyu Pinyin word guanli as an academic basic term to the world.

GUANLI as an academic basic term, which holds multiple meanings of several English words, such as management, administration, governance, etc. As a basic term, GUANLI, derived several words, such as GUANLIOLOGY, GUANLIST/GUANLIER and GUANLIWORK/GUANLIJOB, to precisely and exactly convey the Chinese GUANLI ideas. It is the historical mission and opportunity for the authors to research and establish the Chinese School of Modern GUANLI Science (CSMGS).

It is inevitably necessary to build the combined Chinese–Western discourse system of GUANLI science (CCWDSGS). Some other research results of CSMGS are also presented in this paper.

It is needless to say that there are still lots of problems in China, including in the GUANLI field. These problems will gradually be solved in China’s reform and development that takes place continuously. New problems will come up while old problems are being solved and settled; problems producing in a loop, problems solving in a loop, this is the dialectics. The authors have full confidence in solving problems, as well as in China’s development and future.

Practice comes first and then it is followed by theory. The authors first have the “China Model”, followed by the “Chinese School” consequently. The “China Model” has already been there, and the “Chinese School” relies on the author’s proactive research and innovation. It is just the right time for the authors to study and create the CSMGS. This is the historical mission and opportunity awaited by contemporary Chinese.

The purpose of this paper is to focus on the performance of three typical nonlinear least-squares estimation algorithms in atmospheric density model calibration.

The error of Jacchia-Roberts atmospheric density model is expressed as an objective function about temperature parameters. The estimation of parameter corrections is a typical nonlinear least-squares problem. Three algorithms for nonlinear least-squares problems, Gauss–Newton (G-N), damped Gauss–Newton (damped G-N) and Levenberg–Marquardt (L-M) algorithms, are adopted to estimate temperature parameter corrections of Jacchia-Roberts for model calibration.

The results show that G-N algorithm is not convergent at some sampling points. The main reason is the nonlinear relationship between Jacchia-Roberts and its temperature parameters. Damped G-N and L-M algorithms are both convergent at all sampling points. G-N, damped G-N and L-M algorithms reduce the root mean square error of Jacchia-Roberts from 20.4% to 9.3%, 9.4% and 9.4%, respectively. The average iterations of G-N, damped G-N and L-M algorithms are 3.0, 2.8 and 2.9, respectively.

This study is expected to provide a guidance for the selection of nonlinear least-squares estimation methods in atmospheric density model calibration.

The study analyses the performance of three typical nonlinear least-squares estimation methods in the calibration of atmospheric density model. The non-convergent phenomenon of G-N algorithm is discovered and explained. Damped G-N and L-M algorithms are more suitable for the nonlinear least-squares problems in model calibration than G-N algorithm and the first two algorithms have slightly fewer iterations.

Two perspectives provide alternative insights into household composition in contemporary Eastern Europe. The first stresses that individuals have relatively fixed preferences about living arrangements and diverge from them only when they cannot attain their ideal. The second major approach, the adaptive strategies perspective, predicts that individuals have few preferences. Instead, they use household composition to cope with economic hardship, deploy labor, or care for children or the elderly. This article evaluates these approaches in five post‐socialist East‐European countries, Bulgaria, Hungary, Poland, Romania, and Russia, using descriptive statistics and logistic regression. The results suggest that household extension is common in these countries and provide the most evidence for the adaptive strategies perspective. In particular, the results show that variables operationalizing the adaptive strategies perspective, including measures of single motherhood, retirement status, agricultural cultivation, and poverty, increase the odds of household extension.

There is no proposed solution to address the unresolved issues of constructing the Chinese university intellectual property information service system (IPISS) to promote the whole process service efficiency of IP creation, utilization, protection and management. The purpose of this paper is to propose a complete system, including theoretical framework and system development which addresses the existing difficulties to IP create, protect and transfer for researchers in universities. The paper shares the practice of utilizing the system developed by Wuhan University IP research team known as Wuhan University Intellectual Property Information Service System (WHU-IPISS).

First, the IPISS of 23 universities in China was investigated on the internet. Aiming at the deficiencies of the system, such as single service type, lack of patent display window, low management efficiency. This paper constructs the theoretical framework, proposes the IP ecological chain model, divides it into four sub-chains and carries on the functional design. Further, under the theoretical framework, the IPISS was developed, including the resource supply management system, user demand matching system, resource assessment system and expert support system. Finally, the system was applied to Wuhan University to provide IP services in the whole process for university researchers.

WHU-IPISS realizes the functions of IP resource supply, demand matching, value evaluation and expert support. It solves the IP needs of university researchers and provides a guarantee for their technology research, patent portfolio, patent transfer and patent rights protection. It also improves the efficiency of IP service and can construct the IP ecosphere in universities.

The WHU-IPISS solution resolves issues of “How to develop the university IP whole process service model, fulfilling the IP service needs for universities' researchers”. The software will be released as open-source for other universities' use. The publishing model is also useful for those universities that intend to implement the IPISS.

The purpose of this paper is to analyze the influencing factors of patients’ financial burden through a case study of hospital on public‒private partnerships (PPP) model (Chaonan Minsheng Hospital of Guangdong Province) and provide some useful information to policymakers for better development of hospitals on PPP model.

There are total six indicators that are defined as patients’ financial burden, basing on the policy of “indicators of medical quality management and control on the third level large general hospital (2011 edition),” issued by Chinese Government. In total, 23 potentially influencing factors of patients’ financial burden for hospital on PPP model were chosen from the above policy. The five-year (2007‒2011) data for the above 29 indicators come from statistic department of hospital on PPP model. Grey relational analysis (GRA) was applied to analyze the influencing factors of patients’ financial burden for hospital on PPP model.

A clear rank of influencing factors of patients’ financial burden is obtained and suggestions are provided from results of GRA, which provide reference for policymakers of hospital on PPP model. The five main influencing factors of patients’ financial burden for hospital on PPP model, in sequence, are rescuing critical ill patients on emergency, rescuing critical ill inpatients, inpatient bed occupancy rate, working days per bed and medical building area.

The study on the influencing factors of patients’ financial burden for hospital on PPP model not only provides decision-making for policymaker of hospital and controlling of medical expenditure but also contributes to release patients’ financial burden for hospitals on PPP model.

Big data marketing analytics (BDMA) has been discovered to be a key contributing factor to developing necessary marketing capabilities. This research aims to investigate the impact of the technology and information quality of BDMA on the critical marketing capabilities by differentiating between firms with low and high perceived market performance.

The responses were collected from marketing professionals familiar with BDMA in North America (N = 236). The analysis was done with partial least squares-structural equation modelling (PLS-SEM).

The results indicated positive and significant relationships between the information and technology quality as exogenous constructs and the endogenous constructs of the marketing capabilities of marketing planning, implementation and customer relationship management (CRM) with mainly moderate effect sizes. Differences in the path coefficients in the structural model were detected between firms with low and high perceived market performance.

This research indicates the critical role of technology and information quality in developing marketing capabilities. The study discovered heterogeneity in the sample population when using the low and high perceived market performance as the source of potential heterogeneity, the presence of which would likely cause a threat to the validity of the results in case heterogeneity is not considered. Thus, this research builds on previous research by considering this issue.