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The purpose of this study was threefold: (1) to measure farmers' health poverty, (2) to examine the effect of health vulnerability on health poverty and (3) to identify countermeasures that may alleviate health poverty in rural China.

This study built a health poverty measurement model based on the multi-dimensional poverty framework to evaluate farmers' health vulnerability. Further, this paper used an econometric model to assess the impact of health vulnerability on health poverty. The sample for this study comprised 1,115 rice farmers from Hubei province, China.

The medical affordability poverty ratio was 17.95%, where farmers in the low-income group faced severe medical affordability poverty (27.46%). Results from the multi-dimensional analysis showed that, the health poverty ratios were 17.95 and 30.50%, respectively. Our results indicated that climate change vulnerabilities, living habits, medical facilities and medical accessibility were positively related to health poverty, whereas the regular physical examinations reduced mental health poverty.

Based on this study's findings, we proposed that: (1) to address illness-induced poverty among members of the agricultural community, national and provincial strategies and programs grounded on a multi-dimensional health poverty framework ought to be formulated and implemented, (2) mechanisms of health knowledge exchange may facilitate the improvement of farmers' health status, (3) robust and comprehensive metrics should be employed to understand and improve farmers' ability to absorb and mitigate the negative health impacts and (4) the improvement in both quality and quantity for medical facilities and medical affordability in the rural areas should be key priorities in governmental-wide initiatives.

Existing studies for alleviating poverty caused by disease mainly focus on medical service support to those economic vulnerabilities after a disease happens. However, few studies have focused on the root causes of poverty caused by disease, particularly from the preventive perspective of health vulnerability. To fill this gap, this study, therefore, proposes the health poverty index and analyzes the impact of health vulnerability on health poverty.

The purpose of this paper is to evaluate Iranian newspapers' web sites based on the criteria obtained from Alexa Search Engine using correspondence analysis.

A total of 55 newspaper web sites are selected from Iranian Magazines Information Bank (Magiran.com), the number of which, after investigating the web sites one by one, due to their print prevention, cessation or no coverage by Alexa, is decreased to 24 web sites.

Based on data obtained from Alexa, Iran newspaper has the highest traffic rank and the largest number of links among others. Bashirmazandaran newspaper has the largest number of foreign users whilst Karvakargar newspaper has no foreign users. The results of the study also show that most newspaper web sites' visitors come from the USA. Correspondence analysis classifies 24 web sites into three groupings gathered based on some common attributes.

The results of this research will be useful not only for administrators of Iranian newspapers' web sites but anyone with a need to increase usage of a web site and an interest in analyzing the use of web site which naturally includes librarians and those in charge of library web sites.

The statistical method plays an extremely important role in quantitative research studies in library and information science (LIS). The purpose of this paper is to investigate the status of statistical methods used in the field, their application areas and the temporal change patterns during a recent 15-year period.

The research papers in six major scholarly journals from 1999 to 2013 in LIS were examined. Factors including statistical methods, application areas and time period were analyzed using quantitative research methods including content analysis and temporal analysis methods.

The research studies using statistical methods in LIS have increased steadily. Statistical methods were more frequently used to solve problems in the information retrieval area than in other areas, and inferential statistical methods were used more often than predictive statistical methods and other statistical methods. Anomaly analysis on statistical method uses was conducted and four types of anomaly were specified.

The findings of this study can help educators, graduates and researchers in the field of LIS better understand the patterns and trends of the applications of statistical methods in this field, depict an overall picture of quantitative research studies in LIS from the perspective of statistical methods and discover the change patterns of statistical method applications in LIS between 1999 and 2013.

The aim of this work is to evaluate Greek newspaper websites using clustering and a number of criteria obtained from the Alexa search engine. Furthermore, a recommendation approach is proposed for matching Greek online newspapers with the profiles of potential readers. The paper presents the implementation and validation of a recommender tool that suggests to a user (based on age, education and income) an optional Greek newspaper's website to read.

A total of 25 newspaper websites were selected from the Greek information bank http://edoellada.gr. After investigating these websites one by one, this number was decreased to 16 websites due to their printing prevention, cessation or no coverage by Alexa.

Based on data obtained from Alexa, the Naftemporiki newspaper has the highest traffic rank and the Eleftherotypia newspaper the largest number of links among others. The Macedonia newspaper has the largest number of foreign users. The results of the study also show that most newspaper websites' visitors come from the UK. The expectation‐maximisation (EM) clustering algorithm classifies the 16 websites into two groups based on some common characteristics.

The proposed recommendation approach is generic because it can be applied as a recommendation solution on various types of website, such as educational or commercial. However, slight adjustments are needed depending on the nature of recommending websites.

A website administrator of an online newspaper can adapt the newspaper's features such as content and layout according to the prevailing user profile of the online newspaper. For example, a website administrator of an online newspaper whose dominant user education is “no‐college” should enable the writing style of this newspaper in a more naive way. The administrator can also add advertisements that are more suitable to readers aged between 35 and 55 years, if the most frequent age of users of this online newspaper is between 35 and 55.

The results of this research will be important not only to administrators of Greek newspaper websites but also to anyone with a need to increase the usage of a website.

Through an empirical study, this research proposes a multi-dimensional assessment method for Sustainable Building Design (SBD). This approach is adopted to investigate and evaluate the current practices of SBD and to provide a basis for refining such processes while reducing existing shortfalls. In doing so, a holistic sustainable framework for rating the sustainable performance of buildings is proposed.

To achieve the aforementioned purpose, this research (1) investigates the most current trends in SBD including the use of Building Information Modelling (BIM); (2) examines the practical issues of SBD; (3) proposes a multi-dimensional assessment method; and (4) compares 18 separate case studies in the three countries of Australia, United Kingdom and USA, as part of the SBD implementation. To compare these case studies, an additional SBD tool, Green Building Rating and Certification System (GBELS) was carefully selected and applied. Five core values of SBD were identified based on functionality, accessibility and productivity, which align with the GBELS outcomes.

This research found that, for the 18 examined buildings, the main issues in SBD in the three countries concerned environmental and ecological issues. These included the impacts of buildings on the environment, as well as issues concerning the buildings' life cycle analysis and assessment. It was also determined that energy usage, pollution reduction and climate change concerns were important inclusions in establishing these buildings, particularly in the USA.

To support the research aim, this paper explores the most innovative trends in SBD assessments including their Structural Health Monitoring (SHM), grade (stars) classification, Relative Weight (RW) and particularly GBELS. GBELS was selected for this research, since it is relatively new and there is little available literature discussing its adaptation. Accordingly, this research further evaluates the application of GBELS as a part of versatility in SBD multi-dimensional assessment method. As the basis of these tests, a total of 18 separate case studies are closely evaluated.

This paper aims to present a multi‐dimensional measure of poverty. The proposed method has been applied to the Panel Set of Belgian Households dataset for Belgium for the years between 1994 and 2000.

First, a common model is decided upon by exploratory factor analysis, and applied by confirmatory factor analysis. Cluster analysis (CA) is then used to separate the multi‐dimensional poor. Finally, the possible causes of multi‐dimensional poverty are surfaced by estimating a discrete duration model.

The proposed method reveals three dimensions of poverty: “material deprivation”, “social deprivation” and “psychological health”. Between 9 and 11 per cent of the representative sample of Belgian individuals are poor. The paper also identifies causes of poverty, including not having a job, not having the Belgian nationality, having a poor health or a disability, being lower educated, experiencing financial poverty, being divorced or widowed, living in the Walloon or Brussels regions, and having a bad psychological health.

Research implications include the use of polychoric and tetrachoric correlations as a starting point of factor analysis, as well as the combination of factor analysis and CA.

The paper proposes an alternative multi‐dimensional measure of poverty. It argues that previous measures may suffer from categorisation errors and suggests a solution to this problem. The advantages of the proposed method are that all information is used to disentangle the poor from the non‐poor and that dimensions of poverty are defined using the correlations between deprivations. Finally, the paper identifies “psychological health” as one of the dimensions of poverty.

This paper aims to provide a novel integrated fault detection method for industrial process monitoring.

A novel integrated fault detection method based on the combination of Mallat (MA) algorithm, weight-elimination (WE) algorithm, conjugate gradient (CG) algorithm and multi-dimensional Taylor network (MTN) dynamic model, namely, MA-WE-CG-MTN, is proposed in this paper. First, MA algorithm is taken as data pre-processing. Second, in virtue of approximation ability and low computation complexity owing to the simple structure of MTN, MTN dynamic models are constructed for each frequency band. Furthermore, the CG algorithm is used to discipline the model parameters and the outputs of MTN model of each frequency band are gained. Third, the authors introduce the WE algorithm to cut down the number of middle layer nodes of MTN, reducing the complexity of the network. Finally, the outputs of MTN model for each frequency band are superimposed to achieve outputs of MTN model, and fault detection is proceeded by the residual error generator based on the difference between the output of MTN model and the actual output.

The novel proposed method is used to perform fault detection for industrial process monitoring effectively, such as the Benchmark Simulation Model 1 wastewater treatment process.

The novel proposed method has generality and provides considerably improved performance and effectiveness, which is used to perform fault detection for industrial process monitoring. The proposed method has good robustness, low complexity and easy implementation.

Multi-sensor fusion in robotic dexterous hands is a hot research field. However, there is little research on multi-sensor fusion rules. This study aims to introduce a multi-sensor fusion algorithm using a motor force sensor, film pressure sensor, temperature sensor and angle sensor, which can form a consistent interpretation of grasp stability by sensor fusion without multi-dimensional force/torque sensors.

This algorithm is based on the three-finger force balance theorem, which provides a judgment method for the unknown force direction. Moreover, the Monte Carlo method calculates the grasping ability and judges the grasping stability under a certain confidence interval using probability and statistics. Based on three fingers, the situation of four- and five-fingered dexterous hand has been expanded. Moreover, an experimental platform was built using dexterous hands, and a grasping experiment was conducted to confirm the proposed algorithm. The grasping experiment uses three fingers and five fingers to grasp different objects, use the introduced method to judge the grasping stability and calculate the accuracy of the judgment according to the actual grasping situation.

The multi-sensor fusion algorithms are universal and can perform multi-sensor fusion for multi-finger rigid, flexible and rigid-soft coupled dexterous hands. The three-finger balance theorem and Monte Carlo method can better replace the discrimination method using multi-dimensional force/torque sensors.

A new multi-sensor fusion algorithm is proposed and verified. According to the experiments, the accuracy of grasping judgment is more than 85%, which proves that the method is feasible.

Aiming at the shortcomings of EEG signals generated by brain's sensorimotor region activated tasks, such as poor performance, low efficiency and weak robustness, this paper proposes an EEG signals classification method based on multi-dimensional fusion features.

First, the improved Morlet wavelet is used to extract the spectrum feature maps from EEG signals. Then, the spatial-frequency features are extracted from the PSD maps by using the three-dimensional convolutional neural networks (3DCNNs) model. Finally, the spatial-frequency features are incorporated to the bidirectional gated recurrent units (Bi-GRUs) models to extract the spatial-frequency-sequential multi-dimensional fusion features for recognition of brain's sensorimotor region activated task.

In the comparative experiments, the data sets of motor imagery (MI)/action observation (AO)/action execution (AE) tasks are selected to test the classification performance and robustness of the proposed algorithm. In addition, the impact of extracted features on the sensorimotor region and the impact on the classification processing are also analyzed by visualization during experiments.

The experimental results show that the proposed algorithm extracts the corresponding brain activation features for different action related tasks, so as to achieve more stable classification performance in dealing with AO/MI/AE tasks, and has the best robustness on EEG signals of different subjects.

As an alternative poverty analysis approach, the purpose of this paper is to map the patterns of multiple deprivation in all 13 administrative regions of Namibia using the National Household Income and Expenditure Survey data.

Unsupervised statistical learning methods including the principal component analysis, k-means clustering and bivariate analysis were applied.

The results show that the multiple deprivation approach is a useful alternative in characterising poverty dynamics in the country. Specifically, the mapping shows that other dimensions of poverty such as access to utilities and services among other things are equally useful welfare indicators as they scored higher than income and consumption on discriminant ability.

Unpacking the multi-dimensionality aspect of poverty has drawn significant attention from development economists and continues to play a major role in policy formulation for developing countries. The study recommends buttressing of conventional income poverty measures with multiple deprivation approaches for a comprehensive picture on poverty issues.