A speciation-based bilevel niching method for multimodal truss design problems

Truss design is a well-known structural optimization problem that has important practical applications in various fields. Truss design problems are typically multimodal by nature, meaning that it offers multiple optimal solutions concerning the topology (combinatorial optimization problem) and/or sizes (continuous optimization problem) of the members, but they are evaluated to have similar or equally good objective function values. From a practical standpoint, it is desirable to find as many alternative designs as possible, rather than finding a single design, as often practiced. Several techniques based on classical and metaheuristic optimization methods have been developed for simultaneous optimization of topology and size of a truss. However, all these methods unable to find multiple topologies and their corresponding size solutions in a single run. A few metaheuristics incorporating niching techniques have been developed for finding multiple topologies for the truss design problem, but these studies ignored the fact that for each known topology, multiple design solutions in terms of size can be found. To address this issue, this paper proposes a bi-level truss formulation and subsequently a speciation-based bilevel niching method (BiL-NM) using such a formulation. The BiL-NM consists of a modified SPSO niching method which is robust to find multiple topologies and a canonical PSO for their corresponding size solutions. Extensive empirical studies are carried out to analyze the accuracy, robustness, and efficiency of the BiL-NM. The results confirm that the proposed BiL-NM is superior in all these three aspects over the state-of-the-art methods on several low to high-dimensional truss design problems.

     

Model-based hierarchical clustering with Bregman divergences and Fishers mixture model: application to depth image analysis

Model-based clustering is a method that clusters data with an assumption of a statistical model structure. In this paper, we propose a novel model-based hierarchical clustering method for a finite statistical mixture model based on the Fisher distribution. The main foci of the proposed method are: (a) provide efficient solution to estimate the parameters of a Fisher mixture model (FMM); (b) generate a hierarchy of FMMs and (c) select the optimal model. To this aim, we develop a Bregman soft clustering method for FMM. Our model estimation strategy exploits Bregman divergence and hierarchical agglomerative clustering. Whereas, our model selection strategy comprises a parsimony-based approach and an evaluation graph-based approach. We empirically validate our proposed method by applying it on simulated data. Next, we apply the method on real data to perform depth image analysis. We demonstrate that the proposed clustering method can be used as a potential tool for unsupervised depth image analysis.     

Geriatric Care during Public Health Emergencies: Lessons Learned from Novel Corona Virus Disease (COVID-19) Pandemic

ABSTRACT

Geriatric care in public health emergencies is a serious concern, while, high case-fatalities among older adults across the globe in COVID-19 pandemic implies lack of preparedness. Most of the countries irrespective of developing and developed one enormously struggling because of an inchoate response system ignorant of geriatric health needs. Therefore, a robust approach is highly essential that requires an integrated emergency preparedness by addressing geriatric care.     

Evaluating Quality of Life in Urban Areas (Case Study: Noorabad City, Iran)

Quality of urban life (QOUL) has become an important field within urban studies. The increased level of attention to this topic is due to the increasing importance of QoL studies in monitoring public policies and in the role they can play as effective tools in urban management and planning. The main objective of this study is to measure the QOUL in the town of Noorabad in Iran, using subjective and objective indicators. In addition to secondary datasets, this study relies on a perception survey of households in the selected city. Based on an 11-point Likert scale, the mean of the overall life satisfaction of the respondents was found to be 6.06. At the same time, it has been found that satisfaction from employment opportunities is lowest among all other indicators. The comparison between the subjective and objective QoL in Noorabad indicated that 25 % of the households are in a state of well-being, 30.1 % are in a state of deprivation, while 24.4 % are in dissonance and 20.4 % are in a state of adaptation. Although correlation between objective and subjective dimensions of the QoL has not been found to be high, in general, the findings of this study reveal the importance of simultaneous studying of both objective and subjective dimensions of QoL. Results and findings of this study will be useful in designing and implementing future policies in the town of Noorabad.     

Shrinkage estimation in lognormal regression model for censored data

We introduce in this paper, the shrinkage estimation method in the lognormal regression model for censored data involving many predictors, some of which may not have any influence on the response of interest. We develop the asymptotic properties of the shrinkage estimators (SEs) using the notion of asymptotic distributional biases and risks. We show that if the shrinkage dimension exceeds two, the asymptotic risk of the SEs is strictly less than the corresponding classical estimators. Furthermore, we study the penalty (LASSO and adaptive LASSO) estimation methods and compare their relative performance with the SEs. A simulation study for various combinations of the inactive predictors and censoring percentages shows that the SEs perform better than the penalty estimators in certain parts of the parameter space, especially when there are many inactive predictors in the model. It also shows that the shrinkage and penalty estimators outperform the classical estimators. A real-life data example using Worcester heart attack study is used to illustrate the performance of the suggested estimators.     

SHRINKAGE, PRETEST AND ABSOLUTE PENALTY ESTIMATORS IN PARTIALLY LINEAR MODELS

We consider a partially linear model in which the vector of coefficients β in the linear part can be partitioned as ( β ₁, β ₂) , where β ₁ is the coefficient vector for main effects (e.g. treatment effect, genetic effects) and β ₂ is a vector for ‘nuisance’ effects (e.g. age, laboratory). In this situation, inference about β ₁ may benefit from moving the least squares estimate for the full model in the direction of the least squares estimate without the nuisance variables (Steinian shrinkage), or from dropping the nuisance variables if there is evidence that they do not provide useful information (pretesting). We investigate the asymptotic properties of Stein‐type and pretest semiparametric estimators under quadratic loss and show that, under general conditions, a Stein‐type semiparametric estimator improves on the full model conventional semiparametric least squares estimator. The relative performance of the estimators is examined using asymptotic analysis of quadratic risk functions and it is found that the Stein‐type estimator outperforms the full model estimator uniformly. By contrast, the pretest estimator dominates the least squares estimator only in a small part of the parameter space, which is consistent with the theory. We also consider an absolute penalty‐type estimator for partially linear models and give a Monte Carlo simulation comparison of shrinkage, pretest and the absolute penalty‐type estimators. The comparison shows that the shrinkage method performs better than the absolute penalty‐type estimation method when the dimension of the β ₂ parameter space is large.     

Development NGOs and Political Participation of the Poor in Bangladesh and Nepal

This paper examines the role of development NGOs (nongovernmental organizations) in furthering the political participation of the poor, with data from Bangladesh and Nepal. The topic is discussed from three aspects: the role of NGOs in prodemocracy movements, the issues raised by antiglobalization movements, and the extent of NGO involvement in local government elections. The paper draws on fieldwork conducted in two villages—one in Bangladesh and the other in Nepal. It is concluded that development NGOs tend to contribute more to elite interests than to the democratic political participation of the poor.