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Clustering ensemble indicates to an approach in which a number of (usually weak) base clusterings are performed and their consensus clustering is used as the final clustering. Knowing democratic decisions are better than dictatorial decisions, it seems clear and simple that ensemble (here, clustering ensemble) decisions are better than simple model (here, clustering) decisions. But it is not guaranteed that every ensemble is better than a simple model. An ensemble is considered to be a better ensemble if their members are valid or high-quality and if they participate according to their qualities in constructing consensus clustering. In this paper, we propose a clustering ensemble framework that uses a simple clustering algorithm based on kmedoids clustering algorithm. Our simple clustering algorithm guarantees that the discovered clusters are valid. From another point, it is also guaranteed that our clustering ensemble framework uses a mechanism to make use of each discovered cluster according to its quality. To do this mechanism an auxiliary ensemble named reference set is created by running several kmeans clustering algorithms.

In this paper, we introduce an approach to discriminate unconventional images and their intelligent filtering. As the target data to this issue are huge and consequently, a handling approach might potentially be a very time consuming one, one of the major challenges to be solved by this introduced approach is its ability for dealing with large-scale datasets. A deep neural network might be a good option to resolve this challenge. It can provide a good accuracy while dealing with huge databases. In the proposed approach, the new architecture is introduced using a combination of AlexNet and LeNet architectures. It uses convolutional, polling and fully-connected layers. The results are tested on two large-scale datasets. These tests show that the introduced architecture is more accurate than the other recently developed methods in identifying unconventional images. The proposed approach may be used in different applications such as intelligent filtering of unconventional images or medical images analysis.

Aging is associated with changes in brain functional patterns as well as cognition. The present research sought to investigate longitudinal changes in whole brain functional connectivity strength (FCS) and cognitive performance scores in very old cognitively unimpaired individuals. We studied 34 cognitively normal elderly individuals at both baseline and 4-year follow-up (baseline age = 78 ± 3.14 years) with resting-state functional magnetic resonance imaging (r-fMRI), structural MRI scans, and neuropsychological assessments conducted. Voxel-based whole brain FCS was calculated and we found that bilateral superior parietal and medial frontal regions showed decreased FCS, while the supplementary motor area (SMA) and insula showed increased FCS with age, along with a decrease in bilateral prefrontal cortical thickness. The changes of FCS in left precuneus were associated with an aging-related decline in global cognition. Taken together, our results suggest changes in FCS with aging with the precuneus as a hub and this may underlie changes in global cognition that accompany aging. These findings help better understand the normal aging mechanism.

The alkali activation of mine tailings is of interest to diminish the impoundment storage of large waste stream from mining industry. However, most of the mine tailings, like phosphate mine tailings generated in Finland, are rather inert and need pre-treatment to induce the reactivity for alkali activation. In this work, mechanochemical treatment was conducted to improve the reactivity of phosphate mine tailings. The ground specimens were subjected to the crystal structural analysis of X-Ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and thermal analyses by Thermogravimetry/Differential Thermal Analysis (TG/DTA), showing the increment of amorphous content and structural degradation as a function of grinding time. The subsequent alkaline reactivity test illustrated incremental alkaline dissolution of Si, Al and K and a schematic diagram of altered phlogopite structure (sources of aluminosilicates in tailings) was also proposed. Additionally, the mineralogical composition of individual particles was carried out by mineral liberation analysis (MLA), thereby evaluating the influence of pre-treatment on the mineralogy of tailings. The results indicate profound micromorphological changes and structural cleavage of the precursor due to grinding, which strongly increase alkaline reactivity.

Geopolymers have not been extensively employed as catalytic materials despite of their zeolite-resembling Si–Al structure. Geopolymerization offers a novel way for preparation of catalysts and possibility to use waste or industrial side-stream derived raw material as a resource for catalyst manufacturing. This work concentrates on metakaolin-based geopolymer materials that were prepared, characterized and tested as alternative environmentally benign catalyst supports for the oxidation of dichloromethane. The geopolymers with the Si/Al ratio of 1.5 were modified with HCl to increase their specific surface area, which is important in catalytic applications. Significant increase in specific surface areas was achieved via leaching of Na and Al from the geopolymer structure. Highest specific surface areas achieved for calcined geopolymers were over 500 m²g⁻¹. Use of acid concentrations higher than 1 M led to the dehydroxylation of the geopolymer. Dehydroxylation decreased the total acidity of geopolymer through the loss of the Brønsted acid sites, which are responsible for the adsorption of dichloromethane in the beginning of the catalytic reaction. Absence of Brønsted acid sites was observed by the formation of CH₂O as the only reaction intermediate. The best result in the dichloromethane oxidation was found with the geopolymer treated with 1 M HCl. Without using any additional active sites, the maximum dichloromethane conversion of 90% was reached at 525 °C with the maximum HCl yield of 83%. This result indicates the good potential of modified geopolymers to be used as catalyst supports in environmental applications.

The main objective of this paper was to investigate the alkali activation of mine tailings (MT) after mechanochemical activation and the effect of metakaolin (MK) addition. Finnish mica-rich tailings from a phosphate mine were studied as precursors for alkali-activated materials (AAM) with a potential application as a substitute for ordinary Portland cement (OPC). The principal physical properties (water absorption, apparent porosity and unconfined compressive strength) were measured for samples containing 30% to 70% tailings. Zeolite phases such as natrolite and cancrinite were observed and the formation of C-(N)-A-S-H¹ and N-A-S-H gels was identified by XRD, DRIFT, FESEM-EDS and NMR technologies. A life cycle assessment (LCA) was conducted on specimens in comparison to OPC. This work indicated that phosphate MT can be recycled through alkali activation with lower CO₂ emission compared to all-metakaolin geopolymers and that the binder phase formed at the most promising tailings contents (60– 70%) was C-(N)-A-S-H gel.

Mining activity is inevitable in human societies, and thus, disposal of mining waste in a proper and effective way is crucial to preserving our environment. In this context, studies on the reuse potential for mine tailings in the construction sector are booming. However, utilizing tailings as binder material is complicated due to the high variation in mineralogical composition and the low reactivity of these materials. In this study, an attempt was made to understand the effect of mechanical treatment on silicate mine tailings in order to improve their properties for use as a sole precursor in alkali-activated binders. Two different silicate tailings from Finland were studied: one rich in tremolite, which is high in magnesium (HM tailings) and one rich in anorthite and epidote, which is high in aluminum (HA tailings). Interestingly, grinding activity performed at different durations affected the properties of the tailings with various intensities, including their mineralogical and physical properties and characteristics and, thus the reactivity of tailings. Tremolite does not respond to milling for longer durations, and layered anorthite was easily distorted by the mechanical disturbance. Irrespective of the type of tailings, the compressive strength of alkali-activated milled tailings increased with an increase in grinding time from 1 to 16 min. However, the percentage of compressive strength increase varied with the type of tailings and their mineralogy.