OntoSDM: an approach to improve quality on spatial data mining algorithms

The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.

Cross-Layer Packet Size Optimization for Wireless Terrestrial, Underwater, and Underground Sensor Networks

In this paper, a cross-layer solution for packet size optimization in wireless sensor networks (WSN) is introduced such that the effects of multi-hop routing, the broadcast nature of the physical wireless channel, and the effects of error control techniques are captured. A key result of this paper is that contrary to the conventional wireless networks, in wireless sensor networks, longer packets reduce the collision probability. Consequently, an optimization solution is formalized by using three different objective functions, i.e., packet throughput, energy consumption, and resource utilization. Furthermore, the effects of end-to-end latency and reliability constraints are investigated that may be required by a particular application. As a result, a generic, cross-layer optimization framework is developed to determine the optimal packet size in WSN. This framework is further extended to determine the optimal packet size in underwater and underground sensor networks. From this framework, the optimal packet sizes under various network parameters are determined.

Feasibility Study of Solar Driven Underground Cooling System

In the United States the peak electrical use occurs during the summer. In addition, the building sector consumes a major portion of the annual electrical energy consumption. One of the main energy consuming components in the building sector is the Heating, Ventilation, and Air-Conditioning (HVAC) systems. This research studies the feasibility of implementing a solar driven underground cooling system that could contribute to reducing building cooling loads. The developed system consists of an Earth-to-Air Heat Exchanger (EAHE) coupled with a solar chimney that provides a natural cool draft to the test facility building at the Solar Energy Research Test Facility in Omaha, Nebraska. Two sets of tests have been conducted: a natural passively driven airflow test and a forced fan assisted airflow test. The resulting data of the tests has been analyzed to study the thermal performance of the implemented system. Results show that: The underground soil proved to be a good heat sink at a depth of 9.5ft, where its temperature fluctuates yearly in the range of (46.5°F-58.2°F). Furthermore, the coupled system during the natural airflow modes can provide good thermal comfort conditions that comply with ASHRAE standard 55-2004. It provided 0.63 tons of cooling, which almost covered the building design cooling load (0.8 tons, extreme condition). On the other hand, although the coupled system during the forced airflow mode could not comply with ASHRAE standard 55-2004, it provided 1.27 tons of cooling which is even more than the building load requirements. Moreover, the underground soil experienced thermal saturation during the forced airflow mode due to the oversized fan, which extracted much more airflow than the EAHE ability for heat dissipation and the underground soil for heat absorption. In conclusion, the coupled system proved to be a feasible cooling system, which could be further improved with a few design recommendations.

Bills Favor Mining and Threaten Conservation of Brazilian Merganser (Mergus octosetaceus) at Serra da Canastra National Park, Minas Gerais, Brazil

Serra da Canastra National Park (SCNP) is one of the most important protected areas in the Cerrado biome. Despite its importance to the conservation of rare and endangered species like Brazilian Merganser, two bills were approved in 2010 by Brazil's Chamber of Deputies aiming to reduce SCNP's official boundaries and to transform some of its parts into an Environmental Protection Area (EPA). We evaluated whether such changes would facilitate mining areas to be legally exploited within the park's area, and if those mining areas would represent a threat to Brazilian Merganser populations at SCNP. Results showed that 55% of the mining areas currently within the National Park will be located within the new EPA, and six hydrographic micro-basins inhabited by Brazilian Merganser could be affected by environmental impacts caused by mineral exploitation in those areas. For these reasons, we recommend the two bills be refused at the Federal Senate.

Soil compressibility and least limiting water range of a constructed soil under cover crops after coal mining in Southern Brazil

The use of cover crops affects the support capacity of soil and least limiting water range to crop growth. The objective of this study was to quantify preconsolidation pressure (sigma(p)), compression index (CI) and least limiting water range (LLWR) of a reclaimed coal mining soil under different cover crops, in Candiota, RS, Brazil. In the experiment, with randomized blocks design and four replicates, the following cover crops (treatments) were evaluated: Hemarthria altissima (Poir.) Stapf & C.E. Hubbard, treatment 1 (T1), Paspalum notatum Flugge, treatment 4 (T4), Cynodon dactilon (L) Pers., treatment 5 (T5), control Brachiaria brizantha (Hochst.) Stapf, treatment 7 (T7) and without cover crop treatment 8 (reference treatment, T8). Soil compression and least limiting water range were evaluated with undisturbed samples at a depth of 0.00-0.05 m. In order to evaluate parameters of soil compressibility, the soil samples were saturated with water and subjected to -10 kPa matric potential and then submitted to a uniaxial compression test under the following pressures: 25, 50, 100, 200, 400, 800 and 1600 kPa. Cover crops decreased the preconsolidation pressure of constructed soils after coal mining and the greatest soil reclamation was obtained with the H. altissima cover crop, where the lowest degree of soil compactness and soil load capacity were observed. Soils cultivated under H. altissima or B. brizantha presented the highest least limiting water range and these two cover crops generated similar soil critical bulk density obtained by least limiting water range and soil load support capacity. (C) 2012 Elsevier B.V. All rights reserved.

Potential of a neutrino detector in the ANDES underground laboratory for geophysics and astrophysics of neutrinos

The construction of the Agua Negra tunnels that will link Argentina and Chile under the Andes, the world's longest mountain range, opens the possibility of building the first deep underground laboratory in the Southern Hemisphere. This laboratory has the acronym ANDES (Agua Negra Deep Experiment Site) and its overburden could be as large as similar to 1.7 km of rock, or 4500 mwe, providing an excellent low background environment to study physics of rare events like the ones induced by neutrinos and/or dark matter. In this paper we investigate the physics potential of a few kiloton size liquid scintillator detector, which could be constructed in the ANDES laboratory as one of its possible scientific programs. In particular, we evaluate the impact of such a detector for the studies of geoneutrinos and Galactic supernova neutrinos, assuming a fiducial volume of 3 kilotons as a reference size. We emphasize the complementary roles of such a detector to the ones of the Northern Hemisphere neutrino facilities, given the advantages of its geographical location.

Determination of trace elements in bovine semen samples by inductively coupled plasma mass spectrometry and data mining techniques for identification of bovine class

The reproductive performance of cattle may be influenced by several factors, but mineral imbalances are crucial in terms of direct effects on reproduction. Several studies have shown that elements such as calcium, copper, iron, magnesium, selenium, and zinc are essential for reproduction and can prevent oxidative stress. However, toxic elements such as lead, nickel, and arsenic can have adverse effects on reproduction. In this paper, we applied a simple and fast method of multi-element analysis to bovine semen samples from Zebu and European classes used in reproduction programs and artificial insemination. Samples were analyzed by inductively coupled plasma spectrometry (ICP-MS) using aqueous medium calibration and the samples were diluted in a proportion of 1:50 in a solution containing 0.01% (vol/vol) Triton X-100 and 0.5% (vol/vol) nitric acid. Rhodium, iridium, and yttrium were used as the internal standards for ICP-MS analysis. To develop a reliable method of tracing the class of bovine semen, we used data mining techniques that make it possible to classify unknown samples after checking the differentiation of known-class samples. Based on the determination of 15 elements in 41 samples of bovine semen, 3 machine-learning tools for classification were applied to determine cattle class. Our results demonstrate the potential of support vector machine (SVM), multilayer perceptron (MLP), and random forest (RF) chemometric tools to identify cattle class. Moreover, the selection tools made it possible to reduce the number of chemical elements needed from 15 to just 8.

Glandular trichomes on aerial and underground organs in Chrysolaena species (Vernonieae - Asteraceae): Structure, ultrastructure and chemical composition

Although the occurrence of glandular trichomes is frequently reported for aerial vegetative organs, many questions still remain opened about the presence of such trichomes in underground systems. Here, we present, for the first time, a comparative study concerning the structure, ultrastructure and chemical aspects of both, the aerial and underground glandular trichomes of two different Chrysolaena species, C obovata and C platensis. Glandular trichomes (GTs) were examined using LM, SEM, and TEM and also analyzed by GC-MS and HPLC coupled to UV/DAD and HR-ESI-MS (HPLC-UV-MS). In both aerial (leaf and bud) and underground (rhizophore) organs, the GTs are multicellular, biseriate and formed by five pairs of cells: a pair of support cells, a pair of basal cells, and three pairs of secreting cells. These secreting cells have, at the beginning of secretory process, abundance of smooth ER. The same classes of secondary metabolites are biosynthesized and stored in both aerial and underground GTs of C platensis and C obovata. These GTs from aerial and underground organs have similar cellular and sub-cellular anatomy, however the belowground trichomes show a higher diversity of compounds when compared to those from the leaves. We also demonstrate by means of HPLC-UV-DAD that the sesquiterpene lactones are located inside the trichomes and that hirsutinolides are not artifacts. (C) 2012 Elsevier GmbH. All rights reserved.

Multi-element determination in Brazilian honey samples by inductively coupled plasma mass spectrometry and estimation of geographic origin with data mining techniques

Multi-element analysis of honey samples was carried out with the aim of developing a reliable method of tracing the origin of honey. Forty-two chemical elements were determined (Al, Cu, Pb, Zn, Mn, Cd, Tl, Co, Ni, Rb, Ba, Be, Bi, U, V, Fe, Pt, Pd, Te, Hf, Mo, Sn, Sb, P, La, Mg, I, Sm, Tb, Dy, Sd, Th, Pr, Nd, Tm, Yb, Lu, Gd, Ho, Er, Ce, Cr) by inductively coupled plasma mass spectrometry (ICP-MS). Then, three machine learning tools for classification and two for attribute selection were applied in order to prove that it is possible to use data mining tools to find the region where honey originated. Our results clearly demonstrate the potential of Support Vector Machine (SVM), Multilayer Perceptron (MLP) and Random Forest (RF) chemometric tools for honey origin identification. Moreover, the selection tools allowed a reduction from 42 trace element concentrations to only 5. (C) 2012 Elsevier Ltd. All rights reserved.

Underground leaves of Philcoxia trap and digest nematodes

The recently described genus Philcoxia comprises three species restricted to well lit and low-nutrient soils in the Brazilian Cerrado. The morphological and habitat similarities of Philcoxia to those of some carnivorous plants, along with recent observations of nematodes over its subterranean leaves, prompted the suggestion that the genus is carnivorous. Here we report compelling evidence of carnivory in Philcoxia of the Plantaginaceae, a family in which no carnivorous members are otherwise known. We also document both a unique capturing strategy for carnivorous plants and a case of a plant that traps and digests nematodes with underground adhesive leaves. Our findings illustrate how much can still be discovered about the origin, distribution, and frequency of the carnivorous syndrome in angiosperms and, more generally, about the diversity of nutrient-acquisition mechanisms that have evolved in plants growing in severely nutrient-impoverished environments such as the Brazilian Cerrado, one of the world's 34 biodiversity hotspots.

EFFICIENT FAULT LOCATION IN UNDERGROUND DISTRIBUTION SYSTEMS THROUGH OPTIMUM-PATH FOREST

In this article we propose an efficient and accurate method for fault location in underground distribution systems by means of an Optimum-Path Forest (OPF) classifier. We applied the time domains reflectometry method for signal acquisition, which was further analyzed by OPF and several other well-known pattern recognition techniques. The results indicated that OPF and support vector machines outperformed artificial neural networks and a Bayesian classifier, but OPF was much more efficient than all classifiers for training, and the second fastest for classification.

Preimplantation development regulatory pathway construction through a text-mining approach

Background: The integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms. Results: In this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements. Conclusions: The generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as “seeds” for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.

MR-Radix: a multi-relational data mining algorithm

Abstract Background Once multi-relational approach has emerged as an alternative for analyzing structured data such as relational databases, since they allow applying data mining in multiple tables directly, thus avoiding expensive joining operations and semantic losses, this work proposes an algorithm with multi-relational approach. Methods Aiming to compare traditional approach performance and multi-relational for mining association rules, this paper discusses an empirical study between PatriciaMine - an traditional algorithm - and its corresponding multi-relational proposed, MR-Radix. Results This work showed advantages of the multi-relational approach in performance over several tables, which avoids the high cost for joining operations from multiple tables and semantic losses. The performance provided by the algorithm MR-Radix shows faster than PatriciaMine, despite handling complex multi-relational patterns. The utilized memory indicates a more conservative growth curve for MR-Radix than PatriciaMine, which shows the increase in demand of frequent items in MR-Radix does not result in a significant growth of utilized memory like in PatriciaMine. Conclusion The comparative study between PatriciaMine and MR-Radix confirmed efficacy of the multi-relational approach in data mining process both in terms of execution time and in relation to memory usage. Besides that, the multi-relational proposed algorithm, unlike other algorithms of this approach, is efficient for use in large relational databases.

QuMinS: fast and scalable querying, mining and summarizing multi-modal databases

Given a large image set, in which very few images have labels, how to guess labels for the remaining majority? How to spot images that need brand new labels different from the predefined ones? How to summarize these data to route the user’s attention to what really matters? Here we answer all these questions. Specifically, we propose QuMinS, a fast, scalable solution to two problems: (i) Low-labor labeling (LLL) – given an image set, very few images have labels, find the most appropriate labels for the rest; and (ii) Mining and attention routing – in the same setting, find clusters, the top-'N IND.O' outlier images, and the 'N IND.R' images that best represent the data. Experiments on satellite images spanning up to 2.25 GB show that, contrasting to the state-of-the-art labeling techniques, QuMinS scales linearly on the data size, being up to 40 times faster than top competitors (GCap), still achieving better or equal accuracy, it spots images that potentially require unpredicted labels, and it works even with tiny initial label sets, i.e., nearly five examples. We also report a case study of our method’s practical usage to show that QuMinS is a viable tool for automatic coffee crop detection from remote sensing images.

Tuzla City (BiH): an example of geohazard induced by salt extraction

Salt deposits characterize the subsurface of Tuzla (BiH) and made it famous since the ancient times. Archeological discoveries demonstrate the presence of a Neolithic pile-dwelling settlement related to the existence of saltwater springs that contributed to make the most of the area a swampy ground. Since the Roman times, the town is reported as “the City of Salt deposits and Springs”; "tuz" is the Turkish word for salt, as the Ottomans renamed the settlement in the 15th century following their conquest of the medieval Bosnia (Donia and Fine, 1994). Natural brine springs were located everywhere and salt has been evaporated by means of hot charcoals since pre-Roman times. The ancient use of salt was just a small exploitation compared to the massive salt production carried out during the 20th century by means of classical mine methodologies and especially wild brine pumping. In the past salt extraction was practised tapping natural brine springs, while the modern technique consists in about 100 boreholes with pumps tapped to the natural underground brine runs, at an average depth of 400-500 m. The mining operation changed the hydrogeological conditions enabling the downward flow of fresh water causing additional salt dissolution. This process induced severe ground subsidence during the last 60 years reaching up to 10 meters of sinking in the most affected area. Stress and strain of the overlying rocks induced the formation of numerous fractures over a conspicuous area (3 Km2). Consequently serious damages occurred to buildings and infrastructures such as water supply system, sewage networks and power lines. Downtown urban life was compromised by the destruction of more than 2000 buildings that collapsed or needed to be demolished causing the resettlement of about 15000 inhabitants (Tatić, 1979). Recently salt extraction activities have been strongly reduced, but the underground water system is returning to his natural conditions, threatening the flooding of the most collapsed area. During the last 60 years local government developed a monitoring system of the phenomenon, collecting several data about geodetic measurements, amount of brine pumped, piezometry, lithostratigraphy, extension of the salt body and geotechnical parameters. A database was created within a scientific cooperation between the municipality of Tuzla and the city of Rotterdam (D.O.O. Mining Institute Tuzla, 2000). The scientific investigation presented in this dissertation has been financially supported by a cooperation project between the Municipality of Tuzla, The University of Bologna (CIRSA) and the Province of Ravenna. The University of Tuzla (RGGF) gave an important scientific support in particular about the geological and hydrogeological features. Subsidence damage resulting from evaporite dissolution generates substantial losses throughout the world, but the causes are only well understood in a few areas (Gutierrez et al., 2008). The subject of this study is the collapsing phenomenon occurring in Tuzla area with the aim to identify and quantify the several factors involved in the system and their correlations. Tuzla subsidence phenomenon can be defined as geohazard, which represents the consequence of an adverse combination of geological processes and ground conditions precipitated by human activity with the potential to cause harm (Rosenbaum and Culshaw, 2003). Where an hazard induces a risk to a vulnerable element, a risk management process is required. The single factors involved in the subsidence of Tuzla can be considered as hazards. The final objective of this dissertation represents a preliminary risk assessment procedure and guidelines, developed in order to quantify the buildings vulnerability in relation to the overall geohazard that affect the town. The historical available database, never fully processed, have been analyzed by means of geographic information systems and mathematical interpolators (PART I). Modern geomatic applications have been implemented to deeply investigate the most relevant hazards (PART II). In order to monitor and quantify the actual subsidence rates, geodetic GPS technologies have been implemented and 4 survey campaigns have been carried out once a year. Subsidence related fractures system has been identified by means of field surveys and mathematical interpretations of the sinking surface, called curvature analysis. The comparison of mapped and predicted fractures leaded to a better comprehension of the problem. Results confirmed the reliability of fractures identification using curvature analysis applied to sinking data instead of topographic or seismic data. Urban changes evolution has been reconstructed analyzing topographic maps and satellite imageries, identifying the most damaged areas. This part of the investigation was very important for the quantification of buildings vulnerability.