Academic literature on the topic 'Intercluster Similarity'

Reference to geographic scale and geographic space representation are characteristics of geospatial data. This work has discussed two issues related to satellite image data, namely huge size and mixed pixels. In clustering, an unsupervised classification and a set of similar objects are grouped together based on the similarity measures. The similarity between intracluster objects is high, whereas the similarity between intercluster objects is low. This paper proposes a clustering technique called spatial rough k-means that classifies the mixed pixels based on their spatial neighbourhood relationship. The authors compared the performance of different state-of-the-art clustering algorithms with that of proposed algorithms for image partitioning and map-reduce methods. The results show that the proposed algorithm has produced clusters of better quality than state-of-the-art algorithms in both the approaches used for handling the vast input data size. Experiments conducted on Landsat-TM 5 data of Delhi region demonstrate the effectiveness of the proposed work.

Abstract An ensemble of 72 Weather Research and Forecasting (WRF) Model simulations is evaluated to examine the relationship between the track of Hurricane Sandy (2012) and its structural evolution. Initial and boundary conditions are obtained from ECMWF and GEFS ensemble forecasts initialized at 0000 UTC 25 October. The 5-day WRF simulations are initialized at 0000 UTC 27 October, 48 h into the global model forecasts. Tracks and cyclone phase space (CPS) paths from the 72 simulations are partitioned into 6 clusters using regression mixture models; results from the 4 most populous track clusters are examined. The four analyzed clusters vary in mean landfall location from southern New Jersey to Maine. Extratropical transition timing is the clearest difference among clusters; more eastward clusters show later Sandy–midlatitude trough interaction, warm seclusion formation, and extratropical transition completion. However, the intercluster variability is much smaller when examined relative to the landfall time of each simulation. In each cluster, a short-lived warm seclusion forms and contracts through landfall while lower-tropospheric potential vorticity concentrates at small radii. Despite the large-scale similarity among the clusters, relevant intercluster differences in landfall-relative extratropical transition are observed. In the easternmost cluster the Sandy–trough interaction is least intense and the warm seclusion decays the most by landfall. In the second most eastward cluster Sandy retains the most intact warm seclusion at landfall because of a slightly later (relative to landfall) and weaker trough interaction compared to the two most westward clusters. Nevertheless, the remarkably similar large-scale evolution of Sandy among the four clusters indicates the high predictability of Sandy’s warm seclusion extratropical transition before landfall.

Envenoming byEchissaw-scaled viper is the leading cause of death and morbidity in Africa due to snake bite. Despite its medical importance, there have been few investigations into the toxin composition of the venom of this viper. Here, we report the cloning of cDNA sequences encoding four groups or isoforms of the haemostasis-disruptive Serine protease proteins (SPs) from the venom glands ofEchis ocellatus. All these SP sequences encoded the cysteine residues scaffold that form the 6-disulphide bonds responsible for the characteristic tertiary structure of venom serine proteases. All theEchis ocellatus EoSPgroups showed varying degrees of sequence similarity to published viper venom SPs. However, these groups also showed marked intercluster sequence conservation across them which were significantly different from that of previously published viper SPs. Because viper venom SPs exhibit a high degree of sequence similarity and yet exert profoundly different effects on the mammalian haemostatic system, no attempt was made to assign functionality to the newEchis ocellatus EoSPson the basis of sequence alone. The extraordinary level of interspecific and intergeneric sequence conservation exhibited by theEchis ocellatus EoSPsand analogous serine proteases from other viper species leads us to speculate that antibodies to representative molecules should neutralise (that we will exploit, by epidermal DNA immunization) the biological function of this important group of venom toxins in vipers that are distributed throughout Africa, the Middle East, and the Indian subcontinent.

In the data mining of road networks, trajectory clustering of moving objects plays an important role in many applications. Most existing algorithms for this problem are based on every position point in a trajectory and face a significant challenge in dealing with complex and length-varying trajectories. This paper proposes a grid-based whole trajectory clustering model (GBWTC) in road networks, which regards the trajectory as a whole. In this model, we first propose a trajectory mapping algorithm based on grid estimation, which transforms the trajectories in road network space into grid sequences in grid space and forms grid trajectories by recognizing and eliminating redundant, abnormal, and stranded information of grid sequences. We then design an algorithm to extract initial clustering centers based on density weight and improve a shape similarity measuring algorithm to measure the distance between two grid trajectories. Finally, we dynamically allocate every grid trajectory to the best clusters by the nearest neighbor principle and an outlier function. For the evaluation of clustering performance, we establish a clustering criterion based on the classical Silhouette Coefficient to maximize intercluster separation and intracluster homogeneity. The clustering accuracy and performance superiority of the proposed algorithm are illustrated on a real-world dataset in comparison with existing algorithms.

The degree of DNA banding pattern polymorphism exhibited by vancomycin-resistant Enterococcus faecium (VREM) strains isolated on a renal unit over an 11-month period was investigated. Thirty VREM strains from different patients were analyzed by pulsed-field gel electrophoresis (PFGE; with extended run and optimal pulse times), ribotyping, plasmid profile analysis, biotyping, pyrolysis mass spectrometry, and antibiogram analysis. PFGE resolved 17 banding patterns which formed four distinct clusters at the 82% similarity level. Intercluster band differences ranged from 14 to 31 bands. The strains in one cluster, which contained seven patterns that differed from each other by one to seven bands and from the common pattern by five bands, were confirmed to be a single strain by four of the five other typing methods. The strains in a second cluster with eight patterns, which differed from each other by 1 to 12 bands, contained two subclusters. This subdivision was supported by ribotyping and biotyping. However, it was unclear whether these subclusters represented distinct strains. In one strain, marked polymorphism (patterns that differed from each other by up to four bands) was observed in the ribotype pattern. This study demonstrates the high degree of DNA banding pattern polymorphism found for some strains of VREM and illustrates the complexity involved in defining such strains.

Wireless sensor networks (WSNs) are a huge number of sensors, which are distributed in area monitoring to collect important signals. WSNs are widely used in several applications such as home automation, environment, and healthcare monitoring. However, most of these applications face various difficulties due to sensor design. Therefore, the major challenge of designing WSNs is saving the energy consumed during communication and extending the network lifetime. Multicriteria Decision Analysis (MCDA) methods have been exploited for saving network energy. However, the majority of researches focus on the Cluster Head (CH) selection. In this paper, we aim to enhance the process of forwarder selection using an efficient combined multicriteria model. The proposed scheme improved the intercluster communication by controlling the distance separating CHs from the sink node. To minimize the cluster density, this work consists of activating only sensor nodes that detect enough strong signals. The activation phase presents a fault-tolerant technique to succeed in the communication process. Moreover, the proposed work is aimed at selecting the most efficient hops, which are responsible for routing data to the sink using the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. Simulation results proved that our new protocol maximized the residual energy by 15% and 25% and the network lifetime by 35% and 47% compared to the Distributed Clustering Protocol using Voting and Priority (DCPVP) and Low-Energy Adaptive Clustering Hierarchy (LEACH), respectively.

<p>Genetic Diversity of 50 Soybean Accessions Based on Ten<br />Microsatellite Markers. Chaerani, Nurul Hidayatun, and<br />Dwinita W. Utami. Soybean accessions in germplasm<br />collection have increased in number as a result of<br />exploration, introduction as well as development or release<br />of new commercial varieties. This complicates accurate and<br />reliable evaluation of an accession for purposes of utilization<br />in breeding program and discrimination of a new<br />commercial variety for purposes of plant variety protection.<br />The aims of this study were to identify the genetic diversity<br />of soybean germplasm to complement the existing<br />phenotypic database as the basis for efficient management<br />and accurate discrimination of commercial varieties, and to<br />identify potential parents for hybridizations. Fifty soybean<br />accessions consisting of 12 released varieties, 32 local<br />varieties, and 6 introductions were analyzed using<br />microsatellite DNA markers based on semi-automatic sizing<br />system. A total of 86 alleles were detected with the number<br />of alleles per locus ranged from 4 to 16. Rare alleles were<br />detected at a rate of 53% which was shown by 68% of the<br />genotypes. Informativeness of the microsatellite markers as<br />measured by the average gene diversity (D) or<br />polymorphism information content (PIC) was 0.60 and 0.58,<br />respectively. A heterozygosity level of 0.09 as detected by<br />seven loci was observed among 64% of the genotypes. The<br />average genetic distance among the genotypes was 0.56,<br />which indicated the relatively low polymorphism among the<br />analyzed soybean germplasm. Four microsatellites that<br />showed a high D or PIC value (over 0.75) were able to<br />discriminate between accession reliably. Each soybean<br />accession had different DNA microsatellite fingerprint which<br />can be used for accurate discrimination to complement the<br />previous conventional characterizations. UPGMA clustering<br />separated the 50 accessions into 10 major clusters, which<br />showed no clear pattern of clustering according to varietal<br />group or geographical origin. Genetic similarity data<br />identified five clusters and 15 genotypes with highest intercluster<br />or inter-genotype genetic distances which are<br />potential candidates to be exploited as parents in<br />hybridizations for development of new commercial varieties.</p>

Ichnogeneric classification of sauropod trackways is determined using qualitative and quantitative descriptions of morphological parameters. More recently, the validity of several of these parameters has been called into question (e.g., trackway gauge). This paper aims to test traditional and more novel landmark-based geometric morphometric (GM) analysis to describe sauropod tracks and trackways. The Courtedoux-Tchâfouè (TCH) tracksite, in NW Switzerland, has been used as a test site because it hosted several Late Jurassic sauropod track-bearing levels, over a short time period (∼40 ka), creating a time capsule of sauropod activity. Exploratory statistical analyses suggest that the TCH trackway dataset can be partitioned into clusters based on trackway parameters (e.g., width of pes angulation pattern/pes length) that demonstrate differences between trackways. Nevertheless, clustering reflected a moderate degree of intercluster similarity and a continuum in TCH trackway morphologies. The GM analysis of TCH pes impressions, from several trackways, indicates a similar morphotype and did not significantly differentiate pes tracks from various stratigraphic levels. Currently, the results indicate that neither linear nor landmark-based geometric morphometric methods strongly segregate tracks at TCH nor show a time-control (i.e., via stratigraphic level) over the short interval studied. The methods reinforce that sauropod pes impression shape is conservative and that combining morphological methods to be inclusive of sauropod trackway data is important. The TCH site demonstrates that variability may reflect morphological continuums and behavioural factors and does not unambiguously differentiate unique sauropod trackmakers. More exploration on the minimum number of trackway parameters as predictors of sauropod ichnotaxonomy is needed. Integrating complementary techniques will provide more insight and practical means of identification and delineation of sauropod tracks and their trackways.

In movement science with inertial sensor many different methodologies resolving specific aspects of movement recognition have been proposed. They are very interesting, and useful, but none of them are generally explicative of what is going on in the semantic sense. When we go down to the movement recognition/classification area (for example in Ambient Intelligence) we do not have a feasible model that can be considered generally predictive or usable for activity recognition. Also, in the field of movement recognition with inertial sensors many technological issues arise: technological diversity, calibration matters, sensor model problems, orientation and position of sensors, and a lot of numerous specificities that, with all the above aspects, and the lack of public dataset of movements sufficiently generic and semantically rich, contribute to create a strong barrier to any approach to a classification matters with wearable sensors. We have also to notice that a movement is a phenomenon explicitly or implicitly (voluntary or involuntary) controlled by brain. The individual free-will introduce a further matter when we want to temporary predict the movements looking at the close past. Pattern can change at any time when ambient, psychological context, age of the subject change. Also, pathological issues, and physiological differences and the will of the subject, introduce important differences. For all these reasons I considered that a semantical /lexical approach to movement recognition with sensors, driven by machine learning techniques could be a promising way to solve some of these challenge and problems. In this Ph.D. Thesis wearable inertial sensors has been used to classify movements, the choice of inertial sensors has been driven by technological and practical advantages, they are cheap, lightweight, and - differently from video cameras - are not prone to the hidden face, or luminance problems. The main idea is to use inertial sensor to understand what a person is doing for ambient-intelligent, healthcare, medical-sport applications. My principal concerns was to propose a method that was not centered on technology issues but on data analysis, that could be a general framework and could also create a general representation of movement,that could be useful also in other area of research, like reasoning. Inertial sensors are treated just as an example, a particular type of sensors, the method is new, reusable, algorithmically simple, net and easy to understand. Accuracy is very high outperforming the best results given in literature, reducing the error rate of 4 times.