Rectangular Clusters Research Articles

Speedup of the k-Means Algorithm for Partitioning Large Datasets of Flat Points by a Preliminary Partition and Selecting Initial Centroids

Abstract A problem of partitioning large datasets of flat points is considered. Known as the centroid-based clustering problem, it is mainly addressed by the k-means algorithm and its modifications. As the k-means performance becomes poorer on large datasets, including the dataset shape stretching, the goal is to study a possibility of improving the centroid-based clustering for such cases. It is quite noticeable on non-sparse datasets that the resulting clusters produced by k-means resemble beehive honeycomb. It is natural for rectangular-shaped datasets because the hexagonal cells make efficient use of space owing to which the sum of the within-cluster squared Euclidean distances to the centroids is approximated to its minimum. Therefore, the lattices of rectangular and hexagonal clusters, consisting of stretched rectangles and regular hexagons, are suggested to be successively applied. Then the initial centroids are calculated by averaging within respective hexagons. These centroids are used as initial seeds to start the k-means algorithm. This ensures faster and more accurate convergence, where at least the expected speedup is 1.7 to 2.1 times by a 0.7 to 0.9 % accuracy gain. The lattice of rectangular clusters applied first makes rather rough but effective partition allowing to optionally run further clustering on parallel processor cores. The lattice of hexagonal clusters applied to every rectangle allows obtaining initial centroids very quickly. Such centroids are far closer to the solution than the initial centroids in the k-means++ algorithm. Another approach to the k-means update, where initial centroids are selected separately within every rectangle hexagons, can be used as well. It is faster than selecting initial centroids across all hexagons but is less accurate. The speedup is 9 to 11 times by a possible accuracy loss of 0.3 %. However, this approach may outperform the k-means algorithm. The speedup increases as both the lattices become denser and the dataset becomes larger reaching 30 to 50 times.

Performance Degradation in Static Random Access Memory of 10 nm Node FinFET Owing to Displacement Defects.

We comprehensively investigate displacement-defect-induced current and static noise margin variations in six-transistor (6T) static random access memory (SRAM) based on a 10 nm node fin field-effect transistor (FinFET) using technology computer-aided design (TCAD). Various defect cluster conditions and fin structures are considered as variables to estimate the worst-case scenario for displacement defects. The rectangular defect clusters capture more widely distributed charges at the fin top, reducing the on- and off-current. The read static noise margin (RSNM) is the most degraded in the pull-down transistor during the read operation. The increased fin width decreases the RSNM due to the gate field. The current per cross-sectional area increases when the fin height decreases, but the energy barrier lowering by the gate field is similar. Therefore, the reduced fin width and increased fin height structure suit the 10 nm node FinFET 6T SRAMs with high radiation hardness.

Automatic rape flower cluster counting method based on low-cost labelling and UAV-RGB images

BackgroundThe flowering period is a critical time for the growth of rape plants. Counting rape flower clusters can help farmers to predict the yield information of the corresponding rape fields. However, counting in-field is a time-consuming and labor-intensive task. To address this, we explored a deep learning counting method based on unmanned aircraft vehicle (UAV). The proposed method developed the in-field counting of rape flower clusters as a density estimation problem. It is different from the object detection method of counting the bounding boxes. The crucial step of the density map estimation using deep learning is to train a deep neural network that maps from an input image to the corresponding annotated density map.ResultsWe explored a rape flower cluster counting network series: RapeNet and RapeNet+. A rectangular box labeling-based rape flower clusters dataset (RFRB) and a centroid labeling-based rape flower clusters dataset (RFCP) were used for network model training. To verify the performance of RapeNet series, the paper compares the counting result with the real values of manual annotation. The average accuracy (Acc), relative root mean square error (rrMSE) and R^2 of the metrics are up to 0.9062, 12.03 and 0.9635 on the dataset RFRB, and 0.9538, 5.61 and 0.9826 on the dataset RFCP, respectively. The resolution has little influence for the proposed model. In addition, the visualization results have some interpretability.ConclusionsExtensive experimental results demonstrate that the RapeNet series outperforms other state-of-the-art counting approaches. The proposed method provides an important technical support for the crop counting statistics of rape flower clusters in field.

Effects of Plot Design on Estimating Tree Species Richness and Species Diversity

Species richness and diversity substantially affect forest structures and function and are critical indicators of sustainable forest management. Sampling surveys are widely used in forest inventories because they efficiently assess forest characteristics. However, an appropriate sample plot design is required. The objectives of this study were to evaluate the effects of plot design on estimating species richness and species diversity using a simulation. A 20 ha census plot was established in a temperate forest to obtain the true values of species richness and species diversity. One single plot design and nine cluster plot designs were evaluated. The results indicated significant differences in forest species richness and species diversity for different plot designs. The cluster plot design with a square subplot configuration (SCONFIG) and extent of ground area covered by a cluster (EGROUND) of 500 m2 exhibited the best performance (accuracy, precision) in estimating forest species richness. In contrast, a rectangular cluster plot with an EGROUND of 1000 m2 was more suitable for assessing species diversity. This study demonstrates that cluster plots outperform a single plot for evaluating species richness and species diversity in temperate forests.

Monopulse ladar: super-resolved 3D localization with Si-photonic serpentine optical phased arrays

We present an optical ranging and super-resolution object localization method, monopulse ladar, used to determine the angle of a point target in two dimensions to a few percent of an optical beam width from differential measurements of four just-resolved waveform-encoded beams while simultaneously providing target range via either coherent or incoherent coded waveform correlation. A common optical carrier is shifted by four GHz-scale tones, each modulated with distinct ranging waveforms, which when transmitted from a Si-photonic 2D wavelength-steered serpentine optical phased array (SOPA) aperture form an encoded rectangular beam cluster that propagates to and scatters from a distant point target. Superposed backscattered target returns from each beam are decoded by correlation with reference waveforms at the receiver. The angular position of the target along the two orthogonal axes is calculated from pairwise ratios of beam amplitudes, while target range is determined from the round-trip time delay of each beam as measured with a wideband correlation peak. The analysis of coherent and incoherent monopulse ladar architectures presented herein indicates that a 50-fold increase in angular resolution-to the tens of arcseconds level-of a point target located within a wide field of regard is achievable while maintaining cm-scale resolution-limited ranging using a single SOPA tile transmitter, with further improvement in angular resolution possible through arrayed tiling of SOPAs. Implementation of monopulse ladar with a SOPA aperture enables non-mechanically steered high-resolution 3D object localization in a compact, low-control complexity form factor.

Variational quantum eigensolver simulations with the multireference unitary coupled cluster ansatz: a case study of the C2v quasi-reaction pathway of beryllium insertion into a H2 molecule.

Variational quantum eigensolver (VQE)-based quantum chemical calculations have been extensively studied as a computational model using noisy intermediate-scale quantum devices. The VQE uses a parametrized quantum circuit defined through an "ansatz" to generate approximated wave functions, and the appropriate choice of an ansatz is the most important step. Because most chemistry problems focus on the energy difference between two electronic states or structures, calculating the total energies in different molecular structures with the same accuracy is essential to correctly understand chemistry and chemical processes. In this context, the development of ansatzes that are capable of describing electronic structures of strongly correlated systems accurately is an important task. Here we applied a conventional unitary coupled cluster (UCC) and a newly developed multireference unitary coupled cluster with partially generalized singles and doubles (MR-UCCpGSD) ansatzes to the quasi-reaction pathway of Be insertion into H2, LiH molecule under covalent bond dissociation, and a rectangular tetra-hydrogen cluster known as a P4 cluster; these are representative systems in which the static electron correlation effect is prominent. Our numerical simulations revealed that the UCCSD ansatz exhibits extremely slow convergence behaviour around the point where an avoided crossing occurs in the Be + H2 → BeH2 reaction pathway, resulting in a large discrepancy of the simulated VQE energy from the full-configuration interaction (full-CI) value. By contrast, the MR-UCCpGSD ansatz can give more reliable results with respect to total energy and the overlap with the full-CI solution, insisting the importance of multiconfigurational treatments in the calculations of strongly correlated systems. The MR-UCCpGSD ansatz allows us to compute the energy with the same accuracy regardless of the strength of multiconfigurational character, which is an essential property to discuss energy differences of various molecular systems.

Cluster Expansion versus Complex Formation: Coinage Metal Coordination to Silylated [Ge9] Cages

Deltahedral nine-atom tetrel element Zintl clusters are promising building blocks for the straightforward solution-based synthesis of intermetalloid clusters through the reaction with organometallic compounds. Herein we report on novel coordination sites of metal-N-heterocyclic carbene (NHC) complexes to [Ge9] clusters and unexpected cluster isomerization. We present the synthesis of a series of coinage metal-NHC complexes of silylated [Ge9] clusters [NHCiPrCu(η4-Ge9{Si(TMS)3}3)] (1; TMS = trimethylsilyl) and [NHCRM(η4-Ge9{Si(TMS)3}2)]- (2a, M = Cu, R = iPr; 3a, M = Cu, R = Mes; 4a, M = Cu, R = Dipp; 5a, M = Ag, R = Dipp; 6a, M = Au, R = Dipp), in which the coinage metals coordinate to open rectangular cluster faces and act as additional cluster vertex atoms. Besides representing promising intermediates on the way to larger intermetalloid clusters, the formation of compound 1 shows that Cu-NHC fragments also coordinate to the open-square Ge faces of the tris-silylated [Ge9] clusters, contrasting the typical interactions with triangular faces of tris-silylated [Ge9] clusters. In compounds 3a and 4a bearing bulky NHC moieties, an unusual silyl group substitution pattern is observed in contrast to 2a, which corresponds to the silyl group arrangement of other metal complexes of bis-silylated [Ge9] clusters. In this context, potential silyl group migration mechanisms are discussed.

Quantum quench dynamics in the transverse-field Ising model: A numerical expansion in linked rectangular clusters

We study quantum quenches in the transverse-field Ising model defined on different lattice geometries such as chains, two- and three-leg ladders, and two-dimensional square lattices. Starting from fully polarized initial states, we consider the dynamics of the transverse and the longitudinal magnetization for quenches to weak, strong, and critical values of the transverse field. To this end, we rely on an efficient combination of numerical linked cluster expansions (NLCEs) and a forward propagation of pure states in real time. As a main result, we demonstrate that NLCEs comprising solely rectangular clusters provide a promising approach to study the real-time dynamics of two-dimensional quantum many-body systems directly in the thermodynamic limit. By comparing to existing data from the literature, we unveil that NLCEs yield converged results on time scales which are competitive to other state-of-the-art numerical methods.

Comparison of Spatial Layout of Tall Buildings Clustered in Circular, Rectangular, and Linear Geographical Areas and Impact on Skyline

Modern cities with tall building clusters can create powerful and distinctive features on the skyline more so than those with scattered tall buildings. In terms of their role in the city, tall building clusters can improve the image of the city, provide for high population density, and distinguish the urban centers. However, the planning of tall building clusters needs to be conducted using in-depth analysis in response to the spatial context to create an attractive skyline. This research attempts to compare different layouts of tall building clusters organized in circular, rectangular, and linear geographical areas. Their impact on the skyline was determined by analyzing the visibility and height transitions of these tall building clusters. Grasshopper was used to calculate the degree of surface visibility of these tall buildings from observers in urban spaces. To quantify the height transition of the cluster, the obstructed buildings were identified and mapped on the skyline viewed from a specific viewpoint. The results showed that the linear cluster had high visibility, followed by the circular and rectangular clusters. Decreasing the heights from the center to the periphery supported the focal point of the cluster.

Half-filled stripes in a hole-doped three-orbital spin-fermion model for cuprates

Using Monte Carlo techniques, we study a three-orbital ${\mathrm{CuO}}_{2}$ spin-fermion model for copper-based high-critical-temperature superconductors that captures the charge-transfer properties of these compounds. Our studies reveal the presence of spin order in the parent compound and, more importantly, stripe spin and charge order under hole doping. Due to the $p\text{\ensuremath{-}}d$ orbital hybridization, the added holes are approximately equally distributed among the two $p$ orbitals of the oxygen atoms and the $d$ orbital of the copper atoms in the unit cell. In rectangular clusters of dimension $16\ifmmode\times\else\texttimes\fi{}4$ half-filled stripes are observed upon hole doping; namely, when ${N}_{h}=2n$ holes are introduced in the system, then $n$ vertical stripes of length 4 along the short periodic direction are formed. The original antiferromagnetic order observed in the parent compound develops a $\ensuremath{\pi}$ shift across each stripe, and the magnetic structure factor has a peak at wave vector $\mathbf{k}=(\ensuremath{\pi}\ensuremath{-}\ensuremath{\delta},\ensuremath{\pi})$ with $\ensuremath{\delta}=2\ensuremath{\pi}{N}_{h}/N=\ensuremath{\pi}{N}_{h}/2L$, where $L=16$. The electronic charge is also modulated, and the charge structure factor is maximized at $\mathbf{k}=(2\ensuremath{\delta},0)$. As electrons are removed from the system, intracell orbital nematicity with $\ensuremath{\langle}{n}_{{p}_{x}}\ensuremath{\rangle}\ensuremath{-}\ensuremath{\langle}{n}_{{p}_{y}}\ensuremath{\rangle}\ensuremath{\ne}0$ develops in the oxygen sector, as well as intercell magnetic nematicity with $\ensuremath{\langle}{S}_{\mathbf{i},d}^{z}({S}_{\mathbf{i}+\mathbf{x},d}^{z}\ensuremath{-}{S}_{\mathbf{i}+\mathbf{y},d}^{z})\ensuremath{\rangle}\ensuremath{\ne}0$ in the spin copper sector, in the standard notation. This occurs not only in rectangular but also in square $8\ifmmode\times\else\texttimes\fi{}8$ lattices. Our results suggest that the essence of the stripe spin and charge distribution experimentally observed in hole-doped cuprates is captured by unbiased Monte Carlo studies of a simple hole-doped charge-transfer insulator ${\mathrm{CuO}}_{2}$ spin-fermion model.

Jamming and tiling in aggregation of rectangles

We study a random aggregation process involving rectangular clusters. In each aggregation event, two rectangles are chosen at random and if they have a compatible side, either vertical or horizontal, they merge along that side to form a larger rectangle. Starting with N identical squares, this elementary event is repeated until the system reaches a jammed state where each rectangle has two unique sides. The average number of frozen rectangles scales as in the large-N limit. The growth exponent characterizes statistical properties of the jammed state and the time-dependent evolution. We also study an aggregation process where rectangles are embedded in a plane and interact only with nearest neighbors. In the jammed state, neighboring rectangles are incompatible, and these frozen rectangles form a tiling of the two-dimensional domain. In this case, the final number of rectangles scales linearly with system size.

Mathematical Modeling of the Magnetization of a Two-Dimensional System of Magnetic Moments

Using a system that reaches its minimum energy of interaction at equilibrium, the magnetization of a discrete two-dimensional system of interacting magnetic dipoles by an external magnetic field is modeled mathematically. Magnetization curves for rectangular two-dimensional clusters of dipoles and the region of the magnetic domain are calculated.

THE FRACTAL DIMENSION BASED QUALITY METRICS OF DATA SAMPLES AND DEPENDENCE MODELS

Context. The problem of automating the sampling of the original sample a large amount for the construction of models precedent. The object of the study was to model quality samples to build the models precedents.Objective. The goal of the work is the creation of a set of indicators to assess the quality of samples having a single nature, based on the principles of fractal analysis.Method. A set of indicators is proposed to characterize the quality of the subsample with respect to the original sample with one point of view on the basis of the principles of fractal analysis. The methods of sample fractal dimension evaluation are proposed. They operating with rectangular blocks of equal size and covering by them the feature space. They are method not taking into account the characteristics of the synthesized model, method taking into account the error (accuracy) of synthesized model and method taking into account accuracy and complexity of the synthesized model. Along with the fractal dimension it is also provided a method for determining the sample quality indicators based on the principle of mass dimension with regard to data analysis. The proposed method divides the feature space on clusters of the same size and shape. The method allows obtaining different levels of sampling detail varying the size of the cluster. The method allows to determine the masses of the class center in the sample, the average distance between instances of the cluster, the normalized mean deviation of the distance between instances of their average mass and density of the instances of the cluster, the volume and surface area of rectangular cluster ratio of volume to surface area of the cluster, the weighted average of evenness of instances location in the clusters of a class, the mass and density of instances of the class, the weighted average of sample instances location.Results. The developed indicators have been implemented in software and investigated for solving the problems of Fisher’s Iris classification.Conclusions. The conducted experiments have confirmed the proposed software operability and allow recommending it for use in practice for solving the problems of diagnosis and automatic classification on the features. The prospects for further research may include the creation of parallel methods for calculation of set of proposed indicators, the optimization of their software implementations, as well as a experimental study of proposed indicators on more complex practical problems of different nature and dimensionality

Photovoltaics in the assessment of wireless sensor network reliability with changing environmental conditions

AbstractThis paper presents a reliability assessment of a wireless sensor network (WSN) equipped with mini photovoltaic cells (PV‐WSN) under natural environmental conditions while accounting for different types of system failures. In particular, our assessment considers the hardware specifications of the sensors, photovoltaic (PV) specifications, the use of rechargeable batteries, communication protocols, and various elements required for efficient detection of environmental conditions. We accomplished this by developing a simulator that generated data for 2 broad WSN conditions: (1) WSN without PV and (2) WSN with PV. The dynamic source routing protocol was employed for these simulations, and the following variables were assessed for both conditions: WSN reliability, the impact of energy consumption on the network, and the types of failures that lead to sensor unavailability. The following assumptions were made to run the simulation: the distribution of WSN nodes is random, with 1 sink node per rectangular cluster, the sensor nodes are structurally and functionally identical, environmental interference and suboptimal orientation impair PV cell recharge capacity randomly, and no communication loss occurs. Our reliability assessment assumed extreme environmental conditions and further made assessments of component reliability that included the following parameters: sensor and PV cell hardware specifications, the rechargeable nature of PV cell batteries for different sensor activity states, the availability of sunlight for powering PV cells, and the energy efficiency of PV cells. We found that network lifetime was prolonged for the PV‐WSN condition over the WSN without PV condition, introducing a role for PV cells as potential energy sources for WSNs.

Detection of Multiconfigurational States of Hydrogen-Passivated Silicene Nanoclusters

Utilizing density functional theory (DFT) and a complete active space self-consistent field (CASSCF) approach,we study the electronic properties of rectangular silicene nano clusters with hydrogen passivated edges denoted by H-SiNCs (nz,na), with nz and na representing the zigzag and armchair directions, respectively. The results show that in the nz direction, the H-SiNCs prefer to be in a singlet (S = 0) ground state for nz > na. However, a transition from a singlet (S = 0) to a triplet (S = 1) ground state is revealed for na > nz. Through the calculated Raman spectrum, the S = 0 and S = 1 ground states can be observed by the E2g (G) and A (D) Raman modes. Furthermore, H-SiNC clusters are shown to have HOMO-LUMO (HL) energy gaps, which decrease as a function of na and nz for S = 0 and S = 1 states. The H-SiNC with a S = 1 ground state can be potentially used for silicene-based spintronic devices.

Nonperturbative linked-cluster expansions in long-range ordered quantum systems

We introduce a generic scheme to perform non-perturbative linked cluster expansions in long-range ordered quantum phases. Clusters are considered to be surrounded by an ordered reference state leading to effective edge-fields in the exact diagonalization on clusters which break the associated symmetry of the ordered phase. Two approaches, based either on a self-consistent solution of the order parameter or on minimal sensitivity with respect to the ground-state energy per site, are formulated to find the optimal edge-field in each NLCE order. Furthermore, we investigate the scaling behavior of the NLCE data sequences towards the infinite-order limit. We apply our scheme to gapped and gapless ordered phases of XXZ Heisenberg models on various lattices and for spins 1/2 and 1 using several types of cluster expansions ranging from a full-graph decomposition, rectangular clusters, up to more symmetric square clusters. It is found that the inclusion of edge-fields allows to regularize non-perturbative linked-cluster expansions in ordered phases yielding convergent data sequences. This includes the long-range spin-ordered ground state of the spin-1/2 and spin-1 Heisenberg model on the square and triangular lattice as well as the trimerized valence bond crystal of the spin-1 Heisenberg model on the kagome lattice.

Recognition of self-assembled water-nitrate cluster in a Co(III)-2,2′-bipyridine host: Synthesis, X-ray structure, DNA cleavage, molecular docking and anticancer activity

A mononuclear cobalt(III) complex [Co(bpy)2Cl2]NO3⋅2H2O (1) (bpy = 2,2′-bipyridine) has been synthesized and crystallographically characterized. Self-assembly of the lattice water molecules from rectangular tetrameric water cluster interacts with nitrate anion along the c-axis forming a six membered hexagonal water-nitrate cluster. It presents a new mode of association of water molecules with nitrate molecules which is not predicted theoretically or found experimentally. The molecule effectively cleaves bacterial genomic DNA and shows important cytotoxicity against human hepatocarcinoma cell (HepG2). This paper reports an X-ray crystallographic characterization of a Co(III)-bpy complex which also presents a new mode of association of water molecules with nitrate molecules which was not predicted theoretically or found experimentally or reported in literature. The molecule effectively cleaves bacterial genomic DNA and shows important cytotoxicity against human hepatocarcinoma cell (HepG2).

Photoactivatable compliant substrates for precise analysis of mechanobiological regulation in collective cell migration

Event Abstract Back to Event Photoactivatable compliant substrates for precise analysis of mechanobiological regulation in collective cell migration Masao Kamimura1, Kazuo Yamaguchi2 and Jun Nakanishi1 1 National Institute for Materials Science (NIMS), International center for Materials Nanoarchitectonics (MANA), Japan 2 Kanagawa University, Department of Chemistry, School of Science, Japan Introduction: Collective cell migration is the migration of cells in a group. Basically, epithelial cells migrate collectively, whereas mesenchymal cells prefer to migrate as individuals. However, in some spatiotemporally limited situations of life, cells aggressively ignore this rule via epithelial-mesenchymal transition (EMT) and vice versa (MET). This migration plasticity plays a critical role not only in developmental processes, but also in cancer invasion and metastasis. Therefore, understanding their regulation mechanisms is important from both fundamental and applied biology viewpoints. Various soluble factors and gene expression changes has been shown to affect the migration phenotypes, but the contribution of extracellular matrix (ECM) is still unclear. To precisely dissect mechanobiology in collective cell migration, we herein developed photoactivatable compliant substrates with defined material stiffness (Fig. 1) and conducted proof-of-concept experiments with MDCK cells. Materials and Methods: Polyacrylamide (PAAm) gel was used as a baselayer, whose mechanical property can be tuned depending on the mixing ratio of acrylamide and bisacrylamide. The surface of PAAm gel was functionalized with poly(D-lysine) (PDL) via sulfo-SANPAH. Finally, the PDL surface was successively functionalized with two kinds of PEGs (Mw = 5K and 2K) through a photoclevable 2-nitrobenzyl group. The surface is initially non-cell adhesive due to the PEG brushes, but becomes cell-adhesive upon photocleavage of PEG. Cell migration was studied by photo-confining cells in a given geometry and thereafter inducing migration by irradiating surrounding regions (Fig. 2). The migration behavior was recorded in an incubation chamber equipped on a phase-contrast microscope. Results and Discussions: Two differently-stiff PAAm gels were prepared (5 and 55 kPa), whose mechanical property was characterized by the gel indentation assay. The gel surface functionalization with PDL and photocleavable PEG was confirmed from surface zeta potential changes. The photoswitchabile feature was characterized from protein adsorption tests. These results demonstrated that the two gels had different mechanical properties with identical surface chemistry. Then, collective migration behaviors from rectangular and circular clusters were examined. One-directional migration from the rectangular clusters exhibited faster migration rate on the stiffer gel (data not shown). Moreover, the cluster expansion from the circular clusters exhibited qualitatively different behaviors; cells showed collective wavy motions on the stiffer gel, whereas on the softer gel, the cluster started migration after a certain priming time (~6 h) only to single direction (Fig. 3). It should be noted that migration behaviors were almost identical when cells were sparsely seeded as isolated single cells. Therefore, the observed difference in collective migration behaviors is owing to the emerged mechanical sensitivity when the cells become a group. Conclusions: Out photoactivatable compliant substrates revealed qualitative and quantitative difference in collective migration behaviors in MDCK cells depending on the substrate stiffness and initial cell cluster geometries. Further systematic analysis will help us understand the principle in mechanobiological regulation in collective migration. Keywords: mechanical property, stimuli-response, Pattering, matrix-cell interaction Conference: 10th World Biomaterials Congress, Montréal, Canada, 17 May - 22 May, 2016. Presentation Type: New Frontier Oral Topic: Cellular migration and biomaterials Citation: Kamimura M, Yamaguchi K and Nakanishi J (2016). Photoactivatable compliant substrates for precise analysis of mechanobiological regulation in collective cell migration. Front. Bioeng. Biotechnol. Conference Abstract: 10th World Biomaterials Congress. doi: 10.3389/conf.FBIOE.2016.01.00347 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 27 Mar 2016; Published Online: 30 Mar 2016. Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Masao Kamimura Kazuo Yamaguchi Jun Nakanishi Google Masao Kamimura Kazuo Yamaguchi Jun Nakanishi Google Scholar Masao Kamimura Kazuo Yamaguchi Jun Nakanishi PubMed Masao Kamimura Kazuo Yamaguchi Jun Nakanishi Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. 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A Cognitively Inspired Approach to Two-Way Cluster Extraction from One-Way Clustered Data

Cluster extraction is a vital part of data mining; however, humans and computers perform it very differently. Humans tend to estimate, perceive or visualize clusters cognitively, while digital computers either perform an exact extraction, follow a fuzzy approach, or organize the clusters in a hierarchical tree. In real data sets, the clusters are not only of different densities, but have embedded noise and are nested, thus making their extraction more challenging. In this paper, we propose a density-based technique for extracting connected rectangular clusters that may go undetected by traditional cluster extraction techniques. The proposed technique is inspired by the human cognition approach of appropriately scaling the level of detail, by going from low level of detail, i.e., one-way clustering to high level of detail, i.e., biclustering, in the dimension of interest, as in online analytical processing. A number of experiments were performed using simulated and real data sets and comparison of the proposed technique made with four popular cluster extraction techniques (DBSCAN, CLIQUE, k-medoids and k-means) with promising results.

Spectral evolution of the SU(4) Kondo effect from the single impurity to the two-dimensional limit

We describe the evolution of the SU(4) Kondo effect as the number of magnetic centers increases from one impurity to the two-dimensional (2D) lattice. We derive a Hubbard-Anderson model which describes a 2D array of atoms or molecules with two-fold orbital degeneracy, acting as magnetic impurities and interacting with a metallic host. We calculate the differential conductance, observed typically in experiments of scanning tunneling spectroscopy, for different arrangements of impurities on a metallic surface: a single impurity, a periodic square lattice, and several sites of a rectangular cluster. Our results point towards the crucial importance of the orbital degeneracy and agree well with recent experiments in different systems of iron(II) phtalocyanine molecules deposited on top of Au(111) [N. Tsukahara et al., Phys. Rev. Lett. 106, 187201 (2011)], indicating that this would be the first experimental realization of an artificial 2D SU(4) Kondo-lattice system.