Correct Partitioning Research Articles

Effect of Uncertainty in Water Vapor Continuum Absorption on CO2 Forcing, Longwave Feedback, and Climate Sensitivity

AbstractWe investigate the effect of uncertainty in water vapor continuum absorption at terrestrial wavenumbers on CO2 forcing , longwave feedback λ, and climate sensitivity at surface temperatures Ts between 270 and 330 K. We calculate this uncertainty using a line‐by‐line radiative‐transfer model and a single‐column atmospheric model, assuming a moist‐adiabatic temperature lapse‐rate and 80% relative humidity in the troposphere, an isothermal stratosphere, and clear skies. Due to the lack of a comprehensive model of continuum uncertainty, we represent continuum uncertainty in two different idealized approaches: In the first, we assume that the total continuum absorption is constrained at reference conditions; in the second, we assume that the total continuum absorption is constrained for all atmospheres in our model. In both approaches, we decrease the self continuum by 10% and adjust the foreign continuum accordingly. We find that continuum uncertainty mainly affects through its effect on λ. In the first approach, continuum uncertainty mainly affects λ through a decrease in the total continuum absorption with Ts; in the second approach, continuum uncertainty affects λ through a vertical redistribution of continuum absorption. In both experiments, the effect of continuum uncertainty on is modest at Ts = 288 K (≈0.02 K) but substantial at Ts ≥ 300 K (up to 0.2 K), because at high Ts, the effects of decreasing the self continuum and increasing the foreign continuum have the same sign. These results highlight the importance of a correct partitioning between self and foreign continuum to accurately determine the temperature dependence of Earth's climate sensitivity.

Updated COMAGMAT-5: Modeling the Effects of Sulfide Precipitation in Parallel to Crystallization Of Alumino-Chromian Spinel

An updated version of the COMAGMAT-5.3 program is presented, which enables simulations of the silicate-sulfide immiscibility in parallel to crystallization of Al-Cr spinel and other rock-forming minerals. Main changes include a completed recalibration of the previous Fe-Ni sulfide solubility model (Ariskin et al., 2013) and incorporation of equations describing spinel-melt equilibria in a wide range of magmatic systems (Nikolaev et al., 2018а, 2018b). This allowed us to specify more accurately the link between compositions of immiscible sulfides and magma crystallization temperatures, as well as to correct partitioning of alumina between the model spinel and crystallizing melt. The updated COMAGMAT-5.3 can be used for calculations of the crystallization of basaltic to komatiitic magmas, as well as the history of solidification of mafic to ultramafic cumulates, including relative proportions of Al-Cr spinel and immiscible sulfides. Application example includes solidification of sulfide-bearing primitive olivine cumulate from the endocontact of the Yoko-Dovyren intrusion in Northern Transbaikalia (Russia). It is established that maximum crystallization proportions of Al-Cr spinel as much as 3.5 wt % are observed at Ol-Spl cotectic, following an abrupt decrease to slightly negative values during crystallization of plagioclase-bearing assemblages. This results in the inflection point on the trend of evolution of the spinel compositions, which changes from descending the Cr/Al ratio in the field of olivine to its increase when plagioclase starts to crystallize. As compared to previous version COMAGMAT-5.2, the updated model predicts somewhat higher proportions of precipitated sulfides.

Validating a membership disclosure metric for synthetic health data.

BackgroundOne of the increasingly accepted methods to evaluate the privacy of synthetic data is by measuring the risk of membership disclosure. This is a measure of the F1 accuracy that an adversary would correctly ascertain that a target individual from the same population as the real data is in the dataset used to train the generative model, and is commonly estimated using a data partitioning methodology with a 0.5 partitioning parameter.ObjectiveValidate the membership disclosure F1 score, evaluate and improve the parametrization of the partitioning method, and provide a benchmark for its interpretation.Materials and methodsWe performed a simulated membership disclosure attack on 4 population datasets: an Ontario COVID-19 dataset, a state hospital discharge dataset, a national health survey, and an international COVID-19 behavioral survey. Two generative methods were evaluated: sequential synthesis and a generative adversarial network. A theoretical analysis and a simulation were used to determine the correct partitioning parameter that would give the same F1 score as a ground truth simulated membership disclosure attack.ResultsThe default 0.5 parameter can give quite inaccurate membership disclosure values. The proportion of records from the training dataset in the attack dataset must be equal to the sampling fraction of the real dataset from the population. The approach is demonstrated on 7 clinical trial datasets.ConclusionsOur proposed parameterization, as well as interpretation and generative model training guidance provide a theoretically and empirically grounded basis for evaluating and managing membership disclosure risk for synthetic data.

Bridging the Pragmatic Gaps for Mixed-Criticality Systems in the Automotive Industry

An increasingly important trend in the design of safety-critical systems is the integration of components with different levels of criticality onto a common hardware platform. Mixed-criticality systems (MCSs) have been well researched in academia, but can be difficult to implement in industrial scenarios as the theoretical models underpinning the research do not sufficiently consider industrial safety practice and safety standards. In this article, we make the first attempt toward the implementation of the MCS theoretical model in industrial settings. To this end, we identify the pragmatic gaps between theory and practice, and then propose a generic industrial MCS architecture, termed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P-MCS</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Practical-MCS</i> ). <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P-MCS</i> is built upon the conventional theoretical MCS model with additional considerations of industrial safety requirements: 1) runtime safety analysis, determining preserved applications in each system mode and 2) correct partitioning and isolation of different critical elements. We introduce three implementing methods for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P-MCS</i> . Corresponding to the new system architecture, we present a theoretical model and schedulability analysis (with consideration of shared resources) to ensure system predictability. Finally, we evaluate and demonstrate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P-MCS</i> in terms of system schedulability, overheads, throughput, and predictability, along with a real-world case study. As shown in the evaluation, the considerations of industrial requirements lead to extra overheads and performance reduction in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P-MCS</i> . Such weaknesses can be considerably mitigated by hardware assistance and acceleration.

Eastern Mediterranean climate change deduced from the Soreq Cave fluid inclusion stable isotopes and carbonate clumped isotopes record of the last 160 ka

A fundamental issue in the interpretation of speleothem calcite δ18Occ records is the correct partitioning of the effects of temperature and water δ18O variations. This study explores the paleo-environmental evolution of the Eastern Mediterranean Sea (EMS) region using Soreq Cave speleothems in the last 160 ka, a period covering glacial MIS6 to the present, through the independent determinations of temperatures via carbonate clumped isotopes (Δ47) and fluid inclusion δ18Ow, δDw and d-excess values of cave water entrapped in the speleothems. The observed general agreement between the trends in water δ18Ow composition directly measured from fluid inclusions and calculated from Δ47 temperatures and δ18Occ support the robustness of the data. Δ47 temperatures, derived using a revised thermometer calibration that includes recent modifications in 17O correction, vary from high values of 20–22 °C during interglacial periods to low values of 11–12 °C in cold glacial and stadial periods. Temperatures of 19–22 °C are observed during the time of deposition in the EMS of sapropel S5 in the last interglacial MIS5e period and sapropel S1 in the early Holocene, immediately following Terminations II and I, respectively. The Soreq Cave Δ47 temperatures generally agree with previously estimated EM sea surface temperatures, in support of the absence of a significant land-sea temperature gradient. Cave water δ18Ow values show large variations (from ∼-3 to −7.5‰), with high glacial and low interglacial values. These variations are largely explained by changes in Mediterranean Sea water composition due to glacial ice melting and freshwater input during sapropel periods, combined with the effect of rainfall amounts during interglacial periods. An analysis of relative timing shows that temperature rise precedes hydrological changes in the initial stages of Termination events. Fluid inclusion d-excess values show clear variations between values similar to the Global Meteoric Water Line during cold periods and values similar to the local Eastern Mediterranean Meteoric Water Line (EMMWL) in warm periods.

Distributed clustering in peer to peer networks using multi-objective whale optimization

Multi-objective clustering algorithms have superiority over its single objective counterparts as they include additional knowledge on properties of data in the form of objectives to discover the underlying clusters present in various datasets. This paper proposes a distributed clustering algorithm using multi-objective whale optimization (DMOWOA) for peer to peer network. The algorithm minimizes two objective functions to perform clustering, namely : Total Euclidean Deviation and Total Symmetrical Deviation. Both objective values are shared using diffusion method of cooperation to obtain correct partitioning at each peer. A single solution from the non-dominated solutions is selected as final solution based on its minimum distance to origin in the normalized objective space. The proposed algorithm’s performance is evaluated on four synthetic and five real-life wireless sensor network datasets (Canada weather station dataset, Delhi air pollution content dataset, Intel laboratory dataset, Washington cook agronomy farm dataset and Thames river water quality dataset). The comparison is carried out with multi-objective distributed particle swarm optimization (DMOPSO), distributed K-Means (DK-Means) and other seven recently developed nature inspired multi-objective clustering techniques. The proposed algorithm in most of the cases outperforms the existing techniques in terms of statistical measures Minkowski Score, Dunn index and Silhouette index. The average rank of the proposed algorithm is also better in Kruskal–Wallis statistical test.

Metabolome-Informed Microbiome Analysis Refines Metadata Classifications and Reveals Unexpected Medication Transfer in Captive Cheetahs.

Even high-quality collection and reporting of study metadata in microbiome studies can lead to various forms of inadvertently missing or mischaracterized information that can alter the interpretation or outcome of the studies, especially with nonmodel organisms. Metabolomic profiling of fecal microbiome samples can provide empirical insight into unanticipated confounding factors that are not possible to obtain even from detailed care records. We illustrate this point using data from cheetahs from the San Diego Zoo Safari Park. The metabolomic characterization indicated that one cheetah had to be moved from the non-antibiotic-exposed group to the antibiotic-exposed group. The detection of the antibiotic in this second cheetah was likely due to grooming interactions with the cheetah that was administered antibiotics. Similarly, because transit time for stool is variable, fecal samples within the first few days of antibiotic prescription do not all contain detected antibiotics, and the microbiome is not yet affected. These insights significantly altered the way the samples were grouped for analysis (antibiotic versus no antibiotic) and the subsequent understanding of the effect of the antibiotics on the cheetah microbiome. Metabolomics also revealed information about numerous other medications and provided unexpected dietary insights that in turn improved our understanding of the molecular patterns on the impact on the community microbial structure. These results suggest that untargeted metabolomic data provide empirical evidence to correct records and aid in the monitoring of the health of nonmodel organisms in captivity, although we also expect that these methods may be appropriate for other social animals, such as cats.IMPORTANCE Metabolome-informed analyses can enhance omics studies by enabling the correct partitioning of samples by identifying hidden confounders inadvertently misrepresented or omitted from carefully curated metadata. We demonstrate here the utility of metabolomics in a study characterizing the microbiome associated with liver disease in cheetahs. Metabolome-informed reinterpretation of metagenome and metabolome profiles factored in an unexpected transfer of antibiotics, preventing misinterpretation of the data. Our work suggests that untargeted metabolomics can be used to verify, augment, and correct sample metadata to support improved grouping of sample data for microbiome analyses, here for nonmodel organisms in captivity. However, the techniques also suggest a path forward for correcting clinical information in microbiome studies more broadly to enable higher-precision analyses.

Impact of the adhesion-force lever-arm “a” on the Rock ‘n’ Roll resuspension model and how to compute it from contact mechanics

The paper proposes a methodology to fill a gap in the context of mechanistic particle resuspension models related to the adhesion and lift force lever arms (a): to date, only one experimental observation exists from a centrifuge experiment with a specific particle/surface pair which found rP/a = 100 and assumed that the contact points were symmetric with respect to the particle center (Reeks, M.W., & D. Hall (2001) Kinetic Models for Particle Resuspension in Turbulent Flows: Theory and Measurement. Aerosol Science, 32, 1–31). However, the Reeks and Hall’s (2001) model is highly sensitive to this parameter, which therefore cannot be used as-is for different particle diameters or materials. This paper proposes a methodology to compute the adhesion and lift force lever arms (aA and aL, respectively) based on Atomic Force Microcopy (AFM) surface roughness measurements and contact mechanics arguments. In practice, a spherical, perfectly smooth particle is brought in contact (computationally) with the measured surface roughness and is then rotated by the point of contact to determine the two or more asperities over which the particle would sit on the surface. A method to compute the asperity radius of curvature is devised to compute the asperity deformation and the correct partitioning of the total deformation between the particle and the asperity is presented. For the glass surface under consideration, the asperity deformation was negligible, i.e., it was below the van der Waals radius, which is the limit of applicability of contact mechanics. The Reeks and Hall’s (2001) model is then extended to account for the joint probability of aA and aL. Significant differences in particle resuspended after a day in common atmospheric conditions are found between the approach that uses the lever-arm distributions or their mean values. Also, important differences are found when comparing the lever-arm distribution and rP/a = 100. Hence, one should be cautious of using rP/a = 100 for surface/particle pairs differing from those in the original study. Limits of applicability of the theories used are presented together with considerations regarding how to extend the method to non-spherical particles and different materials.

The Golgi ribbon: mechanisms of maintenance and disassembly during the cell cycle

The Golgi complex (GC) has an essential role in the processing and sorting of proteins and lipids. The GC of mammalian cells is composed of stacks of cisternae connected by membranous tubules to create a continuous network, the Golgi ribbon, whose maintenance requires several core and accessory proteins. Despite this complex structural organization, the Golgi apparatus is highly dynamic, and this property becomes particularly evident during mitosis, when the ribbon undergoes a multistep disassembly process that allows its correct partitioning and inheritance by the daughter cells. Importantly, alterations of the Golgi structure are associated with a variety of physiological and pathological conditions. Here, we review the core mechanisms and signaling pathways involved in both the maintenance and disassembly of the Golgi ribbon, and we also report on the signaling pathways that connect the disassembly of the Golgi ribbon to mitotic entry and progression.

Actin-microtubule interplay coordinates spindle assembly in human oocytes

Mammalian oocytes assemble a bipolar acentriolar microtubule spindle to segregate chromosomes during asymmetric division. There is increasing evidence that actin in the spindle interior not only participates in spindle migration and positioning but also protects oocytes from chromosome segregation errors leading to aneuploidy. Here we show that actin is an integral component of the meiotic machinery that closely interacts with microtubules during all major events of human oocyte maturation from the time point of spindle assembly till polar body extrusion and metaphase arrest. With the aid of drugs selectively affecting cytoskeleton dynamics and transiently disturbing the integrity of the two cytoskeleton systems, we identify interdependent structural rearrangements indicative of a close communication between actin and microtubules as fundamental feature of human oocytes. Our data support a model of actin-microtubule interplay that is essential for bipolar spindle assembly and correct partitioning of the nuclear genome in human oocyte meiosis.

Development of a Distributed Hydrologic Model for a Region with Fragipan Soils to Study Impacts of Climate on Soil Moisture: A Case Study on the Obion River Watershed in West Tennessee

Previous land surface modeling efforts to predict and understand water budgets in the U.S. Southeast for soil water management have struggled to characterize parts of the region due to an extensive presence of fragipan soils for which current calibration approaches are not adept at handling. This study presents a physically based approach for calibrating fragipan-dominated regions based on the “effective” soil moisture capacity concept, which accounts for the dynamic perched saturation zone effects created by the low hydraulic capacities of the fragipan layers. The approach is applied to the Variable Infiltration Capacity model to develop a hydrologic model of the Obion River Watershed (ORW), TN, which has extensive fragipan coverage. Model calibration was performed using observed streamflow data, as well as evapotranspiration and soil moisture data, to ensure correct partitioning of surface and subsurface fluxes. Estimated Nash-Sutcliffe coefficients for the various sub-drainage areas within ORW were all greater than 0.65, indicating good model performance. The model results suggest that ORW has a high responsivity and high resilience. Despite forecasted temperature increases, the simulation results suggest that water budget trends in the ORW are unlikely to change significantly in the near future up to 2050 due to sufficient precipitation amounts.

Activators and Effectors of the Small G Protein Arf1 in Regulation of Golgi Dynamics During the Cell Division Cycle.

When eukaryotic cells divide, they must faithfully segregate not only the genetic material but also their membrane-bound organelles into each daughter cell. To assure correct partitioning of cellular contents, cells use regulatory mechanisms to verify that each stage of cell division has been correctly accomplished before proceeding to the next step. A great deal is known about mechanisms that regulate chromosome segregation during cell division, but we know much less about the mechanisms by which cellular organelles are partitioned, and how these processes are coordinated. The Golgi apparatus, the central sorting and modification station of the secretory pathway, disassembles during mitosis, a process that depends on Arf1 and its regulators and effectors. Prior to total disassembly, the Golgi ribbon in mammalian cells, composed of alternating cisternal stacks and tubular networks, undergoes fission of the tubular networks to produce individual stacks. Failure to carry out this unlinking leads to cell division arrest at late G2 prior to entering mitosis, an arrest that can be relieved by inhibition of Arf1 activation. The level of active Arf1-GTP drops during mitosis, due to inactivation of the major Arf1 guanine nucleotide exchange factor at the Golgi, GBF1. Expression of constitutively active Arf1 prevents Golgi disassembly, and leads to defects in chromosome segregation and cytokinesis. In this review, we describe recent advances in understanding the functions of Arf1 regulators and effectors in the crosstalk between Golgi structure and cell cycle regulation.

Imaging Mitochondrial Calcium Fluxes with Fluorescent Probes and Single- or Two-Photon Confocal Microscopy.

The concentration of calcium ions in the mitochondria has been shown to affect its function, modulating respiratory activity at low levels and causing lethal damage at high concentrations. The rhodamine series of dyes can be used to measure mitochondrial calcium concentration, but the reliability of measurements depends upon correct partitioning of the dye within to the mitochondria. Methods are described to aid verification and quantification of the mitochondrial calcium concentration using single- or two-photon confocal microscopy. The method of linear unmixing to separate fluorescent signals based on either differing excitation or emission spectra is outlined and for the purposes of illustration is applied to the separation of rhod-2 signals originating from the dye within the mitochondria and nucleoli.

Mitotic inheritance of the Golgi complex and its role in cell division.

The Golgi apparatus plays essential roles in the processing and sorting of proteins and lipids, but it can also act as a signalling hub and a microtubule-nucleation centre. The Golgi complex (GC) of mammalian cells is composed of stacks connected by tubular bridges to form a continuous membranous system. In spite of this structural complexity, the GC is highly dynamic, and this feature becomes particularly evident during mitosis, when the GC undergoes a multi-step disassembly process that allows its correct partitioning and inheritance by daughter cells. Strikingly, different steps of Golgi disassembly control mitotic entry and progression, indicating that cells actively monitor Golgi integrity during cell division. Here, we summarise the basic mechanisms and the molecular players that are involved in Golgi disassembly, focussing in particular on recent studies that have revealed the fundamental signalling pathways that connect Golgi inheritance to mitotic entry and progression.

The endoplasmic reticulum is partitioned asymmetrically during mitosis before cell fate selection in proneuronal cells in the early Drosophila embryo.

Asymmetric cell division is the primary mechanism to generate cellular diversity, and it relies on the correct partitioning of cell fate determinants. However, the mechanism by which these determinants are delivered and positioned is poorly understood, and the upstream signal to initiate asymmetric cell division is unknown. Here we report that the endoplasmic reticulum (ER) is asymmetrically partitioned during mitosis in epithelial cells just before delamination and selection of a proneural cell fate in the early Drosophila embryo. At the start of gastrulation, the ER divides asymmetrically into a population of asynchronously dividing cells at the anterior end of the embryo. We found that this asymmetric division of the ER depends on the highly conserved ER membrane protein Jagunal (Jagn). RNA inhibition of jagn just before the start of gastrulation disrupts this asymmetric division of the ER. In addition, jagn-deficient embryos display defects in apical-basal spindle orientation in delaminated embryonic neuroblasts. Our results describe a model in which an organelle is partitioned asymmetrically in an otherwise symmetrically dividing cell population just upstream of cell fate determination and updates previous models of spindle-based selection of cell fate during mitosis.

Exploring differential evolution and particle swarm optimization to develop some symmetry-based automatic clustering techniques: application to gene clustering

In the current paper, we have developed two bio-inspired fuzzy clustering algorithms by incorporating the optimization techniques, namely differential evolution and particle swarm optimization. Both these clustering techniques can detect symmetrical-shaped clusters utilizing the established point symmetry-based distance measure. Both the proposed approaches are automatic in nature and can detect the number of clusters automatically from a given dataset. A symmetry-based cluster validity measure, F-Sym-index, is used as the objective function to be optimized in order to automatically determine the correct partitioning by both the approaches. The effectiveness of the proposed approaches is shown for automatically clustering some artificial and real-life datasets as well as for clustering some real-life gene expression datasets. The current paper presents a comparative analysis of some meta-heuristic-based clustering approaches, namely newly proposed two techniques and the already existing automatic genetic clustering techniques, VGAPS, GCUK, HNGA. The obtained results are compared with respect to some external cluster validity indices. Moreover, some statistical significance tests, as well as biological significance tests, are also conducted. Finally, results on gene expression datasets have been visualized by using some visualization tools, namely Eisen plot and cluster profile plot.

Spindle Micro-Fluctuations of Length Reveal its Dynamics Over Cell Division

The mitotic spindle ensures correct segregation of sister chromatids and correct partitioning in daughter cells. It comprises dynamical microtubules (alternating polymerizing and depolymerizing), a variety of molecular motors and their regulators. Although spindle structure is well known, the link to its functions remains elusive, calling for including the dynamics of its components and their interactions. This question was mostly investigated by in silico or in vitro approaches. But a detailed characterizing of spindle mechanics, in physiological conditions, is missing. We propose an image processing based, non invasive, method combined to an heuristic model to measure mechanical parameters along time.We tracked fluorescently labeled spindle pole at high temporal and spatial resolution and measured the micro-fluctuations of spindle length, in vivo. We computed its power density spectrum using short time Fourier transform (sliding window) — a blueprint of spindle mechanics. Such a spectrum is then fitted with a Kelvin Voigt model with inertia (a spring, a damper, an inertial element in parallel) convolved with the window. We validated this method by recovering the mechanical parameters over time from simulated data. Then we measured them, in vivo, in two model organisms, nematode C. elegans one-cell embryo and fission yeast S. pombe.In control C. elegans embryos, metaphase appeared dominated by damping element, consistent with the slow spindle elongation observed. At anaphase onset, all three parameters collapsed, before increasing about 50s later to reach a regime where damping and inertia dominated, suggesting a dramatic re-arrangement of the spindle. Using a gene candidate approach, we could relate these mechanical behaviors to known structures at work, overlapping and kinetochore microtubules during metaphase and centralspindle at anaphase.With such a tool, we will propose a model of the spindle accounting for the dynamics of its component.

The role of mTOR in lipid homeostasis and diabetes progression.

Metabolic diseases, such as type 2 diabetes, cardiac dysfunction, hypertension, and hepatic steatosis, share one critical causative factor: abnormal lipid partitioning, that redistribution of triglycerides from adipocytes to nonadipose peripheral tissues. Lipid overload of these tissues causes a number of pathological effects collectively known as lipotoxicity. If we find the way to correct lipid partitioning, we will restrain metabolic diseases, improve life quality and life expectancy and radically reduce healthcare costs. Lipid partitioning in the body is maintained by tightly regulated and balanced rates of de novo lipogenesis, lipolysis, adipogenesis, and mitochondrial oxidation primarily in fat and liver. Recent studies highlighted in this review have established mTOR as a central regulator of lipid storage and metabolism. Increased activity of mTOR in obesity may compensate for the negative consequences of overnutrition, whereas dysregulation of mTOR may lead to abnormal lipid partitioning and metabolic disease.

Simultaneous feature selection and symmetry based clustering using multiobjective framework

In this paper a new framework based on multiobjective optimization (MOO), namely FeaClusMOO, is proposed which is capable of identifying the correct partitioning as well as the most relevant set of features from a data set. A newly developed multiobjective simulated annealing based optimization technique namely archived multiobjective simulated annealing (AMOSA) is used as the background strategy for optimization. Here features and cluster centers are encoded in the form of a string. As the objective functions, two internal cluster validity indices measuring the goodness of the obtained partitioning using Euclidean distance and point symmetry based distance, respectively, and a count on the number of features are utilized. These three objectives are optimized simultaneously using AMOSA in order to detect the appropriate subset of features, appropriate number of clusters as well as the appropriate partitioning. Points are allocated to different clusters using a point symmetry based distance. Mutation changes the feature combination as well as the set of cluster centers. Since AMOSA, like any other MOO technique, provides a set of solutions on the final Pareto front, a technique based on the concept of semi-supervised classification is developed to select a solution from the given set. The effectiveness of the proposed FeaClustMOO in comparison with other clustering techniques like its Euclidean distance based version where Euclidean distance is used for cluster assignment, a genetic algorithm based automatic clustering technique (VGAPS-clustering) using point symmetry based distance with all the features, K-means clustering technique with all features is shown for seven higher dimensional data sets obtained from real-life.

Locality-aware policies to improve job scheduling on 3D tori

This paper studies the influence that contiguous job placement has on the performance of schedulers for large-scale computing systems. In contrast with non-contiguous strategies, contiguous partitioning enables the exploitation of communication locality in applications, and also reduces inter-application interference. However, contiguous partitioning increases scheduling times and system fragmentation, degrading system utilization. We propose and evaluate several strategies to select contiguous partitions to allocate incoming jobs. These strategies are used in combination with different mapping mechanisms to perform the task-to-node assignment in order to further reduce application run times. A simulation-based study has been carried out, using a collection of synthetic applications performing common communication patterns. Results show that the exploitation of communication locality by means of a correct partitioning---mapping results in an effective reduction of application run times, and the gains achieved more than compensate the scheduling inefficiency, therefore resulting in better overall system performance.