Global Data Distribution Research Articles

Clustering Based on a Novel Density Estimation Method

We propose a novel density estimation method using both the k-nearest neighbor (KNN) graph and the potential field of the data points to capture the local and global data distribution information respectively. The clustering is performed based on the computed density values. A forest of trees is built using each data point as the tree node. And the clusters are formed according to the trees in the forest. The new clustering method is evaluated by comparing with three popular clustering methods, K-means++, Mean Shift and DBSCAN. Experiments on two synthetic data sets and one real data set show that our approach can effectively improve the clustering results.

Where Will the World's Poor Live? An Update on Global Poverty and the New Bottom Billion

This paper updates the distribution of global poverty data and makes projections up to 2020. The paper asks the following question: Do the world’s extreme poor live in poor countries? It is argued that many of the world’s extreme poor already live in countries where the total cost of ending extreme poverty is not prohibitively high as a percentage of GDP. And in the not-too-distant future, most of the world’s poor will live in countries that do have the domestic financial scope to end at least extreme poverty. This would imply a reframing of global poverty as largely a matter of domestic distribution.

PHA: A fast potential-based hierarchical agglomerative clustering method

A novel potential-based hierarchical agglomerative (PHA) clustering method is proposed. In this method, we first construct a hypothetical potential field of all the data points, and show that this potential field is closely related to nonparametric estimation of the global probability density function of the data points. Then we propose a new similarity metric incorporating both the potential field which represents global data distribution information and the distance matrix which represents local data distribution information. Finally we develop another equivalent similarity metric based on an edge weighted tree of all the data points, which leads to a fast agglomerative clustering algorithm with time complexity O(N2). The proposed PHA method is evaluated by comparing with six other typical agglomerative clustering methods on four synthetic data sets and two real data sets. Experiments show that it runs much faster than the other methods and produces the most satisfying results in most cases.

Frequency of Occurrence and Potency Range Distribution of Activity Cliffs in Bioactive Compounds

We have systematically identified activity cliffs in bioactive compounds for which high-confidence potency data were available. Different molecular representations were utilized and similarity and potency difference criteria for activity cliffs were clearly defined. Cliff formation was studied across the global potency range observed for qualifying bioactive compounds. Depending on the specific representation of activity cliffs, between ∼22% and 34% of all active compounds meeting the data selection criteria were involved in the formation of at least one activity cliff spanning a potency difference of at least two orders of magnitude. However, these cliffs involved only between ∼4.7% and ∼5.7% of all compound pairs meeting the similarity criteria. Hence, in light of these findings, the formation of well-defined activity cliffs is a relatively rare event. Moreover, the potency range distribution of activity cliffs was analyzed in detail, revealing that most activity cliffs were formed between compounds with micro- and nanomolar potency, consistent with the global distribution of potency data. On the basis of our analysis, we propose a general definition of activity cliffs for data mining.

Effect of orbit inclination on the performance of FORMOSAT-3/-7 type constellations

This paper investigates the effect of orbit inclination angle on the performance of the Formosa satellite number 3 (FORMOSAT-3 or FS3) and FORMOSAT-7 (FS7) type constellations. The FS3 developed by National Space Organization (NSPO) of Taiwan was launched on 15 April 2006. It is a constellation consisting of 6 microsatellites at 72° orbit inclination and 800km altitude for the acquisition of the global positioning system (GPS) signal occultation data. The international space community has given very positive comments on the contribution of FS3. Therefore, NSPO is planning the future program and designates FS7 to be the follow-up of FS3. There are two major indexes to assess the performance of FS3/7 type constellations: maximization of daily data acquisition and evenness in global data distribution. From system simulation, the number of data acquisition of FS3 is 2415. However, the number can be increased to 3050 by changing the orbit inclination to 154°. The drawback is that there is no data beyond 45° latitude north/south. After trade-off, it has been found that the optimal configuration is a 3–2–1 combination with 3 satellites deployed at 154° inclination, 2 satellites at 108° and 1 satellite at 90°. Daily data acquisition is 2924 using this configuration. For readers′ information, the 3–2–1 configuration could probably be called the “hybrid constellation” because it is not a standard one like the “Walker” or “Draim” or “Ballard” constellations.

A systematic review of the global distribution and availability of prevalence data for bipolar disorder

The multiple factors likely to influence estimates of the prevalence of bipolar spectrum disorders (BSD) make it difficult to determine its actual prevalence. A systematic review was undertaken to explore the availability and quality of epidemiological data for BSD. This will inform the Global Burden of Disease 2010 study. Electronic databases searched were Medline, PsycInfo and EMBASE using search terms generated in consultation with a research librarian. Reference lists were searched and experts contacted to obtain articles not identified through the database search. Prevalence data pertaining to point, 6 month or 12 month prevalence of BSD were sought. The mean pooled prevalence was 0.741% (point) and 0.843% (6/12 months). The study region, response rate and diagnostic tool had a significant impact on prevalence estimates but there were no significant differences in prevalence across prevalence types, gender, sample coverage, economic status and bipolar subtype. Little or no prevalence data was apparent for many regions of the world. Also, the entire bipolar spectrum was rarely assessed. Although stringent quality assurance methodology was used, controlling for all sources of variability around the pooled prevalence was not possible. This systematic review has made significant contributions to the epidemiological profile of BSD. Prevalence estimates will be used to generate estimates of burden for BSD in the global burden of disease 2010 study.

EpiChIP: gene-by-gene quantification of epigenetic modification levels

The combination of chromatin immunoprecipitation with next-generation sequencing technology (ChIP-seq) is a powerful and increasingly popular method for mapping protein–DNA interactions in a genome-wide fashion. The conventional way of analyzing this data is to identify sequencing peaks along the chromosomes that are significantly higher than the read background. For histone modifications and other epigenetic marks, it is often preferable to find a characteristic region of enrichment in sequencing reads relative to gene annotations. For instance, many histone modifications are typically enriched around transcription start sites. Calculating the optimal window that describes this enrichment allows one to quantify modification levels for each individual gene. Using data sets for the H3K9/14ac histone modification in Th cells and an accompanying IgG control, we present an analysis strategy that alternates between single gene and global data distribution levels and allows a clear distinction between experimental background and signal. Curve fitting permits false discovery rate-based classification of genes as modified versus unmodified. We have developed a software package called EpiChIP that carries out this type of analysis, including integration with and visualization of gene expression data.

Phylogeographic analysis of human papillomavirus 58

Human papillomavirus 58 (HPV58) is one type of HPV with high risk of causing cervical cancer. Unusually high prevalence of HPV58 has been reported in Asia, Africa and some other areas. However, due to the scattered distribution of global data, in addition to the lack of data of some HPV58 high-incidence nations and regions, like Mainland China, a comprehensive analysis of the global geographical distribution of HPV58 remains blank so far. In this study, HPV58 from the human cervical cancer tissue was detected in Mainland China, and 14 new HPV58-E6/L1 gene sequences were obtained. Moreover, phylogeographic analysis has been conducted combining the HPV58 sequences that have been deposited in GenBank since 1985. The study result shows that the sequences detected from the Shanghai, Jiangsu and Sichuan areas are homologous with those found in the past from Hong Kong and Xi'an, China, as well as Japan and other Southeast Asian areas. Furthermore, Western Africa is considered to be the "root" source of the HPV58 variant, while Mainland China and Southeast Asia are "transit points" and the new sources of HPV58 after receiving the isolates from the "root" source; like HPV16 and HPV18, the HPV58 might also be one of the major HPV types associated with the development and spread of cervical cancer.

Multi-dimensional data density estimation in P2P networks

Estimating the global data distribution in Peer-to-Peer (P2P) networks is an important issue and has not yet been well addressed. It can benefit many P2P applications, such as load balancing analys...

Impact of a permanent El Niño (El Padre) and Indian Ocean Dipole in warm Pliocene climates

Pliocene sea surface temperature data, as well as terrestrial precipitation and temperature proxies, indicate warmer than modern conditions in the eastern equatorial Pacific and imply permanent El Niño–like conditions with impacts similar to those of the 1997/1998 El Niño event. Here we use a general circulation model to examine the global‐scale effects that result from imposing warm tropical sea surface temperature (SST) anomalies in both modern and Pliocene simulations. Observed SSTs from the 1997/1998 El Niño event were used for the anomalies and incorporate Pacific warming as well as a prominent Indian Ocean Dipole event. Both the permanent El Niño (also called El Padre) and Indian Ocean Dipole (IOD) conditions are necessary to reproduce temperature and precipitation patterns consistent with the global distribution of Pliocene proxy data. These patterns may result from the poleward propagation of planetary waves from the strong convection centers associated with the El Niño and IOD.

Fuzzy declustering-based vector quantization

Vector quantization is a useful approach for multi-dimensional data compression and pattern classification. One of the most popular techniques for vector quantization design is the LBG (Linde, Buzo, Gray) algorithm. To address the problem of producing poor estimate of vector centroids which are subjected to biased data in vector quantization; we propose a fuzzy declustering strategy for the LBG algorithm. The proposed technique calculates appropriate declustering weights to adjust the global data distribution. Using the result of fuzzy declustering-based vector quantization design, we incorporate the notion of fuzzy partition entropy into the distortion measures that can be useful for classification of spectral features. Experimental results obtained from simulated and real data sets demonstrate the effective performance of the proposed approach.

Group-oriented catalog allocation in heterogeneous distributed database systems

The catalog is a system database, which contains information regarding various objects that are of interest to the system itself. In heterogeneous distributed database systems (HDDBSs), efficient handling of the global catalog is of great practical importance with respect to the site autonomy, global query optimization, global view management, authorization mechanism, and data distribution transparency. In this paper, we propose a new catalog allocation scheme, named GOCAS ( group-oriented catalog allocation scheme). GOCAS can reduce the number of inter-site messages for accessing catalog information by exploiting the locality of references that span a number of sites. This approach is contrary to the previous catalog allocation schemes, where the iocality of references cannot be employed or can be applied restrictively to only one site. We develop an analytical model in order to compare the performance of GOCAS to other schemes. With the analytical model, we describe the performance benefits of GOCAS and its effectiveness to other schemes.

Opportunities to improve hydrologic data

Hydrologic data collection over scales from centimeters to continents, from minutes to years is difficult and expensive, so hydrologic models usually conceptualize processes based on simple, often homogeneous, views of nature. This forced oversimplification impedes scientific understanding and management of water resources. As the focus of hydrologic research shifts to larger regional and global scales, the collection, management, distribution, and analysis of data will improve so that models and data can each drive and direct the other. Better models illuminate the type and quantity of data needed to test hypotheses. Better data permit development and validation of more complete models and new hypotheses. Coordinated hydrologic experiments (such as the Global Energy and Water Cycle Experiment) and remote sensing of hydrologic parameters examine hydrologic variables at these larger scales, and isotope geochemistry, paleohydrology, and biological methods allow analysis and retrieval of new kinds of information. Improvements in the management and accessibility of data will make them more easily available to hydrologic scientists.

Status of the geopotential

Substantial progress has been made in modeling the geopotential field since the last reporting period (Anderle, 1979a). Models of the gravity potential show improvement across the entire gravitational spectrum with resolution down to 1° haIf‐wavelength. Major sources of data utilized for advancing our knowledge of the geopotential field consist of satellite laser ranging (Smith, 1982; Wilson, 1979; Linder, 1981) which contributed to the long wavelength portion of the spectrum, satellite altimetry (GEOS‐3, 1979; SEASAT, 1981) and improved surface gravity anomalies (Rapp, 1981b) both of which contributed to the intermediate and short wavelength features of the spectrum. Uniform global distribution of data in combination solutions is generally achieved by using altimeter data over the ocean and terrestrial gravity anomalies over land.

Evaluation of the SEASAT altimeter time tag bias

Because of the variable effect on the altimeter height processing produced by a constant error in the altimeter time tag, the accuracy of the time tag is an important factor in the applications of the 10‐cm SEASAT altimeter data. An assessment of the internal delays inherent in the altimeter microprocessor suggested that −79.4 ms should be added to the time tags transmitted to the ground receiving stations. To ensure the validity of this value, analyses were undertaken with the altimeter data. Two methods were used in these analyses which benefited from a global data distribution in the oceanic areas. These methods were (1) the crossover method which used altimeter data differenced at points where the SEASAT ground track intersected with itself and (2) the direct use of the altimeter data. The former method is independent of errors in the geoid model; hence it is considered to produce the most reliable results. Using the crossover method and several different ephemerides, various values of the time tag bias were estimated. For all crossover results the adopted value of −79.4 ms is within the bounds of the standard deviation associated with the estimates. In particular, the estimate of −78.1±2.0 ms is considered to best represent the set of estimated values.