GPGPU implementation of growing neural gas: application to 3D scene reconstruction

Self-organising neural models have the ability to provide a good representation of the input space. In particular the Growing Neural Gas (GNG) is a suitable model because of its flexibility, rapid adaptation and excellent quality of representation. However, this type of learning is time-consuming, especially for high-dimensional input data. Since real applications often work under time constraints, it is necessary to adapt the learning process in order to complete it in a predefined time. This paper proposes a Graphics Processing Unit (GPU) parallel implementation of the GNG with Compute Unified Device Architecture (CUDA). In contrast to existing algorithms, the proposed GPU implementation allows the acceleration of the learning process keeping a good quality of representation. Comparative experiments using iterative, parallel and hybrid implementations are carried out to demonstrate the effectiveness of CUDA implementation. The results show that GNG learning with the proposed implementation achieves a speed-up of 6× compared with the single-threaded CPU implementation. GPU implementation has also been applied to a real application with time constraints: acceleration of 3D scene reconstruction for egomotion, in order to validate the proposal.

An approach to the application of shift-and-add algorithms on engineering and industrial processes

Different kinds of algorithms can be chosen so as to compute elementary functions. Among all of them, it is worthwhile mentioning the shift-and-add algorithms due to the fact that they have been specifically designed to be very simple and to save computer resources. In fact, almost the only operations usually involved with these methods are additions and shifts, which can be easily and efficiently performed by a digital processor. Shift-and-add algorithms allow fairly good precision with low cost iterations. The most famous algorithm belonging to this type is CORDIC. CORDIC has the capability of approximating a wide variety of functions with only the help of a slight change in their iterations. In this paper, we will analyze the requirements of some engineering and industrial problems in terms of type of operands and functions to approximate. Then, we will propose the application of shift-and-add algorithms based on CORDIC to these problems. We will make a comparison between the different methods applied in terms of the precision of the results and the number of iterations required.

Detection and mapping of burnt areas from time series of MODIS-derived NDVI data in a Mediterranean region

Moderate resolution remote sensing data, as provided by MODIS, can be used to detect and map active or past wildfires from daily records of suitable combinations of reflectance bands. The objective of the present work was to develop and test simple algorithms and variations for automatic or semiautomatic detection of burnt areas from time series data of MODIS biweekly vegetation indices for a Mediterranean region. MODIS-derived NDVI 250m time series data for the Valencia region, East Spain, were subjected to a two-step process for the detection of candidate burnt areas, and the results compared with available fire event records from the Valencia Regional Government. For each pixel and date in the data series, a model was fitted to both the previous and posterior time series data. Combining drops between two consecutive points and 1-year average drops, we used discrepancies or jumps between the pre and post models to identify seed pixels, and then delimitated fire scars for each potential wildfire using an extension algorithm from the seed pixels. The resulting maps of the detected burnt areas showed a very good agreement with the perimeters registered in the database of fire records used as reference. Overall accuracies and indices of agreement were very high, and omission and commission errors were similar or lower than in previous studies that used automatic or semiautomatic fire scar detection based on remote sensing. This supports the effectiveness of the method for detecting and mapping burnt areas in the Mediterranean region.

Gagauzia: growing separatism in Moldova? OSW Commentary No. 129, 10.03.2014

On 2 February, the regional authorities in Gagauzia - an autonomous region of the Republic of Moldova - carried out two simultaneous referenda. In the first, local residents were asked to declare their support for the country’s integration either with the EU or with the Moscow-led Customs Union (CU); the second referendum sought their opinion on the draft law “On the deferred status of the Autonomous Region of Gagauzia”. Under the proposed legislation, if Moldova were to lose its sovereignty (for example, through the unification of Moldova and Romania, or even as some politicians have argued, through Moldova’s further integration with the EU), the autonomous region would automatically become the independent Republic of Gagauzia. As expected, the outcome of the vote has shown overwhelming support for both the CU and for the draft law. According to the figures released by Gagauzia’s Central Electoral Commission, 98.5% of the voters supported Moldova’s integration with the Customs Union, while 98% voted in favour of the ‘deferred independence’ bill. Support for closer integration with the EU was marginal, reaching just over 2%. Despite the one-sided outcome of the referendum, there is no reliable evidence to suggest that the ballot was rigged. It should also be noted that voter turnout was very high, reaching about 70%. Representatives of the Moldovan Central Electoral Commission, however, believe that the figure may have been artificially inflated by excluding many of the voters currently residing abroad from the count.

Azerbaijan-a growing problem for the West. OSW Commentary No. 146, 15.09.2014

Azerbaijan’s cooperation with the West, launched two decades ago, has helped it become a relatively strong and ambitious actor on the international stage. It has become a key country in the region from the Western (USA and the EU) and Turkish points of view, as well as an important partner in the energy sector. The strategic EU concept of the Southern Gas Corridor, also supported by the United States, is among the initiatives based on cooperation with Azerbaijan. Surprisingly, however, Azerbaijan’s increased ambition and importance have caused its policy to diverge ever farther from the expectations and plans formulated by the West. The changes in the balance of power in the South Caucasus, occurring in the context of the conflict in Ukraine, have forced Azerbaijan to revise its assessment of its position in the region. The main impetus for Azerbaijan’s actions is fear of Russia, as well as the weakness of the West which has become particularly apparent in the recent stages of the Ukrainian crisis. Azerbaijan’s actions so far have displayed its tendency to deepen its self-isolation in foreign affairs and consolidate its authoritarian system. This comes as a challenge to the West, whose ability to shape its relations with Azerbaijan has weakened considerably. This state of affairs poses the threat that in the current situation, the Southern Gas Corridor concept, which Azerbaijan amended in 2012 in its own favour, might become totally blocked.

Growing healthy seedlings : identification and management of pests in Northwest forest nurseries /

"R6-PNW-019-90."

Sequence diversity in the coat protein coding region of the genome RNA of Johnsongrass mosaic virus in Australia

Sequence diversity in the coat protein coding region of Australian strains of Johnsongrass mosaic virus (JGMV) was investigated. Field isolates were sampled during a seven year period from Johnsongrass, sorghum and corn across the northern grain growing region. The 23 isolates were found to have greater than 94% nucleotide and amino acid sequence identity. The Australian isolates and two strains from the U.S.A. had about 90% nucleotide sequence identity and were between 19 and 30% different in the N-terminus of the coat protein. Two amino acid residues were found in the core region of the coat protein in isolates obtained from sorghum having the Krish gene for JGMV resistance that differed from those found in isolates from other hosts which did not have this single dominant resistance gene. These amino acid changes may have been responsible for overcoming the resistance conferred by the Krish gene for JGMV resistance in sorghum. The identification of these variable regions was essential for the development of durable pathogen-derived resistance to JGMV in sorghum.

Expansion-based algorithms for finding single pair shortest path on surface

Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.

Assessment of national health systems performance in the WHO African region

There is growing peer and donor pressure on African countries to utilize available resources more efficiently in a bid to support the ongoing efforts to expand coverage of health interventions with a view to achieving the health-related Millennium Development Goals. The purpose of this study was to estimate the technical and scale efficiency of national health systems in African continent. Methods The study applied the Data Envelopment Analysis approach to estimate the technical efficiency and scale efficiency among the 53 countries of the African Continent. Results Out of the 38 low-income African countries, 12 countries national health systems manifested a constant returns to scale technical efficiency (CRSTE) score of 100%; 15 countries had a VRSTE score of 100%; and 12 countries had a SE score of one. The average variable returns to scale technical efficiency (VRSTE) score was 95% and the mean scale efficiency (SE) score was 59%; meaning that while on average the degree of inefficiency was only 5%, the magnitude of scale inefficiency was 41%. Of the 15 middle-income countries, 5 countries, 9 countries and 5 countries had CRSTE, VRSTE and SE scores of 100%. Ten countries, six countries and 10 countries had CRSTE, VRSTE and SE scores of less than 100%; and thus, they were deemed inefficient. The average VRSTE (i.e. pure efficiency) score was 97.6%. The average SE score was 49.9%. Conclusion There are large unmet need for health and health-related services among countries of the African Continent. Thus, it would not be advisable for health policy-makers address NHS inefficiencies through reduction in excess human resources for health. Instead, it would be more prudent for them to leverage health promotion approaches and universal access prepaid (tax-based, insurance-based or mixtures) health financing systems to create demand for under utilised health services/interventions with a view to increasing ultimate health outputs to efficient target levels.

A Framework for Fast Classification Algorithms

Today, due to globalization of the world the size of data set is increasing, it is necessary to discover the knowledge. The discovery of knowledge can be typically in the form of association rules, classification rules, clustering, discovery of frequent episodes and deviation detection. Fast and accurate classifiers for large databases are an important task in data mining. There is growing evidence that integrating classification and association rules mining, classification approaches based on heuristic, greedy search like decision tree induction. Emerging associative classification algorithms have shown good promises on producing accurate classifiers. In this paper we focus on performance of associative classification and present a parallel model for classifier building. For classifier building some parallel-distributed algorithms have been proposed for decision tree induction but so far no such work has been reported for associative classification.

Neural-Like Growing Networks in Intelligent System of Recognition of Images

The neural-like growing networks used in the intelligent system of recognition of images are under consideration in this paper. All operations made over the image on a pre-design stage and also classification and storage of the information about the images and their further identification are made extremely by mechanisms of neural-like networks without usage of complex algorithms requiring considerable volumes of calculus. At the conforming hardware support the neural network methods allow considerably to increase the effectiveness of the solution of the given class of problems, saving a high accuracy of result and high level of response, both in a mode of training, and in a mode of identification.

Evaluating the spatial transferability and temporal repeatability of remote-sensing-based lake water quality retrieval algorithms at the European scale: a meta-analysis approach

Many studies have shown the considerable potential for the application of remote-sensing-based methods for deriving estimates of lake water quality. However, the reliable application of these methods across time and space is complicated by the diversity of lake types, sensor configuration, and the multitude of different algorithms proposed. This study tested one operational and 46 empirical algorithms sourced from the peer-reviewed literature that have individually shown potential for estimating lake water quality properties in the form of chlorophyll-a (algal biomass) and Secchi disc depth (SDD) (water transparency) in independent studies. Nearly half (19) of the algorithms were unsuitable for use with the remote-sensing data available for this study. The remaining 28 were assessed using the Terra/Aqua satellite archive to identify the best performing algorithms in terms of accuracy and transferability within the period 2001–2004 in four test lakes, namely Vänern, Vättern, Geneva, and Balaton. These lakes represent the broad continuum of large European lake types, varying in terms of eco-region (latitude/longitude and altitude), morphology, mixing regime, and trophic status. All algorithms were tested for each lake separately and combined to assess the degree of their applicability in ecologically different sites. None of the algorithms assessed in this study exhibited promise when all four lakes were combined into a single data set and most algorithms performed poorly even for specific lake types. A chlorophyll-a retrieval algorithm originally developed for eutrophic lakes showed the most promising results (R2 = 0.59) in oligotrophic lakes. Two SDD retrieval algorithms, one originally developed for turbid lakes and the other for lakes with various characteristics, exhibited promising results in relatively less turbid lakes (R2 = 0.62 and 0.76, respectively). The results presented here highlight the complexity associated with remotely sensed lake water quality estimates and the high degree of uncertainty due to various limitations, including the lake water optical properties and the choice of methods.

Giant condyloma acuminatum quickly growing. Case report

Background. Giant Condyloma Acuminatum (GCA) is a rare, slow growing, large cauliflower tumor of the penile foreskin and perianal region with benign histologic appearance but high propensity for local invasion and recurrences. GCA is associated with Human Papilloma Virus (HPV) types 6 and 11 and it also has considerable risk of neoplastic transformation into fully invasive squamous cell carcinoma into about 5 years. Objective. Because of the rarity of perianal GCA, to date there is no general agreement on the best method for treatment. We wanted to know if surgical approach only was a good method to treat our case. Case report. A 28 years old man, HIV-negative, with a 4 years history of perianal GCA quickly growing underwent full tickness local excision at least 0,7 cm margin of normal tissue with skin grafting taken from the thighs. Fecal contamination was avoided by diet and loperamide per os. At two years follow-up no recurrence was detected. Conclusion. Surgical approach with full tickness excision and immediate skin-grafting and regular follow-up demonstrated effective to treat GCA and to minimize disease recurrence.

Active Foreground Region Extraction and Tracking for Sports Video Annotation

Automatic video segmentation plays a vital role in sports videos annotation. This paper presents a fully automatic and computationally efficient algorithm for analysis of sports videos. Various methods of automatic shot boundary detection have been proposed to perform automatic video segmentation. These investigations mainly concentrate on detecting fades and dissolves for fast processing of the entire video scene without providing any additional feedback on object relativity within the shots. The goal of the proposed method is to identify regions that perform certain activities in a scene. The model uses some low-level feature video processing algorithms to extract the shot boundaries from a video scene and to identify dominant colours within these boundaries. An object classification method is used for clustering the seed distributions of the dominant colours to homogeneous regions. Using a simple tracking method a classification of these regions to active or static is performed. The efficiency of the proposed framework is demonstrated over a standard video benchmark with numerous types of sport events and the experimental results show that our algorithm can be used with high accuracy for automatic annotation of active regions for sport videos.

Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off Brazil

Many efforts are currently oriented toward extracting more information from ocean color than the chlorophyll a concentration. Among biological parameters potentially accessible from space, estimates of phytoplankton cell size and light absorption by colored detrital matter (CDM) would lead to an indirect assessment of major components of the organic carbon pool in the ocean, which would benefit oceanic carbon budget models. We present here 2 procedures to retrieve simultaneously from ocean color measurements in a limited number of bands, magnitudes, and spectral shapes for both light absorption by CDM and phytoplankton, along with a size parameter for phytoplankton. The performance of the 2 procedures was evaluated using different data sets that correspond to increasing uncertainties: ( 1) measured absorption coefficients of phytoplankton, particulate detritus, and colored dissolved organic matter ( CDOM) and measured chlorophyll a concentrations and ( 2) SeaWiFS upwelling radiance measurements and chlorophyll a concentrations estimated from global algorithms. In situ data were acquired during 3 cruises, differing by their relative proportions in CDM and phytoplankton, over a continental shelf off Brazil. No local information was introduced in either procedure, to make them more generally applicable. Over the study area, the absorption coefficient of CDM at 443 nm was retrieved from SeaWiFS radiances with a relative root mean square error (RMSE) of 33%, and phytoplankton light absorption coefficients in SeaWiFS bands ( from 412 to 510 nm) were retrieved with RMSEs between 28% and 33%. These results are comparable to or better than those obtained by 3 published models. In addition, a size parameter of phytoplankton and the spectral slope of CDM absorption were retrieved with RMSEs of 17% and 22%, respectively. If these methods are applied at a regional scale, the performances could be substantially improved by locally tuning some empirical relationships.