A simulation model of cereal-legume intercropping systems for semi-arid regions II. Model application

Smallholder farmers in Africa practice traditional cropping techniques such as intercropping. Intercropping is thought to offer higher productivity and resource milisation than sole cropping. In this study, risk associated with maize-bean intercropping was evaluated by quantifying long-term yield in both intercropping and sole cropping in a semi-arid region of South Africa (Bloemfontein, Free State) with reference to rainfall variability. The crop simulation model was run with different cultural practices (planting date and plant density) for 52 summer crop growing seasons (1950/1951-2001/2002). Eighty-one scenarios, consisted of three levels of initial soil water, planting date, maize population, and bean population, were simulated. From the simulation outputs, the total land equivalent ratio (LER) was greater than one. The intercrop (equivalent to sole maize) had greater energy value (EV) than sole beans, and the intercrop (equivalent to sole beans) had greater monetary value (MV) than sole maize. From these results, it can be concluded that maize-bean intercropping is advantageous for this semi-arid region. Soil water at planting was the most important factor of all scenario factors, followed by planting date. Irrigation application at planting, November/December planting and high plant density of maize for EV and beans for MV can be one of the most effective cultural practices in the study region. With regard to rainfall variability, seasonal (October-April) rainfall positively affected EV and MV, but not LER. There was more intercrop production in La Nina years than in El Nino years. Thus, better cultural practices may be selected to maximize maize-bean intercrop yields for specific seasons in the semi-arid region based on the global seasonal outlook. (c) 2004 Elsevier B.V. All rights reserved.

Enhanced detection-guided NLMS estimation of sparse FIR-modeled signal channels

In various signal-channel-estimation problems, the channel being estimated may be well approximated by a discrete finite impulse response (FIR) model with sparsely separated active or nonzero taps. A common approach to estimating such channels involves a discrete normalized least-mean-square (NLMS) adaptive FIR filter, every tap of which is adapted at each sample interval. Such an approach suffers from slow convergence rates and poor tracking when the required FIR filter is "long." Recently, NLMS-based algorithms have been proposed that employ least-squares-based structural detection techniques to exploit possible sparse channel structure and subsequently provide improved estimation performance. However, these algorithms perform poorly when there is a large dynamic range amongst the active taps. In this paper, we propose two modifications to the previous algorithms, which essentially remove this limitation. The modifications also significantly improve the applicability of the detection technique to structurally time varying channels. Importantly, for sparse channels, the computational cost of the newly proposed detection-guided NLMS estimator is only marginally greater than that of the standard NLMS estimator. Simulations demonstrate the favourable performance of the newly proposed algorithm. © 2006 IEEE.

Estimation of concentration-dependent diffusion coefficient in drying process from the space-averaged concentration versus time with experimental data

The estimation of a concentration-dependent diffusion coefficient in a drying process is known as an inverse coefficient problem. The solution is sought wherein the space-average concentration is known as function of time (mass loss monitoring). The problem is stated as the minimization of a functional and gradient-based algorithms are used to solve it. Many numerical and experimental examples that demonstrate the effectiveness of the proposed approach are presented. Thin slab drying was carried out in an isothermal drying chamber built in our laboratory. The diffusion coefficients of fructose obtained with the present method are compared with existing literature results.

Extraction of texture features from arbitrary-shaped regions for image retrieval

Lots of work has been done in texture feature extraction for rectangular images, but not as much attention has been paid to the arbitrary-shaped regions available in region-based image retrieval (RBIR) systems. In This work, we present a texture feature extraction algorithm, based on projection onto convex sets (POCS) theory. POCS iteratively concentrates more and more energy into the selected coefficients from which texture features of an arbitrary-shaped region can be extracted. Experimental results demonstrate the effectiveness of the proposed algorithm for image retrieval purposes.

3D protein structure matching by patch signatures

For determining functionality dependencies between two proteins, both represented as 3D structures, it is an essential condition that they have one or more matching structural regions called patches. As 3D structures for proteins are large, complex and constantly evolving, it is computationally expensive and very time-consuming to identify possible locations and sizes of patches for a given protein against a large protein database. In this paper, we address a vector space based representation for protein structures, where a patch is formed by the vectors within the region. Based on our previews work, a compact representation of the patch named patch signature is applied here. A similarity measure of two patches is then derived based on their signatures. To achieve fast patch matching in large protein databases, a match-and-expand strategy is proposed. Given a query patch, a set of small k-sized matching patches, called candidate patches, is generated in match stage. The candidate patches are further filtered by enlarging k in expand stage. Our extensive experimental results demonstrate encouraging performances with respect to this biologically critical but previously computationally prohibitive problem.

Complex Adaptive On-line Learning System “Theory of Automatic Control"

The controlled from distance teaching (DT) in the system of technical education has a row of features: complication of informative content, necessity of development of simulation models and trainers for conducting of practical and laboratory employments, conducting of knowledge diagnostics on the basis of mathematical-based algorithms, organization of execution collective projects of the applied setting. For development of the process of teaching bases of fundamental discipline control system Theory of automatic control (TAC) the combined approach of optimum combination of existent programmatic instruments of support was chosen DT and own developments. The system DT TAC included: controlled from distance course (DC) of TAC, site of virtual laboratory practical works in LAB.TAC and students knowledge remote diagnostic system d-tester.

Distance Matrix Approach to Content Image Retrieval

As the volume of image data and the need of using it in various applications is growing significantly in the last days it brings a necessity of retrieval efficiency and effectiveness. Unfortunately, existing indexing methods are not applicable to a wide range of problem-oriented fields due to their operating time limitations and strong dependency on the traditional descriptors extracted from the image. To meet higher requirements, a novel distance-based indexing method for region-based image retrieval has been proposed and investigated. The method creates premises for considering embedded partitions of images to carry out the search with different refinement or roughening level and so to seek the image meaningful content.

Event mining for system and service management

Modern IT infrastructures are constructed by large scale computing systems and administered by IT service providers. Manually maintaining such large computing systems is costly and inefficient. Service providers often seek automatic or semi-automatic methodologies of detecting and resolving system issues to improve their service quality and efficiency. This dissertation investigates several data-driven approaches for assisting service providers in achieving this goal. The detailed problems studied by these approaches can be categorized into the three aspects in the service workflow: 1) preprocessing raw textual system logs to structural events; 2) refining monitoring configurations for eliminating false positives and false negatives; 3) improving the efficiency of system diagnosis on detected alerts. Solving these problems usually requires a huge amount of domain knowledge about the particular computing systems. The approaches investigated by this dissertation are developed based on event mining algorithms, which are able to automatically derive part of that knowledge from the historical system logs, events and tickets. ^ In particular, two textual clustering algorithms are developed for converting raw textual logs into system events. For refining the monitoring configuration, a rule based alert prediction algorithm is proposed for eliminating false alerts (false positives) without losing any real alert and a textual classification method is applied to identify the missing alerts (false negatives) from manual incident tickets. For system diagnosis, this dissertation presents an efficient algorithm for discovering the temporal dependencies between system events with corresponding time lags, which can help the administrators to determine the redundancies of deployed monitoring situations and dependencies of system components. To improve the efficiency of incident ticket resolving, several KNN-based algorithms that recommend relevant historical tickets with resolutions for incoming tickets are investigated. Finally, this dissertation offers a novel algorithm for searching similar textual event segments over large system logs that assists administrators to locate similar system behaviors in the logs. Extensive empirical evaluation on system logs, events and tickets from real IT infrastructures demonstrates the effectiveness and efficiency of the proposed approaches.^

Análise da influência do efeito esteira de aerogeradores no microclima na superfície do solo: o caso do parque eólico piloto de Macau/RN

This study aimed to evaluate the microclimate changes surrounding the wind farm Macau Pilot / RN, present in the municipality of the same name. To achieve this goal made use of remote sensing techniques using Landsat - 5 TM and 7 ETM +, from which made it possible evaluation of temperature changes on the surface, this around the park in periods prior to its implementation, to the today. For evaluation of the temperature data that has been generated by applying a template was performed its correlation with field data collection and evaluated the degree of correlation, in order to confirm the validity of the data acquired by satellite. Also held was a characterization of the climate of the region based on the data of this climatological station in Macau. Once collected this data made possible the evaluation of climate change policy in the study region. After validation of the temperature models, an analysis of the generated temperature histograms was performed visually could not identify any significant change. However when analyzing the temperature data at a higher level of detail, a data pattern of behavior was detected for both periods evaluated, yet could not see a distinction between the periods of pre-operation of the park, and post-operation . From this result was levantas hypotheses to explain the behavior of the data, the first of which is the presence of moisture in the soil, and the second to the soil composition. In order to validate the hypotheses were applied PDI techniques, involving a combination of different RGB bands of Landsat 5 and the implementation of Reason bands procedure that might show the elements present on the soil surface.

Representaciones sociales acerca de la televisión colombiana y su vínculo con la identidad cultural en Cartagena.1970-1986

Esta investigación hace un aporte a la construcción de la historia de la televisión colombiana desde la región Caribe, partiendo de los recuerdos de los habitantes de Cartagena, con el objetivo de determinar de qué manera se relacionaron con ella y si existe o no un vínculo con la identidad cultural durante el período 1970-1986. Para identificar este lazo se recurrió a la teoría de las representaciones sociales propuesta por Moscovici y Jodelet, que sirvió como sustento metodológico del trabajo. La información obtenida con la implementación de técnicas cualitativas, dieron origen a una serie de categorías con las cuales se encontró que a través del relacionamiento con la televisión, los cartageneros empezaron a construir una identidad basada en un sentir nacional, que durante un tiempo estuvo influenciada por la mirada construida desde el centro del país. Solo hasta la aparición del canal regional Telecaribe, el televidente de Cartagena inició la construcción de una identidad regional con la cual si se sentía cercano. Las principales representaciones relacionadas con la identidad cultural se refieren a “colombianidad”, “falsa costeñidad” y “costeñidad”, entre otras; la manera en que se nombraron y describieron estas representaciones serán descritas en este informe.

Géodiversité sous-marine de Nouvelle-Calédonie. 1ère partie

The object of this article is to offer a synthesis of the knowledge clarifying the originality and the diversity of the submarine geological formations of the New Caledonian EEZ. A reminder is given onto the geologic history of the region, based upon the dislocation of the Gondwana Continent, the opening of the Tasman Sea, the presence of submarine volcanism, the setting up of heavy peridotitic rocks, the building up of the Fairway and Lord Howe Ridges and of sedimentary basins, the formation of volcanic domes and sea-mounts or guyots, the subduction along the Vanuatu Trench, the uplift of the Loyalty Islands, the development of carbonated ptatforms around the islands etc.... Of this complex history ensues an exceptional submarine geo-diversity. After this presentation the article clarifies the methods and the tools used in marine geosciences to map, explore, observe, analyze, sample, that they are embarked or are autonomous, teleoperated or inhabited systems. A chapter describes the programs which were set up since about forty years and the results obtained as well as the scientific teams concerned with. In conclusion, based on the unpublished character of this geo-diversity, the article introduces the second text to come in a next issue of theTai Kona magazine, text which will focus on the scientific, economic (mineral resources), environmental (deep biodiversity) and risks (seismicity) challenges that are worn by one of the most original submarine geologic context in the world.

A study of computational methods to analyze gene expression data

The recent advent of new technologies has led to huge amounts of genomic data. With these data come new opportunities to understand biological cellular processes underlying hidden regulation mechanisms and to identify disease related biomarkers for informative diagnostics. However, extracting biological insights from the immense amounts of genomic data is a challenging task. Therefore, effective and efficient computational techniques are needed to analyze and interpret genomic data. In this thesis, novel computational methods are proposed to address such challenges: a Bayesian mixture model, an extended Bayesian mixture model, and an Eigen-brain approach. The Bayesian mixture framework involves integration of the Bayesian network and the Gaussian mixture model. Based on the proposed framework and its conjunction with K-means clustering and principal component analysis (PCA), biological insights are derived such as context specific/dependent relationships and nested structures within microarray where biological replicates are encapsulated. The Bayesian mixture framework is then extended to explore posterior distributions of network space by incorporating a Markov chain Monte Carlo (MCMC) model. The extended Bayesian mixture model summarizes the sampled network structures by extracting biologically meaningful features. Finally, an Eigen-brain approach is proposed to analyze in situ hybridization data for the identification of the cell-type specific genes, which can be useful for informative blood diagnostics. Computational results with region-based clustering reveals the critical evidence for the consistency with brain anatomical structure.

O pedestrianismo como instrumento de valorização ecoturística dos sítios da Rede Natura 2000, nas ilhas de São Miguel e Flores

Tese de Doutoramento, Ciências do Ambiente (Ecologia), 30 de Julho de 2013, Universidade dos Açores.

Análise da silvicultura na bacia hidrográfica do rio Jaguarão (Brasil-Uruguai) : diagnóstico para a gestão geoambiental em bacia transfronteiriça

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Humanas, Departamento de Geografia, 2015.

Modelling of an efficient dynamic smart solar photovoltaic power grid system

A smart solar photovoltaic grid system is an advent of innovation coherence of information and communications technology (ICT) with power systems control engineering via the internet [1]. This thesis designs and demonstrates a smart solar photovoltaic grid system that is selfhealing, environmental and consumer friendly, but also with the ability to accommodate other renewable sources of energy generation seamlessly, creating a healthy competitive energy industry and optimising energy assets efficiency. This thesis also presents the modelling of an efficient dynamic smart solar photovoltaic power grid system by exploring the maximum power point tracking efficiency, optimisation of the smart solar photovoltaic array through modelling and simulation to improve the quality of design for the solar photovoltaic module. In contrast, over the past decade quite promising results have been published in literature, most of which have not addressed the basis of the research questions in this thesis. The Levenberg-Marquardt and sparse based algorithms have proven to be very effective tools in helping to improve the quality of design for solar photovoltaic modules, minimising the possible relative errors in this thesis. Guided by theoretical and analytical reviews in literature, this research has carefully chosen the MatLab/Simulink software toolbox for modelling and simulation experiments performed on the static smart solar grid system. The auto-correlation coefficient results obtained from the modelling experiments give an accuracy of 99% with negligible mean square error (MSE), root mean square error (RMSE) and standard deviation. This thesis further explores the design and implementation of a robust real-time online solar photovoltaic monitoring system, establishing a comparative study of two solar photovoltaic tracking systems which provide remote access to the harvested energy data. This research made a landmark innovation in designing and implementing a unique approach for online remote access solar photovoltaic monitoring systems providing updated information of the energy produced by the solar photovoltaic module at the site location. In addressing the challenge of online solar photovoltaic monitoring systems, Darfon online data logger device has been systematically integrated into the design for a comparative study of the two solar photovoltaic tracking systems examined in this thesis. The site location for the comparative study of the solar photovoltaic tracking systems is at the National Kaohsiung University of Applied Sciences, Taiwan, R.O.C. The overall comparative energy output efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic monitoring system as observed at the research location site is about 72% based on the total energy produced, estimated money saved and the amount of CO2 reduction achieved. Similarly, in comparing the total amount of energy produced by the two solar photovoltaic tracking systems, the overall daily generated energy for the month of July shows the effectiveness of the azimuthal-altitude tracking systems over the 450 stationary solar photovoltaic system. It was found that the azimuthal-altitude dual-axis tracking systems were about 68.43% efficient compared to the 450 stationary solar photovoltaic systems. Lastly, the overall comparative hourly energy efficiency of the azimuthal-altitude dual-axis over the 450 stationary solar photovoltaic energy system was found to be 74.2% efficient. Results from this research are quite promising and significant in satisfying the purpose of the research objectives and questions posed in the thesis. The new algorithms introduced in this research and the statistical measures applied to the modelling and simulation of a smart static solar photovoltaic grid system performance outperformed other previous works in reviewed literature. Based on this new implementation design of the online data logging systems for solar photovoltaic monitoring, it is possible for the first time to have online on-site information of the energy produced remotely, fault identification and rectification, maintenance and recovery time deployed as fast as possible. The results presented in this research as Internet of things (IoT) on smart solar grid systems are likely to offer real-life experiences especially both to the existing body of knowledge and the future solar photovoltaic energy industry irrespective of the study site location for the comparative solar photovoltaic tracking systems. While the thesis has contributed to the smart solar photovoltaic grid system, it has also highlighted areas of further research and the need to investigate more on improving the choice and quality design for solar photovoltaic modules. Finally, it has also made recommendations for further research in the minimization of the absolute or relative errors in the quality and design of the smart static solar photovoltaic module.