Soil profile internal drainage for a central pivot fertigated coffee crop

Coffee cultivation via central-pivot fertigation can lead to fertilizer losses by soil profile internal drainage when water application is excessive and soils have low water retention and cation adsorption capacities. This study analyses the deep water losses from the top 1 m sandy soil layer of east Bahia, Brazil, cultivated with coffee at a high technology level (central-pivot fertigation), using above normal N fertilizer rates. The deep drainage (Q) estimation is made through the application of a climatologic water balance (CWB) program having as input direct measures of irrigation and rainfall, climatological data from weather stations, and measured soil water retention characteristics. The aim of the study is to contribute to the understanding of the hydric regime of coffee crops managed by central-pivot irrigation, analyzing three scenarios (Sc): i) rainfall only, ii) rainfall and irrigation full year, and iii) rainfall and irrigation dry season only. Annual Q values for the 2008/2009 agricultural year were: Sc i = 811.5 mm; Sc ii = 1010.5 mm; and Sc iii = 873.1 mm, so that the irrigation interruption in the wet season reduced Q by 15.7%, without the appearance of water deficit periods. Results show that the use of the CWB program is a convenient tool for the evaluation of Q under the cited conditions.

Consumer behavior and profile in cross border tourism destinations

Tourism is a phenomenon that moves millions of people around the world, taking as a major driver of the global economy. Such relevance is reflected in the proliferation of studies in the overall area known as tourism, under various perspectives and backgrounds. In the light of such multitude of insights our study aims at gaining a deeper understanding of customer profiling and behavior in cross-border tourism destinations. Previous studies conducted in such contexts suggest that cross-border regions (CBRs) are an attractive and desirable idea, yet requiring further theoretical and empirical research. The new configuration of many CBRs calls for a debate on issues concerning its development, raising up important dimensions, such as, organization and planning of common tourism destinations. There is still a gap in the understanding of destination management in CBRs and the customer profile and motivations. Overall this research aims at attaining a deeper understanding of the profile and behavior of consumers in tourism settings, addressing the predisposition for the destination. The study addresses the following research question: “What factors influence customer behavior and attitudes in a CBRs tourism destination?” To address our question we will take an interdisciplinary perspective bringing together inputs from marketing, tourism and local economics. When addressing consumer behavior in tourism previous studies considered the following constructs: involvement, place attachment, satisfaction and destination loyalty. In order to establish the causal relationships in our theoretical model, we intend to develop a predominant quantitative design, yet we plan to conduct exploratory interviews. In the analysis and discussion of results, we intend to use Structural Equation Modeling. It will further allow understanding how the constructs in the research model relate to each other in the specified context. Results are also expected to have managerial implications. Consequently our results may assist decision makers in developing their local policies.

Demographic profile and health conditions of the elderly in a community in an urban area of Southeastern Brazil

Some specific characteristics of the aging of the Brazilian population in different areas, states and communities all over the country, have shown significant variations. Historical series of demographic and health indicators for the population in their sixties and over in Brazil, state of S. Paulo and in the municipal district of Araraquara are listed as follows: level of education and urban population growth rate, income distribution, mortality rates and main causes of death. In 1991 the aged constituled were 7,8% of the Brazilian population and 9,7% in Araraquara community. The elderly population (of 70 years of aged and above) as a proportion of the whole, has increased and already stands for 40%. The same trend holds good for both the proportion of aged within the urban population and their level of education wich increased to 90% in 1991. The main causes of death are chronic degenerative diseases which have replaced the infectious illness: firts, the diseases of the circulatory sistem (which account for more than 40% of all deaths) and the neoplasms (which let to 15% of the deaths). On the basis of these health and demographic data relating to people of 60 years of age and over, this study suggests some procedures for the improvement of the quality of the assistance given to the target population: a) the assistance give to the aged should be improved by providing gerontological training for general physicians and nurses, both of public and private clinics; b) the already exixting educational activities for the aged, for health workers and for teachers of secundary education should be further developed; c) the number of day-hospitals should be increased for the purpose of avoiding unnecessary confinement so as maintain the low rate of institutionalization in homes for the elderly (0,7% in Araraquara). It is reported that at least 35% of the aged population in this area is entitled to private health assistance, wich brings out the importance of including such services in the local health programs for this group.

Photonics Active Filters Based on SiC Multi layer Structures: A Two Stage Active Circuit

Characteristics of tunable wavelength filters based on a-SiC:H multi-layered stacked cells are studied both theoretically and experimentally. Results show that the light-activated photonic device combines the demultiplexing operation with the simultaneous photodetection and self amplification of an optical signal. The sensor is a bias wavelength current-controlled device that make use of changes in the wavelength of the background to control the power delivered to the load, acting a photonic active filter. Its gain depends on the background wavelength that controls the electrical field profile across the device.

Definition of MV Load Diagrams via Weighted Evidence Accumulation Clustering using Subsampling

A definition of medium voltage (MV) load diagrams was made, based on the data base knowledge discovery process. Clustering techniques were used as support for the agents of the electric power retail markets to obtain specific knowledge of their customers’ consumption habits. Each customer class resulting from the clustering operation is represented by its load diagram. The Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) were applied to an electricity consumption data from a utility client’s database in order to form the customer’s classes and to find a set of representative consumption patterns. The WEACS approach is a clustering ensemble combination approach that uses subsampling and that weights differently the partitions in the co-association matrix. As a complementary step to the WEACS approach, all the final data partitions produced by the different variations of the method are combined and the Ward Link algorithm is used to obtain the final data partition. Experiment results showed that WEACS approach led to better accuracy than many other clustering approaches. In this paper the WEACS approach separates better the customer’s population than Two-step clustering algorithm.

Determination of electricity consumers’ load profiles via weighted evidence accumulation clustering using subsampling

With the electricity market liberalization, the distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity consumers. A fair insight on the consumers’ behavior will permit the definition of specific contract aspects based on the different consumption patterns. In order to form the different consumers’ classes, and find a set of representative consumption patterns we use electricity consumption data from a utility client’s database and two approaches: Two-step clustering algorithm and the WEACS approach based on evidence accumulation (EAC) for combining partitions in a clustering ensemble. While EAC uses a voting mechanism to produce a co-association matrix based on the pairwise associations obtained from N partitions and where each partition has equal weight in the combination process, the WEACS approach uses subsampling and weights differently the partitions. As a complementary step to the WEACS approach, we combine the partitions obtained in the WEACS approach with the ALL clustering ensemble construction method and we use the Ward Link algorithm to obtain the final data partition. The characterization of the obtained consumers’ clusters was performed using the C5.0 classification algorithm. Experiment results showed that the WEACS approach leads to better results than many other clustering approaches.

Data mining contributions to characterize MV consumers and to improve the suppliers-consumers settlements

This paper deals with the establishment of a characterization methodology of electric power profiles of medium voltage (MV) consumers. The characterization is supported on the data base knowledge discovery process (KDD). Data Mining techniques are used with the purpose of obtaining typical load profiles of MV customers and specific knowledge of their customers’ consumption habits. In order to form the different customers’ classes and to find a set of representative consumption patterns, a hierarchical clustering algorithm and a clustering ensemble combination approach (WEACS) are used. Taking into account the typical consumption profile of the class to which the customers belong, new tariff options were defined and new energy coefficients prices were proposed. Finally, and with the results obtained, the consequences that these will have in the interaction between customer and electric power suppliers are analyzed.

Typical load profiles in the smart grid context – a clustering methods comparison

The present research paper presents five different clustering methods to identify typical load profiles of medium voltage (MV) electricity consumers. These methods are intended to be used in a smart grid environment to extract useful knowledge about customer’s behaviour. The obtained knowledge can be used to support a decision tool, not only for utilities but also for consumers. Load profiles can be used by the utilities to identify the aspects that cause system load peaks and enable the development of specific contracts with their customers. The framework presented throughout the paper consists in several steps, namely the pre-processing data phase, clustering algorithms application and the evaluation of the quality of the partition, which is supported by cluster validity indices. The process ends with the analysis of the discovered knowledge. To validate the proposed framework, a case study with a real database of 208 MV consumers is used.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Contextual intelligent load management with ANN adaptive learning module

With the current increase of energy resources prices and environmental concerns intelligent load management systems are gaining more and more importance. This paper concerns a SCADA House Intelligent Management (SHIM) system that includes an optimization module using deterministic and genetic algorithm approaches. SHIM undertakes contextual load management based on the characterization of each situation. SHIM considers available generation resources, load demand, supplier/market electricity price, and consumers’ constraints and preferences. The paper focus on the recently developed learning module which is based on artificial neural networks (ANN). The learning module allows the adjustment of users’ profiles along SHIM lifetime. A case study considering a system with fourteen discrete and four variable loads managed by a SHIM system during five consecutive similar weekends is presented.

Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming

In the energy management of the isolated operation of small power system, the economic scheduling of the generation units is a crucial problem. Applying right timing can maximize the performance of the supply. The optimal operation of a wind turbine, a solar unit, a fuel cell and a storage battery is searched by a mixed-integer linear programming implemented in General Algebraic Modeling Systems (GAMS). A Virtual Power Producer (VPP) can optimal operate the generation units, assured the good functioning of equipment, including the maintenance, operation cost and the generation measurement and control. A central control at system allows a VPP to manage the optimal generation and their load control. The application of methodology to a real case study in Budapest Tech, demonstrates the effectiveness of this method to solve the optimal isolated dispatch of the DC micro-grid renewable energy park. The problem has been converged in 0.09 s and 30 iterations.

Intelligent SCADA for load control

A supervisory control and data acquisition (SCADA) system is an integrated platform that incorporates several components and it has been applied in the field of power systems and several engineering applications to monitor, operate and control a lot of processes. In the future electrical networks, SCADA systems are essential for an intelligent management of resources like distributed generation and demand response, implemented in the smart grid context. This paper presents a SCADA system for a typical residential house. The application is implemented on MOVICON™11 software. The main objective is to manage the residential consumption, reducing or curtailing loads to keep the power consumption in or below a specified setpoint, imposed by the costumer and the generation availability.

Low Profile Multi-Band Antenna for Mobile Communications

In this paper, the design of low profile antennas by using Electromagnetic Band Gap (EBG) structures is introduced. Taking advantage of the fact that they can behave as Perfect Magnetic Conductor (PMC), it is shown that these structures exhibit dual band in-phase reflection at WLAN (Wireless Local Area Network) bands, the 2.4 GHz and 5.2 GHz bands. These structures are applied to PIFA (Planar Inverted-F Antenna) and the results show that it is possible to obtain low profile PIFA's.

Lipid content and fatty acid profile of Senegalese sole (Solea senegalensis Kaup, 1858) juveniles as affected by feed containing different amounts of plant protein sources

A growth trial with Senegalese Sole (Solea senegalensis Kaup, 1858) juveniles fed with diets containing increasing replacement levels of fishmeal by mixtures of plant protein sources was conducted over 12 weeks. Total fat contents of muscle, liver, viscera, skin, fins and head tissues were determined, as well as fatty acid profiles of muscle and liver (GC-FID analysis). Liver was the preferential local for fat deposition (5.5–10.8% of fat) followed by fins (3.4–6.7% fat). Increasing levels of plant protein in the diets seems to be related to increased levels of total lipids in the liver. Sole muscle is lean (2.4–4.0% fat), with total lipids being similar among treatments. Liver fatty acid profile varied significantly among treatments. Plant protein diets induced increased levels of C16:1 and C18:2 n -6 and a decrease in ARA and EPA levels. Muscle fatty acid profile also evidenced increasing levels of C18:2 n 6, while ARA and DHA remained similar among treatments. Substitution of fishmeal by plant protein is hence possible without major differences on the lipid content and fatty acid profile of the main edible portion of the fish – the muscle.