An analysis of poverty and aquatic resources use - focusing especially on the livelihoods of the poor - in Cambodia

The main objectives of this report, which is based on the current literature and key informant interviews, is to assess and analyse the nature and distribution of poverty and aquatic resources use, focusing especially on the livelihoods of the poor. It describes and reports different ways of measuring poverty that are used in Cambodia and quantifies the diverse nature and geographic distribution of aquatic resources use in Cambodia. (PDF contains 55 pages)

Optimization of Generation and Aggregated Consumption Shifting for Demand Response Programs Definition

The concept of demand response has drawing attention to the active participation in the economic operation of power systems, namely in the context of recent electricity markets and smart grid models and implementations. In these competitive contexts, aggregators are necessary in order to make possible the participation of small size consumers and generation units. The methodology proposed in the present paper aims to address the demand shifting between periods, considering multi-period demand response events. The focus is given to the impact in the subsequent periods. A Virtual Power Player operates the network, aggregating the available resources, and minimizing the operation costs. The illustrative case study included is based on a scenario of 218 consumers including generation sources.

Quantum-based Particle Swarm Optimization Application to Studies of Aggregated Consumption Shifting and Generation Scheduling in Smart Grids

Demand response programs and models have been developed and implemented for an improved performance of electricity markets, taking full advantage of smart grids. Studying and addressing the consumers’ flexibility and network operation scenarios makes possible to design improved demand response models and programs. The methodology proposed in the present paper aims to address the definition of demand response programs that consider the demand shifting between periods, regarding the occurrence of multi-period demand response events. The optimization model focuses on minimizing the network and resources operation costs for a Virtual Power Player. Quantum Particle Swarm Optimization has been used in order to obtain the solutions for the optimization model that is applied to a large set of operation scenarios. The implemented case study illustrates the use of the proposed methodology to support the decisions of the Virtual Power Player in what concerns the duration of each demand response event.

Resources use and conservation attitudes of local people in the Western Terai landscape, Nepal

Two protected areas: Royal Bardia National Park (RBNP) and Royal Suklaphanta Wildlife Reserve (RSWR) in the Western Terai, Nepal, are under threats due to present political turmoil, uncontrolled immigration, inefficient land reform policies and unsustainable resource use. I did a stratified random questionnaire survey of 234 households to determine how resource use patterns and problems influence conservation attitudes. Chi-square, Student's t, Mann-Whitney and Kruskal-Wallis tests, and multiple regression were used. There was spatio-temporal variability in resource use patterns and dependency. People were collecting eight and seven types of resources in RBNP and RSWR, respectively. However, people in RBNP were more dependent on resources than RSWR. In both areas, the problem of firewood is serious. The mean attitude score of RBNP (8.4 ± 1.44) was significantly higher than the score of RSWR (7.7 ± 1.66; t = 3.24, p = 0.0007). Conservation attitude was determined by variables such as participation in trainings, wildlife damage, and satisfaction towards user groups.

Evaluation for use efficiency of agricultural resources in grain production: A case study of Changshu, Taihe and Ansai in China

National Natural Science Foundation of China [70673097]

Constrained Consumption Shifting Management in the Distributed Energy Resources Scheduling Considering Demand Response

Demand response concept has been gaining increasing importance while the success of several recent implementations makes this resource benefits unquestionable. This happens in a power systems operation environment that also considers an intensive use of distributed generation. However, more adequate approaches and models are needed in order to address the small size consumers and producers aggregation, while taking into account these resources goals. The present paper focuses on the demand response programs and distributed generation resources management by a Virtual Power Player that optimally aims to minimize its operation costs taking the consumption shifting constraints into account. The impact of the consumption shifting in the distributed generation resources schedule is also considered. The methodology is applied to three scenarios based on 218 consumers and 4 types of distributed generation, in a time frame of 96 periods.

Optimization techniques for hydrologic engineering /

Mode of access: Internet.

Coping resources, coping strategies and adaptation to organisational change : direct or buffering effects?

This study examined the effects of personal and social resources, coping strategies and appraised stress on employees' levels of anxiety and depression. In relation to the effects of resources and coping strategies, two different models were tested. The main effects model proposes that, irrespective of the level of stress, coping resources and coping strategies have direct effects on well-being. In contrast, the buffering model predicts that the buffering effects of coping resources and strategies are only evident at high levels of stress. One hundred lawyers completed a structured self-administered questionnaire that measured their personal and social resources, use of problem-focused and emotion-focused coping strategies, and appraisals of the stressfulness of the situation. Results revealed generally strong support for the main effects model in the prediction of employee levels of anxiety and depression. Lower levels of anxiety were linked to judgements of lower levels of organizational change, greater self-confidence, greater internality of control beliefs and less use of emotion-focused coping strategies. Lower levels of depression in employees were also linked to judgements of lower levels of organizational change, greater use of resources and less appraised stress. There was only limited support for the buffering effects model. Due to the small size of the sample, the findings need to be explored further in other contexts.

A implantação do sistema gerencial de custos (SISCUSTOS) desenvolvido pelo Exército Brasileiro: estudo de caso na 1 Inspetoria de Contabilidade e Finanças do Exército

A implantação de sistemas de custos no setor público tem sido apontada como uma necessidade gerencial primordial para se alcançar as dimensões dos princípios da eficiência, eficácia e efetividade na administração pública, fato que proporcionaria a otimização do uso dos escassos recursos disponíveis. Com o advento da Lei de Responsabilidade Fiscal entrou em evidência a discussão sobre o tema no cenário nacional, sendo mais recentemente criada no governo federal uma comissão interministerial de custos com objetivo de elaborar estudos e propor diretrizes, métodos e procedimentos para subsidiar a implantação de Sistemas de Custos na Administração Pública Federal. Tendo em vistas essas necessidades, o presente trabalho tem por objetivo principal verificar a adequabilidade do Sistema Gerencial de Custos (SISCUSTOS) implantado no Exército Brasileiro permite a apuração de custos sob a ótica da teoria contábil e complementarmente analisar se o sistema de custos adequasse as metodologias do custeio ABC e fornece subsídios para a tomada de decisões. Para isso realizou-se um estudo de caso de natureza qualitativa, coletando-se dados de fontes primárias e secundárias, além de entrevistas com os servidores responsáveis pelo desenvolvimento, implantação e operacionalização do sistema. O resultado verificado foi que as funcionalidades disponibilizadas pelo SISCUSTOS vislumbram a aderência do sistema com o plano teórico, permitindo que as informações extraídas da contabilidade governamental contemporânea sejam ajustadas, para uma possível aproximação da contabilidade orçamentária com a contabilidade patrimonial, necessitando apenas de alguns ajustes para itens aqui denominados como peculiares da contabilidade governamental. No caso do método de custeio ABC observou-se que a metodologia está sendo subtilizada, e que o grau desejado em extrair todas as contribuições disponibilizadas pelo ABC somente virá com a maturidade da gestão de custos, sendo que, para atingir tais objetivos haverá a necessidade de se fixar como atributos cognitivos os 4C - Cultura de Custos, Comprometimento, Competição e Confiabilidade - entre os usuários do sistema e a alta administração.

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.

Derivative-free optimization and filter methods to solve nonlinear constrained problems

In real optimization problems, usually the analytical expression of the objective function is not known, nor its derivatives, or they are complex. In these cases it becomes essential to use optimization methods where the calculation of the derivatives, or the verification of their existence, is not necessary: the Direct Search Methods or Derivative-free Methods are one solution. When the problem has constraints, penalty functions are often used. Unfortunately the choice of the penalty parameters is, frequently, very difficult, because most strategies for choosing it are heuristics strategies. As an alternative to penalty function appeared the filter methods. A filter algorithm introduces a function that aggregates the constrained violations and constructs a biobjective problem. In this problem the step is accepted if it either reduces the objective function or the constrained violation. This implies that the filter methods are less parameter dependent than a penalty function. In this work, we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of the simplex method and filter methods. This method does not compute or approximate any derivatives, penalty constants or Lagrange multipliers. The basic idea of simplex filter algorithm is to construct an initial simplex and use the simplex to drive the search. We illustrate the behavior of our algorithm through some examples. The proposed methods were implemented in Java.

Environmental impacts of freshwater use and suspended solids in life cycle assessment

Perturbation of natural ecosystems, namely by increasing freshwater use and its degradative use, as well as topsoil erosion by water of land-use production systems, have been emerging as topics of high environmental concern. Freshwater use has become a focus of attention in the last few years for all stakeholders involved in the production of goods, mainly agro-industrial and forest-based products, which are freshwater-intensive consumers, requiring large inputs of green and blue water. This thesis presents a global review on the available Water Footprint Assessment and Life Cycle Assessment (LCA)-based methods for measuring and assessing the environmental relevance of freshwater resources use, based on a life cycle perspective. Using some of the available midpoint LCA-based methods, the freshwater use-related impacts of a Portuguese wine (white ‘vinho verde’) were assessed. However, the relevance of environmental green water has been neglected because of the absence of a comprehensive impact assessment method associated with green water flows. To overcome this constraint, this thesis helps to improve and enhance the LCA-based methods by providing a midpoint and spatially explicit Life Cycle Impact Assessment (LCIA) method for assessing impacts on terrestrial green water flow and addressing reductions in surface blue water production caused by reductions in surface runoff due to land-use production systems. The applicability of the proposed method is illustrated by a case study on Eucalyptus globulus conducted in Portugal, as the growth of short rotation forestry is largely dependent on local precipitation. Topsoil erosion by water has been characterised as one of the most upsetting problems for rivers. Because of this, this thesis also focuses on the ecosystem impacts caused by suspended solids (SS) from topsoil erosion that reach freshwater systems. A framework to conduct a spatially distributed SS delivery to freshwater streams and a fate and effect LCIA method to derive site-specific characterisation factors (CFs) for endpoint damage on aquatic ecosystem diversity, namely on algae, macrophyte, and macroinvertebrates organisms, were developed. The applicability of this framework, combined with the derived site-specific CFs, is shown by conducting a case study on E. globulus stands located in Portugal as an example of a land use based system. A spatially explicit LCA assessment was shown to be necessary, since the impacts associated with both green water flows and SS vary greatly as a function of spatial location.

Liderazgo de rango total y gestión del conocimiento: situación actual y perspectivas de desarrollo

El presente trabajo muestra los tipos de liderazgo de rango total y su relación con respecto a la gestión del conocimiento. Para ello, en primer lugar, se efectúa la investigación teórica del liderazgo transaccional y del liderazgo transformacional, ya que estos hacen parte del liderazgo de rango total, de igual forma se estudiará los aspectos primordiales de la gestión del conocimiento, dando cavidad al análisis de la relación entre dichos conceptos y cómo influyen en la perdurabilidad de las organizaciones. Se evidencian resultados que señalan: La existencia de una fuerte interrelación entre el liderazgo y la gestión del conocimiento, de forma que las empresas precisan de un mayor conocimiento acerca de las características del liderazgo para facilitar la comprensión e implantación de las mejores prácticas en la organización (Barbosa, Mihi & Noguera, 2013, sección de Resumen, párr. 1) Una organización se encuentra orientada a identificar objetivos y las estrategias más adecuadas para conseguirlos, siendo está una actividad primordial en la gestión empresarial, la cual logra organizar y disponer todos los recursos humanos para la optimización de cada uno de sus trabajadores teniendo en cuenta los efectos del entorno, por lo tanto la actualidad empresarial se encuentra guiada hacia la elección de personal con altas habilidades de liderazgo y gestión del conocimiento, siendo de esta forma la razón del estudio adecuado del liderazgo orientándonos en el modelo de liderazgo de rango total y la importancia de la gestión del conocimiento en la actualidad. Se evidencian numerosos estudios de investigación en donde se han relacionado el estilo de liderazgo organizacional con óptimos resultados (Vega & Zavala, 2004). Lo cual permite realizar investigaciones de diferentes autores sobre la relación que se evidencia entre la gestión del conocimiento y los diferentes tipos de liderazgo del modelo de rango total, y como sus actos pueden llevar a la organización privada a la perdurabilidad, lo cual se definiría como una organización que: A través del tiempo presenta resultados financieros superiores. Adecua su manejo a la intensidad de las condiciones del entorno sectorial y las fuerzas del mercado. Se enfoca en espacios no explotados y hace un estudio detallado de sus competidores diseñando y ejecutando productivamente la cadena de valor. Es aquella que obtiene desempeños eficientes en su gestión por la coherencia de su acción, la identificación de su entorno sectorial y sus políticas de gobierno, evitando estados de morbidez que dificultan su crecimiento rentable y que puede llegar a estados tanticos. Propicia la alineación de las personas con la empresa, la construcción de conocimiento y la calidad en los procesos de interacción social. (Rivera, 2012, p.107)

Composite SaaS resource management in cloud computing using evolutionary computation

Cloud computing is an emerging computing paradigm in which IT resources are provided over the Internet as a service to users. One such service offered through the Cloud is Software as a Service or SaaS. SaaS can be delivered in a composite form, consisting of a set of application and data components that work together to deliver higher-level functional software. SaaS is receiving substantial attention today from both software providers and users. It is also predicted to has positive future markets by analyst firms. This raises new challenges for SaaS providers managing SaaS, especially in large-scale data centres like Cloud. One of the challenges is providing management of Cloud resources for SaaS which guarantees maintaining SaaS performance while optimising resources use. Extensive research on the resource optimisation of Cloud service has not yet addressed the challenges of managing resources for composite SaaS. This research addresses this gap by focusing on three new problems of composite SaaS: placement, clustering and scalability. The overall aim is to develop efficient and scalable mechanisms that facilitate the delivery of high performance composite SaaS for users while optimising the resources used. All three problems are characterised as highly constrained, large-scaled and complex combinatorial optimisation problems. Therefore, evolutionary algorithms are adopted as the main technique in solving these problems. The first research problem refers to how a composite SaaS is placed onto Cloud servers to optimise its performance while satisfying the SaaS resource and response time constraints. Existing research on this problem often ignores the dependencies between components and considers placement of a homogenous type of component only. A precise problem formulation of composite SaaS placement problem is presented. A classical genetic algorithm and two versions of cooperative co-evolutionary algorithms are designed to now manage the placement of heterogeneous types of SaaS components together with their dependencies, requirements and constraints. Experimental results demonstrate the efficiency and scalability of these new algorithms. In the second problem, SaaS components are assumed to be already running on Cloud virtual machines (VMs). However, due to the environment of a Cloud, the current placement may need to be modified. Existing techniques focused mostly at the infrastructure level instead of the application level. This research addressed the problem at the application level by clustering suitable components to VMs to optimise the resource used and to maintain the SaaS performance. Two versions of grouping genetic algorithms (GGAs) are designed to cater for the structural group of a composite SaaS. The first GGA used a repair-based method while the second used a penalty-based method to handle the problem constraints. The experimental results confirmed that the GGAs always produced a better reconfiguration placement plan compared with a common heuristic for clustering problems. The third research problem deals with the replication or deletion of SaaS instances in coping with the SaaS workload. To determine a scaling plan that can minimise the resource used and maintain the SaaS performance is a critical task. Additionally, the problem consists of constraints and interdependency between components, making solutions even more difficult to find. A hybrid genetic algorithm (HGA) was developed to solve this problem by exploring the problem search space through its genetic operators and fitness function to determine the SaaS scaling plan. The HGA also uses the problem's domain knowledge to ensure that the solutions meet the problem's constraints and achieve its objectives. The experimental results demonstrated that the HGA constantly outperform a heuristic algorithm by achieving a low-cost scaling and placement plan. This research has identified three significant new problems for composite SaaS in Cloud. Various types of evolutionary algorithms have also been developed in addressing the problems where these contribute to the evolutionary computation field. The algorithms provide solutions for efficient resource management of composite SaaS in Cloud that resulted to a low total cost of ownership for users while guaranteeing the SaaS performance.