Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Synthesis and characterization of carbon-covered alumina (CCA) supported TiO2 nanocatalysts with enhanced visible light photodegradation of Rhodamine B

The anatase phase of titania (TiO2) nano-photocatalysts was prepared using a modified sol gel process and thereafter embedded on carbon-covered alumina supports. The carbon-covered alumina (CCA) supports were prepared via the adsorption of toluene 2,4-diisocyanate (TDI) on the surface of the alumina. TDI was used as the carbon source for the first time for the carbon-covered alumina support system. The adsorption of TDI on alumina is irreversible; hence, the resulting organic moiety can undergo pyrolysis at high temperatures resulting in the formation of a carbon coating on the surface of the alumina. The TiO2 catalysts were impregnated on the CCA supports. X-ray diffraction analysis indicated that the carbon deposited on the alumina was not crystalline and also showed the successful impregnation of TiO2 on the CCA supports. In the Raman spectra, it could be deduced that the carbon was rather a conjugated olefinic or polycyclic hydrocarbons which can be considered as molecular units of a graphitic plane. The Raman analysis of the catalysed CCAs showed the presence of both the anatase titania and D and G band associated with the carbon of the CCAs. The scanning electron microscope micrographs indicated that the alumina was coated by a carbon layer and the energy dispersive X-ray spectra showed the presence of Al, O and C in the CCA samples, with the addition of Ti for the catalyst impregnated supports. The Brunauer Emmet and Teller surface area analysis showed that the incorporating of carbon on the alumina surface resulted in an increase in surface area, while the impregnation with TiO2 resulted in a further increase in surface area. However, a decrease in the pore volume and diameter was observed. The photocatalytic activity of the nanocatalysts was studied for the degradation of Rhodamine B dye. The CCA-TiO2 nanocatalysts were found to be more photocatalytically active under both visible and UV light irradiation compared to the free TIO2 nanocatalysts.

大口径八边形钕玻璃片支撑系统的光机集成分析

控制由机械装夹方式所引入的波前畸变以提高惯性约束聚变(ICF)输出光束的质量，是在大口径钕玻璃片主放大器结构设计中必须考虑的。提出了一种新的有限元变形结果与光学元件面形畸变之间的数据处理方式，并与传统方式进行了对比。基于新的数据处理接口，利用光机集成分析方法对大口径八边形钕玻璃片的支撑系统结构设计参数进行优化。优化的结果保证了由支撑系统引起的透过波前畸变小于十分之一波长，同时波前畸变与设计参数变动的相关性最小。

Design and implementation of a cloud computing adoption decision tool: Generating a cloud road

Migrating to cloud computing is one of the current enterprise challenges. This technology provides a new paradigm based on "on-demand payment" for information and communication technologies. In this sense, the small and medium enterprise is supposed to be the most interested, since initial investments are avoided and the technology allows gradual implementation. However, even if the characteristics and capacities have been widely discussed, entry into the cloud is still lacking in terms of practical, real frameworks. This paper aims at filling this gap, presenting a real tool already implemented and tested, which can be used as a cloud computing adoption decision tool. This tool uses diagnosis based on specific questions to gather the required information and subsequently provide the user with valuable information to deploy the business within the cloud, specifically in the form of Software as a Service (SaaS) solutions. This information allows the decision makers to generate their particular Cloud Road. A pilot study has been carried out with enterprises at a local level with a two-fold objective: To ascertain the degree of knowledge on cloud computing and to identify the most interesting business areas and their related tools for this technology. As expected, the results show high interest and low knowledge on this subject and the tool presented aims to readdress this mismatch, insofar as possible. Copyright: © 2015 Bildosola et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Doação de órgãos: um estudo sobre produção de sentidos

Este trabalho teve por objetivo investigar as representações sociais construídas pelos familiares que, após a morte de seus parentes, ofereceram seus órgãos e tecidos para transplantes. Foi realizada uma pesquisa de campo utilizando como instrumento a entrevista semidirigida, também conhecida pela comunidade científica como pesquisa semiestruturada. Foram entrevistados nove familiares de doadores mortos, um doador vivo e um receptor de órgãos. Dois sentidos emergiram no estudo de campo: um ligado à ideia de vida e outro ligado à ideia de morte. No primeiro, estão as percepções da doação como cura, solidariedade, continuidade e altruísmo; no segundo ocorre principalmente a questão da fragmentação do corpo. Assim, com esta pesquisa foi possível concluir que se as pessoas em vida pudessem falar livremente aos seus familiares sobre seu desejo de serem doadoras, poderiam de certa forma facilitar aos seus familiares a decisão em doar os órgãos no difícil momento da morte. Todos os indivíduos entrevistados neste trabalho expressaram que este fator foi determinante no momento da decisão e tornou a decisão menos estressante. Refletir sobre doação de órgãos no cotidiano permite que o tema saia do anonimato e adentre tanto nas redes de apoio social quanto em instituições hospitalares e de saúde, a ponto de facilitar a decisão posterior de familiares.

Pais frente à malformação craniofacial do filho: uma contribuição da enfermagem para a equipe interdisciplinar

Trata-se de uma pesquisa qualitativa descritiva que teve como objeto de estudo as estratégias de enfrentamento dos pais com o nascimento de uma criança com anomalia craniofacial. Objetivou identificar o impacto causado nos pais frente ao nascimento de um filho portador de anomalia craniofacial; descrever as estratégias de enfrentamento que os pais utilizam para estabelecer vinculação com o filho que apresenta malformação. Utilizou o método Narrativa de Vida, através da entrevista gravada com 15 mães e sete pais de crianças com malformação craniofacial. O estudo foi aprovado pelo Comitê de Ética da Universidade do Estado do Rio de Janeiro. A coleta de dados foi realizada entre junho e agosto de 2014. As narrativas apontaram para a emergência de três categorias: Ter um filho com anomalia craniofacial: situação impactante; Estratégias de enfrentamento utilizadas por pais de crianças com malformação craniofacial; Pais e profissionais da equipe de saúde: uma relação conturbada. As categorias puderam explicitar que a notícia da malformação gera impacto e crise na vida dos pais e no seio familiar. A grande expectativa na gravidez pelo bebê perfeito se transforma em frustração, choque e culpa. Diante dessa adversidade, as famílias começam a desenvolver estratégias de enfrentamento que auxiliam vinculação com seu filho malformado. Essa capacidade de desenvolver forças e habilidades para se adaptar à nova realidade, minimizando os efeitos negativos, é chamada de resiliência. As narrativas apontam a experiência religiosa e a rede de apoio como as principais estratégias de enfrentamento utilizadas pelos participantes. A equipe de saúde é chamada a apoiar os pais ao longo do processo de adaptação com o filho malformado. Os profissionais de saúde podem auxiliar no suporte e adaptação destes pais, diante da nova condição, sendo agentes promotores da escuta terapêutica. Compreender o que há por detrás de cada história desvelada, traz subsídios para potencializar a resiliência no acolhimento institucional dos pais e sua família.

Supporting excavations in clay - From analysis to decision-making

Finite Element Analysis (FEA) is used to calibrate a decision-making tool based on an extension of the Mobilized Strength Design (MSD) method which permits the designer an extremely simple method of predicting ground displacements during construction. This newly extended MSD approach accommodates a number of issues which are important in underground construction between in-situ walls, including: alternative base heave mechanisms suitable either for wide excavations in relatively shallow soft clay strata, or narrow excavations in relatively deep soft strata; the influence of support system stiffness in relation to the sequence of propping of the wall; and the capability of dealing with stratified ground. These developments should make it possible for a design engineer to take informed decisions on the relationship between prop spacing and ground movements, or the influence of wall stiffness, or on the need for and influence of a jet-grouted base slab, for example, without having to conduct project-specific FEA. © 2009 Taylor & Francis Group.

An evaluation of a new product data model

Engineering companies face many challenges today such as increased competition, higher expectations from consumers and decreasing product lifecycle times. This means that product development times must be reduced to meet these challenges. Concurrent engineering, reuse of engineering knowledge and the use of advanced methods and tools are among the ways of reducing product development times. Concurrent engineering is crucial in making sure that the products are designed with all issues considered simultaneously. The reuse of engineering knowledge allows existing solutions to be reused. It can also help to avoid the mistakes made in previous designs. Computer-based tools are used to store information, automate tasks, distribute work, perform simulation and so forth. This research concerns the evaluation of tools that can be used to support the design process. These tools are evaluated in terms of the capture of information generated during the design process. This information is vital to allow the reuse of knowledge. Present CAD systems store only information on the final definition of the product such as geometry, materials and manufacturing processes. Product Data Management (PDM) systems can manage all this CAD information along with other product related information. The research includes the evaluation of two PDM systems, Windchill and Metaphase, using the design of a single-handed water tap as a case study. The two PDMs were then compared to PROSUS/DDM. PROSUS is the Process-Based Support System proposed by [Blessing 94] using the same case study. The Design Data Model is the product data model that includes PROSUS. The results look promising. PROSUS/DDM is able to capture most design information and structure and present it logically. The design process and product information is related and stored within the DDM structure. The PDMs can capture most design information, but information from early stages of design is stored only as unstructured documentation. Some problems were found with PROSUS/DDM. A proposal is made that may make it possible to resolve these problems, but this will require further research.

Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking.

Reducing energy consumption is a major challenge for "energy-intensive" industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of "optimized" operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method.

Data-based robust multiobjective optimization of interconnected processes: Energy efficiency case study in papermaking

Reducing energy consumption is a major challenge for energy-intensive industries such as papermaking. A commercially viable energy saving solution is to employ data-based optimization techniques to obtain a set of optimized operational settings that satisfy certain performance indices. The difficulties of this are: 1) the problems of this type are inherently multicriteria in the sense that improving one performance index might result in compromising the other important measures; 2) practical systems often exhibit unknown complex dynamics and several interconnections which make the modeling task difficult; and 3) as the models are acquired from the existing historical data, they are valid only locally and extrapolations incorporate risk of increasing process variability. To overcome these difficulties, this paper presents a new decision support system for robust multiobjective optimization of interconnected processes. The plant is first divided into serially connected units to model the process, product quality, energy consumption, and corresponding uncertainty measures. Then multiobjective gradient descent algorithm is used to solve the problem in line with user's preference information. Finally, the optimization results are visualized for analysis and decision making. In practice, if further iterations of the optimization algorithm are considered, validity of the local models must be checked prior to proceeding to further iterations. The method is implemented by a MATLAB-based interactive tool DataExplorer supporting a range of data analysis, modeling, and multiobjective optimization techniques. The proposed approach was tested in two U.K.-based commercial paper mills where the aim was reducing steam consumption and increasing productivity while maintaining the product quality by optimization of vacuum pressures in forming and press sections. The experimental results demonstrate the effectiveness of the method. © 2006 IEEE.

Sustainability: A new imperative in contaminated land remediation

Land is not only a critical component of the earth's life support system, but also a precious resource and an important factor of production in economic systems. However, historical industrial operations have resulted in large areas of contaminated land that are only slowly being remediated. In recent years, sustainability has drawn increasing attention in the environmental remediation field. In Europe, there has been a movement towards sustainable land management; and in the US, there is an urge for green remediation. Based on a questionnaire survey and a review of existing theories and empirical evidence, this paper suggests the expanding emphasis on sustainable remediation is driven by three general factors: (1) increased recognition of secondary environmental impacts (e.g., life-cycle greenhouse gas emissions, air pollution, energy consumption, and waste production) from remediation operations, (2) stakeholders' demand for economically sustainable brownfield remediation and "green" practices, and (3) institutional pressures (e.g., social norm and public policy) that promote sustainable practices (e.g., renewable energy, green building, and waste recycling). This paper further argues that the rise of the "sustainable remediation" concept represents a critical intervention point from where the remediation field will be reshaped and new norms and standards will be established for practitioners to follow in future years. This paper presents a holistic view of sustainability considerations in remediation, and an integrated framework for sustainability assessment and decision making. The paper concludes that "sustainability" is becoming a new imperative in the environmental remediation field, with important implications for regulators, liability owners, consultants, contractors, and technology vendors. © 2014 Elsevier Ltd.

Population growth and physiological characteristics of microalgae in a miniaturized bioreactor during space flight

A strain of microalgae (Anabaena siamensis) had been cultured in a miniaturized bioreactor during a retrievable satellite flight for 15 days. By means of remote sensing equipment installed in the satellite, we gained the growth curve of microalgae population in space every day in real time. The curve indicated that the growth of microalgae in space was slower than the control on ground. Inoculation of the retrieved microalgae culture showed that the growth rate was distinctively higher than ground control. But after several generations, both cultures indicated similar growth rates. Those data showed that algae, can adapt to space environment easily which may be valuable for designing more complex bioreactor and controlled ecological life support system in future experiment. (C) 2006 Elsevier Ltd. All rights reserved.

岷江上游农林复合景观管理优先度评价

结合前期研究共辨识出10项景观管理影响因子,依据其作用的性质和特点,将其分为4大类参数,通过NetWeaver模型构建了基于模糊逻辑的优先度评价知识库,在EMDS(Ecosystem Management Decision Support system)和ARCGIS9.x环境下,对4类景观管理影响因子的优先度进行了评价。结果显示:1)可行性因子综合优先度评价结果为除ws3、ws6、ws8和ws9 4个子流域的优先度为低外,其余6个子流域优先度居于中等优先水平;2)有效性因子优先度综合评价结果,ws1、ws9和ws10 3个子流域优先度为强,ws8优先度最低,其余子流域为中等优先;3)景观综合结果除ws1~ws33个子流域属于强外,其余子流域优先度为低;4)所有影响因子的综合结果为ws8子流域优先度最低,其余部分优先度居于中等。

旱地作物需水量预报决策辅助系统

旱地作物需水量预报决策辅助系统是利用人工智能技术 ,在 Penman公式的基础上结合现有西北旱区的农学知识、模型以及经验进行系统集成而建立的智能化计算机软件系统 ,该系统是西北地区节水农业专家系统的一个子系统。在生产实践中可为陕西关中地区的冬小麦、夏玉米的栽培作出灌溉方案的决策咨询。