基于GIS的滑坡危险度区划定量研究

Abstract With the Development of the West Regions, the contradiction between economy and geological hazards was once again brought to our face in the Loess Plateau where was ,and is liable to geological hazards for the unique conditions of geology, hydrogeology, geography and meteorology. The goal to realize harmonious development between human and the earth was always there, and landslide hazard zoning provided us an effective way against geological hazards and damage. In the background of the construction of 750KV transformer substation in TianShui, we summarized some theories, methods and development of landslide hazard zoning and discussed the application of information value model in landslide hazard zoning. A called “judgement matrix” like in AHP was introduced to the information value model to solve the key point of landslide hazard zoning — choice of factors and weight of each factor. GIS was applied in the landslide hazard zoning, with its comprehensive function on data management, spatial analysis and mapping. A zonation map of landslide hazard was worked out on MAPGIS aimed to have something of reference and instruction on the construction of the transformer substation. Key words: landslide; hazard zoning; information value model; GIS; judgement matrix

填土边坡水文作用机理与破坏过程研究—以深圳羊宝地填土滑坡为例

A full understanding of failure mechanism, critical hydrological condition, and process of mobilization and deposition of a landslide is essential for optimal design of stabilization measure and forecasting of landslide hazard. This requires a quantitative study of hydrological response of a slope to rainfall through field monitoring, laboratory test and numerical modelling. At 13:40 on September 18, 2002, a fill slope failed following a period of prolonged rain in Shenzhen, resulting in 5 fatalities and 31 injuries. The failed mass with a volume about 2.5×104m3 traveled about 140m on level ground. Field monitoring, laboratory test, theoretical analysis and numerical modelling were carried out to undestand the hydrological response and failure mechanism of this fill slope. This thesis mainly focuses on the following aspects: (1) The hydrological responses and failure processes of slopes under rainfall infiltration were reviewed. Firstly, the factors influencing on the hydrological responses of slopes were analysed. Secondly, the change of stress state of slope soil and modelling methods of slope failure under rainfall infiltration were reviewed. (2) The characteristics of the Yangbaodi landslide and associated rainfall triggering the failure were presented. The failure was characterized by shallow flowslide, due to an increase of ground water table caused by rainfall infiltration. (3) A fully automated instrumentation was carried out to monitor rainfall, and saturated – unsaturated hydrological response of the fill slope, using a raingauge, piezometers, tensiometers and moisture probes. A conceptual hydrogeological model was presented based on field monitoring and borehole data. Analysis of monitoring data showed that the high pore water pressure in fill slope was caused by upward flow of semiconfined groundwater in the moderately decomposed granite. (4) Laboratory and in-situ testing was performed to study the physical and mechanical properties of fills. Isotropically consolidated undrained compression tests and anisotropically consolidated constant shear stress tests were carried out to understand the failure mechanism of the fill slope. It is indicated that loosely compacted soil is of strain-softening behaviour under undrained conditions, accompanied with a rapid increase in excess pore water pressure. In anisotropically consolidated constant shear stress tests, a very small axial strain was required to induce the failure and the excess pore water pressure increased quickly at failure. This indicated that static liquefaction caused by rise in groundwater table due to rainfall infiltration occurred. (5) The hydraulic conductivity of the highly and moderately decomposed granite was estimated using monitering data of pore water pressure. A saturated – unsaturated flow was modeled to study the hydrological response of the fill slope using rainfall records. It was observed that the lagged failure was due to the geological conditions and the discrepancy of hydraulic conductivity of slope soils. The hydraulic conductivity of moderately decomposed granite is relatively higher than the other materials, resulting in a semiconfied groundwater flow in the moderately decomposed granite, and subsequent upward flow into the upper fill layer. When the ground water table in the fill layer was increased to the critical state, the fill slope failed. (6) Numerical exercises were conducted to replay the failure process of the fill slope, based on field monitoring, laboratory and in-situ testing. It was found that the fill slope was mobilized by a rapid transfer of the concentrated shear stress. The movement of failure mass was characterized by viscosity fluid with a gradual increase in velocity. The failure process, including mobilization and subsequent movement and deposition, was studied using numerical methods.

Fast Learning VIEWNET Architectures for Recognizing 3-D Objects from Multiple 2-D Views

The recognition of 3-D objects from sequences of their 2-D views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With NETworks. VIEWNET incorporates a preprocessor that generates a compressed but 2-D invariant representation of an image, a supervised incremental learning system that classifies the preprocessed representations into 2-D view categories whose outputs arc combined into 3-D invariant object categories, and a working memory that makes a 3-D object prediction by accumulating evidence from 3-D object category nodes as multiple 2-D views are experienced. The simplest VIEWNET achieves high recognition scores without the need to explicitly code the temporal order of 2-D views in working memory. Working memories are also discussed that save memory resources by implicitly coding temporal order in terms of the relative activity of 2-D view category nodes, rather than as explicit 2-D view transitions. Variants of the VIEWNET architecture may also be used for scene understanding by using a preprocessor and classifier that can determine both What objects are in a scene and Where they are located. The present VIEWNET preprocessor includes the CORT-X 2 filter, which discounts the illuminant, regularizes and completes figural boundaries, and suppresses image noise. This boundary segmentation is rendered invariant under 2-D translation, rotation, and dilation by use of a log-polar transform. The invariant spectra undergo Gaussian coarse coding to further reduce noise and 3-D foreshortening effects, and to increase generalization. These compressed codes are input into the classifier, a supervised learning system based on the fuzzy ARTMAP algorithm. Fuzzy ARTMAP learns 2-D view categories that are invariant under 2-D image translation, rotation, and dilation as well as 3-D image transformations that do not cause a predictive error. Evidence from sequence of 2-D view categories converges at 3-D object nodes that generate a response invariant under changes of 2-D view. These 3-D object nodes input to a working memory that accumulates evidence over time to improve object recognition. ln the simplest working memory, each occurrence (nonoccurrence) of a 2-D view category increases (decreases) the corresponding node's activity in working memory. The maximally active node is used to predict the 3-D object. Recognition is studied with noisy and clean image using slow and fast learning. Slow learning at the fuzzy ARTMAP map field is adapted to learn the conditional probability of the 3-D object given the selected 2-D view category. VIEWNET is demonstrated on an MIT Lincoln Laboratory database of l28x128 2-D views of aircraft with and without additive noise. A recognition rate of up to 90% is achieved with one 2-D view and of up to 98.5% correct with three 2-D views. The properties of 2-D view and 3-D object category nodes are compared with those of cells in monkey inferotemporal cortex.

Universal power quality manager with a new control scheme

A new universal power quality manager is proposed. The proposal treats a number of power quality problems simultaneously. The universal manager comprises a combined series and shunt three-phase PWM controlled converters sharing a common DC link. A control scheme based on fuzzy logic is introduced and the general features of the design and operation processes are outlined. The performance of two configurations of the proposed power quality manager are compared in terms of a recently formulated unified power quality index. The validity and integrity of the proposed system is proved through computer simulated experiments

Multiple Input Governor Control for a Diesel Generating Set

The paper presents a multiple input single output fuzzy logic governor algorithm that can be used to improve the transient response of a diesel generating set, when supplying an islanded load. The proposed governor uses the traditional speed input in addition to voltage and power factor to modify the fuelling requirements during various load disturbances. The use of fuzzy logic control allows the use of PID type structures that can provide variable gain strategies to account for non-linearities in the system. Fuzzy logic also provides a means of processing other input information by linguistic reasoning and a logical control output to aid the governor action during transient disturbance. The test results were obtained using a 50 kVA naturally aspirated diesel generator testing facility. Both real and reactive load tests were conducted. The complex load test results demonstrate that, by using additional inputs to the governor algorithm, enhanced generator transient speed recovery response can be obtained.

Behaviours in video

With a significant increment of the number of digital cameras used for various purposes, there is a demanding call for advanced video analysis techniques that can be used to systematically interpret and understand the semantics of video contents, which have been recorded in security surveillance, intelligent transportation, health care, video retrieving and summarization. Understanding and interpreting human behaviours based on video analysis have observed competitive challenges due to non-rigid human motion, self and mutual occlusions, and changes of lighting conditions. To solve these problems, advanced image and signal processing technologies such as neural network, fuzzy logic, probabilistic estimation theory and statistical learning have been overwhelmingly investigated.

Design and analysis of dual-rail circuits for security applications

Dual-rail encoding, return-to-spacer protocol, and hazard-free logic can be used to resist power analysis attacks by making energy consumed per clock cycle independent of processed data. Standard dual-rail logic uses a protocol with a single spacer, e.g., all-zeros, which gives rise to energy balancing problems. We address these problems by incorporating two spacers; the spacers alternate between adjacent clock cycles. This guarantees that all gates switch in every clock cycle regardless of the transmitted data values. To generate these dual-rail circuits, an automated tool has been developed. It is capable of converting synchronous netlists into dual-rail circuits and it is interfaced to industry CAD tools. Dual-rail and single-rail benchmarks based upon the advanced encryption standard (AES) have been simulated and compared in order to evaluate the method and the tool.

Energy monitoring and quality control of a single screw extruder

Polymer extrusion, in which a polymer is melted and conveyed to a mould or die, forms the basis of most polymer processing techniques. Extruders frequently run at non-optimised conditions and can account for 15–20% of overall process energy losses. In times of increasing energy efficiency such losses are a major concern for the industry. Product quality, which depends on the homogeneity and stability of the melt flow which in turn depends on melt temperature and screw speed, is also an issue of concern of processors. Gear pumps can be used to improve the stability of the production line, but the cost is usually high. Likewise it is possible to introduce energy meters but they also add to the capital cost of the machine. Advanced control incorporating soft sensing capabilities offers opportunities to this industry to improve both quality and energy efficiency. Due to strong correlations between the critical variables, such as the melt temperature and melt pressure, traditional decentralized PID (Proportional–Integral–Derivative) control is incapable of handling such processes if stricter product specifications are imposed or the material is changed from one batch to another. In this paper, new real-time energy monitoring methods have been introduced without the need to install power meters or develop data-driven models. The effects of process settings on energy efficiency and melt quality are then studied based on developed monitoring methods. Process variables include barrel heating temperature, water cooling temperature, and screw speed. Finally, a fuzzy logic controller is developed for a single screw extruder to achieve high melt quality. The resultant performance of the developed controller has shown it to be a satisfactory alternative to the expensive gear pump. Energy efficiency of the extruder can further be achieved by optimising the temperature settings. Experimental results from open-loop control and fuzzy control on a Killion 25 mm single screw extruder are presented to confirm the efficacy of the proposed approach.

A computational intelligent approach to multi-factor analysis of violent crime information systems

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Secagem convectiva de produtos alimentares: otimização e controlo

O presente trabalho tem como objetivo analisar a cinética de secagem do bacalhau salgado verde (Gadus morhua) em secador convectivo. É apresentada a análise da composição físico-química dos bacalhaus utilizados nos ensaios experimentais, bem como o estudo das isotermas de sorção do produto, através de experiências e modelação matemática. Dos modelos usados para o ajuste das isotermas de sorção do bacalhau salgado verde, o que melhor se adaptou aos resultados experimentais foi o modelo de GAB Modificado, com coeficientes de correlação variando entre 0,992 e 0,998. Para o controlo do processo de secagem (nomeadamente os parâmetros temperatura, humidade relativa e velocidade do ar) foi utilizada lógica difusa, através do desenvolvimento de controladores difusos para o humidificador, desumidificador, resistências de aquecimento e ventilador. A modelação do processo de secagem foi realizada através de redes neuronais artificiais (RNA), modelo semi-empírico de Page e modelo difusivo de Fick. A comparação entre dados experimentais e simulados, para cada modelo, apresentou os seguintes erros: entre 1,43 e 11,58 para o modelo de Page, 0,34 e 4,59 para o modelo de Fick e entre 1,13 e 6,99 para a RNA, com médias de 4,38, 1,67 e 2,93 respectivamente. O modelo obtido pelas redes neuronais artificiais foi submetido a um algoritmo de otimização, a fim de buscar os parâmetros ideais de secagem, de forma a minimizar o tempo do processo e maximizar a perda de água do bacalhau. Os parâmetros ótimos obtidos para o processo de secagem, após otimização realizada, para obter-se uma humidade adimensional final de 0,65 foram: tempo de 68,6h, temperatura de 21,45°C, humidade relativa de 51,6% e velocidade de 1,5m/s. Foram também determinados os custos de secagem para as diferentes condições operacionais na instalação experimental. Os consumos por hora de secagem variaram entre 1,15 kWh e 2,87kWh, com uma média de 1,94kWh.

A quarter century of creative chaos: Xinhua News Agency 1980-2005

Chinese media in the context of China's rise have puzzled many scholars who used to understand media and communications phenomena by employing the theories generated from a few affluent Western democracies, notably the US. As a result, a complex but more accurate picture has been ignored. Under numerous theoretical polarizations, the contemporary social world seems little changed but polarized. This thesis aims to propose a different approach endeavoring to 'de-Westernize' or 'internationalize' media and communications studies. As a starting point, this study focuses on the globalization debate, Chinese media and news agency studies. The thesis has investigated the Chinese news agency, Xinhua, by employing Fuzzy Logic which captures the complexity of the change in the agency's business structure and journalistic practices over last 25 years. The change is also examined by scrutinizing the role of journalists in the interrelations of Xinhua with its news sources, media and nonmedia clients, and other news agencies. A combination of archive study and 94 semistructured interviews conducted in Beijing, Shanghai, Guangzhou, Hong Kong, Macau and London provides an inclusive account of the Chinese news institution. The key research findings drawn from the empirical research into Xinhua have justified the central argument of this thesis: Crisp Logic or the 'either/or' approach has failed to explain the dynamics of the change to the media system based in a 'non-Western' society. The numerous theoretical polarizations generated by Crisp Logic to a large extent have distorted the understanding of the contemporary social world by polarizing it. Fuzzy Logic serves better(though it is not the only choice)than the traditional approach to reflect on the set of variables existing between the two poles created by Crisp Logic. This thesis is the first doctorate research in the UK and other English-speaking countries to investigate Xinhua by 'going inside' the news institution's headquarters, local branches and overseas bureaus. This is the first comprehensive academic study of the agency, which not only examines the agency's recent change in business structure and journalistic practices, but also provides a historical account of the agency and its relationship with other social institutions. This is the first media study that employs Fuzzy Logic to understand the globalization theory, Chinese media and news agencies.

A hybrid recommendation approach for a tourism system

Many current e-commerce systems provide personalization when their content is shown to users. In this sense, recommender systems make personalized suggestions and provide information of items available in the system. Nowadays, there is a vast amount of methods, including data mining techniques that can be employed for personalization in recommender systems. However, these methods are still quite vulnerable to some limitations and shortcomings related to recommender environment. In order to deal with some of them, in this work we implement a recommendation methodology in a recommender system for tourism, where classification based on association is applied. Classification based on association methods, also named associative classification methods, consist of an alternative data mining technique, which combines concepts from classification and association in order to allow association rules to be employed in a prediction context. The proposed methodology was evaluated in some case studies, where we could verify that it is able to shorten limitations presented in recommender systems and to enhance recommendation quality.