Standpunkte, Praktiken und Kenntnisstand zur Ferkelkastration in Europa (PIGCAS) – Projektziele und erste Ergebnisse

Most of the male piglets in the EU are castrated. According to the current EU legislation, surgical castration can be performed without anaesthesia up to the age of 7 days. A report of the European Food Safety Authority (EFSA) on the welfare aspects in relation to the castration of pigs has underlined the need for further research. As a follow up, the EU has launched a two-year project (Specific Support Action PIGCAS) within the 6^th EU Framework Programme, starting in January 2007. “PIGCAS” is the acronym for “Attitudes, practices and state of the art regarding piglet castration in Europe”. The main objectives are: [A] to collect information on the attitudes of the various stakeholders (consumer groups, NGOs and industry stakeholders); [B] to collect information on the extent of the practice of castration of piglets (male or female) within the EU and the conditions under which castration is performed; [C] to evaluate research work and other sources of information, in order to examine surgical castration without anaesthesia and its possible alternatives from different perspectives and derive research priorities; and [D] to integrate the collected information and evaluation in a report providing support for EU policy in the field of research and legislation. Preliminary results are now available on objectives [A] and [B]. When referring to the alternatives to surgical castration, one has to distinguish between short-term and long-term solutions. Surgical castration with anaesthesia was mentioned by most of the stakeholders as a short-term alternative. Genetic control of boar taint and sperm sexing to select only females for pork production are considered as long-term alternatives. Current practices of castration and levels of acceptability vary substantially between and within countries and regions. The current research focuses on practical methods for acute and postoperative pain alleviation and analyses the complex consequences of raising entire males or immunocastrated boars. Considering the different dimensions (attitudes, extent of practice, animal welfare, pork quality and economy) of importance, it is intended to propose to the EU short and long-term strategies to handle this problem.

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Eingegangen: 26. Februar 2008; angenommen: 29. Februar 2008     

Membranbrennstoffzellen

With the development of polymer membranes suitable as proton‐conducting electrolytes, membrane fuel cells are now successfully applied in various areas. Depending on the application, the service life, the power density or other system aspects are optimized. Common to all applications is the requirement to reduce costs, which, however, plays a decisive role especially in passenger cars. The development of the membrane fuel cell has now reached a high technical level, but political flanking measures are still required to launch it on the market. This applies both to the hydrogen infrastructure for fuel cell vehicles and to the promotion of fuel cell‐based combined heat and power generation.     

Multi-objective optimization of shield construction parameters based on random forests and NSGA-II

Metro shield construction will inevitably cause changes in the stress and strain state of the surrounding soil, resulting in stratum deformation and surface settlement (SS), which will seriously endanger the safety of nearby buildings, roads and underground pipe networks. Therefore, in the design and construction stage, optimizing the shield construction parameters (SCP) is the key to reducing the SS rate and increasing the safe driving speed (DS). However, optimization of existing SCP are challenged by the need to construct a unified multiobjective model for optimization that are efficient, convenient, and widely applicable. This paper innovatively proposes a hybrid intelligence framework that combines random forest (RF) and non-dominant classification genetic algorithm II (NSGA-II), which overcomes the shortcomings of time-consuming and high cost for the establishment and verification of traditional prediction models. First, RF is used to rank the importance of 10 influencing factors, and the nonlinear mapping relationship between the main SCP and the two objectives is constructed as the fitness function of the NSGA-II algorithm. Second, a multiobjective optimization framework for RF-NSGA-II is established, based on which the optimal Pareto front is calculated, and reasonable optimized control ranges for the SCP are obtained. Finally, a case study in the Wuhan Rail Transit Line 6 project is examined. The results show that the SS is reduced by 12.5% and the DS is increased by 2.5% with the proposed framework. Meanwhile, the prediction results are compared with the back-propagation neural network (BPNN), support vector machine (SVM), and gradient boosting decision tree (GBDT). The findings indicate that the RF-NSGA-II framework can not only meet the requirements of SS and DS calculation, but also used as a support tool for real-time optimization and control of SCP.     

Voice conversion using General Regression Neural Network

The objective of voice conversion system is to formulate the mapping function which can transform the source speaker characteristics to that of the target speaker. In this paper, we propose the General Regression Neural Network (GRNN) based model for voice conversion. It is a single pass learning network that makes the training procedure fast and comparatively less time consuming. The proposed system uses the shape of the vocal tract, the shape of the glottal pulse (excitation signal) and long term prosodic features to carry out the voice conversion task. In this paper, the shape of the vocal tract and the shape of source excitation of a particular speaker are represented using Line Spectral Frequencies (LSFs) and Linear Prediction (LP) residual respectively. GRNN is used to obtain the mapping function between the source and target speakers. The direct transformation of the time domain residual using Artificial Neural Network (ANN) causes phase change and generates artifacts in consecutive frames. In order to alleviate it, wavelet packet decomposed coefficients are used to characterize the excitation of the speech signal. The long term prosodic parameters namely, pitch contour (intonation) and the energy profile of the test signal are also modified in relation to that of the target (desired) speaker using the baseline method. The relative performances of the proposed model are compared to voice conversion system based on the state of the art RBF and GMM models using objective and subjective evaluation measures. The evaluation measures show that the proposed GRNN based voice conversion system performs slightly better than the state of the art models.     

A wavelet-based autoregressive fuzzy model for forecasting algal blooms

This paper proposes fuzzy models for forecasting the complex behavior of algal blooms. The models are developed through the integration of autoregressive models, the Takagi-Sugeno fuzzy model, and discrete wavelet transform algorithms. The premise parts of the proposed models are determined using the subtractive clustering technique and the consequent parts are optimized using weighted least squares. To train and validate the proposed fuzzy models, a large number of data sets were collected from Daecheong reservoir in Geum River in the Republic of Korea. The data include both water quality and hydrological variables. Total nitrogen, total phosphorous, dissolved oxygen, chemical oxygen demand, biochemical oxygen demand, pH, air temperature, water temperature and outflow water were evaluated as input signals while chlorophyll-a was used as an output. It is demonstrated from the simulation that the proposed fuzzy models are effective in forecasting algal blooms.     

完全标注、检查尺寸的新方法

详细介绍了一种完全地标注和检查零件图中尺寸的方法—查图线法,并论述了使用该方法时应注意的几个问题。     

粗糙集理论在旋转机械实时故障诊断中的应用

根据旋转机械实时故障诊断的实际需求,引入粗糙集理论中的决策模型,作为典型故障诊断规则的发现工具。并针对故障信号的非平稳性和诊断分析的实时性要求,采用小波包分析(WPA)作为现场数据的频域段特征的提取工具。并首次将小波包分析(WPA)与粗糙集理论的决策模型相结合,提出了适应于现代机械设备在线诊断的故障分析模型WRS。并通过实例,验证了全过程。     

基于一类Daubechies小波自相关函数的研究

讨论了一类Daubechies小波自相关函数的基本性质,着重对Daubechies尺度函数的自相关函数的插值分析做了仔细研究,得出了关于Daubechies小波尺度空间中的若干结果,并将其进一步推广.     

RESEARCH OF PROBLEMS ON REALIZING DIRECT ALGORITHM OF WAVELET TRANSFORM

Direct algorithm of wavelet transform (WT) is the numerical algorithm obtained from the integral formula of WT by directly digitization. Some problems on realizing the algorithm are studied. Some conclusions on the direct algorithm of discrete wavelet transform (DWT), such as discrete convolution operation formula of wavelet coefficients and wavelet components, sampling principle and technology to wavelets, deciding method for scale range of wavelets, measures to solve edge effect problem, etc, are obtained. The realization of direct algorithm of continuous wavelet transform (CWT) is also studied. The computing cost of direct algorithm and Mallat algorithm of DWT are still studied, and the computing formulae are obtained. These works are beneficial to deeply understand WT and Mallat algorithm. Examples in the end show that direct algorithm can also be applied widely.     

振动控制中传感器位置和数目设计的小波分析法

通过对采集的振动信号进行小波多分辨率分析和FFT谱分析 ,得出被测结构振动响应包含的各频率对应的振动波形曲线。依据Parseval能量积分等式 ,计算出各频率对应振动响应的能量值。提出了由不同频率下振动响应信号对应能量大小设计传感器粘贴位置和数目的小波分析法。通过对一简支梁进行激励实验 ,验证了该方法的可行性和有效性。