Depth resolved detection of oceanographic variables in the St. Lawrence estuary using a laser fluorosensor: instrument characteristics and first results†

A 64-channel Laser Environmental Airborne Fluorosensor (LEAF) system for sea surface oil detection was modified for continuous depth-resolved detection of gelbstolT and chlorophyll a spectral fluorescence, and water Raman scattering. The system was successfully tested during shipborne and airborne experiments in the St. Lawrence Estuary. System performance was studied, and the best integration time to optimize the signal to noise ratio (S/N) was determined using dilTerent statistical procedures such as the geophysical and robust statistical methods. In general, raw data indicated S/N of about 150, 10, and 4 for Raman. gelbstolT and chlorophyll a signals, respectively. Results with calibrated LEAF spectra clearly indicated that, with this system, water Raman scattering, geibstolT and chlorophyll a signals could be detected down to a maximum depth of 4·8 m. Spatial distribution of these quantities compared well with simultaneously observed ill Silll structure of oceanographic variables, such as, underwater light attenuation, salinity and chlorophyll a fluorescence. In the perspective of modelling primary production in coastal and estuarine waters in the St. Lawrence system (Case II waters), the utilization of LEAF should provide an adequate representation of the spatial and temporal variation pattern of oceanographic variables, at scales between those from ships and satellites.     

Educational software for electrical engineering: A methodology and some results

In this paper, problems related to the use of the microcomputer as a teaching tool in engineering education are discussed. The objectives and methodological principles of educational software are defined, stressing the need to improve the quality of engineering education. The microcomputer is considered as an engineering tool in the decision-making process, offering possibilities for further deeper analysis of physical phenomena in electrical devices. Examples of applications of the methodological principles developed for the elaboration of educational software packages for electrical engineering are given.     

Detection of potential fishing zones for neon flying squid based on remote-sensing data in the Northwest Pacific Ocean using an artificial neural network

Ommastrephes bartramii is a short-lived species of squid and reacts rapidly to changes in the regional environmental conditions of the fishing ground. Understanding the preferred range of key environmental variables and predicting potential resource distributions are critical to conserve and manage its resources. Commercial fishery data for the western winter–spring cohort of O. bartramii from Chinese squid-jigging vessels during 2003–2013 were used to evaluate a suitable range of three key environmental variables, sea surface temperature (SST), sea surface height (SSH), and chlorophyll-a (chl-a) concentration, and to explore potential fishing zones (PFZs) using an artificial neural network. The neural interpretation diagram and independent variable relevance analysis indicate that month, latitude, and SST had significant influences on the PFZ distribution of O. bartramii, yielding 21.78%, 23.91%, and 26.04% of contribution rates, respectively. Based on the sensitivity analyses, a high abundance of O. bartramii mainly occurred in the waters between 150°–165° E and 37°–42° N during July to August. Suitable ranges of environmental variables for O. bartramii were 11–18°C for SST, ?10 to 60 cm for SSH, and 0.1–1.7 mg/m³ for chl-a concentration, respectively. The back-propagation network model was well developed and could be used to predict the PFZ with 80% accuracy. The actual fishing grounds coincided with the predicted PFZ, suggesting that the established model of PFZ is effective in forecasting the potential habitat of O. bartramii in the Northwest Pacific Ocean.     

Social meaning of personal computers for managers and professionals: methodology and results

The social meaning of personal computers for 34 managers and professionals was measured using a situational approach. The results, in general, indicated a positive perception towards computers within the context of their work situations. The methodology was developed in an attempt to overcome some of the difficulties of traditional measures of attitudes. The advantages and the limitations of the method, as well as the process by which impressions are formed, are discussed.     

Characterising observed patterns of suspended particulate matter and relationships with oceanographic and meteorological variables: Studies in Liverpool Bay

Suspended particulate matter (SPM) in the marine environment is represented by a mixture of organic and inorganic particles, and is characterised by complex structural and dynamical transformations. This paper describes our SPM studies in Liverpool Bay (UK), and identifies (using Stepwise Regression Modelling) the meteorological and oceanographic variables especially important for the characterisation of the SPM at this site. By analysing data sets from 9 cruises conducted between September 2004 and February 2006, it was found that the highest number of significant relationships (25) was shown by Salinity and Temperature. It is therefore evident, that the most important factors influencing SPM-related variables are related to the inshore–offshore gradient. This influence has also been reflected in the importance of such variables as Density (10) relationships and Depth (9). Another very important factor appears to relate to wind waves, with the cubed amplitude of orbital velocity at the bed demonstrating 23 significant relationships, TKE due to wind showing 13 relationships, dominant wave direction 11, and average wave period 9. These figures appear to exceed the numbers of significant relationships shown by the variables related to tides (e.g. tidal level 15, tide direction 9, TKE at the surface due to the tidal current 4). Hence waves appear to matter more than tides. The Matlab function used for stepwise regression modelling is particularly suitable for the analysis of large amounts of repetitive information (e.g. for processing data from a number of cruises where the same or similar protocol was used for data collection and storage), with the results being stored in Excel files. This facilitates the analysis and enables an easy exchange of the results (i.e. due to the widespread use of Microsoft Excel). The Matlab function is provided online as a supplementary appendix.     

溴酸盐电化学传感器研究与应用进展

溴酸盐是饮用水消毒常见的副产物之一,同时也常用作面粉等食品的添加剂。大量研究表明溴酸盐毒性较大,可致癌,因此建立简单、快速而又准确的溴酸盐分析方法意义重大。该文总结了近些年来在溴酸盐检测方面的各类方法报道和技术研究进展,重点评述了电化学修饰电极的制备、性能及其在溴酸盐高灵敏传感识别方面的研究和应用进展。     

A systematic test case selection methodology for product lines: results and insights from an industrial case study

In the context of product lines, test case selection aims at obtaining a set of relevant test cases for a product from the entire set of test cases available for a product line. While working on a research-based innovation project on automated testing of product lines of Video Conferencing Systems (VCSs) developed by Cisco, we felt the need to devise a cost-effective way of selecting relevant test cases for a product. To fulfill such need, we propose a systematic and automated test selection methodology using: 1) Feature Model for Testing (FM_T) to capture commonalities and variabilities of a product line; 2) Component Family Model for Testing (CFM_T) to model the structure of test case repository; 3) A tool to automatically build restrictions from CFM_T to FM_T and traces from CFM_T to the actual test cases. Using our methodology, a test engineer is only required to select relevant features through FM_T at a higher level of abstraction for a product and the corresponding test cases will be obtained automatically. We evaluate our methodology by applying it to a VCS product line called Saturn with seven commercial products and the results show that our methodology can significantly reduce cost measured as test selection time and at the same time achieves higher effectiveness (feature coverage, feature pairwise coverage and fault detection) as compared with the current manual process. Moreover, we conduct a questionnaire-based study to solicit the views of test engineers who are involved in developing FM_T and CFM_T. The results show that test engineers are positive about adapting our methodology in their current practice. Finally, we present a set of lessons learnt while applying product line engineering at Cisco for test case selection.     

Neural networks for the prediction and forecasting of water resources variables: a review of modelling issues and applications

Artificial Neural Networks (ANNs) are being used increasingly to predict and forecast water resources variables. In this paper, the steps that should be followed in the development of such models are outlined. These include the choice of performance criteria, the division and pre-processing of the available data, the determination of appropriate model inputs and network architecture, optimisation of the connection weights (training) and model validation. The options available to modellers at each of these steps are discussed and the issues that should be considered are highlighted. A review of 43 papers dealing with the use of neural network models for the prediction and forecasting of water resources variables is undertaken in terms of the modelling process adopted. In all but two of the papers reviewed, feedforward networks are used. The vast majority of these networks are trained using the backpropagation algorithm. Issues in relation to the optimal division of the available data, data pre-processing and the choice of appropriate model inputs are seldom considered. In addition, the process of choosing appropriate stopping criteria and optimising network geometry and internal network parameters is generally described poorly or carried out inadequately. All of the above factors can result in non-optimal model performance and an inability to draw meaningful comparisons between different models. Future research efforts should be directed towards the development of guidelines which assist with the development of ANN models and the choice of when ANNs should be used in preference to alternative approaches, the assessment of methods for extracting the knowledge that is contained in the connection weights of trained ANNs and the incorporation of uncertainty into ANN models.     

混合域蚂蚁矿工算法的研究与应用

为了提高蚂蚁矿工算法的性能,使蚂蚁矿工算法能够更好处理具有连续离散属性的数据集,采用混合正态核函数处理连续属性。使用混合域蚂蚁矿工算法来发现无序的规则集,这些规则解释了训练集中隐藏的知识,同时能够将给定的数据集进行分类。实验结果表明,混合域蚂蚁矿工算法能产生可以接受的预测准确率,发现更简单的规则,在故障诊断系统中采用混合域蚂蚁矿工算法产生的规则比蚂蚁矿工算法更有效。     

Further validation of a new methodology for surface moisture and vegetation optical depth retrieval

A series of validation studies for a recently developed soil moisture and optical depth retrieval algorithm is presented. The approach is largely theoretical, and uses a non-linear iterative optimization procedure to solve a simple radiative transfer equation for the two parameters from dual polarization satellite microwave brightness temperatures. The satellite retrievals were derived from night-time 6.6?GHz Nimbus Scanning Multichannel Microwave Radiometer (SMMR) observations, and were compared to soil moisture data sets from the USA, Mongolia, Turkmenistan and Russia. The surface temperature, which is also an unknown parameter in the model, is derived off-line from 37?GHz vertical polarized brightness temperatures. The new theoretical approach is independent of field observations of soil moisture or canopy biophysical measurements and can be used at any wavelength in the microwave region. The soil moisture retrievals compared well with the surface moisture observations from the various locations. The vegetation optical depth also compared well to time series of Normalized Difference Vegetation Index (NDVI) and showed similar seasonal patterns. From a global perspective, the satellite-derived surface soil moisture was consistent with expected spatial patterns, identifying both known dry areas such as deserts and semi-arid areas and moist agricultural areas very well. Spatial patterns of vegetation optical depth were found to be in agreement with NDVI. The methodology described in this study should be directly transferable to the Advanced Microwave Scanning Radiometer (AMSR) on the recently launched AQUA satellite.     

Classification of reference models: a methodology and its application

Classification is an important tool for perception and can be found in numerous scientific disciplines. Several application areas of classification are described in the context of information modeling. The usefulness of classification for reuse resp. selection of reference models is emphasized. A methodology to systematically create classification systems will be introduced. Furthermore, a classification system for reference models will be developed with the aid of the proposed methodology. This classification system gives a comprehensive, but abstract survey of 26 reference models found in the literature.     

Generating vegetation leaf area index Earth system data record from multiple sensors. Part 2: Implementation,analysis and validation

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the inter-comparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.     

高准确度的传感器建模方法及应用

通过对纸张定量传感器采用插值法、最小二乘法、最佳一致逼近法建立的模型的比较,提出了一种高准确度的传感器建模方法,并对所建模型的统计特性进行了分析,其所建模型已在纸机上应用。该法也可用于其它类传感器模型的建立。     

Development of an innovative low-cost MARG sensors alignment and distortion compensation methodology for 3D scanning applications

Working in the low cost 3D scanner design domain, it would be very interesting to employ the inertial technologies because they could provide objects’ surface spatial data, recording their movements, and asking a very low cost in term of sensor investment. Unfortunately these technologies are characterized by distortion problems that normally do not allow to obtain satisfying measures for being employed for 3D scanning applications.This situation happens when working with Magnetic Angular Rate Gravity (MARG) sensor, on which many reports have been written to describe the methods used to suitably manage the data provided by the sensors in order to obtain an accurate orientation estimation; but only a few address the problem of calibration and distortion compensation. Furthermore, the proposed approaches usually involve both complex sensors models and accurate calibration facilities expensive from the workload, the computational and the economic points of view which compromise their possible employment in low-cost 3D scanning applications.In this paper, a novel approach for MARG sensors heading alignment and distortion compensation is proposed in order to increase the reliability of the information provided by the sensors and improve the process of attitude estimation, in order to get measurement quality level sufficient to be employable in 3D scanning applications.Both the effectivity and the reliability of the proposed approach are validated by some experimental results and the performances are evaluated considering the quality of the outcome provided by the same attitude estimation algorithm processing raw data and compensated data.     

Towards the sEMG hand: internet of things sensors and haptic feedback application

With the trend going on in ubiquitous computing, everything is going to be connected to the Internet and its data will be used for various progressive purposes, creating not only information from it, but also, knowledge and even wisdom. Internet of Things (IoT) is becoming important because the amount of data could make it possible to create more usefulness and develop smart applications for the users. Meanwhile, it mainly focuses on how to enable general objects to see, hear, and smell the physical world for themselves, and make them connected to share the observations. In this paper, we focus our attention on the integration of artificial sensory perception and haptic feedback in sEMG hands, which is an intelligent application of the IoT. Artificial sensory perception and haptic feedback are essential elements for amputees with myoelectric hands to restore the grasping function. They can provide information to users, such as forces of interaction and surface properties at points of contact between hands and objects. Recent advancements in robot tactile sensing led to development of many computational techniques that exploit this important sensory channel. At the same time, Surface electromyography (sEMG) is perhaps most useful for providing insight into how the neuromuscular system behaves. Therefore, integration of sEMG technology, artificial sensation and haptic feedback plays an important role in improving the manipulation performance and enhancing perceptual embodiment for users. This paper provides sEMG technologies that involve Multichannel sEMG electrodes array and processing methods, and then reviews current state-of-the-art of artificial sensation and haptic feedback. Drawing from advancements and taking into design considerations of each feedback modality and individual haptic technology, the paper outline challenging issues and future developments.

     

A cloudification methodology for multidimensional analysis: Implementation and application to a railway power simulator

Many scientific areas make extensive use of computer simulations to study complex real-world processes. These computations are typically very resource-intensive and present scalability issues as experiments get larger even in dedicated clusters, since these are limited by their own hardware resources. Cloud computing raises as an option to move forward into the ideal unlimited scalability by providing virtually infinite resources, yet applications must be adapted to this new paradigm. This process of converting and/or migrating an application and its data in order to make use of cloud computing is sometimes known as cloudifying the application. We propose a generalist cloudification method based in the MapReduce paradigm to migrate scientific simulations into the cloud to provide greater scalability. We analysed its viability by applying it to a real-world railway power consumption simulatior and running the resulting implementation on Hadoop YARN over Amazon EC2. Our tests show that the cloudified application is highly scalable and there is still a large margin to improve the theoretical model and its implementations, and also to extend it to a wider range of simulations. We also propose and evaluate a multidimensional analysis tool based on the cloudified application. It generates, executes and evaluates several experiments in parallel, for the same simulation kernel. The results we obtained indicate that out methodology is suitable for resource intensive simulations and multidimensional analysis, as it improves infrastructure’s utilization, efficiency and scalability when running many complex experiments.     

The potential of satellite remote sensing of ecological conditions for survey and forecasting desert-locust activity

Agricultural crops and rangeland resources over above 30 million km² in some 55 Third World countries arc subject to ravages by the desert locust. Successful breeding, triggered by suitable ecological conditions when widespread rainfall results in development of vegetation in the desert-locust recession area, can produce rapid increases in desert-locust populations, resulting, if uncontrolled, in large numbers of highly mobile and devastating swarms containing billions of locusts. Satellite remote sensing offers the only possibility of monitoring the 16 million km² desert-locust recession area situated largely in remote and inaccessible deserts of northern and eastern Africa, the Near East, and south-west Asia. Use of LANDSAT and National Oceanic and Atmospheric Administration (NOAA) satellite imagery for analyses of green vegetation blooms in desert-locust breeding areas suggests an operational programme based upon the NOAA Advanced Very-High-Resolution Radiometer sensor     

Modelling handgrip strength in the presence of confounding variables: results from the Allied Dunbar National Fitness Survey

Differences in handgrip strength, caused by risk factors such as physical inactivity, will be influenced by ‘confounding’ variables, e.g. age, body size. The aims of the study were to identify the confounding variables associated with handgrip strength and to assess the benefit that physical activity plays in maintaining grip strength within a population, having adjusted for differences in these confounding variables. The most appropriate linear body size dimension associated with grip strength was height rather than demispan. Non-linear associations with age and body mass were also identified. Handgrip strength peaked in the age group 25 – 34 years for male subjects and in the age group 35 44 years for female subjects. Similarly, handgrip strength increased with body mass until it peaked at a body mass of approximately 100 kg for male and 90 kg for female subjects; thereafter a rapid decline in grip strength was observed. Differences in handgrip strength were found to be significantly associated with levels of physical activity even having controlled for differences in age and body size (height, mass and percentage body fat), but the observed association was not linear. The level of physical activity necessary to maintain an optimal level of handgrip strength was found to be a balance of moderate or vigorous occasions of physical activity.     

Modelling handgrip strength in the presence of confounding variables: results from the Allied Dunbar National Fitness Survey

Differences in handgrip strength, caused by risk factors such as physical inactivity, will be influenced by 'confounding' variables, e.g. age, body size. The aims of the study were to identify the confounding variables associated with handgrip strength and to assess the benefit that physical activity plays in maintaining grip strength within a population, having adjusted for differences in these confounding variables. The most appropriate linear body size dimension associated with grip strength was height rather than demispan. Non-linear associations with age and body mass were also identified. Handgrip strength peaked in the age group 25 - 34 years for male subjects and in the age group 35 - 44 years for female subjects. Similarly, handgrip strength increased with body mass until it peaked at a body mass of approximately 100 kg for male and 90 kg for female subjects; thereafter a rapid decline in grip strength was observed. Differences in handgrip strength were found to be significantly associated with levels of physical activity even having controlled for differences in age and body size (height, mass and percentage body fat), but the observed association was not linear. The level of physical activity necessary to maintain an optimal level of handgrip strength was found to be a balance of moderate or vigorous occasions of physical activity.     

Task and training requirements analysis methodology (TTRAM): an analytic methodology for identifying potential training uses of simulator networks in teamwork-intensive task environments

A methodology designed to identify potential application areas for use of networked simulations is presented. The technique, known as task and training requirements analysis methodology (TTRAM), has been independently applied to the analysis of numerous US military aircraft simulator networking requirements, and appears to effectively discriminate tasks that are prone to skill decay, that are critical to mission success, that require high levels of internal and external teamwork, and that require additional training support.