Emotional clouds: Showing arousal and valence through the movement and darkness of digital cartoonish clouds

While nowadays the most usual way to show emotions in digital contexts is via virtual characters, its use may raise false expectations (the user attributes human abilities to the virtual character). This paper proposes and explores an approach to express emotions which intends to minimize the user's expectations by using a non-anthropomorphic model. Emotions are represented in terms of arousal and valence dimensions. They are visualized in a simple way through the behaviour and appearance of a series of cartoonish clouds. In particular, the arousal value is expressed through the movement of these clouds (controlled by a flocking algorithm), while the valence value is expressed through their degree of darkness. Furthermore, the paper describes a user experiment which investigated whether the arousal and valence expressed by our model are appropriately interpreted by the users or not. The results suggest that movement and darkness are interpreted as arousal and valence respectively and that they are independent of each other.     

云规则生成器的异常分析与对策研究

云规则生成器是实现基于云模型的控制系统的核心模块，该文对云模型、定性知识的表示及云规则生成器的异常情况进行了分析，提出了异常报告、异常处理及前件序列化相结合的方法，从而提高了云规则生成器的稳定性、可靠性、效率及灵活性。最后，据此设计了云规则生成器的实现体系。     

Characterization of cloud cover with a smartphone camera

A smartphone sky camera and associated image analysis algorithm has been developed and validated to determine total cloud cover and the percentage of thick and thin clouds using supervised image classification for a range of cloud types, cloud cover from 4% to 98%, and solar zenith angles between 6° and 49°. Additionally, this system provides the percentage of total, thick, and thin clouds in proximity to the solar disc. The measurement errors were comparable to those associated with values obtained by commercial sky camera systems. The benefits of increasing the availability of cloud fraction measurements include the potential to develop improved local ultraviolet indices and weather forecasts and to provide a better understanding of cloud patterns required for the generation of solar energy.     

Verification of some very simple clear and cloudy sky models to evaluate global solar irradiance

Several very simple clear sky and cloudy sky global irradiance models were tested under the climate and latitudes of Romania (Eastern Europe). The very simple clear sky models do not require meteorological data while the very simple cloudy sky models need only data on the total cloud amount. Three slightly more complex cloudy sky models which use additional meteorological inputs were also tested. The mean absolute error of the very simple clear sky models varies between 7 and 14% in July and between 12 and 19% in January. The best model originates from Western Europe. The performance of the very simple cloudy sky models is comparable to that of the more complicated ones. This is the main conclusion of the paper. Generally, their root mean square error varies between 35 and 45% in close agreement with results from the literature. Twelve classes of daily average cloudiness were defined. The model accuracy is better for the first six classes (with smaller cloud amount) and worse for the other six classes.     

Resource provisioning in Science Clouds: Requirements and challenges

Cloud computing has permeated into the information technology industry in the last few years, and it is emerging nowadays in scientific environments. Science user communities are demanding a broad range of computing power to satisfy the needs of high‐performance applications, such as local clusters, high‐performance computing systems, and computing grids. Different workloads are needed from different computational models, and the cloud is already considered as a promising paradigm. The scheduling and allocation of resources is always a challenging matter in any form of computation and clouds are not an exception. Science applications have unique features that differentiate their workloads; hence, their requirements have to be taken into consideration to be fulfilled when building a Science Cloud. This paper will discuss what are the main scheduling and resource allocation challenges for any Infrastructure as a Service provider supporting scientific applications.     

遥感测云微脉冲激光雷达

文中介绍一种用于大气云层研究与气溶胶监测的结构紧凑、对人眼安全、高性能和高可靠性的新型全固态激光雷达－微脉冲激光雷达（ＭＰＬ）,该雷达可长时间、实时和自动化工作,对人眼十分安全,它的性能在大气辐射测量（ＡＲＭ）项目中得到验证,并和ＵＩＳＡＬＡ云高计进行比较。证实了遥测云层时,在分辨率、成像能力、云层结构分析、抗干扰能力、小型化、多样化运载平台和成本上均优于微波气象雷达。作用距离已达６０ｋｍ以上。三维测量能力和测量度优于被动辐射计。     

Outgoing longwave flux estimation: improvement of angular modelling using spectral information

A radiance-to-flux conversion is needed to estimate radiative fluxes at the top of the atmosphere from directional measurements made by broadband (BB) radiometers on satellites. Such a conversion is known to be one of the major sources of error in the resulting instantaneous shortwave and longwave fluxes. This paper analyzes the possibility to improve the radiance-to-flux conversion for the longwave radiation when spectral information about the radiation is available through a set of narrow-band (NB) measurements. The study is based on a database of spectral radiance fields at the top of the atmosphere built using radiative transfer computation. The analysis of this database shows that there exists a certain degree of correlation between the angular and the spectral behaviors of the radiation field. According to the type and the accuracy of the spectral information, this correlation allows a 25-55% reduction of the error introduced by the radiance-to-flux conversion with respect to a simple model that uses only broadband information. The method discussed in this paper might be used when broadband radiometer and spectral imager data are available together like the combination of Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Radiometer Imager (SEVIRI) or the combination of CERES and MODIS.     

Reconstruction of cloud geometry from multi-view satellite images

Reflected solar radiances measured by the pushbroom cameras of the Multiangle Imaging SpectroRadiometer (MISR) on the Terra satellite at nine viewing angles are combined to give eight stereo pairs. These are analyzed with stereo-photogrammetric methods to measure the geometry of a convective cloud system. Both cloud-top heights and cloud sides are retrieved with a precision of about 200-300 m. Two case studies of deep, convective clouds over ocean are considered. The accuracy of the MISR retrieval is tested in the first case study by reference to coincident, higher resolution stereo data from ASTER, showing how the accuracy of the cloud-top height retrieval is improved using the oblique MISR views. In the second case study, the entire cross-section of the cloud aligned with the viewing azimuthal direction is measured, using all nine cameras. The methodology presented is an important step towards more routine retrievals of the 3D geometrical reconstruction of isolated, deep-convective clouds. Such reconstructions are a necessary prerequisite to the subsequent 3D radiative transfer modeling used to aid the remote sensing of the elusive microphysical properties of such clouds.     

Private Clouds: Secure Managed Services

ABSTRACT

The continuously evolving state of information technology and network infrastructure has created a thriving market for Managed Services (MS). More and more public sector and private companies operate in mixed-mode with internally deployed but externally hosted IT applications and resources. As a result, Managed Service Providers (MSPs) are assuming operational IT responsibility for the enterprise while the customer maintains management oversight. While this MS business model has many advantages, information security remains an inherent weakness. This has lead to the adoption of Private Clouds.