Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion

This work applies remote sensing techniques to estimate dry matter (DM) content in tree leaves. Two methods were used to estimate DM content: a normalized index obtained from the radiative transfer model (RTM) leaf optical properties spectra (PROSPECT) in direct mode and the inversion of the PROSPECT model. The data were obtained from the Leaf Optical Properties Experiment 93 (LOPEX93) database, and only 11 species were used in this study. The species selection was based mainly on the availability of data on fresh and dry samples. The estimation of DM content was obtained from an exponential function that correlated the values of the index proposed, (R₂₃₀₅???R₁₄₉₅)/(R₂₃₀₅?+?R₁₄₉₅), against the DM content of fresh and dry leaf samples. The determination coefficient obtained (r ²?=?0.672) was higher than the coefficient obtained from the inversion of the PROSPECT model (r ²?=?0.507). The data set used to validate the normalized index was provided by the Accelerated Canopy Chemistry Program (ACCP). The determination coefficient between the values obtained from ACCP data and the values estimated for the normalized index was r ²?=?0.767.     

Supporting Ubiquitous IMS-based Teleconferencing Through Discovery and Composition of IMS and Web Components

Natural communication among people happens in flexible ways and is strongly affected by the users’ situation (such as communication tools available, user’s location, and user’s preferences). This situation or context information is seldom used to initiate communication sessions among users. Current communication systems are indifferent about users’ context, often require time consuming manual configurations and often result in conferencing tools not being easily accessible when needed. This leads to lower adoption of innovative communications services. IMS SIP (IP Multimedia Subsystem, Session Initiation Protocol) sessions allow users to access the session from different points of contact (home, office, etc.), however, IMS still requires a prior knowledge of all SIP components that might be used in a SIP session. Furthermore, IMS makes limited use of context information (mainly user-defined availability). To address these issues our research approach combines techniques from pervasive computing with IMS networking principles to facilitate compositions of communication sessions based on users’ context. We propose a platform and APIs for pervasive application development support to allow greater intelligence in IMS applications. We additionally provide mechanisms for IMS applications to apply their intelligence to the configuration of physical devices and web resources used to set up a conference. The innovations proposed in this paper are: (1) A new standard for intelligent IMS-based conferencing applications. (2) Application Development Interfaces (APIs) for a platform for pervasive computing. (3) An architecture for a pervasive IMS platform.

T-MAESTRO and its authoring tool: using adaptation to integrate entertainment into personalized t-learning

Interactive Digital TV opens new learning possibilities where new forms of education are needed. On the one hand, the combination of education and entertainment is essential to boost the participation of viewers in TV learning (t-learning), overcoming their typical passiveness. On the other hand, researchers broadly agree that in order to prevent the learner from abandoning the learning experience, it is necessary to take into account his/her particular needs and preferences by means of a personalized experience. Bearing this in mind, this paper introduces a new approach to the conception of personalized t-learning: edutainment and entercation experiences. These experiences combine TV programs and learning contents in a personalized way, with the aim of using the playful nature of TV to make learning more attractive and to engage TV viewers in learning. This paper brings together our work in constructing edutainment/entercation experiences by relating TV and learning contents. Taking personalization one step further, we propose the adaptation of learning contents by defining A-SCORM (Adaptive-SCORM), an extension of the ADL SCORM standard. Over and above the adaptive add-ons, this paper focuses on two fundamental entities for the proposal: (1) an Intelligent Tutoring System, called T-MAESTRO, which constructs the t-learning experiences by applying semantic knowledge about the t-learners; and (2) the authoring tool which allow teachers to create adaptive courses with a minimal technical background.

Performance analysis of probabilistic timed automata using digital clocks

Probabilistic timed automata, a variant of timed automata extended with discrete probability distributions, is a modelling formalism suitable for describing formally both nondeterministic and probabilistic aspects of real-time systems, and is amenable to model checking against probabilistic timed temporal logic properties. However, the previously developed verification algorithms either suffer from high complexity, give only approximate results, or are restricted to a limited class of properties. In the case of classical (non-probabilistic) timed automata it has been shown that for a large class of real-time verification problems correctness can be established using an integral model of time (digital clocks) as opposed to a dense model of time. Based on these results we address the question of under what conditions digital clocks are sufficient for the performance analysis of probabilistic timed automata and show that this reduction is possible for an important class of systems and properties including probabilistic reachability and expected reachability. We demonstrate the utility of this approach by applying the method to the performance analysis of three probabilistic real-time protocols: the dynamic configuration protocol for IPv4 link-local addresses, the IEEE 802.11 wireless local area network protocol and the IEEE 1394 FireWire root contention protocol.

Apriori算法在红外光谱数据挖掘中的应用

简要地介绍了在大规模数据库中挖掘关联规则的Apriori算法 ,给出了红外光谱数据库知识发现的空间表示方法 ,并根据红外光谱数据挖掘的特点改进了Apriori算法中支持度的计算与频繁集的确定过程 ,运用统计方法把挖掘结果形成可视的特征谱带 -化学基团规则式 ,通过具体的挖掘事例对挖掘结果进行分析与评价。挖掘出的规则式和波谱分析理论比较结果证明了挖掘结果的正确性 ,说明改进过的Apriori算法挖掘红外光谱数据库的有效性     

On commutativity based Edge Lean search

The problem of state space search is fundamental to many areas of computer science, such as, e.g., AI and formal methods. Often, the state space to be searched is huge, so optimizing the search is an important issue. In this paper, we consider the problem of visiting all states in the setting where transitions between states are generated by actions, and the (reachable) states are not known in advance. Some of the actions may commute, i.e., they result in the same state for every order in which they are taken. We show how to use commutativity to achieve full coverage of the states, while traversing a relatively small number of edges.     

Improved sensor network lifetime with multiple mobile sinks

A critical issue for data gathering in wireless sensor networks is the formation of energy holes near the sinks. Sensors near the sinks have to participate in relaying data on behalf of other sensors and thus will deplete their energy very quickly, resulting in network partitioning and limitation of the network lifetime. The solution that we propose in this paper is to use mobile sinks that change their location when the nearby sensors’ energy becomes low. In this way the sensors located near sinks change over time. In deciding a new location, a sink searches for zones with richer sensor energy.First, we study the improvement in network lifetime when sinks move on a predetermined path, along the perimeter of a hexagonal tiling. Two cases are considered for data gathering when sinks stop in the hexagon’s corners and when the sinks stop on multiple locations on the hexagon perimeter. This study shows an improvement of up to 4.86 times in network lifetime. Second, we design a distributed and localized algorithm used by the sinks to decide their next movement location such that the virtual backbone formed by the sinks remains interconnected at all times. Two extensions of the distributed algorithm, coverage requirement and limitation of the time-delivery requirement, are also addressed. Simulation results are presented to verify our approaches.     

Corrected 2D-theories for composite plates

Summary The objective of the paper is to propose a simple method of formulation of 2D-theories for composite thin plates made of an arbitrary inhomogeneous linear-elastic material. The effect of inhomogeneity on the plate stiffness will be described by means of extra unknowns, called correctors, which have to satisfy a system of linear algebraic equations. The elimination of correctors can be performed in explicit form and leads to the formulas for effective stiffnesses of the plates under consideration.