Automatic computation of pebble roundness using digital imagery and discrete geometry

The shape of sedimentary particles is an important property, from which geographical hypotheses related to abrasion, distance of transport, river behavior, etc. can be formulated. In this paper, we use digital image analysis, especially discrete geometry, to automatically compute some shape parameters such as roundness, i.e. a measure of how much the corners and edges of a particle have been worn away.In contrast to previous work in which traditional digital images analysis techniques, such as Fourier transform, are used, we opted for a discrete geometry approach that allowed us to implement Wadell's original index, which is known to be more accurate, but more time consuming to implement in the field.Our implementation of Wadell's original index is highly correlated (92%) with the roundness classes of Krumbein's chart, used as a ground-truth. In addition, we show that other geometrical parameters, which are easier to compute, can be used to provide good approximations of roundness.We also used our shape parameters to study a set of pebbles digital images taken from the Progo basin river network (Indonesia). The results we obtained are in agreement with previous work and open new possibilities for geomorphologists thanks to automatic computation.     

Plans, Actions and Dialogues Using Linear Logic

We describe how Intuitionistic Linear Logic can be used to provide a unified logical account for agents to find and execute plans. This account supports the modelling of agent interaction, including dialogue; allows agents to be robust to unexpected events and failures; and supports significant reuse of agent specifications. The framework has been implemented and several case studies have been considered. Further applications include human–computer interfaces as well as agent interaction in the semantic web.     

Validation of plant part measurements using a 3D reconstruction method suitable for high-throughput seedling phenotyping

In plant phenotyping, there is a demand for high-throughput, non-destructive systems that can accurately analyse various plant traits by measuring features such as plant volume, leaf area, and stem length. Existing vision-based systems either focus on speed using 2D imaging, which is consequently inaccurate, or on accuracy using time-consuming 3D methods. In this paper, we present a computer-vision system for seedling phenotyping that combines best of both approaches by utilizing a fast three-dimensional (3D) reconstruction method. We developed image processing methods for the identification and segmentation of plant organs (stem and leaf) from the 3D plant model. Various measurements of plant features such as plant volume, leaf area, and stem length are estimated based on these plant segments. We evaluate the accuracy of our system by comparing the measurements of our methods with ground truth measurements obtained destructively by hand. The results indicate that the proposed system is very promising.     

Supporting Unified Distributed Management and Autonomic Decisions: Design,Implementation and Deployment

Nowadays, the prevailing use of networks based on traditional centralized management systems reflects on a fast increase of the management costs. The growth in the number of network equipments and services reinforces the need to distribute the management responsibilities throughout the network devices. In this approach, each device executes common network management functionalities, being part of the overall network management platform. In this paper, we present a Unified Distributed Network Management (UDNM) framework that provides a unified (wired and wireless) management network solution, where further different network services can take part of this infrastructure, e.g., flow monitoring, accurate routing decisions, distributed policies dissemination, etc. This framework is divided in two main components: (A) Situation awareness, which sets up initial information through bootstrapping, discovery, fault-management process and exchange of management information; (B) Autonomic Decision System (ADS) that performs distributed decisions in the network with incomplete information. We deploy the UDNM framework in a testbed which involves two cities (\(\approx\)250 km between), different standards (IEEE 802.3, IEEE 802.11 and IEEE 802.16e) and network technologies, such as, wired virtual grid, wireless ad-hoc gateways, ad-hoc mobile access devices. The UDNM framework integrates management functionalities into the managed devices, proving to be a lightweight and easy-respond framework. The performance analysis shows that the UDNM framework is feasible to unify devices management functionalities and to take accurate decisions on top of a real network.     

Hybrid‐impulsive second‐order sliding mode control: Lyapunov approach

Dynamic system of relative degree two controlled by discontinuous‐hybrid‐impulsive feedback in the presence of bounded perturbations is considered. The state feedback impulsive‐twisting control exhibits a uniform exact finite time convergence to the second‐order sliding mode with zero convergence time. The output feedback discontinuous control augmented by a simplified hybrid‐impulsive functions provides uniform exact convergence with zero convergence time of the system's states to a real second‐order sliding mode in the presence of bounded perturbations. Only ‘snap’ knowledge of the output derivative, that is, the knowledge of the output derivative in isolated time instants, is required. The output feedback hybrid‐impulsive control with practically implemented impulsive actions asymptotically drives the system's states to the origin. The Lyapunov analysis of the considered hybrid‐impulsive‐discontinuous system proves the system's stability. The efficacy of the proposed control technique is illustrated via computer simulations. Copyright © 2016 John Wiley & Sons, Ltd.     

Distributed planning and control systems for the virtual enterprise: organizational requirements and development life-cycle

This paper describes the requirements analysis and system specification of an Order Promise module to be used as part of a broader Decision Support System for production and operations planning of a Virtual Enterprise. This work is part of a broader project with a particular focus on the microelectronics industry which is a good example of Virtual Enterprise, and where a quick response to the customers needs and to unpredictable changes in production conditions is considered a major factor for success. First, the analysis and specification are presented within a development framework that involves the study of organizational issues of semiconductor enterprises. The use of ontological engineering for supporting the communication and shared understanding of the system concepts is explained and a virtual enterprise ontology is outlined. Following the clarification of the concept of virtual enterprise, the generic techno-organizational requirements for the information system are derived. Finally, a specification of the global planning module and a more detailed one regarding the order promise module is presented.     

Learning based brain emotional intelligence as a new aspect for development of an alarm system

The multi criteria and purposeful prediction approach has been introduced and is implemented by the fast and efficient behavioral based brain emotional learning method. On the other side, the emotional learning from brain model has shown good performance and is characterized by high generalization property. New approach is developed to deal with low computational and memory resources and can be used with the largest available data sets. The scope of paper is to reveal the advantages of emotional learning interpretations of brain as a purposeful forecasting system designed to warning; and to make a fair comparison between the successful neural (MLP) and neurofuzzy (ANFIS) approaches in their best structures and according to prediction accuracy, generalization, and computational complexity. The auroral electrojet (AE) index are used as practical examples of chaotic time series and introduced method used to make predictions and warning of geomagnetic disturbances and geomagnetic storms based on AE index.     

Integrating Computing Resources on Multiple Grid-Enabled Job Scheduling Systems Through a Grid RPC System

We present a framework for a parallel programming model by remote procedure calls, which bridge large-scale computing resource pools managed by multiple Grid-enabled job scheduling systems. With this system, the user can exploit not only remote servers and clusters, but also the computing resources provided by Grid-enabled job scheduling systems located on different sites. This framework requires a Grid remote procedure call (RPC) system to decouple the computation in a remote node from the Grid RPC mechanism and uses document-based communication rather than connection-based communication. We implemented the proposed framework as an extension of the OmniRPC system, which is a Grid RPC system for parallel programming. We designed a general interface to easily adapt the OmniRPC system to various Grid-enabled job scheduling systems, including XtremWeb, CyberGRIP, Condor and Grid Engine. We show the preliminary performance of these implementations using a phylogenetic application. We found that the proposed system can achieve approximately the same performance as OmniRPC and can handle interruptions in worker programs on remote nodes. Yoshihiro Nakajima is a Research Fellow of the Japan Society for the Promotion of Science     

Snap-stabilization and PIF in tree networks

The contribution of this paper is threefold. First, we present the paradigm of snap-stabilization. A snap- stabilizing protocol guarantees that, starting from an arbitrary system configuration, the protocol always behaves according to its specification. So, a snap-stabilizing protocol is a time optimal self-stabilizing protocol (because it stabilizes in 0 rounds). Second, we propose a new Propagation of Information with Feedback (PIF) cycle, called Propagation of Information with Feedback and Cleaning (). We show three different implementations of this new PIF. The first one is a basic cycle which is inherently snap-stabilizing. However, the first PIF cycle can be delayed O(h ²) rounds (where h is the height of the tree) due to some undesirable local states. The second algorithm improves the worst delay of the basic algorithm from O(h ²) to 1 round. The state requirement for the above two algorithms is 3 states per processor, except for the root and leaf processors that use only 2 states. Also, they work on oriented trees. We then propose a third snap-stabilizing PIF algorithm on un-oriented tree networks. The state requirement of the third algorithm depends on the degree of the processors, and the delay is at most h rounds. Next, we analyze the maximum waiting time before a PIF cycle can be initiated whether the PIF cycle is infinitely and sequentially repeated or launch as an isolated PIF cycle. The analysis is made for both oriented and un-oriented trees. We show or conjecture that the two best of the above algorithms produce optimal waiting time. Finally, we compute the minimal number of states the processors require to implement a single PIF cycle, and show that both algorithms for oriented trees are also (in addition to being time optimal) optimal in terms of the number of states. WARNING: The concept of snap-stabilization was first introduced in [12]. The concept evolved over the last eight years. We take this evolution in consideration in this paper, which includes the early results published in [10] and [12]. In particular, infinite repetition of computation cycles is a requirement of self-stabilizing systems. This is not required in snap-stabilization because snap-stabilization ensures that the first completed computation cycle is executed according to the specification of the problem. The correctness proofs conform to this basic property.     

Bronchoalveolar lavage. Quantitation of intraalveolar fluid?

A precise calculation of the amount of intraalveolar fluid is the basis of a quantitative analysis of intraalveolar compounds. Different approaches have been made to cover this important problem. Here, we report a comparative study with five markers: 99mTc-DTPA, 51Cr-EDTA, inulin, urea, and methylene blue in animal experiments as well as in human experiments. The marker substances were added to the lavage fluid, and the "dilution" of the markers, i.e., the alveolar fluid, was calculated. The results showed that in animals with healthy lungs the tracer methods are able to calculate amounts of intraalveolar fluid that are comparable to morphologic findings. In animals as well as in humans, methylene blue and inulin were shown to be useless in determining alveolar fluid volume compared with the tracer methods. In humans, the calculations with the urea method and with Tc-DTPA were in the same magnitude, but there was no individual correlation. We conclude that, at present, the methods to quantitate alveolar fluid volume lack precision and add nothing to a deeper understanding of alveolar biology.