VIRAL: coupling congestion control with fair video quality metric

Video streaming is often carried out by congestion controlled transport protocols to preserve network sustainability. However, the success of the growth of such non-live video flows is linked to the user quality of experience. Thus, one possible solution is to deploy complex quality of service systems inside the core network. Another possibility would be to keep the end-to-end principle while making aware transport protocols of video quality rather than throughput. The objective of this article is to investigate the latter by proposing a novel transport mechanism which targets video quality fairness among video flows. Our proposal, called VIRAL for virtual rate-quality curve, allows congestion controlled transport protocols to provide fairness in terms of both throughput and video quality. VIRAL is compliant with any rate-based congestion control mechanisms that enable a smooth sending rate for multimedia applications. Implemented inside TFRC a TCP-friendly protocol, we show that VIRAL enables both intra-fairness between video flows in terms of video quality and inter-fairness in terms of throughput between TCP and video flows.     

Connected dominating sets in disk graphs with bidirectional links

In this paper, we study the connected dominating set (CDS) problem in disk graphs. The CDS problem has a significant impact on an efficient design of routing protocols in wireless networks. This problem has been studied extensively in unit disk graphs, in which each node has the same transmission range. However, in wireless ad hoc networks, the transmission ranges of all nodes are not necessary equal. In this paper, we introduce the CDS problem in disk graphs and present a constant approximation algorithm which can be implemented as a distributed algorithm.     

Force control of hybrid actuator using learning vector quantization neural network

Hydraulic actuators are important in modern industry due to high power, fast response, and high stiffness. In recent years, hybrid actuation system, which combines electric and hydraulic technology in a compact unit, can be adapted to a wide variety of force, speed and torque requirements. Moreover, the hybrid actuation system has dealt with the energy consumption and noise problem existed in the conventional hydraulic system. Therefore, hybrid actuator has a wide range of application fields such as plastic injection-molding and metal forming technology, where force or pressure control is the most important technology. In this paper, the solution for force control of hybrid system is presented. However, some limitations still exist such as deterioration of the performance of transient response due to the variable environment stiffness. Therefore, intelligent switching control using Learning Vector Quantization Neural Network (LVQNN) is newly proposed in this paper in order to overcome these limitations. Experiments are carried out to evaluate the effectiveness of the proposed algorithm with large variation of stiffness of external environment. In addition, it is understood that the new system has energy saving effect even though it has almost the same response as that of valve controlled system.     

Machine learning-based optimization of process parameters in selective laser melting for biomedical applications

Journal of Intelligent Manufacturing - Titanium-based alloy products manufactured by Selective Laser Melting (SLM) have been widely used in biomedical applications, owing to their high...     

Foundations for using linear temporal logic in Event-B refinement

In this paper we present a new way of reconciling Event-B refinement with linear temporal logic (LTL) properties. In particular, the results presented in this paper allow properties to be established for abstract system models, and identify conditions to ensure that the properties (suitably translated) continue to hold as those models are developed through refinement. There are several novel elements to this achievement: (1) we identify conditions that allow LTL properties to be mapped across refinement chains; (2) we provide translations of LTL predicates to reflect the introduction through refinement of new events and the renaming and splitting of existing events; (3) we do this for an extended version of LTL particularly suited to Event-B, including state predicates and enabledness of events, which can be model-checked at the abstract level. Our results are more general than any previous work in this area, covering liveness in the context of anticipated events, and relaxing constraints between adjacent refinement levels. The approach is illustrated with a case study. This enables designers to develop event based models and to consider their execution patterns so that liveness and fairness properties can be verified for Event-B systems.     

Temporal and spatial outlier detection in wireless sensor networks

Outlier detection techniques play an important role in enhancing the reliability of data communication in wireless sensor networks (WSNs). Considering the importance of outlier detection in WSNs, many outlier detection techniques have been proposed. Unfortunately, most of these techniques still have some potential limitations, that is, (a) high rate of false positives, (b) high time complexity, and (c) failure to detect outliers online. Moreover, these approaches mainly focus on either temporal outliers or spatial outliers. Therefore, this paper aims to introduce novel algorithms that successfully detect both temporal outliers and spatial outliers. Our contributions are twofold: (i) modifying the Hampel Identifier (HI) algorithm to achieve high accuracy identification rate in temporal outlier detection, (ii) combining the Gaussian process (GP) model and graph‐based outlier detection technique to improve the performance of the algorithm in spatial outlier detection. The results demonstrate that our techniques outperform the state‐of‐the‐art methods in terms of accuracy and work well with various data types.     

A novel size-dependent nonlocal strain gradient isogeometric model for functionally graded carbon nanotube-reinforced composite nanoplates

The paper presents a novel nonlocal strain gradient isogeometric model for functionally graded carbon nanotube-reinforced composite (FG-CNTRC) nanoplates. To observe the length scale and size-dependency effects of nanostructures, the nonlocal strain gradient theory (NSGT) is considered. The present model is efficient to capture both nonlocal effects and strain gradient effects in nanoplate structures. In addition, the material properties of the FG-CNTRC are assumed to be graded in the plate thickness direction. Based on the higher order shear deformation theory (HSDT), the weak form of the governing equations of motion of the nanoplates is presented using the principle of virtual work. Afterward, the natural frequency and deflection of the nanoplates are made out of isogeometric analysis (IGA). Thanks to higher order derivatives and continuity of NURBS basic function, IGA is suitable for the weak form of NSGT which requires at least the third-order derivatives in approximate formulations. Effects of nonlocal parameter, strain gradient parameter, carbon nanotube (CNT) volume fraction, distributions of CNTs and length-to-thickness ratios on deflection and natural frequency of the nanoplates are examined and discussed in detail. Numerical results are developed to show the phenomenon of stiffness-softening and stiffness-hardening mechanisms of the present model.

     

The Ha Tien Plain – wetland monitoring using remote-sensing techniques

The study investigates land-cover change in the Ha Tien Plain, once considered to be the last remaining extensive wetland area of seasonally inundated grassland in the Mekong Delta. For this purpose, two Landsat images recorded in 1991 and 2009, respectively, were classified using the C5.0 decision tree classifier. A subsequent change detection analysis revealed a significant decrease of 77% of the area classified as seasonally inundated grassland in 1991, mainly due to the conversion into agriculture, aquaculture, and forest. Since these wetlands support a high diversity of flora and a rich avifauna, there should be a focus on the protection of the last remnant patches of seasonally inundated grasslands in the Ha Tien Plain in order to preserve their biodiversity values and ecosystem functions.     

Event-B patterns and their tool support

Event-B has given developers the opportunity to construct models of complex systems that are correct-by-construction. However, there is no systematic approach, especially in terms of reuse, which could help with the construction of these models. We introduce the notion of design patterns within the framework of Event-B to shorten this gap. Our approach preserves the correctness of the models, which is critical in formal methods and also reduces the proving effort. Within our approach, an Event-B design pattern is just another model devoted to the formalisation of a typical sub-problem. As a result, we can use patterns to construct a model which can subsequently be used as a pattern to construct a larger model. We also present the interaction between developers and the tool support within the associated RODIN Platform of Event-B. The approach has been applied successfully to some medium-size industrial case studies.