Routing Strategies Under Demand Uncertainty

In this paper, we study network routing and traffic controls under demand uncertainty. Specifically, we examine the strategy of using a deterministic parameter in an optimization setting (a strategy employed in the literature) to represent the demand uncertainty, where traffic flows are modeled using the cell transmission model (CTM). For a special class of networks, for which instances have been previously analyzed in the literature, we provide an optimal policy (i.e., a policy whose solution is optimal for any realization of the demand). Using this optimal policy we show the problems inherent using a deterministic parameter to represent uncertainty. We then show that, for other types of networks, for which optimal policies do not exist, simple heuristics can outperform the use of optimization with a deterministic parameter that represents the demand uncertainty.     

Assessing daily and seasonal satellite rainfall estimates using local gauges for the anomalous 2012 monsoon season in the African East Sahel

Satellite rainfall estimates (SRFEs) are essential for characterizing the seasonal delivery of monsoon rainfall to sub-Saharan Africa. Such data are particularly robust when composited over sufficiently large areas of the Earth's surface (≥2500 km²), and sufficiently long time periods (≥1 month). However, the application of SRFEs to early warning flash-flood and drought-monitoring systems at the hamlet level is less well documented, particularly for areas dominated by intense, small-scale convective storms, which require a higher spatial and temporal resolution than usually expected from standard SRFE products. This report assesses the potential of one of the primary contenders for such applications – the Climate Prediction Center (CPC) Rainfall Estimation Algorithm Version 2.0 (or RFE2) product – posing the specific challenge: How well does the RFE2 product perform on a site-by-site, storm-by-storm basis as a potential tool for early warning flood and drought applications in the East Sahel? Daily gridded (0.1° × 0.1°) RFE2 estimates are compared with daily time series from nine gauges provided by local agencies in the state of Gedaref, Sudan (area of gauge coverage ≈ 160 km × 160 km). Seasonal composites of multiple gauges and multiple RFE2 cells for 2012 (1 April to 31 October) agree quite well. However, daily time series of individual pairs of gauge data and corresponding RFE2 estimates show a remarkable lack of temporal coherence ? typically only 10?20% of the daily variance of the RFE2 time series is associated with the gauge data. Moreover, low-pass filtered (30 day cut-off), smoothed versions of the daily RFE2 data do not conform well to the corresponding gauge distributions over the season, and fail to capture a seasonal bimodal rainfall pattern recorded by a cluster of rain gauges. Finally, there is a characteristic difference in the intensity-versus-frequency statistics of RFE2-produced events compared with corresponding gauge observations: RFE2 estimates imply that rain should have occurred on 70% of the days, whereby gauges recorded rainfall on only 35% of the days. On the other hand, extreme storms recorded by the gauge data are typically twice as strong as those estimated by the RFE2 algorithm. These results circumscribe specific limits on the RFE2 product for the purpose of site-by-site, storm-by-storm early warning monitoring of rainfall events, and for resolving details on the intra-seasonal modulation of rainfall patterns.     

A review on vision-based control of flexible manipulators

In this review, recent developments in the field of flexible robot arm control using visual servoing are reviewed. In comparison to rigid robots, the end-effector position of flexible links cannot be obtained precisely enough with respect to position control using kinematic information and joint variables. To solve the task here the use of a vision sensor (camera) system, visual servoing is proposed to realize the task of control flexible manipulators with improved quality requirements. The paper is organized as follows: the visual servoing architectures will be reviewed for rigid robots first. The advantages, disadvantages, and comparisons between different approaches of visual servoing are carried out. The using of visual servoing to control flexible robot is addressed next. Open problems such as state variables estimation as well as the combination of different sensor properties as well as some application-oriented points related to flexible robot are discussed in detail.     

A novel edge detection method with application to the fat content prediction in marbled meat

Intramuscular fat is an important quality criterion, notably juiciness, in meat grading. But traditional visual inspectors are time consuming and destructive. However, edge detection techniques characterize meat surface in consistence, rapid, and non-destructive approach. In this paper, novel edge detection method applied on intramuscular fat is presented based on the energy and skewness as two smoothed versions of the image. Parametric analyses were investigated and the method was tested on several images, producing minimum improvements of 6.451%, 1.667% and 7.826% in signal to noise ratio, mean square error and edges localization, respectively, in comparison to Roberts, Prewitt, Sobel, and Canny detectors.     

The Calculus of Context-aware Ambients

We present the Calculus of Context-aware Ambients (CCA in short) for the modelling and verification of mobile systems that are context-aware. This process calculus is built upon the calculus of mobile ambients and introduces new constructs to enable ambients and processes to be aware of the environment in which they are being executed. This results in a powerful calculus where both mobility and context-awareness are first-class citizens. We present the syntax and a formal semantics of the calculus. We propose a new theory of equivalence of processes which allows the identification of systems that have the same context-aware behaviours. We prove that CCA encodes the π-calculus which is known to be a universal model of computation. Finally, we illustrate the pragmatics of the calculus through many examples and a real-world case study of a context-aware hospital bed.     

A real-time scheduling framework for embedded systems with environmental energy harvesting

Real-time scheduling refers to the problem in which there is a deadline associated with the execution of a task. In this paper, we address the scheduling problem for a uniprocessor platform that is powered by a renewable energy storage unit and uses a recharging system such as photovoltaic cells. First, we describe our model where two constraints need to be studied: energy and deadlines. Since executing tasks require a certain amount of energy, classical task scheduling like earliest deadline is no longer convenient. We present an on-line scheduling scheme, called earliest deadline with energy guarantee (EDeg), that jointly accounts for characteristics of the energy source, capacity of the energy storage as well as energy consumption of the tasks, and time. In order to demonstrate the benefits of our algorithm, we evaluate it by means of simulation. We show that EDeg outperforms energy non-clairvoyant algorithms in terms of both deadline miss rate and size of the energy storage unit.     

Secure and imperceptible digital image steganographic algorithm based on diamond encoding in DWT domain

This paper presents a new efficient embedding algorithm in the wavelet domain of digital images based on the diamond encoding (DE) scheme. Current discrete wavelet transform (DWT) steganography adds an unacceptable distortion to the images and is considered as an ineffective in terms of security. Applying the DE scheme to the current DWT steganographic methods solves the problems of these methods, and reduces the distortion added to the images, and thus improves the embedding efficiency. The proposed algorithm first converts the secret image into a sequence of base-5 digits. After that, the cover image is transformed into the DWT domain and segmented into 2?×?1 coefficient pairs. The DE scheme is used then to change at most one coefficient of each coefficient pair to embed the base-5 digits. Experimental results depict that the proposed algorithm is more efficient in embedding compared to other methods in terms of embedding payload and image quality. Moreover, the proposed algorithm is attacked by well-known steganalysis software. Results are showing that the proposed algorithm is secure against the powerful universal steganalyzer “ensemble classifier” and the histogram attack. The results also reveal that the proposed algorithm is robust against different image processing attacks such as compression, added noise, and cropping attacks.     

Multi-dimensional optimization of functionally graded material composition using polynomial expansion of the volume fraction

The work of this paper proposes a method for multi-dimensional optimization of functionally graded materials (FGMs) composition. The method is based on using polynomial expansion of the volume fraction of the constituent materials. In this approach, the design variables are the coefficients of the polynomial expansion which to be determined through the optimization process. This method provides much more flexibility in the design compared to the methods based on the power-law, or the exponential-law which will in turn lead to more optimal designs. Also it requires much less number of design variables compared to the grid based approaches which is also utilized for two-dimensional optimization of FGMs structures. As an application of the proposed method, the optimization of a simply supported Aluminum plate reinforced with Silicon Carbide nano-particles is considered. Cost plays a very important role for this type of structures, since the cost of the reinforcements such as Silicon Carbide nano-particles, or carbon nano-tubes is too high. So the aim of the optimization process is to minimize the amount of the reinforcement required to satisfy certain performance criteria. Both static, and dynamic cases are considered in this work; a plate under a transverse pressure distribution is considered as the static case, and the panel flutter problem as the dynamic case.     

拉丁化维吾尔文字特征及其基于规则的正规化

结合网络上流通的拉丁化维吾尔文字特征,以拉丁化维吾尔文单词作为研究单位,首先,通过大规模文本语料库建立了固定词库、词首字母序列库、词尾字母序列库以及特殊词库等正规化规则库。然后,利用维吾尔单词中的字母序列结构特征和相邻字母上下文信息进行了拉丁化维吾尔文的正规化,同时引用最小编辑距离的方法进一步提高了正规化正确率,并用Visual C# 编程工具实现了基于规则的拉丁化维吾尔文的正规化算法。最后,给出了实验结果,并分析了结果不佳的原因及相应的对策。