Optimizing network robustness by edge rewiring: a general framework

Spectral measures have long been used to quantify the robustness of real-world graphs. For example, spectral radius (or the principal eigenvalue) is related to the effective spreading rates of dynamic processes (e.g., rumor, disease, information propagation) on graphs. Algebraic connectivity (or the Fiedler value), which is a lower bound on the node and edge connectivity of a graph, captures the “partitionability” of a graph into disjoint components. In this work we address the problem of modifying a given graph’s structure under a given budget so as to maximally improve its robustness, as quantified by spectral measures. We focus on modifications based on degree-preserving edge rewiring, such that the expected load (e.g., airport flight capacity) or physical/hardware requirement (e.g., count of ISP router traffic switches) of nodes remain unchanged. Different from a vast literature of measure-independent heuristic approaches, we propose an algorithm, called EdgeRewire, which optimizes a specific measure of interest directly. Notably, EdgeRewire is general to accommodate six different spectral measures. Experiments on real-world datasets from three different domains (Internet AS-level, P2P, and airport flights graphs) show the effectiveness of our approach, where EdgeRewire produces graphs with both (i) higher robustness, and (ii) higher attack-tolerance over several state-of-the-art methods.     

Novel Packet Switching for Green IP Networks

A green technology for reducing energy consumption has become a critical factor in ICT industries. However, for the telecommunications sector in particular, most network elements are not usually optimized for power efficiency. Here, we propose a novel energy‐efficient packet switching method for use in an IP network for reducing unnecessary energy consumption. As a green networking approach, we first classify the network nodes into either header or member nodes. The member nodes then put the routing‐related module at layer 3 to sleep under the assumption that the layer in the OSI model can operate independently. The entire set of network nodes is then partitioned into clusters consisting of one header node and multiple member nodes. Then, only the header node in a cluster conducts IP routing and its member nodes conduct packet switching using a specially designed identifier, a tag. To investigate the impact of the proposed scheme, we conducted a number of simulations using well‐known real network topologies and achieved a more energy‐ efficient performance than that achieved in previous studies.     

Composition ofO-alkyl andO-alk-1-enyl moieties in the glycerolipids of the human adrenal

A comparison of human adult and fetal adrenals with respect to their levels of glyceryl ether lipids and other lipid components is reported. Fetal glands contained significantly lower levels of alk-1-enyl phosphoglycerides and of cholesterol. Neutral glyceryl ether diesters, and ethanolamine and choline phosphoglycerides were isolated from adult adrenal tissue. The composition of theO-alkyl glycerol groups in these lipid fractions was obtained by means of gas chromatography of the trimethylsilyl ethers and diacetyl derivatives;O-alk-1-enyl glycerols were analyzed as their diacetates. About one-half of the alkyl and alk-1-enyl glycerol moieties present in glyceryl ether diesters contained hydrocarbon side chains with 20, 22, or 24 carbon atoms. Long hydrocarbon chains (C_19–24) were also found in theO-alkyl glycerol moieties present in the total lipids of fetal adrenals.     

Online decentralized information gathering with spatial–temporal constraints

We are interested in coordinating a team of autonomous mobile sensor agents in performing a cooperative information gathering task while satisfying mission-critical spatial–temporal constraints. In particular, we present a novel set of constraint formulations that address inter-agent collisions, collisions with static obstacles, network connectivity maintenance, and temporal-coverage in a resource-efficient manner. These constraints are considered in the context of the target search problem, where the team plans trajectories that maximize the probability of target detection. We model constraints continuously along the agents’ trajectories and integrate these constraint models into decentralized team planning using a computationally efficient solution method based on the Lagrangian formulation and decentralized optimization. We validate our approach in simulation with five UAVs performing search, and through hardware experiments with four indoor mobile robots. Our results demonstrate team planning with spatial–temporal constraints that preserves the performance of unconstrained information gathering and is feasible to implement with reasonable computational and communication resources.     

Energy conservation in wireless sensor networks: a rule-based approach

The research reported in this paper addresses the problem of energy conservation in wireless sensor networks (WSNs). It proposes concepts and techniques to extract environmental information that are useful for controlling sensor operations, in order to enable sensor nodes to conserve their energy, and consequently prolong the network lifetime. These concepts and techniques are consolidated in a generic framework we term CASE: Context Awareness in Sensing Environments framework. CASE targets energy conservation at the network level. A subset framework of CASE, we term CASE Compact, targets energy conservation at the sensor node level. In this paper, we elaborate on these two frameworks, elucidate the requirements for them to operate together within a WSN and evaluate the applications they can be applied to for energy conservation.     

A manufacturing-oriented approach for multi-platforming product family design with modified genetic algorithm

With highly fragmented market and increased competition, platform-based product family design has been recognized as an effective method to construct a product line that satisfies diverse customer’s demands while aiming to keep design and production cost-effective. The success of the resulting product family often relies on properly resolving the inherent tradeoff between commonality across the family and performance loss. In this paper, a systematic multi-platforming product family approach is proposed to design a scale-based product family. In the light of the basic premise that increased commonality implies enhanced manufacturing efficiency, we present an effective platform decision strategy to quantify family design configuration using a commonality index that couples design varieties with production variation. Meanwhile, unlike many existing methods that assume a single given platform configuration, the proposed method addresses the multi-platforming configuration across the family, and can generate alternative product family solutions with different levels of commonality. A modified genetic algorithm is developed to solve the aggregated multiobjective optimization problem and an industrial example of a planetary gear train for drills is given to demonstrate the proposed method.     

二维数控自动编程系统的设计

介绍了在AutoCAD中采用ADS(AutoCAD development system)实现二维数控自动编程的方法,提供了一条采用特征识别技术实现图形交互式数控机床自动编程的简便途径.     

Synthesis of organic–inorganic hybrid polymeric nanocomposites for the hard coat application

An organic–inorganic hybrid polymeric nanocomposite has been synthesized for making UV‐curable hard coats. This nanocomposite consists of nano‐sized colloidal silica functionalized with vinyltriethoxysilane (VTES) and dendritic acrylic oligomers (DAO) which have been formed earlier via a reaction of ethylenediamine (EDA) with trimethylopropane triacrylate (TMPTA). Applied as a hard coat on top of a polyethylene terephthalate (PET) film, this nanocomposite has a short UV‐cure time and the cured coat has an enhanced thermal decomposition temperature (T_d), 89–90% transparency, increased hardness up to 3H, better adhesion up to 4B, and a flat surface with a root mean square roughness of 2–4 nm. The preparation as well as the characterization of the constituting species and the final hybrid are described in detail. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 103: 3985–3993, 2007     

Development of novel biocomposites based on the clean production of microbial cellulose from dairy waste (sour whey)

This work explores the production of kombucha-derived bacterial cellulose (KBC) from sour whey via the fermentation method using Komagatacibacter xylinus. The biosynthesis process was optimized by design of experiments and the results displayed highest KBC yield at 1000 ml/L sour whey waste, 87.39 g/L cane sugar, 6 g/L black tea, and 78.91 ml/L bacteria volume under 21 days culture period at 30°C. Optimum fermentation batch efficiency was achieved in large scale with cultured medium depths of 0.5 cm and low-residual bacteria suspension volume of 72.31 ± 8.74 ml. The obtained KBC membranes were analyzed by SEM, FTIR, XRD, and TGA. The obtained results show no significant differences for all prepared KBC samples when compared to pristine bacterial cellulose from standard Hestrin and Schramm (HS) medium. In addition, the optimized KBC was investigated as a suitable bio-filler in the preparation of biocomposite materials. The prepared biocomposites as leather alternative were further characterized and their mechanical tensile strength and elongation at break determined in the range of 135.61 ± 9.15 to 154.89 ± 9.09 N/mm² and 31.06 ± 0.32 to 92.33 ± 6.91%, respectively. This model obtained depicts high-yield production of KBC and its potential in the preparation of biocomposites.     

Healing of polymeric artificial muscle reinforced ionomer composite by resistive heating

In this study, structural‐scale crack healing of artificial muscle reinforced ionomer composite was investigated following the close‐then‐heal (CTH) healing strategy. Structural‐scale crack of 3 mm deep and 1 mm wide in notched beam specimens was first closed by actuation of the embedded polymeric artificial muscles made of fishing lines, followed by intrinsic healing of the ionomer matrix. The healing process was triggered by resistive heating of embedded carbon fibers by DC power. It is found that, with 0.7% by volume of polymeric artificial muscles, the wide‐opened cracks are effectively closed, and the closed cracks in the ionomer composite are effectively and repeatedly healed, with a healing efficiency of over 80%. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43660.