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Power supply is the indispensable component for stable non-traditional machining based on electric power, such as electrical discharge machining (EDM), electrochemical machining (ECM), EDM-ECM combined machining, and EDM-ECM hybrid machining. The properties of power supply have significant effects on the machining performance, including efficiency, accuracy, and surface quality. This paper reviews the research progress and technical application in power supply of EDM, ECM, EDM-ECM combined machining, and EDM-ECM hybrid machining. The circuit principle, performance index, process effect of power supply are systematically analyzed. Moreover, the applications are summarized, and the future development are prospected.

Dual layer coatings CrNx and Ni-Fe alloy have been developed for metallic interconnects application by a combined approach. The CrNx layer was deposited on ferritic stainless steel using multi-arc ion plating, and the Ni-Fe alloy coating was electroplated on the CrNx coated steel subsequently. After oxidation at 800 °C in air for 5 h, a multi-layer scale composed of NiFe2O4, Cr2O3, Ni-Fe-Cr alloy and CrNx from outside to inside was formed on the CrNx/substrate with a 1.6 μm thick Ni-32 at%Fe alloy coating. Further oxidation led to the decomposition of the CrNx layer, but no pores could be observed near the scale/substrate interface even after an oxidation of 1000 h. The CrNx layer acted as an effective barrier against the mutual diffusion of elements between the coating and the substrate either before or after decomposition. The employment of the Ni-Fe/CrNx dual layer coating decreased the growth rate of the Cr2O3 scale and thus a lower scale area specific resistance (ASR). The oxidation behavior of the Ni-Fe/CrNx coated substrate and the influence mechanism of the CrNx barrier layer were discussed. Keywords: Solid oxide fuel cell, Interconnect, NiFe2O4, CrNx, Oxidation resistance, Area specific resistance

© 2002-2011 IEEE. A novel method called alternating convex optimization is presented to synthesize unequally spaced linear arrays with minimum element spacing constraint. In this method, the problem of synthesizing an unequally spaced array is formulated as a sequence of alternating convex optimization problems, and the excitation vector and auxiliary weighting vector are alternately chosen as the optimization variables. The minimum spacing constraint for considering the physical element antenna size can be easily imposed in this alternating optimization process. Two examples for synthesizing unequally spaced linear arrays with focused and shaped patterns are provided to validate the effectiveness and advantages of the proposed method.

Optimizing the Map process is important for the improvement of the MapReduce performance. Many efforts have been devoted into the problem to design more efficient scheduling strategies. However, there exists a kind of MapReduce applications, named imprecise applications, where the imprecise results based on part of map tasks can satisfy the requirements of imprecise applications and thus the job processes can be completed when enough map tasks are processed. According to the feature of imprecise applications, the authors propose an improved MapReduce model, named MapCheckReduce, which can terminate the map process when the requirements of an imprecise application is satisfied. Compared to MapReduce, a Check mechanism and a set of extended programming interfaces are added to MapCheckReduce. The Check mechanism receives and analyzes messages submitted by completed map tasks and then determines whether to terminate the map phase according to the analysis results. The programming interfaces are used by the programmers to define the termination conditions of the map process. A data-prefetching mechanism is designed and implemented in MapCheckReduce which can improve the performance of MapCheckReduce effectively. The MapCheckReduce prototype has been implemented and experiment results verify the feasibility and effectiveness of MapCheckReduce.

It is shown in this paper that the problem of reducing the number of elements for multiple- pattern arrays can be solved by a sequence of reweighted � 1 optimizations under multiple linear constraints. To do so, conjugate symmetric excitations are assumed so that the upper and lower bounds for each pattern can be formulated as linear inequality constraints. In addition, we introduce an auxiliary variable for each element to define the common upper bound of both the real and imaginary parts of multiple excitations for different patterns, so that only linear inequality constraints are required. The objective function minimizes the reweighted � 1-norm of these auxiliary variables for all elements. Thus, the proposed method can be efficiently implemented by the iterative linear programming. For multiple desired patterns, the proposed method can select the common elements with multiple set of optimized amplitudes and phases, consequently reducing the number of elements. The radiation characteristics for each pattern, such as the mainlobe shape, response ripple, sidelobe level and nulling region, can be accurately controlled. Several synthesis examples for linear array, rectangular/triangular-grid and randomly spaced planar arrays are presented to validate the effectiveness of the proposed method in the reduction of the number of elements.

Distributed storage systems, built on peer-to-peer networks, can provide large-scale data storage and high data reliability by redundancy. Data backup is the process to store data into a set of redundant storage nodes. Rapid completion of such a process is very critical to maintain system performance. In traditional data backup in distributed systems based on erasure codes, star-structured scheme is used, in which each redundant block is just sent to each target storage node from the source node directly, so the storage throughput and delay are limited by the bottleneck bandwidth, due to bandwidth heterogeneity. The recent “in-network” redundancy generation scheme uses locally repairable property of self-repairing codes to speed up data backup. However, such kind of code does not own maximum distance separable property, thus does not achieve optimal storage efficiency. We still lack a fast backup scheme in distributed systems based on general erasure coding. To this end, we proposed that instead of only focusing on bandwidths between the source node and target nodes, the bandwidths between target storage nodes should be fully taken into account. In our scheme, each redundant data block is divided into some parts according to different proportions and each part of the block is sent to the target storage node via other different storage nodes. The benefit is that spare bandwidths between target storage nodes are used to reduce backup time. We further show how this process can be modeled and derive a formula about the final backup time. We can achieve minimum backup time by solution for classical quadratic programming problem. We conduct both numerical analysis and experimental study. Our experiments shows, the delay reduces 59 %, compared with common star-structured scheme. Meanwhile, the throughput is increased significantly in backup process.

Quality of service (QoS) optimization for end-to-end (e2e) services always depends on performance analysis in cloud-based service delivery industry. However, performance analysis of e2e services becomes difficult as the scale and complexity of virtualized computing environments increase. In this paper, the authors present a novel hierarchical stochastic approach to evaluate the QoS of e2e virtualized cloud services using Quasi-Birth Death structures, where jobs arrive according to a stochastic process and request virtual machines (VMs), which are specified in terms of resources, i.e., VM-configuration. To reduce the complexity of performance evaluation, the overall virtualized cloud services are partitioned into three sub-hierarchies. The authors analyze each individual sub-hierarchy using stochastic queueing approach. Thus, the key performance metrics of e2e cloud service QoS, such as acceptance probability and e2e response delay incurred on user requests, are obtained.

In this paper, numerical pattern synthesis (NPS) algorithm integrated with seeded region growing (SRG) method is proposed to synthesize the array in the presence of mutual coupling. In order to obtain the mutual coupling between the array elements, active pattern technique is used to find active element patterns. A 4 × 8 microstrip antenna array is employed to validate the effectiveness of the proposed algorithm including mutual coupling.

© The Institution of Engineering and Technology. Antenna arrays with shaped patterns have drawn significant attention for their wide applications in radar, sonar and communication systems. The combination of genetic algorithm (GA) and fast Fourier transform (FFT) has been used to synthesise shaped pattern of antenna array's factor without considering coupling effects. In this work, the GA-FFT method is generalised by integrating with a new virtual active element pattern (AEP) expansion method which approximates each AEP as the radiation pattern by exciting several equally spaced virtual elements surrounding the real element position. The generalised GA-FFT can be applied for the shaped pattern synthesis of unequally spaced linear arrays including mutual coupling and platform effect. Several synthesis examples with different pattern shapes and different antenna structures are given to demonstrate the effectiveness, accuracy and robustness of the proposed method.

The aim of this study was to determine the value of C-reactive protein (CRP) in the diagnosis of patients with neonatal sepsis by a meta-analysis. Potential relevant studies were searched through the PubMed, Embase, and Cochrane Library databases before February 2016. We combined estimates of sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), and diagnostic odds ratio (DOR) with their 95% confidence intervals (CIs) of CRP for neonatal sepsis diagnosis. Summary receiver operating characteristic (SROC) curve was applied to evaluate the diagnostic value of CRP. The meta-regression and subgroup analysis were performed when heterogeneity was significant. In total, 31 studies were included in our meta-analysis with 5698 participants. The overall estimates for CRP in the diagnosis of neonatal sepsis were: sensitivity 0.69 (95% CI, 0.66–0.71), specificity 0.77 (95% CI, 0.76–0.78), PLR 3.83 (95% CI, 3.03–4.84), NLR 0.38 (95% CI, 0.31–0.45), and DOR 12.65 (95% CI, 8.91–17.94). The area under the curve (AUC) and Q* index were 0.8458 and 0.7773. Meta-regression analysis showed that heterogeneity was irrelevant to test time, cutoff value, assay method of CRP, neonates, and sepsis type. Heterogeneity still existed but decreased after subgroup analysis. CRP might be a valuable approach for the diagnosis of neonatal sepsis.

A new least-square active element pattern expansion (LS-AEPE) method is presented. With the help of this method, the array's pattern including the element mutual coupling and platform effect can be efficiently calculated by the fast Fourier transform (FFT). These techniques are then combined with the genetic algorithm (GA) to optimise the excitation phases for a 64-element linear array mounted on a trapezoid metal plate.

Sensor information system is a specific distributed information management system for applying sensor data and aims to effectively process, manage, and analyze data emanating from sensor networks. Recently, with the development of sensor networks, sensor information system encounters many challenges, such as huge and diverse data, heterogeneous clients, scalability, and security. In this paper, we propose an extensible and secure cloud architecture model for sensor information system. Firstly, we describe the composition and mechanism of the architecture model using cloud paradigm. Secondly, we design the security solution for accessing sensor data and information services inside the architecture. This security solution ensures legal access and use for sensor data and information services and avoids illegal breach for user data in the cloud environment. In particular, a certificate authority (CA) based Kerberos protocol is proposed to provide strong identity authentication. At last, we introduce the experiment deployment for the architecture. This architecture fully utilizes the virtualization technology and cloud service functions and builds an extensible cloud platform environment supplying scalable, flexible, reliable, and secure sensor information services, which aims to solve the challenges encountered by the present sensor information system. The simulation experiment results show that the architecture gets high performance and stability throughout, while keeping scalability and flexibility brought by cloud.