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We propose two new authentication schemes for the cloud that support private attribute-based authentication services. The basic scheme is non-anonymous attribute-based authentication scheme. The extended scheme of the basic scheme is fully anonymous attribute-based authentication scheme to realize full anonymity and unlinkability services. In the proposed schemes, a user is authenticated by the remote server if the intersection of the set of his/her assigned attributes and the server’s required attributes exceeds a satisfactory predefined level. Unlike existing attribute-based encryption and signature schemes that require the user to perform significant amount of elliptic curve bilinear pairings and modular exponentiations, and require the user to hold a significantly long decryption/signature key, in our schemes the user is not required to perform any bilinear pairings. With a fixed length private key, independent of the number of attributes, the cloud user performs only few exponentiations by which he/she is able to authenticate himself/herself to the remote server and establish a session key with the server with the condition that he/she satisfies a predefined level of the server’s attributes requirement. Therefore, our schemes are suitable for implementation on devices with limited resources. We provide the rigorous security of the proposed schemes and complexity analysis of our schemes. Finally, the security and performance comparisons of our schemes with the existing related schemes show that our schemes outperform other existing schemes. [ABSTRACT FROM AUTHOR]

As is well known, the additional low-order harmonic currents and the huge computation amount of the cost function value with all available control sets are the two special issues of finite-control-set model predictive current control (FCS-MPCC) for multiphase inverters. Thus, this paper proposes a FCS-MPCC scheme with duty-ratio optimization for five-phase inverters. First, a group of the reconstructed virtual voltage vectors (V3) with low-order harmonic elimination is defined and employed as the control sets in FCS-MPCC scheme. Thus, it leads to no requirement for harmonic items and weighting factors existing in the cost function. Then, a combination of zero vectors and the selected V3 during each control horizon is adopted to rearrange the pulse sequence, which can realize constant switching frequency. In addition, the durations of the selected V3 and zero vectors during each control horizon are also estimated to minimize the steady-state current ripples in different subspaces based on the cost function optimization. Finally, a comparison of the proposed V3-FCS-MPCC scheme and the other FCS-MPCCs are presented in simulation and experimental test. Simulation and experimental results verify that the proposed V3-FCS-MPCC scheme can remain the simplified structure, fast dynamic performance, constant switching frequency, and achieve minimum current ripples in different subspaces. [ABSTRACT FROM PUBLISHER]

The modular multilevel converter (MMC) is attractive for medium- or high-power applications because of the advantages of its high modularity, availability, and high power quality. Reliability is one of the most important challenges for the MMC consisting of a large number of power electronic devices. The diode open-circuit fault in the submodule (SM) is an important issue for the MMC, which would affect the performance of the MMC and disrupt the operation of the MMC. This paper analyzes the impact of diode open-circuit failures in the SMs on the performance of the MMC and proposes a protection scheme for the MMC under diode open-circuit faults. The proposed protection scheme not only can effectively eliminate the possible caused high voltage due to the diode open-circuit fault but also can quickly detect the faulty SMs, which effectively avoids the destruction and protects the MMC. The proposed protection scheme is verified with a downscale MMC prototype in the laboratory. The results confirm the effectiveness of the proposed protection scheme for the MMC under diode open-circuit faults. [ABSTRACT FROM PUBLISHER]

Attribute based encryption (ABE) is a good way to achieve flexible and secure access control to data, and attribute revocation is the extension of the attribute-based encryption, and the keyword search is an indispensable part for cloud storage. The combination of both has an important application in the cloud storage. In this paper, we construct a searchable attribute-based encryption scheme with attribute revocation in cloud storage, the keyword search in our scheme is attribute based with access control, when the search succeeds, the cloud server returns the corresponding cipher text to user and the user can decrypt the cipher text definitely. Besides, our scheme supports multiple keywords search, which makes the scheme more practical. Under the assumption of decisional bilinear Diffie-Hellman exponent (q-BDHE) and decisional Diffie-Hellman (DDH) in the selective security model, we prove that our scheme is secure. [ABSTRACT FROM AUTHOR]

Public key encryption with keyword search (PEKS) is a cryptographic primitive that allows a secure search for desired keywords of data users by a cloud server using a search token. To the best of our knowledge, we propose the first practical, semantic secure, and post-quantum PEKS scheme based on rank metric codes. The proposed scheme is secure against keyword guessing attack, reaction attack, and key exposure, and enjoys conjunctive keyword search, verifiability of search results using Bloom filter and garbled Bloom filter. We implement the scheme with C++ programming language on a desktop computer. At the security level of 256 bits, the scheme performs all the necessary steps for encryption, keyword search, and verification of search results for one keyword in 22.5 milliseconds. Furthermore, the public key length at this security level is about 5 kilobytes. We show that the scheme is more efficient than the existing relevant post-quantum ones. [Display omitted] • A public key with keyword search scheme based on rank metric codes is proposed. • The scheme is secure under chosen keyword, keyword guessing, and reaction attacks. • The scheme is secure against quantum processors, having a small public key. • The scheme supports the verifiability of search results and conjunctive keyword search. [ABSTRACT FROM AUTHOR]

The Self-Organizing Networks (SON) paradigm proposes a set of functions to automate network management in mobile communication networks. Within SON, the purpose of Self-Healing is to detect cells with service degradation, diagnose the fault cause that affects them, rapidly compensate the problem with the support of neighboring cells and repair the network by performing some recovery actions. The diagnosis phase can be designed as a classifier. In this context, hybrid ensembles of classifiers enhance the diagnosis performance of expert systems of different kinds by combining their outputs. In this paper, a novel scheme of hybrid ensemble of classifiers is proposed as a two-step procedure: a modeling stage of the baseline classifiers and an application stage, when the combination of partial diagnoses is actually performed. The use of statistical models of the baseline classifiers allows an immediate ensemble diagnosis without running and querying them individually, thus resulting in a very low computational cost in the execution stage. Results show that the performance of the proposed method compared to its standalone components is significantly better in terms of diagnosis error rate, using both simulated data and cases from a live LTE network. Furthermore, this method relies on concepts which are not linked to a particular mobile communication technology, allowing it to be applied either on well established cellular networks, like UMTS, or on recent and forthcoming technologies, like LTE-A and 5G. [ABSTRACT FROM AUTHOR]

In this paper, we show that large annotated data sets have great potential to provide strong priors for saliency estimation rather than merely serving for benchmark evaluations. To this end, we present a novel image saliency detection method called saliency transfer. Given an input image, we first retrieve a support set of best matches from the large database of saliency annotated images. Then, we assign the transitional saliency scores by warping the support set annotations onto the input image according to computed dense correspondences. To incorporate context, we employ two complementary correspondence strategies: a global matching scheme based on scene-level analysis and a local matching scheme based on patch-level inference. We then introduce two refinement measures to further refine the saliency maps and apply the random-walk-with-restart by exploring the global saliency structure to estimate the affinity between foreground and background assignments. Extensive experimental results on four publicly available benchmark data sets demonstrate that the proposed saliency algorithm consistently outperforms the current state-of-the-art methods. [ABSTRACT FROM PUBLISHER]

Masquerade attackers are internal intruders acting through impersonating legitimate users of the victim system. Most of the proposals for their detection suggested recognition methods based on the comparison of use models of the protected environment. However recent studies have shown their vulnerability against adversarial attacks based on imitating the behavior of legitimate users. In order to contribute to their identification, this article introduces a novel detection method robust against evasion strategies based on mimicry. The proposal described two levels of information processing: analysis and verification. At the analysis stage, local alignment algorithms are implemented. In this way it is possible to score the similarity between action sequences performed by users, bearing in mind their regions of greatest resemblance. On the other hand, a novel validation scheme based on the statistical non-parametric U-test is implemented. Through this it is possible to refine the labeling of sequences to avoid making hasty decisions when their nature is not sufficiently clear. In order to strengthen their effectiveness against mimicry attacks, the analysis of the monitored sequences is performed in concurrency. This involves partitioning long sequences with two purposes: making subsequences of small intrusions more visible and analyzing new sequences when suspicious situations occur, such as the execution of never before seen commands or the discovery of potentially harmful activities. The proposal has been evaluated from the functional standard SEA and mimicry attacks. Promising experimental results have been shown, demonstrating great precision against conventional masqueraders (TPR=98.3%, FPR=0.77%) and a success rate of 80.2% when identifying mimicry attacks, hence outperforming the best contributions of bibliography. [ABSTRACT FROM AUTHOR]

This paper analyzes the security issues of the recently proposed image encryption scheme based on paired interpermuting planes. The permutation process of the scheme is designed to permute the pixel values between colour channels and in the diffusion process, the function value of previous cipher is xored to the current pixel, where the function is a permutation map. For a single round encryption/decryption, the chosen plaintext/ciphertext attack is performed to find the permutation map and the keys of the permutation process. A modified scheme is proposed in which the permutation is done in two stages, within the colour channel using generalised cat map and between the colour channels that depends on the values of the pixel after the permutation within the colour channel. The diffusion process chooses the xoring value based on the previous pixel cipher value and the pixel location. These processes are designed to overcome the weaknesses identified and the to resist the chosen plaintext/ciphertext attack. [ABSTRACT FROM AUTHOR]

Here is a proposal of lossless dual-channel audio encryption scheme based on one-time keys, the novelty is to apply chaotic system with changeable multi-scroll to generate key stream to confuse and diffuse audio data, and the one-time keys, such as initial values of state variables, scroll number and initial iteration times of the chaotic system, are dependent on both external keys and hash value of the plain audio file, to make the chaotic trajectory more unpredictable. The algorithm owns large key space to make brute-force attack impossible. Statistical analysis demonstrates the effectiveness for fast audio encryption, and the scheme can also be applied in encrypting audio with more channels. [ABSTRACT FROM AUTHOR]

Predicate encryption is a public-key encryption that supports attribute-hiding as well as payload-hiding and achieves high flexibility in terms of access control. Since Katz, Sahai, and Waters first proposed the predicate encryption scheme in 2008, several predicate encryption schemes have been published. Unfortunately these are impractical as they require O(n) pairing computations for decryption with considerably large sized public parameters, secret key, and ciphertext, where n is the dimension of the attribute/predicate vectors. In this paper, we propose a very efficient predicate encryption scheme that requires only n exponentiation plus three pairing computations for decryption with shorter sized public parameters, secret key, and ciphertext. The proposed scheme is proven selective attribute-secure against chosen-plaintext attacks in the standard model under the Asymmetric Decisional Bilinear Diffie-Hellman assumptions. [ABSTRACT FROM AUTHOR]

The growing demand on the performance of transparent computing systems requires good cache schemes in order to overcome the prolonged network latency. However, evaluating cache schemes, especially measuring the performance of a transparent computing system with particular cache scheme remains challenging. This is because neither method is available to evaluate the effectiveness and efficiency of the cache schemes in transparent computing, nor the simulator has been developed to measure the system performance under particular cache schemes. In this paper, we propose TranSim, a full-featured, high-performance simulation framework for transparent computing. For the first time, TranSim introduces a methodology to evaluate the performance of multi-level cache hierarchies in transparent computing under different cache configurations and cache replacement policies. TranSim can also demonstrate the behavior and performance of the entire transparent computing system rather than only the cache miss/hit rate. Using TranSim, the system designer can quickly evaluate the effectiveness of cache schemes along with the system performance. We construct several experiments to evaluate the effectiveness and efficiency of TranSim. Results show that TranSim can accurately output the performance of both the cache hierarchy and the entire transparent computing system. [ABSTRACT FROM AUTHOR]

Continuous scaling of process technology increases variations in transistors. The process variations cause large fluctuations in the access times of static random-access memory (SRAM) cells. Caches made of those SRAM cells cannot be accessed within the target clock cycle time, which reduces the yield of processors. Many schemes have been proposed to combat these access time failures in caches. However, these schemes are limited in their coverage and do not scale well at high failure rates. We propose a new level one (L1) cache architecture employing multi-cycle cell access (MCCA) and subarray-level parallel access (SLPA). MCCA eliminates all access-time failures in L1 caches. SLPA minimizes the performance impact of cache bandwidth loss due to MCCA. For further performance improvement, architectural techniques are proposed. Our experimental results show that our proposed L1 cache architecture incurs a performance hit of less than 1.2 percent compared to the conventional cache architecture with no access time failure. Our proposed architecture is not sensitive to access time failure rates and has a low overhead compared with previously proposed competitive schemes. [ABSTRACT FROM AUTHOR]

Nodes in a wireless sensor network (WSN) are generally deployed in unattended environments making them susceptible to attacks. Therefore, the need of defending such attacks is of utmost importance. The challenge in providing security in this network is that the securing mechanism must be lightweight to make it implementable for such resource-constrained nodes. A robust security solution for such networks must facilitate authentication of sensor nodes. So far, only data authentication has drawn much attention from the research community. In this paper, a digital watermark based low-overhead solution (LoWaNA) is proposed for node authentication. The proposed watermarking technique consists of three modules viz. watermark generation, embedding and detection. The robustness of the algorithm is measured in terms of cracking probability and cracking time. This robustness analysis helps us to set the design guideline regarding size of watermark. Performance of the scheme is analyzed in terms of storage, computation and communication overhead. The analytical results are compared with two of the existing schemes and that show significant reduction of all such overheads. Thus it proves the suitability of the proposed scheme for resource-constrained networks like WSN. Finally the entire scheme is simulated in Cooja, the Contiki network simulator to make it readily implementable in real life mote e.g. MICAz. [ABSTRACT FROM AUTHOR]

Provisioning buffer management mechanism is especially crucial in resource-constrained delay tolerant networks (DTNs) as maximum data delivery ratio with minimum overhead is expected in highly congested environments. However, most DTN protocols do not consider resource limitations (e.g., buffer, bandwidth) and hence, results in performance degradation. To strangle and mitigate the impact of frequent buffer overflows, this paper presents an adaptive and efficient buffer management scheme called size-aware drop (SAD) that strives to improve buffer utilization and avoid unnecessary message drops. To improve data delivery ratio, SAD exactly determines the requirement based on differential of newly arrived message(s) and available space. To vacate inevitable space from a congested buffer, SAD strives to avoid redundant message drops and deliberate to pick and discard most appropriate message(s) to minimize overhead. The performance of SAD is validated through extensive simulations in realistic environments (i.e., resource-constrained and congested) with different mobility models (i.e., Random Waypoint and disaster). Simulation results demonstrate the performance supremacy of SAD in terms of delivery probability and overhead ratio besides other metrics when compared to contemporary schemes based on Epidemic (DOA and DLA) and PRoPHET (SHLI and MOFO). [ABSTRACT FROM AUTHOR]

As new network applications have arisen rapidly in recent years, it is becoming more difficult to predict the exact traffic pattern of a network. In consequence, a routing scheme based on a single traffic demand matrix often leads to a poor performance. Oblivious routing (Racke in Proceedings of the 43rd annual IEEE symposium on foundations of computer science 43-52, 2002) is a technique for tackling the traffic demand uncertainty problem. A routing scheme derived from this principle intends to achieve a predicable performance for a set of traffic matrixes. Oblivious routing can certainly be an effective tool to handle traffic demand uncertainty in a wireless mesh network (WMN). However, a WMN has an additional tool that a wireline network does not have: dynamic bandwidth allocation. A router in a WMN can dynamically assign bandwidth to its attached links. This capability has never been exploited previously in works on oblivious routing for a spatial time division multiple access (STDMA) based WMN. Another useful insight is that although it is impossible to know the exact traffic matrix, it is relatively easy to estimate the amount of the traffic routed through a link when the routing scheme is given. Based on these two insights, we propose a new oblivious routing framework for STDMA WMNs. Both analytical models and simulation results are presented in this paper to prove that the performance-in terms of throughput, queue lengths, and fairness-of the proposed scheme can achieve significant gains over conventional oblivious routing schemes for STDMA based WMNs. [ABSTRACT FROM AUTHOR]

Mobile ad hoc networks (MANETs) rely on the benevolence of nodes within the network to forward packets from a source node to a destination node. This network construction allows for the forwarding nodes, whether they are selfish or malicious, to drop packets hindering end-to-end communication. In this paper, a new scheme is proposed against collusion black hole and slander attacks in MANETs, named E2EACK. A novel method is used to detect collusion attacks due to collusive malicious nodes which cooperate in the route discovery, but refuse to forward data packets and do not disclose the misbehavior of each other. Contrary to existing methods that detect only collusion black hole attacks, the E2EACK also detects slander attacks and framing attacks. Moreover, the E2EACK uses ACKnowledgment packet to detect malicious nodes on the path and Message Authentication Code (MAC) to authenticate the sender of each data packet. Analytical and simulation results show that the proposed scheme considerably decreases the routing overhead and increases the packet delivery ratio compared to the existing methods. [ABSTRACT FROM AUTHOR]

In mobile social networks, forwarding is a challenging problem since there may be no end-to-end paths. Existing schemes using overlays are not applicable to pure mobile social networks since they use environments different from the mobile social networks. To resolve this problem, we propose a novel forwarding scheme that considers the common neighbor similarity and contact probability. In the proposed scheme, the more nodes have in common, the more likely they are to be friends, and higher contact probabilities between nodes increase the chances they will arrive at the destination. The proposed scheme constructs an overlay using two layers with the common neighbor similarity and the contact probability and forwards messages to the destinations through the overlay. Experimental results show that the proposed scheme outperforms most known forwarding schemes in terms of balancing the network traffic and transmission delay. [ABSTRACT FROM AUTHOR]

Conventional feedback control systems cannot perform well under strong disturbances. Cascade control is an alternative approach to the classical single-input single output-control systems to improve the performance of the control system, especially in the case of disturbances. The general approach to identify the tuning parameters of the controllers used in the inner and the outer loop of the cascade controller structure is to tune the inner and the outer loop in a strict sequence. Here, simultaneous tuning of the inner and outer loop controllers is given. Tuning parameters of the inner and outer loop controllers are determined using a genetic algorithm. Simulation results for stable, unstable and integrating processes in the cascade control scheme are provided to illustrate the performance of the proposed controller design method. [ABSTRACT FROM AUTHOR]

This paper investigates the operation of a smart distribution system comprised of multiple microgrids during emergency conditions. It proposes a two-stage hierarchical scheme for outage management in such a system to enhance the security of supply during contingencies. This goal is achieved through sharing the available generation and storage capacities among different microgrids. In doing so, a well-organized framework is devised in order to introduce the roles and tasks of each player in operation stage of a multi-microgrids system. Based on this framework, the general optimization model that needs to be evaluated at each stage of the proposed outage management scheme is formulated. In this regard, a model predictive control (MPC)-based approach is proposed to determine the optimal scheduling policy of microgrids in the first stage. In the second stage, distribution system operator (DSO) as an independent entity coordinates the operation of different microgrids and schedules their unused generation/storage capacities for minimizing load curtailments in the whole system. This method captures the inherent uncertainties of outage duration and significantly increases the resilience of resulting schedule against prediction errors of load and renewable resources. Various features of this scheme are studied through implementation on a test system. The results verify the effectiveness of the proposed scheme in enhancing the reliability of distribution systems and demonstrate the benefits it will bring to both customers and DSOs. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

3D holoscopic image, also known as integral imaging, light field imaging and plenoptic imaging, can provide a natural and fatigue-free 3D visualization. However, a large amount of data is required to represent the 3D holoscopic content. Therefore, efficient coding schemes for such particular type of image are needed. In this paper, we propose a Gaussian process regression based prediction scheme to compress the 3D holoscopic image. In the proposed scheme, the coding block and its prediction supports are modeled as a Gaussian process (GP) and Gaussian process regression (GPR) is used to obtain a better prediction of the coding block. Limited searching windows in horizontal and vertical directions are used to obtain the prediction supports, and a filtration method is designed to judge the reliability of the obtained prediction supports. Moreover, in order to alleviate the high complexity caused by GPR, a sparsification method is also put forward. Experimental results demonstrate the advantage of the proposed scheme for 3D holoscopic image coding in terms of different quality metrics as well as the visual quality of the views rendered from decompressed 3D holoscopic content, compared to the HEVC intra-prediction method and several other prediction methods in this field. [ABSTRACT FROM AUTHOR]

Recent advancements in high resolution scalable video coding have significantly increased the computational complexities of watermarking solutions for real-time video encoding systems. This paper proposes a human visual system based watermarking algorithm for spatial scalable coding based on the H.264/SVC standard. The proposed algorithm extracts textural feature from a set of 7 high energy quantized coefficients in 4×4 luma INTRA-predicted blocks of all slices and embeds watermark into the highly textured block which has at least one non-zero coefficient in 6 selected locations. The same embedding process is performed for all layers of the video to improve robustness against common video processing attacks. Experiments were conducted by embedding up to 8192 watermark bits into a four-layer spatial scalable coded video. Results suggest that the proposed scheme produces watermarked video with an average visual quality degradation of ∼0.36 dB at the expense of 2.18% bitrate overhead. In addition, the proposed watermarking scheme achieves an average detection rate of 0.98, 0.97 and 0.71 against re-encoding, recompression and Gaussian filtering attacks, respectively, using the base layer, and above 0.97, 0.94 and 0.66, respectively when using any of the enhancement layer. [ABSTRACT FROM AUTHOR]

Dynamic Adaptive Streaming over HTTP (DASH) is the state-of-the-art technology for video streaming and has been widely deployed in both wired and wireless environments. However, mobile DASH users often suffer from video quality oscillation and even video freeze in wireless environments, which results in poor user experience. This is mainly because most quality adaptation algorithms in DASH rely highly on bandwidth estimation to adjust the video quality while wireless network bandwidth is unstable in nature and changes frequently according to wireless channel contention and condition. To provide stable performance, even during severe bandwidth fluctuation, this paper proposes the Wireless Quality Adaptation (WQUAD) algorithm, which eliminates bandwidth estimation from quality adaptation. Thanks to the Scalable Video Codec (SVC), the proposed scheme always prioritizes to lower layers over higher ones as long as the play-out buffer is not completely filled by the lower layers. As a result, the client always fills the buffer with the base layers first and then the upper enhancement layers sequentially. This horizontal adaptation is straightforward and does not require any bandwidth estimation. Through NS-2 simulations, we show that WQUAD achieves (i) stable performance, keeping the video quality level with respect to the long-term network bandwidth, (ii) effective video freeze prevention, and (iii) high video quality on average. [ABSTRACT FROM AUTHOR]

This paper presents an extension of the central scheme of Kurganov and Tadmor (2000) to work with solvers based on conservative face fluxes, which are usual in the solution of incompressible flows by the Finite Volume Method. The proposed scheme retains the desirable properties of simplicity, low numerical viscosity and multidimensionality, and it works on general non-staggered polyhedral meshes. It is applied within a mixture multiphase solver to discretize the mass conservation equation of one of the phases. A series of cases are solved which show that the proposed extension is significantly more robust and monotonicity-preserving than the straightforward application of the Kurganov–Tadmor scheme. [ABSTRACT FROM AUTHOR]

In this paper, we present a novel fault detection and identification (FDI) scheme for a class of nonlinear systems with model uncertainty. At the heart of this approach is an on-line approximator, referred to as fault tracking approximator (FTA). Differently from the other approximators, the FTA uses iterative algorithms to detect and identify nonlinear system faults, even in the presence of model uncertainty, which is motivated by predictive control theory and iterative learning control theory. The FTA can simultaneously detect and identify the shape and magnitude of the faults. The rigorous stability analysis and fault tracking properties of the FTA are also proved. Finally, two examples are given to illustrate the feasibility and effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This article investigates the operation of a microgrid system through a novel control scheme. The proposed microgrid system employs various autonomous generation systems, including photovoltaic, wind, a diesel engine, a fuel cell, an aqua electrolyzer, and a battery. A simulation model for this microgrid system was developed using MATLAB/SIMULINK (The MathWorks, Natick, Massachusetts, USA). A proportion-integral-derivative control scheme is employed, and the parameters of proportion-integral-derivative controllers for various controllable sources are tuned with a firefly algorithm. This is done using a new proposed weighted goal attainment method for achieving improved and fault-tolerant operation. The proposed control scheme shows better performance over the classical proportion-integral-derivative and bacterial foraging–proportion-integral-derivative controller in both transient and steady-state conditions. The firefly algorithm–proportion-integral-derivative controller also shows stronger robustness properties against system perturbations, disturbances, and faults than that with other controller structures. The robustness is a highly desirable property in such a scenario since many components of the microgrid may be switched on/off or may run at lower/higher power output at different time instants. [ABSTRACT FROM AUTHOR]

The Variable-Sized Bin Packing Problem (abbreviated as VSBPP or VBP) is a well-known generalization of the NP-hard Bin Packing Problem (BP) where the items can be packed in bins of M given sizes. The objective is to minimize the total capacity of the bins used. We present an asymptotic approximation scheme (AFPTAS) for VBP and BP with performance guarantee $A_{\varepsilon }(I) \leq (1+ \varepsilon )OPT(I) + \mathcal {O}\left ({\log ^{2}\left (\frac {1}{\varepsilon }\right )}\right )$ for any problem instance I and any ε>0. The additive term is much smaller than the additive term of already known AFPTAS. The running time of the algorithm is $\mathcal {O}\left ({ \frac {1}{\varepsilon ^{6}} \log \left ({\frac {1}{\varepsilon }}\right ) + \log \left ({\frac {1}{\varepsilon }}\right ) n}\right )$ for BP and $\mathcal {O}\left ({ \frac {1}{{\varepsilon }^{6}} \log ^{2}\left ({\frac {1}{\varepsilon }}\right ) + M + \log \left ({\frac {1}{\varepsilon }}\right )n}\right )$ for VBP, which is an improvement to previously known algorithms. Many approximation algorithms have to solve subproblems, for example instances of the Knapsack Problem (KP) or one of its variants. These subproblems - like KP - are in many cases NP-hard. Our AFPTAS for VBP must in fact solve a generalization of KP, the Knapsack Problem with Inversely Proportional Profits (KPIP). In this problem, one of several knapsack sizes has to be chosen. At the same time, the item profits are inversely proportional to the chosen knapsack size so that the largest knapsack in general does not yield the largest profit. We introduce KPIP in this paper and develop an approximation scheme for KPIP by extending Lawler's algorithm for KP. Thus, we are able to improve the running time of our AFPTAS for VBP. [ABSTRACT FROM AUTHOR]

This paper presents a novel space vector modulation (SVM) method combined with a modified four-step commutation to achieve a perfect zero common-mode voltage (CMV) for matrix converters (MCs). The new SVM method was developed by using only rotating input voltage vectors, which results in the CMV for MCs being zero. However, it causes some noise in practical applications that drive MCs with traditional four-step commutation. In order to solve this noise problem, a modified four-step commutation is also proposed to perfectly eliminate the CMV for MCs without any noise. In the modified four-step commutation, a delay time is designed to deal with misjudgment of input voltages. The proposed SVM method and four-step commutation are easily implemented via software and achieve good performance in input/output current waveforms. Prototype experiments were carried out to evaluate the performance of the proposed method. [ABSTRACT FROM AUTHOR]

The shortest path is a basic routing model which is still used in many systems. However, due to the low exploitation of the delivery capacity of peripheral nodes, the performance achieved by this policy is very limited. Starting from the fact that changing all network routers by others more robust is not practical, we propose the improvement of the capacity of a scale-free network under the shortest path strategy by the implantation of global dynamic routers. We have studied two targeting approaches to designate specific nodes to route the packets following the global dynamic protocol; one is based on node degree and the other on its betweenness. We show that we already exceed twice the capacity under the shortest path protocol with only 4 % of global dynamic routers when we target nodes with high betweenness and 10 % when we target nodes with high degrees. Moreover, the average travelling time remains low while the network capacity increases. [ABSTRACT FROM AUTHOR]

Time-division multiplexing (TDM) is a mature scheme for the readout of arrays of transition-edge sensors (TESs). TDM is based on superconducting-quantum-interference-device (SQUID) current amplifiers. Multiple spectrometers based on gamma-ray and X-ray microcalorimeters have been operated with TDM readout, each at the scale of 200 sensors per spectrometer, as have several astronomical cameras with thousands of sub-mm or microwave bolometers. Here we present the details of two different versions of our TDM system designed to read out X-ray TESs. The first has been field-deployed in two 160-sensor (8 columns $$\times $$ 20 rows) spectrometers and four 240-sensor (8 columns $$\times $$ 30 rows) spectrometers. It has a three-SQUID-stage architecture, switches rows every 320 ns, and has total readout noise of 0.41 $$\mu \Phi _{\mathrm {0}} / \surd $$ Hz. The second, which is presently under development, has a two-SQUID-stage architecture, switches rows every 160 ns, and has total readout noise of 0.19 $$\mu \Phi _{\mathrm {0}} / \surd $$ Hz. Both quoted noise values are non-multiplexed and referred to the first-stage SQUID. In a demonstration of this new architecture, a multiplexed 1-column $$\times $$ 32-row array of NIST TESs achieved average energy resolution of $$2.55\pm 0.01$$ eV at 6 keV. [ABSTRACT FROM AUTHOR]

In high frequency induction heating systems, the effective load parameters change during the different operating conditions. It is necessary to maintain constant input voltage to the induction heating load to improve the quality of the heating. The resonant based high frequency converter is generally used for these applications for the reduction of switching losses. The resonant condition is also affected during the variation in load parameters. The controller should provide a good voltage regulation with less response time and less overshoot during the loading conditions. In this paper, a load adaptive fuzzy logic control scheme is proposed to perform the voltage control of the high frequency inverter under variable load conditions. A frequency tracking control system is also employed for the inverter system using the phase lock loop. The phase lock loop ensures the resonant frequency operation of the inverter during the change in load parameters. The state space model of the system is discussed to study the inverter during different operating conditions. The fuzzy logic controller based closed loop control scheme is developed using the MATLAB simulation tool. The responses of the conventional and fuzzy logic controllers are studied for load voltage regulation and the effectiveness of the control schemes is verified. The dynamic behavior of the system is studied under no load and loaded conditions with the two controllers. The fuzzy based closed loop control scheme improves the dynamic response of the system compared to the conventional controller. The response of the induction heating system is validated with a hardware prototype. The results are presented in order to confirm the proposed control strategy. [ABSTRACT FROM AUTHOR]

A peak-to-average power ratio (PAPR) reduction method for an orthogonal frequency division multiplexing (OFDM) system based on a combination of a partial transmit sequence (PTS) scheme with the backtracking search optimization algorithm (BSA) is proposed. The PTS scheme shows good PAPR reduction performance; however, it requires a complex computation to search the set of optimum phase factors, especially for high-speed data transmissions. To minimize the complexity of the search for optimum phase factors, the PTS scheme is combined with the BSA. The BSA is a new and efficient population-based evolutionary search algorithm for real-valued optimization problems. A set of simulations is conducted for the PAPR reduction performance and computational complexity comparisons of the BSA-PTS scheme with different PTS schemes. Simulation results indicate that the BSA-PTS scheme yields an effective PAPR reduction performance with low computational complexity. [ABSTRACT FROM AUTHOR]

The problem of finding similar strings is very important in most real life applications including spell-checking, data cleaning, next generation sequencing, and alignment. In order to query and manage string data online, scalable algorithms and frameworks are essential. Scalable frameworks and algorithms have been introduced in the past few years. However, these frameworks mainly deal with caching and querying structured data. They do not deal with fuzzy queries, where we need to search for an approximate string. In this paper, we propose an edit distance aware filtering algorithm for all kinds of approximate string search problems. We also propose a novel name spell-check engine mainly for social networks. Our experiments show that our edit distance aware filtering mechanism alone improves the query processing time and throughput by almost 30%. Additionally, our name spell-check engine improved the name spell-check response time and throughput almost 10 times by using our filtering scheme and some domain specific observations. [ABSTRACT FROM AUTHOR]

Disease severity prediction is essential in clinical diagnosis nowadays, as correct understandings of the onset and progression of disease are priceless in treatment planning. In this study, dementia disease, one of the most severe non-communicable diseases worldwide, is focused. A novel dementia disease severity prediction scheme is proposed using new big ranking and learning techniques. To be specific, arterial spin labeling, an emerging functional-magnetic resonance imaging technique, is adopted to provide image-based clinical data. There are two steps composed of the whole scheme. First, a single-pixel based method is presented to correct the partial volume effect in arterial spin labeling images. The advantage of this method is that, problems of blurring and brain detail loss can be well tackled. Second, novel big pair-wise ranking and learning techniques is proposed to realize the dementia disease severity prediction task using arterial spin labeling images after partial volume effects correction. Extensive experiments using a big database composed of images acquired from 350 real demented patients are carried out with several conventional methods being compared. Comprehensive statistical analysis is performed and it suggests that the new scheme is promising in dementia disease severity prediction. [ABSTRACT FROM AUTHOR]

Extended Producer Responsibility (EPR) schemes are adopted not only to promote collection and recycling of waste products but also to close material loops and incentivise ecodesign. These outcomes are also part of creating a more circular economy. Evaluations of best practices can inform how to further optimise systems towards more ambitious collection, recycling and recovery of both hazardous and critical materials. Gas discharge lamps in particular are a key product category in this regard, considering both the presence of mercury and of rare earth materials in this waste stream. Nordic countries in particular are known for advanced collection and recycling systems and this article compares the EPR systems for gas discharge lamps. The EPR systems for lamps are evaluated using theory-based evaluation approaches to analyse both the performance of lamp EPR systems and challenges perceived by key stakeholders. The cases were constructed based on primary and secondary literature, statistical data, and interviews with stakeholders. The findings indicate that the collection and recycling performance is generally still high for gas discharge lamps in the Nordic countries, despite some differences in approach and structure of the EPR systems, but there remain opportunities for further improvement. In terms of EPR goals, there is evidence of improved waste management of these products as a result of the systems; however, there also remain significant challenges, particularly in terms of ecodesign incentives. The key factors for best practice are discussed, including aspects of the rule base, infrastructure, and operations. The particular characteristics of this waste category, including the rapidly changing technology, also pose challenges for EPR systems in the future. [ABSTRACT FROM AUTHOR]

Autonomous cluster operation such as cluster reconfiguration is one of the enabling technologies for fractionated spacecraft. By virtue of the multi-agent system theory, this paper presents an organizational architecture for fractionated spacecraft, which not only enables autonomous cluster operations but also facilitates its non-traditional attributes. Within this organizational architecture, a decentralized framework is proposed to solve cluster reconfiguration problems based on primal and dual decomposition, where subgradient methods are adopted to include reconfiguration cases with non-differentiable objectives. Two typical constraints are considered: final configuration constraints representing coupling variables and collision avoidance constraints representing coupling constraints, both of which are non-convex. General schemes are proposed to convexify those constraints via the linearization and convex restriction technology. Then final configuration constraints are tackled by primal decomposition, while collision avoidance constraints by dual decomposition. To the end, multi-level primal and dual decompositions are employed to solve reconfiguration problems with both coupling variables and coupling constraints. For illustration an example of in-plane cluster reconfiguration is solved and compared with the centralized approach the solution is optimal. [ABSTRACT FROM AUTHOR]

We compared the precision of simple random sampling (SimRS) and seven types of stratified random sampling (StrRS) schemes in estimating regional mean of water-limited yields for two crops (winter wheat and silage maize) that were simulated by fourteen crop models. We found that the precision gains of StrRS varied considerably across stratification methods and crop models. Precision gains for compact geographical stratification were positive, stable and consistent across crop models. Stratification with soil water holding capacity had very high precision gains for twelve models, but resulted in negative gains for two models. Increasing the sample size monotonously decreased the sampling errors for all the sampling schemes. We conclude that compact geographical stratification can modestly but consistently improve the precision in estimating regional mean yields. Using the most influential environmental variable for stratification can notably improve the sampling precision, especially when the sensitivity behavior of a crop model is known. [ABSTRACT FROM AUTHOR]

With the increasing availability of medical IoT devices, it becomes feasible to collect health contexts from personal IoT devices and perform analytics to assess the health conditions and identify potential diseases. However, there exist technical challenges in developing such personal healthcare applications; transforming disease diagnosis methods of physicians in machine-readable forms and software implementation of the medical analytic schemes. In this paper, we present a methodology foundation for analyzing medical contexts. That is, we formalize five representative medical diagnosis schemes for personal healthcare application. [ABSTRACT FROM AUTHOR]

In order to improve the stator winding single-phase grounding faults protective scheme for Powerformers, a protective scheme based on Mahal distance discriminant theory is proposed in this paper. By the proposed scheme, the different kinds of fault signals can be integrated. Also, a discriminant analysis model for stator winding single-phase grounding faults is established. In the proposed discriminant analysis model, four parameters including the magnitude of leakage current, the direction of leakage current, the magnitude of zero-sequence current in Powerformer terminal, and the direction of zero-sequence current in Powerformer terminal are selected as the discrimination factor. The method of back substitution estimation is introduced to verify the stability of the distance discriminant analysis model. Twenty-five groups of detected samples were analyzed based on the proposed model. The results are consistent with the measured data and show that the distance discriminant analysis model is with higher accuracy and lower mistake-discrimination ratio. [ABSTRACT FROM AUTHOR]

Importance of protection IEDs in IEC 61850-based substations has increased by enhancing performance of IEDs but local backup scheme in the substation is not considered important. In the existing local backup method, two protection IEDs are installed for one protection target. This method is useful for local backup of the IEDs. However, local backup at simultaneous fault of the protection IEDs is not performed in conventional substation because it has limitations on operational environment. However, IEC 61850-based substation improves operational environment with high speed communication network and high performance IEDs; and the simultaneous fault problem can be resolved by developing new devices and schemes. Therefore, this paper proposes a new local backup scheme for simultaneous faults of protection IEDs in an IEC 61850-based substation. The proposed backup scheme is configured as self-supervision-based monitoring, new improved local backup IED, and local backup scheme; and the proposed scheme is implemented and tested using IEC 61850 SISCO library on a laboratory test bed. [ABSTRACT FROM AUTHOR]

This paper presents a new differential relaying scheme for a mutually coupled, double circuit transmission line in presence of Unified Power Flow Controller (UPFC) in the line. The process starts at retrieving the three phase current signals at both ends of the transmission line synchronously and processing it though the time–frequency transform such as Fast Discrete S-Transform to derive the spectral energy content of the current signals. The differential spectral energy of current signals (difference between the spectral energy of the current signal at the sending and receiving ends, respectively) of the respective phases of transmission line is used to register the fault pattern. The proposed approach includes fault detection and classification along with identification of the fault section with respect to UPFC location in one of the double-circuit transmission line. The extensive test results indicate that the proposed differential relaying scheme is highly reliable in registering fault patterns in UPFC based transmission line including wide variations in operating parameters of the power network. [ABSTRACT FROM AUTHOR]

The domain of Grid Connected Inverter (GCI) and reduced switch topology in multi-level inverter (MLI) are gaining its attention in terms of reducing cost and optimization. For such a motivation, many researchers are addressing their efforts in proposing new MLI topologies or in modifying the existing ones, aiming at improving the quality of the energy available at the inverter terminals. The proposed split capacitor based topology uses only a single dc supply to generate any required output levels. The split capacitors are considered to obtain stepped output by adopting a Time Frame based Switching Scheme (TFSS). The numbers of semiconductor switches are reduced with an improvement in the harmonic factor. The power output is then filtered using passive inductor component and then synchronized to feed the grid power system. The result of the proposed topology is verified by Matlab/Simulink simulation and hardware implementation using a dsPIC30F4011 controller. The simulation and experimental results are compared to previous studies. The proposed scheme offers an excellent performance with significant result in lowest THD obtained and also enables the inverter to operate under unhinged PV conditions comprehensively. [ABSTRACT FROM AUTHOR]

Buildings account for nearly 40 percent of the total energy consumption in the United States. As a critical step toward smart cities, it is essential to intelligently manage and coordinate the building operations to improve the efficiency and reliability of overall energy system. With the advent of smart meters and two-way communication systems, various energy consumptions from smart buildings can now be coordinated across the smart grid together with other energy loads and power plants. In this paper, we propose a comprehensive framework to integrate the operations of smart buildings into the energy scheduling of bulk power system through proactive building demand participation. This new scheme enables buildings to proactively express and communicate their energy consumption preferences to smart grid operators rather than passively receive and react to market signals and instructions such as time varying electricity prices. The proposed scheme is implemented in a simulation environment. The experiment results show that the proactive demand response scheme can achieve up to 10 percent system generation cost reduction and 20 percent building operation cost reduction compared with passive demand response scheme. The results also demonstrate that the system cost savings increase significantly with more flexible load installed and higher percentage of proactive customers participation level in the power network. [ABSTRACT FROM AUTHOR]

Audio represents one of the most appealing yet least exploited modalities in wireless sensor networks, due to the potentially extremely large data volumes and limited wireless capacity. Therefore, how to effectively collect audio sensing information remains a challenging problem. In this paper, we propose a new paradigm of audio information collection based on the concept of audio-on-demand. We consider a sink-free environment targeting for disaster management, where audio chunks are stored inside the network for retrieval. The difficulty is to guarantee a high search success rate without infrastructure support. To solve the problem, we design a novel replication algorithm that deploys an optimal number of O(\sqrtn) replicas across the sensor network. We prove the optimality of the energy consumption of the algorithm. We implement a sink-free audio-on-demand (SAoD) WSN system, and conduct extensive simulations to evaluate the performance and efficiency of our design. The experimental results show that our design can provide satisfactory quality of audio-on-demand service with short startup latency and slight playback jitter. Extensive simulation results show that this design achieves a search success rate of 98 percent while reducing the search energy consumption by an order of magnitude compared with existing schemes. [ABSTRACT FROM AUTHOR]