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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]

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]

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]

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]

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]

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]

Cost-sensitive learning which deals with classification problems that have non-uniform costs has attracted great attention from the machine learning and data mining communities in recent years. In this study, a rescaling based meta-learning scheme is applied to cost-insensitive MEPAR-miner and DIFACONN-miner algorithms which were previously developed by the authors in order to make the algorithms cost-sensitive. Rescaling is realized in two ways by means of oversampling and undersampling by resampling the training instances in proportion to their costs. The proposed algorithms can extract rules for both binary and n-ary classification problems and also handle data sets that have missing values. An extensive computational study is performed on different types of classification benchmark problems with the aim of testing the performances of the algorithms. Comparisons with traditional cost-sensitive meta-learning algorithms and cost-insensitive MEPAR-miner and DIFACONN-miner algorithms show that the proposed cost-sensitive algorithms are competitive meta-learning algorithms and able to produce accurate and effective classification rules with low misclassification costs. [ABSTRACT FROM AUTHOR]

This paper addresses a new model-based fault detection, estimation, and prediction scheme for linear distributed parameter systems (DPSs) described by a class of partial differential equations (PDEs). An observer is proposed by using the PDE representation and the detection residual is generated by taking the difference between the observer and the physical system outputs. A fault is detected by comparing the residual to a predefined threshold. Subsequently, the fault function is estimated, and its parameters are tuned via a novel update law. Though state measurements are utilized initially in the parameter update law for the fault function estimation, the output and input filters in the modified observer subsequently relax this requirement. The actuator and sensor fault functions are estimated and the time to failure (TTF) is calculated with output measurements alone. Finally, the performance of detection, estimation and a prediction scheme is evaluated on a heat transfer reactor with sensor and actuator faults. [ABSTRACT FROM AUTHOR]

This paper studies a numerical optimization-based extremum seeking scheme for systems with unmodeled dynamics and unknown disturbances without using dither signals. The robust extremum seeking scheme is composed of a numerical gradient estimator, a numerical optimizer and an extended-state observer based state regulator. A conjugate gradient method is adopted to achieve extremum seeking. A nonlinear extended-state observer based state regulator is proposed to regulate the states. The robust extremum seeker is based on the numerical optimization based extremum seeking framework. Sufficient conditions are derived to ensure the convergence of the overall extremum seeking scheme. The ultimate convergence bound is quantified for a class of strongly convex functions. A numerical example is presented to verify the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, we propose to implement the heralded pair-coherent source into the measurement-device-independent quantum key distribution. By comparing its performance with other existing schemes, we demonstrate that our new scheme can overcome many shortcomings existing in current schemes, and show excellent behavior in the quantum key distribution. Moreover, even when taking the statistical fluctuation into account, we can still obtain quite high key generation rate at very long transmission distance by using our new scheme. [ABSTRACT FROM AUTHOR]

Optimization algorithms are proposed to tackle different complex problems in different areas. In this paper, we firstly put forward a new memetic evolutionary algorithm, named Monkey King Evolutionary (MKE) Algorithm, for global optimization. Then we make a deep analysis of three update schemes for the proposed algorithm. Finally we give an application of this algorithm to solve least gasoline consumption optimization (find the least gasoline consumption path) for vehicle navigation. Although there are many simple and applicable optimization algorithms, such as particle swarm optimization variants (including the canonical PSO, Inertia Weighted PSO, Constriction Coefficients PSO, Fully Informed Particle Swarm, Comprehensive Learning Particle Swarm Optimization, Dynamic Neighborhood Learning Particle Swarm). These algorithms are less powerful than the proposed algorithm in this paper. 28 benchmark functions from BBOB2009 and CEC2013 are used for the validation of robustness and accuracy. Comparison results show that our algorithm outperforms particle swarm optimizer variants not only on robustness and optimization accuracy, but also on convergence speed. Benchmark functions of CEC2008 for large scale optimization are also used to test the large scale optimization characteristic of the proposed algorithm, and it also outperforms others. Finally, we use this algorithm to find the least gasoline consumption path in vehicle navigation, and conducted experiments show that the proposed algorithm outperforms A* algorithm and Dijkstra algorithm as well. [ABSTRACT FROM AUTHOR]

A comparative study of femtosecond pulse dynamics in a photonic crystal fiber amplifier with backward and forward pump schemes is demonstrated experimentally and numerically. The output power, pulse duration and spectrum width of the amplified soliton pulse at different pump powers under the two pump schemes are discussed. The results show that the evolution of the soliton pulse shape in the temporal and spectral domains is also dependent on the direction of pump besides the output power. A narrower pulse duration and spectral width (i.e. smaller time-bandwidth-product), the much less nonlinearity accumulation (i.e. smaller B-Integral value) and a higher output power can be obtained in the backward pump scheme compared to that in the forward pump scheme. The physical origin can be explained by the interaction among group-velocity dispersion, self-phase modulation and nonuniform gain distribution along the fiber due to different end-pump directions. The results provide convincing support to choose the backward pump scheme rather than the forward pump scheme in soliton amplification region in a femtosecond fiber amplifier. [ABSTRACT FROM AUTHOR]

In this paper, we proposes high payload reversible data hiding scheme using weighted matrix. Generate cover image by enlarge the size of original image using interpolation. Partition the original image into (3 × 3) pixel blocks and cover image into (5 × 5) blocks. Perform modular sum of entry-wise multiplication of an (3 × 3) original pixel block with same size shared predefined weighted matrix W . At most twelve multiplication operations are performed to embed 48 bits secret data within an (5 × 5) overlapped pixel block. In each operation, the data embedding position are identified and stored the positional value by modifying three least significant bits of the interleaved pixel of cover image to hide large amount of secret data. For i -th block i = 1, 2, …, we update the weighted matrix W i +1 as W i +1 = ( W i × κ − 1) mod 9, where gcd ( κ , 9) = 1. The original pixels are not effected during data embedding in our scheme which assure reversibility. The proposed scheme provides average embedding payload 2.97 bits per pixel (bpp) with good visual quality measured by peak signal to noise ratio (PSNR) guaranteed to be higher than 37.97 dB. Finally, we compare our scheme with other state-of-the-art methods and obtain reasonably better performance in terms of data embedding capacity. [ABSTRACT FROM AUTHOR]

Discovering dynamical systems with hidden attractors has become an attractive topic recently. A novel four-dimensional continuous-time autonomous system with a cubic nonlinear term is introduced in this work. It is worth noting that this no-equilibrium system can generate hidden hyperchaotic attractors. The fundamental properties of such systems are investigated by means of equilibrium points, phase portrait, bifurcation diagram and Lyapunov exponents. In addition, an adaptive scheme has been presented to synchronize two such identical hyperchaotic systems. Moreover, an electronic circuit is also designed and implemented to verify the feasibility of the theoretical model. [ABSTRACT FROM AUTHOR]

We present a new strategy for constructing spline spaces over hierarchical T-meshes with quad- and octree subdivision schemes. The proposed technique includes some simple rules for inferring local knot vectors to define C 2 -continuous cubic tensor product spline blending functions. Our conjecture is that these rules allow to obtain, for a given T-mesh, a set of linearly independent spline functions with the property that spaces spanned by nested T-meshes are also nested, and therefore, the functions can reproduce cubic polynomials. In order to span spaces with these properties applying the proposed rules, the T-mesh should fulfill the only requirement of being a 0-balanced mesh. The straightforward implementation of the proposed strategy can make it an attractive tool for its use in geometric design and isogeometric analysis. In this paper we give a detailed description of our technique and illustrate some examples of its application in isogeometric analysis performing adaptive refinement for 2D and 3D problems. [ABSTRACT FROM AUTHOR]

In the context of scientific computing, the mesh is used as a discrete support for the considered numerical methods. As a consequence, the mesh greatly impacts the efficiency, the stability and the accuracy of numerical methods. The goal of anisotropic mesh adaptation is to generate a mesh which fits the application and the numerical scheme in order to achieve the best possible solution. It is thus an active field of research which is progressing continuously. This review article proposes a synthesis of the research activity of the INRIA Gamma3 team in the field of anisotropic mesh adaptation applied to inviscid flows in computational fluid dynamics since 2000. It shows the evolution of the theoretical and numerical results during this period. Finally, challenges for the next decade are discussed. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new adaptive output-feedback tracking control scheme for a class of uncertain nonlinear systems with input quantized by a newly-proposed quantizer. This quantizer is a combination of a logarithmic (or a hysteresis) quantizer and a uniform quantizer, and it has the advantages of both logarithmic and uniform quantizers in ensuring reducible communication expenses and acceptable quantization errors for better system performances. Compared with existing results in adaptive control, the proposed scheme provides a way to relax certain restrictive conditions, in addition to solving the problem of adaptive output-feedback control with input quantization. It is shown that the designed adaptive controller ensures global boundedness of all the signals in the closed-loop system and enables the tracking error to exponentially converge towards a compact set which is adjustable. [ABSTRACT FROM AUTHOR]

This paper focuses on the event-triggered zero-gradient-sum algorithms for a distributed convex optimization problem over directed networks. The communication process is driven by trigger conditions monitored by nodes. The proposed trigger conditions are decentralized and just depend on each node’s own state. In the continuous-time case, we propose an algorithm based on a sample-based monitoring scheme. In the discrete-time case, we propose a new event-triggered zero-gradient-sum algorithm which is suitable for more general network models. It is proved that two proposed event-triggered algorithms are exponentially convergent if the design parameters are chosen properly and the network topology is strongly connected and weight-balanced. Finally, we illustrate the advantages of the proposed algorithms by numerical simulation. [ABSTRACT FROM AUTHOR]

In this paper, an online efficiency enhancement scheme of a cascaded multilevel grid-connected inverter for renewable energy generation systems is researched in detail. Taking the special grid current standard as the limitation condition, an efficiency enhancement scheme with adjusting carrier frequency in real time is proposed. Furthermore, the effect of the harmonics and DC offset of the tied grid on the enhanced phase locked loop (EPLL) is analyzed and a hybrid filter based EPLL is proposed to eliminate the former effect. With the improved EPLL, the amplitude, phase angle and frequency of grid are all estimated correctly and the performance of the efficiency enhancement scheme is maintained even under non-ideal grid conditions. Detailed experimental results validate the accuracy and practicability of the improved EPLL and efficiency enhancement scheme. [ABSTRACT FROM AUTHOR]

In the context of Identity-Based Encryption (IBE), both revocation and delegation of key generation are important functionalities. Although a number of IBE schemes with either efficient revocation or efficient delegation of key generation functionality have been proposed, an important open problem is efficiently delegating both the key generation and revocation functionalities in IBE systems. Seo and Emura (2014) [25] proposed the first realization of Revocable Hierarchical IBE (RHIBE), a sole IBE scheme that achieves both functionalities simultaneously. However, their approach implements history-preserving updates, wherein a low-level user must know the history of key updates performed by ancestors in the current time period, and it renders the scheme very complex. In this paper, we present a new method to construct RHIBE that implements history-free updates. Our history-free approach renders the scheme simple and efficient. As a second contribution, we redefine the security model for RHIBE to ensure security against insiders , where adversaries are allowed to obtain all internal system information, e.g., state information. In addition, we also consider the decryption key exposure attack, which was considered by Seo and Emura (2013) [23] . Further, we propose two RHIBE schemes with shorter secret keys and constant size ciphertexts that implement the aforementioned history-free updates approach and security model. For revocation, our constructions use the Complete Subtree (CS) method and the Subset Difference (SD) method. Both schemes are selectively secure in the standard model under the q -weak Bilinear Diffie–Hellman Inversion assumption. [ABSTRACT FROM AUTHOR]

This paper proposes a three bit-serial and digit-serial semi-systolic GF (2 m ) multipliers using Progressive Product Reduction (PPR) technique. These architectures are obtained by converting the GF (2 m ) multiplication algorithm into an iterative algorithm using systematic techniques for scheduling the computational tasks and mapping them to Processing Elements (PE). Three different semi systolic arrays were obtained. ASIC implementation of the proposed designs and previously published schemes were used to verify the performance of the proposed designs. One proposed design has at least 29% lower area compared to previously published bit/digit serial multipliers. This design has also at least 70% lower power compared to previously published bit/digit serial multipliers. Another proposed design has at least 12% lower power-delay product (PDP) compared to previously published bit/digit serial multipliers. This makes the proposed designs more suited to resource-constrained embedded applications. [ABSTRACT FROM AUTHOR]

In this paper, a novel approach based on minimum enclosing ball support vector machine (BVM) to phishing Website detection is proposed, which aims at achieving high speed and high accuracy for detecting phishing Website. In order to enhance the integrity of the feature vectors, we first perform an analysis of the topology structure of website according to the DOM tree and use the Web crawler to extract 12 topological features of the website. Then, the feature vectors are detected by BVM classifier. Compared with the general SVM, this method has relatively high precision of detecting, and complements the disadvantage of slow speed of convergence on large-scale data. The experimental results show that the proposed method has better performance than SVM, and further validate the validity and correctness of our scheme. [ABSTRACT FROM AUTHOR]

This paper analyzes the security issues of the recently proposed JPEG image encryption scheme. A new image encryption algorithm using modified logistic map is proposed. The chaotic sequences generated using modified logistic map are used for permutation, bit swapping and random diffusion. These processes impose the confusion and diffusion effect on the image and make the scheme secure. The security parameters such as entropy, correlation, NPCR and UACI are tested and the results show the scheme is secure. [ABSTRACT FROM AUTHOR]

The transthoracic echocardiographic (TTE) images used to assess cardiac health are inherent with speckle noise, making it very difficult for accurate abnormality diagnosis. To address this issue, a novel speckle reduction known as extreme total variation bilateral (ETVB) filter is proposed in this paper. The regularizer term of total variation (TV) method is replaced with the bilateral (BL) term in the proposed ETVB filter along with the prior term. The true information is incorporated in the algorithm using Bayesian inference and probability density function. Applications of gradient projection based restoration methods are also analyzed for speckle noise reduction. Denoising characteristics are evaluated in terms of 15 image quality metrics along with visual quality. The performance of proposed ETVB filter is compared with 30 existing despeckling techniques. Exhaustive result analysis reveals that the proposed ETVB filter is superior in terms of edge and texture preservation. The focal points of result analysis are edge, structure and texture preservation along with visual outlook. Edge and structure preservation are measured using beta metric, figure of merit and structure similarity index. The values of β , FoM and SSIM are markedly enhanced using proposed filtering scheme in comparison to other total variation based methods. [ABSTRACT FROM AUTHOR]

A scheme for inducing multipartite entanglement revival in the dissipative environment is proposed, which is implemented by performing a prior quantum uncollapsing (weak measurements or measurement reversals) procedure on partial qubits of the system simultaneously. This procedure preferentially equips our initial states, and make them hold more powerful ability to actively battle against degradation of entanglement, even postpone entanglement sudden death (ESD). Notably, the effect is more pronounced for the multipartite system with less initial entanglement. In addition, we found that our scheme also works for the N -qubit GHZ-class state. [ABSTRACT FROM AUTHOR]

Here we report a precise computer simulation study of the static critical properties of the two-dimensional q -states Potts model using very accurate data obtained from a modified Wang–Landau (WL) scheme proposed by Caparica and Cunha-Netto (2012). This algorithm is an extension of the conventional WL sampling, but the authors changed the criterion to update the density of states during the random walk and established a new procedure to windup the simulation run. These few changes have allowed a more precise microcanonical averaging which is essential to a reliable finite-size scaling analysis. In this work we used this new technique to determine the static critical exponents β , γ , and ν , in an unambiguous fashion. The static critical exponents were determined as β = 0.10811 ( 77 ) , γ = 1.4459 ( 31 ) , and ν = 0.8197 ( 17 ) , for the q = 3 case, and β = 0.0877 ( 37 ) , γ = 1.3161 ( 69 ) , and ν = 0.7076 ( 10 ) , for the q = 4 Potts model. A comparison of the present results with conjectured values and with those obtained from other well established approaches strengthens this new way of performing WL simulations. [ABSTRACT FROM AUTHOR]

A new discrete fractional random transform based on two circular matrices is designed and a novel double-image encryption–compression scheme is proposed by combining compressive sensing with discrete fractional random transform. The two random circular matrices and the measurement matrix utilized in compressive sensing are constructed by using a two-dimensional sine Logistic modulation map. Two original images can be compressed, encrypted with compressive sensing and connected into one image. The resulting image is re-encrypted by Arnold transform and the discrete fractional random transform. Simulation results and security analysis demonstrate the validity and security of the scheme. [ABSTRACT FROM AUTHOR]

This paper presents a triple detection fiber differential interferometer and its passive demodulation scheme. The interferometer is based on an all fiber Mach–Zehnder and Sagnac hybrid configuration, which is composed of a fiber ASE source, a section of delay fiber, a 3×3 fiber coupler and several other fiber components. In the interferometer, the signal beam and reference beam travel along the same path but in opposite directions. The received signal is demodulated by a triple detection passive demodulation scheme. The interferometer can measure the absolute amplitudes and frequencies of phase sensitive signals with large dynamic range, and the low frequency environmental disturbance is removed simultaneously due to the phase compression mechanism. The experimental results demonstrate that the phase demodulation resolution is 6×10 −5 rad and the maximum measuring amplitude is up to 90 rad. This method can be used to measure many kinds of parameters such as vibration and refractive index. [ABSTRACT FROM AUTHOR]

Like all software systems, databases are subject to evolution as time passes. The impact of this evolution can be vast as a change to the schema of a database can affect the syntactic correctness and the semantic validity of all the surrounding applications. In this paper, we have performed a thorough, large-scale study on the evolution of databases that are part of larger open source projects, publicly available through open source repositories. Lehman׳s laws of software evolution, a well-established set of observations on how the typical software systems evolve (matured during the last forty years), has served as our guide towards providing insights on the mechanisms that govern schema evolution. Much like software systems, we found that schemata expand over time, under a stabilization mechanism that constraints uncontrolled expansion with perfective maintenance. At the same time, unlike typical software systems, the growth is typically low, with long periods of calmness interrupted by bursts of maintenance and a surprising lack of complexity increase. [ABSTRACT FROM AUTHOR]

The main interest of this paper is to illustrate a new representation of the Principal Component Analysis (PCA) for fault detection under a Conditional Gaussian Network (CGN), a special case of Bayesian networks. PCA and its associated quadratic statistics such as T 2 and SPE are integrated under a sole CGN. The proposed framework projects a new observation into an orthogonal space and gives probabilities on the state of the system. It could do so even when some data in the sample test are missing. This paper also gives the probabilities thresholds to use in order to match quadratic statistics decisions. The proposed network is validated and compared to the standard PCA scheme for fault detection on the Tennessee Eastman Process and the Hot Forming Process. [ABSTRACT FROM AUTHOR]

In this study, a numerical model based on the non-oscillatory and non-free parameter dissipation (NND) finite difference scheme for shallow water wave equations including sediment concentration is established in order to simulate the phenomena for dam-break flow and the development of alluvial plain in an estuary. Some numerical experiments show that the numerical model is feasible and efficient for simulating the phenomena for dam-break flow and the development of alluvial plain in an estuary. [ABSTRACT FROM AUTHOR]

A closed-loop, time-optimal path-following control scheme is proposed for a class of constrained differentially flat systems. Within a receding horizon framework, a finite horizon optimisation problem is solved at each sample, using available state feedback and feedforward path information. Irrespective of horizon length, the proposed formulation guarantees exact path-following. Moreover, the requirements under which the proposed algorithm achieves minimum-time path-following are established. Simulations conducted with a rigid X–Y table model confirm the theoretical results. [ABSTRACT FROM AUTHOR]

Zero-knowledge protocols are often studied through specific problems, like Graph-Isomorphism . In many cases this approach prevents an important level of abstraction and leads to limited results, whereas in fact the constructions apply to a wide variety of problems. We propose to address this issue with a formal framework of non-interactive instance-dependent commitment schemes (NIC). We define NIC in the perfect, statistical, and computational settings, and formally characterize problems admitting NIC in all of these settings. We also prove other useful lemmas such as closure properties. Consequently, results that previously applied only to specific problems are now strengthened by our framework to apply to classes of problems . By providing formal yet intuitive tools, our framework facilitates the construction of zero-knowledge protocols for a wide variety of problems, in various settings, without the need to refer to a specific problem. Our results are unconditional. [ABSTRACT FROM AUTHOR]

A hierarchical Bayesian model is developed to characterize the complex-valued high range resolution (HRR) radar target signal, motivated by the problem of radar automatic target recognition (RATR) robust to low signal-to-noise ratio (SNR) or narrowband interference. Here we assume a sparseness-promoting prior on the complex echoes and a Markov dependency for the location of the dominant scattering center between consecutive HRR signals. The number of the dominant scattering centers can be automatically determined, while the posterior distributions of their complex coefficients and locations can be inferred via such Bayesian model. In the training stage, based on the proposed Bayesian model, the statistical aspect-frame template can be learned for HRR complex training samples from each target-aspect sector under high SNR and without any interference. Considering the low SNR or narrowband interference problem for a test sample, the aspect-frame templates can be updated to make a robust recognition decision for the noised and interfered test sample. Simultaneously, the test sample can be denoised and recovered via the analytically posterior estimation for the reconstruction, which is referred to as the statistical compressive sensing (CS) inversion. In contrast to the traditional CS methods that only utilize the underlying sparse property of a measurement (here a measurement is a test sample), our statistical CS inversion also exploits the statistical information of the training samples, which are under high SNR and without any interference. Therefore, the better recognition and reconstruction performances can be obtained via our method. Efficient inference is performed via variational Bayesian (VB) for the proposed Bayesian model. To validate the formulation, we present our experimental results on the measured HRR dataset, with comparisons to some state-of-the-art methods. [ABSTRACT FROM AUTHOR]

This paper presents a safe-triggering-region control strategy suitable for operating a static transfer switch. The suggested approach is helpful in limiting the cross current surge and enhances system's reliability. The maximum transfer time of the suggested control scheme is analyzed and found to be shorter than one cycle in all cases. The proposed approach does not require any additional components in the system. The theoretical expectations are validated by simulations and experimental results. [ABSTRACT FROM AUTHOR]

Although parallelization of computationally intensive algorithms has become a standard with the scientific community, the possibility of in-core vectorization is often overlooked. With the development of modern HPC architectures, however, neglecting such programming techniques may lead to inefficient code hardly utilizing the theoretical performance of nowadays CPUs. The presented paper reports on explicit vectorization for quadratures stemming from the Galerkin formulation of boundary integral equations in 3D. To deal with the singular integral kernels, two common approaches including the semi-analytic and fully numerical schemes are used. We exploit modern SIMD (Single Instruction Multiple Data) instruction sets to speed up the assembly of system matrices based on both of these regularization techniques. The efficiency of the code is further increased by standard shared-memory parallelization techniques and is demonstrated on a set of numerical experiments. [ABSTRACT FROM AUTHOR]