In GNSS (Global Navigation Satellite System) Distributed Simulation Environment (GDSE), the simulation task could be designed with the sharing models on the Internet. However, too much information and relation of model need to be managed in GDSE. Especially if there is a large quantity of sharing models, the model retrieval would be an extremely complex project. For meeting management demand of GDSE and improving the model retrieval efficiency, the characteristics of service simulation model are analysed firstly. A semantic management method of simulation model is proposed, and a model management architecture is designed. Compared with traditional retrieval way, it takes less retrieval time and has a higher accuracy result. The simulation results show that retrieval in the semantic management module has a good ability on understanding user needs, and helps user obtain appropriate model rapidly. It improves the efficiency of simulation tasks design.

This paper presents the method of moments based on electric field integral equation which is capable of solving three-dimensional metallic waveguide problem with no use of another method. Metals are treated as perfectly electric conductor. The integral equation is derived in detail. In order to validate the proposed method, the numerical results are compared with those in a published paper. Three types of waveguide are considered: step discontinuity waveguide, symmetrical resonant iris waveguide, and unsymmetrical resonant iris waveguide. The numerical results are also verified by the law of conservation of energy.

Bilinear-type conversion is to translate a cryptographic scheme designed over symmetric bilinear groups into one that works over asymmetric bilinear groups with small overhead regarding the size of objects concerned in the target scheme. In this paper, we address scalability for converting complex cryptographic schemes. Our contribution is threefold. Investigating complexity of bilinear-type conversion. We show that there exists no polynomial-time algorithm for worst-case inputs under standard complexity assumption. It means that bilinear-type conversion in general is an inherently difficult problem. Presenting a new scalable conversion method. Nevertheless, we show that large-scale conversion is indeed possible in practice when the target schemes are built from smaller building blocks with some structure. We present a novel conversion method, called IPConv, that uses 0-1 Integer Programming instantiated with a widely available IP solver. It instantly converts schemes containing more than a thousand of variables and hundreds of pairings. Application to computer-aided design. Our conversion method is also useful in modular design of middle to large scale cryptographic applications; first construct over simpler symmetric bilinear groups and run over efficient asymmetric groups. Thus one can avoid complication of manually allocating variables over asymmetric bilinear groups. We demonstrate its usefulness by somewhat counter-intuitive examples where converted DLIN-based Groth-Sahai proofs are more compact than manually built SXDH-based proofs. Though the early purpose of bilinear-type conversion is to save existing schemes from attacks against symmetric bilinear groups, our new scalable conversion method will find more applications beyond the original goal. Indeed, the above computer-aided design can be seen as a step toward automated modular design of cryptographic schemes.

Kirchhoff approximation (KA) method has been applied for ray-mode conversion to analyze the plane wave scattering by conducting thick slits. The scattering fields can be considered as field radiations from equivalent magnetic current sources assumed by closing the aperture of the slit. The obtained results are compared with those of other methods to validate the accuracy of the proposed formulation in different conditions of slit dimension.

An ASIC crypto processor optimized for the 254-bit prime-field optimal-ate pairing over Barreto-Naehrig (BN) curve is proposed. The data path of the proposed crypto processor is designed to compute five Fp2 operations, a multiplication, three addition/subtractions, and an inversion, simultaneously. We further propose a design methodology to automate the instruction scheduling by using a combinatorial optimization solver, with which the total cycle count is reduced to 1/2 compared with ever reported. The proposed crypto processor is designed and fabricated by using a 65nm silicon-on-thin-box (SOTB) CMOS process. The chip measurement result shows that the fabricated chip successfully computes a pairing in 0.185ms when a typical operating voltage of 1.20V is applied, which corresponds to 2.8× speed up compared to the current state-of-the-art pairing implementation on ASIC platform.

In this paper, we propose a novel algorithm called multi-projection ensemble discriminant clustering (MPEDC) for JPEG steganalysis. The scheme makes use of the optimal projection of linear discriminant analysis (LDA) algorithm to get more projection vectors by using the micro-rotation method. These vectors are similar to the optimal vector. MPEDC combines unsupervised K-means algorithm to make a comprehensive decision classification adaptively. The power of the proposed method is demonstrated on three steganographic methods with three feature extraction methods. Experimental results show that the accuracy can be improved using iterative discriminant classification.

Side scan sonar using low frequency can quickly search a wide range, but the images acquired are of low quality. The image super resolution (SR) method can mitigate this problem. The SR method typically uses sparse coding, but accurately estimating sparse coefficients incurs substantial computational costs. To reduce processing time, we propose a region-selective sparse coding based SR system that emphasizes object regions. In particular, the region that contains interesting objects is detected for side scan sonar based underwater images so that the subsequent sparse coding based SR process can be selectively applied. Effectiveness of the proposed method is verified by the reduced processing time required for image reconstruction yet preserving the same level of visual quality as conventional methods.

In this study, transverse magnetic electromagnetic plane wave scatterings by rectangular cylinders have been analyzed by a high frequency asymptotic method. Scattering field can be generated by the equivalent electric and magnetic currents which are obtained approximately from the geometrical optics (GO) fields. Our formulation is found to be exactly the same with the physical optics (PO) for the conducting cylinders, and it can also be applicable for dielectric cylinders. Numerical calculations are made to compare the results with those by other methods, such as the geometrical theory of diffraction (GTD) and HFSS simulation. A good agreement has been observed to confirm the validity of our method.

Depth image based rendering (DIBR), which is utilized to render virtual views with a color image and the corresponding depth map, is one of the key procedures in the 2D to 3D conversion process. However, some troubling problems, such as depth edge misalignment, disocclusion occurrences and cracks at resampling, still exist in current DIBR systems. To solve these problems, in this paper, we present a robust depth image based rendering scheme for stereoscopic view synthesis. The cores of the proposed scheme are two depth map filters which share a common domain transform based filtering framework. As a first step, a filter of this framework is carried out to realize texture-depth boundary alignments and directional disocclusion reduction smoothing simultaneously. Then after depth map 3D warping, another adaptive filter is used on the warped depth maps with delivered scene gradient structures to further diminish the remaining cracks and noises. Finally, with the optimized depth map of the virtual view, backward texture warping is adopted to retrieve the final texture virtual view. The proposed scheme enables to yield visually satisfactory results for high quality 2D to 3D conversion. Experimental results demonstrate the excellent performances of the proposed approach.

This paper proposes a block-permutation-based encryption (BPBE) scheme for the encryption-then-compression (ETC) system that enhances the color scrambling. A BPBE image can be obtained through four processes, positional scrambling, block rotation/flip, negative-positive transformation, and color component shuffling, after dividing the original image into multiple blocks. The proposed scheme scrambles the R, G, and B components independently in positional scrambling, block rotation/flip, and negative-positive transformation, by assigning different keys to each color component. The conventional scheme considers the compression efficiency using JPEG and JPEG 2000, which need a color conversion before the compression process by default. Therefore, the conventional scheme scrambles the color components identically in each process. In contrast, the proposed scheme takes into account the RGB-based compression, such as JPEG-LS, and thus can increase the extent of the scrambling. The resilience against jigsaw puzzle solver (JPS) can consequently be increased owing to the wider color distribution of the BPBE image. Additionally, the key space for resilience against brute-force attacks has also been expanded exponentially. Furthermore, the proposed scheme can maintain the JPEG-LS compression efficiency compared to the conventional scheme. We confirm the effectiveness of the proposed scheme by experiments and analyses.

A tremendous amount of knowledge is present in the ever-growing scientific literature. In order to efficiently grasp such knowledge, various computational tasks are proposed that train machines to read and analyze scientific documents. One of these tasks, Scientific Relation Extraction, aims at automatically capturing scientific semantic relationships among entities in scientific documents. Conventionally, only a limited number of commonly used knowledge bases, such as Wikipedia, are used as a source of background knowledge for relation extraction. In this work, we hypothesize that unannotated scientific papers could also be utilized as a source of external background information for relation extraction. Based on our hypothesis, we propose a model that is capable of extracting background information from unannotated scientific papers. Our experiments on the RANIS corpus [1] prove the effectiveness of the proposed model on relation extraction from scientific articles.

As LSI chips integrate more transistors and the operating power supply voltage decreases, LSI chips are becoming more vulnerable to the soft error caused by neutrons induced from cosmic rays. The soft error is detected by comparing the duplicated operation results in double modular redundancy (DMR) and the error is corrected by re-executing necessary operations. In this paper, based on the error recovery scheme of re-executing necessary operations, the minimization of the vote operations for error checking with respect to given resource constraints is considered. An ILP model for the optimal solution to the problem is presented and a heuristic algorithm is proposed to minimize the vote operations.

The network load is increasing due to the spread of content distribution services. Caching is known as a technique to reduce a peak network load by prefetching popular contents into memories of users. Coded caching is a new caching approach based on a carefully designed content placement in order to create coded multicasting opportunities. Recent works have discussed single-layer caching systems, but many networks consist of multiple layers of cache. In this paper, we discuss a coded caching problem for a hierarchical network that has a different number of layers of cache. The network has users who connect to an origin server via a mirror server and users who directly connect to the origin server. We provide lower bounds of the rates for this problem setting based on the cut-set bound. In addition, we propose three basic coded caching schemes and characterize these schemes. Also, we propose a new coded caching scheme by combining two basic schemes and provide achievable rates of the combination coded caching scheme. Finally, we show that the proposed combination scheme demonstrates a good performance by a numerical result.

The Infrastructure as a Service (IaaS) Clouds are emerging as a promising platform for the execution of resource demanding and computation intensive workflow applications. Scheduling the execution of scientific applications expressed as workflows on IaaS Clouds involves many uncertainties due to the variable and unpredictable performance of Cloud resources. These uncertainties are modeled by probability distribution functions in past researches or totally ignored in some cases. In this paper, we propose a novel robust deadline constrained workflow scheduling algorithm which handles the uncertainties in scheduling workflows in the IaaS Cloud environment. Our proposal is a static scheduling algorithm aimed at addressing the uncertainties related to: the estimation of task execution times; and, the delay in provisioning computational Cloud resources. The workflow scheduling problem was considered as a cost-optimized, deadline-constrained optimization problem. Our uncertainty handling strategy was based on the consideration of knowledge of the interval of uncertainty, which we used to modeling the execution times rather than using a known probability distribution function or precise estimations which are known to be very sensitive to variations. Experimental evaluations using CloudSim with synthetic workflows of various sizes show that our proposal is robust to fluctuations in estimates of task runtimes and is able to produce high quality schedules that have deadline guarantees with minimal penalty cost trade-off depending on the length of the interval of uncertainty. Scheduling solutions for varying degrees of uncertainty resisted against deadline violations at runtime as against the static IC-PCP algorithm which could not guarantee deadline constraints in the face of uncertainty.

In this paper, we propose a highly efficient mobile visual search algorithm. For descriptor extraction process, we propose a low complexity feature detection which utilizes the detected local key points of the coarse octaves to guide the scale space construction and feature detection in the fine octave. The Gaussian and Laplacian operations are skipped for the unimportant area, and thus the computing time is saved. Besides, feature selection is placed before orientation computing to further reduce the complexity of feature detection by pre-discarding some unimportant local points. For the image retrieval process, we design a high-performance reranking method, which merges both the global descriptor matching score and the local descriptor similarity score (LDSS). In the calculating of LDSS, the tf-idf weighted histogram matching is performed to integrate the statistical information of the database. The results show that the proposed highly efficient approach achieves comparable performance with the state-of-the-art for mobile visual search, while the descriptor extraction complexity is largely reduced.

A 256-bit $mathbb{F}_p$ ECDSA crypto processor featuring low latency, low energy consumption and capability of changing the Elliptic curve parameters is designed and fabricated in SOTB 65nm CMOS process. We have demonstrated the lowest ever reported signature generation time of 31.3 μs at 238MHz clock frequency. Energy consumption is 3.28 μJ/signature-generation, which is same as the lowest reported till date. We have also derived addition formulae on Elliptic curve useful for reduce the number of registers and operation cycles.

Network coding signature (NCS) scheme is a cryptographic tool for network coding against pollution attacks. In [5], Chang et al. first introduced the related-key attack (RKA) to the NCS schemes and tried to give an instantiation of it. However, their instantiation is based on the random oracle (RO) model. In this letter, we present a standard-model instantiation. In particular, we prove that standard-model-based NCS scheme introduced by Boneh et al. in [4] (BFKW scheme, for short) can achieve Φ-RKA security if the underlying signature scheme is also Φ-RKA secure, where Φ is any family of functions defined on signing keys of NCS schemes.

This study proposes a multiple-output differential-input operational transconductance amplifier-C (MODI OTA-C) filter with an impedance scaler to detect cardiac activity. A ladder-type fifth-orderButterworth low-pass filter with a large time constant and low noise is implemented to reduce coefficient sensitivity and address signal distortion. Moreover, linearized MODI OTA structures with reduced transconductance and impedance scaler circuits for noise reduction are used to achieve a wide dynamic range (DR). The OTA-based circuit is operated in the subthreshold region at a supply voltage of 1 V to reduce the power consumption of the wearable device in long-term use. Experimental results of the filter with a bandwidth of 250 Hz reveal that DR is 57.6 dB, and the harmonic distortion components are below -59 dB. The power consumption of the filter, which is fabricated through a TSMC 0.18 µm CMOS process, is lower than 390 nW, and the active area is 0.135 mm2.

This paper describes a broadband low phase noise VCO implemented in 0.13 µm CMOS process. A 1-bit switched varactor and a 4-bit capacitor array are adopted in cooperation with the automatic frequency calibration (AFC) circuit to lower the VCO tuning gain (KVCO), with a measured AFC time of 6 µs. Several noise reduction techniques are exploited to minimize the phase noise of the VCO. Measurement results show the VCO generates a high frequency range from 11.37 GHz to 14.8 GHz with a KVCO of less than 270 MHz/V. The prototype exhibits a phase noise of -114.6 dBc/Hz @ 1 MHz at 14.67 GHz carrier frequency and draws 10.5 mA current from a 1.2 V supply. The achieved figure-of-merits (FoM=-186.9dBc/Hz, FoMT=-195.3dBc/Hz) favorably compares with the state-of-the-art.

Datacenter growth in traffic and scale is driving innovations in constructing tightly-coupled facilities with low-latency communication for different specific applications. A famous custom design is rackscale (RS) computing by gathering key server resource components into different resource pools. Such a resource-pooling implementation requires a new software stack to manage resource discovery, resource allocation and data communication. The reconfiguration of interconnection networks on their components is potentially needed to support the above demand in RS. In this context as an evolution of the original RS architecture the inter-rackscale (IRS) architecture, which disaggregates hardware components into different racks according to their own areas, has been proposed. The heart of IRS is to use a limited number of free-space optics (FSO) channels for wireless connections between different resource racks, via which selected pairs of racks can communicate directly and thus resource-pooling requirements are met without additional software management. In this study we evaluate the influences of FSO links on IRS networks. Evaluation results show that FSO links reduce average communication hop count for user jobs, which is close to the best possible value of 2 hops and thus provides comparable benchmark performance to that of the counterpart RS architecture. In addition, if four FSO terminals per rack are allowed, the CPU/SSD (GPU) interconnection latency is reduced by 25.99% over Fat-tree and by 67.14% over 2-D Torus. We also present the advantage of an FSO-equipped IRS system in average turnaround time of dispatched jobs for given sets of benchmark workloads.