To improve throughput of Electron Beam Direct Writing (EBDW) with Character Projection (CP) method, a structured routing architecture (SRA) has been proposed to restrict VIA placement and wire-track transition. It reduces possible layout patterns in the interconnect layers, and increases VIA and metal figure numbers in the EB shots while suppressing the CP character number explosion. In this paper, we discuss details of the SRA design methodology, and demonstrate the CP performance by SRA in comparison with other EBDW techniques. Our experimental results show viable CP performance for practical use, and prove SRA's feasibility in 14nm mass fabrication.

Ultra-wide band (UWB) radar has a great advantage for range resolution, and is suitable for 3-dimensional (3-D) imaging sensor, such as for rescue robots or surveillance systems, where an accurate 3-dimensional measurement, impervious to optical environments, is indispensable. However, in indoor sensing situations, an available aperture size is severely limited by obstacles such as collapsed furniture or rubles. Thus, an estimated region of target image often becomes too small to identify whether it is a human body or other object. To address this issue, we previously proposed the image expansion method based on the ellipse extrapolation, where the fitting space is converted from real space to data space defined by range points to enhance the extrapolation accuracy. Although this method achieves an accurate image expansion for some cases, by exploiting the feature of the efficient imaging method as range points migration (RPM), there are still many cases, where it cannot maintain sufficient extrapolation accuracy because it only employs the single scattered component for imaging. For more accurate extrapolation, this paper extends the above image expansion method by exploiting double-scattered signals between the target and the wall in an indoor environment. The results from numerical simulation validate that the proposed method significantly expands the extrapolated region for multiple elliptical objects, compared with that obtained using only single scattered signal.

The last decade has witnessed an explosion of interest in research on human emotion modeling for generating intelligent virtual agents. This paper proposes a novel personality model based on the Revised NEO Personality Inventory (NEO PI-R). Compared to the popular Big-Five-Personality Factors (Big5) model, our proposed model is more capable than Big5 on describing a variety of personalities. Combining with emotion models it helps to produce more reasonable emotional reactions to external stimuli. A novel Resistant formulation is also proposed to effectively simulate the complicated negative emotions. Emotional reactions towards multiple stimuli are also effectively simulated with the proposed personality model.

The increasing demand of indoor location based service (LBS) has promoted the development of localization techniques. As an important alternative, fingerprinting localization technique can achieve higher localization accuracy than traditional trilateration and triangulation algorithms. However, it is computational expensive to construct the fingerprint database in the offline phase, which limits its applications. In this paper, we propose an efficient indoor positioning system that uses a new empirical propagation model, called regional propagation model (RPM), which is based on the cluster based propagation model theory. The system first collects the sparse fingerprints at some certain reference points (RPs) in the whole testing scenario. Then affinity propagation clustering algorithm operates on the sparse fingerprints to automatically divide the whole scenario into several clusters or sub-regions. The parameters of RPM are obtained in the next step and are further used to recover the entire fingerprint database. Finally, the location estimation is obtained through the weighted k-nearest neighbor algorithm (WkNN) in the online localization phase. We also theoretically analyze the localization accuracy of the proposed algorithm. The numerical results demonstrate that the proposed propagation model can predict the received signal strength (RSS) values more accurately than other models. Furthermore, experiments also show that the proposed positioning system achieves higher localization accuracy than other existing systems while cutting workload of fingerprint calibration by more than 50% in the offline phase.

This paper covers new architectures, technologies, and performance benchmarking together with prospects for high productivity and high performance computing enabled by photonics. The exponential and sustained increases in computing and data center needs are driving the demands for exascale computing in the future. Power-efficient and parallel computing with balanced system design is essential for reaching that goal as should support ∼billion total concurrencies and ∼billion core interconnections with ∼exabyte/second bisection bandwidth. Photonic interconnects offer a disruptive technology solution that fundamentally changes the computing architectural design considerations. Optics provide ultra-high throughput, massive parallelism, minimal access latencies, and low power dissipation that remains independent of capacity and distance. In addition to the energy efficiency and many of the fundamental physical problems, optics will bring high productivity computing where programmers can ignore locality between billions of processors and memory where data resides. Repeaterless interconnection links across the entire computing system and all-to-all massively parallel interconnection switch will significantly transform not only the hardware aspects of computing but the way people program and harness the computing capability. This impacts programmability and productivity of computing. Benchmarking and optimization of the configuration of the computing system is very important. Practical and scalable deployment of photonic interconnected computing systems are likely to be aided by emergence of athermal silicon photonics and hybrid integration technologies.

This paper presents a fundamental locally one-dimensional (FLOD) method for 3-D thermal simulation. We first propose a locally one-dimensional (LOD) method for heat transfer equation within general inhomogeneous media. The proposed LOD method is then cast into compact form and formulated into the FLOD method with operator-free right-hand-side (RHS), which leads to computationally efficient update equations. Memory storage requirements and boundary conditions for both FLOD and LOD methods are detailed and compared. Stability analysis by means of analyzing the eigenvalues of amplification matrix substantiates the stability of the FLOD method. Additionally, the potential instability of the Douglas Gunn (DG) alternating-direction-implicit (ADI) method for inhomogeneous media is demonstrated. Numerical experiments justify the gain achieved in the overall efficiency for FLOD over LOD, DG-ADI and explicit methods. Furthermore, the relative maximum error of the FLOD method illustrates good trade-off between accuracy and efficiency.

Many detailed studies ranging from networking to hardware as well as standardization activities over the last few years have advanced the performance of the elastic optical network. Thanks to these intensive works, the elastic optical network has been becoming feasible. This paper reviews the recent advances in the elastic optical network from the aspects of networking technology and hardware design. For the former, we focus on the efficient elastic network design technology related to routing and spectrum assignment (RSA) of elastic optical paths including network optimization or standardization activities, and for the latter, two key enabling technologies are discussed: elastic transponders/regenerators and gridless optical switches. Making closely-dependent networking and hardware technologies work synergistically is the key factor in implementing truly effective elastic optical networks.

Now that the subject of green computing is receiving a lot of attention, the energy consumption of datacenters has emerged as a significant issue. Consolidation of Virtual Machines (VMs) reduces the energy consumption since VM live migration not only optimizes VM placement, but also switches idle nodes to sleep mode. However, VM migration may negatively impact the performance of the system and lead to violations in SLA (Service Level Agreement) requirements between end users and cloud providers. In this study, we propose a VM consolidation mechanism that reduces the energy consumption of datacenters, eliminates unnecessary migrations, and minimizes the SLA violations. Compared to previous studies, the proposed policy shows a reduction of 2% to 3% in energy consumption, 13% to 41% in VM migration frequency, and 15% to 50% in SLA violations.

The k-error linear complexity of periodic sequences is an important security index of stream cipher systems. By using an interesting decomposing approach, we investigate the intrinsic structure for the set of 2n-periodic binary sequences with fixed complexity measures. For k ≤ 4, we construct the complete set of error vectors that give the k-error linear complexity. As auxiliary results we obtain the counting functions of the k-error linear complexity of 2n-periodic binary sequences for k ≤ 4, as well as the expectations of the k-error linear complexity of a random sequence for k ≤ 3. Moreover, we study the 2t-error linear complexity of the set of 2n-periodic binary sequences with some fixed linear complexity L, where t < n-1 and the Hamming weight of the binary representation of 2n-L is t. Also, we extend some results to pn-periodic sequences over Fp. Finally, we discuss some potential applications.

This paper reduces the total number of lifting steps of a two dimensional (2D) discrete wavelet transform (DWT) under the constraint that the DWT has full compatibility with a given separable 2D DWT. In a DWT composed of several lifting steps in cascade, a lifting step must wait for a calculation result of its previous lifting step. Therefore more lifting steps bring about longer latency from the input to the output. In this paper, we reduce the total number of lifting steps of a quadruple lifting DWT which is widely utilized as the 9/7 DWT in the JPEG 2000 international standard for image data compression. Firstly, we introduce basic properties for modification of signal flow structure inside a DWT without changing its output. Secondly, we convert the separable 2D quadruple lifting DWT into the non-separable 2D DWT utilizing the basic properties so that the total number of the lifting steps is reduced. As a result, the lifting steps were reduced to 75[%]. Finally, we evaluate the proposed non-separable 2D DWT in respect of compatibility with the conventional separable 2D DWT.

In the design of distributed systems, defending against Sybil attack is an important issue. Recently, OSN (Online Social Network)-based Sybil defending approaches, which use the fast mixing property of a social network graph with sufficient length of random walks and provide Sybil-resistant trust values, have been proposed. However, because of the probabilistic property of the previous approaches, some honest (non-Sybil) identities obtain low trust value and they are mistakenly considered as Sybil identities. A simple solution of boosting the trust value of honest identities is using longer random walks, but this direct boosting method also increases trust values of Sybil identities significantly. In this paper, a two-step boosting method is proposed to increase the Sybil-resistant trust value of honest identities reasonably and to prevent Sybil identities from having high trust values. The proposed boosting method is composed of two steps: initializing the trust value with a reasonably long random walks and boosting the trust value by using much longer random walks than the first step. The proposed method is evaluated by using sampled social network graphs of Facebook, and it is observed that the proposed method reduces the portion of honest identities mistakenly considered as Sybil identities substantially (from 30% to 1.3%) and keeps the low trust values of Sybil identities.

Location fingerprinting utilizes periodic beacons transmitted by Wireless Local Area Network (WLAN) Access Points (APs) to provide localization in indoor environments. Currently no method is able to quantify the effectiveness of localization information provided by individual APs. Such a metric would enable the optimal placement of new APs as well as eliminating redundant APs so as to reduce the resources consumed by indoor localization software in client devices. This paper proposes LocationInfo, a metric that utilizes walk test data for quantifying the localization efficacy of APs. The performance of LocationInfo is evaluated using two experimental settings. First, it is used for identifying the optimal location for new APs. Second, it is used for filtering out excess APs in a crowded WLAN environment. In both experiments, LocationInfo outperforms existing metrics.

In this paper, we first prove beyond-birthyday-bound security for the Misty structure. Specifically, we show that an r-round Misty structure is secure against CCA attacks up to $O(2^{rac{rn}{r+7}})$ query complexity, where n is the size of each round permutation. So for any ε>0, a sufficient number of rounds would guarantee the security of the Misty structure up to 2n(1-ε) query complexity.

This letter proposes an efficient Two-stage Resource scheduling algorithm for cloud based Live Media Streaming system (TRLMS). It transforms the cloud-based resource scheduling problem to a min-cost flow problem in a graph, and solves it by an improved Successive Short Path (SSP) algorithm. Simulation results show that TRLMS can enhance user demand satisfaction by 17.1% than mean-based method, and its time complexity is much lower than original SSP algorithm.

The body-of-revolution finite-difference time-domain method (BOR-FDTD) based on the locally one-dimensional (LOD) scheme is extended to a frequency-dependent version for the analysis of the Drude and Drude-Lorentz models. The formulation is simplified with a fundamental scheme, in which the number of arithmetic operations is reduced by 40% in the right-hand sides of the resultant equations. Efficiency improvement of the LOD-BOR-FDTD is discussed through the analysis of a plasmonic rod waveguide and a plasmonic grating.

This paper presents a novel test data compression scheme for SoCs based on block merging and compatibility. The technique exploits the properties of compatibility and inverse compatibility between consecutive blocks, consecutive merged blocks, and two halves of the encoding merged block itself to encode the pre-computed test data. The decompression circuit is simple to be implemented and has advantage of test-independent. In addition, the proposed scheme is applicable for IP cores in SoCs since it compresses the test data without requiring any structural information of the circuit under test. Experimental results demonstrate that the proposed technique can achieve an average compression ratio up to 68.02% with significant low test application time.

The relative arrangement, such as relative positions and orientations among objects, can play an important role in expressing the situation such as sports games and race scenes. In this paper, we propose a retargeting method that allows maintaining the relative arrangement. Our proposed retargeting method is based on a warping method which finds an optimal transformation by solving an energy minimization problem. To achieve protection of object arrangement, we introduce an energy that enforces all the objects and the relative positions among these objects to be transformed by the same transformation in the retargeting process. In addition, our method imposes the following three types of conditions in order to obtain more satisfactory results: protection of important regions, avoiding extreme deformation, and cropping with preservation of the balance of visual importance. Experimental results demonstrate that our proposed method maintains the relative arrangement while protecting important regions.

We give a unified view to greedy geometric routing algorithms in ad hoc networks. For this, we first present a general form of greedy routing algorithm using a class of objective functions which are invariant under congruent transformations of a point set. We show that several known greedy routing algorithms such as Greedy Routing, Compass Routing, and Midpoint Routing can be regarded as special cases of the generalized greedy routing algorithm. In addition, inspired by the unified view of greedy routing, we propose three new greedy routing algorithms. We then derive a sufficient condition for our generalized greedy routing algorithm to guarantee packet delivery on every Delaunay graph. This condition makes it easier to check whether a given routing algorithm guarantees packet delivery, and it is closed under convex linear combination of objective functions. It is shown that Greedy Routing, Midpoint Routing, and the three new greedy routing algorithms proposed in this paper satisfy the sufficient condition, i.e., they guarantee packet delivery on Delaunay graphs. We also discuss merits and demerits of these methods.

Pattern-avoiding permutations are permutations where none of the subsequences matches the relative order of a given pattern. Pattern-avoiding permutations are related to practical and abstract mathematical problems and can provide simple representations for such problems. For example, some floorplans, which are used for optimizing very-large-scale integration (VLSI) circuit design, can be encoded into pattern-avoiding permutations. The generation of pattern-avoiding permutations is an important topic in efficient VLSI design and mathematical analysis of patten-avoiding permutations. In this paper, we present an algorithm for generating pattern-avoiding permutations, and extend this algorithm beyond classical patterns to generalized patterns with more restrictions. Our approach is based on the data structure πDDs, which can represent a permutation set compactly and has useful set operations. We demonstrate the efficiency of our algorithm by computational experiments.

A whitelisting approach is a promising solution to prevent unwanted processes (e.g., malware) getting executed. However, previous solutions suffer from limitations in that: 1) Most methods place the whitelist information in the kernel space, which could be tempered by attackers; 2) Most methods cannot prevent the execution of kernel processes. In this paper, we present VAW, a novel application whitelisting system by using the virtualization technology. Our system is able to block the execution of unauthorized user and kernel processes. Compared with the previous solutions, our approach can achieve stronger security guarantees. The experiments show that VAW can deny the execution of unwanted processes effectively with a little performance overhead.