This paper presents a method to realize index generation functions using multiple Index Generation Units (IGUs). The architecture implements index generation functions more efficiently than a single IGU when the number of registered vectors is very large. This paper proves that independent linear transformations are necessary in IGUs for efficient realization. Experimental results confirm this statement. Finally, it shows a fast update method to IGUs.

Self-Aligned Quadruple Patterning (SAQP) is an important manufacturing technique for sub 14nm technology node. Although various routing algorithms for SAQP have been proposed, it is not easy to find a dense SAQP compliant routing pattern efficiently. Even though a grid for SAQP compliant routing pattern was proposed, it is not easy to find a valid routing pattern on the grid. The routing pattern of SAQP on the grid consists of three types of routing. Among them, third type has turn prohibition constraint on the grid. Typical routing algorithms often fail to find a valid routing for third type. In this paper, a simple directed grid-graph for third type is proposed. Valid SAQP compliant two dimensional routing patterns are found effectively by utilizing the proposed directed grid-graph. Experiments show that SAQP compliant routing patterns are found efficiently by our proposed method.

Verification of logic designs has been a long-standing bottleneck in the process of hardware design, where its automation and improvement of efficiency has demanding needs. Mainly simulation-based verification has been used for this purpose, and recently, coverage-driven verification has been widely used, of which target is improvement of some metric called coverage. Our target is the metric called toggle coverage. To find input patterns which cause some toggles on each signal, a SAT solver could be used, but this is computationally costly. In this paper, we study the effect of combination of random simulation and usage of a SAT solver. In particular, we use a SAT solver which can find multiple “diverse” solutions. With this solver, we can avoid generating similar patterns, which are unlikely to improve coverage. The experimental results show that, a small number of calls of a SAT solver can improve entire toggle coverage effectively, compared with simple random simulation.

A comprehensive method applying a nonlinear frequency compression (FC) as complementary to multi-band loudness compensation is proposed, which is able to improve loudness compensation and simultaneously increase high-frequency speech intelligibility for digital hearing aids. The proposed nonlinear FC (NLFC) improves the conventional methods in the aspect that the compression ratio (CR) is adjusted based on the speech intelligibility percentage in different frequency ranges. Then, an adaptive wide dynamic range compression (AWDRC) with a time-varying CR is applied to achieve adaptive loudness compensation. The experimental test results show that the mean speech identification is improved in comparison with the state-of-art methods.

This report presents experimental measurements of mixed-mode oscillations (MMOs) generated by a weakly driven four-segment piecewise linear Bonhoeffer-van der Pol (BVP) oscillator. Such a roughly approximated simple piecewise linear circuit can generate MMOs and mixed-mode oscillation-incrementing bifurcations (MMOIBs). The laboratory experiments well agree with numerical results. We experimentally and numerically observe time series and Lorenz plots of MMOs generated by successive and nonsuccessive MMOIBs.

This paper presents an ontology-based driving decision making system, which can promptly make safety decisions in real-world driving. Analyzing sensor data for improving autonomous driving safety has become one of the most promising issues in the autonomous vehicles research field. However, representing the sensor data in a machine understandable format for further knowledge processing still remains a challenging problem. In this paper, we introduce ontologies designed for autonomous vehicles and ontology-based knowledge base, which are used for representing knowledge of maps, driving paths, and perceived driving environments. Advanced Driver Assistance Systems (ADAS) are developed to improve safety of autonomous vehicles by accessing to the ontology-based knowledge base. The ontologies can be reused and extended for constructing knowledge base for autonomous vehicles as well as for implementing different types of ADAS such as decision making system.

For a multiuser multi-input multi-output (MU-MIMO) multicell network, the Han-Kobayashi strategy aims to improve the achievable rate region by splitting the data information intended to a serviced user (UE) into a common message and a private message. The common message is decodable by this UE and another UE from an adjacent cell so that the corresponding intercell interference is cancelled off. This work aims to design optimal precoders for both common and private messages to maximize the network sum-rate, which is a highly nonlinear and nonsmooth function in the precoder matrix variables. Existing approaches are unable to address this difficult problem. In this paper, we develop a successive convex quadratic programming algorithm that generates a sequence of improved points. We prove that the proposed algorithm converges to at least a local optimum of the considered problem. Numerical results confirm the advantages of our proposed algorithm over conventional coordinated precoding approaches where the intercell interference is treated as noise.

This letter presents a novel memory-based architecture for radix-2 fast Walsh-Hadamard-Fourier transform (FWFT) based on the constant geometry FWFT algorithm. It is composed of a multi-function Processing Engine, a conflict-free memory addressing scheme and an efficient twiddle factor generator. The address for memory access and the control signals for stride permutation are formulated in detail and the methods can be applied to other memory-based FFT-like architectures.

This paper presents accurate DC and high frequency power-supply rejection (PSR) models for low drop-out (LDO) regulators using different types of active loads and pass transistors. Based on the proposed PSR model, we suggest design guidelines to achieve a high DC PSR or flat bandwidth (BW) by choosing appropriate active loads and pass transistors. Our PSR model captures the intricate interaction between the error amplifiers (EAs) and the pass devices by redefining the transfer function of the LDO topologies. The accuracy of our model has been verified through SPICE simulation and measurements. Moreover, the measurement results of the LDOs fabricated using the 0.18 µm CMOS process are consistent with the design guidelines suggested in this work.

The Seebeck coefficient of Si wire co-doped with P and Ga atoms is investigated for applying thermoelectric devices. The observed Seebeck coefficient is closed to the theoretical values of electronic part of Seebeck coefficient due to the electronic transport. From the estimation of phonon scattering processes, it is found that the phonon-drag contribution to the Seebeck coefficient in co-doped Si wire is mainly governed by the phonon-boundary scattering.

The phonon-drag contribution to the Seebeck coefficient (Sph) for p-type Si, Ge and Si1-xGex is investigated for thermoelectric applications. The Sph in Si and Ge is found to mainly determined by the phonon velocity, phonon mean free path and carrier mobility associated with acoustic deformation potential scattering. Moreover, the Sph in Si1-xGex is predictable by the above-mentioned material parameters interpolated with those in Si and Ge.

The sub-blocking algorithm has been known as a core component in implementing a turbo decoder using a Graphic Processing Unit (GPU) to use as many cores in the GPU as possible for parallel processing. However, even though the sub-blocking algorithm allows a large number of threads in a given GPU to be adopted for processing a large number of sub-blocks in parallel, each thread must access the global memory with strided addresses, which results in uncoalesced memory access. Because uncoalesced memory access causes a lot of unnecessary memory transactions, the memory bandwidth efficiency drops significantly, possibly as low as 1/8 in the case of an Long Term Evolution (LTE) turbo decoder, depending upon the compute capability of a GPU. In this paper, we present a novel method for converting uncoalesced memory access into coalesced access in a way that completely recovers the memory bandwidth efficiency to 100% without additional overhead. Our experimental tests, performed with NVIDIA's Geforce GTX 780 Ti GPU, show that the proposed method can enhance the throughput by nearly 30% compared with a conventional turbo decoder that suffers from uncoalesced memory access. Throughput provided by the proposed method has been observed to be 51.4Mbps when the number of iterations and that of sub-blocks are set to 6 and 32, respectively, in our experimental tests, which far exceeds the performance of previous works implemented the Max-Log-MAP algorithm.

For IP-based mobile networks, efficient mobility management is vital to provision seamless online service. IP address starvation and scalability issue constrain the wide deployment of existing mobility schemes, such as Mobile IP, Proxy Mobile IP, and their derivations. Most of the studies focus on the scenario of mobility among public networks. However, most of current networks, such as home networks, sensor networks, and enterprise networks, are deployed with private networks hard to apply mobility solutions. With the rapid development, Software Defined Networking (SDN) offers the opportunity of innovation to support mobility in private network schemes. In this paper, a novel mobility management scheme is presented to support mobile node moving from public network to private network in a seamless handover procedure. The centralized control manner and flexible flow management in SDN are utilized to provide network-based mobility support with better QoS guarantee. Benefiting from SDN/OpenFlow technology, complex handover process is simplified with fewer message exchanges. Furthermore, handover efficiency can be improved in terms of delay and overhead reduction, scalability, and security. Analytical analysis and implementation results showed a better performance than mobile IP in terms of latency and throughput variation.

In order to realize solid-state drives (SSDs) with high performance, low energy consumption and high reliability, storage class memory (SCM)/multi-level cell (MLC) NAND flash hybrid SSD has been proposed. Algorithm of the hybrid SSD should be designed according to SCM specifications and workload characteristics. In this paper, SCMs are used as non-volatile cache. Cache operation guidelines and optimal SCM specifications for the hybrid SSD are provided for various workload characteristics. Three kinds of non-volatile cache operation for the hybrid SSD are discussed: i) write cache, ii) read-write cache without space control (RW cache) and iii) read-write cache with space control (RW cache w/ SC). SSD workloads are categorized into eight according to read/write ratio, access frequency and access data size. From evaluation result, the write cache algorithm is suitable for write-intensive workloads and read-cold-sequential workloads, while the RW cache algorithm is suitable for read-cold-random workloads to achieve the highest performance of the hybrid SSD. In contrast, as for read-hot-random workloads, write cache is appropriate when the SCM capacity is less than 3% of the NAND flash capacity. On the other hand, RW cache should be used in case that SCM capacity is more than 5% of NAND flash capacity. The effect of Memory-type SCM (M-SCM) and Storage-type SCM (S-SCM) on the hybrid SSD performance is also analyzed. The M-SCM latency is below 1 us (high speed) but the capacity is only 2% of the NAND flash capacity (small capacity). On the other hand, the S-SCM capacity is assumed to be 5% of the NAND flash capacity (large capacity) but S-SCM speed is larger than 1 us (low speed). If the additional SCM cost is limited to 20% of MLC NAND flash cost, up to 7-times and 8-times performance improvement are achieved in write-hot-random workload and read-hot-random workloads, respectively. Moreover, if the additional SCM cost is the same as MLC NAND flash cost, M-SCM/MLC NAND flash hybrid SSD achieves 24-times performance improvement.

This paper proposes a new approach for generating pseudo random multi-valued (including binary-valued) sequences. The approach uses a primitive polynomial over an odd characteristic prime field ${p}$, where p is an odd prime number. Then, for the maximum length sequence of vectors generated by the primitive polynomial, the trace function is used for mapping these vectors to scalars as elements in the prime field. Power residue symbol (Legendre symbol in binary case) is applied to translate the scalars to k-value scalars, where k is a prime factor of p-1. Finally, a pseudo random k-value sequence is obtained. Some important properties of the resulting multi-valued sequences are shown, such as their period, autocorrelation, and linear complexity together with their proofs and small examples.

The present paper introduces the construction of quadriphase sequences having a zero-correlation zone. For a zero-correlation zone sequence set of N sequences, each of length l, the cross-correlation function and the side lobe of the autocorrelation function of the proposed sequence set are zero for the phase shifts τ within the zero-correlation zone z, such that |τ|≤z (τ ≠ 0 for the autocorrelation function). The ratio $rac{N(z+1)}{ell}$ is theoretically limited to one. When l=N(z+1), the sequence set is called an optimal zero-correlation sequence set. The proposed zero-correlation zone sequence set can be generated from an arbitrary Hadamard matrix of order n. The length of the proposed sequence set can be extended by sequence interleaving, where m times interleaving can generate 4n sequences, each of length 2m+3n. The proposed sequence set is optimal for m=0,1 and almost optimal for m>1.

Load size for a service on the Internet changes remarkably every hour. Thus, it is expected for service system scales to change dynamically according to load size. KVS (key-value store) is a scalable DBMS (database management system) widely used in largescale Internet services. In this paper, we focus on Cassandra, a popular open-source KVS implementation, and discuss methods for improving dynamic scaling performance. First, we evaluate node joining time, which is the time to complete adding a node to a running KVS system, and show that its bottleneck process is disk I/O. Second, we analyze disk accesses in the nodes and indicate that some heavily accessed files cause a large number of disk accesses. Third, we propose two methods for improving elasticity, which means decreasing node adding and removing time, of Cassandra. One method reduces disk accesses significantly by keeping the heavily accessed file in the page cache. The other method optimizes I/O scheduler behavior. Lastly, we evaluate elasticity of our methods. Our experimental results demonstrate that the methods can improve the scaling-up and scaling-down performance of Cassandra.

The Android pattern unlock is a widely adopted graphical password system that requires a user to draw a secret pattern connecting points arranged in a grid. The theoretical security of pattern unlock can be defined by the number of possible patterns. However, only upper bounds of the number of patterns have been known except for 3×3 and 4×4 grids for which the exact number of patterns was found by brute-force enumeration. In this letter, we present the first lower bound by computing the minimum number of visible points from each point in various subgrids.

Network servers and applications commonly use static IP addresses and communication ports, making themselves easy targets for network reconnaissances and attacks. Moving target defense (MTD) is an innovatory and promising proactive defense technique. In this paper, we develop a novel MTD mechanism, called Random Port and Address Hopping (RPAH). The goal of RPAH is to hide network servers and applications and resist network reconnaissances and attacks by constantly changing their IP addresses and ports. In order to enhance the unpredictability, RPAH integrates source identity, service identity and temporal parameter in the hopping to provide three hopping frequencies, i.e., source hopping, service hopping and temporal hopping. RPAH provides high unpredictability and the maximum hopping diversities by introducing port and address demultiplexing mechanism, and provides a convenient attack detection mechanism with which the messages from attackers using invalid or inactive addresses/ports will be conveniently detected and denied. Our experiments and evaluation on campus network and PlanetLab show that RPAH is effective in resisting various network reconnaissance and attack models such as network scanning and worm propagation, while introducing an acceptable operation overhead.

Driver behavior assessment is a hard task since it involves distinctive interconnected factors of different types. Especially in case of insurance applications, a trade-off between application cost and data accuracy remains a challenge. Data uncertainty and noises make smart-phone or low-cost sensor platforms unreliable. In order to deal with such problems, this paper proposes the combination between the Belief and Fuzzy theories with a two-level fusion based architecture. It enables the propagation of information errors from the lower to the higher level of fusion using the belief and/or the plausibility functions at the decision step. The new developed risk models of the Driver and Environment are based on the accident statistics analysis regarding each significant driving risk parameter. The developed Vehicle risk models are based on the longitudinal and lateral accelerations (G-G diagram) and the velocity to qualify the driving behavior in case of critical events (e.g. Zig-Zag scenario). In case of over-speed and/or accident scenario, the risk is evaluated using our new developed Fuzzy Inference System model based on the Equivalent Energy Speed (EES). The proposed approach and risk models are illustrated by two examples of driving scenarios using the CarSim vehicle simulator. Results have shown the validity of the developed risk models and the coherence with the a-priori risk assessment.