This paper addresses a high-level synthesis (HLS) using dual-edge-triggered flip-flops (DETFFs) as memory elements. In DETFF-based HLS, the duty cycle becomes a manageable resource to improve the timing performance. To utilize the duty cycle radically, a programmable duty cycle (PDC) mechanism is built into this HLS, and captured by a new HLS task named PDC scheduling. As a first step toward DETFF-based HLS with PDC, the execution time minimization problem is formulated for given results of operation scheduling. A linear program is presented to solve this problem in polynomial time. As a next step, simultaneous operation scheduling and PDC scheduling problem for the same objective is tackled. A mixed integer linear programming-based (MILP) approach is presented to solve this problem. The experimental results show that the MILP can reduce the execution time for several benchmarks.

A novel depth perception control method for a monocular head-up display (HUD) in a car has been developed, which is called the dynamic perspective method. The method changes a size and a position of the HUD image such as arrow for depth perception and achieves a depth perception position of 120 [m] within an error of 30% in a simulation. However, it is difficult to achieve an accurate depth perception in the real world because of car vibration. To solve this problem, we focus on a property, namely, that people complement hidden images by previous continuously observed images. We hide the image on the HUD when the car is vibrated very much. We aim to point at the accurate depth position by using see-through HUD images while having users complement the hidden image positions based on the continuous images before car vibration. We developed a car that detects big vibration by an acceleration sensor and is equipped with our monocular HUD. Our new method pointed at the depth position more accurately than the previous method, which was confirmed by t-test.

Weissman introduced a coding problem for channels with action-dependent states. In this coding problem, there are two encoders and a decoder. An encoder outputs an action that affects the state of the channel. Then, the other encoder outputs a codeword of the message into the channel by using the channel state. The decoder receives a noisy observation of the codeword, and reconstructs the message. In this paper, we show an exponential error bound for channels with action-dependent states based on the random coding argument.

In this letter, we first introduce a stronger notion of the optimistic achievable coding rate and discuss a coding theorem. Next, we give a necessary and sufficient condition under which the coding rates of all the optimal FF codes asymptotically converge to a constant.

This paper presents a GPU (Graphics Processing Units) implementation of dynamic programming for the optimal polygon triangulation. Recently, GPUs can be used for general purpose parallel computation. Users can develop parallel programs running on GPUs using programming architecture called CUDA (Compute Unified Device Architecture) provided by NVIDIA. The optimal polygon triangulation problem for a convex polygon is an optimization problem to find a triangulation with minimum total weight. It is known that this problem for a convex n-gon can be solved using the dynamic programming technique in O(n3) time using a work space of size O(n2). In this paper, we propose an efficient parallel implementation of this O(n3)-time algorithm on the GPU. In our implementation, we have used two new ideas to accelerate the dynamic programming. The first idea (adaptive granularity) is to partition the dynamic programming algorithm into many sequential kernel calls of CUDA, and to select the best parameters for the size and the number of blocks for each kernel call. The second idea (sliding and mirroring arrangements) is to arrange the working data for coalesced access of the global memory in the GPU to minimize the memory access overhead. Our implementation using these two ideas solves the optimal polygon triangulation problem for a convex 8192-gon in 5.57 seconds on the NVIDIA GeForce GTX 680, while a conventional CPU implementation runs in 1939.02 seconds. Thus, our GPU implementation attains a speedup factor of 348.02.

A shift of finite type (SFT) is a set of all bi-infinite sequences over some alphabet which is characterized by a finite set of forbidden words. It is a typical example of sofic shifts and has been used in media storage area, such as CD's or DVD's. The study of sofic shifts is based on graph theory, and the irreducibility of shifts is an important property to be considered for the study. In this paper, we will provide some sufficient conditions for an SFT to be irreducible from the perspective of the antidictionary of a word and the number of forbidden words. We also present a necessary and sufficient condition for an SFT to be irreducible when the number of forbidden words is one less than the alphabet size.

To enhance user privacy, anonymous credential systems allow the user to convince a verifier of the possession of a certificate issued by the issuing authority anonymously. In the systems, the user can prove relations on his/her attributes embedded into the certificate. Previously, a pairing-based anonymous credential system with constant-size proofs in the number of attributes of the user was proposed. This system supports the proofs of the inner product relations on attributes, and thus can handle the complex logical relations on attributes as the CNF and DNF formulas. However this system suffers from the computational cost: The proof generation needs exponentiations depending on the number of the literals in OR relations. In this paper, we propose a pairing-based anonymous credential system with the constant-size proofs for CNF formulas and the more efficient proof generation. In the proposed system, the proof generation needs only multiplications depending on the number of literals, and thus it is more efficient than the previously proposed system. The key of our construction is to use an extended accumulator, by which we can verify that multiple attributes are included in multiple sets, all at once. This leads to the verification of CNF formulas on attributes. Since the accumulator is mainly calculated by multiplications, we achieve the better computational costs.

The use of computing resources on network is becoming active in the Internet and private networks. OpenFlow/Software-Defined Networking (SDN) is drawing attention as a method to control network virtualization for the cloud computing services and other carrier services. This paper introduces examples of OpenFlow/SDN technologies applied to commercial cloud services. Various activities to expand coverage over commercial carrier networks are also mentioned.

Nowadays, with spreads of inexpensive small communication devices, a number of wireless local area networks (WLANs) have been deployed even in the same building for the Internet access services. Their wireless access-points (APs) are often independently installed and managed by different groups such as departments or laboratories in a university or a company. Then, a user host can access to multiple WLANs by detecting signals from their APs, which increases the energy consumption and the operational cost. It may also degrade the communication performance by increasing interferences. In this paper, we present an AP aggregation approach to solve these problems in multiple WLAN environments by aggregating deployed APs of different groups into limited ones using virtual APs. First, we formulate the AP aggregation problem as a combinatorial optimization problem and prove the NP-completeness of its decision problem. Then, we propose its heuristic algorithm composed of five phases. We verify the effectiveness through extensive simulations using the WIMNET simulator.

To achieve high recording density in a bit-patterned media recording system, the spacing between data bit islands in both the along-track and the across-track directions must be decreased, thus leading to the increase of two-dimensional (2D) interference. One way to reduce the 2D interference is to apply a 2D coding scheme on a data sequence before recording; however, this method usually requires many redundant bits, thus lowering a code rate. Therefore, we propose a novel 2D coding scheme referred to as a recorded-bit patterning (RBP) scheme to mitigate the 2D interference, which requires no redundant bits at the expense of using more buffer memory. Specifically, an input data sequence is first split into three tracks in which will then be rotated to find the best 3-track data pattern based on a look-up table before recording, such that the shifted data tracks yield the least effect of 2D interference in the readback signal. Numerical results indicate that the proposed RBP scheme provides a significant performance improvement if compared to a conventional system (without 2D coding), especially when the recording density is high and/or the position jitter noise is large.

In this study, the influence of Gd composition on current-induced domain wall motion in a Gd-Co ferrimagnetic nanowire was theoretically investigated with taking into account of composition dependence of magnetic properties. As a result, the intrinsic critical density to move domain wall significantly reduces near the compensation composition, which is achieved to be less than 105A/cm2. Moreover, the intrinsic critical current density also significantly reduces near a certain Gd composition where the domain wall energies of Bloch and Néel walls are almost the same.

This paper presents a real-time and memory-efficient arrhythmia detection system with binary classification that uses antidictionary coding for the analysis and classification of electrocardiograms (ECGs). The measured ECG signals are encoded using a lossless antidictionary encoder, and the system subsequently uses the compression rate to distinguish between normal beats and arrhythmia. An automated training data procedure is used to construct the automatons, which are probabilistic models used to compress the ECG signals, and to determine the threshold value for detecting the arrhythmia. Real-time computer simulations with samples from the MIT-BIH arrhythmia database show that the averages of sensitivity and specificity of the proposed system are 97.8% and 96.4% for premature ventricular contraction detection, respectively. The automatons are constructed using training data and comprise only 11 kilobytes on average. The low complexity and low memory requirements make the system particularly suitable for implementation in portable ECG monitors.

The equivalent circuit of aperture-coupled cavities filled with a lossy dielectric is considered by means of an eigenmode expansion technique founded on the segmentation concept. It is different from a series LCR resonant circuit, and the resistor which symbolizes the dielectric loss is connected to the capacitor in parallel. If the cavities are formed by a short-circuited oversize waveguide, then the input admittance can be represented by the product of a coupling factor to the connected waveguide port and the equivalent admittance of the short-circuited waveguide. The transmission line model is effective even if lossy wall effect and dielectric partially-loading effect are considered. As a result, three-dimensional eigenmode parameters, such as the resonant frequency and the Q-factor, become dispensable and the computational complexity for the cavity simulation in the field of microwave heating is dramatically reduced.

In this paper, we propose a synchronization-aware VM scheduler for parallel applications in Xen. The proposed scheduler prevents threads from waiting for a significant amount of time during synchronization. For this purpose, we propose an identification scheme that can identify the threads that have awaited other threads for a long time. In this scheme, a detection module that can infer the internal status of guest OSs was developed. We also present a scheduling policy that can accelerate bottlenecks of concurrent VMs. We implemented our VM scheduler in the recent Xen hypervisor with para-virtualized Linux-based operating systems. We show that our approach can improve the performance of concurrent VMs by up to 43% as compared to the credit scheduler.

The optimum generalized partial response (GPR) target for barium ferrite (BaFe) tape systems was studied. The shift in perpendicular magnetic recording technology in HDDs to systems employing single-pole-type (SPT) recording heads and media with a soft under layer (SUL) has been accompanied by a change in the read channel design, whereas current magnetic tape recording systems utilize a combination of a ring-type recording head with a single magnetic layer structured medium. Therefore, the read channel performance of current oriented BaFe particulate tape systems needs to be studied to best exploit the potential of this medium. Toward this end, DC-free, DC-full, and DC-suppressed targets were compared. The results show that assuming a GPRML detector with 16 or more states, a traditional DC-free target exhibits the best bit error rate performance for both longitudinally and perpendicularly oriented BaFe media, suggesting that the current read channel designed for longitudinally oriented media can also be utilized for BaFe particulate tape systems.

A new theoretical formulation based on BIBO (Bounded Input Bounded Output) operators is proposed for a general feedback amplifier circuit. Several fundamental theorems are derived in this letter. The main theorem provides a basis for a realization of an inverse of a feedback-branch linear or nonlinear BIBO operator satisfying the associative law.

Electromagnetic scattering and radiation in cylindrical electromagnetic bandgap (EBG) structure is analyzed. The radiated field from a line source placed inside the eccentric configuration of the cylindrical EBG structure and plane wave incident on the cylindrical EBG structure is numerically studied based on the method proposed by the authors in their early papers. Using the developed formulation, it is shown first time that when the cylindrical EBG is illuminated by plane wave of particular resonance frequencies, the field are strongly enhanced or shaded inside the cylindrical EBG structure and this effect depends on the angle of incidence of the plane waves. We give a deep physical insight into explanation of this phenomenon based on the Lorentz reciprocity relation for cylindrical structures.

This paper presents a unified treatment of the tracking analysis of adaptive filters with data normalization and error nonlinearities. The approach we develop is based on the celebrated energy-conservation framework, which investigates the energy flow through each iteration of an adaptive filter. Aside from deriving earlier results in a unified manner, we obtain new performance results for more general filters without restricting the regression data to a particular distribution. Simulations show good agreement with the theoretical findings.

Channel modeling, which is quite important for wireless communications system design, is difficult to be statistically generated from experimental results due to the expense and time constraints. However, with the computational electromagnetics method, the Electro-Magnetic (EM) field can be emulated and the corresponding EM wave propagation scenario can be analyzed. In this letter, the Finite Integration Technique (FIT) method is utilized to calculate the EM wave propagation of the onboard mobile communications in the cabin of an aircraft. With the simulation results, the channel model is established. Compared with Finite-Difference Time-Domain (FDTD), the proposed scheme is more accurate, which is promising to be used in the cabin channel modeling for onboard mobile system design.

This paper addresses the sensing-throughput tradeoff problem by using cluster-based cooperative spectrum sensing (CSS) schemes in two-layer hierarchical cognitive radio networks (CRNs) with soft data fusion. The problem is formulated as a combinatorial optimization problem involving both discrete and continuous variables. To simplify the solution, a reasonable weight fusion rule (WFR) is first optimized. Thus, the problem devolves into a constrained discrete optimization problem. In order to efficiently and effectively resolve this problem, a lexicographical approach is presented that solving two optimal subproblems consecutively. Moreover, for the first optimal subproblem, a closed-form solution is deduced, and an optimal clustering scheme (CS) is also presented for the second optimal subproblem. Numerical results show that the proposed approach achieves a satisfying performance and low complexity.