With the scaling of technology, nanoscale CMOS integrated circuits are becoming more sensitive to single event double node upsets induced by charge sharing. A novel highly robust hardened latch design is presented that is fully resilient to single event double node upsets and single node upsets. The proposed latch employs multiple redundant C-elements to form a dual interlocked structure in which the redundant C-elements can bring the affected nodes back to the correct states regardless of the energy of the striking particle. Detailed HSPICE results confirm that the proposed latch features complete resilience to double node upsets and achieves an improved trade-off in terms of robustness, area, delay and power in comparison with previous latches. Extensive Monte Carlo simulations validate the proposed latch features as less sensitive to process, supply voltage and temperature variations.

The purpose of DNA sequencing is to determine the order of nucleotides within a DNA molecule of target. The target DNA molecules are fragmented into short reads, which are short fixed-length subsequences composed of ‘A’, ‘C’, ‘G’ ‘T’, by next generation sequencing (NGS) machine. To reconstruct the target DNA from the short reads using a reference genome, which is a representative example of a species that was constructed in advance, it is necessary to determine their locations in the target DNA from where they have been extracted by aligning them onto the reference genome. This process is called short read mapping, and it is important to improve the performance of the short read mapping to realize fast DNA sequencing. We propose three types of FPGA acceleration methods based on hash table; (1) sorting and parallel comparison, (2) matching that allows one mutation to reduce the number of the candidates, (3) optimized hash function using variable masks. The first one reduces the number of accesses to off-chip memory to avoid the bottleneck by access latency. The second one enables to reduce the number of the candidates without degrading mapping sensitivity by allowing one mutation in the comparison. The last one reduces hash collisions using a table that was calculated from the reference genome in advance. We implemented the three methods on Xilinx Virtex-7 and evaluated them to show their effectiveness of them. In our experiments, our system achieves 20 fold of processing speed compared with BWA, which is one of the most popular mapping tools. Furthermore, we shows that the our system outperforms one of the fastest FPGA short read mapping systems.

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.

We propose a wideband reconfigurable circular-polarized single-port antenna to realize high-density linear integration for use in ground penetrating radars. We switch PIN diodes at a T-shaped probe to change its polarization. The forward- and reverse-biased probes work in cooperation to generate circular polarization. Experiments demonstrate the working bandwidths of 20.0% and 18.6% in the left- and right-hand polarization states, respectively, with 7.2 GHz center frequency. They are wider than those of conventional reconfigurable single-port circular-polarized antennas.

In a real-time system, tasks are required to be completed before their deadlines. Under normal workload conditions, a scheduler with a proper scheduling policy can make all the tasks meet their deadlines. However, in practical environment, system workload may vary widely. Once system workload becomes too heavy, so that there does not exist a feasible schedule can make all the tasks meet their deadlines, we say the system is overloaded under which some tasks will miss their deadlines. To alleviate the degrees of system performance degradation caused by the missed deadline tasks, the design of scheduling is crucial. Many design objectives can be considered. In this paper, we first focus on maximizing the total number of tasks that can be completed before their deadlines. A scheduling method based on satisfiability modulo theories (SMT) is proposed. In the method, the problem of scheduling is treated as a satisfiability problem. The key work is to formalize the satisfiability problem using first-order language. After the formalization, a SMT solver (e.g., Z3, Yices) is employed to solve this satisfiability problem. An optimal schedule can be generated based on the solution model returned by the SMT solver. The correctness of this method and the optimality of the generated schedule can be verified in a straightforward manner. The time efficiency of the proposed method is demonstrated through various simulations. Moreover, in the proposed SMT-based scheduling method, we define the scheduling constraints as system constraints and target constraints. This means if we want to design scheduling to achieve other objectives, only the target constraints need to be modified. To demonstrate this advantage, we adapt the SMT-based scheduling method to other design objectives: maximizing effective processor utilization and maximizing obtained values of completed tasks. Only very little changes are needed in the adaption procedure, which means the proposed SMT-based scheduling method is flexible and sufficiently general.

In this letter, a simple and robust synchronization algorithm for second generation terrestrial digital video broadcasting (DVB-T2) receivers is proposed. In the proposed detection scheme, the coarse symbol timing is estimated by decimating a correlation output to give a sharper peak timing detection metric. Such a design can improve the timing synchronization accuracy as well as enhance its robustness to frequency selective channels.

We propose a microphone array speech enhancement method that integrates spatial-cue-based source power spectral density (PSD) estimation and statistical speech model-based PSD estimation. The goal of this research was to clearly pick up target speech even in noisy environments such as crowded places, factories, and cars running at high speed. Beamforming with post-Wiener filtering is commonly used in many conventional studies on microphone-array noise reduction. For calculating a Wiener filter, speech/noise PSDs are essential, and they are estimated using spatial cues obtained from microphone observations. Assuming that the sound sources are sparse in the temporal-spatial domain, speech/noise PSDs may be estimated accurately. However, PSD estimation errors increase under circumstances beyond this assumption. In this study, we integrated speech models and PSD-estimation-in-beamspace method to correct speech/noise PSD estimation errors. The roughly estimated noise PSD was obtained frame-by-frame by analyzing spatial cues from array observations. By combining noise PSD with the statistical model of clean-speech, the relationships between the PSD of the observed signal and that of the target speech, hereafter called the observation model, could be described without pre-training. By exploiting Bayes' theorem, a Wiener filter is statistically generated from observation models. Experiments conducted to evaluate the proposed method showed that the signal-to-noise ratio and naturalness of the output speech signal were significantly better than that with conventional methods.

In this letter, we present a novel method for reconstructing continuous data field from scattered point data, which leads to a more characteristic visualization result by volume rendering. The gradient distribution of scattered point data is analyzed for local feature investigation via singular-value decomposition. A data-adaptive ellipsoidal shaped function is constructed as the penalty function to evaluate point weight coefficient in MLS approximation. The experimental results show that the proposed method can reduce the reconstruction error and get a visualization with better feature discrimination.

The increase in network access devices and demand for high quality of service (QoS) by the users have led to insufficient capacity for the network operators. Moreover, the existing control equipment and mechanisms are not flexible and agile enough for the dynamically changing environment of heterogeneous cellular networks (HetNets). This non-agile control plane is hard to scale with ever increasing traffic demand and has become the performance bottleneck. Furthermore, the new HetNet architecture requires tight coordination and cooperation for the densely deployed small cell base stations, particularly for interference mitigation and dynamic frequency reuse and sharing. These issues further complicate the existing control plane and can cause serious inefficiencies in terms of users' quality of experience and network performance. This article presents an SDN control framework for energy efficient downlink/uplink scheduling in HetNets. The framework decouples the control plane from data plane by means of a logically centralized controller with distributed agents implemented in separate entities of the network (users and base stations). The scheduling problem consists of three sub-problems: (i) user association, (ii) power control, (iii) resource allocation and (iv) interference mitigation. Moreover, these sub-problems are coupled and must be solved simultaneously. We formulate the DL/UL scheduling in HetNet as an optimization problem and use the Markov approximation framework to propose a distributed economical algorithm. Then, we divide the algorithm into three sub-routines for (i) user association, (ii) power control, (iii) resource allocation and (iv) interference mitigation. These sub-routines are then implemented on different agents of the SDN framework. We run extensive simulation to validate our proposal and finally, present the performance analysis.

In this paper, the differences in navigation information design, which is important for kiosk-type pedestrian navigation systems, were experimentally examined depending on presence or absence of carriable navigation information in order to acquire the knowledge to contribute design guidelines of kiosk-type pedestrian navigation systems. In particular, we used route complexity information calculated using a regression equation that contained multiple factors. In the absence of carriable navigation information, both the destination arrival rate and route deviation rate improved. Easy routes were designed as M (17 to 39 characters in Japanese), while complicated routes were denoted as L (40 or more characters in Japanese). On the contrary, in the presence of carriable navigation information, the user's memory load was found to be reduced by carrying the same navigation information as kiosk-type terminals. Thus, the reconsideration of kiosk-type pedestrian navigation systems design, e.g., the means of presenting navigation information, is required. For example, if the system attaches importance to a high destination arrival rate, L_Carrying without regard to route complexity is better. If the system attaching importance to the low route deviation rate, M_Carrying in the case of easy routes and L_Carrying in the case of complicated routes have been better. Consequently, this paper presents the differences in the designs of pedestrian navigation systems depending on whether carriable navigation information is absent or present.

Key fabrication technology for the Pt/TiO2-x/TiO2/TiO2+x/Pt nano-film memristor is investigated, including preparing platinum (Pt) electrodes and TiO2-x/TiO2/TiO2+x nano-films. The effect of oxygen flow rate and deposition rate during fabrication on O:Ti ratio of thin films is demonstrated. The fabricated nano-films with different oxygen concentration are validated by the analyzed results from X-ray photoelectron spectroscopy (XPS). The obtained memristor device shows the typical resistive switching behavior and nonvolatile memory effects. An analytical device model for Pt/TiO2-x/TiO2/TiO2+x/Pt nano-film memristor is developed based on the fundamental linear relationships between drift-diffusion velocity and the electric field, and boundary conditions are also incorporated in this model. This model is able to predict the relation between variables in the form of explicit formula, which is very critical in memristor-based circuit designs. The measurement results from real devices validate the proposed analytical device model. Some deviations of the model from the measured data are also analyzed and discussed.

Nowadays, vector map content is widely used in the areas of life, science and the military. Due to the fact that vector maps bring great value and that their production process is expensive, a large volume of vector map data is attacked, stolen and illegally distributed by pirates. Thus, vector map data must be encrypted before being stored and transmitted in order to ensure the access and to prevent illegal copying. This paper presents a novel perceptual encryption algorithm for ensuring the secured storage and transmission of vector map data. Polyline data of vector maps are extracted to interpolate a spline curve, which is represented by an interpolating vector, the curvature degree coefficients, and control points. The proposed algorithm is based on encrypting the control points of the spline curve in the frequency domain of discrete cosine transform. Control points are transformed and selectively encrypted in the frequency domain of discrete cosine transform. They are then used in an inverse interpolation to generate the encrypted vector map. Experimental results show that the entire vector map is altered after the encryption process, and the proposed algorithm is very effective for a large dataset of vector maps.

Image steganography is a technique of embedding secret message into a digital image to securely send the information. In contrast, steganalysis focuses on detecting the presence of secret messages hidden by steganography. The modern approach in steganalysis is based on supervised learning where the training set must include the steganographic and natural image features. But if a new method of steganography is proposed, and the detector still trained on existing methods will generally lead to the serious detection accuracy drop due to the mismatch between training and detecting steganographic method. In this paper, we just attempt to process unsupervised learning problem and propose a detection model called self-learning ensemble discriminant clustering (SEDC), which aims at taking full advantage of the statistical property of the natural and testing images to estimate the optimal projection vector. This method can adaptively select the most discriminative subspace and then use K-means clustering to generate the ultimate class labels. Experimental results on J-UNIWARD and nsF5 steganographic methods with three feature extraction methods such as CC-JRM, DCTR, GFR show that the proposed scheme can effectively classification better than blind speculation.

New volatile memory (e.g. Phase Change Memroy) presents fast access, large capacity, byte-addressable, and non-volatility features. These features will bring impacts on the design of current software system. It has become a hot research topic of how to manage it and provide what kind of interface for upper application to use it. This paper proposes FP-Heap. FP-Heap supports direct access to non-volatile memory through a persistent heap interface. With FP-Heap, traditional persistent object systems can benefit directly from the byte-persistency of non-volatile memory. FP-Heap extends current virtual memory manager (VMM) to manage non-volatile memory and maintain a persistent mapping relationship. Also, FP-Heap offers a lightweight transaction mechanism to support atomic update of persistent data, a simple namespace to facilitate data indexing, and a basic access control mechanism to support data sharing. Compared with previous work Mnemosyne, FP-Heap achieves higher performance by its customized VMM and optimized transaction mechanism.

In this paper, we examine the locality property of the original Fractional Repetition (FR) codes and propose two constructions for FR codes with better locality. For this, we first derive the capacity of the FR codes with locality 2, that is the maximum size of the file that can be stored. Construction 1 generates an FR code with repetition degree 2 and locality 2. This code is optimal in the sense of achieving the capacity we derived. Construction 2 generates an FR code with repetition degree 3 and locality 2 based on 4-regular graphs with girth g. This code is also optimal in the same sense.

This paper proposes a novel multiple chaos embedded gravitational search algorithm (MCGSA) that simultaneously utilizes multiple different chaotic maps with a manner of local search. The embedded chaotic local search can exploit a small region to refine solutions obtained by the canonical gravitational search algorithm (GSA) due to its inherent local exploitation ability. Meanwhile it also has a chance to explore a huge search space by taking advantages of the ergodicity of chaos. To fully utilize the dynamic properties of chaos, we propose three kinds of embedding strategies. The multiple chaotic maps are randomly, parallelly, or memory-selectively incorporated into GSA, respectively. To evaluate the effectiveness and efficiency of the proposed MCGSA, we compare it with GSA and twelve variants of chaotic GSA which use only a certain chaotic map on a set of 48 benchmark optimization functions. Experimental results show that MCGSA performs better than its competitors in terms of convergence speed and solution accuracy. In addition, statistical analysis based on Friedman test indicates that the parallelly embedding strategy is the most effective for improving the performance of GSA.

A 1.9GHz film bulk acoustic resonator (FBAR)-based low-phase-noise complementary cross-coupled voltage-controlled oscillator (VCO) is presented. The FBAR-VCO is designed and fabricated in 0.18µm CMOS process. The DC latch and the low frequency instability are resolved by employing the NMOS source coupling capacitor and the DC blocked cross-coupled pairs. Since no additional voltage headroom is required, the proposed FBAR-VCO can be operated at a low power supply voltage of 1.1V with a wide voltage swing of 0.9V. An effective phase noise optimization is realized by a reasonable trade-off between the output resistance and the trans-conductance of the cross-coupled pairs. The measured performance shows the proposed FBAR-VCO achieves a phase noise of -148dBc/Hz at 1MHz offset with a figure of merit (FoM) of -211.6dB.

This study introduces large-scale field experiments of VoiceTra, which is the world's first speech-to-speech multilingual translation application for smart phones. In the study, approximately 10 million input utterances were collected since the experiments commenced. The usage of collected data was analyzed and discussed. The study has several important contributions. First, it explains system configuration, communication protocol between clients and servers, and details of multilingual automatic speech recognition, multilingual machine translation, and multilingual speech synthesis subsystems. Second, it demonstrates the effects of mid-term system updates using collected data to improve an acoustic model, a language model, and a dictionary. Third, it analyzes system usage.

There are increasing demands for improved analysis of multimodal data that consist of multiple representations, such as multilingual documents and text-annotated images. One promising approach for analyzing such multimodal data is latent topic models. In this paper, we propose conditionally independent generalized relational topic models (CI-gRTM) for predicting unknown relations across different multiple representations of multimodal data. We developed CI-gRTM as a multimodal extension of discriminative relational topic models called generalized relational topic models (gRTM). We demonstrated through experiments with multilingual documents that CI-gRTM can more effectively predict both multilingual representations and relations between two different language representations compared with several state-of-the-art baseline models that enable to predict either multilingual representations or unimodal relations.

In Twitter-like services, countless messages are being posted in real-time every second all around the world. Timely knowledge about what kinds of information are diffusing in social media is quite important. For example, in emergency situations such as earthquakes, users provide instant information on their situation through social media. The collective intelligence of social media is useful as a means of information detection complementary to conventional observation. We have developed a system for monitoring and analyzing information diffusion data in real-time by tracking retweeted tweets. A tweet retweeted by many users indicates that they find the content interesting and impactful. Analysts who use this system can find tweets retweeted by many users and identify the key people who are retweeted frequently by many users or who have retweeted tweets about particular topics. However, bursting situations occur when thousands of social media messages are suddenly posted simultaneously, and the lack of machine resources to handle such situations lowers the system's query performance. Since our system is designed to be used interactively in real-time by many analysts, waiting more than one second for a query results is simply not acceptable. To maintain an acceptable query performance, we propose a capacity control method for filtering incoming tweets using extra attribute information from tweets themselves. Conventionally, there is a trade-off between the query performance and the accuracy of the analysis results. We show that the query performance is improved by our proposed method and that our method is better than the existing methods in terms of maintaining query accuracy.