We propose a home base-aware store-carry-forward routing scheme using location-dependent utilities of nodes, which adopts different message forwarding strategies depending on location where nodes encounter. Our routing scheme first attempts to deliver messages to its home base, the area with the highest potential for the presence of the destination node in the near future. Once a message copy reaches its home base, message dissemination is limited within the home base, and nodes with message copies wait for encountering the destination node. To realize our routing scheme, we use two different utilities of nodes depending on location: Outside the home base of a message, nodes approaching to the home base have high utility values, while within the home base, nodes staying the home base have high utility values. By using these utilities properly, nodes with message copies will catch the destination node “by ambush” in the home base of the destination node. Through simulation experiments, we demonstrate the effectiveness of our routing scheme.

We propose a synthesis and automatic layout method for mixed-signal circuits with high regularity. As the first step of this research, a resistive digital-to-analog converter (RDAC) is presented. With a size calculation routine, the area of this RDAC is minimized while satisfying the required matching precision without any optimization loops. We propose to partition the design into slices comprising of both analog and digital cells. These cells are programmed to be synthesized as similar as custom P-Cells based on the calculation above, and automatically laid out to form one slice cell. To synthesize digital circuits, without using digital standard cell library, we propose a versatile unit digital block consisting of 8 transistors. With one or several blocks, the transistors' interconnections are programmed in the units to realize various logic gates. By using this block, the slice shapes are aligned so that the layout space in between the slices are minimized. The proposed mixed-signal slice-based partition facilitates the place-and-route of the whole RDAC. The post-layout simulation shows that the generated 9-bit RDAC achieves 1GHz sampling frequency, -0.11/0.09 and -0.30/0.75 DNL and INL, respectively, 3.57mW power consumption, and 0.0038mm2 active area.

We investigate the coding scheme and error probability in information transmission over continuous-time additive Gaussian noise channels with feedback. As is known, the error probability can be substantially reduced by using feedback, namely, under the average power constraint, the error probability may decrease more rapidly than the exponential of any order. Recently Gallager and Nakibolu proposed, for discrete-time additive white Gaussian noise channels, a feedback coding scheme such that the resulting error probability Pe(N) at time N decreases with an exponential order αN which is linearly increasing with N. The multiple-exponential decay of the error probability has been studied mostly for white Gaussian channels, so far. In this paper, we treat continuous-time Gaussian channels, where the Gaussian noise processes are not necessarily white nor stationary. The aim is to prove a stronger result on the multiple-exponential decay of the error probability. More precisely, for any positive constant α, there exists a feedback coding scheme such that the resulting error probability Pe(T) at time T decreases more rapidly than the exponential of order αT as T→∞.

In this paper, we propose a novel placement algorithm for mixed-grained reconfigurable architectures (MGRAs). MGRA consists of coarse-grained and fine-grained clusters, in order to implement a combined digital systems of high-speed data paths with multi-bit operands and random logic circuits for state machines and bit-wise operations. For accelerating simulated annealing based FPGA placement algorithm, range limiter has been proposed to control the distance of two blocks to be interchanged. However, it is not applicable to MGRAs due to the heterogeneous structure of MGRAs. Proposed range limiter using connection bounding box effectively keeps the size of range limiter to encourage moves across fine-grain blocks in non-adjacent clusters. From experimental results, the proposed method achieved 47.8% reduction of cost in the best case compared with conventional methods.

Faster-than-Nyquist (FTN) signaling is investigated for quasi-static flat fading massive multiple-input multiple-output (MIMO) systems. In FTN signaling, pulse trains are sent at a symbol rate higher than the Nyquist rate to increase the transmission rate. As a result, inter-symbol interference occurs inevitably for flat fading channels. This paper assesses the information-theoretically achievable rate of MIMO FTN signaling based on the optimum joint equalization and multiuser detection. The replica method developed in statistical physics is used to evaluate the achievable rate in the large-system limit, where the dimensions of input and output signals tend to infinity at the same rate. An analytical expression of the achievable rate is derived for general modulation schemes in the large-system limit. It is shown that FTN signaling does not improve the channel capacity of massive MIMO systems, and that FTN signaling with quadrature phase-shift keying achieves the channel capacity for all signal-to-noise ratios as the symbol period tends to zero.

Synthetic over-sampling is a well-known method to solve class imbalance by modifying class distribution and generating synthetic samples. A large number of synthetic over-sampling techniques have been proposed; however, most of them suffer from the over-generalization problem whereby synthetic minority class samples are generated into the majority class region. Learning from an over-generalized dataset, a classifier could misclassify a majority class member as belonging to a minority class. In this paper a method called TRIM is proposed to overcome the over-generalization problem. The idea is to identify minority class regions that compromise between generalization and overfitting. TRIM identifies all the minority class regions in the form of clusters. Then, it merges a large number of small minority class clusters into more generalized clusters. To enhance the generalization ability, a cluster connection step is proposed to avoid over-generalization toward the majority class while increasing generalization of the minority class. As a result, the classifier is able to correctly classify more minority class samples while maintaining its precision. Compared with SMOTE and extended versions such as Borderline-SMOTE, experimental results show that TRIM exhibits significant performance improvement in terms of F-measure and AUC. TRIM can be used as a pre-processing step for synthetic over-sampling methods such as SMOTE and its extended versions.

The key escrow problem and high computational cost are the two major problems that hinder the wider adoption of hierarchical identity-based signature (HIBS) scheme. HIBS schemes with either escrow-free (EF) or online/offline (OO) model have been proved secure in our previous work. However, there is no much EF or OO scheme that has been evaluated experimentally. In this letter, several EF/OO HIBS schemes are considered. We study the algorithmic complexity of the schemes both theoretically and experimentally. Scheme performance and practicability of EF and OO models are discussed.

Current signature-based antivirus solutions have three limitations such as the large volume of signature database, privacy preservation, and computation overheads of signature matching. In this paper, we propose LigeroAV, a light-weight, performance-enhanced antivirus, suitable for pervasive environments such as mobile phones. LigeroAV focuses on detecting MD5 signatures which are more than 90% of signatures. LigeroAV offloads matching computation in the cloud server with up-to-dated signature database while preserving privacy level using the Bloom filter.

This paper presents a novel non-native speech synthesis technique that preserves the individuality of a non-native speaker. Cross-lingual speech synthesis based on voice conversion or Hidden Markov Model (HMM)-based speech synthesis is a technique to synthesize foreign language speech using a target speaker's natural speech uttered in his/her mother tongue. Although the technique holds promise to improve a wide variety of applications, it tends to cause degradation of target speaker's individuality in synthetic speech compared to intra-lingual speech synthesis. This paper proposes a new approach to speech synthesis that preserves speaker individuality by using non-native speech spoken by the target speaker. Although the use of non-native speech makes it possible to preserve the speaker individuality in the synthesized target speech, naturalness is significantly degraded as the synthesized speech waveform is directly affected by unnatural prosody and pronunciation often caused by differences in the linguistic systems of the source and target languages. To improve naturalness while preserving speaker individuality, we propose (1) a prosody correction method based on model adaptation, and (2) a phonetic correction method based on spectrum replacement for unvoiced consonants. The experimental results using English speech uttered by native Japanese speakers demonstrate that (1) the proposed methods are capable of significantly improving naturalness while preserving the speaker individuality in synthetic speech, and (2) the proposed methods also improve intelligibility as confirmed by a dictation test.

This paper proposes a low power single-ended successive approximation register (SAR) analog-to-digital converter (ADC) to replace the only analog active circuit, the comparator, with a digital circuit, which is an inverter-based comparator. The replacement helps possible design automation. The inverter threshold voltage variation impact is minimal because an SAR ADC has only one comparator, and many applications are either insensitive to the resulting ADC offset or easily corrected digitally. The proposed resetting approach mitigates leakage when the input is close to the threshold voltage. As an intrinsic headroom-free, and thus low-rail-voltage, friendly structure, an inverter-based comparator also occupies a small area. Furthermore, an 11-bit ADC was designed and manufactured through a 0.35-µm CMOS process by adopting a low-power switching procedure. The ADC achieves an FOM of 181fJ/Conv.-step at a 25kS/s sampling rate when the supply voltage VDD is 1.2V.

The privacy of users' data has become a big issue for cloud service. This research focuses on image cloud database and the function of similarity search. To enhance security for such database, we propose a framework of privacy-enhanced search scheme, while all the images in the database are encrypted, and similarity image search is still supported.

Many distributed systems use a replication mechanism for reliability and availability. On the other hand, application developers have to consider minimum consistency requirement for each application. Therefore, a replication protocol that supports multiple consistency models is required. Multi-Consistency Data Replication (McRep) is a proxy-based replication protocol and can support multiple consistency models. However, McRep has a potential problem in that a replicator relaying all request and reply messages between clients and replicas can be a performance bottleneck and a Single-Point-of-Failure (SPoF). In this paper, we introduce the multi-consistency support mechanism of McRep to a combined state-machine and deferred-update replication protocol to eliminate the performance bottleneck and SPoF. The state-machine and deferred-update protocols are well-established approaches for fault-tolerant data management systems. But each method can ensure only a specific consistency model. Thus, we adaptively select a replication method from the two replication bases. In our protocol, the functionality of the McRep's replicator is realized by clients and replicas. Each replica has new roles in serialization of all transactions and managing all views of the database, and each client has a new role in managing status of its transactions. We have implemented and evaluated the proposed protocol and compared to McRep. The evaluation results show that the proposed protocol achieved comparable throughput of transactions to McRep. Especially the proposed protocol improved the throughput up to 16% at a read-heavy workload in One-Copy. Finally, we demonstrated the proposed failover mechanism. As a result, a failure of a leader replica did not affect continuity of the entire replication system unlike McRep.

Since digital ICs are often designed and fabricated by third parties at any phases today, we must eliminate risks that malicious attackers may implement Hardware Trojans (HTs) on them. In particular, they can easily insert HTs during design phase. This paper proposes an HT rank which is a new quantitative analysis criterion against HTs at gate-level netlists. We have carefully analyzed all the gate-level netlists in Trust-HUB benchmark suite and found out several Trojan net features in them. Then we design the three types of Trojan points: feature point, count point, and location point. By assigning these points to every net and summing up them, we have the maximum Trojan point in a gate-level netlist. This point gives our HT rank. The HT rank can be calculated just by net features and we do not perform any logic simulation nor random test. When all the gate-level netlists in Trust-HUB, ISCAS85, ISCAS89 and ITC99 benchmark suites as well as several OpenCores designs, HT-free and HT-inserted AES netlists are ranked by our HT rank, we can completely distinguish HT-inserted ones (which HT rank is ten or more) from HT-free ones (which HT rank is nine or less). The HT rank is the world-first quantitative criterion which distinguishes HT-inserted netlists from HT-free ones in all the gate-level netlists in Trust-HUB, ISCAS85, ISCAS89, and ITC99.

In order to realize high-yield speckle modulation, we developed a novel spatial light modulator using zinc oxide single crystal doped with nitrogen ions. The distribution of dopants was optimized to induce characteristic optical functions by applying an annealing method developed by us. The device is driven by a current in the in-plane direction, which induces magnetic fields. These fields strongly interact with the doped material, and the spatial distribution of the refractive index is correspondingly modulated via external control. Using this device, we experimentally demonstrated speckle modulation, and we discuss the quantitative superiority of our approach.

In this paper, a morpheme-based weighting and its integration method are proposed as a smoothing method to alleviate the data sparseness in Chinese-Mongolian statistical machine translation (SMT). Besides, we present source-side reordering as the pre-processing model to verify the extensibility of our method. Experi-mental results show that the morpheme-based weighting can substantially improve the translation quality.

In this paper, we introduce a fully automatic approach to construct action datasets from noisy Web video search results. The idea is based on combining cluster structure analysis and density-based outlier detection. For a specific action concept, first, we download its Web top search videos and segment them into video shots. We then organize these shots into subsets using density-based hierarchy clustering. For each set, we rank its shots by their outlier degrees which are determined as their isolatedness with respect to their surroundings. Finally, we collect high ranked shots as training data for the action concept. We demonstrate that with action models trained by our data, we can obtain promising precision rates in the task of action classification while offering the advantage of fully automatic, scalable learning. Experiment results on UCF11, a challenging action dataset, show the effectiveness of our method.

We propose an exponent-based partitioning broadcast protocol (EPBP) to promise the prompt dissemination of emergency message (EM) in vehicular networks. EPBP divides the communication range into segments with different widths iteratively. The width varies corresponding to the exponential curve. The design makes the farther no-empty segment thinner, as a result of which the collision rate of candidates' contention for the relay node decreases and the one-hop message progress increases efficiently. In addition, we adjust the interval of back-off timers to avoid the spurious forwarding problem, and develop more accurate analytical models for the performance. Our simulation verifies these models and show a significant increase of EPBP compared with the state-of-the-art protocols. EM dissemination speed can be improved as 55.94% faster in dense vehicle networks, and packet delivery ratio has risen to higher than 99.99%.

This paper proposes statistical analysis of phase-only correlation functions with phase-spectrum differences following wrapped distributions. We first assume phase-spectrum differences between two signals to be random variables following a linear distribution. Next, based on directional statistics, we convert the linear distribution into a wrapped distribution by wrapping the linear distribution around the circumference of the unit circle. Finally, we derive general expressions of the expectation and variance of the POC functions with phase-spectrum differences following wrapped distributions. We obtain exactly the same expressions between a linear distribution and its corresponding wrapped distribution.

Two new authenticated key agreement protocols in the certificateless setting are presented in this paper. Both are proved secure in the extended Canetti-Krawczyk model, under the BDH assumption. The first one is more efficient than the Lippold et al.'s (LBG) protocol, and is proved secure in the same security model. The second protocol is proved secure under the Swanson et al.'s security model, a weaker model. As far as we know, our second proposed protocol is the first one proved secure in the Swanson et al.'s security model. If no pre-computations are done, the first protocol is about 26% faster than LBG, and the second protocol is about 49% faster than LBG, and about 31% faster than the first one. If pre-computations of some operations are done, our two protocols remain faster.

This paper presents a weighted diversity combining technique for the cyclostationarity detection based spectrum sensing of orthogonal frequency division multiplexing signals in cognitive radio. In cognitive radio systems, secondary users must detect the desired signal in an extremely low signal-to-noise ratio (SNR) environment. In such an environment, multiple antenna techniques (space diversity) such as maximum ratio combining are not effective because the energy of the target signal is also extremely weak, and it is difficult to synchronize some received signals. The cyclic autocorrelation function (CAF) is used for traditional cyclostationarity detection based spectrum sensing. In the presented technique, the CAFs of the received signals are combined, while the received signals themselves are combined with general space diversity techniques. In this paper, the value of the CAF at peak and non-peak cyclic frequencies are computed, and we attempt to improve the sensing performance by using different weights for each CAF value. The results were compared with those from conventional methods and showed that the presented technique can improve the spectrum sensing performance.