A 50-Gb/s optical transmitter, consisting of a 25-Gb/s-class lens-integrated DFB-LD (with -3-dB bandwidth of 20GHz) and a LD-driver chip based on 0.18-µm SiGe BiCMOS technology for inter and intra-rack transmissions, was developed and tested. The DFB-LD and LD driver chip are flip-chip mounted on an alumina ceramic package. To suppress inter-symbol interference due to a shortage of the DFB-LD bandwidth and signal reflection between the DFB-LD and the package, the LD driver includes a two-tap pre-emphasis circuit and a high-speed termination circuit. Operating at a data rate of 50Gb/s, the optical transmitter enhances LD bandwidth and demonstrated an eye opening with jitter margin of 0.23UI. Power efficiency of the optical transmitter at a data rate of 50Gb/s is 16.2mW/Gb/s.

The scan segmentation method is an efficient solution to deal with the test power problem; However, the use of multiple capture cycles may cause capture violations, thereby leading to fault coverage loss. This issue is much more severe in at-speed testing. In this paper, two scan partition schemes based on complex networks clustering ara proposed to minimize the capture violations without increasing test-data volume and extra area overhead. In the partition process, we use a more accurate notion, spoiled nodes, instead of violation edges to analyse the dependency of flip-flops (ffs), and we use the shortest-path betweenness (SPB) method and the Laplacian-based graph partition method to find the best combination of these flip-flops. Beyond that, the proposed methods can use any given power-unaware set of patterns to test circuits, reducing both shift and capture power in at-speed testing. Extensive experiments have been performed on reference circuit ISCAS89 and IWLS2005 to verify the effectiveness of the proposed methods.

This paper proposes a method of incrementally constructing semantic representations. Our method is based on Steedman's Combinatory Categorial Grammar (CCG), which has a transparent correspondence between syntax and semantics. In our method, a derivation for a sentence is constructed in an incremental fashion and the corresponding semantic representation is derived synchronously. Our method uses normal form CCG derivation. This is the difference between our approach and previous ones. Previous approaches use most left-branching derivation called incremental derivation, but they cannot process coordinate structures incrementally. Our method overcomes this problem.

The automation of traceability links or traceability matrices is important to many software development paradigms. In turn, the efficiency and effectiveness of the recovery of traceability links in the distributed software development is becoming increasingly vital due to complexity of project developments, as this include continuous change in requirements, geographically dispersed project teams, and the complexity of managing the elements of a project - time, money, scope, and people. Therefore, the traceability links among the requirements artifacts, which fulfill business objectives, is also critical to reduce the risk and ensures project‘s success. This paper proposes Autonomous Decentralized Semantic based Traceability Link Recovery (AD-STLR) architecture. According to best of our knowledge this is the first architectural approach that uses an autonomous decentralized concept, DBpedia knowledge-base, Babelnet 2.5 multilingual dictionary and semantic network, for finding similarity among different project artifacts and the automation of traceability links recovery.

One problem in the use of wireless Content Centric Networks (CCNs) is the need for substantial overhead to achieve reliability in content delivery due to the requirement for a request packet per each data packet transmission. This paper introduces a novel protocol to reduce overhead and achieve reliability. The protocol allows an interest packet to request multiple data packets and an intermediate node, rather than the provider, to send the data packet. Simulation results show that the proposed protocol improves the performance of wireless CCN.

Recently, Doppler radars have been used in various applications from the detection and the classification of indoor human activities to the detection of airplanes. To improve both the degrees of freedom (DOF) and the estimation accuracy of the direction-of-arrival (DOA) of targets, multiple-input multiple-output (MIMO) radar has received much attention in recent years. The temporal spatial virtual array based on Doppler shift of a moving target has been one of methods to improve DOA estimation accuracy. However, the DOA estimation accuracy based on the method depends on the velocity and the direction of the target on which we focus. Also, the temporal spatial virtual array should be generated based on the information of the single target. Thus, it is difficult to implement the method if there are multiple targets. In this paper, we propose a new method that provides high accuracy of DOA estimation by using the temporal spatial virtual array without dependence on the velocity, the direction and the number of existing targets. We demonstrate the DOA estimation accuracy and the effectiveness of the proposed method via simulations.

To help elderly and physically disabled people to become self-reliant in daily life such as at home or a health clinic, we have developed a network-type brain machine interface (BMI) system called “network BMI” to control real-world actuators like wheelchairs based on human intention measured by a portable brain measurement system. In this paper, we introduce the technologies for achieving the network BMI system to support activities of daily living.

In this letter, we present a spectrally efficient multicast method which enables a transmitter to simultaneously transmit multiple multicast streams without any interference among multicast groups. By using unique combiners at receivers with multiple antennas within each multicast group, the proposed method simplifies multiple channels between the transmitter and the receivers to an equivalent channel. In addition, we establish the sufficient condition for the system configuration which should be satisfied for the channel simplification and provide a combiner design technique for the receivers. To remove interference among multicast groups, the precoder for the transmitter is designed by utilizing the equivalent channels. By exploiting time resources efficiently, the channel simplification (CS) based method achieves a higher sum rate than the time division multiplexing (TDM) based method, which the existing multicast techniques fundamentally employ, at high signal-to-noise ratio (SNR) regime. Furthermore, we present a multicast method combining the CS based method with the TDM based method to utilize the benefits of both methods. Simulation results successfully demonstrate that the combined multicast method obtains a better sum rate performance at overall SNR regime.

In this letter, fast intra mode decision algorithms for HEVC Screen Contents Coding (SCC) are proposed. HEVC SCC has been developed to efficiently code mixed contents consisting of natural video, graphics, and texts. Comparing to HEVC version 1, the SCC encoding complexity significantly increases due to the newly added intra block copy mode. To reduce the heavy encoding complexity, the evaluation orders of multiple intra modes are rearranged and several early termination schemes based on intermediate coding information are developed. Based on our evaluation, it is found that the proposed method can achieve encoding time reduction of 13∼30% with marginal coding gain or loss, compared with HEVC SCC test model 2.0 in all intra (AI) case.

In densely deployed wireless local area network (WLAN) environments, the arbitrary deployment of WLAN access points (APs) can cause serious cell overlaps among APs. In such situations, the ability to realize adaptable coverage using transmission power control (TPC) is effective for improving the area spectral efficiency. Meanwhile, it should be guaranteed that no coverage holes occur and that connectivity between APs and wireless stations (STAs) is maintained. In this paper, the self-organization of coverage domains of APs using TPC is proposed. The proposed technique reduces the incidence of coverage overlaps without generating area coverage holes. To detect coverage holes, STAs and/or APs are used as sensors that inform each AP of whether or not the points at which they exist are covered by the APs. However, there is a problem with this approach in that when the density of STAs is not sufficiently large, the occurrence of area coverage holes is inevitable because the points at which the sensors do not exist are not guaranteed to be covered by APs. This paper overcomes the problem by focusing APs that belong to network's outer boundary (boundary APs) and prohibiting the APs from operating at low transmission power levels, the idea being that the coverage domains of such APs always include the region covered by only those APs. The boundary APs are determined by performing Delaunay triangulation of the set of points at which all APs exist. Simulation results confirm the effectiveness of the proposed TPC scheme in terms of its ability to reduce the total overlap area while avoiding the occurrence of area coverage holes.

This paper proposes a blind, inaudible, robust digital-audio watermarking scheme based on singular-spectrum analysis, which relates to watermarking techniques based on singular value decomposition. We decompose a host signal into its oscillatory components and modify amplitudes of some of those components with respect to a watermark bit and embedding rule. To improve the sound quality of a watermarked signal and still maintain robustness, differential evolution is introduced to find optimal parameters of the proposed scheme. Test results show that, although a trade-off between inaudibility and robustness still persists, the difference in sound quality between the original and the watermarked one is considerably smaller. This improved scheme is robust against many attacks, such as MP3 and MP4 compression, and band-pass filtering. However, there is a drawback, i.e., some music-dependent parameters need to be shared between embedding and extraction processes. To overcome this drawback, we propose a method for automatic parameter estimation. By incorporating the estimation method into the framework, those parameters need not to be shared, and the test results show that it can blindly decode watermark bits with an accuracy of 99.99%. This paper not only proposes a new technique and scheme but also discusses the singular value and its physical interpretation.

In this paper, we propose an overloaded multiple-input multiple-output (MIMO) signal detection scheme with slab decoding and lattice reduction (LR). The proposed scheme firstly splits the transmitted signal vector into two parts, the post-voting vector composed of the same number of signal elements as that of receive antennas, and the pre-voting vector composed of the remaining elements. Secondly, it reduces the candidates of the pre-voting vector using slab decoding and determines the post-voting vectors for each pre-voting vector candidate by LR-aided minimum mean square error (MMSE)-successive interference cancellation (SIC) detection. From the performance analysis of the proposed scheme, we derive an upper bound of the error probability and show that it can achieve the full diversity order. Simulation results show that the proposed scheme can achieve almost the same performance as the optimal ML detection while reducing the required computational complexity.

Information floating delivers information to mobile nodes in specific areas without meaningless spreading of information by permitting mobile nodes to directly transfer information to other nodes by wireless links in designated areas called transmittable areas. In this paper, we assume that mobile nodes change direction at intersections after receiving such information as warnings and local advertisements and that an information source remains in some place away from the transmittable area and continuously broadcasts information. We analyze performance of information floating under these assumptions to explore effects of the behavior changes of mobile nodes, decision deadline of the behavior change, and existence of a fixed source on information floating. We theoretically analyze the probability that a node cannot receive information and also derive the size of each transmittable area so that this probability is close to desired values.

A self-adaptive scaled min-sum algorithm for LDPC decoding based on the difference between the first two minima of the check node messages (Δmin) is proposed. Δmin is utilized for adjusting the scaling factor of the check node messages, and simulation results show that the proposed algorithm improves the error correcting performance compared to existing algorithms.

We reported a secure scan design approach using shift register equivalents (SR-equivalents, for short) that are functionally equivalent but not structurally equivalent to shift registers [10 and also introduced generalized shift registers (GSRs, for short) to apply them to secure scan design [11]-[13]. In this paper, we combine both concepts of SR-equivalents and GSRs and consider the synthesis problem of SR-equivalent GSRs, i.e., how to modify a given GSR to an SR-equivalent GSR. We also consider the enumeration problem of SR-equivalent GFSRs, i.e., the cardinality of the class of SR-equivalent GSRs to clarify the security level of the secure scan architecture.

Forming Business Continuity Planning (BCP) is recognized as a significant counter-measure against future large-scale disasters by private enterprises after the 2011 Great East Japan Earthquake more than before. Based on a questionnaire survey, this paper reports business recovery conditions of private enterprises in Miyagi Prefecture affected by the disaster. Analyzing the results of questionnaire, it suggests some important points: (1) estimation of long-term internal/external factors that influence business continuity, (2) development of concrete pre-disaster framework, (3) multi-media-based advertising strategy, and (4) re-allocation of resources.

It is qualitatively considered that emergency information processing by using UTM grids is effective in generating COP (Common Operational Pictures). Here, we conducted a numerical evaluation based on emergency information-processing training to examine the efficiency of the use of UTM grid maps by staff at the Tagajo City Government office. The results of the demonstration experiment were as follows: 1) The time required for information propagation and mapping with UTM coordinates was less than that with address text consisting of area name and block number. 2) There was no measurable difference in subjective estimates of the training performance of participants with or without the use of UTM grids. 3) Fear of real emergency responses decreased among training participants using UTM grids. 4) Many of the negative free answers on a questionnaire evaluation of participants involved requests regarding the reliability and operability of UTM tools.

Estimation of the time delay of arrival (TDOA) problem is important to acoustic source localization. The TDOA estimation problem is defined as finding the relative delay between several microphone signals for the direct sound. To estimate TDOA, the generalized cross-correlation (GCC) method is the most frequently used, but it has a disadvantage in terms of reverberant environments. In order to overcome this problem, the adaptive eigenvalue decomposition (AED) method has been developed, which estimates the room transfer function and finds the direct-path delay. However, the algorithm does not take into account the fact that the room transfer function is a sparse channel, and so sometimes the estimated transfer function is too dense, resulting in failure to exact direct-path and delay. In this paper, an enhanced AED algorithm that makes use of a proportionate step-size control and a direct-path constraint is proposed instead of a constant step size and the L2-norm constraint. The simulation results show that the proposed algorithm has enhanced performance as compared to both the conventional AED method and the phase-transform (PHAT) algorithm.

Logistic regression is a powerful machine learning tool to classify data. When dealing with sensitive or private data, cares are necessary. In this paper, we propose a secure system for privacy-protecting both the training and predicting data in logistic regression via homomorphic encryption. Perhaps surprisingly, despite the non-polynomial tasks of training and predicting in logistic regression, we show that only additively homomorphic encryption is needed to build our system. Indeed, we instantiate our system with Paillier, LWE-based, and ring-LWE-based encryption schemes, highlighting the merits and demerits of each instantiation. Besides examining the costs of computation and communication, we carefully test our system over real datasets to demonstrate its utility.

Energy-efficient resource allocation is considered in sensing-based spectrum sharing for cooperative cognitive radio networks (CCRNs). The secondary user first listens to the spectrum allocated to the primary user (PU) to detect the PU state and then initiates data transmission with two power levels based on the sensing decision (e.g., idle or busy). Under this model, the optimization problem of maximizing energy efficiency (EE) is formulated over the transmission power and sensing time subject to some practical limitations, such as the individual power constraint for secondary source and relay, the quality of service (QoS) for the secondary system, and effective protection for the PU. Given the complexity of this problem, two simplified versions (i.e., perfect and imperfect sensing cases) are studied in this paper. We transform the considered problem in fractional form into an equivalent optimization problem in subtractive form. Then, for perfect sensing, the Lagrange dual decomposition and iterative algorithm are applied to acquire the optimal power allocation policy; for imperfect sensing, an exhaustive search and iterative algorithm are proposed to obtain the optimal sensing time and corresponding power allocation strategy. Finally, numerical results show that the energy-efficient design greatly improves EE compared with the conventional spectrum-efficient design.