Optical circuits using nanophotonic devices attract significant interest due to its ultra-high speed operation. As a consequence, the synthesis methods for the optical circuits also attract increasing attention. However, existing methods for synthesizing optical circuits mostly rely on straight-forward mappings from established data structures such as Binary Decision Diagram (BDD). The strategy of simply mapping a BDD to an optical circuit sometimes results in an explosion of size and involves significant power losses in branches and optical devices. To address these issues, this paper proposes a method for reducing the size of BDD-based optical logic circuits exploiting wavelength division multiplexing (WDM). The paper also proposes a method for reducing the number of branches in a BDD-based circuit, which reduces the power dissipation in laser sources. Experimental results obtained using a partial product accumulation circuit used in a 4-bit parallel multiplier demonstrates significant advantages of our method over existing approaches in terms of area and power consumption.

We have proposed a generic architecture that can integrate the aspects of confidentiality and integrity into the A/D conversion framework. A conceptual account of the development of the proposed architecture is presented. Using the principle of this architecture we have presented a CMOS circuit design to facilitate a fully integrated Authenticated-Encrypted ADC (AE-ADC). We have implemented and demonstrated a partial 8-bit ADC Analog Front End of this proposed circuit in 0.18µm CMOS with an ENOB of 7.64 bits.

This paper constructs packet-oriented erasure correcting codes and their systematic forms for the distributed storage systems. The proposed codes are encoded by exclusive OR and bit-level shift operation. By the shift operation, the encoded packets are slightly longer than the source packets. This paper evaluates the extra length of the encoded packets, called overhead, and shows that the proposed codes have smaller overheads than the zigzag decodable codes, which are existing codes using bit-level shift operation and exclusive OR.

In this paper, we consider a source coding with side information partially used at the decoder through a codeword. We assume that there exists a relative delay (or gap) of the correlation between the source sequence and side information. We also assume that the delay is unknown but the maximum of possible delays is known to two encoders and the decoder, where we allow the maximum of delays to change by the block length. In this source coding, we give an inner bound and an outer bound on the achievable rate region, where the achievable rate region is the set of rate pairs of encoders such that the decoding error probability vanishes as the block length tends to infinity. Furthermore, we clarify that the inner bound coincides with the outer bound when the maximum of delays for the block length converges to a constant.

In this paper the quality of adaptive bit rate video streaming is investigated and two state-of-the-art models, i.e., the NTT audiovisual quality-estimation and ITU-T P.1203 models, are considered. This paper shows how these models can be applied to new conditions, e.g., 4K ultra high definition (4K-UHD) videos encoded using H.265, considering that they were originally designed and trained for HD videos encoded with H.264. Six subjective evaluations involving up to 192 participants and a large variety of test conditions, e.g., durations from 10sec to 3min, coding-quality variation, and stalling events, were conducted on both TV and mobile devices. Using the subjective data, this paper addresses how models and coefficients can be transferred to new conditions. A comparison between state-of-the-art models is conducted, showing the performance of transferred and retrained models. It is found that other video-quality estimation models, such as VMAF, can be used as input of the NTT and ITU-T P.1203 long-term pooling modules, allowing these other video-quality-estimation models to support the specificities of adaptive bit-rate-streaming scenarios. Finally, all retrained coefficients are detailed in this paper allowing future work to directly reuse the results of this study.

A novel matrix completion ESPRIT (MC-ESPRIT) algorithm is proposed to estimate the direction of arrival (DOA) with nonuniform linear arrays (NLA). By exploiting the matrix completion theory and the characters of Hankel matrix, the received data matrix of an NLA is tranformed into a two-fold Hankel matrix, which is a treatable for matrix completion. Then the decision variable can be reconstructed by the inexact augmented Lagrange multiplier method. This approach yields a completed data matrix, which is the same as the data matrix of uniform linear array (ULA). Thus the ESPRIT-type algorithm can be used to estimate the DOA. The MC-ESPRIT could resolve more signals than the MUSIC-type algorithms with NLA. Furthermore, the proposed algorithm does not need to divide the field of view of the array compared to the existing virtual interpolated array ESPRIT (VIA-ESPRIT). Simulation results confirm the effectiveness of MC-ESPRIT.

This paper proposes a secure distributed transmission method that establishes multiple transmission routes in space to a destination. In the method, the transmitted information is divided into pieces of information by a secret-sharing method, and the generated pieces are separately transmitted to the destination through different transmission routes using individually-controlled antenna directivities. As the secret-sharing method can divide the transmitted information into pieces in such a manner that nothing about the original information is revealed unless all the divided pieces are obtained, the secrecy of the transmitted information is greatly improved from an information-theoretic basis. However, one problem is that it does not perform well in the vicinity around the receiver. This is due to the characteristics of distributed transmission that all distributed pieces of information must eventually gather at the destination; an eavesdropper can obtain the necessary pieces to reconstruct the original information. Then, this paper expands the distributed transmission method into a two-way communication scheme. By adopting the distributed transmission in both communication directions, a secure link can be provided as a feedback channel to enhance the secrecy of the transmitted information. The generation of the shared pieces of information is given with signal forms, and the secrecy of the proposed method is evaluated based on the signal transmission error rates as determined by computer simulation.

Two frequency sharing criteria for BSS (Broadcasting-Satellite Service) are enacted in Sect.1 of Annex 1 to Appendix 30 to Radio Regulations. These two criteria are pfd (power flux-density) and EPM (Equivalent Protection Margin) values. In this paper, the two criteria are compared and studied from the view point of applicability to the sharing cases between BSS and BSS. In particular, it is shown that in some cases, the EPM criterion contributes to alleviate the problem of “sensitive satellite network”, i.e., one that has relatively low transmission power and is very weak against interference and blocks the new satellite to enter. Disclaimer The views and positions expressed by the authors are strictly personal and do not constitute, nor can be interpreted as, the position of the International Telecommunication Union on the topics addressed in this paper.

Linear Prediction (LP) analysis is commonly used in speech processing. LP is based on Auto-Regressive (AR) model and it estimates the AR model parameter from signals with l2-norm optimization. Recently, sparse estimation is paid attention since it can extract significant features from big data. The sparse estimation is realized by l1 or l0-norm optimization or regularization. Sparse LP analysis methods based on l1-norm optimization have been proposed. Since excitation of speech is not white Gaussian, a sparse LP estimation can estimate more accurate parameter than the conventional l2-norm based LP. These are time-invariant and real-valued analysis. We have been studied Time-Varying Complex AR (TV-CAR) analysis for an analytic signal and have evaluated the performance on speech processing. The TV-CAR methods are l2-norm methods. In this paper, we propose the sparse TV-CAR analysis based on adaptive LASSO (Least absolute shrinkage and selection operator) that is l1-norm regularization and evaluate the performance on F0 estimation of speech using IRAPT (Instantaneous RAPT). The experimental results show that the sparse TV-CAR methods perform better for a high level of additive Pink noise.

In wireless networks, efficient topology improves the performance of network protocols. The previous research mainly focuses on how to construct a cost-efficient network structure from a static and connected topology. Due to lack of continuous connectivity in the underlying topology, most traditional topology control methods are not applicable to the delay or disruption tolerant networks (DTNs). In this paper, we consider the topology control problem in a predictable DTN where the dynamic topology is known a priori or can be predicted over time. First, this dynamic topology is modeled by a directed space-time graph that includes spatial and temporal information. Second, the topology control problem of the predictable DTN is formulated as building a sparse structure. For any pair devices, there is an efficient path connecting them to improve the efficiency of the generated structure. Then, a topology control strategy is proposed for this optimization problem by using a kth shortest paths algorithm. Finally, simulations are conducted on random networks and a real-world DTN tracing date. The results demonstrate that the proposed method can significantly improve the efficiency of the generated structure and reduce the total cost.

A one-dimensional lattice of tunnel-diode oscillators is investigated for potential high-speed frequency divider. In the evolution of the investigated lattice, the high-frequency oscillation dominates over the low-frequency oscillation. When a base oscillator is connected at the end, and generates oscillatory signals with a frequency higher than that of the synchronous lattice oscillation, the oscillator output begins to move in the lattice. This one-way property guarantees that the oscillation dynamics of the lattice have only slight influence on the oscillator motion. Moreover, counter-moving pulses in the lattice exhibit pair annihilation through head-on collisions. These lattice properties enable an efficient frequency division method. Herein, the operating principles of the frequency divider are described, along with a numerical validation.

This paper focuses on power-area trade-off axis to memory systems. Compared with the power-performance-area trade-off application on the traditional high performance cache, this paper focuses on the edge processing environment which is becoming more and more important in the Internet of Things (IoT) era. A new power-oriented trade-off is proposed for on-chip cache architecture. As a case study, this paper exploits a good energy efficiency of Standard-Cell Memory (SCM) operating in a near-threshold voltage region and a good area efficiency of Static Random Access Memory (SRAM). A hybrid 2-level on-chip cache structure is first introduced as a replacement of 6T-SRAM cache as L0 cache to save the energy consumption. This paper proposes a method for finding the best capacity combination for SCM and SRAM, which minimizes the energy consumption of the hybrid cache under a specific cache area constraint. The simulation result using a 65-nm process technology shows that up to 80% energy consumption is reduced without increasing the die area by replacing the conventional SRAM instruction cache with the hybrid 2-level cache. The result shows that energy consumption can be reduced if the area constraint for the proposed hybrid cache system is less than the area which is equivalent to a 8kB SRAM. If the target operating frequency is less than 100MHz, energy reduction can be achieved, which implies that the proposed cache system is suitable for low-power systems where a moderate processing speed is required.

In order to obtain high-performance circuits in advanced technology nodes, design methodology has to take the existence of large delay variations into account. Clock scheduling and speculative execution have overheads to realize them, but have potential to improve the performance by averaging the imbalance of maximum delay among paths and by utilizing valid data available earlier than worst-case scenarios, respectively. In this paper, we propose a high-performance digital circuit design method with speculative executions with less overhead by utilizing clock scheduling with delay insertions effectively. The necessity of speculations that cause overheads is effectively reduced by clock scheduling with delay insertion. Experiments show that a generated circuit achieves 26% performance improvement with 1.3% area overhead compared to a circuit without clock scheduling and without speculative execution.

A privacy-preserving support vector machine (SVM) computing scheme is proposed in this paper. Cloud computing has been spreading in many fields. However, the cloud computing has some serious issues for end users, such as the unauthorized use of cloud services, data leaks, and privacy being compromised. Accordingly, we consider privacy-preserving SVM computing. We focus on protecting visual information of images by using a random unitary transformation. Some properties of the protected images are discussed. The proposed scheme enables us not only to protect images, but also to have the same performance as that of unprotected images even when using typical kernel functions such as the linear kernel, radial basis function (RBF) kernel and polynomial kernel. Moreover, it can be directly carried out by using well-known SVM algorithms, without preparing any algorithms specialized for secure SVM computing. In an experiment, the proposed scheme is applied to a face-based authentication algorithm with SVM classifiers to confirm the effectiveness.

High frame rate and ultra-low delay matching system plays an important role in various human-machine interactive applications, which demands better performance in matching deformable and out-of-plane rotating objects. Although many algorithms have been proposed for deformation tracking and matching, few of them are suitable for hardware implementation due to complicated operations and large time consumption. This paper proposes a hardware-oriented template update and recovery method for high frame rate and ultra-low delay deformation matching system. In the proposed method, the new template is generated in real time by partially updating the template descriptor and adding new keypoints simultaneously with the matching process in pixels (proposal #1), which avoids the large inter-frame delay. The size and shape of region of interest (ROI) are made flexible and the Hamming threshold used for brute-force matching is adjusted according to pixel position and the flexible ROI (proposal #2), which solves the problem of template drift. The template is recovered by the previous one with a relative center-shifting vector when it is judged as lost via region-wise difference check (proposal #3). Evaluation results indicate that the proposed method successfully achieves the real-time processing of 784fps at the resolution of 640×480 on field-programmable gate array (FPGA), with a delay of 0.808ms/frame, as well as achieves satisfactory deformation matching results in comparison with other general methods.

Real-time 3D players tracking plays an important role in sports analysis, especially for the live services of sports broadcasting, which have a strict limitation on processing time. For these kinds of applications, 3D trajectories of players contribute to high-level game analysis such as tactic analysis and commercial applications such as TV contents. Thus real-time implementation for 3D players tracking is expected. In order to achieve real-time for 60fps videos with high accuracy, (that means the processing time should be less than 16.67ms per frame), the factors that limit the processing time of target algorithm include: 1) Large image area of each player. 2) Repeated processing of multiple players in multiple views. 3) Complex calculation of observation algorithm. To deal with the above challenges, this paper proposes a representative spatial selection and temporal combination based real-time implementation for multi-view volleyball players tracking on the GPU device. First, the representative spatial pixel selection, which detects the pixels that mostly represent one image region to scale down the image spatially, reduces the number of processing pixels. Second, the representative temporal likelihood combination shares observation calculation by using the temporal correlation between images so that the times of complex calculation is reduced. The experiments are based on videos of the Final and Semi-Final Game of 2014 Japan Inter High School Games of Men's Volleyball in Tokyo Metropolitan Gymnasium. On the GPU device GeForce GTX 1080Ti, the tracking system achieves real-time on 60fps videos and keeps the tracking accuracy higher than 97%.

The windowed interpolation DFT methods have been utilized to estimate the parameters of a single frequency and multi-frequency signal. Nevertheless, they do not work well for the real-valued sinusoids with closely spaced positive- and negative- frequency. In this paper, we describe a novel three-point windowed interpolation DFT method for frequency measurement of real-valued sinusoid signal. The exact representation of the windowed DFT with maximum sidelobe decay window (MSDW) is constructed. The spectral superposition of positive- and negative-frequency is considered and calculated to improve the estimation performance. The simulation results match with the theoretical values well. In addition, computer simulations demonstrate that the proposed algorithm provides high estimation accuracy and good noise suppression capability.

This paper reports a high-quality hardware-friendly integer motion estimation (IME) scheme. According to different characteristics of CTU content, the proposed method adopts different adaptive multi-resolution strategies coupled with accurate full-PU modes IME at the finest level. Besides, by using motion vector derivation, IME for the second reference frame is simplified and hardware resource is saved greatly through processing element (PE) sharing. It is shown that the proposed architecture can support the real-time processing of 4K-UHD @60fps, while the BD-rate is just increased by 0.53%.

MQTT is one of the promising protocols for various data exchange in IoT environments. Typically, those environments have a characteristic called “edge-heavy”, which means that things at the network edge generate a massive volume of data with high locality. For handling such edge-heavy data, an architecture of placing multiple MQTT brokers at the network edges and making them cooperate with each other is quite effective. It can provide higher throughput and lower latency, as well as reducing consumption of cloud resources. However, under this kind of architecture, heterogeneity could be a vital issue. Namely, an appropriate product of MQTT broker could vary according to the different environment of each network edge, even though different products are hard to cooperate due to the MQTT specification providing no interoperability between brokers. In this paper, we propose Interworking Layer of Distributed MQTT brokers (ILDM), which enables arbitrary kinds of MQTT brokers to cooperate with each other. ILDM, designed as a generic mechanism independent of any specific cooperation algorithm, provides APIs to facilitate development of a variety of algorithms. By using the APIs, we also present two basic cooperation algorithms. To evaluate the usefulness of ILDM, we introduce a benchmark system which can be used for both a single broker and multiple brokers. Experimental results show that the throughput of five brokers running together by ILDM is improved 4.3 times at maximum than that of a single broker.

This paper proposes a novel multi-exposure image fusion (MEF) scheme for single-shot high dynamic range imaging with spatially varying exposures (SVE). Single-shot imaging with SVE enables us not only to produce images without color saturation regions from a single-shot image, but also to avoid ghost artifacts in the producing ones. However, the number of exposures is generally limited to two, and moreover it is difficult to decide the optimum exposure values before the photographing. In the proposed scheme, a scene segmentation method is applied to input multi-exposure images, and then the luminance of the input images is adjusted according to both of the number of scenes and the relationship between exposure values and pixel values. The proposed method with the luminance adjustment allows us to improve the above two issues. In this paper, we focus on dual-ISO imaging as one of single-shot imaging. In an experiment, the proposed scheme is demonstrated to be effective for single-shot high dynamic range imaging with SVE, compared with conventional MEF schemes with exposure compensation.