In order to optimize the performance of thermoelectric devices, we have fabricated and characterized the micrometer-scaled Si thermopile preserving the phonon-drag effect, where the Si thermopile consists of p- and n-type Si wire pairs. The measured Seebeck coefficient of the p-type Si wire was found to be higher than the theoretical value calculated only from the carrier transport, which indicates the contribution of phonon-drag part. Moreover, the measured Seebeck coefficient increased with increasing the width of Si wire. This fact is considered due to dependency of phonon-drag part on the wire width originating from the reduction of phonon-boundary scattering. These contributions were observed also in measured output voltage of Si-wire thermopile. Hence, the output voltage of Si-wire thermopile is expected can be enhanced by utilizing the phonon-drag effect in Si wire by optimizing its size and carrier concentration.

Network virtualization is viewed as a promising approach to facilitate the sharing of physical infrastructure among different kinds of users and applications. In this letter, we propose a topological consistency-based virtual network embedding (TC-VNE) over elastic optical networks (EONs). Based on the concept of topological consistency, we propose a new node ranking approach, named Sum-N-Rank, which contributes to the reduction of optical path length between preferred substrate nodes. In the simulation results, we found our work contributes to improve spectral efficiency and balance link load simultaneously without deteriorating blocking probability.

For the three-user X channel, its degree of freedom (DoF) 9/5 has been shown achievable theoretically through asymptotic model with infinite resources, which is impractical. In this article, we explore the propagation delay (PD) feature among different links to maximize the achievable DoF with the minimum cost. Since perfect interference alignment (IA) is impossible for 9 messages within 5 time-slots, at least one extra time-slot should be utilized. By the cyclic polynomial approach, we propose a scheme with the maximum achievable DoF of 5/3 for 10 messages within 6 time-slots. Feasibility conditions in the Euclidean space are also deduced, which demonstrates a quite wide range of node arrangements.

With the existing of coverage holes, the Quality of Service (such as event response, package delay, and the life time et al.) of a Wireless Sensor Network (WSN) may become weaker. In order to recover the holes, one can locate them by identifying the boundary nodes on their edges. Little effort has been made to distinguish the boundary nodes in a model where wireless sensors are randomly deployed on a three-dimensional surface. In this paper, we propose a distributed method which contains three steps in succession. It first projects the 1-hop neighborhood of a sensor to the plane. Then, it sorts the projected nodes according to their angles and finds out if there exists any ring formed by them. At last, the algorithm validates a circle to confirm that it is a ring surrounding the node. Our solution simulates the behavior of rotating a semicircle plate around a sensor under the guidance of its neighbors. Different from the existing results, our method transforms a three-dimensional problem into a two-dimensional one and maintaining its original topology, and it does not rely on any complex Hamiltonian Cycle finding to test the existence of a circle in the neighborhood of a sensor. Simulation results show our method outperforms others at the correctness and effectiveness in identifying the nodes on the edges of a three-dimensional WSN.

Data-driven untying of a recursive autoencoder (RAE) is proposed for utterance intent classification for spoken dialogue systems. Although an RAE expresses a nonlinear operation on two neighboring child nodes in a parse tree in the application of spoken language understanding (SLU) of spoken dialogue systems, the nonlinear operation is considered to be intrinsically different depending on the types of child nodes. To reduce the gap between the single nonlinear operation of an RAE and intrinsically different operations depending on the node types, a data-driven untying of autoencoders using part-of-speech (PoS) tags at leaf nodes is proposed. When using the proposed method, the experimental results on two corpora: ATIS English data set and Japanese data set of a smartphone-based spoken dialogue system showed improved accuracies compared to when using the tied RAE, as well as a reasonable difference in untying between two languages.

Among the five carrier aggregation (CA) deployment scenarios, the most preferred scenario is Scenario 1, which maximizes CA gain by fully overlapping a primary cell (PCell) and one or more secondary cells (SCells). It is possible since the same frequency band is used between component carriers (CCs) so nearly the same coverage is expected. However, Scenario 1 cannot guarantee high throughput in multi-radio access technology carrier aggregation (multi-RAT CA) which is actively being researched. Different carrier frequency characteristics in multi-RAT CA makes it hard to accurately match different frequency ranges. If the ranges of PCell and SCell differ, high throughput may not be obtained despite the CA operation. We found a coverage mismatch of approximately 37% between the PCell and SCell in the deployed network and realized a reduced CA gain in those areas. In this paper, we propose a novel PCell change approach named “PCell frequency switching (PFS)” to guarantee high throughput against cell coverage mismatch in multi-RAT CA deployment scenario 1. The experiment results show that the throughput increased by 9.7% on average and especially by 80.9% around the cell edge area when PFS is applied instead of the legacy CA handover operation.

In this paper, a reduction of the number of components included in direct simulation type active complex filter is proposed. The proposed method is achieved by sharing NIC's (Negative Impedance Converters) which satisfy some conditions. Compared with the conventional method, the proposed one has wide generality. As an example, a third-order complex elliptic filter is designed. The validity of the proposed method is confirmed through experiment.

In this paper, we show exact bit error rates (BERs) for orthogonal space-time block code (OSTBC) decoded-and-forward (DF) relaying networks over independent and non-identically distributed (INID) Rayleigh fading channels. We consider both non-adaptive DF (non-ADF) and adaptive DF (ADF) schemes for OSTBC relay networks with arbitrary multiple-input multiple-output (MIMO) relay antenna configurations. For each scheme, we derive the probability density functions (PDFs) of indirect link and combined links, respectively. Based on the derived PDFs, we express exact BERs and then, their accuracy is verified by the comparison with simulation results. It is confirmed that the transmit diversity gain of the relay node can be obtained when the relay is close to the source and then, the receive diversity gain of the relay node as well as ADF gain over non-ADF can be obtained when the relay is close to the destination.

Salient region detection is a fundamental problem in computer vision and image processing. Deep learning models perform better than traditional approaches but suffer from their huge parameters and slow speeds. To handle these problems, in this paper we propose the multi-feature fusion network (MFFN) - a efficient salient region detection architecture based on Convolution Neural Network (CNN). A novel feature extraction structure is designed to obtain feature maps from CNN. A fusion dense block is used to fuse all low-level and high-level feature maps to derive salient region results. MFFN is an end-to-end architecture which does not need any post-processing procedures. Experiments on the benchmark datasets demonstrate that MFFN achieves the state-of-the-art performance on salient region detection and requires much less parameters and computation time. Ablation experiments demonstrate the effectiveness of each module in MFFN.

It has been reported repeatedly that discriminative learning of distance metric boosts the pattern recognition performance. Although the ITML (Information Theoretic Metric Learning)-based methods enjoy an advantage that the Bregman projection framework can be applied for optimization of distance metric, a weak point of ITML-based methods is that the distance threshold for similarity/dissimilarity constraints must be determined manually, onto which the generalization performance is sensitive. In this paper, we present a new formulation of metric learning algorithm in which the distance threshold is optimized together. Since the optimization is still in the Bregman projection framework, the Dykstra algorithm can be applied for optimization. A nonlinear equation has to be solved to project the solution onto a half-space in each iteration. We have developed an efficient technique for projection onto a half-space. We empirically show that although the distance threshold is automatically tuned for the proposed metric learning algorithm, the accuracy of pattern recognition for the proposed algorithm is comparable, if not better, to the existing metric learning methods.

Communication reliability and energy efficiency are important issues that have to be carefully considered in WBAN design. Due to the large path loss variation of the WBAN channel, transmission power control, which adaptively adjusts the radio transmit power to suit the channel condition, is considered in this paper. Human motion is one of the dominant factors that affect the channel characteristics in WBAN. Therefore, this paper introduces motion-aware temporal correlation model-based transmission power control that combines human motion classification and transmission power control to provide an effective approach to realizing reliable and energy-efficient WBAN communication. The human motion classification adopted in this study uses only the received signal strength to identify the human motion; no additional tool is required. The knowledge of human motion is then used to accurately estimate the channel condition and suitably select the transmit power. A performance evaluation shows that the proposed method works well both in the low and high WBAN network loads. Compared to using the fixed Tx power of -5dBm, the proposed method had similar packet loss rate but 20-28 and 27-33 percent lower average energy consumption for the low network traffic and high network traffic cases, respectively.

Signed networks are ubiquitous in the real world. It is of great significance to study the problem of community detection in signed networks. In general, the behaviors of nodes in a signed network are rational, which coincide with the players in the theory of game that can be used to model the process of the community formation. Unlike unsigned networks, signed networks include both positive and negative edges, representing the relationship of friends and foes respectively. In the process of community formation, nodes usually choose to be in the same community with friends and between different communities with enemies. Based on this idea, we proposed a game theory model to address the problem of community detection in signed networks. Taking nodes as players, we build a gain function based on the numbers of positive edges and negative edges inside and outside a community, and prove the existence of Nash equilibrium point. In this way, when the game reaches the Nash equilibrium state, the optimal strategy space for all nodes is the result of the final community division. To systematically investigate the performance of our method, elaborated experiments on both synthetic networks and real-world networks are conducted. Experimental results demonstrate that our method is not only more accurate than other existing algorithms, but also more robust to noise.

In secret sharing schemes for general access structures, an important issue is the number of shares distributed to each participant. However, in general, the existing schemes are impractical in this respect when the size of the access structure is very large. In 2015, a secret sharing scheme that can reduce the number of shares distributed to specified participants was proposed (the scheme A of T15). In this scheme, we can select a subset of participants and reduce the number of shares distributed to any participant who belongs to the selected subset though this scheme cannot reduce the number of shares distributed to every participant. In other words, this scheme cannot reduce the number of shares distributed to each participant who does not belong to the selected subset. In this paper, we modify the scheme A of T15 and propose a new secret sharing scheme realizing general access structures. The proposed scheme can reduce the number of shares distributed to each participant who does not belong to the selected subset as well. That is, the proposed scheme is more efficient than the scheme A of T15.

Rotation symmetric Boolean functions which are invariant under the action of cyclic group have been used in many different cryptosystems. This paper presents a new construction of balanced odd-variable rotation symmetric Boolean functions with optimum algebraic immunity. It is checked that, at least for some small variables, such functions have very good behavior against fast algebraic attacks. Compared with some known rotation symmetric Boolean functions with optimum algebraic immunity, the new construction has really better nonlinearity. Further, the algebraic degree of the constructed functions is also high enough.

This report focuses on an optimization scheme of advanced MOSFETs for designing CMOS circuits with high power efficiency. For this purpose the physics-based compact model HiSIM2 is applied so that the relationship between device and circuit characteristics can be investigated properly. It is demonstrated that the short-channel effect, which is usually measured by the threshold-voltage shift relative to long-channel MOSFETs, provides a consistent measure for device-performance degradation with reduced channel length. However, performance degradations of CMOS circuits such as the power loss cannot be predicted by the threshold-voltage shift alone. Here, the subthreshold swing is identified as an additional important measure for power-efficient CMOS circuit design. The increase of the subthreshold swing is verified to become obvious when the threshold-voltage shift is larger than 0.15V.

We have comprehensively studied by numerical simulation high power transmission properties through single mode fiber for non-repeatered system application. We have clearly captured bit error rates (BERs) of digital coherent signal exhibit specific floor levels, depending on transmitter powers, due to fiber nonlinearity. If the maximum transmitter powers are defined as the powers at which BER floor levels are 1.0×10-2 without error correction, those are found to be approximately +20.4dBm, +14.8dBm and +10.6dBm, respectively, for single-channel 120Gbps DP-QPSK, DP-16QAM and DP-64QAM formats in large-core and low-loss single-mode silica fibers. In the simulations, we set fiber lengths over 100km, which is much longer than the effective fiber length, thus the results are applicable to any of long-length non-repeatered systems. We also show that the maximum transmitter powers gradually decrease in logarithmic feature with the increase of the number of DWDM channels. The channel number dependence is newly shown to be almost independent on the modulation format. The simulated results have been compared with extended Gaussian-Noise (GN) model with introducing adjustment parameters, not only to confirm the validity of the results but to explore possible new analytical modeling for non-repeatered systems.

The large computational complexity makes stereo matching a big challenge in real-time application scenario. The problem of stereo matching in a video sequence is slightly different with that in a still image because there exists temporal correlation among video frames. However, no existing method considered temporal consistency of disparity for algorithm acceleration. In this work, we proposed a scheme called the dynamic disparity range (DDR) to optimize matching cost calculation and cost aggregation steps by narrowing disparity searching range, and a scheme called temporal cost aggregation path to optimize the cost aggregation step. Based on the schemes, we proposed the DDR-SGM and the DDR-MCCNN algorithms for the stereo matching in video sequences. Evaluation results showed that the proposed algorithms significantly reduced the computational complexity with only very slight loss of accuracy. We proved that the proposed optimizations for the stereo matching are effective and the temporal consistency in stereo video is highly useful for either improving accuracy or reducing computational complexity.

Correctly understanding microarchitectural bottlenecks is important to optimize performance and energy of OoO (Out-of-Order) processors. Although CPI (Cycles Per Instruction) stack has been utilized for this purpose, it stacks architectural events heuristically by counting how many times the events occur, and the order of stacking affects the result, which may be misleading. It is because CPI stack does not consider the execution path of dynamic instructions. Critical path analysis (CPA) is a well-known method to identify the critical execution path of dynamic instruction execution on OoO processors. The critical path consists of the sequence of events that determines the execution time of a program on a certain processor. We develop a novel representation of CPCI stack (Cycles Per Critical Instruction stack), which is CPI stack based on CPA. The main challenge in constructing CPCI stack is how to analyze a large number of paths because CPA often results in numerous critical paths. In this paper, we show that there are more than ten to the tenth power critical paths in the execution of only one thousand instructions in 35 benchmarks out of 48 from SPEC CPU2006. Then, we propose a statistical method to analyze all the critical paths and show a case study using the benchmarks.

This paper presents an analysis of random number generators based on continuous-time chaotic oscillators. Two different methods for random number generation have been studied: 1) Regular sampling of a chaotic waveform, and 2) Chaotic sampling of a regular waveform. Kernel density estimation is used to analytically describe the distribution of chaotic state variables and the probability density function corresponding to the output bit stream. Random bit sequences are generated using analytical equations and results from numerical simulations. Applying the concepts of autocorrelation and approximate entropy, randomness quality of the generated bit sequences are assessed to analyze relationships between the frequencies of the regular and chaotic waveforms used in both random number generation methods. It is demonstrated that in both methods, there exists certain ratios between the frequencies of regular and chaotic signal at which the randomness of the output bit stream changes abruptly. Furthermore, both random number generation methods have been compared against their immunity to interference from external signals. Analysis shows that chaotic sampling of regular waveform method provides more robustness against interference compared to regular sampling of chaotic waveform method.