Space optical communication has been considered one of the major candidates for high-rate data transmission and it reaches the practical stage to operate as a high-rate data transmission system. In this paper, the author reports the latest situation of space optical communication around the world, flight demonstrations, technological research and standardization. Research and development activities at Japan aerospace exploration agency (JAXA) are also presented.

Gender classification with hand-dorsa vein information, a new soft biometric trait, is solved with the proposed unsupervised sparse feature learning model, state-of-the-art accuracy demonstrates the effectiveness of the proposed model. Besides, we also argue that the proposed data reconstruction model is also applicable to age estimation when comprehensive database differing in age is accessible.

In this paper, we present a new three-way split formula for binary polynomial multiplication (PM) with five recursive multiplications. The scheme is based on a recently proposed multievaluation and interpolation approach using field extension. The proposed PM formula achieves the smallest space complexity. Moreover, it has about 40% reduced time complexity compared to best known results. In addition, using developed techniques for PM formulas, we propose a three-way split formula for Toeplitz matrix vector product with five recursive products which has a considerably improved complexity compared to previous known one.

In this paper, we propose a received signal interpolation method for enhancing the performance of multiple signal classification (MUSIC) algorithm. In general, the performance of the conventional MUSIC algorithm is very sensitive to signal-to-noise ratio (SNR) of the received signal. When array elements receive the signals with nonuniform SNR values, the resolution performance is degraded compared to elements receiving the signals with uniform SNR values. Hence, we propose a signal calibration technique for improving the resolution of the algorithm. First, based on original signals, rough direction of arrival (DOA) estimation is conducted. In this stage, using frequency-domain received signals, SNR values of each antenna element in the array are estimated. Then, a deteriorated element that has a relatively lower SNR value than those of the other elements is selected by our proposed scheme. Next, the received signal of the selected element is spatially interpolated based on the signals received from the neighboring elements and the DOA information extracted from the rough estimation. Finally, fine DOA estimation is performed again with the calibrated signal. Simulation results show that the angular resolution of the proposed method is better than that of the conventional MUSIC algorithm. Also, we apply the proposed scheme to actual data measured in the testing ground, and it gives us more enhanced DOA estimation result.

Let G be a graph such that each edge has its list of available colors, and assume that each list is a subset of the common set consisting of k colors. Suppose that we are given two list edge-colorings f0 and fr of G, and asked whether there exists a sequence of list edge-colorings of G between f0 and fr such that each list edge-coloring can be obtained from the previous one by changing a color assignment of exactly one edge. This problem is known to be PSPACE-complete for every integer k ≥ 6 and planar graphs of maximum degree three, but any computational hardness was unknown for the non-list variant in which every edge has the same list of k colors. In this paper, we first improve the known result by proving that, for every integer k ≥ 4, the problem remains PSPACE-complete even for planar graphs of bounded bandwidth and maximum degree three. Since the problem is known to be solvable in polynomial time if k ≤ 3, our result gives a sharp analysis of the complexity status with respect to the number k of colors. We then give the first computational hardness result for the non-list variant: for every integer k ≥ 5, the non-list variant is PSPACE-complete even for planar graphs of bandwidth quadratic in k and maximum degree k.

The generalized spatial modulation (GSM) is a new transmission technique that can realize high-performance multiple-input multiple-output (MIMO) communication systems with a low RF complexity. This paper presents an efficient sphere decoding method used to perform the symbol detection for the generalized spatial modulation (GSM) multiple-input multiple-output (MIMO) systems. In the proposed method, the cost metric is modified so that it does not include the cancellation of the nonexistent interference. The modified cost metric can be computed by formulating a detection tree that has a regular structure representing the transmit antenna combinations as well as the symbol vectors, both of which are detected efficiently by finding the shortest path on the basis of an efficient tree search algorithm. As the tree search algorithm is performed for the regular detection tree to compute the modified but mathematically-equivalent cost metric, the efficiency of the sphere decoding is improved while the bit-error rate performance is not degraded. The simulation results show that the proposed method reduces the complexity significantly when compared with the previous method: for the 6×6 64QAM GSM-MIMO system with two active antennas, the average reduction rate of the complexity is as high as 45.8% in the count of the numerical operations.

Query autocompletion is an important and practical technique when users want to search for desirable information. As mobile devices become more and more popular, one of the main applications is location-aware service, such as Web mapping. In this paper, we propose a new solution to location-aware query autocompletion. We devise a trie-based index structure and integrate spatial information into trie nodes. Our method is able to answer both range and top-k queries. In addition, we discuss the extension of our method to support the error tolerant feature in case user's queries contain typographical errors. Experiments on real datasets show that the proposed method outperforms existing methods in terms of query processing performance.

A quantized index for evaluating the pattern similarity of two different datasets is designed by calculating the number of correlated dictionary atoms. Guided by this theory, task-specific biometric recognition model transferred from state-of-the-art DNN models is realized for both face and vein recognition.

Wireless sensor networks usually deploy sensor nodes with limited energy resources in unattended environments so that people have difficulty in replacing or recharging the depleted devices. In order to balance the energy dissipation and prolong the network lifetime, this paper proposes a routing spanning tree-based clustering algorithm (RSTCA) which uses routing spanning tree to analyze clustering. In this study, the proposed scheme consists of three phases: setup phase, cluster head (CH) selection phase and steady phase. In the setup phase, several clusters are formed by adopting the K-means algorithm to balance network load on the basis of geographic location, which solves the randomness problem in traditional distributed clustering algorithm. Meanwhile, a conditional inter-cluster data traffic routing strategy is created to simplify the networks into subsystems. For the CH selection phase, a novel CH selection method, where CH is selected by a probability based on the residual energy of each node and its estimated next-time energy consumption as a function of distance, is formulated for optimizing the energy dissipation among the nodes in the same cluster. In the steady phase, an effective modification that counters the boundary node problem by adjusting the data traffic routing is designed. Additionally, by the simulation, the construction procedure of routing spanning tree (RST) and the effect of the three phases are presented. Finally, a comparison is made between the RSTCA and the current distributed clustering protocols such as LEACH and LEACH-DT. The results show that RSTCA outperforms other protocols in terms of network lifetime, energy dissipation and coverage ratio.

In this paper, we propose a new spatial modulation (SM) scheme based on quaternary quasi-orthogonal sequences (Q-QOSs), referred to as Q-QOS-SM. First, the conventional SM and generalized-SM (GSM) schemes are reinterpreted as a new transmission scheme based on a spatial modulation matrix (SMM), whose column indices are used for the mapping of spatial-information bits unlike the conventional ones. Next, by adopting the SMM comprising the Q-QOSs, the proposed Q-QOS-SM that guarantees twice the number of spatial bits at a transmitter compared with the SM with a constraint of transmit antennas, is designed. From the computer-simulation results, the Q-QOS-SM is shown to achieve a greatly improved throughput compared with the conventional SM and GSM schemes, especially, for a large number of the receive antennas. This finding is mainly because the new scheme offers a much higher minimum Euclidean distance than the other schemes.

Nonnegative Matrix Factorization (NMF) with sparseness and smoothness constraints has attracted increasing attention. When these properties are considered, NMF is usually formulated as an optimization problem in which a linear combination of an approximation error term and some regularization terms must be minimized under the constraint that the factor matrices are nonnegative. In this paper, we focus our attention on the error measure based on the Euclidean distance and propose a new iterative method for solving those optimization problems. The proposed method is based on the Hierarchical Alternating Least Squares (HALS) algorithm developed by Cichocki et al. We first present an example to show that the original HALS algorithm can increase the objective value. We then propose a new algorithm called the Gauss-Seidel HALS algorithm that decreases the objective value monotonically. We also prove that it has the global convergence property in the sense of Zangwill. We finally verify the effectiveness of the proposed algorithm through numerical experiments using synthetic and real data.

A new type of spatially coupled low density parity check (SCLDPC) code is proposed. This code has two benefits. (1) This code requires less number of iterations to correct the erasures occurring through the binary erasure channel in the waterfall region than that of the usual SCLDPC code. (2) This code has lower error floor than that of the usual SCLDPC code. Proposed code is constructed as a coupled chain of the underlying LDPC codes whose code lengths exponentially increase as the position where the codes exist is close to the middle of the chain. We call our code spatially “Mt. Fuji” coupled LDPC (SFCLDPC) code because the shape of the graph representing the code lengths of underlying LDPC codes at each position looks like Mt. Fuji. By this structure, when the proposed SFCLDPC code and the original SCLDPC code are constructed with the same code rate and the same code length, L (the number of the underlying LDPC codes) of the proposed SFCLDPC code becomes smaller and M (the code lengths of the underlying LDPC codes) of the proposed SFCLDPC code becomes larger than those of the SCLDPC code. These properties of L and M enables the above reduction of the number of iterations and the bit error rate in the error floor region, which are confirmed by the density evolution and computer simulations.

On an inference-enabled Linked Open Data (LOD) endpoint, usually a query execution takes longer than on an LOD endpoint without inference engine due to its processing of reasoning. Although there are two separate kind of approaches, query modification approaches, and ontology modifications have been investigated on the different contexts, there have been discussions about how they can be chosen or combined for various settings. In this paper, for reducing query execution time on an inference-enabled LOD endpoint, we compare these two promising methods: query rewriting and ontology modification, as well as trying to combine them into a cluster of such systems. We employ an evolutionary approach to make such rewriting and modification of queries and ontologies based on the past-processed queries and their results. We show how those two approaches work well on implementing an inference-enabled LOD endpoint by a cluster of SPARQL endpoints.

We proposed the simulation method of reconstructed holographic images in considering phase distribution in the small pixels of liquid crystal spatial light modulator (LC-SLM) and clarified zero-order diffraction appeared on the reconstructed images when the phase distribution in a single pixel is non-uniform. These results are useful for design of fine LC-SLM for realizing wide-viewing-angle holographic displays.

We developed flexible liquid crystal devices using ultra-thin polyimide substrates and bonding polymer spacers, and discussed the effects of polymer spacer structure on the cell thickness uniformity of flexible LCDs. We clarified that the lattice-shaped polymer spacer is effective to stabilize the cell thickness by suppressing the flow of the liquid crystal during bending process.

This study involves proposing a high-speed computer-generated hologram playback by using a digital micromirror device for high-definition spatiotemporal division multiplexing electroholography. Consequently, the results indicated that the study successfully reconstructed a high-definition 3-D movie of 3-D objects that was comprised of approximately 900,000 points at 60 fps when each frame was divided into twelve parts.

A single-dimensional interface which enables users to obtain diverse localizations of audio sources is proposed. In many conventional interfaces for arranging audio sources, there are multiple arrangement parameters, some of which allow users to control positions of audio sources. However, it is difficult for users who are unfamiliar with these systems to optimize the arrangement parameters since the number of possible settings is huge. We propose a simple, single-dimensional interface for adjusting arrangement parameters, allowing users to sample several diverse audio source arrangements and easily find their preferred auditory localizations. To select subsets of arrangement parameters from all of the possible choices, auditory-localization space vectors (ASVs) are defined to represent the auditory localization of each arrangement parameter. By selecting subsets of ASVs which are approximately orthogonal, we can choose arrangement parameters which will produce diverse auditory localizations. Experimental evaluations were conducted using music composed of three audio sources. Subjective evaluations confirmed that novice users can obtain diverse localizations using the proposed interface.

In this paper, a novel approach is proposed for stereo vision-based ground plane detection at superpixel-level, which is implemented by employing a Disparity Texture Map in a convolution neural network architecture. In particular, the Disparity Texture Map is calculated with a new Local Disparity Texture Descriptor (LDTD). The experimental results demonstrate our superior performance in KITTI dataset.

In this paper, we applied cavity resonator wireless power transfer (CR WPT) to an enclosed space with scatterers and revealed that high transfer efficiency at line-of-sight (LOS) and non-line-of-sight (NLOS) position in the power transmitter can be achieved by this method. In addition, we propose a method for limiting the wireless power transfer space utilizing metal mesh and show its effectiveness by experiment. First, we confirm that the constructed experimental model is working as a cavity resonator by theoretical formula and electromagnetic field analysis. Next, we calculate the maximum power transfer efficiency using a model including a plurality of scatterers by installing a power receiver at LOS and NLOS positions in the power transmitter, and it was confirmed that transfer efficiency of 30% or more could be expected even at the NLOS position. Then, we measured the frequency characteristics of a model in which one surface of the outer wall was replaced with a metal mesh, and it was clarified that the characteristics hardly changed in the power transfer frequency band. Finally, we confirmed that simultaneous communication can be performed with driving of the battery-less sensor by CR WPT, and clarify effectiveness of the proposed method.

Human activity prediction has become a prerequisite for service recommendation and anomaly detection systems in a smart space including ambient assisted living (AAL) and activities of daily living (ADL). In this paper, we present a novel approach to predict the next-activity set in a multi-user smart space. Differing from the majority of the previous studies considering single-user activity patterns, our study considers multi-user activities that occur with a large variety of patterns. Its complexity increases exponentially according to the number of users. In the multi-user smart space, there can be inevitably multiple next-activity candidates after multi-user activities occur. To solve the next-activity problem in a multi-user situation, we propose activity set prediction rather than one activity prediction. We also propose activity sequence partitioning to reduce the complexity of the multi-user activity pattern. This divides an activity sequence into start, ongoing, and finish zones based on the features in the tendency of activity occurrences. The majority of the activities in a multi-user environment occur at the beginning or end, rather than the middle, of an activity sequence. Furthermore, the types of activities typically occurring in each zone can be sufficiently distinguishable. Exploiting these characteristics, we suggest a two-step procedure to predict the next-activity set utilizing a long short-term memory (LSTM) model. The first step identifies the zones to which current activities belong. In the next step, we construct three different LSTM models to predict the next-activity set in each zone. To evaluate the proposed approach, we experimented using a real dataset generated from our campus testbed. Our experiments confirmed the complexity reduction and high accuracy in the next-activity set prediction. Thus, it can be effectively utilized for various applications with context-awareness in a multi-user smart space.