Recent localization methods for wireless networks cannot be applied to dynamic networks with unknown topology. To solve this problem, we propose a localization method based on partial correlation analysis in this paper. We evaluate our proposed localization method in terms of accuracy, which shows that our proposed method can achieve high accuracy localization for dynamic networks with unknown topology.

This letter proposes a transmission scheme called spatial vector (SV), which is effective for Nakagami-m fading multiple-input multiple-output channels. First, the analytical error rate of SV is derived for Nakagami-m fading MIMO channels. Next, an example of SV called integer SV (ISV) is introduced. The error performance was evaluated over Nakagami-m fading from m = 1 to m = 50 and compared with spatial modulation (SM), enhanced SM, and quadrature SM. The results show that for m > 1, ISV outperforms the SM schemes and is robust to m variations.

In this paper, we propose a novel centralized control method to handle multi-radio and terminal connections in an 802.11ax wireless LAN (802.11ax) mixed environment. The proposed control method can improve the throughput by applying 802.11ax Spatial Reuse in an environment hosting different terminal standards and mixed terminal communication quality. We evaluate the proposed control method by computer simulations assuming environments with mixed terminal standards, mixed communication quality, and both.

With the increase of IoT devices, P2P-based IoT platforms have been attracting attention because of their capabilities of building and maintaining their networks autonomously in a decentralized way. In particular, Skip Graph, which has a low network rebuilding cost and allows range search, is suitable for the platform. However, when data observed at geographically close points have similar values (i.e. when data have strong spatial autocorrelation), existing types of Skip Graph degrade their search performances. In this paper, we propose a query transfer method that enables efficient search even for spatially autocorrelated data by adaptively using two-types of Skip Graph depending on the key-distance to the target key. Simulation results demonstrate that the proposed method can reduce the query transfer distance compared to the existing method even for spatially autocorrelated data.

Differential Evolution (DE) algorithm is simple and effective. Since DE has been proposed, it has been widely used to solve various complex optimization problems. To further exploit the advantages of DE, we propose a new variant of DE, termed as ranking-based differential evolution (RDE), by performing ranking on the population. Progressively better individuals in the population are used for mutation operation, thus improving the algorithm's exploitation and exploration capability. Experimental results on a number of benchmark optimization functions show that RDE significantly outperforms the original DE and performs competitively in comparison with other two state-of-the-art DE variants.

In this paper, a special class of two-generator quasi-twisted (QT) codes with index 2 will be presented. We explore the algebraic structure of the class of QT codes and the form of their Hermitian dual codes. A sufficient condition for self-orthogonality with Hermitian inner product is derived. Using the class of Hermitian self-orthogonal QT codes, we construct two new binary quantum codes [[70, 42, 7]]2, [[78, 30, 10]]2. According to Theorem 6 of Ref.[2], we further can get 9 new binary quantum codes. So a total of 11 new binary quantum codes are obtained and there are 10 quantum codes that can break the quantum Gilbert-Varshamov (GV) bound.

The continuous development of the mobile computing environment has led to the emergence of fintech to enable convenient financial transactions in this environment. Previously proposed financial identity services mostly adopted centralized servers that are prone to single-point-of-failure problems and performance bottlenecks. Blockchain-based self-sovereign identity (SSI), which emerged to address this problem, is a technology that solves centralized problems and allows decentralized identification. However, the verifiable credential (VC), a unit of SSI data transactions, guarantees unlimited right to erasure for self-sovereignty. This does not suit the specificity of the financial transaction network, which requires the restriction of the right to erasure for credit evaluation. This paper proposes a model for VC generation and revocation verification for credit scoring data. The proposed model includes double zero knowledge - succinct non-interactive argument of knowledge (zk-SNARK) proof in the VC generation process between the holder and the issuer. In addition, cross-revocation verification takes place between the holder and the verifier. As a result, the proposed model builds a trust platform among the holder, issuer, and verifier while maintaining the decentralized SSI attributes and focusing on the VC life cycle. The model also improves the way in which credit evaluation data are processed as VCs by granting opt-in and the special right to erasure.

We propose a non-invasive and cost-effective method to automatically detect dementia by utilizing solely speech audio data. We extract paralinguistic features for a short speech segment and use Gated Convolutional Neural Networks (GCNN) to classify it into dementia or healthy. We evaluate our method on the Pitt Corpus and on our own dataset, the PROMPT Database. Our method yields the accuracy of 73.1% on the Pitt Corpus using an average of 114 seconds of speech data. In the PROMPT Database, our method yields the accuracy of 74.7% using 4 seconds of speech data and it improves to 80.8% when we use all the patient's speech data. Furthermore, we evaluate our method on a three-class classification problem in which we included the Mild Cognitive Impairment (MCI) class and achieved the accuracy of 60.6% with 40 seconds of speech data.

In [31], Shin et al. proposed a Leakage-Resilient and Proactive Authenticated Key Exchange (LRP-AKE) protocol for credential services which provides not only a higher level of security against leakage of stored secrets but also secrecy of private key with respect to the involving server. In this paper, we discuss a problem in the security proof of the LRP-AKE protocol, and then propose a modified LRP-AKE protocol that has a simple and effective measure to the problem. Also, we formally prove its AKE security and mutual authentication for the entire modified LRP-AKE protocol. In addition, we describe several extensions of the (modified) LRP-AKE protocol including 1) synchronization issue between the client and server's stored secrets; 2) randomized ID for the provision of client's privacy; and 3) a solution to preventing server compromise-impersonation attacks. Finally, we evaluate the performance overhead of the LRP-AKE protocol and show its test vectors. From the performance evaluation, we can confirm that the LRP-AKE protocol has almost the same efficiency as the (plain) Diffie-Hellman protocol that does not provide authentication at all.

In conclusion, an initialization method has been introduced and studied to improve the SET speed in PCM. Before experiment verification, a two-dimensional finite analysis is used, and the results illustrate the proposed method is feasible to improve SET speed. Next, the R-I performances of the discrete PCM device and the resistance distributions of a 64 M bits PCM test chip with and without the initialization have been studied and analyzed, which confirms that the writing speed has been greatly improved. At the same time, the resistance distribution for the repeated initialization operations suggest that a large number of PCM cells have been successfully changed to be in an intermediate state, which is thought that only a shorter current pulse can make the cells SET successfully in this case. Compared the transmission electron microscope (TEM) images before and after initialization, it is found that there are some small grains appeared after initialization, which indicates that the nucleation process of GST has been carried out, and only needs to provide energy for grain growth later.

In this paper, a stochasic geometry analysis of the inversely proportional setting (IPS) of carrier sense threshold (CST) and transmission power for densely deployed wireless local area networks (WLANs) is presented. In densely deployed WLANs, CST adjustment is a crucial technology to enhance spatial reuse, but it can starve surrounding transmitters due to an asymmetric carrier sensing relationship. In order for the carrier sensing relationship to be symmetric, the IPS of the CST and transmission power is a promising approach, i.e., each transmitter jointly adjusts its CST and transmission power in order for their product to be equal to those of others. This setting is used for spatial reuse in IEEE 802.11ax. By assuming that the set of potential transmitters follows a Poisson point process, the impact of the IPS on throughput is formulated based on stochastic geometry in two scenarios: an adjustment at a single transmitter and an identical adjustment at all transmitters. The asymptotic expression of the throughput in dense WLANs is derived and an explicit solution of the optimal CST is achieved as a function of the number of neighboring potential transmitters and signal-to-interference power ratio using approximations. This solution was confirmed through numerical results, where the explicit solution achieved throughput penalties of less than 8% relative to the numerically evaluated optimal solution.

Crowd flow prediction in high density urban scenes is involved in a wide range of intelligent transportation and smart city applications, and it has become a significant topic in urban computing. In this letter, a CNN-based framework called Pyramidal Spatio-Temporal Network (PSTNet) for crowd flow prediction is proposed. Spatial encoding is employed for spatial representation of external factors, while prior pyramid enhances feature dependence of spatial scale distances and temporal spans, after that, post pyramid is proposed to fuse the heterogeneous spatio-temporal features of multiple scales. Experimental results based on TaxiBJ and MobileBJ demonstrate that proposed PSTNet outperforms the state-of-the-art methods.

In this paper, we examine techniques for improving the throughput of unlicensed radio systems such as wireless LANs (WLANs) to take advantage of multi-radio access to mobile broadband, which will be important in 5G evolution and beyond. In WLANs, throughput is reduced due to mixed standards and the degraded quality of certain frequency channels, and thus control techniques and an architecture that provide efficient control over WLANs are needed to solve the problem. We have proposed a technique to control the terminal connection dynamically by using the multi-radio of the AP. Furthermore, we have proposed a new control architecture called WiSMA for efficient control of WLANs. Experiments show that the proposed method can solve those problems and improve the WLAN throughput.

Recently the data-driven learning of dynamic systems has become a promising approach because no physical knowledge is needed. Pure machine learning approaches such as Gaussian process regression (GPR) learns a dynamic model from data, with all physical knowledge about the system discarded. This goes from one extreme, namely methods based on optimizing parametric physical models derived from physical laws, to the other. GPR has high flexibility and is able to model any dynamics as long as they are locally smooth, but can not generalize well to unexplored areas with little or no training data. The analytic physical model derived under assumptions is an abstract approximation of the true system, but has global generalization ability. Hence the optimal learning strategy is to combine GPR with the analytic physical model. This paper proposes a method to learn dynamic systems using GPR with analytic ordinary differential equations (ODEs) as prior information. The one-time-step integration of analytic ODEs is used as the mean function of the Gaussian process prior. The total parameters to be trained include physical parameters of analytic ODEs and parameters of GPR. A novel method is proposed to simultaneously learn all parameters, which is realized by the fully Bayesian GPR and more promising to learn an optimal model. The standard Gaussian process regression, the ODE method and the existing method in the literature are chosen as baselines to verify the benefit of the proposed method. The predictive performance is evaluated by both one-time-step prediction and long-term prediction. By simulation of the cart-pole system, it is demonstrated that the proposed method has better predictive performances.

We investigate an interactive evolutionary computation (IEC) using multiple users' gaze information when users partially participate in each design evaluation. Many previous IEC systems have a problem that user evaluation loads are too large. Hence, we proposed to employ user gaze information for evaluating designs generated by IEC systems in order to solve this problem. In this proposed system, users just view the presented designs, not assess, then the system automatically creates users' favorite designs. With the user's gaze information, the proposed system generates coordination that can satisfy many users. In our previous study, we verified the effectiveness of the proposed system from a real system operation viewpoint. However, we did not consider the fluctuation of the users during a solution candidate evaluation. In the actual operation of the proposed system, users may change during the process due to the user interchange. Therefore, in this study, we verify the effectiveness of the proposed system when varying the users participating in each evaluation for each generation. In the experiment, we employ two types of situations as assumed in real environments. The first situation changes the number of users evaluating the designs for each generation. The second situation employs various users from the predefined population to evaluate the designs for each generation. From the experimental results in the first situation, we confirm that, despite the change in the number of users during the solution candidate evaluation, the proposed system can generate coordination to satisfy many users. Also, from the results in the second situation, we verify that the proposed system can also generate coordination which both users who participate in the coordination evaluation can more satisfy.

We provide a formal proof for the indifferentiability of SKINNY-HASH internal function from a random oracle. SKINNY-HASH is a family of sponge-based hash functions that use functions (instead of permutations) as primitives, and it was selected as one of the second round candidates of the NIST lightweight cryptography competition. Its internal function is constructed from the tweakable block cipher SKINNY. The construction of the internal function is very simple and the designers claim n-bit security, where n is the block length of SKINNY. However, a formal security proof of this claim is not given in the original specification of SKINNY-HASH. In this paper, we formally prove that the internal function of SKINNY-HASH has n-bit security, i.e., it is indifferentiable from a random oracle up to O(2n) queries, substantiating the security claim of the designers.

We revisit the design of Lesamnta-LW, which is one of the three lightweight hash functions specified in ISO/IEC 29192-5:2016. Firstly, we present some updates on the bounds of the number of active S-boxes for the underlying 64-round block cipher. While the designers showed that the Viterbi algorithm ensured 24 active S-boxes after 24 rounds, our tool based on Mixed Integer Linear Programming (MILP) in the framework of Mouha et al. ensures the same number of active S-boxes only after 18 rounds. The tool completely evaluates the tight bound of the number of active S-boxes, and it shows that the bound is 103 for full (64) rounds. We also analyze security of the Shuffle operation in the round function and resistance against linear cryptanalysis. Secondly, we present a new mode for a pseudorandom function (PRF) based on Lesamnta-LW. It is twice as efficient as the previous PRF modes based on Lesamnta-LW. We prove its security both in the standard model and the ideal cipher model.

In daily reality, people often pay attention to several objects that change positions while being observed. In the laboratory, this process is investigated by a phenomenon known as multiple object tracking (MOT) which is a task that evaluates attentive tracking performance. Recent findings suggest that the attentional set for multiple moving objects whose depth changes in three dimensions from one plane to another is influenced by the initial configuration of the objects. When tracking objects, it is difficult for people to expand their attentional set to multiple-depth planes once attention has been focused on a single plane. However, less is known about people contracting their attentional set from multiple-depth planes to a single-depth plane. In two experiments, we examined tracking accuracy when four targets or four distractors, which were initially distributed on two planes, come together on one of the planes during an MOT task. The results from this study suggest that people have difficulty changing the depth range of their attention during attentive tracking, and attentive tracking performance depends on the initial attentional set based on the configuration prior to attentive tracking.

In this paper, we address the problem of detector design in severely frequency-selective channels for spatial multiplexing systems that adopt filter bank multicarrier based on offset quadrature amplitude modulation (FBMC/OQAM) as the communication waveforms. We consider decision feedback equalizers (DFEs) that use multiple feedback filters to jointly cancel the post-cursor components of inter-symbol interference, inter-antenna interference, and, in some configuration, inter-subchannel interference. By exploiting the special structures of the correlation matrix and the staggered property of the FBMC/OQAM signals, we obtain an efficient method of computing the DFE coefficients that requires a smaller number of multiplications than the linear equalizer (LE) and conventional DFE do. The simulation results show that the proposed detectors considerably outperform the LE and conventional DFE at moderate-to-high signal-to-noise ratios.

In this paper, we focus on developing efficient multi-configuration selection mechanisms by exploiting the spatial degrees of freedom (DoF), and leveraging the simple design benefits of spatial modulation (SM). Notably, the SM technique, as well as its variants, faces the following critical challenges: (i) the performance degradation and difficulty in improving the system performance for higher-level QAM constellations, and (ii) the vast complexity cost in precoder designs particularly for the increasing system dimension and amplitude-phase modulation (APM) constellation dimension. Given this situation, we first investigate two independent modulation domains, i.e., the original signal- and spatial-constellations. By exploiting the analog shift weighting and the virtual spatial signature technologies, we introduce the signature spatial modulation (SSM) concept, which is capable of guaranteing superior trade-offs among spectral- and cost-efficiencies, and system bit error rate (BER) performance. Besides, we develop an analog beamforming for SSM by solving the introduced unconstrained Lagrange dual function minimization problem. Numerical results manifest the performance gain brought by our developed analog beamforming for SSM.