This letter deals with the joint direction of arrival and direction of departure estimation problem for overloaded target in bistatic multiple-input multiple-output radar system. In order to achieve the purpose of effective estimation, the presented Khatri-Rao (KR) MUSIC estimator with the ability to handle overloaded targets mainly combines the subspace characteristics of the target reflected wave signal and the KR product based on the array response. This letter also presents a computationally efficient KR noise subspace projection matrix estimation technique to reduce the computational load due to perform high-dimensional singular value decomposition. Finally, the effectiveness of the proposed method is verified by computer simulation.

This study discusses the feasibility to estimate the concentration level of Japanese document workers using computer. Based on the previous findings that dual-task scenarios increase reaction time, we hypothesized that the Kana-Kanji conversion confirmation time (KKCCT) would increase due to the decrease in cognitive resources allocated to the document task, i.e. the level of concentration on the task at hand. To examine this hypothesis, we conducted a set of experiments in which sixteen participants copied Kana text by typing and concurrently converted it into Kanji under three conditions: Normal, Dual-task, and Mental-fatigue. The results suggested the feasibility that KKCCT increased when participants were less concentrated on the task due to subtask or mental fatigue. These findings imply the potential utility of using confirmation time as a measure of concentration level in Japanese document workers.

In this paper, we describe the Galois dual of rank metric codes in the ambient space FQn×m and FQmn, where Q=qe. We obtain connections between the duality of rank metric codes with respect to distinct Galois inner products. Furthermore, for 0 ≤ s < e, we introduce the concept of qsm-dual bases of FQm over FQ and obtain some conditions about the existence of qsm-self-dual basis.

A new method for hiding information in digital images is proposed. Our method differs from existing techniques in that the information is hidden in a mixture of colors carefully tuned on a specific device according to the device's signal-to-luminance (gamma) characteristics. Because these reproduction characteristics differ in general from device to device and even from model to model, the hidden information appears when the cover image is viewed on a different device, and hence the hiding property is device-dependent. To realize this, we modulated a cover image using two identically-looking checkerboard patterns and switched them locally depending on the hidden information. Reproducing these two patterns equally on a different device is difficult. A possible application of our method would be secure printing where an image is allowed to be viewed only on a screen but a warning message appears when it is printed.

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 purpose of this paper is to find an automated pricing algorithm to calculate the real cost of each product by considering the associate costs of the business. The methodology consists of two main stages. A brief semi-structured survey and a mathematical calculation the expenses and adding them to the original cost of the offered products and services. The output of this process obtains the minimum recommended selling price (MRSP) that the business should not go below, to increase the likelihood of generating profit and avoiding the unexpected loss. The contribution of this study appears in filling the gap by calculating the minimum recommended price automatically and assisting businesses to foresee future budgets. This contribution has a certain limitation, where it is unable to calculate the MRSP of the in-house created products from raw materials. It calculates the MRSP only for the products bought from the wholesaler to be sold by the retailer.

With the development and spread of Internet of Things (IoT) technology, various kinds of data are now being generated from IoT devices. Some data generated from IoT devices depend on geographical location and time, and we refer to them as spatio-temporal data (STD). Since the “locally produced and consumed” paradigm of STD use is effective for location-dependent applications, the authors have previously proposed a vehicle-based STD retention system. However, in low vehicle density environments, the data retention becomes difficult due to the decrease in the number of data transmissions in this method. In this paper, we propose a new data transmission control method for data retention in the low vehicle density environments.

In IoT era, the growth of data variety is driven by cross-domain data fusion. In this paper, we advocate that “local production for local consumption (LPLC) paradigm” can be an innovative approach in cross-domain data fusion, and propose a new framework, geolocation-centric information platform (GCIP) that can produce and deliver diverse spatio-temporal content (STC). In the GCIP, (1) infrastructure-based geographic hierarchy edge network and (2) adhoc-based STC retention system are interplayed to provide both of geolocation-awareness and resiliency. Then, we discussed the concepts and the technical challenges of the GCIP. Finally, we implemented a proof-of-concepts of GCIP and demonstrated its efficacy through practical experiments on campus IPv6 network and simulation experiments.

Maximum inner product search (MIPS) problem has gained much attention in a wide range of applications. In order to overcome the curse of dimensionality in high-dimensional spaces, most of existing methods first transform the MIPS problem into another approximate nearest neighbor search (ANNS) problem and then solve it by Locality Sensitive Hashing (LSH). However, due to the error incurred by the transmission and incomprehensive search strategies, these methods suffer from low precision and have loose probability guarantees. In this paper, we propose a novel search method named Adaptive-LSH (AdaLSH) to solve MIPS problem more efficiently and more precisely. AdaLSH examines objects in the descending order of both norms and (the probably correctly estimated) cosine angles with a query object in support of LSH with extendable windows. Such extendable windows bring not only efficiency in searching but also the probability guarantee of finding exact or approximate MIP objects. AdaLSH gives a better probability guarantee of success than those in conventional algorithms, bringing less running times on various datasets compared with them. In addition, AdaLSH can even support exact MIPS with probability guarantee.

This paper demonstrates how to achieve simulation-based strong attribute hiding against adaptive adversaries for predicate encryption (PE) schemes supporting expressive predicate families under standard computational assumptions in bilinear groups. Our main result is a simulation-based adaptively strongly partially-hiding PE (PHPE) scheme for predicates computing arithmetic branching programs (ABP) on public attributes, followed by an inner-product predicate on private attributes. This simultaneously generalizes attribute-based encryption (ABE) for boolean formulas and ABP's as well as strongly attribute-hiding PE schemes for inner products. The proposed scheme is proven secure for any a priori bounded number of ciphertexts and an unbounded (polynomial) number of decryption keys, which is the best possible in the simulation-based adaptive security framework. This directly implies that our construction also achieves indistinguishability-based strongly partially-hiding security against adversaries requesting an unbounded (polynomial) number of ciphertexts and decryption keys. The security of the proposed scheme is derived under (asymmetric version of) the well-studied decisional linear (DLIN) assumption. Our work resolves an open problem posed by Wee in TCC 2017, where his result was limited to the semi-adaptive setting. Moreover, our result advances the current state of the art in both the fields of simulation-based and indistinguishability-based strongly attribute-hiding PE schemes. Our main technical contribution lies in extending the strong attribute hiding methodology of Okamoto and Takashima [EUROCRYPT 2012, ASIACRYPT 2012] to the framework of simulation-based security and beyond inner products.

Inner product functional encryption (IPFE) is a subclass of functional encryption (FE), whose function class is limited to inner product. We construct an efficient private-key IPFE scheme with full-hiding security, where confidentiality is assured for not only encrypted data but also functions associated with secret keys. Recently, Datta et al. presented such a scheme in PKC 2016 and this is the only scheme that achieves full-hiding security. Our scheme has an advantage over their scheme for the two aspects. More efficient: keys and ciphertexts of our scheme are almost half the size of those of their scheme. Weaker assumption: our scheme is secure under the k-linear (k-Lin) assumption, while their scheme is secure under a stronger assumption, namely, the symmetric external Diffie-Hellman (SXDH) assumption. It is well-known that the k-Lin assumption is equivalent to the SXDH assumption when k=1 and becomes weak as k increases.

We propose hardware-aware sum-product (SP) decoding for low-density parity-check codes. To simplify an implementation using a fixed-point number representation, we transform SP decoding in the logarithm domain to that in the decision domain. A polynomial approximation is proposed to implement an update rule of the proposed SP decoding efficiently. Numerical simulations show that the approximate SP decoding achieves almost the same performance as the exact SP decoding when an appropriate degree in the polynomial approximation is used, that it improves the convergence properties of SP and normalized min-sum decoding in the high signal-to-noise ratio regime, and that it is robust against quantization errors.

In this paper, we consider a wide family of λ-quasi-twisted (λ-QT) codes of index 2 and provide a bound on the minimum Hamming distance. Moreover, we give a sufficient condition for dual containing with respect to Hermitian inner product of these involved codes. As an application, some good stabilizer quantum codes over small finite fields F2 or F3 are obtained from the class of λ-QT codes.

In stepped FM radar, the transmitter intermittently transmits narrowband pulse trains of frequencies that are incremented in steps, and the receiver performs phase detection on each pulse and applies the inverse discrete Fourier transform (IDFT) to create ultra-short pulses in the time domain. Furthermore, since the transmitted signal consists of a narrowband pulse train of different frequencies, the transmitter can avoid arbitrary frequency bands while sending the pulse train (spectrum holes), allowing these systems to coexist with other narrowband wireless systems. However, spectrum holes cause degradation in the distance resolution and range sidelobe characteristics of wireless systems. In this paper, we propose a spectrum hole compensation method for stepped FM radars using Khatri-Rao product extended-phase processing to overcome the problem of spectrum holes and investigate the effectiveness of this method through experiments. Additionally, we demonstrate that the proposed method dramatically improves the range sidelobe and distance resolution characteristics.

Optimal loads and maximum achievable efficiency for multiple-receiver inductive power transfer (IPT) system have been formulated by theoretical studies in literatures. This paper presents extended analysis on system behavior at optimal load condition and extensive S-parameter evaluation to validate the formulas. Our results confirm that at the optimal load condition, the system is in a resonance state; the impact of cross-coupling among receivers is completely mitigated; and the efficiency reaches its maximum expressed by an efficiency angle tangent, in an manner analogous to the well-known kQ-theory for single-receiver IPT. Our contributions do not lie in practical applications of multiple-receiver IPT but in establishing principles for design and benchmarking the system.

In this study, we developed a new orthogonal partition concept for asymmetric orthogonal arrays and used it for the construction of orthogonal arrays for the first time. Permutation matrices and the Kronecker product were also successfully and skillfully used as our main tools. Hence, a new general iterative construction method for asymmetric orthogonal arrays of high strength was developed, and some new infinite families of orthogonal arrays of strength 3 and several new orthogonal arrays of strength 4, 5, and 6 were obtained.

Functional encryption is a new paradigm of public-key encryption that allows a user to compute f(x) on encrypted data CT(x) with a private key SKf to finely control the revealed information. Multi-input functional encryption is an important extension of (single-input) functional encryption that allows the computation f(x1,...,xn) on multiple ciphertexts CT(x1),...,CT(xn) with a private key SKf. Although multi-input functional encryption has many interesting applications like running SQL queries on encrypted database and computation on encrypted stream, current candidates are not yet practical since many of them are built on indistinguishability obfuscation. To solve this unsatisfactory situation, we show that practical two-input functional encryption schemes for inner products can be built based on bilinear maps. In this paper, we first propose a two-input functional encryption scheme for inner products in composite-order bilinear groups and prove its selective IND-security under simple assumptions. Next, we propose a two-client functional encryption scheme for inner products where each ciphertext can be associated with a time period and prove its selective IND-security. Furthermore, we show that our two-input functional encryption schemes in composite-order bilinear groups can be converted into schemes in prime-order asymmetric bilinear groups by using the asymmetric property of asymmetric bilinear groups.

In this paper, a new array geometry is proposed which is capable of performing underdetermined Direction-Of-Arrival (DOA) estimation for the circular array configuration. DOA estimation is a classical problem and one of the most important techniques in array signal processing as it has applications in wireless and mobile communications, acoustics, and seismic sensing. We consider the problem of estimating DOAs in the case when we have more sources than the number of physical sensors where the resolution must be maintained. The proposed array geometry called Nested Sparse Circular Array (NSCA) is an extension of the two level nested linear array obtained by nesting two sub-circular arrays and one element is placed at the origin. In order to extend the array aperture, a Khatri-Rao (KR) approach is applied to the proposed NSCA which yields the virtual array structure. To utilize the increase in the degrees of freedom (DOFs) that this new array provides, a subspace based approach (MUSIC) for DOA estimation and l1-based optimization approach is extended to estimate DOAs using NSCA. Simulations show that better performance for underdetermined DOA estimation is achieved using the proposed array geometry.

Bent functions have been applied to cryptography, spread spectrum, coding theory, and combinatorial design. Permutations play an important role in the design of cryptographic transformations such as block ciphers, hash functions and stream ciphers. By using the Kronecker product this paper presents a general recursive construction method of permutations over finite field. As applications of our method, several infinite classes of permutations are obtained. By means of the permutations obtained and M-M functions we construct several infinite families of bent functions.

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.