This paper presents a new method to translate a regular expression into a nondeterministic finite automaton (an NFA for short). Let r be a regular expression and let M be a Thompson automaton for r. We first introduce a labeled Thompson automaton defined by assigning two types of expressions which denote prefixes and suffixes of words in L(r) to each state of M. Then we give new ϵ-free NFAs constructed from a labeled Thompson automaton. These NFAs are called a prefix equation automaton and a suffix equation automaton. We show that a suffix equation automaton is isomorphic to an equation automaton defined by Antimirov. Furthermore we give an NFA called a unified equation automaton by joining two NFAs. Thus the number of states of a unified equation automaton can be smaller than that of an equation automaton.

Orthogonal frequency division multiplexing (OFDM) technique has been widely used in communication systems in pursuit of the most efficient utilization of spectrum. However, the increase of the number of orthogonal subcarriers will lead to the rise of the peak-to-average power ratio (PAPR) of the waveform, thus reducing the efficiency of the power amplifiers. In this letter we propose a phase-changed PAPR reduction technique based on windowing function architecture for OFDM systems. This technique is based on the idea of phase change, which makes the spectrum of output signal almost free of regrowth caused by peak clipping. It can reduce more than 28dBc adjacent channel power ratio (ACPR) compared with the traditional peak windowing clipping methods in situation that peak is maximally suppressed. This technique also has low algorithm complexity so it can be easily laid out on hardware. The proposed algorithm has been laid out on a low-cost field-programmable gate array (FPGA) to verify its effectiveness and feasibility. A 64-QAM modulated 20M LTE-A waveform is used for measurement, which has a sampling rate of 245.67M.

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.

Recently, image compression systems based on convolutional neural networks that use flexible nonlinear analysis and synthesis transformations have been developed to improve the restoration accuracy of decoded images. Although these methods that use objective metric such as peak signal-to-noise ratio and multi-scale structural similarity for optimization attain high objective results, such metric may not reflect human visual characteristics and thus degrade subjective image quality. A method using a framework called a generative adversarial network (GAN) has been reported as one of the methods aiming to improve the subjective image quality. It optimizes the distribution of restored images to be close to that of natural images; thus it suppresses visual artifacts such as blurring, ringing, and blocking. However, since methods of this type are optimized to focus on whether the restored image is subjectively natural or not, components that are not correlated with the original image are mixed into the restored image during the decoding process. Thus, even though the appearance looks natural, subjective similarity may be degraded. In this paper, we investigated why the conventional GAN-based compression techniques degrade subjective similarity, then tackled this problem by rethinking how to handle image generation in the GAN framework between image sources with different probability distributions. The paper describes a method to maximize mutual information between the coding features and the restored images. Experimental results show that the proposed mutual information amount is clearly correlated with subjective similarity and the method makes it possible to develop image compression systems with high subjective similarity.

The plain bend in a pair of differential transmission lines causes a path difference, which leads to differential-to-common mode conversion due to the phase difference. This conversion can cause serious common-mode noise issues. We previously proposed a tightly coupled asymmetrically tapered bend to suppress forward differential-to-common mode conversion and derived the constraint conditions for high-density wiring. To provide sufficient suppression of mode conversion, however, the additional correction was required to make the effective path difference vanish. This paper proposes a practical and straightforward design methodology by using a very tightly coupled bend (decreasing the line width and the line separation of the tightly coupled bend). Full-wave simulations below 20GHz demonstrated that sufficient suppression of the forward differential-to-common mode conversion is successfully achieved as designed. Measurements showed that our design methodology is effective.

We consider all-to-all broadcast and unicast among nodes in a multi-channel single-hop ad hoc network, with no time synchronization. Motivated by the hard delay requirement for ultra-reliable and low-latency communication (URLLC) in 5G wireless networks, we aim at designing medium access control (MAC) schemes to guarantee successful node-to-node transmission within a bounded delay. To provide a hard guarantee on the transmission delay, deterministic sequence schemes are preferred to probabilistic schemes such as carrier sense multiple access (CSMA). Therefore, we mainly consider sequence schemes, with the goal to design schedule sequence set to guarantee successful broadcast/unicast within a common sequence period. This period should be as short as possible since it determines an upper bound on the transmission delay. In previous works, we have considered sequence design under time division duplex (TDD). In this paper, we focus on another common duplex mode, frequency division duplex (FDD). For the FDD case, we present a lower bound on period of feasible sequence sets, and propose a sequence construction method by which the sequence period can achieve the same order as the lower bound, for both broadcast and unicast models. We also compare the sequence length for FDD with that for TDD.

Many approaches enable teachers to digitalize students' answers and mark them on the computer. However, they are still limited for supporting marking descriptive mathematical answers that can best evaluate learners' understanding. This paper presents clustering of offline handwritten mathematical expressions (HMEs) to help teachers efficiently mark answers in the form of HMEs. In this work, we investigate a method of combining feature types from low-level directional features and multiple levels of recognition: bag-of-symbols, bag-of-relations, and bag-of-positions. Moreover, we propose a marking cost function to measure the marking effort. To show the effectiveness of our method, we used two datasets and another sampled from CROHME 2016 with synthesized patterns to prepare correct answers and incorrect answers for each question. In experiments, we employed the k-means++ algorithm for each level of features and considered their combination to produce better performance. The experiments show that the best combination of all the feature types can reduce the marking cost to about 0.6 by setting the number of answer clusters appropriately compared with the manual one-by-one marking.

In this paper, we present a novel method for vehicle detection based on the Faster R-CNN frame. We integrate MobileNet into Faster R-CNN structure. First, the MobileNet is used as the base network to generate the feature map. In order to retain the more information of vehicle objects, a fusion strategy is applied to multi-layer features to generate a fused feature map. The fused feature map is then shared by region proposal network (RPN) and Fast R-CNN. In the RPN system, we employ a novel dimension cluster method to predict the anchor sizes, instead of choosing the properties of anchors manually. Our detection method improves the detection accuracy and saves computation resources. The results show that our proposed method respectively achieves 85.21% and 91.16% on the mean average precision (mAP) for DIOR dataset and UA-DETRAC dataset, which are respectively 1.32% and 1.49% improvement than Faster R-CNN (ResNet152). Also, since less operations and parameters are required in the base network, our method costs the storage size of 42.52MB, which is far less than 214.89MB of Faster R-CNN(ResNet50).

This paper expands our previously proposed semi-blind uplink interference suppression scheme for multicell multiuser massive MIMO systems to support multi modulus signals. The original proposal applies the channel state information (CSI) aided blind adaptive array (BAA) interference suppression after the beamspace preprocessing and the decision feedback channel estimation (DFCE). BAA is based on the constant modulus algorithm (CMA) which can fully exploit the degree of freedom (DoF) of massive antenna arrays to suppress both inter-user interference (IUI) and inter-cell interference (ICI). Its effectiveness has been verified under the extensive pilot contamination constraint. Unfortunately, CMA basically works well only for constant envelope signals such as QPSK and thus the proposed scheme should be expanded to cover QAM signals for more general use. This paper proposes to apply the multi modulus algorithm (MMA) and the minimum mean square error weight derivation based on data-aided sample matrix inversion (MMSE-SMI). It can successfully realize interference suppression even with the use of multi-level envelope signals such as 16QAM with satisfactorily outage probability performance below the fifth percentile.

In this paper, we propose new generation methods of two-dimensional (2D) optical zero-correlation zone (ZCZ) sequences with the high peak autocorrelation amplitude. The 2D optical ZCZ sequence consists of a pair of a binary sequence which takes 1 or 0 and a bi-phase sequence which takes 1 or -1, and has a zero-correlation zone in the two-dimensional correlation function. Because of these properties, the 2D optical ZCZ sequence is suitable for optical code-division multiple access (OCDMA) system using an LED array having a plurality of light-emitting elements arranged in a lattice pattern. The OCDMA system using the 2D optical ZCZ sequence can be increased the data rate and can be suppressed interference by the light of adjacent LEDs. By using the proposed generation methods, we can improve the peak autocorrelation amplitude of the sequence. This means that the BER performance of the OCDMA system using the sequence can be improved.

This paper proposes a novel weight derivation method to improve adaptive array interference suppression performance based on our previously conceived sample matrix inversion algorithm using common correlation matrix (CCM-SMI), by data-aided approach. In recent broadband wireless communication system such as orthogonal frequency division multiplexing (OFDM) which possesses lots of subcarriers, the computation complexity is serious problem when using SMI algorithm to suppress unknown interference. To resolve this problem, CCM based SMI algorithm was previously proposed. It computes the correlation matrix by the received time domain signals before fast Fourier transform (FFT). However, due to the limited number of pilot symbols, the estimated channel state information (CSI) is often incorrect. It leads limited interference suppression performance. In this paper, we newly employ a data-aided channel state estimation. Decision results of received symbols are obtained by CCM-SMI and then fed-back to the channel estimator. It assists improving CSI estimation accuracy. Computer simulation result reveals that our proposal accomplishes better bit error rate (BER) performance in spite of the minimum pilot symbols with a slight additional computation complexity.

When applying estimation methods, the issue of outliers is inevitable. The extent of their influence has not been clarified, though several studies have evaluated outlier elimination methods. It is unclear whether we should always be sensitive to outliers, whether outliers should always be removed before estimation, and what amount of precaution is required for collecting project data. Therefore, the goal of this study is to illustrate a guideline that suggests how sensitively we should handle outliers. In the analysis, we experimentally add outliers to three datasets, to analyze their influence. We modified the percentage of outliers, their extent (e.g., we varied the actual effort from 100 to 200 person-hours when the extent was 100%), the variables including outliers (e.g., adding outliers to function points or effort), and the locations of outliers in a dataset. Next, the effort was estimated using these datasets. We used multiple linear regression analysis and analogy based estimation to estimate the development effort. The experimental results indicate that the influence of outliers on the estimation accuracy is non-trivial when the extent or percentage of outliers is considerable (i.e., 100% and 20%, respectively). In contrast, their influence is negligible when the extent and percentage are small (i.e., 50% and 10%, respectively). Moreover, in some cases, the linear regression analysis was less affected by outliers than analogy based estimation.

We propose a novel framework for integrating beginners' machine operational experiences with those of experts' to obtain a detailed task model. Beginners can provide valuable information for operation guidance and task design; for example, from the operations that are easy or difficult for them, the mistakes they make, and the strategy they tend to choose. However, beginners' experiences often vary widely and are difficult to integrate directly. Thus, we consider an operational experience as a sequence of hand-machine interactions at hotspots. Then, a few experts' experiences and a sufficient number of beginners' experiences are unified using two aggregation steps that align and integrate sequences of interactions. We applied our method to more than 40 experiences of a sewing task. The results demonstrate good potential for modeling and obtaining important properties of the task.

This paper proposes an id-eCK secure identity-based authenticated key exchange (ID-AKE) scheme, where the id-eCK security implies that a scheme resists against leakage of all combinations of master, static, and ephemeral secret keys except ones trivially break the security. Most existing id-eCK secure ID-AKE schemes require two symmetric pairing operations or a greater number of asymmetric pairing, which is faster than symmetric one, operations to establish a session key. However, our scheme is realized with a single asymmetric pairing operation for each party, and this is an advantage in efficiency. The proposed scheme is based on the ID-AKE scheme by McCullagh and Barreto, which is vulnerable to an active attack. To achieve id-eCK security, we apply the HMQV construction and the NAXOS technique to the McCullagh-Barreto scheme. The id-eCK security is proved under the external Diffie-Hellman for target group assumption and the q-gap-bilinear collision attack assumption.

Software maintenance is an important activity in the software lifecycle. Software maintenance does not only mean removing faults found after software release. Software needs extensions or modifications of its functions owing to changes in the business environment and software maintenance also refers to them. To help users and service suppliers benchmark work efficiency for software maintenance, and to clarify the relationships between software quality, work efficiency, and unit cost of staff, we used a dataset that includes 134 data points collected by the Economic Research Association in 2012, and analyzed the factors that affected the work efficiency of software maintenance. In the analysis, using a multiple regression model, we clarified the relationships between work efficiency and programming language and productivity factors. To analyze the influence to the quality, relationships of fault ratio was analyzed using correlation coefficients. The programming language and productivity factors affect work efficiency. Higher work efficiency and higher unit cost of staff do not affect the quality of software maintenance.

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.

Resource limitations require that bugs be resolved efficiently. The bug modification process uses bug reports, which are generated from service user reports. Developers read these reports and fix bugs. Developers discuss bugs by posting comments directly in bug reports. Although several studies have investigated the initial report in bug reports, few have researched the comments. Our research focuses on bug reports. Currently, everyone is free to comment, but the bug fixing time may be affected by how to comment. Herein we investigate the topic of comments in bug reports. Mixed topics do not affect the bug fixing time. However, the bug fixing time tends to be shorter when the discussion length of the phenomenon is short.

This paper proposes an encryption-then-compression (EtC) system-friendly data hiding scheme for images, where an EtC system compresses images after they are encrypted. The EtC system divides an image into non-overlapping blocks and applies four block-based processes independently and randomly to the image for visual encryption of the image. The proposed scheme hides data to a plain, i.e., unencrypted image and the scheme can take hidden data out from the image encrypted by the EtC system. Furthermore, the scheme serves reversible data hiding, so it can perfectly recover the unmarked image from the marked image whereas the scheme once distorts unmarked image for hiding data to the image. The proposed scheme copes with the three of four processes in the EtC system, namely, block permutation, rotation/flipping of blocks, and inverting brightness in blocks, whereas the conventional schemes for the system do not cope with the last one. In addition, these conventional schemes have to identify the encrypted image so that image-dependent side information can be used to extract embedded data and to restore the unmarked image, but the proposed scheme does not need such identification. Moreover, whereas the data hiding process must know the block size of encryption in conventional schemes, the proposed scheme needs no prior knowledge of the block size for encryption. Experimental results show the effectiveness of the proposed scheme.

A novel shuffle converter by using 3D waveguide of MCF (multi-core fiber)/SMF (single mode fiber) ribbon fan-in fan-out configuration towards over 1,000 port count optical matrix switch has been proposed. The shuffle converter enables to avoid waveguide crossing section in the optical matrix switch configuration, and the principle device showed sufficient crosstalk of less than -54.2 dB, and insertion loss of 2.1 dB successfully.

We propose a novel hue-correction scheme for multi-exposure image fusion (MEF). Various MEF methods have so far been studied to generate higher-quality images. However, there are few MEF methods considering hue distortion unlike other fields of image processing, due to a lack of a reference image that has correct hue. In the proposed scheme, we generate an HDR image as a reference for hue correction, from input multi-exposure images. After that, hue distortion in images fused by an MEF method is removed by using hue information of the HDR one, on the basis of the constant-hue plane in the RGB color space. In simulations, the proposed scheme is demonstrated to be effective to correct hue-distortion caused by conventional MEF methods. Experimental results also show that the proposed scheme can generate high-quality images, regardless of exposure conditions of input multi-exposure images.