In OFDM systems, link performance depends heavily on the estimation of symbol-timing and frequency offsets. Performance sensitivity to these estimates is a major drawback of OFDM systems. Timing errors destroy the orthogonality of OFDM signals and lead to inter-symbol interference (ISI) and inter-carrier interference (ICI). The interference due to timing errors can be exploited as a metric for symbol-timing synchronization. In this paper, we propose a novel method to extract interference components using a DFT of the upsampled OFDM signals. Mathematical analysis and formulation are given for the dependence of interference on timing errors. From a numerical analysis, the proposed interference estimation shows robustness against channel dispersion.

Massive multiple input multiple output (MIMO) communication system offers high rate transmission and/or support of a large number of users by invoking the power of a large array antenna, but one of its problem is the heavy computational burden required for the design and signal processing. Assuming the utilization of a large array in the transmitter side and much fewer users than the maximum possible value, this paper first presents a subarray based design approach of MIMO system with a low computational load taking into account efficient subarray grouping for the realization of higher performance; a large transmit array is first divided into subarrays based on channel gain or channel correlation, then block diagonalization is applied to each of them, and finally a large array weight is reconstructed by maximal ratio combining (MRC). In addition, the extension of the proposed method to two-stage design is studied in order to support a larger number of users; in the process of reconstruction to a large array, subarrays are again divided into groups, and block diagonalization is applied to those subarray groups. Through computer simulations, it is shown that the both channel gain and correlation based grouping strategies are effective under certain conditions, and that the number of supported users can be increased by two-stage design if certain level of performance degradation is acceptable.

Android is one of the most popular mobile device platforms. However, since Android apps can be disassembled easily, attackers inject additional advertisements or malicious codes to the original apps and redistribute them. There are a non-negligible number of such repackaged apps. We generally call those malicious repackaged apps “clones.” However, there are apps that are not clones but are similar to each other. We call such apps “relatives.” In this work, we developed a framework called APPraiser that extracts similar apps and classifies them into clones and relatives from the large dataset. We used the APPraiser framework to study over 1.3 million apps collected from both official and third-party marketplaces. Our extensive analysis revealed the following findings: In the official marketplace, 79% of similar apps were attributed to relatives, while in the third-party marketplace, 50% of similar apps were attributed to clones. The majority of relatives are apps developed by prolific developers in both marketplaces. We also found that in the third-party market, of the clones that were originally published in the official market, 76% of them are malware.

To promote effective guidance by health checkup results, this paper predict a likelihood of developing lifestyle-related diseases from health check data. In this paper, we focus on the fluctuation of hemoglobin A1c (HbA1c) value, which deeply connected with diabetes onset. Here we predict incensement of HbA1c value and examine which kind of health checkup item has important role for HbA1c fluctuation. Our experimental results show that, when we classify the subjects according to their gender and triglyceride (TG) fluctuation value, we will effectively evaluate the risk of diabetes onset for each class.

The Möbius cube is a variant of the hypercube. Its advantage is that it can connect the same number of nodes as a hypercube but with almost half the diameter of the hypercube. We propose an algorithm to solve the node-to-node disjoint paths problem in n-Möbius cubes in polynomial-order time of n. We provide a proof of correctness of the algorithm and estimate that the time complexity is O(n2) and the maximum path length is 3n-5.

The rapid development of information techniques has lead to more and more high-dimensional datasets, making classification more difficult. However, not all of the features are useful for classification, and some of these features may even cause low classification accuracy. Feature selection is a useful technique, which aims to reduce the dimensionality of datasets, for solving classification problems. In this paper, we propose a modified bat algorithm (BA) for feature selection, called MBAFS, using a SVM. Some mechanisms are designed for avoiding the premature convergence. On the one hand, in order to maintain the diversity of bats, they are guided by the combination of a random bat and the global best bat. On the other hand, to enhance the ability of escaping from local optimization, MBAFS employs one mutation mechanism while the algorithm trapped into local optima. Furthermore, the performance of MBAFS was tested on twelve benchmark datasets, and was compared with other BA based algorithms and some well-known BPSO based algorithms. Experimental results indicated that the proposed algorithm outperforms than other methods. Also, the comparison details showed that MBAFS is competitive in terms of computational time.

The user authorization query (UAQ) problem determines whether there exists an optimum set of roles to be activated to provide a set of permissions requested by a user. It has been deemed as a key issue for efficiently handling user's access requests in role-based access control (RBAC). Unfortunately, the weight is a value attached to a permission/role representing its importance, should be introduced to UAQ, has been ignored. In this paper, we propose a comprehensive definition of the weighted UAQ (WUAQ) problem with the role-weighted-cardinality and permission-weighted-cardinality constraints. Moreover, we study the computational complexity of different subcases of WUAQ, and show that many instances in each subcase are intractable. In particular, inspired by the idea of the genetic algorithm, we propose an algorithm to approximate solve an intractable subcase of the WUAQ problem. An important observation is that this algorithm can be efficiently modified to handle the other subcases of the WUAQ problem. The experimental results show the advantage of the proposed algorithm, which is especially fit for the case that the computational overhead is even more important than the accuracy in a large-scale RBAC system.

We present the first demonstration of an electro-optic modulator based on a photolithographically fabricated photonic crystal (PhC) nanocavity with a p-i-n junction with SiO2 cladding. We show that the device exhibits an ultrahigh quality factor (Q∼105) and allow us to demonstrate electro-optic modulation through the integrated p-i-n diode structure. We demonstrate an electro-optic modulation based on the carrier injection.

Improved fractional variable tap-length adaptive algorithm that contains Sigmoid limited fluctuation function and adaptive variable step-size of tap-length based on fragment-full error is presented. The proposed algorithm can solve many deficiencies in previous algorithm, comprising small convergence rate and weak anti-interference ability. The parameters are able to modify reasonably on the basis of different situations. The Sigmoid constrained function can decrease the fluctuant amplitude of the instantaneous errors effectively and improves the ability of anti-noise interference. Simulations demonstrate that the proposed algorithm equips better performance.

This paper presents some results of an experimental trial for the 5th generation (5G) wireless communication systems using 28GHz band. In order to tackle rapidly increasing traffic for 2020 and beyond, new radio access networks for the 5G mobile communication systems will introduce the use of higher frequency bands such as spectra higher than 10GHz to achieve higher capacity and super high bit rate transmission of several tens of Gbps. The target of this experimental trial is to evaluate the feasibility of using the 28GHz band with super-wide bandwidth of 800MHz for 5G wireless communication systems. To compensate large path-loss in higher frequency, the beamforming (BF) based on Massive multiple-input multiple-output (MIMO) is one of promising techniques and can be combined with spatial multiplexing of multiple data streams to achieve much higher capacity. In addition, to support the mobility of mobile station (MS), beam tracking technique is important. In this trial, we first conduct a basic experiment of single-stream transmission by using prototype system with base station (BS) having 96-element antenna and MS having 8-element antenna to evaluate the effectiveness of joint transmitter/receiver BF in 28GHz band in terms of coverage, impact of path loss, shadowing loss and penetration loss under indoor, outdoor and outdoor-to-indoor (O-to-I) environments. We show that by using 28 GHz band with BF based on Massive MIMO, higher throughput near 1.2Gbps can be achieved at many points in the indoor environment. It is also shown that the throughput of over 1Gbps can be achieved at points around 200m distant from BS in outdoor line-of-site (LOS) environment. Secondly, to evaluate the effectiveness of spatial multiplexing and beam tracking under more realistic environment, we also conduct the outdoor experiment of BF combined with 2-stream spatial multiplexing in high mobility environment with MS speed of up to 60km/h by using smartphone-shape MS antenna. We also show that maximum throughput of 3.77Gbps can be achieved with MS speed of 60km/h by using BF with 2-stream multiplexing and beam tracking.

This work develops a third-order multibit switched-current (SI) delta-sigma modulator (DSM) with a four-bit switched-capacitor (SC) flash analog-to-digital converter (ADC) and an incremental data weighted averaging circuit (IDWA), which is fabricated using 0.18µm 1P6M CMOS technology. In the proposed DSM, a 4-bit SC flash ADC is used to improve its resolution, and an IDWA is used to reduce the nonlinearity of digital-to-analog converter (DAC) by moving the quantization noise out of the signal band by first-order noise shaping. Additionally, the proposed differential sample-and-hold circuit (SH) exhibits low input impedance with feedback and width-length adjustment in the SI feedback memory cell (FMC) to increase the conversion rate. A coupled differential replicate (CDR) common-mode feedforward circuit (CMFF) is used to compensate for the mirror error that is caused by the current mirror. Measurements indicate that the signal-to-noise ratio (SNR), dynamic range (DR), effective number of bits (ENOB), power consumption, and chip area are 64.1 dB, 64.4 dB, 10.36 bits, 18.82 mW, and 0.45 × 0.67 mm2 (without I/O pad), respectively, with a bandwidth of 20 kHz, an oversampling ratio (OSR) of 256, a sampling frequency of 10.24 MHz, and a supply voltage of 1.8 V.

This paper presents a method to realize index generation functions using multiple Index Generation Units (IGUs). The architecture implements index generation functions more efficiently than a single IGU when the number of registered vectors is very large. This paper proves that independent linear transformations are necessary in IGUs for efficient realization. Experimental results confirm this statement. Finally, it shows a fast update method to IGUs.

Named Entity Translation Equivalents extraction plays a critical role in machine translation (MT) and cross language information retrieval (CLIR). Traditional methods are often based on large-scale parallel or comparable corpora. However, the applicability of these studies is constrained, mainly because of the scarcity of parallel corpora of the required scale, especially for language pairs of Chinese and Japanese. In this paper, we propose a method considering the characteristics of Chinese and Japanese to automatically extract the Chinese-Japanese Named Entity (NE) translation equivalents based on inductive learning (IL) from monolingual corpora. The method adopts the Chinese Hanzi and Japanese Kanji Mapping Table (HKMT) to calculate the similarity of the NE instances between Japanese and Chinese. Then, we use IL to obtain partial translation rules for NEs by extracting the different parts from high similarity NE instances in Chinese and Japanese. In the end, the feedback processing updates the Chinese and Japanese NE entity similarity and rule sets. Experimental results show that our simple, efficient method, which overcomes the insufficiency of the traditional methods, which are severely dependent on bilingual resource. Compared with other methods, our method combines the language features of Chinese and Japanese with IL for automatically extracting NE pairs. Our use of a weak correlation bilingual text sets and minimal additional knowledge to extract NE pairs effectively reduces the cost of building the corpus and the need for additional knowledge. Our method may help to build a large-scale Chinese-Japanese NE translation dictionary using monolingual corpora.

The cloud radio access network (C-RAN) is embracing unprecedented popularity in the evolution of current RAN towards 5G. One of the essential benefits of C-RAN is facilitating cooperative transmission to enhance capacity and energy performances. In this paper, we argue that the conventional symmetric coordination in which all antennas participate in transmission does not necessarily lead to an energy efficient C-RAN. Further, the current assessments of energy consumption should be modified to match this shifted paradigm in network architecture. Towards this end, this paper proposes an asymmetric coordination scheme to optimize the energy efficiency of C-RAN. Specifically, asymmetric coordination is approximated and formulated as a joint antenna selection and power allocation problem, which is then solved by a proposed sequential-iterative algorithm. A modular power consumption model is also developed to convert the computational complexity of coordination into baseband power consumption. Simulations verify the performance benefits of our proposed asymmetric coordination in effectively enhancing system energy efficiency.

The compressive sensing (CS) theory has been recognized as a promising technique to achieve the target localization in wireless sensor networks. However, most of the existing works require the prior knowledge of transmitting powers of targets, which is not conformed to the case that the information of targets is completely unknown. To address such a problem, in this paper, we propose a novel CS-based approach for multiple target localization and power estimation. It is achieved by formulating the locations and transmitting powers of targets as a sparse vector in the discrete spatial domain and the received signal strengths (RSSs) of targets are taken to recover the sparse vector. The key point of CS-based localization is the sensing matrix, which is constructed by collecting RSSs from RF emitters in our approach, avoiding the disadvantage of using the radio propagation model. Moreover, since the collection of RSSs to construct the sensing matrix is tedious and time-consuming, we propose a CS-based method for reconstructing the sensing matrix from only a small number of RSS measurements. It is achieved by exploiting the CS theory and designing an difference matrix to reveal the sparsity of the sensing matrix. Finally, simulation results demonstrate the effectiveness and robustness of our localization and power estimation approach.

Biomimetics is a new research field that creates innovation through the collaboration of different existing research fields. However, the collaboration, i.e., the exchange of deep knowledge between different research fields, is difficult for several reasons such as differences in technical terms used in different fields. In order to overcome this problem, we have developed a new retrieval platform, “Biomimetics image retrieval platform,” using a visualization-based image retrieval technique. A biological database contains a large volume of image data, and by taking advantage of these image data, we are able to overcome limitations of text-only information retrieval. By realizing such a retrieval platform that does not depend on technical terms, individual biological databases of various species can be integrated. This will allow not only the use of data for the study of various species by researchers in different biological fields but also access for a wide range of researchers in fields ranging from materials science, mechanical engineering and manufacturing. Therefore, our platform provides a new path bridging different fields and will contribute to the development of biomimetics since it can overcome the limitation of the traditional retrieval platform.

The present paper proposes a dynamic spectrum access policy for multi-hop cognitive radio networks (CRNs), where the transmission in each hop suffers a delay waiting for the communication channel to become available. Recognizing the energy constraints, we assume that each secondary user (SU) in the network is powered by a battery with finite initial energy. We develop an energy-efficient policy for CRNs using the Markov decision process, which searches for spectrum opportunities without a common communication channel and assigns each sensor's decision to every time slot. We first consider a single-sensor scenario. Due to the intermittent activation of the sensor, achieving the optimal sensing schedule requires excessive complexity and is computationally intractable, owing to the fact that the state space of the Markov decision process evolves exponentially with time variance. In order to overcome this difficulty, we propose a state-reduced suboptimal policy by relaxing the constrained state space, i.e., assuming that the electrical energy of a node is infinite, because this state-reduced suboptimal approach can substantially reduce the complexity of decision-making for CRNs. We then analyze the performance of the proposed policy and compare it with the optimal solution. Furthermore, we verify the performance of this spectrum access policy under real conditions in which the electrical energy of a node is finite. The proposed spectrum access policy uses the dynamic information of each channel. We prove that this schedule is a good approximation for the true optimal schedule, which is impractical to obtain. According to our theoretical analysis, the proposed policy has less complexity but comparable performance. It is proved that when the operating time of the CRN is sufficiently long, the data reception rate on the sink node side will converge to the optimal rate with probability 1. Based on the results for the single-sensor scenario, the proposed schedule is extended to a multi-hop CRN. The proposed schedule can achieve synchronization between transmitter and receiver without relying on a common control channel, and also has near-optimal performance. The performance of the proposed spectrum access policy is confirmed through simulation.

With the availability of virtualization extension in mobile processors, e.g. ARM Cortex A-15, multiple virtual execution domains are efficiently supported in a mobile platform. Each execution domain requires high-performance graphics services for full-featured user interfaces such as smooth scrolling, background image blurring, and 3D images. However, graphics service is hard to be virtualized because multiple service components (e.g. ION and Fence) are involved. Moreover, the complexity of Graphical Processing Unit (GPU) device driver also makes harder virtualizing graphics service. In this paper, we propose a technique to virtualize the graphics architecture of Android mobile platform in KVM/ARM environment. The Android graphics architecture relies on underlying Linux kernel services such as the frame buffer memory allocator ION, the buffer synchronization service Fence, GPU device driver, and the display synchronization service VSync. These kernel services are provided as device files in Linux kernel. Our approach is to para-virtualize these device files based on a split device driver model. A major challenge is to translate guest-view of information into host-view of information, e.g. memory address translation, file descriptor management, and GPU Memory Management Unit (MMU) manipulation. The experimental results show that the proposed graphics virtualization technique achieved almost 84%-100% performance of native applications.

Feature extractor is an important component of a tracker and the convolutional neural networks (CNNs) have demonstrated excellent performance in visual tracking. However, the CNN features cannot perform well under conditions of low illumination. To address this issue, we propose a novel deep correlation tracker with backtracking, which consists of target translation, backtracking and scale estimation. We employ four correlation filters, one with a histogram of oriented gradient (HOG) descriptor and the other three with the CNN features to estimate the translation. In particular, we propose a backtracking algorithm to reconfirm the translation location. Comprehensive experiments are performed on a large-scale challenging benchmark dataset. And the results show that the proposed algorithm outperforms state-of-the-art methods in accuracy and robustness.

This paper presents an automatic hierarchical formal verification method for arithmetic circuits over Galois fields (GFs) which are dedicated digital circuits for GF arithmetic operations used in cryptographic processors. The proposed verification method is based on a combination of a word-level computer algebra procedure with a bit-level PPRM (Positive Polarity Reed-Muller) expansion procedure. While the application of the proposed verification method is not limited to cryptographic processors, these processors are our important targets because complicated implementation techniques, such as field conversions, are frequently used for side-channel resistant, compact and low power design. In the proposed method, the correctness of entire datapath is verified over GF(2m) level, or word-level. A datapath implementation is represented hierarchically as a set of components' functional descriptions over GF(2m) and their wiring connections. We verify that the implementation satisfies a given total-functional specification over GF(2m), by using an automatic algebraic method based on the Gröbner basis and a polynomial reduction. Then, in order to verify whether each component circuit is correctly implemented by combination of GF(2) operations, i.e. logic gates in bit-level, we use our fast PPRM expansion procedure which is customized for handling large-scale Boolean expressions with many variables. We have applied the proposed method to a complicated AES (Advanced Encryption Standard) circuit with a masking countermeasure against side-channel attack. The results show that the proposed method can verify such practical circuit automatically within 4 minutes, while any single conventional verification methods fail within a day or even more.