In recent years, deep learning has been widely applied in relation extraction task. The method uses only word embeddings as network input, and can model relations between target named entity pairs. It equally deals with each relation mention, so it cannot effectively extract relations from the corpus with an enormous number of non-relations, which is the main reason why the performance of relation extraction is significantly lower than that of relation classification. This paper designs a deep reinforcement learning framework for relation extraction, which considers relation extraction task as a two-step decision-making game. The method models relation mentions with CNN and Tree-LSTM, which can calculate initial state and transition state for the game respectively. In addition, we can tackle the problem of unbalanced corpus by designing penalty function which can increase the penalties for first-step decision-making errors. Finally, we use Q-Learning algorithm with value function approximation to learn control policy π for the game. This paper sets up a series of experiments in ACE2005 corpus, which show that the deep reinforcement learning framework can achieve state-of-the-art performance in relation extraction task.

Non-contiguous orthogonal frequency-division multiplexing (OFDM) is a promising technique for cognitive radio systems. The secondary users transmit on the selected subcarriers to avoid the frequencies being used by the primary users. However, the out-of-band power (OBP) of the OFDM-modulated tones induces interference to the primary users. Another major drawback of OFDM-based system is their high peak-to-average power ratio (PAPR). In this paper, algorithms are proposed to jointly reduce the OBP and the PAPR for non-contiguous OFDM based on the method of alternating projections onto convex sets. Several OFDM subcarriers are selected to accommodate the adjusting weights for OBP and PAPR reduction. The frequency-domain OFDM symbol is projected onto two convex sets that are defined according to the OBP requirements and the PAPR limits. Each projection iteration solves a convex optimization problem. The projection onto the set constrained by the OBP requirement can be calculated using an iterative algorithm which has low computational complexity. Simulation results show good performance of joint reduction of the OBP and the PAPR. The proposed algorithms converge quickly in a few iterations.

Side match vector quantization (SMVQ) has been originally developed for image compression and is also useful for steganography. SMVQ requires to create its own state codebook for each block in both encoding and decoding phases. Since the conventional method for the state codebook generation is extremely time-consuming, this letter proposes a fast generation method. The proposed method is tens times faster than the conventional one without loss of perceptual visual quality.

This paper experimentally verifies the potential of higher order space division multiplexing in line-of-sight (LOS) channels for multiuser massive MIMO. We previously proposed an inter-user interference (IUI) cancellation scheme and a simplified user scheduling method for Massive Antenna Systems for Wireless Entrance (MAS-WE). In order to verify the effectiveness of the proposed techniques, channel state information (CSI) for a 1×32 SIMO channel is measured in a real propagation environment with simplified test equipment. Evaluations of the measured CSI data confirm the effectiveness of our proposals; they offer good equal gain transmission (EGT) performance, reduced spatial correlation with enlarged angular gap between users, and quite small channel state fluctuation. Link level simulations elucidate that the simple IUI cancellation method is stable in practical conditions. The degradation in symbol error rate with the measured CSI, relative to that yielded by the output of the theoretical LOS channel model, is insignificant.

For some applications, it has been known that stochastic computing (SC) has many potential advantages compared with conventional computation on binary radix encoding. Thus, there has been proposed many design methodologies to realize SCs. Recently, a general design method to realize SC operations by designing Boolean circuits (functions) has been proposed. As a central part of the method, we need to design a logic circuit such that its output becomes 1 with a certain desired probability with respect to random inputs. Also, to realize an SC arithmetic operation with a constant value, in some situations we need to prepare a random bit-stream that becomes 1 with a desired probability from a set of predetermined physical random sources. We call such a bit-stream as a stochastic number (SN). We can utilize the above-mentioned previous method to prepare stochastic numbers by designing Boolean circuits. The method assumes all the random sources become 1 with the same probability 1/2. In this paper, we investigate a different framework where we can prepare different probabilities of each stochastic number in the physical random sources. Then, this paper presents the necessary and sufficient condition of given random inputs in order to produce a stochastic number with a given specified precision. Based on the condition, we can propose a method to generate a stochastic number by using the minimum number of random inputs. Indeed our method uses much less number of inputs than the previous method, and our preliminary experiment shows that the generated circuits by our method also tend to be smaller than the ones by the previous method.

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.

In this study, an anonymization infrastructure for the secondary use of data is proposed. The proposed infrastructure can publish data that includes privacy information while preserving the privacy by using anonymization techniques. The infrastructure considers a situation where ill-motivated users redistribute the data without authorization. Therefore, we propose a watermarking method for anonymized data to solve this problem. The proposed method is implemented, and the proposed method's tolerance against attacks is evaluated.

Index generation functions model content-addressable memory, and are useful in virus detectors and routers. Linear decompositions yield simpler circuits that realize index generation functions. This paper proposes a balanced decision tree based heuristic to efficiently design linear decompositions for index generation functions. The proposed heuristic finds a good linear decomposition of an index generation function by using appropriate cost functions and a constraint to construct a balanced tree. Since the proposed heuristic is fast and requires a small amount of memory, it is applicable even to large index generation functions that cannot be solved in a reasonable time by existing heuristics. This paper shows time and space complexities of the proposed heuristic, and experimental results using some large examples to show its efficiency.

To drastically increase the splitting ratio of extended-reach (40km span) time- and wavelength-division multiplexed passive optical networks (WDM/TDM-PONs), we modify the gain control scheme of our automatic gain controlled semiconductor optical amplifiers (AGC-SOAs) that were developed to support upstream transmission in long-reach systems. While the original AGC-SOAs are located outside the central office (CO) as repeaters, the new AGC-SOAs are located inside the CO and connected to each branch of an optical splitter in the CO. This arrangement has the potential to greatly reduce the costs of CO-sited equipment as they are shared by many more users if the new gain control scheme works properly even when the input optical powers are low. We develop a prototype and experimentally confirm its effectiveness in increasing the splitting ratio of extended-reach systems to 512.

This paper studies the multi-link multi-antenna amplify-and-forward (AF) relay system, in which multiple source-destination pairs communicate with the aid of an energy harvesting (EH)-enabled relay and the relay utilizes the power splitting (PS) protocol to accomplish simultaneous EH and information forwarding (IF). Specifically, independent PS, i.e., allow each antenna to have an individual PS factor, and cooperative power allocation (PA) i.e., adaptively allocate the harvested energy to each channel, are proposed to increase the signal processing degrees of freedom and energy utilization. Our objective is to maximize the minimum rate of all source-destination pairs, i.e., the max-min rate, by jointly optimizing the PS and PA strategies. The optimization problem is first established for the ideal channel state information (CSI) model. To solve the formulated non-convex problem, the optimal forwarding matrix is derived and an auxiliary variable is introduced to remove the coupling of transmission rates in two slots, following which a bi-level iteration algorithm is proposed to determine the optimal PS and PA strategy by jointly utilizing the bisection and golden section methods. The proposal is then extended into the partial CSI model, and the final transmission rate for each source-destination pair is modified by treating the CSI error as random noise. With a similar analysis, it is proved that the proposed bi-level algorithm can also solve the joint PS and PA optimization problem in the partial CSI model. Simulation results show that the proposed algorithm works well in both ideal CSI and partial CSI models, and by means of independent PS and cooperative PA, the achieved max-min rate is greatly improved over existing non-EH-enabled and EH-enabled relay schemes, especially when the signal processing noise at the relay is large and the sources use quite different transmit powers.

In this paper, the recent advances in cooperative distributed antenna transmission (CDAT) are introduced for spatial diversity and multi-user spatial multiplexing in 5G mobile communications network. CDAT is an advanced version of the coordinated multi-point (CoMP) transmission. Space-time block coded transmit diversity (STBC-TD) for spatial diversity and minimum mean square error filtering combined with singular value decomposition (MMSE-SVD) for multi-user spatial multiplexing are described under the presence of co-channel interference from adjacent macro-cells. Blind selected mapping (blind SLM) which requires no side information transmission is introduced in order to suppress the increased peak-to-average signal power ratio (PAPR) of the transmit signals when CDAT is applied. Some computer simulation results are presented to confirm the effectiveness of CDAT techniques.

Ultra-wideband millimeter wave radars significantly enhance the capabilities of three-dimensional (3D) imaging sensors, making them suitable for short-range surveillance and security purposes. For such applications, developed the range point migration (RPM) method, which achieves highly accurate surface extraction by using a range-point focusing scheme. However, this method is inaccurate and incurs great computation cost for complicated-shape targets with many reflection points, such as the human body. As an essential solution to this problem, we introduce herein a range-point clustering algorithm that exploits, the RPM feature. Results from numerical simulations assuming 140-GHz millimeter wavelength radar verify that the proposed method achieves remarkably accurate 3D imaging without sacrificing computational efficiency.

The growing demand for high-speed data communication has continued to meet the need for ever-increasing I/O bandwidth in recent VLSI systems. However, signal integrity issues, such as intersymbol interference (ISI) and reflections, make the channel band-limited at high-speed data rates. We propose high-speed data transmission techniques for VLSI systems using Tomlinson-Harashima precoding (THP). Because THP can eliminate ISI by inverting the characteristics of channels with limited peak and average power at the transmitter, it is suitable for implementing advanced low-voltage and high-speed VLSI systems. This paper presents a novel double-rate THP equalization technique especially intended for multi-valued data transmission to further improve THP performance. Simulation and measurement results show that the proposed THP equalization with a double sampling rate can enhance the data transition time and, therefore, improve the eye opening.

In this paper, the problem of channel estimation in orthogonal frequency-division multiplexing systems over fast time-varying channel is investigated by using a Basis Expansion Model (BEM). Regarding the effects of the Gibbs phenomenon in the BEM, we propose a new method to alleviate it and reduce the modeling error. Theoretical analysis and detail comparison results show that the proposed BEM method can provide improved modeling error compared with other BEMs such as CE-BEM and GCE-BEM. In addition, instead of using the frequency-domain Kronecker delta structure, a new clustered pilot structure is proposed to enhance the estimation performance further. The new clustered pilot structure can effectively reduce the inter-carrier interference especially in the case of high Doppler spreads.

Recently, numerous methods have been proposed to tackle the problem of fine-grained image classification. However, rare of them focus on the pre-processing step of image alignment. In this paper, we propose a new pre-processing method with the aim of reducing the variance of objects among the same class. As a result, the variance of objects between different classes will be more significant. The proposed approach consists of four procedures. The “parts” of the objects are firstly located. After that, the rotation angle and the bounding box could be obtained based on the spatial relationship of the “parts”. Finally, all the images are resized to similar sizes. The objects in the images possess the properties of translation, scale and rotation invariance after processed by the proposed method. Experiments on the CUB-200-2011 and CUB-200-2010 datasets have demonstrated that the proposed method could boost the recognition performance by serving as a pre-processing step of several popular classification algorithms.

IEEE 802.11ah is an emerging wireless LAN standard in the sub-1-GHz license-exempt bands for cost-effective and range-extended communication. One of the most challenging issues that need to be overcome in relation to IEEE 802.11ah is to ensure that thousands of stations are able to associate efficiently with a single access point. During network initialization, several thousand stations try to associate with the access point, leading to heavy channel contention and long association delay. Therefore, IEEE 802.11ah has introduced an authentication control mechanism that classifies stations into groups and only a small number of stations in a group are allowed to access the medium in a beacon interval. This grouping strategy provides fair channel access to a large number of stations. However, the approach to grouping the stations and determining the best group size is undefined in the draft of IEEE 802.11ah. In this paper, we first model the authentication/association in IEEE 802.11ah. Our analysis shows that there exists the best group size that results in minimal association delay. Consequently, the analytical model is extended to determine the best group size. Finally, an enhanced authentication control algorithm, which utilizes the best group size to provide the minimum association delay, is proposed. The numerical and the simulation results we obtained with the proposed method demonstrate that our method succeeds in minimizing the association delay.

The Internet of Things (IoT) is defined as a global infrastructure for the Information Society, enabling advanced services by interconnecting (physical and virtual) things based on, existing and evolving, interoperable information and communication technologies by ITU-T. Data may be communicated in low-power and lossy environments, which causes complicated security issues. Furthermore, concerns are raised over access of personally identifiable information pertaining to IoT devices, network and platforms. Security and privacy concerns have been main barriers to implement IoT, which needs to be resolved appropriate security and privacy measures. This paper describes security threats and privacy concerns of IoT, surveys current studies related to IoT and identifies the various requirements and solutions to address these security threats and privacy concerns. In addition, this paper also focuses on major global standardization activities for security and privacy of Internet of Things. Furthermore, future directions and strategies of international standardization for theInternet of Thing's security and privacy issues will be given. This paper provides guidelines to assist in suggesting the development and standardization strategies forward to allow a massive deployment of IoT systems in real world.

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.

The use of flash memory based storage devices is rapidly increasing, and user demands for high performance are also constantly increasing. The performance of the flash storage device is greatly influenced by cleaning operations of Flash Translation Layer (FTL). Various studies have been conducted to lower the cost of cleaning operations. However, there are limits to achieve sufficient performance improvement of flash storages without help of a host system, with only limited information in storage devices. Recently, SCSI, eMMC, and UFS standards provide an interface for sending semantic information from a host system to a storage device. In this paper, we analyze effects of semantic information on performance and lifetime of flash storage devices. We evaluate performance and lifetime improvement through SA-FTL (Semantic Aware Flash Translation Layer), which can take advantage of semantic information in storage devices. Experiments show that SA-FTL improves performance and lifetime of flash based storages by up to 30 and 35%, respectively, compared to a simple page-level FTL.

Hybrid vehicles (HVs) and electric vehicles (EVs) have become widespread. These vehicles incorporate a large number of electronic devices, which requires the use of a high-voltage (200 V) battery. Power electronics devices driven by the 200 V battery is expected to increase in the future. As such, we herein propose a power line communication (PLC) method that uses a high-voltage power line. In the present paper, we first clarify the transmission channel through modeling of an equivalent circuit and channel measurement. We then conduct noise measurements and determine the noise characteristics of the proposed PLC. Finally, we evaluate the bit error rate performance through computer simulations based on the measured transmission channel and noise.