This paper discusses the collection of sensor data for power distribution systems. In current power distribution systems, this is usually performed solely by the Remote Terminal Unit (RTU) which is located at the root of a power distribution network. The recent rise of distributed power sources, such as photovoltaic generators, raises the demand to increase the frequency of data collection because the output of these distributed generators varies quickly depending on the weather. Increasing data collection frequency in turn requires shortening the time required for data collection. The paper proposes the use of aggregation points for this purpose. An aggregation point can collect sensor data concurrently with other aggregation points as well as with the RTU. The data collection time can be shortened by having the RTU receive data from aggregation points, instead of from all sensors. This approach then poses the problem of finding the optimal location of aggregation points. To solve this problem, the paper proposes a Mixed Integer Linear Problem (MILP) formulation of the problem. The MILP problem can then be solved with off-the-shelf mathematical optimization software. The results of experiments show that the proposed approach is applicable to rather large scale power distribution systems.

The abnormal crowd behavior detection is an important research topic in computer vision to improve the response time of critical events. In this letter, we introduce a novel method to detect and localize the crowd gathering in surveillance videos. The proposed foreground stillness model is based on the foreground object mask and the dense optical flow to measure the instantaneous crowd stillness level. Further, we obtain the long-term crowd stillness level by the leaky bucket model, and the crowd gathering behavior can be detected by the threshold analysis. Experimental results indicate that our proposed approach can detect and locate crowd gathering events, and it is capable of distinguishing between standing and walking crowd. The experiments in realistic scenes with 88.65% accuracy for detection of gathering frames show that our method is effective for crowd gathering behavior detection.

Existing trajectory prediction methods suffer from the “data sparsity” and neglect “time awareness”, which leads to low accuracy. Aiming to the problem, we propose a fast time-aware sparse trajectories prediction with tensor factorization method (TSTP-TF). Firstly, we do trajectory synthesis based on trajectory entropy and put synthesized trajectories into the original trajectory space. It resolves the sparse problem of trajectory data and makes the new trajectory space more reliable. Then, we introduce multidimensional tensor modeling into Markov model to add the time dimension. Tensor factorization is adopted to infer the missing regions transition probabilities to further solve the problem of data sparsity. Due to the scale of the tensor, we design a divide and conquer tensor factorization model to reduce memory consumption and speed up decomposition. Experiments with real dataset show that TSTP-TF improves prediction accuracy generally by as much as 9% and 2% compared to the Baseline algorithm and ESTP-MF algorithm, respectively.

Although Wolf Pack Algorithm (WPA) is a novel optimal algorithm with good performance, there is still room for improvement with respect to its convergence. In order to speed up its convergence and strengthen the search ability, we improve WPA with the Differential Evolution (DE) elite set strategy. The new proposed algorithm is called the WPADEES for short. WPADEES is faster than WPA in convergence, and it has a more feasible adaptability for various optimizations. Six standard benchmark functions are applied to verify the effects of these improvements. Our experiments show that the performance of WPADEES is superior to the standard WPA and other intelligence optimal algorithms, such as GA, DE, PSO, and ABC, in several situations.

The deep neural named entity recognition model automatically learns and extracts the features of entities and solves the problem of the traditional model relying heavily on complex feature engineering and obscure professional knowledge. This issue has become a hot topic in recent years. Existing deep neural models only involve simple character learning and extraction methods, which limit their capability. To further explore the performance of deep neural models, we propose two character feature learning models based on convolution neural network and long short-term memory network. These two models consider the local semantic and position features of word characters. Experiments conducted on the CoNLL-2003 dataset show that the proposed models outperform traditional ones and demonstrate excellent performance.

This paper proposes a semi-supervised source separation method for stereophonic music signals containing multiple recorded or processed signals, where synthesized music is focused on the stereophonic music. As the synthesized music signals are often generated as linear combinations of many individual source signals and their respective mixing gains, phase or phase difference information between inter-channel signals, which represent spatial characteristics of recording environments, cannot be utilized as acoustic clues for source separation. Non-negative Tensor Factorization (NTF) is an effective technique which can be used to resolve this problem by decomposing amplitude spectrograms of stereo channel music signals into basis vectors and activations of individual music source signals, along with their corresponding mixing gains. However, it is difficult to achieve sufficient separation performance using this method alone, as the acoustic clues available for separation are limited. To address this issue, this paper proposes a Cepstral Distance Regularization (CDR) method for NTF-based stereo channel separation, which involves making the cepstrum of the separated source signals follow Gaussian Mixture Models (GMMs) of the corresponding the music source signal. These GMMs are trained in advance using available samples. Experimental evaluations separating three and four sound sources are conducted to investigate the effectiveness of the proposed method in both supervised and semi-supervised separation frameworks, and performance is also compared with that of a conventional NTF method. Experimental results demonstrate that the proposed method yields significant improvements within both separation frameworks, and that cepstral distance regularization provides better separation parameters.

In this letter, we consider a multiple-input multiple-output (MIMO) simultaneous wireless information and power transfer (SWIPT) system, in which the confidential message intended for the information receiver (IR) should be kept secret from the energy receiver (ER). Our goal is to design the optimal transmit covariance matrix so as to maximize the secrecy energy efficiency (SEE) of the system while guaranteeing the secrecy rate, energy harvesting and transmit power constraints. To deal with the original non-convex optimization problem, we propose an alternating optimization (AO)- based algorithm and also prove its convergence. Simulation results show that the proposed algorithm outperforms conventional design methods in terms of SEE.

In X-ray computed tomography, scattered X-rays are generally removed by using a post-patient collimator located in front of the detector. In this paper, we show that the scattered X-rays have the potential to improve the estimation accuracy of the attenuation coefficient in computed tomography. In order to clarify the problem, we simplified the geometry of the computed tomography into a thin cylinder composed of a homogeneous material so that only one attenuation coefficient needs to be estimated. We then conducted a Monte Carlo numerical experiment on improving the estimation accuracy of attenuation coefficient by measuring the scattered X-rays with several dedicated toroidal detectors around the cylinder in addition to the primary X-rays. We further present a theoretical analysis to explain the experimental results. We employed a model that uses a T-junction (i.e., T-junction model) to divide the photon transport into primary and scattered components. This division is processed with respect to the attenuation coefficient. Using several T-junction models connected in series, we modeled the case of several scatter detectors. The estimation accuracy was evaluated according to the variance of the efficient estimator, i.e., the Cramer-Rao lower bound. We confirmed that the variance decreases as the number of scatter detectors increases, which implies that using scattered X-rays can reduce the irradiation dose for patients.

We present a modular way of implementing adaptive decisions in performing scientific simulations. The proposed method employs modern software engineering mechanisms to allow for better software management in scientific computing, where software adaptation has often been implemented manually by the programmer or by using in-house tools, which complicates software management over time. By applying the aspect-oriented programming (AOP) paradigm, we consider software adaptation as a separate concern and, using popular AOP constructs, implement adaptive decision separately from the original code base, thereby improving software management. We demonstrate the effectiveness of our approach with applications to stochastic simulation software.

Multiuser MIMO (MU-MIMO) improves the system channel capacity by generating a large virtual MIMO channel between a base station and multiple user terminals (UTs) with effective utilization of wireless resources. Block beamforming algorithms such as Block Diagonalization (BD) and Block Maximum Signal-to-Noise ratio (BMSN) have been proposed in order to realize MU-MIMO broadcast transmission. The BD algorithm cancels inter-user interference (IUI) by creating the weights so that the channel matrices for the other users are set to be zero matrices. The BMSN algorithm has a function of maintaining a high gain response for each desired user in addition to IUI cancellation. Therefore, the BMSN algorithm generally outperforms the BD algorithm. However, when the number of transmit antennas is equal to the total number of receive antennas, the transmission rate by both BD and BMSN algorithms is decreased. This is because the eigenvalues of channel matrices are too small to support data transmission. To resolve the issue, this paper focuses on an antenna selection (AS) method at the UTs. The AS method reduces the number of pattern nulls for the other users except an intended user in the BD and BMSN algorithms. It is verified via bit error rate (BER) evaluation that the AS method is effective in the BD and BMSN algorithms, especially, when the number of user antennas with a low bit rate (i.e., low signal-to-noise power ratio) is increased. Moreover, this paper evaluates the achievable bit rate and throughput including an actual channel state information feedback based on IEEE802.11ac standard. Although the number of equivalent receive antenna is reduced to only one by the AS method when the number of antennas at the UT is two, it is shown that the throughputs by BD and BMSN with the AS method (BD-AS and BMSN-AS) are higher than those by the conventional BD and BMSN algorithms.

Bug report summarization has been explored in past research to help developers comprehend important information for bug resolution process. As text mining technology advances, many summarization approaches have been proposed to provide substantial summaries on bug reports. In this paper, we propose an enhanced summarization approach called TSM by first extending a semantic model used in AUSUM with the anthropogenic and procedural information in bug reports and then integrating the extended semantic model with the shallow textual information used in BRC. We have conducted experiments with a dataset of realistic software projects. Compared with the baseline approaches BRC and AUSUM, TSM demonstrates the enhanced performance in achieving relative improvements of 34.3% and 7.4% in the F1 measure, respectively. The experimental results show that TSM can effectively improve the performance.

Non-volatile memories are a promising alternative to memory design but data stored in them still may be destructed due to crosstalk and radiation. The data stored in them can be restored by using error-correcting codes but they require extra bits to correct bit errors. One of the largest problems in non-volatile memories is that they consume ten to hundred times more energy than normal memories in bit-writing. It is quite necessary to reduce writing bits. Recently, a REC code (bit-write-reducing and error-correcting code) is proposed for non-volatile memories which can reduce writing bits and has a capability of error correction. The REC code is generated from a linear systematic error-correcting code but it must include the codeword of all 1's, i.e., 11…1. The codeword bit length must be longer in order to satisfy this condition. In this letter, we propose a method to generate a relaxed REC code which is generated from a relaxed error-correcting code, which does not necessarily include the codeword of all 1's and thus its codeword bit length can be shorter. We prove that the maximum flipping bits of the relaxed REC code is still limited theoretically. Experimental results show that the relaxed REC code efficiently reduce the number of writing bits.

This letter proposes a numerical method for approximating the location of and dynamics on a class of chaotic saddles. In contrast to the conventional strategy of maximizing the escape time, our proposal is to impose a zero-expansion condition along transversely repelling directions of chaotic saddles. This strategy exploits the existence of skeleton-forming unstable periodic orbits embedded in chaotic saddles, and thus can be conveniently implemented as a variant of subspace Newton-type methods. The algorithm is examined through an illustrative and another standard example.

In this letter, we study a wireless powered communication network (WPCN) with non-orthogonal multiple access (NOMA), where the user clustering scheme that groups each two users in a cluster is adopted to guarantee the system performance. The two users in a cluster transmit data simultaneously via NOMA, while time division multiple access (TDMA) is used among clusters. We aim to maximize the system throughput by finding the optimal cluster permutation and the optimal time allocation, which can be obtained by solving the optimization problems corresponding to all cluster permutations. The closed-form solution of each optimization problem is obtained by exploiting its constraint structures. However, the complexity of this exhaustive method is quite high, we further propose a sub-optimal clustering scheme with low complexity. The simulation results demonstrate the superiority of the proposed scheme.

By focusing on the recent swing to the centralized approach by the software defined network (SDN), this paper presents a novel network architecture for refactoring the current distributed Internet protocol (IP) by not only utilizing the SDN itself but also implementing its cooperation with the optical transport layer. The first IP refactoring is for flexible network topology reconfiguration: the global routing and explicit routing functions are transferred from the distributed routers to the centralized SDN. The second IP refactoring is for cost-efficient maintenance migration: we introduce a resource portable IP router that can behave as a shared backup router by cooperating with the optical transport path switching. Extensive evaluations show that our architecture makes the current IP network easier to configure and more scalable. We also validate the feasibility of our proposal.

This paper presents low-noise amplifier (LNA)-less 300-GHz CMOS receivers that operate above the NMOS unity-power-gain frequency, fmax. The receivers consist of a down-conversion mixer with a doubler- or tripler-last multiplier chain that upconverts an LO1/n signal into 300 GHz. The conversion gain of the receiver with the doubler-last multiplier is -19.5 dB and its noise figure, 3-dB bandwidth, and power consumption are 27 dB, 27 GHz, and 0.65 W, respectively. The conversion gain of the receiver with the tripler-last multiplier is -18 dB and its noise figure, 3-dB bandwidth, and power consumption are 25.5 dB, 33 GHz, and 0.41 W, respectively. The receivers achieve a wireless data rate of 32 Gb/s with 16QAM. This shows the potential of the moderate-fmax CMOS technology for ultrahigh-speed THz wireless communications.

To realize three-dimensional (3D) optical interconnection on large-scale integration (LSI) circuits, layer-to-layer couplers based on Si-photonics platform were reviewed. In terms of optical cross talk, more than 1 µm layer distance is required for 3D interconnection. To meet this requirement for the layer-to-layer optical coupler, we proposed two types of couplers: a pair of grating couplers with metal mirrors for multi-layer distance coupling and taper-type directional couplers for neighboring layer distance coupling. Both structures produced a high coupling efficiency with relatively compact (∼100 µm) device sizes with a complementary metal oxide semiconductor (CMOS) compatible fabrication process.

This paper introduces a formation method for 3-dimensional 6 ch.×6 ch. shuffling structures with graded-index (GI) circular core in a multimode polymer optical waveguide for optical printed circuit boards (OPCBs) using a unique photomask-free fabrication technique named the Mosquito method. The interchannel pitch of the fabricated waveguides is 250µm, where all the channels consist of both horizontal and vertical bending structures and the last 6 channels in parallel cross over the first 6 channels. We also report 3-dimensional S-shaped polymer waveguides. In the S-shaped waveguides, the first and last 6 channels with both horizontal and vertical core bending composing the above 3-dimensional shuffling waveguide are separated, in order to evaluate the effect of over-crossing on the loss. It is experimentally confirmed that there is no excess insertion loss due to the shuffling structure in the 3-D shuffling waveguide. The evaluated crosstalk of the 3-D shuffling waveguide is lower than -30dB. The 3-D shuffling waveguide proposed in this paper will be a promising component to achieve high bandwidth density wiring for on-board optical interconnects.

Internal quantum efficiency (IQE) is usually estimated from temperature dependence of photoluminescence (PL) intensity by assuming that the IQE at cryogenic temperature is unity. III-nitride samples, however, usually have large defect density, and the assumption is not necessarily valid. In 2016, we proposed a new method to estimate accurate IQE values by simultaneous PL and photo-acoustic (PA) measurements, and demonstratively evaluated the IQE values for various GaN samples. In this study, we have applied the method to InGaN quantum-well active layers and have estimated the IQE values and their excitation carrier-density dependence in the layers.

We discuss our recent progress in photonic crystal nanocavity quantum dot lasers. We show how enhanced light matter interactions in the nanocavity lead to diverse and fascinating lasing phenomena that are in general inaccessible by conventional bulky semiconductor lasers. First, we demonstrate thresholdless lasing, in which any clear kink in the output laser curve does not appear. This is a result of near unity coupling of spontaneous emission into the lasing cavity mode, enabled by the strong Purcell effect supported in the nanocavity. Then, we discuss self-frequency conversion nanolasers, in which both near infrared lasing oscillation and nonlinear optical frequency conversion to visible light are simultaneously supported in the individual nanocavity. Owing to the tight optical confinement both in time and space, a high normalized conversion efficiency over a few hundred %/W is demonstrated. We also show that the intracavity nonlinear frequency conversion can be utilized to measure the statistics of the intracavity photons. These novel phenomena will be useful for developing various nano-optoelectronic devices with advanced functionalities.