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Aspect-based sentiment analysis is an important task in fine-grained sentiment analysis, which aims to infer the sentiment towards a given aspect. Previous studies have shown notable success when sufficient labeled training data is available. However, annotating adequate data is labor-intensive, which sets substantial barriers for generalizing the sentiment predictor to the new domain. Two main challenges exist in cross-domain aspect-based sentiment analysis. One challenge is acquiring the domain-invariant knowledge; the other challenge is mining the syntactic-related words towards the aspect-term. In this article, we propose a transformer-based semantic-primary knowledge transferring network (TSPKT) for cross-domain aspect-term sentiment analysis, which utilizes semantic-primary knowledge as a bridge to enable knowledge transfer across domains. Specifically, we first build an S-Graph from external semantic lexicons, and extract the semantic-primary knowledge from the S-Graph. Second, AoaGraphormer is proposed to learn the syntactically relevant words towards the aspect-term. Third, we extend the standard biLSTM classifier to fully integrate the semantic-primary knowledge by adding a novel knowledge-aware memory unit (KAMU) to the biLSTM cell. Extensive experiments on six cross-domain setups demonstrate the superiority of TSPKT against the state-of-the-art baseline methods. [ABSTRACT FROM AUTHOR]

A family of interleaved boost converters and an original systematic derivation method based on the two-phase interleaved inverse-coupled inductor concept are proposed in this article for battery discharging in spacecraft applications. The family, including 14 converters, is generated by interconnecting multiple pulsating voltage cells through the energy storage cells. The basic pulsating voltage cells are derived from an inverse-coupled boost converter, and the energy storage cells include an inductor cell, tapped inductor cell, flyback cell, buck-current-fed cell, and partially current-fed cell. The proposed family of converters achieves high efficiency, step-up power conversion without the right-half-plane zero effect, continuous output current and low side switch driver. The operational principle and small-signal analysis of a representative topology in the proposed family of converters are discussed in detail. Moreover, experimental and simulation results are presented to verify the feasibility and effectiveness of the developed converter. Finally, the characteristics of the proposed family of converters are compared with other state-of-the-art converters. [ABSTRACT FROM AUTHOR]

We propose a partial point cloud completion approach for scenes that are composed of multiple objects. We focus on pairwise scenes where two objects are in close proximity and are contextually related to each other, such as a chair tucked in a desk, a fruit in a basket, a hat on a hook and a flower in a vase. Different from existing point cloud completion methods, which mainly focus on single objects, we design a network that encodes not only the geometry of the individual shapes, but also the spatial relations between different objects. More specifically, we complete missing parts of the objects in a conditional manner, where the partial or completed point cloud of the other object is used as an additional input to help predict missing parts. Based on the idea of conditional completion, we further propose a two-path network, which is guided by a consistency loss between different sequences of completion. Our method can handle difficult cases where the objects heavily occlude each other. Also, it only requires a small set of training data to reconstruct the interaction area compared to existing completion approaches. We evaluate our method qualitatively and quantitatively via ablation studies and in comparison to the state-of-the-art point cloud completion methods. [ABSTRACT FROM AUTHOR]

In the analytic hierarchy process (AHP), the reciprocal matrix is generated based on the pairwise comparisons completed among all the alternatives or attributes under consideration. To ensure reliability and validity of the decision solution, a certain modification of entries of the matrix is usually needed to improve the consistency of the reciprocal matrix. This study aims to present a consistency improvement method by admitting some level of information granularity in the evaluation process. This gives rise to a granular rather than numeric matrix of pairwise comparisons. First, with a given average level of information granularity, we present an optimal granularity model that is characterized by maximal consistency. One can maximize the consistency degree by invoking a process of allocation of information granularity across the corresponding modifications of the reciprocal matrix. Based on the optimal granularity model, an interactive consistency improvement process is presented with the involvement of the decision maker. Then, an adaptive differential evolution algorithm is applied to optimize entries of the modified reciprocal matrix. Detailed experiments along with a thorough comparative analysis are completed to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Deep convolutional neural networks (DCNNs) have been proposed as enhanced developments of neural networks (NNs) in the field of artificial intelligence (AI) and successfully applied in deep learning (DL) scenarios. With the advancement of technology, the number of network layers has continuously increased, resulting in a huge number of calculations and memory accesses required in the training and inference process of DCNNs and thereby hindering their further deployment and application. Using a specific dataflow formed by reusable DCNN data in the network-on-chip (NoC), reducing the memory access pressure and improving DCNN processing efficiency has become a promising acceleration scheme for the current DCNN. In this article, a novel convolution layer (CONV) acceleration strategy based on logical PE set segmentation for row stationary (RS) dataflow is proposed to solve the problems of low flexibility and inefficient processing array utilization faced by the conventional folding mapping strategy. The simulation results show that the new mapping strategy based on PE set segmentation can achieve better processing element utilization and CONV acceleration improvement at the expense of little increase in the data movement energy consumption compared with the conventional strategy. [ABSTRACT FROM AUTHOR]

Annealing effects on optical losses in silica optical fiber drawn from 3D-printed preform were investigated. An irreversible reduction in loss was observed through multiple annealing cycles at a temperature $T =$ 800 ° C. Changes in Raman spectroscopy confirm densification of the core as the stresses in glass relax with annealing. The temperature-dependent loss in the 3D printed fiber is consistent with modal field overlap at the core-cladding interface. [ABSTRACT FROM AUTHOR]

Lidar is an important sensor of the autonomous driving system to detect environmental obstacles, but the spatial distribution of its point cloud is non-uniform because of the scanning mechanism. For adaption to this spatial non-uniformity, a dynamic clustering algorithm is proposed based on the spatial distribution analysis of the point cloud along different directions. The proposed algorithm adopts an elliptical function to describe the neighbor, whose semi-minor and semi-major are adjusted dynamically according to the position of the core point. Base on the relationship analysis of different clustering parameters, they are further designed quantitatively by KITTI dataset considering comprehensive clustering performances. To validate the effectiveness of the proposed algorithm, several comparative experiments with different clustering methods and projection planes have been conducted in the campus by an electric sedan equipped with three IBEO LUX 8 lidars. The experimental results show that the proposed elliptical neighbor can deal with the uneven point cloud more effectively, the performances of over-segmentation, under- segmentation and missed detection all are improved and accordingly a higher detection accuracy is achieved. [ABSTRACT FROM AUTHOR]

Information granules are concise abstract descriptors of data supported by experimental evidence. They summarize the data by forming a small collection of well justified information granule. Fuzzy sets of type-2 generalize type-1 fuzzy sets. In this article, we present an original design of interval type-2 information granules based on a collection of type-1 fuzzy sets by engaging the principle of justifiable granularity. This principle generates an information granule by maximizing a product of two generic characteristics of the granule, such as coverage and specificity. Given a collection of type-1 fuzzy sets, the result of the principle comes in a form of a single type-2 information granule. In general, we emphasize the effect of type elevation of information granules by stressing that a family of type-n information granules gives rise to a single type-(n+1) information granule. The overall optimization process is discussed along with a series of related optimization procedures. A series of experimental studies is included to illustrate the essence of the approach. [ABSTRACT FROM AUTHOR]

The analytic hierarchy process (AHP) is widely employed to guide the decision-maker to rank or evaluate the alternatives in decision activities. Its fuzzy set-based version, i.e., the fuzzy AHP, has also been widely studied and applied since its inception. The essential distinction between the AHP and fuzzy AHP comes from the diverse transformation methods between the linguistic and numeric judgments. In this article, we conduct a thorough comparative study between the AHP and fuzzy AHP methods in the framework of two linguistic models, i.e., the linguistic model based on the membership functions and two-tuple linguistic model. First, four AHP and three fuzzy AHP methods are revisited with the involvement of two linguistic models. Then, the comparison criteria are involved by calculating the cardinal or ordinal deviation between the original information and decision solutions, and the effects of the transitivity of the reciprocal matrix are also discussed in the comparative study. Finally, the detailed experiments along with a thorough comparative analysis are conducted based on the random and publicly available data to show the difference between the AHP and fuzzy AHP methods. [ABSTRACT FROM AUTHOR]

Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique investigated for the treatment of various neuropsychiatric disorders such as major depressive disorder and obsessive-compulsive disorder. Coil design and analysis has been a popular topic in TMS studies, primarily as the coil geometry significantly affects the induced electric field ($E$ -field) distribution. In this work, we compare the distribution of the induced $E$ -field of 16 different TMS coils by finite element analysis. The coils are positioned at two head locations: the vertex and the dorsolateral prefrontal cortex (DLPFC). Due to the coil geometry, only nine of the 16 coils are positioned at the DLPFC. Notably, the authors use 50 heterogeneous head models derived from MRI scans of healthy patients in this analysis. As a result, the sensitivity of the $E$ -field intensity and focality to anatomical variations is investigated. The maximum $E$ -field intensity induced in the brain ($E$ -Max brain), and the volume in the brain exposed to the $E$ -field with at least half the $E$ -Max ($V$ -Half) were metrics used to assess the intensity and focality of the induced $E$ -field. It was observed that some of the coils induced high $E$ -field intensity and were highly sensitive to anatomical variations. Other coils exhibited high focality and lower sensitivity to anatomical variations at the same time. For the coils positioned at the DLPFC, less variability was observed when compared to the vertex location. This study provides an understanding of the effect of coil geometry and anatomical variation on the induced $E$ -field during TMS. [ABSTRACT FROM AUTHOR]

In group decision-making, the consensus reaching process (CRP) is usually designed as an interactive discussion and negotiation process to guide decision-makers in modifying their opinions. In CRP, consensus measure may mean agreement among most but not all the decision-makers, and the actual or virtual moderator may provide modification suggestions with his/her own interests besides the consensus-oriented suggestions. With consideration of fuzzy consensus and private interest of the moderator, this article presents two optimal feedback mechanisms with private interest (PIFM), which aim to minimize the consensus cost with an established consensus threshold and maximize the fuzzy consensus measure with a given cost budget. First, the fuzzy consensus measure is defined by means of specificity and coverage of information granule. Then, two PIFMs based on the minimum consensus cost and maximum fuzzy consensus are proposed to obtain the optimal modified individual opinions, and these two PIFMs are equivalently transformed into the mixed 0–1 programming models. In what follows, we develop an interactive CRP based on the proposed PIFMs, where the optimal modified individual opinions are considered as the modification references in the feedback mechanism. Finally, detailed experiment studies are conducted to demonstrate the effectiveness and validity of the proposed methods. [ABSTRACT FROM AUTHOR]

With the growing penetration of power electronic converters in power systems, the issue of reliability becomes more critical than ever before. This paper proposes a hierarchical reliability framework to evaluate the electric power system reliability from the power electronic converter level to the overall system level. On the converter level, the reliability model of a power electronic converter is developed based on the power electronic devices it is composed of, for which various hourly based input profiles and converter topologies are considered. On the system level, reliability metrics such as expected energy not served (EENS) and loss of load expectation (LOLE) are estimated through a non-sequential Monte Carlo simulation. Machine learning regression models, such as support vector regression (SVR), and random forests (RF) are implemented to bridge the nonlinear reliability relationship between two levels. The proposed framework is demonstrated through the modified IEEE Reliability Test System (RTS) 24-bus network. Numerical results show power converter reliability should be considered as an important factor when evaluating overall system reliability performance. [ABSTRACT FROM AUTHOR]

Quite often, complex systems or phenomena are observed from various points of view yielding the particular subsets of data usually being composed of locally available attributes. Such datasets give rise to individual models. As is reflective of the local behavior of the system (global data), each model can produce different, albeit similar results. A critical issue is to aggregate the results coming from the individual models. In virtue of the diversity of the produced results, the aggregation process has to be reflective of this variety. Equally important is a way of quantifying the diversity of the individual results. In this article, we provide an efficient and original way of aggregation of the results by engaging a principle of justifiable granularity and in this manner leading to interval-valued results summarizing the results produced by a collection of models. We develop an overall design process and discuss the associated optimization mechanism leading to a granular fuzzy model of a global nature. The detailed scheme of the principle of justifiable granularity is discussed along with the related performance indexes; in particular, two modes of design of information granules are investigated. The quality of the granular model is quantified with the aid of the criteria of coverage and specificity. [ABSTRACT FROM AUTHOR]

A major landslide in Nanyu township, Zhouqu county, Western China, occurred on July 12, 2018, causing widespread damage and blocking the Bailong river. As a widely used surface deformation measurement technique, persistent scatterer interferometry (PSI) method fails in the precursory slope deformation detection over Nanyu landslide for two reasons: the high rate slope deformation of the landslide body before the occurrence of the disaster and the low density of measurement points in the widespread nonurban regions over hillside area. To solve these problems, a two-step multitemporal interferometric synthetic aperture radar (MTInSAR) method is proposed in this letter. In the proposed method, first, a carefully designed small baseline subsets (SBASs) method is applied to extract the linear high rate deformation component, which is then subtracted from the wrapping interferogram to reduce the likelihood of signal aliasing. In the second step, a two-tier network-based MTInSAR method by exploiting both persistent scatterers (PSs) and distributed scatterers (DSs) is employed to retrieve the residual deformation. The proposed method is applied to 47 Sentinel-1 images acquired between December 2016 and July 2018 and successfully detects the precursory deformation over Nanyu landslide for the first time. Experiment results illustrate the advantage of the proposed method for measuring high rate deformation compared with the traditional PSI. By using the proposed algorithm, the deformation rate map shows a clear landslide boundary and precursors of the rapid slope movements with a maximum displacement rate of 483 mm/year along the line of sight of the satellite. [ABSTRACT FROM AUTHOR]

The impact of thermal quenching on the photostability of bismuth active center (BAC) is investigated through measuring the photo-bleaching process under 830 nm irradiation in quenched Bi/Er co-doped fiber (BEDF). By fitting with the stretched-exponential model, the emission intensity ascribed to the photostable BAC associated with silica (BAC-Si) at 1400 nm (I($\infty $)), unbleachable ratio $(\gamma _{\textrm {UB}})$ and bleaching time $(\tau _{\mathbf {B}})$ are obtained. Compared to the untreated sample, the $\text{I}(\infty) $ increases with higher temperature or a longer dwell time, while both the $\gamma _{\textrm {UB}}$ and $\tau _{\mathbf {B}}$ decrease. The results show that BAC-Si could be bleached faster, while additional amount of BAC-Si could be retained in thermally quenched samples. Besides, the lower photostability of the newly quenching activated BAC, impacted by different quenching conditions, is estimated. [ABSTRACT FROM AUTHOR]

A microwave frequency measurement system utilizing the optical injection technology in a semiconductor laser is proposed. A single-wavelength optical carrier is generated and divided into two parts. One part is intensity-modulated by a control signal with a triangular shape and then injected into a semiconductor laser to generate a frequency scanning optical sideband. The other part is modulated by the microwave signal under test, which is then coupled with the frequency scanning optical sideband and detected by a photodetector (PD). The output of the PD is filtered by an electrical passband filter and detected by an envelope detector. Electrical pulses will be obtained with the time interval proportional to the microwave frequency. Thus the microwave frequency can be retrieved from the time interval of the generated pulses. A proof of concept experiment is taken. The microwave frequency measurement from 3 to 40 GHz is achieved, and the frequency measurement errors are within ±30 MHz. [ABSTRACT FROM AUTHOR]

The impact of dispersion effects on temporal-convolution-based real-time Fourier transformation (RTFT) systems, including the residual 2nd-order dispersion effect, the 3rd-order dispersion effect, and their joint effect, is theoretically analyzed. To reduce these effects, an optical RTFT system based on a bidirectional chirped fiber Bragg grating (CFBG) and an optical filter is proposed. Only one optical pulse source, a bidirectional CFBG, a Mach–Zehnder modulator (MZM) and a photodetector (PD) are needed. RTFT with a bandwidth of 40 GHz and a frequency resolution of 0.7 GHz has been experimentally achieved. [ABSTRACT FROM AUTHOR]

This paper proposes a quadrature-shaped pickup coil, which can realize an angular-misalignment insensitive omnidirectional wireless charging system. Recently, the three-dimensional wireless charging has shown promising prospects for removing the performance deterioration caused by the positional misalignment, which can transfer power to arbitrary spatial objectives. In the conventional design, the strength and the direction of the induced magnetic field can be adjusted by controlling the excitation currents of transmitting coils. However, the existence of angular misalignment caused by the self-rotation of the pickup unit still can result in a sharp decrease of the transmitted power. Accordingly, this paper proposes and implements a novel pickup coil topology to compensate such huge fluctuations in power transfer, which aims to ensure an angular misalignment insensitive omnidirectional wireless charging. Simulated and experimental results are both given to verify the feasibility of the proposed quadrature-shaped topology. [ABSTRACT FROM AUTHOR]

In this article, an improved polarization interference method is proposed for fiber birefringence measurement. This method uses two different lengths of a birefringence fiber with their birefringent axes orthogonally coupled to compensate the phase difference and achieve the required pitch in interferogram for determining birefringence accurately. Experiments and analysis demonstrate that the method could offer improved accuracy and expanded range in birefringence measurement with relatively low spectral resolution systems. [ABSTRACT FROM AUTHOR]

Optical networks on chip (ONoC) has been proposed as a promising alternative paradigm for electronic NoC with the benefit of optical signaling communications such as ultrahigh bandwidth, extremely low energy consumption, and negligible transmission latency. To accommodate the layout of tile-based chip multicore processors, a torus-based passive ONoC architecture, TAONoC, is proposed in this paper. Relying on the unique designs of three function modules, TAONoC can still support contention-free communication without the need for arbitration. TAONoC employs comb switches instead of general microring resonators (MRs). TAONoC has a low demand for the number of MRs because of the ultrahigh utilization of resonant wavelengths owned by a single MR. Simulation results show that TAONoC performs well under three different synthetic traffic patterns. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal design of quadrature-shaped pickup to satisfy various demands on performance at special positions for omnidirectional wireless power transfer (WPT). Omnidirectional WPT technology as a brand new way of energy supply has shown great potentials for charging objectives at all directions. In order to ensure the energy can be transmitted to arbitrary spatial directions, the orthogonal structure of three circular transmitting coils has been widely accepted matched with non-identical current control scheme. However, there are still some special positions where the transmitted power drops to the bottom which is not suitable for applications. Accordingly, this paper proposes an optimal design analysis for the quadrature-shaped pickup to satisfy different demands on either power or efficiency at such positions. The simulated analysis and experimental results are both given to verify the enhancement of the proposed quadrature-shaped pickup, which aims to provide a reference to fabricate an appropriate pickup up for utilizations. [ABSTRACT FROM AUTHOR]

A novel approach for simultaneous and instantaneous measurement of the center frequency (CF), bandwidth (BW), pulse width (PW), pulse amplitude (PA), and time of arrival (TOA) of a linear frequency modulation (LFM) pulse signal is proposed and experimentally demonstrated. The approach is based on a linear amplitude comparison function (ACF) obtained by intensity modulation and first-order differentiated phase modulation, which are realized using a polarization modulator, two polarizers, and an optical linear filter. The linearity characteristic of the ACF ensures the ability of the proposed system to measure multiple parameters of an LFM pulse signal. In a proof-of-concept experiment, the measurement errors for CF, BW, PW, PA, and TOA of an LFM pulse are within ±0.3 GHz, ±0.4 GHz, ±120 ps, ±50 mV, and ±15 ps, respectively. Factors affecting the performance of the measurement system, such as the shape, slope, and resolution of the ACF, are discussed. [ABSTRACT FROM AUTHOR]

This paper proposes a framework and its mathematical model for optimal routing and charging of an electric vehicle fleet for high-efficiency dynamic transit systems, while taking into account energy efficiency and charging price. Based on an extended pickup and delivery problem, an optimization model is formulated from the transit service providers’ perspective and is applied to an electric vehicle (EV) fleet with economically efficient but small batteries in very urbanized areas. It aims to determine the best route from the origin to the final destination for each EV to satisfy the welfare of all passengers (e.g., travel time and passengers’ travel distance), while maximizing the energy efficiency (e.g., by reducing fuel and charging cost), subject to local/global constraints (e.g., EV charging station availability and battery state-of-charge dynamics). This optimization model is solved as a mixed-integer quadratically constrained programming problem. This paper also explores the potential impact of EV fleet of dynamic commuter transit services on electric distribution systems, such as increased average load. [ABSTRACT FROM AUTHOR]

In this paper, the low rank prior of abundances of hyperspectral data is explored and combined with semantic information to develop a new Group Low-rank constrained Nonnegative Matrix Factorization (GLrNMF) method for linear hyperspectral unmixing. First, hyperspectral image pixels are divided into several groups of superpixels, and then low-rank constraints are cast on them to explore the semantic geometry in both spatial and spectral domains. By incorporating semantic information into the NMF, we can recover more accurate endmembers and abundances in the linear unmixing model. Some experiments are taken on several synthetic and real hyperspectral data to investigate the performance of GLrNMF, and the results show that it can outperform some state-of-the-art unmixing results. [ABSTRACT FROM PUBLISHER]

Coil design for transcranial magnetic stimulation (TMS) is a critical factor that is constantly being investigated to provide more focused stimulation of the brain. The design of focal coils is important because TMS uses time-varying magnetic fields generated from electromagnetic coils to stimulate a specific region of interest of the brain non-invasively. TMS is a useful tool in both diagnostic and therapeutic purposes for identifying and treating psychiatric and neurological disorders. Currently, TMS is approved by the U.S. Food and Drug Administration for the treatment of chronic depression and is being researched for the treatment of stroke, obsessive compulsive disorder, post-traumatic stress disorder, and Parkinson’s disease. In this paper, the authors are proposing to further improve the focality of the quadruple butterfly coil (QBC) by using a high-permeability ferromagnetic material acting as passive magnetic shield. Analyses of the resulting field profiles with 50 heterogeneous head models using a single and double magnetic shield has been conducted at two different positions in the brain: the vertex and the dorsolateral prefrontal cortex. Comparison of the results has been illustrated with the help of QBC and figure-8 coil by using parameters of interest such as maximum electric field intensities in both the brain and the entire head, the volume of the brain receiving strong stimulation intensities, and the surface area of the brain receiving strong stimulation intensities. There is a significant amount of improvement found in focality when the QBC is used with a magnetic shield. With a shield, the coil is still able to maintain a comparable maximum electric field intensity in the targeted region of the brain to that of the original QBC. Although both shielding solutions show significant improvement, no notable difference has been found in the results between single and double shields with the QBC. [ABSTRACT FROM AUTHOR]

The multitemporal interferometric synthetic aperture radar (InSAR) technique is a potential tool for measuring digital elevation models and surface deformation. It has the advantage of high precision, competitive spatial resolution, and wide coverage. To improve the accuracy of the final results, some adaptive multilook strategies have been proposed in which the identification of statistically homogeneous pixels (SHPs) is the key task. However, these methods are not always reliable in the case of small data sets. To improve this reliability, SHPs are identified based on the adaptive joint data vector comprising of temporal sample and spatial information in this letter. Additionally, the formulation of adaptive joint data vector is combined with local spatial features of SAR images. The presented adaptive multilook approach can be used in many interferometric applications, such as InSAR data filtering and coherence estimation. Experiments on six TerraSAR-X stripmap images of Tianjin in China validate the feasibility and effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]

Optical network-on-chip (ONoC) is a promising technology for future on-chip many-core communications. ONoC can achieve high bandwidth density and low communication latency under low network cost, which leads to an energy-efficient network. Time-division multiplexing (TDM)-based ONoC aims to solve the congestion problem faced by many optical circuit switching (OCS)-based mesh ONoCs. But TDM-based ONoC still suffers fromhigh network polling time, which causes high average network latency, especially under low network load. In this paper, we propose a novel TDMONoC using torus topology and direction-based wavelength assignment, named TTWA. TTWA ONoC combines TDM communication strategy and torus network topology to solve the congestion problem under the heavy network load faced by OCS-based ONoCs.With the utilization of direction-based wavelength assignment and torus topology, we further propose a high-efficiency communication strategy to improve the adjacent inter-cluster parallel communications and decrease the total TDM slot number, which contributes to a smaller network polling time and lower average network latency. A novel optical router is simultaneously designed to meet the communication strategy in TTWA. The analyses and simulation results indicate that TTWA ONoCimproves the polling time compared with other TDM-based ONoCs and achieves better network performance compared with the equivalent OCS-based ONoCs under various synthetic traffic patterns and realistic scientific applications. After the calculation,TTWA ONoC reduces the network insertion loss of OCS-based mesh ONoC 46.92% and that of OCS-based torus ONoC 31.75% and reduces the required laser power of OCS-based mesh ONoC 62.90% and that of OCSbased torus ONoC 40.66% under the worst-case situation. [ABSTRACT FROM PUBLISHER]

Future many-core processors will require high-performance yet energy-efficient on-chip networks to provide a communication substrate for the continually increasing number of cores on one chip. Optical networkon- chip (ONoC) is employed as a promising candidate interconnection solution for its high bandwidth and low energy consumption. However, optical circuit-switching (OCS) based architectures face the problem of high network congestion, low network utilization, and an overhead in power dissipation under heavy loads. In this paper, we propose an ONoC architecture with time-division multiplexing (TDM) and wavelength-division multiplexing (WDM) technology to solve the network contention problem faced by OCSbased ONoC. The number of wavelength groups and timeslots is optimized by using a genetic algorithm. A new optical router is designed to realize our TDM?WDM communication technology. A detailed model is built to analyze insertion loss and crosstalk noise. The simulation results show that TDM?WDM-based ONoC has better performance compared with equivalent OCS-mesh ONoC under a uniform traffic pattern. Similar analysis can be drawn for the real science application based on the PARSEC benchmark. [ABSTRACT FROM PUBLISHER]

The circuit switched optical network on chip (ONoC) is popularly employed since the optical buffer is not available. However, this technique suffers from limited transmission bandwidth, high setup-time overhead, and high network resource contention, which consequentially induces long latency and degraded throughput. In this paper, we propose a new ONoC architecture aiming at ultralow setup cost, improved scalability, and contention-free communication. We first utilize wavelength division multiplexing (WDM) to introduce the basic version of this ONoC with efficient wavelength assignment. A series of potential versions are developed by using multiple waveguides to relieve the pressure on the number of wavelengths. These potential versions can make a tradeoff between required wavelengths and waveguides and improve the scalability. The new architectures employ two layers relying on the interlayer coupler, which contributes to the decrease of crossing losses. The simulation results show that the architecture can achieve 133% saturated bandwidth improvement compared with the traditional mesh ONoC employing WDM technology under the uniform traffic pattern. [ABSTRACT FROM PUBLISHER]

Optical networks-on-chips (ONoCs) have emerged as a promising candidate for the future generation of multicore systems on chips. In ONoCs, an optical circuitswitching mechanism is preferred for its buffer-free mechanism. Unfortunately, blocking is a serious problem that restrains ONoCs from fully utilizing the available bandwidth. In this paper, a network condition-aware communication mechanism is proposed for circuit-switched optical networks-on-chip. The new mechanism employs a new joint metric of predicting the time and the number of blocking packets. The rules are defined according to the new metric for the setup packet, thus increasing the link utilization. Compared with previous methods, the simulation results based on synthetic traffic patterns and PARSEC benchmarks reveal that the proposed mechanism increases the efficiency of links, with higher throughput and lower endto- end latency. [ABSTRACT FROM PUBLISHER]

Recent communication, computation, and technology advances coupled with climate change concerns have transformed the near future prospects of electricity transmission, and, more notably, distribution systems and microgrids. Distributed resources (wind and solar generation, combined heat and power) and flexible loads (storage, computing, EV, HVAC) make it imperative to increase investment and improve operational efficiency. Commercial and residential buildings, being the largest energy consumption group among flexible loads in microgrids, have the largest potential and flexibility to provide demand-side management. Recent advances in networked systems and the anticipated breakthroughs of the Internet of Things will enable significant advances in demand-response capabilities of intelligent load networks of power-consuming devices such as HVAC components, water heaters, EV charging stations, and many more. In this paper, a new operating framework, called packetized direct load control (PDLC), is proposed based on the notion of quantization of energy demand. This control protocol is built on top of two communication protocols that carry either complete or binary information regarding the operation status of appliances. We discuss the optimal demand-side operation for both protocols and analytically derive the performance differences between the protocols. We propose an optimal reservation strategy for traditional and renewable energy for the PDLC in both day-ahead and real-time markets. At the end of the paper, we discuss the fundamental tradeoff between achieving controllability and endowing consumer choice and flexibility. [ABSTRACT FROM AUTHOR]

In order to interface one photovoltaic (PV) port, one bidirectional battery port, and one load port of a PV-battery dc power system, a novel nonisolated three-port dc/dc converter named boost bidirectional buck converter (B3C) and its control method based on three-domain control are proposed in this paper. The power flow and operating principles of the proposed B3C are analyzed in detail, and then, the dc voltage relation between three ports is deduced. The proposed converter features high integration and single-stage power conversion from both PV and battery ports to the load port, thus leading to high efficiency. The current of all three ports is continuous; hence, the electromagnetic noise can be reduced. Furthermore, the control and modulation method for B3C has been proposed for realizing maximum power point tracking (MPPT), battery management, and bus voltage regulation simultaneously. The operation can be transited between conductance mode and MPPT mode automatically according to the load power. Finally, experimental verifications are given to illustrate the feasibility and effectiveness of the proposed topology and control method. [ABSTRACT FROM PUBLISHER]