This paper presents a 3rd-order ΔΣAD modulator with noise coupling structure using the proposed passive adder embedded quantization noise shaping (QNS) SAR quantizer. QNS SAR quantizer can feedback shaped quantization noise and realize an additional 1st-order noise shaping by noise coupling technique. As a result, the 3rd-order noise coupled ΔΣAD modulator is realized by two integrators with ring amplifier and the QNS SAR quantizer. The SPICE simulation results demonstrate the feasibility of the proposed ΔΣAD modulator in 90nm CMOS technology. Simulated SNDR of 81.05dB is achieved while a sinusoid -4.32dBFS input is sampled at 100MS/s and the bandwidth is BW=3.125MHz. The total power consumption in the modulator is 4.58mW while the supply voltage is 1.2V.

This paper describes a top-down design methodology to optimize resonant capacitance in a wireless power transfer system with 3-D stacked two receivers. A 1:2 selective wireless power transfer is realized by a frequency/time division multiplexing scheme. The power transfer function is analytically formulated and the optimum tuning capacitance is derived, which is validated by comparing with system simulation results. By using the optimized values, power transfer efficiencies at 6.78MHz and 13.56MHz are simulated to be 80% and 84%, respectively, which are <3% worse than a conventional wireless power transfer system.

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.

Development of narrowband thermal emitters whose emission wavelengths are dynamically tunable is highly desired for various applications including the sensing of gases and chemical compounds. In this paper, we review our recent demonstration of wavelength-switchable mid-infrared thermal emitters based on multiple quantum wells (MQWs) and photonic crystals (PCs). Through the control of absorptivity by using intersubband transitions in MQWs and optical resonances in PC slabs, we demonstrate novel control of thermal emission, including realization of high-Q (Q>100) thermal emission, dynamic control of thermal emission (∼MHz), and electrical wavelength switching of thermal emission from a single device.

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.

A PLC based mode multi/demultiplexer based on asymmetric directional coupler has advantages in terms of compactness, mass productivity, low insertion loss, and matured reliability. However, it has relatively large wavelength dependence due to the difference of coupling length. To expand the bandwidth, we have designed two-mode (LP01/LP11a) multi/demultiplexer by wavefront matching method and demonstrated the broadband and low-loss characteristics. This paper reviews the device design by wavefront matching method and investigates the mechanism of its broadband characteristics.

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.

Frequency chirp of a semiconductor laser is controlled by using hybrid modulation, which simultaneously modulates intra-cavity loss and injection current to the laser. The positive adiabatic chirp of injection-current modulation is compensated with the negative adiabatic chirp created by intra-cavity-loss modulation, which enhances the chromatic-dispersion tolerance of the laser. A proof-of-concept transmission experiment confirmed that the hybrid modulation laser has a larger dispersion tolerance than conventional directly modulated lasers due to the negative frequency chirp originating from intra-cavity-loss modulation.

A lens-integrated surface-emitting DFB laser and its application to low-cost single-mode optical sub-assemblies (OSAs) are discussed. By using the LISEL, high-efficient optical coupling with reduced number of optical components and non-hermetic packaging are demonstrated. Designing the integrated lens of LISELs makes it possible to achieve passive alignment optical coupling to an SMF without the need for an additional lens. For SiP coupling, the light-emission angle from the LISEL can be controlled by the mirror angle and by displacing the lens. The capability for a low coupling loss of 3.9 dB between the LISEL and a grating coupler on the SiP platform was demonstrated. The LISEL with facet-free structure, integrating DBR mirror, PD, and window structure on its end facet, showed the same lasing performance as the conventional laser with AR facet coating. A storage test (200-hour saturated pressure-cooker test (PCT) at 138°C and 85% RH.) showed that the lasing characteristics did not degrade with high-humidity, demonstrating the potential for applying non-hermetic packaging. Our results indicate that the LISEL is one of the promising light sources for creating cost-effective OSAs.

To meet the demand for continuous increase in data traffic, full usage of polarization freedom of light is becoming inevitable in the next-generation optical communication and datacenter networks. In particular, Stokes-vector modulation direct-detection (SVM-DD) formats are expected as potentially cost-effective method to transmit multi-level signals without using costly coherent transceivers in the short-reach links. For the SVM-DD formats to be practical, both the transmitter and receiver need to be substantially simpler, smaller, and lower-cost as compared to coherent counterparts. To this end, we have recently proposed and demonstrated novel SV modulator and receiver circuits realized on monolithic InP platforms. With compact non-interferometric configurations, relatively simple fabrication procedures, and compatibility with other active photonic components, the proposed devices should be attractive candidate in realizing low-cost monolithic transceivers for SVM formats. In this paper, we review our approaches as well as recent progresses and provide future prospects.

Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combinationBS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks.

Ring-based topology is popular for optical network-on-chip. However, the network congestion is serious for ring topology, especially when optical circuit-switching is employed. In this paper, we proposed an algorithm to build a low congestion multi-ring architecture for optical network-on-chip without additional wavelength or scheduling overhead. A network congestion model is established with new network congestion factor defined. An algorithm is developed to optimize the low congestion multi-ring topology. Finally, a case study is shown and the simulation results by OPNET verify the superiority over the traditional ONoC architecture.

This paper focuses mainly on issues related to the pricing of American options under a fuzzy environment by taking into account the clustering of the underlying asset price volatility, leverage effect and stochastic jumps. By treating the volatility as a parabolic fuzzy number, we constructed a Levy-GJR-GARCH model based on an infinite pure jump process and combined the model with fuzzy simulation technology to perform numerical simulations based on the least squares Monte Carlo approach and the fuzzy binomial tree method. An empirical study was performed using American put option data from the Standard & Poor's 100 index. The findings are as follows: under a fuzzy environment, the result of the option valuation is more precise than the result under a clear environment, pricing simulations of short-term options have higher precision than those of medium- and long-term options, the least squares Monte Carlo approach yields more accurate valuation than the fuzzy binomial tree method, and the simulation effects of different Levy processes indicate that the NIG and CGMY models are superior to the VG model. Moreover, the option price increases as the time to expiration of options is extended and the exercise price increases, the membership function curve is asymmetric with an inclined left tendency, and the fuzzy interval narrows as the level set α and the exponent of membership function n increase. In addition, the results demonstrate that the quasi-random number and Brownian Bridge approaches can improve the convergence speed of the least squares Monte Carlo approach.

The accurate assessment of infants' pain is important for understanding their medical conditions and developing suitable treatment. Pediatric studies reported that the inadequate treatment of infants' pain might cause various neuroanatomical and psychological problems. The fact that infants can not communicate verbally motivates increasing interests to develop automatic pain assessment system that provides continuous and accurate pain assessment. In this paper, we propose a new set of pain facial activity features to describe the infants' facial expression of pain. Both dynamic facial texture feature and dynamic geometric feature are extracted from video sequences and utilized to classify facial expression of infants as pain or no pain. For the dynamic analysis of facial expression, we construct spatiotemporal domain representation for texture features and time series representation (i.e. time series of frame-level features) for geometric features. Multiple facial features are combined through both feature fusion and decision fusion schemes to evaluate their effectiveness in infants' pain assessment. Experiments are conducted on the video acquired from NICU infants, and the best accuracy of the proposed pain assessment approaches is 95.6%. Moreover, we find that although decision fusion does not perform better than that of feature fusion, the False Negative Rate of decision fusion (6.2%) is much lower than that of feature fusion (25%).

Certain open issues challenge the software engineering of autonomous robot software (ARS). One issue is to provide enabling software technologies to support autonomous and rational behaviours of robots operating in an open environment, and another issue is the development of an effective engineering approach to manage the complexity of ARS to simplify the development, deployment and evolution of ARS. We introduce the software framework AutoRobot to address these issues. This software provides abstraction and a model of accompanying behaviours to formulate the behaviour patterns of autonomous robots and enrich the coherence between task behaviours and observation behaviours, thereby improving the capabilities of obtaining and using the feedback regarding the changes. A dual-loop control model is presented to support flexible interactions among the control activities to support continuous adjustments of the robot's behaviours. A multi-agent software architecture is proposed to encapsulate the fundamental software components. Unlike most existing research, in AutoRobot, the ARS is designed as a multi-agent system in which the software agents interact and cooperate with each other to accomplish the robot's task. AutoRobot provides reusable software packages to support the development of ARS and infrastructure integrated with ROS to support the decentralized deployment and running of ARS. We develop an ARS sample to illustrate how to use the framework and validate its effectiveness.

In this letter, we explored the usage of spatio-temporal information in one unified framework to improve the performance of multichannel speech recognition. Generalized cross correlation (GCC) is served as spatial feature compensation, and an attention mechanism across time is embedded within long short-term memory (LSTM) neural networks. Experiments on the AMI meeting corpus show that the proposed method provides a 8.2% relative improvement in word error rate (WER) over the model trained directly on the concatenation of multiple microphone outputs.

This paper proposes a hardware configuration for uplink multi-user multiple-input multiple-output (MU-MIMO) transmissions in a distributed antenna system (DAS). The demand for high-speed transmission in the uplink has increased recently, because of which standardizations in LTE-advanced and IEEE 802.11ax networks is currently underway. User terminal (UT) scheduling on the downlink MU-MIMO transmission is easy even in unlicensed band such as those in wireless local area network (WLAN) systems. However, the detailed management of the UTs is difficult on the uplink MU-MIMO transmissions because of the decentralized wireless access control. The proposed configuration allows an antenna to be selected from an external device on the access point (AP). All AP antennas are divided into groups, and the received signal in each group is input to the amplitude detector via a directional coupler. Subsequently, the selected antenna is fed by a multiple-to-one switch instead of a matrix switch. To clarify the effectiveness of the proposed configuration, we conduct computer simulations based on the ray-tracing method for propagation channels in an indoor environment.

We have proposed and developed new electro-optic modulators for the pre-equalization of signal distortion caused by the optical fiber chromatic dispersion effect. We found that the synthesis of an almost arbitrary impulse response function is obtainable by utilizing an electro-optic modulator composed of a Mach-Zehnder waveguide and travelling-wave electrodes on a ferro-electric material substrate with polarization-reversed structures. In this paper, the operational principle, design and simulation results of the pre-equalization modulator are presented. Some preliminary experimental results are also shown with future prospects.

Real-time weather radar imaging technology is required for generating short-time weather forecasts. Moreover, such technology plays an important role in critical-weather warning systems that are based on vast Doppler weather radar data. In this study, we propose a weather radar imaging method that uses multi-layer contour detection and segmentation based on MAP-MRF estimation. The proposed method consists of three major steps. The first step involves generating reflectivity and velocity data using the Doppler radar in the form of raw data images of sweep unit in the polar coordinate system. Then, contour lines are detected on multi-layers using the adaptive median filter and modified Canny's detector based on curvature consistency. The second step interpolates contours on the Cartesian coordinate system using 3D scattered data interpolation and then segments the contours based on MAP-MRF prediction and the metropolis algorithm for each layer. The final step involves integrating the segmented contour layers and generating PPI images in sweep units. Experimental results show that the proposed method produces a visually improved PPI image in 45% of the time as compared to that for conventional methods.