3D FEM simulation of responses of LWD multi-mode resistivity imaging sonde

A new multi-mode resistivity imaging sonde, with toroidal coils as source, can conduct three resistivity measurements: azimuthal resistivity, lateral resistivity, and bit resistivity measurements. Thus, the logging time and cost are greatly saved. The toroidal coils are simplified as an extended voltage dipole and the response equations are derived for a homogenous formation. Based on 3D FEM, the depth of investigation(DOI), vertical resolution, circumferential azimuthal capacity, borehole diameter, mud resistivity, thickness of target formation, and the resistivity of the surrounding formation and mud invasion are simulated. The results suggest that the three measurement modes of the new sonde are different in vertical resolutions and DOIs. The circumferential detection ability of the azimuth button depends on the contrast between the anomaly and formation resistivity and the open angle of the anomaly. Whether the borehole is truncated at the bit or not has a great influence on the simulation results. The borehole and mud invasion affect the apparent resistivity in all modes, but the effects of resistivity of surrounding formation and thickness of the target formation are only corrected for lateral resistivity measurement.

Signal classification method based on data mining formulti-mode radar

For the multi-mode radar working in the modern electronicbattlefield, different working states of one single radar areprone to being classified as multiple emitters when adoptingtraditional classification methods to process intercepted signals,which has a negative effect on signal classification. A classificationmethod based on spatial data mining is presented to address theabove challenge. Inspired by the idea of spatial data mining, theclassification method applies nuclear field to depicting the distributioninformation of pulse samples in feature space, and digs out thehidden cluster information by analyzing distribution characteristics.In addition, a membership-degree criterion to quantify the correlationamong all classes is established, which ensures classificationaccuracy of signal samples. Numerical experiments show that thepresented method can effectively prevent different working statesof multi-mode emitter from being classified as several emitters,and achieve higher classification accuracy.

Multi-mode process monitoring based on a novel weighted local standardization strategy and support vector data description

There are multiple operating modes in the real industrial process, and the collected data follow the complex multimodal distribution, so most traditional process monitoring methods are no longer applicable because their presumptions are that sampled-data should obey the single Gaussian distribution or non-Gaussian distribution. In order to solve these problems, a novel weighted local standardization(WLS) strategy is proposed to standardize the multimodal data, which can eliminate the multi-mode characteristics of the collected data, and normalize them into unimodal data distribution. After detailed analysis of the raised data preprocessing strategy, a new algorithm using WLS strategy with support vector data description(SVDD) is put forward to apply for multi-mode monitoring process. Unlike the strategy of building multiple local models, the developed method only contains a model without the prior knowledge of multi-mode process. To demonstrate the proposed method's validity, it is applied to a numerical example and a Tennessee Eastman(TE) process. Finally, the simulation results show that the WLS strategy is very effective to standardize multimodal data, and the WLS-SVDD monitoring method has great advantages over the traditional SVDD and PCA combined with a local standardization strategy(LNS-PCA) in multi-mode process monitoring.

Current multifunctional albumin-based nanoplatforms for cancer multi-mode therapy

Albumin has been widely applied for rational design of drug delivery complexes as natural carriers in cancer therapy due to its distinct advantages of biocompatibility,abundance,low toxicity and versatile property.Hence,various types of multifunctional albumin-based nanoplatforms(MAlb-NPs)that adopt multiple imaging and therapeutic techniques have been developed for cancer diagnosis and treatment.Stimuli-responsive release,including reduction-sensitive,p H-responsive,concentration-dependent and photodynamic-triggered,is important to achieve low-toxicity cancer therapy.Several types of imaging techniques can synergistically improve the effectiveness of cancer therapy.Therefore,combinational theranostic is considered to be a prospective strategy to improve treatment efficiency,minimize side effects and reduce drug resistance,which has received tremendous attentions in recent years.In this review,we highlight several stimuli-responsive albumin nanoplatforms for combinational theranostic.

Vortex-Induced Vibration of a Tension Leg Platform Tendon:Multi-Mode Limit Cycle Oscillations

This paper studies the application of mathematical models to analyze the vortex-induced vibrations of the tendons of a given TLP along the Indian coastline, by using an analytical approach, using MATLAB. The tendon is subjected to a steady current load, which causes vortex-shedding downstream, leading to cross-flow vibrations. The magnitude of the excitation(lift and drag coefficients) depends on the vortex-shedding frequency. The resulting vibration is studied for possible resonant behavior. The excitation force is quantified empirically, the added mass by potential flow hydrodynamics, and the vibration by normal mode summation method. Non-linear viscous damping of the water is considered. The non-linear oscillations are studied by the phase-plane method, investigating the limit-cycle oscillations. The stable/unstable regions of the dynamic behavior are demarcated. The modal contribution to the total deflection is studied to establish the possibility of resonance of one of the wet modes with the vortex-shedding frequency.

A global analysis of multi-mode sea surface temperature pattern

The variability of the air-sea system in the low-frequency time domain can be decomposed into several systematic climate modes, namely, the decadal variability （DV） mode, the El Nino Southem Oscillation （ENSO） mode, the annual cycle （AC） mode, the semiannual cycle （ SC ） mode and the intraseasonal variability （ ISV ） mode. The combination of these primary modes in the air - sea system orchestrates a complex climate system. The multi-mode low-frequency variability in SST is investigated based on 22 a SST records from 1982 through 2003. The variation of SST in the past two decades undergoes a different combination of these dominant climate modes over different regions, which leads to an interesting new classification of the global ocean based on the relative importance of these modes. The new classification can provide ideal locations for better monitoring of these low-frequency modes in the scientific proof sense. Moreover, two no-annual variation and 14 no-semiannual variation oceanic points, termed annual and semiannual amphidromes, have been well defined in the AC and SC phase maps. The formation of these nodal points is attributed to the couplings of climate modes in EOF analysis results.

Memetic algorithm for multi-mode resource-constrained project scheduling problems

A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.

Multi-model comparison of CO2 emissions peaking in China:Lessons from CEMF01 study

The paper summarizes results of the China Energy Modeling Forum's(CEMF)first study.Carbon emissions peaking scenarios,consistent with China's Paris commitment,have been simulated with seven national and industry-level energy models and compared.The CO2 emission trends in the considered scenarios peak from 2015 to 2030 at the level of 9e11 Gt.Sector-level analysis suggests that total emissions pathways before 2030 will be determined mainly by dynamics of emissions in the electric power industry and transportation sector.Both sectors will experience significant increase in demand,but have low-carbon alternative options for development.Based on a side-by-side comparison of modeling input and results,conclusions have been drawn regarding the sources of emissions projections differences,which include data,views on economic perspectives,or models'structure and theoretical framework.Some suggestions have been made regarding energy models'development priorities for further research.

Unconventional geometric logic gate in a strong-driving-assisted multi-mode cavity

We propose a scheme to implement an unconventional geometric logic gate separately in a two-mode cavity and a multi-mode cavity assisted by a strong classical driving field. The effect of the cavity decay is included in the investigation. The numerical calculation is carried out, and the result shows that our scheme is more tolerant to cavity decay than the previous one because the time consumed for finishing the logic gate is doubly reduced.

基于Multi-Agent的无人机集群体系自主作战系统设计

针对无人集群自主作战体系设计中的关键问题,提出基于Multi-Agent的无人集群自主作战系统设计方法。建立无人集群各节点的Agent模型及其推演规则;对于仿真系统模块化和通用化的需求,设计系统互操作式接口和无人集群自主作战的交互关系;开展无人集群系统仿真推演验证。仿真结果表明,所提设计方案不仅能够有效开展并完成自主作战网络生成-集群演化-效能评估的全过程动态演示验证,而且能够通过重复随机试验进一步评估无人集群的协同作战效能,最后总结了集群协同作战的策略和经验。

Single-mode low threshold current multi-hole vertical-cavity surface-emitting lasers

A multi-hole vertical-cavity surface-emitting laser （VCSEL） operating in stable single mode with a low threshold current was produced by introducing multi-leaf scallop holes on the top distributed Bragg-refleetor of an oxidation- confined 850 nm VCSEL. The single-mode output power of 2.6 mW, threshold current of 0.6 mA, full width of half maximum lasing spectrum of less than 0.1 nm, side mode suppression ratio of 28.4 dB, and far-field divergence angle of about 10% are obtained. The effects of different hole depths on the optical characteristics are simulated and analysed, including far-field divergence, spectrum and lateral cavity mode. The single-mode performance of this multi-hole device is attributed to the large radiation loss from the inter hole spacing and the scattering loss at the bottom of the holes, particularly for higher order modes.

Multi-mode coupling analysis of a sub-terahertz band planar corrugated Bragg reflector

Planar Bragg reflector operating in the sub-terahertz wavelength installed at the upstream end of a sheet beam back- ward wave oscillator （BWO） is very promising to minimize the whole circuit structure and make it more compact. In this paper, a sub-terahertz wavelength （0.18-0.22 THz） tunable planar Bragg reflector is numerically analyzed by using multi-mode coupling theory （MCT）. The operating mode TE10 and dominant coupling mode TE01 are mainly considered in this theory. Reflection and transmission performance of the reflector are demonstrated in detail and the results, in excellent agreement with the theoretical analysis and simulation, are also presented in this paper. Self- and cross-coupling coefficients between these two modes are presented as well. The reflector behaviors with different Bragg dimensions are discussed and analyzed in the 0.16-0.22 THz range. The analysis in this paper can be of benefit to the design and fabrication of the whole BWO circuit.

联合物理层与MAC层的multi-TRP上行重叠传输处理机制

针对非理想回程下现有协议难以有效处理多传输接收节点(multi-TRP)场景中多定时提前(multi-TA)导致的严重上行链路(UL)重叠传输问题,联合改进物理层复用技术和介质访问控制(MAC)令牌桶技术,提出了一种新型的UL重叠传输处理机制。该新型机制通过改进物理层重叠信道识别流程、复用要求及复用规则,将物理层复用信息与重叠信息反馈至MAC层,并对MAC层令牌桶技术进行优化。通过仿真实验对所提机制与现有协议机制进行对比,结果表明,在逻辑时隙不可重叠和可重叠2种情形下,物理上行控制信道(PUCCH)实际复用数量性能平均提升了57.58%和49.40%,物理上行共享信道(PUSCH)实际可用资源数量性能平均提升了12.09%和26.03%;优先级最高逻辑信道实际占用资源数量性能平均提升了33.33%和45.48%。

Design of a Novel Multi-Mode LED Dimming and Color Control System

Aiming at the needs of different lighting applications, combined with the characteristics of LED dimming and color control, and using MSP430 digital control technology, a novel LED intelligent dimming and color control system was designed. The system integrated Bluetooth remote, human infrared sensor, voice/gesture control and other control modes, which could achieve LED multi-mode dimming and color intelligent control. System hardware and software were designed to develop a prototype to experimental verification. The designed method proposes new ideas and information for LED control.

2.9 - 8.4 GHz Filter Bank Using Stub-Loaded Multi-Mode Resonators

This paper consolidates the activity of design and fabrication of 2.9 - 4.32 GHz, 4.3 - 6.42 GHz, and 6.4 - 8.4 GHz filter bank. Novel compact microstrip bandpass filters with stub-loaded multi-mode resonators are proposed. Simulated results indicate that all the filters exhibit insertion losses less than 1.5 dB with passband ripples of 1 dB and sharp attenuations of above 40 dB in their stopbands. The maximums of input and output VSWRs are 1.742 and 1.734, respectively. Due to fabrication error, the initial measured passbands show frequency shifts and insertion losses in upper passbands deteriorate seriously. After tuning of the filter bank, measured results imply that the input and output VSWRs are found lower than 2.135 and 2.187, and the insertion loss in 1 dB bandwidth is less than 2.52 dB. Filter bank has a sharp skirt and out-of-band rejection levels approaching to 40 dB in all desired stopbands except at the frequencies near 2f0.

基于Multi-Agent的水电站变压器故障诊断系统

为了精准、快速完成水电站变压器的故障诊断,设计基于Multi-Agent的水电站变压器故障诊断系统。变压器状态监控agent将检测到的变压器故障信息发送给系统管理agent,系统管理agent通过通信agent将变压器故障信息发送给变压器故障诊断agent,变压器故障诊断agent利用小波变换方法提取变压器故障特征,并将其作为IFOA-SVM模型输入,完成变压器故障分类后,获取变压器故障诊断结果,该结果通过通信agent显示给用户。实验表明,该系统可有效诊断变压器故障诊断,诊断成功率受系统故障信息丢失率的影响较小,诊断耗时、耗能小,并具有较高故障诊断成功率。

Method of Multi-Mode Sensor Data Fusion with an Adaptive Deep Coupling Convolutional Auto-Encoder

To address the difficulties in fusing multi-mode sensor data for complex industrial machinery, an adaptive deep coupling convolutional auto-encoder (ADCCAE) fusion method was proposed. First, the multi-mode features extracted synchronously by the CCAE were stacked and fed to the multi-channel convolution layers for fusion. Then, the fused data was passed to all connection layers for compression and fed to the Softmax module for classification. Finally, the coupling loss function coefficients and the network parameters were optimized through an adaptive approach using the gray wolf optimization (GWO) algorithm. Experimental comparisons showed that the proposed ADCCAE fusion model was superior to existing models for multi-mode data fusion.

Modeling of Few-Mode Multi-Core Optical Fiber Channel Based on Non-Uniform Mode Field Distribution

In this paper, the influencing factors that affect few-mode and multi core optical fiber channel are analyzed in a comprehensive way. The theoretical modeling and computer simulation of the information channel are carried out and then the modeling scheme of few-mode multicore optical fiber channel based on non-uniform mode field distribution is put forward. The proposed modeling scheme can not only exponentially increases the system capacity through fewmode multi-core optical fiber channel, but has better transmission performance compared to the channel of the same type to the uniform channel revealing from the simulation results.

Support vector machine-based multi-model predictive control

In this paper, a support vector machine-based multi-model predictive control is proposed, in which SVM classification combines well with SVM regression. At first, each working environment is modeled by SVM regression and the support vector machine network-based model predictive control （SVMN-MPC） algorithm corresponding to each environment is developed, and then a multi-class SVM model is established to recognize multiple operating conditions. As for control, the current environment is identified by the multi-class SVM model and then the corresponding SVMN-MPC controller is activated at each sampling instant. The proposed modeling, switching and controller design is demonstrated in simulation results.