Advanced Schemes Research Articles

A robust surrogate data assimilation approach to real-time forecasting using polynomial chaos expansion

Data assimilation plays an essential role in real-time forecasting but demands repetitive model evaluations given ensembles. To address this computational challenge, a novel, robust and efficient approach to surrogate data assimilation is presented. It replaces the internal processes of the ensemble Kalman filter (EnKF) with polynomial chaos expansion (PCE) theory. Eight types of surrogate filters, which can be characterized according to their different surrogate structures, building systems, and assimilating targets, are proposed and validated. To compensate for the potential shortcomings of the existing sequential experimental design (SED), an advanced optimization scheme, named sequential experimental design-polynomial degree (SED-PD), is also advised. Its dual optimization system resolves the issue of SED by which the value of the polynomial degree had to be selected ad-hoc or by trial and error; its multiple stopping criteria ensure convergence even when an accuracy metric does not monotonically decrease over iterations. A comprehensive investigation into how to configure a surrogate filter indicates that the new partial (replacing part of original filters) and invariant (valid for entire time periods) approaches are preferred in terms of accuracy and efficiency, which helps directly reduce the number of dimensions and bridge the gap between hindcasting and real-time forecasting. Of the eight filters, the Dual Invariant Partial filter performs best, with equivalent accuracy to Dual EnKF and about 500 times greater computational efficiency. Ultimately, this proposed surrogate filter will be a promising alternative tool for performing computationally-intensive data assimilation in high-dimensional problems.

Deformation control method of a large cross-section tunnel overlaid by a soft-plastic loess layer: a case study

This paper presents a case study of a large cross-section high-speed railway tunnel overlaid by a Q2 soft-plastic loess layer. Due to poor engineering properties of the soft-plastic loess, two unexpected collapses occurred. This indicates that there is great difficulty and risk during tunneling. In this paper, the deformation control methods are studied by carrying out a series of numerical simulations and then validating via field tests. The stress and seepage coupling equations are deducted to embed into a 3D fluid-mechanical coupled numerical analysis. The results show that the curtain grouting scheme can effectively control the deformation of surrounding rock, and the real field data of settlement and horizontal convergence are 152 mm and 37 mm, respectively. However, the tunneling advance rate is slow (0.6 m/day) in trial sections because of the mutual interference between construction procedures. It can be used as an alternative scheme for lager deformation. The advanced drainage scheme can lower the ground water table below the excavation outline. The average water content of soft-plastic loess decreases from 26 to 22%, and the state of surrounding rock changes from soft plastic to hard plastic. The in situ settlement and horizontal convergence are 165 mm and 51 mm, respectively. Finally, it is proposed to use advanced drainage in combination with advanced small pipe grouting as a follow-up construction scheme. The successful completion of the whole tunnel proved the effectiveness of the proposed method.

A Noise-Tolerant Audio Encryption Framework Designed by the Application of S8 Symmetric Group and Chaotic Systems

The recent decade has witnessed an exponential surge of digital content, especially multimedia and its applications. The security requirements of these innovative platforms necessitate the significance of enhancing advanced encryption schemes. In this paper, a novel encryption scheme is presented for real-time audio applications. The framework of the proposed scheme is grounded on the principles of confusion and diffusion. The confusion incorporates nonlinearity by the application of Mordell elliptic curves (MEC) and a symmetric group of permutations S8. The endurance of the proposed scheme is further enriched through the application of chaotic maps. The proposed scheme is intended to cater requirements of real-time voice communications in defense applications particularly warzones. The adoption of a modular design and fusion of chaotic maps makes the algorithm viable for numerous real-time audio applications. The security can further be enriched by incorporating additional rounds and number of S-boxes in the algorithm. The security and resistance of the algorithm against various attacks are gaged through performance evaluation and security measurements. The audio encryption scheme has the ability to tolerate noise triggered by a channel or induced by an invader. The decryption was successful and the resultant output was audible for noisy data. The overall results depict that the proposed audio encryption scheme contains an excellent cryptographic forte with the minimum computational load. These characteristics allow the algorithm to be a hotspot for modern robust applications.

A Novel Risk Evaluation Procedure Using a Kriging-Based Surrogate Modeling for Offshore Structures

An innovative reliability estimation procedure for Jacket-type offshore platforms is proposed. The information on risk is extracted using multiple deterministic analyses using advanced mathematical theories resulting in compounding beneficial effects. The platforms are modeled by finite elements. Nonlinearity and major sources of uncertainty are incorporated. The wave loading model is realistically developed to satisfy the underlying physics. It is applied in three-dimension in time domain incorporating the uncertainties in the parameters. Implicit performance functions are expressed explicitly using several advanced factorial schemes and significantly improved response surface method. The efficiency and accuracy of the method are improved using a comprehensively improved Kriging-based surrogate modeling technique. The risk is evaluated for the serviceability and strength limit state functions for a jacket-type offshore platform using about two hundred nonlinear finite element analyses. The procedure was verified using simulation techniques. The concept can be considered an alternative to the conventional random vibration techniques and the standard Monte Carlo simulation procedure.

Hybrid Integrated Silicon Nitride–Polymer Optical Phased Array For Efficient Light Detection and Ranging

Silicon nitride (SiN) optical phased arrays (OPAs) have emerged as a potential alternative to their silicon counterparts, owing to their low nonlinearity, easy scalability, and low propagation loss. However, the development of SiN OPAs for light detection and ranging (LiDAR) applications has attracted less attention due to the low thermo-optic (TO) effect of SiN. Moreover, SiN OPAs are considered to be undesirable for transmitters in LiDAR systems because of the limited longitudinal tuning efficiency of SiN grating antenna. We present a hybrid integrated SiN-polymer OPA for realizing an efficient LiDAR. Owing to the large TO effect of polymer, the proposed OPA with polymeric phase modulators resolves the power dissipation drawback of the SiN devices. The polymeric modulators are integrated with a SiN power splitter and grating antenna, and the coupling loss is alleviated via a spot-size converter. Additionally, a steering angle magnifying lens is used to enhance the tuning efficiency of the antenna, expanding the longitudinal beam steering range. The prepared OPA transmitter equipped with the lens exhibits decent two-dimensional beam steering, featuring stable emission characteristics over a 12° × 30° field of view. With the transmitter, efficient time-of-flight based LiDAR is demonstrated to provide a detection range of 10 m under a peak optical power of 55 dBm. The proposed SiN-polymer OPA is highly anticipated to circumvent the challenges of conventional SiN counterparts and potentially spearhead the development of a prominent OPA platform for advanced LiDAR schemes.

Moving Least Squares Method and its Improvement: A Concise Review

The concise review systematically summarises the state-of-the-art variants of Moving Least Squares (MLS) method. MLS method is a mathematical tool which could render cogent support in data interpolation, shape construction and formulation of meshfree schemes, particularly due to its flexibility to form complex arithmetic equation. However, the conventional MLS method is suffering to deal with discontinuity of field variables. Varied strategies of overcoming such shortfall are discussed in current work. Although numerous MLS variants were proposed since the introduction of MLS method in numerical/statistical analysis, there is no technical review made on how the methods evolve. The current review is structured according to major strategies on how to improvise MLS method: the modification of weight function, the manipulation of discrete norms, the inclusion of iterative feature for residuals minimising and integration of these strategies for more robust computation. A wide range of advanced MLS variants have been compiled, summarised, and reappraised according to its underlying principle of improvement. In addition, inherent limitation of MLS method and its possible strategy of improvement is discussed too in this article. The current work could render valuable reference to implement and develop advanced MLS schemes, whenever complexity of the specific scientific problems arose.

Multipath Scheduling for 5G Networks: Evaluation and Outlook

The fifth generation (5G) of cellular networks aims at providing very high data rates, ultra-reliable low latency, and massive connection density. As one of the fundamental design trends toward these objectives, 5G exploits multi-connectivity (i.e., the concurrent use of multiple access networks), where multipath transport protocols have emerged as key technology enablers. The scheduler of a multipath transport protocol determines how to distribute the data packets onto different paths and has a critical impact on the protocol performance. Within this context, we present in this article the first empirical evaluation of state-of-the-art multipath schedulers based on real 5G data, for both static and mobile scenarios. Furthermore, we introduce M-Peekaboo, which builds on a state-of-the-art learning-based multipath scheduler and extends its usage to 5G networks. Our results illustrate the benefits of employing a learning-based multipath scheduler for 5G networks and motivate further studies of advanced learning schemes that can adapt more quickly to the path conditions, and take into account the emerging features and requirements of 5G and beyond networks.

Intelligent coding metasurface holograms by physics-assisted unsupervised generative adversarial network

Intelligent coding metasurface is a kind of information-carrying metasurface that can manipulate electromagnetic waves and associate digital information simultaneously in a smart way. One of its widely explored applications is to develop advanced schemes of dynamic holographic imaging. By now, the controlling coding sequences of the metasurface are usually designed by performing iterative approaches, including the Gerchberg–Saxton (GS) algorithm and stochastic optimization algorithm, which set a large barrier on the deployment of the intelligent coding metasurface in many practical scenarios with strong demands on high efficiency and capability. Here, we propose an efficient non-iterative algorithm for designing intelligent coding metasurface holograms in the context of unsupervised conditional generative adversarial networks (cGANs), which is referred to as physics-driven variational auto-encoder (VAE) cGAN (VAE-cGAN). Sharply different from the conventional cGAN with a harsh requirement on a large amount of manual-marked training data, the proposed VAE-cGAN behaves in a physics-driving way and thus can fundamentally remove the difficulties in the conventional cGAN. Specifically, the physical operation mechanism between the electric-field distribution and metasurface is introduced to model the VAE decoding module of the developed VAE-cGAN. Selected simulation and experimental results have been provided to demonstrate the state-of-the-art reliability and high efficiency of our VAE-cGAN. It could be faithfully expected that smart holograms could be developed by deploying our VAE-cGAN on neural network chips, finding more valuable applications in communication, microscopy, and so on.

Performance Analysis of Filtered OFDM Based Downlink and Uplink NOMA System over Nakagami-m Fading Channel

Efficient consumption of available resources and fulfillment of increasing demands are the two main challenges which are addressed by exploring advanced multiple access schemes along with efficient modulation techniques. To this end, non-orthogonal multiple access (NOMA) is discussed as a promising scheme for future 5G traffic. NOMA enables the users to share same resource block, permitting certain level of interference. In this paper, we propose filtered OFDM (F-OFDM) as a transmission waveform for NOMA systems, as it offers all the advantages of OFDM with the additional provision of sub-band filtering to satisfy the diverse services of the users. We examine F-OFDM in both downlink and uplink NOMA systems. Error-related performances of both downlink and uplink F-OFDM NOMA systems are analyzed and compared with conventional OFDM NOMA system over Nakagami-m fading channel. The results show that the error performance of F-OFDM NOMA is better than that of OFDM NOMA. An improvement of about 2 dB and 1 dB in bit error rate is achieved in downlink and uplink F-OFDM NOMA, respectively. Monte Carlo simulations are conducted for different values of fading parameter m, supporting the obtained analytical results

Demonstration of a fiber optical communication system employing a silica microsphere-based OFC source.

The fabrication of microsphere resonators and the generation of optical frequency combs (OFC) have achieved a significant breakthrough in the past decade. Despite these advances, no studies have reported the experimental implementation and demonstration of silica microsphere OFCs for data transmission. In this work, to the best of our knowledge, we experimentally for the first time present a designed silica microsphere whispering-gallery-mode microresonator (WGMR) OFC as a C-band light source where 400 GHz spaced carriers provide data transmission of up to 10 Gbps NRZ-OOK modulated signals over the standard ITU-T G.652 telecom fiber span of 20 km in length. A proof-of-concept experiment is performed with two newly generated carriers (from 7-carrier OFC) having the highest peak power. The experimental realization is also strengthened by the modeling and simulations of the proposed system showing a strong match of the results. The demonstrated setup serves as a platform for the future experimental implementation of silica microsphere WGMR-OFC in more complex WDM transmission system realizations with advanced modulation schemes.

MECHANISM FOR IMPLEMENTING THE COMPANY'S PRODUCT POLICY

Search for the most advanced schemes and models of the Corporation's product policy, selection of tools and mechanisms for their adaptation to the conditions of a particular market. The importance of justifying marketing decisions for the development of such a policy is of increased interest to researchers in this issue. Originality of the research. Scientific novelty consists in the development of methodological recommendations and practical proposals for improving the product policy at the enterprise. Research result. The conceptual framework of market research studies and the role of product policy in the marketing development Corporation; the specificity of marketing researches for specific food market; conducted market analysis of market conditions and formulates the algorithm of development of commercial policy on the selected segment; modeled the mechanism of implementation of managerial decisions of the Corporation in the sphere of commercial policy in its implementation.

MECHANISM FOR IMPLEMENTING THE COMPANY'S PRODUCT POLICY

Search for the most advanced schemes and models of the Corporation's product policy, selection of tools and mechanisms for their adaptation to the conditions of a particular market. The importance of justifying marketing decisions for the development of such a policy is of increased interest to researchers in this issue. Originality of the research. Scientific novelty consists in the development of methodological recommendations and practical proposals for improving the product policy at the enterprise. Research result. The conceptual framework of market research studies and the role of product policy in the marketing development Corporation; the specificity of marketing researches for specific food market; conducted market analysis of market conditions and formulates the algorithm of development of commercial policy on the selected segment; modeled the mechanism of implementation of managerial decisions of the Corporation in the sphere of commercial policy in its implementation.

An enhanced planned obsolescence attack by aging networks-on-chip

Despite of a controversial practice, having the key components of a product undergo accelerated aging has been a very effective approach for planned obsolescence. All previous studies on planned obsolescence merely focused on the aging process itself; however, if a malfunctioned product due to aging is still under its warranty, the manufacturer suffers from financial losses in the form of customer refund and/or product repair. In this paper, we reveal an enhanced planned obsolescence attack that takes the warranty issue into consideration. More specifically, aging of an NoC-based many-core chip is set to be slow before the warranty expires, and its aging process gets accelerated afterwards. Such controlled aging is achieved by manipulating the routing algorithm that influences the lifetime distribution of the NoC nodes. The routing-induced aging process is also integrated with a profit model to evaluate the profit gained from chip aging. Experimental results show that, with the proposed planned obsolescence attack and the profit model, the manufacturer can increase its profit margin by 15.54%, 25.69%, and 53.36%, respectively, compared to devices under a scheme without any attack, a scheme that aggressively accelerates chip aging, and a scheme that employs a measure to mitigate chip aging. Overall speaking, the proposed attack can give the manufacturer a clear advantage over customer who can barely notice the existence of such business practices, and consequently, some advanced countermeasure schemes need to be developed to balance the interests of the two parties.

An advanced marine engine waste heat utilization scheme: Electricity-cooling cogeneration system integrated with heat storage device

The waste heat recovery technology is an effective means to cut down the consumption of fossil fuel by ships, which improves the energy efficiency but reduces the pollution emissions caused by marine diesel engines. Unlike previous simple cascade utilization of energy, this paper designs two evaporators for Organic Rankine cycle to make full use of exhaust heat and takes the heat from condenser as heat source to drive absorption refrigeration system for reducing heat loss. The thermodynamic models of integrated system, optimization program of genetic algorithm and evaluation modules of economy are established. From the selection of non-azeotropic mixtures, it can be aware of that cyclopentane/pentane is adaptable to the variable working conditions of ship. Meanwhile, the calculation results indicate that output power, thermal and exergy efficiency of this binary fluid are up to 2866 kW, 16.22% and 48.25% at 80% engine load. In view of the case that cooling capacity produced by refrigeration system cannot meet the demand, a heat storage device is used to reserve heat and supply the extra cooling energy. The effect analysis shows that the material with higher specific heat is more conform to the refrigeration target. However, from the economic point of view, the various evaluation indexes are improved notably with the support of heat storage device.

Dynamic Power–Frequency Control in a Hybrid Wind-PV Plant Interlinked with AC Power System

Hybrid renewable energy-based generation can improve the reliability in power supply. While avoiding the big cost in energy storage/battery, it is apparent that, such hybrid plants could be interlinked with the conventional power system for ensuring continuous power supply in the local area and better utilization of renewable energy sources. As generation from the renewable energy sources are intermittent, the interaction of such hybrid plants with the traditional power network can abruptly disturb the power/frequency level. Thus, devising a robust power–frequency control (PFC) scheme for the contemporary hybrid renewable interlinked power systems is highly obligatory. In this context, this paper presents a fractional-order-proportional-integral-derivative (FOPID) controller based advanced PFC scheme. Bacterial-foraging optimization (BFO) technique is adopted for computing the design parameters, namely, the controller gains and set-point weights. A typical hybrid wind- photovoltaic (PV) Plant interlinked thermal power system is modelled and simulated in order to investigate the system dynamics. Effectiveness of the proposed PFC scheme corroborated with the renewable power variations as well as load perturbation is confirmed and the results are presented.

An Advanced Phase Synchronization Scheme Based on Coherent Integration and Waveform Diversity for Bistatic SAR

In the bistatic synthetic aperture radar (BiSAR) system, the deviation between two oscillators in different platforms will cause an additional modulation of BiSAR echoes. Therefore, phase synchronization is one of the key issues that must be addressed for the BiSAR system. The oscillator phase error model and the principle of phase synchronization are firstly described. The waveform diversity technology has been widely used in many fields, for example, the hearing aids device and the recognition of auditory input source in cocktail party problem. Inspired by this, an advanced phase synchronization scheme based on coherent integration and waveform diversity is proposed. The synchronization signal and radar signal are orthogonal signals which can be separated by using waveform diversity technique. After extracting the synchronization signal, the phase synchronization accuracy can be further improved by coherent integration. The transmission of synchronization signals between two synchronization antennas is analyzed, followed by the theoretical error analysis. Then, the processing of separating the echo signal and synchronization signal is described in detail. The simulation experiments are performed. The accuracy of phase synchronization can reach 1 degree, which verifies the effectiveness of the proposed synchronization scheme.

An Improved and Novel Approach for Frequency Domain Forward Modeling of GPR Data Using the Finite Difference Staggered Grid Technique

Forward modeling of ground penetrating radar (GPR) data is important for understanding relationships between dielectric layers. For the inversion of GPR data, an effective and advanced forward modeling scheme is always desirable. Here, staggered grid formulations for the finite difference frequency domain (FDFD) method have been developed and modified for the forward modeling of GPR data. The forward problem is first solved using a nine-point regular staggered grid that basically approximates and discretizes the Laplacian operator. In the case of transverse electric mode FDFD method, the implementation of a perfectly matched layer (PML) has been shown to be effective. Among the several PML techniques, the complex frequency shifted perfectly matched layer method has proven to be most useful for absorbing evanescent waves. In this paper, a new and improved nine-point mixed staggered grid formulation is proposed by considering the combination of a five-point Cartesian and nine-point rotated staggered grid. The derived stencils are compared after estimating the reflection errors from the computed simulated wavefields ( $${E}_{y}$$ ) of the homogeneous subsurface model. This newly developed technique exhibits less error than the regular and unstaggered mixed stencils. Lastly, this better and less-time consuming grid is used to extract GPR data from realistic sedimentary models with a surface acquisition setup.

Advanced nonlinear control strategies for a fermentation bioreactor used for ethanol production

This study addresses the design of advanced control schemes implemented for a continuous fermentation process used to produce ethanol. Due to the inaccuracy of the models that express this complex process, a feasible controller is required to maximize the production of ethanol and to minimize its environmental impact, despite the existence of some significant uncertainties. Therefore, novel estimation and control schemes are designed and tested. These schemes are adaptive control laws including nonlinear estimation algorithms: a sliding mode observer to estimate the unknown influent concentration, but also state observers and parameter estimators used to estimate the unknown states and kinetics. Since the temperature is an important factor for an efficient operation of the process, an algorithm for temperature control in the bioreactor is also developed. To verify the control algorithms effectiveness, several tests performed via numerical simulations under realistic conditions are presented.

A 6-Bit 1.5-GS/s SAR ADC With Smart Speculative Two-Tap Embedded DFE in 130-nm CMOS for Wireline Receiver Applications

Implementing wireline receivers with a front-end analog-to-digital converter (ADC) allows for complex, flexible, and robust signal processing algorithms in the digital domain, as well as easy implementation of advanced modulation schemes beyond binary PAM2. However, the power consumption of the ADC and ensuing digital equalization is a key issue for such receivers in high-speed applications. Embedding analog equalization inside the ADC architecture allows for both a lower ADC resolution and a reduced-complexity digital equalizer, resulting in a more power-efficient receiver. This article presents a 6-bit 1.5-GS/s time-interleaved successive approximation register (SAR) ADC with low-overhead two-tap embedded decision-feedback equalizer (DFE). A smart speculative DFE is proposed to reduce additional conversion cycles required for the equalization realization in the ADC. Moreover, DFE functions are efficiently embedded in the capacitive digital-to-analog converter (DAC) references. The prototype ADC with two-tap DFE is implemented in a 130-nm CMOS process and achieves a 5.24-bit peak effective number of bits and 0.59-pJ/conversion-step figure-of-merit (FOM) at a 1.5-GS/s sampling rate while consuming 34.1 mW and occupying a core area of 0.32 mm2. The effectiveness of the embedded DFE in timing margin improvement is verified for 1.5-Gb/s operation over high-loss FR4 channels at a bit error rate (BER) of 10−9.

Aviation Data Lake: Using Side Information to Enhance Future Air-Ground Vehicle Networks

Future denser air-ground vehicle networks (AGVNs) face challenges such as resource allocation, mobility management, secure transmission, and so on. At the same time, surveillance is a must for modern air traffic management. This motivates us to find opportunities in the aerial vertical by forming a conceptual surveillance plane for aerial vehicles. In this article, we propose an enhanced software-defined network architecture where the surveillance plane can provide local and global surveillance information to macro stations, acting as a side system for the communication links. We review air- ground communications and, by summarizing challenges and opportunities, propose the enhanced architecture of side-information-assisted networks in detail. We then present how we obtain, organize, manage, and utilize the local and global side information by a so-called aviation data lake (ADL). The data lake can be easily connected with advanced machine learning schemes and, thus, provide timely, context-aware metrics and predictions.