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A reconfigurable wearable textile antenna with wide frequency tuning range is demonstrated in this work. The frequency agility is realized by adding a coplanar reconfiguration module to a planar inverted-F antenna (PIFA) constructed in textile technology. The reconfiguration module consists of a small flexible printed circuit board (PCB) which integrates a tuning circuitry with commercial snap-on buttons as electronic-to-textile connectors. Using this module equipped with a varactor diode, the frequency reconfigurability of the PIFA is investigated and optimized parametrically for maximum tuning range, exploiting a smooth transition from a quarter-wave to a half-wave patch resonant mode. A fabricated prototype demonstrates a very wide tuning range of approximately 70% (or one octave) with stable directive radiation characteristics, as predicted by simulations. The robust performance and mechanical stability of the reconfigurable antenna in various on-body and bending configurations validates the viability of the antenna tuning concept and the practicality of the proposed coplanar reconfiguration module.

Origami, the ancient art of paper folding, has shown its potential as a versatile platform to design various reconfigurable structures. The designs of most origami-inspired architected materials rely on a periodic arrangement of identical unit cells repeated throughout the whole system. It is challenging to alter the arrangement once the design is fixed, which may limit the reconfigurable nature of origami-based structures. Inspired by phase transformations in natural materials, here we study origami tessellations that can transform between homogeneous configurations and highly heterogeneous configurations composed of different phases of origami unit cells. We find that extremely localized and reprogrammable heterogeneity can be achieved in our origami tessellation, which enables the control of mechanical stiffness and in-situ tunable locking behavior. To analyze this high reconfigurability and variable stiffness systematically, we employ Shannon information entropy. Our design and analysis strategy can pave the way for designing new types of transformable mechanical devices. Origami-inspired metamaterials are attractive for their programmable shape-shifting properties but are typically characterized by low structural rigidity. Here, 3D heterogeneous origami structures display highly reconfigurable mechanical properties, including finely controllable and reversible stiffness variation.

In this article, we present the novel hardware and software architecture of a smart optical force–torque sensor. The proposed configurable, modular, and compact electronics lead to performance characteristics that cannot be reached by currently available sensors: ultra-low noise with average noise power spectral density of 15 nV/ $\sqrt{\text{Hz}}$ over a signal bandwidth of 500 Hz, a resolution of 0.0001% full scale at a 95% confidence level, and a hardware latency of less than 100 $\mu$ s. Performance is achieved by local synchronized oversampling of the sensor's optical transducers and parallel hardware processing of the sensor data using a field-programmable gate array (FPGA). The FPGA's reconfigurability provides for easy customization and updates; for example, by increasing the FPGA system clock rate to a maximum of 160 MHz, latency can be decreased to 50 $\mu$ s, limited by the current analog-to-digital converter. Furthermore, the approach is generic and could be duplicated with other types of transducers. An inertial measurement unit and a temperature sensor are integrated into the sensor electronics for gravity, inertia, and temperature compensations. Two software development kits that allow for the use of the sensor and its integration into the robot operating system have been developed and are discussed.

Nowadays, supply chain disruptions caused by COVID-19 pandemic, demand variation, raw material shortage, etc., made the supply chains unable to deal with emerging market problems. Responding to the new requirements has underscored the need to ensure a reconfigurable supply chain in order to survive in this uncertain economic environment. Indeed, the objective of this study is to identify the quantitative factors of each reconfigurability characteristic representing the reconfigurability assessment indicators (modularity, integrability, convertibility, diagnosability, scalability and customization). Based on the literature review, quantitative factors used to assess the degree of reconfigurability in supply chain are determined. These factors allow classifying reconfigurability characteristics according to the degree of their influence on the supply chain structure or supply chain functions. Through this research work, we try to facilitate the assessment of reconfigurability based on its characteristics in order to determine the ability of the supply chain to cope with new emerging disruptions.

Fifth-generation networks are becoming a reality, and radio access network architectures are being redefined and rebuilt to accommodate the emerging specifications and demands. The future radio access networks need to incorporate in their architectural design smooth reconfigurability and high flexibility without compromising the throughput and the perceived quality of the new services and traffic types that future networks introduce. Such densely distributed access networks suffer the effect of inter-cell interference. Robust and intelligent coordination of multiple access networks is required in order to minimize the effect of interference and maximize users' gains. Coordinated multipoint operation is already considered as a promising technique for satisfying the challenges of the spectrum and interference management, especially for users at the edge of the cell coverage area. To increase the benefits of coordination multipoint technology in optimizing service quality in dense small cell networks, this study proposes the adaptation of game theory, which will optimize the formation of cooperated base station clusters. The system-level simulations performed indicate that there is a significant increase in the throughput of users located at the edge of cells, without compromising the quality of service experienced by the rest of the users, thus rendering it a suitable candidate for the emerging next-generation networks.

International audience; Enterprises now face a global, dynamic, and unpredictable economic environment. In response to quick changes of the demand, the production needs to have the ability to adapt rapidly to meet the production requirements. The Reconfigurable Manufacturing System (RMS) paradigm enables such capabilities. However, defining design and reconfiguration rules is highly challenging, as it requires a broad knowledge encompassing the inclusion of technological, production, and economic metrics, as well as an understanding of a reconfiguration strategy, determining the necessary reconfiguration frequency of the system. For now, no global methodology taking all those aspects into account has been proposed. This article presents an original framework for the design, evaluation, and reconfiguration of the Reconfigurable Production System (RPS). New metrics to measure reconfigurability are defined. The design approach consists in three main steps which are individually developed. The selection of the appropriated production system is based on the comparison of reconfigurability and productivity indicators. Finally, the reconfiguration strategy is presented. The methodology is applied on a case study from the automotive industry.

Bidirectional associative memories (BAMs) have been extensively applied in auto and heteroassociative learning. However, the research on the hardware implementation of BAM neural networks is relatively few. Memristor, a nanoscale synaptic-like element, provides a new perspective for the circuit implementation of neural networks. In this work, we improve a threshold memristor bridge circuit (T-MBC) and design a novel memristive bidirectional associative memory (MBAM) network circuit on this basis. T-MBC is capable to achieve positive, negative, and zero synaptic weights without any switches, inverters, transistors, and current–voltage conversion processes. The validity of T-MBC is illustrated by PSPICE. MBAM has a simpler structure and gains excellent effects in flexibility, and reconfigurability. Besides, it is shown that MBAM can be trained to recall both disturbed binary images and incomplete/noisy grey-scale images robustly. Meanwhile, a more complex application of emotion classification based on MBAM is also accomplished. Experimental results verify the effectiveness of the MBAM neural network and demonstrate that the MBAM neural network has high recognition accuracy and strong noise immunity.

Analog photonic solutions offer unique opportunities to address complex computational tasks with unprecedented performance in terms of energy dissipation and speeds, overcoming current limitations of modern computing architectures based on electron flows and digital approaches. The lack of modularization and lumped element reconfigurability in photonics has prevented the transition to an all-optical analog computing platform. Here, we explore, using numerical simulation, a nanophotonic platform based on epsilon-near-zero materials capable of solving in the analog domain partial differential equations (PDE). Wavelength stretching in zero-index media enables highly nonlocal interactions within the board based on the conduction of electric displacement, which can be monitored to extract the solution of a broad class of PDE problems. By exploiting the experimentally achieved control of deposition technique through process parameters, used in our simulations, we demonstrate the possibility of implementing the proposed nano-optic processor using CMOS-compatible indium-tin-oxide, whose optical properties can be tuned by carrier injection to obtain programmability at high speeds and low energy requirements. Our nano-optical analog processor can be integrated at chip-scale, processing arbitrary inputs at the speed of light. All-optical platforms hold potential for fast and efficient analog computing, but are limited by their size and poor reconfigurability. Here, a zero-index nanophotonic platform enables post-Moore’s law analog optical computing, processing data with high throughput and low-energy levels.

Reconfigurable and scalable plasmonics demultiplexers have attracted increasing attention due to its potential applications in the nanophotonics. Therefore, here, a novel method to design compact plasmonic wavelength demultiplexers (DEMUXes) is proposed. The designed structures (two, four, and six-channel DEMUXes) consist of symmetrical rectangular resonators (RRs) incorporating metal nano-rod defects (NRDs). In the designed structures, the RRs are laterally coupled to metal–insulator-metal (MIM) waveguides. The wavelengths of the output channels depend on the numbers and radii of the metal NRDs in the RRs. The results obtained from various device geometries, with either a single or multiple output ports, are performed utilizing a single structure, showing real reconfigurability. The finite-difference time-domain (FDTD) method is used for the numerical investigation of the proposed structures. The metal and insulator used for the realization of the proposed DEMUXes are silver and air, respectively. The silver’s permittivity is characterized by the well-known Drude model. The basic plasmonic filter which is used to design plasmonic DEMUXes is a single-mode filter. A single-mode filter is easier to cope with in circuits with higher complexity such as DEMUXes. Also, different structural parameters of the basic filter are swept and their effects on the filter’s frequency response are presented, to provide a better physical insight. Taking into account the compact sizes of the proposed DEMUXes (considering the six-channel DEMUX), they can be used in integrated optical circuits for optical communication purposes.

An asynchronous event-driven approach to clocking and timing control is explored in the context of pipelined ADCs. It is shown how a conventional global clock tree can be replaced by localized control units coordinated through inter-stage communication protocols. The approach is found to yield many compelling advantages in terms of power efficiency, speed, robustness, and reconfigurability. It is shown how these benefits are particularly well leveraged when used in combination with dynamic-power residue amplifiers such as ring amplifiers. Several challenges also arise: re-synchronization of the digital outputs, mitigation of possible deadlock scenarios, and robust timing control configuration. Solutions to these problems are presented. Two single-channel 11-bit 1.5-bit/stage pipelined ADC designs are fabricated in a 16nm CMOS technology, each with a different implementation approach to the asynchronous control units. The trade-offs of both approaches are considered. At 1 GS/s the fastest prototype achieves 59.5 dB SNDR and 75.9 dB SFDR at Nyquist, consuming 10.9 mW including reference regulator. Due to fully-dynamic operation, it maintains a near-constant Walden Figure of Merit (FoM) of 14 fJ/conversion-step from 1 MS/s to 1 GS/s.

Digital microfluidic biochips (DMFBs) have been a revolutionary platform for automating and miniaturizing laboratory procedures with the advantages of flexibility and reconfigurability. The placement problem is one of the most challenging issues in the design automation of DMFBs. It contains three interacting NP-hard sub-problems: resource binding, operation scheduling, and module placement. Besides, during the optimization of placement, complex constraints must be satisfied to guarantee feasible solutions, such as precedence constraints, storage constraints, and resource constraints. In this article, a new placement method for DMFB is proposed based on an evolutionary algorithm with novel heuristic-based decoding strategies for both operation scheduling and module placement. Specifically, instead of using the previous list scheduler and path scheduler for decoding operation scheduling chromosomes, we introduce a new heuristic scheduling algorithm (called order scheduler) with fewer limitations on the search space for operation scheduling solutions. Besides, a new 3D placer that combines both scheduling and placement is proposed where the usage of the microfluidic array over time in the chip is recorded flexibly, which is able to represent more feasible solutions for module placement. Compared with the state-of-the-art placement methods (T-tree and 3D-DDM), the experimental results demonstrate the superiority of the proposed method based on several real-world bioassay benchmarks. The proposed method can find the optimal results with the minimum assay completion time for all test cases.

Under the current volatile business environment, the requirement of flexible production is becoming increasingly urgent. As an innovative production mode, seru-system with reconfigurability can overcome the lack of flexibility in traditional flow lines. Compared with pure seru-system, the hybrid seru-system composed of both serus and production lines is more practical for adapting to many production processes. This paper addresses a specific hybrid seru-system scheduling optimization problem (HSSOP), which includes three strongly coupled sub-problems, i.e., hybrid seru formation, seru scheduling and flow line scheduling. To minimize the makespan of the whole hybrid seru-system, we propose an efficient cooperative coevolution algorithm (CCA). To tackle three sub-problems, specific sub-algorithms are designed based on the characteristic of each sub-problem, i.e., a sub-space exploitation algorithm for hybrid seru formation, an estimation of distribution algorithm for seru scheduling, and a first-arrive-first-process heuristic for flow line scheduling. Since three sub-problems are coupled, a cooperation coevolution mechanism is proposed for the integrated algorithm by information sharing. Moreover, a batch reassign rule is designed to overcome the mismatch of partial solutions during cooperative coevolution. To enhance the exploitation ability, problem-specific local search methods are designed and embedded in the CCA. In addition to the investigation about the effect of parameter setting, extensive computational tests and comparisons are carried out which demonstrate the effectiveness and efficiency of the CCA in solving the HSSOP.

This article presents an active cylindrical metasurface with spatial reconfigurability to achieve dynamic control of the radar cross section (RCS) reduction. The proposed metasurface is designed based on the combination of microwave transmission network and Mie scattering. In particular, by modulating the spatial coding sequence of p-i-n diodes in meta-atoms, the surface impedance of the metasurface can be dynamically changed, which enables an active metasurface to operate in an expanded frequency band via time-division multiplexing technique. Both simulated and measured results demonstrate that the proposed cylindrical metasurface with an ultrathin thickness of $0.018\lambda $ can be continuously tuned across a wide fractional bandwidth over 32% for reducing backward scattering by 10 dB. The proposed metasurface with ultrathin thickness, tunability, conformal profile, and high performance may be applied to wideband RCS reduction, as well as advanced noninvasive detection, communication, etc.

The COVID 19 pandemic, fluctuating demand, market uncertainty and the emergence of new technologies explain the need for a more flexible and agile supply chain. In fact, several important factors should be taken into account in the process of building an adaptive and reconfigurable supply chain. Reconfigurability is used to measure quantitatively the capability of supply chain to change easily their structure and functions. The aim of this work is to evaluate the level of reconfigurability of a supply chain. Quantitative measures of six indicators that characterize reconfigurability are presented in this paper. Then, an index of reconfigurability in supply chain is developed based on The Multi-Attribute Utility Theory in order to choose the most reconfigurable configuration. An illustrative example is also given. From the discussion, it is deduced that the characteristics of the reconfigurable supply chain impacts positively on the degree of reconfigurability.

Physical Unclonable Functions (PUFs) address the inherent limitations of conventional hardware security solutions in edge-computing devices. Despite impressive demonstrations with silicon circuits and crossbars of oxide memristors, realizing efficient roots of trust for resource-constrained hardware remains a significant challenge. Hybrid organic electronic materials with a rich reservoir of exotic switching physics offer an attractive, inexpensive alternative to design efficient cryptographic hardware, but have not been investigated till date. Here, we report a breakthrough security primitive exploiting the switching physics of one dimensional halide perovskite memristors as excellent sources of entropy for secure key generation and device authentication. Measurements of a prototypical 1 kb propyl pyridinium lead iodide (PrPyr[PbI3]) weak memristor PUF with a differential write-back strategy reveals near ideal uniformity, uniqueness and reliability without additional area and power overheads. Cycle-to-cycle write variability enables reconfigurability, while in-memory computing empowers a strong recurrent PUF construction to thwart machine learning attacks., Despite the impressive demonstrations with silicon and oxide memristors, realizing efficient roots of trust for resource-constrained hardware remains a challenge. Here, the authors exploit switching behavior in one dimensional perovskite memristors to design security primitives for key generation and device authentication.

Shape-changing mechanical metamaterials have drawn the attention of researchers toward the development of continuous-range tunable frequency selective surfaces (FSSs). In this paper, a novel tunable FSS utilizing an origami-inspired “eggbox” structure is presented featuring four-degrees of freedom that can change the frequency response of two orthogonal linear polarizations. The centrosymmetric “eggbox” structure can be folded or rotated along two axes that lead to unprecedented reconfigurability compared to traditional Miura-Ori-based structures which have fewer degrees of control. The utilized cross-shaped dipole FSS element shows enhanced bandwidth, support for orthogonal linear polarization, and ease of fabrication. The prototype is fabricated using a low-cost fully additive inkjet printing process with silver nanoparticle conductive ink. The outcome of this study shows a 25% frequency tunable range over two polarization directions. The design can be an ideal spatial filtering candidate for advanced ultra-wideband terrestrial and space applications.

Physically unclonable function (PUF) has been increasingly used as a promising primitive for hardware security with a wide range of applications in the Internet of Things (IoT). In recent years, novel PUF techniques based on resistive switching mechanism in various emerging nonvolatile memories have demonstrated superior performance on reliability and integration density. In this work, a resistive random access memory (RRAM)-based PUF chip with 8-kb capacity is developed. Two operation modes, namely differential mode and median mode, are embedded on chip. To implement these modes, a current sampling-based sense amplifier is designed to distinguish the current values of the PUF cells and the reference cell. In addition, a split-resistance scheme is proposed to enhance the PUF’s reliability significantly. The experiment results show that the differential PUF exhibits excellent performance with native bit error rate (N-BER) below 6 $\times $ 10−6 and inter-Hamming distance (inter-HD) of 49.99%. In the meanwhile, the reconfigurability of PUF challenge-response pairs (CRPs) is demonstrated with 49.77% and 47.29% reconfigure-Hamming distance (reconfigure-HD) in the median mode and the differential mode, respectively.

Deep neural networks (DNNs) have substantial computational requirements, which greatly limit their performance in resource-constrained environments. Recently, there are increasing efforts on optical neural networks and optical computing based DNNs hardware, which bring significant advantages for deep learning systems in terms of their power efficiency, parallelism and computational speed. Among them, free-space diffractive deep neural networks (D$^2$NNs) based on the light diffraction, feature millions of neurons in each layer interconnected with neurons in neighboring layers. However, due to the challenge of implementing reconfigurability, deploying different DNNs algorithms requires re-building and duplicating the physical diffractive systems, which significantly degrades the hardware efficiency in practical application scenarios. Thus, this work proposes a novel hardware-software co-design method that enables robust and noise-resilient Multi-task Learning in D$^2$NNs. Our experimental results demonstrate significant improvements in versatility and hardware efficiency, and also demonstrate the robustness of proposed multi-task D$^2$NN architecture under wide noise ranges of all system components. In addition, we propose a domain-specific regularization algorithm for training the proposed multi-task architecture, which can be used to flexibly adjust the desired performance for each task., Comment: 23 pages including references and Supplementary Information. To appear in Nature Scientific Reports

This article presents a 3-D reconfigurable memory I/O transceiver using a quad-band interconnect (QBI). The 3-D QBI provides I/O data reconfigurability, decreases latency, and reduces pin count for future compact mobile memory interfaces. The 3-D integrated circuit (3-D IC) technique is utilized to reduce signal latency and improve signal integrity. A novel quad-band transformer is proposed to achieve reconfigurable four-band data communication and reduce the I/O pin count by four times. A two-tier QBI die-stack is implemented to verify the QBI design. Face-to-face configuration with $\mu $ bump interconnects is used to save cost. The QBI chips are designed and fabricated in a 180-nm CMOS process. The chip areas of the top and bottom dies are 1.77 and 1.4 mm2, respectively. The measured data rates, with bit error rate (BER) $ , are up to 2 Gb/s in the baseband (BB) and 2.3, 2.5, and 3 Gb/s in RF-bands. The QBI energy efficiencies, with a 1.8-V supply voltage, are 5.9 pJ/b in the BB and 6.2, 7.4, and 8 pJ/b in the RF-bands.

Being a structure like a two-dimensional (2D) array of microvalves and cells, Programmable Microfluidic Device PMD biochips have the characteristics of reconfigurability and flexibility unlike conventional flow-based microfluidic biochips. In recent years, several design automation techniques for PMD biochips have been reported. For automated control of the PMD chip implementing a bioprotocol, one of the important tasks is to minimize the number of fluid flows for loading the reactant fluids into specific cells before the bioprotocol is executed. In this work we intensively study the fluid loading problem for PMD chips and we propose a two-phase approach to solve this problem. First, we propose a constraint satisfaction problem (CSP) based method, called loading-aware fluid-to-cell assignment (LAFCA) in order to obtain a suitable fluid-to-cell assignment, which will be beneficial for fluid loading phase. Then we propose an exact method, called CSP-based loading algorithm (CSPLA) and a near-optimal heuristic method, called determining flows from the last (DFL), for determining a sequence of fluid flows required to load different fluids into the cells of a PMD chip. We formulate CSPLA as a single objective optimization problem to minimize the total number of flows. For the output as a sequence of fluid flows we define three loading parameters, the total number of flows (K), the total number of 90° bends in all flow paths (B), and the total flow path length (L). Simulation results confirm that LAFCA combined with CSPLA outperforms (K, B and L reduced by 63.9%, 31.7% and 59.9%, respectively) the state-of-the-art method fluid loading algorithm for PMD (FLAP) [Gupta et al., TODAES, 2019]. Whereas, LAFCA combined with DFL can reduce the loading parameters K, B and L by 61.2%, 20.8% and 57.4%, respectively over using only FLAP. Also from the overall simulation results we can conclude that for many testcases, DFL can find the near-optimal Ks.

This work aims to develop a quantitative reconfigurability evaluation method for control systems with disturbances in the case of actuator outages. The basic idea of this method is to investigate and quantify the performance of the nominal system under the condition that the specified faults are recoverable. We propose a reconfigurability index based on H 2 performance that simultaneously considers both the normal scenario and various fault scenarios. A modified Newton–Kleinman algorithm is used to calculate the evaluation index. Guided by the result of the reconfigurability evaluation, the system structure is optimized to achieve a tradeoff between the control performance under normal conditions and the reconfiguration performance under the fault conditions. Finally, the effectiveness of the proposed method is illustrated through two application examples, namely, aircraft and satellite attitude control systems.

This communication proposes a wideband circular-polarized (CP) beam steering dielectric resonator antenna (DRA) using a gravitational ball lens. It offers a passive means for wall or ceiling mounted base station antennas to adjust their patterns by the gravity of ball lenses. This novel antenna concept overcomes the difficulties of achieving wideband axial ratio versus the pattern reconfigurability of the existing antennas. The operation of the ball lens has been intensively studied. It is found that the ball lens provides 1.2 dB antenna gain enhancement, whereas enabling beam tilting via energy coupling to the offset direction. As a demonstration, a codesign of DRA and ball lens has been developed at 2.4 GHz, achieving 42% impedance bandwidth, 39% axial ratio bandwidth, and ±40° beam steering. Reasonable agreement between simulated and measured results is observed. The proposed DRA provides a low-cost solution for base stations to be mounted at an angle and effectively cover the indoor users.

This paper proposes a reconfigurable circular microstrip antenna to serve the wireless communication applications that make use frequency bands such as ISM (Industrial Scientific and Medical), WLAN (Wireless Local Area Network), UMTS (Universal Mobile Telecommunications Service). Reconfigurability is achieved with the help of four MEMS (Micro-Electro-Mechanical Systems) switches to change the frequency and radiation properties of the antenna. By choosing either of the two states of each of the MEMS switches, the radius of the circular patch is varied and subsequently the operating resonant frequency. This gives rise to multiple configurations of the antenna to serve for different wireless applications. Defected Ground Structure is employed in this design to lower the resonant frequency and improve the bandwidth. Concentric rings are implemented along with a core circular patch in order to increase the radiating area of the patch in association with the MEMS-based switches to operate in toggle mode of ON and OFF. The concentric rings also helping in obtaining dual-frequency behavior of the antenna and the measured results are showing good agreement with the simulation results.

Large-distance communications beyond a few meters is challenging for Terahertz (THz) signals because of high spreading loss and absorption in the media. The smart antenna concept used for RF antennas to improve the signal-to-interference/noise level can be extended to these THz antennas. Out of the two types of implementations of this concept, viz. (i) adaptive array and (ii) switched-beam antenna, this paper presents the switched-beam nanoantenna for the THz wave region. Based on the Yagi-Uda antenna concept, switched-beam graphene nanoantennas over silicon dioxide (SiO2) substrate is proposed in this paper. In one case (Antenna-I), the antenna is able to switch the beam in ± 90o directions, whereas in the other case (Antenna-II), the switching directions are 0o, ± 90o, 180o. This pattern reconfigurability can also be observed over a frequency range leading to simultaneous pattern and frequency reconfigurable nature of the nanoantenna. The reconfigurability is obtained by changing the graphene conductivity through its chemical potential. Due to plasmonic wave propagation in graphene at THz, the proposed graphene nanoantenna resonates at a sub-wavelength scale. Design aspects and the working principle of switched-beam graphene plasmonic nanoantennas in the THz region are discussed in this paper.

Nonvolatile and durable ionogels are emerging and promising stretchable ionic conductors for wearable electronics. However, the construction of reconfigurable and recyclable ionogels with high mechanical robustness, high stretchability, and autonomous healability, while heavily demanded, is very challenging. Here, we present a gradient-responsive cross-linking strategy for preparing a highly stretchable and reconfigurable thermoplastic engineering ionogel (TPEI). The design of both microcrystalline and dense hydrogen bonds in TPEI contributed to the formation of a unique gradient-responsive network. When the TPEI was melt-processed under heating, the microcrystalline network structure was destroyed to form entangled polymer chains, while the high-density hydrogen-bonded network structure was only partially destroyed. The remaining hydrogen-bonded network allowed the TPEI to have a high viscosity for melt processing. When the TPEI was cooled upon melting injection, extrusion, and spinning, the hydrogen-bonded network was rapidly reconstructed in tens of seconds, allowing it to be reconfigured and reshaped, while the microcrystalline network was further reconstructed to improve its mechanical strength and elasticity during subsequent aging. As a result, the TPEI exhibited engineering-hydrogel-level mechanical robustness (>100 kPa), extremely high stretchability (>1000%), wide-temperature tolerance (−20 to 80 °C), and ultrafast self-healability in few seconds. Due to its mechanical adaptability, high ionic conductivity, and reconfigurability, the TPEI was demonstrated to readily work as a self-healable and recyclable stretchable conductor in a wearable skin-inspired sensor for monitoring sophisticated human motions.

Fiber Reinforced Elastomeric Enclosures (FREEs) have gained significant popularity as a form of soft artificial muscle for the diversified deformation behaviors upon pressurization. In particular, modular FREEs connected in series, demonstrate enhanced flexibility and reconfigurability, thus are adaptable to more complex trajectory tasks. Morphology and motion parameters are strongly coupled for soft manipulators to achieve desired motion behaviors. In contrast to the traditional way of alternating between design optimization in either morphology or actuation space, we seek to co-optimize over parameters in both spaces in an end-to-end fashion with gradient-free optimization. The co-optimization framework allows for faster convergence towards optimal performance given desired trajectory plans. We demonstrated the feasibility of the framework with two simulated tasks: the multiple shape matching task and the octopus reaching task. The former task was further evaluated with real-world experiments.

This paper presents a 32-channel analog filterbank for front-end signal processing in sound classification systems. It employs a passive N-path switched capacitor topology to achieve high power efficiency and reconfigurability. The circuit’s unwanted harmonic mixing products are absorbed by the machine learning model during training. To enable a systematic pre-silicon study of this effect, we develop a computationally efficient circuit model that can process large machine learning datasets on practical time scales. Measured results using a 130 nm CMOS prototype IC indicate competitive classification accuracy on datasets for baby cry detection (93.7% AUC) and voice commands (92.4% average precision), while lowering the feature extraction energy compared to digital realizations by approximately $2\times $ and $10\times $ , respectively. The 1.44 mm2 chip consumes 800 nW, which corresponds to the lowest normalized power per simultaneously sampled channel in recent literature.

Scientific computations with a wide range of applications in domains such as developing vaccines, forecasting the weather, predicting natural disasters, simulating aerodynamics of spacecraft, and exploring oil resources, create the main workloads of supercomputers. The key integration of such scientific computations is modeling physical phenomena that are done with the aid of partial differential equations (PDEs). Solving PDEs on supercomputers, even with those equipped with GPUs, consumes a large amount of power and yet is not as fast as desired. The main reason behind such slow processing is data dependency. The key challenge is that software techniques cannot resolve these dependencies, therefore, such applications cannot benefit from the parallelism provided by processors such as GPUs. Our key insight to address this challenge is that although we cannot resolve the dependencies, we can reduce their negative impacts by using hardware/software co-optimization. To this end, we propose breaking down the data-dependent operations into two groups of operations: a majority of parallelizable and the minority of data-dependent operations. We execute these two groups in the desired order: first, we put together all parallelizable operations and execute them all, subsequently; then, we switch to execute the small data-dependent part. As long as the data-dependent part is small, we can accelerate them by using fast hardware mechanisms. Besides, our proposed hardware mechanisms guarantee quickly switching between the two groups of operations. To follow the same order of execution, dictated by our software mechanism, and implemented in hardware, we also propose a new low-overhead compression format – sparsity is another attribute of PDEs that require compression. Furthermore, the core generic architecture of our proposed hardware allows the execution of other applications including sparse matrix-vector multiplication (SpMV) and graph algorithms. The key feature of the proposed hardware is partial reconfigurability, which on one hand, facilitates the execution of data-dependent computations, and on the other hand, allows executing broad application without changing the entire configuration. Our evaluations show that compared to GPUs, we achieve an average speedup of 15.6× for scientific computations while consuming 14× less energy.

In this letter, a novel reconfigurable filter concept, which is called assembly reconfigurability through rotation, is proposed for the first time to implement a high-Q filter with adjustable frequency response. Two separated printed circuit boards (PCBs) are designed and assembled together to build a double-layer substrate integrated waveguide (SIW) filter. Guided by coupling matrix synthesis, the filter is designed to have adjustable filtering features by mechanically rotating one of the boards. Specifically, by only rotating the top PCB layer to different directions, three kinds of assembly states can be achieved, resulting in variable frequency response with transmission zeros (TZs) created at below, above, or both sides of the passband. Two design prototypes, which present 2- and 3-pole responses, respectively, are simulated and measured to validate the novel idea. The results show that two compact, low-loss fully shielded filters with adjustable response shape are developed, which well verify the concept of assembly reconfigurability for filter synthesis.

This article presents a design strategy to improve the bandwidth of the three-stage Doherty Power Amplifier (DPA) by controlling the phase difference between the dual RF inputs digitally. The theory also proposes multiple back-off reconfigurability without using tuning elements and extra circuitry. The proposed theory is validated by demonstration of a dual-input three-stage DPA which is designed and implemented using Wolfspeed’s GaN HEMT transistors. The measured results show a drain efficiency of 50.4 – 58% and 46.1 – 65.4% at 12 dB and 6 dB back-off respectively, over the frequency range of 550-900 MHz. Over this 350 MHz band, the drain efficiency is between 53.97% and 71.5% at saturation, corresponding to 48.3% fractional bandwidth. The measurement results also show that both the back-offs are reconfigurable by changing the drain bias of main and first auxiliary power amplifier. The modulated measurements are carried with a 10 MHz LTE signal with a PAPR of 11.75 dB. The high average efficiency of 51.6%, 54.9%, and 52.6% is reported at 600, 700, and 800 MHz, respectively, at an average power of around 30 dBm. The measurement results validate the theory proposed making the presented DPA as a potential candidate for future wireless transmitters.

A reconfigurable antenna with a compact size and quad-polarization reconfigurability is presented. By employing a switchable feed scheme, the antenna can operate at single-fed and dual-fed modes. At single-fed mode, the feed structure allows output ports switching to produce the excitations for either slant +45° or −45° linear polarization (LP). At dual-fed mode, it serves as a switchable phase-shifting power splitter for generating left-hand circular polarization (LHCP) or right-hand circular polarization (RHCP). To realize a simple and space-saving configuration, the antenna makes efficient use of the proposed feed structure, which is highly shared among the four polarization states. Measured results show that the antenna exhibits operating bandwidths of 230 and 260 MHz at circular polarization CP and LP states, respectively. Moreover, stable broadside radiation patterns as well as moderate gains could also be obtained.

Cloud computing is a scalable and efficient technology for providing different services. For better reconfigurability and other purposes, users build virtual networks in cloud environments. Since some applications bring heavy pressure to cloud datacenter networks, it is necessary to recognize and optimize virtual networks with different applications. In some cloud environments, cloud providers are not allowed to monitor user private information in cloud instances. Therefore, in this paper, we present a virtual network recognition and optimization method to improve quality-of-service (QoS) of cloud services. We first introduce a community detection method to recognize virtual networks from the cloud datacenter network. Then, we design a scheduling strategy by combining SDN-based network management and instance placement to improve the service-level agreements (SLA) fulfillment. Our experimental result shows that we can achieve a recognition accuracy as high as 80 percent to find out the virtual networks, and the scheduling strategy increases the number of SLA fulfilled virtual networks.

A reconfigurable and application-specific tunable microwave photonic filter having finite impulse response is proposed. The filter exploits the differential mode group delays of linearly polarized modes in a multi-mode fiber to achieve single and multiple high-frequency passband response. The filter taps are realized using a single continuous wave laser source and differential delays among modes that are propagated through a single spool of graded index multi-mode fiber. Depending upon the application requirement, different values of free spectral range of the microwave photonic filter are obtained by employing fiber spools of different lengths. The reconfigurability of the microwave photonic filter is achieved by varying the number of linearly polarized modes. It has been shown that the passband ripple can be reduced by employing higher order spatial modes and unequal power ratio among different modes. The proposed filter enables application-specific free spectra range tunability and reconfigurability along with added advantages of easy implementation and passband optimization.

To satisfy the stringent requirements of the emerging wireless communication system, the dual-band operation and reconfigurability are both desired for the front end. However, few works can realize them simultaneously. In addition, the flexibility of the implemented reconfigurability is limited. In this article, a reconfigurable dual-band quadrature coupler with independently tunable characteristics at the lower band is proposed. Based on the investigation of an ideal model, the design requirements to achieve the previous reconfigurability can be obtained. Thus, the coupled line loaded with varactor is proposed on a patch coupler to implement the desired functionality. By varying the voltages applied on the varactors, the frequency and coupling coefficient at the lower band of the proposed coupler can be tuned independently with the characteristics at the upper band fixed. For validation, a prototype was designed, fabricated, and measured. Measured results show that the frequency of the coupler at the lower band can be tuned from 2.9 to 3.2 GHz. Meanwhile, the corresponding coupling coefficient can be tuned from 3 to 10 dB. During the lower band tuning, 3 dB coupling coefficient and quadrature phase difference can be always maintained for upper band, which is fixed at 4.7 GHz.

With the speedy evolution in the wireless communication systems, there is an extreme requirement for extraordinary data rate, high reliability, and good quality of transmission link. To aid these requirements, techniques involving Multiple-Input-Multiple-Output- (MIMO) antenna is one of the utmost promising implementations. Without surplus power requirement, it employs multiple radiators at both transmitting and receiving side that further improves the system capability and reliability. Strength of a signal and data throughput of wireless communication systems can be enhanced further by implementing a system which is reconfigurable with MIMO antenna. However, there can also be a common situation where there can be coexistence of all the wireless bands. Hence designing of UWB-MIMO is a challenging assignment and it turns into a more challenging task when the preference of selective band rejection is also integrated (i.e.) a method of introducing reconfigurability. This article gives a bird view for the beginners those work on reconfigurable MIMO antennas with band notch features and develops them to have a great insight about the available reconfigurable MIMO antennas. Further this type of review is not presented in the literature to our knowledge.

This article presents novel designs of reconfigurable microwave filters based on the recently introduced concept of field programmable microwave substrate (FPMS). Using reconfigurable FPMS substrate, significant tuning freedom of the designed microwave filters can be achieved. It allows implementation of smart filter designs with tunable center frequencies, operational bandwidths, and filter orders. Moreover, different microwave filter types are also realizable on one FPMS board with simple dynamic control. As a proof-of-concept, design steps are described for three filter types, including waveguide bandpass filter, quarter-wave-coupled bandpass filter, and waveguide bandstop filter. A good match between the simulated and measured results is presented, showing good tuning range for the center frequency and bandwidth of the bandpass filters around 2 GHz. In addition, the reconfigurability of the design allows it to switch to bandstop filters, which is a complete change in topology from a single physical design. The merits of the proposed design are reflected in the realized bandpass filter, exhibiting center frequency tuning of more than 20% along with bandwidth variability spanning three times its minimum value. Finally, a significant size reduction compared with the designs using conventional technologies is also demonstrated. With its inherent flexibility, low cost, and high degree of integration, FPMS filtering is suited to a wide variety of RF applications.

Industrial Internet of Things (IIoT) represents a backbone of modern reconfigurable manufacturing systems (RMS), which enable manufacturing of a high product variety through rapid and easy reconfiguration of manufacturing equipment. In IIoT-enabled RMS, modular equipment is built from smart devices, each performing its own tasks, whereas the global functioning is achieved through their networking and intensive communication. Although device communication contributes to the system reconfigurability, it also opens up new security challenges due to potential vulnerability of communication links. In this article, we present security analysis for a major part of RMS in which manufacturing equipment is sequentially controlled and can be modeled as discrete event systems (DES). Control distribution within DES implies communication of certain events between smart modules. Specifically, in this work, we focus on attacks on communication of these events. In particular, we develop a method for modeling such attacks, including event insertion and removal attacks, in distributed sequential control; the method is based on the supervisory control theory framework. We show how the modeled attacks can be detected and provide a method for identification of communication links that require protection to avoid catastrophic damage of the system. Finally, we illustrate and experimentally validate applicability of our methodology on a real-world industrial case study with reconfigurable manufacturing equipment.

Swift and dynamic reconfigurability of network topology, even at the optical layer, is essential for satisfying the various requirements of future networks in diverse areas (e.g., data centers, 5G/Beyond-5G/Local-5G/6G, factory-related networks, and telecom networks) and for addressing issues arising during a disaster. Because of recent efforts to disaggregate optical transport networks, various compact disaggregate blades (e.g., wavelength selective switches and optical amplifier blades) have become commercially available. In principle, such disaggregation technology enables network operators to optimize their networks precisely at the blade level according to their distinctive needs, although the management complexity can increase with the number and diversity of the managed equipment. This paper presents transformation algorithms for mapping between a reconfigurable optical add/drop multiplexer (ROADM)-based model and a disaggregate-blade-based model to realize a flexible and agile optical physical layer based on disaggregation technology without increasing control plane complexity. In this study, a disaggregate-blade-based model named functional block-based disaggregation (FBD) is used, in which the switching functionalities of individual optical components are defined by the integer linear programming (ILP) method using machine-readable GNU MathProg modeling language. By computing the ILP formula, the switching functionalities of whole nodes/networks can be analyzed; that is, the FBD model can form the ROADM-level nodal model by aggregating the individual blade models. With the developed transformation algorithms, automated network operations, including optical path establishment/removal and node structure updates, are experimentally demonstrated on a field testbed. After physically plugging in the new components, the node structure update including the logical topology information is automatically recognized within 5 min. Multi-domain cooperative optical path recovery triggered by the update is also performed.

As a typical Internet-of-Things (IoT) scenario, massive machine-type communications (mMTC) services are expected to grow exponentially and create a multibillion-dollar industry spanning a broad range of vertical sectors. In literature, wireless software-defined network (SDN) is viewed as a promising approach to facilitate the degree of reconfigurability on extended sets of mMTC devices via centralized software updates. However, most of the current anomaly detection scheme (ADS) in SDN suffers from the high risk of overwhelming of the controller as well as excessive energy consumption if directly applied in the network with enormous devices. To address the scalability issues in centralized ADS, we propose a localized ADS scheme, called scalable and energy-efficient anomaly detection scheme (SEE-ADS), comprising of a detection activation module, a lightweight predetection module, a heavyweight anomaly detection module, and a dynamic strategy selection module. Through the cooperation among these modules, the proposed ADS is capable of detecting attacks dynamically and effectively without the risk of energy depletion via discontinuous activation of the heavyweight detection. The lower complexity is fulfilled by developing a localized and adaptive heavyweight detection module, called a localized evolving semisupervised learning-based anomaly detection scheme (LESLA). Besides, the proposed scheme makes full use of feedback from the previous heavyweight activation and the indication of predetection on each packet. The simulation results show that the proposed scheme greatly reduces the overall energy consumption over heavyweight detection. Furthermore, the proposed scheme shows higher sensitivity on abnormal packets and similar false alarm compared with the literature work.

In this article, a polarization reconfigurable concentric circle microstrip antenna with simultaneous frequency agility has presented. The frequency agility and polarization reconfigurability have ...

In this article, the design of a radiation beam-reconfigurable antenna using the reflector pins is presented. The reflector pins make a short or open connection with the ground, via switches and Plated Through Hole (PTH), which helps in controlling radiation characteristics of the proposed antenna. This design contains a simple 3D printed Cylindrical Dielectric Resonator Antenna that is located at the center of the substrate. The beam-sweeping of the antenna is attained by operating switches in different combinations of ON and OFF states. The reconfigurable CDRA operates at 4.5 GHz and covers all azimuth angles in four steps with a maximum measured gain of 6.6 dBi. This beam-switching antenna is very advantageous because of its trait of eliminating fade zones and beamforming.

In these days of great attention around the dawn of 5G deployment, the future 6G scenario poses challenges and sketches trends that, according to the opinion of prominent scholar and scientists, fall far beyond the boundaries of the field that 5G will manage to conquer. In a nutshell, the classical approaches in designing devices, systems and infrastructures, which have been seamlessly followed from 1 to 5G, will not be suitable to build the artificial intelligence-driven (AI) 6G network. Self-adapting capabilities, which 6G will push to the edge, urge for a pronounced separation between hardware (HW) and software (SW), this being in full contrast with the consolidated HW-SW co-design philosophy followed up to date. On one side, algorithms will have to be able to estimate the physical resources they can rely on in order to run in an optimal way. On the other hand, the HW will need to gain more symmetry with respect to the SW, in terms of flexibility, functions reconfigurability and self-adaptivity/self-evolution. This work envisions a prime role for micro/nanotechnologies, embodying materials, electronics and micro/nanosystems, in the future scenario of 6G and of the tactile internet. Such a part is expected to be so prominent that a reformulation of the common concept of HW, triggered by micro/nanotechnologies, is suggested in the next pages. To this end, the WEAF Mnecosystem, i.e. the water, earth, air and fire micro/nanotechnologies Ecosystem, is conceived, leveraging the analogy with the four classical elements in nature. In brief, earth and air represent the classical concepts of HW and SW, respectively. Water is the new formulation of HW that, like water, is liquid in terms of functional characteristics. Moreover, it gains some features typical of the SW (i.e. air). Fire, eventually, is the HW devoted to harvest, store and transfer energy, making it available everywhere at the network edge, i.e. when needed, where needed. Concerning the few reference application examples that are going to be listed below, for the purpose of this work they will focus on MEMS technology.

This paper presents a compact reconfigurable elliptical shaped fractal patch (ESFP) antenna with elliptical shaped RF MEMS switch is used for satellite applications at X-band. The proposed work involves the incorporation of RF MEMS switches loaded using parasitic elements with ease of simpler implementation without using DC bias lines. The proposed antenna is integrated with two MEMS switches and reconfigurability is obtained for varying the capacitance of the switch by actuating the switch to ON and OFF states. The elliptical shape is considered for the proposed microstrip patch antenna is to attain large flexibility in the design and attain good return loss, radiation patterns, gain and bandwidth of the antenna. The proposed antenna is designed on flexible polyamide substrate and resonating frequency is obtained at 9.07 GHz frequency with − 43 dB return loss with gain of 6.05 dB. When the proposed switch is integrated on to the elliptical patch fractal antenna it resonates at four different operating frequencies. Among all the four states the state-4 resonates at 9.02 GHz frequency with − 52.8 dB return loss with gain of 6.36 dB. The ESFP antenna has perform four operating frequencies with two RF-MEMS switches for reconfigurability applications. The simulated results are in good agreement between the measured results. A small deviation is observed between simulated and measured results.

In the last decade, traditional industrial and market features were replaced by emerging factors, such as the variable market demand, the need for flexibility, the shorter product life cycles and the mass personalisation, which drastically modified the production environment, pressing industrial companies to embrace and implement new types of production paradigms. Reconfigurable Manufacturing Systems (RMSs) rose as effective systems able to meet the current challenges rapidly changing their hardware, i.e. physical, and software, i.e. logical, structures to address changes in market needs. The manufacturing environment is usually characterised by dynamic cells, i.e. Reconfigurable Machine Cells (RMCs), including intelligent machines called Reconfigurable Machine Tools (RMTs). Such machines consist of fixed parts, i.e. basic modules, and dynamic parts, i.e. auxiliary modules, which allow performing different tasks, i.e. operations. This paper aims at proposing an optimisation linear programming model for the dynamic management of RMSs best balancing the RMTs reconfiguration, considering the auxiliary modules availability, i.e. the efforts to install and disassemble the auxiliary modules on/from the machines, and the part flows among the RMTs. The application to an operative case study widens the model discussion and a multi-scenario analysis concludes the study analysing how the overall system performances change varying the available auxiliary modules. Globally, results show the joint presence of multiple parts on the same RMT in each period allow concluding about the key role of the auxiliary modules to create useful and flexible structures suitable for multiple part processing.

Assembly systems must provide maximum flexibility qualified by organization and technology to offer cost-compliant performance features to differentiate themselves from competitors in buyers’ markets. By mobilization of multipurpose resources and dynamic planning, Line-less Mobile Assembly Systems (LMASs) offer organizational reconfigurability. By proposing a holarchy to combine LMASs with the concept of an Internet of Production (IoP), we enable LMASs to source valuable information from cross-level production networks, physical resources, software nodes, and data stores that are interconnected in an IoP. The presented holarchy provides a concept of how to address future challenges, meet the requirements of shorter lead times, and unique lifecycle support. The paper suggests an application of decision making, distributed sensor services, recommender-based data reduction, and in-network computing while considering safety and human usability alike.

This paper presents a complete procedure on prototyping using the FPGA of the STEMlab board and is intended to serve as a guide for developers, students and researchers interested in speeding up their projects and experiments. Due to the reconfigurability of its internal circuitry, being as simple as a code modification (using hardware description language), FPGA technology allows testing of several controller topologies and/or parameters without the need of any physical change at hardware. This feature allows a much faster development cycle of either commercial products or academic experiments. Besides the reconfigurability of the FPGA, the STEMlab board also offers the advantage of several peripheral already available, which includes, among others, high speed analog-to-digital and digital-to-analog converters, Ethernet communication and a dual-core ARM processor capable of running a Linux operating system. In this paper, a didactic method of use of this board is presented, from getting started to a complete academic and industrial application: detection of early damage on an induction motor using frequency response analysis.

In this article, we propose a method of designing programmable coding metasurface with a reconfigurable number of reflected beams. Each unit cell of the metasurface is loaded with one varactor to enable adjustable phase responses. The bias, beneath the ground drilled with small holes, is connected to unit cells by a thin via through the holes, to avoid adverse influences on unit cells. To simplify the bias network, a super unit composed of $5 \times 5$ unit cells is taken as the coding element of realizing 2-D coding sequences. With different bias voltages, the unit cell will produce different reflection phases. By programming the bias voltages, the number and directions of reflected beams can be tailored due to different coding sequences. Under normal incident, reflected waves will be split into multiple beams whose directions can be flexibly controlled. We designed a prototype, implemented our design, and carried out experiments. Both the simulation and experiment results show that the number of reflected beams can be reconfigured between 1 and 5. Reflect beam number reconfigurability of such metasurfaces can be readily used as planar reflector of antennas and may find applications in wireless communications.

Since their inception more than thirty years ago, field-programmable gate arrays (FPGAs) have been widely used to implement a myriad of applications from different domains. As a result of their low-level hardware reconfigurability, FPGAs have much faster design cycles and lower development costs compared to custom-designed chips. The design of an FPGA architecture involves many different design choices starting from the high-level architectural parameters down to the transistor-level implementation details, with the goal of making a highly programmable device while minimizing the area and performance cost of reconfigurability. As the needs of applications and the capabilities of process technology are constantly evolving, FPGA architecture must also adapt. In this article, we review the evolution of the different key components of modern commercial FPGA architectures and shed the light on their main design principles and implementation challenges.

Due to the increasing competition in the global market and to fulfill the need for rapid changes of products variability, it is necessary to introduce reconfigurability and smart solutions within the entire process chain including manual assembly. The aim of the paper is to introduce a new manual assembly station equipped with smart technologies and tools. The manual workstation is self-configurable according to the constitution of the individual worker, the product variety and the product structure in order to quickly adapt the workplace to new products, to optimize assembly process, to minimize assembly times and to provide ergonomic working conditions through Digital Human Modeling. The effectiveness of the implemented technologies and tools will be demonstrated through a case study, which includes a comparison of assembly times and number of errors when assembly operations are performed by an unskilled worker at a traditional and smart assembly workstations.

Phase-locked loop (PLL)-based frequency synthesizers are pervasively utilized in almost every electronic system for generating welldefined clock frequencies of interest. For instance, in a modern wireless transceiver, a radio-frequency (RF) synthesizer is typically used as a local oscillator to upconvert/downconvert the desired signal to and from the proper communication bands. A similar utilization of RF PLL can be seen in a wireline transceiver, which modulates and demodulates the data symbol at a precise frequency and phase. In addition to RF applications, PLL is also commonly used in baseband and digital circuitry, such as generating a sampling clock for switched-capacitor circuits and clocking the sequential logic of the digital circuitry. As the complexity of the modern system-onchip (SoC) platform continues to grow, it is likely to require numerous highperformance PLLs. Moreover, interference coupling through the same silicon substrate is exacerbated. As a result, the low implementation (area and power) cost, high reconfigurability, resilience over interferences, and reduced design time of a PLL have become increasingly important in light of this new trend.