Configuration Mode Research Articles

All optical frequency encoded quaternary memory unit using symmetric configuration of MZI-SOA

Optical memory is an essential optical element for optical communication and computing system. Here the authors propose an optical scheme for developing a quaternary memory unit associated with wavelength encoding technique and based on Mach Zhender Interferometer based semiconductor optical amplifier (MZI-SOA) optical switches in symmetric configuration mode. Here the symmetry is introduced by injecting same biasing current to two SOAs of a MZI-SOA optical switch.

Reliability and power supply capability evaluation of active distribution networks with four‐terminal soft open points

Soft open points (SOPs) have the ability to regulate the power flow among their terminals in a continuous manner, which can solve the problems brought by the synergy of distribution networks and distributed generation, and improve the system reliability and power supply capability. To address the current lack of quantitative measurement on the effects of SOPs, the power supply capability evaluation method for active distribution networks (ADNs) with four-terminal SOPs considering reliability is proposed. Firstly, the topology and configuration modes of four-terminal SOPs are studied, and their control modes are investigated in normal operation and supply restoration conditions. Then, using the feeder partition method, the effects of four-terminal SOPs on the power outage duration of different load areas after a fault are studied, and the reliability evaluation process for ADNs with four-terminal SOPs is developed based on the quasi-Monte Carlo method. Later, with reliability as the main constraint, the power supply capability evaluation model for ADNs with four-terminal SOPs is established, and the solution algorithm is proposed. Finally, the effectiveness and applicability of the method proposed are verified through a case study.

Low motional impedance distributed Lam\xe9 mode resonators for high frequency timing applications

This paper presents a novel high-Q silicon distributed Lamé mode resonator (DLR) for VHF timing reference applications. The DLR employs the nature of shear wave propagation to enable a cascade of small square Lamé modes in beam or frame configurations with increased transduction area. Combined with high efficiency nano-gap capacitive transduction, it enables low motional impedances while scaling the frequency to VHF range. The DLR designs are robust against common process variations and demonstrate high manufacturability across different silicon substrates and process specifications. Fabricated DLRs in beam and frame configurations demonstrate high performance scalability with high Q-factors ranging from 50 to 250 k, motional impedances <1 kΩ, and high-temperature frequency turnover points >90 °C in the VHF range, and are fabricated using a wafer-level-packaged HARPSS process. Packaged devices show excellent robustness against temperature cycling, device thinning, and aging effects, which makes them a great candidate for stable high frequency references in size-sensitive and power-sensitive 5 G and other IoT applications.

Low-cost IoT framework for irrigation monitoring and control

PurposeThe purpose of this work is to make an IoT-based low-cost and power-efficient portable system to control irrigation using a threshold value algorithm and to measure soil-irrigation-related parameters such as soil moisture, soil temperature, humidity and air temperature.Design/methodology/approachThis paper presents a threshold value algorithm to optimize power consumption and to control irrigation process.FindingsThe system uses ESP-12F 8266 as the main microcontroller unit to monitor and control irrigation system. The system also consists of an actuator system that triggers automatically based on a threshold value algorithm. An open-source cloud platform is used to monitor and store all the data for future perspective. To make the system run for a long time without any human intervention, a solar panel is used as an alternate source of energy for charging the 12V lithium-ion battery. The battery takes 2.64 h for full charging considering peak intensity of sunlight. A capacitive moisture sensor is included using less expensive 555 timer and calibrated to measure water content in the soil. The 555 timer is used in astable mode of configuration to generate a signal of 572 KHz. The calibrated sensor data when compared with a standard SEN0193 moisture sensor shows an error of 3.4%. The prototype model is made to optimize the power consumption. This can be achieved by utilizing sleep mode of ESP-12F 8266. The total cost involved to make the system is 3900.55 Indian rupees and around US$54.90.Practical implicationsThe device is tested in a flower garden during winter season of Nagaland, India, for 75 days to collect all the data and to automate the irrigation process.Originality/valueThe proposed threshold value algorithm optimizes the power consumption of the device, and wastage of water is reduced up to 60% as compared to the traditional method of irrigation.

A flexible encryption technique for the internet of things environment

IoT promises a new era of connectivity that goes beyond laptops and smart connected devices to connected vehicles, smart homes, smart cities and connected healthcare. The huge volume of data that is collected from millions of IoT devices raises information security and privacy concerns for users. This paper presents a new scalable encryption technique, called Flexible encryption Technique (FlexenTech), to protect IoT data during storage and in transit. FlexenTech is suitable for resource constrained devices and networks. It offers a low encryption time, defends against common attacks such as replay attacks and defines a configurable mode, where any number of rounds or key sizes may be used. Experimental analysis of FlexenTech shows its robustness in terms of its multiple configurable confidentiality levels by allowing various configurations. This configurability provides several advantages for resource constrained devices, including reducing the encryption computation time by up to 9.7% when compared to its best rivals in the literature.

Vibrational Couplings in Hydridocarbonyl Complexes: A 2D-IR Perspective.

Hydridocarbonyl complexes, a class of industrially relevant catalysts, contain both the M-H and M-CO moieties. Here, using two-dimensional infrared spectroscopy, we examine the coupling of the typically weak M-H stretching mode and the intense M(C≡O) mode. By studying a series of Ir(I)- and Ir(III)-based hydridocarbonyl complexes, we show that the arrangement of the H and CO ligands in a trans configuration leads to strong vibrational coupling and mode delocalization. In contrast, a cis arrangement leads to no coupling, with the localized M-H mode having a much larger anharmonicity. These results highlight a promising strategy for enhancing the M-H vibration by intensity borrowing from the strong C≡O modes in a trans configuration, allowing for direct determination by infrared spectroscopy of both the oxidation (by frequency shifts) and the protonation state (via vibrational coupling) of the complex, in mechanistic studies of proton-coupled electron transfer reactions.

Egg volume estimation based on image processing and computer vision

In chicken egg production line systems, grading based on vision systems is challenging due to ambient light conditions and egg occlusion problems. This study introduces a depth image-based chicken-egg volume estimation system. Two modes of egg configurations on a sorting line were evaluated; single-egg (no occlusion) and multi-eggs (partially occluded, i.e., simple and complex). Contour curvature analysis and k-closest M-circle-center algorithms were used to segment the occluded eggs. Thirteen regression models based on the egg image (single egg) features were trained. The Exponential Gaussian Process Regression outperformed all the explored models with RMSE of 1.175 cm3 and R2 of 0.984. The same model estimated the volume of the eggs under partial occlusion at RMSE of 1.080 and 1.294 cm3 for simple and complex, respectively. This introduced system can be applied as an accurate, consistent, fast, and non-destructive in-line sorting technique of chicken eggs in a production line system.

EO-MTRNN: evolutionary optimization of hyperparameters for a neuro-inspired computational model of spatiotemporal learning

For spatiotemporal learning with neural networks, hyperparameters are often set manually by a human expert. This is especially the case with multiple timescale networks that require a careful setting of the values of timescales in order to learn spatiotemporal data. However, this implies a cumbersome trial-and-error process until suitable parameters are found and it reduces the long-term autonomy of artificial agents, such as robots that are controlled by multiple timescale networks. To solve the problem, we propose the evolutionary optimized multiple timescale recurrent neural network (EO-MTRNN) that is inspired by the neural plasticity of the human cortex. Our proposed network uses a method of evolutionary optimization to adjust its timescales and to rewire itself in terms of number of neurons and synapses. Moreover, it does not require additional neural networks for pre- and postprocessing input–output data. We validate our EO-MTRNN by applying it to a proposed benchmark training dataset with single and multiple sequence training cases, as well as by applying it to sensory-motor data from a robot. We compare different configuration modes of the network, and we compare the learning performance between a network configuration with manually set hyperparameters and a configuration with automatically estimated hyperparameters. The results show that automatically estimated hyperparameters yield approximately 43% better performance than manually estimated ones, without overfitting the given teaching data. We also validate the generalization ability by successfully learning data that were not included in the hyperparameter estimation process.

A practical approach for multiagent manufacturing system based on agent computing nodes

With the increasing requirement for personalized customization service, discrete manufacturing workshop, as the parts processing unit in manufacturing system, is expected for more agile and fast adaptation to environment changes, dynamically handling production tasks according to resource conditions. Simultaneously, distributed artificial intelligence system (e.g. multiagent manufacturing system and the holonic manufacturing system) has been considered as an important approach for developing industrial applications to solve the problems of complexity, uncertainty, and dynamic in the modern manufacturing environment. But the lack of universality and the difficulty in deployment have restricted the use of distributed artificial intelligence in actual industrial sites. For this issue, a new concept of agent computing node is proposed in this paper to enable the realization of multiagent manufacturing system. Adaptation layer, information development layer, and intelligent analysis layer are investigated for standardizing the configuration mode of agent computing node. Cooperating agent computing node with the radio frequency identification-based dynamic recognition technology for workpiece machining process is presented in this paper, and a practical approach for multiagent manufacturing system is considered, which can apply the functions regarding to deployment of dynamic scheduling and plug-and-play. A laboratory discrete manufacturing workshop system is used as a case study to prove the feasibility of this approach. In addition, a verification in industry is carried out, and the result proves the universality of this approach.

Development and validation of a photobioreactor for uniform distribution of light intensity along the optical path based on numerical simulation

A theoretical approach was followed to optimize the design of a cylindrical photobioreactor for wastewater treatment based on algal culture. In particular, the problem of uneven light distribution that impairs algal growth was minimized by optimizing the area of uniform illumination distribution for a bioreactor design that can be enlarged without affecting its performance. The theoretical analysis was based on modeled simulations to determine the best configuration and illumination mode. The Monte Carlo method was used to simulate the illumination distribution inside the bioreactor, and the relationships between the width of the area with uniform illumination and related parameters were explored. Based on these theoretical considerations and predictions, an actual experimental photobioreactor was built containing a working area (where culture of Chlorella pyrenoidosa was enabled) and a catchment area for effluent. The performance of this bioreactor was tested with synthetic wastewater as a substrate. The light distribution was found to be relatively uniform inside the bioreactor, supporting excellent algal growth and resulting in maximum removal rates of 84.41% for total nitrogen, 99.73% for total phosphorus, 85.03% for NH4+-N, and 75.94% for chemical oxygen demand (COD) over a period of 32days of operation. The presented approach provides new insights for improving the efficiency and scalability of photobioreactors and promotes their development for wastewater treatment and resource utilization.

Evaluation of power regeneration in primary suspension for a railway vehicle

To improve the fuel economy of rail vehicles, this study presents the feasibility of using power regenerating dampers (PRDs) in the primary suspension systems of railway vehicles and evaluates the potential and recoverable power that can be obtained. PRDs are configured as hydraulic electromagnetic-based railway primary vertical dampers and evaluated in parallel and series modes (with and without a viscous damper). Hydraulic configuration converts the linear behavior of the track into a unidirectional rotation of the generator, and the electromagnetic configuration provides a controllable damping force to the primary suspension system. In several case studies, generic railway vehicle primary suspension systems that are configured to include a PRD in the two configuration modes are modeled using computer simulations. The simulations are performed on measured tracks with typical irregularities for a generic UK passenger route. The performance of the modified vehicle is evaluated with respect to key performance indicators, including regenerated power, ride comfort, and running safety. Results indicate that PRDs can simultaneously replace conventional primary vertical dampers, regenerate power, and exhibit desirable dynamic performance. A peak power efficiency of 79.87% is theoretically obtained in series mode on a top-quality German Intercity Express track (Track 270) at a vehicle speed of 160 mile/h (∼257 km/h).

Locomotion of a multi-link non-holonomic snake robot with passive joints

Conventional approaches in prescribing controls for locomoting robots assume control over all input degrees of freedom (DOFs). Many robots, such as those with non-holonomic constraints, may not require or even allow for direct command over all DOFs. In particular, a snake robot with more than three links with non-holonomic constraints cannot achieve arbitrary configurations in all of its joints while simultaneously locomoting. For such a system, we assume partial command over a subset of the joints, and allow the rest to evolve according to kinematic chained and dynamic models. Different combinations of actuated and passive joints, as well as joints with dynamic elements such as torsional springs, can drastically change the coupling interactions and stable oscillations of joints. We use tools from nonlinear analysis to understand emergent oscillation modes of various robot configurations and connect them to overall locomotion using geometric mechanics and feedback control for robots that may not fully utilize all available inputs. We also experimentally verify observations and motion planning results on a physical non-holonomic snake robot.

Nanoscale photovoltage mapping in CZTSe/CuxSe heterostructure by using kelvin probe force microscopy

In the present work, kelvin probe force microscopy (KPFM) technique has been used to study the CZTSe/CuxSe bilayer interface prepared by multi-step deposition and selenization process of metal precursors. Transmission electron microscopy (TEM) confirmed the bilayer configuration of the CZTSe/CuxSe sample. Two configuration modes (surface mode and junction mode) in KPFM have been employed in order to measure the junction voltage under illumination conditions. The results show that CZTSe/CuxSe has small junction voltage of ∼21 mV and the presence of CuxSe secondary phase in the CZTSe grain boundaries changes the workfunction of the local grain boundaries region. The negligible photovoltage difference between grain and grain boundaries in photovoltage image indicates that CuxSe phase deteriorates the higher photovoltage at grain boundaries normally observed in CZTSe based device. These results can be important for understanding the role of secondary phases in CZTSe based junction devices.

Numerical analysis of planar multimode optical sensor with active nanolayer

In the paper, numerical studies of the model of an optical sensor, based on interference of modes in a planar one-dimensional step-index configuration, are presented. Calculations are performed using the method of mode field analysis. The structure consists of the single-mode input waveguide, the multimode waveguide that guides only a few modes and the single-mode output waveguide. The structure is covered by a nanometer active sensor layer of a high refractive index, which changes its optical properties in contact with the measured external surrounding. The refractive index variation of an active sensor layer affects the modal properties of the multimode waveguide and the output optical field distribution. By the proper selection of the active layer, the considered configuration can be used for gas detection.

Virtual Agglomeration of Producer Services and the Changing Geography of Innovation Systems: Implications for Developing Countries

The rapid development of new generation of information and communication technology (ICT) has changed the traditional mode of service spatial configuration. A virtual agglomeration mode of producer service via internet platform is forming and reshaping the spatial organization structure of service industry. Producer services usually show the characteristics of high added value, high knowledge talents and high technology content, which can meet the diversified needs of complex innovation process in the manufacturing industries. Therefore, this paper explores the impact of virtual agglomeration of producer services on the manufacturing enterprises’ innovation performance and the changing geography of innovation systems. Compared with the traditional entity agglomeration model, the virtual agglomeration of producer services breaks through the time and space limitations of traditional service provision. It can realize the scale economy effect and knowledge spillover effect in a larger scope, reduce the service input cost, improve the quality of service allocation, and reshape the regional innovation ecosystem. Furthermore, this article conducts a data statistics and a case analysis, and finally puts forward implications for the integration of virtual agglomeration of producer services and manufacturing innovation process especially for enterprises in the developing countries.

Unstable spectra of the tearing modes in a triple current sheet configuration with sub-Alfvénic shear flows

Effects of sub-Alfvénic shear flows on the complicated properties of three types of unstable eigenmodes, namely, coupled triple tearing mode (M1), coupled double tearing mode (M2), and three single tearing modes (M3), in a triple current sheet configuration are studied by means of an eigenvalue analysis. It is identified that the difference of velocity among three resonant surfaces rather than the local flow shear rate plays the more important role in the three types of eigenmodes. Thus, it is found that for the symmetric shear flow (SSF), the growth rate of the M1/M3 mode decreases/increases with the increasing strength of the shear flow, while the growth rate of the M2 mode is almost uninfluenced by SSF. For the antisymmetric shear flow (ASF), it is interestingly observed that in the small wavenumber regime, the M1 and M2 modes degenerate into similar eigenmode states with the same growth rate and opposite traveling frequencies. In the large wavenumber regime, the M2 and M3 modes degenerate into similar eigenmode states. Moreover, for both SSF and ASF, the growth rates of the three types of modes are almost the same in the small and large wavenumber limits.

Forecasting potato tuber yield using a soil electromagnetic induction method

AbstractTimely forecasting of crop yield is vital for precision agriculture management practices. This study used on‐the‐go proximal soil sensing using electromagnetic induction (EMI) readings of apparent ground electrical conductivity (ECa) to map ECa and forecast potato tuber yield in four fields across Atlantic Canada. The ECa data, measured in the horizontal co‐planar (HCP) configuration mode of the DualEM‐2 instrument, were segmented to the top 0.30‐m thickness of the soil layer using a standard method to compare mapping/prediction accuracy. Results showed that ECa correlated well (R2 = 0.81–0.90) with a 1:5 soil‐to‐water ratio solution's electrical conductivity (EC1:5). The actual tuber yield, which moderately varied (CV = 18.9–27.5%) across the fields and significantly correlated with ECa, explained more than 55% of the yield variability (R2 = 0.57–0.66). The forecasted tuber yield calculated from cubic regression models of the actual tuber yield versus ECa was non‐significantly different from the actual tuber yield (RMSE = 12.2–18.3%; R2 = 0.57–0.66). Interpolated maps of the predicted and the actual yields, and their correlation analyses, showed similar trends of variations within the study fields (r = 0.69–0.80). The higher values of cation exchange capacity, calcium, phosphate, potash, organic matter and soil moisture content in the New Brunswick soils compared to the Prince Edward Island soils resulted in an overestimation of the predicted tuber yield than the actual yield at the lower ECa values, and an underestimation of the predicted tuber yield at higher ECa values for New Brunswick. The results revealed that the province‐based calibrations produced more accurate predictions when compared with the single calibration by combining all of the data from New Brunswick and Prince Edward Island. The non‐destructive prediction of potato tuber yield can enable the development of precision agricultural techniques and management practices for yield forecasting, in addition to making informed decisions for enhanced potato productivity.Highlights Potato cropping is highly important to the economy of Atlantic Canada. The DualEM‐2 sensor was used to forecast and map tuber yield to advance crop management. The tuber yields significantly correlated with ground conductivity that explained &gt;55% of variability in yield. The DualEM‐2 sensor can accurately predict potato yield under agricultural conditions similar to Atlantic Canada.

Cost-benefit analysis of integrated energy system planning considering demand response

The power-gas-coupling can realize the cascade utilization of energy in the integrated energy system, which is conducive to improving the utilization of energy and reducing pollution gases emissions. With the installation of smart metering, two-way communication between suppliers and consumers is feasible, which enables the implementation of demand response. A generic optimal planning model is proposed to assess the economic and environmental benefits of the capacity allocation of the grid-connected integrated energy system considering both price-based demand response and incentive-based demand response respectively. The optimal planning problem is formulated as a mixed-integer linear programming model with the objective to minimize the total annual cost. The results from three configuration modes are compared in the case study, which illustrate the economic and environmental benefits from demand response. In addition, the impact of the sales capacity constraint on the grid and the fluctuation of electricity and gas prices on the planning of the integrated energy system are also extensively studied considering demand response.

Double Dirac cones in two-dimensional photonic crystals with C6 symmetry

ABSTRACTWe analyse the double Dirac cones in two-dimensional photonic crystals with symmetry, which lack the reflection symmetry about six-fold axes of the triangular lattice. The double Dirac cones are constructed by accidental degeneracy of the and modes at the Brillouin zone center, which corresponds to the transition point between a trivial and a nontrivial topological phase. Based on the tight-binding approximation, the dispersion relation near the Brillouin zone center is analytically solved to give a pair of identical and isotropic cones, that is, the double Dirac cone. In particular, the double Dirac cones occur for both TM and TE modes in a complementary configuration of the photonic crystal consisting of triangular rods or holes as hexagonal clusters. The topological feature of the photonic crystal is manifest on the robust transport of helical edge states at the interface between two topologically distinct phases.

Modelling for the in-plane plateau stress of honeycomb paperboard based on the induce effect of face paper with honeycomb core

The in-plane uniaxial crushing behavior of honeycomb paperboard is studied, and three types of deformation modes, namely no debonding mode, partial debonding mode, complete debonding mode, are identified under uniaxial loading along the y-axis direction. The interaction between face paper and honeycomb core is modeled, and the mutual induce effect between the deformation mode of the core configuration and the face paper was combined with the theory of energy conservation to derive the corresponding plateau stress of the honeycomb paperboard structure. A good consistency is obtained through the comparison of the experimental results and theoretical values. The suggested three models may help to reveal the deformation and energy absorption mechanism of paper honeycomb structures.