Parallel inverter control using different conventional control methods and an improved virtual oscillator control method in a standalone microgrid

This paper develops a multi-timescale coordinated operation method for microgrids based on modern deep reinforcement learning. Considering the complementary characteristics of different storage devices, the proposed approach achieves multi-timescale coordination of battery and supercapacitor by introducing a hierarchical two-stage dispatch model. The first stage makes an initial decision irrespective of the uncertainties using the hourly predicted data to minimize the operational cost. For the second stage, it aims to generate corrective actions for the first-stage decisions to compensate for real-time renewable generation fluctuations. The first stage is formulated as a non-convex deterministic optimization problem, while the second stage is modeled as a Markov decision process solved by an entropy-regularized deep reinforcement learning method, i.e., the Soft Actor-Critic. The Soft Actor-Critic method can efficiently address the exploration–exploitation dilemma and suppress variations. This improves the robustness of decisions. Simulation results demonstrate that different types of energy storage devices can be used at two stages to achieve the multi-timescale coordinated operation. This proves the effectiveness of the proposed method.     

A robust and high precision optimal explicit guidance scheme for solid motor propelled launch vehicles with thrust and drag uncertainty

A new nonlinear optimal and explicit guidance law is presented in this paper for launch vehicles propelled by solid motors. It can ensure very high terminal precision despite not having the exact knowledge of the thrust–time curve apriori. This was motivated from using it for a carrier launch vehicle in a hypersonic mission, which demands an extremely narrow terminal accuracy window for the launch vehicle for successful initiation of operation of the hypersonic vehicle. The proposed explicit guidance scheme, which computes the optimal guidance command online, ensures the required stringent final conditions with high precision at the injection point. A key feature of the proposed guidance law is an innovative extension of the recently developed model predictive static programming guidance with flexible final time. A penalty function approach is also followed to meet the input and output inequality constraints throughout the vehicle trajectory. In this paper, the guidance law has been successfully validated from nonlinear six degree-of-freedom simulation studies by designing an inner-loop autopilot as well, which enhances confidence of its usefulness significantly. In addition to excellent nominal results, the proposed guidance has been found to have good robustness for perturbed cases as well.     

A novel residual energy‐based distributed clustering and routing approach for performance study of wireless sensor network

Non‐uniform energy consumption during operation of a cluster‐based routing protocol for large‐scale wireless sensor networks (WSN) is major area of concern. Unbalanced energy consumption in the wireless network results in early node death and reduces the network lifetime. This is because nodes near the sink are overloaded in terms of data traffic compared with the far away nodes resulting in node deaths. In this work, a novel residual energy–based distributed clustering and routing (REDCR) protocol has been proposed, which allows multi‐hop communication based on cuckoo‐search (CS) algorithm and low‐energy adaptive‐clustering–hierarchy (LEACH) protocol. LEACH protocol allows choice of possible cluster heads by rotation at every round of data transmission by a newly developed objective function based on residual energy of the nodes. The information about the location and energy of the nodes is forwarded to the sink node where CS algorithm is implemented to choose optimal number of cluster heads and their positions in the network. This approach helps in uniform distribution of the cluster heads throughout the network and enhances the network stability. Several case studies have been performed by varying the position of the base stations and by changing the number of nodes in the area of application. The proposed REDCR protocol shows significant improvement by an average of 15% for network throughput, 25% for network scalability, 30% for network stability, 33% for residual energy conservation, and 60% for network lifetime proving this approach to be more acceptable one in near future.     

Shorter Quasi-Adaptive NIZK Proofs for Linear Subspaces

We define a novel notion of quasi-adaptive non-interactive zero-knowledge (NIZK) proofs for probability distributions on parameterized languages. It is quasi-adaptive in the sense that the common reference string (CRS) generator can generate the CRS depending on the language parameters. However, the simulation is required to be uniform, i.e., a single efficient simulator should work for the whole class of parameterized languages. For distributions on languages that are linear subspaces of vector spaces over bilinear groups, we give computationally sound quasi-adaptive NIZKs that are shorter and more efficient than Groth–Sahai NIZKs. For many cryptographic applications quasi-adaptive NIZKs suffice and our constructions can lead to significant efficiency improvements in the standard model. Our construction can be based on any k-linear assumption, and in particular under the eXternal Diffie Hellman (XDH) assumption our proofs are even competitive with Random Oracle-based \(\Sigma \)-protocol NIZK proofs. We also show that our system can be extended to include integer tags in the defining linear equations, where the tags are provided adaptively by the adversary. This leads to applicability of our system to many applications that use tags, e.g., applications using Cramer–Shoup projective hash proofs. Our techniques also lead to the shortest known (ciphertext) fully secure identity-based encryption scheme under standard static assumptions. Further, we also get a short publicly verifiable CCA2-secure IBE scheme.     

Assessment of the nutritional quality of fish cultured in Samdihi,an open cast coalpit at the Raniganj Coal Field areas,West Bengal,India

The present study assessed the nutritional quality of four major teleostean fishes (Catla catla; Labeo rohita; Notopterus notopterus and Oreochromis niloticus) cultured in the Samdihi, an opencast coalpit (OCP). The physicochemical parameters were within the pisciculture standard limits, and the heavy metal contents of the fish were within safe concentrations and below the target hazard quotient (THQ) level (<1). The zooplankton abundance and density were sufficient as food item for the fish faunas. Ash and moisture contents confirmed the good quality of the fish as food. The results of the other analysed nutritional parameters indicated the total protein content was highest in the herbivorous fish Labeo rohita (85.32 ± 0.61 mg/g), compared to Catla catla, Notopterus notopterus and Oreochromis niloticus (50.34 ± 0.43, 71.32 ± 0.49 and 75.14 ± 0.53 mg/g, respectively). The order of decreasing lipid content was Notopterus notopterus > Catla catla > Labeo rohita > Oreochromis niloticus (7.04 ± 1.02 > 6.01 ± 0.01 > 1.83 ± 0.03 > 1.46 ± 0.04%). The percentage of carbohydrates was highest in the omnivorous Oreochromis niloticus (18.2 ± 0.8), followed by Notopterus notopterus, Catla catla and Labeo rohita (15.1 ± 0.7, 13.9 ± 0.5 and 9.4 ± 0.4, respectively). The sodium content was higher in the column feeders Labeo rohita (82.06 ± 0.61 mg/g) and Notopterus notopterus (81.87 ± 0.61 mg/g) than in the surface feeders Catla catla (69.16 ± 0.55 mg/g) and Oreochromis niloticus (79.33 ± 0.60 mg/g). The potassium content exhibited similar trends, being higher in the column feeders Notopterus notopterus (204.8 ± 1.52 mg/g) and Labeo rohita (199.5 ± 1.81 mg/g) than in the surface feeders Oreochromis niloticus (190.8 ± 1.13 mg/g) and Catla catla (183.2 ± 1.3) mg/g). The trend in iron content was in the order of Oreochromis niloticus > Labeo rohita > Notopterus notopterus > Catla catla (5.60 ± 0.01 > 4.806 ± 0.01 > 4.25 ± 0.01 > 1.303 ± 0.01 mg/g, respectively). The results of the present study highlight the potential and feasibility of conducting pisciculture in the abandoned OCP as a means increasing the economic livelihoods of the core group of people in and around the mining areas of RCF regions. The estimated fish nutritional index (EFNI) analysis also revealed the fish cultured in this OCP exhibited a good nutritional quality standard.     

The subspace Gaussian mixture model—A structured model for speech recognition

We describe a new approach to speech recognition, in which all Hidden Markov Model (HMM) states share the same Gaussian Mixture Model (GMM) structure with the same number of Gaussians in each state. The model is defined by vectors associated with each state with a dimension of, say, 50, together with a global mapping from this vector space to the space of parameters of the GMM. This model appears to give better results than a conventional model, and the extra structure offers many new opportunities for modeling innovations while maintaining compatibility with most standard techniques.     

Biofidelic human brain tissue surrogates

ABSTRACT

Traumatic brain injury (TBI) due to blast exposure or head impacts in accidents or contact sports is one of the most critical and poorly understood areas of research in the 21st century. To date, the unavailability of human brain tissues (grey and white matter especially) due to ethical and biosafety issues has not allowed for much experimental research into the study of the mechanics of brain tissues under impact or dynamic loading. In the current work, for the first time, biofidelic brain tissue surrogates have been developed using a low cost, castable (to any shape or size), two-part silicone-based material system to precisely mimic the nonlinear mechanical properties of both the white and the grey matter. The fabrication methodology involves the iterative mixing of the two parts of silicone at certain mix ratios (by weight) to generate a biomechanical behavior similar to the white and the grey matter tissues, respectively, at two different strain rates (low and high). The nonlinear behavior of these novel brain tissue surrogates have been characterized using five hyperelastic material models. These brain tissue simulant materials would be indispensable not only for the study of TBI, but also to allow doctors to practice brain surgeries (for training purposes) in a clinical setting. Additionally, crucial brain tissue modifications in Alzheimer's disease and dementia can be studied in the future with such accessible biofidelic brain tissue surrogate materials.     

Estimation of particle size distribution of nanoparticles from electrical characteristics

An indirect method of estimation of size distribution of nanoparticles in a nanocomposite is proposed in this paper. The present approach exploits DC electrical current–voltage characteristics (CVC) of ZnO nanocomposite specimen in bio-polymer background. The nature of DC CVC is found to be oscillatory with respect to applied voltage. The nature of CVC is a consequence of Coulomb blockade (CB) phenomena of electrical conduction through a tiny nanoparticle. Considering the ZnO nanocomposites to be spherical, Coulomb-blockade model of quantum dot is applied here. The size distribution of particle is estimated from that model and compared with the results obtained from AFM and XRD analyses. The results from CVC are found to be consistent with these conventional microscopic results.