Real-Time Control System Adopted to Energy Storage for Smart Grid Low Wind Applications: A Part of Distributed Renewables in Smart City

In this paper, extensive efforts have been undertaken to design and develop a control system, which is incorporated with an energy storage device that can store energy from low-voltage renewable sources. The developed device acts as a storage element, which can be used to charge small-scale batteries, cellular devices, and other applications in remote places where the grid connection is not available. The circuit is developed using a case-by-case analysis. In order to solve the low output voltage problem, a bipolar junction transistor-metal oxide semiconductor field-effect transistor (BJT-MOSFET) based switch control technology with the Arduino microcontroller has been implemented. The developed control system is extremely efficient in charging batteries through a supercapacitor for low-voltage sources. In this research, a small-scale 200-W portable vertical axis wind turbine is used at a wind speed of 3 m/s. The result shows the efficiency of the proposed system as compared with the conventional systems. The proposed system can be an important tool of the latest distributed energy generation technology which is an important part of a smart city. Lastly, the limitations and future scopes of the development of the control device are discussed for the future barrier. An important future scope identified is to integrate the Internet of Things based mobile interface for remote monitoring for any kind of pandemic situation like COVID-19. Now, it is high time to get our smart city concept aligned with the post COVID pandemic situation and get us prepared smartly for similar future occurrences.     

Explainable deep neural networks for novel viral genome prediction

Viral infection causes a wide variety of human diseases including cancer and COVID-19. Viruses invade host cells and associate with host molecules, potentially disrupting the normal function of hosts that leads to fatal diseases. Novel viral genome prediction is crucial for understanding the complex viral diseases like AIDS and Ebola. While most existing computational techniques classify viral genomes, the efficiency of the classification depends solely on the structural features extracted. The state-of-the-art DNN models achieved excellent performance by automatic extraction of classification features, but the degree of model explainability is relatively poor. During model training for viral prediction, proposed CNN, CNN-LSTM based methods (EdeepVPP, EdeepVPP-hybrid) automatically extracts features. EdeepVPP also performs model interpretability in order to extract the most important patterns that cause viral genomes through learned filters. It is an interpretable CNN model that extracts vital biologically relevant patterns (features) from feature maps of viral sequences. The EdeepVPP-hybrid predictor outperforms all the existing methods by achieving 0.992 mean AUC-ROC and 0.990 AUC-PR on 19 human metagenomic contig experiment datasets using 10-fold cross-validation. We evaluate the ability of CNN filters to detect patterns across high average activation values. To further asses the robustness of EdeepVPP model, we perform leave-one-experiment-out cross-validation. It can work as a recommendation system to further analyze the raw sequences labeled as ‘unknown’ by alignment-based methods. We show that our interpretable model can extract patterns that are considered to be the most important features for predicting virus sequences through learned filters.

     

Coking of athabasca bitumen: effect of oxidation and sand

The effect of low temperature oxidation on the ultimate coke residue from Athabasca bitumen was examined quantitatively for extents of oxidation up to 100 mg O₂/g bitumen. The residue yield was found to increase linearly with extent of oxidation. When sand was introduced during the oxidation or pyrolysis processes, a smaller increase in coke yield was observed.     

Scratch deformation characteristics of micrometric wollastonite‐reinforced ethylene‐propylene copolymer composites

The scratch deformation behavior of neat and wollastonite‐containing ethylene‐propylene copolymer composites has been studied by electron microscopy and atomic force microscopy techniques. The study indicates that the severity of plastic deformation during scratch testing in reinforced ethylene‐propylene copolymers is a function of debonding/detachment of wollastonite mineral particles from the ethylene‐propylene matrix. The resistance to scratch deformation was evaluated in terms of scratch hardness, scratch depth, average scratch roughness, and change in gray level before and subsequent to scratching. The data suggests that resistance to scratch deformation follows the sequence: coated + coupled wollastonite‐containing EP copolymer > fine wollastonite‐containing EP copolymer > coated wollastonite‐containing EP copolymer > coarse wollastonite‐containing EP copolymer > neat EP copolymer. EP copolymer containing coated wollastonite and coupling agent is characterized by highest scratch hardness and minimum scratch depth and scratch roughness. The visibility of scratch, quantified in terms of gray level, suggests that coated + coupled wollastonite‐containing copolymer exhibits significantly reduced susceptibility to stress whitening, and is characterized by a lower gray level in the scratch‐deformed regions. In the present case of wollastonite‐containing copolymer composites, the resistance to scratch deformation follows a trend similar to that of gray level or scratch visibility. Polym. Eng. Sci. 44:1738–1748, 2004. © 2004 Society of Plastics Engineers.     

Micro‐ and Nanoscale Evaluation of Scratch Damage in Poly(propylene)s

The technique of atomic force microscopy (AFM) has been used to obtain comparative evaluation of scratch damage in polymeric materials (low‐ and high‐crystallinity poly(propylene)s and ethylene‐propylene diblock copolymers) and examine the surface deformation processes. A comparative assessment of scratch damage is made in terms of average surface height of the plastically deformed region, and the depth, thickness, and density of the scratch tracks. The resistance to scratch deformation under identical conditions of scratch test follows the sequence: high‐crystallinity poly(propylene)s > low‐crystallinity poly(propylene)s > ethylene‐propylene diblock copolymers. Additionally, short‐chain polymers are characterized by a greater resistance to mechanical deformation than their respective long‐chain polymers. The scratch tracks in low‐ and high‐crystallinity poly(propylene)s are zig‐zag in shape, while in ethylene‐propylene diblock copolymers they are parabolic with localized plastic flow involving voids. The AFM observations suggest that higher tensile modulus and higher yield stress are key factors responsible for superior resistance to mechanically induced deformation in high‐crystallinity poly(propylene)s.

Low magnification SEM micrographs of the scratch deformed regions of long‐chain EP‐L (e) and short‐chain EP‐S (f).     

Analysis of Surface Textured Air Bearing Sliders with Rarefaction Effects

A numerical model is developed to study the effect of texture on air bearing sliders for large Knudsen numbers. The effect of texture location, texture size, and density on the pressure generation is studied. First, a textured plane slider parallel to the disk surface is investigated, and the texture parameters are determined that result in optimum pressure generation. Then, a plane inclined slider is studied using optimum texture parameters found in the parallel slider case. Thereafter, the effect of texture on the steady state flying characteristics of an actual magnetic recording slider is investigated. Finally, the flying height modulation, pitch, and roll motion of a textured slider (pico and femto form factors) are determined numerically by exciting the slider using a step on the disk. Comparison of the results for textured and untextured sliders is made. It is found that textured sliders show better dynamic performance compared to the untextured sliders in terms of stiffness and damping.     

Determination on the Effect of Ti Addition on the Microstructural,Mechanical and Wear Behavior of Cu–6Sn Alloy in as—Cast Condition

The objective of this research is to fabricate a ternary alloy (Cu–Sn–Ti), incorporating titanium into bronze with varying weight percentage of titanium (0.5 wt%, 1 wt%) to investigate its impact on microstructural and mechanical properties and wear behavior and to collate these results with those of conventional bronze (Cu–6Sn). The microstructure of the alloys was observed using a metallurgical microscope, and results exhibit a finer grain refinement in the dendritic structure, which causes an improvement in mechanical properties. The mechanical properties were tested (tensile strength, hardness), and they showed an increment in values corresponding to the increase in the weight percentage of titanium. However, owing to the formation of an inclusion (blowhole), there was a reduction in the tensile strength for Cu–6Sn.0.5Ti. The wear analysis was also carried out using a pin-on-disk tribometer with selected parameters of load (10–30 N), sliding distance (1000 m) and sliding velocity (1–3 m/s), and it was noted that there was an increase in the wear rate with an increase in load and distance for all combinations of parameters. There was also an improvement in the wear resistance with an increase in the weight percentage of Ti, in comparison with the conventional base alloy.     

Nonsupercritically Dried Silica–Alumina Aerogels—Effect of Gelation pH

Silica–alumina mixed oxide aerogels, with 5, 10, 15, 20, and 25 wt% of alumina in silica, have been synthesized by a hybrid sol–gel technique followed by subcritical drying. The gelation has been carried out under pH values of 3 and 5. pH is a decisive parameter that affects the rate of hydrolysis and condensation of alkoxides. Moreover, it also influences the surface area and porosity features of the final material. The gelation time has been found to be much longer for gels that were gelled at pH 3. Nitrogen sorption studies of the aerogels calcined at 500°C indicate that the mixed oxide aerogels are mesoporous in nature and the gels prepared under a gelation pH of 3 have been found to have higher surface area than the pH 5 counterpart. Transmission electron microscopy and X-ray diffraction analysis have been performed to verify the homogeneity of the mixed oxide aerogel.     

Simple,space-efficient,and fairness improved FCFS mutual exclusion algorithms

Let n$n$ be the number of threads that can compete for a shared resource R$R$. The mutual exclusion problem involves coordinating these n$n$ concurrent threads in accessing R$R$ in a mutually exclusive way. This paper addresses two basic questions related to the First-Come-First-Served (FCFS) mutual exclusion algorithms that use only read–write operations: one is regarding the lower bound on the shared space requirement and the other is about fairness.     

Cost-Sharing Mechanisms for Network Design

We consider a single-source network design problem from a game-theoretic perspective. Gupta, Kumar and Roughgarden (Proc. 35th Annual ACM STOC, pp. 365–372, 2003) developed a simple method for a single-source rent-or-buy problem that also yields the best-known approximation ratio for the problem. We show how to use a variant of this method to develop an approximately budget-balanced and group strategyproof cost-sharing method for the problem. The novelty of our approach stems from our obtaining the cost-sharing methods for the rent-or-buy problem by carefully combining cost-shares for the simpler Steiner tree problem. Our algorithm is conceptually simpler than the previous such cost-sharing method due to Pál and Tardos (Proc. 44th Annual FOCS, pp. 584–593, 2003), and improves the previously-known approximation factor of 15 to 4.6. A preliminary version of this work appears in the Proc. International Workshop on Approximation Algorithms for Combinatorial Optimization Problems, 2004. This research was done in part during the IMA Workshop on Network Management and Design at the University of Minnesota, April 2003. A. Gupta supported in part by an NSF CAREER award CCF-0448095, and by an Alfred P. Sloan Fellowship. A. Srinivasan supported in part by the National Science Foundation under Grant No. 0208005 and ITR Award CNS-0426683. Research of é. Tardos supported in part by ONR grant N00014-98-1-0589, and NSF grants CCR-0311333 and CCR-0325453.