Oxidation of some aliphatic polyols on anodically deposited MnO2

Galvanostatic steady state current potential measurements were carried out for oxidation of a series of aliphatic alcohols having varying number of hydroxyl groups. The anodically deposited layer of MnO₂ on platinum was used as the electrode material. The deposit was characterised by scanning electron microscopy (SEM), energy dispersive X-ray analysis (EDAX) and electrode potential measurements. The catalytic role of MnO₂ in the electro-oxidation of alcohols was indicated by the chronopotentiograms and the cyclic voltammograms. An analysis of the electrochemical data indicated a catalytic EC mechanism in which Mn (V) is generated electrochemically and consumed chemically in succession. Based on this and the hydrogen bonding interaction between alcoholic hydroxyl groups and MnO₂ layer, a mechanism was proposed which accounts for the variation in the observed electrochemical reaction orders. Tafel behaviour was found to be followed only approximately. Current efficiency of the electrochemical oxidation of polyols was studied. Replacement of platinum by carbon as current collector was found to leave the electrocatalytic activity of the MnO₂ deposit practically unaltered.     

Realization of a temperature sensor using both two- and three-dimensional photonic structures through a machine learning technique

A temperature sensor based on photonic crystal structures with two- and three-dimensional geometries is proposed, and its measurement performance is estimated using a machine learning technique. The temperature characteristics of the photonic crystal structures are studied by mathematical modeling. The physics of the structure is investigated based on the effective electrical permittivity of the substrate (silicon) and column (air) materials for a signal at 1200 nm, whereas the mathematical principle of its operation is studied using the plane-wave expansion method. Moreover, the intrinsic characteristics are investigated based on the absorption and reflection losses as frequently considered for such photonic structures. The output signal (transmitted energy) passing through the structures determines the magnitude of the corresponding temperature variation. Furthermore, the numerical interpretation indicates that the output signal varies nonlinearly with temperature for both the two- and three-dimensional photonic structures. The relation between the transmitted energy and the temperature is found through polynomial-regression-based machine learning techniques. Moreover, rigorous mathematical computations indicate that a second-order polynomial regression could be an appropriate candidate to establish this relation. Polynomial regression is implemented using the Numpy and Scikit-learn library on the Google Colab platform.

     

A numerical study of particle wall-deposition in a turbulent square duct flow

The deposition of dense solid particles in a downward, fully developed turbulent square duct flow at Re_τ = 360, based on the mean friction velocity and the duct width, is studied using large eddy simulations of the fluid flow. The fluid and the particulate phases are treated using Eulerian and Lagrangian approaches, respectively. A finite-volume based, second-order accurate fractional step scheme is used to integrate the incompressible form of the unsteady, three-dimensional, filtered Navier-Stokes equations on an 80 × 80 × 128 grid. A dynamic subgrid kinetic energy model is used to account for the unresolved scales. The Lagrangian particle equation of motion includes the drag, lift, and gravity forces and is integrated using the fourth-order accurate Runge-Kutta scheme. Two values of particle to fluid density ratio (ρ_p/ρ_f = 1000 and 8900) and five values of dimensionless particle diameter (d_p/δ × 10⁶ = 100, 250, 500, 1000 and 2000, δ is the duct width) are studied. Two particle number densities, consisting of 10⁵ and 1.5 × 10⁶ particles initially in the domain, are examined.Variations in the probability distribution function (PDF) of the particle deposition location with dimensionless particle response time, i.e. Stokes number, are presented. The deposition is seen to occur with greater probability near the center of the duct walls, than at the corners. The average streamwise and wall-normal deposition velocities of the particles increase with Stokes number, with their maxima occurring near the center of the duct wall. The computed deposition rates are compared to previously reported results for a circular pipe flow. It is observed that the deposition rates in a square duct are greater than those in a pipe flow, especially for the low Stokes number particles. Also, wall-deposition of the low Stokes number particles increases significantly by including the subgrid velocity fluctuations in computing the fluid forces on the particles. Two-way coupling and, to a greater extent, four-way coupling are seen to increase the deposition rates.     

Structural variability and its relation to edaphic attributes of mangroves in the south‐west coast of India

We estimated the tree structural variables (density, frequency and basal area) of true mangroves and soil variables like particle size distribution, carbon, available nitrogen and phosphorus, sulphur, nutrient cations (K, Na, Ca, Mg) of Cochin mangroves and examined the relationship between vegetation and environment. The study sites were classified as seaward fringe, riverine and interior. Of the thirteen true mangrove species present, Avicennia officinalis, Sonneratia caseolaris and Excoecaria agallocha showed higher Importance Value Index. The mean stem density varied from 80 to 25,000 no./ha and basal area from 0.1 to 39.68 m²/ha. Seaward mangroves showed maximum stand basal area and biomass production while riverine exhibited maximum density. Maturity Index value of Cochin mangroves revealed a very low degree of structural maturity. Interior mangroves were characterized by silty soil with higher nutrient concentrations. Principal component analysis of soil data revealed that the major factors influencing mangrove vegetation were soil texture, nutrients, salinity and oxidation–reduction potential. The stem density and basal area of different species correlated highly with soil nutrients and texture (p < .001) while salinity showed negative correlations with vegetation characteristics. The data generated in the study would be fundamental in site‐specific management and conservation efforts of these degrading mangroves.     

Secure video communication using firefly optimization and visual cryptography

In recent years, we face an increasing interest in protecting multimedia data and copyrights due to the high exchange of information. Attackers are trying to get confidential information from various sources, which brings the importance of securing the data. Many researchers implemented techniques to hide secret information to maintain the integrity and privacy of data. In order to protect confidential data, histogram-based reversible data hiding with other cryptographic algorithms are widely used. Therefore, in the proposed work, a robust method for securing digital video is suggested. We implemented histogram bit shifting based reversible data hiding by embedding the encrypted watermark in featured video frames. Histogram bit shifting is used for hiding highly secured watermarks so that security for the watermark symbol is also being achieved. The novelty of the work is that only based on the quality threshold a few unique frames are selected, which holds the encrypted watermark symbol. The optimal value for this threshold is obtained using the Firefly Algorithm. The proposed method is capable of hiding high-capacity data in the video signal. The experimental result shows the higher capacity and video quality compared to other reversible data hiding techniques. The recovered watermark provides better identity identification against various attacks. A high value of PSNR and a low value of BER and MSE is reported from the results.

     

Improving Throughput of Transmission Control Protocol Using Cross Layer Approach

Most of the internet users connect through wireless networks. Major part of internet traffic is carried by Transmission Control Protocol (TCP). It has some design constraints while operated across wireless networks. TCP is the traditional predominant protocol designed for wired networks. To control congestion in the network, TCP used acknowledgment to delivery of packets by the end host. In wired network, packet loss signals congestion in the network. But rather in wireless networks, loss is mainly because of the wireless characteristics such as fading, signal strength etc. When a packet travels across wired and wireless networks, TCP congestion control theory faces problem during handshake between them. This paper focuses on finding this misinterpretation of the losses using cross layer approach. This paper focuses on increasing bandwidth usage by improving TCP throughput in wireless environments using cross layer approach and hence named the proposed system as CRLTCP. TCP misinterprets wireless loss as congestion loss and unnecessarily reduces congestion window size. Using the signal strength and frame error rate, the type of loss is identified and accordingly the response of TCP is modified. The results show that there is a significant improvement in the throughput of proposed TCP upon which bandwidth usage is increased.     

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

LDA + U Study of Induced Half Metallicity in Cr-Doped GaN

Half-metallic ferromagnetism in the Ga_{1 ? x}Cr _x N compound at different concentrations, x = 25, 12.5 and 6.25 %, have been investigated using density functional theory as implemented in code Spanish Initiative for Electronic Simulations with Thousands of Atoms (SIESTA) using LDA + U as exchange-correlation (XC) potential, to find out the possibility of new diluted DMSs. The outcomes reveal that transition metal atom (Cr) doping in GaN induces ferromagnetism. The 3d levels of the TM ion originate a half-metallic gap at the Fermi level in the majority spin channel for all concentrations. Moreover, diluted magnetic semiconductor compounds retain the half-metallic nature at all concentrations, i.e., x = 0.25, 0.125 and 0.0625, with 100 % spin polarization at the Fermi level (E _F). The total magnetic moment of these compounds is due to Cr-3d states, and the existence of a small magnetic moment on Ga and N, non-magnetic atoms, for all doping concentrations is a consequence of p-d hybridization of Cr-d and N-p states. The calculated values of s-d exchange constant N α and p-d exchange constant N βconfirm the ferromagnetic character of the Cr-doped GaN compound.     

Improving cache locking performance of modern embedded systems via the addition of a miss table at the L2 cache level

To confer the robustness and high quality of service, modern computing architectures running real-time applications should provide high system performance and high timing predictability. Cache memory is used to improve performance by bridging the speed gap between the main memory and CPU. However, the cache introduces timing unpredictability creating serious challenges for real-time applications. Herein, we introduce a miss table (MT) based cache locking scheme at level-2 (L2) cache to further improve the timing predictability and system performance/power ratio. The MT holds information of block addresses related to the application being processed which cause most cache misses if not locked. Information in MT is used for efficient selection of the blocks to be locked and victim blocks to be replaced. This MT based approach improves timing predictability by locking important blocks with the highest number of misses inside the cache for the entire execution time. In addition, this technique decreases the average delay per task and total power consumption by reducing cache misses and avoiding unnecessary data transfers. This MT based solution is effective for both uniprocessors and multicores. We evaluate the proposed MT-based cache locking scheme by simulating an 8-core processor with 2 levels of caches using MPEG4 decoding, H.264/AVC decoding, FFT, and MI workloads. Experimental results show that in addition to improving the predictability, a reduction of 21% in mean delay per task and a reduction of 18% in total power consumption are achieved for MPEG4 (and H.264/AVC) by using MT and locking 25% of the L2. The MT results in about 5% delay and power reductions on these video applications, possibly more on applications with worse cache behavior. For the FFT and MI (and other) applications whose code fits inside the level-1 instruction (I1) cache, the mean delay per task increases only by 3% and total power consumption increases by 2% due to the addition of the MT.