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.     

Security Driven Scheduling Model for Computational Grid Using NSGA-II

Number of software applications demands various levels of security at the time of scheduling in Computational Grid. Grid may offer these securities but may result in the performance degradation due to overhead in offering the desired security. Scheduling performance in a Grid is affected by the heterogeneities of security and computational power of resources. Customized Genetic Algorithms have been effectively used for solving complex optimization problems (NP Hard) and various heuristics have been suggested for solving Multi-objective optimization problems. In this paper a security driven, elitist non-dominated sorting genetic algorithm, Optimal Security with Optimal Overhead Scheduling (OSO₂S), based on NSGA-II, is proposed. The model considers dual objectives of minimizing the security overhead and maximizing the total security achieved. Simulation results exhibit that the proposed algorithm delivers improved makespan and lesser security overhead in comparison to other such algorithms viz. MinMin, MaxMin, SPMinMin, SPMaxMin and SDSG.     

Comprehensive study of RF analysis of G/GO-based NEMS shunt switch

Microsystem Technologies - High isolation and low insertion loss are the key design parameters for the NEMS switch at high frequency. The comprehensive study of radio frequency (RF) performance...     

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.     

Hydrostatic Pressure Effect on Ga<Subscript>0.75</Subscript>Cr<Subscript>0.25</Subscript>As DMS: DFT Study

This paper studies the first-principles calculations of the effect of hydrostatic pressure on the structural, electronic and magnetic properties of Ga_0.75Cr_0.25As dilute magnetic semiconductor in zb (B3) phase. High-pressure behaviour of Ga_0.75Cr_0.25As has been investigated between 0 and 100 GPa. The calculations have been performed using DFT as implemented in code SIESTA using LDA + U as an exchange-correlation (XC) potential. The study of band structures shows half-metallic ferromagnetic nature with 100% spin polarization. Under application of external pressure, the valence band and conduction band are shifted from their positions which lead to modification of electronic structure.     

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.