Adaptive backtracking search optimization algorithm with pattern search for numerical optimization

The backtracking search optimization algorithm（BSA） is one of the most recently proposed population-based evolutionary algorithms for global optimization. Due to its memory ability and simple structure, BSA has powerful capability to find global optimal solutions. However, the algorithm is still insufficient in balancing the exploration and the exploitation. Therefore, an improved adaptive backtracking search optimization algorithm combined with modified Hooke-Jeeves pattern search is proposed for numerical global optimization. It has two main parts： the BSA is used for the exploration phase and the modified pattern search method completes the exploitation phase. In particular, a simple but effective strategy of adapting one of BSA＇s important control parameters is introduced. The proposed algorithm is compared with standard BSA, three state-of-the-art evolutionary algorithms and three superior algorithms in IEEE Congress on Evolutionary Computation 2014（IEEE CEC2014） over six widely-used benchmarks and 22 real-parameter single objective numerical optimization benchmarks in IEEE CEC2014. The results of experiment and statistical analysis demonstrate the effectiveness and efficiency of the proposed algorithm.

Exhibition of Bleaching Resistance Via Adaptive Bleaching Pattern by Coral Reefs of the Gulf of Mannar during Massive Bleaching Event 2019

Coral reefs in the Gulf of Mannar(GoM)and Palk Bay regions are facing potential threats from climate change,sedimentation and anthropogenic activities.Considerably,coral reefs in these two regions are highly damaged due to frequent bleaching events caused by increased sea surface temperature(SST)recorded over the past two decades.Recently,during February to May 2019,mass bleaching event of corals was documented again in GoM and Palk Bay regions due to increased sea surface temperatures ranged between 32°C to 36°C.Despite of completely bleached corals,some coral colonies of the same bleached coral species have displayed adaptive bleaching pattern(ABP)for survival.This incidence is displayed by the symbiotic zooxanthellae to protect coral polyps from environmental stress such as elevated temperatures.These observations infer that coral colonies with preferential bleaching pattern ability would serve as environmental stress resisting coral colonies which can be used for restoration activities and cryopreservation.Further studies are needed to explain the potential mechanisms or specific environmental drivers responsible for ABP.

Phase-only pattern synthesis based on gradient-descent optimization

By applying phase-only technique in array antenna pattern synthesis, antenna arrays can form desired patterns with the use of phase shifters only. A novel phase-only pattern synthesis algorithm is proposed for the passive phased array seeker. This algorithm synthesizes the main beam of the antenna pattern through least-squares approximation, thus minimizing the errors between the actual and the desired main beams. The synthesis problem can be solved by applying gradient-descent optimization. The item for suppressing side lobes is added to the above synthesis problem. To obtain a side lobe level as low as possible, the algorithm assigns different weights to different directions in the side lobe region. The algorithm is run repeatedly and the weights are adjusted adaptively according to the normalized power in the side lobe directions. Detailed examples are presented to demonstrate the accuracy and effectiveness of the proposed approach.

Impacts of climate change on water quantity, water salinity, food security, and socioeconomy in Egypt

Climate change might have direct impacts on water quantity in Egypt and lead to indirect effects on Mediterranean saltwater intrusion to groundwater,which exposes agriculture to vulnerability.This study investigated impacts of climate change on agriculture,with particular regard to food security and socioeconomy,and quantified the effectiveness of cropping pattern adaptation measures by integrating three mathematical models.The BlueM model was used for hydrological simulations of Nasser Lake under flooding scenarios to predict the water supply from the High Aswan Dam.The water and salinity balance(WB-SAL)model was adopted to estimate the water salinity in the Nile Delta.The simulated results from the BlueM and WB-SAL models were integrated with the agricultural simulation model for Egypt(ASME)to project cropping patterns,food security,and socioeconomy throughout the country.The results showed that future climate change will directly affect the total crop area;crop areas for 13 crop types;the self-sufficiency of wheat,rice,cereal,and maize supplies;and socioeconomic indicators.The proposed cropping pattern adaptation measures focus on fixing the crop areas of rice and orchards and providing half of the population with lentils,maize,onion,vegetables,milk,and meat.The adaptation measures have the potential to promote food security without causing deterioration of the socioeconomic situation.However,water availability has much more significant effects on food security and socioeconomy than cropping pattern adaptation measures do.Accordingly,the country should rationalize water use efficiency and increase water supply.©2021 Hohai University.Production and hosting by Elsevier B.V.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

A Novel Forgery Detection in Image Frames of the Videos Using Enhanced Convolutional Neural Network in Face Images

Different devices in the recent era generated a vast amount of digital video.Generally,it has been seen in recent years that people are forging the video to use it as proof of evidence in the court of justice.Many kinds of researches on forensic detection have been presented,and it provides less accuracy.This paper proposed a novel forgery detection technique in image frames of the videos using enhanced Convolutional Neural Network(CNN).In the initial stage,the input video is taken as of the dataset and then converts the videos into image frames.Next,perform pre-sampling using the Adaptive Rood Pattern Search(ARPS)algorithm intended for reducing the useless frames.In the next stage,perform preprocessing for enhancing the image frames.Then,face detection is done as of the image utilizing the Viola-Jones algorithm.Finally,the improved Crow Search Algorithm(ICSA)has been used to select the extorted features and inputted to the Enhanced Convolutional Neural Network(ECNN)classifier for detecting the forged image frames.The experimental outcome of the proposed system has achieved 97.21%accuracy compared to other existing methods.