Adaptive Particle Swarm Optimization Data Hiding for High Security Secret Image Sharing

The main aim of this work is to improve the security of data hiding forsecret image sharing. The privacy and security of digital information have becomea primary concern nowadays due to the enormous usage of digital technology.The security and the privacy of users’ images are ensured through reversible datahiding techniques. The efficiency of the existing data hiding techniques did notprovide optimum performance with multiple end nodes. These issues are solvedby using Separable Data Hiding and Adaptive Particle Swarm Optimization(SDHAPSO) algorithm to attain optimal performance. Image encryption, dataembedding, data extraction/image recovery are the main phases of the proposedapproach. DFT is generally used to extract the transform coefficient matrix fromthe original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtainingthe encrypted image by data-hider, additional data embedding is formulated intohigh-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the imagefor secret bits concealment. In addition, the secret data embedding capacityenhancement is focused on image visual quality maintenance. Hence, it isobserved from the simulation results that the proposed SDHAPSO techniqueoffers high-level security outcomes with respect to higher PSNR, security level,lesser MSE and higher correlation than existing techniques. Hence, enhancedsensitive information protection is attained, which improves the overall systemperformance.

Use AMMI model to analyze adaptability of rice varieties

The adaptability of rice varieties is one of themost concerned questions to rice breeders.Inrice breeding,combined variety test and re-gional trials which included multiple genotypesand environments were conducted to identifythe adaptability of new rice varieties.In mostregional trials,interaction between genotypeand environment is significant,so it is impor-tant to analyze the interaction for estimating

Hybrid approach used for extended image-based wavefront sensor-less adaptive optics

The stochastic paralld gradient descent （SPGD） algorithm is widely used in wavefront sensor-less adaptive optics （WSAO） systems. However, the convergence is relatively slow. Modal-based algorithms usually provide much faster convergence than SPGD; however, the limited actuator stroke of the deformable mirror （DM） often prohibits the sensing of higher-order modes or renders a closed-loop correction inapplicable. Based on a comparative analysis of SPGD and the DM-modal-based algorithm, a hybrid approach involving both algorithms is proposed for extended image-based WSAO, and is demonstrated in this experiment. The hybrid approach can achieve similar correction results to pure SPGD, but with a dramatically decreased iteration number.

Rural coping and adaptation strategies for climate change by Himalayan communities in Nepal

Climate change has major impacts on the livelihoods of forest-dependent communities.The unpredictable weather conditions in rural Nepal have been attributed to a changing climate.This study explored the climate change adaptation and coping strategies that rural communities adopt for the conservation of natural resources and livelihoods in the mid-hills of Nepal.This paper explored major climatic hazards,assessed different coping and adaptation measures,and barrier faced to climate change adaptation based on perceptions by forest-dependent communities.We conducted focus group discussions,questionnaire surveys,and semistructured interviews with local communities and stakeholders.The results showed that rural communities had experienced significant impacts of climate change and variability.In response,they are practicing diverse coping and adaptation strategies,including the construction of bioengineering structures and planting different species that grow quickly and establish promptly.

AN IMPROVED ALGORITHM OF GMM VOICE CONVERSION SYSTEM BASED ON CHANGING THE TIME-SCALE

This paper improves and presents an advanced method of the voice conversion system based on Gaussian Mixture Models(GMM) models by changing the time-scale of speech.The Speech Transformation and Representation using Adaptive Interpolation of weiGHTed spectrum(STRAIGHT) model is adopted to extract the spectrum features,and the GMM models are trained to generate the conversion function.The spectrum features of a source speech will be converted by the conversion function.The time-scale of speech is changed by extracting the converted features and adding to the spectrum.The conversion voice was evaluated by subjective and objective measurements.The results confirm that the transformed speech not only approximates the characteristics of the target speaker,but also more natural and more intelligible.

First light on an adaptive optics system using a non-modulation pyramid wavefront sensor for a 1.8 m telescope

Our adaptive optics system based on a non-modulation pyramid wavefront sensor is integrated into a 1.8 m astronomical telescope installed at the Yunnan Observatory in LiJiang, and the first light with high-resolution imaging of an astronomical star is successfully achieved. In this Letter, the structure and performance of this system are introduced briefly, and then the observation results of star imaging are reported to show that the angular resolution of an adaptive optics system using a non-modulation pyramid wavefront sensor can approach the diffraction limit quality of a 1.8 m telescope.

Three-dimensional color photon counting microscopy using Bayesian estimation with adaptive priori information

In this Letter, we propose a novel three-dimeusional （3D） color microscopy for microorganisms under photon- starved conditions using photon counting integral imaging and Bayesian estimation with adaptive priori infor- mation. In photon counting integral imaging, 3D images can be visualized using maximum likelihood estimation （MLE）. However, since MLE does not consider a priori information of objects, the visual quality of 3D images may not be accurate. In addition, the only grayscale image can be reconstructed. Therefore, to enhance the visual quality of 3D images, we propose photon counting microscopy using maximum a posteriori with adaptive priori information. In addition, we consider a wavelength of each basic color channel to reconstruct 3D color images. To verify our proposed method, we carry out optical experiments.