Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region

This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method

Ant colony optimization (ACO) based data hiding in image complex region

This paper presents data an Ant colony optimization (ACO) based data hiding technique. ACO is used to detect complex region of cover image and afterward, least significant bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. ACO is an algorithm developed inspired by the inborn manners of ant species. The ant leaves pheromone on the ground for searching food and provisions. The proposed ACO-based data hiding in complex region establishes an array of pheromone, also called pheromone matrix, which represents the complex region in sequence at each pixel position of the cover image. The pheromone matrix is developed according to the movements of ants, determined by local differences of the image element’s intensity. The least significant bits of complex region pixels are substituted with message bits, in order to hide secret information. The experimental results, provided, show the significance of the performance of the proposed method

CLIFD: A novel image forgery detection technique using digital signatures

The paper presents a new image forgery detection technique. The proposed technique uses digital signatures; it generates a digital signature for each column and embeds the signature in the least significant bits of each corresponding column's selected pixels. The message digest algorithm 5 (MD5) is used for digital signature generation, and the fourleast-significant-bit substitution mechanism is used to embed the signature in the designated pixels. The embedding of the digital signature in the selected pixel remains completely innocent and undetectable for the human visual system. The proposed forgery detection technique has demonstrated significant results against different types of forgeries introduced to digital images and successfully detected and pointed out the forged columns

Endoscopic image analysis using Deep Convolutional GAN and traditional data

One big challenge encountered in the medical field is the availability of only limited annotated datasets for research. On the other hand, medical image annotation requires a lot of input from medical experts. It is noticed that machine learning and deep learning are producing better results in the area of image classification. However, these techniques require large training datasets, which is the major concern for medical image processing. Another issue is the unbalanced nature of the different classes of data, leading to the under-representation of some classes. Data augmentation has emerged as a good technique to deal with these challenges. In this work, we have applied traditional data augmentation and Generative Adversarial Network (GAN) on endoscopic esophagus images to increase the number of images for the training datasets. Eventually we have applied two deep learning models namely ResNet50 and VGG16 to extract and represent the relevant cancer features. The results show that the accuracy of the model increases with data augmentation and GAN. In fact, GAN has achieved the highest accuracy, that is, 94% over non-augmented training set and traditional data augmentation for VGG16

Anthropometric Study of the Human Craniofacial Morphology among different castes of Punjab Pakistan

Background: It appears from the literature that there is a research vacuum in craniofacial anthropometric studies in Pakistani population. Therefore, this study was carried out to characterize the craniofacial parameters among different castes of the Punjab Pakistan.Methods: This cross-sectional study was conducted on population of the Punjab, Pakistan, with age 18-45 years in a normal healthy state and data was collected using a questionnaire. Anthropometric instruments such as standard spreading caliper, round ended caliper, vernier caliper and scale were used for the measurement of craniofacial parameters. Data was analyzed by using SPSS version 20.0 and MS Excel 16. Morphological anthropometry of face, head, nose and ears was observed and noted.Results: Hyperleptoprosopic face was most common one in the studied population. The dominant nose type was Leptorrhine while the most dominant head shape was Dolichocephalic. The average ear index was 50.42 and 51.19 of right and left ears, respectively.Conclusion: This data is a base for the anthropometric data bank of the Punjab province of Pakistan. This data is helpful in medico legal cases, forensic investigations, and in facial surgeries. This study is also important for anthropological and forensic research.Keywords: Anthropology, Anthropometry; Craniofacial; Morphology; Populatio

A Novel Fractional-Order Variational Approach for Image Restoration Based on Fuzzy Membership Degrees

We propose a new fractional-order (space and time) total variation regularized model for multiplicative noise removal in this research article. We use the regularly varying fuzzy membership degrees to characterize the likelihood of a pixel related to edges, texture regions, and flat regions to improve model efficiency. This approach is capable of maintaining edges, textures, and other image information while significantly reducing the blocky effect. We opt for the option of local actions. In order to efficiently find the minimizer of the prescribed energy function, the semi-implicit gradient descent approach is used (which derives the corresponding fractional-order Euler-Lagrange equations). The existence and uniqueness of a solution to the suggested variational model are proved. Experimental results show the efficiency of the suggested model in visual enhancement, preserving details and reducing the blocky effect while extracting noise as well as an increase in the PSNR (dB), SSIM, relative error, and less CPU time(s) comparing to other schemes

Songs between cities: Listening to courtesans in colonial north India

In the aftermath of 1857, urban spaces and cultural practices were transformed and contested. Regional royal capitals became nodes in a new colonial geography, and the earlier regimes that had built them were recast as decadent and corrupt societies. Demolitions and new infrastructures aside, this transformation was also felt at the level of manners, sexual mores, language politics, and the performing arts. This article explores this transformation with a focus on women's language, female singers and dancers, and the men who continued to value their literary and musical skills. While dancing girls and courtesans were degraded by policy-makers and vernacular journalists alike, their Urdu compositions continued to be circulated, published, and discussed. Collections of women's biographies and lyrics gesture to the importance of embodied practices in cultivating emotional positions. This cultivation was valued in late Mughal elite society, and continued to resonate for emotional communities of connoisseurs, listeners, and readers, even as they navigated the expectations and sensibilities of colonial society

Novel supervisory management scheme of hybrid sun empowered grid-assisted microgrid for rapid electric vehicles charging area

The spread of electric vehicles (EV) contributes substantial stress to the present overloaded utility grid which creates new chaos for the distribution network. To relieve the grid from congestion, this paper deeply focused on the control and operation of a charging station for a PV/Battery powered workplace charging facility. This control was tested by simulating the fast charging station when connected to specified EVs and under variant solar irradiance conditions, parity states and seasonal weather. The efficacy of the proposed algorithm and experimental results are validated through simulation in Simulink/Matlab. The results showed that the electric station operated smoothly and seamlessly, which confirms the feasibility of using this supervisory strategy. The optimum cost is calculated using heuristic algorithms in compliance with the meta-heuristic barebones Harris hawk algorithm. In order to long run of charging station the sizing components of the EV station is done by meta-heuristic barebones Harris hawk optimization with profit of USD 0.0083/kWh and it is also validated by swarm based memetic grasshopper optimization algorithm (GOA) and canonical particle swarm optimization (PSO)

A Modulo Function-Based Robust Asymmetric Variable Data Hiding Using DCT

This work presents a new asymmetric data hiding technique that hides a variable number of secret message bits in the discrete cosine transform (DCT) coefficients of a cover image using a modular distance technique. Prior to data hiding, the proposed framework transforms a cover image from a spatial domain to various frequency coefficients using DCT. The DCT coefficients are arranged in two groups: one with low-frequency coefficient, and the other with the medium and high-frequency coefficients. The medium and higher frequency coefficients are processed for variable data hiding asymmetrically. The proposed technique hides variable sets of secret information bits in different coefficients. The variation in hidden secret information is maintained using a key developed based on the modulo of distance of a coefficient from the reference point. The same key is also used to retrieve the confidential information at the receiver ends. The results reveal that the presented framework does not create any visually significant distortion, and thus the hidden information does not attract the human visual system (HVS). The technique also results in high data hiding efficiency