Boosting image watermarking authenticity spreading secrecy from counting-based secret-sharing

This study presents enhancing images authentication by securing watermarking hidden data via shares generated from counting-based secret sharing.The trustfulness of shares utilised secret-sharing as an applicable privacy creation tool for the authentication of real-life complex platforms.This research adjusts embedding the watermarking data over the images by innovative redistribution of shares to be embedded spread over all the images.The anticipated watermarking technique guaranteed to scatter the share bits implanting at different least significant bits of image pixels as boosting up the trust overall authentication practicality.The paper experimentation performance analysis shows that this improved image watermarking authentication(capacity)is averagely better by 33%–67%than other related exclusive-OR oriented and octagon approaches.Interestingly,these measurement improvements did not degrade the robustness and security of the system,inspiring our research for opening novel track of related future counting-based secret-sharing authentication progresses to come.

Analysis of community question-answering issues via machine learning and deep learning:State-of-the-art review

Over the last couple of decades,community question-answering sites(CQAs)have been a topic of much academic interest.Scholars have often leveraged traditional machine learning(ML)and deep learning(DL)to explore the ever-growing volume of content that CQAs engender.To clarify the current state of the CQA literature that has used ML and DL,this paper reports a systematic literature review.The goal is to summarise and synthesise the major themes of CQA research related to(i)questions,(ii)answers and(iii)users.The final review included 133 articles.Dominant research themes include question quality,answer quality,and expert identification.In terms of dataset,some of the most widely studied platforms include Yahoo!Answers,Stack Exchange and Stack Overflow.The scope of most articles was confined to just one platform with few cross-platform investigations.Articles with ML outnumber those with DL.Nonetheless,the use of DL in CQA research is on an upward trajectory.A number of research directions are proposed.

Improving data hiding within colour images using hue component of HSV colour space

Data hiding technologies aim to hide the existence of secret information within digital covers such as images by causing unnoticeable degradation to their quality.Reducing the image distortion and increasing the embedding capacity are the main points that the data hiding techniques revolved around.This article proposes two high payload embedding methods with high stego image quality using the Hue-Saturation-Value(HSV)colour model.The first method is hue-based embedding(HBE)that employs the H plane for hiding one or two bits in non-grey pixels.The second method uses the three HSV components,so it is called three-planes embedding(TPE).In TPE,one bit is hidden in the least significant bit(LSB)of V of the grey pixels,one or two bits in H of the pixels having low saturation or low brightness and one bit in the LSB of S otherwise.The experiments were conducted on 25 images and the results show that HBE hides more data on average than TPE with its quality reaching 60 dB.TPE achieves quality up to 61 dB and capacity reaches 364 Kb.TPE scores the highest capacity among six state-of-the-art techniques in Red-Green-Blue,HSV,Hue-Saturation-Intensity and YCbCr spaces with the highest average peak signal to noise ratio midst five of them.By embedding 60,90,and 120 Kb,this TPE attains the best average quality amid all the methods.

Efficient computation of Hash Hirschberg protein alignment utilizing hyper threading multi-core sharing technology

Due to current technology enhancement,molecular databases have exponentially grown requesting faster efficient methods that can handle these amounts of huge data.There-fore,Multi-processing CPUs technology can be used including physical and logical processors(Hyper Threading)to significantly increase the performance of computations.Accordingly,sequence comparison and pairwise alignment were both found contributing significantly in calculating the resemblance between sequences for constructing optimal alignments.This research used the Hash Table-NGram-Hirschberg(HT-NGH)algo-rithm to represent this pairwise alignment utilizing hashing capabilities.The authors propose using parallel shared memory architecture via Hyper Threading to improve the performance of molecular dataset protein pairwise alignment.The proposed parallel hyper threading method targeted the transformation of the HT-NGH on the datasets decomposition for sequence level efficient utilization within the processing units,that is,reducing idle processing unit situations.The authors combined hyper threading within the multicore architecture processing on shared memory utilization remarking perfor-mance of 24.8%average speed up to 34.4%as the highest boosting rate.The benefit of this work improvement is shown preserving acceptable accuracy,that is,reaching 2.08,2.88,and 3.87 boost-up as well as the efficiency of 1.04,0.96,and 0.97,using 2,3,and 4 cores,respectively,as attractive remarkable results.

基于信息隐藏的RGB图像像素指示高容量技术

基于掩密图像而使用的图像称为掩护媒体。最低有效位(LSB)是在此领域常用的一种技术,个别使用图像内的LSB进行掩密的方案是可利用的。本文综合了随机像素操作方法和掩密密钥的思想指导研究工作,即使用其中一个通道的最低2bits来显示其他两个通道数据的存在。这项工作最终显示出许多值得关注的结果,尤其是与RGB图像像素有关的被隐藏的数据位的容量。