Reviewerly/exHarmony huggingface dataset:
Embedding and Extraction of Image Watermarking Based on the Discrete Wavelet Transform and Alpha Blending using RSA

Digital watermarking has become a promising research area to face the challenges created by the rapid growth in distribution of digital content over the iPnternet. To prevent misuse of this data, digital image watermarking techniques are very useful. Here, a new algorithm in the domain of discrete wavelet transform (DWT) is introduced and used for copyright protection. The elements of the logo watermark are embedded directly to the one-level DWT decomposed sub-bands. In addition to that, the watermark is encrypted using RSA algorithm for secure transmission of watermark. Few attacks have been conducted which shows the security of this work. The experimental runs and results of this work have shown that this proposed technique or method has the desired properties of digital image watermarking i.e. invisibility and robustness.
Robustness Security of Data Hiding for H.265/HEVC Video Streams

In the current age of IoT and Industry 4.0, vast amounts of big data are exchanged in the cloud, social media and among sensing devices, at times causing videos to go viral and proliferating fake news. Ultra high quality videos such as in the latest H.265/HEVC standard format have the capacity for data to be embedded in them for different security applications. Security for high quality videos is a concern in our current technological age where netizens often share videos with others through social media and video hosting sites like YouTube. In this paper, we focus on data hiding for H.265/ HEVC and perform detailed security analysis of a recent H. 265/HEVC data hiding scheme. Our security consideration includes the hiding properties of secrecy and undetectability, as well as the robustness security property of tamper resistance. We show specifically an attack against the robustness security of this data hiding scheme. We discuss reasons causing the insecurity against robustness and justify strategies to improve the scheme’s protection against these types of attacks
Fex: Assisted Extraction of Domain Features from C Programs

Welcome to the 21st IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2021)! We hope that you enjoy the conference and that it will inspire you in your future research. Should you require a certificate of participation please contact Alexander Serebrenik, the general chair of SCAM, at a.serebrenik@tue.nl. For questions related to the Morressier virtual platform please contact support@morressier.com.
In Shortly about Neural Networks

A neural network is a collection of neurons that are interconnected and interactive through signal processing operations.The traditional term "neural network" refers to a biological neural network, i.e., a network of biological neurons.The modern meaning of this term also includes artificial neural networks, built of artificial neurons or nodes.Machine learning includes adaptive mechanisms that allow computers to learn from experience, learn by example and by analogy.Learning opportunities can improve the performance of an intelligent system over time.One of the most popular approaches to machine learning is artificial neural networks.An artificial neural network consists of several very simple and interconnected processors, called neurons, which are based on modeling biological neurons in the brain.Neurons are connected by calculated connections that pass signals from one neuron to another.Each connection has a numerical weight associated with it.Weights are the basis of long-term memory in artificial neural networks.They express strength or importance for each neuron input.An artificial neural network "learns" through repeated adjustments of these weights.
Interactive comment on “Global whole-rock geochemical database compilation” by Matthew Gard et al.

Gard and coauthors present a curated database of (primarily) whole-rock elemental and isotopic analyses.This work fills a useful niche between domain-specific manual compilations and large but less-curated online repositories such as EarthChem.
Preface

The International Workshop “Navigation and Motion Control” (NMC) is organized by the State Research Centre of the Russian Federation – Concern CSRI Elektropribor, JSC, with participation of ITMO University and St. Petersburg Electrotechnical University. Also, the Workshop would not have been held without support of the Academy of Navigation and Motion Control and its President, Academician of the Russian Academy of Sciences (RAS) Vladimir G. Peshekhonov. The Workshop is aimed at making the participants familiar with new technologies in presentday navigation and motion control systems, in the fields of data processing and systems development. The scope of problems discussed at the Workshop covers the upcoming trends such as inertial sensors based on new physical principles, cyber-physical systems, UAV navigation, and many others. Plenary papers are presented by well-known scientists from the leading institutes of Russia and Europe. List of Logo, International Workshop photograph, program committee, Local organizing committee and The editors are availabel in the pdf.
Frontmatter

Phase Transitions in Grey Matter: Brain Architecture and Mind Dynamics relates the complex systems that we know as ‘mind’ and ‘brain’ to simple concepts in physics such as ‘phase transition’ and ‘criticality’ and establishes a close mathematical link between them. A serious review of live issues in science – from interaction and correlation to emergence, scale invariance, attractors, noise and chaos—this book demonstrates their relevance to intelligence and consciousness. The result is a significant and useful portrait of what ‘mind’ currently means to science and aggregates widely dispersed and sometimes hard to find topics into one resource.Key highlights: •Provides a coherent basis for the existence of criticality in the brain, and shows how some of its main outstanding properties may be understood•Deeply explores the assumption that phase transition is the most relevant concept to understand the mind•Offers a strong foundation for those interested in making a complete and useful portrait of the brainThis book is for advanced graduate and graduate students in physics, applied mathematics, biology and medicine. It is an excellent resource for practitioners and those curious about recent advances in neurosciences.
Explanation

Different styles of explanation employ different patterns. In narrative explanation, people tell a story concerning how events come about. Explanation by elimination occurs when a phenomenon is explained away as being nonexistent. Explanation by deduction is powerful in mathematical fields such as physics, but is rarely possible in more qualitative fields such as biology, psychology, and sociology. In these fields, the most useful approach is mechanistic, where events are explained by showing how they causally result from regular changes in systems of connected and interacting parts. Like explanation, causality cannot be captured by a simple analysis in terms of universal regularities, manipulations, probabilities, or causal networks. Rather, a three-analysis marks all of these as typical features of causal relations, on top of familiar exemplars such as pushes and pulls.
Generating redundant features with unsupervised multi-tree genetic programming

© Springer International Publishing AG, part of Springer Nature 2018. Recently, feature selection has become an increasingly important area of research due to the surge in high-dimensional datasets in all areas of modern life. A plethora of feature selection algorithms have been proposed, but it is difficult to truly analyse the quality of a given algorithm. Ideally, an algorithm would be evaluated by measuring how well it removes known bad features. Acquiring datasets with such features is inherently difficult, and so a common technique is to add synthetic bad features to an existing dataset. While adding noisy features is an easy task, it is very difficult to automatically add complex, redundant features. This work proposes one of the first approaches to generating redundant features, using a novel genetic programming approach. Initial experiments show that our proposed method can automatically create difficult, redundant features which have the potential to be used for creating high-quality feature selection benchmark datasets.
Lessons Learned from Implementing a Textbook’s Companion Website into a Production Operations Management Course

The availability and use of online textbooks or companion websites for textbooks coupled to engineering management courses has been increasing.With this increase, the effective integration of assignments conducted via these online textbook companion tools can increase student engagement with the course material as well as within the classroom to enhance the student learning experience.But experience shows that use of these online tools can seem ineffective at best or a waste of time from a student perspective.Student feedback often expresses displeasure with the cost of purchasing access to the companion site, frustration with the precision required to correctly answer quantitative problems, and the tedious nature of completing assignments that they perceive lack connection to the in-class lessons.Successful integration of the companion site into the course that overcomes these obstacles can lead to students perceptions that use of the companion website is value added, not just another tedious task.For these reasons, the course director of the Production Operations Management course at the United States Military Academy utilized student assessment data, end of course feedback, and pre/post course student surveys to assess the effectiveness of use of assignments through the textbook companion website.This assessment drove changes in the implementation and integration of the companion website into the course in order to increase student engagement with the textbook material and classroom discussion.The changes focused on both frequency and content of the online assignments conducted through the textbook companion site.Implementation of these changes showed a dramatic improvement in student attitudes and performance over five semesters.This paper discusses the assessments that led to the changes in use of the textbook companion website as well as specific practices and recommendations for implementation of textbook companion website assignments.Use of textbook companion websites can positively impact student interaction and achievement.
De-Noising of Mango fruits using Mean Convolution Mass Filter (MCMF)

In this modern age transmission of visual information in the form of digital images are becoming a major method of communication. The noise is the result of errors in image acquisition process and they do not replicate the accurate intensities of the actual scene. This image can be utilized as an input for decision making. To produce high quality image it should be de-noised using suitable algorithm. There are various types of noises that degrades the image such as salt and pepper noise, Gaussian noise and Poisson noise, it is necessary to have knowledge about the noise present in the image. The paper proposed a new algorithm “Mean Convolution Mass Filter (MCMF)”. This approach has been proved to have better PSNR value in de-noising the digital image when compared to the other existing algorithms.
Hash Tables

A hashtable is a fixed-sized data structure in which the size is defined at the start. This chapter explains how hashtables work by focusing on hashing, the method of generating a unique key. By the end of this chapter, you will understand various hashing techniques and know how to implement a hashtable from scratch.
Modeling Probabilities

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.
Antiforensics Techniques

As we mentioned before, digital forensics, also known as cyber or computer forensics, is a branch of forensic science that uses scientific knowledge, methodology, and rigor to aid the solving of crimes and incidents by collecting, analyzing, and presenting digital evidence to use in remedial action or a court of law. The primary goal of digital forensics is to perform a structured investigation of digital evidence and prepare this evidence for presentation in a court of law. Digital forensic investigators use different forensic tools to collect, preserve, and interpret digital evidence. Based on their findings, they will draw conclusions and present these conclusions to those who will act on them.
Red-green-blue (RGB) profiling of pancreatic mass-elastographies: validation of a predictive model for non-invasive assessment of malignancy

Aim To evaluate the accuracy of quantitative image analysis of pancreatic tumor elastographies obtained by EUS to predict malignancy.
Automated Code Inspection of Twitter Data using Software Repository Mining

The project proposes an application that reviews and analysis tweets on twitter application by doing software repository mining on the information gathered. The main purpose of this project is to investigate a few computational strategies to estimate the effect of web based life. Propelled by the techniques recently created to break down software systems and other unique frameworks, these strategies measure different static and dynamic parts of interpersonal organizations, the possibility and advantages of these estimation techniques with regards to Twitter is shown. By investigating the tweets the connection between the imperativeness of the news and the volume of the related tweets can be seen, which gets refreshed after every constant period of time. Using this strategy the tweets are ranked according to the highest priority.
Need of Technology Changes in Hospital Domains for Improved Nursing Service using Ai (Artificial Intelligence) and IoT (Internet of Things)

Healthcare has come a long way with the technological upgrades that it has witnessed and embraced. Technological disrupters like automation, big data, cloud, AI, IOT, have contributed in making the healthcare domain more enhanced and efficient. In the healthcare when we focus more on hospital related services, we see that the changes have started to reflect. Considering Nursing as one of the major services, this study attempts to understand the long ranging impact of AI and IOT on nursing specifically. Nursing as a choice of work has always been looked down upon by the society. The overall work environments, pay structures have also not been conducive for the work force. Being a crucial component of the healthcare domain, the impact of AI and IOT would be more pronounced and visible on nursing in the coming years. The paper attempts to find the gaps and areas of improvement in nursing to make it more efficient. Research Methods and Approach: The paper finds relevant attributes which impact the performance of the nurses. The attributes are derived using mixed method of research and triangulation. This is planned by conducting the systematic literature review followed first by qualitative research methodology based semi structured interviews of patients and their relatives and later by interviewing the doctors and nurses, hospital management. A Systematic literature review of minimum 75 to 100 research papers from the following databases Pubmed, Ieee, ACM, Science Direct and Google Scholar was planned. For the interviews it was decided to conduct a heterogeneous quota sampling for interviewing the patients, their relatives and doctors and nurses, hospital management. Purpose of the Study: Artificial intelligence and Internet-of-Things are the most path breaking techniques today69. The paper integrates these in the hospital domain focussing only “nursing” as service. It answers the crucial research questions like ‘If AI and IOT is used as a methodology in ”nursing Services” ,visualizing the impact of AI enabled Bots in nursing, pros and cons of introducing the AI technology intervention in Nursing and to conceptualize a model for the same. Results/Findings &amp; Interpretation: The paper maps the AI algorithms and IOT to the basic nurse functions. These AI-IOT enabled bots are better in performance compared to nurses. Implications: description of main outcomes of the study. a) The paper helps to address the manpower shortage in rural regions which are deprived of hospital services. b) Can help better care of elderly patients c) Can provide a substantial support for the human nurses and d) Can help to improve the nursing on the whole. Originality/Novelty: The literature review proved that the concept of the paper is very original. Nowhere had the AI algorithms mapped to any hospital service efficiently.
Medios educativos como espacios subversivos en América Latina: potencialidades, inconvenientes y consideraciones en el contexto de la pandemia

The aim of this dossier is to transcend the conventional academic discussion regarding the incorporation of digital media at school, its benefits, and drawbacks, and to center the analysis on the way that educational media boosts social empowerment and cultural resistance. The dossier articles debate how digital media may be of use not just as tools and platforms to improve traditional learning, but promote social change, empower individuals and organizations, and sponsor community action even in adverse contexts, such as in our present situation shaped by the negative effects caused by the COVID-19 pandemic. The matter under investigation is how educational media become objects and spaces for social criticism, political contestation, and the support of minorities as what James C. Scott termed a “weapon of the weak,” used to fight back social exclusion and cultural domination.
Development of an Optimized Digital E-Recruitment Model for Sindh Police

Information and communication technology (ICT) have profound influence in the modern world such that it has taken every sphere of life today. The advent of ICT has made the all activities relating to human and material resources utilize unto optimum level and making every aspect of life easier. In these days, the use of latest ICT technology like digital finger print identification, surveillance camera, and radiofrequency identificationdevices ensure transparency and identity fraud. However, existing manual recruitment process in Sindh Police of Pakistanhas been disputed at various platforms to ensure transparency. There have been several issues such as physical document identification and verification, physical tests, such as, running, jumping, obstaclesoverpassing, finger printsneed to be transparent and apparent to respective authorities and aspirants during the recruitment process. Therefore, the purpose of this research article isto identify existing issues in current recruitment process. It provides appropriate solutions for fare recruitment process in Sindh Police Pakistan. This research isintended to Development of an Optimized Digital E-Recruitment Model of Sindh Policefor Sindh Police connectedto National Database &amp; Registration Authority (NADARA) of Pakistan to verify aspirants’ identity online, monitor their physical tests using RFID, surveillance cameras, GPS enabled bracelets generating automated digital reports of all aspirants, ensuring transparency and fairness in recruitment system ofSindh Police of Pakistan.
CREATING STYLE SHEET BY USING SPEECH RECOGNITION

Today’s rich Web applications use a mix of Java Script and Asynchronous communication with the application server. This mechanism is also known as Ajax: Asynchronous JavaScript and XML. The intent of Ajax is to exchange small pieces of data between the browser and the application server, and in doing so, use partial page refresh instead of reloading the entire Web page. AJAX (Asynchronous JavaScript and XML.) is a powerful web development model for browser-based Web applications. This project is designed and developed keeping that factor into mind, and a little effort is made to achieve this aim. Our project is capable to recognize the speech and convert the input audio into text &amp; style sheet it also enables a user to perform operations “save, open, exit” a file by providing voice input.
Authenticated Medical Image Transmission using Enhanced Reversible Data Hiding (RDH) with NNP2 Algorithm and Rhombus Prediction

During the last few years, the medical information of concerned patient is transferred from one doctor to another doctor via internet for better diagnosis and studies. Transferring medical information over a transmission medium is known as telemedicine. Telemedicine has been used to overcome distance barriers and to improve access to medical service. The telemedicine application includes emergency treatment, home monitor, military applications, and medical education. These medical images are corrupted by hackers when it is transferred through internet. Hence security of medical images is necessary. Watermarking is used for providing security while transferring medical images. Reversible Data Hiding (RDH) is one of the efficient methods for secure transmission of medical images. In this method, data hiding capacity is very small and the distortion level of recovers images is very large. To avoid these drawbacks, Nearest Neighborhood Pixel Prediction (NNP2) algorithm based on Chinese Remainder Theorem (CRT) is proposed and Rhombus Prediction is applied in NNP2 to increase data hiding capacity. The distortion level is reduced by Histogram Shifting. The performance of proposed method is evaluated using PSNR for number of medical images. The results shows that the proposed method gives good results when compared with traditional methods.