Reviewerly/exHarmony huggingface dataset:
Relax Player App With Relaxation Melodies and Different Sounds

When mind is at peace, body responds in the same tone. Contrarily, a little anxiety or worry may upset the peace of mind and body, leading to faster heartbeat, taut muscles, high or low blood pressure, abnormal hormone secretion, and over sweating. These are the common symptoms of stress. These may, in turn, lead to serious health issues, as well as psychological disorders, such as insomnia (sleeplessness), anger, and tendency to commit suicide. Nowadays the ratio of suicide is on the increase on a day-to-day scale. To overcome all these problems, and cater to human right to enjoy an environment of peace and quiet for better mental and physical performance, the authors have developed an Android-based offline, multi-functional mobile application: Relax Player App. It panoramically arrays natural sounds, animal sounds, instrumental music, white noise, and brain soothing melodies to relax and freshen up user's ears and mind. It also has in-built mechanism to create one's own melody by mixing these sounds, adding to its appeal.
Disclosure Analysis of SQL Workflows

In the context of business process management, the implementation of data minimization requirements requires that analysts are able to assert what private data each worker is able to access, not only directly via the inputs of the tasks they perform in a business process, but also indirectly via the chain of tasks that lead to the production of these inputs. In this setting, this paper presents a technique which, given a workflow that transforms a set of input tables into a set of output tables via a set of inter-related SQL statements, determines what information from each input table is disclosed by each output table, and under what conditions this disclosure occurs. The result of this disclosure analysis is a summary representation of the possible computations leading from the inputs of the workflow to a given output thereof.
Maintaining Security in Software Evolution

In this chapter, we introduce a three-layered framework for maintaining security in software evolution at design time and run time. Additionally, we present a suite of five approaches that employ the framework. Two approaches focus on design-time use of knowledge extracted from natural-language documents to identify potential steps for co-evolving the system’s design and on integrating architecture model information with program code. A third approach bridges design time and run time to support architects as the software evolves. The two remaining approaches focus on run-time security maintenance. The fourth approach monitors run-time information in order to detect suspicious behaviour, which is reacted to automatically by adapting the system with mitigation, while the fifth approach focuses on interdisciplinary changes in automation software. In combination, the approaches address current challenges for security maintenance at design time and run time.
Analysis of Nonlinear Activation Functions for Classification Tasks Using Convolutional Neural Networks

We give an overview of several nonlinear activation functions in deep neural networks that are used to solve various complex machine learning applications. We make the comparison on effectiveness of using these functions and conduct empirical analysis on the Cat/Dog dataset with the aim of clarifying which function produce the best results overall. We also make the prediction by taking the number of input images on CNN model by applying different activation functions at the number of hidden layers.
3D visualization of 2D/360&amp;#xB0; image and navigation in virtual reality through motion processing via smartphone sensors

The 360&#xB0; images or regular 2D images look appealing in Virtual Reality yet they fail to represent depth and how the depth can be used to give an experience to the user from two dimensional images. We proposed an approach for creating stereogram from computer generated depth map using approximation algorithm and later use these stereo pairs for giving a complete experience on VR along with forward and backward navigation using mobile sensors. Firstly the image is being segmented into two images from which we generated our disparity map and afterwards generate the depth image from it. After the creation of the depth image, stereo pair which is the left and right image for the eyes were created. Acquired image from the previous process then handled by Cardboard SDK for VR support used in the Android devices using Google Cardboard headset. With the VR image in the stereoscopic device, we use the accelerometer sensor of the device to determine the movement of the device while head mounted. Unlike the other VR navigation systems offered (HTC Vibe, Oculus) using external sensors, our approach is to use the built-in sensors for motion processing. Using the accelerometer reading from the movement, the user will be able to move around virtually in the constructed image. The results of this experiment are the visual changes of the image displayed in VR according to the viewer&#x2019;s physical movement.
Retraction: Honggang Yu, An efficient face recognition algorithm using the improved convolutional neural network

Honggang Yu, An efficient face recognition algorithm using the improved convolutional neural networkDiscrete &amp; Continuous Dynamical Systems - S, 12 (2019), 901-914This paper is retracted by decision of the Editors in Chief of the journal Discrete &amp;Continuous Dynamical Systems - S.
Retraction: Xiaohong Zhu, Lihe Zhou, Zili Yang and Joyati Debnath, A new text information extraction algorithm of video image under multimedia environment

Xiaohong Zhu, Lihe Zhou, Zili Yang and Joyati Debnath, A new text information extraction algorithm of video image under multimedia environmentDiscrete &amp; Continuous Dynamical Systems - S, 12 (2019), 1265-1279This paper is retracted by decision of the Editors in Chief of the journal Discrete &amp;Continuous Dynamical Systems - S.
Proofs of several conjectures on linear codes from Boolean functions

Ding (2016) introduced a generic construction of linear codes over F p from a subset of F p m . Many combinatorially interesting sets give rise to codes with good parameters under this generic construction. Ding also provided a set of interesting conjectures related to the properties of several sets arising from vectorial Boolean functions and their corresponding linear codes under this construction. In this paper we prove four of these conjectures (Conjectures 38–41).
The Messaging Layer Security (MLS) Architecture

This document describes the architecture and requirements for theMessaging Layer Security (MLS) protocol. MLS provides a security layerfor group messaging applications with from two to a large number ofclients. It is meant to protect against eavesdropping, tampering, andmessage forgery.
X*: Anytime Multiagent Planning With Bounded Search

Multi-agent planning in dynamic domains is a challenging problem: the size of the configuration space increases exponentially in the number of agents, and plans need to be re-evaluated periodically to account for moving obstacles. However, we have two key insights that hold in several domains: 1) conflicts between multi-agent plans often have geometrically local resolutions within a small repair window, even if such local resolutions are not globally optimal; and 2) the partial search tree for such local resolutions can then be iteratively improved over successively larger windows to eventually compute the global optimal plan. Building upon these two insights, we introduce 1) a class of anytime multiagent planning solvers, 2) a naive solver in this class, and 3) an efficient solver in this class which reuses prior search information when improving a solution.
A study on use of the web for automatic answering of remedy finding questions of common users

BACKGROUND: The World Wide Web has become a huge repository of knowledge in many domains, including health problems and remedy. An intelligent system, having the capability of mining the relevant information from the web, can provide instant guidance in our basic health problems. OBJECTIVE: The fir st objective is to convert the free-form long user query into a structured summary. The second objective is to provide an advice for a health query posed by a user. The suggestion can be in the form of names of medicines and related information or a warning to indicate that the situation is a medical emergency. METHODS: First, a set of template information is extracted from the user question. A search query is formed to retrieve relevant pages from a set of trusted websites. The retrieved pages are processed in various levels to extract the remedy and related information. RESULTS AND CONCLUSION: The system is tested using a set of real questions collected from various relevant websites. The system generated suggestions are evaluated by experts. Evaluation results show that the system provides relevant results in 92.92% cases.
A New Cross-Layer FPGA-Based Security Scheme for Wireless Networks

This chapter presents a new cross-layer security scheme which deploys efficient coding techniques in the physical layer in an upper layer classical cryptographic protocol system. The rationale in designing the new scheme is to enhance security-throughput trade-off in wireless networks which is in contrast to existing schemes which either enhances security at the detriment of data throughput or vice versa. The new scheme is implemented using the residue number system (RNS), non-linear convolutional coding and subband coding at the physical layer and RSA cryptography at the upper layers. The RNS reduces the huge data obtained from RSA cryptography into small parallel data. To increase the security level, iterated wavelet-based subband coding splits the ciphertext into different levels of decomposition. At subsequent levels of decomposition, the ciphertext from the preceding level serves as data for encryption using convolutional codes. In addition, throughput is enhanced by transmitting small parallel data and the bit error correction capability of non-linear convolutional code. It is shown that, various passive and active attacks common to wireless networks could be circumvented. An FPGA implementation applied to CDMA could fit into a single Virtex-4 FPGA due to small parallel data sizes employed.
Gaussian Process Deep Belief Networks: A Smooth Generative Model of Shape with Uncertainty Propagation

The shape of an object is an important characteristic for many vision problems such as segmentation, detection and tracking. Being independent of appearance, it is possible to generalize to a large range of objects from only small amounts of data. However, shapes represented as silhouette images are challenging to model due to complicated likelihood functions leading to intractable posteriors. In this paper we present a generative model of shapes which provides a low dimensional latent encoding which importantly resides on a smooth manifold with respect to the silhouette images. The proposed model propagates uncertainty in a principled manner allowing it to learn from small amounts of data and providing predictions with associated uncertainty. We provide experiments that show how our proposed model provides favorable quantitative results compared with the state-of-the-art while simultaneously providing a representation that resides on a low-dimensional interpretable manifold.
Inferring User Needs &amp; Tasks from User Interactions

The need for search often arises from a broad range of complex information needs or tasks (such as booking travel, buying a house, etc.) which lead to lengthy search processes characterised by distinct stages and goals. While existing search systems are adept at handling simple information needs, they offer limited support for tackling complex tasks. Accurate task representations could be useful in aptly placing the user in the task-subtask space and enable systems to contextually target the user, provide them better query suggestions, personalization and recommendations and help in gauging satisfaction.
Dashboard settings design in SVARA using user-centred design method

SVARA is the first Social Media audio application in Indonesia developed by PT. Zamrud Teknologi Khatulistiwa. At present, this application does not have feature settings to display content and other basic settings on the user's side. This situation results in users not having the role to manage the appearance of the dashboard according to their preferences. Settings are done entirely by administrators using scripts and must take APIs with regular PHP scripts. And this is very troublesome. So to give a role to the view of user management, the application needs to be made a dashboard setting feature as a follow-up. Through this paper, the researchers propose designing this dashboard feature using the User-Centered Design (UCD) method. The design results show that this method has a positive correlation with user involvement support in the application development process.
Mold

Breathing well at the wastelands? Indoor climate change in schools and the daily lives of arctic children is a chapter by Tuure Tammi. In his chapter he creates a vision about the indoors, and especially indoor-air, as a natural-cultural entanglement. He does this by looking at “mold schools” as an example of entanglement where indoor-air materializes as an issue of environmental health. When concerning children, healthy indoor-air becomes even more important. Tuure discusses how adults take children into consideration and how the children are and can be agents in the matter at hand. He points out that children in many ways are considered as ‘generalized subjects’ even though they are seen to ‘practice their environment’. Tuure shows different ways in which humans are tangled with microbes and how this entanglement is changed through technologies. He concludes by stating how the phenomenon of “mold schools” shows the ways in which nature remains inside buildings and how this materialization matters to children in different ways.
A New Approach for Image Compression Using Efficient Coding Technique and BPN for Medical Images

Medical images produce a digital form of human body pictures. Most of the medical images contain large volumes of image data that is not used for further analysis. There exists a need to compress these images for storage issues and to produce a high-quality image. This paper discusses an image compression using Back Propagation Neural network (BPN) and an efficient coding technique for MRI images. Image compression using BPN produces an image without degrading its quality and it requires less encoding time. An efficient coding technique—Arithmetic coding is used to produce an image with better compression ratio and redundancy is much reduced. Back-Propagation Neural Network with arithmetic coding gives the better results.
MapReduce Algorithms and Patterns

In this chapter, I will show you a few examples of the most common types of MapReduce patterns and algorithms. They will guide your thinking on how to encode typical operations in a MapReduce way. This should guide you in a way you think about your own coding challenges.
Designing the Software Systems of the Future

We report here on the Future of Software Design Workshop that was held on Jan 12-14, 2018 in Pittsburgh, PA under the sponsorship of the Carnegie Mellon University Software Engineering Institute. The software industry is awash in modern trends that involve artificial intelligence (AI), autonomy, data everywhere, etc. These trends affect the structure of softwareintensive systems and their designs. The goal of the workshop was to bring together participants from diverse backgrounds to formulate ideas for software design of future systems and related research opportunities and challenges. In this report we summarize the outcomes of the workshop
Logarithmic Transform based Digital Watermarking Scheme

In this chapter, a new frequency domain transformation based digital watermarking technique has been introduced. The proposed technique adopts logarithmic transformation in order to embed the watermark image into the host image. The algorithm is subjected for various security attacks and compared with other frequently available digital watermarking schemes. The results obtained from the proposed algorithm are more satisfied compared to the existing systems.
An intelligent system for paper currency verification using support vector machines

In recent years, with the advent of digital imaging technology such as color printers and color scanners, it has become easier for counterfeiters to produce fake banknotes. The spread of counterfeit money causes loss to everyone involved in financial transactions. Therefore, an effective and reliable   verification technique is necessary for successful and reliable financial transactions. This paper presents a cognitive computation based technique for paper currency verification. In this regard, Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) analysis of counterfeit and genuine banknotes are performed. This experimentation confirmed that, material used in preparation of genuine and counterfeit banknotes is totally different from each other. Based on these findings, a set of discriminative and robust features is proposed to reflect these differences in currency images. The proposed features represent the material of the banknote such as printing ink, chemical composition, and surface coarseness of the banknotes. With these robust features, Support Vector Machines (SVMs) is employed for classification. In order to evaluate the performance of proposed technique, experimentations are performed on a self-constructed dataset of Pakistani banknotes, comprised of 195 currency images, including 35 counterfeit banknotes. The results confirm that proposed system achieves 98.57% verification ability on properly captured images.
The Golden Age of Software Engineering [From the Editor]

Presents the introductory editorial for this issue of the publication.
Multi-Classification and Automatic Text Summarization of Kannada News Articles

Kannada is a historical language with abundant resources which display the tradition and culture of Karnataka.Extraction of most important and meaningful information from one or more large documents of text in the form of summary is a challenging task in regional languages compared to English.The main objective of present paper is to get the automatic summary of news articles from several sources.Naive-Bayes algorithm is used for classification of different categories of news articles include sports, politics and general.To find the sub-categories from each category such as state, national and international a Rock clustering algorithm has been used and the summary have been extracted automatically.Data is collected from multiple sources of summarization.A word vectorising stemmer approach is used to reduce the morphological complexity of the resources and a sub-sampling approach is used for efficient optimization and to reduce the complexity
La monografia ad accesso aperto e gli sviluppi dell'Open Access

The Open Access Book (OAB) is a product of the research that in recent years has gained its place in scientific publishing and Open Access (OA). Both have gone from initial diffidence (for different reasons) to a growing interest. In the first part of the article we present the most recent data relating to this type of publication (published ebooks, number of publishers, etc.) while in the second part the OAB phenomenon is examined within a more general evolution of the OA.
Industrial Memories: Exploring the Findings of Government Inquiries with Neural Word Embedding and Machine Learning

We present a text mining system to support the exploration of large volumes of text detailing the findings of government inquiries. Despite their historical significance and potential societal impact, key findings of inquiries are often hidden within lengthy documents and remain inaccessible to the general public. We transform the findings of the Irish government’s inquiry into industrial schools and through the use of word embedding, text classification and visualization, present an interactive web-based platform that enables the exploration of the text to uncover new historical insights. Code related to this paper is available at: https://industrialmemories.ucd.ie .
Justification of bioactivated grain triticale use in alcohol production

Triticale accounts for the biggest share in gross processing and state procurement of grain in Belarussian production of alcohol. The main difficulty in its processing is the formation of viscous technological fluids due to the presence of non-starch polysaccharides in its chemical composition. All measures taken to solve the problem come down to the selection of the efficient enzyme preparations, hydrolyzing grain polymers into low molecular weight compounds, which have the ability to be disposed by the yeast cells and form the ethyl alcohol. But grain own enzymes are not involved. It is possible to solve the problem by means of biological activation, which will activate grain enzyme systems and partially hydrolyze grain polymers into low molecular weight compounds. The article considers general and special technological parameters of six cultivars of triticale selected in the Republic of Belarus: Antos, Kastus, Dubrava, Run, Prometheus, Impulse. The authors determined that the most promising cultivars for bioactivation and food grade ethyl alcohol production are Antos and Dubrava. The authors explored the possibility of using hot soaking of triticale grain for the biological activation. They also showed the advantages of introduction of amaranth green mass in the amount of 8% during hot soaking for the reduction of grain microbiological contamination. They studied the changes in the technological properties of triticale cultivars Antos and Dubrava after the bioactivation with the green mass of amaranth. The authors determined that grain microbiological characteristics improved, the activity of grain enzymes increased, proportion of low molecular weight compounds in the chemical composition increased. They studied the processes taking place during wort and mash production from the bioactivated triticale grain. The authors showed that the processing of bioactivated triticale grain resulted in the production of wort with higher concentration of dry matter which allowed to increase the ethanol content in the mature mash produced from triticale cultivar Antos by 19.5% and from the triticale cultivar Dubrava by 29.3% and reduce the total quantity of the main impurities in distillates.