Reviewerly/exHarmony huggingface dataset:
Hg- and Cd-bearing Pd, Pt, Au, AND Ag minerals in sulfide-bearing mafic and ultramafic rocks of the Yoko-Dovyren intrusion in the baikalides of the Northern Baikal area

Hg and Cd are rare chemical elements found in magmatic PGE and Au mineralization and typical of this mineralization in the Late Riphean Yoko-Dovyren plagioperidotite–troctolite–gabbronorite intrusion hosted in the Baikalides of the Baikal area. The paper discusses variations in the composition, associations, and distribution traits of the Hg- and Cd-bearing Pt, Pd, Au, and Ag minerals. Many of the precious-metal minerals are Pt, Pd, and Au chalcogenides and intermetallic compounds of postmagmatic genesis and occur as single crystals and stringers in sulfides and silicate matrix and at their contacts. The minerals were formed with the participation of fluids from the crystallizing Cu–Fe–Ni sulfide melts. They are constrained to the central part of the intrusion and found in sulfide-bearing plagiolherzolite (PL) in the lower part of the intrusion, in sulfide-bearing pegmatoid troctolite (T) in the bottom portion of the troctolite unit, and in sulfide-bearing pegmatoid anorthosite (A) in the top part of the troctolite unit. From PL to T and further to A, the content and diversity of the Hg-bearing minerals remarkably increase, with Hg distributed in these minerals very unevenly, and with Cd-bearing minerals identified only in A. The leading Hg concentrators in T and A are pneumatolytic (fluid–metasomatic) moncheite and, particularly, later telargpalite (Pd,Ag)3(Te,Pd,Hg), which contains up to 11 wt % Hg. The latter mineral is sometimes found in association with Hg-electrum, kustelite, and potarite. Potarite in T is Pb-rich, and this mineral in A is Pb-free. Appreciable Hg concentrations in precious-metal minerals in the Yoko-Dovyren intrusion suggest that these minerals crystallized in a closed system at high temperatures. Potarite content in A is much higher, and Hg concentration in telargpalite in A is notably lower (2.9 wt % Hg on average) than in this mineral in T (5.9 wt % Hg on average). The potarite might have been produced by epigenetic serpentinization processes (low-grade metamorphism) at the expense of the material of pneumatolytic Hg-bearing telatgpalite, kotulskite, and zvyagentsivite. This corresponds to specifics in Hg distribution in the telatgpalite, kotulskite, and zvyagentsivite in T and A and much higher intensity of metamorphism.
Quantum surfing

Abstract Here we report a project in which time-dependent supersymmetry has been employed to derive a new potential and eigenfunctions that satisfy the Schrödinger equation. The supersymmetry method is outlined and we apply it to a wavefunction obeying the free-particle Schrödinger equation. This leads to an exactly soluble model in which a quantum particle is seen to ‘surf’ on a time-dependent potential. The model can be solved and understood within both classical and quantum mechanics and the relationship between the two approaches is discussed. The mathematics of this formalism is accessible to a final year British undergraduate making supersymmetry derived Hamiltonians suitable as a final year theoretical physics research project.
A Visual Cryptographic Technique for Transferring Secret Image in Public Cloud

The use of “Asymmetric Cryptography” provides the way to avail the feature of non-repudiation, encryption of data and defining the user digital identity to map with the authenticating user in the Public Cloud. A security technique is to be provided for the data even before it is stored on the Cloud. The public key certificate can be transferred into key server for encrypting the data by other users or devices in the public cloud. By using OpenPGP standard (PGP)/GNU Privacy Guard (GnuPG), public key certificate and the private key certificate can be generated by the user in the client system itself. The client private key can never be moved out from the client system and users only responsibility is to decrypt their data like images. This methodology will be very much suitable for authenticating, transferring, accessing and storing the images in the Public Cloud. The computational cost for encrypting the whole image with public key will be huge and so the hybrid methodology is proposed with visual cryptography technique and Elliptic-Curve Diffie–Hellman (ECDH) methodology. This paper proposes secure transfer of secret image by using visual cryptography technique and thereby modifying any one of the visual shares into encrypted data with ECDH secret key and finally converted those two shares into base64 format. The proposed algorithm is implemented by using the Python language and their results are discussed with sample images.
A fuzzy inference-based trust model estimation system for service selection in cloud computing

Cloud computing assures to be the fundamental changeover in the evolution of the computing world. The cloud computing helps the users to have no Capex, which is making a lot of businesses and individuals to it. Many services are provided by the cloud, for users to meet their application's functional as well as non-functional. Due to the vast number of available services, ambiguous requirements, security and trust measures and efficiency provided by different cloud providers, it is often difficult for the users to select the cloud services. This paper proposes a system that assesses trust of cloud services by providers using a fuzzy-based inference system for selecting the services dynamically.
Reversible data hiding scheme based on the AMBTC compression technique and Huffman coding

This paper proposes a reversible data hiding (RDH) method based on the absolute moment block truncation coding (AMBTC) compression technique and Huffman coding. First, AMBTC is used to compress the original greyscale image to obtain two quantisation levels and a bitmap of each block. Next, the bitmap of each block is converted into a decimal number to calculate the frequency of the decimal number. A user-defined threshold is used to classify the block as embeddable or not. If the frequency of the decimal number is larger than or equal to the threshold, the bitmap is embeddable and is then compressed by the Huffman coding technology. The scheme takes the redundancy of each block by using the Huffman code instead of the bitmap to embed secret information. Experimental results show that our proposed scheme has a better hiding payload than other methods, as well as an acceptable image visual quality.
A Linked-Data Method to Organize an XML Database for Mathematics Education

This paper presents work in progress to support fine-grained semantic relationships between mathematical concepts and educational resources. Can RDF ontologies and XML structure support a high-capacity database application for lesson planning, teaching, assessment, and tutoring?
Are You AI’S Favourite? EU Legal Implications of Biased AI Systems in Clinical Genetics and Genomics

The article provides a legal overview of biased AI systems in clinical genetics and genomics. For the overview, two perspectives to look at bias are taken into consideration: societal and statistical. The paper explores how biases can be defined in these two perspectives and how generally they can be classified. Based on two perspectives, the paper explores three negative consequences of biases in AI systems: discrimination and stigmatization (as the more societal concepts) and inaccuracy of AI’s decisions (more related to the statistical perception of bias). Each of these consequences is analyzed within the frameworks they correspond to. Recognizing inaccuracy as harm caused by biased AI systems is one of the most important contributions of the article. It is argued that once identified, bias in an AI system indicates possible inaccuracy in its outcomes. The article demonstrates it through the analysis of the medical devices framework: if it is applicable to AI applications used in genomics and genetics, how it defines bias, and what are the requirements to prevent them. The paper also looks at how this framework can work together with anti-discrimination and stigmatization rules, especially in the light of the upcoming general legal framework on AI. The authors conclude that all the frameworks shall be considered for fighting against bias in AI systems because they reflect different approaches to the nature of bias and thus provide a broader range of mechanisms to prevent or minimize them.
Computer-Based Test Application to Support E-Learning in Pandemic Situation

The use of information technology in education is a new breakthrough. During the current COVID-19 pandemic, many teaching and learning activities are carried out online using the internet in the form of e-learning. one important part of e-learning is the test. Computer based test (CBT) can be implemented in schools that should be accessed by students from remote places. Computer-based test applications can be used as a complement to online learning by utilizing the web technology. Web-based applications allows access by students with an internet connection using PC/Laptop or other mobile devices. In addition, implementation costs can be saved because paperless. Computer-based test applications also make it easier for teachers to grade the answer where the application can automatically provide the score instantly when students finish the test. In this study, the application was built using the web technology that run from various devices and platforms. Access applications can be designed for local network use (intranet) or online by hosting the application on a webserver. The application development uses a system development life cycle approach using PHP-MySQL technology.&#x0D; &#x0D; Keyword : CBT, computer base test, PHP-MySQL, webapps.
A survey on contrastive opinion summarisation

Contrastive opinion summarisation (COS) is jointly generating summaries for two entities in order to highlight their differences based on the features. COS comprises of feature extraction, Sentiment prediction and summarisation. Recently, the research focus in COS has been in using semantics associated with words and multi-word expressions to shift from syntactic to semantic level. This survey paper covers different methods used for feature extraction, various similarity measures and different types of summarisation. In addition to these, various datasets and performance measures are also addressed. Finally, future research directions are also suggested.
k-MACE Clustering for Gaussian Clusters

&lt;p&gt;Conventional clustering approaches require a preprocessing step that estimates the correct number of cluster prior to the cluster center allocation step. In these approaches, the preprocessing step minimizes one objective function while the second step concentrates on optimization of another objective function. Inspired by MACE-means, we use a single objective function to simultaneously estimate the Correct Number of Cluster (CNC) and acquire the cluster centers. Similarly, we use the Average Central Error (ACE) as ourcost function. The proposed method, denoted by k-minimum ACE (k-MACE), improves MACE-means by rigorous calculation of probabilistic estimate of ACE. While MACE-means (Minimum ACE) only concentrates on Independent Indentically Distributed (IID) clusters, k 􀀀 MACE is a solution for Gaussian clusters with any covariance structure. Simulation results show superiority of k 􀀀 MACE over MACE means and over conven- tional clustering methods such as G-means, DBSCAN, and validity indices methods such as Calinkski Harabaz, Silhoutte, and gap index. Performance is evaluated in terms of&lt;/p&gt;
MPEG column: 127th MPEG meeting in Gothenburg, Sweden

The original blog post can be found at the Bitmovin Techblog and has been modified/updated here to focus on and highlight research aspects.
A STUDY ON REGISTER USED IN BUSINESS PLATFORMS IN SOCIAL MEDIA

The language used for daily conversation is different from the language used in online conversation for a business. For business, usually different set of language is used. Language has a function in media. Certain communities use a language varietyas Register that has a specific meaning. It is used in certain purposes for occupation.Most of the formal language used in online business is in English language. Communication situation enhances to improve similar intonation and vocabulary used in a situation called as register.This research aims in finding different register used in online business platforms. Different formal words and phrases are collected from social media platforms of online business. The different formal words used in online shopping platforms are collected from comment section, reviews, seller reviews, and questions and answer area of e-commerce websites and their social media platforms, by identifying repeated words and phrases.
Harmony

This chapter explores the harmonic resources of the instrument and builds upon the fingerboard harmony material in chapter 1. Playing homophonic textures on the guitar creates problems of smoothness and connection. Fernando Sor recognized this and provided rests between chords in his Op. 35, No. 11 and Op. 31, No. 20. Two arpeggio pieces of special harmonic interest are also included. This chapter challenges the widely accepted instruction that recommends the placing of all the left-hand fingers that are to form a chord <italic>at the same time</italic>, whether or not the notes of the chord are arpeggiated or struck simultaneously. This advice, repeated in almost every guitar method since the early 19th century, accounts for one of the reasons guitarists have difficulty performing convincing legato phrasing. The chapter presents alternative advice, the reasons behind it, and exercises to help develop this technical and artistic refinement.
Creative Lab: Learning Vocabulary in Elementary School

The article deals with the problem of the development of creative thinking of younger schoolchildren. The features of educational creative tasks and ways of their use when learning vocabulary in primary school are discussed. The potential of the lessons of the Russian language for the formation of students’ cognitive activity and their needs for creative authoring activities are revealed.
Enhancing the Security in ElGamal Cryptosystem using Paring Functions

The potential disadvantage of ElGamal cryptosystem is the ciphertext produced is always twice as long as the plaintext i.e., the message expansion by a factor of two takes place during encryption. When the message is too long the ciphertext produced by the ElGamal cryptosystem is also too long. i.e., when the ciphertexts are transmitted through the communication channel which lead to provide less security because if anyone of the ciphertext from two ciphertexts for each character of the plaintext is intercepted by the adversary, the other may be retrieved easily because there is a relationship between the two ciphertexts. If two ciphertexts are reduced to one, the adversary may not be able to predict the two ciphertexts from one. To enhance the security of ElGamal cryptosystem, the binary Cantor function , Rosenberg pairing function and Elegant pairing functions are used in this paper. When the said functions are used, the two ciphertexts produced by each plaintext character are reduced to one, so that the adversary cannot easily be recovered the plaintext. Experimental results clearly revealed enhancing the security of ElGamal cryptosystem after incorporating the pairing functions into it.
Sense of Presence and Learning Satisfaction among Students of Different Age Groups in a 3-D Virtual World

<p class='IJASEITAbtract'>Virtual worlds are growing in popularity very quickly. This growing popularity of 3-dimensional (3-D) virtual worlds has drawn attention from educationists. Today, 3-dimensional (3-D) virtual worlds are exploited for online and virtual learning. Unlike the common online learning platforms, a virtual world environment closely resembles a 3-D video games environment. Thus the age of students might affect their sense of presence, interaction, and satisfaction in the said environment. Hence this study was conducted to investigate whether there are differences between students of different age groups on their sense of presence (place presence, social presence, and co-presence) and their learning satisfaction. The study was carried out for six weeks and involved 33 part-time diploma students with the use of interview and questionnaires as instruments. In this study, the researcher developed our own 3-D virtual world, known as ViEW, by using the Open Wonderland open source virtual world program. A nonparametric Mann-Whitney U analysis was applied to explore the differences between young and senior participants in terms of their sense of place presence, social presence, co-presence, and learning satisfaction. The results indicated significant differences between young and senior students in terms of place presence, co-presence, and learning satisfaction, but no differences were identified for social presence. These results might be in regard with the means of conducted the learning, which were in the forms of cooperative and synchronous learning by utilizing audio communication most of the time. Several recommendations for future research related to the study were also provided.
An Amalgamated Probabilistic Structure for Unconstrained Facial Activity Utilizing Dynamic Bayesian Network

Outward appearance was a characteristic and incredible method for human correspondence. Perceiving unconstrained facial activities in any case, is trying because of unpretentious facial miss happening, visit head developments and vague and unsure facial movement estimation. In light of these difficulties, ebb and flow look into in outward appearance acknowledgment is restricted to presented articulations and frequently in frontal view. An unconstrained outward appearance is described by inflexible head developments and non-rigid facial strong developments. All the more critically, it is the intelligible and steady spatiotemporal collaborations among unbending and non-rigid facial movements that produce an important outward appearance. Perceiving this reality, we present a bound together probabilistic facial activity model dependent on the Dynamic Bayesian system (DBN) to all the while and intelligibly speak to unbending and non-rigid facial movements, their spatiotemporal conditions, and their picture estimations. Propelled AI techniques are acquainted with gain proficiency with the model dependent on both preparing information and emotional earlier information. Given the model and the estimations of facial movements, facial activity acknowledgment is practiced through probabilistic surmising by deliberately incorporating visual estimations with the facial activity model. Analyses show that contrasted with the best in class strategies, the proposed framework yields huge enhancements in perceiving both inflexible and non-rigid facial movements, particularly for unconstrained outward appearances.
Quantum tomograph for measurement and characterization of quantum states of biphoton sources

The method and prototype of a device for characterizing of biphoton light sources based on spontaneous parametric downdonversion by quantum tomography are described. The prototype is an experimental implementation of a specialized quantum tomograph designed to measure the quantum polarization states of radiation generated by biphoton sources. Specially developed software will determine the statistical characteristics of the measured quantum state, calculate the tomographic and likelihood estimations of the density matrix, calculate the measurement errors of the density matrix elements and evaluate the quality of the quantum state of biphotons.
A cloud-based near real-time slope movement monitoring system

A cloud-based near real-time data management system for geotechnical monitoring that can efficiently record, transfer, store, manage, process, analyse and evaluate monitoring data and generate easy to view and use information is presented. The database structure and manual of the system functionalities for addressing issues during data upload and processing, record handling for multisensory devices, data visualisation using common reference dates, data error correction and parametric handling of import files are presented in detail. New features that are in development include a more robust warning system and a journaling system for visual observations. The system can reliably and quickly generate alarms and information about excessive movements with respect to mining and other operations that require monitoring.
Enhanced H-ABE-R and T-ABKS for cloud computing environment

For a data owner (patient) wants to share his health data, data which is extremely sensitive in nature and when he wishes to maintain privacy it is common for data owners to encrypt the data. Sharing encrypted data leads to difficulties in key management (traditional PKI infrastructure). In the first half of our work, we propose an novel attribute-based encryption, a further extension of identity-based encryption that allows roles or policies to be defined over a set of attributes and propose a hybrid attribute-based encryption - with revocation (H-ABE-R) which is more suitable for multi-user hospital settings as it allows us to give permissions to access data for short periods of time. We then propose a time and attribute-based keyword search (T- ABKS). We check our algorithm and prove our scheme comparably efficient.
Recognising continuous emotions in dialogues based on DISfluencies and non-verbal vocalisation features for a safer network environment

With the development of networks and social media, audio and video have become a more popular way to communicate. Those audio and video can spread information to create some negative effect, e.g., negative sentiment with suicide tendency or threatening messages to make people panic. In order to keep a safe network environment, it is necessary to recognise emotion in dialogues. To improve recognition of continuous emotion in dialogues, we propose to combine DISfluencies and non-verbal vocalisations (DIS-NV) features with bidirectional long short-term memory (BLSTM) model to predict continuous emotion. DIS-NV features are effective emotion features, including filled pauses features, fillers features, shutters features, laughter feature and breath feature. Bidirectional long short-term memory (BLSTM) can learn past information and use future information. State-of-the-art recognition attains 62% accuracy. Our experimental method can increase accuracy to 76%.