Reviewerly/exHarmony huggingface dataset:
Abstraction Based Bengali Text Summarization Using Bi-directional Attentive Recurrent Neural Networks

Summarizing text is recognized as a vital problem in the field of deep learning and natural language processing (NLP). The entire process of text summarization is proved to be critical in correct and quickly summarizing massive texts, something which could be not only time consuming but also expensive if it is done without the help of machines. We intended to make a model that will be able to generate fluent, effective human likely summarized Bengali text. We built the model with the help of bi-directional RNNs with LSTM cells at the encoding layer and in the decoder layer. We used the attention mechanism for an appropriate result. We followed the structure of sequence-to-sequence model which is mostly used in machine translation. We also used a word embedding file that was pre-trained and specially created for Bengali NLP researches. We tried to keep the entire train loss as low as possible and build a useful and most human likely text summarizer. After the entire experiment, our model can predict quite meaningful and fluent text summaries with a training loss of 0.007.
High-dimensional Private Quantum Channels and Regular Polytopes

As the quantum analog of the classical one-time pad, the private quantum channel (PQC) plays a fundamental role in the construction of the maximally mixed state (from any input quantum state), which is very useful for studying secure quantum communications and quantum channel capacity problems. However, the undoubted existence of a relation between the geometric shape of regular polytopes and private quantum channels in the higher dimension has not yet been reported. Recently, it was shown that a one-to-one correspondence exists between single-qubit PQCs and three-dimensional regular polytopes (i.e., regular polyhedra). In this paper, we highlight these connections by exploiting two strategies known as a generalized Gell-Mann matrix and modified quantum Fourier transform. More precisely, we explore the explicit relationship between PQCs over a qutrit system (i.e., a three-level quantum state) and regular 4-polytope. Finally, we attempt to devise a formula for connections on higher dimensional cases.
JECL: Joint Embedding and Cluster Learning for Image-Text Pairs

We propose JECL, a method for clustering image-caption pairs by training parallel encoders with regularized clustering and alignment objectives, simultaneously learning both representations and cluster assignments. These image-caption pairs arise frequently in high-value applications where structured training data is expensive to produce, but free-text descriptions are common. JECL trains by minimizing the Kullback-Leibler divergence between the distribution of the images and text to that of a combined joint target distribution and optimizing the Jensen-Shannon divergence between the soft cluster assignments of the images and text. Regularizers are also applied to JECL to prevent trivial solutions. Experiments show that JECL outperforms both single-view and multi-view methods on large benchmark image-caption datasets, and is remarkably robust to missing captions and varying data sizes.
Creating a Disaster Chain Diagram from Japanese Newspaper Articles Using Mechanical Methods

A new method for creating a chain diagram of events that occur during disasters by extracting causal knowledge from Japanese newspaper articles and designing a causal network is proposed herein. Machine learning discriminant models were created for both conventional cue phrases and succession expressions with causation to extract causal sentences. We found that causal sentences can be extracted with a certain degree of accuracy from disaster articles. We were also able to create a causal network using sentences as nodes and links. The chain diagram using our new method extracted events and causal knowledge that were unavailable in a disaster chain diagram designed using conventional methods.
High-speed face measurement system based on near-infrared fringe projection

Fringe Projection Profiler (FPP) is one of the most popular optical non-contact three-dimensional (3D) shape measurement technologies and a research hotspot in 3D face recognition. However, due to the use of a digital light projector (DLP), high-speed, low-cost, and small-size face measurement is still a big challenge. In this article, we developed a high-speed 3D face measurement system based on near-infrared, and proposed using a projection module to replace DLP for projection. Through the accuracy experiment, the measurement accuracy of this system is better than 0.15mm. Experiments on real faces show that this method can collect 3D face data at a lower cost and at a higher speed, and meet the requirements of the field of 3D face recognition.
DeepBlockShield: Blockchain Agent-Based Secured Clinical Data Management Model from the Deep Web Environment

With the growth of artificial intelligence in healthcare and biomedical research, many researchers are interested in large amounts of data in hospitals and medical research centers. Then the need for remote medicine services and clinical data utilization are expanding. However, since the misuse and abuse of clinical data causes serious problems, the scope of its use is bound to have a limited range physically and logically. Then a security-enhanced data distribution system for medical deep web environments. Therefore, in this paper, we propose a blockchain-based clinical data management model named DeepBlockshield to prevent information leakage between the deep web and the surface web. Blockchain supports data integrity and user validation to support data sharing in closed networks. Meanwhile, the agent performs integrity verification between the blockchain and the deep web and strengthens the security between the surface web and the deep web. DeepBlockShield verifies the user’s validity through the records of the deep web and blockchain. Furthermore, we wrap the results analyzed by the valid request into a web interface and provide information to the requester asynchronously. In the experiment, the block generation cycle and size on the delay time was analyzed for verifying the stability of the blockchain network. As a result, it showed that the proposed approach guarantees the integrity and availability of clinical data in the deep web environment.
Decoherence in quantum cavities: Environmental erasure of carpet-type structures

The interaction with an environment provokes decoherence in quantum systems, which gradually suppresses their capability to display interference traits. Hence carpet-type structures, which arise after the release of a localized state inside a quantum cavity, constitute an ideal laboratory to study and analyze the robustness of the interference process that underlies this phenomenon against the harmful effects of decoherence. Such a released localized state may represent a radiation mode inserted into a multimode interference device or a cold-atom system released in an optical trap, for instance. Here, without losing any generality, for simplicity, the case of a particle with a mass $m$ is considered and described by a localized state corresponding to the ground state of a square box of width $w$, which is released inside a wider cavity (with a width $L&gt;w$). The effects of decoherence are then numerically investigated by means of a simple dynamical model that captures the essential features of the phenomenon under Markovian conditions, leaving aside extra complications associated with a more detailed dynamical description of the system-environment interaction. As it is shown, this model takes into account and reproduces the fact that decoherence effects are stronger as energy levels become more separated (in energy), which translates into a progressive collapse of the energy density matrix to its main diagonal. However, because energy dissipation is not considered, an analogous behavior is not observed in the position representation, where a proper spatial localization of the probability density does not take place, but rather a delocalized distribution. This result emphasizes the fact that classicality is reached only if both decoherence and dissipation coexist; otherwise, nonclassical traits might still persist. Actually, as it is also shown, in the position representation some off-diagonal correlations indeed survive unless an additional spatial-type factor is included in the model. This makes evident the rather complex nature of the decoherence phenomenon and hence the importance to have a familiarity with how it manifests in different representations, particularly with the purpose to determine and design reliable control mechanisms.
Digital educational resources for English language studies: teachers and learners’ attitude

The introduction of electronic educational content optimizes and facilitates the learning process. This attitudinal study aims to investigate the relation of English teachers and students of the Russian universities (pointed out below) towards digital educational recourses and their usage in the context of foreign language learning. In general, it enables the authors to gather the information about popularity of digital educational recourses for English language learning in order to identify: 1) for what purposes and which digital education recourses are mainly used by English language teachers and whether they manage to achieve the planned result; 2) which resources are of the students’ greatest interest and what is the base of their choice; 3) weather the students are satisfied with the introduction of digital education recourses in the educational process in general and in the ELT in particular. The study is based on the analysis of the results of the questioning. Participants of the study were school and university teachers and students from Universities of Moscow and Moscow region. The findings of the study showed that there is no significant difference between educators and students’ attitudes towards digital education resources. The most participants both teachers and students consider them increasing the effectiveness of learning English. Some of the recourses are popular with both groups of respondents while others have been adopted by one group and easy accessed to the process of language learning.
ContextLabeler dataset: Physical and virtual sensors data collected from smartphone usage in-the-wild

This paper describes a data collection campaign and the resulting dataset derived from smartphone sensors characterizing the daily life activities of 3 volunteers in a period of two weeks. The dataset is released as a collection of CSV files containing more than 45K data samples, where each sample is composed by 1332 features related to a heterogeneous set of physical and virtual sensors, including motion sensors, running applications, devices in proximity, and weather conditions. Moreover, each data sample is associated with a ground truth label that describes the user activity and the situation in which she was involved during the sensing experiment (e.g., working, at restaurant, and doing sport activity). To avoid introducing any bias during the data collection, we performed the sensing experiment in-the-wild, that is, by using the volunteers' devices, and without defining any constraint related to the user's behavior. For this reason, the collected dataset represents a useful source of real data to both define and evaluate a broad set of novel context-aware solutions (both algorithms and protocols) that aim to adapt their behavior according to the changes in the user's situation in a mobile environment.
Database Creation for Marathi QA System

The use of the internet has grown extremely over the last two decades, resulting in the proliferation of massive volumes of data on the internet. Since there is so much data available online, researchers are interested in the Question Answering era, in which users ask questions and obtain correct answers. A classic NLP programme is answering questions although work on some Indian regional languages, such as Tamil, Punjabi, Hindi, Malayalam, and Bengali, is ongoing; there is little work available for Question Answering (QA) Systems in Marathi. The construction of a text corpus, question generation, and question classification for a Marathi question answering method were the key topics of this paper.
MODERN METHODS OF TESTING AND INFORMATION SECURITY PROBLEMS IN IoT

This article analyzes the technology of the internet of things, ie its architecture, communication standards, threats to security and safety, methods and types of testing devices of the internet of things. In short, the architectures proposed by ITU-T and IWF, IEEE standards for Internet of Things, LPWAN standards, four levels of security (devices/gateways, network/transport, services and applications), components according to test methods, performance, loading, security, etc.
Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis

Genomic analysis and digitalization of medical records have led to a big data scenario within hematopathology. Artificial intelligence and machine learning tools are increasingly used to integrate clinical, histopathological, and genomic data in lymphoid neoplasms. In this study, we identified global trends, cognitive, and social framework of this field from 1990 to 2020. Metadata were obtained from the Clarivate Analytics Web of Science database in January 2021. A total of 525 documents were assessed by document type, research areas, source titles, organizations, and countries. SciMAT and VOSviewer package were used to perform scientific mapping analysis. Geographical distribution showed the USA and People's Republic of China as the most productive countries, reporting up to 190 (36.19%) of all documents. A third-degree polynomic equation predicts that future global production in this area will be three-fold the current number, near 2031. Thematically, current research is focused on the integration of digital image analysis and genomic sequencing in Non-Hodgkin lymphomas, prediction of chemotherapy response and validation of new prognostic models. These findings can serve pathology departments to depict future clinical and research avenues, but also, public institutions and administrations to promote synergies and optimize funding allocation.
Cryptocurrency and Privacy: Economic Analysis of Law

The dynamic technology junction of Cryptocurrency and Privacy pose several implications to the existing economic and legal regulations. The present work intends to take up an economic analysis of the laws relating to Cryptocurrency in the context of Privacy. The concept of money and development of fiat currency with role of banking industry leads one to understand the background of Cryptocurrency basis, therefore a segment on the historic perspective of money, development of fiat money and role of banking industry as an intermediary are added in the present work. The technology of Blockchain used in Cryptocurrency transaction transmits the existing monetary regulations across the globe thereby challenging the financial systems. The economics of Cryptocurrency has generated sufficient interest and the present work surveys such interest.The most comprehensive regulation on Privacy and Data protection having a global impact is the European Union’s General Data Protection Regulation (EUGDP), which took effect in May 2018. The EUGDP Regulations by giving much needed importance and protection to the individual’s data privacy and security have altered the functionality of the Data driven companies such as Facebook, Google and others. The work takes a brief note of issues such as data controller and data processor identification, territorial and cross-border data transfer issues, legitimate bases for processing personal data and individual’s privacy rights as some of necessary compliance under the EUGDP Regulations that interact with the blockchain technology used under Cryptocurrency transactions. The conclusion suggests the need for economic analysis of laws relating to Cryptocurrency and Privacy for their intrinsic economic value.
Design and deployment of relational geodatabase on mobile GIS platform for real-time COVID-19 contact tracing in Ghana

This study reviewed the design and deployment of relational geodatabase on mobile GIS application, using collector for ArcGIS and survey 123 for ArcGIS platforms for COVID-19 contact tracing in Ghana during the lockdown. The study assessed whether cases spread by physical neighborhood contacts, defined by a 2km buffer of initial known 60 cases location. The application was deployed on the android tablet, which was used by field workers. Application Post-deployment review shows that from 30th March to 4th April 2020, 828 samples were collected with 34 confirmed cases, of which 61% occurred outside the 2km buffer. From 1-30 April 2020, 8,748 individuals with 16,087 contacts were tested within the physical neighbourhoods, 2.4% turned positive. Similarly, 7,501 individuals with 17,071 contacts were tested outside the physical neighbourhoods with 4.3% positives. Results suggest that more infections occurred outside the case’s physical neighbourhoods possibly due to; (1) existence of unknown cases prior to lockdown; (2) cases were moving outside their physical neighborhood and infecting others; (3) panic movements of cases within the 3 days window between announcement and enforcement of lockdown; (4) movement of cases into the country through unapproved routes. New cases were identified outside the lockdown areas, which could not be explained. This study raises questions about (1) the understanding of the mode of spread of the virus (2) the implementation of the lockdown, including the geographic coverage and timing. It is recommended that future decisions on contact tracing and lockdown should be guided by an understanding of the disease geography.
Extraction of isomorphic subformulas as a tool for logic ontology construction

Abstract A way of constructing a logic ontology for complex structured objects is considered in the paper. The descriptions of such objects are given in the predicate calculus language. An algorithm for extracting subsets of objects with the same properties and establishing their relative position is described. To construct such an ontology, an algorithm for extracting the largest subformula isomorphic to subformulas of all descriptions of objects from the class is used.
Blockchain and the Common Good Reimagined

Blockchain, Smart Contracts and Distributed Ledger Technology (DLT) are being touted to revolutionise digital services - through decentralisation. Cryptocurrencies, self-sovereign identities, decentralised certificate registries, and transparent voting systems are but a few applications which promise to empower endusers and provide assurances that neither data nor the associated computational logic have been tampered with. Decentralisation, disintermediation, transparency, verifiability, auditability, openness, inclusion, tamper-proof, immutability are just some of the buzz words that continue to be swung around in the promotion of the benefits brought about by Blockchain-based systems to the users. The rhetoric used creates parallels between the features brought about through blockchains and values that many try to uphold, for example honesty, openness, transparency, teamwork and unchanging truth. In this paper a number of blockchain applications aimed at supporting initiatives for common good are highlighted. This is followed by a discussion on technology decentralisation and a thought experiment used to raise questions regarding the use of decentralised technology in terms of social implications.
Encoding the information in relative parameters

We investigate the problem of communicating three parameters in the absence of shared reference frame. We explore two methods in which the relative angles of spins are used to encode the parameters. In the first method we use three spins that carry the information in their relative angles while in the second method we use three disjoint spin-pairs and the information is sent through the relative angles of each individual pair. We show that in the first method, the information conveyed by each qubit is more than the second one, and that is while it requires fewer particles.
Educación Física Interdisciplinaria ecuatoriana en el contexto dela covid-19

The Ecuadorian educational policy in the face of the healthemergency caused by covid-19, proposed the prioritization of content in all curriculabyareas and the application of project-basedlearning as a methodological alternative forremote education. The purpose of this research is to offer a proposal for the design of a Physical Education learning objective oriented to interdisciplinary built from the evaluation criteria of the disciplinary areas. Them et hod used was the phenomenological-hermeneutic one, two techniques were applied: the bibliographic review of documents and scientific articles from the platforms of the Ministry of Education of Ecuador and the Academic Google, with which the proposal could be partially founded; and the interview with 15 Physical Education teachers from various educational institutions in the city of Quito, whose instrument was validated by the judgment of seven experts, this information complements the justification of the proposal. The proposal to develop the projects based on the evaluation criteria of the disciplinary areas, combined in the interdisciplinary, will serve the teachers as an input for proposing interdisciplinary micro curricular learning objectives, leaving in view of the problems to be solved for each grade, established in the Emergency Prioritized Curriculum, all with the vision of directing students towards autonomy o learning.
Implementation of Contextual Based Teaching Materials on Various Work Themes of Primary School Students

This study aimed to analyze the hypothetical model and analyze the effectiveness of the use of teaching materials. The research design used in this study is research and development. The study was conducted in elementary schools in the District Diponegoro Force Gringsing Batang with research subjects fourth-grade learners at three elementary schools SDN Yosorejo, SDN Krengseng 2, and SDN Sidorejo 1. Sources of research data derived from the expert of experts, education professionals, and learners, The data collection method used measurement scales and tests. Teaching materials developed using seven syntax contextual learning model that integrates seamlessly with the theme of learning various jobs. The results of product validation by expert gets an average value of 3.34 with a percentage of 83.58%. It shows that the product of teaching materials in this study deserves to be tested further. The results showed that an increase in outcomes after using the instructional materials with N-Gain test results on a limited scale trial of 0.55 with category and 0.50 on the results of the use of teaching materials are also categorized as moderate.