Reviewerly/exHarmony huggingface dataset:
Deep Adaptive Attention Triple Hashing

Recent studies have verified that learning compact hash codes can facilitate big data retrieval processing. In particular, learning the deep hash function can greatly improve the retrieval performance. However, the existing deep supervised hashing algorithm treats all the samples in the same way, which leads to insufficient learning of difficult samples. Therefore, we cannot obtain the accurate learning of the similarity relation, making it difficult to achieve satisfactory performance. In light of this, this work proposes a deep supervised hashing model, called deep adaptive attention triple hashing (DAATH), which weights the similarity prediction scores of positive and negative samples in the form of triples, thus giving different degrees of attention to different samples. Compared with the traditional triple loss, it places a greater emphasis on the difficult triple, dramatically reducing the redundant calculation. Extensive experiments have been conducted to show that DAAH consistently outperforms the state-of-the-arts, confirmed its the effectiveness.
NFCMF: Noise Filtering and CrossModal Fusion for Multimodal Sentiment Analysis

Multimodal sentiment analysis aims to predict the sentiment of text or video with the help of other modalities, such as acoustic and vision. Most of previous studies mainly focus on learning the joint representation of multiple modalities after coding by RNN-based network and ignore the mischief of noisy modal information to the fusion of multimodal information. Moreover, the multimodal information cannot be effectively fused when it appears asynchronously. To address these limitations, in this paper, we propose a Noise Filtering and CrossModal Fusion network (NFCMF) to better obtain the fusion of multiple modalities. We conduct several experiments on the CMU-MOSI, CMU-MOSEI and YouTube datasets. The competitive experimental results and qualitative analysis demonstrate the effectiveness of our model.
Analysis of SIDH Alghoritm

Modern systems of cryptographic protection of information, which are built on the basis of mathematical transformations in a group of points of elliptic curves are no longer considered a promising area for further development of information security systems. This is due to the emergence of the real quantum computer, which led to the activation of a new stage in the development of cryptosystems, which is conventionally called post-quantum stable cryptographic algorithms.
Multilocation Watermarking Algorithm for Energy Big Data Based on Orthogonal Coding

Grid energy data contains a large amount of user data. How to protect the privacy of user data is a hot issue in related fields today. In order to protect the privacy of energy big data and improve the correctness of watermark embedding, this paper proposes a multi-location watermark embedding algorithm based on orthogonal coding. Based on the analysis of the demand of big data privacy protection in energy internet, the demand response mechanism is calculated, and the multi-location watermarking is embedded in the energy big data text. Experimental results show that the watermark embedding algorithm is correct and the transmission delay is 4ms, which improves the performance of the watermark embedding algorithm.
Balanced DATA by DBSCAN and Weighted Arithmetic Mean to Improve Performance of Machine Learning Algorithms

Improvement of digital technology has caused the collected data sizes to increase at an accelerating rate. The increase in data size comes with new problems such as unbalanced data. If a dataset is unbalanced, the classes are not equally distributed. Therefore, classification of the data causes performance losses since the classification algorithms treat as the datasets are balanced. While the classification favors the majority class, the minority class is often misclassified. The majority of collected datasets, especially medical datasets, have an unbalanced distribution problem. To reduce the unbalance datasets, various studies have been performed in recent years. In general terms, these studies are undersampling, oversampling, or both to balance the datasets. In this study, an oversampling method is proposed employing distance and mean based resampling method to produce synthetic samples. For the resampling process, the distances between pairs are calculated by the Euclidean distance in the minority class. The calculated distances are considered in the sense of DBSCAN to obtain a sufficient amount of pairs. The new synthetic samples were formed between listed pairs by using the Weighted Arithmetic Mean. Thus, the dataset has been approximated 500 (majority) and 535 (from 268 minority data). The Random Forest (RF) and Support Vector Machine (SVM) algorithms are used for classification the raw and balanced datasets, and the results were compared with each other and the other well known methods such as Random Over Sampling (ROS), Random Under Sampling (RUS), and Synthetic Minority Oversampling Technique (SMOTE). The result showed that the proposed method has the best performance among all the listed methods. The accuracy performance of RF is 0.751 and 0.798 for raw data and resampled data respectively. Likewise, the accuracy performance of SVM is 0.762 and 0.781 for raw data and resampled data respectively.
Developing CRMSys at SoftTel: Traditional or agile?

The increasing popularity of agile software development has significantly changed the way organizations plan, design, and implement software applications. However, considering the complexity involved with software development, the decision to choose an agile approach over the traditional waterfall approach is not straightforward. Organizations should carefully evaluate a variety of factors when choosing a development approach. In this teaching case study, the authors provide a discussion case to facilitate the students’ learning of using agile vs. traditional approaches in software development. This case study is developed based on experiences of multiple real-world software development projects and the literature on software development. It is designed to reflect the complexities students are likely to encounter in actual software development projects. The case can be used in undergraduate or graduate level management information systems courses that cover agile software development approaches. Students can gain an understanding of factors to consider when choosing a development approach, which tailors to the organization, the project environment, and the project team.
Statistics in Corpus Linguistics: A New Approach by Sean Wallis. New York/Oxon: Routledge, 2021. ISBN 9781138589384 (PB: 44.95), ISBN 9781138589377 (HB: 160.00), ISBN 9780429491696 (eBook: 44.95), xxvi+382 pages.

Statistics in Corpus Linguistics: A New Approach by Sean Wallis. New York/Oxon: Routledge, 2021. ISBN 9781138589384 (PB: 44.95), ISBN 9781138589377 (HB: 160.00), ISBN 9780429491696 (eBook: 44.95), xxvi+382 pages. - Volume 29 Issue 1
New McEliece Cryptosystem Based on Polar-LDPC Concatenated Codes as a Post-quantum Cryptography

With the increase of computing power of quantum computers, classical cryptography schemes such as RSA and ECC are no longer secure in the era of quantum computers. The Cryptosystem based on coding has the advantage of resisting quantum computing and has a good application prospect in the future. McEliece Public Key Cryptography is a cryptosystem based on coding theory, whose security can be reduced to the decoding problem of general linear codes and can resist quantum attacks. Therefore, this paper proposes a cryptosystem based on the Polar-LDPC Concatenated Codes, which is an improvement on the original McEliece cipher scheme. The main idea is to take the generation matrix of Polar code and LDPC code as the private key, and the product of their hidden generation matrix as the public key. The plain text is encoded by Polar code and LDPC code in turn to obtain the encrypted ciphertext. The decryption process is the corresponding decoding process. Then, the experimental data presented in this paper prove that the proposed scheme can reduce key size and improve security compared with the original McEliece cryptosystem under the condition of selecting appropriate parameters. Moreover, compared with the improvement schemes based on McEliece proposed in recent years, the proposed scheme also has great security advantages.
Creation of a MOOC and an Augmented Reality application on exoplanets for the Exoplanets-A project

Abstract The European Exoplanets-A project aims to provide a comprehensive view of the nature of exoplanet atmospheres, through an interdisciplinary approach. Exoplanets-A includes a knowledge server where we provide the scientific results and educational resources gathered and developed during the project. In this proceedings, we present two such educational resources: a MOOC and an augmented reality application.
Low-Complexity Chroma Subsampling Using Optimal Lines of Subproblems of Pixel Distortion

Video compression is an important procedure for digital applications. A commonly used format for inputs to video coders is YUV420, which is a subsampled result from YUV444, that is transformed and demosaicked from a color filter array (CFA) format. The process of chroma subsampling is a crucial step for the reconstructed image quality. A state-of-the-art method utilizes the solution of a prior method to compute the starting point, and devises a search method to improve the results. However, the search method does not consider the optimality condition of the problem, and the overall computational complexity is high because of the execution of the prior method for the starting point. In the proposed work, the cost function of the optimization problem is analyzed and decomposed into 4 subchannels based on the CFA format. The optimal line of each subterm is studied in 3-dimensional space. The problem is then mathematically reduced to a 3-subchannel problem. Based on the combinations of the optimal lines, a triangle search area is formed and proved to contain the optimal solution. And because the derived triangle search area is small on average, the search for the optimal value can be considerably fast. Experimental results demonstrate that the proposed approach can produce reconstructed images with qualities that are exactly the same as those generated using the state-of-the-art method. Relative to the state-of-the-art method, the proposed approach can reduce the time complexity by 84.08%–84.91%, and reduce the number of search points by 40.24%–85.25%, for the image datasets Kodak and IMAX with different demosaicking methods.
Educational Goals and Achievements of Undergraduate and Graduate Programs of Data Science in Shiga University

Shiga University established the first faculty of data science in Japan in 2017 with the enrollment of 100 students each year. These students obtained their Bachelor′s degrees in March of this year. In 2019 it established the first graduate school of data science and the graduate students obtained the Master′s degree. We discuss educational goals of the undergraduate and the graduate programs and achievements of these programs.
The Need for a Novel Approach to Design Derivation Lexicon for Semitic Languages

Morphology knowledge is relevant in language learning, information retrieval and natural language processing. Derivation lexicons are comprehensive and organized collections of the morphological variants of a language’s vocabulary. These lexicons can be developed through either analysis-based synthesis of large text corpora or synthesis of surface forms from roots, stems, lemmas and morphological rules. Much of the research in developing derivation lexicon for Indo-European languages, which are concatenative, focus on analysis-based synthesis, as they do have well-developed preprocessing tools and organized text corpora. However, the methods for these languages are not appropriate for non-concatenative languages such as Semitic languages. Moreover, most of the Semitic languages, except Arabic and Hebrew, do not have well-developed text corpora and language processing tools. Hence, a novel approach that can cater for the root-pattern and rich morphology of these languages is necessary. This paper is therefore both a comprehensive survey of the literature and an analysis, motivating morphological synthesis approach coupled with a novel architecture with illustration. It is part of a larger project tailored for designing an innovative, generic, approach to derivation lexicon development for Semitic languages.
Research on Blockchain Security Protection

In recent years, with the characteristics of nonforgery, nontampering and traceability, blockchain has changed the way of human social value transmission with a new trust system, and has been deeply integrated with industry applications. Due to the imbalance of security and privacy protection between nodes, however, the security and stability of blockchain system are damaged in the process of integration. The security and privacy of blockchain have attracted much more attention. From the perspective of security, this paper summarizes the security problems from the perspective of blockchain platform architecture, analyses the security issues such as data encryption storage, cross chain technology, key management technology, authorized consensus mechanism, and discusses the coping mechanisms and strategies. This paper also proposes the future development direction of blockchain based on the analysis of blockchain technology, transaction mechanism and supervision mechanism.
Detection of Collective Anomalies in Images for Automated Driving Using an Earth Mover’s Deviation (EMDEV) Measure

For visual perception in automated driving, a reliable detection of so-called corner cases is important. Corner cases appear in many different forms and can be image frame- or sequence-related. In this work, we consider a specific type of corner case: collective anomalies. These are instances that appear in unusually large amounts in an image. We propose a detection method for collective anomalies based on a comparison of a test (sub-)set instance distribution to a training (i.e., reference) instance distribution, both distributions obtained by an instance-based semantic segmentation. For this comparison, we propose a novel so-called earth mover’s deviation (EMDEV) measure, which is able to provide signed deviations of instance distributions. Further, we propose a sliding window approach to allow the comparison of instance distributions in an online application in the vehicle. With our approach, we are able to identify collective anomalies by the proposed EMDEV measure, and to detect deviations from the instance distribution of the reference dataset.
Implementation of Language Processing Tools for the University Quality System

The processing of surveys, reports and comments is a tedious and time-consuming process, especially for the reports and questionnaires which are not multiple choice documents, but which contain open questions or text fields generate a heavy workload. The Educational Ecosystem is heavily challenged with this task in their quality processes due to their legal tasks, and because of the many different stakeholders (individual students, individual staff). The development of on AI-tool to help with the processing of text and give an assessment on the “sentiment” of the text (rather positive or rather negative) is described in the paper. Sentiment analysis helps the assessor focus on the important conclusions (positive or negative sentiments depending on the type and function of used documents).
Indonesian Language Learning Process Through Online System at SDN Class 1V Muara Tiku Musirawas Utara

This research is looking at the current conditions that hit the whole world, namely the corona virus pandemic. A pandemic that causes the entire order of world life to change in all fields, one of which is in the field of education. Due to a pandemic, all activities outside the home are limited. Education is very important in life, therefore education must continue to be carried out during this pandemic. Schools during the pandemic are completed remotely or also known as web or internet learning. Distance learning interactions can maintain distance, and do not cause extreme sports outside the home, of course to maintain health. Furthermore, to find on the web or the internet the learning steps are well done. Exploration is subjective and the subjects of this test are educators and students of SDN class 1V Muara Tiku. The exam cycle begins with the perception to decide on the school's internet learning interactions. Further meetings and documentation. The information collected is checked using reports or explanations from educators and students. The achievement of learning with an online framework in Indonesian language learning includes (a) the use of whatsapp gatherings, (b) dramatization techniques and online conversations, (c) supporting elements for picking up network distances that must be steady and displaced using media, (d) inhibiting factors for interaction learning is an organization that is often disconnected from the network, the topics are difficult to understand.
Reflections on the nature of individuality in the process of identifying handwriting and signatures

The fundamental principle of identification, based on the condition that there is a unique combination of independent discriminating elements in handwriting, is analysed. The results of experiments conducted on distorted handwriting suggest that there may only be one handwriting habit that is responsible for the individuality of handwriting. By analysing disguised and simulated signatures and applying the isochrony principle, it seems reasonable to conclude that the mutual interaction between the speed of writing and the curvature of a graphic line is the only habit, and the quality of a graphic line the only feature responsible for the individuality of handwriting. The article introduces a number of ideas for evaluating the quality of a graphic line during handwriting examination, and a number of new opportunities for research into biometric electronic signatures.
Linear Complexity of a Class of Quaternary Sequences with Optimal Autocorrelation

A unified construction for yielding optimal and balanced quaternary sequences from ideal/optimal balanced binary sequences was proposed by Zeng et al. In this paper, the linear complexity over finite field 𝔽2, 𝔽4 and Galois ring ℤ4 of the quaternary sequences are discussed, respectively. The exact values of linear complexity of sequences obtained by Legendre sequence pair, twin-prime sequence pair and Hall's sextic sequence pair are derived.
Evaluating of Mobile User Interface: A Design Lenses Approach

In the last few years, mobile devices have become the main type of device used to access the Internet in several countries. The software normally used, the personal computer, is gradually being replaced by applications on mobile devices. These applications could be considered as compact versions of software (even though they usually present added features), designed to minimize what is required from the user, and to work quickly and easily. For desktop-oriented software, evaluation processes are designed with the purpose of verifying if the applications are easy to use. However, in the context of mobile devices, there is a dearth of methods for the same purpose. For these reasons, the present work focuses on proposing an evaluation process focused on interfaces for mobile devices. In this way, interviews were performed to understand how evaluation processes are considered within the routines of professionals who deal with mobile devices. The proposed process has a set of associated evaluation lenses. To facilitate access to the process, an application was developed, and it is presented at the end of this paper. This work concludes that there are discussions about processes that help in the evaluation and improvement of interfaces, but they are still deficient, or their executions deprioritized. Accessibility is generally not considered primarily for financial reasons. Therefore, it is necessary to develop more research like this one, which seek to propose new methods that are flexible and useful in practical market contexts.
System and Methods for Blockchain-Inspired Digital Game Asset Management

In 2017, IGT’s Italian Software Architecture team, identified some features of the emerging blockchain, as enabling technologies to manage a ledger (or data store) that used cryptography and digital signatures to prove identity and authenticity (G. Ragnoni, E. Martire, F. Battini, System and Methods for Blockchain-Based Digital Lottery Ticket Generation and Distribution USPTO, Application Number 15/916,620 Filing date Mar 9 2018. https://patents.google.com/patent/US10931457B2). The idea was to design and implement a fully managed ledger database that provided a transparent, immutable and cryptographically verifiable platform for managing the creation of digital assets (e.g. game ticket) and the transfer of asset’s ownership between users. Following the above idea, the team designed and implemented Transaction Certification Authority (TCA), an IGT platform that tracks each and every asset’s transactions and maintains a complete and verifiable history of ownership change over time. The aim of this paper is to present TCA, its features and functioning mechanism.
A Dynamic and Secure Migration Method of Cryptographic Service Virtual Machine for Cloud Environment

In order to improve the continuity of cryptographic services and ensure the quality of services in the cloud environment, a dynamic migration framework of cryptographic service virtual machines based on the network shared storage system is proposed. Based on the study of the security threats in the migration process, a dynamic migration attack model is established, and the security requirement of dynamic migration is analyzed. It designs and implements the dynamic security migration management software, which includes a dynamic migration security enhancement module based on the Libvirt API, role-based access control policy, and transmission channel protection module. A cryptographic service virtual machine migration environment is built, and the designed management software and security mechanism are verified and tested. The experimental results show that the method proposed in the paper can effectively improve the security of cryptographic service virtual machine migration.
¿Cómo ayudar a los estudiantes en la vuelta a la educación presencial después de la educación a distancia durante la pandemia? El papel de las actividades colectivas de interacción en los libros de texto de ELE seleccionados

The aim of the article is to reflect upon the tasks which might help students in the crisis caused by the return to school after distance learning connected with the pandemic. To start with, the data presented concern both mental and physical well-being, as well as the needs of Polish secondary school students during the pandemic (distance learning and the return to schools). Next, the author analyses the place of textbooks during the return to schools and suggests the typology of team tasks facilitating this process, with a special emphasis on the ones which develop the oral interaction and are in accordance with the processual approach to writing. Furthermore, in the research part, the tasks analysed proposed in the four textbooks of Spanish as a foreign language, destined for students aged 15-19 years, in order to state to what degree, they may facilitate the return to schools and what kind of adjustment to this situation they need. Finally, the conclusions were presented.