Reviewerly/exHarmony huggingface dataset:
Αναγνώριση φωνημάτων με μεθόδους βαθιάς μάθησης

In this thesis, an implementation of a neural network model for phonetic recognition in TensorFlow is presented. With this library, a Deep Long Short-Term Memory (DLSTM) neural network was created. The choice of this specific neural network was based on the fact that human speech is a sequence of phones, and by extension sequential data. For this specific implementation, the Mel Frequency Cepstral Coefficients (MFCCs) were used to present the acoustic features and with the DLSTM model the phonetic recognition was succeded. The experiments were conducted in the most widespread data base for phonetic recognition-classification problems, the Texas Instruments Massachusetts Institute of Technology (TIMIT) data base. A frame error rate of 30.12% was reported for the DLSTM architecture, thatcorresponds to 69.88% accuracy.
E-Loox, A Hybrid Learning Management System

E-loox is an educational software application that has been designed specifically for students located in areas with limited Internet access. Unlike the majority of existing educational applications, E-loox is a “hybrid app”– meaning it can function both on and offline. As a hybrid app, E-loox allows students to complete assignments, access course materials, and conduct research in places where there is no Internet access. While global Internet access has expanded rapidly in the last decade, there are still more than 3.5 billion people who lack access, including approximately 60 million people in the United States. E-loox seeks to bridge the gap for the millions of students who have internet in the classroom but lack a home connection.
Adversarial Masking: Towards Understanding Robustness Trade-off for Generalization

Adversarial training is a commonly used technique to improve model robustness against adversarial examples. Despite its success as a defense mechanism, adversarial training often fails to generalize well to unperturbed test data. While previous work assumes it is caused by the discrepancy between robust and non-robust features, in this paper, we introduce \emph{Adversarial Masking}, a new hypothesis that this trade-off is caused by different feature maskings applied. Specifically, the rescaling operation in the batch normalization layer, when combined together with ReLU activation, serves as a feature masking layer to select different features for model training. By carefully manipulating different maskings, a well-balanced trade-off can be achieved between model performance on unperturbed and perturbed data. Built upon this hypothesis, we further propose Robust Masking (RobMask), which constructs unique masking for every specific attack perturbation by learning a set of primary adversarial feature maskings. By incorporating different feature maps after the masking, we can distill better features to help model generalization. Sufficiently, adversarial training can be treated as an effective regularizer to achieve better generalization. Experiments on multiple benchmarks demonstrate that RobMask achieves significant improvement on clean test accuracy compared to strong state-of-the-art baselines.
Self-Regulated Learning in Students of the Faculty of Medicine and Surgery, Southeast Regional University (Oaxaca, Mexico)

Introduction: Self-regulated learning is identified as an active, independent, autonomous, critical, adaptive, reflective and strategic process, to achieve comprehensive training, continuous selfimprovement, self-determination, autonomy and update itself permanently. The objective of this work is to analyze the self-regulation strategies of undergraduate students assigned to the Faculty of Medicine and Surgery of the Southeast Regional University for the 2019-2020 school year. Methodology: This is a descriptive-cross-sectional study, the sample was obtained through a simple random sampling among students from first to fifth year, with substitution of exclusion elements, the instrument used was the adapted Torre questionnaire (2016) and validated for this study. Results: Study subjects demonstrated adequate metacognitive awareness, control and verification, in addition to having active processing during classes, however, they present little effort in performing tasks, which leads us to establish recommendations for the educational practice that reinforces above all the teaching of these strategies in the university environment of health sciences. Conclusion: The undergraduate students of the Faculty of Medicine and Surgery of the Southeast Regional University are clear about what self-regulated learning is mainly in students of more advanced years or who have already begun to contact the clinical area, unlike the students of the first years where behavioral strategies are still perceived.
I.A. Bunin and ‛Book Publishing of Writers in Moscow’. Materials and Comments

The article presents an attempt to chronically highlight the episodes of collaboration between I. A. Bunin and the “Book Publishing of Writers in Moscow” (1912 –1923) based on the preserved archival materials, both those that have already been introduced into scientific circulation and those that are published for the first time, help to look at them with a possible degree of objectivity. Chronologically, its center will be 1912, as well as the first few years of the existence of “Book Publishing”. Since 1963, the topic of the article has been covered in a number of articles and publications, but not as a separate independent story, but in the context of studying the activities of “Book Publishing” as a whole. I.A. Bunin was one of the most active and authoritative employees and authors of the publishing house. For seven years, eighteen books (including reprints) were published, including milestone books that were important for the development of Bunin's literary reputation. “Memoirs” of N.S. Angarsky-Klestov are published according to the latest authorized typescript (with additions from the 1992 publication in the journal “Voprosy literatury”); letters of S.N. Sergeyev-Tsensky, V.V. Veresayev, M.V. Averyanov, V. V. Muyzhel to AngarskyKlestov, letters of the Angarsky-Klestov to Sergeyev-Tsensky and Bunin, fragments of correspondence between Bunin and Veresayev, Veresaev’s letter to S.D. Makhalov, as well as the agreement between Bunin and “Book Publishing” concerning the fifth edition of the book “Mountain Pass. Short Stories 1892 –1902” (1913) are published according to manuscripts.
Galois hulls of cyclic serial codes over a finite chain ring

In this paper, we explore some properties of Galois hulls of cyclic serial codes over a chain ring and we devise an algorithm for computing all the possible parameters of the Euclidean hulls of that codes. We also establish the average $p^r$-dimension of the Euclidean hull, where $\mathbb{F}_{p^r}$ is the residue field of $R$, and we provide some results of its relative growth.
Information as Order Hidden within Chance: An Application to Biology

We show, by didactical examples, how algorithmic information (coded e.g., into a computer program) is required to build the structure of an organized system (either simple or complex).Ordered structures can be obtained as attractors both by some dynamics starting from sequential initial conditions (order from order) and by some dynamics starting from random initial conditions (order from chance) provided that a leading algorithmic information is assigned to govern the evolution of the generating process.In absence of information emergence of some ordered structure, like e.g., an organ of a living system is so highly improbable to be impossible in practice.We provide didactical examples of static models of a human heart, each generated starting either from ordered initial conditions, or from random sparse initial conditions, or more realistically by random cellular automata (so that any mother cell is allowed to generate a daughter cell only in a random contiguous location).Significantly, as it was pointed out by Gregory Chaitin, not all algorithmic information can be compressed into a string shorter than the sequence of its original individual code digits (incompressible information string).A question is still open about the DNA and, more generally, any biological information: is it to be considered as a compressible or an incompressible code string?In our example of anatomic human heart model we have treated the sequence of the co-ordinates of each sphere (roughly modeling a cell) as an uncompressed string, while a compressed program string seems to be able to provide only less realistic models.
Integration of Blockchain and IoT: An Enhanced Security Perspective

Blockchain (BC), a by-product of Bitcoin cryptocurrency, has gained immense and wide scale popularity for its applicability in various diverse domains – especially in multifaceted non-monetary systems. By adopting cryptographic techniques such as hashing and asymmetric encryption - along with distributed consensus approach, a Blockchain based distributed ledger not only becomes highly secure but also immutable and thus eliminates the need for any third-party intermediators. On the contrary, innumerable IoT (Internet of Things) devices are increasingly being added to the network. This phenomenon poses higher risk in terms of security and privacy. It is thus extremely important to address the security aspects of the growing IoT ecosystem. This paper explores the applicability of BC for ensuring enhanced security and privacy in the IoT ecosystem. Recent research articles and projects/applications were surveyed to assess the implementation of BC for IoT Security and identify associated challenges and propose solutions for BC enabled enhanced security for the IoT ecosystem.
WGAN with an Infinitely Wide Generator Has No Spurious Stationary Points

Generative adversarial networks (GAN) are a widely used class of deep generative models, but their minimax training dynamics are not understood very well. In this work, we show that GANs with a 2-layer infinite-width generator and a 2-layer finite-width discriminator trained with stochastic gradient ascent-descent have no spurious stationary points. We then show that when the width of the generator is finite but wide, there are no spurious stationary points within a ball whose radius becomes arbitrarily large (to cover the entire parameter space) as the width goes to infinity.
Sparse analysis of deep features for characterization of breast masses

Breast cancer is the second most common type of cancer of women in the U.S. behind skin cancer. Early detection and characterization of breast masses is critical for effective diagnosis and treatment of breast cancer. Computer-aided breast mass characterization methods would help to improve the accuracy of diagnoses, their reproducibility, and the throughput of breast cancer screening workflows. In this work, we introduce sparse representations of deep learning features for separation of malignant from benign breast masses in mammograms. We expect that the use of deep feature-based dictionaries will produce better benign/malignant class separation than straightforward sparse representation techniques, and fine-tuned convolutional neural networks (CNNs). We performed 10- and 30-fold cross-validation experiments for classification of benign and malignant breast masses on the MIAS and DDSM mammographic datasets. The results show that the proposed deep feature sparse analysis produces better classification rates than conventional sparse representations and fine-tuned CNNs. The top areas under the curve (AUC) for the receiver operating curve are 80.64% for 10-fold and 97.44% for 30-fold cross-validation in MIAS, and 77.29% for 10-fold and 76.02% for 30-fold cross-validation in DDSM. The main advantages of this approach are that it employs dictionaries of deep network features that are sparse in nature and that it alleviates the need for large volumes of training data and lengthy training procedures. The interesting results from this work prompt further exploration of the relationship between sparse optimization problems and deep learning.
PENGEMBANGAN MEDIA ADOBE FLASH BERBASIS DISCOVERY LEARNING UNTUK MENINGKATKAN HASIL BELAJAR IPA

The background of this depevelopment is lack of media usage in learning sciences that limited using books and blackboard. This development which aims to identify the feasibility and effectiveness of adobe flash learning media based on discovery learning developed. The development of learning media used ADDIE’s model of development. The development procedure which used in the research consists of five steps, namely: (1) analyze, (2) design, (3) development, (4) implementation, (5) evaluation. The data collecting instruments were assessment sheets for the material expert, media expert, instructional design expert, class teacher, and achievement test. The data analysis technique was the qualitative descriptive technique using score distributions and assessment scale categories. The result of research producing products that meet the eligibility criteria reached 3,80 that have a valid criteria and fit for use, also effectively used to improve students learning outcomes  include mastery learning individual reached 85,7%, completness of classical study reached 80,5%  and with N-gain percentage reached 0,68 with medium category.
Implementation of media practices in the work of libraries for children and youth

The relevance of the study is due to the expansion of the media space of Ukrainian libraries for children and youth and the use of media practices on their pages in social networks. The aim is to study and compare the applied media practices by domestic libraries for children and youth, to consider new forms of work with the use of media content by libraries for young people and to illustrate their attractiveness to the user. To solve the tasks, the method of analysis of library content in new media, methods of comparison, generalization and sociocommunication were used. The presence of libraries in new media attracts the attention of young people, and information and communication technologies become intermediaries between the book collection and the user. An important component of the attractiveness of the library’s page in social networks is not only the expansion of new channels of communication, but also the creation of the author’s media content.
Recurrent Graph Convolutional Network for Skeleton-Based Abnormal Driving Behavior Recognition

Abnormal driving behavior recognition is important in driving and traffic safety. Currently, skeleton-based action recognition has achieved significant improvement. However, how to effectively recognize abnormal driving behavior is still challenging in real applications, especially for subtle and similar behaviors. In this work, we propose a novel recurrent graph convolution network, which combines spatiotemporal graph convolutional networks and recurrent neural networks. First, we design a new spatial topological graph that includes the joints of the hands and face, which is advantageous to recognize subtle abnormal driving behaviors, such as yawning. Second, the proposed network can extract discriminative spatial and temporal representation features of the segmented skeleton sequences. Our method achieves an accuracy of 90.04% on the dataset collected by ourselves. Moreover, experiments on the Kinetics dataset verify the generalization ability of our method.
AFFORDANCE DALAM DESAIN INTUITIF DAN HUMAN COMPUTER INTERACTION (HCI)

Abstract The concept of affordance comes from ecological psychology proposed by James Gibson to show the possibility of actions given to actors by the environment. Something has a quality to understand, where they are capable of being something when they are felt. Product perception is connected with the perception of its function. Affordance as a perception of meaning by combining the functions and meanings of a product. Thus, the meaning of a product will make what the product is capable of. People treat products from their environment according to the affordance of the product. Good product design is intuitive, can be used without thinking hard. Design that allows us, by seeing it we can do things directly and correctly. The concept of affordance was also introduced to the field of design, and finally Human Computer Interaction, by Donald Norman. He defines affordance as the perceived or actual nature of the object, especially the fundamental properties that determine how objects or technological products can be used. Affordance is the interpretive relationship between users and technology that arises during user interaction with technology in the environment that is lived. In a broader view of affordance, it covers social and cultural aspects in the use of technology in our daily lives.
FORMATION OF CREATIVE POTENTIAL OF STUDENTS BASED ON INNOVATIVE APPROACHES

In the context of the reform and modernization of education in Kazakhstan and the accession of the Republic of Kazakhstan to the Bologna process, Akhmet Yassawi International Kazakh-Turkish University has aimed to train specialists of an international level and improve the quality of education, the main course is to develop new pedagogical grounds for the formation of a future specialist both as a professional and as a creative person with creative potential and professional-creative competence. The search for personnel reserves to improve the professional training of future specialists is shifting to the development of creative potential and communicative competence. There is a need to transform the educational environment of higher education into a single creatively developing educational space that promotes the formation and development of students' creative potential and competence as a factor in successful self-realization in the profession and the prerequisites for competent support for the creative development of students.
KORELASI KETERAMPILAN MEMBACA PEMAHAMAN TEKS DESKRIPSI DENGAN KETERAMPILAN MENULIS TEKS DESKRIPSI SISWA KELAS VII SMP NEGERI 1 BATANG KAPAS

ABSTRACT This article reveals the contribution of skills reading comprehension text descriptions to writing skills text description grade students VII SMP Negeri Batang Kapas 1. The purpose of this research there are three. First, it describes the skills of reading comprehension text description grade VII SMP Negeri 1 field. Second, it describes the writing skills text description grade VII SMP Negeri 1 field. Third, describing the contribution of the intermediate reading comprehension text descriptions against writing skills text description grade VII SMP Negeri 12 field. The design used in this research is the design contribution. This research population is grade VII SMP Negeri Padang are registered on the 12th school year 2018/2019, i.e. as many as 286 students. The sample in this research are determined by proportional random sampling of 20% of the population, i.e. 54 students. Research data is a score test. The data obtained through two types of tests i.e. objective tests to measure the skills of reading comprehension text description and performance tests to measure the skills of writing a text description.. First, the skills of reading comprehension text description grade VII SMP Negeri Padang 12 are on good qualifications (B) by the value of the average 80.09. Second, the skills of writing text descriptions grade VII SMP Negeri Padang 12 are on good qualifications (B) with an average of 80.86. Third, there is a contribution reading skills in the description text to the skills of writing description texts of class grade VII SMP Negeri Padang 1 at 62.73% Kata kunci: Korelasi, Keterampilan, Membaca Pemahaman, Menulis, Teks Deskripsi
An improved upper bound on self-dual codes over finite fields $GF(11), GF(19)$, and $GF(23)$

This paper gives new methods of constructing {\it symmetric self-dual codes} over a finite field $GF(q)$ where $q$ is a power of an odd prime. These methods are motivated by the well-known Pless symmetry codes and quadratic double circulant codes. Using these methods, we construct an amount of symmetric self-dual codes over $GF(11)$, $GF(19)$, and $GF(23)$ of every length less than 42. We also find 153 {\it new} self-dual codes up to equivalence: they are $[32, 16, 12]$, $[36, 18, 13]$, and $[40, 20,14]$ codes over $GF(11)$, $[36, 18, 14]$ and $[40, 20, 15]$ codes over $GF(19)$, and $[32, 16, 12]$, $[36, 18, 14]$, and $[40, 20, 15]$ codes over $GF(23)$. They all have new parameters with respect to self-dual codes. Consequently, we improve bounds on the highest minimum distance of self-dual codes, which have not been significantly updated for almost two decades.
“SuperWomen”: A Smart Mobile Application for Social Security focusing Threats and Supports for Women

&lt;p&gt;Though in this modern society men and women are said to be given equal rights, having no gender discrimination, women are still considered weak and endlessly facing rape, domestic violence, eve-teasing, workplace violence, physical assault, cyberbullying even being killed. In South Asian countries, like Bangladesh, India, Pakistan there are thousands of cases regarding violence against women. The use of ICT including smartphone applications can be an aid in building awareness and support against these issues. Although several applications were developed worldwide, but not out there online for sensible use. In this paper, we aspire to present women with a technical solution by providing them a mobile application “SuperWomen” that is centered on urban and rural women of Asian countries and also available online. Not only women, but its voice-controlled siren feature is also a great help for physically challenged individuals, that works even on the lock screen. Survey feedback of this application shows that it takes care of each pre-incidental and post-incidental condition like an expert. This application provides user-friendly navigation for women with less technical knowledge. Its key features are secret button emergency SMS alert, location sharing with any social media, lawyer chatbot, pictorial self-defense techniques, etc. The effectiveness of this application has been justified through extensive literature review, application benchmark, performance evaluation, user survey, deployment in Google Play Store. We believe that this will bring a holistic resolution to safeguard suppressed women worldwide.&lt;strong&gt; &lt;/strong&gt;&lt;/p&gt;
Robust Domain-Free Domain Generalization with Class-aware Alignment

While deep neural networks demonstrate state-of-the-art performance on a variety of learning tasks, their performance relies on the assumption that train and test distributions are the same, which may not hold in real-world applications. Domain generalization addresses this issue by employing multiple source domains to build robust models that can generalize to unseen target domains subject to shifts in data distribution. In this paper, we propose Domain-Free Domain Generalization (DFDG), a model-agnostic method to achieve better generalization performance on the unseen test domain without the need for source domain labels. DFDG uses novel strategies to learn domain-invariant class-discriminative features. It aligns class relationships of samples through class-conditional soft labels, and uses saliency maps, traditionally developed for post-hoc analysis of image classification networks, to remove superficial observations from training inputs. DFDG obtains competitive performance on both time series sensor and image classification public datasets.
Differentially Private Correlation Clustering

Correlation clustering is a widely used technique in unsupervised machine learning. Motivated by applications where individual privacy is a concern, we initiate the study of differentially private correlation clustering. We propose an algorithm that achieves subquadratic additive error compared to the optimal cost. In contrast, straightforward adaptations of existing non-private algorithms all lead to a trivial quadratic error. Finally, we give a lower bound showing that any pure differentially private algorithm for correlation clustering requires additive error of $Ω(n)$.