Reviewerly/exHarmony huggingface dataset:
SAFE VAULT: A PASSWORD MANAGER

Text passwords have long been the most popular user authentication method, with a huge number of Internet services using them. Users are faced with the almost insurmountable difficulty of generating and managing a huge number of site-unique and strong (i.e., non-guessable) passwords if they follow suggested practice. A password generator, i.e., a client-side technique that generates (and regenerates) site-specific strong passwords on demand with minimal user input, is one solution to handle this problem. Safe Vault, a password generating scheme previously defined as part of a wider review of such schemes, is detailed specified and analyzed in this work. Safe Vault was created to address flaws that had previously been recognized in password generators, and it uses unique approaches to do so. Safe Vault allows you to create passwords that meet critical real-world needs, such as required password updates, pre-specified passwords, and passwords that meet site-specific requirements.
Text Chatbot Assisted Edublogs for Enhancing the EFL Technical Writing Performance among Computer and Informatics Students

This research aimed to enhance the EFL technical writing performance among Computer and Informatics Students.The research design was one group pre and post-test quasi-experimental design.The participants were 69 2 nd year students at Ismailia Faculty of Computer and Informatics in Suez Canal University.To address students' needs of the EFL technical writing for their future career in different fields of work, text chatbot assisted edublogs were prepared and oriented towards the participants' practice of the EFL technical skills of writing computer software guides, writing technical reports on network problems and writing technical evaluations of websites.There were two text chatbot assisted edublogs for each writing skill so that there were two tasks for each writing skill and there was one edublog for each writing task.Four tools were developed, validated and implemented by the researcher.They were: 1) Needs Assessment Questionnaire, 2) EFL Technical Writing Test, 3) Scoring Rubric for the EFL Technical Writing Performance and 4) Online Reflection Paper for students to provide written responses to open-ended questions about their satisfaction and the benefits of text chatbot assisted edublogs.The findings revealed that text chatbot assisted edublogs had a high positive impact on enhancing Computer and Informatics students' EFL technical writing performance as those text chatbot assisted edublogs were satisfactory, credible, authentic and beneficial to their future career.
The use of techniques of artistic and aesthetic education in a preschool institution based on folk tales

The article examines the potential of the artistic word as a method of artistic and aesthetic education in a preschool institution. The article notes the significance of folk tales as a method of teaching and upbringing, the aesthetic, cultural and psychological significance of fairy tales and the pedagogical technology of using the artistic word as a means of teaching and upbringing. The article examines the organization of artistic activity, which makes it possible to reveal the meaning and potential of national fiction, using the example of preschool institutions in the Komi Republic
Experimental certification of nonprojective quantum measurements under a minimum overlap assumption

Certifying quantum measurements is increasingly important for foundational insights in quantum information science. Here, we report an experimental certification of unknown quantum measurements in a semi-device-independent setting. For the first time, we experimentally demonstrate that genuine three-outcome positive operator-valued measures (POVMs) can be certified under the assumption of a limited overlap between the prepared quantum states. The generalized quantum measurements are realized through discrete-time quantum walk and our experimental results clearly show that three-outcome POVMs can be certified even in the presence of noise. Finally, we experimentally investigate that optimal POVMs for performing unambiguous state discrimination can be self-tested. Our work opens new avenues for robust certification of quantum systems in the prepare-and-measure scenario.
Code-Mixing and Code-Switching in Maths Online Classroom: The Language Function in Interaction of Junior High School Students

Globally speaking, bilingual languages are spoken by most human.It is common for us to find people talking in varieties of languages in such their native language and their common language at the same time.When people speak two different languages at a time, they are mixing language and switching it among languages they know.In bilingual phenomenon, people tend to mix or switch one language into another.Bilingual phenomenon is also known as Multilingual phenomenon.Mixing and switching languages are commonly happened from the bilingual ability of a language speaker.Bilingual societies especially people in Indonesia prefer to express in numerous languages to interact in the society.Generally, groups of people speak bilingual languages live in a
The Effect of Using Listen and Draw and Dictogloss Technique on Students’ Ability in Listening Comprehension at the Tenth Grade of SMA Negeri 1 Lahewa

English is one of the languages in the world that has an important role for communication.Studying English means to study the four language skills; (1) listening, (2) speaking, (3) reading and (4) writing.Based on the researcher experienced about teaching listening in Nias Island especially in SMA Negeri 1 Lahewa.There were some problems has found in the field: (1) the students were unable to descriminate between the distinctive sounds, (2) the limited facility of the school, especially tools for teaching listening, (3) the students were unable to recognise the stress patterns of words, (4) the students were unable to recognise reduced forms of words, (5) the students were unable to predict outcomes from events described, and the last (6) the students were unable to distinguish between literal and applied meanings.So, most of the students less ability in listening skill because the teaching listening at SMA Negeri 1 Lahewa still conventional method.Language is one of the most important things in the life of every human being.
Covid-19 nei testi di stampa italiana

This article aims to present how the COVID-19 has influenced the current texts of the Italian press. We pay attention to the vocabulary relating to the pandemic in the most characteristic linguistic phenomena of the Italian language. We support the theoretical questions with examples taken from Italian newspapers (current articles). The goal of our work is to characterize „la vivacità espositiva”, the captivating titles, their nominalization, the phraseological verbs, the direct speech, cleft sentence, „il c’è presentativo, la dislocazione a si-nistra”, whose purpose is mainly to simplify the language of the press and to make the text more attractive. The presence of neologisms, plasticisms, acronyms, and war metaphors are particularly characteristic of the press language during the pandemic. The language of the press occupies a special place among the sectoral languages, currently undergoing changes also due to the world situation during the pandemic.
Discorso figurato e pandemia : una focalizzazione sulla metafora del PERCORSO

Among the linguistic outcomes of the pandemic are the discourse strategies applied by speakers belonging to different sociolinguistic groups in different communicative contexts. In particular, the study highlights the widespread use in Italian of a densely figurative language, aimed at representing in an effective and cognitively manageable way the dramatic novelty of the phenomenon and the exceptionality of proposed measures (typically, on the part of institutions, politicians and the press), and at expressing the unique and emotionally charged nature of the new experience (typically, on the part of the ordinary speaker). Among different possible source domains, the study focuses on that of the journey, which appears to have been overlooked in the literature, though it constitutes, crosslinguistically, a fundamental resource for the representation of several aspects of human experience.
Diario lessicale di una pandemia – dimensione contrastiva descrittiva nell’ambito italo-polacco

Considering the fact that languages are defined by users and remains in constant evolution, the main goal of this paper is to focus on how to reflect the contemporary situation through the terms relating to the period of crisis due to the coronavirus pandemic. The descriptive contrastive dimension of the analysis (ACD) is proposed with reference to the Italian-Polish context and with regard to the different language solutions (semantic, semiotic and structural) such as: resemantization, types of loanwords (adapted and not adapted, semantic casts and structural casts), medical technicalities, vocabulary of politicians and others government institutions. Referring to some theories, implemented in today’s circumstances, such as the linguistic relativism of Benjamin Lee Whorf (1950 : 52-55) and the observations of Ludwig Wittgenstein (1953), current article current article also reflects the application of Aristotle’s considerations concretized in Rhetoric (330 BCE).
Message

It is my great pleasure to welcome all the guest and participants to the 5th International Conference on Information Systems and Computer Networks (ISCON-2021) held in GLA University Mathura, India.The ISCON 2021 is an interdisciplinary conference of the IEEE U.P. section and represents one of the largest gatherings of researchers and industry professionals from all over the world.This conference brings together more than 250 delegates from around the globe to discuss the latest advances in this vibrant and constantly evolving field.
A Study on the Impact of Data Augmentation for Training Convolutional Neural Networks in the Presence of Noisy Labels

Label noise is common in large real-world datasets, and its presence harms the training process of deep neural networks. Although several works have focused on the training strategies to address this problem, there are few studies that evaluate the impact of data augmentation as a design choice for training deep neural networks. In this work, we analyse the model robustness when using different data augmentations and their improvement on the training with the presence of noisy labels. We evaluate state-of-the-art and classical data augmentation strategies with different levels of synthetic noise for the datasets MNist, CIFAR-10, CIFAR-100, and the real-world dataset Clothing1M. We evaluate the methods using the accuracy metric. Results show that the appropriate selection of data augmentation can drastically improve the model robustness to label noise, increasing up to 177.84% of relative best test accuracy compared to the baseline with no augmentation, and an increase of up to 6% in absolute value with the state-of-the-art DivideMix training strategy.
Lybid Publishing House: pages of history and the present

The history of the founding of the publishing house "Lybid" dates back to 1835, when a year after the opening of the Kiev University of St. Vladimir began printing.&#x0D; The history of the foundation is described in detail in the book "Her Majesty - a book. The history of publishing at the University of Kiev 1834-1999" by M. Tymoshyk - a famous journalist, doctor of philology, who once worked as editor in chief of the publishing house "Lybid".
Optimal Path Planning for Navigation Using a Generalized Genetic Algorithm

The International Scientific Research Organization for Science, Engineering and Technology (ISROSET) is a Non-Profit Organization; The ISROSET is dedicated to improvement in academic sectors of Science (Chemistry, Bio-chemistry, Zoology, Botany, Biotechnology, Pharmaceutical Science, Bioscience, Bioinformatics, Biometrics, Biostatistics, Microbiology, Environmental Management, Medical Science, Forensic Science, Home Science, Library Science, Material Science Military Science, Physical Science, Physical Education Science, Educational Science, Fisheries, seed technology, Agriculture, Forestry Science, Mathematics, Physics, Statistics and Geology/Earth Science), Computer Science, Engineering and Information Technology, Commerce, Management, Economics Sociology and Social Science.
Analyzing Trends in Tor

The Tor Network has been a significant part of the Internet for years. Tor was originally started in the Naval Research Laboratory for anonymous Internet browsing and Internet-based communication. From being used for anonymous communications, it has now segmented into various other use-cases like censorship circumvention, performing illegal activities, etc. In this paper, we perform empirical measurements on the Tor network to analyze the trends in Tor over the years. We gather our measurements data through our measurement scripts, past research in this domain, and aggregated data provided by the Tor metrics directory. We use this data to analyze trends and understand the incidents that caused fluctuations in the trends of different data parameters. We collect measurements data for Tor parameters like Tor users, onion services, Tor relays, and bridges, etc. We also study censorshiprelated events and study trends by analyzing censorship-related metrics. Finally, we touch upon the location diversity in Tor and study how the Tor circuit selection and construction are impacted by the bandwidth distribution of Tor relays across geographies.
Visual Book as a Learning Medium of Islamic Religious Education Courses for Politeknik Elektronika Negeri Surabaya (PENS) Students

The Islamic Religious Education course, which is then abbreviated as PAI, is a compulsory subject for Muslim students that must be implemented in every university in Indonesia. This is stated in Law No. 12 of 2012 Article 35 Paragraph 3 concerning Higher Education. In its implementation, Politeknik Elektronika Negeri Surabaya (PENS) has given these courses to students. This course aims to shape students into human beings who believe and fear Allah SWT. and have noble character. On the other hand, an understanding of the subject matter of PAI is very important in order to realize this main goal. Based on the results of research entitled Questionnaire for Islamic Religious Education Courses at PENS, it was stated that 75% of the 40 respondents found it difficult to learn and understand some chapters due to the lack of visualization of the material and too many terms that were difficult to understand or memorize. Another problem found through this research is that the intensity of respondents' reading activities is still relatively low. Therefore, this research is expected to be able to increase understanding related to PAI courses through reading activities for PENS students by contributing in the form of making visual books as interesting PAI learning medium.
AniWho : A Quick and Accurate Way to Classify Anime Character Faces in Images

In order to classify Japanese animation-style character faces, this paper attempts to delve further into the many models currently available, including InceptionV3, InceptionResNetV2, MobileNetV2, and EfficientNet, employing transfer learning. This paper demonstrates that EfficientNet-B7, which achieves a top-1 accuracy of 85.08%, has the highest accuracy rate. MobileNetV2, which achieves a less accurate result with a top-1 accuracy of 81.92%, benefits from a significantly faster inference time and fewer required parameters. However, from the experiment, MobileNet-V2 is prone to overfitting; EfficienNet-B0 fixed the overfitting issue but with a cost of a little slower in inference time than MobileNet-V2 but a little more accurate result, top-1 accuracy of 83.46%. This paper also uses a few-shot learning architecture called Prototypical Networks, which offers an adequate substitute for conventional transfer learning techniques.
Perbandingan Algoritma Naive Bayes dan Linear Discriminant Analysis dengan Dataset Car Evaluation

&#x0D; &#x0D; &#x0D; Safety, price, and luxury are important factors to consider when buying a car. These factors depend on the type, model and make of the vehicle. In fact, these factors are very important in terms of reducing the number of accidents. However, the many variables that must be considered make it difficult for consumers to determine which car to buy and are prone to human error. With these problems, the need for an efficient decision-making system, one of which uses Machine Learning algorithms, the author tries to find out the difference between the Naïve Bayes method and Linear Discriminant Analysis (LDA) on the Car Evaluation data set. It is hoped that from this research, the accuracy of the two methods on the Car Evaluation data set can be known. the results of the tests that we carried out using both classifications obtained the results of 73.98% and 82.23% for the time range of 0.002 and 0.001. &#x0D; &#x0D; &#x0D;
Grad-Align+: Empowering Gradual Network Alignment Using Attribute Augmentation

Network alignment (NA) is the task of discovering node correspondences across different networks. Although NA methods have achieved remarkable success in a myriad of scenarios, their satisfactory performance is not without prior anchor link information and/or node attributes, which may not always be available. In this paper, we propose Grad-Align+, a novel NA method using node attribute augmentation that is quite robust to the absence of such additional information. Grad-Align+ is built upon a recent state-of-the-art NA method, the so-called Grad-Align, that gradually discovers only a part of node pairs until all node pairs are found. Specifically, Grad-Align+ is composed of the following key components: 1) augmenting node attributes based on nodes' centrality measures, 2) calculating an embedding similarity matrix extracted from a graph neural network into which the augmented node attributes are fed, and 3) gradually discovering node pairs by calculating similarities between cross-network nodes with respect to the aligned cross-network neighbor-pair. Experimental results demonstrate that Grad-Align+ exhibits (a) superiority over benchmark NA methods, (b) empirical validation of our theoretical findings, and (c) the effectiveness of our attribute augmentation module.
Learning to Solve Optimization Problems with Hard Linear Constraints

Constrained optimization problems appear in a wide variety of challenging real-world problems, where constraints often capture the physics of the underlying system. Classic methods for solving these problems rely on iterative algorithms that explore the feasible domain in the search for the best solution. These iterative methods are often the computational bottleneck in decision-making and adversely impact time-sensitive applications. Recently, neural approximators have shown promise as a replacement for the iterative solvers that can output the optimal solution in a single feed-forward providing rapid solutions to optimization problems. However, enforcing constraints through neural networks remains an open challenge. This paper develops a neural approximator that maps the inputs to an optimization problem with hard linear constraints to a feasible solution that is nearly optimal. Our proposed approach consists of four main steps: 1) reducing the original problem to optimization on a set of independent variables, 2) finding a gauge function that maps the infty-norm unit ball to the feasible set of the reduced problem, 3)learning a neural approximator that maps the optimization's inputs to an optimal point in the infty-norm unit ball, and 4) find the values of the dependent variables from the independent variable and recover the solution to the original problem. We can guarantee hard feasibility through this sequence of steps. Unlike the current learning-assisted solutions, our method is free of parameter-tuning and removes iterations altogether. We demonstrate the performance of our proposed method in quadratic programming in the context of the optimal power dispatch (critical to the resiliency of our electric grid) and a constrained non-convex optimization in the context of image registration problems.
Deep transfer learning base on sequenced edge grid image technique for sign language recognition

Sign language is a visual-gestural language used by hearing impaired person, they modality the gesture to convey meaning. The main problem with sign language communication is ordinary people do not understand the sign language. Therefore, sign language is one of the challenging problems in machine learning. In this paper, researchers focus on visual-based methods and optimize the data preprocessing apply with existing sign language resources. Researchers propose an innovative technique for video processing called Sequenced Edge Grid Images (SEGI) for sign language recognition to interpret hand gesture, body movement, and facial expression. Researchers collected several of sign language data from the internet, the data including Thai sign language utilize in everyday life. The proposed technique was implemented with a convolutional neural network (CNN). The experiments showed SEGI with CNN has increases test accuracy rate with approximately 11% compared to static hand gesture images. Finally, researchers discovered a CNN structure suitable for dataset and examination data by transferring a pre-trained CNN. The fine-tuning with SEGI technique improved 99.8%, thus highest among all the methods. From the results data-preprocesses technique of dataset generation and deep transfer learning was an effective way to improve the accuracy of sign language recognition.
The Degree of Applying Knowledge Management Processes from the Perspective of Faculty Members at Colleges of Educational Sciences in Private Jordanian Universities in the Capital Governorate

The study aimed to identify the degree of applying processes of knowledge management at colleges of educational sciences in private Jordanian universities in the Capital Governorate from the perspective of faculty members, and the effect of gender, academic rank and experience variables on the degree of application. To achieve this, the analytical descriptive survey method was used, and a questionnaire was developed and included (25) items, covering three dimensions: knowledge generation, knowledge storage, knowledge transfer, and knowledge application. The questionnaire was distributed to as ample of (77) faculty members in the college of educational sciences in private universities in the capital governorate (Al-Zaytouna, the Middle East, Al-Isra and Petra) during the academic year 2018/2019. The results showed that the degree of application of knowledge management processes by colleges in the field of knowledge generation and knowledge transfer were medium (2.07) and (1.91), while the degree of application in the two fields of knowledge application and knowledge generation was low with means of (1.64) and (1.40). Results also showed that there were no statistically significant differences at (α&lt;0.05) on all domains of knowledge management attributed to the variable of sex. There were statistically significant differences at (α&lt;05.0) for the domains of knowledge management processes, all attributable to the variable of academic rank. However, there were no statistically significant differences at (α&lt;05.0) in the degree of applying knowledge management processes among faculty members attributed to the variable of experience in all majors. It can be concluded that the degree of applying knowledge management processes at Colleges of Educational Sciences in private Jordanian universities in the Capital Governorate varied between medium and low. Therefore, the study recommended that knowledge management processes be adopted by Jordanian private universities in the Capital Governorate.