Reviewerly/exHarmony huggingface dataset:
The impact of verbal working memory on written translation: Empirical evidence and an initial model

Working memory refers to a metaphorical mental workspace involved in the temporary storage and processing of information which has been considered a key construct in Cognitive Translation Studies. This study investigates whether verbal working memory in the translator’s first and/or second language is related to written translation speed and quality. Through three selection tests, 33 student translators in the second or third year of their Master’s in Translation and Interpreting at nine Chinese universities were selected to participate. In the first test, processing and storage capacities of verbal working memory in their first and second language were assessed separately by means of a dual-task paradigm implemented in the e-Prime software suite. In the second study, participants translated a technical text from their second language to their first language. Their behavioural data were collected with a keylogger and the quality of their translations was evaluated by four expert translators. The correlation analysis suggests that the processing function of verbal working memory in the second language does affect logged translation speed; and that the processing function of verbal working memory in the first language has an effect on translation quality. Furthermore, through regression analysis, an initial model was established, which shows the precise structure of the impact of bilingual working memory on written translation. These findings have significant implications for translation skills training. It appears that additional verbal working memory training for both first and second languages would enhance the students’ translation skills.
Encoding classical information in gauge subsystems of quantum codes

In this paper, we show how to construct hybrid quantum-classical codes from subsystem codes by encoding the classical information into the gauge qudits using gauge fixing. Unlike previous work on hybrid codes, we allow for two separate minimum distances, one for the quantum information and one for the classical information. We give an explicit construction of hybrid codes from two classical linear codes using Bacon–Casaccino subsystem codes, as well as several new examples of good hybrid code.
THE IMPLEMENTATION OF STUDENTS FACILITATOR AND EXPLAINING MODEL THROUGH VIDEO BLOG (VLOG) TO ENHANCE SPEAKING SKILL

Student Facilitator and Explaining Learning Model is a learning model where students learn to present ideas / opinions to other fellow students. This learning model is effective for training students to speak to convey their own ideas or opinions. This learning model will be relevant if students actively participate in designing the learning material to be presented. By collaborating students' ideas into video blogs or digital content that can be uploaded on social media such as Instagram, YouTube or Facebook, it is hoped that students can improve their speaking skills and be able to motivate students in the language learning process. This study used a quasi-experimental method. The population of this study is the ninth grade of SMPN 35 Makassar in the academic year 2020/2021. This study uses cluster random sampling. The sample in the study consisted of 60 students who were in two groups; 30 students in the control group and 30 students in the experimental group. The research data were collected using speaking tests, which was analyzed descriptively, and inferential statistics through the SPSS version 22 program for Windows. The results of this study indicate that there was a significant improvement after the implementation of the Student Facilitator and Explaining Learning Model on students' speaking skills. Based on these results, it is hoped that teachers, principals and stakeholders with an interest in education development can apply this learning model in terms of improving students' speaking skills and increasing student motivation in learning languages.
Research on the Principles and Strategies of Cultivating the Sports Core Quality of Students in Higher Vocational Colleges

Under the guidance of China's policy of attaching great importance to the cultivation of socialist builders and successors, the task of higher vocational colleges is to train students with certain higher education knowledge and professional skills under the general requirements of "Literal cultivation".Under this goal, how the sports curriculum reform of higher vocational colleges occupy an important position in the talent training system and support the sports core quality in the training process of students.This depends on the cultivation and the construction of the sports core qualities.This paper is based on the definition of the core literacy of the system.From the perspective of discovering and solving problems, it faces the problems encountered in the research process of sports core literacy, analyzes the causes, and studies the training principles and training strategies from the problems.The core literacy training principles and strategies are used to continuously enrich the research standards and framework of the core literacy of the sports discipline, make the system and structure of the sports core literacy more in line with the requirements of curriculum reform, and broaden the training ideas of the core literacy of the students in higher vocational colleges to meet the country and society's demand for talents.
Toric invariant theory for maximum likelihood estimation in log-linear models

We establish connections between invariant theory and maximum likelihood estimation for discrete statistical models. We show that norm minimization over a torus orbit is equivalent to maximum likelihood estimation in log-linear models. We use notions of stability under a torus action to characterize the existence of the maximum likelihood estimate, and discuss connections to scaling algorithms.
Risk Resilient Supply Chain Management using Blockchain Technology

In recent times, Blockchain technology (BCT) has also received considerable attention outside the financial sector. The thought of Blockchain is much beyond than Bitcoin and Cryptocurrencies. Exploring the chances within the Blockchain universe multiple applications of BCT in Supply Chain Management (SCM) are often implemented. During this paper, we shall combine these two perspectives on BCT in SCM to summarize a current state of the art and to derive avenues for further research. This paper aims to investigate the role of Blockchain in sustainable supply chain management and explore the applications which can contribute towards building a risk resilient supply chain. This paper examines the supply chain management system including the technologies involved and the methodologies. The approach used for making a supply chain monitoring web app through which we can implement a system which makes it easy and efficient to track a product throughout its life-cycle.
Model for implementing project-based learning at a regional university

The project idea is to create a management model of student project activity in a particular University based on empirical research of universities that implement student project activities and analysis of accumulated theoretical data. The purpose of the master’s thesis is to form a management model of student project activities at the State Humanitarian University of technology. The developed model is based on the empirical experience of implementing student project activities in both domestic and foreign universities, as well as the results of a pre-project study that analyzed potential stakeholders. The main elements of the management model are: the formation of a digital project platform, the formation of a motivation system for students and teachers, the creation of a new structural division of the University-the project office and the criteria for evaluating the planned activities. The results of the work are: a management model of student project activities at the State Humanitarian University of technology.
2017 Volcanic activity in Alaska—Summary of events and response of the Alaska Volcano Observatory

First posted December 14, 2020 For additional information, contact: Alaska Volcano ObservatoryU.S. Geological Survey4210 University DriveAnchorage, AK 99508 The Alaska Volcano Observatory responded to eruptions, significant and minor volcanic unrest, and seismic events at 16 volcanic centers in Alaska during 2017. The most notable volcanic activity consisted of a major eruption at Bogoslof Island, continuing intermittent dome growth and ash eruptions from Mount Cleveland, the end of the Pavlof Volcano eruption, volcanic unrest at Shishaldin Volcano, and significant earthquake activity at Tanaga and Great Sitkin Islands. This report also documents reports of degassing at Redoubt Volcano, Makushin Volcano, Mount Gareloi, and Kiska Volcano, anomalous seismicity at Mount Spurr, Augustine Volcano, Akutan Peak, and Makushin Volcano, landslides at Iliamna Volcano, resuspended ash from the 1912 Novarupta-Katmai eruption, and continuing inflation at Okmok Caldera.
Water Conservation and Smart Agriculture in India

In India about 70% of population depends upon farming and one third of the nation’s capital comes from agriculture. Water is one of the most important components used in agriculture. Water is one of the most fundamental resources required in agriculture. Flooding the field is one of the most common practices of soil irrigation used in India, even though options like sprinklers, drip irrigation, and others are available. These issues concerning agriculture have been always hindering the development of the country. The only solution to this problem is smart agriculture, in essence, by modernizing the current traditional methods of agriculture, it is possible to help develop the nation and society as a whole. Hence, the project aims at making the practice of agriculture smart by using automation and IoT technologies.
Sistem Deteksi Kualitas Buah Jambu Air Berdasarkan Warna Kulit Menggunakan Algoritma Principal Component Analysis (Pca) dan K-Nearest Neigbor (K-NN)

One form of artificial intelligence is the automatic detection of images. so the system can determine precisely the type of image or it can be called computer vision. Water guava fruit is a fruit that is often encountered in Indonesia, but many of the water guavas in the community are of poor quality, thus detrimental to consumers. Therefore we need a system that can detect the quality of the water guava. The Principal Component Analysis (PCA) algorithm and the k-nearest neighbor (k-NN) algorithm can be combined to do this job. PCA is an algorithm that can convert to a group of data that is initially correlated into uncorrelated data (Principal Component). The number of Principal Components generated is the same as the original data, but can be reduced to a smaller amount and is still able to represent the original data well. Meanwhile, k-NN is a method for classifying objects based on learning data that is closest to the object. The research model used in this research is a prototype, and the development tools used are UML. In making the water guava quality detection system, the MATLAB programming language is used, and the test uses the blacbox method. The result of this system is that the system is able to produce output in the form of quality classification of water guava fruit automatically.Keywords: Computer vision, PCA, k-NN
MEDIA QUIZIZZ SEBAGAI APLIKASI EVALUASI PEMBELAJARAN KELAS VI DI SDN GUNTUR KOTA CIREBON

This study aims to describe quizizz application as a learning evaluation application for 6th grade SDN Guntur Cirebon City and improve learning evaluation results through quizizz as a fun learning application. This classroom action research was conducted in two cycles with two learning meetings in each cycle. Each cycle consists of planning, implementing, observing, and reflecting. Every meeting, students work on learning evaluations through quizziz. The subjects of this study were 32 students of class VI A SDN Guntur, Cirebon City. The results of this study indicate that quizizz is one of the learning media for learning evaluation activities. Quizizz is an online application that can be accessed via a computer, laptop or smartphone. The advantage of this application is that it can use images, sounds, and animations. There is an interaction when students work on learning evaluations, so that students feel motivated to do the evaluation and feel happy. Students can improve their learning outcomes as indicated by the increase in quizizz results. In the first cycle of the first meeting, the number of students who completed was 37.5%. This result increased in the first cycle of the second meeting to 62.5%. In the second cycle of the first meeting, completeness reached 87.5%, and in the second cycle of the second meeting, completeness reached 100%. All students can achieve completeness in the evaluation of learning because students are increasingly motivated to be able to do quizzes, so that students' understanding of the material increases. This causes the learning outcomes of students to increase. Keywords: learning evaluation, media, quizizz
Correction to: Problem-based gaming via an augmented reality mobile game and a printed game in foreign language education

A Correction to this paper has been published: https://doi.org/10.1007/s10639-020-10409-8
Beyond PS-LTE: Security Model Design Framework for PPDR Operational Environment

National disasters can threaten national security and require several organizations to integrate the functionalities to correspond to the event. Many countries are constructing a nationwide mobile communication network infrastructure to share information and promptly communicate with corresponding organizations. Public Safety Long-Term Evolution (PS-LTE) is a communication mechanism adopted in many countries to achieve such a purpose. Organizations can increase the efficiency of public protection and disaster relief (PPDR) operations by securely connecting the services run on their legacy networks to the PS-LTE infrastructure. This environment allows the organizations to continue facilitating the information and system functionalities provided by the legacy network. The vulnerabilities in the environment, which differ from commercial LTE, need to be resolved to connect the network securely. In this study, we propose a security model design framework to derive the system architecture and the security requirements targeting the restricted environment applied by certain technologies for a particular purpose. After analyzing the PPDR operation environment’s characteristics under the PS-LTE infrastructure, we applied the framework to derive the security model for organizations using PPDR services operated in their legacy networks through this infrastructure. Although the proposed security model design framework is applied to the specific circumstance in this research, it can be generally adopted for the application environment.
On Exploiting Hitting Sets for Model Reconciliation

In human-aware planning, a planning agent may need to provide an explanation to a human user on why its plan is optimal. A popular approach to do this is called model reconciliation, where the agent tries to reconcile the differences in its model and the human's model such that the plan is also optimal in the human's model. In this paper, we present a logic-based framework for model reconciliation that extends beyond the realm of planning. More specifically, given a knowledge base KB1 entailing a formula phi and a second knowledge base KB2 not entailing it, model reconciliation seeks an explanation, in the form of a cardinality-minimal subset of KB1, whose integration into KB2 makes the entailment possible. Our approach, based on ideas originating in the context of analysis of inconsistencies, exploits the existing hitting set duality between minimal correction sets (MCSes) and minimal unsatisfiable sets (MUSes) in order to identify an appropriate explanation. However, differently from those works targeting inconsistent formulas, which assume a single knowledge base, MCSes and MUSes are computed over two distinct knowledge bases. We conclude our paper with an empirical evaluation of the newly introduced approach on planning instances, where we show how it outperforms an existing state-of-the-art solver, and generic non-planning instances from recent SAT competitions, for which no other solver exists.
SDCT: Multi-Dialects Corpus Classification for Saudi Tweets

There is an increasing demand for analyzing the contents of social media.However, the process of sentiment analysis in Arabic language especially Arabic dialects can be very complex and challenging.This paper presents details of collecting and constructing a classified corpus of 4180 multi-dialectal Saudi tweets (SDCT).The tweets were annotated manually by five native speakers in two stages.The first stage annotated the tweets as Hijazi, Najdi, and Eastern based on some Saudi regions.The second stage annotated the sentiment as positive, negative, and natural.The annotation process was evaluated using Kappa Score.The validation process used cross validation technique through eight baseline experiments for training different classifier models.The results present that the 10-folds validation provides greater accuracy than 5-folds across the eight experiments and the classification of the Eastern dialects achieved the best accuracy compared to the other dialects with an accuracy of 91.48%.
Enhancement in data security and integrity using minhash technique

Data &lt;span&gt;encryption process and key generation techniques protect sensitive data against any various attacks. This paper focuses on generating secured cipher keys to raise the level of security and the speed of the data integrity checking by using the MinHash function. The methodology is based on applying the cryptographic algorithms rivest-shamir-adleman (RSA) and advanced encryption standard (AES) to generate the cipher keys. These keys are used in the encryption/decryption process by utilizing the Pearson Hash and the MinHash techniques. The data is divided into shingles that are used in the Hash function to generate integers and in the MinHash function to generate the public and the private keys. MinHash technique is used to check the data integrity by comparing the sender’s and the receiver’s encrypted digest. The experimental results show that the RSA and AES algorithms based on the MinHash function have less encryption time compared to the normal hash functions by 17.35% and 43.93%, respectively. The data integrity between two large sets is improved by 100% against the original algorithm in terms of completion time, and 77% for small/medium data and 100% for large set data in terms of memory utilization.&lt;/span&gt;
Analisis Minat Belajar Siswa Pada Proses Pembelajaran Daring Di Kelas Va SDN Lembursitu

This study aims to analyze the student learning interest the process of online learning in SDN Lembursitu Kota Sukabumi, and the role of parents in the online learning process. This study qualitative descriptive research methods with research subjects are teacher, parents and students. The technique for data collection using interviews, questionnaires and documentation. Technique semi-structed interview and open questionnaire. Data analysis techniques with three stage are data reduction, data display and data conclusion/verification. Covid-19 pandemic in Indonesia has an impact on students interest in learning, when the learning process switches to online learning it results in decreased student interest marked by the lack of active student participation whe following the learning process. In this case parents are very involved in the implementation of the learning process online, parents play a role in guilding students when doing assignments, providing facilities in the form of phone and internet quota, motivate students to study spirit, help and supervise students when carrying out the learning process so that students follow the learning process well and smoothly by always coordinating with the teacher regarding the development of student learning.
A Multilingual Handwritten Character Dataset: T-H-E Dataset

The absence of handwritten special Latin character datasets prompted the creation of the T-H-E Dataset (Turkish-Hungarian-English handwritten character dataset) contributing to the recognition of multilingual handwritten texts. This paper represents a public-domain dataset including handwritten Turkish, Hungarian and English characters collected from 200 participants. The T-H-E Dataset is formed from 78 different letters represented in 156000 binary characters including both the upper and lower-case versions. The dataset can be downloaded from the web in six different versions enabling users to combine the different alphabets for different recognition purposes. The evaluation of the dataset is carried out by applying the same deep learning architecture on the T-H-Edataset and the EMNIST dataset.The dataset is publicly available at https://github.com/bartosgaye/thedataset.
Teachers’ Attributions and Intervention Strategies for Students’ Classroom Misbehaviours: Evidence from Senior High Schools in Komenda Edina Eguafo Abrem Municipality

&#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; &#x0D; The study explored teachers’ attributions in addressing misbehaviour of students in the classroom. To achieve this, a descriptive survey was adopted through the use of quantitative approach. A sample size of 140 teachers was selected for the study using cluster sampling technique. Questionnaires were used to elicit responses from the selected teachers. Inferential statistics and descriptive statistics were used to analyse the research questions. The findings from the study revealed that generally, teachers in the Komenda Edina Eguafo Abirem Municipality attribute students’ disruptive behaviours to blame and intentionality of the students. Again, in the quest for managing these attributed behaviours, supportive measures were identified by the teachers to be very effective. It was recommended that teachers’ beliefs about causality with reference to student misbehaviour be improved by training teachers to embrace controllable as opposed to non-controllable attributions. Teachers who might otherwise embrace unsupportive interventions may be more open to implementing research-based interventions for students who exhibit problem behaviour.
Upgrading qualifications as a means of professional advancement and success

The aim of this study was to find out whether upgrading university teachers’ qualifications would enhance their professional advancement and success. To address these issues, this paper presents a research held in Samara State Technical University for three years. The participants of the study were 15 university teachers who were staff members of the Department of Linguistics, Intercultural Communication and Russian as a Foreign Language. These teachers were given an opportunity to obtain new competencies aimed at implementing the university strategy by taking additional training programmes and upgrading qualifications courses. This paper aims explores these teachers experiences and outcomes and demonstrates that professional development is not always connected with mastering teaching skills but can serve as a means of promoting university strategy and achieving personal goals.