Reviewerly/exHarmony huggingface dataset:
Metacognitive Proactive Hybrid Learning Model Using ICT Tools

Many aspects characterized novelty. In both practical and theoretical regards, the difficulties observed in technical education are addressed from the psycho-cognitive and the psycho-pedagogical point of view. The modern education system slowly adapts itself to the most powerful educational tools such as Web-based learning, problem-based learning, and collaborative learning methods. Still, they have their scope and limitations, such as difficulty in integrating online and offline, lack of an assessment tool for quality assurance, etc. Hence, the research work’s objective was to develop a Metacognitive Hybrid Model (MHM) for enhancement of the transformative potential of outcome-based, blended learning in higher technical institutions. The MHM model consists of both full-fledged online as well as conventional classroom instructions. Hence, the proposed MHM is a highly effective and efficient model to improve the basic knowledge of the heterogeneous student community and improve their technical knowledge and progression rate. The analysis of the proposed model’s results was computed based on C.O. (Course Outcomes) attainments, grading statistics, and the success rate. The research results show that the success rate of students who adopted the MHM improved by ~8% compared to conventional teaching methods. MHM increases Course Outcome-1 and Course Outcome-2 by 18% and 9%, respectively, which leads to the improvement of basic understanding and application of technology. A minimal impact on Course Outcome-3 and Course Outcome-4 was observed, which is less than 6% due to an increase in the design aspects of the respective courses that were adopted. MHM has been progressively recognized as one of the essential components for the faculties to nurture their students in an Outcome-Based Education (OBE) System.
Klasifikasi Tingkat Ancaman Kriminalitas Bersenjata Menggunakan Metode You Only Look Once (YOLO)

The research aim to recognize potential weapon threats through object detection on camera. This research utilize YOLO (You Only Look Once) method in object detection which implemented on Raspberry Pi 4. The process was by detecting object from the camera and classify the object class in 2 available classes : Gun and Knife. Meanwhile, in the classifying process, it also count the object in every classes. When the system detect object in the process, it will send notification in terms of threat level through android application so that the user or operator can mitigate the threat immediately. From the research, we achieve the mAP of 85.12% in which YOLOv4 tiny is used and the testing is done inside a room environment. In its application in detecting weapon in Raspberry Pi 4, the result is around 1.53 fps (frame per second), in which is accommodate to be implemented on, but with a very limited fps.
Project Activities At The University: Russian And European Experience

The article discusses the experience of implementing project activities at a university on the example of the project-oriented model of NovSU and the problem-oriented model of Aalborg University.The authors believe that the development of education models based on the introduction of project activities into the educational process can be among the methods of transforming Russian higher education.Modeling the educational process on the basis of project activities allows universities to achieve a systemic result associated with solving the problems of self-development of students and the formation of an individual educational trajectory.The authors have identified a number of identical components of the models as a result of a comparative analysis of Russian and European education models.The system-forming factor in the models is project activity, which provides not only an orientation towards the student's activity in the educational process (through solving specific problems within the framework of the project), but also involves modeling practical situations.Both universities provide for teamwork on the project by small groups of students, the implementation of the project by students every semester with subsequent defense, close communication with industrial partners, systemic changes in the principles of teaching and assessment of those academic disciplines for which the project is envisaged, personnel support for the work of project teams.The project-oriented model in the conditions of the Russian higher education system fulfills the task of complementing and updating the disciplinary approach to teaching, allowing to combine the individualization of education and an interdisciplinary approach.
Partial Wasserstein Covering

We consider a general task called partial Wasserstein covering with the goal of providing information on what patterns are not being taken into account in a dataset (e.g., dataset used during development) compared to another (e.g., dataset obtained from actual applications). We model this task as a discrete optimization problem with partial Wasserstein divergence as an objective function. Although this problem is NP-hard, we prove that it satisfies the submodular property, allowing us to use a greedy algorithm with a 0.63 approximation. However, the greedy algorithm is still inefficient because it requires solving linear programming for each objective function evaluation. To overcome this inefficiency, we propose quasi-greedy algorithms, which consist of a series of techniques for acceleration such as sensitivity analysis based on strong duality and the so-called C-transform in the optimal transport field. Experimentally, we demonstrate that we can efficiently fill in the gaps between the two datasets, and find missing scene in real driving scene datasets.
The Impact of Online Quizzes on Student Success

In today’s modern world, the pace of technological development can be con-sidered exponential. Education must constantly adapt to this dynamic devel-opment. It must be able to innovate, to use modern tools and methods that are effectively integrated into the learning process. Education should provide an appropriate learning environment to meet changing needs, one way of which is e-learning. This environment can be an excellent support for the learning process; however, it will hardly be effective without developing the right student learning attitude. The e-learning environment gives freedom and independence to the individual, at the same time. For the learner's individual endeavor to be successfully completed as expected, control and continuous feedback are needed. &#x0D; One way to do this is through self-quizzing. Self-quizzes, divided into units, related to the learning material, with appropriate difficulty and amount, can help to understand and engrave the processed material, and thus improve the effectiveness of learning. Self-quizzes create the opportunity for imme-diate feedback, which is a very important feature of an e-learning environ-ment. According to many scientific research, immediate feedback can greatly help maintain interest and motivation, and quizzes are suitable tools for this purpose. &#x0D; In our research, we sought to answer the question of how the continuous, self-monitoring practice opportunity provided by online quizzes affects stu-dent achievement. In the case of an online course held at the University of &#x0D; Dunaújváros in 2019, we examined whether students who continuously per-form self-quizzes will be more effective by the end of the learning process than their peers who are less receptive to independent self-quizzing. We also addressed the effect of the nature of time spent on self-reflexive quizzing on learning success.
Transformation of the Educational Process within Online Technologies Implementation in the Period of the Global Crisis

The COVID-19 pandemic has led to drastic changes in all spheres of life. In terms of education, the pandemic modified the way of teaching and learning. To meet the demands of new circumstances, the priorities shifted towards the implementation of online technology. Thus, the article examines the peculiarities of changes that happened in the educational sphere due to the online technology implementation. It analyzes the positive and negative aspects of this phenomenon. Based on the results of the survey conducted among educators, the article identifies weak points and challenges that should be overcome in the future for the successful operation of educational establishments online. Besides, it studies a material base and tools available for free use for world educational establishments as well as a problem of creating online groups with an optimal number of students. The purpose of the research is a comprehensive study of transformations happening in the educational process due to the application of online technology tools at the world level.
Do RNN States Encode Abstract Phonological Alternations?

Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details with limited training data.Despite the performance, the opacity of neural models makes it difficult to determine whether complex generalizations are learned, or whether a kind of separate rote memorization of each morphophonological process takes place.To investigate whether complex alternations are simply memorized or whether there is some level of generalization across related sound changes in a sequence-to-sequence model, we perform several experiments on Finnish consonant gradation-a complex set of sound changes triggered in some words by certain suffixes.We find that our models oftenthough not always-encode 17 different consonant gradation processes in a handful of dimensions in the RNN.We also show that by scaling the activations in these dimensions we can control whether consonant gradation occurs and the direction of the gradation.
An Innovative Approach for Enhancing Cloud Data Security using Attribute based Encryption and ECC

Cloud computing is future for upcoming generations. Nowadays various companies are looking to use Cloud computing services, as it may benefit them in terms of price, reliability and unlimited storage capacity. Providing security and privacy protection for the cloud data is one of the most difficult task in recent days. One of the measures which customers can take care of is to encrypt their data before it is stored on the cloud. Recently, the attribute-based encryption (ABE) is a popular solution to achieve secure data transmission and storage in the cloud computing. In this paper, an efficient hybrid approach using attribute-based encryption scheme and ECC is proposed to enhance the security and privacy issues in cloud. Here, the proposed scheme is based on Cipher text-Policy Attribute Based Encryption (CP-ABE) without bilinear pairing operations. In this approach, the computation-intensive bilinear pairing operation is replaced by the scalar multiplication on elliptic curves. Experimental results show that the proposed scheme has good cryptographic properties, and high security level which depends in the difficulty to solve the discrete logarithm problem on elliptic curves (ECDLP).
An empirical study of the development of types of educational staff's self-efficacy during the COVID-19 pandemic

Introduction. The COVID-19 pandemic has significantly affected educational organizations. Therefore, studying the psychological factors that can increase educational organization staff's efficiency during the pandemic is very relevant to the present day and socially significant. Aim: to empirically investigate the development of different types of educational staff's self-efficacy during the COVID-19 pandemic. Methods. J. Maddux and M. Scheer The Level of Self-Efficacy (modified by L. Boyarintseva), Short Occupational Self-Efficacy (adapted by O. Kredentser), and a passport-questionnaire. Results. There is an insufficient level of development of all types of staff' self-efficacy in educational organizations. Particularly low self-efficacy has been found in teaching subjects. Staff's organizational and professional characteristics (work experience, position, qualification category) and socio-demographic characteristics (marital status) are associated with different types of staff's self-efficacy. There is also a close relationship between staff's self-efficacy and the characteristics of educational organizations. Conclusions. The obtained data necessitate the creation of special psychological technologies for the development of various types of educational staff's self-efficacy.
Microblade Technology in Quartz during the Mesolithic in Eastern Middle Sweden

Thc authors present a material that has previously not been given much attcntion : microblades and microblade cores of quartz from eastern middle Sweden. The focus is on the technology. core types, geographical distribution and dating. The debate on how to interpret the quartz material ofthe region in cultural tenns and the role of the microblade technology in this discussion, are also dealt with. During recent years, many excavations and special surveys have supplied the archaeologists in easterll middle Sweden with new source material. An increased knowledge of quartz is an important factor in the dcvclopment of this field of research. The authors found it vely helpful to discuss the newly found cores and blades and their technical execution with Kjel knutsson of Uppsala University. Gcnerally speaking, the Mesolithic quartz materials from eastern middle Sweden are dominated by two methods ol'reduction; freehand-platform and bipolar-on-anvil. The latter method regularly produces thin flakcs that resemble microblades. In this articlc, however, focus will be on microblades sensu stricto. It seems that the production of'quartz microblades is more common than previously thought. Early reports from sites such as Sjövreten and Skumparberget are no longer anomalies.
Crime, Penal Transportation, and Digital Methodologies

This article argues that the ability to systematically analyze hundreds of thousands of life course events provides an opportunity to explore the ways in which an Australian convict archive was originally intended to be used, as well as a means of placing information supplied by subalterns within context.We also show how the digital reconstruction of the bureaucratic instruments of colonial labor management can be used to shed light on state actions.Using a combination of longitudinal and cross-sectional techniques, we place the experience of transported men and women within the colonial context of evolving labor markets, policing, and criminal justice systems, exploring questions of colonial class formation, gender, and labor mobility in the process.We end by pointing to how such datasets might be used in future undergraduate teaching and digitization initiatives.
Deterministic generation of high-dimensional entanglement between distant atomic memories via multiphoton exchange

Promising access to high-speed quantum networks relies on the creation of high-dimensional entangled memories that provide quantum communication with higher capacity of noisy quantum channels, thereby reducing the transmission time of information. Yet, the distribution of multidimensional entanglement between remote memory nodes is still faintly investigated. We propose an experimentally feasible protocol of deterministic generation of high-dimensional entanglement between distant multi-level atoms confined in high-finesse optical cavities and driven by laser pulses. Three-dimensional entanglement is generated deterministically between remote atoms by triggering a two-photon wavepacket, which mediates a superposition of states chosen by the laser pulse parameters. The efficient transfer of atomic states between remote nodes allows the construction of a three-dimensional quantum repeater, where the successful creation of entanglement can be verified by a simple method for reliable measurement of atomic ground Zeeman states.
Studi Kebijakan Mengenai Gerakan Literasi Sekolah

The purpose of this research was to find out the policy on the issuance of the Minister of Education and Culture Regulation on the development of character against the background of Indonesia's literacy level, which is ranked 64th out of 72 countries. The school literacy movement is an effort that is carried out comprehensively and continuously to make schools a learning organization whose citizens are literate throughout life through public involvement. The qualitative approach was designed for this study. The analysis showed that Starting from the existence of Permendikbud Number 23 of 2015, which is the basis of the School Literacy Movement, it must make several literacy programs in each region different because Indonesia is an autonomous country. To get around this, the government has made a legal umbrella and guidelines regarding the activities of the school literacy movement program. In implementing the school literacy movement, school principals have a very big share considering the government policy allows each school institution to develop programs that have been agreed upon by the government
Customer Opinion Mining by Comments Classification using Machine Learning

In this era of digital and competitive market, every business entity is trying to adopt a digital marketing strategy to get global business benefits.To get such competitive advantages, it is necessary for E-commerce business organizations to understand the feelings, thinking and seasons of their customers regarding their products and services.The major objective of this study is to investigate customers' buying behavior and consumer behavior to enable the customer to evaluate an online available product in various perspectives like variety, convenience, trust and time.It performs data analysis on the Ecommerce customer data which is collected through intelligent agents (automated scripts) or web scrapping techniques to enable the customers to quickly understand the product in given perspectives through other customers' opinion at a glance.This is qualitative and quantitative e-commerce content analysis in using various methods like data crawling, manual annotation, text processing, feature engineering and text classification.We have employed got manually annotated data from e-commerce experts and employed BOW and N-Gram techniques for Feature Engineering and KNN, Naïve Bays and VSM classifiers with different features extraction combinations are applied to get better results.This study also incorporates data mining and data analytics results evaluation and validation techniques like precision, recall and F1-score.
KonTra at CMCL 2021 Shared Task: Predicting Eye Movements by Combining BERT with Surface, Linguistic and Behavioral Information

This paper describes the submission of the team KonTra to the CMCL 2021 Shared Task on eye-tracking prediction.Our system combines the embeddings extracted from a finetuned BERT model with surface, linguistic and behavioral features, resulting in an average mean absolute error of 4.22 across all 5 eyetracking measures.We show that word length and features representing the expectedness of a word are consistently the strongest predictors across all 5 eye-tracking measures.
Perturbation Theory for Quantum Information

We report a lowest-order Taylor-like series expansion that enables efficient analytical computation of primary matrix functions of perturbed quantum states whose perturbation preserves the vector support of the original state. We apply our theory to find simple expressions for four important quantities in quantum information theory: the von Neumann entropy, the quantum relative entropy, the quantum Chernoff bound, and the quantum fidelity. Our results, which we elegantly represent using Fréchet derivatives, require only knowledge of the eigenspectrum of the unperturbed state and the density matrix elements of the perturbation, bypassing eigenanalysis of the full perturbed state. These results were recently used to derive the fundamental quantum limits of identifying diffraction-limited objects in passive incoherent imaging [1] and in an approach to quantify the covert communications capacity of a bosonic channel [2]. We discuss other avenues where our results could be applied.
Agile Methodology (SCRUM) Approach for Web Application Testing Process to Reduce Time, Cost and Improve the Quality

According to the finding of agile turn of events, Testing is perceived not to be a different stage, however a basic piece of Software Development with Coding. The Entire approach is being utilized by the agile group to heating quality to the Software Product. The agile group containing the Testers, who loan their aptitude in evoking instances of wanted conduct from clients. They work together with the improvement group that guides Coding, to transform those into executable details. Testing and Coding are being performed gradually and iteratively until it offers sufficient benefit to delivery to create each element developing is made. Its quadrants give a supportive scientific classification which helps groups in distinguishing and arranging the testing need.
Unsupervised Domain Extension for Nighttime Semantic Segmentation in Urban Scenes

This paper deals with the problem of semantic image segmentation of street scenes at night, as the recent advances in semantic image segmentation are mainly related to daytime images.We propose a method to extend the learned domain of daytime images to nighttime images based on an extended version of the CycleGAN framework and its integration into a self-supervised learning framework.The aim of the method is to reduce the cost of human annotation of night images by robustly transferring images from day to night and training the segmentation network to make consistent predictions in both domains, allowing the usage of completely unlabelled images in training.Experiments show that our approach significantly improves the performance on nighttime images while keeping the performance on daytime images stable.Furthermore, our method can be applied to many other problem formulations and is not specifically designed for semantic segmentation.
Team Ohio State at CMCL 2021 Shared Task: Fine-Tuned RoBERTa for Eye-Tracking Data Prediction

This paper describes Team Ohio State's approach to the CMCL 2021 Shared Task, the goal of which is to predict five eye-tracking features from naturalistic self-paced reading corpora.For this task, we fine-tune a pretrained neural language model (RoBERTa; Liu et al., 2019) to predict each feature based on the contextualized representations.Moreover, motivated by previous eye-tracking studies, we include word length in characters and proportion of sentence processed as two additional input features.Our best model strongly outperforms the baseline and is also competitive with other systems submitted to the shared task.An ablation study shows that the word length feature contributes to making more accurate predictions, indicating the usefulness of features that are specific to the eye-tracking paradigm.