Reviewerly/exHarmony huggingface dataset:
Gamificación, una forma divertida de aprender

This research is a pedagogical contribution that aims to promote the widespread use oftechnological tools in classroom practices, as some teachers resist entering the digital worlddespite having technological resources in the classroom; in many cases they are limited todeveloping own classes of traditional pedagogy, which are monotonous, repetitive, withunmotivated students, who suppose the existence of active teachers and passive students.The pedagogical design is based on the principles of gamification to facilitate thedevelopment of reading skills in children from the Stars Kids institute in the city of Bogota,whose ages range from 6 to 8 years corresponding to the first to third grades of basicprimary education. As a method, the instrumental single-case study was used, whichfavored the reflective understanding of classroom experiences and institutional imagery.The process was developed in four points: definition of the study object, on-siteinvestigation, data analysis, and the design of gamified pedagogical activities.The research showed that gamified pedagogical activities are a valuable strategy foreducation because they naturally favor student learning. At this time, technology venturesinto the life scenes of all people, and by integrating them with the game, collaborativeenvironments are achieved that lead to the achievement of common goals and challenges.Key words: Tic, pedagogy, gamification, reading skills, sociocultural practice, playexperiences, concepts, environments, skills, reading, knowledge, sociocultural,experiences, imaginary.
Keefektifan Penerapan Model Talking Stick Terhadap Hasil Belajar Tema Cita-Citaku

This study aims to describe the effectiveness of the Talking Stick model to the learning outcomes of students in the theme of the ideals of my fourth grade students at SD N 1 Sukodadi. This research method used is a quasi- experimental method with the research design used was pre experimental design. The sample in this study were 32 students. The results of data analysis showed that the learning outcomes of students in the posttest in the experimental class were effectively used at 0,14. This mean learning by applying an effective Talking Stick model with high criteria towards learning outcomes of class IV students in learning the theme of my ideals at SD N 1 Sukodadi.
BLOCK CHAIN BASED EFFICIENT MANAGEMENT OF IOT SMART VIDEO SURVEILLANCE SYSTEM

A management of surveillance of video process which is based on block chain technology has been proposed. The system which has been intended contains a network of block chain with internal nodes which are trusted. The distributed ledger of blockchain includes the metadata of the surveillance footage, thereby stopping the possibility of the data forgery. The architecture of proposed system saves and encrypts the footage, generates a license inside the block chain and exports the footage. Since the private database manages the decryption key for the footage in the block chain, it is not exposed by the internal nodes illegally. Also, the internal administrator can handle and export surveillance footage safely by decrypting the frames stored in the block chain and reconstructing the footage which can be later downloaded.
Trading Agent Competition with Autonomous Economic Agents

In this demonstration, we introduce a system that facilitates trading agent competitions. Competitions mirror a Walrasian Exchange Economy. Each agent is endowed with a set of digital assets and preferences over them. Agents then trade these assets with each other to increase their respective utilities. They negotiate one-on-one to arrive at an optimal trade, and if successful, settle their transaction trustlessly on an emulated permissionless blockchain. This system is a precursor to a trading platform for digital assets and crypto-tokens in which agents trade on behalf of their users.
Place Recognition with DAG-CNN

This paper presents the development of a convolutional neural network with a directed acyclic graph architecture (DAG-CNN) focused on the recognition of places. The network is focused on identifying six types of rooms in various houses. For this purpose, five houses have been built in a virtual environment from which the training and validation database has been obtained through an on-site panning camera. In order to select the number of filters required for the proposed architecture, the internal behavior of each training has been verified through neuron activation heat maps in order to reduce the learning repetitions of little relevant objects or the characteristics of the scene as much as possible, obtaining a network capable of recognizing 96.5% of the individual images from room sequence photographs and 100% individual recognition of each room (complete sequence). Thus, the capacity and the robustness of the selected architecture for recognizing indoor places are demonstrated.
Method of calibrating an active optical stereoscopic system that consists of a monocular camera and structured illumination in the form of a line

This article is devoted to the development and study of a method of calibrating an active stereoscopic system that consists of a monocular camera and a source of structured illumination in the form of a line. The chief feature of the proposed method is to use a standard checkerboard calibration pattern as the only basic equipment needed for calibration. The proposed calibration method has been experimentally studied on actual data in order to compute the distance to objects observed by the camera and illuminated by a projector. The experimental results, along with theoretical calculations, confirm that the proposed calibration method can be used for 3D modeling systems and for determining the distance to surrounding objects.
A decade since the International Year of Planet Earth – Earth Sciences for society

Developed between 2007 and 2008, the International Year of Planet Earth (IYPE) was proclaimed by United Nations Organization with the objective to divulge the importance of the Earth Sciences for society and to alert for the main problems mankind will face in this Century related to ten big themes: Groundwater, Megacities, Climate, Earth crust and core, Natural disasters, Oceans, Natural resources (minerals) and Energy, Soils, Earth and health (or medical geology) and Earth and life. After ten years of the suggestions and recommendations to be developed by geoscientists there were important advances in some of those themes such as Climate, Earth crust, and core and Natural resources and Energy. In the other seven years, there was relatively few scientific or technological advances in the word. This shows that one decade was not enough for mankind to get knowing and solving the big problems itself caused and continues to cause to the planet. In spite of this, the Brazilian geoscientific community was sensitive to most of the IYPE themes and promoted the divulging of Earth sciences through workshops, symposia, congresses, classes, becoming one of the most active groups in the world.
In-place bijective burrows-wheeler transforms

One of the most well-known variants of the Burrows-Wheeler transform (BWT) [Burrows and Wheeler, 1994] is the bijective BWT (BBWT) [Gil and Scott, arXiv 2012], which applies the extended BWT (EBWT) [Mantaci et al., TCS 2007] to the multiset of Lyndon factors of a given text. Since the EBWT is invertible, the BBWT is a bijective transform in the sense that the inverse image of the EBWT restores this multiset of Lyndon factors such that the original text can be obtained by sorting these factors in non-increasing order.In this paper, we present algorithms constructing or inverting the BBWT in-place using quadratic time. We also present conversions from the BBWT to the BWT, or vice versa, either (a) in-place using quadratic time, or (b) in the run-length compressed setting using 𝒪(n lg r / lg lg r) time with 𝒪(r lg n) bits of words, where r is the sum of character runs in the BWT and the BBWT.
Asset Integration: An Exceptional Undergraduate Student Project.

This paper outlines an exceptional 1st year undergraduate student project that involves the creation of a CG asset (goblet), and the integration of that asset into a live action photographed background. The final created shot of the animated asset shows a high level of photo-realism, and is an exceptionally close match to the live action reference photography of the real goblet.
L'attualità degli studi docimologici

Scholastic evaluation is an issue that has long engaged research in the fields of humanities, social sciences and education. The evaluation involves psychological variables and is inextricably linked to learning and teaching: monitoring the achievement of the objectives on which the teaching action is based necessarily involves measuring the results achieved. In recent years the theme of evaluation has taken on a central role in the scholastic debate, enriching itself with reflections and connotations that today give us a very different idea of ​​evaluation that is certainly more complex than in the past. To reach these conclusions, the step was not short nor without problems in the scientific community. Compared to traditional models of evaluation, a new positioning had to be sought, reasoning based on objective measurement criteria, promoting an idea of ​​mature evaluation and above all an evaluation of one's own training potential. The present work aims to carry out an examination of the peculiar problems of docimology, tracing its developments over time and to propose a reflection on the relevance of docimological studies.
A WATERMARKING SCHEME TO PROTECT 3D MODELS

Three-dimensional (3D) models are used to imitate, represent, and resemble objects in a real world. But with its emergence, comes also issuesrelating to ownership claiming. There is an obvious need for multimedia data copyright protection and ownership claiming techniques and one seentechnique is digital watermarking. Hence, this study demonstrated an invisibly-blind robust semi-public watermarking scheme to protect 3D modelsfrom data compression attack. The scheme used the Autodesks 3DS Max software which generated a 3D polygonal mesh model. The watermarkingwas made on its mesh vertices where a 3-bit sequence was embedded through its binary file on the chunk of the file containing the vertices list andon its 0 bits. A software was designed for the process of embedding and extraction of the watermark. Data compression, as the form of attack on 3Dmodels, was done in Autodesks maxzip archiving system wherein the file size of a 3D model was narrowed down to a smaller file size for purposesof minimum storage and portability. The software then determined the presence of the watermark after decompression of the attackedwatermarked file. Findings show that the watermarking scheme used in this study exhibited an imperceptible, detectable, and compression-resilientwatermark for 3D polygonal mesh models.
Meaningful and Memorable Learning: Integrating TPR and Youtube Videos to teach Vocabulary

The teaching of vocabulary is very essential in teaching a particular language. In Indonesia, English is taught from kindergarten up to higher educations. Unfortunately not all of the teachers in those levels especially in kindergartens and primary schools major in English or at least have good English proficiency. That is why English Language Education Study Program, the Faculty of Teacher Trainings and Educational Sciences, Pakuan University always conducts community service to provide trainings to teachers from any part of the city. The first thing done before the community service was doing need analysis. In 2019, the result of the need analysis was the teaching of vocabulary which is fun and meaningful. 28 teachers were involved in this research. They were divided into two groups to conduct experiment. From the experiment, it is proven that the training given to the teachers increase their understanding about TPR and the teaching of vocabulary. The teachers were also given questionnaire to find out their perception on the use of TPR and YouTube and from the questionnaire the teachers think that their knowledge on the teaching using TPR increased their knowledge and they can find benefits in using TPR and YouTube in the classroom namely: the use of TPR itself can help them accommodate students’ different learning styles, teach vocabulary in context so that it is more meaningful, and the teaching learning situation becomes more fun.
DEVELOPMENT OF E-LEARNING APPLICATIONS AS A MEANS OF ONLINE LEARNING IN SMP AL AZHAR 1 BANDAR LAMPUNG

In current teaching and learning activity on SMP Al Azhar 1 Lampung's Port, tutorial material application by teacher is done by use of conventional method.  In students appreciative data processing be done by use of calculator then menginput assesses student into excel's file then printed by that point data then that point data is kept in schooled cabinet so at alarms its happening lose point and damage data on students appreciative data. Base that thing therefore needed Application Development E Learning  As Medium Of Learning Online  at SMP Al Azhar 1 Lampung's Port. Base observational result in analyse Application Development E Learning  As Medium Of Learning Online  at SMP Al Azhar 1 Lampung's Port by use of system scheme utilize that web waters down deep implementation process and Application Development E Learning  As Medium Of Learning Online  at SMP Al Azhar 1 Lampung's Port.
Refining Constructive Hybrid Games.

We extend the constructive differential game logic (CdGL) of hybrid games with a refinement connective that relates two hybrid games. We use this connective to prove a folk theorem relating hybrid games to hybrid systems.
Single Believe State Generation for Handling Partial Observability with MCTS in StarCraft

A significant amount of work exists on handling partial observability for different game genres in the context of game tree search. However, most of those techniques do not scale up to RTS games. In this paper we present an experimental evaluation of a recently proposed technique, "single believe state generation," in the context of StarCraft. We evaluate the proposed approach in the context of a StarCraft playing bot and show that the proposed technique is enough to bring the performance of the bot close to the theoretical optimal where the bot can observe the whole game state.
Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference

Systems for ML inference are widely deployed today, but they typically optimize ML inference workloads using techniques designed for conventional data serving workloads and miss critical opportunities to leverage the statistical nature of ML. In this paper, we present Willump, an optimizer for ML inference that introduces two statistically-motivated optimizations targeting ML applications whose performance bottleneck is feature computation. First, Willump automatically cascades feature computation for classification queries: Willump classifies most data inputs using only high-value, low-cost features selected through empirical observations of ML model performance, improving query performance by up to 5x without statistically significant accuracy loss. Second, Willump accurately approximates ML top-K queries, discarding low-scoring inputs with an automatically constructed approximate model and then ranking the remainder with a more powerful model, improving query performance by up to 10x with minimal accuracy loss. Willump automatically tunes these optimizations' parameters to maximize query performance while meeting an accuracy target. Moreover, Willump complements these statistical optimizations with compiler optimizations to automatically generate fast inference code for ML applications. We show that Willump improves the end-to-end performance of real-world ML inference pipelines curated from major data science competitions by up to 16x without statistically significant loss of accuracy.
Load Balancing Algorithms in Cloud Computing

Cloud computing plays an important role in enhancing the effective sharing of resources in virtual machines. Scheduling and load balancing are the two common concepts that cloud computing relies on ensuring that a prescribed task is assigned to the most appropriate virtual machine. Also, cloud computing should have the ability to handle multiple independent tasks that are arriving and execute them in the same or multiple nodes. In a heterogeneous environment, static and dynamic scheduling plays an important role by enhancing the allocation of tasks to the appropriate resources to satisfy the internet users' requests and making cloud computing technology more efficient. This work aims to evaluate and discuss important algorithms that will help improve the load balancing performance of cloud systems.
User-Models to Drive an Adaptive Virtual Advisor: Demonstration

Agents that adapt to their user need to have knowledge of their user and expertise on how best to adapt to that type of user. In this paper we describe the addition of an agent's expertise and collection of machine-learnt user profiles to the proposed extended FAtiMA (Fearnot AffecTive Mind Architecture) cognitive agent architecture. A study to evaluate the extended architecture is presented which compares the benefit (i.e. reduced stress and increased rapport) of tailoring dialogue (i.e. empathic or neutral) to the specific user.
PENGGUNAAN ALAT PERAGA SUMPIT UNTUK MENINGKATKAN HASIL BELAJAR MATEMATIKA KELAS XII MIPA 2 SMAN 1 PANGKALAN KERINCI

This research starts from the low results of learning mathematics students. This can be seen in the daily test of students who are below the Minimum Completion Criteria (KKM). One reason is a low understanding of mathematical concepts. Low understanding of concepts is due to the fact that mathematics is still abstracted by students. Abstract mathematical concepts for students will be easily understood when learning using teaching aids. Learning carried out is direct learning using chopstick props. This study aims to determine the improvement in learning outcomes of students of class XII MIPA 2 SMAN 1 Pangkalan Kerinci and carried out in two cycles consisting of planning, action, observation and reflection. The research data collected is data on learning outcomes and field notes. The collected data was analyzed descriptively. The results of this study indicate that the application of direct learning models using chopstick props can improve learning outcomes. Increased learning outcomes for KD 3.1 amounted to 22.58% or reached 96.77% of students who were above the KKM. While for KD 4.1 the increase from cycle I to cycle II is 22.58% or reaches 93.55% of students are above the KKM.
DEVELOPING A COMPUTER VISION RE-IDENTIFICATION SYSTEM

Background. The rapid growth of computational power of machines and amount of data caused exploding usage of computer vision in a large variety of tasks and in particular for people recognition.Objective. The aim of the paper is to propose a computer vision re-identification system based on research. Also improvements for detection and recognition models of the system are made.Methods. We used classical computer vision and deep learning techniques to create the system.Results. The main contribution of the research is a description of the optimal system structure with a trade-of between speed and quality. Furthermore, requirements for an environment are proposed, which allows to set up the system in the real world with guaranteed quality.Conclusions. Real-time computer vision re-identification system was developed and can be used in a production environment which satisfy requirements.
Regulating Accuracy-Efficiency Trade-Offs in Distributed Machine Learning Systems.

In this paper we discuss the trade-off between accuracy and efficiency in distributed machine learning (ML) systems and analyze its resulting policy considerations. This trade-off is in fact quite common in multiple disciplines, including law and medicine, and it applies to a wide variety of subfields within computer science. Accuracy and efficiency trade-offs have unique implications in ML algorithms because, being probabilistic in nature, such algorithms generally exhibit error tolerance. After describing how the trade-off takes shape in real-world distributed computing systems, we show the interplay between such systems and ML algorithms, explaining in detail how accuracy and efficiency interact particularly in distributed ML systems. We close by making specific calls to action for approaching regulatory policy for the emerging technology of real-time distributed ML systems.
Improving Chinese Word Representation with Conceptual Semantics

The meaning of a word includes a conceptual meaning and a distributive meaning. Word embedding based on distribution suffers from insufficient conceptual semantic representation caused by data sparsity, especially for low-frequency words. In knowledge bases, manually annotated semantic knowledge is stable and the essential attributes of words are accurately denoted. In this paper, we propose a Conceptual Semantics Enhanced Word Representation (CEWR) model, computing the synset embedding and hypernym embedding of Chinese words based on the Tongyici Cilin thesaurus, and aggregating it with distributed word representation to have both distributed information and the conceptual meaning encoded in the representation of words. We evaluate the CEWR model on two tasks: word similarity computation and short text classification. The Spearman correlation between model results and human judgement are improved to 64.71%, 81.84%, and 85.16% on Wordsim297, MC30, and RG65, respectively. Moreover, CEWR improves the F1 score by 3% in the short text classification task. The experimental results show that CEWR can represent words in a more informative approach than distributed word embedding. This proves that conceptual semantics, especially hypernymous information, is a good complement to distributed word representation.
Contact-tracing issues

England is continuing to remove coronavirus restrictions but efforts to track and stop infections are still struggling, reports Adam Vaughan.
Unsur-Unsur Fantasi dalam Motif Novel Franskenstein Karya Marry Shelly

This writing study of novels which contain elements of fantasy. Data taken from a novel titled frankenstein the work of marry shelly. That has been a problem in writing this is fantasy elements that was found in a motive. The purpose of this writing is described the fantasy elements that was found in a motive a novel franskenstein shelly marry work. Data collection techniques use the technique of documentation. The result of for the assessment of novels states that there are several motives that was found in the novel. Namely the motives have good enough fantasy elements, oddity as well as something that was felt to be does not make sense that was found in the motives. Motives which contain elements of fantasy of them the success of created man, pursued shadow fear, the sinister which is thirsty creature is knowledge, the sinister which is benevolent creature, the wickedness of human beings, heartache and revenge, the creation of the new man. In that they exist motives fantasy elements commit the morbidly artist footage, oddity, as well as something that does not make sense.
Neural networks in recognition of handwriting

Artificial neural networks consist of many simple elements capable of processing data. These are tools inspired by the construction of the human brain, used in machine learning. The aim of the research was to analyze the occuracy of the created neural network in the process of handwriting recognition. The article presents the results obtained during the learning and testing of a convolution network with a different number of hidden layers. Each time learning and testing the network was carried out using the same set of images (taken from the publicly available IAM database) depicting handwritten words in English.