Reviewerly/exHarmony huggingface dataset:
Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras

Increasing demand for meat products combined with farm labor shortages has resulted in a need to develop new real-time solutions to monitor animals effectively. Significant progress has been made in continuously locating individual pigs using tracking-by-detection methods. However, these methods fail for oblong pens because a single fixed camera does not cover the entire floor at adequate resolution. We address this problem by using multiple cameras, placed such that the visual fields of adjacent cameras overlap, and together they span the entire floor. Avoiding breaks in tracking requires inter-camera handover when a pig crosses from one camera's view into that of an adjacent camera. We identify the adjacent camera and the shared pig location on the floor at the handover time using inter-view homography. Our experiments involve two grow-finish pens, housing 16-17 pigs each, and three RGB cameras. Our algorithm first detects pigs using a deep learning-based object detection model (YOLO) and creates their local tracking IDs using a multi-object tracking algorithm (DeepSORT). We then use inter-camera shared locations to match multiple views and generate a global ID for each pig that holds throughout tracking. To evaluate our approach, we provide five two-minutes long video sequences with fully annotated global identities. We track pigs in a single camera view with a Multi-Object Tracking Accuracy and Precision of 65.0% and 54.3% respectively and achieve a Camera Handover Accuracy of 74.0%. We open-source our code and annotated dataset at https://github.com/AIFARMS/multi-camera-pig-tracking
Autonomous bot with ML-based reactive navigation for indoor environment

Local or reactive navigation is essential for autonomous mobile robots which operate in an indoor environment. Techniques such as SLAM, computer vision require significant computational power which increases cost. Similarly, using rudimentary methods makes the robot susceptible to inconsistent behavior. This paper aims to develop a robot that balances cost and accuracy by using machine learning to predict the best obstacle avoidance move based on distance inputs from four ultrasonic sensors that are strategically mounted on the front, front-left, front-right, and back of the robot. The underlying hardware consists of an Arduino Uno and a Raspberry Pi 3B. The machine learning model is first trained on the data collected by the robot. Then the Arduino continuously polls the sensors and calculates the distance values, and in case of critical need for avoidance, a suitable maneuver is made by the Arduino. In other scenarios, sensor data is sent to the Raspberry Pi using a USB connection and the machine learning model generates the best move for navigation, which is sent to the Arduino for driving motors accordingly. The system is mounted on a 2-WD robot chassis and tested in a cluttered indoor setting with most impressive results.
DUNE Computing

as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment.
MOTIVATING LEARNING WITH THE USE OF DIGITAL MEDIA IN THE MIDST OF A PANDEMIC

The educational sytem, from elementary to tertiary level, collapsed during 2020 due to the novel coronavirus disease 2019 (COVID-19), not only in Peru but across Latin America. This is a descriptive study of the process followed in the course called Anthropoly of Education, of the Faculty of Education in a private university located in Lima, Peru. The aim of the study was to motivate learning of both the course and the improvement of English command as a second language, using digital media. The objective of this research is to show how it is possible to motivate learning in the midst of adversity by incorporating digital media. The design that was followed was qualitative and the sample was formed by 33 students from different regions of the country and on scholarship status. For the study, there was a differentiation on what was done in the course and the English language improvement.The results highlight a high motivation of the student body both in participation and in learning outcomes. It is concluded that this was possible due to the institutional support; the coordinated work of the teaching staff; the use of an instructional design that facilitated adjustments in the process; the bond that was established with the students; prior knowledge of digital media by teachers and students and the collaborative work generated between them. All done through digital media.
Role of Community Participation in Promoting Basic Education Services Delivery in Sabon Gari Local Government Area of Kaduna State

The paper assesses the role of community participation in promoting Basic education service delivery in Sabon Gari local government area of Kaduna State. The study highlights the significant problems facing community participation, such as inadequate functioning of SBMCs, inadequate clarity of roles of SBMCs. An objective had been set to determine the role of SBMC in promoting basic education service delivery in Sabon Gari local government area. The study adopted collaboration theory, which helped in explaining the role of community participation on basic education in Sabon Gari local government area of Kaduna State. The researcher has employed primary method in collecting data for the study; the primary data has been gathered through a questionnaire and oral interview, mainly with simple percentage and chi-square statistical analysis. The study reveals that the SBMCs plays significant role in promoting basic education service delivery. The study recommends that any program/project to be executed should be identified by the community based on the felt need of the community. Boosting the level of community participation through engagement to raise awareness on basic education.
Perbandingan Aktivitas Belajar Siswa Yang Tinggal di Asrama dan di Luar Asrama Madrasah Aliyah Swasta (MAS) YASTI Singkawang Tahun 2019/2020

The results showed that the average learning activity of students living in dormitories was 98.35 with a percentage of 78% (high), with an average visual activities of 21.53 with a percentage of 86% (high), oral activitis of 19.48 with a percentage 77% (high), listening activities at 20.93 with a percentage of 83% (high), writing activities of 17.69 with a percentage of 70% (high), and mental activities of 18.69 with a percentage of 74% (high). While the average learning activity of students living outside the dormitory was 72.12 with a percentage of 57% (moderate), with an average visual activities of 16.21 with a percentage of 77% (high), oral activities of 13.53 with a percentage of 77% (high), oral activities of 13.53 with a percentage of 77% 64% (high), listening activities at 15.46 with a percentage of 73% (high), writing activities of 12.19 with a percentage of 58% (moderate), and mental activities of 14.95 with a percentage of 71% (high). Thus the average study activity of students living in dormitories was 98.35 with a percentage of 78% (high), and students living outside the dormitory at 72.12 with a percentage of 57% (moderate), with an average difference of 26,227 and a percentage difference of 21%. Hypothetical test results show a t count value greater than the table t (9,290 &gt; 1,980). It can be concluded that there are significant differences in learning activities in Islamic Cultural History subjects between students living in dormitories and living outside the Private Madrasah Aliyah Dormitory (MAS) Yasti Singkawang in 2019/2020.
Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic

Recent text-to-image matching models apply contrastive learning to large corpora of uncurated pairs of images and sentences. While such models can provide a powerful score for matching and subsequent zero-shot tasks, they are not capable of generating caption given an image. In this work, we repurpose such models to generate a descriptive text given an image at inference time, without any further training or tuning step. This is done by combining the visual-semantic model with a large language model, benefiting from the knowledge in both web-scale models. The resulting captions are much less restrictive than those obtained by supervised captioning methods. Moreover, as a zero-shot learning method, it is extremely flexible and we demonstrate its ability to perform image arithmetic in which the inputs can be either images or text and the output is a sentence. This enables novel high-level vision capabilities such as comparing two images or solving visual analogy tests.
Assessment of the proficiency level in digital competences of Higher Education instructors in Portugal

The study aims to assess the level of digital competences of higher education instructors in Portugal. The methodology used was a survey, involving an online self-assessment questionnaire, based on DigCompEdu, a framework developed and validated by the European Commission. The survey collected data in three dimensions: personal (gender, level of education, age group and career years), teaching (college levels and teaching modality) and institutional (higher education subsystems, type of establishment and administrative region). The questionnaire was answered by 695 participants. The data analysis involved the application of statistical techniques such as t-test and ANOVA. The results showed an intermediate level of proficiency in the instructors’ digital competences. There were no statistically significant effects of variables such as: gender, age group, career years, type of establishment and administrative region. However, teachers with a higher level of academic qualifications and who teach at postgraduate levels, as well as teaching at a distance and in technical institutions showed a higher level of digital competence. The study concludes that the following actions are needed: the development of frameworks focusing on online higher education and the development of continuous training for instructors to improve their digital proficiency level.
StrokeNet: Stroke Assisted and Hierarchical Graph Reasoning Networks

Scene text detection is still a challenging task, as there may be extremely small or low-resolution strokes and close or arbitrary-shaped texts. In this paper, StrokeNet proposes to effectively detect the texts by capturing the fine-grained strokes and inferring structural relations between the hierarchical representations of each text area in the graph-based network. Different from existing approaches that represent the text area by a series of points or rectangular boxes, we directly localize the strokes of each text instance. We introduce Stroke Assisted Prediction Network (SAPN), which performs hierarchical representation learning of text areas, effectively capturing extremely small or low-resolution texts. We extract a series of text- and stroke-level rectangular boxes on the predicted text areas, which are treated as graph nodes and grouped to form the corresponding local graphs. Hierarchical Relation Graph Network (HRGN) then performs relational reasoning and predicts the likelihood of linkages among graph nodes of different levels. It efficiently splits the close text instances and grouping node classification results into the arbitrary-shaped text area. We introduce a novel dataset with stroke-level annotations, namely <i>SynthStroke</i>, for offline pre-training of widespread text detectors. Experiments on benchmarks verify the State-of-the-Art performance of our method.
APLIKASI PENJUALAN BATIK JAMBI FARAS BERBASIS WEB

Jambi Faras Batik Shop is a business engaged in the sale of Jambi batik clothes. Currently, Jambi Faras Batik Shop wants to increase its sales level by expanding its sales outside the city of Jambi to seek greater sales profits. The purpose of this research is to build a web-based computerized sales application that includes product catalogs, sales transactions, and reports that are expected to increase batik sales turnover. This application is built using the PHP programming language and MySQL database. The input to this application is in the form of admin data, item data, sales data, and customer data. Process data in this application are in the form of admin data processing, goods data processing, sales data processing, and customer data processing. The output of this application is a sales report. The results of this study are in the form of a web-based sales application that can help Jambi Faras Batik Stores in marketing merchandise with a wider range and make it easier to make sales reports.
A Systematic Study of the Control Failures in the Equifax Cybersecurity Incident

The Equifax data breach, announced in September 2017, occupies the top 10 charts of the largest data breaches in history. While the 148 million affected persons do not bring the event to the top, but the sensitivity of the data stolen makes it one of the most impactful incidents for consumers. The data breach has been investigated by various federal and state agencies that collected and analyzed over 45,000 pages of related documents. This research is built upon those findings and identifies the root causes of the control failures of Equifax’s cyber defense system, and determines the improvements to reduce the likelihood of future similar incidents. We reconstructed the Equifax hierarchical cyber safety control system, identified what parts failed and why, and determined the necessary improvements by applying our Cybersafety method, inspired by Causal Analysis using Systems Theory (CAST). This work demonstrates how to discover reasons for the failure of safety and security mechanisms and compose improvement actions. It also provides a set of points individuals can evaluate in their organizations.
VR을 이용한 중국어 말하기 교육방안 - 개별 연습도구의 개발을 중심으로

The purpose of this study aims to try to develop a speaking practice tool using virtual reality(VR) technology and share the process of development, to discuss what to keep in mind before development and what to improve after development. The study first reviews the meaning of VR as an educational medium based on “the cone of experience(Dale 1969).” And then, it looks back on the transformation of educational media and discusses the role of VR as a foreign language learning medium. Next, the study describes the process that the VR contents have been produced based on theoretical review. Finally, it introduces the path that access to the VR contents and discusses improvements after analyzing the survey results from VR experience participants.
Implicatures in Altfatah Nando’s Short Movie Terlanjur Mencinta

YouTube has been flooded with contents within a movie genre, mostly the products by junior creators. It is therefore important to appreciate their works to maintain their creativities and innovations. Positive responses to such literary works are also required to improve their quality writing. The current study was aimed at identifying and at the same time construing the implicatures found in each act of the movie entitled “Terlanjur Mencinta” directed by Alfatah Nando. George Yule’s pragmatic theory (1996) was used in relation to implicatures caused by conversational maxims (Grice, 1975) supported by linguistic evidence-based contextual interpretation, namely utterances and stage directions. Findings show that generalized conversational implicatures were identified, namely 12 implicatures in which 42% was due to violation of manner maxim, 33% attributed to that of relation maxim, 17% due to that of quantity maxim, and 8% due to that of quality maxim. In addition, 4 conventional implicatures were found in the monologue. The study concludes that the implicatures can be easily understood through the contexts of situations. It is recommended that future researchers can formulate the ideal proportion and distribution of implicatures in a particular text in terms of quality, employing comparative rhetoric and a special research instrument.
Design and Implementation of School English Course Teaching System Based on Moodle

In this paper, the author studies on the design and implementation of school English course teaching system based on Modular Object-Oriented Dynamic Learning Environment (Moodle). The basic task of the subject technology of teaching is to research how to improve the efficiency of teaching by using various medium. Our final purpose is to make teaching efficiency best. This article according to the new network teaching theory and teaching practice, has discussed based on the Moodle platform English school-based curriculum development. Based on the Moodle platform for middle school English school-based curriculum development and implementation can not only provide the school-based curriculum, the curriculum design of the new method and new ideas, but also for other school based curriculum development and implementation of reference, through the introduction of Moodle, for teachers to provide an economic application, open teaching environment, promoting the development of school-based curriculum development and school information technology development, but also for the promotion of open source software in the primary and secondary school popularization and application for a contribution.
Automatic Index Point Detection and Semantic Indexing of Educational Videos

The purpose of this study is to identify the need for automatic video indexing and present a system to automatically construct a digital video index for better information retrieval. This project aims to solve a specific problem i.e., extracting keywords from video frames so that a lecture may be split. An index point is a term that additionally carries the relative video time instance's timestamp. To extract the video's textual information, Google's OCR Engine is used. The research is confined to educational videos that include presentation slides in English only. We have tested three methods for index point detection and finally concluded that automatic index points detection and extraction using deep learning neural network outperforms the other two methods in terms of speed and accuracy.
ABLTagger (Lemmatizer) - 3.1.0

A neural Lemmatizer for Icelandic.In this submission, you will find a pretrained lemmatizer model for ABLTagger v3.1.0. In this submission we provide a small lemmatizer that accepts as input the tokens and tags from the revised tagset. The lemmatizer achieves an accuracy of 98.3% on MIM-Gold (21.05, cross-validation). Það er minni nakvaemni en Nefnir.For installation, usage, and other instructions see https://github.com/cadia-lvl/POS/releases/tag/m6You should also check if a newer version is out (see README.md - versions)on CLARIN:- Model files-------------------------------------------------------------------------------------------Lemmari fyrir islensku.I þessum pakka er forþjalfað lemmunar likan fyrir ABLTagger v3.1.0. I þessari utgafu er litill lemmari sem tekur inn toka og mork ur nýja markamengið. Lemmarinn naer 98.3% nakvaemni a MIM-Gull (21.05, krossprofanir). Það er minni nakvaemni en Nefnir.Fyrir uppsetningar-, notenda- og aðrar leiðbeiningar sja https://github.com/cadia-lvl/POS/releases/tag/m6Einnig er gott að athuga þar hvort ný utgafa se komin ut (sja README.md - versions)A CLARIN:- Gogn fyrir likan
Narrativas docentes para la producción de memorias: Prospectiva de la escolarización en pandemia

In this article we address narrative records produced by secondary and higher education teachers from provinces of northwestern Argentina, with the aim of making memories of pedagogical experiences, focusing on some openings that could be capitalized for the drawing of guidelines aimed at the revision of schooling secondary in the post-pandemic. A corpus was formed with the records produced by 74 male and female professors at different times in 2020. The records were produced in virtual logs housed in two virtual classrooms on digital platforms. The narratives were reflexively approached in biweekly synchronous encounters with the participants in order to collectively explore their meanings. The work presents three axes on which the exercise of memorizing the pandemic has been carried out and concludes by recovering some professional learning built in the course of the experience as a critical event in school life.
Russian film education: problems and prospects

The subject of the study is education in the field of culture and art, its purpose is to assess public policy in the field of art education. The article analyzes the reasons for the appearance in the film industry of specialists with a low level of training. The study was based on the regulatory legal acts of the Ministry of Education and Science of Russia, data from Federal State Statistics Service, portals of the Ministry of Education and Science of Russia: ‘Monitoring the employment of graduates’ and ‘How to enter the UNIVERSITY correctly’. During the study, a hypothesis was formulated on the trend of an increase in the training of specialists in creative specialties in non-core educational organizations. The hypothesis was tested on the basis of a regressive analysis of the distribution of admission quotas to higher education organizations, regardless of their departmental affiliation, and the construction of a linear regression. The article applies methods based on the establishment of an internal relationship of phenomena, their mathematical description. According to the analysis, the assessment of the quality of education in the field of culture and art should be determined not only by conducting online exams and testing graduates, and by questioning employers about the quality of their professional training. The author suggests measures aimed at changing the existing methodology for distributing admission quotas for creative specialties to educational organizations of higher education of the Ministry of Culture of Russia and other universities for which creative specialties are not specialized, and tightening requirements for material, technical and personnel support of a full-fledged educational process.
Towards a Pluralist Approach to Translation Theory Development in CTIS

In the last decades, Cognitive Translation Studies (CTIS) has grown into a discipline that investigates all forms of multilectal mediated communication. The broadening of the object of study has brought along a multiplicity of tools for data gathering as well as interpretation – concepts and constructs that are key in the development and understanding of a new theoretical apparatus. In this process, CTIS scholars have adopted a wealth of research methods and analytical perspectives from numerous disciplines and epistemic traditions. Despite the view that mature science tends to establish one, all-encompassing theory or paradigm, I claim that epistemic contradictions are a normal feature of science and are not detrimental to scientific progress. In elaborating my argument, I will introduce pluralism as an epistemological position and will apply it to propose a framework for the development of theories in CTIS.
레미콘 품질 안정화를 위한 효율적인 단위수량 관리 방안

In the manufacturing process of ready-mixed concrete, quantity management directly affects the workability and strength of concrete. Therefore, water quantity is the most important management factor for water quality control of ready-mixed concrete. It can be said that the number of unit water in the mix design, the water quantity due to the surface water contained in the aggregate used, and the water quantity taking into account the concentration of sludge contained in the recycling water when using the recycling water are factors that affect the quantity management of ready-mixed concrete. In this study, as a stable quality control method of ready-mixed concrete, a quantity management method by aggregate surface water and a sludge concentration management method according to the use of recycling water were proposed. Thus, we tried to suggest an efficient quantity management method for stabilizing the quality of ready-mixed concrete.