Reviewerly/exHarmony huggingface dataset:
USING THE MENTIMETER INFORMATION PLATFORM FOR FORMATION OF A COMMUNICATIVE EDUCATIONAL ENVIRONMENT

The objective of the article is to highlight and analyze the pedagogical experience of the Department of Philosophy and Pedagogy of Kyiv National University of Culture and Arts (KNUC&amp;A) in attracting the Mentimeter platform in the forming an innovative, communicative and educational environment of the higher education institutions during lectures on the example of educational course “Philosophy”. The article notes that the communicative component of the educational process has a great significance for humanitarian education in the field of culture, which is aimed at forming competencies related to creativity and using communication skills. The demand of the society for these competencies actualizes the urgency of studying the experience of using online educational platforms in the educational process of cultural and artistic education, which have significant communicative potential. The article uses such research methods as pedagogical observation and experiment, methods of analysis, synthesis and generalization. The scientific novelty of the study is to highlight the experience of the department in attracting online educational platforms to work with students during lectures (on the example of teaching in terms of distance learning). It is found that the use of the Mentimeter platform, which is used by lecturer while working with students during lectures both for educational purposes and getting feedback from students about the content of the course or lecturer’s methodological developments, significantly increases the interest of students in the materials of educational course and the learning process in general. Online surveys, created employing the platform, provide an opportunity to establish synchronous communication with students during lectures, which is extremely important for both full-time and distance institutional education. Students’ assessment of the communication and educational components of distance learning has much higher rates. Communicative practices in the educational process in the context of the pandemic are important not only for learning but also for the harmonious development of personality and overcoming the socio-psychological challenges of the time.&#x0D; Keywords: feedback; lecture; online survey; Mentimeter; communicative educational environment; learning experience of KNUC&amp;A; distance learning; humanitarian education.
Dynamic analysis of optical imaging electro-system

An Optical Imaging Electro-System (OIES) is an equipment used to capture images from a long range in the form of electromagnetic radiations and convert them into electrical signals which are then transferred to a system where these signals are converted for visual display. These systems are always operated in an environment exposed to wind gust, shocks, earthquakes, etc. The optical systems are sensitive to these effects and the equipment housing the system must tolerate these effects. In the present work, study is carried out on dynamic behavior such as Modal, Harmonic and Shock analysis of the external body which houses the OIES. Several iterations are carried out by making changes in geometry (varying thickness, inclusion of stiffeners, etc.) and material (Aluminium 2024, Aluminium 7075 and Titanium alloy). The CAD models are developed using ANSYS SPACECLAIM and analysis was carried out using ANSYS workbench software. Natural frequencies of the system are obtained from modal analysis and are used for harmonic and shock analysis. Natural Frequencies obtained for mode 1 to mode 10 are in the range of 69 Hz to 313 Hz for different models. In harmonic analysis, the deformation, stress and acceleration response of the frequencies are studied. From Harmonic analysis, deformation in X axis is found to be 1.71 mm to 6.75 mm, stress of 1.33 MPa to 26.36 MPa for different models. In Shock analysis, the behavior of the natural frequencies is studied under the influence of shock loads. The model that is best suited for the operation is selected by considering all the factors.
Expert System to Diagnose Bonsai Plant Pests With Certainty Factor Method

Bonsai ornamental plants are dwarf plants which are generally planted in shallow pots. The main element in bonsai is harmony between pots and plants, in addition to harmony between pots and plants there are also other elements such as trunk size, tree height, root distribution, twigs, and leaf size as well as diseases and pests that attack the bonsai plants need to be considered. The difficulty of the community in conducting consultations and the unavailability of funds and time, so that the community has never conducted consultations about diseases and pests that attack their bonsai plants to experts or plant extension workers from the relevant agencies. Therefore, it is necessary to take action to anticipate the increasing number of bonsai farmers who do not consult on diseases and pests of bonsai plants. This is due to the delay in the diagnosis of the disease. The unavailability of experts or plant extension workers who are close, the community does not have time to conduct consultations and requires money. An expert system is a computer-based system that uses knowledge, facts, and techniques and reasoning in solving problems that can usually only be solved by an expert in the field. The Certainty Factor method is efficient enough to be used in diagnosing the diseases and pests of the bonsai plant. This system can provide early diagnosis of diseases and pests on the bonsai plant based on the symptoms and intensity of the symptoms that are visible from the outside. Users only need to enter the Web to take the first step in solving bonsai plant diseases and pests and choose the symptoms of the disease they are experiencing without having to ask an expert directly. This system is made web-based with PHP programming language and MySQL database.
Aplikasi Surat Pertanggung Jawaban Kegiatan Dana Bantuan Operasional Kesehatan Pada Puskesmas Bati – Bati Berbasis Web

In the national and political unitary body in Tanah Laut district, there is actually a system created to deal with staffing problems in the environment. However, there are still many shortcomings in the system. The first thing is seen in the retirement status of employees, in this information system there is no feature that can know when the employee retires, this is clearly very detrimental to the national and political unitary body of Tanah Laut Regency, because retired employees may still be registered in the system So far, the admin cannot know when the employee will retire, because there is no feature made to find out this information. Based on the description of the explanation, it is necessary to develop a personnel information system that can manage pension data and manage class data on a regular basis. . In developing the application, the author uses the waterfall method using the PHP programming language (Framework CodeiIgniter), HTML, CSS, JavaScript, and is designed using Entity Relationship Diagrams, Data Flow Diagrams and Flowcharts. This application is expected to be able to assist in viewing the data of retired employees.
Review of The Age of Algorithms by Serge Abiteboul and Gilles Dowek

This book is about algorithms and their enormous influence on people in the current age. Algorithms are precise sets of rules to solve problems. They are ubiquitous and have a great effect on the lives of contemporary people, primarily due to technological advancement. A common example is searching for information using an Internet search engine such as Google. This book is not technical in nature and was first published in French as Le Temps des Algorithmes, by ´ Editions Le Pommier in 2020. The authors Serge Abiteboul and Gilles Dowek are computer scientists, with Institut National de Recherche en Informatique et en Automatique (INRIA), Rocquencourt and ´ Ecole Normale Sup´erieure, Paris respectively. They believe that algorithms have made life easier, nevertheless, they dread that algorithms may subjugate humans. This book is intended to serve as an eye-opener on the impact of algorithms on daily life.
Narrativas de vida de mulheres assentadas rurais durante a pandemia de Covid-19 [Life narratives of women in rural settlements during the Covid-19 pandemic] [Narrativas de vida de las mujeres de asentamientos rurales durante la pandemia de Covid-19]

Objetivo: refletir sobre a produção de material etnográfico, a partir de narrativas de 19 mulheres de assentamentos rurais, durante a pandemia de Covid-19, utilizando o método qualitativo narrativa de vida. Conteúdo: o material obtido nos registros do diário de campo propiciou, em sua análise, a reflexão sobre os diferentes aspectos de vulnerabilidade das mulheres assentadas. As soluções para o cuidado e manutenção da saúde, incluem ajuda mútua, utilização de conhecimentos tradicionais e populares e utilização dos equipamentos de saúde dos municípios onde vivem. Considerações finais: a utilização de recursos tecnológicos para conduzir as entrevistas com as participantes permitiu contornar o distanciamento social imposto pela pandemia. A compreensão das histórias de vida e experiências de cuidado na pandemia revelou a vulnerabilidade social desse grupo e a necessidade de maior acolhimento da enfermagem às suas demandas na rede de atenção à saúde.ABSTRACTObjective: to reflect on the ethnographic material produced on the basis of the narratives of 19 women living in rural settlements during the Covid-19 pandemic, using the qualitative life story method. Content: analysis of the material obtained from field diary records provided food for thought on various aspects of the vulnerability of women in settlements. Their health care and health maintenance solutions included mutual help, as well as using both traditional and popular knowledge, and the health facilities in the towns where they lived. Final considerations: digital communication tools made it possible to conduct interviews at a distance, bypassing the social distancing imposed by the pandemic. Understanding their life stories and care experiences in the pandemic revealed this group’s social vulnerability and the need for nursing care services to be more receptive to their demands in the healthcare system.RESUMENObjetivo: reflexionar sobre la producción de material etnográfico, desde narrativas de 19 mujeres de asentamientos rurales, durante la pandemia Covid-19, utilizando el método cualitativo de los relatos de vida. Contenido: el material obtenido de los registros del diario de campo propició, en su análisis, la reflexión sobre diferentes aspectos de vulnerabilidad de las mujeres asentadas. Las soluciones para el cuidado y el mantenimiento de la salud incluyen ayuda mutua, uso de conocimientos tradicionales y populares y utilización de equipos de salud en los municipios donde habitan. Consideraciones finales: el uso de recursos tecnológicos para la realización de entrevistas junto a las participantes permitió superar la distancia social impuesta por la pandemia. La comprensión de las historias de vida y de las experiencias de cuidado en la pandemia reveló la vulnerabilidad social de este grupo y la necesidad de un acogimiento de enfermería más receptivo a sus demandas en la red de atención a la salud.
Abstract WP93: An Internet Of Things Based Real Time Location System With Machine Learning For Coordination Of Acute Stroke Endovascular Intervention: A Proof-of-concept Study

Introduction: The delivery of mechanical thrombectomy in acute stroke can be challenging because it requires coordination between patient travel and multiple stroke team members across different locations in the hospital. A Real Time Location System (RTLS) can facilitate a streamlined workflow by determining a patient’s location, but the required infrastructure can be costly to set up. We investigated the feasibility of a machine learning based RTLS using an Internet Of Things (IOT) device prototype to coordinate acute stroke endovascular intervention. Methods: In this proof-of-concept study, study investigators programmed an IOT device to collect WiFi signals from different hospital zones relevant to the mechanical thrombectomy workflow. Different machine learning (ML) algorithms were trained on location labelled training WiFi signals to predict location. The accuracies of the different ML algorithms to predict unlabeled testing WiFi signals collected on a separate day were measured, in percentages. Results: The training and testing datasets contained 1,179 and 293 samples respectively, with 2,516 and 2,618 unique WiFi signals detected in each dataset. The trained neural network, random forest, support vector machine, K-nearest neighbors, decision tree and ensemble classifiers achieved accuracies of 96.6%, 96.2%, 97.3%, 97.3%, 83.6% and 97.3% on the testing dataset respectively. Additionally, the neural network model produced estimates of uncertainty, which were significantly associated with the correctness of predictions based on logistic regression analysis (p &lt; 0.001). Conclusions: An IOT based real time location system with machine learning can accurately predict locations within the hospital, demonstrating immense potential for the future applications of streamlining delivery of acute stroke endovascular intervention.
Resource Augmentation

A summary is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Penerapan Support Vector Machine dengan SMOTE Untuk Klasifikasi Sentimen Pemberitaan Omnibus Law Pada Situs CNNIndonesia.com

The declaration of the omnibus law reaped the pros and cons in the community. In a situation like this, the media should be neutral. One of the media that still maintains neutrality is Detik (Rumata 2017). Detik owns several channels such as detikNews, detikFinance, and CNN Indonesia. In this study, the neutrality of the CNN Indonesia media as part of Detik will be studied based on the tendency of sentiment on the omnibus law-related news. Sentiment analysis is used to examine the trend of opinion on news headlines. In conducting sentiment analysis, a method that supports classification is needed. The classification method that will be used in this research is the Support Vector Machine (SVM). There is an imbalance of data in the three categories of sentiment so that the Synthetic Minority Oversampling Technique (SMOTE) method is used to overcome this imbalance. The omnibus law tends to be reported neutrally by CNNIndonesia.com site. The one vs all method has a better classification result than the one vs one method. The application of SMOTE only gives slightly better results than data classification without the application of SMOTE because the imbalance in the data is not too extreme. Modeling using the one vs all method with SMOTE and distribution of data 90% train data 10% test data gives the best classification results with a macro average f1-score of 60,33%.
Implementasi Algoritma Kruskal Dalam Menentukan Rute Terdekat Pada Tempat Pariwisata di Daerah Lombok Tengah

When visiting several tourist attractions at once with limited time and an irregular schedule, of course, visitors choose the closest route to be able to visit all the places to be visited at once. This study uses an algorithm, namely the Kruskal algorithm, which aims to find the closest route to visit the five tourist attractions at once in Central Lombok Regency. The tourist attractions in question are Tanjung Aan Beach, Kuta Mandalika Beach, Sukarara Village, Sade Hamlet, Benang Kelambu Waterfall. This type of research is applied research which is generally a type of descriptive research that encourages further research. This study applies a modified Kruskal algorithm so as to produce 4 alternative closest routes with different starting points to be able to visit the five tourist attractions at once in Central Lombok Regency, namely 1) If the journey starts from Tanjung Aan Beach or Benang Kelambu Waterfall, the closest route is 60,1 km; 2) If the journey starts from Kuta Mandalika Beach, the closest route is 73.6 km; 3) If the journey starts from Sade Hamlet, the closest route is 73.6 km; 4) If the journey starts from Sukarara Village, the closest route is 82.9 km
Research on Key Algorithms of Intelligent Recommendation System for Retired soldiers’ Employment Training

In view of the problem that retired soldiers are faced with the choice of hundreds of industries and tens of thousands of positions in the society and can't accurately select appropriate training, based on the analysis of the current recommendation algorithm and its shortcomings, this paper constructs the main process of the intelligent recommendation system for retired soldiers’ employment training, and puts forward a recommendation algorithm integrating professional interest, personal ability, social needs and other factors, An example is given to verify the effectiveness of the algorithm. The research helps to accurately recommend training suitable for their own development for retired soldiers, quickly improve their employment and entrepreneurship ability, and then find a job smoothly.
Visual-Syntactic Embedding for Video Captioning

Video captioning is the task of predicting a semantic and syntactically correct sequence of words given some context video. The most successful methods for video captioning have a strong dependency on the effectiveness of semantic representations learned from visual models, but often produce syntactically incorrect sentences which harms their performance on standard datasets. We address this limitation by considering syntactic representation learning as an essential component of video captioning. We construct a visual-syntactic embedding by mapping into a common vector space a visual representation, that depends only on the video, with a syntactic representation that depends only on Part-of-Speech (POS) tagging structures of the video description. We integrate this joint representation into an encoder-decoder architecture that we call Visual-Semantic-Syntactic Aligned Network (SemSynAN), which guides the decoder (text generation stage) by aligning temporal compositions of visual, semantic, and syntactic representations. We tested our proposed architecture obtaining state-of-the-art results on two widely used video captioning datasets. This is a short version of a paper recently published at a Computer Vision Conference. The complete reference has been redacted to fulfill the double-blind restriction.
Didactic basis for the development of professional competence of university students

The article deals with the actualization of the problem of didactic foundations of the development of professional competence of University students. It is considered the concept of professional competence from a pedagogical point of view. The article substantiates the idea that professional competence is the creation of qualitatively new values that are important in the process of personal development because of the independent acquisition of subjectively new knowledge, skills and methods of research activities in the process of studying at a university.
HYDROLOGY CHARACTERISTICS IN KRUKUT RIVER RIPARIAN BUFFER ZONE

This research aims to investigate the characteristic of hydrology in the Krukut River. However, it studies an interesting floodplain like the riparian buffer zone (RBZ). RBZ is close adjacent to the river waters, generally accompanied by shrubs and the other crops along a river. It is useful for stabilizing the streams and minimizing the flood damages. The development of a region will impact the surrounding ecosystem that has been a developed human activity along the river, one of which is the Krukut River. The methodology consists of hydrological analysis for finding the characteristic of hydrology. The hydrology is analyzed using the water discharge data of Krukut River headwater. However, the maximum water discharge frequency is analyzed by using two models that are a) Log Pearson distribution and b) Gumbel distribution. The observations are made during the survey reveal that RBZs and floodplain areas are dominated by human habitation on both banks. The result of the analysis showed that human habitation accounts for 77.5% and 22.5% respectively, different types of vegetation such as shrubs account for 10.5%, shrubs – for 5%, and erosion – for 7%, so the environmental conditions of the river are directly disturbed due to excessive human activities. The result indicates that in order to stabilize the river banks, the riparian can be cropped by humans for a specific aim, reducing water loss by the evaporation and reducing the flood damage risk in low-lying areas that may be the location near to the water.
The diagnosis methods for the obstacles and difficulties in computer sciences of nursing students

Computer science as a school subject has been a regular media subject for more than 20 years. Indeed, all the educational systems of the world are now convinced that today's learners, brought to live in a hyper-scientific society. This research aims to discover the sources of computer difficulties encountered by some nursing students. We used two well-known methods of analysis: the Nominal Group Technique (NGT) and the Pencil/Paper Questionnaire. Data obtained revealed that the prerequisites are overestimated because the notions learned in high school are forgotten and that the basic notions of computer science seem to present difficulties for these learners. The results of the questionnaire and the NGT are similar and complementary. It becomes clear that using NGT and the questionnaire are efficient tools to diagnose the difficulties and obstacles of nursing students. The NGT can be used not only in identifying students’ problems with scientific notions in computer science, but also in other subjects. Keywords: Questionnaire, difficulties, obstacles, computer science, nursing students.
PENGEMBANGAN SISTEM INFORMASI MANAJEMEN PENGELOLAAN KEARSIPAN DI LEMBAGA JAMINAN SOSIAL

This study aims to see to what extent the effectiveness of an information system that has just been implemented in a social security institution where this system is a replacement for the previous system which is considered less effective in managing archives. Based on the results of research and testing, it was found that this new system has a better effectiveness value and a far more optimal level of accuracy in archiving management.
Platforms and Practice of Heterogeneous Graph Representation Learning

It is challenging to build a Heterogeneous Graph (HG) representation learning model because HG is heterogeneous, irregular, and sparse. An easy-to-use and friendly framework is important for a beginner to make an understanding and get deep into this field. In this chapter, we are going to introduce OpenHGNN, a toolkit that can help to build HG models in a predesigned pipeline. And we will present the procedures with three well-known HG models that are HAN, the model first introduces attention mechanism to heterogeneous graph neural networks, RGCN, a model used to model multi-relational graphs with GCN, and HERec, a heterogeneous graph embedding method for recommendation.