Reviewerly/exHarmony huggingface dataset:
Bimbingan Teknis Pengelolaan Pembelajaran secara Video Conference dengan aplikasi Zoom dan Youtube di Era Pandemi Covid-19

The aims to provide teachers and lecturers with understanding and skills on how to manage learning online or online. This stage of community service includes analyzing the need for an online learning management platform, conducting technical guidance, and conducting evaluations. After the technical guidance activity, the participants liked the material and speakers in the technical guidance which indicated that the participants understood the material presented by the resource persons. Based on the evaluation results it was found that the implementation of this activity was successful with a high level of attendance of the participants, a level of likeness that was evenly distributed in all material presented by the resource persons, and a very high level of satisfaction with the guidance committee services .
PENGARUH JENIS BOLPOIN TERHADAP MOOD MENULIS DAN BELAJAR PELAJAR SMA (THE EFFECT OF A BALLPOINT TO THE MOOD OF WRITING AND STUDYING OF SENIOR HIGH SCHOOL STUDENTS)

Writing is an activity representing contents of the mind into written form. Oneof tool for writing is a ballpoint. Student criteria for choosing a ballpoint can bebased on ink, appearance, or color. Sometimes the type of ballpoint used can affect tothe mood and the beauty of writing or even affect the spirit of learning. Therefore, weconducted a research to find out the relationship between the type of ballpoint andstudent's writing activities of SMA Negeri 1 Ngemplak. The research method we use isa survei method by distributing questionnaires. The results showed that: 1)Respondents agreed on the statement of the type of ballpoint influencing the moodand frequency of writing, the beauty of writing, and the assumption that writingmust use the pen they like. 2) The spirit of learning is not very influenced by the typeof ballpoint. 3) Respondents prefer medium and ordinary ink (not gel and not glossy),medium size, and plain appearance. 4) The reason for writing must use the preferredballpoint is because it is comfortable. The conclusion that can be drawn from theseresults is the type of ballpoint can affect the mood and frequency of writing, as wellas the beauty of writing, but does not greatly affect the spirit of learning. Ballpointsthat are preferred by students are medium-sized, normal-thickness ink and plainappearance.
Parallel Stochastic Asynchronous Coordinate Descent: Tight Bounds on the Possible Parallelism

Several works have shown linear speedup is achieved by an asynchronous parallel implementation of stochastic coordinate descent so long as there is not too much parallelism. More specifically, it is known that if all updates are of similar duration, then linear speedup is possible with up to $\Theta(L_{\max}\sqrt n/L_{\overline{{res}}})$ processors, where $L_{\max}$ and $L_{\overline{{res}}}$ are suitable Lipschitz parameters. This paper shows the bound is tight for almost all possible values of these parameters.
ИСПОЛЬЗОВАНИЕ ОБЛАЧНЫХ ХРАНИЛИЩ ДАННЫХ ДЛЯ ОРГАНИЗАЦИИ САМОСТОЯТЕЛЬНОЙ РАБОТЫ СТУДЕНТОВ

The article deals with the use of cloud technologies in the organization of independent activities of University students. This problem is particularly relevant at present due to the significant increase in the hours allocated for independent work of students at universities in Ukraine. There are many technological tools for effective organization of independent activities of students, one of which can be considered cloud technologies, as the most popular in the modern world, due to its advantages: they can be applied in the educational process not only for the organization of independent work (or distance learning) – versatility; ability to work anywhere (where there is Internet access) and at any time-versatility; reduced financial costs for training – cost-effectiveness; reach a large number of trainees-progress in learning; allow you to use a wide variety of forms of learning and types of control; allow you to release creative thinking (Sway, DropBox Paper). The use of cloud-based data storage helps each student create their own personal cloud-oriented learning environment during the learning process (personal cloud-oriented learning environment). Therefore, it is important to teach students how to use cloud services correctly at the initial stages of University education, as well as to familiarize them with the diverse functionality of modern cloud software products. The modern labor market places high demands on the level of training of modern personnel. As statistics show, one of the most popular specialists are specialists in the field of cloud technologies. If we want our graduates to be competitive in today's society, we need to train them in the latest technologies and the ability to use these skills in their future professional activities. Thus, the main task of a modern school of higher education is to cultivate a highly qualified, competitive specialist who is able to improve their professional level and update their knowledge and skills. Using the latest digital technologies in the educational process, you should not underestimate the role of the teacher in the educational process. Therefore, it is obvious that the future of the education system is in the use of a combined approach (Blended learning) to learning.
An Entropy Based Outlier Score and its Application to Novelty Detection for Road Infrastructure Images.

A novel unsupervised outlier score, which can be embedded into graph based dimensionality reduction techniques, is presented in this work. The score uses the directed nearest neighbor graphs of those techniques. Hence, the same measure of similarity that is used to project the data into lower dimensions, is also utilized to determine the outlier score. The outlier score is realized through a weighted normalized entropy of the similarities. This score is applied to road infrastructure images. The aim is to identify newly observed infrastructures given a pre-collected base dataset. Detecting unknown scenarios is a key for accelerated validation of autonomous vehicles. The results show the high potential of the proposed technique. To validate the generalization capabilities of the outlier score, it is additionally applied to various real world datasets. The overall average performance in identifying outliers using the proposed methods is higher compared to state-of-the-art methods. In order to generate the infrastructure images, an openDRIVE parsing and plotting tool for Matlab is developed as part of this work. This tool and the implementation of the entropy based outlier score in combination with Uniform Manifold Approximation and Projection are made publicly available.
PENGARUH IMPLEMENTASI TEORI HIRARKI KEBUTUHAN ABRAHAM MOSLOW TERHADAP PENINGKATAN KINERJA PEGAWAI PADA DINAS PERPUSTAKAAN DAN KEARSIPAN KOTA SUNGAI PENUH

study aims to determine the effect of the implementation of the Moslow Abraham theory of hierarchy needs on improving employee performance at the Dinas Perpustakaan dan Kearsipan Kota Sungai Penuh. The research results are based on the results of the analysis where the t value of 3.869> t table 1,703. This means that the hierarchy theory needs Moslow Abraham influence on performance. Meanwhile, for the large influence of the hierarchy theory of Moslow Abraham needs on employee performance improvement that is equal to 0.118 or 11.8%.
Constructing Naive Bayesian Classification Model by Spark for Big Data

Due to the development of big data technology, traditional machine learning algorithms are difficult to deal with massive data. To solve this problem, a naive Bayesian classifier based on parallel training and prediction on Spark platform is proposed. The classifier includes Laplace smoothing and normal distribution functions. Bayesian classification algorithm combined with Spark distributed platform to build a complete functional naive Bayesian model for data mining and data analysis and testing. Experimental results show that the accuracy of MLlib -based optimized continuous feature vector dataset is 9.75 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">%</sup> higher than that of the traditional naive Bayes classification algorithm.
Covid-19: Better contact tracing could help save lives and the economy

The rates of daily infections are rising significantly. In order to save lives and to keep the UK economy open, improvements to the UK contact tracing system are urgently needed. Woolliscroft et al. outlined how the UK contact tracing system could be improved. Detailed evaluation of the Sheffield based community contact tracing pilot project offers additional insights. [1,2] An independent group of mainly retired NHS staff called Sheffield Community Contact Tracers (SCCT) conducted a pilot contact tracing project from April to May 2020 before the national system was introduced. The project was assessed to determine the feasibility and impact of a volunteer staffed community contact tracing approach. The assessment found that contact tracing was enhanced by: trust, local knowledge, interviewer skills and expertise, cooperation from employers, and contact in a timely manner.
Penerapan Metode Anaconda Untuk Mendeteksi Orisinalitas Citra Digital

Image plays a very important role in the form of visual information as one of the multimedia components. The circulation of images in digital form is very easy and fast either through social media or E-mail (Electronic-mail). Digital images are more dynamic and can be easily changed (editable) in terms of shapes, sizes, and objects that are in the digital image. Along with the development of technology and computers, the increase in computer crime has also increased, especially in image manipulation. There are many ways that people use to manipulate images that have a detrimental effect on others. The originality of a digital image is the authenticity of the image in terms of colors, shapes, objects and information without the slightest change from the other party. Nowadays many digital images circulating on the internet have been manipulated and even images have been used for material fraud in the competition, so we need a method that can detect the image is genuine or fake. In this study, the author uses the Anaconda Hash method to detect the originality of digital images, by using this method an image that is still doubtful of its authenticity can be found out that the image is authentic or fake.
Interactive Reading System Based on AI

In the existing enrollment teaching training, the low ratio of teachers / students causes small training scale and low training efficiency. In order to solve this problem, an interactive enrollment system based on AI is designed. The system mainly includes four modules: speech recognition module, evaluation and analysis module, comprehensive data module and scenario interface module. It realizes the functions of human-computer interaction, scenario design/import, realtime automatic scoring, teaching data analysis and so on. The introduction of enrollment system will effectively improve the training efficiency and expand the training scale.
Conditions Militating Against Peace Process in the Alavanyo-Nkonya Area, Ghana

The study of peace processes seems to be gaining grounds in scholarship the world over, given that peace processes are very vital to establishing permanent armistice. Arguments are provided to the effect that peace processes provide key opportunities for major reforms that transform institutions, structures, and relationships in societies affected by conflict or crises (Brewer, 2010; O’Reilly, O Suilleabhain, and Paffenholz, 2015). This article, however, outlines some of the factors which have undermined peace processes not only in Alavanyo-Nkonyo area of Ghana but across all African countries. Interview, observation were amongst the major ways of data collection. This research used empirical methods in its analysis. The observation made conclusively stated that peace process in this region is undermined by several factors, these include undressed needs, rumours, war, beneficiaries and financiers, national and ethno-politics and damaged relationships. The study recommended the need for grounded research on ways to deal with the spoiler problems in peace processes.
Commutation as a substitute phenomenon of the communicative competence of a hearing-impaired student with a complex defect structure

Abstract The article is devoted to a possible commutation resource as a phenomenon of substitute commutation in supporting education by the model of "mother hearing-impaired student with a complex defect structure, which includes autism spectrum disorder"; the commutation reserves are considered to understand family support technologies. On the one hand, the communication technologies manifesting the new digital communication era may be demanded by today’s disabled young people as alternative tools for virtualization of modern life. On the other, the modern digital environment supports the concept of accessibility and equal opportunities for building individual education paths at the stages of both secondary and accessible professional education.
A framework for learned CountSketch

Sketching is a compression technique that can be applied to many problems to solve them quickly and approximately. The matrices used to project data to smaller dimensions are called In this work, we consider the problem of optimizing sketches to obtain low approximation error over a data distribution. We introduce a general framework for learning and applying CountSketch, a type of sparse sketch. The sketch optimization procedure has two stages: one for optimizing the placements of the sketch's non-zero entries and another for optimizing their values. Next, we provide a way to apply learned sketches that has worst-case guarantees for approximation error. We instantiate this framework with three sketching applications: least-squares regression, low-rank approximation (LRA), and k-means clustering. Our experiments demonstrate that our approach substantially decreases approximation error compared to classical and naively learned sketches. Finally, we investigate the theoretical aspects of our approach. For regression and LRA, we show that our method obtains state-of-the art accuracy for fixed time complexity. For LRA, we prove that it is strictly better to include the first optimization stage for two standard input distributions. For k-means, we derive a more straightforward means of retaining approximation guarantees.
Improving Security of Patient Health Information Regarding Wireless LANNetworks

The objective of this article is to report the results of data collected to search for solutions towards advancements in strengthening hospital wireless network security. Patient data breaches cost hospitals billions of dollars annually. The analysis of the data collected for this qualitative exploratory historic case study indicated that hospitals are searching for solutions to protect patient data from wireless network breaches, and the results of the analysis are available for review. This article presents results of the data collected and reviewed for this qualitative exploratory historical case study, as well as the results of the analysis of the data
Cognitive component diagnostics of the future primary school teachers readiness to design educational content

The article focuses on the issue of training primary school teachers to design educational content. The cognitive component of the readiness formation and its criteria are described. The criterion-level characteristic of this component is presented, consisting of three levels: high, medium and primary. Diagnostics of the readiness cognitive component primary school teachers to design educational content is shown. Primary school teachers cognitive component diagnostics methods of the readiness to design educational content are demonstrated and its results are demonstrated. The procedure for applying the methods of questioning, testing, and activity products analysis for the diagnosis of the cognitive component is presented. It is concluded that it is necessary to organize purposeful work on the formation of this component in the training primary school teachers process in a pedagogical University.
<i>Retracted on June 26, 2023</i> : Optimal strategy solution based on Cooperative Game Theory

Aiming at the problem of solving the optimal strategy in multiplayer game, this paper introduces the theory of cooperative game, puts forward the concept of risk degree, quantifies the game psychology of players as decision probability η, constructs a new cooperative game model by adding the decision probability η to the terminal revenue model, so as to solve the problem of multiparty benefit distribution.
Contribution of Environmental Factors to Quality Education Delivery in Public Junior High Schools in Talensi-Nabdam District

This study investigates the contribution of environmental factors to quality education delivery in public Junior High School in Talensi-Nabdam district.Quantitative approach using descriptive survey design was adopted for the study.All 32 headmasters and 230 teachers of the 32 public Junior High Schools in the Talensi-Nabdam district, all the supervisors for the 8 circuits, the District Director of education (DDE), 32 Parent-Teacher Associations (PTAs) and 32 School Management Committees (SMCs), and the District Chief Executive (DCE) of Talensi-Nabdam totaling 303 participants were randomly selected.Results of the study showed that parents engaged in dressmaking and tailoring, shea butter extraction, pito brewing, pottery, dry season gardening, animal husbandry there are available income generating activities within the communities that parents often engage in for a living.Also, findings revealed that parents used income they generate to support quality education delivery by buying their school uniform for their children, provide exercise books and other writing materials, provide pocket money to their children for school, pay for mock examinations, pay for registration fee for final examinations, and other special levies that a school's PTA may ask for.
Learning with Mobile Technologies at Public Primary Schools in Costa Rica: The case of the National Program of Educational Informatics of the Ministry of Public Education and the Omar Dengo Foundation

This article presents the experience of the National Program of Educational Informatics of the Ministry of Public Education and the Omar Dengo Foundation of Costa Rica designing and executing a national project to encourage and develop learning experiences for teachers and students using mobile technologies at public schools. To describe this experience, first, the Omar Dengo Foundation and their National Educational Program is introduced. This program works under certain conceptual and methodological principles. The Learning with Mobile Technologies Area (ATM for its acronym in Spanish) includes more than 2400 schools, and has beneficiated 206.096 students up to September. The paper examines a description of this model, the main results with primary teachers and students, as well its coverage all throughout the country. This analysis includes the essential pedagogical principles of the program, their main outcomes and challenges ahead.
Deep Learning P and S wave phase picking of Ocean Bottom Seismometer (OBS) data

&amp;lt;p&amp;gt;Ocean Bottom Seismometers (OBS) are the primary instruments used in the study of marine seismicity. Due to the characteristics of their emplacement on the sea bottom, these instruments have a much lower signal-noise ratio than land seismometers. Therefore, difficulties arise on the analysis of the data, specially when using automatic methods.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;During recent years the use of machine learning methods applied to seismic signal analysis has increased significantly. We have developed a neural network algorithm that allows to pick seismic body signals, allowing to correctly identify P and S waves with a precision higher than 98%. This network was trained using data of the Southern California Seismic Network and was applied satisfactorily in analysis of data from Large-N experiments in different regions from Europe and Asia.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;One of the remarkable characteristics of the network is the ability to identify the noise, both in the case of seismic signals with low signal-noise ratio and in the case of large amplitude non-seismic signals, such as human-induced noise. This feature makes the network an optimal candidate to study data recorded using OBS.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We have modified this neural network in order to analyze OBS data from different deployments. Combined with the use of an associator, we have successfully located events with very low signal-noise ratio, achieving results with a precision comparable or superior to a human operator.&amp;lt;/p&amp;gt;
Application of machine learning in business district operation

Since the concept of “artificial intelligence” was first proposed in Dartmouth Conference in 1956, the discipline of artificial intelligence has entered an era of steady progress. Recently, the emergence of new technology such as big data, cloud computing and Internet of Things has promoted the rapid development of artificial intelligence technology represented by deep neural network.
A Systematic Study of Inner-Attention-Based Sentence Representations in Multilingual Neural Machine Translation

Neural machine translation has considerably improved the quality of automatic translations by learning good representations of input sentences. In this article, we explore a multilingual translation model capable of producing fixed-size sentence representations by incorporating an intermediate crosslingual shared layer, which we refer to as attention bridge. This layer exploits the semantics from each language and develops into a language-agnostic meaning representation that can be efficiently used for transfer learning.We systematically study the impact of the size of the attention bridge and the effect of including additional languages in the model. In contrast to related previous work, we demonstrate that there is no conflict between translation performance and the use of sentence representations in downstream tasks. In particular, we show that larger intermediate layers not only improve translation quality, especially for long sentences, but also push the accuracy of trainable classification tasks. Nevertheless, shorter representations lead to increased compression that is beneficial in non-trainable similarity tasks. Similarly, we show that trainable downstream tasks benefit from multilingual models, whereas additional language signals do not improve performance in non-trainable benchmarks. This is an important insight that helps to properly design models for specific applications. Finally, we also include an in-depth analysis of the proposed attention bridge and its ability of encoding linguistic properties. We carefully analyze the information that is captured by individual attention heads and identify interesting patterns that explain the performance of specific settings in linguistic probing tasks.