Reviewerly/exHarmony huggingface dataset:
Research on Multimodal Summarization by Integrating Visual and Text Modal Information

With the rapid development of information technology, Internet data is growing exponentially, which makes it difficult for users to extract key information from massive Internet data. Data compression technology represented by text summary has gradually attracted extensive attention from academia and industry. As an extension of text summarization, multimodal summarization task can effectively reduce users’ information burden and improve users’ information acquisition speed by integrating visual and auditory modal information and using the mutual supplement and verification of different modal data. It has high research value in the fields of information retrieval, public opinion analysis, content review and so on. This paper combs the related research of multimodal summarization in recent years, summarizes the existing technologies and related data sets for multimodal summarization tasks, and summarizes the development direction of future research in this field.
The Development Of Short Story Text Materials In E-Modules Sigil For High School Class XI Students Muhammadiyah 1 Medan

This study aims to determine the results of the development of short story text material in e-modul sigil for high school class XI Students Muhammadiyah 1 Medan.This type of research is development research based on the Brog and Gall development model.The test subjects consisted of class XI students of Senior High School Muhammadiyah 1 Medan.The results showed that: (1) material expert validation included content eligibility 94.31% on very good criteria, 92.71% presentation feasibility on very good criteria, and language eligibility 88.88% on very good criteria, (2) validation design experts with an average of 97.91% on very good criteria, (3) individual group trials of 86.80% on very good criteria, (4) small group trials of 90.04% on very good criteria, (5) The field group test was limited to 92.12% on very good criteria, (6) The effectiveness of the module in improving student learning outcomes.Student learning outcomes based on the pretest and posttest showed the difference from pretest to posttest the value obtained was 28.59% with an average pretest of 58.75% and an average posttest of 87.34%.Based on the results of the study, it was concluded that the short story text material in the sigil-assisted e-module that was developed was feasible and effective to be used by class XI students of Senior High School Muhammadiyah 1 Medan in short story text learning.The implication of this research is to provide convenience for teachers in delivering material by using e-modules assisted by sigils as learning resources in schools and for students to improve student learning outcomes in writing short stories.
PENERAPAN METODE ENTROPY DAN METODE TOPSIS PADA TINGKAT KESESUAIAN LAHAN TANAMAN KOPI DI PROVINSI BENGKULU

Coffea sp (coffee plant) is one of Indonesia's mainstay export commodities which has an important role as the third-largest foreign exchange earner after wood and rubber in the agricultural sub-sector. Coffee is one of the most popular beverage offerings in the world, as evidenced by the fact that coffee consumption has soared to 174 percent in 2016 (International Coffee Organization/ICO data). Bengkulu also produces a lot of coffee production including pickled red Robusta, Arabica super, and Arabica luak which usually the farmers also keep badgers in their cages. Bengkulu, which is known as the golden triangle, is the largest Robusta producer on the island of Sumatra. Land use that is by the potential of the land makes the quality of the land maintained and can optimize production results. Therefore, a Decision Support System is needed to provide recommendations for Robusta coffee farmers in determining the lands to be planted. This research uses the entropy weighting method and TOPSIS ranking. The resulting output is in the form of ranking from the highest to the lowest value of each land contained in 28 sub-districts in 4 districts of Bengkulu Province, namely Rejang Lebong, Lebong, Kepahiang, and Seluma from the highest to the lowest value. This system was built using the PHP programming language and system design with the Unified Modeling Language (UML). The development of this system uses the waterfall method. The accuracy of this system based on the tested data is 100%. Based on the results of calculations using a combination of the entropy weighting method and the TOPSIS ranking method, the results of the largest preference value of 0.815 are in the Seberang Musi and Tebat Karai sub-districts, Kepahiang Regency .
TripleNet: A Low-Parameter Network for Low Computing Power Platform

Deep learning has achieved great success in computer vision (CV), and convolutional neural networks (CNN) have become an important network architecture for CV tasks. With the widespread use of mobile devices, neural network models based on low-computing power platforms have received much attention. This paper proposes a lightweight CNN model named TripleNet. TripleNet learns the model compression methods of HarDNet and ThreshNet and improves on them. TripleNet completes the network architecture by combining three different convolutional layers, which has the advantages of small model size and high test accuracy. With similar test accuracy, TripleNet model has fewer parameters than HarDNet and ThreshNet. This paper conducts image classification experiments using TripleNet and other networks on CIFAR-10 and SVHN datasets. The experimental results show that compared with HarDNet, the parameters of TripleNet are reduced by 66% and the accuracy rate is improved by 18%; compared with ThreshNet, the parameters of TripleNet are reduced by 37% and the accuracy rate is improved by 5%.
Implementation of the Prophet Model in COVID-19 Cases Forecast

One of the steps to understanding this pandemic is to look at the spread of the data by predicting an increase in cases in various countries so that prevention can be carried out as early as possible. One way to see fluctuations in COVID-19 pandemic data is to predict the rate of cases using forecasting methods so that conclusions can be drawn on the spread of COVID-19 pandemic data around the world to be processed using statistical models. This study will implement the use of the Prophet Model in seeing the rate of development of COVID-19 in the world using four features in the forecasting process such as the number of confirmed cases, the number of cases of recovered patients, the number of cases of death, and the number of active cases. The results of this study produce forecasting data on the number of cases of the COVID-19 pandemic that can be viewed daily, weekly, and even monthly. Forecasting results show the first spike at the end of March until the number of cases reached around 10,275,800 million as of June 29, 2020, where the number of cases grew exponentially until June 29, 2020. The case rate of growth in many instances experienced significant growth until the end of October, touching the number in the range of 34,507,150 million as of October 25, 2020. After June 29, 2020, a very high spike was different from the increase in cases in the previous months. Forecasting results show no point decline because historical data on the number of daily confirmed cases of the COVID-19 pandemic has not decreased. The forecasting results in this study are expected to be able to systematically predict events or events that will occur in the COVID-19 pandemic around the world with the help of valid periodic data so that some information can be obtained for preventive measures related to the COVID-19 pandemic.
Automatic Test Scoring System Based on Deep Learning Technology

The traditional examination papers generally use manual marking, which is a very time-consuming and inefficient marking method. If teachers manually correct students' examination papers every time, not only the workload is heavy, but also due to the influence of subjective factors, they will not be able to objectively and impartially reflect the students' learning effect. If automatic scoring can be realized, it will greatly reduce the workload of teachers, improve the accuracy and objectiveness of scoring, and thus improve the quality of teaching. Therefore, solving the automatic scoring of examination papers is a key problem that needs to be solved urgently at present. In this paper, the BP neural network model in the deep learning technology is used to establish an automatic examination scoring system, which optimizes the information management performance of the system.
Generating Spanning-Tree Sequences of a Fan Graph in Lexicographic Order and Ranking/Unranking Algorithms

Cameron et al. [27th Int. Conf. Computing and Combinatorics (COCOON 2021), LNCS 13025, pp. 49–60] recently presented an algorithm for generating all spanning trees of a fan graph in $$\mathcal {O}(1)$$ -amortized time. The listing of spanning trees fulfills the so-called pivot Gray code property so that successive trees differ by pivoting a single edge around a vertex. They also presented algorithms for ranking and unranking a spanning tree in the listing in $$\mathcal {O}(n)$$ time using $$\mathcal {O}(n)$$ space. In this paper, we first observe that all spanning trees of a fan graph can be naturally represented by integer sequences so that their coding tree has properties with regularity. Then, we propose a simple algorithm for generating spanning-tree sequences in lexicographic order in $$\mathcal {O}(1)$$ -amortized time according to these properties. Additionally, based on the lexicographic order, we develop ranking and unranking algorithms in $$\mathcal {O}(n)$$ -time using $$n+\mathcal {O}(1)$$ space (i.e., the size of the space is just slightly larger than n).
PENGARUH KONDISI EKONOMI ORANG TUA TERHADAP MOTIVASI BELAJAR SANTRI KELAS XI MA TAHUN AJARAN 2020-2021 DI PONDOK PESANTREN MODREN DINIYYAH PASIA

The economic situation of parents is closely related to the learning motivation of children at school, students who have different economies from one another. Different economies, the motivation to learn will also be different and varied. The purpose of this study is to describe the economic situation of the families of the Islamic boarding school students in the modern diniyyah Islamic boarding school, to find out about how the learning motivation of the students at the modern diniyyah Islamic boarding school, and to determine the effect of the economic situation and the motivation of the students on the learning achievement of the students at the modern diniyyah Islamic boarding school. the population in this study were students of class XI MA in the academic year 2020-2021 as many as 110 people, and the sample in this study was 30 people from the population above. Data collection techniques in this study the authors used several methods, namely: questionnaires and questionnaires. , documentation, validity test and reliability test.This type of research is quantitative research with the type of expost facto research. Based on the level of explanation, this research includes causal associative research, because this research aims to identify the effect of elastic X on Y which is causal in nature. This type of research is to examine the influence of parents' economic conditions (X) on learning motivation in class XI MA students for the 2020-2021 academic year at the Modren Diniyyah Pasia Islamic Boarding School (Y). The data was obtained from a questionnaire given to 30 respondents who examined property ownership, type of parental education, family income, family expenses and type of residence. Analysis of the data used in this study is multiple regression analysis using the SPSS IBM Statistics 25 For Windows program.The result of this research is significant by calculating the correlation, so it can be seen that rcount is greater than rtable (rcount &gt; rtable) with an error rate of 5% (0.729 &gt; 0.361). There is a significant influence between the economic conditions of parents on the learning motivation of class XI MA students for the 2020-2021 academic year at the Modren Diniyyah Pasia Islamic Boarding School. Furthermore, the correlation coefficient of 0.729 which can be high/strong correlation with the interpretation of r = 0.70 to 0.90 (between variable X and variable Y there is a high/strong relationship).
Desarrollo de competencias digitales del profesorado mediante entornos virtuales

This article deals with a study on digital skillsin secondary school teachers in the city ofGuayaquil, Ecuador, through dimensionalanalysis and the influence of a web designdeveloped in Moodle for the improvementof digital skills in teachers. His approach wasquantitative with a descriptive - correlationalscope and non-longitudinal experimentaldesign by pre-post test model, the unit ofanalysis was 53 teachers applying non-probabilistic sampling for convenience. Forthe diagnosis (pre-test) and measurementof the stimulus (post-test) two instrumentsadapted to the context of the research wereused, their names were: University teachertraining and Digital teaching competenciesapplied virtually. The results after the stimu-lus were that 88.67% improved their abilitiesto innovate in the field of communication,also in terms of content creation and digitalliteracy teachers obtained 84.9% and 83.02%.
Opinion paper: The Ethics of AI in the Age of Hypertourism

Artificial intelligence (AI) is increasingly present in the hospitality industry. While on the one hand it is explicitly used to automate or improve the efficiency of tourism services, through robotics and chatbots, on the other hand it is crucial to increase sales margins on the web. In particular, AI-driven marketing becomes the main tool in the construction of each tourist’s imagination in the preparatory phase (before choosing the destination) and in the reflective phase (after returning from the trip). Inspired by literature from other industries, this research aims to predict what the ethical risks of using AI in tourism might be. Two main risks can be identified: the creation of a monothematic imagery of the tourist and the risk of radicalisation of tourism destinations.
DEVELOPING STUDENTS’ DESCRIPTIVE WRITING ABILITY BY USING ANIMATION MOVIE

This study's objective is to study how using animated movie might help students improve their writing skills. One class served as the research sample for the pre-experimental methodology used in this study. In the first year of the MA Muhajirin, As'adiyah Kampiri, served as the research sample. Twenty students made up the study's sample. In order to select the sample for the study, the researcher employed the cluster random sampling technique and chose X A. Their understanding of the subject matter for text writing was made simple and enjoyable by the audio and visual mix. It was also acceptable for junior high school kids to get excited and interested in writing in order to hone their descriptive text-writing abilities. Writing tests were used to gather data on the students' descriptive writing abilities, which were then evaluated using SPSS 20. There were noticeable improvements, as seen by the pre-test and post-test results. The pupils' experimental post-test score of (82.11) was greater than their pre-test score, which served as evidence (52.63). The results also revealed that the probability value (0.00) was less than the level of significance (0.05). Based on the findings, the researcher concluded that using animation movies could help students in their first year of MA strengthen their descriptive writing skills. As'adiyah Kampiri Muhajirin.
AsyFed: Accelerated Federated Learning With Asynchronous Communication Mechanism

As a new distributed machine learning (ML) framework for privacy protection, federated learning (FL) enables substantial Internet of Things (IoT) devices (e.g., mobile phones, tablets, etc.) to participate in collaborative training of an ML model. FL can protect the data privacy of IoT devices without exposing their raw data. However, the diversity of IoT devices may degrade the overall training process due to the straggler issue. To tackle this problem, we propose a gear-based asynchronous FL (AsyFed) architecture. It adds a gear layer between the clients and the FL server as a mediator to store the model parameters. The key insight is that we group these clients with similar training abilities into the same gear. The clients within the same gear conduct synchronous training. These gears then communicate with the global FL server asynchronously. Besides, we propose a T-step mechanism to reduce the weight from the slow gear when they are communicating with the FL server. The extensive experiment evaluations indicate that AsyFed outperforms FedAvg (baseline synchronous FL scheme) and some state-of-the-art asynchronous FL methods in terms of training accuracy or speed under different data distributions. The only negligible overhead is that we leverage the extra layer (gear layer) to preserve part of the model parameters.
Penggunaan Media Gambar Seri untuk Meningkatkan Kemampuan Menulis dan Membaca Mata Pelajaran Tematik

Given the importance of reading and writing in the learning process at school, the teacher plays an essential role in motivating students to like reading and writing. Learning media helps teachers manage the teaching process and use class time well. The type of research used is classroom action research. The result stated that the serial picture media greatly influenced the students' writing and reading abilities. Students' writing and reading skills increased significantly, with complete writing ability reaching 93% and full writing ability by 89%.
The Fly Swatter Game to Enrich Students’ Vocabulary

Learning vocabulary is one of the most important thing in learning English. Most of students still get the difficulties in learning vocabulary. They felt hard in memorizing vocabulary and they felt bored when learning vocabulary. The objective is to increase the learners’ vocabulary in mastering English language. Fly swatter game is one of the game that can use in learning English and can make the students creative and active in getting the new vocabulary by teacher instruction. Therefore, the students can implement the words that they have gotten in their speaking, writing, reading and listening. They can express their own idea when they want to speak with other, they can write their idea in writing, they can understand the meaning from the text and they can listen the speakers say something.&#x0D; Keywords:&#x0D; Fly Swatter Game, Enrich, Students’ vocabulary&#x0D;
ПАРАДОКС УЧЕНЬ-ВЧИТЕЛЬ ОСВІТНЬОГО ДИСТАНЦІЙНОГО МИСТЕЦЬКОГО ПРОЦЕСУ

The aim of the article is to research of the latest human educational evolution, with its paradox – what is a student-teacher? Is it just a biological creature, physically limited by skin and intellectually limited by the contents of the skull? Researching the topic, the author sought to take into account the peculiarities of the mental state of the modern young generation, which is totally dependent on digital technology. The emphasis is on the unexpected expectation of a meeting between a person (teacher) and a machine (student) at the point of obtaining artistic knowledge. The method is to transcend the essence of the student in the field of relations with teachers. Studying the role of the body as a tool to achieve the learning goal. Comparison of the tools of a living human teacher, which is in front of the monitor screen and the screen image of a student who is deprived of natural tools (hearing, sight, touch, etc.). Finding the equivalent of transferring virtual artistic knowledge to the other side of the screen, where the receiver is a digital image of the student. The invention of a new way to return the organic tools of the human body and its components. What exactly will give rise to the transition and long stay of human consciousness where there is no language of the human body, which identifies our state in the living space of art and education? The final result of the possible synthesis of the primary source of human tools and the tools of the screen image of the virtual student is impressive. What to expect if we find ourselves in front of a horrible face of a robot machine that will dictate its own algorithms for obtaining virtual knowledge? Defining human quality as a subject of virtual new knowledge in the period of distance learning.
Sneaky Were-Bees: Dynamics of an Augmented Dodgeball Game Played In The Dark

Predatory team games, such as dodgeball, have been played for centuries.This paper investigates what happens when such a game is augmented with motion sensitive lighting wearables and played in a dark environment.Looking at earlier adaptations of games as well as at the capabilities of the human body and the dynamics of predatory games we developed a new game, 'Sneaky Were-Bees', to explore the possible effects of a motion sensitive lighting wearable on the dynamics in a predatory team game.Through continuous playtesting the rules for the game, and functionality of the wearables were iteratively developed.In playtesting many interesting dynamics emerged in relation to how players attempted to identify and communicate with team members.Moreover, an in the dark predatory game seems to be much less dependent on physical prowess and more strategy based than un-augmented, traditional dodgeball.Altering a game this way sheds a new light on team dynamics and the ways a game such as dodgeball is played.These explorations are hoped to contribute to other attempts to understand the potential of adding digital technology to physical games and increasing the physicality of immersive digital experiencers.
Preface

Extract A random or stochastic process is a process that can be defined by random variables. In other words, it is a process involving observations whose outcome at every time instant is not certain. Mathematically, this reflects in working with functions whose arguments are characterized by a probability distribution instead of having a certain value. The choice of describing a phenomenon by deterministic or probabilistic laws may depend upon several reasons. The phenomenon appears to be conceptualized only as a random process. On the other hand, we know that it can be described by deterministic laws, but due to lack of knowledge about system parameters or high complexity, we decide to model it as a random process. Overall, what is a random process? Is randomness an inherent feature of nature or simply our inability to describe it with deterministic laws? Therefore, is there an inherent randomness in nature or is it our lack of knowledge that bring us to describe it as a random process?
Key technologies for exchange and sharing of multiple data information resources

In the information processing technology, when confront the problem of multi-dimensional data processing capability limitation, a quality data information resource exchange prototype system is designed, and the key technologies involved in the system design are analyzed to realize the exchange and sharing of irrelevant information between different networks.