Reviewerly/exHarmony huggingface dataset:
Pelatihan Peningkatan Kualitas Pembelajaran dengan Pemanfaatan Media Digital di SMK Muhammadiyah 15 Jakarta

In the era of School from Home (SFH) due to the outbreak of Covid-19 has certainly affected the learning process for all students. Students and teachers have to plunge into the new world in which they must adapt to the new pattern of education. Both of them, like it or not, should immerse in digital world, in the sense they have to acquire technology to run teaching learning process by virtual. For this reason, it is necessary for the team of Community Service (PkM) of Muhammadiyah University of Prof. Dr. Hamka to participate in supporting teachers’ teaching learning process at SMK Muhammadiyah 15 Jakarta to equip them with the knowledge of selecting the appropriate digital media for better teaching. The method used is giving training how to select digital media before implementing in the class. Therefore, this training started with a questionnaire, recognizing learning problems, selecting suitable digital media and putting them in a research proposal. The results of training show that the teachers are able to recognize learning problems, select the appropriate digital media, and put them in a research proposal. Through the post-questionnaire, the teachers realized the importance of selecting suitable digital media for virtual teaching in the time of online learning.
PENERAPAN ROLE PLAY DALAM BASIC ENGLISH CONVERSATION UNTUK ANAK-ANAK GRIYA YATIM DHUAFA PERMATA PAMULANG

This Community Service (PkM) aims to apply the Role Play learning method in Basic English Conversation. This learning model can foster students' enthusiasm for learning and create fun English learning. This learning method is believed to be able to increase interest in learning English, especially for children because this method involves motion games that create fun which is closely related to children. The Role Play method is a learning model that requires students to play one's character. This model is a technique that allows students to explore realistic conditions, situations or events by interacting with other students in a managed manner to enhance the experience. This Community Service activity began with a pre-survey/observation in April 2022 and the core of this activity is conducting teaching and learning activities for the children of Griya Yatim Dhuafa Permata Pamulang by implementing Role Play which was held in mid-May 2022. The PkM results show there is an increase in students' motivation and enthusiasm in learning English so that it is expected to be a reference for educators in creating new nuances in learning English so as to create fun classes and achieve maximum learning goals.
Soccer Player Pose Recognition in Games

Computational models and statistics are becoming more important in professional sports, particularly in soccer. With the advance in the Computer Vision area, information such as pose recognition and player orientation are useful for several applications: team statistics, player tracking, etc. Analyzing the data achieved can improve team performance. This article presents a technique to determine the pose of every player on a soccer field throughout the match. Specific hand-held devices for soccer players can determine and track the position of the player only for their own team. However, it fails in determining the posture of the player. Conventional pose determination of the player does not work well when there is a large number of people in the image. This work overcomes such gaps by combining the person detector YOLO and the pose recognizer OpenPose. The proposed solution utilizes regular transmission recordings of previous matches. The developed approach can successfully determine the player’s posture through these videos. However, this is only the beginning of Computer Vision applied to sports. For future work, player orientation and automatic event detection and classification are expected to be developed.
The Restoration of Mathematical Cabinets Between Rapid Prototyping and Augmented Reality

Physical mathematical models, conceived for distinctly didactic purposes, became the main protagonists in teaching mathematics and geometry between the end of the nineteenth century and the first half of the twentieth century. Long since abandoned in storerooms or the increasingly small display cabinets of mathematic halls, in recent years, they have been the topic of a movement of rediscovery. This study proposes the restoration of collections of mathematical models through rapid prototyping and the integration of explanatory content in Augmented Reality directly on the physical models. The main objective of the research aims at defining a methodology for the renewal of the teaching of geometry, proposing a multimedia didactic theater in which the physical model is once more the protagonist. Initially, an in-depth study is proposed on the mathematical model types representing polyhedra, which display characteristics that derive from the ancient fascination with the perfection of these geometric shapes, selecting for first experimentation the unique collection of Max Brückner’s paper polyhedra.
Media Architecture as Innovative Method of Urban Environment Organizing

The paper considers the aesthetic characteristics of architectural objects formed using media facades, features of the created artistic images on the examples of a number of implemented projects of the Nur-Sultan city. Another area of ​ ​media design research is aimed at highly developed structures of cognition and their regularities: the tendency to completeness, harmony, symmetry, simplicity. The socio-psychological mechanism for the formation and assimilation of stable aesthetic stereotypes - “archetypes” can be interpreted as fixing social experience in the subconscious. This should include the formation of style, artistic image of media design, taste. The image of the city develops in the process of its everyday perception. The authors revealed the conditions for visual perception of the media design of the architectural and spatial environment of the city.
IoT-enabled product development method to support rapid manufacturing using a nature-inspired algorithm

Abstract Investigations illustrate that the Internet of Things (IoT) can save costs, increase efficiency, improve quality, and provide data-driven preventative maintenance services. Intelligent sensors, dependable connectivity, and complete integration are essential for gathering real-time information. IoT develops home appliances for improved customer satisfaction, personalization, and enhanced big data analytics as a crucial Industry 4.0 enabler. Because the product design process is an important part of controlling manufacturing, there are constant attempts to improve and minimize product design time. Utilizing a hybrid algorithm, this research provides a novel method to schedule design products in production management systems to optimize energy usage and design time (combined particle optimization algorithm and shuffled frog leaping algorithm). The issue with particle optimization algorithms is that they might become stuck in local optimization and take a long time to converge to global optimization. The strength of the combined frog leaping algorithm local searching has been exploited to solve these difficulties. The MATLAB programming tool is used to simulate the suggested technique. The simulation findings were examined from three perspectives: energy usage, manufacturing time, and product design time. According to the findings, the recommended strategy performed better in minimizing energy use and product design time. These findings also suggest that the proposed strategy has a higher degree of convergence when discovering optimal solutions.
Training PPA Models for Embedded Memories on a Low-data Diet

Supervised machine learning requires large amounts of labeled data for training. In power, performance, and area (PPA) estimation of embedded memories, every new memory compiler version is considered independently of previous compiler versions. Since the data of different memory compilers originate from similar domains, transfer learning may reduce the amount of supervised data required by pre-training PPA estimation neural networks on related domains. We show that provisioning times of PPA models for new compiler versions can be reduced significantly by exploiting similarities among different compilers, versions, and technology nodes. Through transfer learning, we shorten the time to provision PPA models for new compiler versions, which speeds up time-critical periods of the design cycle. Using only 901 training samples (10%) is sufficient to achieve an almost worst-case (98th percentile) estimation error of 2.67% and allows us to shorten model provisioning times from 40 days to less than one week without sacrificing accuracy. To enable a diverse set of source domains for transfer learning, we devise a new, application-independent method for overcoming structural domain differences through domain equalization that attains competitive results when compared to domain-free transfer. A high degree of automation necessitates the efficient assessment of the best source domains. We propose using various metrics to accurately identify four of the five best among 45 datasets with low computational effort.
Fuzzy Logic in Text Mining Using Python

This chapter introduces about fuzzy logic, its membership functions, and rules followed by various text mining concepts using the fuzzy logic using python. Different open-source libraries for fuzzy logic, preprocessing concepts in fuzzy logic text mining, different feature extraction techniques, fuzzy clustering concepts, classification in fuzzy text mining, fuzzy association rule mining concepts, and visualization in fuzzy text mining are presented.
A model for a practical evaluation of a DASH-based rate adaptive algorithm over HTTP

The proliferation of multimedia devices and user-generated content has driven a massive growth in Internet traffic for video streaming. There is a dire need to propose such solutions that can address multimedia streaming issues to achieve a user’s quality. Dynamic adaptive streaming over HTTP (DASH) improves the user’s quality through practical systems with limited bandwidth that enables the streaming media to run smoothly. This modern technology makes it easy to improve user perception and define the media presentation description (MPD) in terms of Uniform Resource Locator, content file, etc. The proposed adaptation algorithm attempts to determine the optimal solution to alleviate the conflict between maximizing the video quality and avoiding buffer stalls. We evaluate the proposed algorithm against alternative solutions such as ALDASH and FDASH for video content by taking into account the video bitrate, buffer level, and video bitrate switches for the single-user environment. A set of experiments have been conducted to investigate and analyze the benefits of our proposed algorithm. Our proposed algorithm is tested using the NS-3 network simulator, which shows that it improves video quality performance when compared to ALDASH and FDASH in terms of user satisfaction. Last but not least, the experimental results of our proposed algorithm provide high viewer quality in adaptive streaming as compared to its compititors.
Modeling Bounded Surfaces Using Cylindrical Coordinates Using GeoGebra AR

This research focuses on the modeling of bounded surfaces using parameterizations based on cylindrical coordinates, which is one of the topics of the multivariable calculus course, where it seeks to develop modeling and problem-solving skills in real context, being essential for this to develop geometric skills that allow sketching graphs in space. Therefore, the main objective of the research was to present a modeling case of a sludge decanting tank, through cylindrical coordinates, using the GeoGebra software in its Suite version for mobile devices, in addition to interacting with augmented reality (GeoGebra AR). With this, a didactic, dynamic, and iterative form is proposed where the inter-action between mathematics, engineering and technology is evidenced, and seeks to improve the teaching-learning experience.
Introduction

In this chapter, the basic idea of what text data is, along with the definition of natural language and techniques involved in it has been clearly explained. Besides this, the framework of text mining and its workflow framework is explained.
The Development of the Wayang Panji Nusantara Network Model to Strengthen the Articulation of the Panji Culture in Southeast Asia

Wayang Panji is a puppet based on Panji stories that developed in Southeast Asia. The story of Panji in the art of wayang is found in Malang mask puppet art, Krucil Kediri puppets, Madurese puppeteers’ puppets, Banjar Kalimantan puppets, Thai Siamese puppets, and wayang puppets in Kelantan Malaysia. The development of Panji culture in Indonesia has been partly through the Panji Nusantara Week activity, which is held once a year, and features performances of Panji-themed arts in several cities in Indonesia. The Panji Cultural Week, which has been held for the past few years, has yet to touch all areas of Panji-themed art, both in Indonesia and abroad. Panji wayang art, which is one of the Panji cultural products, is overlooked by practitioners of Panji culture, even though Panji wayang art is spread across several regions in Indonesia and in several Southeast Asian countries. This research sought to develop Panji-themed wayang art in the Southeast Asian region, so that it has parallels with other Panji-themed arts, through the development of the Panji wayang network in the Southeast Asian region. The Panji Nusantara wayang network aims to build cultural communication between actors and observers of Panji wayang art in the Southeast Asia region and serve as a publication media for Panji puppets for the general public. The cultural communication media was formed as a virtual collaborative performance event, while the wayang Panji publication media is in the form of a digital application-based platform that contains a database for the Panji Nusantara puppet, profiles of the Panji wayang artists, and a roster of the performance activities. This research used the Willis design development method combined with ethnographic methods. The research data were collected in East Java and Kelantan Malaysia.&#x0D; Keywords: Development, puppet, panji nusantara, southeast asia
Optimization of Online Learning With the Development of Video Learning Media for Early Children's Education

Since the start of its spread in 2020, the COVID-19 pandemic has had an impact on various fields in Indonesia, one of which is education. Because of the pandemic, the Indonesian Government has called for replacing face-to-face learning with online learning. Teachers are required to be more creative in developing learning media that can be used for the online learning process. In this study, teachers developed learning media in the form of videos for early childhood levels. The development of this learning media used the ADDIE approach (analysis, design, development, implementation and evaluation). The media developed were validated by material experts and media experts. Then a product trial was conducted at the TK/KB Laboratory of the State University of Malang. The results of the product trial showed that there is student interest in video learning media for online learning.&#x0D; Keywords: online learning, media, video
CRAIG INTERPOLATION THEOREM FAILS IN BI-INTUITIONISTIC PREDICATE LOGIC

Abstract In this article we show that bi-intuitionistic predicate logic lacks the Craig Interpolation Property. We proceed by adapting the counterexample given by Mints, Olkhovikov and Urquhart for intuitionistic predicate logic with constant domains [13]. More precisely, we show that there is a valid implication $\phi \rightarrow \psi $ with no interpolant. Importantly, this result does not contradict the unfortunately named ‘Craig interpolation’ theorem established by Rauszer in [24] since that article is about the property more correctly named ‘deductive interpolation’ (see Galatos, Jipsen, Kowalski and Ono’s use of this term in [5]) for global consequence. Given that the deduction theorem fails for bi-intuitionistic logic with global consequence, the two formulations of the property are not equivalent.
Finding answers to COVID-19-specific questions: An information retrieval system based on latent keywords and adapted TF-IDF

The scientific community has reacted to the COVID-19 outbreak by producing a high number of literary works that are helping us to understand a variety of topics related to the pandemic from different perspectives. Dealing with this large amount of information can be challenging, especially when researchers need to find answers to complex questions about specific topics. We present an Information Retrieval System that uses latent information to select relevant works related to specific concepts. By applying Latent Dirichlet Allocation (LDA) models to documents, we can identify key concepts related to a specific query and a corpus. Our method is iterative in that, from an initial input query defined by the user, the original query is expanded for each subsequent iteration. In addition, our method is able to work with a limited amount of information per article. We have tested the performance of our proposal using human validation and two evaluation strategies, achieving good results in both of them. Concerning the first strategy, we performed two surveys to determine the performance of our model. For all the categories that were studied, precision was always greater than 0.6, while accuracy was always greater than 0.8. The second strategy also showed good results, achieving a precision of 1.0 for one category and scoring over 0.7 points overall.
Automatic selection of coordinate systems for learning relative and absolute spatial concepts

Robots employed in homes and offices need to adaptively learn spatial concepts using user utterances. To learn and represent spatial concepts, the robot must estimate the coordinate system used by humans. For example, to represent spatial concept "left," which is one of the relative spatial concepts (defined as a spatial concept depending on the object's location), humans use a coordinate system based on the direction of a reference object. As another example, to represent spatial concept "living room," which is one of the absolute spatial concepts (defined as a spatial concept that does not depend on the object's location), humans use a coordinate system where a point on a map constitutes the origin. Because humans use these concepts in daily life, it is important for the robot to understand the spatial concepts in different coordinate systems. However, it is difficult for robots to learn these spatial concepts because humans do not clarify the coordinate system. Therefore, we propose a method (RASCAM) that enables a robot to simultaneously estimate the coordinate system and spatial concept. The proposed method is based on ReSCAM+O, which is a learning method for relative spatial concepts based on a probabilistic model. The proposed method introduces a latent variable that represents a coordinate system for simultaneous learning. This method can simultaneously estimate three types of unspecified information: coordinate systems, reference objects, and the relationship between concepts and words. No other method can estimate all these three types. Experiments using three different coordinate systems demonstrate that the proposed method can learn both relative and absolute spatial concepts while accurately selecting the coordinate system. The proposed approach can be beneficial for service robots to flexibly understand a new environment through the interactions with humans.
A Study on Teacher’s Questioning Practice in an ESL Learning Context in Hong Kong

This empirical study intends to explore the questioning behaviors of an English as a second language (hereinafter referred to as ESL) teacher in Hong Kong by quantitatively looking at the distribution of the two types of questions, namely display questions and referential questions, as well as by qualitatively evaluating the universally accepted functions of the questions and the effectiveness of the modification techniques used to enhance the factual value of the questions. Data-based explorations challenging the traditional views toward questions are critically presented, and new findings are excavated and advocated. Pedagogical implications are considerably raised as they serve as a theoretical framework to be applied and further analyzed in future real-life EFL and ESL settings, so as to realize better assessment for learning.
Distributed Random Beacon for Blockchain Based on Share Recovery Threshold Signature

Random beacons play a crucial role in blockchains. Most random beacons in a blockchain are performed in a distributed approach to secure the generation of random numbers. However, blockchain nodes are in an open environment and are vulnerable to adversary reboot attacks. After such an attack, the number of members involved in a random number generation decreases. The random numbers generated by the system become insecure. To solve this problem while guaranteeing fast recovery of capabilities, we designed a threshold signature scheme based on share recovery. A bivariate polynomial was generated among the participants in the distributed key generation phase. While preserving the threshold signature key share, it can also help participants who lost their shares to recover. The same threshold setting for signing and recovery guarantees the security of the system. The results of our scheme show that we take an acceptable time overhead in distributed key generation and simultaneously enrich the share recovery functionality for the threshold signature-based random number generation scheme.
Auto calibration of multi‐camera system for human pose estimation

The multi-camera calibration is an essential step for many spatially aware applications, such as robotic navigation, augmented reality, and 3D human pose estimation. Traditional calibration methods use off-the-shelf checkerboards or triangles as the known world coordinate system and their corresponding corners are set as control points, which heavily depends on specific calibration patterns and is not suitable for calibration pattern-denied environments. In this paper, an automatic calibration method is proposed to calibrate the multi-camera system without the aid of a known calibration pattern. The key idea of the proposed method is that the authors consider the human body, which is always available, as the counterpart of the calibration pattern. The authors’ approach starts with binocular camera calibration, in which the extrinsic and intrinsic parameters are calculated in order and followed by a joint optimisation. With the results of each pair of binocular camera calibration, the multi-camera system calibration is carried out in three steps: (i) parameters initialisation, (ii) extrinsic parameters optimisation, and (iii) jointly optimising intrinsic and extrinsic parameters. Since the authors’ approach does not require additional calibration patterns except for one visible person, it is flexible and easy to be implemented. Real experiments are conducted in different scenes, camera angles, and camera settings. Human pose estimation with the multi-camera system is additionally performed for exhaustive experiments. The experimental results demonstrate that the authors’ method shows superior performance than the traditional method with the aid of a specific calibration pattern.