Reviewerly/exHarmony huggingface dataset:
Signal transmission optimization moving-vector classification mpeg standard video coding

The rise of useful multimedia applications has sparked a rush to perfect video compression methods. Over the last decade, there has been a lot of interest in using motion-compensated frame interpolation (MCFI) methods to boost video frame rate during playback in both the academic and consumer electronics sectors. Interpolation refers to the process of defining the values of a function at places that are not represented by any of the examples. It accomplishes this process by fitting a constant function across the discrete input samples. We based our methodology on the fact that color cameras function similarly to the human eye. We have been used to black and white photographs, yet the real world is full of color. Grayscale images were the sole option until the advent of color monitors and cameras. Energy assessment calls for photo capture using a camera. Light's electromagnetic waves provide the observable energy in this scheme. For motion-compensated video vector frame interpolation or frame rate up-conversion and Phase frame interpolation Method, the authors present a novel approach with low vector dispensation method in the conclusion. Using optical flow or other conventional methods, it is necessary to have precise pixel correspondences between pictures to compute interpolated frames in a video series. We provide a practical replacement by capitalizing on advances in phase-based approaches, which use the phase shift of individual pixels to express motion. In challenging interpolation conditions, such as major appearance changes, flow-based algorithms frequently create severe visual distortions, yet our solution fails gently. Our approach is particularly useful for retiming and interpolating frames in high-resolution video shot at a high frame rate. Estimating motion for the purpose of improving the quality of the decompressed video requires more research on the nature of the compression problem. a novel way to estimating motion that is analogous to full-search 3ss,4ss, block-matching, and parametric techniques. The primary focus will be research into both error-free compression and the development of novel motion estimation algorithms. The results of the research indicate that the suggested system has the potential to increase visual superiority and is also robust, especially when applied to video sequences with quick movements and challenging portions. By combining phase based and conventional Lagrangian, which is utilized to get better quality results and deal with variations in light more gracefully.
From University to Start-Up: The Experience of Akina [Student’s Corner]

Transition from university to a company is always a challenging task. Sometimes you want to keep going in the direction of your studies, focusing on a particular aspect of interest; other times you want to start your own business based on an idea or a technology that you developed during your studies.
‘Where Did THAT Come from?!’ The Giza Project’s Development of Citation and Referencing Documentation for 3D Archaeological Visualizations

Within a broader mission to comprehensively integrate archival data for the site of Giza, the Giza Project at Harvard University has applied over a century’s-worth of archival resources to produce 3D models of the Giza Plateau and many of its major monuments. As technology has expanded the options for documentation and communication of archaeological information to both academic and popular audiences, it has been challenging to adequately preserve fundamental standards of academic transparency and citation for 3D media. Whether intended as visualizations of selected data or as detailed visions of ancient milieus, 3D digital models—along with other media that incorporate them—often include significant elements of reconstruction. Once released, often they become disassociated from the sources and thought processes that informed their creation. By conceiving of 3D archaeological reconstructions as “new data” that integrate with “old data,” the Giza Project has developed referencing protocols and documentation that promote necessary, reasonable, and accessible standards of transparency and citation for 3D archaeological reconstructions and visualizations.
A Study of Application of Task-based Teaching Method in Junior Middle School in English Reading Teaching

English reading is not only an important part in English teaching, but also an important English ability.There are various teaching methods about English reading teaching, but many of them haven't embodied good effects which makes many students' English reading in trouble.Nowadays, many scholars in English teaching advocate task-based teaching method.This method emphasizes English reading teaching and task in order to make students have purpose to read relevant articles.This paper intends to explore how to improve the quality of English reading teaching through Task-based teaching method.As an important part of English teaching, the main purpose of English reading teaching is to cultivate students' reading comprehension ability and cultivate students' understanding of English reading.But the current situation is that English reading teaching in middle school emphasizes more grammar points and word memory and neglects the cultivation of students' reading ability, which will formal a negative impact on students' English learning.As I just mentioned nowadays, more and more scholars advocate task-based teaching method, which can not only improve students' reading ability, but also help them master relevant reading strategies more effectively.At the same time, it can also motive students' learning interests in English reading.
The Digital Rosetta Stone Project

The goal of this contribution is to present The Digital Rosetta Stone, which is a project developed at Leipzig University by the Chair of Digital Humanities and the Egyptological Institute/Egyptian Museum Georg Steindorff in collaboration with the British Museum and the Digital Epigraphy and Archaeology Project at the University of Florida. The aims of the project are to produce a collaborative digital edition of the Rosetta Stone, address standardization and customization issues for the scholarly community, create data that can be used by students to understand the language and content of the document, and produce a high-resolution 3D model of the stone. First, the three versions of the text were transcribed and encoded in XML according to the EpiDoc guidelines. Next, the versions were aligned with the Ugarit iAligner tool that supports the alignment of ancient texts with modern languages, such as English and German. All three texts were then parsed syntactically and morphologically through Treebank annotation. Finally, the project explored new 3D-digitization techniques of the Rosetta Stone in the British Museum in order to enhance traditional archaeological methods and facilitate the study of the artifact. The results of this work were used in different courses in Digital Humanities, Digital Philology, and Egyptology.
Effective Prostate Cancer Detection using Enhanced Particle Swarm Optimization Algorithm with Random Forest on the Microarray Data

Prostate Cancer (PC) is the leading cause of mortality among males, therefore an effective system is required for identifying the sensitive bio-markers for early recognition. The objective of the research is to find the potential bio-markers for characterizing the dissimilar types of PC. In this article, the PC-related genes are acquired from the Gene Expression Omnibus (GEO) database. Then, gene selection is accomplished using enhanced Particle Swarm Optimization (PSO) to select the active genes, which are related to the PC. In the enhanced PSO algorithm, the interval-newton approach is included to keep the search space adaptive by varying the swarm diversity that helps to perform the local search significantly. The selected active genes are fed to the random forest classifier for the classification of PC (high and low-risk). As seen in the experimental investigation, the proposed model achieved an overall classification accuracy of 96.71%, which is better compared to the traditional models like naïve Bayes, support vector machine and neural network.
Reordering of Source Side for a Factored English to Manipuri SMT System

Similar languages with massive parallel corpora are readily implemented by large-scale systems using either Statistical Machine Translation (SMT) or Neural Machine Translation (NMT). Translations involving low-resource language pairs with linguistic divergence have always been a challenge. We consider one such pair, English-Manipuri, which shows linguistic divergence and belongs to the low resource category. For such language pairs, SMT gets better acclamation than NMT. However, SMT’s more prominent phrase- based model uses groupings of surface word forms treated as phrases for translation. Therefore, without any linguistic knowledge, it fails to learn a proper mapping between the source and target language symbols. Our model adopts a factored model of SMT (FSMT3*) with a part-of-speech (POS) tag as a factor to incorporate linguistic information about the languages followed by hand-coded reordering. The reordering of source sentences makes them similar to the target language allowing better mapping between source and target symbols. The reordering also converts long-distance reordering problems to monotone reordering that SMT models can better handle, thereby reducing the load during decoding time. Additionally, we discover that adding a POS feature data enhances the system’s precision. Experimental results using automatic evaluation metrics show that our model improved over phrase-based and other factored models using the lexicalised Moses reordering options. Our FSMT3* model shows an increase in the automatic scores of translation result over the factored model with lexicalised phrase reordering (FSMT2) by an amount of 11.05% (Bilingual Evaluation Understudy), 5.46% (F1), 9.35% (Precision), and 2.56% (Recall), respectively.
VÉgA (Vocabulaire de l’Égyptien Ancien): A New Definition of a Dictionary

VÉgA (Vocabulaire de l’Égyptien Ancien, Vocabulary of Ancient Egyptian) is an online digital dictionary developed in collaboration between Egyptologists, designers and computer engineers specialized in the creation of digital interfaces. The first goal was to create a platform where we can model and present the evolving knowledge of Ancient Egyptian by bringing together and cross-checking words, references, their hieroglyphic forms, as well as creating links to a collection of records related to the texts in question. Since 2017, VÉgA has been accessible using a simple web browser. There are no other installation requirements. Its interface is tailor-made and user-friendly to address the public, whether they be an amateur, professional, student or linguist with needs from the simple translation to a complete lexicographical study. However, after two years of platform development, the outcome ended being radically different from the initial idea. The freedom offered by digital technology to create what we need, the way we want it, pushed the team to rethink how we used a dictionary and to model a new methodology along the way, especially taking advantage of the opportunity to open the tool to scientific and even non-scientific users.
Sejarah dan Perkembangan Kesenian Wayang Gantung di Kota Singkawang

The purpose of this study is to find out how the history and development of the hanging puppet tradition in Singkawang City. This research is basic research. Qualitative data collected mainly in the form of words. To answer how the history and development of the hanging puppet art in Singkawang City, the informants who will be used as resource persons are Singkawang local traditional arts figures. In addition, it also utilizes the literature or the results of previous research. This interactive analysis technique has three components of analysis, namely data reduction, data presentation and drawing conclusions or verification. The result of this research is that the Hanging Puppet in Singkawang City became known in the early 20th century. The character who first introduced the wayang hang art in Singkawang City was Ajo or A Jong. The Chinese community in Singkawang City usually knows the hanging wayang with the term Chiao thew hi which comes from the Hakka language (Khek). The love of the people of Singkawang City for the art of wayang hanging began to increase rapidly in the 1960s. The large number of associations or groups of wayang hang artists in Singkawang City is one of the characteristics of the golden age of wayang hanging.
School Meals Program and Its Impact Towards Student’s Cognitive Achievement

Nutrition food is one of the factors influencing student academic development. By providing a good nutrition for children in school is one of the way to increase economy development in Indonesia. School meals program has important role in order to improve children participation and children performance in school. Some previous research founds that nutrition food ables to increase children cognitive. However, those have not taken into account the direct impact of school meals program on children cognitive. Therefore, this study aims to analyze the direct impact of school meals program toward children cognitive. The data was taken from Indonesia Family Life Survei (IFLS) wave 5. This study is conducting Propensity Score Matching method to knowing the impact of school meal program on children cognitive. The result shows that school meal program has impact to increase children cognitive score on mathematic. It shows that these program has impact on children score by 0.2 point higher than children in school without school meal program.
Fuzzy clustering analysis for the loan audit short texts

Abstract In China, post loan management is usually executed in the form of visit survey by credit man. Through quarterly visit survey, a large number of loan audit short texts are collected, which contain valuable information for evaluating the credit status small and micro enterprises. However, there is still lack of methods for analyzing this kind of short texts. This paper proposes a method for processing these loan audit short texts called Fuzzy Clustering Analysis (FCA). This method firstly transforms short texts into a fuzzy matrix through lexical analysis; Then, the similarity between records is calculated based on each fuzzy matrix, and an association graph is constructed with the similarity. Finally, Prim minimum spanning tree is used to extract clusters based on different α cuts. Experiments with actual data from a commercial bank in China have revealed that FCA yields suitable clustering results when handling loan audit briefs. Moreover, it exhibits superior performance compared to BRICH, Kmean, and FCM..
Enhanced Collaborative Filtering Recommendation Model for Graph Neural Networks Based on Meta-Paths

Abstract With the development of web information technology, recommendation systems are widely used in social media networks, news delivery, and shopping platforms. Collaborative filtering (CF) is one of the main methods in recommendation systems. In recent years, the graph convolutional neural network (GCN) has emerged as the hottest research method in the current recommendation system due to its powerful ability to learn embedding representations on graph structures. Although graph convolutional neural networks have been recognized as having significant advantages in recommendation tasks, the proposed GCN-based recommendation models have generally neglected two aspects. The graph convolution layer of most models does not take full advantage of the covariance signals of higher order neighbors. For example, GCMC only uses the signal update node inlay of the 1st order neighborhood. The graph convolution layer of existing models pays little attention to the impact of different user opinions on the recommendation results when propagating and aggregating synergistic signals. In the recommendation scenario, the rating represents the user's opinion. To address these problems, this paper proposes an enhanced collaborative filtering algorithm for graph neural networks based on meta-paths (MPECFG). The study exploits the synergistic signals of 2nd order neighbors and user's view to improve the accuracy of graph convolutional neural networks in learning node embedding. In particular, we first construct bipartite graphs of users and items, embed their historical interactions into feature vectors, and then obtain higher-order representations of users and items by multi-layer propagation of the neural network. We experimented on public datasets and compared them with traditional algorithms to verify the effectiveness of our model.
ETHNOPEDAGOGY-BASED LITERACY E-MODULE ON INDONESIAN LEARNING SUBJECT

This paper discusses a product of an Ethnopedagogy-based literacy e-module on Indonesian learning subjects for grade IV text material. The research is the ADDIE model development research, which consists of five stages, analysis, design, planning, implementation, and evaluation. The research subjects involved linguists, materials experts, culture experts, design experts and media experts, and teacher and student trials. The object of the research is an Ethnopedagogy-based literacy e-module for grade IV SD students on Indonesian learning subjects. Data collection used questionnaires, observations, and interviews through the validity of the learning media questionnaire instrument. Data were analyzed using quantitative descriptive and qualitative descriptive analysis methods. The results indicate that the product validation test based on the subject matter expert test percentage was 97.00%, the learning culture expert test was 98.00%, the learning media expert test was 92.56%, the design expert test was 98.76%, and the language expert test was 96.00%. The teacher trial was 97.25%, the individual trial was 94.25%, and the small group trial was 90.00%. It can be concluded that pedagogy-based literacy e-modules are feasible and practical to use as teaching materials for story text material in Indonesian language learning subject content for grade IV SD and can be used as a medium for literacy and introduction to local culture.
Accademia Toscana di Scienze e Lettere “La Colombaria”

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Decentralized Finance (DeFi), Strengths Become Weaknesses: a Literature Survey

The use of blockchain technology in Decentralized Finance (DeFi) has gained popularity, with 23 public companies and one country holding bitcoin. DeFi aims to create an open and decentralized financial ecosystem that is accessible to everyone, eliminates intermediaries like financial institutions, and is verifiable, immutable, globally accepted, fast, low-cost, anonymous, and non-custodial. Despite its benefits, the rapid growth of DeFi has led to increased security risks. This study assesses the validity of DeFi's superiority claims in light of security incidents and events in 2022 and Twitter trends. This study used a Systematic Literature Review from various research articles and news from 2022. This research found that DeFi's superiority claims seem to be inconsistent with what is being advertised. It also found that if DeFi is not properly prepared and audited, its strength (Anonymous, open-source, decentralized, non-custodial, eliminates third parties and regulation) may become its weakness. Despite this, users still exhibit high levels of trust and optimism, as seen in the most popular terms shared by user tweets during significant losses, with 301,654 unique tweets between April 30 and May 31, 2022 and 344,519 unique tweets between October 3 and December 3, 2022, that are crypto, nft, and blockchain.
RAS New Quadruped Robot Challenges: Pushing the Boundaries of Robotics Research and Development [Competitions]

Competitions have been a regular feature at almost every ICRA and IROS conference. So far, the organization of competitions has been entirely up to the conference organizing committee (OC). The OC usually issues a call for competition proposals; collects them; and decides which competitions will be hosted based on the conference site and budget conditions. Many big companies, such as Amazon, Airbus, and DJI, have successfully organized competitions at ICRA and IROS, some of which have continued for multiple years and have driven technological advances in robotics. The OC may also organize competitions based on the interests of its financial supporters. Many such competitions have been one-time events, but the Autonomous Drone Racing competition, which ran for four years until it was interrupted by the COVID-19 pandemic, was a successful testbed for vision-based autonomous navigation of quadcopters and attracted participation from many top-tier research teams.
Sentiment Analysis of Twitter Users to the PeduliLindungi Using Naïve Bayes Algorithm

Covid-19 was declared as a pandemic by World Health Organization (WHO) in March 2020, has a major impact on the lives. Indonesian’s government has made several efforts to suppress the spread of the virus by requiring the societies to use PeduliLindungi in every activity. There are many pros and cons from the societies in using PeduliLindungi, many reviews about the performance of this application found through playstore, app store or social media. Twitter is one of social media that allows the societies to express their feeling, idea, opinion, or critics about any topics. This study takes the review of PeduliLindungi from Twitter with period from June up to December 2021, which has the highest cases of covid-19 and tighter movement restriction from the government. The data collected were manually labeling into positive and negative class and processed using sentiment analysis with Naïve Bayes algorithm, give the result 64.69% positive sentiment and 35.5% negative sentiment regarding PeduliLindungi. The model tested using Naïve Bayes algorithm with 10-fold cross validation has the highest performance, the accuracy obtained is 95.86%, with precision 96.99% and recall 94.12%. The positive sentiment indicates the pro expression from society, like the data integration with vaccine certificate, PCR or antigen result, that makes the activities to entry public transport or public space easily. The negative sentiment indicates the cons expression from the societies, related with the performance of the application and the data security. The result of this study expected being reference, give insight, and information for developers and governments to build a better strategy in improving the performance of PeduliLindungi application.
Vibration measurement by projection of phase-modulated and amplitude-modulated structured light

Most of the whole-field optical methods for vibration measurement have low sensitivity when the points of the studied surface vibrate with the same amplitude. Those techniques also usually require complex and/or expensive solutions which are difficult to implement in engineering processes when the vibration amplitudes are relatively high. In order to overcome those limitations we propose a method for out-of-plane vibration measurement which uses structured light projection. The vibrating surface is obliquely illuminated by straight and parallel interference fringes produced by a Twyman-Green interferometer with a 532-nm laser as light source. In order to enable fringe visualization two techniques were employed, namely, the phase modulation of the fringe pattern by using a vibrating mirror in the interferometer, and a stroboscopic illumination by using a Fabry-Perot etalon amplitude modulator. We demonstrated the technique by measuring the vibration amplitudes of small objects in the millimeter and submillimeter range.