Reviewerly/exHarmony huggingface dataset:
Metaverse: Innovation in Teaching Methods and Game Design for Teenagers' Second Language

Metaverse is based on reality and beyond reality.Its popularity has made many people understand the world of virtual reality.Neal stephenson (American writer)described that everyone in the Metaverse has a dual identity, and ontology can exist in the parallel world of the real world and the network at the same time.If the current Internet is regarded as a two-dimensional world, then the Metaverse can be regarded as a three-dimensional world that exists in parallel.If can let second language learners enter the Metaverse, and rely on AI (artificial intelligence), VR (virtual reality) , and MR (mixed reality) to obtain a better environment experience of language learning and social language application,to solve the barriers of language learning, combine teaching with fun, and combine learning with fun. Learn from the relaxed and virtual real world, deepen learning, and apply emotion and language cultural motivation to the design of learning games,It is not only the innovation and improvement of second language classroom teaching methods, but also the perfect integration of second language learning and modern high-tech technology, and the complex international Chinese teaching is presented in a popular gamification method, which is more conducive to improving the teaching quality of second language learning.
Studying “Pre-Truth” Science: The 2023 Scholarly Communications Institute

By Alice Fleerackers, with input from Yao-Hua Law, Mario Malički, Luisa Massarani, Chelsea Ratcliff, and François van Schalkwyk &lt;em&gt; The annual Scholarly Communications Institute (SCI) offers opportunities for interdisciplinary and international teams to come together to pursue complex projects related to a common theme. &lt;/em&gt;
Designing A Web-Based Employee Payroll Application

The fulfillment of the employees' payroll is a crucial task of the firm, ensuring the well-being of its workforce following a complete month of employment. The wage calculation system employed by a raw material distribution company in West Java currently relies on semi-computerized methods, specifically utilizing MS Excel for processing purposes. This approach is considered less efficient and susceptible to inaccuracies in its computations. This study aims to design and implement a system that can aid the organization in reducing computation errors. The author employs a qualitative descriptive methodology in their study. The author employs the OOSE (Object Oriented System Engineering) method as the chosen approach for development, emphasizing use cases. The employee payroll application was designed and implemented using the PHP programming language with the Laravel framework. The MySQL database was utilized for data storage. The anticipated outcome of the investigation into the employee payroll application is poised to provide the organization with improved efficiency and precision in processing employee wage calculations while concurrently mitigating the potential for data loss.
Estimation of Seismic Phase Delays Using Evolutionary Algorithms

In modern seismology, a comparison between the synthetic seismogram generated using a synthetic model of the Earth and the observed seismogram helps in understanding the structure of the Earth and the difference between the actual structure of the planet and the synthetic structure. The phase delay between synthetic and observed seismograms is one of the sources of such information. The traditional method of calculating phase delay includes translating the seismogram from the time domain to the frequency domain using Discrete Fourier Transform. This research aims to develop a method to find phase delays using Evolutionary Algorithms. We show that phase delays can be estimated using Genetic Algorithm with comparable or better accuracy than Discrete Fourier Transform. It is more flexible, allowing for example to add prior information. This is particularly useful also to avoid the so-called cycle-skip effects (an ambiguity of $$\pm 2\pi $$ in the recovered phase-delay), a significant drawback with Discrete Fourier Transform methods.
A Framework to Authenticate Signature using Machine Learning Technique

The main objective of this research study is to implement signature verification using machine learning and also to verify the validity of signatures. This study has collected some original signatures and are verified with a random signature. In the proposed model, each signature will have a unique ID. The signatures can be uploaded in different formats like .PNG, .JPG, etc., and the proposed system will check whether the given signature matches with original signature. Initially, pre-processing will be done on the input image to convert it into black and white format and then the x and y coordinates and curves will be extracted to verify the signature. Features like ratio, centroid, eccentricity, solidity, skewness, and kurtosis will be extracted from pre-processed image to characterize various aspects like shape, size, and texture. These features will then help in classifying the genuine and forged signatures. Whenever the input image is given, the original data will be verified and classified either as real signature or forged.
Designing of a Decentralized Cluster Data Warehouse using Amdahl's and Gustafson's Law

Decentralized cluster data warehouses are popular owing to their scalability and availability. Performance and resource consumption must be considered while creating such systems. Amdahl's law argues that the proportion of the workload that cannot be parallelized limits a system's speedup. This law affects system design in decentralized cluster data warehousing. In creating a decentralized cluster data warehouse, Amdahl's law requires detecting and evaluating bottlenecks in data input, storage, processing, and query execution. Designers may improve parallelizable components by understanding non-parallelizable components. A decentralized cluster data warehouse needs data propagation. Keeping frequently accessible data close may impair system performance. This requires exact data partition, replication, and cluster node data placement. Decentralized cluster data warehouses need technical, organizational, and governance concerns. Data security, privacy, regulatory compliance, and accessibility are examples. John Gustafson and Edwin Barsis' Gustafson's Law stresses parallel computing's scalability and workload rise. Gustafson's Law allows scaling up the issue and using more computer resources to handle higher workloads, unlike Amdahl's Law. The law shows that as the issue size increases, the percentage of the program that may be processed in parallel becomes a bigger fraction of the entire execution time, improving efficiency and speedup. Gustafson's Law promotes reducing execution time by dividing task over numerous processors. This abstract compares Gustafson's Law with Amdahl's Law, revealing parallel computing's advantages for bigger problem instances and the impact of increasing workload in parallel efficiency.
MATHEMATICAL DESCRIPTION OF THE DIFFERENTIATION OPERATION IN THE LOGICAL-TIME ENVIRONMENT

Effective and timely processing of information is one of the most important problems of creating means of its processing at the level of human perception and thinking. Analytical processing of digital signals in a graphical or purely digital representation is somewhat limited and does not take into account the dynamics of signals and messages. The classical apparatus of logic is insufficient to describe the dynamics of system behavior over time. Therefore, it is important to develop models of so-called Boolean differential calculus, as this approach is based on the general concept of changing the logical variable, which will lead to a universal, in terms of dynamics, system of concepts and operations. To facilitate the preprocessing of dynamic digital variables and signals, the logic-time function of multivalued logic can be used. The purpose of this article is a mathematical representation of the differentiation of logic-time functions of multi-valued logic in the index form of the record using the simulation of its scheme. The paper shows the expediency of the idea of replacing an arbitrary digital signal (variable) that changes over time with a logic-time function, which allows to facilitate the preliminary analytical processing of digital signals and variables using the properties of such functions. The article presents a new mathematical apparatus for describing logic-time functions of multivalued logic and individual operations on them using modeling of known implementation schemes. The paper considers the peculiarities of the derivative of the multivalued logical-time function (LMF), as one of the most used and basic operations used in the study of signals and images. Its characteristics and features are shown for functions presented in index form. The general expression of the derivative of the n order is obtained and it is shown that different logic-time functions can have the same derivative. The concepts of the left and right derivative of the LMF are introduced and the relationship between them is shown. The properties of the k derivative of the BLMF were considered and the expressions for the derivative conjunction and disjunction were obtained. A possible structural scheme of the differentiator is presented, which opens up the possibility of hardware processing of multi-valued LMFs.
The Effects of Viewing Formats and Song Genres on Audience Experiences in Virtual Avatar Concerts

With the recent advancements in multimedia and computer graphics technology, virtual avatar concerts have become increasingly popular among both well-known celebrities and subculture-based virtual YouTubers, attracting large audiences. Although this new form of performance art can be delivered through various platforms that use different viewing formats, research on the components of enjoying virtual avatar concerts and their effects on the audience experience is lacking. This study aims to explore the effects of different viewing formats and song genres on sickness, presence, and immersion and identify preferences for enjoying virtual avatar concerts. We first analyzed data from 64 virtual avatar concert cases to identify the most commonly used viewing media, methods, and song genres. Based on our analysis, we designed and conducted a user experiment with four virtual avatar concert scenarios. The experiment compared two viewing methods (audience's point of view and director's edited view) and two song genres (dance and ballad) for 2D display and a head-mounted display. The results show that the audience's point of view and a dance song can be advantageous in increasing the immersive experience irrespective of the viewing medium. Furthermore, the participants show different expectations regarding performances according to song genres. We discuss these findings and propose guidelines to help design and conduct virtual avatar concerts effectively.
Do universities wait for graduates of secondary vocational educational institutions?

Introduction . Within the framework of the methodology of modern vocational education, the article examines the transformation of communication campaigns of universities to attract applicants after colleges and technical schools. Purpose setting . The main problem of communication campaigns of higher educational institutions is insufficient attention to narrower segments of applicants, especially college and technical school graduates. Methodology and methods of the study . It is reasoned that college graduates have different needs and values, hence the focus of attention of the communication campaign should also be different. Results . After the analysis, some shortcomings in communication campaigns aimed at college graduates become apparent: for example, the lack of a full-fledged communication campaign as such, the lack of information necessary for full enrollment on some college websites, the lack of «college representatives» who visit colleges in person and talk about their college. Conclusion . Measures were proposed to improve the communication campaign of higher educational institutions to attract applicants entering on the basis of secondary vocational education.
DESIGN AND BUILD VR HORROR GAMES WITH PROCEDURAL CONTENT GENERATION USING CELLULAR AUTOMATA ALGORITHM

The development of video games is very fast according to data obtained by ESA in 2021, about 226 million people on American played video games and in Indonesia 105 million people play video games and this will continue to increase, it is predicted that in 2025 video players gaming in Indonesia will reach 127 million people, this causes the need for game content continues to increase while for making game content it is not something that cheap, one way to reduce costs in making content in the game is to implement procedural content generation, procedural content generation is one way of creating content game automatically by using an algorithm. This research aims to design and build a virtual reality horror game using use cellular automata algorithm, cellular automata algorithm in research This research is used for map making, besides that this research also aims to measure the level of player satisfaction with the game that has been made. Game created using the Unity 3D game engine and the C# programming language. After game has been successfully built, will measure the level of satisfaction through cakes. questionnaire using GUESS-18, based on tests that have been carried out with GUESS-18, the results obtained are 77.1 percent, which can be concluded that the level of player satisfaction is categorized as good.
1D-Touch: NLP-Assisted Coarse Text Selection via a Semi-Direct Gesture

Existing text selection techniques on touchscreen focus on improving the control for moving the carets. Coarse-grained text selection on word and phrase levels has not received much support beyond word-snapping and entity recognition. We introduce 1D-Touch, a novel text selection method that complements the carets-based sub-word selection by facilitating the selection of semantic units of words and above. This method employs a simple vertical slide gesture to expand and contract a selection area from a word. The expansion can be by words or by semantic chunks ranging from sub-phrases to sentences. This technique shifts the concept of text selection, from defining a range by locating the first and last words, towards a dynamic process of expanding and contracting a textual semantic entity. To understand the effects of our approach, we prototyped and tested two variants: WordTouch, which offers a straightforward word-by-word expansion, and ChunkTouch, which leverages NLP to chunk text into syntactic units, allowing the selection to grow by semantically meaningful units in response to the sliding gesture. Our evaluation, focused on the coarse-grained selection tasks handled by 1D-Touch, shows a 20% improvement over the default word-snapping selection method on Android.
Implementation of AR and VR using 5G in conventional industry applications

Various industry verticals have tedious tasks that are vital in terms of maintenance, operations and customer service. These repetitive activities use traditional methods to achieve the goal, however, the methods are not efficient, as they are time consuming and resource heavy. Emerging technology of Augmented Reality (AR) and Virtual Reality (VR) brought the drastic change for example in Bridge check-up, Big Box stores, Health care, Supply-chain management. But these sharp change in our life demands more work in less time with precision and high resolution. To implement AR and VR under 5G there are challenges, such as: how to get fidelity and high resolution, where Drone or Robot-assisted bridge inspection is required. The objective of this research work is twofold: 1) meet the challenges and 2) figure out optimize solutions.
Serverless Scheduling Policies based on Cost Analysis

Current proprietary and open-source serverless platforms follow opinionated, hardcoded scheduling policies to deploy the functions to be executed over the available workers. Such policies may decrease the performance and the security of the application due to locality issues (e.g., functions executed by workers far from the databases to be accessed). These limitations are partially overcome by the adoption of APP, a new platform-agnostic declarative language that allows serverless platforms to support multiple scheduling logics. Defining the "right" scheduling policy in APP is far from being a trivial task since it often requires rounds of refinement involving knowledge of the underlying infrastructure, guesswork, and empirical testing. In this paper, we start investigating how information derived from static analysis could be incorporated into APP scheduling function policies to help users select the best-performing workers at function allocation. We substantiate our proposal by presenting a pipeline able to extract cost equations from functions' code, synthesising cost expressions through the usage of off-the-shelf solvers, and extending APP allocation policies to consider this information.
Spreadsheet-based Configuration of Families of Real-Time Specifications

Model checking real-time systems is complex, and requires a careful trade-off between including enough detail to be useful and not too much detail to avoid state explosion. This work exploits variability of the formal model being analysed and the requirements being checked, to facilitate the model-checking of variations of real-time specifications. This work results from the collaboration between academics and Alstom, a railway company with a concrete use-case, in the context of the VALU3S European project. The configuration of the variability of the formal specifications is described in MS Excel spreadsheets with a particular structure, making it easy to use also by developers. These spreadsheets are processed automatically by our prototype tool that generates instances and runs the model checker. We propose the extension of our previous work by exploiting analysis over valid combination of features, while preserving the simplicity of a spreadsheet-based interface with the model checker.
Early Breast Cancer Prediction using Machine Learning and Deep Learning Techniques

Breast Cancer (BC) is a considered as one of the utmost lethal diseases across the globe that has a very high morbidity and mortality rate. Accurate and early prediction along with diagnosis is one of the most crucial characteristics for the treatment of Breast Cancer. Doctors can have an edge over Breast cancer if they are able to predict it in its early stages using deep learning and machine learning techniques. This paper proposed consists of comparison between the and accuracy of various machine learning models like Support vector machine (SVM), K-Nearest Neighbours (KNN), Naïve Bayes (NB), Logistic Regression (LR), Random Forest (RF), Decision Tree (DT), XGB Classifier and deep learning model of Artificial neural networks (ANN) for the precise detection of breast cancer.&#x0D; The most crucial properties from the database have been chosen using one feature-selection technique. Correlation is also used to choose the most correlated features from the data. Implementing the ANN model consists of one input layer, two hidden layers, and one output layer. All Machine Learning models and ANN model are then applied to selected features. The results demonstrated that the SVM classifier achieved the highest performance with an accuracy of ~98.24%.
360$$^{\circ }$$ Omnidirectional Salient Object Detection with Multi-scale Interaction and Densely-Connected Prediction

Despite the fact that 360 $$^{\circ }$$ cameras have become affordable, the efforts in salient object detection (SOD) of 360 $$^{\circ }$$ omnidirectional images are still relatively few. The performance of the SOD task is significantly hindered by the severe distortion and the large range of object sizes in omnidirectional images. Therefore, we propose a Multi-scale Interaction and Densely-connected Prediction network (MIDP-Net) to counteract distortion and extract multi-scale information in 360 $$^{\circ }$$ omnidirectional images. Specifically, we introduce a Multi-Level Features Interaction (MLFI) module that firstly integrates the features with different receptive fields from adjacent levels, and then fuses the semantic cues from upper-level decoder to obtain the accurate multi-scale information. In addition, to overcome the distortion of 360 $$^{\circ }$$ omnidirectional image, we design a Two-Pass Decoder (TPD) module, which further strengthen the semantic information by secondary decoding and combines the edge cues and saliency cues to optimizes the details of prediction map. The comprehensive experiments on two public 360 $$^{\circ }$$ omnidirectional datasets indicate that the proposed MIDP-Net outperforms the state-of-the-art methods.
Study on the Process Establishment Using FOM-BI and CPS for a Small and Medium-sized Food Manufacturing Company

As innovative products and services are rapidly created in the era of the Fourth industrial revolution, and the convergence of digital and analog accelerates, smart manufacturing operation management is required to respond to a rapidly changing business environment, and FOM-BI, a low-cost and customized platform, can be an alternative. CPS simulations were conducted and verified for small and medium-sized food manufacturers, focusing on improvements made through FOM and VSM analysis. Optimal solutions were found to improve the non-value-added process, and productivity improvement measures were derived. The KPI visualization dashboard made it possible to detect problems in real time and make data-based decisions. Leveraging the FOM-BI platform will contribute to enhanced corporate performance and competitiveness by establishing a smart manufacturing company.
The phenomenology of architectural “space-time” in the digital dimension

Innovations in modeling the environment of architectural objects as a database of localized events require an in-depth study of the convergence potential of the humanities and exact sciences. The ontology of the digital twin of architecture in the categorical pair “space-time” is considered in the concept of “chronolocus”, the meaning of which is reduced to the temporal exposition of architectural space as a process. Synthesis of the topological description of the architectural form at the moment of the event based on the theory of A. Gabrichevsky is seen as a necessary research step in the design of the environment of four-dimensional architectural objects. The applied meaning of the “chronolocus” model as a way of describing a four-dimensional architectural environment lies in the variable possibilities of digital fixation of the “cultural code” of an architectural object in the process of synthesis of “space” in the functional and aesthetic dimension and “time” in the social and event dimension.
Program Literasi di SDN 112 Pekanbaru, SDN 161 Pekanbaru, SDN 018 Kubang Raya dan SDN 028 Rimbo Panjang

The problem in this study is related to the implementation of literacy in elementary schools (SD). This study uses a literature study from previous research observation reports. Data tracking is done by conducting searches during observations in elementary schools. From the results of the search, it was found that several literacy practices were implemented in elementary schools and regarding literacy that had not been implemented in elementary schools. The obstacles encountered in implementing some of the non-existent literacy are demanding the abilities of students and teachers, students who have not been able to think critically and teachers who do not know how to apply it properly and correctly.