Reviewerly/exHarmony huggingface dataset:
MAKNA KONTEKSTUAL PADA MOTTO SKRIPSI MAHASISWA BAHASA DAN SASTRA INDONESIA ANGKATAN 2015

The history of human civilization shows that language is a form of human behavior that has its own characteristics. Another definition, language is a means of thought, a system of expression that mediates the transmission of thoughts from one person to another. Meaning is a symptom in speech. Contextual meaning is a meaning of a lexeme or word that is in one context. Motto is a word or exclamation that describes the motivation, spirit, and goals of an organization. This research is a qualitative research. Qualitative research is research that intends to understand the phenomenon of what is experienced by research subjects. Based on the results of the discussion, it can be concluded about the Analysis of Contextual Meaning in the Thesis Motto of Indonesian Language and Literature Students Class of 2015 as follows: contextual meaning of setting, contextual meaning of activities, and contextual meaning of relationships.
The Effect of Class Linked with Extracurricular Programs Influencing the Learning Competency of University Students

본 연구의 목적은 대학생의 학습역량을 개발하기 위하여 교양교과와 비교과 프로그램을 연계하여 수업을 운영하고, 그 효과를 검증하는 것이다. 이를 위해 2021학년도 2학기 ‘대학에서의 학습전략’ 수업과 다양한 비교과 프로그램을 연계하여 수업을 설계하고 운영하였다. 25명의 참여학생을 대상으로 학습역량을 측정하여 수업 전과 후 학습전략 검사, 자기주도학습역량 검사를 실시하여 분석하였다. 학생들의 학습경험을 확인하기 위한 심층면접에는 10명이 참여하였고, 2회 인터뷰한 결과를 분석하였다. 연구 결과, 대학생들은 교양수업과 비교과 프로그램 연계 수업참여를 통해 학습역량을 개발할 수 있었다. 수업 전보다 참여한 후 학생들의 학습전략과 자기주도학습역량 점수가 유의미하게 증가하였다. 인터뷰 결과에서는 학생들의 인지적 전략, 학습동기 전략, 학습행동 전략에서 긍정적인 변화가 나타났다. 따라서 교양교과와 비교과 프로그램 연계를 통해 학습역량을 개발할 수 있다는 것과 연계 목적에 따른 연계 방식을 고려하여 체계적으로 설계하고 운영하는 것이 중요하다는 것을 확인하였다. The study was to examine the effect of the regular curricular instruction which had incorporated with the extracurricular activities program on the development of learning competency of the university students. For the purpose, it implemented the "Learning strategies" class incorporating with the extracurricular programs. And the gathered quantitative and qualitative data in the students’ learning competency were processed to show any changes. The tests of the learning strategies and self-directed competency were given 25 students. And, further, interviews with 10 students were taken to test instructional effect. The results obtained showed the competency of the learning strategies and self-directed learning had been significantly increased. These included the positive change in the area of cognitive, motive as well as active learning strategies. The study might imply that university instruction should be planned and executed to incorporate and infuse varieties of the hands-on outside activities with the regular curricular instruction.
Development of the Minimal Achievement Standards for Middle School English Subject

This research aims to develop minimal achievement standards based on the 2015 revised national curriculum and identify potential issues to lay the foundation for the future development of the minimal achievement standards for the 2022 revised national curriculum. The minimal achievement standards of the 2015 revised national curriculum were developed based on the “low” level assessment criteria, with additional examples of level-appropriate tasks. The draft underwent multiple expert reviews and was revised accordingly.&#x0D; The conclusion of this research suggests that each grade should have its own minimal standards instead of having one-size-fits-all standards for all middle school grades. This will better reflect the appropriate achievement levels for each grade. Additionally, there is a need for assessment tools that can evaluate students who fall below the minimal achievement standard, and educational materials should be developed based on the minimal achievement standards. Further research is necessary to update the minimal achievement standards in accordance with the up-to-date 2022 revised curriculum.
3 The Overview of Data Virtualizations and Its Modern Tools in the Domain of Data Fabrics

There is a huge research gape between the traditional data fabrics, its Virtualization tools and the advanced and best tools in today’s date. Getting aroused with this fact this research is written to through light on the data fabrics and there are many data Virtualization tools available, and we’ve done the research to determine the best for small businesses. These tools should be versatile, easy to use and allow you to visualize data in a variety of ways to suit your business needs. The research clearly distinguishes the pros and cons of particular tool used in the research.
Implementation of Digital Transformation in Student Organizations

With technological developments that are increasingly significant every year, many organizations or companies are led to change activities digitally without exception for student organizations that are required to do the same thing.Student organizations have the meaning of an organization that is formally and officially registered under the university.Other than that, it is not included in the context of student organizations.However, the implementation of digital transformation encountered many obstacles, such as a lack of prepared human resources, lack of support, and the reluctance to make significant changes.The method used in this research qualitatively uses a literature review method.The results of this research propose implementation steps that can be applied to student organizations, solutions to challenges during implementation, and a new factor in the digital organization, namely the digital mindset.
Prediction of Cr and Ni contents in soil from hyperspectral data combined with Al-Fe minerals

Hyperspectral analysis is useful in monitoring and evaluating soil heavy metal pollution. The difficulty in estimation of heavy metals by hyperspectral analysis is to extract the spectral features related to soil heavy metal concentration which may be interfered by signals resulting from other soil components. In this study, we established a comprehensive framework for prediction of Cr and Ni from hyperspectral data combined with soil Al-Fe minerals using advanced machine learning methods. The Al-Fe minerals were measured in laboratory and predicted from the spectral data, respectively. The results show that (1) from the original hyperspectral data, the model performances for Cr (R2 = 0.61, RMSE = 16.96) and Ni (R2 = 0.34, RMSE = 6.92) are not satisfactory. (2) With the incorporation of the measured Al-Fe minerals as the predictors, the optimal machine learning method for prediction of Cr and Ni is XgBoost, and the model performances are improved obviously (Cr: R2 = 0.85, RMSE = 10.67; Ni: R2 = 0.71, RMSE = 4.55). (3) With the incorporation of the Al-Fe minerals predicted from the spectral data, the optimal machine learning method for prediction of Cr and Ni is GdBoost, and the model performances are acceptable (Cr: R2 = 0.74, RMSE = 13.93; Ni: R2 = 0.68, RMSE = 4.79). This study provides a preliminary analysis for mapping soil heavy metal content and monitoring heavy metal pollution over a large spatial extent.
Mesh Optimization using Python Libraries

Abstract: In this project, the mesh of a 3D model is optimised using Python tools (Pymeshlab and Blender python). This is accomplished by the "mesh decimation" procedure, which involves lowering the mesh's total number of triangles. The goal of this procedure is to reduce the complexity of the mesh while preserving the general form and geometry of the original model. The project's main objective is to boost real-time applications' performance, which must provide quick rendering and visualisation. The project attempts to optimise the mesh in order to achieve higher frame rates and better animations, which can enhance the user experience as a whole. It is important to note that the project's main goal is to optimise the mesh without modifying the model's topology or geometry. This indicates that the original structure and shape
Generalised Scale-Space Properties for Probabilistic Diffusion Models

Probabilistic diffusion models enjoy increasing popularity in the deep learning community. They generate convincing samples from a learned distribution of input images with a wide field of practical applications. Originally, these approaches were motivated from drift-diffusion processes, but these origins find less attention in recent, practice-oriented publications. We investigate probabilistic diffusion models from the viewpoint of scale-space research and show that they fulfil generalised scale-space properties on evolving probability distributions. Moreover, we discuss similarities and differences between interpretations of the physical core concept of drift-diffusion in the deep learning and model-based world. To this end, we examine relations of probabilistic diffusion to osmosis filters.
A covert communication model of Ethereum based on smart contracts

To solve the problems of low hidden capacity, weak concealment and low transmission efficiency in the existing blockchain covert communication, a covert communication model of Ethereum based on smart contracts is proposed. First, the sender processes the plaintext information and the key information into a binary sequence, to get the secret information to be embedded. The sender embeds the secret information into the smart contract source code by using the space method. Secondly, the sender compiles and deploys the smart contract containing the secret information to the Ethereum network. Finally, the receiver can use the pre-shared account information and key to restore the plaintext information to the acquired smart contract through the inverse process of the embedding algorithm. Through the deployment experiment of the Ethereum test network, the results show that the model realizes covert communication based on smart contract information hiding. By analysing and comparing the existing similar models, the model further improves the hidden capacity, reduces the communication cost, has better performance concealment and security.
ANALISIS KESESUAIAN IMPLEMENTASI PROGRAM GERAKAN LITERASI DI SEKOLAH BERDASARKAN DESAIN INDUK GERAKAN LITERASI SEKOLAH (STUDI KASUS DI SMA NEGERI 2 BLITAR)

The School Literacy Movement is a person's ability to access, understand, and use information and media intelligently. This movement is an effort to make schools educational institutions so that students are literate. The regulation of the main design of this movement is in Design of the School Literacy Movement. This study aims to determine the suitability of implementing the school literacy movement program based on the guidelines in the Master Design of the School Literacy Movement. This research is a mixed method research with quantitative and qualitative approaches. The data-collecting methods are interviews, observation, and documentation at SMA Negeri 2 Blitar. To analyze the data used, Milles and Huberman's theory through 3 steps; data reduction, data presentation, and conclusion. The validity test in this research uses triangulation and member checks. The decision of the study is the implementation of the School Literacy Action program in SMA Negeri 2 Blitar generally was appropriate with the Main Design of School Literacy Action. SMA Negeri 2 Blitar has implemented most of the program of school literacy criteria in the physical environment, socio-affective environment, academic environment, and stage of development. The achievement of implementing the School Literacy Action program in SMA Negeri 2 Blitar was 90,63 %. The researcher suggests that it needs to provide books and reading materials for the student's parents or visitors in the school environment, except classrooms, such as corridors and the head's office, and determine some required books to be read by the school members. Moreover, schools should give special attention to the XII grade students in the second semester and emphasize literacy learning against the awareness of each individual.
CBDC-MXN: Challenges and Perspectives in The Implementation as a Mexican Digital Currency

This research shows a proposal for developing of a Mexican Central Bank Digital Currency by Banco de México. Therefore, a dynamic SWOT matrix is used to present the strengths, weaknesses, opportunities, and threats of the development of the Mexican Central Bank Digital Currency. In addition, an analysis of the stablecoins of the Mexican peso is made to know their landscape and current use, the above making use of Blockchain explorers such as BscScan, Etherscan, Polygonscan, and Tronscan. MMXN, Moneta Digital, is the stablecoin of the Mexican Peso with the most significant number of users and transactions. According to the results obtained, it is shown that the Mexican CBDC is viable, but it must overcome challenges and issues to be implemented and used by the population.
Design and implementation of service registration and configuration center supporting heterogeneous systems

With the rapid development of computer communication technology, open source service framework system, represented by Dubbo and Spring Cloud in the Internet field, and internal private service framework system are applied to different business scenarios. How to share service registration and configuration information among multiple service frameworks in a simple, efficient and stable way has become an urgent problem to be solved. This paper proposes a service registration and configuration center supporting heterogeneous systems, which is responsible for providing unified service registration and configuration management, and supports clients between heterogeneous systems to obtain the latest service registration and configuration information in real time. Supports the service registration and configuration center of heterogeneous systems to store and take effect in real time service registration and configuration information between heterogeneous systems through the regularization processing and change information push functions. The experiment shows that the heterogeneous system service registration and configuration center can meet the needs of unified management of service registration and configuration between different business systems in the new generation control system, and ensure the reliable acquisition of service registration and configuration information under different architectures.
A novel framework to enhance the performance of training distributed deep neural networks

There are many attempts to implement deep neural network (DNN) distributed training frameworks. In these attempts, Apache Spark was used to develop the frameworks. Each framework has its advantages and disadvantages and needs further improvements. In the process of using Apache Spark to implement distributed training systems, we ran into some obstacles that significantly affect the performance of the systems and programming thinking. This is the reason why we developed our own distributed training framework, called Distributed Deep Learning Framework (DDLF), which is completely independent of Apache Spark. Our proposed framework can overcome the obstacles and is highly scalable. DDLF helps to develop applications that train DNN in a distributed environment (referred to as distributed training) in a simple, natural, and flexible way. In this paper, we will analyze the obstacles when implementing a distributed training system on Apache Spark and present solutions to overcome them in DDLF. We also present the features of DDLF and how to implement a distributed DNN training application on this framework. In addition, we conduct experiments by training a Convolutional Neural Network (CNN) model with datasets MNIST and CIFAR-10 in Apache Spark cluster and DDLF cluster to demonstrate the flexibility and effectiveness of DDLF.
Accelerated Verifiable Fair Digital Exchange

A Fair Digital Exchange is defined as either all or none of the participants achieving a (predetermined) desirable outcome. This work addresses third party mediated systems for digital content where mutually unknown, and hence non-trusting, buyers, sellers and the mediator (third party) take part in an exchange protocol. We address the lack of guaranteed fairness, as defined above, in the existing platforms for this setting. We present TEDX, a decentralized solution for guaranteed three party fair exchange of digital goods with scalability and support for incremental deployment over the existing (non-fair) platforms. TEDX combines carefully crafted message exchanges with incentive schemes designed to deter malicious behavior. TEDX also leverages ideas from blockchain anchored state-channels to provide trusted execution while minimizing the operational overheads of blockchain. We present the design and a security analysis of TEDX to validate the claimed fairness properties. We also present the details of a prototype implementation of TEDX leveraging Hyperledger Fabric and performance evaluation of the same on a realistic testbed spanning five public cloud zones. Our results indicate that TEDX adds only a minimal overhead of 16% while being 46x faster than a naive blockchain solution, thereby demonstrating that TEDX is scalable.
iLearning Education 2.0 Based MooC Platform as Collaborative Learning Smart Technology

Media Education iLearning Education 2.0 (iDu 2.0) supports web-based adaptive collaborative learning that can be used to support online or distance learning activities. This paper aim how the emergence of innovation can change the educational process by utilizing the Learning Management System (LMS). Students can be motivated to work on assignments flexibly without being limited by space and time. The goal is to optimize the way and time of learning to improve academic achievement. Therefore, to produce highly effective learning innovations through iDu 2.0, an open source based Learning Management System (LMS) technology has now been utilized. Using Agile development methods allows software development in a short time. iDu 2.0 can be a solution to the innovation needed to support distance learning more effectively and efficiently. Based on these findings, iDu 2.0 is expected to be a breakthrough in technological innovation in this 4.0 era to increase the quantity and quality of distance learning for students in universities.
An Evaluation Method of Load Adjustable Potential Based on Two-Dimensional Chain Cloud Model Optimization

With the rise of social electricity consumption and the continuous development of renewable energy, renewable energy has become one of the important resources for the operation of the power system, and it has also brought great pressure to the operation of the power grid. How to evaluate the power consumption of consumers on the power demand side and improve the operation stability of the power grid is an urgent problem to be solved. In this paper, a method of load adjustability potential evaluation based on two-dimensional chain cloud model optimization is proposed, which provides an important reference for power load regulation. Based on the two-dimensional chain cloud model, this method introduces the baseline load and uses the historical data to forecast the load, and then uses Dynamic Time Warping (DTW) to optimize the forecast data to obtain the load adjustability that is most similar to the historical situation. The feasibility and effectiveness of the evaluation method are verified by a specific example.
KARAKTERISTIK RESPON SISWA SEKOLAH DASAR DENGAN MODEL PEMBELAJARAN BERBASIS MASALAH BERDASARKAN TAKSONOMI SOLO

This research was purposed for knowing Students Respon Characteristic in Problem Based Learning Model based on SOLO Taxonomy. We know that, taxonomy was able to help teacher and students on the learning process. It was used for facilitating mental process, and reach out the aims of learning process. This research is qualitative, which has three steps of analyses. The first step is data reduction, the second is data presentation, the last is data verification. This researchment proves that elementary school students’ cognitive are in multistruktural level. It is proved by ten of twelve students’ answer that stop on the third question, eventhough, two of them are in higher level. SOLO taxonomy is easy to do in learning process, it can help teachers to know students cognitive level, so that they are able to choice the best strategy that fit in to learning process.
Securing Information Management in Collaborative Environments Using Machine Learning

Recently, there has been a significant increase in the use of collaborative environments for managing and sharing information. However, these environments often present significant security risks due to the potential for unauthorized access, data leakage, and other security breaches. To address these risks, machine learning (ML) techniques have been increasingly used to secure information management in collaborative environments. We propose a novel ML approach to be applied to detect and prevent security threats in collaborative environments. Our approach integrates temporal convolution to detect and prevent security threats by analyzing spatial-temporal patterns in data from various sources, such as network traffic, system logs, and user behavior. Furthermore, we present a case study demonstrating the effectiveness of our model in securing collaborative information management. The case study involves the development of our system for detecting insider threats in a collaborative environment. Extensive experimentation on this case study demonstrates the efficiency and effectiveness of the proposed system for securing information management and promoting further developments.
A data transmission security model based on anti-sniffing and intrusion detection

In this paper, we propose a data transmission security model based on anti-sniffing and intrusion detection for the traditional TCP/IP protocol cluster and SSL protocol which are easily affected by data interference and cannot guarantee data transmission security. According to the network anti-sniffing technology approach, we adopt the constant updating of the illegal intrusion ratio weights during data network transmission to solve the problem of long detection time of illegal intrusion due to too many parameters of weights in initialization. A data transmission security model is constructed by improving the mode of data transmission through encrypted tunnels so as to protect the data transmission security. The data to be received is kept within the secure cache queue by encrypting the initial key. Then the received data is decrypt to finalize the secure network data transmission. From the experimental results, it can be seen that the model has a maximum transmission error of only 20 bit in the case of random data, which has the effect of secure transmission.
World of Information: Psychoanalysis and More

This is the most extensive chapter for a good reason. The area to be described in methods and terms of information technology is divided into the neurosymbolic part and that of the psyche. There are three underlying methods of description: information technology, psychoanalysis, and neurosymbolism. All three are covered so that the reader can gain insight into what the essential aspects and emphases are in each case. The three descriptive methods are among the cornerstones for understanding the three-layer model of the Ψ-organ.