Reviewerly/exHarmony huggingface dataset:
Penerapan Algoritma C4.5 Dalam Memprediksi Ketersediaan Uang Pada Mesin ATM

This study aims to provide an evaluation of the availability of money in ATM machines using data mining. Data mining with the C4.5 algorithm is used to predict cash demand or total cash withdrawals at ATMs. To determine the need for ATM cash based on cash transaction data. It is hoped that this forecasting can help the monitoring department in making decisions about the money requirements that must be allocated to each ATM machine. The results of this study are expected to assist the ATM management unit in optimizing and monitoring the availability of money at an ATM machine for cash needs, so that it can provide optimal service to customers. Algortima C4.5 is an algorithm that is able to form a decision tree, where the decision tree will then generate new knowledge. The results of the test matched the data on the availability of money at the ATM machine. The results of implementing the C4.5 method on the availability of money at the ATM machine are seen from the travel time to the ATM location and also the remaining balance in the machine. The resulting decision tree model is to make the balance variable as the root, then the travel time as a branch at Level 1 with the variables fast, medium, long, and the bank becomes a branch at the last level (Level 2). Then the C4.5 algorithm was tested using the K-Fold Cross validation method with the value of fold = 10, it can be seen that the accuracy rate is 85%, the Precision value is 80% and the Recall value is 66.67%. While the AUC (Area Under Curve) value is 0.833, this shows that if the AUC value approaches the value 1, the accuracy level is getting better
Fabrication-aware design for furniture with planar pieces

Abstract We propose a computational design tool to enable casual end-users to easily design, fabricate, and assemble flat-pack furniture with guaranteed manufacturability. Using our system, users select parameterized components from a library and constrain their dimensions. Then they abstractly specify connections among components to define the furniture. Once fabrication specifications (e.g., materials) designated, the mechanical implementation of the furniture is automatically handled by leveraging encoded domain expertise. Afterwards, the system outputs three-dimensional models for visualization and mechanical drawings for fabrication. We demonstrate the validity of our approach by designing, fabricating, and assembling a variety of flat-pack (scaled) furniture on demand.
Denoising Terahertz Image Using Non-Linear Filters

This work was supported by the National Natural Science Foundation of China, (Grant No. 11872058), the Sichuan Science and Technology Program of China (No.2019YFG0114) Abstract A major challenge in the processing and analysis of images is the presence of noise especially in terahertz images. Denoising techniques are designed to remove noise or distorted images while maintaining the original image quality. In this paper, terahertz image denoising is proposed using different filtering methods. This work provides an algorithm that denotes the terahertz image with a non- linear and spatial function of mean and medium filter. The THz images were transformed using Gaussian and Salt &amp; Pepper noise at different percentage levels from 5% to 50%. Universal Image Quantitative Analysis was utilized specifically the most renowned PSNR, MSE, MAE and IEF were explored in this work. Experimental results show that the mean-median filter outperforms Salt and Pepper in removing the Gaussian noise especially when noise factor is increasing. Keywords: Mean- median filter, terahertz image, Gaussian noise, Salt &amp; pepper noise DOI: 10.7176/CEIS/12-2-02 Publication date: April 30 th 2021
Comparing Virtual Environments for Cybersickness Using a Cumulative Optical Flow Entropy Metric

Cybersickness, or feelings of nausea, discomfort or unease, are common in virtual reality experiences with head-mounted displays.With the widespread availability of virtual reality headsets across a wide domain of uses including industry, defence, education and the commercial market, is it critical that virtual environments are developed that minimise cybersickness.Unfortunately, determining whether a virtual reality experience will induce cybersickness is difficult.Typically this requires user studies with a completed, or almost completed, virtual environment.This is time consuming and expensive, both to run participant-based user studies and for any rework to the virtual environment needed due to identified issues.As part of modern iterative development processes it would be useful to pre-evaluate virtual environments for cybersickness before engaging user studies.This paper presents a new approach and metric to compare virtual environments' susceptibility to induce cybersickness.The approach combines visual optical flow, an entropy metric of complexity and a cumulative time-series measure.Virtual environments with known cybersickness attributes are used to demonstrate the approach.Results indicate that the approach can successfully differentiate between known levels of cybersickness and attributes contributing to cybersickness, such as motion direction and field of view.
Extended Chaotic Nonlinear Programming Technique Constructing with Genetic Algorithms

Chaos theory has attracted much attention because it fully reflects the complexity of the system, which is an essential property in many applications, especially in the optimization problem.In this paper, the possibility of improving research by means of evolutionary algorithms (genetic algorithms) will be discussed which used to solve non-linear programming problems.This improvement and development are carried out using a highly quality chaotic map, which was proposed to be used for generating real values (keys) that are used as reference values for the genetic algorithm.A comparison between the results without using chaotic systems and the results after generating the keys is performed.It shows that the results after the chaotic local search (CLS) are improved and congregate with the optimum value of the solutions obtained by the projected process before the CLS.Moreover, the differences between the proposed systems for improvement are also compared.The evaluation parameters for the proposed chaotic function are developed using the Mathematica 11.2 program.
Correction to: Content valuation strategies for digital subscription platforms

A correction to this paper has been published: https://doi.org/10.1007/s10824-021-09408-5
Using Simulation to Understand and Respond to Real World and Cyber Crises

Crisis situations require decisions to be made rapidly and under higher pressure than under normal circumstances. In many cases, not all of the information required to make an optimal decision will be readily available, meaning decisions will need to be made with limited information or as information is being collected. This chapter considers how simulation can be used to prepare for and respond to crisis situations, both in the real world and in the cyber realm. To this end, prior uses of simulations are reviewed. Then a paradigm for the use of simulation to prepare for and respond to real-world and cyber crises is proposed and evaluated using four case studies. From this, general conclusions are drawn, and areas for additional study are identified.
AplikasiI Klonosewandono Sebagai Bahan Ajar BIPA Pada Ketrampilan Membaca Tingkat Dasar

This study discusses the application of a BIPA teaching, especially in reading skills through an application. The purpose of this study is to explain the teaching materials presented in the Klonosewandono application at basic level BIPA teaching. The research method used is descriptive qualitative. The reference source used here is in the form of the BIPA AI handbook "Sahabatku Indonesia" published by the Language Agency of the Ministry of Education and Culture. The technique for checking the validity of the data in this study uses method triangulation techniques by checking the understanding of lecturers and students on the use of this application. This is that BIPA teaching materials, especially reading skills presented in the Klonosewandono application, are quite helpful in providing a breakthrough in teaching online or remotely. This application of course also still has a weakness, namely that there are no different types of text presented. Hopefully this application can be used as a source of inspiration for further research that is more complete and innovative.
Library-Based Overview of Multicriteria Decision Making for Continuous Software Improvement for Internet of Software Industry

The revolution in software development is increasing with the use of advanced techniques and tools. Software development organizations are considering standards, methods, approaches, and tools to support them in maintaining the effectiveness of software. An effective implementation of software process improvement (SPI) is important in order to gain effectiveness in the software industry. Disasters are happening in software projects and industry of software, which hinder the success of software and ultimately lead the software to failure. Peoples of organizations are demanding to devise methodological approaches for reducing the failure rate of software, but it perceived slight success. The proposed study’s aim is to offer multicriteria decision making for continuous Internet of software industry and to report the literature to early decision making associated to software developments. The study has devised a comprehensive overview of the existing methodological approaches, tools, and mechanisms applied in software improvement for the software industry and is based on multicriteria decision making. The research has analyzed the available literature from different perspectives and then reported it. The results of the study will help researchers to devise new solutions for effective software process improvement, and the this study will consider as a support of evidence.
The identification of power IoT devices on differential constellation trajectory map

As a long-distance wireless transmission technology based on spread spectrum, LoRa is a hot research object in the field of power Internet of Things. To solve the problem of terminal authentication, this paper proposes a LoRa device identification method based on a differential constellation trajectory map, which skillfully transforms the radiofrequency fingerprint feature matching problem into the image processing problem. This method first obtains the constellation locus of the received signal. It performs differential processing and then USES the clustering algorithm to get the constellation locus's clustering center. It then calculates the Euclidean distance between the clustering centers of two devices to obtain the similarity between them and USES this as a basis for equipment identification. The experimental results show that the LoRa device recognition method based on differential constellation trajectory map can effectively identify five LoRa transmission modules and have a high recognition accuracy even in low SNR.
TSSN-Net: Two-step Sparse Switchable Normalization for learning correspondences with heavy outliers

In this paper, we solve the problem of feature matching by designing an end-to-end network (called TSSN-Net). Given putative correspondences of feature points in two views, existing deep learning based methods formulate the feature matching problem as a binary classification problem. In these methods, a normalizer plays an important role in the networks. However, they adopt the same normalizer in all normalization layers of the entire networks, which will result in suboptimal performance. To address this problem, we propose a Two-step Sparse Switchable Normalization Block, which involves the advantage of adaptive normalization for different convolution layers from Sparse Switchable Normalization and robust global context information from Context Normalization. Moreover, to capture local information of correspondences, we propose a Multi-Scale Correspondence Grouping algorithm, by defining a multi-scale neighborhood representation, to search for consistent neighbors of each correspondence. Finally, with a series of convolution layers, the end-to-end TSSN-Net is proposed to learn correspondences with heavy outliers for feature matching. Our experimental results have shown that our network achieves the state-of-the-art performance on benchmark datasets.
Some problems of using MOODLE platform when teaching ESL to university students of non-linguistic departments majoring in Education science

This article examines the problems of distance education in teaching students of non-linguistic departments a foreign language. In the realities of our time, this topic is very relevant, because there was no experience of widespread use of online learning before. The article analyzes the views of some researchers on the problem of distance learning. It also provides characteristics of MOOKS (mass open online courses) and the MOODLE in terms of such parameters as the dynamics of attendance and the number of students who completed the course to the end. It should be noted that the performance of tasks in the MOODLE system at the Herzen State Pedagogical University has been used as a prerequisite for obtaining certification since the spring of 2020. Thus, the main content of the study is the analysis of factors that affect the effectiveness of online academic training in this system. The authors were interested in indicators of academic performance and students ‘ attendance at online classes. The article analyzes the psychological and psychological-pedagogical impact on the effectiveness of the educational process in the framework of the MOODLE system. Special attention was paid to the conditions for students to enroll in a distance learning course (whether the student signed up or was enrolled in their course by the teacher), the availability of deadlines for completing tasks by students, and the form of final certification. Of the three factors considered by the authors for the effectiveness of an online course, the most significant is the presence of a deadline for completing work, which affects the external motivation of students and thereby increases the discipline of students in passing work. It should also be noted that groups of students who actively used video chats have higher academic performance. Based on the research, the authors give recommendations for improving the effectiveness of students’ work in the distance format.
An Efficient Two-layer based Technique for Content-based Image Retrieval

The rapid advancement and exponential evolution in the multimedia applications raised the attentional research on content-based image retrieval (CBIR). The technique has a significant role for searching and finding similar images to the query image through extracting the visual features. In this paper, an approach of two layers of search has been developed which is known as two-layer based CBIR. The first layer is concerned with comparing the query image to all images in the dataset depending on extracting the local feature using bag of features (BoF) mechanism which leads to retrieve certain most similar images to the query image. In other words, first step aims to eliminate the most dissimilar images to the query image to reduce the range of search in the dataset of images. In the second layer, the query image is compared to the images obtained in the first layer based on extracting the (texture and color)-based features. The Discrete Wavelet Transform (DWT) and Local Binary Pattern (LBP) were used as texture features. However, for the color features, three different color spaces were used, namely RGB, HSV, and YCbCr. The color spaces are utilized by calculating the mean and entropy for each channel separately. Corel-1K was used for evaluating the proposed approach. The experimental results prove the superior performance of the proposed concept of two-layer over the current state-of-the-art techniques in terms of precision rate in which achieved 82.15% and 77.27% for the top-10 and top-20, respectively.
Students’ Perception of Teachers’ Creativity in Implementing Home Learning at SMK Duta Mas

&lt;p&gt;The Indonesian government formally enforces rules of study, worship, and work from home from March 16th, 2020. Minimizing and limiting meetings involving physical contact are efforts to reduce the spread of the COVID-19 virus. These conditions have implications for the effectiveness of the learning process in schools. The implementation of a home learning program replacing face to face-to-face schooling raised some problems from the lack of teachers’ skills to hazy educational policies. Because of that reason this study is conducted to find out students’ perception of teachers’ creativity in implementing home learning programs during the pandemic. There were 60 participants chosen by simple random sampling from grade 11th, the academic year 2019-2020, SMK Duta Mas. A questionnaire with a Likert scale was used to collect data. Then data analysis employed qualitative descriptive research to analyse indicators of teachers’ creativity proposed by Slameto. The findings of this study reveal that from 6 indicators of teachers’ creativity, 5 of them have a high percentage and the average total percentage is 79.26%. Therefore, it can be concluded that students’ perception of teachers’ creativity in SMK Duta Mas in implementing home learning during the pandemic is considered high. However, teachers need to improve their ability in creating media for learning because it is very important to improve students’ learning achievement and to motivate them to learn.&lt;/p&gt;
Transformation Of Education In The Context Of Digitalization

Over the past five years, the newest and most discussed political trend has been the integration of digitalization into all spheres of human life, including science and education.Digital education creates new learning opportunities.The modern approach to studying the stages of formation of digitalization of education in the Russian Federation regulates relations related to the creation and development of conditions for the implementation of educational programs using e-learning, distance learning technologies, taking into account the functioning of the electronic information and educational environment.In the course of research and analysis of this topic, the authors clearly identified the advantages and disadvantages of this transformation.Digitalization of the educational process implies transformation and integration of educational technologies into all stages of the educational process: training, education, methodological integration, career guidance.There are opportunities for personalized learning, new models of cooperation are emerging, the form of organizing distance learning contributes to the development of independent work skills, and the range of innovative and attractive learning strategies for students is becoming wider.However, despite the fact that the digitalization of the educational process has become quite strong at this stage of development, it needs to be refined, changed, include new and additional elements and functions, and it is also worth paying attention to the revision of the regulatory framework of modern legislation.
Implementation of Blockchain-based technique to a Hostel Room Booking System: Practical Aspects

The hospitality industry is an emerging employment generator in any Economy. Hostel management is an important part of hospitality in towns, villages and tier3 cities in India. With the broadband penetration in remote places and mobile Hostel room booking in real-time is possible today. Blockchain being web3.0 is a promising technology that has made many real-time applications in this decade. Hostel room booking fairly and transparently manner is important for many organizations and institutions. A blockchain-based booking system would provide such a solution. This paper explores the potentials and proposes one basic contract for the booking system.
Evaluation of Backpropagation Neural Network Models for Early Prediction of Studentâ€™s Graduation in XYZ University

The study period of the student in a tertiary institution is undoubtedly essential in implementing the objectives of the tertiary institution, particularly for the implementation of the study program, so that its outcomes will affect accreditation. Prediction of students' study period can be a reference for higher education institutions in making policies for the future. Based on XYZ University data, especially in the informatics study program, many students have the different generation and concentration therein. In the implementation of students in studying, several factors, including the value of the Grade Point Average (GPA), can affect the study period taken. Likewise, the institutions often do not understand the conditions or predictive value of students' study period on campus. The application of neural networks in predicting the students’ study period at the XYZ University uses a network model with GPA values as input and 1 layer of hidden layers with 10, 50 and 100 neurons; learning rate values used are 0.01, 0.1 and 0.3 and 1 output target for the study period. Prediction results obtained the best results on the neuron network pattern 50 with 0.01 as a learning rate, which detail of MSE value, the training is 0,017516 and the testing is 0,047721, with an accuracy value of 77%.
Level of Individual Performance in the Context of Referencing Competency

Referencing competency is the knowledge, skills, and ability to use, edit, and disseminate different types of referencing standards and referencing software.Referencing competency helps to improve the quality of publication through proper citation and references.However, there is a scarcity of knowledge on the level of impact of referencing competency towards individual performance especially among undergraduate students.Therefore, the purpose of this study is to determine the level of individual performance in the context of referencing competency.A quantitative research instrument was developed, pretested, sent for pilot study before been analysed based on descriptive analysis using Statistical Package for Social Sciences (SPSS) version 26.The result shows that the respondents have a moderate level of task productivity and task satisfaction.
THE STUDENTS’ DIFFICULTIES IN LEARNING ENGLISH AT MADRASAH IBTIDAIYAH TEACHER EDUCATION STUDY PROGRAM

English is one of compulsory subjects that must be learned by students of elementary school to collage level. In fact, some students have difficulty in learning English. This study aims to describe the factors affect students’ difficulties in learning English. The subjects of the study were 30 students of the Madrasah Ibtidaiyah Teacher Education Study Program at Universitas Islam Negeri Sumatera Utara. This study applied a qualitative descriptive research with a questionnaire and observation instruments. The data analysis of this study used interview, observation, documentation and triangulation. The researchers found that there are two difficulties factors in learning English particularly internal factors and external factors, including 1) students’ low motivation; 2) lack of understanding of the importance in learning English (3) lack of opportunities to learn English (4) Lack of environment supports such as parents, friends, etc.Keywords: Learning difficulties, factors of difficulties in learning English