Reviewerly/exHarmony huggingface dataset:
RETRACTED: PENGARUH METODE PEMBELAJARAN DISCOVERY MENGGUNAKAN E-LEARNING TERHADAP KEMAMPUAN LITERASI MATEMATIS SISWA

Following a rigorous, carefully concerns and considered review of the article published in Jurnal Edukasi dan Sains Matematika (JES-MAT) to article entitled “PENGARUH METODE PEMBELAJARAN DISCOVERY MENGGUNAKAN E-LEARNING TERHADAP KEMAMPUAN LITERASI MATEMATIS SISWA” Vol 8, No 1, pp. 95-106, March 2022, DOI: https://doi.org/10.25134/jes-mat.v8i1.5594This paper has been found to be in violation of the Jurnal Edukasi dan Sains Matematika (JES-MAT) Publication principles and has been retracted.The article contained redundant material, the editor investigated and found that the paper published in JNPM (Jurnal Nasional Pendidikan Matematika), Vol. 6, No. 1, pp. 145-157, 2022, DOI : 10.33603/jnpm.v6i1.6264, URL: https://jurnal.ugj.ac.id/index.php/JNPM/article/view/6264 entitled "PENGARUH METODE PEMBELAJARAN DISCOVERY MENGGUNAKAN E-LEARNING TERHADAP KEMAMPUAN LITERASI MATEMATIS MTS ".The document and its content has been removed from Jurnal Edukasi dan Sains Matematika (JES-MAT), and reasonable effort should be made to remove all references to this article.
Incorporating Task-Agnostic Information in Task-Based Active Learning Using a Variational Autoencoder

It is often much easier and less expensive to collect data than to label it.Active learning (AL) ([Set09]) responds to this issue by selecting which unlabeled data are best to label next.Standard approaches utilize task-aware AL, which identifies informative samples based on a trained supervised model.Task-agnostic AL ignores the task model and instead makes selections based on learned properties of the dataset.We seek to combine these approaches and measure the contribution of incorporating task-agnostic information into standard AL, with the suspicion that the extra information in the task-agnostic features may improve the selection process.We test this on various AL methods using a ResNet classifier with and without added unsupervised information from a variational autoencoder (VAE).Although the results do not show a significant improvement, we investigate the effects on the acquisition function and suggest potential approaches for extending the work.
popmon: Analysis Package for Dataset Shift Detection

popmon is an open-source Python package to check the stability of a tabular dataset.popmon creates histograms of features binned in time-slices, and compares the stability of its profiles and distributions using statistical tests, both over time and with respect to a reference dataset.It works with numerical, ordinal and categorical features, on both pandas and Spark dataframes, and the histograms can be higher-dimensional, e.g. it can also track correlations between sets of features.popmon can automatically detect and alert on changes observed over time, such as trends, shifts, peaks, outliers, anomalies, changing correlations, etc., using monitoring business rules that are either static or dynamic.popmon results are presented in a self-contained report.
PENGEMBANGAN PERANGKAT PEMBELAJARAN MATERI PROGRAM LINEAR BERBASIS MODEL PROBLEM BASED LEARNING BERBANTUAN GEOGEBRA ANDROID

This study aims to develop mathematics learning tools for linear programming materials based on problem based learning assisted by GeoGebra Android to increase the mathematical problem solving skills of students and to find out the validity of learning tools. Developed learning tools consist of modules, worksheets, and evaluation tools. This development research refers to the Plomp development model consisting of 3 phases, preliminary phase, prototyping phase, and assessment phase. The subjects of the study consisted of 3 validators. The instruments of the study consisted of validation sheets and learning tools in the form of modules, worksheets, and evaluation tools. The data collection technique used was expert validation sheets. The developed learning media were validated by 3 validators consisting of 2 lecturers and 1 teacher. The data analysis technique used was by searching the average of each aspect in the validation sheet so that the average total validator assessment was obtained for each learning tools. Based on the results of learning tools validation, it was obtained the average score of module validation of 4.04 (valid), worksheet validation of 4.18 (valid), and evaluation tool validation of 4.17 (valid). Based on the validator assessment, the results of the study were obtained that developed learning tools are stated valid.
Security-Enhanced Certificate-Based Remote Data Integrity Batch Auditing for Cloud-IoT

The Internet of Things (IoT) plays a crucial role in the generation of new, intelligent information technologies. Generally, the IoT facilities are composed of lightweight devices, and they expand computing and storage resources primarily through the cloud. Massive data collected by intelligent devices will be stored in cloud servers, but the vulnerabilities of cloud servers will directly threaten the security and reliability of the IoT. To ensure the integrity of data in the cloud, data owners need to audit the integrity of their outsourced data. Recently, several remote data integrity batch auditing protocols have been proposed to reduce transmission loss and time cost in the auditing process. However, most of them cannot resist collusion attacks. Meanwhile, certificate management problem exists in their system, which brings an enormous burden on the system. In this paper, we construct a certificate-based remote data integrity batch auditing protocol which can issue batch auditing and resist the highest level of collusion attacks—the fully chosen-key attacks for cloud-IoT . Our protocol makes use of a certificate-based cryptosystem which gets rid of the certificate management problem and key escrow problem, with no need for secret channels. Our protocol is proved to be secure in the random oracle model and implemented to show its efficiency. The simulation results illustrate that, in the case of enhanced security, our batch auditing protocol still has computational efficiency and practicability.
Investigating the differential item functioning of a PIRLS Literacy 2016 text across three languages

This study forms part of a larger study (Roux, 2020), which looked at the equivalence of a literary text across English, Afrikaans, and isiZulu from the Progress in International Reading Literacy Study (PIRLS). PIRLS is a large-scale reading comprehension assessment that assesses Grade 4 students' reading literacy achievement. PIRLS Literacy 2016 results for South African Grade 4 students indicated poor performance in reading comprehension, with approximately eight out of 10 Grade 4 students who could not read for meaning. Descriptive statistics led to the Rasch analysis, which was conducted using the South African PIRLS Literacy 2016 data. Even though the Rasch analysis indicated differential item functioning across the three languages for this specific passage, there was no universal discrimination against one particular language. By conducting differential item functioning, it was possible to determine whether the selected text had metric equivalence, in other words, whether the test questions were of similar difficulty across languages.
Image encryption algorithm based on rear-mountedphase mask and random decomposition

To escalate the image encryption a new method has been devised which includes double random phase encoding (DRPE) using rear phase masking and random decomposition (RD) technique stranded on fractional Fourier transform. Here, asymmetric cryptographic system is developed in fractional Fourier transform (FrFT) mode using two random phase masks (RPM) and a rear mounted phase mask. In the projected scheme a colored image is decomposed into R, G and B channels. The amplitude of each channel is normalized, phase encoded and modulated using RPM. The modulated R, G and B channels of the colored image are individually transformed using FrFT to produce corresponding encrypted image. The proposed scheme is authorized on grayscale image also. The norm behind the development of the suggested scheme has been elaborated by carrying out cryptanalysis on system based on the RD. The method helps in escalations of the protection of double random phase encoding by cumulating the key length and the parameter amount, so that it vigorously can be used against various attacks. The forte of the suggested cryptographic system was verified using simulations with MATLAB 7.9.0 (R2008a). The efficiency of the suggested scheme includes the analysis using singular value decomposition (SVD), histogram and correlation coefficient.
Kesiapan perpustakaan perguruan tinggi dalam mendukung proses pembelajaran secara daring

Introduction. Since the outbreak of the COVID-19 pandemic, the government has stopped all face-to-face learning activities and replaced it with an online distance learning process. With this change in the learning system, there needs to be readiness from various parties such as students, educators, availability of communication tools, internet network support and support for learning facilities by implementing digital-based services.Data Collection Methods. This paper tries to explore the readiness of university libraries in supporting the distance learning process in a study at the Kandaga central library, Padjadjaran University. This research uses a qualitative approach with case study research. Data collection techniques were carried out through observation, interviews and literature study. The subject of the research is the librarian of the Kandaga UNPAD central library and the object of the research is library service activities.Data Analysis. For the data analysis technique, the data reduction stage, data presentation and conclusion-making stages are carried out..Results and Discussion. Based on the results of the study, it is known that the outbreak of the COVID-19 pandemic has changed learning activities that were previously carried out face-to-face into an online learning process. Then related to the readiness of libraries to support distance learning in this study, it is seen from the aspect of human resources, namely librarians, aspects of collections and supporting facilitiesConclusion. For the aspect of human resources in supporting the distance learning process, the Kandaga central library, Unpad has prepared librarians based on the grouping of faculties in UNPAD, for library collections it has provided various digital collections in the form of e-books, e-journals and various other digital collections, Meanwhile, for service facilities, apart from providing the Unpad website, it also provides social media-based services such as WhatsApp, Instagram and several other social media.Keywords: pandemic covid-19; readiness, library services, digital collections; college library; distance education.
Development of a virtual platform for the metaheuristic optimization of heat exchangers

Independently of the implemented heat exchange technology for industrial applications, it is necessary to apply an optimization routine to obtain the best heat exchanger design according to an objective function. This work presents a design and optimization environment for heat exchangers where the total annual cost is used as an objective function. Eight metaheuristic algorithms are employed to carry out the optimization procedure independently: Cuckoo Search, Differential Evolution, Grey Wolf Optimizer, Jaya Algorithm, Particle Swarm Optimization, Univariate Marginal Optimization Algorithm, and Whale Optimization Algorithm. Three different types of heat exchangers are contemplated: shell-and-tube heat exchanger, plate fin heat exchanger and plate heat exchanger. The performance of each optimization algorithm is assessed for each kind of exchanger.
Classification of Graduate Profiles Based on Graduate Tracer Study Using Algorithm Naive Bayes Classifier

The graduate profile is the role of the graduate of the study program or field of expertise / field of work planned after completing education from the study program. The determination of the profile of study program graduates is generally carried out based on the results of the assessment of stakeholder needs. Based on data from the Ministry of Research, Technology and Higher Education, the IT study program is one of the most majors or study programs in Indonesian universities and the highest number of enthusiasts choose this study program each year. Each year, graduates of IT study programs have a large number of graduates, both vocational and non- vocational colleges. The number of IT graduates is large but they have low graduate competencies, even they do not have competencies in the IT field so that their work is not in accordance with the graduate profile that has been designed. Therefore, it is necessary to conduct research to classify the profile of graduates who have worked based on tracer study data using the Naïve Bayes Classifier method. This study uses attributes, namely study program, value criteria, gender and field of work and the labels used are status (Linear and Non-Linear). The results of the study on the classification of the profile of graduates using the Naïve Bayes Classfier method show that alumni work not according to the profile of graduates by 73% and according to the profile of graduates by 23%, with a data accuracy rate of 87% and are included in the good classification category.
Orchestrating Production Processes with Cloud Native Pipelines

This paper gives the reader a behind the scenes look at how cloud native automation pipelines play a significant role in the production of Live Action, Visual Effects, and Animated content at Netflix Studios. Netflix's Studio Orchestrator is used to connect creators around the globe by efficiently sharing, tracking, and transforming production data on a scalable architecture that can be customized to meet the needs of production. We will uncover how our approach provides a way for geographically distributed creative teams to share and collaborate on assets as well as save our developer's time by leveraging shared infrastructure and shared components to build automation pipelines. We will use specific examples of automation pipelines that are in production today across Live Action, Visual Effects, and Animation to highlight the benefits of our approach to solving common industry workflows.
Adaptive speech compression based on AMBTC

Most of the AMBTC-based RDH (absolute instantaneous block truncation) schemes Cannot be decrypted because AMBTC, which is unknown to most device.Also, some of the RDH methods based on AMBTC.But the load capacity obtained is low.For this purpose, in this work, a scalable RDH scheme based on AMBTC was introduced from the AMBTC zip code.In contrast to the decoder-based AMBTC-based RDH methods that are only able to achieve a constant payload for adjust the audio.Due to its advantages, sound pressure has attracted a great deal of attention in the last 20 years.The main developments concern transmission requirements and storage capacity.The need for high-quality audio data has been increased due to sudden improvements in computer manufacturers and technologies.Therefore, the developments include speech compression technologies, in which the two compression classes are lossless.This paper aims to review techniques for specification compression methods using AMBTC (a momentary absolute block truncation notation based ) method, and to summarize their importance and uses.
Efficient failure detection and consensus at extreme-scale systems

&lt;span&gt;Distributed systems and extreme-scale systems are ubiquitous in recent years and have seen throughout academia organizations, business, home, and government sectors. Peer-to-peer (P2P) technology is a typical distributed system model that is gaining popularity for delivering computing resources and services. Distributed systems try to increase its availability in the event of frequent component failures and functioning the system in such scenario is notoriously difficult. In order to identify component failures in the system and achieve global agreement (consensus) among failed components, this paper implemented an efficient failure detection and consensus algorithm based on fail-stop type process failures. The proposed algorithm is fault-tolerant to process failures occurring before and during the execution of the algorithm. The proposed algorithm works with the epidemic gossip protocol, which is a randomly generated paradigm of computation and communication that is both fault-tolerant and scalable. A simulation of an extreme-scale information dissemination process shows that global agreement can be achieved. A P2P simulator, PeerSim, is used in the paper to implement and test the proposed algorithm. The proposed algorithm results exhibited high scalability and at the same time detected all the process failures. The status of all the processes is maintained in a Boolean matrix.&lt;/span&gt;
A new three-term conjugate gradient method with application to regression analysis

Conjugate gradient (CG) method is well-known for its ability to solve unconstrained optimization (UO.) problems. This article presenting a new CG method with sufficient descent conditions which improves the former method developed by Rvaie, Mustafa, Ismail and Leong (RMIL). The efficacy of the proposed method has been demonstrated through simulations on the Kijang Emas pricing regression problem. The daily data between January 2021 to May 2021 were obtained from Malaysian Ministry of Health and Bank Negara Malaysia. The dependent variable for this study was the Kijang Emas price, and the independent variables were the coronavirus disease (COVID-19) measures (i.e., new cases, R-naught, death cases, new recovered). Data collected were analyzed on its correlation and coefficient determinant, and the influences of COVID-19 on Kijang Emas price was examined through multiple linear regression model. Findings revealed that the suggested technique outperformed the existing CG algorithms in terms of computing efficiency.
Multiclassification Models Applied to Medical Diagnoses Registered by the Ministry of Public Health in Ecuador

The database of the Ministry of Public Health of Ecuador contains valuable information that can potentially be used to learn about the performance of the application of procedures concerning medical diagnoses. Considering that each element of the database corresponding to a patient is classified according to multiple labels, multilabel classification methods are applied in this research. The calculations are made using MEKA, a software that supports the implementation of this kind of method. The goal of this paper is comparing the different multilabel classification methods to select the most appropriate one(s) in the context of Ecuadorian public health, particularly in diagnosis, and to obtain rules to associate every diagnosis with a corresponding procedure.
Design of a Resident Physical Fitness Data Monitoring System Based on the Sensor and Fuzzy Algorithm

This article first introduces the working principle and research progress of motion sensors and analyzes the advantages and disadvantages of motion tracking sensors to provide a reference for in-depth research on motion sensing technology. By combining the fuzzy judgment method to identify the kinematic parameters, this paper establishes the statistical identification of features to predict the kinematic parameters and uses the fuzzy identification method to model the human behavioral characteristics. At the same time, the article designs a set of real-time data monitoring system for athletes’ real-time monitoring behavior under actual sports conditions, which is used to obtain residents’ sports data. Then, based on such requirements, the overall system architecture was designed to integrate the data acquisition module, data storage and processing module, and real-time data presentation module. The motion monitor can initiate a real-time monitoring request for a specific system group, the server can monitor individual groups to add real-time individual motion status, and the system will issue an alert if the system monitors a potentially dangerous situation.
FEATURES OF PROFESSIONAL AND PEDAGOGICAL TRAINING OF THE FUTURE TEACHER OF TECHNOLOGIES IN THE HIGHER EDUCATION INSTITUTION

The article considers the problems of intensive restructuring of certain parameters of training of future teachers of technology, in particular those that strengthen their professional and pedagogical qualifications, without violating the constructive developments of the past. The need for significant updating of the content, forms, methods, means and methods of teaching is determined, which will improve the quality of pedagogical qualification of graduates and its contradiction with the lack of reasonable and experimentally tested organizational and pedagogical conditions for modernizing professional and pedagogical training of future teachers of technology. It also reveals the professional and pedagogical training of future teachers of technology, which is based on strict consideration of modern educational requirements, such as: qualification characteristics of teachers and working professions in certain fields; requirements for the system of continuing professional education; subject-activity approach to professional training; age and individual opportunities of higher education students in the field of "Technology".
Language Learning Engagement Among Malaysian Undergraduates During MCO 1.0

The Covid-19 pandemic has changed the education practice in Malaysia. Online mode has become the new teaching and learning norm in Malaysia. This study applied the L2 language learning engagement to investigate the language engagement and motivation among the undergraduates in online language learning during the pandemic. The study was conducted in one of the local universities, the University of Malaysia Sabah as the research site. A survey by using questionnaire and interview session were administered to collect data for the study. The research sample of the study comprised of 42 respondents and five interviewees and they were the second-year undergraduates. The research findings of the study showed i) the synchronised online classroom learning is the main platform for the undergraduates to practise their listening skill; ii) all the undergraduates practised their speaking skill in language learning through online mode; iii) the reading material for the undergraduate students to practise their reading skill is related to the language lessons and preparation of course work and iv) the undergraduates write in the language they learnt when preparing for their course work and texting their language lecturers. The study also highlighted the telcos played the most importance role in making the online teaching and learning successful.