Reviewerly/exHarmony huggingface dataset:
Peran Orang Tua Terhadap Kemampuan Literasi Dini Anak Di Desa Banturung Kecamatan Bukit Batu

This research aims to determine the role of parents in children's early literacy skills in Banturung Village, Bukit Batu District. The research method is a quantitative descriptive method. The research was conducted by distributing questionnaires to parents. The research procedures were determining the research subjects, making research instruments, validating instruments in the form of questionnaires, testing questionnaires, giving questionnaires, processing research data, and drawing research conclusions. Researchers present the results of research related to the role of parents in early literacy skills of children aged 5-6 years in Banturung Village, Bukit Batu District. Data obtained from the results of a questionnaire 30 respondents. The questionnaire consists of 24 statement items that include indicators of the role of parents on children's early literacy skills, namely Modelling, Mentoring, Organizing, Teaching with sub indicators namely Print Motivation, Phonological Awareness, Vocabulary, Narrative Skill, Print Awareness and Letter Knowledge. The Modelling shows a percentage of 66.38% which is included in the high criteria. The Mentoring shows a percentage of 76.38% which is included in the high criteria. The Organizing shows a percentage of 71.80% which is included in the high criteria. Teaching shows a percentage of 71.52% is included in the high criteria. Based on the results of the questionnaire research as a whole, it can be concluded that 72.22% stated that the role of parents in early literacy abilities of children aged 5-6 years was included in the high category
APN Fonksiyonlar ile Tanımlanan Bazı İkili Yarı-mükemmel Lineer Kodlar

In 2021, Tutdere proved that the covering radii R of a class of primitive binary cyclic codes with minimum distance strictly greater than an odd integer l satisfy r≤R≤l, where l, r are some integers depending on the given code. We here first discuss some equivalences of linear codes defined by Gold functions, which are quadratic APN (almost perfect nonlinear) functions. We then show that by applying the result of Tutdere one can find the covering radii of these quasi-perfect codes. In 2016, Li and Helleseth proved that the linear codes defined by the quadratic APN functions are quasi-perfect and they asked whether the linear codes defined by the non-quadratic APN functions are quasi-perfect or not. We here prove that the linear codes defined by some non-quadratic APN functions over the finite field〖 F〗_(2^m ) , for 1≤m≤8, are quasi-perfect, by computing the covering radii of these codes.
An approach to achieve message integrity using SHA-256 and Elliptic Curve Cryptography with Salting

In this digital world, securing the integrity of the information plays an important role.For a modernized venture, information integrity is requisite for the veracity & competence of employment processes and decision-making.Integrity verification is the one where the information has not been tampered with while it is stored or communicated.Hash function such as SHA-256 is the strongest function, can be used to achieve information integrity.In this paper, a method is proposed where the images are hashed using SHA-256, scrambled using Elliptic Curve Cryptography (ECC), and then added the salted values to generate the secret image.ECC helps achieve high security with a smaller key size.Salting is applied to the scrambled image to increase the randomness.This makes it difficult for the attacker to identify the secret image and reverse back the hashing as hashing is a one-way function.Simulation outcomes of the proposed method have been analyzed by measuring Peak Signal to Noise Ratio (PSNR), Mean Squared Error (MSE), Structural Similarity Index (SSIM), Number of Pixel Change Rate (NPCR), and Unified Average Changing Intensity (UACI).The proposed method is strong against the differential attacks.
Retraction: Building Logistics Block Chain Platform Based on Cloud Computing (J. Phys.: Conf. Ser. 1486 032022)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 23 September 2022
Retraction: Research on the Fusion of Decoration Design and Modern Elements of the Oroqen Nationality Based on Big Data Analysis (J. Phys.: Conf. Ser. 1574 012027)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 23 September 2022
Retraction: The Practical Dilemma and Method of Personal Information Protection in the Era of Big Data (J. Phys.: Conf. Ser. 1574 012107)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 23 September 2022
Retraction: Role of Digital Image Processing in Image Art under the Background of Big Data (IOP Conf. Ser.: Mater. Sci. Eng. 750 012095)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 23 September 2022
Pembelajaran Multiliterasi: Implementasinya dalam Pelatihan Pengembangan Model Pembelajaran Guru SMA di Malang

There was a limited teacher empowerment program to develop a multiliteracy-based learning model. The urgency of the program is quite substantial because learning barriers during the Covid19 pandemic must be overcome through innovative learning models that stimulate students' multiliteracy skills. This activity aims to empower high school teachers in developing a multiliteracy-based learning model to implement independent learning. This program consists of six meetings, including preparation, incubation, illumination, and verification stages. This activity was conducted online and offline for three months with 15 teachers from SMA Aisyiyah Boarding School Malang. The instruments used are worksheets and interview guides. It was declared successful if 75% of the participants got a minimum of 75 on the worksheet. The results showed that 87% of teachers had exceeded the minimum score. Most teachers have carried out the activities well, starting from the preparation, incubation, illumination, and verification stages. Teachers can find ideas, analyze learning needs, design and display learning models. Multiliteracy learning is implemented through various learning resources and critical literacy stimulation. The teachers' learning model has been applied to online and offline learning practices.
Unimodal and Multimodal Integrated Representation Learning via Improved Information Bottleneck for Multimodal Sentiment Analysis

Representation learning is a significant and challenging task in multimodal sentiment analysis (MSA). It aims to improve the performance of model by learning effective unimodal or multimodal representation. To obtain desired characteristics of representation, various constraints are proposed in previous works. However, these constraints are less concerned with the filtering of task-irrelevant information, which is highly correlated with robustness of representation. In this paper, we design a framework based on information bottleneck to filter noise information. By maximizing mutual information between pairwise unimodal representations and minimizing mutual information between unimodal representation and corresponding input, we can promote unimodal representation for including more task-relevant information and filtering out task-irrelevant information. Furthermore, attention bottleneck is embedded into the unimodal encoding process to realize the interaction between different modalities. Then, to improve the discrimination of multimodal representation, we introduce supervised contrastive learning as a constraint of multimodal representation. Last, we conduct extensive experiments on two public multimodal baseline datasets. The experimental results validate the effectiveness of our model.
Media Informasi Peraga Alat Fitness Berbasis Multimedia

Fitness sports is one of the most popular sports by today's society, even fitness has become a people's lifestyle. But not everyone can make fitness a healthy lifestyle due to limited knowledge and knowledge about the world of fitness itself. This has been anticipated by providers of fitness sports venues. By providing the services of several trainers who help customers in running fitness properly and correctly. However, to be able to use the services of a Personal Trainer provided by the place provider requires a large amount of money. Another obstacle when doing fitness activities is the lack of understanding of good and correct fitness movements so that participants make the wrong movements during exercise so that they are not healthy and the ideal body is obtained but muscle injury due to incorrect fitness training patterns that are applied, this is because some customers do not use the services of a Personal Trainer. The problem of this research is how to design and manufacture a software in the form of multimedia-based information media for fitness equipment, which can provide information about usability, images, animations, and video demonstrations of fitness equipment. The purpose of making this program is as a media demonstration of how to use fitness equipment properly and correctly to help fitness customers use Macromedia Flash. The final result of this research is the application of multimedia-based fitness equipment demonstration media information as a fitness equipment demonstration media that can be used by fitness instructors or customers for fitness activities
Sistem Informasi Pengelolaan Data Inventarisasi Barang Pada Kantor Kecamatan Dusun Utara Kabupaten Barito Selatan

The data collection of inventory items carried out at the North Dusun District Office in South Barito Regency uses the Microsoft Word application in the Microsoft Office application. Data collection in this way takes a lot of time when making reports when needed. With the existence of these problems, the writer will discuss them in this final project research. By taking the title "Goods Inventory Data Processing Information System in North Dusun District, South Barito Regency". With the hope that the application will provide answers to the solution in processing data to obtain the desired information, especially in processing goods inventory in North Dusun District with Microsoft ® Visual Basic .NET2010 Ultimate and MySQL as a database.&#x0D; The methodology used in making this application is a waterfall. The programming language is Microsoft ® Visual Basic .NET 2010 Ultimate. The database uses MySQL. Tools and Editor used are XAMPP for windows. The methods used in data collection such as interviews, observations, documentation of study literature and experiments&#x0D; The system is expected to help the process of managing inventory data of KIB A, KIB B, KIB C and reports. From the results of the questionnaire with the Likert Scale method, the writer can conclude about the user's opinion regarding the application made, that the user is satisfied with the display design and presentation of the information presented. the results of the questionnaire that have been calculated using the Likert scale method, the Likert scale results are 84.2% or 337 point values included in the interval category Setuju (S).
Impulse Noise Reduction using Isolated Vector Median Filtering using K- Means Clustering in Digital Color Images with Application to Medical Diagnosis of SARS-COV-2 Covid19 Disease and Visual Tracking

Abstract This paper proposes a new approach for filtering out impulse noise in digital color images. This work is of critical interest in biomedical imaging, visual tracking, etc. The conventional filtering methods operate by applying a noise reduction scheme, generally the vector median filtering approach and its variants, for the center pixel of a suitably chosen window that iteratively slides along the entire image. These methods consider the window in its entirety in the filtering process. This consideration, however, comprehends the noise within the noisy pixels in the filtering process and could prove detrimental to the overall output. The method proposed in this paper operates by clustering the pixels in the chosen window into two groups, one that corresponds to the pixel intensities that lie in the signal space and the other to those that lie in the noise space. The motivating rationale for this clustering scheme is to marginalize those pixels that lie in the noise space that seemingly do not contribute to the information in the image. The median filter is then applied to the pixels that contribute to the signal, in isolation of the color components, to filter out the impulse noise. Simulation results show that the proposed method outperforms conventional filtering methods in terms of noise reduction and structural similarity and thus validates the proposed approach. The proposed method is applied to analyze CT scans for improved diagnosis of SARS-COV-2 Covid19 disease. The method is also applied to a visual tracking example as a preprocessor.
Mineral prospectivity mapping of tungsten polymetallic deposits using machine learning algorithms and comparison of their performance in the Gannan region of China

The current study aimed at assessing the capabilities of five machine learning models in term of mapping tungsten polymetallic prospectivity in the Gannan region of China.The five models include logistic regression (LR), support vector machine (SVM), random forest (RF), convolutional neural network (CNN), and light gradient boosting machine (LGBM) models.Geochemical, lithostratigraphic, and structural datasets were used to generate 16 evidential maps, which were integrated into the machine learning models.Tungsten polymetallic deposits were randomly separated into two parts: 80% for training and 20% for validating.Performances of the models were evaluated through receiver operating characteristic (ROC) and K-fold cross validation, with an emphasis on the variable influence within different machine learning methods.The results show that the models are especially sensitive to the chemical elements: Be, Bi, Pb and Cd, implying that these are closely related to tungsten polymetallic mineralization.Compared to other models, the LGBM and CNN models performed best, while the LR model was the most stable.The results also indicated that the CNN model can predict maximum known deposits within a minimum area, based on the prediction-area plot analysis of the five models, while the RF model can capture the most well-known deposits within the smallest study area.Finally, eighteen prospective areas were delineated according to the predicting results of the machine learning models, which will provide important guidance for further tungsten polymetallic exploration and associated studies.
It Takes Two Flints to Make a Fire: Multitask Learning of Neural Relation and Explanation Classifiers

Abstract We propose an explainable approach for relation extraction that mitigates the tension between generalization and explainability by jointly training for the two goals. Our approach uses a multi-task learning architecture, which jointly trains a classifier for relation extraction, and a sequence model that labels words in the context of the relations that explain the decisions of the relation classifier. We also convert the model outputs to rules to bring global explanations to this approach. This sequence model is trained using a hybrid strategy: supervised, when supervision from pre-existing patterns is available, and semi-supervised otherwise. In the latter situation, we treat the sequence model’s labels as latent variables, and learn the best assignment that maximizes the performance of the relation classifier. We evaluate the proposed approach on the two datasets and show that the sequence model provides labels that serve as accurate explanations for the relation classifier’s decisions, and, importantly, that the joint training generally improves the performance of the relation classifier. We also evaluate the performance of the generated rules and show that the new rules are a great add-on to the manual rules and bring the rule-based system much closer to the neural models.
Activation of pedagogical cooperation between school and family in physical education

The article describes the issue of developing ecological culture in physical education classes, high-class students are encouraged to work together with parents and pedagogues on the formation of tourism and ecological knowledge in natural landscapes, but the effective solution of educational tasks is possible only in the conditions of family and school cooperation. Also, the article deals with the study of view of researchers who consider the cooperation of teachers and parents in pedagogical activities in determining the indicators of the level of pedagogical cooperation between school and family: firstly, teachers and parents stimulate and create conditions for students’ self-development, self-discipline, and independent education as the art of developing a private pedagogical position.
SENTIMENT ANALYSIS OF REDDIT COMMENTS

A significant amount of data is generated as well as being made available to internet users thanks to the development and growth of online technologies. The internet has developed into a forum for online education, idea sharing, and opinion exchange. Social networking services like Twitter, Facebook, and Google+ are quickly gaining popularity as a result of the ability for users to share and express their opinions on many subjects, engage in conversation with various communities, and broadcast messages globally. Reddit data sentiment analysis has been the subject of a great deal of research. This study focuses on Reddit comments from the AMC, Clover, and GameStop subreddits using sentiment analysis. We provide study on Reddit comments where a radar chart was produced displaying comparison between AMC, Clover, and GameStop using machine learning methods Network analysis.
Analisis Perkembangan Kognitif Terhadap Pola Tingkah Laku Siswa Dalam Kegiatan Pembelajaran Di Sekolah Dasar

Cognitive development, especially in elementary school age children, is an important thing for a classroom teacher to know and understand. Each child has different cognitive abilities and influences changes in behavior during the learning process. Behavior is essentially a form of students' attitudes in interacting with their learning environment. The purpose of this study was to analyze the cognitive development of students' behavior patterns in learning activities. The method used in this study is a qualitative descriptive approach and using data collection techniques carried out in three ways, namely through document studies, interviews, and observations. The behavior patterns that students show at school during the learning process are, 1) independent behavior, 2) student discipline, 3) curiosity behavior, 4) honest behavior.
Retraction: Energy Analysis of Integrated Energy Based on Cloud Computing (J. Phys.: Conf. Ser. 1346 012016)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 23 September 2022
Retraction: Accounting Information Revolution Based on Cloud Computing Technology (IOP Conf. Ser.: Mater. Sci. Eng. 750 012201)

This article has been retracted by IOP Publishing following an allegation that raises concerns this article may have been created, manipulated, and/or sold by a commercial entity. In addition, IOP Publishing has seen no evidence that reliable peer review was conducted on this article, despite the clear standards expected of and communicated to conference organisers. The authors of the article have been given opportunity to present evidence that they were the original and genuine creators of the work, however at the time of publication of this notice, IOP Publishing has not received any response. IOP Publishing has analysed the article and agrees there are enough indicators to cause serious doubts over the legitimacy of the work and agree this article should be retracted. The authors are encouraged to contact IOP Publishing Limited if they have any comments on this retraction. Retraction published: 23 September 2022