Reviewerly/exHarmony huggingface dataset:
Understanding Big Data Framework Related to a Data Mining Technique

The computing and communication power in the cyber-physical world is expanding greatly. As a result, a lot of data is generated to manage these activities. Big data has four primary challenges: volume, variety, velocity, and authenticity. Some storage-based data processing systems, like Hadoop, manage volume and variety. However, the speed and accuracy of processing such a vast volume of data require an overly complicated process. In this paper, we'll put into practice a system that can deal with huge volumes, varied patterns, and the speed of data. To extract valuable information from the data stream, we'll use correlation analytics and data mining. The system must be able to process data in real time, using an event processing engine like Esper that can generate various events using different language queries. Storm, which uses topology, is used to capture real-time data and for straightforward filtering of that data stream. Apriori and FP-Growth are two separate algorithms that are used for correlation and mining. Data centers all across the world are now using Apache Hadoop. The common programmer can now use parallel processing. It is essential to convert current data mining methods to the Hadoop platform as more data centers support it to maximize the effectiveness of parallel processing. The tendency of moving current data mining algorithms to the Hadoop platform has grown widespread with the advent of big data analytics. We examine the present migration activities and problems in this survey research. The reader's suggestions for solutions to the present migration difficulties will be guided by this essay.
Examining and juxtaposing the two NoSQL databases MongoDB and CouchDB

Relational databases have been an essential component of technology for many years. It has been, and in some cases, still is, the foundation of both large and small organizations. However, a few flaws in relational databases gave rise to NoSQL databases. NoSQL is not a particularly new technology, but it is one that is rapidly expanding. The structured query language is also known as NoSQL. Today, a variety of NoSQL databases are accessible depending on the user's needs. This review combines numerous comparisons of these databases based on various attributes. A few terms relating to NoSQL databases are also clarified and brought to light. Additionally, a detailed comparison of the two most popular NoSQL databases is evaluated.NoSQL is a component of a very narrow ecosystem with fewer applications than relational databases. Relational databases are fairly straightforward, which makes them easy to use, but the non-uniformity of the expanding data causes an issue with them. Organizations manage millions of pieces of data, which makes using a relational database challenging. Additionally, the IoT is right outside our door, and NoSQL is better for IoT applications. NoSQL was developed to address this non-uniformity and the rapidly expanding data sets. NoSQL is mostly utilized in distributed, cloud, and IoT systems. NoSQL databases eschew rigid schemas and prioritize availability, scalability, and fault tolerance as key properties.
Passion and Resilience: Experiences of Public Primary School Teachers in Handling Children with Reading Difficulties in Online Teaching

Aim: This phenomenological study explored the lived experiences of public primary school teachers in handling children with reading difficulties during online teaching.&#x0D; Study Design: Descriptive Phenomenology.&#x0D; Place and Duration of the Study: Bacolod City, Philippines, February to July 2022.&#x0D; Methods: Participants were identified using a purposive sampling technique. Nine (9) public primary school teachers answered the interview using an unstructured in-depth interview. The data collection was done sequentially. In analyzing the participants' transcripts, thematic analysis using the modified van Kaam approach popularized by Moustakas (1994) was utilized.&#x0D; Results: Analyses of the data revealed that utilizing innovative practices in the teaching-learning process helped teachers handle children with reading difficulties. Also, the aide of Parent Facilitated Learning as an ally for teaching remediated the exhaustion of teachers' workloads. Furthermore, this qualitative research generated data from the participants with three major themes, and 12 sub-themes emerged: (1) dealing with children's problems in fundamental skills; subthemes (8): poor letter identification, poor phonetic foundation, a poor blending of word pattern, poor word recognition, poor reading comprehension, low academic motivation, low academic performance, attention deficit, (2) dealing with online instructions; subthemes (2): poor internet access and problems with the schedule of classes, and (3) utilizing innovative practices to address problems on reading difficulties of children, sub-themes (2): using word and picture cues and parent-facilitated learning.&#x0D; Conclusion: Public primary school teachers encountered challenges and struggles handling children with reading difficulties in the new learning platform. These experiences create an opportunity to pursue their passion and commitment to teaching during the COVID-19 Pandemic. This paved the way for passionate and resilient teachers in precarious times.
"Exploring NoSQL Databases and Cloud Computing Security Implementations"

It is commonly known that cloud computing, with its prospective benefits, has completely changed the enterprise IT sector. Due to the advantages of worryfree hardware maintenance, many businesses and sectors are transitioning to the cloud computing era. Large businesses are still not migrating to the cloud, which is reducing the market share of cloud computing. From the standpoint of the consumer, the biggest obstacles to using the cloud for data storage are security and privacy concerns. This paper outlines the numerous restrictions relating to data security and privacy protection issues and provides a few technologies, such as Trend Micro's SecureCloudTM, which enables users to function in the cloud safely and securely. Additionally, employing NoSQL databases, personal data security on the cloud. SecureCloud, FIPS 140-2, NoSQL databases, NSA, IAM rules, Accumulo Apache, Amazon DynamoDB, MarkLogic are some of the terms in the index.As a result, cloud users can benefit from the services provided by the cloud while still having total control over their data thanks to encryption keys. The SecureCloudTM uses VM-level encryption to encrypt data in working storage, enabling the use of distinct encryption keys for each user's particular data. This lessens the possibility of recycled disk blocks being sent to other users or of a configuration error causing data privacy violations. The third is commonplace encryption. Data is encrypted using Industry Standard AES by SecureCloudTM, making it inaccessible to anybody missing the encryption keys. The ability of SecureCloudTM to encrypt data gives users advantages when switching users or terminating storage.
THE CONCEPTUAL ANALYSIS OF TASKS USED IN INTERNATIONAL EVALUATION RESEARCH

In the article, the conceptual analysis of assignments used in international assessment studies, their comparative analysis with existing educational assignments, as well as the content of assignments in the case of natural sciences are analyzed. KEY WORDS: international assessment studies, natural sciences, academic assignments, literacy.
The College English Teacher Behavior and Teaching Effect Based on Big Data Technology

In order to explore the correlation between college English teacher behavior and teaching effects, this paper applies data mining technology to related research. Moreover, this paper uses Bloom Filter to represent the efficiency of insert queries and space usage of dynamic data sets and designs a multichannel balanced matrix Bloom Filter. In addition, this paper uses the longest prefix matching filling algorithm when selecting the element insertion position in multiple candidate Bloom Filters, and uses this algorithm to process the college teacher behavior and teaching effect data. Finally, this paper combines investigation and experiment to conduct research. Through the investigation, it can be seen that the teaching behavior of college English teachers will have a certain impact on students, and the positive behavior of teachers can effectively improve the teaching effect, which can be used as a reference for the formulation of subsequent teaching plans.
The effectiveness of a training program based on social networks in the achievement and development of historical understanding among female fifthgrade literary students in history subject

The research aims to know the effectiveness of a training program based on social networks in developing literary achievement among fifth-grade students and developing their historical understanding. The researcher used experimental design with partial control and the pre and post-test. The researcher choses Division (60) to represent the experimental group that is taught according to a training program based on social networks, and Division (A) represented the control group that taught in the traditional way. The number of students reached (30) students in each division. The variables (chronological age of students, intelligence, previous year grades) The researcher prepared two research tools: the achievement test and the historical understanding test, and the validity and reliability of the two tools were verified. The T-test was used to process the data. The results showed the superiority of the experimental group that was studied according to the program. A training program based on social networks in developing the achievement and skills of historical understanding. The researcher recommended the use of the training program based on social networks in teaching history.
The Effectiveness of Audio-Visually Manipulated PPP Strategy in Teaching EFL to Intermediate School Students

Foreign language teaching methodology has been changing over the years; however, there is no one single best strategy to use in teaching English as a foreign language (EFL).The best language teaching method depends on several factors such as: learners' levels, learning processes, teacher competencies, and the goals of learning.Hence, the current study aims at specifying the Audio-Visually Manipulated PPP Strategy and finding out the effectiveness of the specified strategy in teaching EFL to Iraqi intermediate school students.In order to achieve the aims of the study, and verify its hypotheses, a sample of sixty Iraqi intermediate school students has been randomly selected, equalized, and divided into two equal groups, i.e. experimental and control groups.The experimental group has been taught English according to the Audio-Visually Manipulated PPP strategy, whereas the control group has been taught by using the conventional method for a period of twelve weeks.An achievement posttest has been constructed and applied to the two involved groups.The collected data has been treated statistically and in terms of the obtained results it is concluded that the Audio-Visually Manipulated PPP Strategy is efficient in improving intermediate school students' achievement in English.Finally, some pedagogical recommendations are put forward.
Penerapan Datamining Menentukan Minat Baca Mahasiswa Di Perpustakaan Universitas Bina Darma Palembang Menggunakan Metode Clustering

Abstract : This study was conducted to determine student interest in reading in the library Bina Darma with clustering method. The data used in this study is Bina Darma library database that consists of three tables are tables collection, patron tables and tables of visitors who will be selected to be integrated and combined as a data warehouse. Application of data mining to determine the titles of the most demanding of students and courses are most borrowed books and read a book in the library building dharma. The information obtained is that the course is more interested in information systems to borrow and read books compared to the industrial engineering courses. Titles that most interest is the title of the book basics of programming, while the lowest book is the title of students interested in a practical handbook using Microsotf word and cluster categories of books that most interest students are computer science book category books category Indonesian whereas lower.&#x0D; &#x0D; Keywords : Clustering, Data Mining, Data Warehouse, Visitor, Collection, Dan Patron.
Sistem Pakar Menentukan Kerusakan Gigi Menggunakan Metode Certainty Factor

Damage to the teeth can affect the health of other members of the body, so that it will interfere with activity. Symptoms of this disease are often not considered or considered unimportant. This also occurs in dental diseases including those that damage tooth structure and cause cavities. To find out the symptoms of tooth decay that are owned by patients, users or users only answer a few questions that exist on the Expert System web as a tool in providing consulting services like an expert through the web. The purpose of this study is to create an Expert System program that contains the knowledge of an expert who has the ability to diagnose human tooth decay based on the physical form that occurs and the taste experienced and the position of human teeth based on expert / expert knowledge (dentists) using the Certainty Factor method . This system will provide solutions and make it easier for doctors to socialize their patients.
Penerapan Metode Forward Chaining Pada Sistem Pakar Untuk Mengetahui Kepribadian Seseorang

Personality is the overall behavior and emotions that become a unique characteristic of someone who is stable and predictable. Characteristics or personality traits affect directly or indirectly on work and family conflicts. To find out someone's personality type, generally a person must consult directly with a psychologist or by conducting a questioner that is provided to find out which personality types he belongs to. By utilizing technology that is rapidly developing nowadays, a system that can help people to know their personality is needed or needed, the system is an expert system. This expert system was built using the forward chaining method. This expert system is designed and built with the PHP programming language or often called a web-based system. Due to the web-based system, system users will not be limited by space, time, and minimize the cost and energy to find out which personality belongs to which type of personality
Validitas Jobsheet Instalasi Perumahan Berbasis Proyek Berbantuan E-Learning Di Pendidikan Vokasi

The problem in learning residential houses installations is that the results of student practice are not in accordance with the existing job sheets. Students have difficulty understanding the work steps in the existing job sheet. E-learning is one of the answers to the demands of learning at this time. Therefore, learning media using e-learning is needed. This article aims to test the validity of e-learning-assisted project-based residential houses installation job sheet. The research method used is the mix method. Testing using validity instruments on aspects of content, format and presentation. The analysis used is Aiken's V formula. The results of testing and analysis show that the e-learning-assisted project-based residential houses installation job sheet is valid in the aspects of content, format and presentation.
Classification of Facial Expressions using Convolutional Neural Networks

We can recognize the emotion of a human by seeing their facial expression and it is an efficient way of human communication. It is the easiest way and essential technology for realizing the human and machine interaction. Facial expression recognition task can be able to classify the face images into various categories of emotions such as happy, sad, angry, fear, surprise, disgust and neutral. In this paper, we are analysing and efficiently classifying each facial image into one of the emotion category. There are numerous approaches to address and solve this problem, out of them convolutional neural network (CNN) is the best approach. Here, we are proposing a novel technique called facial emotion recognition using convolutional neural networks. It is based on the feature extractor to extract the feature and the classifier to produce the label based on the feature. The extraction of feature may be imprecise by variance of location of object and lighting condition on the image. The feature of image can be extracted without user defined feature engineering, and classifier model is integrated with feature extractor to produce the result when input is given. In this way, the CNN approach can produces a feature location invariant image classifier that achieves higher accuracy than conventional linear classifier and our model classified the emotions with 66.62 accuracy.
Joint Denoising and Super-Resolution for Fluorescence Microscopy Using Weakly-Supervised Deep Learning

Recent studies have shown that joint denoising and super-resolution (JDSR) approach is capable of producing high-quality medical images. The training process requires noise-free ground truth or multiple noisy captures. However, these extra training datasets are often unavailable in fluorescence microscopy. This paper presents a new weakly-supervised method, in which different from other approaches, the JDSR model is trained with a single noisy capture alone. We further introduce a novel training framework to approximate the supervised JDSR approach. In this paper, we present both theoretical explanation and experimental analysis for our method validation. The proposed method can achieve an approximation accuracy of $$98.11\%$$ compared to the supervised approach. The source code is available at https://github.com/colinsctsang/weakly_supervised_JDSR .
Calibration of Deep Medical Image Classifiers: An Empirical Comparison Using Dermatology and Histopathology Datasets

As deep learning classifiers become ever more widely deployed for medical image analysis tasks, issues of predictive calibration need to be addressed. Mis-calibration is the deviation between predictive probability (confidence) and classification correctness. Well-calibrated classifiers enable cost-sensitive and selective decision-making. This paper presents an empirical investigation of calibration methods on two medical image datasets (multi-class dermatology and binary histopathology image classification). We show the effect of temperature scaling with temperature optimized using various measures of calibration replacing the standard negative log-likelihood. We do so not only for networks trained using one-hot encoding and cross-entropy loss, but also using focal loss and label smoothing. We compare these with two Bayesian methods. Results suggest little or no advantage to the use of alternative calibration metrics for tuning temperature. Temperature scaling of networks trained using focal loss (with appropriate hyperparameters) provided strong results in terms of both calibration and accuracy across both datasets.
Retraction: Research on the Application Analysis of Four-dimensional Teaching Method in Higher Vocational English Teaching Based on Big Data Analysis (J. Phys.: Conf. Ser. 1744 032059)

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: 16 September 2022
Retraction: A Study on English Teaching Model under the Background of Big Data (J. Phys.: Conf. Ser. 1744 032061)

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: 16 September 2022
Retraction: Analysis on the Teaching Reform of College Physical Education Informationization Based on Computer Technology (J. Phys.: Conf. Ser. 1648 032042)

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: 16 September 2022
Retraction: Analyze the Direction of Visual Symbols in Digital Media Technology Based on Big Data Technology (J. Phys.: Conf. Ser. 1648 032110)

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: 16 September 2022