Reviewerly/exHarmony huggingface dataset:
THE INFLUENCE OF DIRECTED READING THINKING ACTIVITY (DRTA) TOWARDS STUDENTS’ READING ABILITY

The research aimed to know the influence of using DRTA Strategy towards students’ reading ability at MTs Nurul Iman Pesawaran. The research was conducted at the eighth grade of MTs Nurul Iman Pesawaran in academic year 2020/2021. The writer took two clasess in the eighth grade as the samples. The population was 40 students’ in 2 clasess. The sample was taken by using cluster random sampling technique. 20 students’ were as experimental class and 20 students’ were as control class. The main technique in measuring students’ reading comprehension was multiple choice test that consisted of 40 test items. The score for each item was 2,5 for true and 0 for wrong. In analyzing the data, the writer used t-test formula. Based on the data analysis, The result showed that t-test was 2.9. From the distribution table at the significance level of 5% is known that t-table = t (1- ½ α) (df) = 2.00 and at the significance level of 1% is known that t-table = t (1- ½ α) (df) = 2.37. It means t-test &gt; t-table as in (2.9&gt; 2.00 &gt; 2.37). Based on the calculation, Ha was accepted, it means that there was an influence of using DRTA (Directed Reading Thinking Activity) strategy towards the students’ reading ability at the eighth grade of MTs Nurul Iman Pesawaran in 2020/2021. Then the average score of students reading ability who learnt through DRTA (Direct Reading Thinking Activity) was higher than those who learnt reading throurgh conventional technique. It was 70.1 &gt; 65.6. Based on the result above, it is clear that DRTA (Directed Reading Thinking Activity) can increase students’ reading ability at the eighth grade of MTs Nurul Iman Pesawaran in 2020/2021.
Does the Use of Dictogloss Strategy Affect Writing Ability of Junior High School Students?

Writing ability becomes one of the difficulties encountered by students, moreover at the junior high school levels. One of the ways to solve this problem is by finding an appropriate way to teach this skill. This study aims to reveal the significant effect of using Dictogloss strategy on the students’ writing ability at Junior the High School levels. The study used a quasi-experimental design with pretest and posttest. The total population of the study was 160 eighth graders that consist of five classes. From the population, 64 students (two classes, one class as the experiment group, and the other as the control group) were taken as the samples through cluster random sampling. The data were obtained through tests, pretest and posttest. Then, they were analyzed using independent sample t-test and paired sample t-test. The result showed a significant effect of using Dictogloss strategy on the students’ writing ability with a = 0.05 &gt; sig. 0.000. It indicates that Dictogloss strategy can be used to improve students’ writing ability at the Junior High School levels.
OAEvolution: Trends in Open Access and Scholarly Communications

This week marks the 10 year anniversary of Open Access Week—a global event that strives “to make Open Access a new norm in scholarship and research.” In celebration of this momentous occasion, the University of Ottawa Library asked ScholCommLab co-director Stefanie Haustein about recent trends in open access and scholarly communication. In this interview with the Library’s Communication Advisor Meryem El Marzouki, Stefanie reflects on the past, present, and future of OA in...
Celebrating one year of Open Science Beers

Click to view slideshow. “It all started with a pang of jealousy,” says Asura Enkhbayar when asked what inspired him to start Open Science Beers YVR. Stefanie Haustein had pointed out that Montreal hosted a regular open science meetup every Wednesday. But Vancouver, Asura realized, had nothing of the sort. “I had always found it quite amazing that Vancouver was the home of so many amazing folks involved in Open Science, Open Access, Open Data without offering the opportunity...
Assessment of user information needs in the scientific library of the Academy of Economic Studies from Moldova

The paper highlights the results of a study of the information needs of users of the ASEM Scientific Library. The results of the survey demonstrated the high status of the Scientific Library and made it possible to propose new strategies for the development of the library.
Comic Media Development in Thematic Learning For Elementary School Students

This study aims to determine the feasibility and practicality of comic-based learning media on animal growth materials for third grade at SDN 18 Sungai Kakap in printed form. The research method used was research and development (RnD) by adapting ADDIE. The data sources for this research were a media expert, a material expert, a teacher, and 12 students from Elementary School. The research instruments used were interview guides, questionnaires, and documentation. Based on expert assessments, the research results on the feasibility of learning comics media-based expert assessments, the average percentage from the media aspect is 93% categorized as very feasible criteria. From the material aspect, 94% has very feasible criteria. The feasibility of learning comics in the first phase of the trial based on the user response from the teacher was 98% considered as very feasible and 88% from the students with very feasible criteria. In the second phase of the trial, based on the teacher's response, the percentage was 100% considered as very feasible, and 92% of the students' assessments had very feasible criteria. Keywords: Comic. Learning Media Development, Thematic
The Effect of Video Presentation on Achieving Academic Performance Among ESL Students in Malaysia

Technology is an important part of education, and when used correctly, it can help students learn languages well. Technology's impact on education has had a significant impact on how English as a Second Language (ESL) is taught. Malaysia seeks to develop well -educated individuals. To adequately explain this phenomenon, the Malaysian Ministry of Education has coined the phrase "bilingual proficiency"(MOE). The high demand for communication skills in the twenty-first century places them at the top of the list of desirable soft skills.Video presentations are an excellent tool for enhancing the spoken presentation skills of English language students. The purpose of this research is to determine the extent to which students studying English as a Second Language (ESL) can benefit from making use of video presentations to assist them in achieving their learning outcomes. To highlight the links between the variables, a review of the relevant material was carried out and examined. The outcomes of this study offered a conceptual framework that predicts the relevant aspects that are related to students' use of video presentations in their academia. To verify the validity of this conceptual framework, more empirical research must be carried out.
Retraction: Indoor human occupancy detection using Machine Learning classification algorithms &amp; their comparison (IOP Conf. Ser.: Mater. Sci. Eng. 1110 012020)

This article has been retracted by IOP Publishing following an allegation that this article may contain tortured phrases [1]. IOP Publishing has investigated and agrees the article contains a number of nonsensical phrases that feature throughout the paper [2], to the extent that the article makes very little sense. This casts serious doubt over the legitimacy of the article. IOP Publishing wishes to credit PubPeer commenters [3] for bringing the issue to our attention. The authors neither agree nor disagree to this retraction. [1] Cabanac G, Labbe C, Magazinov A, 2021, Tortured phrases: A dubious writing style emerging in science. Evidence of critical issues affecting established journals, arXiv:2107.06751v1 [2] Disha Giri et al 2021 IOP Conf. Ser.: Mater. Sci. Eng. 1110 012020 [3] https://pubpeer.com/publications/5FB003F61C2E05795EED79EFFD5C4E Retraction published: 19 July 2023
The Effectiveness of Quizlet on Teaching Grammar at Eleventh Grade Students of SMA Negeri 1 Bantarsari Cilacap

&lt;p&gt;The problems of this research were students’ difficulties in mastering grammar because of monotonous activity and less interest to learn. Quizlet application was proposed as a new alternative media to engage students’ interest in learning grammar. This study aims to find there was a significant different or not between the experiment class and control class. This study used quasi experimental design and quantitative approach. The population of this research was the eleventh-grade as much as 172students . The sample was chosen by purposive sampling, with 35 students in experimental class and 35 students in control class. This study used pre-test and post-test to collect the data and was analyze used IBM SPSS V 25. The result of Independent Sample T-test showed that the sig.value was 0.298, it means that there was not significant effect. The use of Quizlet to teaching grammar at this school was less effective, but can still use to learn other English subject.&lt;/p&gt;
Differentially Private Simple Genetic Algorithms

The differentially private (DP) selection problem is a fundamental building block in the private literature that is commonly solved with the exponential mechanism. It is well known that efficiency is the major drawback of the exponential mechanism, as the utility function must be computed for all elements in the domain. Genetic algorithms (GAs) use the principles of evolution in nature to efficiently search through large domains and select the best candidate. We observe that GAs have many appealing properties for DP Selection. These include being robust to noisy objectives, placing no restriction on the utility function, and efficient runtime for large domains. However, prior work investigating DP GAs has shown poor utility in practice and often gives the highest utility when zero generations are conducted (indicating that GA operations are not beneficial under DP). This work provides a new DPGA based on the simple GA that addresses the weaknesses of prior solutions. We reduce the destructive nature of previous GA operators and utilize several techniques to reduce the noise from DP. Our modifications allow us to utilize the GA operators over multiple generations (under DP) and improve the GA's overall utility over zero generation techniques. Our work shows that private GAs are competitive with state-of-the-art general and problem-specific solutions to the DP selection problem, with runtime sublinear in the domain size.
The Impact of Product Reviews on E-Commerce Performance: A Comprehensive Review

Abstract: Sentiment analysis of product reviews has become an important research area in recent years. With the rise of ecommerce platforms, online reviews have become an essential part of the decision-making process for consumers. This paper presents a review of the recent advancements in sentiment analysis techniques for product reviews. The paper covers various aspects of sentiment analysis, such as feature extraction, sentiment classification, and aspect-based sentiment analysis. This paper is to analyse the strengths and weaknesses of different techniques, such as rule-based approaches, machine learningbased approaches, and deep learning-based approaches. The paper also highlights the challenges in sentiment analysis, such as handling negation, sarcasm, and irony in reviews. Furthermore, the paper discusses the future research directions in this field. Finally, this paper conclude with a discussion on the potential applications of sentiment analysis, such as market research, product development, and customer service. Overall, this paper provides an overview of the recent advancements in sentiment analysis techniques for product reviews and serves as a roadmap for future research in this field
Comparative Analysis of Support Vector Machine And Perceptron Algorithms In Classification Of The Best Work Programs In P2KBP3A

With the rapid growth of government agencies that are required to carry out an activity in every aspect that publishes and carries out obligations every year, it is required to be held accountable and also implemented for every device that receives such as fostered villages by utilizing the available APBD funds to maximize the work program that has been designed. so that it can be implemented as much as possible. That way, to get the best from all aspects of every work program implementation, there must be an important point from the annual work program design that is made without exception. Data mining itself can help P2KBP3A in analyzing each work program that is designed before being implemented in the future for the annual work program by looking at various aspects of past work program data and grouping work programs in the form of classification. In designing the work program, this research builds a classification model by adding a sigmoid activation function that uses SVM and perceptron to compare the accuracy results of the algorithm used to get the best work program design. From the various classifications used, the best value for classifying the dataset of the best P2KBP3A work programs can be seen from the average accuracy value of 87.5%, F1 value of 82.2%, the precision value of 80.2%, and recall value of 87.5%.
Analysis of Machine Learning Algorithms in Predicting the Flood Status of Jakarta City

By mining the information in the dataset, we can solve a prediction problem, especially flood status prediction based on floodgate levels, using machine learning algorithms. This research employs three machine learning algorithms (K-Nearest Neighbor, Naive Bayes, and Support Vector Machine) for predicting the flood status using a dataset containing the data of DKI Jakarta's floodgate levels. Using a 5-fold, 10-fold, and 20-fold cross-validation evaluation, we get the highest accuracy (85.096%), f-score (85.1%), precision (85.641%), and recall (85.096%) from the model using the SVM algorithm with a polynomial kernel. Average performance-wise, the K-NN algorithm performs better than the other algorithm with an average accuracy of 83.147%, an average f-score of 83.156%, an average precision of 83.566%, and an average recall of 83.147%.
MAPLE: A Metadata-Hiding Policy-Controllable Encrypted Search Platform with Minimal Trust

Commodity encrypted storage platforms (e.g., IceDrive, pCloud) permit data store and sharing across multiple users while preserving data confidentiality. However, end-to-end encryption may not be sufficient since it only offers confidentiality when the data is at rest or in transit. Meanwhile, sensitive information can be leaked from metadata representing activities during data operations (e.g., query, processing). Recent encrypted search platforms such as DORY (OSDI’20) or DURASIFT (WPES’19) permit multi-user data query functionalities, while protecting metadata privacy. However, they either incur a high processing overhead or offer limited security/functionality, and require strong trust assumptions. We propose MAPLE, a new metadata-hiding encrypted search platform that offers query functionalities (search, update) on the shared data across multiple users with complex policy controls. MAPLE protects metadata privacy all the time during query processing, while achieving significantly (asymptotically) lower processing overhead than state-of-the-art platforms. The core technique of MAPLE is the design of oblivious data structures for search index and access control coupled with secure computation techniques to enable efficient query processing with a minimal trust. We fully implemented MAPLE and evaluated its performance on commodity cloud (Amazon EC2) under real settings. Experimental results showed that MAPLE achieved a concrete performance comparable with its counterparts, while offering provably stronger security guarantees and more diverse functionalities.
Evaluating practical QUIC website fingerprinting defenses for the masses

Website fingerprinting (WF) is a well-known threat to users' web privacy. New Internet standards, such as QUIC, include padding to support defenses against WF. Previous work on QUIC WF only analyzes the effectiveness of defenses when users are behind a VPN. Yet, this is not how most users browse the Internet. In this paper, we provide a comprehensive evaluation of QUIC-padding-based defenses against WF when users directly browse the web, i.e., without VPNs, HTTPS proxies, or other tunneling protocols. We confirm previous claims that network-layer padding cannot provide effective protection against powerful adversaries capable of observing all traffic traces. We show that the claims hold even against adversaries with constraints on traffic visibility and processing power. We then show that the current approach to web development, in which the use of third-party resources is the norm, impedes the effective use of padding-based defenses as it requires first and third parties to coordinate in order to thwart traffic analysis. We show that even when coordination is possible, in most cases, protection comes at a high cost.
Funshade: Function Secret Sharing for Two-Party Secure Thresholded Distance Evaluation

We propose a novel privacy-preserving, two-party computation of various distance metrics (e.g., Hamming distance, Scalar Product) followed by a comparison with a fixed threshold, which is known as one of the most useful and popular building blocks for many different applications including machine learning, biometric matching, etc. Our solution builds upon recent advances in function secret sharing and makes use of an optimized version of arithmetic secret sharing. Thanks to this combination, our new solution named Funshade is the first to require only one round of communication and two ring elements of communication in the online phase, outperforming all prior state-of-the-art schemes while relying on lightweight cryptographic primitives. Lastly, we implement our solution from scratch in portable C and expose it in Python, testifying its high performance by running secure biometric identification against a database of 1 million records in ~10 seconds with full correctness and 32-bit precision, without parallelization.
Challenges and Solutions of Public Cloud Carrying 5GC Network

With the progress of digital construction process, telecom operators keep up with the pace of enterprise cloud, and explore the deployment of 5G networks on the public cloud. Taking AWS as an example, this paper describes the architecture and capability requirements of the public cloud deploying 5GC network. Based on current situation of the public cloud deploying 5GC network, this paper has summarized the main challenges of deploying 5GC network on the public cloud, and gives corresponding suggestions
Design of Cloud Service Customer Experience Management System Enhanced by AI

The design goal of Cloud Service Customer Experience Management System Enhanced by AI is to optimize cloud product and service modes to achieve the best customer experience. The system designed in this paper constructs a multidimensional customer label system, a cloud product knowledge graph, and a cloud service knowledge graph, and analyzes and mines customers’ real-time feedback data collected by a variety of AI interactive methods.
Retraction Notice: Mobile Application for Cholesterol Detection Using Iridology with Image Processing and Support Vector Machine

Cholesterol is one of the factors than can cause disability and other diseases that is fatal to one’s life. Data from World Health Organization (WHO) said that around 4.4 million people die because of cholesterol related diseases and 40.4 million people are disabled because of cholesterol. To avoid this, people usually check their cholesterol rate so that they can control their cholesterol. That said the current method for checking cholesterol is by doing blood test, which is an inefficient method if we want to check our cholesterol regularly because it is time consuming and money consuming. This paper presents an application based on mobile to detect cholesterol rate using iridology with the use of Image Processing and Support Vector Machine. By taking a picture of someone eye, which will go through the process such as pre-processing, segmentation, normalization, and classification, it will return three kind of output which is "Normal", "Medium", and "High". By analyzing data from Mugi Barokah Clinic, we managed to create a system to extract the feature of an image and a SVM model to classify the said image with the final result of 80% accuracy.
[People in Control]

In this issue of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">IEEE Control Systems</i> , we speak with Cristina Stoica, a professor at CentraleSupélec, Laboratoire des Signaux et Systèmes (L2S), Université Paris-Saclay, France; Samer S. Saab, a professor of electrical engineering at Lebanese American University (LAU), Byblos, Lebanon; and Umit Ozguner, emeritus professor at The Ohio State University (OSU), Columbus, OH, USA.
AVIATION CADETS’ PERCEPTION ON CONTENT-BASED LANGUAGE TRAINING AND SELF-ASSESSMENT

This research is aimed to find out the effects of content-based language training on cadets speaking skills and to find out the effects of self-assessment on cadets speaking skills. The method employed in this research is survey. The research was done in semester six cadets at Indonesia Aviation Polytechnic in Curug and Makassar. Data was collected by administering an oral test (5 items), a content-based language training questionnaire (5 items), and a self-assessment questionnaire (30 items), in March until June 2021. The result of the research showed that (1) there are significant effects of Content-Based Language Training and Self-Assessment upon Cadets Speaking Skills. These have been proved by Sig score = 0.000 less than 0.05 and F count = 46.781 and the multiple contribution of Content-Based Language Training and Self-Assessment simultaneously gives 62.1% contribution on variable Cadets Speaking Skills; (2) there are significant effects of Content-Based Language Training upon Cadets Speaking Skills. These have been proved by Sig score = 0.000 less than 0.05 and t count = 7.226 and the partial contribution of Content-Based Language Training on Cadets Speaking Skills is 57.85%; (3) there are no effects of Self-Assessment on Cadets Speaking Skills. These have been proved by Sig score = 0.423 more than 0.05 and t count = 0.806 and the partial contribution of Self-Assessment on Cadets Speaking Skills is only 4.30%.
Automated brain morphometry for sub-millimeter 7T MRI using transfer learning

Large spatial signal variations due to field inhomogeneities complicate the application of automated brain morphometry at 7T. In this work, we propose to use transfer learning to adapt a template-based segmentation algorithm to sub-millimeter ultra-high field applications. More specifically, a convolutional neural network pre-trained on T 1 -weighted scans to extract the total intracranial volume (TIV) from MP-RAGE acquisitions was re-trained to retrieve the TIV mask directly from MP2RAGE volumes. The developed method proved to reliably deliver brain tissue masks and volumetry at 7T.