Reviewerly/exHarmony huggingface dataset:
Tren Penggunaan Media Pembelajaran Pada Jenjang Sekolah Dasar

The purpose of this research is to re-examine the trend of employing learning media to enhance primary school learning outcomes. A meta-analysis strategy was employed in this study. In order to make the author's data collection process easier, this research starts by looking for pertinent themes. Searches in online publications using the terms Learning Media on Learning Outcomes of Elementary School Students produced the results. Ten articles from the years 2020–2022, which are still very relevant, are the only ones that can be found after a limited search. In order to support this paper, the data that has been collected is next examined. According to the analysis's findings, media use in the classroom has been shown to enhance student learning outcomes. Additionally, students' interactions with the media during the learning process vary. Through the usage of media during the learning process, it can also boost students' capacity to comprehend the subject matter readily.
Wadudia School and Swat Museum: Lost Heritage of Swat

In the last decade, two significant buildings of the swat state’s era were deteriorated and damaged due to natural and man-made disasters, the wadudia school and swat museum. This paper aims to document, analyze and compare these events and subsequent reconstruction of these buildings. Conservation and preservation of built heritage is the collective responsibility of the state and citizens, due to its role as a valuable resource for present and future generations. Heritage buildings not only contain the material evidence of their time but carry itself the long history. This research used a case study as the primary research method combined with a descriptive research method. This study emphasizes the basic consideration for the protection and conservation of numerous heritage sites and buildings of the swat region. This is high time to consider built heritage as assets and resources, for their long-listed benefits including economic educational, and cultural tourism.
Role of Laboratories and Science Teaching Material in Science Teaching and Students Learning at Secondary Level in Public Schools

The focus of this study is on the Role of laboratories in science teaching and students learning at secondary level in public schools. The science education is incomplete without the practical work and use of labs. This research study find out the utilization, availability and role of labs and science teaching material in science teaching and students learning at secondary level. It is a qualitative study and the purpose of this study is to explore the present difficulties and problems in science due to deficiencies of labs which affect both on science teaching and learning of students. Data is collected by interviews directed to science teachers. Interviews were semi structured. Researcher used open-ended questions. These interviews were recorded and transcribed by using thematic analysis, themes and subthemes are used for the analysis of data. The findings of this study showed that labs and science material is very essentials for the improvement of student learning and play significant role in the development of science education. Government should ensure the availability of science lab with enrich material in each school.
Covid-19 is A Catalyst for the Emergence of Information Technology in Education Institutes

The education sector without information technology is like a man with no eyes. It plays a vital role in the development of the education sector. This study examines how the covid 19 has positively expanded information technology in the education sector, especially in higher education institutes, and the primary usage of information technology in the higher education institutes. A qualitative based on conceptual analysis was used to address the said issue based on the secondary data in the literature. This study found that due to the emergence of the covid 19, information technology usage in higher education institutes has increased rapidly. There are three main domains for higher education institutes to use information technology: teacher-to-student real-time interaction for the classes, teacher-to-student transfer of educational materials, and students-to-administration contacts.
Exploring Errors Treatment Impacts on Undergraduate Learners in English Language Classrooms at Kohat University of Science &amp; Technology, Kohat

The objective of this study is to develop a comprehensive understanding about the various impacts of language teachers’ written or oral corrective feedback techniques and strategies on learners’ language learning. This study also investigates learners’ attitudes and perceptions about their teachers’ corrective feedback strategies applied in the classrooms. Using inappropriate approaches in learner errors treatment process can hold back learner language learning performance in the classroom. This study employs mixed method approach by collecting data through questionnaire and interview. Quantitative data is collected from 219 students by using five-point Likert scale questionnaire. To determine the results, descriptive analysis and regression analysis is applied; while qualitative data is analyzed through thematic analysis. Research study concluded that teacher’s attitude and strategies during learner errors treatment process can cast enormous positive or negative impacts on learner language learning. Learners recommended appropriate and well accepted feedback strategies for their better learning in language classrooms.
Functional Morphology: Patterns Rules Sets for Morphological Parsing of Urdu Regular Verbs

Affixation of Urdu regular verbs give multiple patterns providing various verbs, varying in meaning and use regarding aspect and gender following similar root verb. Taking into consideration the pattern variations in verbs the aim of this study was to identify morphological patterns of regular Urdu verbs, whereas objective of this research was to explore morphological patterns of stemming in case of Urdu verbs. A corpus of more than 1500 regular verbs is developed. 16 rules sets were developed following 13 different affixation patterns. Out of which 7 specific rules combinations were designed following these combinations in relation to 1 root verb. According to functional morphology these rules set follow a morphological parser for Natural language processing (NLP). The results are significant to design Urdu database of regular verbs corpus for Urdu NLP. This morphological implementation can be used to develop Urdu data base dealing with Functional Morphology and lexicology while dealing Urdu regular Verb forms.
Private Information Retrieval with Result Verification for More Servers

Private information retrieval (PIR) allows a client to retrieve an element from a database without revealing which element is downloaded to the database servers. PIR protocols with unconditional privacy and sublinear (in n) communication complexity can be constructed assuming multiple honest-but-curious servers. This assumption however cannot be guaranteed in many real life scenarios such as using cloud servers as database servers. We consider an multi-server information-theoretic PIR with result verification (PIR-RV) model where the client can detect the existence of malicious servers even if only one server is honest. We construct a t-private k-server PIR-RV protocol for arbitrary $$k\ge 2$$ and $$1 \le t < k$$ , and show its security for $$2 \le k\le 5$$ . The protocol’s communication complexity is $$O(\frac{k^2}{t} (\frac{nk}{t})^{ 1 / (\lfloor (2k-1)/t\rfloor -1)} \log p )$$ , where p is the size of finite field.
HistoChain: Improving Consortium Blockchain Scalability using Historical Blockchains

Blockchain technology has been successfully applied in many fields for immutable and secure data storage.However, for applications with on-chain big data, blockchain scalability remains to be a main concern.In this paper, we propose a novel scalable storage scheme, called HistoChain, for a consortium blockchain network to manage blockchain data.We use a current blockchain and historical blockchains to store on-chain big data, where the current blockchain and the historical blockchains store data from recent years and earlier years, respectively.Both the current blockchain and the historical blockchains are maintained by super peers in the network; while regular peers manage only the current blockchain and can retrieve historical data by making queries to the super peers.We present procedures for generating historical blockchains, dynamically balancing the data retrieval workload of super peers, and concurrently retrieving historical blockchain data in response to queries.We further provide a case study of healthcare data storage using a consortium blockchain, and the simulation results show that our scalable HistoChain storage scheme supports efficient access and sharing of big data on the blockchain.
Correction to: Multi-valued neural networks I: a multi-valued associative memory

Here we provide a corrigendum on Theorem 2 to Article Title: Multi-Valued Neural Networks I: A Multi-Valued Associative Memory. https://doi.org/10.1007/s00521-021-05781-6.
Multi-agent Modal Logic Evaluating Implicit Information

This paper studies relational Kripke models for computation truth values in some extended logical language. The multi-agent modal language is extended by introduction a new modal operation $$D (\alpha , \beta )$$ . The truth of this operation is determined in a way by implicit information: it is true only if the number of states where the formula $$\alpha $$ is true is strictly less than the number of states where the formula $$\beta $$ is true. From mathematical point of view, the paper investigates satisfiability problem for formulas in such language, we construct a mathematical algorithm verifying satisfiability the formulas.
Extracting Statistically Plausible Heuristics with Association Rule Mining

One critical aspect of decision-making research pertains to the use of cues and the strategies employed for making choices in real-world scenarios. This article aims to shed light on the utilization of association rule mining, a data mining method, to uncover hidden patterns of cue usage in the context of decision-making. While association rule mining is widely employed in fields such as genetics and medicine, its application in the psychology of decision-making remains largely unexplored. We begin by presenting the features of association rule mining and subsequently provide an illustrative procedure using real-world data. Finally, we offer recommendations and discuss the potential application of this tool in the field of judgment and decision-making , particularly in relation to heuristics.
Memahami Filsafat Galileo dan Hubungannya Dengan Kehidupan Kepercayaan

Abstract:Galileo's philosophy played an important role in the history of science because he showed how the scientific method can be used to understand the universe. Galileo was a philosopher known for his rational and empirical approach to studying the universe. He is also a scientist, mathematician. This article identifies key concepts in Galileo's philosophy, including the role of rational thought, empirical testing, and the importance of science in the search for truth. This article also explores the relationship between Galileo's philosophy and beliefs in life, especially in the opinions and beliefs of individuals towards religion and science. We can see Galileo's philosophy from his views on scientific methodology and its relation to the life of belief. In his efforts to obtain the truth about the universe, Galileo presented various important views that made him an important figure in the development of modern philosophy.Keywords: Galileo, Philosophy, Belief Life, Science
Fuzzy Inference System for The Risks Pregnancy Detection

Abstract&#x0D; One of the causes of the high Maternal Mortality Rate (MMR) and Infant Mortality Rate (IMR) in Aceh is the delay in handling cases of at risk pregnancies due to the lack of availability of easily accessible and well-documented information about conditions during pregnancy. So far, manual reporting through data recapitulation report was difficult to access quickly if there are cases maternal and infant mortality. Fuzzy logic can be used as an alternative for classifying pregnant women at risk with supporting data when examining pregnant women. Data related to pregnancy checks will be analyzed with a Fuzzy Inference System (FIS) to obtain information on pregnancy risks. The results of this study indicate that FIS can determine the risk of pregnancy more detailed range than using a manual scoring card. The results of the defuzzyfication value will describe the final decision related to pregnancy risk which can be categorized into low risk, high risk and very high risk. The problem solving steps in this study can be used for algorithms in the development of application programming for risky pregnancy early detection systems based on programming languages. ​​
Image Denoising using Mean Filter

The first step in any image processing process is to remove noise from an image, and this is the aim of every de-noising technique. The noise removal technique should be used carefully to avoid introducing artifacts that could cause the image to become blurry. In this paper, five levels of Gaussian noise and Salat &amp; Peppers are applied to original images to add noise (σ=5, σ=10, σ=15, σ=20, σ=25 σ=50) and also combination Gaussian and Salt &amp; peepers are used with noise level 25. Removing noising is filtered in mean filter. Performance evaluation of the mean filter with three methods of noise is provided. After testing all the approaches with Gaussian noise σ =15, the results revealed that Lena's image was superior to the others. The other photos, however, performed better for the Gaussian levels 20 and 25 than the Lena image. With all types of noise, the mean filter produced good results.
On the Ordering of Pooled Web Pages, Gold Assessments, and Bronze Assessments

The present study leverages a recent opportunity we had to create a new English web search test collection for the NTCIR-16 We Want Web (WWW-4) task, which concluded in June 2022. More specifically, through the test collection construction effort, we examined two factors that may affect the relevance assessments of depth- k pools, which in turn may affect the relative evaluation of different IR systems. The first factor is the document ordering strategy for the assessors, namely, prioritisation (PRI) and randomisation (RND). PRI is a method that has been used in NTCIR tasks for over a decade; it ranks the pooled documents by a kind of pseudorelevance for the assessors. The second factor is assessor type, i.e., Gold or Bronze. Gold assessors are the topic creators and therefore they “know” which documents are (highly) relevant and which are not; Bronze assessors are not the topic creators and may lack sufficient knowledge about the topics. We believe that our study is unique in that the authors of this article served as the Gold assessors when creating the WWW-4 test collection, which enabled us to closely examine why Bronze assessments differ from the Gold ones. Our research questions examine assessor efficiency ( RQ1 ), inter-assessor agreement ( RQ2 ), system ranking similarity with different qrels files ( RQ3 ), system ranking robustness to the choice of test topics ( RQ4 ), and the reasons why Bronze assessors tend to be more liberal than Gold assessors ( RQ5 ). The most remarkable of our results are as follows: First, in the comparisons for RQ1 through RQ4 , it turned out that what may matter more than the document ordering strategy (PRI vs. RND) and the assessor type (Gold vs. Bronze) is how well-motivated and/or well-trained the Bronze assessors are. Second, regarding RQ5 , of the documents originally judged nonrelevant by the Gold assessors contrary to the Bronze assessors in our experiments, almost one half were truly relevant according to the Gold assessors’ own reconsiderations. This result suggests that even Gold assessors are far from perfect; budget permitting, it may be beneficial to hire highly motivated Bronze assessors in addition to Gold assessors so they can complement each other.
Studying the Mediating Role of Intellectual Ethics in the Relationship of Digital Leadership and Smart Decision-making

Studying the Mediating Role of Intellectual Ethics in the Relationship of Digital Leadership and Smart Decision-making
ANALISIS KETERTARIKAN MAHASISWA DEPARTEMEN SEJARAH FIS UNP TERHADAP SISTEM BELAJAR DARING

This research was raised due to the COVID-19 pandemic that hit the world. This pandemic certainly has an impact on the world of education. The government overcame the spread of COVID-19 by moving all face-to-face activities online. Padang State University also appealed to students, teaching staff, and staff to do work at home (online). In the online learning system, researchers saw that students of the History Department of FIS UNP experienced culture shock, that they were surprised and unprepared for online learning. This research was raised to determine the factors and analysis of interest of FIS UNP History Department Students. This online learning system has both positive and negative impacts. The positive impact of the online learning system is that students have no difficulty in doing learning. They don't need to do activities to class just do it at home. While the negative impact of students who use telecomference will consume excess internet quota and adequate internet signal. The method used in this study is qualitative descriptive. This method is used to describe and expose the object to be studied in the form of analysis and make conclusions from the data. This has been reviewed from the distribution of questionnaires to students and descriptive analysis conducted by researchers. From the results, 60% of students of the History Department of FIS UNP have an interest and motivation in doing an online learning system rather than conventional learning.
The Effect of Synthesizing Strategy on Students’ Reading Comprehension at SMA Serdang Murni Lubuk Pakam

This study focused on finding out the effect of Synthesizing Strategy on Students’ Reading Comprehension at SMASerdang Murni buk Pakam. A Thesis.This study was conducted in experimental Quantitative design. The populationof this research was Tenth Grade of students in SMA Serdang Murni Lubuk Pakam . There were seventy six studentsof the tenth grade senior high school students as the sample of research. This study was conducted with tworandomized groups namely Experimental Group and Control Group. The experimental group was taught by usingSynthesizing Strategy, while control group was taught without Synthesizing Strategy. The instrument of collectingthe data was a multiple choice test. The data were analyzed by using t-test. The calculation shown that t-observed(3.65) was higher than t-table (1.68) at the level of significance (α) 0.05 with the degree of freedom (df) 58. Itmeans that there was a significant effect of Synthesizing Strategy on students reading comprehension. So, the nullhypothesis (H0) is rejected and alternative hypothesis (Ha) is accepted.
Saxe: Text-to-Speech Synthesis Engine Applicable to Diverse Use Cases

from input text and a speech-synthesis section that generates synthesized speech from the
Attendance System using Haar Cascade Approach

Abstract: The participation framework is utilized to track and screen whether an understudy goes to a class. There are various kinds of participation frameworks like Biometric-based, Radio recurrence card-based, face acknowledgment based and old paper-based participation framework. Out of them every one of the, a Face acknowledgment based participation framework is safer and efficient. There are a few examination papers zeroing in on just the acknowledgment pace of understudies.. This research focusing on a face recognition based attendance system with getting a less false-positive rate using a threshold to confidence We used Haar cascade for face detection of their strength and LBPH calculation for face acknowledgment. It is hearty against monotonic dark scale changes. Situations, for example, face acknowledgment rate, misleading positive rate for that and bogus positive rate with and without involving an edge in recognizing obscure people are considered to assess our framework. We got face acknowledgment pace of understudies is 77% and its bogus positive rate is 28%. This system is seeing students regardless, when students are wearing glasses or grown a beard development . Face Recognition of unknown persons is nearly 60% for both with and without applying threshold value. Its bogus positive rate is 14% and 30% with and without applying edge separately.
Text based Tweet Classification using Ensemble Classifier

There are so many social networking sites available. Tweets have evolved into a crucial tool for gathering people's thoughts, ideas, behaviours and sentiments surrounding particular entities. One of the most intriguing subjects in this context is analyzing the sentiment of tweets using natural language processing (NLP). Although several methods have been created, the accuracy and effectiveness of those methods for sentiment analysis are yet to be improved. This paper proposes an innovative strategy that takes advantage of machine learning and lexical dictionaries. Tweets are classified using a stacked ensemble model that has Naive Bayes as a base classifier and the Logistic Regression as a meta classifier model. The performance of the proposed method is compared with common machine learning models such as Naïve Bayes and Logistic Regression using the sentiment140 dataset, experiments were carried out and their accuracy was determined. The results of the experiment endorse the proposed methodology. exhibits better outcomes of attaining accuracy score of 86%.
Satellite Image Dehazing

Abstract: The images captured during haze, murkiness and raw weather has serious degradation in them. Image dehazing of a single image is a problematic affair. While already-in-use systems depend on high-quality images, some Computer Vision applications, such self-driving cars and image restoration, typically use input from data that is of poor quality.. This paper proposes a deep CNN model based on dehazing algorithm using U-NET, dynamic U-NET and Generative Adversarial Networks (CycleGANs). CycleGAN is a method that comprehends automatic training of image-to-image transformation without associated examples. To train the model network, we use SIH dataset as the training set. The superior performance is accomplished using appreciably small dataset, the corresponding outcomes confirm the adaptability and strength of the model.
Augmented Reality based Home Decor App

Abstract: In this paper, AR based Home Decor App is implemented which uses FAST corner detection. The Proposed System implements Home Decor App for furniture units using concept of Augmented Reality, which changes world of E-commerce by providing best solution to the customers while purchasing online products. The customer buys the product after virtual trial, which is possible through the concept of Augmented Reality. This is just completely new experience to online customers
Gesture Based Handling of Virtual Mouse and Keyboard

Abstract: Keyboard and Mouse handling is very essential for Human Computer Interaction. So, we promotes an approach for the Human Computer Interaction (HCI) where cursor movement can be controlled using a real-time camera, it is an alternative to the current methods including manual input of buttons or changing the positions of a physical computer mouse. Instead, it uses cameras and computer vision technology to control various mouse events and can perform all the tasks that a physical computer mouse can do.