Reviewerly/exHarmony huggingface dataset:
Chess Software based on AI

Chess, which is played between two players on a board, is an intellectual and mental game. Its unique rules of play help to better the player's mental and intellectual activities, and it has a huge following of players all over the world who are keen to play it. This document discusses the completely computerized chess game. The game is first computerized so that two players can play chess on a computer using all of the current rules. Second, the AI program was used to create the game, adding the computer's intelligence to make it more compelling for players to play directly against it.
KOMPARASI SUPPORT VECTOR MACHINE (SVM) DAN AUTOREGRESSIVE INTEGRATED MOVING AVERAGE (ARIMA) PADA PERAMALAN HUJAN DI DAERAH ALBURY, AUSTRALIA

Rain is one of the 4 weather conditions on earth. The rain itself is sometimes erratic. For some people, rain is sometimes seen as an obstacle in carrying out their daily activities. Therefore, predictions about rain are needed. Predictions about rain really help people in carrying out their daily activities. The research aims to compare the predictive performance of SVM and ARIMA in forecasting rain. The data used in this case study research is data regarding daily weather for 10 years in the Albury area, Australia from 2008-2017 with a lot of 3040 data. The results obtained from SVM for forecasting rain using daily weather data for 10 years in the Albury area, Australia with the best accuracy rate with the SVM model is 97.532% with an error rate of 2.468%, while in the ARIMA model, the results are MAE 0.181, RMSE 0.254 and MAPE 0.159. So it can be concluded that the ARIMA model has a better performance in predicting rain than the SVM method.
SPN-AS: A new white-box cryptographic algorithm based on AS iteration structure

Abstract The attacker in white-box model has full access to software implementation of a cryptographic algorithm and full control over its execution environment. In order to solve the issues of high storage cost and inadequate security about most current white-box cryptographic schemes, SPN-AS, a novel white-box block cipher based on AS iterative structure is proposed. This scheme utilizes the AS iterative structure to construct a lookup table with a five-layer ASASA structure, and the maximum distance separable matrix is used as a linear layer to achieve complete diffusion in a small number of rounds. Attackers can be prevented from recovering the key under black-box model. The length of nonlinear layer S and affine layer A in lookup table is 16 bits, which effectively avoids decomposition attack against the ASASA structure and makes the algorithm possess anti-key extraction security under the white-box model, while SPN-AS possesses weak white-box (32KB, 112)-space hardness to satisfy anti-code lifting security. SPN-AS has provable security and better storage cost than existing schemes, with the same anti-key extraction security and anti-code lifting security, only 128KB of memory space is required in SPN-AS, which is only 14% of SPACE-16 algorithm and 33% of Yoroi-16 algorithm.
Perceived Motivational Effects of Mobile Learning Technique to Higher Education Students: An Exploratory Study

This article aims to examine how adopting the M-Learning technique affects students' intrinsic motivation and ability to learn new material. All in all, 283 higher education students of the University of Education. Twice they were evaluated to see how they fared. Ten multiple-choice questions were utilized for the evaluation, all of which were administered using the Socrative mobile apps. An evaluation form was utilized to get students' feedback on the experiment. According to responses from respondents all of the University of Education, M-Learning creates a more positive classroom atmosphere (71 percent), boosts attendance rates (80 percent), and aids in the retention of material studied (72 percent). All groups' aggregate performance improved as they used the app more often (initial-final evaluation: 5.8 vs. 7.2 points). The results imply that the M-Learning approach is a valuable instrument for enhancing the teaching-learning process and is helpful in the academic setting as a facilitator of knowledge absorption.
InterCriteria Analysis applied to the Turkish Health and Social Protection datasets

In the current investigation InterCriteria Analysis is applied to the main diseases declared by individuals in 15-and-over age group in the last 12 months. The information is downloaded from the website of TurkStat – Turkish Statistical Institute. The received outcomes present dependencies between the distribution of the health problems in Turkey and their frequency in the years.
Effectiveness of Learning Package on Knowledge Regarding Child Rearing Among Mothers of Under Five Children

Background: Children are future of society and mothers are guardian of that future, foremost health, safety, and nutrition are important for under five children. Child rearing refer generally to all interactions between mothers and children. They often are unaware that their child rearing knowledge that can affect their children's health includes healthy food habits, Developmental milestones, and preventive measures of accidents. Mothers of under-five children does not have adequate knowledge about child rearing. Thus, by educating theme helps to update knowledge. Aim: This study aimed to evaluate the effectiveness of learning package on knowledge regarding child rearing among mothers of under-five children. Methodology: A Quasi- experimental Two group pre-test post-test design and non-probability purposive sampling techniques was adopted to assess the effectiveness of learning package. The sample size was and equally divided into two group,30 in each group (experimental and control group). Result: The finding of the study reveals that majority of mothers of under-five children belong to the age group 21-25 years. In the experimental group pre-test mean ± SD of level knowledge was 8.47 ± 2.54 were significant different with post-test mean ± SD was 20.2± 2.55. In the experimental group pre-test post-test obtained calculated “t” value was (15.41), Mean Difference was 11.73. p-value (&lt;0.0001) was less than 0.05. In the control group and experimental group there was a significance association between marital status and level of knowledge among mothers of under-five children at 0.05 level of significance. Others demographic variables had no significant association with level of knowledge regarding child rearing among mothers of under-five children. Conclusion: The result showed that there was a significant increase in level of knowledge among mothers of under-five children in the experimental group after administration of learning package.
The Morphometrical Variation of adult’s Human Face in Nepal

Background: The evaluation and measurement of human body dimensions are achieved by physical anthropometry. Cephalometery is a branch of anthropometry science in which the head and face anatomical dimensions are measured. This research was conducted in view of the importance of anthropometric indices of the face in forensic medicine, surgery, paediatrics and medical imaging. Material and Methods: This cross-sectional study was set up to determine and compare the face shapes Nepalese populations aged between 17 &amp; 30 -year-old males and females. The length and width of faces were determined by using Digital vernier calliper and martin spreading calliper respectively. The shape of faces in among male and female of Nepalese population were determined and was compared with other studied and population. Results: In this research, we found that mean values face height and width among male and female were 115.78±7.02 and 112.78±4.7 and were 127.19±6.59 and 130.18±7.44 respectively. Prosopic Index among male and female were 89.01±3.82 and 88.83±3.82 respectively. The result showed that both male and female was found to round face. This showed that Nepali population face was Mesoprosopic (round) PI= 85 &lt;PI&lt;89.9. Conclusion: This study determined the possible effect of ethnicity on the diversity of face shapes in males and females adult Nepalese and was found to Mesoprosopic face.
Image Forgery Detection Using Copy-Move Technique

A digital image is a data representation of a two-dimension scene.Digital images are easy to manipulate and edit due to the availability of powerful image processing and editing software.So, it is possible to add or remove important features from an image without leaving any obvious traces of tampering.In today's world of advanced computer technology, tampering with a digital image can be easily performed by a novice with a number of available sophisticated image processing software like Adobe Photoshop, Corel Draw, etc. So, it is very difficult for a viewer to judge the authenticity of a given image.In fields such as forensics, medical imaging, e-commerce, and the film industry, the authenticity and integrity of digital image is essential.In the medical field physicians and researchers make diagnoses based on imaging.In this paper, we proposed a method for image tamper detection that is based on copy move technique.Copying parts of an image and pasting in the same image for creating a fake image is called copy move.
The Effect of Trust at Work, Knowledge Sharing Behavior, and Innovative Behavior on The Operational Performance: Empirical Analysis on Courier and Delivery Services Firms

Purpose-Courier &amp; Delivery Services (CDS) firms are third-party logistics companies that provide material flow between the manufacturer and the consumer. The operational performance of CDS firms determines the success of logistics performance. Trust at work (TW), Knowledge Sharing Behavior (KSB), and Innovative Behavior (IB) are among the variables that affect operational performance (OP). This research purposes to determine the effect of TW, KSB,and IB on operational performance and to decide the finest model structure with hierarchical regression analysis.Design/methodology/approach-This study aims to the effects of trust at work, knowledge-sharing behavior, and innovative behavior on operational performance. With this context, a survey that consists of items about trust at work knowledge sharing behavior, innovative behavior, and organizational performance is used for creating a dataset.In this process, 433 employees of CDS were interviewed face-to-face, via e-mail, and by telephone. 3 model proposals are presented and these models are tested by hierarchical regression analysis. Findings-Proposed Model-3 is the best model structure for explanation TW, KSB, and IB’s effects of on OP. Discussion –To improve the operational performance of CDS companies, trust, knowledge-sharing behavior, and innovative behavior should be considered holistically.
Survey on Aspect Based Sentimental Analysis using Deep Learning Techniques

People People are increasingly using social media to communicate their views and ideas in daily life.Analysis, processing, interpretation, and inference of subjective texts with the sentiment are all steps in the sentiment analysis process.Businesses utilise sentiment analysis for a variety of purposes, including market research, brand reputation analysis, customer experience evaluation, and social media influence research.It can be classified into document, sentence, and aspect-based types in accordance with the various needs for aspect granularity.In order to determine the aspects of entities and the sentiment conveyed for each one, Aspect Based Sentimental Analysis (ABSA), a fine-grained task in sentiment analysis, is performed.Since it offers more thorough and detailed data, ABSA has drawn a lot of interest in recent years.Product dependence, target dependence, and aspect dependence are the three fundamental difficulties ABSA faces.In order to choose the best aspect extraction approach for the proposed model, we first compared the accuracy of two different methods, TF-IDF and PMI.The precise extraction technique is examined first with Bert and subsequently with various classifiers.The many classifiers are finally combined to produce a superior accuracy.Pretrained BERT that has been fine-tuned performs very well on ABSA.It makes use of BERT intermediate layers to improve the effectiveness of BERT finetuning.The suggested approach will be tested using two datasets, Amazon Unlocked Mobile and tripadvisor hotel reviews, where hotel reviews produce more accurate findings.
Deep Learning-based Image Denoising for Enhanced Image Quality using Convolutional Neural Networks

Deep Learning-based Image Denoising for Enhanced Image Qualityusing Convolutional Neural Networks
Data-driven Learning: Aiming at the Bigger Picture

There has been increasing interest in corpus-based teaching of rhetorical features in academic writing at the discourse level (Chen and Flowerdew 2018; Dong and Lu 2020; Moreno and Swales 2018). In line with this tendency, this paper explores the potential of using corpus tools in teaching rhetorical elements of academic writing and considers the ways in which wider aspects of academic writing can be addressed through the use of corpora, for example rhetorical moves in argumentation and counter-argumentation, authorial presence, evaluating an argument and problem–solution patterns. The paper places specific emphasis on practical suggestions for tasks and activities, locating these practical applications within the framework of existing corpus research. The tasks are based on the use of several corpus tools, Lextutor concordance, SkELL, BNC-English corpora and MICUSP. They are targeted at upper-intermediate and advanced second language learners—senior undergraduates, postgraduates and researchers—and can be used across multiple disciplines.
AERODYNAMICS CHARACTERISTICS DEVELOPMENT of TARUMANAGARA ECO-VEHICLE (MOBIL IRIT UNIVERSITAS TARUMANAGARA) USING CFD METHOD

Vehicles experience the forces of aerodynamics at various degrees and magnitude. The impact of aerodynamic must be considered because it affects the efficiency of the object. Because aerodynamic forces highly affect a vehicle’s efficiency, improvement in aerodynamics characteristics will improve the vehicles efficiency. However, the aerodynamic characteristic involves vehicle profile, dimensions. Designers now have the option of using a CFD software to simulate and calculate the aerodynamic properties of an object before production. The 2 objects on this research are an improved version of Mobil Irit Universitas Tarumanagara body by modifying its length therefore reducing the angle of the body, the body is named 3a and 3b. CFD simulation of body 3a and 3b is used to determine whether the flow characteristic is improved by the length modification of the object, and will be done using ANSYS Workbench R1 Academics Version at 5 different inlet velocity (1,39 m/s; 2,78 m/s; 4,17 m/s; 5,56 m/s; and 12,5 m/s) and will use a 3D simulation with single phase fluid. Subject 3a has 42699 nodes 234941 elements, subject 3b has 49535 nodes 272509 elements. The result shows a reduction in wake size at the back of subject 3b, whereas wake size increased in subject 3a. The drag coefficient result in reduction on 3b and an increase in 3a.
Challenges in the development of digital competence in secondary school teachers

Currently, due to emerging paradigms of teach¬ing and learning as a result of health contingen¬cy, digital competence has become a necessity in educational centers. Furthemore, the new teach¬ing role is no longer just that of being a facilita¬tor of face-to-face learning, but now it generates knowledge, communicates and transmits emo¬tions through various virtual environments. This paper has as aim to identify the level of digital competence in secondary level teachers, as well as the factors associated with it. The study has a quantitative approach, with a correlational scope, transactional temporality, with an obser¬vational prediction control and a retrospective chronological order of events. As a result of the research, a low level of digital competence was identified among secondary school teachers in Merida, Yucatan, Mexico. There was evidence that the factors that were significantly associ¬ated with this competence were age and training in the use of Information and Communication Technologies (ICT). This sets the foundations for the design of teacher training proposals focused on the development of their digital competence.
Techno-crime cause, prevention, and control: issues to consider

The chapters included in our Handbook on Crime and Technology provide considerable evidence that criminals - like ordinary citizens in every global region - have embraced technology and its opportunities (Holt and Bossler, 2015; McGuire and Holt, 2017; Wall, 2007). Stalans and Finn have documented the changes in technology access and use (2016: 1): “The Internet, mobile apps, and information technology are now embedded in societal structures of finance, health, education, and business in many countries throughout the world.” In the years since Stalans and Finn provided this assessment, global reliance on information technology has increased exponentially. In 2016, over 3 billion people, 44 percent of the global population, had used the internet. As of December 31, 2021, more than 5 billion people, over 66 percent of the world population, have used the internet (http:// www .internetlivestats .com).
Country Report

After a brief presentation of the Italian education system, the article (a) describes the current situation of the teaching of philosophy in Italy, then (b) it presents the method and the laws that regulate this teaching. Moreover it illustrates the current compulsory philosophical curriculum in grammar schools and the situation of teacher training in philosophy.
Predicting Breast Cancer with Ensemble Methods on Cloud

There are many dangerous diseases and high mortality rates for women (including breast cancer). If the disease is detected early, correctly diagnosed and treated at the right time, the likelihood of illness and death is reduced. Previous disease prediction models have mainly focused on methods for building individual models. However, these predictive models do not yet have high accuracy and high generalization performance. In this paper, we focus on combining these individual models together to create a combined model, which is more generalizable than the individual models. Three ensemble techniques used in the experiment are: Bagging; Boosting and Stacking (Stacking include three models: Gradient Boost, Random Forest, Logistic Regression) to deploy and apply to breast cancer prediction problem. The experimental results show the combined model with the ensemble methods based on the Breast Cancer Wisconsin dataset; this combined model has a higher predictive performance than the commonly used individual prediction models.
Work-family Conflict and Psychological Stress among Nurses in Irbid Hospitals

Objectives: This study aimed to investigate the extent to which the content of the basic first-grade mathematics textbook in Jordan complies with the standards of the National Council of teachers of mathematics (NCTM). The study's authors expect that it will help those responsible for creating mathematics curricula at all levels, and in the fundamental first grade in particular, by highlighting areas of strength and need.&#x0D; Method: The study sample consisted of a mathematics book for the first grade in Jordan, with its first and second parts, and two exercise books. An analysis instrument was designed; the validity and reliability of the instrument were ensured. The analysis process was carried out by monitoring the set of paragraphs, each of which includes one idea, and then calculating the number of ideas that represent one of the elements of the analysis, and calculating their repetitions and percentages in light of the sum of repetitions of the elements of the criterion.&#x0D; Results: The results of the study showed that the content of the first-grade mathematics textbook was the highest in data analysis and probability (0.00−79.31)% while it was the lowest in numbers and operations (0.00−18.69)%. The results also showed that the extent of the operations standards was the highest in problem-solving (0.00−76.92)% and the lowest was in communication (3.57−35.71)%.&#x0D; Conclusions: The study recommended the necessity of developing the book according to NCTM standards, and conducting studies to evaluate mathematics books for other classes in light of the current curricular development movement in Jordan.
Exploring the Interconnections and Applications of AI, Blockchain, Machine Learning, and Deep Learning

The domains of deep learning (DL), machine learning (ML), artificial intelligence (AI), and block chain technology are all intricately related and have the capacity to revolutionize a number of distinct industries. This essay focuses on how they interconnect and how they are used to acquire a better comprehension of how these innovations correlate. In this piece, we investigate how ML and DL can be employed for tasks such as speech recognition, image recognition, and natural language processing.We also analyze how DL can be intertwined into block chain solutions to enhance safety and privacy, in addition to how block chain technology can enhance the security and lucidity of AI systems. We also assess how investigators are concocting pioneering solutions for a diversity of fields by harnessing the advantages of these technologies. This paper delves deep into how these inventions clash and how they can result in groundbreaking progress.
Financial Liberalization and Banking System Development: Evidence from Arab Countries

Financial liberalization is a process that could be profitable for growth but it may pose serious problems to the development and economic prosperity. The objective of this paper thesis is to evaluate by using panel data, the effect of financial liberalization and institutional quality on banking development on a sample of 17 Arab countries over the period 1990-2012. The empirical findings suggest that financial liberalization could have a positive effect as well as the institutional quality on banking development for the Arab region.
Java Script Powered Web Based Speech to Text Converter

Java script-powered web-based speech-to-text converter interface is used to access speech recognition, which involves the use of the Web Speech API, which allows web developers to incorporate speech recognition and synthesis capabilities into their web applications. The Web Speech API offers a selection of APIs for recording audio input, identifying speech, and speech to text conversion. We have developed a speech-to-text input method for use with web platforms. The system is provided as a JavaScript with dynamic HTML files, and CSS. Users can use voice commands to create content and articles instead of typing. Speech recognition entails listening to speech through a device's microphone and having a speech recognition service check proper grammar for any sentence or word phrases and use as a translator from one language to other. A result (or series of results) is returned as a text string when a word or phrase is correctly identified, and subsequent actions can be started as a result. The quality of the audio input, background noise, and language support are some of the variables that affect how accurately speech-to-text recognition performed using JavaScript. However, the technology has improved significantly over the years and can provide accurate and reliable results for many use cases. Typically, the device's built-in default speech recognition system—which is present in the majority of contemporary operating systems and may be used to provide voice commands—will be utilized for speech recognition. Think about Dictation on mac OS, Siri on iOS, Cortana on Windows 10, Android Speech, etc.
Image Denoising with Convolutional Neural Networks: A Promising Approach for Better Image Quality

Image Denoising with Convolutional Neural Networks: A PromisingApproach for Better Image Quality