Reviewerly/exHarmony huggingface dataset:
Penerapan Metode Quantum Teaching dalam Meningkatkan Hasil Belajar Matematika dalam Materi Bentuk Pangkat dan Akar pada Siswa SMA Negeri 1 Gondang Bojonegoro

This study aims to improve the results of learning mathematics using quantum teaching models. This research uses the method of action research. The subjects of the study were students and math teachers of grade X SMA Negeri 1 Gondang Bojonegoro, with class X MIPA 1 as a test class and class X MIPA 2 as a research class. The results showed a significant improvement in teacher performance variables in the learning process from cycle I by 62.5% increased to 79.17% in cycle II. In the student's activity variable increased by 67.5% from cycle I to 75.63% in cycle II. Student learning outcomes have also increased by 71.88% to 87.5% and have achieved indicators of success. Quantum teaching model can improve students' learning outcomes.
Uses and Gratification of Social Networking Websites; A Case of Housewive of Lahore City

The internet is the biggest community at the planet, connecting your laptop to computer systems everywhere in the world. The interconnected nature of the net offers you get right of entry to sources saved on far flung computer systems, inclusive of multimedia pages, audio and video clips, video games and programs. And due to the fact, the net connects you with different net users, you could change email, chat, be a part of in dialogue businesses or even make in telephone calls to different individuals who are linked to the net. Quota sampling is used for this research because it is a quick and cheap method to organize. The researcher has taken the 200 respondents between the ages of 25-35 old. This study has conducted the survey from two famous areas of Lahore i.e., Gulberg Town and Iqbal Town.
A New Blowfish Using A Neural Network

The Blowfish algorithm is one of the most popular, but it requires significant computational power with many details that make them prey to many attackers. In this paper, the original Blowfish algorithm was optimized by reducing the size of the s-box and then designing and implementing it on a neural network (NN). The input to the neural network is text either the(plaintext or ciphertext) and the output obtained from the network is the equivalent text and the key used in both encryption and decryption are the initial weights of the neural network that are trained using the backpropagation network. The proposed neural network (NN) model was designed and simulated by a computer. Simulation results demonstrate reduced complexity of the algorithm, implementation speed, and convergence of results achieved through the NN-based optimized Blowfish algorithm encryption system with optimized Blowfish results.
Probabilistic Memory Model for Visual Images Categorization

During the past decades, numerous memory models have been proposed, which focused mainly on how spoken words are studied, whereas models on how visual images are studied are still limited. In this study, we propose a probabilistic memory model (PMM) for visual images categorization which is able to mimic the workings of the human brain during the image storage and retrieval. First, in the learning phase, the visual images are represented by the feature vectors extracted with convolutional neural network (CNN) and each feature component is assumed to conform to a Gaussian distribution and may be incompletely copied with a certain probability or randomly produced in accordance to an exponential distribution. Then, in the test phase, the likelihood ratio between the test image and each studied image is calculated based on the probabilistic inference theory, and an odd value in favor of an old item over a new one is obtained based on all likelihood values. Finally, if the odd value is above a certain threshold, the Bayesian decision rule is applied for image classification. Experimental results on two benchmark image datasets demonstrate that the proposed PMM can perform well on categorization tasks for both studied and non-studied images.
PERHITUNGAN TARIF IMBAL JASA KAFALAH PENSIUN DAN PRAPENSIUNAN BERBASIS WEB PADA PT. PENJAMINAN JAMKRINDO SYARIAH CABANG PALEMBANG

PT Penjaminan Jamkrindo Syariah then abbreviated as PT Jamkrindo Syariah was born from the Sharia Guarantee Division which is a Sharia Business Unit in the Indonesian General Credit Guarantee Company. The problem that arises in the guarantor company is the difficulty in calculating the price of the Kafalah fee when outside the office if it has to do calculations in the office making prospective customers feel the service provided is slow and unable to compete with other competitors, so we need an application that can help sales in calculating the cost of a Kafalah fee if it is outside the office so the calculation process is fast. The application that will be built is a web-based application software and uses the Prototype method.
Kalamezhuthu Pattu: A Linguistical Analysis Tracing The Cultural Values

Language is intrinsic to the expression of culture. It is the channel through which culture and its traditions may be conveyed and preserved. The main goal of this paper is to inculcate the reciprocity of the Sapir-Whorf Hypothesis theory otherwise known as linguistic relativity with the traditional Indian ritual Kalamezhuthu Pattu celebrated in the temples of Kerala as these rituals play a vital role in enriching the cultural heritage of India. This theory claims that the structure of a language affects its speaker’s worldview or cognition and thus people’s perceptions are relative to their spoken language. This paper focuses on the symbols associated with the ritual and how these symbols contribute to the visual aesthetics of humans and how it helps in the cognition of linguistic and cultural connectivity. The authors also try to assay this ritual as a custom for ecological preservation which is in contrast to the current mechanized world.
Reading Data into the Power BI Data Model via an API

Many governmental entities and private companies have made their data more accessible via Data APIs. Data APIs provide interfaces that enable you to programmatically retrieve data from data providers. The data sets that these Data APIs provide can bring great value to your Power BI data model.
Parents Income and Education as the Factors Affecting the Learning of English at the Intermediate Level

This study is mainly concerned with exploring the extent of involvement of the factors understudy in English learning of the intermediate level students of government degree colleges in District Bannu. Many factors are involved in learning of English but only two social factors were selected for the study i.e. parents income and parents education. The manner of the research was explorative. Primary data was collected from the five degree colleges in District Bannu. Out of the 800 students one hundred students were randomly selected as sample following L.R. Gays sample criteria. Through close-ended Likert agreement scale questionnaire, the primary data was collected, analyzed, and interpreted through tables, 3D Columns and Exploded Pi-Charts. The researcher found that the factors of parents income and education had the main role in the learning of English at the intermediate level. The scholar also found that parents low income was at the top of the factors understudy with respect to their extent of involvement in the English learning.
The Effectiveness of “Dialogic Reading Method” in Increasing Prosocial Behavior in Preschool Children

This study aims to stimulate prosocial communication through active two-way communication in dialogic reading speech method. Prosocial behavior reflected in this study consisted of: (1) Helping; (2) Sharingand (3) Comforting. Prosocial behavior is important for children to be accepted and make friends. It supports the process of teaching and learning activities. One intervention that is considered effective in improving prosocial communication is through active two-way communication. This study involved preschool children (n = 100) spread across two early childhood institutions in Bandung Regency using the-before-after-experimental study method consisting of a control group and an experimental group. The result of this study showed that Dialogic reading effectiveness test in the experimental group through dialogic reading method had a significant influence on the prosocial behavior of preschool children (Asymp. Sig. (2-tailed) = 0 <α = 0.05).
Deep Learning for Functional Data Analysis with Adaptive Basis Layers

Despite their widespread success, the application of deep neural networks to functional data remains scarce today. The infinite dimensionality of functional data means standard learning algorithms can be applied only after appropriate dimension reduction, typically achieved via basis expansions. Currently, these bases are chosen a priori without the information for the task at hand and thus may not be effective for the designated task. We instead propose to adaptively learn these bases in an end-to-end fashion. We introduce neural networks that employ a new Basis Layer whose hidden units are each basis functions themselves implemented as a micro neural network. Our architecture learns to apply parsimonious dimension reduction to functional inputs that focuses only on information relevant to the target rather than irrelevant variation in the input function. Across numerous classification/regression tasks with functional data, our method empirically outperforms other types of neural networks, and we prove that our approach is statistically consistent with low generalization error. Code is available at: \url{this https URL}.
Investigation of geochemical correlation between radioactive and rare earth elements; case study of Baghak mine, NE of Iran

In several uranium (U) prospecting projects in Iran, particularly Central Iran, the association and enrichment of rare earth elements (REEs) are known as the usual features. Sometimes the association of REEs and U with high economic perspective has caused that the relation between the rare earth and radioactive elements is taken into consideration in other types of mineralization, and if there is any relation, radioactivity will be applied in the exploration of REEs. In the current work, sampling from Baghak anomaly in the Sangan mines is carried out based on the radioactivity and radiation measurement methods (as the optimal sampling pattern). In fact, the goal of this work is to survey the presence or absence of such a relation in a skarn mine, which is a different case study from Central Iran. In the case of presence, this will lead to a new exploration method and sampling pattern for REEs. The mineralogical studies (based on the optical and electronic microscopic observations), statistical investigations, and geochemical analyses are applied in this research work. The results obtained from the statistical studies show that the Baghak anomaly due to involving a significant amount of U, Ce, and La and a high concentration of REEs can be considered as one of the important mines. Spider diagrams and their geochemical investigations include the features that are typical of the subduction-related magmas in the calcalkaline volcanic arcs of the continental active margins. The chondrite-normalized REE pattern shows the enrichment of LREE, and a positive pattern close to flat HREE due to the entry of LREE ions into the allanites network. The mineralogical study results also confirm that REEs (especially Ce) are accumulated as a solid solution in the allanite minerals. Moreover, from the mineralogical, geochemical, and statistical analyses, it can be observed that in addition to the presence of such a relation in the mentioned mineralization (Central Iran mineralizations), there is an acceptable correlation between these elements in the Baghak iron-skarn mineralization. Eventually, it can be said that the idea and introduced method for the exploration of REEs in this work could present a new viewpoint to the decision-makers of this industry.
Scientific and Methodological Support for Teachers in the Context of Gamification in Mathematics Study in the Russian System of Additional Education

The relevance of this study is due to the practical significance of the issues of using game mechanisms in the process of teaching mathematics, the lack of research into the issues of symbiosis of game and didactic technologies in mastering complex mathematical knowledge, the need to search for effective technologies to establish how they affect the development of students and the formation of a modern style of thinking. The analysis of global trends and practices of introducing elements of gamification into the education system has shown that the mastering of complex knowledge and patterns of mathematical activity, the solution of problem areas of mathematics at different levels of learning and complexity is carried out by a complex of mathematical and information methods without the integration of game elements. It has been substantiated that gaming technologies in combination with the informatization of mathematical activity give a powerful motivational charge to the study of mathematics, actualize the processes of self-organization of cognitive activity, and contribute to the development of a probabilistic style of thinking. The purpose of the study is to provide a theoretical substantiation and effective methodological support for the process of professional development of mathematics teachers in the context of gamification in mathematics study with the effect of developing a probabilistic style of thinking. The authors have developed an arrangement mechanism and determined the content of scientific and methodological support for teachers working in the constituent entities of the Russian Federation to provide additional educational services in the context of gamification in education. The developed materials, in particular, include evaluative case tests for identifying competence deficiencies in teachers, which ensure the formation of a probabilistic style of thinking based on gamification processes by managing the information saturation of the motivational field of learning. In addition, the authors proposed an additional professional education program for teachers, Mathematics in Gaming Activities (Business, Didactic and Intellectual Games) , and developed new forms of certification and assessment materials (gamification-based didactic solutions and effective practices). Using the concept of gamification, it was possible to demonstrate the activation of cognitive and motivational structures, in particular, the effective development of a probabilistic style of thinking in the process of mastering complex mathematical knowledge through its adaptation to school mathematics. The results of the study allow making it possible to bring the process of teaching students and developing their personalities to a modern qualitative level using current achievements in the field of digitalized education.
The Value of Using Grey Scale Ultrasound in the Estimation of Palpable Breast Lumps in a Specialist Breast Clinic in Mosul City of Iraq

Background: Breast carcinoma is one of the most common female malignancies affecting the females within the 30-60 years age groups in many parts of the world.The aim of the study was to assess the using of grey scale ultrasound in the evaluation of palpable breast lumps in Mosul city and compare the finding with the histopathology. Materials and Methods:The study was retrospective study which was done at Al-Khansa Specialist Breast Clinic, from January 2019 to July 2019.155 patients with palpable breast lump were evaluated by grey scale ultrasound and their characteristics radiological features were studied and compared with the final histopathological diagnosis.Results: By ultrasound, about 60% of the cases were benign, 13.5 % were intermediate and 26.4 % were malignant compared with the histopathology which showed 71.6 % were benign and 28.4 % were malignant.The most common benign lesion was fibroadenoma while mastitis was the most common intermediate lesion diagnosed on histopathology.The specificity and sensitivity of the ultrasound in detection of breast carcinoma were 92.7% and 88.6% respectively.PPV of 82.9% and NPV of 95.3% with diagnostic accuracy 91.6%. Conclusion:In our study, the grey scale ultrasonography has high specificity, sensitivity and diagnostic accuracy in detection of breast carcinoma to reduce the morbidity and mortality of the disease.In general, ultrasound' s availability and low cost in developing countries and comfort to the patients with no radiation effect; making it considered as 1 st line investigation modality in females breast lumps.
Search Tree Pruning for Progressive Neural Architecture Search

Our neural architecture search algorithm progressively searches a tree of neural network architectures. Child nodes are created by inserting new layers determined by a transition graph into a parent network up to a maximum depth and pruned when performance is worse than its parent. This increases efficiency but makes the algorithm greedy. Simpler networks are successfully found before more complex ones that can achieve benchmark performance similar to other top-performing networks.
THE RETROSPECTIVE POTENTIAL OF DOCUMENTARY-INFORMATION RESOURCES: THEORETICAL ASPECTS

The purpose of the article. Based on the study of documents, problem-thematic historiography, guided by the latest methodology formulated the purpose of the work, which is to explore the theoretical aspects of establishing the content potential of documentary and information resources, to make a general picture of their external, internal elements and characteristics, identify features, find out efficiency methods of scientific criticism. Methodology. The research methods of document science, archival science, information studies, and social communication were used, which allowed to reveal the content of documentary and information resources, to analyze their external and internal characteristics, to identify interdisciplinary connections in the study of documentary sources. The scientific novelty of the work is to establish the features and content of documents, analysis of the phenomenon of documentary information resources as a source of information, the specifics of reflecting their time and reality, processing documents of archival, museum, and library repositories and establishing information value and significance. Conclusions. The study of documentary and information resources as a reflection of time and space revealed communication relationships identified the needs of society in information documentation, and the creation of specific document forms and organization of their storage, which arose to meet these needs. The study allowed us to study the theoretical foundations of documentary information resources, see their capabilities, create a holistic comprehensive vision of external and internal features of the document as a source of information and means of communication of a particular period in terms of theoretical and thematic issues.
A Secret Share and Key Generation Based Visual Cryptography Approach For Retaining 2D and 3D RGB Color Using Transposition.

These days advanced symbolism is utilized for some reasons. Beginning similarly as a leisure activity of photography up to the motivation behind security or ID. For more delicate purposes, a picture should be encoded so the picture isn't perceived by an unapproved individual. In this investigation, crossbreed rendering is utilized to scramble and decode RGB pictures. The crossbreed rendering here includes the cycle of randomization and repositioning of pixels before interpretation is made. The presentation of the encryption is estimated by the relationship coefficient where the great outcome is shown by the connection coefficient esteem near 0 (zero). The littlest coefficient esteems acquired are - 0.0227 for test pictures as chessboard pieces that have practically similar highly contrasting zones. The unscrambling cycle delivers precisely the same picture as the first picture, this is shown by the MAE esteem equivalent to 0 (zero) and the relationship coefficient equivalent to 1.0.
Review of Researches on Arabic Social Media Text Mining

Social media sites and applications have allowed people to share their comments, opinions, and point of views in different languages on mass scale. Arabic language is one of the languages that has seen huge surge in production of its digital textual content. The Arabic content and its metadata are a goldmine of useful information for a wide variety of applications. A large number of researchers are working on Arabic data in various domains of research such as natural language processing, sentiment analysis, event detection, named entity recognition, etc. This article presents a review of number of such studies conducted between 2014 and 2019 using their data sources from social media websites. We found that Twitter was the most used source to contribute data for dataset construction for Arabic text mining researchers. Our study also found that the Sport Vector Machine (SVM) and Naïve Bayesian (NB) classifiers were the most used classifiers in the previous researches. Moreover, the results of the previous studies indicate that SVM classifier provided the best performance compared to other classifiers.
Multi-Agent Training beyond Zero-Sum with Correlated Equilibrium Meta-Solvers

Two-player, constant-sum games are well studied in the literature, but there has been limited progress outside of this setting. We propose Joint Policy-Space Response Oracles (JPSRO), an algorithm for training agents in n-player, general-sum extensive form games, which provably converges to an equilibrium. We further suggest correlated equilibria (CE) as promising meta-solvers, and propose a novel solution concept Maximum Gini Correlated Equilibrium (MGCE), a principled and computationally efficient family of solutions for solving the correlated equilibrium selection problem. We conduct several experiments using CE meta-solvers for JPSRO and demonstrate convergence on n-player, general-sum games.
India’s Discomfort with Blockchain Based Currency: A Vacuum on The Legality of Bitcoins

Cryptocurrency is a digitally created financial asset, used as a medium of exchange without any authority of bank, with no physical structure and legal tender someway giving disrespect to sovereign boundaries and authorities in absence of specific regulatory structure. Bitcoin is the first blockchain-based currency created in 2009 and is highest priced on crypto exchanges worldwide. Bitcoin was introduced in India in 2012 and has been one of the tops searched word on Google last year in India. Since the government’s Demonetization announcement, Indian Bitcoin adoption has been on the rise. However, the mushrooming usage of Bitcoins in terrorism funding, ransom wares, illicit drugs trade and cybercrime has raised red flags among the security and law enforcement agencies. The watch guard of Indian Economy and apex authority for Banking, Reserve bank of India (RBI), cautioned the users of cryptocurrencies to its potential risks and threats in 2013. The Ministry of Finance also conducted a public consultation on regulations for virtual currencies in May 2017. In 2018, RBI banned banks from facilitating the activities of cryptocurrency exchange platforms. This move of RBI has stunned the whole industry based on Blockchain financial activities. The decision of RBI is the Supreme Court of India for hearing. The paper discusses the challenges to Bitcoins in India beyond the RBI’s ban & way forward. The paper also provides a legal and regulatory perspective of cryptocurrencies particularly Bitcoins in India with a comparison to crypto positive countries.